85415 Global Tracking Framework Global Tracking Framework © 2014 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org Some rights reserved 1 2 3 4 15 14 13 12 This work is a product of the staff of The World Bank with external contributions. Note that The World Bank does not necessarily own each component of the content included in the work. The World Bank therefore does not warrant that the use of the content contained in the work will not infringe on the rights of third parties. The risk of claims resulting from such infringement rests solely with you. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved. Rights and Permissions This work is available under the Creative Commons Attribution 3.0 Unported license (CC BY 3.0) http://creativecommons. org/licenses/by/3.0. Under the Creative Commons Attribution license, you are free to copy, distribute, transmit, and adapt this work, including for commercial purposes, under the following conditions: Attribution—Please cite the work as follows: International Energy Agency (IEA) and the World Bank. 2014. Sustainable Energy for All 2013-2014: Global Tracking Framework Report. Washington, DC: World Bank. DOI: 10.1596/978-1-4648-0200-3 License: Creative Commons Attribution CC BY 3.0 Translations—If you create a translation of this work, please add the following disclaimer along with the attribution: This translation was not created by The World Bank and should not be considered an official World Bank translation. The World Bank shall not be liable for any content or error in this translation. All queries on rights and licenses should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@worldbank.org. ISBN (electronic): 978-1-4648-0200-3 DOI: 10.1596/978-1-4648-0200-3 Table of Contents Foreword i Executive Summary iv Abbreviations xii Regional Classification xvi Overview 1 Chapter 1: The SE4ALL Global 35 Tracking Framework Chapter 2: Energy Access 43 Chapter 3: Energy Efficiency 103 Chapter 4: Renewable Energy 163 Chapter 5: Conclusions 221 Data Annexes Energy Access 231 Energy Efficiency 241 Renewable Energy 250 Foreword At the 2012 Rio+20 Conference on Sustainable Develop- the global objectives for energy efficiency and renewable ment, world leaders agreed to develop a set of Sustainable energy hinges on efforts in some 20 developed and Development Goals. For many, the Sustainable Energy for emerging economies that account for 80 percent of global All (SE4ALL) initiative launched that year—a year designat- energy consumption. Finally, the report identifies a number ed to highlight that same theme—and backed by a global of “fast-moving” countries whose exceptionally rapid prog- coalition of public and private sector organizations, as well ress on the triple energy agenda since 1990 provides not as civil society, is an illustration of what a Sustainable De- just inspiration, but know-how that can help us replicate velopment Goal for the energy sector would look like. their success elsewhere. SE4ALL seeks to achieve, by 2030, universal access to In many respects, what you measure determines what you electricity and safe household fuels, a doubled rate of im- get. That is why it is critical to get measurement right and provement of energy efficiency, and a doubled share of re- to collect the right data, which is what this report has done. newable energy in the global energy mix. As the Millennium It has charted a map for our achievement of sustainable Development Goals process has shown, measurable goals energy for all and a way to track progress. Let the journey that enjoy widespread consensus can mobilize whole soci- begin! eties behind them. An issue for any set of goals is how to measure progress towards their achievement. This can be —Kandeh Yumkella tricky on methodological and political grounds. In the light Secretary General’s Special Representative for of this challenge, the rigor and even-handedness evident Sustainable Energy for All in this first SE4ALL Global Tracking Framework is all the more welcome. A team of energy experts from 15 agencies worked un- der the leadership of the World Bank and the International Energy Agency to produce this comprehensive snapshot of the status of more than 170 countries with respect to energy access, action on energy efficiency and renewable energy, and energy consumption. The report’s framework for data collection and analysis will enable us to monitor progress on the SE4ALL objectives from now to 2030. It is methodologically sound and credible. It produces findings that are conclusive and actionable. The report also shows how different countries can boost progress toward sustainable energy. Reaching universal energy access depends decisively on actions in some 20 “high-impact” countries in Africa and Asia. Attaining i Global tracking framework Acknowledgments The development of the Global Tracking Framework was and Nigel Bruce (WHO); and Simon Trace (Practical Action). made possible by exceptional collaboration within a spe- Substantive comments were also provided by Radha cially constituted Steering Group led jointly by the World Muthiah, Ranyee Chiang, and Sumi Mehta (GACC); Drew Bank/Energy Sector Management Assistance Program Corbin (Practical Action); Stephen Gitonga (UNDP); and (ESMAP) and the International Energy Agency (IEA). Venkata Ramana Putti (WB/ESMAP). Dr Francis Vella, Edmond Villani Chair of Economics, Georgetown University Members of the Steering Group include the Global Alliance provided expert guidance to the team for the development for Clean Cookstoves (“the Alliance”), the International of the World Bank Global Electrification Database. Institute for Applied Systems Analysis (IIASA), the IEA, the International Partnership for Energy Efficiency Cooperation The energy efficiency chapter (chapter 3) was prepared by (IPEEC), the International Renewable Energy Agency (IRE- a working group comprising World Bank/ESMAP and IEA. NA), Practical Action, the Renewable Energy Network for The main contributing authors were Ivan Jaques, Ashok the 21st Century (REN21), UN Energy, the United Nations Sarkar, Irina Bushueva, and Javier Gustavo Iñon (World Development Programme (UNDP), the United Nations Bank/ESMAP); and Philippe Benoit, Robert Tromop, Sara Environment Programme (UNEP), the United Nations Bryan Pasquier, Laura Cozzi, Fabian Kesicki, Taejin Park, Foundation, the United Nations Industrial Development Nathalie Trudeau and Anna Zyzniewski (IEA). Substantive Organization (UNIDO), the World Bank, the World Energy comments were also provided by Amit Bando and Thibaud Council (WEC), and the World Health Organization (WHO). Voita (IPEEC), and by Mark Hopkins (UN Foundation). The Steering Group’s collaboration was made possi- The renewable energy chapter (chapter 4) was prepared ble by agreement among the senior management of the by a working group comprising the World Bank/ESMAP , member agencies, many of whom were represented on IEA, IRENA, REN21, and UNEP . The main contributing the Sustainable Energy for All High Level Group in 2012. authors were Gabriela Elizondo Azuela, Javier Gustavo Vijay Iyer (World Bank) and Fatih Birol (IEA), with Rohit Iñon, and Irina Bushueva (World Bank/ESMAP); Paolo Khanna (ESMAP), oversaw the development of the Global Frankl, Adam Brown, and Zuzana Dobrotkova (IEA); Dolf Tracking Framework. Directors of other Steering Group Gielen, Ruud Kempener, and Zuzana Dobrotkova (IRENA); agencies provided important strategic input: Radha Muthiah Christine Lins (REN21); and Martina Otto and Djaheezah (GACC); Nebojsa Nakicenovic (IIASA); Amit Bando (IPEEC); Subratty (UNEP). (Ms. Dobrotkova moved from IEA to IRENA Adnan Amin (IRENA); Simon Trace (Practical Action); in the course of the work.) Substantive comments were Christine Lins (REN21); Kandeh Yumkella (UN Energy); also provided by Pierre Audinet (ESMAP). Richenda van Leeuwen (UN Foundation); Veerle Vander- weerd (UNDP); Mark Radka (UNEP); Morgan Bazilian and All chapters draw on results of the IEA’s World Energy Outlook Marina Ploutikhina (UNIDO); Christoph Frei (WEC); and and World Energy Statistics and Balances, and on IIASA’s Maria Neira (WHO). Global Energy Assessment. Marco Baroni and Fabian Kesicki facilitated input from the World Energy Outlook. The technical work on the Global Tracking Framework was Jean-Yves Garnier, Pierre Boileau, Roberta Quadrelli, and coordinated by Vivien Foster (World Bank) and Dan Dorner Karen Treanton provided substantive statistical input and (IEA). comments. Nebojsa Nakicenovic, Keywan Riahi, Shonali Pachauri, Volker Krey, and Peter Kolp facilitated input from The chapter on access to energy (chapter 2) was prepared the Global Energy Assessment. by a working group comprising World Bank/ESMAP and IEA, GACC, Practical Action, UNDP and WHO. The main The World Bank peer review process was led by Marianne contributing authors were Sudeshna Ghosh Banerjee, Fay, with contributions from Jeff Chelsky, Mohinder Gulati, Mikul Bhatia, Elisa Portale, and Nicolina Angelou (World Todd Johnson, Luiz Maurer, Mohua Mukherjee, and Dana Bank/ESMAP); Dan Dorner, Jules Schers, and Nora Selmet Rysankova. (IEA); Carlos Dora, Heather Adair-Rohani, Susan Wilburn, foreword / Acknowledgments ii The two rounds of public consultation were coordinated by The design and publication of the final documents was Simon Trace, Helen Morton, and Lucy Stevens from Practical coordinated by Ryan Hobert and Daniel Laender at the UN Action and benefited from use of the REN21 online consul- Foundation in collaboration with Nicholas Keyes of ESMAP . tation platform. More than 100 stakeholders participated The creation of the online data platform was undertaken by in the process. The first consultation event was organized Shaida Badiee, Neil Fantom, and Shelley Liu of the World by Sandra Winkler at WEC as part of the WEC Executive Bank. Assembly in Monaco, November 2012. The second con- sultation was facilitated by Christine Lins of REN21, as The report was edited by Steven B. Kennedy and designed a side event of the World Future Energy Summit in Abu by Eighty2degrees. The communications and launch pro- Dhabi, January 2013. cess was coordinated by Christopher Neal and Jonathan Davidar at the World Bank and Cynthia Scharf at the United The report has also benefitted from dialogue with the Nations. following government agencies: The work was largely funded by the participating agencies Germany (Bundesministerium für wirtschaftliche Zusam- of the Steering Group. Financial support from ESMAP and menarbeit und Entwicklung – BMZ, Deutsche Gesellschaft DFID was critical in covering certain costs. für Internationale Zusammenarbeit – GIZ, Kreditanstalt für Wiederaufbau – KfW); Netherlands (Energieonderzoek Centrum Nederland – ECN); Norway (Ministry of Foreign Affairs – MFA); United Kingdom (Department for International Development – DFID); and United States (Department of State – DOS, Office of Energy Efficiency and Renewable Energy – EERE). Coordinators For sustainable energy. iii Global tracking framework EXECUTIVE SUMMARY executive summary In declaring 2012 the “International Year of Sustainable Energy for All,” the UN General Assembly (2011) established—at the personal initiative of the UN Secretary General—three global objectives to be accomplished by 2030. Those goals are to ensure universal access to modern energy services (including electricity and clean, modern cooking solutions), to double the global rate of improvement in energy efficiency, and to double the share of renewable energy in the global energy mix. Some 70 countries have formally embraced the Sustainable Energy for All (SE4ALL) initiative, while numerous corporations and agencies have pledged tens of billions of dollars to achieve its objectives. As 2012 drew to a close, the UN General Assembly announced a “Decade of Sustainable Energy for All” stretching from 2014 to 2024. Sustaining momentum for the achievement of the SE4ALL objectives will require a means of charting global progress over the years leading to 2030. Construction of the necessary framework has been coordinated by the World Bank/Energy Sector Management Assistance Program (ESMAP) and the International Energy Agency (IEA), in collaboration with 13 other agencies (see logos on final page). The process has benefited from public consultation with more than a hundred stakeholder groups. A new framework for tracking progress toward the goal of “Sustainable Energy for All” The Global Tracking Framework described in this report efficiency. The framework adopts this approach but moves provides an initial system for regular global reporting beyond this initial proxy, using statistical analysis to get based on indicators that are both technically rigorous closer to underlying energy efficiency, as well as comple- and feasible to compute from current global energy menting national energy intensity indicators with equivalent databases, and that offer scope for progressive improve- indicators for four key economic sectors. For renewable ment over time. Although the identification of suitable energy, the indicator is the share of total final energy con- indicators required for the framework posed significant sumption1 derived from all renewable sources (bioenergy, methodological challenges, those challenges were no aerothermal, geothermal, hydro, ocean, solar, wind). more complex than those faced when attempting to measure other aspects of development—such as poverty, To make it possible to track progress, SE4ALL has com- human health, or access to clean water and sanitation piled a global data platform from the full range of available —where global progress has long been tracked. In all household surveys and national energy balances. Those these aspects of development, a sustained effort of sources encompass a large group of countries—ranging building analytical capability and data capacity has been from 181 for clean energy and 212 for modern energy required across most countries. services—that cover an upwards of 98 percent of the world’s population over the period 1990–2010. Indicators For energy access, household survey evidence is used for individual countries can be found in a data annex to the to determine the percentage of the population with an Global Tracking Framework, as well as online through the electricity connection and the percentage of the population World Bank’s Open Data platform: http://data.worldbank. who primarily use non-solid fuels for cooking. Aggregate org/data-catalog. energy intensity has long been used as a proxy for energy 1 Though technically energy cannot be consumed, in this report the term energy consumption means “quantity of energy applied”, following the definition in ISO 50001:2011 and the future standard ISO 13273-1 Energy efficiency and renewable energy sources - Common international terminology Part 1: Energy Efficiency. v Global tracking framework Electricity powers a garment factory in Guatemala. Photo: Maria Fleischmann / World Bank Recent progress has been too slow to reach the new objectives By the indicators identified above, the world made major behind global population that grew at 1.3 percent per year advances on the energy front during the last 20 years. An over the same period. This held back the growth of energy additional 1.7 billion people (equivalent to the combined access rates to around just one percentage point of popu- population of India and Sub-Saharan Africa) gained the lation annually. While renewable final energy consumption benefits of electrification, while 1.6 billion people (equiv- grew at 2 percent annually over 1990-2010, this was only alent to the combined population of China and the United slightly ahead of the 1.5 percent annual growth rate in total States) secured access to generally less-polluting non- final energy consumption. As a result, the correspond- solid fuels. Energy intensity has dropped significantly, ing share of renewable energy increased only slightly from avoiding the cost of developing 2,300 exajoules of new 16.6 percent in 1990 to 18.0 percent in 2010. energy supply over the past 20 years, cutting cumulative global energy demand by more than 25 percent over The Global Tracking Framework has set starting points 1990–2010, and leaving 2010 consumption more than a against which progress will be measured under the third lower than it would otherwise have been. Renewable SE4ALL initiative (table ES.1). The rate of access to elec- energy supplied a cumulative total of more than 1,000 tricity and of use of non-solid fuel as the primary fuel for exajoules globally over 1990–2010, an amount comparable cooking will have to increase from their 2010 levels of 83 to the cumulative final energy consumption of China and and 59 percent, respectively, to 100 percent by 2030. The France over the same period. rate of improvement of energy intensity will have to dou- ble from –1.3 percent for 1990–2010 to –2.6 percent for Yet rapid demographic and economic growth over the last 2010–30. The share of renewable energy in the global final 20 years has to some extent diluted the impact of these energy consumption will have to double from an estimated advances. For example, the population with access to starting point of at most 18 percent in 2010, implying an electricity and non-solid fuels grew respectively at 1.2 and objective of up to 36 percent by 2030. 1.1 percent annually over 1990-2010, yet this was slightly The world made major advances on the energy front in the last 20 years … yet rapid demographic and economic growth has to some extend diluted the impact of these advances. executive summary vi Objective 1 Objective 2 Objective 3 Doubling share Doubling global of renewable Universal access to modern energy services rate of improvement energy in global of energy efficiency energy mix Percentage of Percentage of Rate of improvement population with Renewable energy Proxy indicator population with in energy intensity* primary reliance on share in TFEC (%) electricity access (%) non-solid fuels Historic reference 1990 76 47 16.6 –1.3 Starting point 2010 83 59 18.0 Objective for 2030 100 100 –2.6 36.0 Table ES.1 SE4ALL objectives in historical perspective Source: Authors. Note: TFEC = total final energy consumption *Measured in primary energy terms and GDP at purchasing power parity Groups of “high-impact” and “fast-moving” countries hold the key While progress in all countries is important, achievement objective globally will depend critically on the progress that of the global SE4ALL objectives will depend critically on can be made in these countries. A third group of 20 high- the efforts of certain high-impact countries that have a income and emerging economies accounts for four-fifths particularly large weight in aggregate global performance. of global energy consumption. Thus, the achievement of Two overlapping groups of 20 such countries in Asia and the global SE4ALL objectives for renewable energy and Africa account for about two-thirds of the global electrifica- energy efficiency will not be possible without major prog- tion deficit and four-fifths of the global deficit in access to ress in these high-impact countries. non-solid fuels (figure ES.1). Meeting the universal access Electricity use in classroom to support use of information technology in Namibia. Photo: John Hogg / World Bank vii Global tracking framework Electricity access non-solid fuel access Primary energy demand Electricity access deficit Non-solid fuel access deficit Primary energy demand deficit (million) deficit (million) (exajoules) (millions of people) (millions of people) (exajoules) India 306 306.2 India 705 705 China 107 107.4 Nigeria 82 82.4 China 613 612.8 USA 93 92.8 Bangladesh 67 66.6 Bangladesh 135 134.9 Russia 29 29.4 Ethiopia 64 63.9 Indonesia 131 131.2 India 29 29 Congo, DR 56 55.9 Nigeria 118 117.8 Japan 21 20.8 Tanzania 38 38.2 Pakistan 111 110.8 Germany 14 13.7 Kenya 31 31.2 Ethiopia 81 81.1 Brazil 11 11.1 Sudan 31 30.9 Congo, DR 61 61.3 France 11 11 Uganda 28 28.5 Vietnam 49 49.4 Canada 10 10.5 Myanmar 25 24.6 Philippines 46 46.2 S. Korea 10 10.5 Mozambique 20 19.9 Myanmar 44 44 Iran 9 8.7 Afghanistan 18 18.5 Tanzania 42 42.3 Indonesia 9 8.7 Korea, DR 18 18 Sudan 34.6 UK 8 8.5 Madagascar 18 17.8 Kenya 32.6 Mexico 8 7.5 Philippines 16 15.6 Uganda 32.2 Italy 7 7.1 Pakistan 15 15 Afghanistan 26.7 S. Arabia 7 7.1 Burkina Faso 14 14.3 Nepal 24.6 S. Africa 6 5.7 Niger 14 14.1 Mozambique 22.2 Ukraine 6 5.5 Indonesia 14 14 Korea, DR 22.2 Spain 5 5.3 Malawi 14 13.6 Ghana 20.4 Australia 5 5.2 figure es.1 Overview of high-impact countries, 2010 Source: Authors. Note: DR = “Democratic Republic of.” FIG o.27 overview of high-impact countries SOURCE: WB, WHO, IEA In charting a course toward the achievement of the SE4ALL relatively easy to make. In the case of renewable energy, objectives, it will also be important to learn from the experi- the fastest-moving countries have experienced compound ence of fast-moving countries that made particularly rapid annual growth rates of 10–15 percent in the consumption progress on the three energy indicators over the period of energy from renewable sources (excluding traditional 1990–2010. In the case of electrification and cooking fuel, biomass), albeit from a very low base. the most fast-moving countries have expanded access by around 3–4 percentage points of their population each On all three aspects of energy sector development, China, year. The most rapid improvements in energy intensity, and to a lesser extent India, stand out as being both amounting to a compound annual growth rate of minus 4–8 high-impact and fast-moving countries. percent, have been achieved in countries that began with high levels of energy intensity, where efficiency gains were The achievement of the global SE4ALL objectives will depend critically on the efforts of certain high-impact countries that have a particularly large weight in aggregate global performance. executive summary viii Electric lighting supports evening commerce in Morocco. Photo: Arne Hoel / World Bank Gauging the scale of the sustainable energy challenge … What will it take to achieve SE4ALL’s three energy objec- objectives are tentatively estimated to be at least $600–800 tives globally by 2030? Scenarios based on global energy billion per year over and above existing levels, entailing a models make it possible to gauge the scale of the global doubling or tripling of financial flows over current levels. effort required to meet the three objectives. Those scenarios The bulk of those investments are associated with the make it plain that business as usual will not remotely suffice. energy efficiency and renewable energy objectives, with With regard to universal access, business as usual would access-related expenditures representing a relatively small leave 12 percent and 31 percent of the world’s population percentage of the incremental costs (10–20 percent). in 2030 without electricity and modern cooking solutions, Achieving such a steep increase in financing for energy is respectively. With regard to energy efficiency, implementing unlikely to be possible without substantial investment from all currently available measures with reasonable payback the private sector. periods would be enough to meet or even exceed the SE4ALL objective. However, barriers hold back the adop- The global energy models also help to clarify the kinds of tion of many of those measures, with the result that their policy measures that would be needed to reach the three current uptake is relatively low, ranging from about about sustainable energy objectives. The IEA’s World Energy 20 percent for power generation and building construction Outlook (WEO) and the Global Energy Assessment (GEA) to about 40 percent for manufacturing and transportation. of the International Institute for Applied Systems Analysis With regard to renewable energy, few scenarios point to (IIASA) coincide in highlighting the importance of phasing renewable energy shares above 30 percent by 2030. out fossil fuel subsidies, pricing energy to fully reflect all the associated local and global environmental costs, Actual global investment in the areas covered by the three embracing consistent global technology standards for SE4ALL objectives has been estimated at about $400 bil- energy efficiency, and carefully designing targeted subsidies lion in 2010. The investments required to achieve the three to increase access to electricity and clean cooking fuels. ix Global tracking framework Business as usual will not remotely suffice ... achieving the three global SE4ALL objectives will require bold policy measures to stimulate a doubling or tripling of financial flows over current levels. … and the shortest paths to the goal The Global Tracking Framework also clarifies the likely neither energy efficiency nor renewable energy measures pattern of efforts across geographical regions toward the alone will be sufficient to contain global warming to within achievement of the three objectives, based on their starting two degrees Celsius by 2030, but that the two, in tandem, points, their potential for improvement, and their compar- could bring that objective much closer. At the same time, ative advantage. For energy efficiency, the highest rates of achieving universal access to modern energy would improvement—about minus 4 percent annually—are pro- raise global carbon dioxide emissions by a negligible jected for Asia (particularly China) and the countries of the 0.6 percent over business as usual. The GEA estimates former Soviet Union. For renewable energy, Latin America that the probability of limiting global warming to two and Sub-Saharan Africa (the latter owing to its strong reliance degrees Celsius increases to between 66 and 90 percent on traditional biomass) emerge as the regions projected to when the SE4ALL objectives for renewable energy and reach the highest share of renewable energy in 2030—in energy efficiency are simultaneously met—higher than if excess of 50 percent, while much of the rest of the world either objective were met individually. The achievement of will be in the 20–40 percent range. the universal access objective for modern cooking, which would increase reliance on typically fossil-based non- Moreover, the global energy models clarify how the three solid fuels for cooking, would have a small offsetting effect, SE4ALL objectives interact with each other (generally in a reducing the share of renewable energy in the global mix complementary way) and how they affect climate change by some two percentage points, with a negligible impact and other global concerns. The achievement of the renew- on the probability of achieving the two degree Celsius target. able energy objective, for example, will be facilitated by strong progress on energy efficiency that dampens growth in overall energy demand. Moreover, the IEA finds that Better statistical methods for better tracking Looking ahead, while the methodology of the SE4ALL Global of biomass. For energy efficiency, the main concern is to Tracking Framework provides an adequate basis for basic strengthen countries’ capacity to produce disaggregated global tracking, the framework could be vastly improved. data on sectoral and subsectoral energy consumption that To effectively monitor progress through 2030, incremental are fully integrated with measures of the output of those investments in energy data systems will be essential, both same sectors. In the case of renewable energy, the main at the global and national levels. These cost-effective, high- priority will be to improve the ability to gauge the sustain- impact improvements could be implemented over the ability of various forms of renewable energy, particularly next five years contingent on the availability of financial traditional biomass. All of these statistical improvements resources. For energy access, the focus will be to go are required to support the conception and execution of beyond binary measures to a multi-tier framework that policies that produce tangible results. Developing the better captures the quantity and quality of electricity sup- capacity of countries to develop and respond to improved plied, as well as the efficiency, safety and convenience indicators is in itself a significant task. of household cookstoves, including those that make use executive summary x Electricity powers critical health equipment to support delivery of newborn baby in Argentina. Photo: Nahuel Berger / World Bank Bold policy and an enabling environment for investment and innovation Finally, given the scale of the challenge of meeting the three mix. A detailed analysis of the policy environment at the SE4ALL objectives for energy, it is clear that bold policy country level lies beyond the immediate scope of this measures, combined with a regulatory and institutional Global Tracking Framework, which has focused on the environment that supports innovation and encourages monitoring of global progress toward the stated SE4ALL investment, will be required to produce the requisite objectives. However, it will be an important focus for future increases in the energy sector’s capacity to widen access, work in support of the critical social, economic, and envi- boost the output derived from a given unit of energy, and ronmental goals that the SE4ALL initiative addresses. raise the share of renewable energy in the overall energy xi Global tracking framework Acronyms and abbreviations Agence de l'Environnement et de la Maîtrise de l'Énergie, France (French Agency for ADEME Environment and Energy Management) adt air dry tonne AGECC Advisory Group on Energy and Climate Change bcm billion cubic meters BLEN biogas-LPG-electricity-natural gas BNEF Bloomberg New Energy Finance BP British Petroleum CAGR compound annual growth rate CCA Caucasian and Central Asia region CCS carbon capture and storage CIF cost, insurance and freight CIS Commonwealth of Independent States CPA Centrally Planned Asia region CPS Current Policies Scenario (International Energy Agency) CSP concentrating solar thermal power DCF discounted cash flow DHS Demographic and Health Survey EA East Asia region EE Eastern Europe region EIA Energy Information Administration, U.S. Department of Energy EJ exajoule (one million trillion joules, 1018J) EREC European Renewable Energy Council EU European Union EUEI European Union Energy Initiative Eurostat Statistical Office of the European Union EWS Efficient World Scenario of the International Energy Agency FAO Food and Agriculture Organization FITP feed-in tariff policy FOB free on board FSU former Soviet Union region GBEP Global Bioenergy Partnership GDP gross domestic product GEA Global Energy Assessment (IIASA) GHG greenhouse gas Acronyms and abbreviations xii GJ gigajoule (one billion joules, 109J) GNI gross national income GW gigawatt (one billion watts, 109W) GWEC Global Wind Energy Council GWh gigawatt-hour (one billion watt-hours) HAP household air pollution HIC high-income country IAEA International Atomic Energy Agency ICP International Comparison Program IEA International Energy Agency IHA International Hydropower Association IIASA International Institute for Applied Systems Analysis ILUC indirect land use change IMF International Monetary Fund IPCC Intergovernmental Panel on Climate Change IRENA International Renewable Energy Agency ISIC United Nations International Standard Industrial Classification of All Economic Activities ISO International Standards Organization IWA International Workshop Agreement kWh kilowatt-hour (one thousand watt-hours) LAC Latin America and Caribbean region LCOE levelized cost of energy LIC low-income country LMDI logarithmic mean divisia index LMIC lower middle-income country LPG liquefied petroleum gas LSMS living standards measurement survey MDG Millennium Development Goal MER market exchange rate MICS middle-income countries Mtce million tons of coal equivalent Mtoe million tons of oil equivalent MW megawatt (one million watts, 10 6W) NAF North Africa region NAM North America region NCRE nonconventional renewable energy (i.e. renewable energy excluding biomass and hydro) xiii Global tracking framework NGO nongovernmental organization NPS New Policies Scenario of the International Energy Agency NSS National Sample Survey OECD Organisation for Economic Co-operation and Development PAT perform, achieve, and trade PJ petajoule (one thousand trillion joules, 1015J) PLDV passenger light duty vehicle PLI price level index PPEO Poor People’s Energy Outlook PPP purchasing power parity PV photovoltaic R&D research and development RE renewable energy REN21 Renewable Energy Policy Network for the 21st Century RPS Renewables Portfolio Standard SA South Asia region SARA serviceability and readiness assessment SAS South Asia region SE4ALL Sustainable Energy for All SEA Southeast Asia region SIDS small island developing states SSA Sub-Saharan Africa region T&D transmission and distribution TFC total final consumption TFEC total final energy consumption TJ terajoule (one trillion joules, 1012J) tn trillion TPED total primary energy demand TWh terawatt-hour (one trillion watt-hours) UK United Kingdom UMIC upper middle-income country UN United Nations UNDP United Nations Development Programme UNEP United Nations Environment Programme UNESCO United Nations Educational, Scientific, Cultural Organization UNIDO United Nations Industrial Development Organization Acronyms and abbreviations xiv VA value added WA West Asia region WACC weighted average cost of capital WDI World Development Indicators (World Bank) WEC World Energy Council WEO World Energy Outlook (IEA) or World Economic Outlook (IMF) WEU Western Europe region WHO World Health Organization WHS World Health Survey WWF World Wide Fund For Nature ton / tonne = metric tons (International System). $ = U.S. dollar unless otherwise indicated. xv Global tracking framework Regional classifications used in this report The table below allows interested readers to quickly check according to regional classifications defined and followed the regional classification of any country with respect to by the two organizations. Those classifications do not cor- the data appearing in any part of the SE4ALL Global Track- respond with those of the United Nations, either in name ing Framework (GTF). Following the country table are four or in scope. Because the IEA and IIASA outputs studied in short tables presenting the four regional classifications section 4 for chapters 2–4 are available only in regionally found in this volume. aggregated form, the GTF could not convert them into the UN-MDG classification. For that reason, they are presented The GTF analyzes data on countries and regions. Those according to the original regional classifications used by data are obtained from a variety of sources. When aggre- the IEA and IIASA. gating data and reporting the results of its analyses, SE4ALL has followed, wherever possible, the regional classification Sections 1–3 of chapter 2 deviate slightly from the same devised by the United Nations for tracking progress on the sections of chapters 3 and 4 in that they use the designa- Millennium Development Goals (http://mdgs.un.org/unsd/ tion “developed countries” to refer to all countries whose mdg/host.aspx?content=data/regionalgroupings).That populations are assumed to have 100 percent access to rule holds for the first three sections of chapters 2–4 of electricity and modern cooking fuels, so that these coun- this report. The fourth section of those chapters, however, tries are not included in the aggregates for their respective relies on data and analysis from the International Energy geographical regions. Chapters 3 and 4, break the devel- Agency (IEA) and the International Institute for Applied oped countries down by region. Systems Analysis (IIASA), whose outputs are aggregated Regional classifications used in chapters 2–4 of SE4ALL Global Tracking Framework, by country Region Section 4 Country International Institute for Sections 1–3 International Energy Applied Systems Analysis, Agency, World Energy Global Energy Outlook 2012 Assessment 2012 Afghanistan Southern Asia Developing Asia South Asia Chapter 2: Developed Albania Eastern Europe / Eurasia Central and Eastern Europe Chapters 3-4: Europe Middle East and North Algeria Northern Africa Africa Africa Chapter 2: Oceania American Samoa n.a. Other Pacific Asia Chapters 3-4: n.a. Chapter 2: Developed Andorra Western Europe Chapters 3-4: n.a. Angola Sub-Saharan Africa Africa Sub-Saharan Africa Latin America and the Antigua and Barbuda Latin America and Caribbean South America Caribbean Latin America and the Argentina Latin America and Caribbean South America Caribbean Armenia Caucasus and Central Asia Eastern Europe / Eurasia Former Soviet Union Regional classifications used in this report xvi Region Section 4 Country International Institute for Sections 1–3 International Energy Applied Systems Analysis, Agency, World Energy Global Energy Outlook 2012 Assessment 2012 Chapter 2: Latin America and Aruba Caribbean South America n.a. Chapters 3-4: n.a. Chapter 2: Developed Australia Asia Oceania Pacific OECD Chapters 3-4: Oceania Chapter 2: Developed Austria Europe Western Europe Chapters 3-4: Europe Azerbaijan Caucasus and Central Asia Eastern Europe / Eurasia Former Soviet Union Latin America and the Bahamas Latin America and Caribbean South America Caribbean Middle East and North Bahrain Western Asia Middle East Africa Bangladesh Southern Asia Developing Asia South Asia Latin America and the Barbados Latin America and Caribbean South America Caribbean Chapter 2: Developed Belarus Eastern Europe / Eurasia Former Soviet Union Chapters 3-4: Eastern Europe Chapter 2: Developed Belgium Europe Western Europe Chapters 3-4: Europe Latin America and the Belize Latin America and Caribbean South America Caribbean Benin Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Latin America and the Bermuda South America Chapters 3-4: n.a. Caribbean Bhutan Southern Asia Developing Asia South Asia Bolivia, Plurinational State Latin America and the Latin America and Caribbean South America of Caribbean Chapter 2: Developed Bosnia and Herzegovina Eastern Europe / Eurasia Central and Eastern Europe Chapters 3-4: Europe Botswana Sub-Saharan Africa Africa Sub-Saharan Africa Latin America and the Brazil Latin America and Caribbean South America Caribbean Brunei Darussalam Southeastern Asia Developing Asia Other Pacific Asia Chapter 2: Developed Bulgaria Eastern Europe / Eurasia Central and Eastern Europe Chapters 3-4: Eastern Europe Burkina Faso Sub-Saharan Africa Africa Sub-Saharan Africa Burundi Sub-Saharan Africa Africa Sub-Saharan Africa Centrally planned Asia and Cambodia Southeastern Asia Developing Asia China Cameroon Sub-Saharan Africa Africa Sub-Saharan Africa xvii Global tracking framework Region Section 4 Country International Institute for Sections 1–3 International Energy Applied Systems Analysis, Agency, World Energy Global Energy Outlook 2012 Assessment 2012 Chapter 2: Developed Canada North America North America Chapters 3-4: North America Cape Verde Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Latin America and Cayman Islands Caribbean South America n.a. Chapters 3-4: n.a. Central African Republic Sub-Saharan Africa Africa Sub-Saharan Africa Chad Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Channel Islands Western Europe Chapters 3-4: n.a. Latin America and the Chile Latin America and Caribbean South America Caribbean Centrally planned Asia and China Eastern Asia Developing Asia China Centrally planned Asia and China, Hong Kong SAR Eastern Asia n.a. China China, Macau SAR Eastern Asia Developing Asia Latin America and the Colombia Latin America and Caribbean South America Caribbean Comoros Sub-Saharan Africa Africa Sub-Saharan Africa Congo Sub-Saharan Africa Africa Sub-Saharan Africa Congo, Democratic Repub- Sub-Saharan Africa Africa Sub-Saharan Africa lic of Latin America and the Costa Rica Latin America and Caribbean South America Caribbean Cote d'Ivoire Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Croatia Eastern Europe / Eurasia Central and Eastern Europe Chapters 3-4: Europe Chapter 2: Latin America and Latin America and the Cuba Caribbean South America Caribbean Chapters 3-4: n.a. Chapter 2: Latin America and Curaçao Caribbean n.a. n.a. Chapters 3-4: n.a. Chapter 2: Developed Cyprus Eastern Europe / Eurasia Western Europe Chapters 3-4: Western Asia Chapter 2: Developed Czech Republic Europe Central and Eastern Europe Chapters 3-4: Eastern Europe Chapter 2: Developed Denmark Europe Western Europe Chapters 3-4: Europe Regional classifications used in this report xviii Region Section 4 Country International Institute for Sections 1–3 International Energy Applied Systems Analysis, Agency, World Energy Global Energy Outlook 2012 Assessment 2012 Djibouti Sub-Saharan Africa Africa Sub-Saharan Africa Latin America and the Dominica Latin America and Caribbean South America Caribbean Latin America and the Dominican Republic Latin America and Caribbean South America Caribbean Latin America and the Ecuador Latin America and Caribbean South America Caribbean Middle East and North Egypt Northern Africa Africa Africa Latin America and the El Salvador Latin America and Caribbean South America Caribbean Equatorial Guinea Sub-Saharan Africa Africa Sub-Saharan Africa Eritrea Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Estonia Europe Central and Eastern Europe Chapters 3-4: Europe Ethiopia Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Faeroe Islands n.a. Western Europe Chapters 3-4: n.a. Fiji Oceania Developing Asia Other Pacific Asia Chapter 2: Developed Finland Europe Western Europe Chapters 3-4: Europe Chapter 2: Developed France Europe Western Europe Chapters 3-4: Europe Chapter 2: Oceania French Polynesia Developing Asia Other Pacific Asia Chapters 3-4: n.a. Gabon Sub-Saharan Africa Africa Sub-Saharan Africa Gambia Sub-Saharan Africa Africa Sub-Saharan Africa Georgia Caucasus and Central Asia Eastern Europe / Eurasia Former Soviet Union Chapter 2: Developed Germany Europe Western Europe Chapters 3-4: Europe Ghana Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Greece Europe Western Europe Chapters 3-4: Europe Chapter 2: Developed Greenland n.a. Western Europe Chapters 3-4: n.a. Latin America and the Grenada Latin America and Caribbean South America Caribbean Chapter 2: Oceania Guam n.a. n.a. Chapters 3-4: n.a. Latin America and the Guatemala Latin America and Caribbean South America Caribbean xix Global tracking framework Region Section 4 Country International Institute for Sections 1–3 International Energy Applied Systems Analysis, Agency, World Energy Global Energy Outlook 2012 Assessment 2012 Guinea Sub-Saharan Africa Africa Sub-Saharan Africa Guinea-Bissau Sub-Saharan Africa Africa Sub-Saharan Africa Latin America and the Guyana Latin America and Caribbean South America Caribbean Latin America and the Haiti Latin America and Caribbean South America Caribbean Latin America and the Honduras Latin America and Caribbean South America Caribbean Chapter 2: Developed Hungary Europe Central and Eastern Europe Chapters 3-4: Eastern Europe Chapter 2: Developed Iceland Europe Western Europe Chapters 3-4: Europe India Southern Asia Developing Asia South Asia Indonesia Southeastern Asia Developing Asia Other Pacific Asia Middle East and North Iran, Islamic Republic of Southern Asia Middle East Africa Middle East and North Iraq Western Asia Middle East Africa Chapter 2: Developed Ireland Europe Western Europe Chapters 3-4: Europe Chapter 2: Developed Isle of Man n.a. Western Europe Chapters 3-4: n.a. Chapter 2: Developed Middle East and North Israel Europe Chapters 3-4: Western Asia Africa Chapter 2: Developed Italy Europe Western Europe Chapters 3-4: Europe Latin America and the Jamaica Latin America and Caribbean South America Caribbean Chapter 2: Developed Japan Asia Oceania Pacific OECD Chapters 3-4: Eastern Asia Middle East and North Jordan Western Asia Middle East Africa Kazakhstan Caucasus and Central Asia Eastern Europe / Eurasia Former Soviet Union Kenya Sub-Saharan Africa Africa Sub-Saharan Africa Kiribati Oceania Developing Asia Chapter 2: Developed Centrally planned Asia and Korea, Dem. Rep. Developing Asia Chapters 3-4: n.a. China Korea, Rep. of Eastern Asia Asia Oceania Other Pacific Asia Chapter 2: Developed Kosovo n.a. n.a. Chapters 3-4: n.a. Regional classifications used in this report xx Region Section 4 Country International Institute for Sections 1–3 International Energy Applied Systems Analysis, Agency, World Energy Global Energy Outlook 2012 Assessment 2012 Middle East and North Kuwait Western Asia Middle East Africa Kyrgyzstan Caucasus and Central Asia Eastern Europe / Eurasia Former Soviet Union Centrally planned Asia and Laos Southeastern Asia Developing Asia China Chapter 2: Developed Latvia Eastern Europe / Eurasia Eastern Europe / Eurasia Chapters 3-4: Europe Middle East and North Lebanon Western Asia Middle East Africa Lesotho Sub-Saharan Africa Africa Sub-Saharan Africa Liberia Sub-Saharan Africa Africa Sub-Saharan Africa Middle East and North Libya Northern Africa Africa Africa Chapter 2: Developed Liechtenstein n.a. Western Europe Chapters 3-4: n.a. Chapter 2: Developed Lithuania Eastern Europe / Eurasia Central and Eastern Europe Chapters 3-4: Europe Chapter 2: Developed Luxembourg Europe Western Europe Chapters 3-4: Europe Macedonia, Former Yugo- Chapter 2: Developed Chap- Eastern Europe / Eurasia Central and Eastern Europe slav Republic of ters 3-4: Europe Madagascar Sub-Saharan Africa Africa Sub-Saharan Africa Malawi Sub-Saharan Africa Africa Sub-Saharan Africa Malaysia Southeastern Asia Developing Asia Other Pacific Asia Maldives Southern Asia Developing Asia South Asia Mali Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Malta Eastern Europe / Eurasia Western Europe Chapters 3-4: Europe Chapter 2: Developed Marshall Islands n.a. n.a. Chapters 3-4: n.a. Mauritania Sub-Saharan Africa Africa Sub-Saharan Africa Mauritius Sub-Saharan Africa Africa Sub-Saharan Africa Latin America and the Mexico Latin America and Caribbean North America Caribbean Chapter 2: Oceania Micronesia, Fed. States of n.a. n.a. Chapters 3-4: n.a. Chapter 2: Developed Moldova, Republic of Eastern Europe / Eurasia Former Soviet Union Chapters 3-4: Eastern Europe Monaco n.a. n.a. Western Europe Centrally planned Asia and Mongolia Eastern Asia Developing Asia China xxi Global tracking framework Region Section 4 Country International Institute for Sections 1–3 International Energy Applied Systems Analysis, Agency, World Energy Global Energy Outlook 2012 Assessment 2012 Chapter 2: Developed Montenegro n.a. n.a. Chapters 3-4: Europe Middle East and North Morocco Northern Africa Africa Africa Mozambique Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Southeastern Asia Myanmar Developing Asia Other Pacific Asia Chapters 3-4: n.a. Namibia Sub-Saharan Africa Africa Sub-Saharan Africa Nepal Southern Asia Developing Asia South Asia Chapter 2: Developed Netherlands Europe Western Europe Chapters 3-4: Europe Chapter 2: Oceania New Caledonia Developing Asia Other Pacific Asia Chapters 3-4: n.a. Chapter 2: Developed New Zealand Asia Oceania Pacific OECD Chapters 3-4: Oceania Latin America and the Nicaragua Latin America and Caribbean South America Caribbean Niger Sub-Saharan Africa Africa Sub-Saharan Africa Nigeria Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Norway Europe Western Europe Chapters 3-4: Europe Middle East and North Oman Western Asia Middle East Africa Pakistan Southern Asia Developing Asia South Asia Palau Oceania n.a. n.a. Latin America and the Panama Latin America and Caribbean South America Caribbean Papua New Guinea Oceania Developing Asia Other Pacific Asia Latin America and the Paraguay Latin America and Caribbean South America Caribbean Latin America and the Peru Latin America and Caribbean South America Caribbean Philippines Southeastern Asia Developing Asia Other Pacific Asia Chapter 2: Developed Poland Europe Central and Eastern Europe Chapters 3-4: Eastern Europe Chapter 2: Developed Portugal Europe Western Europe Chapters 3-4: Europe Chapter 2: Latin America and Puerto Rico Caribbean n.a. North America Chapters 3-4: n.a. Regional classifications used in this report xxii Region Section 4 Country International Institute for Sections 1–3 International Energy Applied Systems Analysis, Agency, World Energy Global Energy Outlook 2012 Assessment 2012 Middle East and North Qatar Western Asia Middle East Africa Chapter 2: Developed Romania Eastern Europe / Eurasia Central and Eastern Europe Chapters 3-4: Eastern Europe Chapter 2: Developed Russian Federation Eastern Europe / Eurasia Former Soviet Union Chapters 3-4: Eastern Europe Rwanda Sub-Saharan Africa Africa Sub-Saharan Africa Latin America and the Saint Lucia Latin America and Caribbean South America Caribbean Samoa Oceania Developing Asia Chapter 2: Developed San Marino n.a. n.a. Chapters 3-4: n.a. Sao Tome and Principe Sub-Saharan Africa Africa Sub-Saharan Africa Middle East and North Saudi Arabia Western Asia Middle East Africa Senegal Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Serbia Eastern Europe / Eurasia Chapters 3-4: Europe Seychelles Sub-Saharan Africa Africa Sub-Saharan Africa Sierra Leone Sub-Saharan Africa Africa Sub-Saharan Africa Singapore Southeastern Asia Developing Asia Other Pacific Asia Chapter 2: Developed Slovak Republic Europe Central and Eastern Europe Chapters 3-4: Eastern Europe Chapter 2: Developed Slovenia Europe Central and Eastern Europe Chapters 3-4: Europe Solomon Islands Oceania Developing Asia Other Pacific Asia Chapter 2: Sub-Saharan Somalia Africa Africa Sub-Saharan Africa Chapters 3-4: n.a. South Africa Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Sub-Saharan South Sudan Africa n.a. n.a. Chapters 3-4: n.a. Chapter 2: Developed Spain Europe Western Europe Chapters 3-4: Europe Sri Lanka Southern Asia Developing Asia South Asia Latin America and the St. Kitts and Nevis Latin America and Caribbean South America Caribbean xxiii Global tracking framework Region Section 4 Country International Institute for Sections 1–3 International Energy Applied Systems Analysis, Agency, World Energy Global Energy Outlook 2012 Assessment 2012 Chapter 2: Latin America and St. Martin (French part) Caribbean n.a. n.a. Chapters 3-4: n.a. St. Vincent and the Gren- Latin America and the Latin America and Caribbean South America adines Caribbean Middle East and North Sudan Sub-Saharan Africa Africa Africa Latin America and the Suriname Latin America and Caribbean South America Caribbean Swaziland Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Sweden Europe Western Europe Chapters 3-4: Europe Chapter 2: Developed Switzerland Europe Western Europe Chapters 3-4: Europe Middle East and North Syrian Arab Republic Western Asia Middle East Africa Tajikistan Caucasus and Central Asia Eastern Europe / Eurasia Former Soviet Union Tanzania, United Republic Sub-Saharan Africa Africa Sub-Saharan Africa of Thailand Southeastern Asia Developing Asia Other Pacific Asia Timor-Leste Southeastern Asia Developing Asia n.a. Togo Sub-Saharan Africa Africa Sub-Saharan Africa Tonga Oceania Developing Asia Other Pacific Asia Latin America and the Trinidad and Tobago Latin America and Caribbean South America Caribbean Middle East and North Tunisia Northern Africa Africa Africa Turkey Western Asia Europe Western Europe Turkmenistan Caucasus and Central Asia Eastern Europe / Eurasia Former Soviet Union Chapter 2: Latin America and Turks and Caicos Islands Caribbean South America n.a. Chapters 3-4: n.a. Chapter 2: Oceania Tuvalu n.a. n.a. Chapters 3-4: n.a. Uganda Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Developed Ukraine Eastern Europe / Eurasia Former Soviet Union Chapters 3-4: Eastern Europe Middle East and North United Arab Emirates Western Asia Middle East Africa United Kingdom of Great Chapter 2: Developed Europe Western Europe Britain and Northern Ireland Chapters 3-4: Europe Regional classifications used in this report xxiv Region Section 4 Country International Institute for Sections 1–3 International Energy Applied Systems Analysis, Agency, World Energy Global Energy Outlook 2012 Assessment 2012 Chapter 2: Developed United States of America North America North America Chapters 3-4: North America Latin America and the Uruguay Latin America and Caribbean South America Caribbean Uzbekistan Caucasus and Central Asia Eastern Europe / Eurasia Former Soviet Union Vanuatu Oceania Developing Asia Other Pacific Asia Latin America and the Venezuela Latin America and Caribbean South America Caribbean Centrally planned Asia and Vietnam Southeastern Asia Developing Asia China Chapter 2: Latin America and Virgin Islands (U.S.) Caribbean n.a. North America Chapters 3-4: n.a. Chapter 2: Western Asia West Bank and Gaza n.a. n.a. Chapters 3-4: n.a. Middle East and North Yemen Western Asia Middle East Africa Zambia Sub-Saharan Africa Africa Sub-Saharan Africa Chapter 2: Sub-Saharan Zimbabwe Africa Africa Sub-Saharan Africa Chapters 3-4: n.a. UN-MDG regions and regional abbreviations appearing in sections 1–3 of chapter 2 Region Abbreviation Region Abbreviation Caucasus and Central Asia CCA Oceania n.a. Developed countries DEV Southern Asia SA Eastern Asia EA Southeastern Asia SEA Latin America and Caribbean LAC Sub-Saharan Africa SSA Northern Africa NA Western Asia SAS xxv Global tracking framework UN-MDG regions and regional abbreviations appearing in sections 1–3 of chapters 3 and 4 Region Abbreviation Region Abbreviation Caucasus and Central Asia CCA Northern Africa NAf Eastern Asia EA North America NAm Eastern Europe EE Oceania n.a. Europe EU Southeastern Asia SEA Latin America and Caribbean LAC Southern Asia SA Middle East and North Africa MEA Sub-Saharan Africa SSA Western Asia WA IEA regions appearing in section 4 of chapters 2–4: Region Region Africa Europe Asia Oceania Middle East Developing Asia North America Eastern Europe/Eurasia South America IIASA regions and regional abbreviations appearing in section 4 of chapters 2–4 Region Abbreviation Region Abbreviation Central and Eastern Europe EEU North America NAM Centrally planned Asia and CPA Pacific OECD PAO China Former Soviet Union FSU Other Pacific Asia PAS Latin America and Caribbean LAM South Asia SAS Middle East and North Africa MEA Sub-Saharan Africa AFR Western Europe WEU Regional classifications used in this report xxvi Overview Overview In declaring 2012 the “International Year of Sustainable Energy for All,” the UN General Assembly established three global objectives to be accomplished by 2030: to ensure universal access to modern energy services,1 to double the global rate of improvement in global energy efficiency, and to double the share of renewable energy in the global energy mix. Some 70 countries have formally embraced the Secretary General’s initiative, while numerous corporations and agencies have pledged tens of billions of dollars to achieve its objectives. As 2012 drew to a close, the UN General Assembly announced a “Decade of Sustainable Energy for All” stretching from 2014 to 2024. The Secretary General provided a compelling rationale for SE4ALL in his announcement of the new program. For further information about the SE4ALL initiative, please go to www.sustainableenergyforall.org. The SE4ALL Global Tracking Framework full report, overview paper, executive summary and datasets can be downloaded from: www.worldbank.org/se4all. The SE4ALL objectives are global objectives, applying to Framework described in this report provides a system for both developed and developing countries, with individual regular global reporting, based on rigorous—yet practical nations setting their own domestic targets in a way that is —technical measures. Although the technical definitions consistent with the overall spirit of the initiative. Because required for the framework pose significant methodological countries differ greatly in their ability to pursue each of the challenges, those challenges are no more complex than three objectives, some will make more rapid progress in those faced when attempting to measure other aspects of one area while others will excel elsewhere, depending on development—such as poverty, human health, or access their respective starting points and comparative advantages to clean water and sanitation—for which global progress as well as on the resources and support that they are able has long been tracked. to marshal. For the time being, the SE4ALL tracking framework must The three SE4ALL objectives, though distinct, form an inte- draw upon readily available global databases, which vary grated whole. Because they are related and complementary, in their usefulness for tracking the three central variables of it is more feasible to achieve all three jointly than it would interest. Over the medium term, the framework includes a be to pursue any one of them individually. In particular, concerted effort to improve these databases as part of the achievement of the energy efficiency objective would make SE4ALL initiative (table O.1). This report lays out an agenda the renewable energy objective more feasible by slowing for the incremental improvement of available global energy the growth in global demand for energy. Tensions between databases in those areas likely to yield the highest value the goals also exist, though they are less pronounced than for tracking purposes. the complementarities. One possible tension between the objectives is that the achievement of universal access to While global tracking is very important, it can only help to modern cooking solutions will tend to shift people from portray the big picture. Appropriate country tracking is an reliance on traditional biomass, a renewable source of essential complement to global tracking and will allow for a energy, to greater reliance on non-solid fuels that are typi- much richer portrait of energy sector developments. Global cally (though not always) based on fossil fuels. tracking and country tracking need to be undertaken in a consistent manner, and the Global Tracking Framework To sustain momentum for the achievement of the SE4ALL provides guidance that will be of interest to all countries objectives, a means of charting global progress over the participating in the SE4ALL initiative. years leading to 2030 is needed. The Global Tracking 1 The SE4ALL universal access goal will be achieved only if every person on the planet has access to modern energy services provided through electricity, clean cooking fuels, clean heating fuels, and energy for productive use and community services. overview 2 Immediate Medium term Indicators that are essential for global Proxy indicators already available for global tracking and that would require a feasible Global tracking tracking, with all data needs (past, present, incremental investment in global energy and future) already fully met data systems over the next five years Indicators highly suitable for country-level Country-level tracking Not applicable tracking and desirable for global tracking Table o.1 A phased and differentiated approach to selecting indicators for tracking The SE4ALL Global Tracking team was able to construct and energy efficiency are primarily from national energy global energy databases that cover a large group of countries balances. Indicators for individual countries can be found —ranging from 181 for clean energy and 212 for modern in the data annex to this report, as well as on-line through energy services—that cover an upwards of 98 percent of the the World Bank’s Open Data Platform: http://data.world- world’s population (table O.2). The data on energy access bank.org/data-catalog. (electrification and cooking fuels) draw primarily on house- hold surveys, while those pertaining to renewable energy Category Data sources Country coverage (% of global population) Electrification Global networks of household surveys plus some censuses 212 (100) Cooking fuels Global networks of household surveys plus some censuses 193 (99) IEA and UN for energy balances Energy intensity 181 (98) WDI for GDP and sectoral value added IEA and UN for energy balances Renewable energy 181 (98) REN 21, IRENA, and BNEF for complementary indicators Table o.2 Overview of data sources and country coverage under global tracking NOTE: IEA = International Energy Agency; UN = United Nations; REN 21 = Renewable Energy Network for the 21st Century; IRENA = International Renewable Energy Agency; BNEF = Bloomberg New Energy Finance; WDI = World Development Indicators (World Bank); GDP= gross domestic product. The SE4ALL global tracking framework sets 2010 as the fuels.2 Solid fuels are defined to include both traditional starting point against which the progress of the initiative biomass (wood, charcoal, agricultural and forest residues, will be measured. The framework provides an initial sys- dung, and so on), processed biomass (such as pellets and tem for regular global reporting, based on indicators that briquettes), and other solid fuels (such as coal and lignite). are technically rigorous and at the same time feasible to As a proxy for energy efficiency, the framework takes the compute from current global energy databases, and that compound annual growth rate of energy intensity of gross offer scope for progressive improvement over time. For domestic product (GDP) measured in purchasing power energy access, household survey evidence is used to de- parity (PPP) terms, complemented by supporting analysis termine the percentage of the population with an electricity of underlying factors as well as sectoral disaggregation. connection and the percentage with access to non-solid For renewable energy, the indicator is the share of total final 2 Non-solid fuels include (i) liquid fuels (for example, kerosene, ethanol, and other biofuels), (ii) gaseous fuels (for example, natural gas, liquefied petroleum gas [LPG], biogas), and (iii) electricity. 3 Global tracking framework energy consumption3 deriving from all renewable sources steering group for the framework is co-chaired by the World (bioenergy, aerothermal, geothermal, hydro, ocean, solar, Bank and its Energy Sector Management Assistance Pro- wind). Further methodological details and directions for gram (ESMAP , a multidonor technical assistance trust fund future improvement are provided below and described administered by the World Bank) and the IEA. Members extensively in the main report. of the group are the Global Alliance for Clean Cookstoves (the Alliance), IIASA, the International Partnership for In addition to measuring progress at the global level, the Energy Efficiency Cooperation (IPEEC), the International report sheds light on the starting point for regional and in- Renewable Energy Agency (IRENA), Practical Action, the come groupings. It also identifies two important categories Renewable Energy Network for the 21st Century (REN21), of countries: high-impact countries, whose efforts will be the United Nations Development Programme, UN–Energy, particularly critical to the achievement of the objectives the United Nations Environment Programme, the United globally; and fast-moving countries, which are already Nations Foundation, the United Nations Industrial Devel- making rapid progress toward the SE4ALL goals and may opment Organization (UNIDO), the World Energy Council have valuable policy and implementation lessons to share. (WEC), and the World Health Organization (WHO). Experts from all of these agencies have collaborated intensively in Scenarios based on the various existing global energy the development of this report. models—such as the World Energy Model of the Interna- tional Energy Agency (IEA) and the Global Energy Assess- The report also benefited from two rounds of public consul- ment (GEA) of the International Institute for Applied Sys- tation. The first round, which took place in October 2012, tems Analysis (IIASA)—clarify the scale of the challenge focused on the proposed methodology for global tracking. involved in meeting the SE4ALL objectives. In particular, It was launched by a special session of the World Ener- they illustrate the combinations of technological change, gy Council’s Executive Assembly in Monaco. The second policy frameworks, and financing flows that will be needed round, in February 2013, focused on data analysis. It was to reach the objectives. They also shed light on the rela- preceded by a consultation workshop held in conjunction tionship between the three objectives, as well as the differ- with the World Future Energy Summit in Abu Dhabi in Janu- ential contributions to global targets across world regions ary 2013. The consultation documents reached more than based on respective comparative advantage. a hundred organizations drawn from a broad cross-section of stakeholders and covering a wide geographic area. This Development of the Global Tracking Framework has been report benefited greatly from the contributions of those made possible through a unique partnership of interna- organizations. tional agencies active in the energy knowledge space. The Achieving universal access to modern energy services By some measures, progress on access to modern energy the global electrification rate increased only modestly, from services was impressive over the 20 years between 1990 76 to 83 percent, while the rate of access to non-solid fuels and 2010. The number of people with access to electricity rose from 47 to 59 percent (figure O.1). In both cases, this increased by 1.7 billion, while the number of those with represents an increase in access of about one percentage access to non-solid fuels for household cooking increased point of global population annually. by 1.6 billion. Yet this expansion was offset by global popu- lation growth of 1.6 billion over the same period. As a result, 3 Though technically energy cannot be consumed, in this report the term energy consumption means “quantity of energy applied”, following the definition in ISO 50001:2011 and the future standard ISO 13273-1 Energy efficiency and renewable energy sources - Common international terminology Part 1: Energy Efficiency. overview 4 80 60 100 100 80 40 80 60 60 20 40 40 20 20 0 0 0 sa ea a a a ea a c ev a d ia n w sas se c la el ia a sa a a c a a a ev d na a a a c ev a d ia d ss se w n c ea s n w la ss se rl c c r la n rl n d d c c a o o ea o e w w c c w o c o o figure O.1 Global and regional trends in electrification and non-solid fuel access rates, 1990–2010 figure O.1 Global and regional trends in electrification and non-solid fuel access rates, 1990–2010 figure O.1A Global and Regional Trends in figure O.1B Global 1990 and 2000 Regional 2010 Trends in 1990 2000 2010 IEA Electrification SOURCE: WB, WHO,figure 1990-2010, O.1 Global and regional Percent trends in electrificationAccess SOURCE: and WB, IEA to non-solid WHO, non-solid fuel 1990-2010, fuel access Percent rates, 1990–2010 1990 2000 2010 SOURCE: WB, WHO, IEA SOURCE: World Bank Global Electrification Database, 2012. Indicators (World Bank); WHO Global Household Energy Database, 2012. NOTE: Access numbers in millions of people. CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SEA = South-Eastern Asia; SA = Southern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. Starting point The starting point for global electrification against which Modern cooking solutions4 are important because they future progress will be measured is 83 percent in 2010. curtail harmful indoor air pollution that leads to the loss of The SE4ALL global objective is 100 percent by 2030. lives of 3.5 million people each year, mainly women and children; they also improve energy efficiency. Similar to Electrification rates likely overestimate access to electricity. electrification, rates of access to non-solid fuel do not fully The reason is that some of those with access to an elec- capture access to modern cooking solutions. The reason tricity connection receive a service of inadequate quantity, for this is that an unknown and likely growing percentage quality, or reliability of supply, which prevents them from of those without access to non-solid fuels may nonethe- reaping the full benefits of the service. A proxy for supply less be using acceptable cooking solutions based on pro- problems (albeit an imperfect one) is the average residential cessed biomass (such as fuel pellets) or other solid fuels electricity consumption derived from the IEA World Energy paired with stoves exhibiting overall emissions rates at or Statistics and Balances (2012a). Globally, the average near those of liquefied petroleum gas (LPG). At present, household electricity consumption was around 3,010 it is not possible to adequately measure the number of kilowatt-hours (kWh) per year in 2010. However, average households in this situation. It is believed to be relatively household electricity consumption varies considerably small but is expected to grow over time as governments ranging from over 6,000 kWh in developed countries to and donors place growing emphasis on more advanced around 1,000 kWh in underserved regions of South Asia biomass cookstoves as a relatively low-cost and accessible and Sub-Saharan Africa. method of improving the safety and efficiency of cooking practices. These and other methodological challenges The starting point for access to non-solid fuels for household associated with the measurement of energy access are cooking against which future progress will be measured more fully described in box O.1. is 59 percent in 2010. The SE4ALL global objective is 100 percent by 2030. 4 The term “modern cooking solutions” will be used throughout this document and includes solutions that involve electricity or gaseous fuels (including liquefied petroleum gas), or solid/liquid fuels paired with stoves exhibiting overall emissions rates at or near those of liquefied petroleum gas. 5 Global tracking framework Box O.1 Methodological challenges in defining and measuring energy access There is no universally agreed-upon definition of energy access, and it can be a challenge to determine how best to capture issues such as the quantity, quality, and adequacy of service, as well as complementary issues such as informality and affordability. Because currently available global databases only support binary global track- ing of energy access (that is, a household either has or does not have access, with no middle ground), this is the approach that will be used to determine the starting point for the SE4ALL Global Tracking Framework. Based on an exhaustive analysis of existing global household survey questionnaires, the following binary measures will be used: }} Electricity access is defined as availability of an electricity connection at home or the use of electricity as the primary source for lighting. }} Access to modern cooking solutions is defined as relying primarily on non-solid fuels for cooking. An important limitation of these binary measures is that they do not capture improvements in cookstoves that burn solid fuels, nor are they able to register progress in electrification through off-grid lighting products. In the case of electricity, the binary measure fails to take into account whether the connection provides an adequate and reliable service, which it may often fail to do. A variety of data sources—primarily household surveys (including national censuses) and in a few cases, utility data—contribute to the measurement of access. Two global databases—one on electricity and another on non-solid fuel—have been compiled: the World Bank’s Global Electrification Database and WHO’s Global Household Energy Database. IEA data on energy access were also reviewed in the preparation of these databases. Both databases encompass three datapoints for each country—around 1990, around 2000, around 2010. Given that surveys were carried out infrequently, statistical models have been developed to estimate missing datapoints. While the binary approach serves the immediate needs of global tracking, there is a growing consensus that measurements of energy access should be able to reflect a continuum of improvement. A candidate multi-tier metric put forward in this report for medium-term development under the SE4ALL initiative addresses many of the limitations of the binary measures described above: For electricity, the recommended new metric measures the degree of access to electricity supply along various dimensions. This is complemented by a parallel multi-tier framework that captures the use of key electricity services. For cooking, the candidate proposal measures access to modern cooking solutions by measuring the tech- nical performance of the primary cooking solution (including both the fuel and the cookstove) and assessing how this solution fits in with households’ daily life. For medium term country tracking, the further development of the multi-tier metric can be substantially strengthened by rigorous piloting of questionnaires, certification, and consensus building in SE4ALL opt-in countries. The metric is flexible and allows for country-specific targets to be set to adequately account for varying energy challenges. For medium-term global tracking, a condensed version of the new metric would support a three-tier access framework requiring only marginal improvements in existing global data collection instruments. The SE4ALL universal access goal will be achieved only if every person on the planet has access to modern energy services provided through electricity, clean cooking fuels, clean heating fuels, and energy for produc- tive use and community services. Although global tracking of energy sources for heating, community services, and productive uses will not be possible in the immediate future, it is recommended that an approach to track them at the country level be developed in the medium term. overview 6 With respect to electricity, the global access deficit amounts cooking, the access deficit amounts to 2.8 billion people to 1.2 billion people. Close to 85 percent of those who live who primarily rely on solid fuels. About 78 percent of that without electricity (the “nonelectrified population”) live in ru- population lives in rural areas, and 96 percent are geo- ral areas, and 87 percent are geographically concentrated graphically concentrated in Sub-Saharan Africa, Eastern in Sub-Saharan Africa and South Asia (figure O.2). For Asia, Southern Asia, and South-Eastern Asia. Oth 157 SSA Oth 157 With electricity Without 590 rural 5714 electricity 993 83% 1166 SSA With electricity Without 17% electricity 590 SA rural 5714 993 1166 418 urban 173 83% 17% SA 418 urban 173 figure O.2A Source of electrification access deficit, 2010 Oth 124 urban 598 ssa 690 Oth 124 Non Solid Fuel Solid Fuel urban 598 SA 4076 2777 ssa 690 1018 59% 41% rural Non Solid Fuel Solid Fuel SeASA308 2179 4076 2777 1018 59% 41% eA rural 637 SeA 308 2179 eA 637 figure O.2b Source of non-solid fuel access deficit, 2010 SOURCE: World Bank Global Electrification Database, 2012; WHO Global Household Energy Database, 2012. NOTE: Access numbers in millions of people. EA = Eastern Asia; SEA = South-Eastern Asia; SA = Southern Asia; SSA = Sub-Saharan Africa; oth = others. Most of the incremental electrification over the period overall in the rural space. The rate of increase in access to 1990–2010 was in urban areas, where electrification in- non-solid fuel over the two decades was higher in urban creased by 1.7 percent of the population annually, about areas, at around 1.7 percent of the population annually, twice the rate in rural areas (0.8). However, even with this with the overall urban access rate rising from 77 to 84 per- significant expansion, electrification only just kept pace cent. Rural growth in non-solid fuel use was as low as 0.6 with rapid urbanization in the same period, so that the percent annually on average, while overall access in rural overall urban electrification rate remained relatively stable, areas grew from 26 to 35 percent. Thus, most of the ex- growing from 94 to 95 percent across the period. By con- pansion in energy access between 1990 and 2010 was in trast, more modest growth in rural populations allowed the urban areas, while most of the remaining deficit in 2010 electrification rate to increase more steeply, from 61 to 70 was in rural areas (figure O.3). percent, despite a much lower level of electrification effort 7 Global tracking framework 0 1000 2000 3000 4000 5000 6000 7000 Population (million) Population with access in 1990 Incremental access in 1990-2010 Population without access in electricity non-solid cooking fuels Rural Rural Rural Urban Urban Urban Total Total Total 0 1000 2000 3000 4000 5000 6000 7000 0 1000 2000 3000 4000 5000 6000 7000 Population (million) Population (million) 0 1000 2000 3000 4000 5000 6000 7000 figure Population with access in 1990 O.3A Global Incremental accesstrends in access in 1990-2010 Populationto without access Population figure in 2010 with access O.3B in 1990 Globalaccess trends Incremental in access in 1990-2010 to without access in Population Population electricity, 1990-2010, Population million (million) fuel, 1990-2010, Population million non-solid Population with access in 1990 Incremental access in 1990-2010 Population without access in 2010 Rural SOURCE: World Bank Global Electrification Database, 2012; WHO Global Household Energy Database, 2012. Urban High-impact countries Rural Total The achievement of universal access to modern energy The access challenge is particularly significant in Sub-Sa- will depend critically on the efforts of 20 high-impact coun- haran Africa, which is the only region where the rate of 0 1000 2000 3000 4000 5000 6000 7000 tries. Together, these Urbancountries account for more than two- progress on energy access fell behind population growth Population thirds of the population (million) presently living without electricity in 1990–2010, both for electricity and for non-solid fuels. (0.9 billion Population with access in 1990 people) and more than four-fifths Incremental access in 1990-2010 of the global Among the 20 countries with the highest deficits in access, Population without access in 2010 population without Total access to non-solid fuels (2.4 billion 12 are in Sub-Saharan African countries; of those, eight people). This group of 20 countries is split between Africa report an access rate below 20 percent. Similarly, among and Asia (figure O.4). For 0 electricity, 1000India has by 2000 far 3000 the 20 the countries 4000 with the lowest 5000 6000 rates7000 of use of non-solid largest access deficit, exceeding 300 million people, while fuel for cooking, nine are Sub-Saharan African countries, for non-solid cooking fuel India and China each have Population ac- (million) of which five have rates of access to non-solid fuel below cess deficits that exceed 600 million people. 10 percent. Population with access in 1990 Incremental access in 1990-2010 Population without access in 2010 Malawi 13.6 Ghana 20.4 Indonesia 14.0 Korea, DR 22.2 Niger 14.1 Mozambique 22.2 Burkina Faso 14.3 Nepal 24.6 Pakistan 15.0 Afghanistan 26.7 Philippines 15.6 Uganda 32.2 Madagascar 17.8 Kenya 32.6 Korea, DR 18.0 Sudan 34.6 Afghanistan 18.5 Tanzania 42.3 Mozambique 19.9 Myanmar 44.0 Myanmar 24.6 Philippines 46.2 Uganda 28.5 Vietnam 49.4 Sudan 30.9 Congo, DR 61.3 Kenya 31.2 Ethiopia 81.1 Tanzania 38.2 Pakistan 110.8 Congo, DR 55.9 Nigeria 117.8 Ethiopia 63.9 Indonesia 131.2 Bangladesh 66.6 Bangladesh 134.9 China 612.8 Nigeria 82.4 India 705.0 India 306.2 0 200 400 600 800 0 50 100 150 200 250 300 350 Population (million) Population (million) figure O.4A the 20 countries with the high- figure O.4b the 20 countries with the high- est deficit in access to electricity, 2010, est deficit in access to non-solid fuel, 2010, Population million Population million SOURCE: World Bank Global Electrification Database, 2012; WHO Global Household Energy Database, 2012. NOTE: DR = “Democratic Republic of.” overview 8 Fast-moving countries In charting a course to universal access, it will be important to countries that have made the most progress on the cook- learn from those countries that have successfully achieved ing side—most of them in Asia—moved 1.2 billion people universal energy access and those that have advanced the to non-solid fuel use. Whereas the global annual average fastest toward this goal during the last two decades. The increase in access was 1.2 percent for electrification and 20 countries that have made the most progress provided 1.1 percent for non-solid fuels, the countries making the electricity to an additional 1.3 billion people in the past most progress in scaling up energy access reached an two decades. India has made particularly rapid progress, additional 3–4 percent of their population each year (figures electrifying an average of 24 million annually since 1990, O.5 and O.6). with an annual growth rate of 1.9 percent. Similarly, the 20 25 23.7 4% 20 3% 25 23.7 4% 15 12.9 20 2% 10 3% 15 12.9 5.1 5 4.6 1% 3 2.8 1.9 1.8 2% 1.6 1.3 1.3 1.1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 10 0 5.1 0% 5 4.6 1% a t o o bia pia l sia sh ria ey m n a nd a q ia an es 3 2.8 1.9 1.8 yp zi in ric di ra o xic cc na Ira 1.6 1.3 1.3 1.1 ia mb 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 n ey rk sh de a ist ud Sapia hio sia ne nd ila bia ra ria ige h yp Eg In i I az Br in ipp na Viet cc ro 0 ric Af C 0% xic Me mb lo rk Tu de gla ne do ra i A s Pak la Tha ge N o Et pp hil ro Mo lo Co Af th a t i A ud o Pl m n a a la ann q es do In i n di Ira a Ira u i ng Bt Ch ut So Eg In Br et hi Me Tu ki ai Ni Et ili Vi Pa Mo Th Co h Ph O.5 The 20 countries with the greatest annual increases in In figure Annual incremental access (million people) Annual growth in access (%) Ba Sa So access to electricity, 1990–2010 Annual incremental access (million people) Annual growth in access (%) SOURCE: World Bank Global Electrification Database, 2012. 25 4% 20.1 20 15.9 3% 25 4% 15 20.1 20 2% 10 15.9 3% 15 1% 5 3.1 2.4 2.4 1.8 2% 1.7 1.5 1.4 1.4 1.3 1.1 1 10 0.8 0.8 0.7 0.7 0.7 0.7 0.7 0 0% 5 3.1 1% il ria ia ia ria a a a a sia p. q o nd 2.4 2.4 1.8 es n m an t ey 1.7 1.5 in di a ric in il az Re 1.4 1.4 1.3 1.1 yp q Ira o xic ia mb ys n Ira m na 1 0.8 0.8 0.7 0.7 0.7 0.7 0.7 es in ey rk sia ne ria ige ria ge nd ila an kist in nt Ch In yp Eg Br ys la 0 0% , ric Af in ipp mb lo Re ea na Viet xic Me rk Tu ne do ge Al nt ge la a ge N la Ma lo Co ki Pa pp il r Af uth ai Th ia a a a p. t re Ko ge Ar do In ili Ph di in az Ira Ira st Ch In ut So Eg Br a, et Me Tu Ni Al Ma Vi Co Pa h Th Ko Ar In Ph figure O.6 The 20 countries with the greatest Annual incremental access (million people) annual increases in Annual growth in access (%) So access to non-solid fuels, 1990–2010 Annual incremental access (million people) Annual growth in access (%) SOURCE: WHO Global Household Energy Database, 2012. 9 Global tracking framework Scale of the challenge If the global trends observed during the last two decades GEA projects 84 percent access to electricity by 2030 were to continue, the SE4ALL objective of universal ac- under business-as-usual assumptions. cess would not be met. The IEA’s World Energy Outlook for 2012 (IEA 2012b) projects that under a New Policies The IEA projects that under the New Policies Scenario ac- Scenario that reflects existing and announced policy com- cess to non-solid fuel would climb to 70 percent in 2030, mitments, access rates would climb to just 88 percent by leaving the number of people without access to non-sol- 2030, still leaving almost a billion people without access id fuels largely unchanged at 2.6 billion by the end of the to electricity (figure O.7). Access to electricity would im- period (figure O.7b). By comparison, the GEA projects prove for all regions except Sub-Saharan Africa, which is 64 percent access to non-solid fuels by 2030 under busi- expected soon to overtake developing Asia as the region ness-as-usual assumptions. with the largest electrification deficit. By comparison, the electricity 1200 1000 Million people Rest of the World 800 Sub-Saharan Africa 600 South-Eastern Asia South Asia 400 200 0 2010 2010 2030 2030 Rural Urban Rural Urban Modern cooking solutions 2500 Rest of the World Million people 2000 Sub-Saharan Africa 1500 South-Eastern Asia South Asia 1000 East Asia and Oceania 500 0 2010 2010 2030 2030 Rural Urban Rural Urban figure O.7 Number of people without access in rural and urban areas, by region, 2010 and 2030 SOURCE: IEA 2012b. overview 10 Looking ahead, population growth over the next 20 years The IEA estimates that achievement of universal access for is expected to occur entirely in urban areas. Thus, while electricity and modern cooking solutions would add only today’s access deficit looks predominantly rural, consid- about 1 percent to global primary energy demand over erable future electrification efforts in urban areas will be current trends. About half of that additional demand would needed simply to keep electrification rates constant. likely be met by renewable energy and the other half by fossil fuels, including a switch to LPG for cooking. As a According to the IEA, achieving universal access to elec- result, the impact of achieving universal access on global tricity by 2030 will require an average annual investment CO2 emissions is projected to be negligible, raising total of $45 billion (compared to $9 billion estimated in 2009). emissions by around 0.6 percent in 2030. More than 60 percent of the incremental investment re- quired would have to be made in Sub-Saharan Africa and Several barriers must be overcome to increase access to 36 percent in developing Asia. Universal access to mod- electrification and modern cooking solutions. A high level ern cooking solutions by 2030 will require average annual of commitment to the objective from the country’s politi- investment of around $4.4 billion, a relatively small sum in cal leadership and the mainstreaming of a realistic energy global terms but a large increase compared with negligible access strategy into the nation’s overall development and current annual investments of about $0.1 billion. budget processes are important. So are capacity building for program implementation, a robust financial sector, a le- IIASA’s 2012 GEA provides estimates (based on different gal and regulatory framework that encourages investment, assumptions than those used by the IEA) of the cost of and active promotion of business opportunities to attract reaching universal access, which amount to $15 billion per the private sector. In some cases, carefully designed and year for electricity and $71 billion per year for modern cooking targeted subsidies may also be needed. Nonfinancial bar- solutions. The higher estimate for modern cooking solutions riers to the expansion of access include poor monitoring is based on the assumption that providing universal access systems and sociocultural prejudices. will not be feasible without fuel subsidies of around 50 per- cent for LPG, as well as microfinance (at an interest rate of 15 percent) to cover investments in improved cookstoves. Doubling the rate of improvement of energy efficiency The energy intensity of the global economy (the ratio of over the 20-year period (figure O.8). Strong demographic the quantity of energy consumption per unit of economic and economic growth around the world caused global pri- output) fell substantially during the period 1990–2010, from mary energy supply to continue to grow at a compound 10.2 to 7.9 megajoules per U.S. dollar (2005 dollars at annual rate of 2 percent annually over the period, nonethe- PPP).5 This reduction in global energy intensity was driven less improvements in energy intensity meant that global by cumulative improvements in energy efficiency, offset by energy demand in 2010 was more than a third lower than it growth in activity, resulting in energy savings of 2,276 EJ would otherwise have been. 900 900 600 600 EJ 300 300 00 1990 1900 2000 2000 2010 2010 figure O.8 Energy savings owing to realized improvements in energy intensity (exajoules) Primary Primary Energy Energy Consumption Consumption Avoided AvoidedEnergy Consumption Energy Consumption SOURCE: Based on World Development Indicators, World Bank; IEA 2012a; UN Energy Statistics Database. 5 Countries with a high level of energy intensity use more energy to create a unit of GDP than countries with lower levels of energy intensity. Throughout the report, energy intensity is measured in primary energy terms and GDP at PPP unless otherwise specified. More details on the accounting methodology and the terminology used can be found in the energy efficiency chapter of the report. 11 Global tracking framework Starting point Globally, energy intensity decreased at a compound an- This is because energy intensity is affected by other factors, nual growth rate (CAGR) of –1.3 percent over the 20 years such as shifts in the structure of the economy over time, between 1990 and 2010. The rate of improvement slowed typically from less energy-intensive agriculture to higher considerably during the period 2000–2010, however, to a energy-intensive industry and then back toward lower energy CAGR of –1.0, compared to –1.6 per year for 1990–2000 -intensive services. A review of the methodological issues (figure O.9a). in measuring energy efficiency is presented in box O.2. With the starting point for measuring future progress in global Statistical techniques that allow for the confounding energy efficiency under the SE4ALL, set as –1.3 percent, effects of factors other than energy efficiency to be partially the SE4ALL global objective is therefore a CAGR in energy stripped out reveal that the adjusted energy intensity trend intensity of –2.6 percent for the period 2010–2030.6 with a CAGR of –1.6 could be significantly higher than the unadjusted CAGR of –1.3 (figure O.9b). The effect of this Energy intensity is an imperfect proxy for underlying energy adjustment is particularly evident for the period 2000–2010, efficiency (defined as the ratio between useful output and when globalization led to a major structural shift toward the associated energy input). Indeed, the global rate of industrialization in emerging economies, partially eclipsing improvement of global energy intensity may over- or under- their parallel efforts to improve energy efficiency. state the progress made in underlying energy efficiency. Energy intensity, CAGR Adjusted energy intensity, CAGR 1990-2000 2000-2010 1990-2000 1990-2010 2000-2010 1990-2010 1990-2000 2000-2010 1990-2000 1990-2010 2000-2010 1990-2010 -1.0% -1.0% -1.4% -1.4% -1.3% -1.3% -1.6% -1.6% -1.6% -1.6% -1.9% -1.9% Energy intensity Energy intensity Energy Intensity Energy Decomposition Intensity Decomposition figure O.9 Rate of improvement in global energy intensity, 1990–2010 (PPP terms) SOURCE: Based on World Development Indicators, World Bank; IEA 2012a. NOTE: PPP = purchasing power parity; CAGR = compound annual growth rate. “Adjusted energy intensity” is a measure derived from the Divisia decomposition method that controls for shifts in the activity level and structure of the economy. 6 When measured in final energy terms, the compound annual growth rate is –1.5 percent for the period 1990–2010. Thus the goal is –3.0 percent on average for the next 20 years. overview 12 Box O.2 Methodological challenges in defining and measuring energy efficiency Energy efficiency is defined as the ratio between useful outputs and associated energy inputs. Rigorous mea- surement of this relationship is possible only at the level of individual technologies and processes, and the data needed for such measures are available only for a handful of countries. Even where data are available, they result in hundreds of indicators that cannot be readily used to summarize the situation at the national level. For these reasons, energy intensity (typically measured as energy consumed per dollar of gross domestic product, GDP) has traditionally been used as a proxy for energy efficiency when making international compar- isons. Energy intensity is an imperfect proxy for energy efficiency because it is affected not only by changes in the efficiency of underlying processes, but also by other factors such as changes in the volume and sectoral structure of GDP . These concerns can be partially addressed by statistical decomposition methods that allow confounding effects to be stripped out. Complementing national energy intensity indicators with sectoral ones also helps to provide a more nuanced picture of the energy efficiency situation. Calculation of energy intensity metrics requires suitable measures for GDP and energy consumption. GDP can be expressed either in terms of market exchange rate or purchasing power parity (PPP). Market exchange rate measures may undervalue output in emerging economies because of the lower prevailing domestic price levels and thereby overstate the associated energy intensity. PPP measures are not as readily available as market exchange rate measures, because the associated correction factors are updated only every five years. Energy consumption can be measured in either primary or final energy terms. While it may make sense to use primary energy for highly aggregated energy intensity measures (relative to GDP) because it captures intensity in both the production and use of energy, it is less meaningful to use it when measuring energy intensity at the sectoral or subsectoral level, where final energy consumption is more relevant. Based on a careful analysis of these issues and of global data constraints, the SE4ALL Global Tracking Frame- work for energy efficiency will: }} Rely primarily on energy intensity indicators }} Use PPP measures for GDP and sectoral value-added }} Use primary energy supply for national indicators and final energy consumption for sectoral indicators }} Complement those indicators with energy intensity of supply and of the major demand sectors }} Provide a decomposition analysis to at least partially strip out confounding effects on energy intensity }} Use a five-year moving average for energy intensity trends to smooth out extraneous fluctuations For the purposes of global tracking, data for the period 1990–2010 have been compiled from energy balances for 181 countries published by the International Energy Agency and the United Nations. These are comple- mented by data on national and sectoral value-added from the World Bank’s World Development Indicators. Looking ahead, significant international efforts are needed to improve the availability of energy input and output metrics across the main sectors of the economy to allow for more meaningful measures of energy efficiency. 13 Global tracking framework Global final energy consumption can be broadly divided By contrast, the ratio of final to primary energy consumption, among the following major economic sectors: agriculture, which provides a measure of the overall efficiency of con- industry, residential, transport, and services. For the pur- version in the energy supply industry, actually deteriorated pose of initial global tracking, residential, transport, and during the period 1990-2010, falling from 72 to 68 percent. services are aggregated into a single category of “other This reflects relatively little improvement in the efficiency of sectors” owing to data limitations. Industry is by far the the electricity supply industry over the same period. The most energy-intensive of these sectors, consuming around efficiency of thermal generation (defined as the percent- 6.8 megajoules per 2005 dollar in 2010, compared with 5.5 age of the energy content of fossil fuels that is converted to for “other sectors” (residential, transport, and services) and electricity during power generation) improved only slightly 2.1 for agriculture.7 The most rapid progress in reducing from 38 to 39 percent, while transmission and distribution energy intensity has come in the agricultural sector, which losses remained almost stagnant at around 9 percent recorded a CAGR of –2.2 percent during 1990–2010 (fig- of energy produced. Gas supply losses fell a little more ure O.10a). Although progress was significantly slower in steeply, from 1.4 to 0.9 percent. the industry and other sectors, due to their much-higher levels of energy consumption they made far larger con- tributions to global energy savings than did agriculture during the same period (figure O.10b). Industry Agriculture Other Sectors 0% 10 Industry Agriculture Other Sectors 0% 10 (MJ/$2005 at PPP) (MJ/$2005 at PPP) 5 -1.4% -1.4% 5 -1.4% -1.4% -3% -2.2% 0 -3% -2.2% 0 Energy intensity trends by sector Energyintensity figure O.10A Energy trends intensity trends by sector (PPP terms) by sector CAGR 1990-2010 (left) EI in 1990 (right) EI in 2010 (right) CAGR 1990-2010 (left) EI in 1990 (right) EI in 2010 (right) industry (40%) agriculture (4%) other sectors (56%) figure O.10B Share of Share cumulative ofsavings energy cumulative by sector energy savings by sector Source: Based on World Development Indicators, World Bank; IEA 2012a. Note: “Other sectors” include residential, transport, and services. CAGR = compound annual growth rate; EI = energy intensity; PPP = purchasing power parity. 7 Owing to data limitations, in this report the category “other sectors” includes transport, residential, services, and others. The medium- and long-term methodology considers them separately. overview 14 The rate of progress on energy intensity varied dramati- as the Middle East) was the only region to show a deterio- cally across world regions over the period 1990–2010. At rating trend in energy intensity, with a CAGR of +0.8 per- one end of the spectrum, the Caucasus and Central Asia cent. Overall, 85 percent of the energy savings achieved region achieved a CAGR of –3.2 percent while nonethe- between 1990 and 2010 were contributed by Eastern Asia less remaining the region with the highest energy intensity and the developed countries (figure O.11b). (figure O.11a). At the other end, Western Asia (also known 2% 40 2% 40 0.8% 0.8% 30 30 0% (MJ/$2005 0% (MJ/$2005 -0.1% -0.5% -0.5% -0.1% -0.5% -0.5% -1.1% -1.1% 20 -1.3% -1.3% -1.1% -1.3% -1.5% -1.3% -1.1% 20 -1.7% -1.5% at -1.7% at -2% -2.3% PPP) -2% -2.3% PPP) 10 10 -3.2% -3.2% -4% 0 -4% 0 mm eu ee aa aa ea aa sa iaia cc ff aa aa ww cc ss se la eu ee ea oo sa aa nn nn ss cc se la nn ea ea cc figure O.11A Energy figure O.11 figure O.11 Energy Energyintensity trends intensity trends intensity trends by 1990-2010 by region, by region, region (PPP terms) 1990-2010 CAGR 1990-2010 (left) EI in 1990 (right) EI in 2010 (right) CAGR 1990-2010 (left) EI in 1990 (right) EI in 2010 (right) SOURCE: IEA, WDI SOURCE: IEA, Note: nam WDI = northern america; eu = europe; ee = eastern europe; cCA = Caucasus and Central Asia; Note: nam = northern WA = Western Asia; EA = Eastern eu america; = europe; AsiA; ee = eastern europe; SEA = South-Eastern cCA Asia; SA = Caucasus = Southern and Asia; LACCentral Asia; = Latin America WA = Western Asia; EA = AsiA; SEA Eastern Africa; and Caribbean; NAF = Northern = South-Eastern SSA = Sub-Saharan Asia; SA = Southern Asia; LAC = Latin America Africa. and Caribbean; NAF = Northern Africa; SSA = Sub-Saharan Africa. EA (58%) NAm (17%) EU (10%) EE (6%) SA (4%) CCA (2%) LAC (1%) SSA (1%) Oceania ( <1%) SEA (<1%) figure O.11B Share of cumulative energy savings by region Source: Based on World Development Indicators, World Bank; IEA 2012a; UN Energy Statistics Database. Note: PPP = purchasing power parity; CAGR = compound annual growth rate; EI = energy intensity; NAm = North America; EU = Europe; EE = Eastern Europe; CCA = Caucasus and Central Asia; WA = Western Asia; EA = Eastern Asia; SEA = South- Eastern Asia; SA = Southern Asia; LAC = Latin America and the Caribbean; NAf = Northern Africa; SSA = Sub-Saharan Africa. High-impact countries Energy consumption is distributed unequally across for 40 percent of the total (figure O.12). The achievement countries, almost to the same degree as income. The of the global objective of doubling the rate of improvement 20 largest energy consumers account for 80 percent of of energy efficiency will therefore depend critically on primary energy consumption, with the two largest consum- energy consumption patterns in these countries. ers (the United States and China) together accounting 15 Global tracking framework As of 2010, the high-income countries (with the exception mix of the countries of the former Soviet Union and those of Saudi Arabia) show the lowest energy intensity relative of Sub-Saharan Africa—report intensities of 20–30 mega- to GDP . Nevertheless, energy consumption per capita varies joules per 2005 PPP dollar (figure O.13). At the other hugely across this group, from 110 gigajoules per capita in extreme, the least energy-intensive countries—predom- Western Europe to 300 in North America. By contrast, the inantly small island developing states with exceptionally middle-income countries (with the exception of Russia and high energy costs—report intensities of 2–4 megajoules Kazakhstan) show much lower levels of per capita energy per 2005 PPP dollar (figure O.14). Even among the 20 larg- consumption but vary widely in their energy intensities. In est energy consuming countries, energy intensities range particular, energy intensities in Latin America are comparable from more than 12 megajoules per 2005 PPP dollar in to those found in Western Europe, whereas in the Ukraine Ukraine, Russia, Saudi Arabia, South Africa, and China to and Uzbekistan they are exceptionally high (figure O.13). less than 5 in the United Kingdom, Spain, Italy, Germany, and Japan. The gap between the world’s most and least energy- intensive economies is wide—more than tenfold. At one ex- treme, the most energy-intensive countries—a heterogenous Primary energy supply/GDP (PPP) hics Uzbekistan umics lmics Ukraine Kazakhstan iraq Russia nigeria south africa Saudi Arabia china iran vietnam venezuela canada indonesia S. Korea Primary energy pakistan Thailand consumption/capita Malaysia egypt Czech Rep. Belgium uaE india algeria Sweden Poland mexico France Australia brazil italyjapan Philippines argentina Netherlands usa turkey Germany spain uk figure O.12 Energy intensity (PPP) vs. energy consumption per capita in 40 largest energy consumers, 2010 Source: Based on World Development Indicators, World Bank; IEA 2012a. Note: Values are normalized along the average. Bubble size represents volume of primary energy consumption. PPP = purchasing power parity. GDP = gross domestic product; PPP = purchasing power parity; HICs = higher-income countries; UMICs = upper-middle-income countries; LMICs = lower-middle-income countries; UAE = United Arab Emirates. overview 16 Liberia 59.8 St. Lucia 3.9 Congo, DRC 47.6 Botswana 3.8 Burundi 33.3 Ireland 3.7 Trinidad & T. 28.8 Bahamas 3.7 Sierra Leone 26.7 Switzerland 3.7 Turkmenistan 23.8 Malta 3.7 Uzbekistan 23.3 Grenada 3.6 Guinea 22.2 Kiribati 3.6 Mozambique 22.2 Panama 3.6 Iceland 21.6 Albania 3.5 Togo 20.8 Colombia 3.4 Ukraine 19.8 Antigua & Barb. 3.4 Zambia 18.8 Peru 3.3 Uganda 18.2 Solomon Isl. 3.0 Ethiopia 18.0 St. Vincent 2.9 Kazakhstan 17.6 Afghanistan 2.9 Sao Tome & P. 16.3 Vanuatu 2.7 Guyana 16.3 Dominica 2.6 Bhutan 16.0 Hong Kong 2.0 Swaziland 15.9 Macau 1.0 figure O.13 Countries with highest energy figure O.14 Countries with lowest energy intensity level in 2010 (MJ/$2005) intensity level in 2010 (MJ/$2005) Source: Based on World Development Indicators, World Bank; IEA 2012a; UN Energy Statistics Database. Note: PPP = purchasing power parity; DR = “Democratic Republic of.” Fast-moving countries In doubling the rate of energy efficiency improvement glob- countries of the former Soviet Union, and several countries ally, it will be important to learn from those countries that in Sub-Saharan Africa (figure O.16). By far the largest ab- made the most rapid progress toward this goal during the solute energy savings have been made by China, where 20 years between 1990 and 2010. While the global CAGR energy efficiency efforts have yielded savings equivalent of energy intensity was only –1.3 percent over the period in magnitude to the energy used by the country over the 1990–2010, 20 countries achieved rates of –4.0 percent or same time frame. Savings in the United States, the Euro- greater (figure O.15). The countries making the most rapid pean Union, and India have also been globally significant. progress on energy intensity often started out with partic- ularly high levels of energy intensity—notably China, the   Unadjusted adjusted Bosnia & Herz. 11.9% Armenia 11.2% Estonia 8.4% Estonia 9.3% Azerbaijan 7.9% Azerbaijan 8.5% Armenia 7.3% China 6.5% Afghanistan 6.8% Myanmar 5.6% East Timor 6.3% Uganda 5.5% Sao Tome & P. 5.9% Dominican Rep. 5.5% Belarus 5.3% Mongolia 5.2% Georgia 4.9% Laos 5.0% China 4.7% Georgia 4.8% Lithuania 4.6% Lithuania 4.7% Kyrgyzstan 4.5% Belarus 4.6% Albania 4.4% Turkmenistan 4.5% Bhutan 4.3% Moldova 4.1% Laos 4.2% Swaziland 4.1% Eritrea 4.1% India 4.1% Romania 4.0% Romania 4.0% Turkmenistan 4.0% Uzbekistan 3.9% Moldova 3.9% Bulgaria 3.8% Uganda 3.9% Slovakia 3.7% figure O.15 Reductions in energy intensity of 20 fastest-moving countries, CAGR, 1990–2010 (PPP terms) Source: Based on World Development Indicators, World Bank; IEA 2012a; UN Energy Statistics Database. Note: CAGR = compound annual growth rate. “Adjusted energy intensity” is a measure derived from the Divisia decomposition method that controls for shifts in the activity level and structure of the economy. 17 Global tracking framework Cumulative primary energy demand, 1990-2010 Cumulative energy savings, 1990–2010 USA 1,904 China 1,320 China 1,269 USA 369 Russia 595 India 114 Japan 435 Germany 69 India 413 UK 47 Germany 297 Poland 46 France 221 Bosnia & Herz. 38 Canada 214 Russia 35 UK 190 Iraq 24 Brazil 168 Canada 23 Korea 155 Belarus 18 Italy 146 Romania 18 Ukraine 138 Estonia 16 Indonesia 134 Mexico 14 Mexico 131 France 14 Iran 118 Australia 13 Spain 103 Kazakhstan 12 S. Africa 101 Argentina 11 S. Arabia 99 Nigeria 11 Australia 93 Czech Rep. 10 figure O.16 Largest cumulative consumers of primary energy, and cumulative energy savings as a result of reductions in energy intensity, 1990–2010 (exajoules) Source: Based on World Development Indicators, World Bank; IEA 2012a; UN Energy Statistics Database. Note: Bosnia & = Bosnia & Herzegovina. Scale of the challenge Looking ahead, analysis from the IEA’s World Energy Out- policies (referred to as the New Policies Scenario in figure look 2012 indicates that energy efficiency policies currently O.17; IEA 2012b). Under an Efficient World Scenario that in effect or planned around the world would take advantage exploits all cost-effective improvements, it would be pos- of just a third of all economically viable energy efficiency sible to improve energy intensity by an average CAGR of measures. The current or planned uptake of available –2.8 percent through 2030, more than double historic rates measures is highest in the industrial sector at 44 percent, and even somewhat beyond the SE4ALL objective. About followed by transport at 37 percent, power generation at 21 80 percent of the energy savings that are achievable under percent, and buildings at 18 percent. this scenario would result from measures taken by energy consumers in end-use sectors, with much of the remaining Recent analysis shows that the existing potential for 20 percent attributable to fuel switching and supply-side cost-effective improvements in energy efficiency goes far efficiency measures. By far the largest potential for energy beyond what will be captured through current and planned efficiency improvements is to be found in developing Asia. 800 750 Efficiency in end-uses 700 Fuel and technology switching 650 Activity EJ Efficiency in energy supply 600 Current Policies Scenario 550 New Policies Scenario 500 Efficient World Scenario 450 2010 2020 2030 figure O.17 Change in global primary energy demand by measure between IEA Efficient World Scenario and IEA New Policies Scenario, 2010–2030 (exajoules) Source: IEA 2012b. overview 18 The Efficient World Scenario would slow the CAGR of global adoption of a strong set of energy policy measures, including energy demand to 0.6 percent through 2030, compared the phasing out of fossil-fuel subsidies, the provision of with an anticipated 1.3 percent under current and planned price signals for carbon emissions, and the adoption of policies. It should be noted that even the Efficient World strict energy efficiency standards. Scenario does not bring about an overall decline in global energy demand over the period 2010–2030. IIASA’s GEA presents six scenarios that meet all three SE4ALL objectives while also meeting the requirement to Mobilizing these improvements would call for cumulative limit global temperature increases to 2°C. All six of these additional investments of close to $400 billion annually scenarios require CAGRs for energy intensity on the or- through 2030, more than triple historic levels. These invest- der of –3.0 percent annually. Achieving the global objec- ments—although high—would offer the prospect of rapid tive would entail CAGRs for energy intensity in the range of payback, giving a boost to the global economy of $11.4 –4.0 to –6.0 percent for Asia and the former Soviet Union trillion over the same period. As in the case of renewable (figure O.18). energy, achieving change on this scale is contingent on the d rl EU M EA O M PA U FR S S U d o A PA PA SA LA EE FS W M N C A rl W 0% EU M EA O M PA U FR S S U o A PA PA SA LA EE FS W -1% M N C A W 0% -2% -1% -3% -2% -4% -3% -5% -4% -6% -5% -6% figure O.18 Annual rate of improvement in primary energy intensity: IIASA Global Energy AssessmentBaseline SE4ALL baseline vs. SE4ALL scenario, CAGR, 2010–2030 Baseline SE4ALL Source: IIASA (2012). Note: On the chart above GDP is measured at market exchange rate and primary energy is measured using direct equivalent method as opposed to the physical content method used elsewhere. CAGR = compound annual growth rate. NAM = North America; WEU = Western Europe; PAO = Pacific OECD; MEA = Middle East and North Africa; AFR = Sub-Saharan Africa; EEU = Eastern Europe; LAM = Latin America; FSU = former Soviet Union; PAS = Pacific Asia; SAS = South Asia; CPA = Centrally Planned Asia. Doubling the share of renewable energy in the global energy mix The amount of energy provided from renewable sources the consumption of energy from renewable sources rose, for electricity, heating, and transportation has expanded global TFEC grew at a comparable pace of 1.1 percent rapidly since 1990, and particularly since 2000, with a com- during 1990–2000 and 2.0 percent during 2000–2010. As pound annual growth rate (CAGR) of 1.5 percent during a result, the share of renewable energy in the total final en- 1990–2000 and 2.4 percent during 2000–2010.8 Global ergy consumption remained relatively stable, growing from consumption of renewable energy grew from 40 exajoules 16.6 percent in 1990 to 18.0 percent in 2010. (EJ) in 1990 to almost 60 EJ in 2010 (figure O.19). Yet as 8 Nuclear energy is not considered renewable. 19 Global tracking framework 70 18.0% 17.2% 17.4% 17.0% 16.6% 60 50 Other RE 40 Hydro 30 Modern Biomass Traditional Biomass 20 RE share in TFEC 10 - 1990 1995 2000 2005 2010 figure O.19 World consumption of renewable energy (exajoules) and share of renewable energy in TFEC (%) SOURCE: IEA 2012a. Note: TFEC = total final energy consumption; RE = renewable energy. Focusing specifically on electricity, power generation from electricity generation of China, the United States, and India renewable sources increased from 2,300 terawatt-hours in 2010. As of 2011, renewable energy sources account- (TWh) in 1990 to 4,160 TWh in 2010. The increase in ed for more than 20 percent of global power generated, electricity generation from renewable sources is equivalent 25 percent of global installed power generation capacity, to the combined electricity output of Russia and India and half of newly installed power generation capacity in 2010. Global electricity generation almost doubled in added that year. More than 80 percent of all renewable the 20-year period, growing from 11,800 TWh in 1990 to electricity generated globally was from hydropower. 21,400 TWh in 2010, which is equivalent to the combined The starting point The starting point for the share of renewable energy in total of the renewable energy total relates to modern forms of final energy consumption against which future progress bioenergy, and most of the remainder is hydropower. will be measured is estimated to be at most 18 percent of Remaining forms of renewable energy—including wind, TFEC in 2010, reflecting uncertainties over whether some solar, geothermal, waste, and marine—together contribute types of renewable energy usage (notably traditional bio- barely 1 percent of global energy consumption, though mass) meet sustainability criteria (figure O.20). The implied they have been growing at an exponential rate. For example, SE4ALL global objective is up to 36 percent by 2030. wind power grew at a CAGR of 25.0 percent and solar at 11.4 percent, compared with a growth rate of slightly over It is estimated that traditional biomass accounts for about 1 percent for traditional biomass (figure O.21). half of the renewable energy total, although data on these traditional usages are imprecise, and the sustainability of An examination of the methodological issues of measuring these sources cannot be reliably gauged.9 A further quarter the renewable energy share can be found in box O.3. 9 The UN Food and Agriculture Organization defines traditional biomass as “woodfuels, agricultural by-products, and dung burned for cooking and heating purposes.” In developing countries, traditional biomass is still widely harvested and used in an unsustainable and unsafe way. It is mostly traded informally and non-commercially. So-called modern biomass, by contrast, is produced in a sustainable manner from solid wastes and residues from agriculture and forestry. overview 20 traditional biomass (9.6%) modern biomass (3.7%) liquid biofuels (0.8%) fossil fuels (79.1%) wind (0.3%) Nuclear (2.5%) 18.0% solar (0.2%) renewable energy (18%) biogas (0.2%) geothermal (0.2%) waste (0.1%) marine (0.01%) hydro (3.1%) figure O.20 Global Share of Renewable Energy in TFEC, 2010 figure O.20 Share of renewable energy in global TFEC, 2010 SOURCE: IEA SOURCE: IEA 2012a. Note: TFEC = total final energy consumption; 25.0% 16.7% 11.1% 11.4% 6.6% 5.1% 1.2% 1.9% 2.3% 0.0% e ss ss ro l e s r s d a el a n st la in a a m g ri yd fu a W m m So o er a W o o H Bi M o th Bi Bi Bi eo l n a er n G d io o it M d a Tr figure O.21 Compound annual growth rates (CAGRs) by renewable energy source, 1990–2010 SOURCE: IEA 2012a. 21 Global tracking framework Box O.3 Methodological challenges in defining and measuring renewable energy There are various definitional and methodological challenges in measuring and tracking the share of renew- able energy in the global energy mix used for heating, electricity, and transportation. First, while there is a broad consensus among international organizations and government agencies on what constitutes renewable energy, their legal and formal definitions vary slightly in the type of resources included and the sustainability considerations taken into account. For the purposes of the SE4ALL Global Tracking Framework, it is important that the definition of renewable energy should be specific about the range of sources to be included, should embrace the notion of natural replenishment, and should espouse sustainability. But the data and agreed-upon definitions needed to determine whether renewable energy—notably biomass—has been sustainably produced are not currently available. Therefore, it is proposed that, as an interim measure for immediate tracking purposes, renewable energy should be defined and tracked without the application of specific sustainability criteria. Accordingly, its broad definition is as follows: “Renewable energy is energy from natural sources that are replenished at a faster rate than they are con- sumed, including hydro, bioenergy, geothermal, aerothermal, solar, wind, and ocean.” Second, an important methodological choice is whether tracking should be undertaken at the primary level of the energy balance or on the basis of final energy. Power generation from fossil fuels leads to substantial energy losses in conversion, leading to a discrepancy between primary energy, or fuel input, and final energy, or useful energy output. Since renewable energy sources do not have fuel inputs, they are only reported in final energy terms; expressing them in primary terms would require the use of somewhat arbitrary conversion factors. Third, the high aggregation levels and data gaps in certain categories of available data repositories still limit the analysis. Data gaps have also been identified in the areas of distributed generation and off-grid electricity services. An additional challenge is related to measuring the heat output from certain renewable sources of energy such as heat pumps and solar water heaters. These missing components of renewable energy are relatively small in scale at present but are expected to grow significantly through 2030, making it increasingly important to develop methodologies and systems for capturing the associated data. For the purposes of global tracking, data for the period 1990–2010 have been compiled from energy balances for 181 countries published by the International Energy Agency and the United Nations. Those data will be complemented by indicators on: (i) policy targets for renewable energy and adoption of relevant policy measures; (ii) technology costs for each of the renewable energy technologies; and (iii) total investment in renewable energy from the Renewable Energy Network 21, the International Renewable Energy Agency, and Bloomberg New Energy Finance, respectively. Looking ahead, significant international efforts are needed to improve data collection methodologies and bridge identified data gaps. In particular, there is a need to develop internationally agreed-upon standards for sustainability for each of the main technologies, which can then be used to assess the degree to which deployment meets the highest sustainability standards. This is particularly critical in the case of biomass, where traditional harvesting practices can be associated with deforestation. overview 22 Looking across regions, it is striking that lower-income energy (in the range of 10 to 15 percent), although those regions, such as Africa and Asia, have the highest shares shares grew steadily over the two decades. Overall, Africa of renewable energy, ranging from 20 to 60 percent. These and Asia alone accounted for about two-thirds of global shares declined significantly in 1990–2010, however, in part share of renewable energy in TFEC in 2010, while Europe due to decreased reliance on traditional biomass for cook- and North America together contributed about 20 percent ing and wider adoption of non-solid cooking fuels (figure (figure O.23). O.22). By contrast, higher-income regions such as Europe and America present much lower shares of renewable 80% ssa 70% sa sea 60% lac 50% ea 40% oceania eu 30% nam 20% ee naf 10% cca 0% wa 1990 2000 2010 figure O.22 Evolving renewable energy share by region, 1990-2010 (percentage of total final energy consumption) SOURCE: IEA 2012a. Note: TFEC = total final energy consumption; RE = renewable energy. CCA = Caucasus and Central Asia; EA = Eastern Asia; LAC = Latin America and Caribbean; NAf = Northern Africa; SEA = South-Eastern Asia; SA = Southern Asia; SSA = Sub-Saharan Africa; WA = Western Asia; EU = Europe. Ssa (21%) Ea (20%) Sa (16%) LAC (11%) eu (10%) nam (10%) sea (8%) other (5%) figure O.23 Regional contributions to global renewable energy 2010 (percentage contribution to the global share of renewable energy in TFEC) SOURCE: IEA 2012a. Note: CCA = Caucasus and Central Asia; EA = Eastern Asia; LAC = Latin America and Caribbean; NAf = Northern Africa; SEA = South-Eastern Asia; SA = Southern Asia; SSA = Sub-Saharan Africa; WA = Western Asia; EU = Europe; other = All other regions. 23 Global tracking framework If we confine attention to power generation only, the regional highest regions – Caucuses and Central Asia, Europe, picture for the share of renewable energy in the electricity Oceania and Sub-Saharan Africa – all of them above 20 mix looks quite different. Latin America and Caribbean percent. Globally, 80 percent of renewable electricity gen- emerges as the region with by far the highest share of eration is found evenly spread across just four regions: renewable energy in the electricity generation portfolio of East Asia, Europe, Latin America and Caribbean and North 56 percent, which is more than twice the level in the next America. High-impact opportunities Substantial potential exists for further tapping of renewable and solar—have been falling steeply and are expected to energy sources. Studies have consistently found that the fall further as the scale of production increases. As a result, technical potential for renewable energy use around the renewable energy sources—in particular hydropower, globe is substantially higher than projected global energy wind, and geothermal—are increasingly competitive in demand in 2050. The technical potential for solar energy many environments, while solar energy is becoming com- is the highest among the renewable energy sources, but petitive in some environments. Nevertheless, it is still chal- there is also substantial untapped potential for biomass, lenging for renewable energy to compete financially with geothermal, hydro, wind, and ocean energy. Available data conventional fossil-fuel alternatives, particularly given that suggest that most of this technical potential is located in the local and global environmental impact of these con- the developing world. For instance, at least 75 percent of ventional sources of energy is not fully reflected in costs. the world’s unexploited hydropower potential is found in The further integration of renewable energy sources into Africa, Asia, and South America, and about 65 percent of the public electricity supply system also calls for more total geothermal potential is found in countries that are not proactive expansion of both transmission grids and back- members of the Organisation for Economic Co-operation up capacity for handling higher levels of variability in the and Development (OECD). The solar belt—that is, the trop- production of wind and solar energy and this further adds ical latitudes that have the highest solar irradiance across to the associated cost. The relatively high capital costs of the globe—endows many developing countries with a high renewable energy, even when overall lifecycle costs may potential for solar-based power generation and heating. be lower, adds further to the financing challenge. Despite the major technical potential of renewable energy, large-scale adoption will ultimately depend on economic factors. The costs of renewable energy—particularly wind Fast-moving countries Over the 20 years between 1990 and 2010, renewable the United States, Brazil, Germany, India, Italy, and Spain energy technologies matured and became more widely (figure O.24). The technology of focus differs from case adopted. Both developed and developing countries are to case, with China focusing mainly on hydropower; the increasingly motivated by the social benefits offered by United States on liquid biofuels; Brazil, Germany, and renewable energy, including enhanced energy security, re- India on modern biomass; and Spain on wind power. Those duced greenhouse gas emissions and local environmental countries moving most rapidly, such as China and Germany, impacts, increased economic and industrial development, experienced average annual rates of growth of 8–12 and more options for reliable and modern energy access. percent in 1990–2010. As of 2010, the countries with the Today, about 120 countries—more than half of them devel- highest shares of renewable energy (excluding traditional oping countries—have a national target related to renew- biomass) were Norway, Sweden, and Tajikistan, where the able energy. Moreover, 88 countries have introduced price- shares were about 50 percent (figure O.25). Many other or quantity-based incentives for renewable energy. Just emerging countries—among them Argentina, Mexico, Tur- over half of those countries are in the developing world. key, Indonesia, Philippines, and a few African countries— are starting to show progress in adopting policies to scale Almost 80 percent of renewable energy other than traditional up renewables. biomass has been produced and consumed by high- income and emerging economies, most notably China, overview 24 china 2,804 United States 2,274 brazil 1,719 Germany 730 india 546 Waste Italy 340 spain 297 Modern Biomass Sweden (4) 221 Biogas thailand 214 France (1) 209 liquid Biofuels canada (0) 204 Hydro Poland 198 nigeria 159 Geothermal Austria 139 Solar finland 138 United Kingdom 142 Wind congo, drc 118 Chile 112 pakistan 95 Venezuela 94 (500) - 500 1000 1500 2000 2500 3000 figure O.24 Volume of incremental consumption of renewable energy (excluding traditional biomass), 1990–2010 (petajoules) SOURCE: IEA 2012a. Note: “Incremental consumption” indicates additional consumption of renewable energy over and above the level of consumption in 1990. DRC = Democratic Republic of Congo. Share of RE in TFEC norway 55% Tajikistan hics Sweden Brazil umics 45% lmics Paraguay lics 35% Finland Canada Chile Sri Lanka 25% Colombia DRC Tanzania Mozambique Turkey Spain 15% Thailand Germany mexico India Italy China 5% Indonesia Myanmar russia japan USA Compound Annual -2% 0% 2% 4% 6% 8% 10% 12% 14% Growth Rate, -5% 1990-2010 figure O.25 Share of renewable energy in total final energy consumption and compound annual growth rate in consumption of renewable energy, 2000–10 SOURCE: IEA 2012a. Note: TFEC = total final energy consumption; CAGR = compound annual growth rate; RE = renewable energy. Figure excludes traditional biomass, but includes the use of modern biomass. Congo and Tanzania appear due to their high use of modern biomass in the industrial sector. Negative CAGRs shown denote a reduction in the use of non- traditional solid biomass (most notably in industry) in Turkey, Mexico, and Indonesia. Unlabeled bubbles represent countries with a low share of RE in TFEC and a low CAGR. 25 Global tracking framework Scale of the challenge If current trends were to continue, the expansion of renew- greatly in terms of their methodologies (that is, forecasting able energy would barely keep pace with the projected versus goal-seeking) as well as their assumptions about expansion of global energy demand. Consequently, the the prevailing policy environment. A review of energy mod- expected renewable energy share in 2030 would be no eling scenarios by the Intergovernmental Panel on Climate greater than 19.4 percent—barely one percentage point Change finds that more than half of 116 scenarios indicate higher than it is today. a renewable energy share in total primary energy supply of less than 17 percent by 2030, with the highest cases Furthermore, if current overall growth in energy demand projecting a renewable energy share of 43 percent (figure continues, renewable energy consumption would have O.26). Those scenarios in which renewable energy shares to triple, growing at an annual rate of 5.9 percent—or two rise above the 30 percent mark typically assume a strong and a half times the current growth rate—in order meet the package of policy measures, such as elimination of fossil target of doubling by 2030. Given that traditional biomass -fuel subsidies, imposition of carbon pricing, aggressive (representing about half of renewable energy use in 2010) pursuit of energy efficiency, sustained support for research is not expected to expand greatly, the annual growth rate and development of emerging renewable technologies, for other forms of renewable energy would have to be in and the advent of advanced transport fuels and technologies. double digits. Achieving the SE4ALL renewable energy objective within By contrast, if overall energy demand were to stabilize a supportive policy environment will call for sustained (due to greater energy efficiency, for example), doubling global investments in the range of $250 to $400 billion per the renewable energy contribution would require an annual year, depending on the pace of growth in energy demand. growth rate of 3.5 percent, or a 50 percent increase over Financing for renewable energy rose exponentially in the levels observed in 1990–2010. This analysis highlights 2000–2010, reaching $277 billion in 2011. Only the last four the critical linkage between the SE4ALL objectives for years of this period, however, saw an investment exceed- renewable energy and energy efficiency. ing the bottom of the required range; the total investment over the ten-year period amounted to an annual average of Several agencies and organizations have modeled sce- just $120 billion. narios of the evolution of renewable energy. These vary 60% 50% Greenpeace 60% 40% GEA6 & GEA 4 50% Greenpeace GEA1 & GEA 2 GEA3 & GEA 5 30% 40% GEA6 & GEA 4 WEO 450 GEA1 & GEA 2 GEA3 & GEA WEO NPS 5 & EM 20% 30% WEO CPS WEO 450 10% 20% WEO NPS & EM WEO CPS 0% 10% 1990 2000 2010 2020 2030 0% figure 1990 % RE - Historical O.26 Projections 2000 % RE - Trends of share 2010 Continued 2020 % RE2030 of renewable energy- SE4ALL Target Growth Rate in TFEC, 1990–2030 % RE - Historical % RE - Trends Continued % RE - SE4ALL Target Growth Rate Source: IEA (2012b): Greenpeace International (2012); IIASA (2012); ExxonMobil (2012). Note: TFEC = total final energy consumption; RE = renewable energy; WEO = World Energy Outlook; GEA = Global Energy Assessment; NPS = New Policies Scenario (IEA); CPS = Current Policies Scenario (IEA); EM = ExxonMobil; SEFA = Sustainable Energy for All (SE4ALL). overview 26 The way forward On the basis of the Global Tracking Framework, it is possi- energy intensity will need to double from –1.3 percent in ble to establish the following starting points against which 1990–2010 to –2.6 percent in 2010–30; and the share of progress will be measured under the SE4ALL initiative: the renewable energy in the global energy mix will need to rate of access to electricity and primary non-solid fuel will double from an estimated 18 percent in 2010 to up to 36 have to increase from 83 and 59 percent in 2010, respec- percent by 2030 (table O.3). tively, to 100 percent by 2030; the rate of improvement of Objective 1 Objective 2 Objective 3 Doubling share Doubling global of renewable Universal access to modern energy services rate of improvement energy in global of energy efficiency energy mix Percentage of Percentage of population with Rate of improvement Renewable energy Proxy indicator population with primary reliance on in energy intensity* share in TFEC electricity access non-solid fuels Historic reference 1990 76 47 16.6 –1.3 Starting point 2010 83 59 18.0 Objective for 2030 100 100 –2.6 36.0 Table o.3 SE4ALL historic references, starting points, and global objectives (%) Source: Authors. Note: TFEC = total final energy consumption *Measured in primary energy terms and GDP at purchasing power parity While progress in all countries is important, achievement of the progress that can be supported in these countries. A the global SE4ALL objectives will depend critically on prog- third group of 20 high-income and emerging economies ress in the 20 high-impact countries that have a particularly accounts for four-fifths of global energy consumption. large weight in aggregate global performance. Two over- Therefore, the efforts of those high-impact countries to lapping groups of 20 high-impact countries in Asia and accelerate improvements in energy efficiency and develop Africa account for about two-thirds of the global electrifica- renewable energy will ultimately determine the global tion deficit and four-fifths of the global deficit in access to achievement of the corresponding targets. non-solid fuels (figure O.27). Meeting the universal access objective globally will depend to a considerable extent on   27 Global tracking framework Electricity access Electricity access deficit non-solid fuel Non-solid fuel access access deficit Primary Primary energy energy demand demand deficit (million) (millions of people) deficit (million) (millions of people) (exajoules) (exajoules) India 306 306.2 India 705 705 China 107 107.4 Nigeria 82 82.4 China 613 612.8 USA 93 92.8 Bangladesh 67 66.6 Bangladesh 135 134.9 Russia 29 29.4 Ethiopia 64 63.9 Indonesia 131 131.2 India 29 29 Congo, DR 56 55.9 Nigeria 118 117.8 Japan 21 20.8 Tanzania 38 38.2 Pakistan 111 110.8 Germany 14 13.7 Kenya 31 31.2 Ethiopia 81 81.1 Brazil 11 11.1 Sudan 31 30.9 Congo, DR 61 61.3 France 11 11 Uganda 28 28.5 Vietnam 49 49.4 Canada 10 10.5 Myanmar 25 24.6 Philippines 46 46.2 S. Korea 10 10.5 Mozambique 20 19.9 Myanmar 44 44 Iran 9 8.7 Afghanistan 18 18.5 Tanzania 42 42.3 Indonesia 9 8.7 Korea, DR 18 18 Sudan 34.6 UK 8 8.5 Madagascar 18 17.8 Kenya 32.6 Mexico 8 7.5 Philippines 16 15.6 Uganda 32.2 Italy 7 7.1 Pakistan 15 15 Afghanistan 26.7 S. Arabia 7 7.1 Burkina Faso 14 14.3 Nepal 24.6 S. Africa 6 5.7 Niger 14 14.1 Mozambique 22.2 Ukraine 6 5.5 Indonesia 14 14 Korea, DR 22.2 Spain 5 5.3 Malawi 14 13.6 Ghana 20.4 Australia 5 5.2 figure o.27 Overview of high-impact countries Source: IEA, WB Global Electrification Database, WHO Global Household Energy Database. Note: DR = “Democratic Republic of.” FIG o.27 overview of high-impact countries SOURCE: WB, WHO, IEA In charting a course toward the achievement of the SE4ALL more than 3–4 percentage points annually. In the case objectives, it will also be important to learn from the of energy efficiency, the countries with the most rapid experience of the fast-moving countries that made the improvements in energy intensity have seen CAGRs of most progress during the 20 years between 1990 and 2010 minus 4–8 percent annually. In the case of renewable ener- (figure O.28). China and (to a lesser extent) India stand out gy, the most rapidly moving countries experienced CAGRs as both high-impact and fast-moving countries on all three of 10–20 percent (excluding traditional biomass). aspects of energy sector development.   In the case of electrification and cooking, even the most rapidly moving countries have not expanded access by overview 28 average annual rate global average fast moving countries of improvement (%) Electrification 1.2 2.5 to 3.7 Non-solid fuel use 1.1 2.2 to 4.0 Energy intensity 1.3 3.9 to 11.9 Renewable energy [w/o trad. biomass] 3.0 7.0 to 18.2 Table o.4 Fast moving countries relative to global average, Average annual rate of improvement (%) Cumulative population connected to Cumulative population gaining electricity (million) access to non-solid fuels (million) India 474 473.7 India 402 402.5 India 474 473.7 India 402 402.5 China 258 258.1 China 318 318.4 China 258 258.1 China 318 318.4 Indonesia 103 102.6 Brazil 62 62.5 Indonesia 103 102.6 Brazil 62 62.5 Pakistan 92 92 Pakistan 49 49 Pakistan 92 92 Pakistan 49 49 Bangladesh 59 59.3 Indonesia 47 47.1 Bangladesh 59 59.3 Indonesia 47 47.1 Brazil 55 55.4 Vietnam 36 36.3 Brazil 55 55.4 Vietnam 36 36.3 Philippines 37 37.4 Mexico 34 34.4 Philippines 37 37.4 Mexico 34 34.4 Nigeria 35 35.2 Thailand 30 30.1 Nigeria 35 35.2 Thailand 30 30.1 Mexico 32 32.3 Egypt, Arab Rep. 28 28.4 Mexico 32 32.3 Egypt, Arab Rep. 28 28.4 Egypt 26 26.5 Turkey 27 27.4 Egypt 26 26.5 Turkey 27 27.4 Vietnam 25 25.3 Iran, Islamic Rep. 26 25.5 Vietnam 25 25.3 Iran, Islamic Rep. 26 25.5 Iran 21.5 Philippines 22.5 Iran 21.5 Philippines 22.5 Morocco 19.4 South Africa 20.1 Morocco 19.4 South Africa 20.1 Turkey 18.6 Iraq 16.2 Turkey 18.6 Iraq 16.2 South Africa 17.5 Colombia 15.1 South Africa 17.5 Colombia 15.1 Thailand 15.7 Nigeria 14.8 Thailand 15.7 Nigeria 14.8 Iraq 15.1 Malaysia 14.2 Iraq 15.1 Malaysia 14.2 Colombia 14.8 Korea, Rep. 13.9 Colombia 14.8 Korea, Rep. 13.9 Ethiopia 14.2 Algeria 13.7 Ethiopia 14.2 Algeria 13.7 Saudi Arabia 11.8 Argentina 13.2 Saudi Arabia 11.8 Argentina 13.2 Cumulative energy saved through Cumulative renewable energy consumed, reductions in energy intensity (exajoules) excluding traditional biomass (exajoules) China 1320 1,320 USA 62 62 China 1320 1,320 USA 62 62 USA 369 369 Brazil 50 50 USA 369 369 Brazil 50 50 India 114 114 India 32 32 India 114 114 India 32 32 Germany 69 Canada 29 29 Germany 69 Canada 29 29 UK 47 China 24 24 UK 47 China 24 24 Poland 46 France 13 13 Poland 46 France 13 13 Bosnia H. 38 Russia 11 11 Bosnia H. 38 Russia 11 11 Russia 35 Sweden 11 11 Russia 35 Sweden 11 11 Iraq 24 Japan 10 10 Iraq 24 Japan 10 10 Canada 23 Mexico 9 9 Canada 23 Mexico 9 9 Belarus 18 Norway 9 9 Belarus 18 Norway 9 9 Romania 18 Germany 9 9 Romania 18 Germany 9 9 Estonia 16 Turkey 8 8 Estonia 16 Turkey 8 8 Mexico 14 Indonesia 8 8 Mexico 14 Indonesia 8 8 France 14 Nigeria 7 7 France 14 Nigeria 7 7 Australia 13 Spain 6 6 Australia 13 Spain 6 6 Kazakhstan 12 Finland 6 6 Kazakhstan 12 Finland 6 6 Argentina 11 Italy 6 6 Argentina 11 Italy 6 6 Nigeria 11 Austria 5 5 Nigeria 11 Austria 5 5 Czech Rep. 10 Chile 5 5 Czech Rep. 10 Chile 5 5 figure o.28 Overview of fast moving countries (1990-2010) Source: IEA, UN, WB Global Electrification Database, WHO Global Household Energy Database. Note: Bosnia H. = Bosnia and Herzegovina. 29 Global tracking framework Global energy model scenarios enable us to gauge the The global energy models also help to clarify the kinds of scale of the global challenge of achieving the SE4ALL ob- policy measures that would be needed to reach the Sec- jectives. Based on these scenarios, it is clear that business retary General’s three sustainable energy objectives. The as usual will not suffice (table O.4). With regard to universal WEO and GEA coincide in highlighting the importance access, business as usual would leave 12–16 percent and of phasing out fossil-fuel subsidies, adopting measures 31–36 percent of the world’s population in 2030 without to provide price signals for carbon, embracing stringent electricity and non-solid fuels, respectively. Implement- technology standards for energy efficiency, and carefully ing all currently available energy efficiency measures with designing and targeting subsidies to increase access. reasonable payback periods would be enough to meet or even exceed the SE4ALL objective. However, numerous In addition, global models help to clarify the likely pattern barriers prevent wider adoption of many of those mea- of efforts to achieve the SE4ALL objectives across geo- sures, so that the current uptake ranges from around 20 graphical regions based on starting points, potential for percent for power generation and building construction to improvement, and comparative advantage. On energy around 40 percent for manufacturing and transportation. access, greatest efforts are needed in Sub-Saharan Africa Furthermore, few scenarios point to renewable energy and South Asia. For energy efficiency, the highest rates of shares above 30 percent by 2030. improvement are projected at around –4 percent annually in Asia (particularly China) and the countries of the former Existing global investment in the areas covered by the Soviet Union. For renewable energy, Latin America and three SE4ALL objectives was estimated at around $400 Sub-Saharan Africa (with its strong reliance on traditional billion in 2010 (table O.5). The additional annual invest- biomass) emerge as the regions projected to reach the ments required to achieve the three objectives are tenta- highest share of renewable energy in 2030—in excess of tively estimated to be at least $600–800 billion—a doubling 50 percent, compared to the 20–40 percent range in much or tripling of current levels. The bulk of those investments of the rest of the world (table O.6). is associated with the renewable energy and energy effi- ciency objectives, with access-related expenditures rep- resenting a relatively small share (10–20 percent) of the incremental costs. overview 30 Objective 1 Objective 2 Objective 3 Doubling global Doubling share rate of improve- Universal access to modern energy services of renewable ment of energy energy in global mix efficiency Renewable energy Population with Global rate of Population with share in total final Percentage in 2030 primary reliance on improvement in electricity access energy consumption non-solid fuels energy intensity* (%) (%) IEA scenarios   New policies 88 69 –2.3 20   Efficient world 88 69 –2.8 22  450 n.a. n.a. –2.9 27 GEA scenarios Baseline 84 64 –1.0 12   GEA Pathways 100 100 –3.0 to –3.2 34 to 41  20 Celsius n.a. n.a. –1.8 to –3.2 23 to 41 Table o.5 Overview of projected outcomes for 2030 from IEA World Energy Outlook and IIASA Global Energy Assessment Source: IEA (2012) and IIASA (2012). n.a. = not applicable. * IEA scenarios are presented in primary energy terms while GEA scenarios in final energy terms (GDP at purchasing power parity in both cases) Objective 1 Objective 2 Objective 3 Average annual Doubling global rate Doubling share Universal access to investment 2010–30 of improvement of of renewable Total modern energy services (US$ billion) energy efficiency energy in global mix Electrification Cooking Energy efficiency Renewable energy Actual for 2010 9.0 0.1 180 228 417.1 Additional from WEO 45.0 4.4 393 >>174 >>616.4* Additional from GEA 15.0 71.0 259–365 259–406 604–858** Table o.6 Overview of projected annual investment needs for 2010–2030 from World Energy Outlook and Global Energy Assessment Source: IEA (2012) and IIASA (2012). * WEO estimates are taken to be those closest to the corresponding SE4ALL objective: the Energy for All Scenario in the case of universal access, the Efficient World Scenario in the case of energy efficiency, and the 450 Scenario in the case of renewable energy. The 450 Scenario corresponds to a 27 percent renewable energy share, which is significantly below the SE4ALL objective. The Efficient World Scenario corresponds to a –2.8 percent CAGR for global energy intensity, which is significantly above the SE4ALL objective. ** GEA estimates that a further $716–910 billion would be needed annually for complementary infrastructure and broader energy sector investments not directly associated with the three objectives. 31 Global tracking framework Objective 1 Objective 2 Objective 3 Doubling global rate Doubling share Universal access to modern of improvement of of renewable energy energy services energy efficiency in global mix Percentage of Percentage of Renewable energy population with Rate of improvement population with share in total final primary reliance on in energy intensity* electricity access energy consumption non-solid fuels 2010 SE4ALL 2010 SE4ALL 1990–2010 SE4ALL 2010 SE4ALL Sub-Saharan Africa 32 100 19 100 1.1 2.2–2.4 56 60–73 Centrally Planned Asia 98 100 54 100 5.2 3.6–3.9 17 27–31 Central and Eastern Europe 100 100 90 100 3.1 2.6–3.0 8 28–36 Former Soviet Union 100 100 95 100 2.4 3.7–4.3 6 27–48 Latin America and Caribbean 95 100 86 100 0.7 2.6–3.0 25 49–57 Middle East and North Africa 95 100 99 100 -0.9 1.8–2.1 3 13–17 North America 100 100 100 100 1.7 2.4–2.6 8 26–34 Pacific OECD 100 100 100 100 0.7 2.9–3.4 6 30–41 Other Pacific Asia 89 100 57 100 1.2 3.6–4.0 18 30–37 South Asia 74 100 38 100 2.9 2.7–2.9 47 25–32 Western Europe 100 100 100 100 1.1 3.2–3.5 11 27–43 World 83 100 59 100 1.5 3.0–3.2 17 34–41 Table o.7 Global Energy Assessment: Regional projections under SE4ALL scenarios Source: IIASA (2012). Access to electricity for 2010 is from WB Global Electrification Database, 2012. Access to non-solid fuel for 2010 is from WHO Global Household Energy Database, 2012. * Measured in final energy terms and GDP at purchasing power parity Moreover, the global energy models clarify how the three for modern cooking, which would increase reliance on SE4ALL objectives interact with one another and contribute typically fossil-fuel-based and non-solid fuels for cooking, to addressing global concerns, such as climate change. would have a small offsetting effect, reducing the share of The IEA finds that energy efficiency and renewable energy renewable energy in the global mix by some two percent- are mutually reinforcing—neither one on its own is sufficient age points, with a negligible impact on the probability of to contain global warming to 2°C. Furthermore, achieving achieving the 2°C target. universal access to modern energy would lead to a negligi- ble increase—only 0.6 percent—of global carbon dioxide In conclusion, the Global Tracking Framework has con- emissions. The GEA estimates that the probability of limit- structed a robust data platform capable of monitoring ing global warming to 2°C increases to between 66 and 90 global progress toward the SE4ALL objectives on an im- percent when the SE4ALL objectives for renewable energy mediate basis, subject to improvement over time. Looking and energy efficiency are simultaneously met, higher than ahead, the consortium of agencies that has produced this if either objective was met individually (Rogelj and others report recommends a biannual update on the status of the 2013). The achievement of the universal access objective three SE4ALL objectives that will build on this framework. overview 32 While the methodology here developed provides an ade- forms of renewable energy, and most particularly the use quate basis for basic global tracking, there are a number of of traditional biomass. These are all required to ensure that significant information improvements that would be desir- high-performing policies are developed that effectively tar- able to implement in the medium term. To effectively mon- get tangible results. Developing the capability of countries itor progress through 2030 incremental investments in en- to develop and respond to such improved indicators is in ergy data systems will be essential over the next five years, itself a significant task. both at the global and national levels. These represent relatively cost-effective high-impact improvements, whose Finally, given the scale of the challenge inherent in meet- implementation would be contingent on the availability of ing the three SE4ALL objectives for energy, it is clear that financial resources. For energy access, the focus will be to a combination of bold policy measures with a supportive go beyond binary measures to a multi-tier framework that regulatory and institutional environment is required to sup- better captures the quantity and quality of electricity sup- port the requisite ramp-up of delivery capacity and finan- plied, as well as the efficiency, safety, and convenience of cial flows to the sector. A detailed analysis of the policy the cookstoves that are used for cooking, including those environment at the country level lies beyond the immediate that make use of biomass. For energy efficiency, the main scope of this Global Tracking Framework, which has fo- concern is to strengthen country capacity to produce more cused on the monitoring of global progress toward out- disaggregated data on sectoral and subsectoral energy comes. Such an analysis, however, would be an important consumption that are fully integrated with associated out- focus for future work in support of the SE4ALL initiative. put measures from the key energy consuming sectors. In the case of renewable energy, the main priority will be to improve the ability to gauge the sustainability of different Recommended targeting of effort over next five years Work to improve energy questionnaires for global networks of household surveys. Pilot country-level surveys to provide more precise and informative multi-tier measures Energy access of access to electricity and clean cooking Develop suitable access measures for heating. Integrate data systems on energy use and associated output measures. Strengthen country capacity to collect data on sectoral (and ideally subsectoral process) intensities. Energy efficiency Improve data on physical activity drivers (traffic volumes, number of households, floor space, etc.). Improve data on energy efficiency targets, policies, and investments. Improve data and definitions for bio-energy and sustainability. Capture renewable energy used in distributed generation. Renewable energy Capture renewable energy used off-grid and in micro-grids. Promote a more harmonized approach to target-setting. Table o.8 Medium-term agenda for the improvement of global energy databases 33 Global tracking framework References ExxonMobil. 2012. ExxonMobil—The Outlook for Energy: A View to 2040. Irving, Texas: ExxonMobil. Greenpeace International, EREC (European Renewable Energy Council), and GWEC (Global Wind Energy Council). 2012. Energy [R]evolution: A Sustainable World Energy Outlook. Greenpeace International, EREC, and GWEC. Amsterdam. IEA (International Energy Agency). 2012a. IEA World Energy Statistics and Balances. Paris. ———. 2012b. World Energy Outlook. Paris. http://www.worldenergyoutlook.org/publications/weo-2012/. IIASA (International Institute for Applied Systems Analysis). 2012. Global Energy Assessment – Toward a Sustainable Future. Cambridge, England, and Laxenburg, Austria: Cambridge University Press and IIASA. http://www.iiasa.ac.at/web/home/research/researchPrograms/Energy/Home-GEA.en.html Ki-moon, Ban. 2011. “Sustainable Energy for All: A Vision Statement.” United Nations Organization, New York. www.sustainableenergyforall.org. Rogelj, Joeri, David L. McCollum, and Keywan Riahi. 2013. “The UN’s ‘Sustainable Energy for All Initiative’ Is Compatible with a Warming Limit of 2°C.” Perspective DOI 10.1038/NCLIMATE1806, Nature Climate Change, February 24. overview 34 chapter 1 The SE4ALL Global Tracking Framework CHAPTER 1: The SE4ALL Global Tracking Framework At the behest of the UN Secretary General, the UN General Assembly declared 2012 the International Year of Sustainable Energy for All. The Secretary General’s Sustainable Energy for All (SE4ALL) initiative has three critical objectives to be achieved globally by 2030: (i) to ensure universal access to modern energy services; (ii) to double the global rate of improvement in energy efficiency; and (iii) to double the share of renewable energy in the global energy mix. SE4ALL is rapidly establishing itself as a catalyst for public-private action toward the achievement of the Secretary General’s three declared energy objectives. At the UN Con- ference on Sustainable Development in Rio de Janeiro (Rio+20) in June 2012, more than 60 countries opted into SE4ALL; that number has subsequently risen above 70. In addition, corporations and agencies have pledged tens of billions of dollars to the initiative. This combined effort will amount to an expansion of energy access to hundreds of millions of people worldwide. As 2012 drew to a close, the UN General Assembly announced that 2014–24 would be the Decade of Sustainable Energy for All. The need for a global tracking framework Given the need to sustain global attention on the SE4ALL replaced by the SE4ALL Advisory Board. The objectives objectives over the 20 years to 2030, it was soon recog- set for the Global Tracking Framework were three: (i) to nized that a mechanism to track global progress from the build consensus among all relevant institutions about the starting point would be an important component of the best methodology for tracking progress toward the three initiative. The mechanism would also enable tracking of SE4ALL objectives through 2030; (ii) to apply that method- country-level information and therefore allow stakehold- ology, with the year 2010 as the starting point for the three ers to highlight successful experiences and identify areas objectives; and (iii) to provide a road map for the gradual where additional effort may be needed. improvement of the Global Tracking Framework through 2030. The resulting Global Tracking Framework complements the SE4ALL initiative’s accountability framework, which Responsibility for the development of the Global Tracking provides transparent recognition and tracking of voluntary Framework was assigned to a Steering Group of interna- commitments to the initiative by specific institutions, there- tional energy-knowledge institutions with a history of strong by facilitating feedback, learning, and action. At the level of engagement in the SE4ALL initiative. The Steering Group is individual commitments, stakeholders are responsible for co-chaired by the World Bank/Energy Sector Management establishing milestones to record their progress for annual Assistance Program (ESMAP) and the International Energy reporting. Agency (IEA). Its members are: The Global Tracking Framework was commissioned by the original SE4ALL High-Level Group, which has since been 36 Global tracking framework }} Global Alliance for Clean Cookstoves (“the }} UN Energy Alliance”) }} UN Foundation }} International Institute for Applied Systems }} United Nations Development Programme Analysis (IIASA) (UNDP) }}International Partnership for Energy Efficiency }} United Nations Environment Programme (UNEP) Cooperation (IPEEC) }} United Nations Industrial Development Organi- }} International Renewable Energy Agency (IRENA) zation (UNIDO) }} Practical Action }} World Energy Council (WEC) }} Renewable Energy Network for the 21st Century }} World Health Organization (WHO) (REN21) Global versus country objectives The three SE4ALL objectives are conceived of as global economies, the nature of their climate and, in particular, objectives, applying to both developed and developing how aggressively they have pursued energy efficiency pol- countries, with individual nations setting their own domes- icies in the past. tic targets in a way that is consistent with the overall spirit of the initiative, depending on where they can make the For many developed and developing countries, renewable greatest contribution to the global effort. Some countries energy offers promise as a means of improving energy se- may be able to set national targets that are more ambitious curity, reducing the environmental impact of energy use, than the global ones, while the energy situation of others and promoting economic development. The availability may restrict them to more modest targets. of renewable energy resources around the globe varies greatly in extent and composition, however, affecting the For example, energy access remains a pressing concern degree to which individual countries may scale up the con- in many low- and middle-income countries. In high-income tribution of renewable energy to their overall energy mix. countries, on the other hand, universal access to modern energy has largely been achieved, even if some challeng- Already, more than 70 countries have opted into the es of energy poverty may remain. SE4ALL initiative. These countries are developing individu- al country action plans in which they will articulate their own In many cases, improving energy efficiency is the cheapest national targets within the context of the global SE4ALL way to expand the energy supply. Once again, however, framework. Overall, if all countries make their best efforts the potential to improve energy efficiency varies signifi- in the areas in which they have the most to contribute the cantly across countries depending on the structure of their global targets may be attained. The interconnected SE4ALL objectives The three SE4ALL objectives—though distinct—were con- tional methods used to do so have thermal efficiencies as ceived as an integrated whole. The three objectives are low as 10–20 percent. Providing universal access to mod- mutually supportive. In other words, it is more feasible to ern cooking solutions can help to shift households away achieve the three objectives together than it would be to from cooking on open fires in favor of improved cooking pursue them individually. stoves and non-solid fuels, which would significantly im- prove a given country’s overall energy efficiency. At the To illustrate this idea, consider the links between energy same time, on the electricity side, improvements in energy access and energy efficiency. The achievement of univer- efficiency enable existing power generation capacity to go sal energy access contributes to boosting energy efficien- further, thereby leaving more energy available to meet the cy and becomes more feasible as a result of advances in need for basic electricity access. Finally, improved energy energy efficiency. For example, a significant share of glob- efficiency makes energy more affordable by reducing the al energy consumption is traceable to household cooking implicit price of energy services, which helps to support the and heating, yet in many developing countries the tradi- expansion of access. chapter 1: The SE4ALL Global Tracking Framework 37 Improving energy efficiency also has the potential to arrest most remote and dispersed populations. Furthermore, as the growth of global energy consumption, making it possible part of the transition to modern cooking solutions, some to meet the SE4ALL objective of doubling the contribution households will substitute unsustainable forms of tradition- of renewable energy with a lower level of installed capacity. al biomass (such as wood and charcoal) for more sustain- able forms (such as wood pellets). Other households will Improvements in energy access and renewable energy are eventually substitute solid fuels derived from renewable also fundamentally related. The rollout of renewable ener- biomass for non-solid fuels (such as liquid petroleum gas) gy technologies, such as mini-grids and home systems, that are fossil-fuel based, however, with potentially offset- opens up new possibilities for providing electricity to the ting effects on the share of renewable energy. Toward a global tracking framework Concepts, data, and methodology While the three SE4ALL pillars—energy access, energy ef- next three chapters will map out the conceptual issues in- ficiency, and renewable energy—make sense intuitively, a volved in the definition of indicators, review the availability formal Global Tracking Framework necessitates rigorous of relevant global databases, and propose an accommo- technical definitions of improvement in those areas that dation of the two. can be measured consistently across countries and over time. In the case of energy access, even coming up with a While the immediate basis for global tracking is con- definition is conceptually challenging and subject to ongo- strained by what is already available, the quality and scope ing technical debate. In the case of energy efficiency, direct of global energy databases can be improved over time. To measurement is very demanding in data terms, and it may that end, this report also identifies incremental improve- be necessary to rely on proxies such as energy intensity. In ments to global energy databases that would significantly the case of renewable energy, on the other hand, deciding improve the resolution of the global tracking process and on a definition may be more straightforward, but choices that could be implemented in a five-year, medium-term still have to be made between alternative technical mea- scenario. Each chapter distinguishes between the immedi- sures (with regard to sustainability, for example). ate tracking methodology and the proposed medium-term improvements (table 1.1). A detailed road map for ongoing Providing rigorous technical definitions surely comes with improvements to global tracking will be presented in the significant challenges, but these are no greater in com- closing chapter. plexity than those faced in many other areas of develop- ment—such as poverty, human health, or water and san- In some cases, the development of global energy data- itation—where the global community has already pushed bases with the ideal level of detail and disaggregation ahead in tracking global progress. desired for tracking purposes may be beyond the realm of feasibility, even over a five-year period. Nevertheless, The development of sound technical definitions must as mentioned above, SE4ALL is designing country action necessarily be informed by a thorough understanding of plans and programs for the countries that have opted into the different global databases that are currently available. the initiative. It is highly desirable that these country ac- However compelling a definition may be, it is of little use tion programs use a standardized tracking framework, one for global tracking if corresponding time series data are that is consistent with the Global Tracking Framework while unavailable for the vast majority of the countries involved. still allowing for a more refined and detailed account of In the case of energy efficiency, for example, very detailed the countries’ individual energy situation. Therefore, each indicators are available for a small group of countries, but chapter will also identify which indicators may best be cap- these data are of limited value for global tracking. There tured at the country level. is often a trade-off, therefore, between the precision of an indicator and the scope of country coverage. The develop- ment of a tractable definition requires an iterative process that shuttles between the underlying concepts of interest and the constraints of data availability. Accordingly, the 38 Global tracking framework Immediate Medium-term Indicators highly desirable for global track- Indicators already available for global track- ing but that require a feasible incremental Global tracking ing, with all data needs (past, present, and investment in global energy data systems future) already fully met over the next five years Indicators ideal for country tracking but too Country-level tracking Not applicable ambitious for global tracking Table 1.1 Framework for identifying suitable global and country-level tracking indicators While the main focus of the methodology will be on the de- of complementary indicators can indicate that intermedi- velopment of a headline global tracking indicator, support- ate steps are being taken that should support more rapid ing indicators may also be helpful or necessary to interpret progress over time. For example, in the case of renewable the headline indicator. For example, the headline indicator energy, it is important to track policy commitments and proposed to proxy for economy-wide energy efficiency technology costs, which are key drivers of the scaling up will be complemented by measures of energy intensity in of renewable energy. four key sectors of the economy. In other cases, tracking Historic trends and a starting point The year 2010 was chosen as a starting point for SE4ALL and income groupings—to improve understanding of the because it is the most recent year for which all necessary variation around the current global average. data were available at the time of writing the report. It also provides a round 20-year period (2010–30) over which The starting-point indicators become much more mean- progress on the SE4ALL initiative can be charted. Once ingful when they are placed in the context of recent histor- the methodology for choosing indicators is defined and the ical trends. Subsequent chapters will show trends for the appropriate data sources identified, it becomes possible to 20 years leading up to 2010. Ultimately, an examination of compute starting-point indicators for the year 2010, against progress over the past two decades will help to clarify what which progress can be tracked. The chapters that follow has been achieved and to permit comparisons with what will report the reference indicators for each of the initiative’s needs to be achieved over the next 20 years if the SE4ALL three objectives—both globally and for large geographical objectives are to be met. Country performance The SE4ALL objectives are global, and progress toward In order to draw attention to high-impact countries, subse- them will be evaluated on a global basis. At the same time, quent chapters will identify countries that have the greatest global progress reflects the sum of efforts across the coun- opportunity to make substantial progress on any of the tries involved. Accelerating progress toward the achieve- SE4ALL objectives, particularly those whose efforts will ment of the SE4ALL objectives requires targeting efforts have greatest impact on the achievement of the global tar- where they are likely to have the greatest impact, as well as gets. Ongoing international efforts must pay special atten- identifying countries that have made rapid progress in the tion to addressing the challenges faced by these high-im- past and that may have valuable experiences to share with pact countries and providing the support necessary for others. Countries will need to understand their respective further progress; without success in these countries, the starting points to inform their individual target-setting pro- global targets are unlikely to be reached. cesses. For these reasons, the report provides a data an- nex that lists starting point indicators for the more than 180 Many countries are already doing well and have been countries for which data are available. This is accompa- making rapid progress on one or more of the three en- nied by an on-line database on the World Bank’s World De- ergy objectives. These fast-moving countries can provide velopment Indicators platform where all the global tracking others with policy lessons and concrete experience on the indicators can be downloaded: http://data.worldbank.org/ ground. The global effort to achieve the three SE4ALL ob- data-catalog. jectives will need to reflect a clear understanding of what chapter 1: The SE4ALL Global Tracking Framework 39 has worked in these countries and why. Facilitation of The good news is that some countries are both high-im- knowledge exchanges between fast-moving and high-im- pact and fast-moving, which suggests that opportunities pact countries promises to be particularly valuable. for progress are already being seized. The scale of the challenge How difficult will it be to reach the SE4ALL objectives? This report will draw on this important body of material to Comparing the road ahead with that already travelled pro- ascertain how challenging it will be to meet the SE4ALL vides some sense of the scale of the challenge. In addition, targets. In particular, it will examine what combinations of important insights can be gleaned by examining some of technology, policy, and finance may be needed for suc- the major recent global energy modeling exercises that cess. The models can also inform understanding of the re- project future trends in energy access, energy efficiency, lationship between the three objectives and their potential and renewable energy. for mutual reinforcement. Finally, they can help to clarify how the achievement of different objectives is likely to draw The outcomes of these modeling exercises ultimately differentially on different regions of the world, based on depend on underlying assumptions about technological their starting points and comparative advantages. change, policy adoption, and finance. Some, such as the IEA’s World Energy Outlook, focus on projecting trends It was not possible within the time available to prepare the from the underlying variables and gauging the resulting report to commission modeling exercises of scenarios impact on energy-system outcomes. Others, such as the designed specifically for the Global Tracking Framework. IIASA’s Global Energy Assessment, focus more on setting Instead, the report relies on preexisting scenarios, many specific targets for the global energy system and determin- of which are related to SE4ALL. As a result, however, the ing the technology, policy, and financing inputs that would reporting of results is limited to what is already available make reaching those targets feasible. In both cases, the in the literature and could not be standardized within this results are highly informative, even if direct comparisons report. between models may not be possible (box 1.1). Box 1.1. Global energy projections as a tool for understanding the scale of the se4all challenge The IEA’s World Energy Model The World Energy Model (WEM) is a large-scale model designed to simulate energy markets. It is the prin- cipal tool used to generate detailed sector-by-sector and region-by-region projections for the World Energy Outlook (WEO) scenarios. Developed over many years, the model consists of four main modules: final energy consumption (covering residential services, agriculture, industry, transport, and nonenergy use); energy trans- formation, including power generation and heat, refinery/petrochemicals, and other transformation; biomass supply; and fossil-fuel supply. The model’s outputs include energy flows by fuel, investment needs and costs, CO2 emissions, and end-user pricing. It is a partial equilibrium model; major macroeconomic assumptions are exogenously determined. The WEM is data intensive and covers the whole global energy system. Much of the data on energy supply, transformation and demand, and energy prices is obtained from the IEA’s own databases of energy and eco- nomic statistics. Various external sources provide additional data. The current version of WEM covers energy developments in 25 regions through 2035. Twelve large countries are individually modeled. The WEM is designed to analyze: 40 Global tracking framework }} Global and regional energy prospects. These include trends in demand, supply availability and constraints, international trade, and energy balances by sector and by fuel through 2035. }} Environmental impact of energy use. Estimates of CO2 emissions from fuel combustion are derived from the projections of energy consumption. Greenhouse gases and local pollutants are also estimated in order to link WEM with other models. }} Effects of policy actions and technological changes. Alternative scenarios analyze the impact of policy actions and technological developments on energy demand, supply, trade, investments, and emissions. }} Investment in the energy sector. The model evaluates investment requirements in the fuel supply chain needed to satisfy projected energy demand through 2035. Alternative scenarios also evaluate demand-side investment requirements. The WEM covers energy supply, energy transformation, and energy demand. The majority of the end-use sectors use stock models to characterize the energy infrastructure. In addition, energy-related CO2 emissions and investment in energy developments are specified. Though the general model is built up as a simulation model, specific costs play an important role in determining the share of technologies in satisfying energy service demand. In some parts of the model, Logit and Weibull functions are used to determine the share of technologies based on their specific costs. This includes investment costs, operating and maintenance costs, fuel costs and, in some cases, the costs of emitting CO2. The main exogenous assumptions of the model concern economic growth, demographics, international fos- sil-fuel prices, and technological developments. Electricity consumption and electricity prices dynamically link the final energy demand and transformation sector. Demand for primary energy is an input for the supply mod- ules. Complete energy balances are compiled at a regional level, and the CO2 emissions of each region are then calculated using derived CO2 factors. The time horizon of the model goes out to 2035, with annual time steps. Each year, the model is recalibrated to the latest available data point. Main model outputs and data of the WEO scenarios can be downloaded from: http://www.worldenergyoutlook.org/weomodel/. The IIASA’s Global Energy Assessment IIASA’s MESSAGE model was used for the development of the Global Energy Assessment (GEA) scenarios. MESSAGE is a systems engineering model for medium- to long-term energy-system planning, energy-policy analysis, and scenario development. The model represents the energy system in detail, from resource ex- traction, trade, conversion, transport, and distribution, to the provision of energy end-use services such as light, space conditioning, industrial production processes, and transportation. Specific features of the model include the explicit modeling of the vintaging of long-lived infrastructure, with assumptions regarding costs, penetration rates, and resource constraints based on literature surveys. In addition to the energy system, the model also includes generic representations of agriculture and the forestry sector, which allows incorporation of a full basket of greenhouse gas and air pollutant emissions (CO2, CH4, N2O, NOx, PM2.5, CO, SO2, BC, OC, SF6, volatile organic compounds, and various halocarbons). The current version of MESSAGE operates on the level of 11 world regions and can be used for short- to medium- term energy planning to 2030 as well as for long-term scenario analysis to 2100. The modeling framework and the results provide core inputs for major international assessments and scenarios studies, such as the Inter- governmental Panel on Climate Change (IPCC), the World Energy Council (WEC), the European Commission, chapter 1: The SE4ALL Global Tracking Framework 41 the German Advisory Council on Global Change (WBGU), and other multinational and national organizations. Principal applications of the model include the development of global and regional energy transformation pathways to address adverse social, environmental, and economic impacts of the energy systems. In the context of the GEA, the model was applied for the assessment of costs and benefits of the transformation in the following areas: }} Climate change }} Air pollution }} Energy access }} Energy security MESSAGE is a technology-rich optimization model. It minimizes total discounted energy system costs and provides information on the utilization of domestic resources, energy imports and exports, trade-related mon- etary flows, investment requirements, the types of production or conversion technologies selected (technology substitution), pollutant emissions, and interfuel substitution processes, as well as temporal trajectories for pri- mary, secondary, final, and useful energy. MESSAGE is coupled to the macroeconomic model MACRO for the assessment of macroeconomic feedbacks and internally consistent projections of energy demand and prices. Further linkages with IIASA’s GLOBIOM (agricultural) model allow the assessment of land, forest, and water implications of energy systems. Finally, an explicit linkage to IIASA’s GAINS air pollution framework allows the assessment of health impacts of energy systems. Main model outputs and data of the GEA scenarios can be downloaded at the interactive GEA scenario data- base: http://www.iiasa.ac.at/web-apps/ene/geadb/. The remainder of the report The remainder of this report follows through on the frame- down a road map for future global tracking of progress to- work laid down in this introductory chapter. Chapters 2-4 ward the objectives through 2030—proposing a number present a detailed discussion of energy access, energy of improvements that look to be feasible in the medium efficiency, and renewable energy. Each chapter begins by term—before synthesizing the main substantive conclu- addressing concepts, methodology, and sources of data sions of the report. and then goes on to present the starting point in 2010, to identify high-impact and fast-moving countries, and to sketch out the scale of the global challenge. Chapter 5 lays 42 Global tracking framework chapter 2 Universal Access CHAPTER 2: Universal Access to Modern Energy Services One of the three objectives of the Sustainable Energy for All (SE4ALL) initiative is to ensure universal access to modern energy services by 2030. The first section of this chapter examines the methodological challenges of measuring progress toward that goal and sug- gests approaches to address them. It also explains the methodology used to establish a starting point for the initiative. Succeeding sections describe global trends in access, opportunities to expand it, and the scale of the challenge ahead. Section 1: Methodological challenges in measuring access to energy There are two initial challenges in measuring access to en- household surveys, household connection data obtained ergy: (i) the absence of a universally accepted definition of from utilities, or residential consumption information at the “access” and (ii) the difficulty of measuring any definition in country level. a precise manner. Access to electricity is usually equated with the availability of an electricity connection at home or Taking advantage of the unique opportunity for international the use of electricity for lighting. Similarly, access to energy collaboration that SE4ALL presents, the data needed to for cooking is usually equated with the use of non-solid measure access can be improved over time, making it fuels1 as the primary energy source for cooking. These possible within five years to track access on the basis of binary metrics, however, fail to capture the multifaceted, multi-tier metrics supported by appropriate refinements in multi-tier nature of energy access and do not go beyond data-collection instruments. The rigorous piloting of ques- a household focus to include productive and community tionnaires, technology certification, and consensus build- applications of energy. ing in participating countries can substantially improve future measures of access. There is a growing consensus that access to energy should be measured not by binary metrics but along a The following subsection begins by identifying the data- continuum of improvement. Over the past decade, there bases currently available for measuring access and the have been several attempts to develop a more compre- main challenges of defining and measuring it. Proposals hensive measure—using single and multiple indicators, for multi-tier metrics of electrification and cooking solu- composite indicators, and multi-tier frameworks (annex 1). tions are laid out, and elements of those proposals are However, all these approaches have been underpinned integrated into the proposed global and country-level by available databases, which are typically derived from tracking frameworks. Compiling global databases to measure access at the starting point A variety of data sources, including primarily household relying primarily on non-solid fuels for cooking, and (iii) surveys and utility data, are used to measure access today. average residential electricity consumption.2 These indica- The most common indicators are (i) the rate of household tors are assembled from the following databases. connection to electricity, (ii) the proportion of households 1 Non-solid fuels include (i) liquid fuels (for example, kerosene, ethanol, or other biofuels), (ii) gaseous fuels (such as natural gas, liquefied petroleum gas [LPG], and biogas), and (iii) electricity. Solid fuels include (i) traditional biomass (for example, wood, charcoal, agricultural residues, and dung), (ii) processed biomass (such as pellets, and briquettes); and (iii) other solid fuels (such as coal and lignite). 2 Some household surveys also track certain electrical appliances (for example, radios, televisions, refrigerators), but data are not sufficient to build a global data base. chapter 2: universal access 44 The World Bank’s Global Electrification Database and the World Health Organization’s Global Household Energy Database To estimate access at the initiative’s starting point, set as cooking, the coverage was 142 countries and 97 percent 2010, the partner agencies used two global databases: of the world’s population. Countries classified as devel- the World Bank’s Global Electrification Database and the oped countries according to the regional aggregation of World Health Organization’s (WHO’s) Global Household the United Nations6 are assumed to have achieved a 100 Energy Database.3 Various household data sources were percent rate of access to electricity and non-solid fuel (that leveraged in compiling these two databases to establish a is, they are assumed to have made a complete transition to historical series of data on electrification and primary fuel using primarily non-solid fuels or modern cooking devices use between 1990 and 2010. Among the different sources, with solid fuels) (Rehfuess, Mehta, and Prüss-Üstün 2006).7 data from nationally representative household surveys (including national censuses) were given preference wher- Household surveys, though a consistent and standard- ever possible4, as these provide the most promising basis ized source of information, also present a number of for future global tracking (table 2.1). Sources include the challenges. Surveys such as the DHS or the LSMS/in- United States Agency for International Development’s come-expenditure surveys are typically conducted every (USAID’s) demographic and health surveys (DHS) and liv- 3–4 years, while most censuses are held every 10 years. ing standards measurement surveys (LSMS), the United Thus, a number of countries have gaps in available data Nations Children’s Fund’s (UNICEF’s) multi-indicator cluster in any given year. Further, different surveys may provide surveys (MICS), the WHO’s World Health Survey, other na- different types of data because of differences in questions tionally developed and implemented surveys, and various posed to respondents. For example, the question “Does government agencies (for example, ministries of energy your household have an electricity connection?” may elicit and utilities). While utility data are a valuable complement a different perspective on the household’s electrification to household survey data, they provide a different perspec- status than would another question, such as “What is the tive on access and cannot be expected to yield the same primary source of lighting?” This is especially the case for results. In particular, utility data may fail to capture (i) highly people who do not use electrical lighting despite having a decentralized forms of electrification in rural areas and connection—owing, for example, to a lack of supply during (ii) illegal access to electricity in urban areas.5 Given the evening hours or the need to use what little electricity is importance of these phenomena in the developing world, available for other activities. Similarly, different results are global tracking will be grounded in a household survey observed when “expenditure on electricity” data are trian- perspective. gulated with “having an electricity connection.” Further, most nationally representative surveys on household en- The development of the two global databases used in the ergy use fail to capture “fuel/cookstove stacking,” or the Global Tracking Framework followed an iterative process. parallel use of various kinds of stoves and fuels. Data col- As a first step, data on low- and middle-income countries lected are typically limited to primary cooking fuel. In some were compiled from nationally representative household cases, inconsistencies may arise purely from sampling surveys. For electrification, this included 126 countries and error or from the different sampling methodologies of the encompassed 96 percent of the world’s population; for underlying surveys. 3 World Health Organization (WHO), http://www.who.int/indoorair/health_impacts/he_database/en/index.html. 4 For cooking solutions, only nationally-representative surveys are included in the WHO Global Household Energy Database and used to derive modeled estimates. 5 The distinction between household survey data and utility data is clearly highlighted in the case of Indonesia. The utility (PLN) reports an electrification rate of 74 percent, while the national statistical agency (BPS) puts forth a figure of 94 percent based on household surveys. http://www.pln.co.id/eng/?p=55 and http://sp2010.bps.go.id/index.php/site/tabel?tid=301&wid=0 6 High-income countries with a gross national income (GNI) of more than $12,276 per capita (World Bank, http://data.worldbank.org/about/country-classifications) and countries in the developed country group according to the UN aggregation (see table at front of this report). 7 The International Energy Agency (IEA) also publishes energy access databases, with broad country coverage (on electricity access and on the traditional use of bio mass for cooking) and collates these in its annual World Energy Outlook (WEO). The World Bank and IEA electricity access databases are consistent for most countries but, in some cases, differences in methodology mean that they rely on differing sources. 45 Global tracking framework Number Coverage of Question: Question: name Description (no. of countries) surveys Electricity Cooking fuel (1990−2010) Is the household connected to an What is the main National statistical electricity supply source of cooking Census 214 346 agencies or does the fuel in your household have household? electricity? What type of fuel Demographic Does your house- MACRO International, does your house- and health 90 195 hold have elec- supported by USAID hold mainly use surveys (DHS) tricity? for cooking? Living standards Is the house measurement connected to an National statistical Which is the main surveys (LSMS) 29 LSMS 15 electricity supply? agencies, supported source of energy or income 116 IE 453 or What is your by the World Bank for cooking? expenditure (IE) primary source of surveys lighting? What type of fuel Multi-indicator Does your house- does your house- cluster surveys UNICEF 65 144 hold have elec- (MICS) hold mainly use tricity? for cooking? What type of fuel World Health does your house- WHO 71 71 Survey hold mainly use for cooking? Table 2.1 Description of household surveys source: authors. As a second step to develop the historical evolution and For the WHO Global Household Energy Database a mixed starting point of electrification rates, a simple modeling model8 was used to obtain a set of annual access rates approach was adopted to fill in the missing datapoints – to non-solid fuel for each country between 1990 and 2010 around 1990, around 2000, and around 2010. Therefore, a (see annex 2) (Bonjour and others 2012). This model de- country can have a continuum of zero to three datapoints. rived solid fuel use estimates for 193 countries. Generating There are 42 countries with zero data point and the weight- time-series curves for countries based on available actual ed regional average was used as an estimate for access data points has several advantages. It can derive point esti- to electricity in each of the data periods. 170 countries mates for those countries for which there are no data by using have between one and three data points and missing data regional trends. It also incorporates all the available data to are estimated by using a model with region, country, and derive point estimates and is not unduly influenced by large time variables. The model keeps the original observation if fluctuations in survey estimates from one year to the next. data is available for any of the time periods. This modeling approach allowed the estimation of access rates for 212 countries over these three time periods. chapter 2: universal access 46 Comparing the survey data from the latest available year estimates and data on the latest survey year are remark- and the modeled estimates suggests that differences ably aligned, at 83 percent (table 2.2). Oceania is the only are driven by inconsistent intervals between successive region with a substantial divergence, but that region in- household surveys and by the absence of survey data cludes the largest group of countries with the least num- for some countries at the starting point in 2010. Even so, ber of survey data points. the global and regional access rates from the modeled Access rate (% of population) CCA 99 100 DEV 100 100 EA 100 98 LAC 95 95 NA 99 99 Oceania 18 25 SA 75 75 SEA 88 88 SSA 32 32 WA 90 91 WORLD 83 83 Table 2.2 Comparing survey data and modeled estimates in the Global Electrification Database source: authors. NOTe: CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. IEA World Energy Statistics and Balances The International Energy Agency’s (IEA’s) World Energy the electrification rate and average annual household elec- Statistics and Balances database includes time series in- tricity consumption can suggest a country’s electricity ac- formation on total annual energy consumption in house- cess profile. However, as figure 2.1a shows, the correlation holds at the aggregate level.9 The database draws from a between the two variables is minimal. The spread of aver- variety of sources—including meter readings made by util- age consumption levels is extremely wide, not only among ity companies and surveys of household energy consump- countries that achieved universal access but also among tion—and represents 132 countries (but none in Oceania countries with lower electrification rates. The most dramat- and only 21 in Sub-Saharan Africa), covering 96 percent ic increase in residential consumption between 2000 and of the world’s population. The global information on resi- 2010 occurred in Eastern Asia, where it rose by more than dential electricity consumption presented in this chapter is twice (figure 2.1b). taken from this database. When plotted together, data on 9 Statistics on energy consumption in households include those on gas, electricity, and stockable fuel consumption (IEA 2012). 47 Global tracking framework 3022 World consumption 2545 7000 average annual consumption per HH (kwh) 6096 DEV World 3022 consumption 5434 2545 5991 6000 wa DEV 6096 4911 5434 (kwh) 2652 na wa 5991 electricity 1947 4911 5000 2081 2652 (kwh) lac na per household 1764 1947 electricity 1567 4000 ssa lac 2081 1474 per household 1764 1560 1567 residential ssa sea 1048 3000 1474 1333 1560 cca residential sea 10481460 2000 ea 1267 1333 cca 495 1460 average 1140 1267 1000 SA ea 844 495 average 1140 SA 0 844 2000 4000 6000 0 20 40 60 80 100 0 2000 4000 6000 Access rate (%) 2010 2000 2010 2000 Figure 2.1 Average annual household electricity consumption source: Based on the World Bank’s Global Electrification Database and IEA (2012). Note: IEA = International Energy Agency. Challenges to defining and measuring access at the starting point Access to electricity The existing definitions and measurements of access to Supply problems. In many developing countries, grid elec- electricity, although convenient, fail to capture several im- tricity, typically provided by utility companies, suffers from portant aspects of the problem. irregular supply, frequent breakdowns, and problems of quality (such as low or fluctuating voltage). Power is often Multiple access solutions. Off-grid options (for example, supplied only at odd hours (such as midnight or midday), solar lanterns or stand-alone home systems) and isolated when the need for electricity is minimal. Low wattage also mini-grids are required in many countries as transitional significantly reduces the usefulness of access under such alternatives to grid-based electricity. In geographically conditions. Connection costs and electricity charges con- remote areas, these options could potentially serve as strain energy use among households that cannot afford long-term solutions as well.10 Therefore, expansion of ac- them. Illegal and secondary connections serve a signifi- cess through off-grid and mini-grid solutions needs to be cant proportion of the population in many countries, rep- tracked in addition to main grid connections, though it is resenting lost revenues for the utility and posing a safety important to recognize that such solutions may vary in the hazard. None of these attributes of the availability, quality, quantity and quality of electricity they can provide—and affordability, and legality of supply are reflected in existing the measurement of electricity access should reflect those data on access. differences. Using current data and measures, access to electricity cannot be differentiated based on the supply Electricity supply and electricity services. Finally, electricity characteristics of the electricity source. is useful only if it allows desired energy services to be run 10 The International Energy Agency (IEA) has projected that about 60 percent of households not connected to the main grid at present are likely to obtain electricity through such systems by 2030 (IEA 2012). chapter 2: universal access 48 adequately. Access to electricity supply is therefore dif- higher consumption, clashing with energy-efficiency goals. ferent from use of electricity services, which implies the Poor households often have no choice other than to op- ownership of the appropriate electrical appliance and erate old and inefficient applications to meet their needs, the actual use of electricity.11 It is nonetheless important despite high unit costs. Finally, electricity consumption to measure both of these in order to inform policies and depends on several external factors, such as household project design. Meanwhile, measuring access to electricity income, household size, household spending priorities, services through consumption of kilowatt-hours (kWh) fails and so on. Therefore, ownership of appliances rather than to capture several important factors. First, such a measure electricity consumption provides a preferable measure of does not reflect which energy services are actually oper- access to electricity services. ated within the household. Second, it tends to emphasize Access to cooking solutions Current measures of access to modern cooking solutions fuel collection, particularly for women.13 Several studies are confined to fuels and therefore omit the role of the analyze the impacts of this burden on women’s health, cookstove. Understanding the cooking solutions of house- income-generating opportunities, and time for other tasks, holds entails knowing not only the fuels but also the type of not to mention leisure and repose (Clancy, Skutsch, and cookstoves used. It is the combination of the two that will Batchelor 2003). Time and effort invested in cookstove determine levels of efficiency, pollution, and safety out- preparation and cleaning, as well as in cooking itself, comes. Meanwhile, individual behaviors, cooking practices, are also important dimensions to consider. It is therefore and housing characteristics also affect the actual perfor- important to measure the “convenience factor” along with mance of a household’s cooking solutions. the technical performance of a cooking solution to obtain a comprehensive measure of access. Technical standards and certification systems related to cookstoves. Ongoing development of improved or ad- The variability of performance outcomes. The performance vanced cookstoves shows that high performance in terms of cooking solutions, as evaluated under standard test- of efficiency, pollution, and safety can be achieved even ing conditions, may not be achieved in practice owing to with solid fuels. This is important, since it is projected that individual behavior, cooking practices, and site conditions. a large part of the developing world will continue to rely on Maintenance requirements may have been disregarded solid fuels (biomass and coal) for cooking despite increas- and accessories such as chimneys, hoods, or pot skirts ing use of non-solid fuels (IEA 2012). Therefore, advanced not used, deteriorating the performance of the cookstove. biomass cookstoves that offer significant improvements over traditional self-made cookstoves may serve as a tran- Fuel stacking. Any measure of access solely based on the sitional alternative to the most modern cooking solutions. primary cooking solution will fail to capture the complex Nonetheless, it is not possible to evaluate the technical phenomenon of fuel stacking, which refers to the parallel performance of a cookstove through simple observa- use of multiple fuels and cookstoves (box 2.1). The tran- tion. A certification system is therefore needed, whereby sition to more modern energy solutions in the home is cookstoves carry a stamp that indicates their perfor- a dynamic process, and many factors contribute to the mance level.12 This presents an additional challenge to choice of fuels and cookstoves.14 Even households that reach universal consensus on the technical standards have adopted a modern fuel or an advanced cookstove used for certification. may continue to use—in parallel—secondary and tertiary fuels and cookstoves on a regular basis. The underlying Convenience of cooking solutions. For the poorest house- causes of this practice need to be identified to inform pol- holds cooking often involves lengthy and exhausting icy and project design. 11 Measurement of access to electricity supply reflects the performance of utilities, markets, and policies in ensuring that electricity supply is fully usable, while measurement of access to electricity services reflects the combination of electricity supply and consumer behavior. Greater use of modern energy affects socioeconomic development. 12 A stamp or label could indicate the stove’s performance as measured during laboratory tests and field-tests where available. 13 Gender roles and inequalities impose differential burdens on family members with regard to cooking energy systems. Women and children bear the main negative impacts of fuel collection and transport, indoor air pollution, and time-consuming and unsafe cooking technologies. 14 Modern cooking solutions include those that involve electricity or liquid/gaseous fuels (including liquefied petroleum gas), or the use of solid/liquid fuels paired with stoves that have overall emissions rates at or near those of LPG. 49 Global tracking framework Box 2.1 Capturing home energy needs: Fuel stacking and multiple end uses Regular use of multiple fuels and cookstoves, also called “fuel stacking,” is a common practice throughout the developing world. Households in both urban and rural areas routinely use two or more fuels for cooking alone. Different studies in Latin America find that even households that have switched to liquefied petroleum gas (LPG) as a primary cooking fuel still rely on simpler, less-efficient cookstoves or open fires to prepare some types of foods (for example, tortillas—a daily staple), or to meet their space or water heating needs (Masera, Díaz, and Berrueta 2005; Davis 1998). Similar patterns of multiple fuel use have been documented in Viet- nam, Brazil, Nepal, Ghana, India, and South Africa (Heltberg 2004). Fuel and cookstove stacking have been attributed to a combination of factors, including household income, multiple end uses (cooking, re-heating, boiling, etc.), cooking practices (types of food prepared, cooking time, taste, etc.), fuel availability and fuel consumption, as well as available infrastructure (access to electricity and gas pipelines) (Heltberg 2005; Davis 1998; Link, Axinn, and Ghimire 2012). Access to heating Heating is a major energy requirement in many countries, weather patterns of a country, but also on the housing sit- and its measurement presents several challenges. Heating uation (poor insulation can substantially increase heating needs can be met through a range of solutions: heat from needs). As yet, there are no available data on energy for a cookstove, fuel-based heating devices, a district heat- heating that would allow the compilation of a global data- ing system provided by a public utility based on combined base. In the medium term, SE4ALL envisions development generation of heat and power, or electric heating. Heating of a framework to adequately measure access to heating. needs depend not only on the geographical location and Community and productive uses of energy A household-based definition of access to energy excludes community infrastructure (such as clean water, street light- access to energy for community services and productive ing, and so on) have better chances of escaping the pov- uses.15 erty trap (Cabraal, Barnes, and Agarwal 2005). Models that deliver energy and energy services to poor households in Energy is crucial for enterprises. It drives economic and a financially sustainable manner by leveraging productive social development by increasing productivity, incomes, and community energy users as anchor loads have been and employment16; reducing workloads and freeing up demonstrated across many countries—albeit still on a time for other activities; and facilitating the availability of small scale. higher-quality or lower-priced products through local pro- duction. In addition, providing energy to businesses se- Data paucity is again a major constraint in measuring cures the higher economic sustainability of electrification access to energy for community services and productive projects, as productive activities often translate into higher uses. Only recently, the IEA attempted to measure access energy demand density and more reliable capacity to pay to energy for public services and productive uses (IEA (EUEI 2011). 2012). Similarly, the nongovernmental organization (NGO) Practical Action has identified households, community in- Energy for community services (e.g., health and education) stitutions, and productive enterprises as three dimensions is fundamental for socioeconomic development, because of energy access (PPEO 2012; 2013). In the health sector, it can lead to the substantial improvement of human capital. a recent joint WHO and USAID collaboration to harmonize Healthier, more-educated people with access to basic indicators for health-facility assessments resulted in a 15 Productive uses of energy are defined as those that increase income or productivity and refer to the activities that add value, which could be taxable if part of the formal economy (EUEI 2011). 16 It is understood that energy access is a necessary but rarely sufficient condition for driving economic growth. Access to finance, markets, raw materials, technology, and a qualified workforce are also determinant factors. chapter 2: universal access 50 comprehensive and cross-cutting facility-assessment tool Scientific, and Cultural Organization (UNESCO) has been called the Service Availability and Readiness Assessment tracking access to electricity, teaching aids, and comput- (SARA), which includes an energy component. Created to ers in schools as a part of its survey of school infrastructure fill critical gaps in measuring and tracking progress in the quality. These available data, based on connection rates, strengthening of health systems based on minimum ser- indicate that many schools and health clinics are not elec- vice standards, SARA provides a consistent methodology trified (figure 2.2). for annual country-led monitoring of health service delivery in the country, including energy access (that is, the avail- Relying on such efforts and methodologies, the SE4ALL ability, source, and reliability of electricity). Currently, addi- initiative will begin to develop comprehensive frameworks tional efforts by the WHO are under way to develop an en- for measuring energy access across community services ergy module for health-care facilities that can be used as a and productive uses. Those frameworks will be implement- stand-alone assessment tool or in conjunction with SARA. ed over the medium term. In the education sector, the United Nations Educational, Cape Verde (2010) Gabon (2011) Rwanda (2011) Equatorial Guinea (2010) Eritrea (2010) Nigeria (2008) Senegal (2010) Ghana (2011) Gambia(2004) Côte d'Ivoire (2009) Egypt (2004) Cameroon (2010) Namibia (2009) Gambia (2010) Ethiopia (2008) Malawi (2010) Rwanda (2007) Mali (2011) Zambia (2005) Burkina Faso (2010) Bangladesh (1999-00) Togo (2010) Kenya (2010) DRC (2010) Nigeria (2011) Tanzania (2010) Ghana (2002) Guinea (2010) Sierra Leone (2012) Burundi (2010) Guyana (2004) Niger (2010) Tanzania (2006) Cen. African Rep. (2011) Uganda (2007) 0 20% 40% 60% 80% 100% 0% 10% 20% 30% 40% 50% 60% Figure 2.2A public primary schools Figure 2.2B health clinics without electricity without electricity source: UNESCO Institute of Statistics (UIS) Database. source: WHO Energy in Health Care Facilities Database A candidate proposal for tracking access The multi-tier metric described below may be considered set too high (for example, universal access to uninterrupt- as a candidate proposal to address the challenges in cur- ed grid-based electricity or to gaseous fuels for cooking rent definition and measurement techniques, drawing on by 2030) would be unachievable for many countries. A bar numerous recent efforts. The metric is flexible and allows set too low (for example, universal access to lighting) risks for country-specific targets to be set. Because the chal- making the SE4ALL initiative less relevant for countries lenge of energy access varies across and within countries, with high rates of grid electrification but suffering from poor setting minimum standards of energy access without due supply. A multi-tier approach would embrace the appro- regard to the stage of evolution of energy systems would priate interventions to adequately track progress toward understate the challenges faced around the world. A bar universal energy access across countries. 51 Global tracking framework Access to electricity The candidate proposal consists of a multi-tier measurement Incidence and intensity of access. The proposed approach encompassing the following considerations (figure 2.3). evaluates both the extent of access (how many house- holds have access) and the intensity of that access (the Electricity supply and electricity services. The multi-tier level of access that households have). This structure allows proposal consists of two distinct yet intertwined electricity for an aggregated analysis of access to electricity supply measurements that can be compiled into two indices. On as well as use of electricity services using two separate the one hand, it measures access to electricity supply17 indices that can be calculated for any geographical area.19 using multiple tiers, defined by increasing levels of sup- It is possible that the same household would not reach the ply attributes, including quantity (peak available capacity), same tier across the two measurements. Indeed, a higher duration, evening supply, affordability, legality, and quality, level of electricity supply does not automatically result in whereby more and more electricity services become feasi- additional electricity services. Electricity services typically ble (annex 3). Different energy services (such as lighting, lag behind improvements in supply, as consumers grad- television, air circulation, refrigeration, ironing, and food ually acquire electrical appliances. Increased use of elec- processing) require different levels of electricity supply in tricity is also constrained by limited household income terms of quantity, time of day, supply duration, quality, and and telescopic electricity tariffs.20 Some households may affordability.18 On the other hand, it measures use of elec- also benefit from higher tiers of electricity services despite tricity services using multiple tiers, based on ownership of having poor electricity supply because they can afford appliances categorized by tier, each corresponding to the stand-alone solutions (for example, diesel generators and equivalent tier of electricity supply needed for their ade- inverters) as backups. Thus, gaps between access to elec- quate operation. For instance, in tier 1, access to basic ap- tricity supply and access to electricity services are to be plications such as task lighting, radio, and phone charging expected, revealing important information on the types of is possible. From tier 2 onwards, access becomes increas- interventions needed to improve access. ingly advanced, allowing a higher number of electricity applications to be used. Data collected in the course of calculating the two indices can also be used to conduct a disaggregated analysis of Diversity of supply options. The structure of this proposal the incidence of various aspects of supply constraint,21 by is technology-neutral and encompasses off-grid, mini-grid, type of supply technology or by level of access to elec- and grid solutions, while reflecting the large spectrum of tricity services. electricity access levels. Each technology is evaluated based on its capacity to provide for a certain tier of elec- tricity supply, which subsequently affects the provision of energy services. 17 Access to electricity supply can be achieved through a combination of central grid, mini-grid, and stand-alone solutions. 18 For example, a grid-based electricity connection where supply is not available during the evening hours is not suitable even for basic lighting. 19 A village, a district, a province, a country, a continent, or the whole world. 20 The unit price of electricity increases at higher consumption levels. 21 Share of households receiving less than four hours of electricity per day, share of households facing affordability issues or poor quality of supply, and so on. chapter 2: universal access 52 access to electricity supply Attributes Tier 0 Tier 1 Tier 2 Tier 3 Tier 4 Tier 5 Peak available capacity (W) - >1 >50 >500 >2,000 >2,000 Duration (hours) - ≥4 ≥4 ≥8 ≥16 ≥22 Evening supply (hrs) - ≥2 ≥2 ≥2 ≥4 ≥4 Affordability - - √ √ √ √ Legality - - - √ √ √ Quality (voltage) - - - √ √ √ }} Five-tier framework. Index of access to electricity supply = ∑(PT x T) }} Based on six attributes of electricity supply. with PT = Proportion of households at tier T }} As electricity supply improves, an increasing T = tier number {0,1,2,3,4,5} number of electricity services become possible. use of electricity services Tier 0 Tier 1 Tier 2 Tier 3 Tier 4 Tier 5 - Task lighting General Tier 2 Tier 3 Tier 4 AND lighting AND AND AND phone charging AND any any medium- any (OR radio) television low-power power appliances high-power AND appliances appliances fan (if needed) }} Five-tier framework. Index of access to electricity supply = ∑(PT x T) }} Based on of appliances. with PT = Proportion of households at tier T T = tier number {0,1,2,3,4,5} Figure 2.3 Candidate framework for multi-tier measurement of household electricity access source: authors Cooking The candidate proposal measures access to cooking by solutions meet the needs of households. The combination evaluating, on the one hand, the technical performance of of the two metrics offers a comprehensive measurement of the primary22 cooking solution (including the fuel and the access to cooking. Similar to electricity, the methodology cookstove), and, on the other hand, assessing how those is based on multiple tiers and is fuel-neutral (figure 2.4). 22 The primary cookstove is defined as the one that is the most used for cooking meals. 53 Global tracking framework Step 1: technical performance • Multi-tier technical measurement of the primary cooking solution in two steps: 1. Three-level measurement based on the direct observation of the cookstove and fuel. 2. Manufactured non-BLEN cookstoves (medium grade) are further categorized into four grades based on technical attributes. This grade categorization would only be possible for cookstoves that have under- gone third-party testing. Non-BLEN manufactured cookstoves that have not been tested are assumed to be Grade D. Low grade Medium grade High grade Self-made1 cookstove Manufactured2 non-BLEN cookstove BLEN3 cookstove Low grade Medium grade High grade Attributes Grade-E Grade-D Grade-C Grade-B Grade-A Efficiency Certified Non-BLEN manufactured Cookstoves Indoor pollution Overall pollution Self-made Uncertified Non- BLEN cookstoves or BLEN manufac- cookstoves or Safety equivalent tured cookstoves equivalentt 1 A self-made cookstove refers to a three-stone fire or equivalent, typically made by an untrained person without the use of premanufactured parts. 2 A manufactured cookstove refers to any cookstove available in the market (including cookstoves from artisans and small local producers trained under a cookstove program) 3 BLEN cookstove refers to stove-independent fuels (such as biogas, LPG, electricity, natural gas). BLEN equivalence of more fuels (such as ethanol) would be examined going forward. Non-BLEN cookstoves include most solid and liquid fuels for which performance is stove dependent. Step 2: actual use • Measurement of additional aspects of access beyond technical performance. • Three types of attributes, as listed below: • Chimney/hood/pot skirt used (as required). Conformity • Stove regularly cleaned and maintained (as required). • Household spends less than 12 hrs/week on fuel collection/preparation. Convenience • Household spends less than 15 min/meal for stove preparation. • Ease of cooking is satisfactory. • Primary stove fulfills most cooking needs of the household, and it is not constrained by availability or affordability of fuel, cultural fit, or number of burners. Adequacy • If multiple cooking solutions are used (stacking), other stoves are not of a lower technical grade. • Multi-tier measurement is based on technical performance adjusted for the above attributes. level 0 level 1 level 2 level 3 level 4 level 5 Grade-A w/o CCA w/ CCA Grade-B w/o CCA w/ CCA Grade-C w/o CCA w/ CCA Grade-D w/o CCA w/ CCA Grade-E w/o CCA w/ CCA Figure 2.4 Candidate framework for multi-tier measurement of household cooking solutions* chapter 2: universal access 54 Index of access to electricity supply = ∑(PT x T) with PT = Proportion of households at tier T T = tier number {0,1,2,3,4,5} source: authors. Note: BLEN = biogas-LPG-electricity-natural gas; CCA = conformity, convenience, and adequacy. * The proposed multi-tier framework (above) is complementary to the multi-tiered technical standards for cookstove performance proposed by the Alliance led International Workshop Agreement (IWA). The IWA multi-tier standards provide the basis for measurement of cookstove performance on the four techni- cal attributes—efficiency, indoor pollution, overall pollution, and safety (annex 4). Laboratory measurements based on the IWA standards would be used by the multi-tier framework (above) to determine the overall technical performance of the primary cookstove in step-1. The objective of the multi-tier framework (above) is to measure the level of household access to cooking solutions. It builds upon the technical performance of each of the multiple cooking solu- tions being used in the household (including the use of non-solid fuels), while also taking into account CCA attributes. The technical performance of the primary cooking solution stove performance on these attributes may be measured is evaluated in two steps. First, the cooking solution is cat- using the IWA developed by the Global Alliance for Clean egorized as low, medium, or high grade, based on direct Cookstoves (hereafter, the Alliance)27 (annex 4). observation of stove and fuel type, and on whether it is (i) a self-made cookstove,23 (ii) a biogas-LPG-electricity–natural Results from the third-party testing of cookstoves should gas (BLEN) cookstove,24 or (iii) a manufactured non-BLEN be reported publicly through the Stove Performance Inven- cookstove (including kerosene cookstoves— see box 2.2).25 tory, which is maintained by the Alliance. Certified cook- A self-made cookstove is assigned a Grade E, while the stoves may also carry an easily identifiable stamp or label BLEN cookstove is assigned a Grade A. Second, the (or brand name) that provides easy indication of their tech- manufactured non-BLEN cookstove is assessed based nical performance based on laboratory testing, through a on whether it has been tested or not. If it is not tested, its certification system developed at the country level. A network performance is unknown and it is assigned a Grade D. If of designated certification agencies and laboratories could results are available from third-party testing that meet the be established for this purpose, possibly assisted by the requirements of the International Standards Organization’s Alliance and WHO.28 (ISO’s) International Workshop Agreement (IWA),26 the technical grades can be refined further. It is acknowledged that the evaluation of tested or certified cookstoves adds complexity to the framework. Yet it is Non-BLEN manufactured cookstoves are differentiated desirable to base the evaluation of technical performance across Grades A, B, C, D, and E based on their perfor- on empirical data and capture the efforts of the Alliance, mance across four technical attributes that correspond to testing centers, donors, and manufacturers in promoting the four performance indicators in the IWA: (i) fuel efficiency, advanced cookstoves. The five-grade technical measure- (ii) overall emissions, (iii) indoor emissions, and (iv) safety. ment is therefore essential for capturing the wide spectrum The IWA tiers of performance have been directly mapped of manufactured cookstoves, and for incentivizing testing to Grades A to E for this measurement system. The cook- and certification.29 23 Including open fires and all types of self-made cooking arrangements. 24 BLEN fuels are stove independent, that is, their technical performance does not depend on the type of stove used. 25 Including locally made or imported traditional stoves, clay stoves, improved stoves, advanced stoves, or any type of stove on the market. It is assumed for practical reasons that manufactured cookstoves perform better than self-made cookstoves, although this may not always be true. 26 The standards have been developed in collaboration with the WHO and International Standards Organization (ISO), and the latest version was agreed on at the International Workshop Agreement (IWA) meeting in February 2012. Protocols are under development for additional types of cookstoves (for example, plancha and charcoal) and multiple end-use stoves and will be incorporated into the IWA framework. 27 The Global Alliance is a public-private partnership aiming to achieve universal access to modern cooking by promoting a global market for clean and efficient household cooking solutions. 28 The Global Alliance has started the process of establishing regional testing sites and aims to encompass a wide range of cookstoves and fuels. 29 A manufactured cookstove without certification is automatically categorized into the lowest level of manufactured stoves (Grade D), since its performance is unknown. 55 Global tracking framework Beyond the technical performance of the cooking solution, of burners). If the use of the primary cooking solution is the framework attempts to evaluate its impact on the daily constrained by such factors, it is inadequate. lives of users. First, it determines whether the household uses the cooking solution in conformity with instructions Conformity, convenience, and adequacy (CCA) are the (that is, a chimney, hood, or pot skirt is used if required three attributes considered, in addition to technical perfor- and regular cleaning and maintenance are performed). mance, to obtain an integral measurement of access to a It also evaluates convenience, by considering how long modern cooking solution. The methodology proposes to it takes the household to collect the fuel and how long it adjust the technical grade of a cooking solution to account takes to prepare the cookstove. Finally, it examines the for these attributes to obtain the household tier (level) of issue of fuel stacking by considering whether the house- access. If all three attributes are satisfied, the technical hold regularly uses a secondary cooking solution and for grade is raised to a higher tier (level). If the household’s what reason (for example, the primary fuel is too expensive solution does not comply with all three attributes, the tech- or is not always available; or the solution does not satisfy nical grade remains unchanged at the lower tier (level). cultural preferences or does not have the desired number Box 2.2 Kerosene use in the home for cooking, heating, and lighting Kerosene makes a significant contribution to the basket of fuels that households use to meet their energy needs. In several Sub-Saharan countries, national surveys show that more than 80 percent of households rely on kerosene as their primary energy source for lighting. Similarly in some Middle Eastern and Sub-Saharan countries, national surveys indicate that more than 25 percent of households rely mainly on kerosene to meet their space-heating needs. The results of national surveys from 122 low- and middle-income countries show that, on average, approxi- mately 4 percent of households use kerosene as their primary cooking fuel. These households are concen- trated in two regions, Sub-Saharan Africa and South Asia, with some countries exhibiting much higher levels of reliance on kerosene for cooking—such as Nigeria and Eritrea at about 20 percent, and Maldives and Indonesia closer to 40 percent of households. Kerosene: A risk for health In the past, kerosene stoves and lamps were considered a cleaner-burning alternative to traditional solid fuel for cooking, heating and lighting. But recent scientific studies have shown that, depending on the design of the device (cookstove, lamp), household use of kerosene can emit troubling amounts of health-damaging pollutants (particulate matter, carbon monoxide, and formaldehyde) that have been shown to impair lung function, increase infectious illnesses (for example, tuberculosis), and cancer risk (Lam and others 2012). Kerosene use also poses a number of health and safety risks in and around the home, including poisoning and burns (Mills 2012). Accordingly, use of kerosene lamps for lighting is classified as tier 0 in the multi-tier framework for access to electricity supply. For the purpose of tracking access to modern cooking solutions, kerosene is classified as a non-BLEN fuel (see figure 2.4). Because emissions from kerosene-based cooking depend on the design of the cookstove (whether wick-type or pressurized-type), technical performance can vary substantially. Source: WHO Global Household Energy Database. chapter 2: universal access 56 Global and country tracking of access SE4ALL’s goal of universal access to modern energy ser- tricity in any meaningful form might set a target of achieving vices by 2030 will be achieved only if every person has ac- universal access to electric lighting. Other countries may cess to modern cooking and heating solutions, as well as choose to set the target of universal grid connectivity. Coun- productive uses and community services (SE4ALL 2012). tries that have recently achieved near-universal electricity This report proposes tracking arrangements for access to connections but face problems of adequacy, quality, and re- electricity and modern cooking solutions. It is expected liability of supply may choose to set a target that emphasiz- that similar frameworks for heating, productive uses, and es improved supply. Similarly, for household cooking solu- community services will be developed and implemented tions, countries with very low penetration of modern fuels or over the medium term. electricity may choose to set a target of certified advanced biomass cookstoves. Other countries may aim to achieve Given that access to modern energy is a continuum of universal access to BLEN fuels. Countries have the flexibility improvement and will be measured using the proposed of choosing whether they will improve access tier by tier or multi-tier methodology, countries are encouraged to set their jump across tiers. Large countries may set different targets own targets (choosing any tier above tier 0). Such targets for different provinces or subregions. will depend on the current access situation in the country, the evolution of the energy needs of users, the availability To address limitations in data availability, a phased (imme- of energy supply for income-generating activities, and the diate versus medium term) and differentiated (global ver- affordability of different energy solutions in the country. For sus country-level) approach is proposed (table 2.3). example, countries in which most people are without elec- Immediate Medium term • Modification of global omnibus surveys to obtain information for simplified three-tier measurement. Binary measurement of Global • Simplified three-tier measurement of access to electricity and access to electricity and tracking cooking solutions. cooking solutions. • Piloting and possible regular implementation of customized energy surveys to obtain five-tier access information globally. • Piloting of multi-tier framework for electricity and cooking solutions in select countries. Country-level • Development and piloting of approaches to track access to energy tracking for heating, community, and productive uses. • Regular multi-tier measurement of access to electricity and cooking solutions through table 2.3 Immediate and medium-term tracking across global and country levels source: authors. Tracking access to energy in the immediate term In the immediate term, the nature of existing databases cooking, the use of non-solid fuel as the primary cooking constrains measurement possibilities. The World Bank’s fuel is deemed to constitute access. In the absence of Global Electrification Database and the WHO’s Global data on cookstove type, the primary use of solid fuels is Household Energy Database will continue to support the treated as lack of access. Apart from the World Bank and tracking process. For estimating the starting point of elec- WHO databases, the IEA’s energy access databases are tricity access and tracking in the immediate future, house- a valuable additional source of information to support the hold connection to electricity constitutes the threshold, tracking process. regardless of the type of supply or services. Similarly, for 57 Global tracking framework Tracking access to energy in the medium term The adoption of a multi-tier metric, either in its entirety or in Country-level tracking. Countries that opt into a program part, would require enhancements to existing data-collec- to expand access to energy under the SE4ALL initiative tion instruments, moving away from a binary definition and will likely be able to implement a more elaborate system measurement of access. of monitoring access. A multi-tiered, comprehensive mea- surement of access, as in the candidate proposal, is possi- Household surveys remain the instruments best suited to ble only if a country’s government has developed the requi- obtaining the data required, but additional energy-focused site methodologies, extensively revised household surveys, questions should be designed. For electricity, surveys established testing laboratories, and carried out detailed could facilitate the reporting of households served by off- consultations with the parties involved. Such efforts need grid technologies (for example, solar lanterns or stand- to ensure that high-quality data are consistently generated. alone home systems), as well as households connected to decentralized mini-grids. Such technologies are most likely Global tracking. It is acknowledged that a major effort to to reach underserved peri-urban and rural populations— improve data is a long and intensive process and that where substantial progress is likely to be made in coming not all countries will be able to collect all the new data re- decades. Household surveys are also able to capture the quired. A simplified three-level measurement system that level of electricity supply (in terms of duration, quality, af- condenses the six tiers of the multi-tier candidate proposal fordability, and so on) availed by end-users and to identify would require only marginal improvement in data collec- the electricity applications used within the household. On tion (figure 2.5). The few additional questions needed to the cooking side, in the absence of any centralized utili- capture this information could be added to the household ty, household surveys are the only sources of data avail- survey instruments of the various international survey net- able to comprehensively capture all the fuels and types of works (such as DHS, LSMS, and MICs). cookstoves used by households and to assess questions of convenience and fuel stacking. no access BASIC access advanced access solar lantern global tracking tracking access no electricity or rechargeable home system or grid connection battery lantern to electricity country-level tracking tier-0 tier-1 tier-2 tier-3 tier-4 tier-5 no access basic access advanced access global tracking self-made cookstove manufactured non-blen cookstove blen cookstove tracking access to cooking country-level tracking tier-0 tier-1 tier-2 tier-3 tier-4 tier-5 Figure 2.5 Tracking access in the medium term source: authors. note: BLEN = biogas-LPG-electricity–natural gas. For electricity, access is graded as “no access,” “basic ac- data-collection process, this simplified version is technol- cess,” and “advanced access.” No access is aligned with ogy-based. It does not capture the nuances of advanced tier 0 of the multi-tier measurement, reflecting a complete access or the different attributes of electricity supply. lack of electricity. Basic access, aligned with tier 1, cor- responds to the level of supply and the level of electricity For cooking, access is graded as for electricity. No access services that a solar lantern can provide. Advanced ac- is aligned with tier 0 of the multi-tier measurement, and cess corresponds to tiers 2 and above, which are likely ob- corresponds mainly to self-made cookstoves. Basic ac- tained by off-grid and grid solutions. Using this simplified cess, aligned with tiers 1–3, reflects the use of manufac- measurement system, advances under programs such tured non-BLEN cookstoves. Advanced access, aligned as Lighting Africa and Lighting Asia would be counted as with tiers 4 and 5, corresponds to BLEN cookstoves or basic access. Stand-alone off-grid and mini-grid solutions the equivalent. Under this simplified measurement sys- would be counted as advanced access. To facilitate the tem, the use of manufactured non-BLEN cookstoves is chapter 2: universal access 58 captured as basic access, while the use of BLEN fuels multi-tier approaches that address many of the shortcom- would be considered advanced access. To facilitate the ings of the binary metric will be refined and piloted in select data-collection process, this measurement system is participating countries in order to validate them for wider based on the simple observation of fuels and cookstoves. application. The feasibility of rolling out global customized It does not capture the technical grade of the cooking energy surveys will also be explored. Methodologies for solution or additional details about the convenience or measuring access to energy for productive and commer- adequacy of the cooking solution. cial uses, as well as for heating applications, will also be developed. For country tracking in the medium term, the Such a simplified three-level measurement system follows refined version of the multi-tier metric for electricity and the same methodology of weighted aggregation as the full modern cooking solutions will be implemented across all multi-tier system. It is therefore possible to construct an in- participating countries. Selected implementation of mea- dex to capture both the incidence of access (how many surements of heating, productive, and community uses will households have access) and its intensity (the level of ac- also be carried out over this period. For global tracking in cess the households have—basic or advanced). the medium term, a simplified version of the multi-tier met- ric comprising two thresholds will be adopted. Nationally To sum up this section, binary metrics that rely on avail- representative household surveys will need to be modified able data have been used to set the starting point for the to capture the necessary household information for an ef- SE4ALL initiative and will continue to be used for global and fective implementation of this tiered metric (table 2.4). country-level tracking in the immediate future. Meanwhile, Proposed approach to Proposed approach to Challenge global tracking country tracking Two-threshold measurement to reflect Off-grid, mini- Technology-neutral multi-tier measurement access to electricity for lighting and for more grid, and grid based on attributes of supply and covering grid advanced applications on a technology- solutions and off-grid solutions. neutral basis. Not reflected. Quality of supply cannot Quality of supply aspects are reflected through Quality of supply be measured without detailed household detailed household surveys using the multi-tier surveys or reliable utility data. framework. Access to Both electricity services and electricity sup- electricity supply Electricity supply and services overlap ply are measured through separate multi-tier versus electricity across the two-threshold measurement. frameworks. services Productive and New methodologies to be developed. New methodologies to be developed. community uses Heating New methodologies to be developed. New methodologies to be developed. Two-threshold measurement to reflect the Technology-neutral multi-tier framework reflects Improved solid use of manufactured non-BLEN cookstoves the wide range of technical performance of fuel cookstoves and BLEN cookstoves (based on direct non-BLEN cookstoves, along with the associated observation). CCA attributes. Stacking of Multi-tier framework reflects fuel stacking Only the primary cooking solution is reflected. stoves and fuels through the adequacy attribute. Convenience and Not reflected. BLEN cookstoves may be Multi-tier framework reflects all actual use conformity assumed to be convenient and conforming. attributes. table 2.4 Addressing methodological challenges through the medium term source: authors. note: BLEN = biogas-LPG-electricity–natural gas; CCA = conformity, convenience, and adequacy. 59 Global tracking framework Section 2. Access to electricity This section presents a global and regional snapshot of access metrics and rests on modeled estimates from electricity access in 2010 and access trends since 1990. the World Bank’s Global Electrification Database, as It delves into country trends, identifying high-impact and elaborated in section 1. fast-moving countries. The analysis makes use of binary Global snapshot in 2010 The starting point for global electrification, against which future improvement will be measured, is established as 83 percent in 2010, with the SE4ALL global objective being 1.2 billion 100 percent by 2030. Due to the limitations of the binary people lived without electricity in 2010 metric in capturing inadequate service quality, this can be considered an upper bound for electrification. The electricity access deficit affects 17 percent of the Southeastern Asia (figure 2.6). The primary sources of en- global population, or 1.2 billion people, about 85 percent ergy for the unelectrified population are kerosene, candles, of whom live in rural areas and 87 percent in Sub-Saha- and batteries. Ensuring sustainable delivery of modern en- ran Africa and Southern Asia. The rest of the unelectrified ergy services to this unserved population is vital to global are scattered around the world, with a sizeable number in prosperity and development. Oth 157 SSA With electricity Without rural 590 5714 electricity 1166 993 83% 17% SA 418 urban 173 Figure 2.6 The electricity access deficit in 2010 (% and absolute number of unelectrified people in millions) source: World Bank’s Global Electrification Database 2012. note: Australia and New Zealand are included in the developed countries group (and not in Oceania). CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and the Caribbean; NA = Northern Africa; SEA = Southeastern Asia; SA = Southern Asia; SSA = Sub-Saharan Africa; WA = Western Asia; oth = others. chapter 2: universal access 60 The regional electrification rate varies from 25 percent in developing regions. Western Asia and Latin America are Oceania to 32 percent in Sub-Saharan Africa to near-uni- to some extent outliers which report by far the highest versal access (greater than 95 percent) in the Caucasus income and urbanization rate, yet report lower elec- and Central Asia, Eastern Asia, Northern Africa, and the trification rates than Eastern Asia and Northern Africa developed countries. More-urbanized and higher-income (figure 2.7). Southern Asia also stands out as having regions typically exhibit higher electrification rates. Northern an electrification rate of around double that observed in Africa, Eastern Asia, Southeastern Asia, and the Cauca- Sub-Saharan Africa and Oceania both with comparable sus and Central Asia are clustered together and demon- income levels and rates of urbanization. strate a distinctly higher electrification rate than the other 100 LAC 95% 80 urbanization rate (%) WA 91% 60 NA EA 99% 98% CCA 100% SEA 40 88% SSA SA 32% 75% 25% 20 Oceania 0 0 1000 2000 3000 4000 5000 6000 GDP per capita (constant US$) Figure 2.7 Regional electrification Note: CCA = Caucasus and Centralrate Asia; DEV in 2010, = developed by level countries; EA = Eastof urbanization Asia; LAC and income = Latin America and Caribbean; NA = Northern Africa; SEA = Southeast Asia; SA = Southern Asia; SSA = Sub-Saharan Africa; WA = West Asia source: World Bank’s Global Electrification Database 2012. note: Size of bubble indicates electrification rate by region. CCA = Caucasus and Central Asia; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SEA = Southeastern Asia; SA = Southern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. Sub-Saharan Africa and Oceania are the only regions in bot region). Similarly, urban areas have achieved more where the majority of the population remains unelectri- than a 90 percent electrification rate in every region except fied. In fact, Sub-Saharan Africa accounts for 48 percent Sub-Saharan Africa (63 percent of urban population) and of the unelectrified rural population in the world. Rural ar- Oceania (65 percent of urban population). It is evident that eas have achieved more than 63 percent electrification rural areas the world over remain far from universal access, in every region except Sub-Saharan Africa and Oceania while in urban areas the challenge is largely concentrated (where only 14 percent of the rural population is electrified in Sub-Saharan Africa and Oceania (figure 2.8). 61 Global tracking framework Access rate (% of population) total rural urban CCA CCA CCA WORLD 100 EA WORLD 100 EA WORLD 100 EA 80 80 80 60 60 60 40 40 40 WA LAC WA LAC WA LAC 20 20 20 SSA NA SSA NA SSA NA SEA Oceania SEA Oceania SEA Oceania SA SA SA total rural urban Figure 2.8 Regional electrification rates in 2010: by region source: World Bank’s Global Electrification Database 2012. note: CCA = Caucasus and Central Asia; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SEA Note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = East Asia; LAC = Latin America and Caribbean; = Southeastern Asia; SA = NASouthern Asia; = Northern Africa; SSA SEA = Sub-Saharan = Southeast Africa; Asia; SA = Southern WA Asia; SSA = Western = Sub-Saharan Asia. Africa; WA = West Asia Global trends In the 1990s and 2000s, the global electrification rate rose from 76 percent to 83 percent within 20 years, driven by expansion in rural areas, where the access rate grew from 1.7 billion 61 percent to 70 percent. The urban electrification rate people gained remained relatively stable, growing from 94 to 95 percent access to across the period. Southeastern Asia and Southern Asia electricity; witnessed dramatic progress, both displaying a 24 and 17 just slightly ahead of global percentage point increase respectively. Sub-Saharan Afri- population growth ca followed far behind, with gains of 9 percentage points and Oceania with 4 percentage increased in 20 years. ulation rose by around 1.7 billion people. Globally, there- Eastern Asia, Northern Africa, Latin America and the Carib- fore, access to electricity outpaced population growth by bean, and the Caucasus and Central Asia had already ac- about 128 million people during the period. While growth complished near-universal access by 2000. The remaining in the electrified population in Southern Asia, Eastern Asia, regions registered modest or negligible changes in the two Southeastern Asia, Latin America and the Caribbean, decades and remained in the 80−95 percent electrification Northern Africa, the Caucasus and Central Asia, and Asia range (figure 2.9). Oceania kept pace with growth in population, the growth in the electrified population of Sub-Saharan Africa fell behind 70% growth in population. of those The increment in electrification was comparable across gaining accesS both decades, but the geographical growth centers var- to electricity between 1990 and 2010 ied. Southeastern Asia, Western Asia, and Northern Afri- were from urban areas ca added an almost equivalent number of people in both decades. Southern Asia and Sub-Saharan Africa added a comparatively higher number of people in the second half Between 1990 and 2010, the global population expand- of the period (figure 2.10). ed by around 1.6 billion, while the global electrified pop- chapter 2: universal access 62 100 Access rate (% of Population) 80 60 40 20 0 1990 2000 2010 Figure 2.9A Global trends in the electrification rate, 1990−2010 Total Rural Urban source: World Bank’s Global Electrification Database 2012. 100 100 Access rate (% of Population) 80 80 60 60 40 40 20 20 0 0 sasa ea a w a asa se ea c aev a evld ia n w c la n a a a c ss s a s ed d c dor ia ea n c la rl n w c eac o co w o Global and regional trends in electrification and non-solid fuel access rates, 1990–2010 Figure Global 2.9B regional and regional trends 1990 trends in the in electrification 2000 electrification and non-solid 2010 rate, fuel access 1990−2010 rates, 1990–2010 SOURCE: WB, WHO, IEA 1990 2000 2010 SOURCE: WB, WHO, IEA source: World Bank’s Global Electrification Database 2012. Note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. 63 Global tracking framework Access Oceania Population Access CCA Population Access NA Population Access WA Population Access SSA Population Access LAC Population Access SEA Population Access EA Population Access SA Population Access WORLD Population 0 200 400 600 800 1000 1200 1400 1600 1800 population (million) Figure 2.10 Population growth and progress in access to electricity, 1990–2010 1990-2000 2001-2010 source: World Bank Global Electrification Database 2012. note: CCA = Caucasus and Central Asia; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. Dramatic urbanization has altered the profile of electrifica- ban areas, at 1.7 percent annually, far outstripped the 0.8 tion during 1990–2010. Population growth in urban areas percent growth rate found in rural areas. However, due to was explosive (about 1.3 billion people, compared to 315 more rapid demographic growth in cities, electrification in million in rural areas). As a result, the global population urban areas falls behind population growth by 56 million is now roughly equally divided between urban and rural people. On the other hand, the relatively modest popula- areas. The evolution of electrification, meanwhile, differed tion growth in rural populations made it possible for rural in its pattern. Starting in 1990, the electrified population electrification to outstrip population growth by 195 million. was 2.1 billion in urban areas and 1.8 billion in rural areas, Consequently, rural electrification rates jumped by 9 per- respectively (figure 2.11). Expansion of electrification in ur- centage points in 1990–2010. chapter 2: universal access 64 Rural Urban Total 0 1000 2000 3000 4000 5000 6000 7000 Population (million) Figure 2.11A Global progress in access, by urbanization status, 1990–2010 Population with access in 1990 Incremental access in 1990-2010 Population without access in 2010 source: World Bank’s Global Electrification Database 2012. Oceania CCA NA WA LAC SEA SSA DEV EA SA 0 200 400 600 800 1000 1200 1400 1600 1800 population (million) Figure 2.11B Global progress in access, by region, 1990–2010 Population with access in 1990 Incremental access in 1990-2010 Population without access in 2010 source: World Bank’s Global Electrification Database 2012. note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. The most-remarkable urban growth stories occurred in the In every region in the world, urban electrification expand- Asian regions and in particular in Eastern Asia, Southeast- ed by around 1 percent a year. Rural electrification, on the ern Asia, Western Asia and Southern Asia. The four regions other hand, witnessed minimal growth rates in Sub-Sa- displayed close to a 2.5 percent annual urban growth rate haran Africa and Oceania and a negative growth rate in and together managed to move 788 million people—39 Eastern Asia and the developed countries. The growth per- million a year—into electricity use. The rural increment was formance of Southeastern Asia and in Southern Asia was highest in Southern Asia and Southeastern Asia, where impressive in both rural and urban areas. 534 million, or 27 million people annually, were added to the rolls of rural electricity users. 65 Global tracking framework Though the access deficit in 2010 is geographically con- Sub-Saharan Africa, by contrast, only 156 million people centrated in Sub-Saharan Africa and Southern Asia, the gained access to electricity in 1990–2010, trailing popula- electrification trends in these two regions have moved in tion growth by 189 million people. Rural electrification was opposite directions. Sub-Saharan Africa is the only region particularly slow in Sub-Saharan Africa, where the elec- where the unelectrified population increased in both urban trified population grew only by 0.4 percent (figure 2.12). and rural areas, owing to an inability to keep pace with a Eastern Asia experienced a decrease in rural population growing population. Southern Asia recorded the most re- of about 163 million people over the two decades, with a markable progress in electrification, adding 669 million consequent annual decline of 1 percent in the electrified new users of electricity (about 33 million each year and rural population. 161 million more than population growth for the period). In 3 3% Annual growth in access (%) Incremental access growth (%) 2 2% 1 1% 0 0% -1 EA SEA WA SA NA SSA LAC Oceania DEV CCA WORLD -1% EA SEA Figure WA Annual 2.12 SA growth NA SSAin population LAC with access: Oceania DEV CCA WORLD Urban and rural Rural areas, 1990−2010 Urban Rural Urban Note: CCA source: World Bank’s = Caucasus Global and Central Asia; Electrification DEV = developed Database 2012. countries; EA = East Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SEA = Southeast Asia; SA = Southern Asia; SSA = Sub-Saharan Africa; WA = West Asia note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Caribbean; Note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = East Asia; LAC = Latin America and Caribbean; NA = Northern Africa; Africa; SEAAsia; SA = Southern NA = Northern SEA = Southeastern = Southeast Asia; SA = Southern Asia; SSA Asia; SSA == Sub-Saharan Sub-Saharan Africa; Africa; WAAsia = Western Asia. WA = West Country snapshots in 2010 The electrification rate spans a wide range: from just 1.5 lower end (<30 percent), those in the middle (30−95 per- percent in South Sudan to near-universal access in 39 cent), and those at the high end (>95 percent). At the low- developing countries. (When the developed countries are er end are 32 countries—28 in Sub-Saharan Africa, 3 in added, the number of countries with near-universal ac- Oceania, and 1 in Eastern Asia. Seven of these lower-end cess rises to 95.) Even within regions, there is heteroge- countries, all in Sub-Saharan Africa, have an access rate neity in the electrification rate. For example, in Sub-Saha- lower than 10 percent. At the higher end are 95 countries, ran Africa, Mauritius is the only country with access rates only one of them in Sub-Saharan Africa (Mauritius). The above 95 percent. In Southern Asia, the outliers are Bhu- Caucasus and Central Asia, Northern Africa, and the de- tan and the Islamic Republic of Iran where access rates veloped countries have homogenous universal access exceed 95 percent. rates. In all other regions, the countries are spread across the three blocks, though in Sub-Saharan Africa countries The world can be arbitrarily divided into three blocks of at the lower end of the electrification rate outnumber the countries based on the electrification rate—those at the countries at the higher end (figure 2.13). chapter 2: universal access 66 The heterogeneity stems primarily from disparities in rural uniform in urban areas, with 123 countries reporting areas. Four countries, all located in Sub-Saharan Africa, near-universal access. In urban areas, the median is higher still have less than 1 percent of their rural population in than 99.6 percent in all regions, except in Sub-Saharan the electrified category. The median rural access rate is Africa, where it is 53 percent. at 9 percent in Sub-Saharan Africa, compared to a global median of 89 percent. The electrification rate is relatively 1 1 2 3 4 2 13 20 11 8 56 5 3 7 8 27 9 28 3 1 CCA DEV EA LAC NA Oceania SA SEA SSA WA Figure 2.13 Distribution of rates of access to electricity, by number of countries per region <30 30<>95 >95 source: World Bank’s Global Electrification Database 2012. note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. High-impact countries The 20 countries with the highest access deficits and the 20 with the lowest electrification rates—dubbed “high-im- pact countries” for purposes of achieving the SE4ALL 74% target of universal access by 2030—illustrate the magni- of the global tude of the access challenge. The 20 countries with the access deficit greatest access deficits measured in absolute terms are for electricity is concentrated in home to 889 million people who lack access to electric- just 20 countries ity—more than two-thirds of the global total. Eight are in Asia and 12 in Africa. India’s share is the largest—India’s of the United States. 19 of the top 20 countries with the unelectrified population is equivalent to the total population lowest electrification rates are in Sub-Saharan Africa. All 20 countries together represent about 287 million unelectri- 19/20 fied people, one-fourth of the global total (figure 2.14). The development impact of electrification in these countries is countries immense, even though their contribution to the SE4ALL with the lowest energy universal access objective is projected to be substantially access rates globally are in Sub- smaller than that of the group of countries with the largest Saharan Africa access deficits. 67 Global tracking framework Malawi 13.6 South Sudan 2 1.5 Indonesia 14.0 Chad 4 3.5 Niger 14.1 Liberia 4 4.1 Burkina Faso 14.3 Burundi 5 5.3 Pakistan 15.0 Malawi 9 8.7 Philippines 15.6 Niger 9 9.3 10 9.5 Madagascar 18 17.8 CAR 11 10.8 Korea, DR 18 18.0 Rwanda 12 12.1 Afghanistan 18 18.5 Sierra Leone 13 13.1 Mozambique 20 19.9 Burkina Faso 14 14.3 Myanmar 25 24.6 Madagascar 14 14.5 Uganda 28 28.5 PNG Sudan 31 30.9 Uganda 15 14.6 Kenya 31 31.2 Tanzania 15 14.8 Tanzania 38 38.2 Mozambique 15 15.0 Congo, DR 56 55.9 Congo, DR 15 15.2 Ethiopia 64 63.9 Mali 17 16.6 Bangladesh 67 66.6 Lesotho 17 17.0 Nigeria 82 82.4 Mauritania 18 18.2 India 306 306.2 Zambia 18 18.5 0 100 200 300 400 0 2 4 6 8 10 12 14 16 18 20 access rate (% of population) population (million) Figure 2.14a Top 20 countries with Figure 2.14b Top 20 countries with lowest access rates largest access deficits source: World Bank’s Global Electrification Database 2012. source: World Bank’s Global Electrification Database 2012. note: CAR=Central African Republic; PNG=Papua New Guinea; note: DR = Democratic Republic. DR =Democratic Republic. Fast-moving countries Of the 20 countries with the largest number of people that Indonesia, Pakistan and Bangladesh. The advances in have been electrified during the last 20 years, 12 are in these populous countries are of enormous significance for Asia. Their experience could hold valuable policy lessons achievement of the global universal access target. In par- for other countries aiming to accelerate electrification. They ticular, India charted a remarkable trajectory, electrifying introduced 1.3 billion people to electricity (of the 1.7 billion 474 million people over two decades, or 24 million people electrified globally between 1990 and 2010), 283 million annually (figure 2.15), with an annual growth rate of around more than their population increase. The most impres- 1.9 percent. sive expansion of electrification occurred in India, China, chapter 2: universal access 68 25 5 20 4 annual growth in access (%) population (million) 15 3 10 2 5 1 0 0 l a ia a ia a ia a aq o o a d es n n h t m ey zi ic in bi pi bi yp ic c n a es es a er d a n a Ir st rk io m fr Ir a c ra h tn In ex Eg pi n d Br ig il C ro lo h ki A Tu o la ip iA e M a N Et Pa d Vi o il th o Th g d In C Ph M n u u Sa Ba So Figure 2.15 Top 20 developing countries with greatest annual progress in access to electricity, 1990−2010 incremental access (million) incremental total population (million) Annual growth in access (%) source: World Bank’s Global Electrification Database 2012. Focusing on absolute increments in the electrified popu- country—United Arab Emirates and Qatar—raised its pace lation tends to highlight the experience of populous coun- of electrification beyond 3.5 percent of the population an- tries. Another measure identifies a different group of 20 nually (figure 2.16). Interestingly, Iraq , Indonesia, Bangla- countries whose electrified population grew the fastest desh and Pakistan belong to both groups showing sub- relative to the size of their overall population. The analysis stantial progress in electrification both in absolute terms shows that these countries provided new electricity service and relative to the size of their respective populations. to at least 2 percent of their populations annually. Only two 4 annual growth in access (%) 3 2 1 0 ia ia a ba l a o a r s aq n s k es Se lic in h E n a o ri a d n bi n ta UA c es ys es a ra eg n at u a ic n Ba Ir Sy c rd ra b la Ar s pi d n h la pu ro a Q h ki n o la G ip iA Jo t C Ba a Is Pa Re d es il o M g d d In M Ph n W n n u n a Sa Ba a a m ic s ay rk in C Tu m o D Figure 2.16 Top 20 fastest-growing countries Global annual growth in access= 1.2% Annual growth in access (%) Developing Countries annual growth in access= 1.4% source: World Bank’s Global Electrification Database 2012. note: UAE = United Arab Emirates. 69 Global tracking framework Mapping multi-tier measurements with existing databases The World Bank’s Global Electrification Database and the sumption range of less than 3 kWh per year. From tier-tier 1 IEA’s World Energy Statistics and Balances can be used onwards, households have access to electricity at different with the multi-tier methodology for measuring electric- levels of service and quality. Each tier corresponds, among ity access by combining the country’s electrification rate other attributes, to the use of several appliances, which with average residential electricity consumption. But it is determine the definition of the range of kilowatt-hours per important to recognize that the approximation of the tier household per year equivalent to each tier. The associated (T), based on average consumption at the country level, annual household consumption range increases accord- does not provide the distribution of households across all ingly, with tier 5 corresponding to consumption in excess five tiers of access for the country. Moreover, an indicator of 2,121 kWh per year. based on kilowatt hours consumed cannot accurately re- flect the diversity of appliances used or appropriately ac- Residential electricity consumption data available from the count for energy efficiency. Implementation of the house- IEA,31 together with the electrification rate, make it pos- hold-level multi-tier framework using survey data is critical sible to place a country’s households either in tier 0 for to capture progress in electricity access in its entirety. those who lack access or in the tier corresponding to the average residential electricity consumption of the popula- This adaptation of the multi-tier methodology to available tion with access. In Zambia, for example, 81.5 percent of databases employs two variables to assign a tier to a households are categorized as tier 0 (no access) and 18.5 country and create an “index of access.” First, each tier is percent as tier 5 based on the average annual electricity transformed into annual consumption ranges by assuming residential consumption of 5,779 Kwh per household per indicative use (in hours) of a minimum package of electric- year. The index of access for Zambia is therefore a pop- ity services (in wattage) (annex 5). Tier 0 represents a cat- ulation-weighted average of these two tiers, which comes egory of households that do not receive electricity by any to 0.9. means and is associated with an annual household con- Tier 0 Tier 1 Tier 2 Tier 3 Tier 4 Tier 5 Task lighting General light- Tier 3 Tier 4 + ing Tier 2 + + Indicative elec- Phone + + - Medium or Heavy or tricity services charging Air circulation Light continuous continuous or + appliances appliances appliances Radio Television Consumption (kWh) <3 3–66 67–321 322–1,318 1,319–2,121 >2,121 per household per year Index of access to electricity supply = ∑(PT x T) with PT = Proportion of households at tier T T = tier number {0,1,2,3,4,5} Figure 2.17 Mapping of tiers of electricity consumption to indicative electricity services source: authors. note: kWh = kilowatt-hour. 31 The residential annual consumption per household varies in developing countries from 255 kWh in Sub-Saharan Africa to 20,000 kWh in Western Asia, with a median consumption of 1,696 kWh. chapter 2: universal access 70 The access index can range from 0 to 5. In 2000 the global reported an average index of 1.4 and 2.8, respectively (figure average of the simplified energy access index based on 2.18). All regions have shown progress in their indices average consumption was 3.6, and by 2010 it had in- over time, recording both higher electrification rates and creased to 3.9. 32 In 2010, 103 countries (78 percent) increased average consumption.33 The strongest improve- reported a value of 3 or above; the remaining 29 countries ments in performance were in Southeastern Asia and East- scored between 0.6 and 2.6 (19 of them in Sub-Saharan ern Asia. Sub-Saharan Africa reported weak improvement Africa). At the regional level, all regions had an index above in both electrification and average consumption. 3, except Sub-Saharan Africa and Southern Asia, which 6 5 4.9 5.0 4.7 4.4 4.4 4.1 4.2 4 3.9 3.9 4.0 4.0 3.9 3.7 3.6 3.3 index (0-5) 3.0 3 2.8 2.3 2 1.4 1.1 1 0 SSA SA SEA EA CCA WA LAC NA DEV WORLD Figure 2.18 Approximation to multi-tier index of electricity access based on national data, 2000 and 2010 2000 2010 source: Based on the World Bank’s Global Electrification Database and IEA (2012). note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SEA = Southeastern Asia; SA = Southern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. 32 The IEA’s World Energy Statistics and Balances database reports average consumption data by country for 132 countries out of the 212 countries included in the World Bank’s Global Electrification Database, leaving out 4 percent of the global population (295 million people in 2010). The lack of data is particularly acute in Sub-Saharan Africa, where 28 countries out of 49 do not report consumption data, accounting for 207 million people in 2010 (or 24 percent of Sub-Saharan Africa’s population). There are relatively large countries among them—one-third of the missing countries have populations in excess of 10 million people, and one country (Uganda) has a population of more than 30 million. 33 The only exception is the Caucasus and Central Asia region, which recorded a slight decrease in the average consumption. 71 Global tracking framework Section 3. Access to non-solid fuels This section presents a global and regional snapshot of holds still dependent on solid fuels.34 The country snap- access to non-solid fuels in 2010, as well as global trends shots provided in this section focus on high-impact and since 1990. Current global data capture only primary fuel fast-moving nations that are introducing large numbers of use. Given this constraint, in estimating the starting point new households to non-solid fuel. The analysis rests on for access to modern cooking solutions, access is defined modeled estimates from the WHO’s Global Household in terms of the primary non-solid fuel used by households Energy Database and explained in section 1. for cooking. The access deficit is represented by house- Global snapshot in 2010 The starting point for global access to non-solid fuel, against which future improvement will be measured, is established as 59 percent in 2010, with the SE4ALL global objective be- 2.8 billion ing 100 percent access by 2030. Owing to the limitations of people relied the binary metric in capturing usage of improved biomass primarily cookstoves, this can be considered a slight lower bound for on solid fuels for cooking in 2010 access to modern cooking solutions. geographically concentrated in Sub-Saharan Africa, East- If the share of the global population that used primarily ern Asia, Southern Asia, and Southeastern Asia (figure non-solid fuels in 2010 was 59 percent, that means that 2.19). Ensuring sustainable delivery of non-solid fuel to 41 percent of the global population, or 2.8 billion people, these households is vital to global prosperity and devel- relied mainly on solid fuels for cooking. About 78 percent opment (box 2.3). of that population lived in rural areas, and 96 percent was Oth 124 urban 598 ssa 690 Non Solid Fuel Solid Fuel SA 4076 2777 1018 59% 41% rural SeA 308 2179 eA 637 Figure 2.19 Deficit in access to non-solid fuel, 2010 (% and absolute number of people, in millions, using solid fuels) source: WHO’s Global Household Energy Database 2012. note: EA = Eastern Asia; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; Oth=Others. 3.5 million people die each year - mainly women and children - due to harmful indoor air pollution caused by unsafe cooking practices 34 Non-solid fuels include (i) liquid fuels (for example, kerosene, ethanol, or other biofuels), (ii) gaseous fuels (such as natural gas, liquefied petroleum gas [LPG], and biogas), and (iii) electricity. Solid fuels include (i) traditional biomass (for example, wood, charcoal, agricultural residues, and dung), (ii) processed biomass (such as pellets, and briquettes); and (iii) other solid fuels (such as coal and lignite). chapter 2: universal access 72 Box 2.3 Health and safety risks of the inefficient use of household fuels The inefficient use of energy in the home for cooking, heating, and lighting is a major health risk across the developing world. Gender roles and inequalities impose differential costs on family members, with women bearing most of the negative effects of fuel collection and transport, household air pollution, and time-con- suming and unsafe cooking technologies (Clancy, Skutsch, and Batchelor 2005). The smoke resulting from the incomplete combustion of fuels (for example, wood, coal, kerosene) is a major source of household air pollu- tion (HAP), which contains fine particles (for example, black carbon), carcinogens, and other health-damaging pollutants (for example, carbon monoxide). Exposure to HAP has been shown to increase the risk of communi- cable diseases (pneumonia, tuberculosis) and noncommunicable diseases (heart disease, cancer, cataracts) and is responsible for a large fraction (3−5 percent) of the total global disease burden (WHO 2006b; Lim and others 2012). WHO estimated in 2004 that close to 2 million deaths, mostly of women and children, were at- tributed to exposure to HAP alone, the highest among the environmental risk factors (figure A). The toll includes more than half a million deaths from childhood pneumonia, almost a million deaths from chronic obstructive pulmonary disease, and around 36,000 from lung cancer traceable to coal use (WHO 2009). Another recent global disease burden assessment, which accounts for cardiovascular disease in addition to other health outcomes, estimates that in 2010 HAP was directly responsible for around 3.5 million deaths, and another half a million deaths from the ambient air pollution produced by HAP leaking outdoors (Lim and others 2012). Inefficient energy use in the home also poses substantial risks to safety and is the cause of a large number of burns and injuries across the developing world. More than 95 percent of the 200,000 deaths from fire-related burns occur in developing countries; many can be attributed to the use of kerosene, open fires, and simple stoves in the home (Mills 2012). Fuel collection, typically done by women and children, puts people at risk of injury (for example, from land mines, snake, or insect bites) and violence (for example, rape, harassment) (WHO 2006b; Popalzai 2012). The ingestion of kerosene, often from unsafe storage containers (for example, soft drink and water bottles), is a major cause of child poisonings worldwide and can lead to death, chemical pneumotitis, and impairments to the central nervous system (Mills 2012). 2000 1600 Attributable deaths ('000) 1200 800 400 0 Household Unsafe water, Urban outdoor Lead exposure Global air pollution sanitation, hygiene air pollution climate change environmental risk factors Figure A. Deaths attributable to environmental risk factors Source: WHO 2009. 73 Global tracking framework Within the developing world, the rate of access to non-solid More-urbanized and higher-income regions typically ex- fuel varies from 19 percent in Sub-Saharan Africa to about hibit higher reliance on non-solid fuel. Western Asia, the 95 percent in Western Asia and 100 percent in Northern wealthiest and most urbanized developing region, has Africa. Except in Western Asia, the Caucasus and Central close to universal access to non-solid fuel. At the lower end Asia, and Northern Africa, more than two-thirds of the rural of the income and urbanization profile are Southern Asia, population of the developing world depends on solid fuels. Sub-Saharan Africa, and Oceania, which also report the The situation is particularly dire in Sub-Saharan Africa (94 lowest access rates. But Southeastern Asia and Eastern percent), Oceania (79 percent), Southeastern Asia (77 per- Asia, with incomes and urbanization rates similar to those cent), and Southern Asia (73 percent). These four regions of Northern Africa, show markedly lower access rates (as together account for three-quarters of the total rural use of indicated by the size of the bubbles in figure 2.21). solid fuel in the world. In urban areas, more than 70 per- cent of the population has access to non-solid fuel, except Access rate (% of population) in Sub-Saharan Africa (42 percent) (figure 2.20). total rural urban CCA CCA CCA WA 100 EA WA 100 EA WA 100 EA 80 80 80 60 60 60 40 40 40 SSA 20 LAC SSA 20 LAC SSA 20 LAC SEA NA SEA NA SEA NA SA Oceania SA Oceania SA Oceania total Figure 2.20 Rates of access to non-solid rural fuel in 2010, by region urban source: WHO’s Global Household Energy Database 2012. note: CCA = Caucasus and Central Asia; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. Note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = East Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SEA = Southeast Asia; SA = Southern Asia; SSA = Sub-Saharan Africa; WA = West Asia 100 LAC 86% 80 urbanization rate (%) WA 95% 60 NA CCA 100% EA 85% SEA 55% 48% 40 SSA 19% 40% SA 20 31% Oceania 0 0 1000 2000 3000 4000 5000 6000 GDP per capita (constant US$) Figure 2.21 Rates of access to non-solid fuel in 2010, by level of urbanization and income source: Bonjour and others 2012. note: Size of bubble indicates access rate by region. CCA = Caucasus and Central Asia; EA = Eastern Asia; GDP = gross domestic product; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. chapter 2: universal access 74 Global trends The share of the global population with access to non-sol- percentage points, respectively, over the two decades. id fuel rose from 47 percent (2.5 billion people) in 1990 On average, Eastern Asia, Latin America, Northern Africa, to approximately 59 percent (4.1 billion people) in 2010 Oceania, Southeastern Asia, and Western Asia exhibited (figure 2.22). The access rate in rural areas increased an increase in non-solid fuel use of 15 percentage points. over the same period from 26 percent to 35 percent; in Sub-Saharan Africa followed far behind, with an increase urban areas, from 77 percent to 84 percent. The Cau- from 14 to 19 percent during the same period. Eastern casus and Central Asia and Southern Asia all witnessed Europe and Western Asia had accomplished near-univer- dramatic progress, registering increases of 27 and 24 sal access by 2010. 100 80 Access rate (% of Population) 60 40 20 0 1990 2000 2010 Figure 2.22a Global trends in rates of access to non-solid fuel, 1990−2010 Total Rural Urban source: WHO’s Global Household Energy Database 2012. 100 Access rate (% of Population) 80 60 40 20 0 ia a sa a a c a a ea ev d ss se w n c la rl n d c ea o w c o Global and regional trends in electrification and non-solid fuel access rates, 1990–2010 Figure 2.22b Regional trends in rates of access to non-solid fuel, 1990−2010 1990 2000 2010 source: WHO’s SOURCE: Global WB, WHO, IEA Household Energy Database 2012. note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Carib- bean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. 75 Global tracking framework The global population grew by 1.6 billion in the two de- access kept up with population growth in Central Asia, cades between 1990 and 2010, and non-solid fuel use Northern Africa, Southeastern Asia, Latin America and almost kept pace (figure 2.23). Globally the increment in Oceania in both decades. In Eastern Asia, access grew non-solid fuel access was comparable across both de- much faster than the population, especially in the 2000s. cades, but with some variation geographically. Growth in Access Oceania Population Access CCA Population Access NA Population Access WA Population Access SSA Population Access SEA Population Access LAC Population Access EA Population Access SA Population Access WORLD Population 0 200 400 600 800 1000 1200 1400 1600 population (million) Figure 2.23 Growth in population and in access to non-solid fuel, 1990−2010 1990-2000 2001-2010 source: WHO’s Global Household Energy Database, 2012. note: CCA = Caucasus and Central Asia; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. The access deficit—or the use of solid fuel—in 2010 was geographically concentrated in Sub-Saharan Africa and Southern Asia. From 1990, both regions experienced an 1.6 billion expansion of reliance on solid fuels in both urban and rural people gained areas. In Southern Asia, an additional 490 million people access gained access to non-solid fuel as their primary cooking to non-solid fuels between between fuel, but even that impressive figure trailed population 1990 and 2010 growth—by 18 million people in the same time period. Sub-Saharan Africa increased non-solid fuel use by only 92 million people, falling behind population growth by 248 million people (figure 2.24). 17 Further details are provided in IEA 2012b. chapter 2: universal access 76 Total Urban Rural 0 1000 2000 3000 4000 5000 6000 7000 population (million) Figure 2.24a Global progress in access to non-solid fuel, by urbanization status, 1990–2010 Population with access in 1990 Incremental access in 1990-2010 Population without access in 2010 source: WHO’s Global Household Energy Database 2012. SA EA DEV SSA SEA LAC WA NA CCA Oceania 0 200 400 600 800 1000 1200 1400 1600 1800 population (million) Figure 2.24b Global progress in access to non-solid fuel, by region, 1990–2010 Population with access in 1990 Incremental access in 1990-2010 Population without access in 2010 note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. 77 Global tracking framework Between 1990 and 2010 the rapid rate of urbanization areas, by contrast, access grew faster than the population added 1.2 billion people to urban populations; populations by 67 million people. The remarkable urban growth story living in rural areas increased by only 0.4 billion over the has occurred for the most part in the Asian regions (East- same period. The growth rate of access to non-solid fuel in ern Asia, Western Asia, Southern Asia, and Southeastern urban areas, at 1.7 percent, far outpaced the rural growth Asia), which together managed to provide 760 million rate of 0.6 percent (figure 2.25). Nevertheless, the rapid people—or 38 million people annually—with access to pace of urban population growth over this period made non-solid fuel. The rural increment was highest in Western it difficult for non-solid fuel access in urban areas to keep Asia, Southern Asia, and the Caucasus and Central Asia, up, with the expansion of access falling short of population where 334 million people—or 17 million annually—began growth by 51 million people over the two decades. In rural to use primarily non-solid fuel for cooking. 3% 3% Annual growth in access (%) Incremental access growth (%) 2% 2% 1% 1% 0% 0% WA EA SA SEA NA LAC Oceania SSA CCA DEV WORLD -1% WA EA SA SEA NA LAC Oceania SSA CCA DEV WORLD Figure 2.25 Annual increments in growth of access to non-solid fuels -1% Rural Urban in urban and rural areas, 1990−2010 Rural Urban source: WHO’s Global Household Energy Database 2012. note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Caribbe- an; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. Country snapshots in 2010 The rate of access to non-solid fuel spans a wide range: are the outliers in Sub-Saharan Africa, with access rates from 2 percent in many Sub-Saharan African countries above 95 percent; South Africa can also be considered an to near-universal access (greater than 95 percent ac- outlier, as its rate of access to non-solid fuel is 85 percent. cess) in 73 countries of the world (37 of which are de- Northern Africa and Western Asia are the only regions with veloping countries). Even within a given region, access an almost homogenous universal access rate (figure 2.26). rates are heterogeneous. The heterogeneity stems primarily from rural areas, where The world can be arbitrarily divided into three country 68 countries still have less than 30 percent non-solid fuel blocks based on the degree of access to non-solid fuel: access. The median rural access rate is at 5 percent in those at the lower end (<30 percent), those in the middle Sub-Saharan Africa, compared to a global median of 63 (30−95 percent), and those at the higher end (>95 per- percent. Non-solid fuel access is relatively uniform in urban cent). At the low end are 47 countries, 33 of which are in areas; 92 countries report near-universal urban access. In Sub-Saharan Africa. Among them, 21 show less than 10 urban areas, the median is 100 percent in all regions ex- percent access to non-solid fuel. Mauritius and Seychelles cept Sub-Saharan Africa, where it stands at 28 percent. chapter 2: universal access 78 2 1 1 1 1 3 12 13 74 37 1 4 4 5 11 69 7 20 33 2 4 4 12 3 47 10 1 CCA DEV EA LAC NA Oceania SA SEA SSA WA WORLD Figure 2.26 Distribution of rates of access to non-solid fuel, by number of countries per region <30 30<>95 >95 source: WHO’s Global Household Energy Database, 2012. note: CCA = Caucasus and Central Asia; DEV = developed countries; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = Southeastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia. High-impact countries Among the 20 countries with the lowest rates of access to ple) of the absolute global deficit in access to non-solid non-solid fuel (figure 2.27a), 18 are in Sub-Saharan Afri- fuel (figure 2.27b). Eleven of the 20 are in Asia and nine in ca. Solid-fuel users make up 369 million. Another 20 “high Sub-Saharan Africa. India and China together account for impact” countries account for 85 percent (2.4 billion peo- 1.3 billion solid-fuel users. a. Lowest access rates, 2010: 369 million solid-fuel users b. Largest access deficits, 2010: 2.4 billion solid-fuel users Madagascar 2 2.0 Ghana20 20.4 Mali 2 2.0 Korea, DR22 22.2 Rwanda 2 2.0 Mozambique22 22.2 Sierra Leone 2 2.0 Nepal25 24.6 Liberia 2 2.2 Afghanistan 27 26.7 Ethiopia 2 2.2 Uganda 32 32.2 Guinea-Bissau 2 2.4 Kenya 33 32.6 Guinea 3 3.2 Sudan 35 34.6 Malawi 3 3.4 Tanzania 42 42.3 Uganda 4 3.6 Myanmar 44 44.0 Lao PDR 4 3.7 Philippines 46 46.2 CAR 4 3.8 Vietnam 49 49.4 Niger 4 4.0 Congo, DR 61 61.3 Burundi 4 4.4 Ethiopia 81 81.1 Somalia 5 4.7 Pakistan 111 110.8 Mozambique 5 5.0 Nigeria 118 117.8 Tanzania 6 5.6 Indonesia 131 131.2 Togo 6 5.6 Bangladesh 135 134.9 Congo, DR 7 7.0 China 613 612.8 Timor-Leste 8 8.0 India 705 705.0 0 2 4 6 8 10 0 160 320 480 640 800 access rate (% of population) population (million) Figure 2.27 Top 20 countries: the lowest access rates and largest deficits in access to non-solid fuel source: WHO’s Global Household Energy Database 2012. source: WHO’s Global Household Energy Database 2012. note: CAR = Central African Republic; DR = Democratic note: DR = Democratic Republic of. Republic of. 79 Global tracking framework Fast-moving countries Of the 20 countries that have shown the largest numbers Brazil, where a total of 783 million people secured access of people transitioning to primary use of non-solid fuels, to non-solid fuel as their primary cooking fuel during this most are in Asia (figure 2.28). The 20 countries moved an period. India charted a remarkable trajectory, providing ac- additional 1.2 billion people to non-solid fuel in 1990–2010, cess to non-solid fuel to 402 million over two decades, or but that figure was 200 million behind their overall popula- 20 million people annually. 25 tion increase. The greatest growth was in India, China, and 3.0% 25 3.0 20 2.4% annual growth in access (%) 20 2.4 annual growth in access (%) population (million) population (million) 15 15 1.8 1.8% 10 1.2 10 1.2% 5 0.6 5 0.6% 0 0.0 l a a a ia a a ia ia a o a d q es n m n ey t zi in bi ri si n ic ia e yp c ra n ta n ra er d m es ic na in r a ti rk ia ay m e xi a h fr In 0 0.0% Eg ys Ko r ia kis n on I a ig Ko Alg a I en il pi lipp C o t e nB er al eyTu A ex Vie M a l bi N es a g l o et Ind a ia a ia a h o th Aa Td aq ig M us t n P zi i r Ir C in il Ph n ic So e re yp n a er d a n a ti rk st m a h Ir fr In Eg la Br lg en il C lo ki Tu o A ip M a N a A Pa Vi rg o d Th th M Figure 2.28 Top 20 countries with highest annual incremental growth in access In C Ph A u incremental access (million) incremental total population (million) Annual growth in access (%) So to non-solid fuel, 1990−2010 incremental access (million) incremental total population (million) Annual growth in access (%) source: WHO’s Global Household Energy Database 2012. Focusing on absolute increments in non-solid fuel ac- at least 2.5 percent of their population annually to primary cess tends to highlight the experiences of large countries. use of non-solid fuel. But only the United Arab Emirates Twenty fast-moving small countries—many of them island (UAE) and Qatar increased access to non-solid fuel at an nations—also showed substantial growth in access as a annual rate greater than 3.5 percent of the population. percentage of their population over the two decades from Their performance is the upper bound of what any country 1990 to 2010 (figure 2.29). Fourteen countries transitioned has been able to achieve in the past two decades. 4 annual growth in access (%) 3 2 1 0 ia la ia ia ia n r r n Tu q p es ze E Jo n in lu n n t a o Re UA ja en a en a a ys c yr ta bo a o v at li va rd st d Ir u r i g la ai u S c n rm ld Be ua .L a Q h ki n Bh a in rb G Ba a St A a ji ic Ec A .V M ze M Ta in St A m o D Figure 2.29 Top 20 fastest-growing countries in non-solid fuel use, 1990−2010 growth Annual WHO’s source: in access Global (%) HouseholdGlobal Energyannual growth Database innote: 2012. access= 1.1% UAE = UnitedDeveloping Countries annual growth in access= 1.3% Arab Emirates. chapter 2: universal access 80 Section 4. Scale of the challenge Building on the foregoing analysis, this section looks to mitments. The projections provide a basis from which to the future, mapping out today’s energy access trajectory analyze what needs to be done to achieve universal ac- and quantifying the scale of the challenges that must be cess by 2030. Variables include how many more people overcome to achieve the SE4ALL goal of universal ac- will need to obtain access to modern energy services by cess to modern energy services by 2030. Drawing on the region, the levels of investment and types of technolo- World Energy Outlook (IEA 2012), it presents global and gies required, the barriers to achieving the goal, and the regional projections for modern energy access under a benefits and broader implications of achieving it (such as so-called New Policies Scenario (NPS) that estimates the impact on energy demand and energy-related carbon the likely impact of existing and announced policy com- dioxide [CO2] emissions). Methodology for projecting energy access developments to 2030 This section draws heavily on data, projections, and anal- As a point of reference, the observed average electricity ysis from the IEA’s World Energy Outlook35 (box 2.4). The consumption in India in 2009 was 96 kWh per person in energy access projections under the NPS reflect the im- rural areas and 288 kWh in urban areas, for all people con- pact that existing and announced policy commitments nected to electricity, with those connected more recently (assuming cautious implementation) are expected to consuming lower amounts (Government of India 2011). have by 2030. In the spirit of the multi-tier candidate proposal presented For this analysis, the following definitions and methodolo- in section 1, the projections for electricity access that fol- gy have been adopted.36 Access to electricity is indicated low go beyond a simple binary definition and make some by a household’s first connection to electricity and by con- allowance for different tiers of access, as reflected in dif- sumption of a specified minimum level of electricity, with ferentiated levels of electricity consumption. Once an initial the amount varying depending on whether the household connection to electricity is made, the level of consumption is in a rural or an urban area. The initial threshold level of is assumed to rise gradually over time, moving toward a electricity consumption for rural households is defined as regional average level of consumption after several years. 250 kilowatt-hours (kWh) per year; for urban households, The initial period of growing consumption is a deliberate 500 kWh. The higher consumption in urban areas reflects attempt to reflect the fact that eradication of energy poverty urban consumption patterns. Both levels are calculated is a long-term endeavor. In the analysis, the average lev- based on an assumption of five people per household. In el of electricity consumption per capita across all house- rural areas, the minimum level of consumption could, for holds newly connected over the period is assumed to rise example, provide for the use of a floor fan, a mobile tele- to about 750 kWh by 2030. phone, and two compact fluorescent light bulbs for about five hours per day. In urban areas, consumption might also Access to modern cooking solutions focuses on the provi- include an efficient refrigerator, a second mobile telephone sion of an appropriate stove and refers primarily to biogas per household, and another appliance (such as a small systems, LPG stoves, and advanced biomass cookstoves television or computer). that have considerably lower emissions and higher effi- ciencies than traditional three-stone fires for cooking. We Different levels of electricity consumption are adopted in assume that LPG stoves and advanced biomass cook- other published analyses. Sanchez (2010), for example, stoves require replacement every five years, while a biogas bases access on consumption of 120 kWh per person (600 digester is assumed to last 20 years. kWh per household, assuming five people per household). 35 This section of the report uses the IEA’s World Energy Outlook databases on electricity access and on the traditional use of biomass for cooking. On many counts, the IEA’s electricity access database, which reports 1.3 billion people without access, is consistent with the World Bank’s Global Electrification Database, which reports 1.2 billion people lacking access. The major share of the discrepancy between the two global estimates can be ascribed to differences in a relatively small number of countries, including Pakistan, Indonesia, South Africa, Thailand, and Gabon, where the IEA uses government data (which typically report more people without access) while the World Bank uses estimates derived from various types of household surveys. 36 For more about the IEA’s energy access data and modeling methodologies, see http://www.worldenergyoutlook.org/resources/energydevelopment. 81 Global tracking framework To arrive at estimates of the investments needed to achieve Advanced biomass cookstoves and biogas systems are the SE4ALL goal of universal access to electricity, an as- relatively more common solutions in rural areas, while LPG sessment was conducted of the required combination of stoves play a more significant role in urban areas. Related on-grid, mini-grid, and isolated off-grid solutions in each infrastructure, distribution, and fuel costs are not included region. This assessment accounts for regional costs and in the estimate of investment costs. consumer density to determine a regional cost per mega- watt-hour (MWh). When delivered through an established Projections are shown at the regional level because the grid, the cost per MWh is cheaper than other solutions, but available data do not permit a more disaggregated analy- extending the grid to sparsely populated, remote, or moun- sis over the time frame. The regional aggregations used in tainous areas can be very expensive, and long-distance this section differ slightly from those in the first three sec- transmission systems can have high technical losses. Grid tions of this report, reflecting the usages of the IEA’s World extension is the most suitable option for urban areas and Energy Model.37 As examples of the differences in country for about 30 percent of rural areas, but not for more re- classification, the IEA’s World Energy Outlook groups Iran mote rural areas. The remaining rural areas are connected in the Middle East region, rather than in Southern Asia. The either with mini-grids (65 percent of this share) or small, IEA excludes Bhutan and the Maldives from Southern Asia; stand-alone off-grid solutions (the remaining 35 percent) both are part of Eastern Asia and Oceania in the figures that have no transmission and distribution costs. shown in this section. Furthermore, Timor-Leste is part of Eastern Asia and Oceania, not Southeastern Asia, in the Investment needs for modern cooking solutions are based data presented here. Finally, the Republic of Korea is not on the expectation that a combination of different techni- included in Eastern Asia or any other region here, whereas cal solutions will be provided. These include advanced it is included in the UN region of Eastern Asia. biomass cookstoves, LPG stoves, and biogas systems. Box 2.4 IEA’s energy access model The energy access projections presented in this section of the report come from the IEA’s World Energy Model, which integrates trends in demography, economy, technology, and policy. This kind of integrated analysis of- fers valuable insights into the globe’s energy trajectory and what will have to be done to attain the SE4ALL goal of universal access to modern energy services by 2030. The projections for access to electricity and to modern cooking solutions are based on separate econometric panel models that regress the electrification rates and rates of reliance on biomass for different countries over many variables to test their level of significance. In the case of electrification, the variables that were determined to be statistically significant and thus included in the equations are per capita income, demographic growth, urbanization level, fuel prices, level of subsidies for electricity consumption, technological advances, electricity consumption, and electrification programs. In the case of cooking solutions, variables that were determined statistically significant and consequently included in the equations are per capita income, demographic growth, urbanization level, level of prices of alternative modern fuels, level of subsidies to alternative modern fuel consumption, technological advances, and govern- ment programs to promote modern cooking. The models are run under the following economy and population assumptions: world gross domestic product (in purchasing power parity terms) grows by an average of 3.6 percent per year over the period 2010−2030, with the rate of growth slowing gradually over time as the emerging economies mature. The assumed rate varies by region. The rates of population growth assumed for each region are based on UN projections (UNDP 2011). World population is projected to grow from an estimated 6.8 billion in 2010 to 8.3 billion in 2030. In line with the long-term historical trend, population growth slows over the projection period. Almost all of the increase in global population is expected to occur in countries outside the Organisation for Economic Co-op- eration and Development (OECD), mainly in Asia and Africa. Source: Authors. chapter 2: universal access 82 Access to electricity in 2030 under the New Policies Scenario Under the assumptions of the NPS the number of people lacking access to electricity around the world will decline to just over 990 million in 2030, around 12 percent of the 12% global population at that time (figure 2.30). About 1.7 bil- of the world’s lion people will gain access to electricity by 2030, but that population achievement will be counteracted, to a large extent, by will still lack access to electricity in global population growth. Those gaining access to elec- 2030 under business as usual tricity will reach a range of consumption levels, and there- fore a range of tiers in the electricity access framework, by 2030—ranging from the defined minimum consumption The NPS projects the largest populations without access in levels in urban and rural areas to consumption levels above 2030 to be found in developing Asia (mainly Southern Asia) the regional average at that time. Access to electricity will and Sub-Saharan Africa. Sub-Saharan Africa is projected improve in relative terms for all regions except Sub-Saha- to overtake developing Asia in a few years as the region ran Africa, where the current trend will worsen over time. with the largest population without access to electricity. 1200 960 Population (Million) 720 480 240 0 2010 Rural 2010 Urban 2020 RURAL 2020 Urban 2030 Rural 2030 Urban Figure 2.30 Number of people without access to electricity in rural and urban areas, by region, 2010–2030 Sub-Saharan Africa South Asia South-Eastern Asia Rest of the World source: Based on data/analysis from IEA (2012). 83 Global tracking framework In developing Asia the number of people without electricity suggest that the worsening trend will extend to around access under the NPS scenario is projected to be halved 2025 and that the prospect of improvement from that date by 2030, reaching around 335 million. That will extend an is fragile, remaining vulnerable to upset by a change in already positive trend, with China (which today reports economic fortunes, higher energy prices, or a failure to im- more than 99 percent access) expected to reach universal plement policy. Over the projection period, those lacking access by the middle of the current decade. The remain- electricity access in Sub-Saharan Africa will be increasingly der of Eastern Asia and Southeastern Asia will have much concentrated in rural areas, which will account for more smaller numbers without access in 2030; Southern Asia is than 85 percent of the regional deficit in 2030. Owing to also expected to see significant improvement. Even so, a projected improvements elsewhere, Sub-Saharan Africa population larger than that of the United States today is still will account for an increasing share of the global popula- expected to be without access to electricity in developing tion without electricity access, going from less than half to Asia in 2030, with India expected to have the largest single around two-thirds by 2030. no-access population, at around 150 million. Nine out of 10 people without access to electricity in developing Asia The regions projected to reach universal access to elec- in 2030 are expected to live in rural areas. tricity before 2030 are Latin America and the Caribbean, the Middle East, and Northern Africa. That success is not In Sub-Saharan Africa, the number of people without ac- guaranteed but relies on the continuation of trends in eco- cess to electricity is projected to increase under the NPS nomic growth, investment, and policies to improve elec- by around 11 percent, to 655 million in 2030. Projections tricity access. Access to electricity in 2030: Achieving universal access To achieve universal access to electricity by 2030, some 50 year (2011−2030). The annual level of investment would million more people will have to gain access to electricity increase over time, reflecting the escalating number of each year than under the NPS. About 40 percent of the connections being made. More than 60 percent of the ad- additional electricity supply needed for universal access ditional investment required would come in Sub-Saharan in 2030 would come from grid solutions (of which almost Africa, because the region would need the equivalent of two-thirds would be fossil-fuel based) and the remainder an extra $19 billion per year to achieve universal electricity from mini-grid and stand-alone off-grid solutions (of which access by 2030 (figure 2.31). Achieving universal access around 80 percent would be based on renewables). in Sub-Saharan Africa would depend more heavily than elsewhere on mini-grid and isolated off-grid solutions, par- It is estimated that universal access to electricity by 2030 ticularly in countries such as Ethiopia, Nigeria, and Tan- will require investment of around $890 billion over the peri- zania, where a relatively high proportion of those lacking od (2010 dollars), of which around $288 billion is projected electricity live in rural areas. Developing Asia accounts for to be forthcoming under the NPS, meaning that an addi- 36 percent of the additional investment required to achieve tional $602 billion would be required to provide universal universal electricity access, with Southern Asia accounting access to electricity by 2030—an average of $30 billion per for the largest share. chapter 2: universal access 84 LAtin America middle east & north africa Clean cooking Clean cooking 3% 18% LPG stoves Advanced 31% biomass cookstoves Biogas systems LPG stoves Biogas systems Adva LPG stoves Advanced biomass cookstoves Biogas systems $0.2 $0.01 LPG stoves Biogas systems Advanced biomass cookstoves billion LPG stoves Biogas systems Advanced biomass cookstoves LPG stoves billion Biogas systems Advanced biomass cookstoves LPG stoves Biogas systems Advanced biomass cookstoves 69% 79% LPG stoves Biogas Advanced biomass LPG stoves Biogas Advanced biomass systems cookstoves systems cookstoves eastern asia & oceania sub-saharan africa 20 20 Clean cooking electricity Clean cooking electricity 20 20 20 20 $19.1 billion 6% 16 16 15% 16 16 16 16 25% 12 34% 12 $0.9 12 12 12 billion 12 $1.1 8 billion 8 8 8 8 8 79% 4 41% 4 4 4 4 4 LPG stoves Biogas Advanced biomass 0 $0.4 billion 0 0 0 systems cookstoves LPG stoves Biogas Advanced biomass 0 systems0 cookstoves LPG stoves Biogas systems On grid On gridAdvanced Mini grid Mini biomassgrid Isolated cookstoves Isolated Off grid Offstoves LPG grid On grid Biogas systems Mini On grid grid Advanced Isolated Mini biomass grid OffIsolated grid cookstoves Off as systems On grid Advanced biomass Mini grid LPG cookstoves Isolated grid systems stoves OffBiogas On grid Advanced biomass Mini grid cookstoves Isolated Off grid southern asia south-eastern asia 20 20 Clean cooking electricity Clean cooking electricity 20 20 20 20 16 16 16 16 16 16 33% 33% 35% 12 12 37% $1.2 12 12 $0.4 12 12 billion $9.2 billion billion 8 8 8 8 8 8 32% 30% 4 4 4 4 4 4 $1.3 billion LPG stoves Biogas Advanced biomass 0 0 LPG stoves Biogas Advanced biomass 0 0 systems 0 cookstoves systems 0 cookstoves LPG stoves Biogas systems On grid On grid Advanced Mini Mini grid biomassgrid Isolated OffIsolated cookstoves grid Offstoves LPG grid On grid Advanced Biogas systems On grid Mini Mini grid gridbiomass Isolated Off cookstoves Isolated Off grid as systems On grid Advanced biomass Mini grid LPG cookstoves stoves OffBiogas Isolated grid systems On grid Advanced biomass Mini grid cookstoves Isolated Off grid world Access to clean cooking facilities: $3.8 billion & world Access to electricity: $30.1 billion Figure 2.31 Additional average annual investment needed to achieve universal access to modern energy services by 2030, by region and technical solution source: Based on data/analysis from IEA (2012). 85 Global tracking framework As a high-quality and highly flexible form of energy, elec- needed medicines on hand and for households to keep tricity can enable a whole range of social and economic food fresh. Access to electricity also provides the means benefits, empowering the leap from poverty to a better fu- to generate income and improve productivity, which in turn ture. Electric light extends the day, providing extra hours creates wealth and new markets. In agriculture, electrici- for studying and work. Access to radio and television can ty can support various forms of modernization, enabling help keep communities up to date on events both local people to pump water for household use and irrigation and global. Street lighting has been reported to increase and to use mobile phones to access new markets for their social mobility, especially of women. Electricity in schools crops. Expanding access to modern energy services can can improve education by enabling access to lighting, yield significant social and economic returns, especially heating, water, and sanitation. In health facilities, it can also when integrated with efforts to promote the efficient use bring benefits by powering medical and communications of limited energy resources and the harnessing of locally equipment. Refrigeration allows health facilities to keep available renewable energy sources. Access to modern cooking solutions in 2030 under the New Policies Scenario Under the NPS, the number of people lacking access to modern cooking solutions is projected to remain, because of population growth, almost unchanged at around 2.6 bil- 30% lion in 2030—more than 30 percent of the projected global of the world’s population in that year (figure 2.32). population will still depend on solid fuels in 2030 under business as usual 2500 2000 Population (Million) 1500 1000 500 0 2010 Rural 2010 Urban 2020 RURAL 2020 Urban 2030 Rural 2030 Urban Figure 2.32 Number of people without access to modern cooking solutions in rural and urban areas by region, 2010–2030 Sub-Saharan Africa South Asia East Asia and Oceania South-Eastern Asia Rest of the World source: Based on data/analysis from IEA (2012). chapter 2: universal access 86 In developing Asia, China is projected to show the single 310 million people will achieve access to modern cooking biggest improvement, with almost 150 million fewer people solutions by 2030, their number will not keep pace with the lacking access to modern cooking solutions by 2030. That population growth expected over the period. As in all re- improvement will come from economic growth, urbaniza- gions, the lack of access will continue to be concentrated tion, and deliberate policy interventions, such as actions in rural areas. to expand natural gas networks. India will see a small im- provement but is still expected to account for the largest Latin America and the Middle East have much smaller single population going without modern cooking solu- populations lacking modern cooking solutions. There, NPS tions—nearly 30 percent of the world’s total in 2030. The projections show a slight improvement over time, focused rest of developing Asia is also projected to see only a mar- on urban areas. In rural areas, the size of the population ginal improvement by 2030, with half of its population still without access to modern cooking solutions will remain lacking access to modern cooking solutions at that time. essentially unchanged, as population growth offsets pos- itive efforts. In Latin America, 11 percent of the population In Sub-Saharan Africa, NPS projections reveal a worsen- is projected still to be without access to modern cooking ing situation over time, with the number of people without solutions in 2030, while the figure is less than 3 percent in modern cooking solutions increasing by more than a quar- the Middle East. ter, reaching around 880 million in 2030. While more than Access to modern cooking solutions in 2030: Achieving universal access To achieve universal access, modern cooking solutions will to modern cooking solutions by 2030. For comparison, the need to be provided to an additional 135 million people per Global Energy Assessment of the International Institute for year, on average, over and above those gaining access Applied Systems Analysis, IIASA, also estimates the in- under the NPS. This could occur through a combination of vestment required to achieve universal energy access in various technical solutions, including advanced biomass 2030, but based on different assumptions (box 2.5). cookstoves, LPG stoves, and biogas systems.38 In rural ar- eas, advanced biomass cookstoves and biogas systems The benefits of universal access to clean cookstoves are are relatively more common solutions, whereas in urban clear. A huge proportion of the world’s population still uses areas LPG stoves play a more significant role. While the tar- polluting, inefficient cookstoves that emit toxic smoke. In- get population is much larger than for access to electricity door air pollution is the fifth-largest health risk in the devel- and the operational challenge no less significant, it is striking oping world. Millions of people are estimated to die prema- how much less investment is needed is to provide universal turely each year from exposure to cookstove smoke many access to modern cooking solutions than to electricity. of which are children (WHO, 2009). Moving away from biomass for cooking and heating would also free women It is estimated that universal access to modern cooking and children from spending hours each week collecting solutions by 2030 would require investment of about $89 wood, allowing this time to be used more productively. It billion over the period (in 2010 dollars), of which about would also reduce or remove the personal security risks $13 billion is projected to be forthcoming under the NPS, that women face when searching for fuel. Finally, use of meaning that an additional $76 billion ($3.8 billion per clean fuels and cookstoves, many of which do not con- year, 2011−2030) would be required to provide universal sume wood fuel, could help reduce the risks of local defor- access to modern cooking solutions by 2030. Figure 2.31 estation and other forms of damage to natural resources breaks down the additional investment required by region, (see boxes 2.2 and 2.3). as well as technical solutions to achieve universal access 38 Section 3 of this chapter presented global and country snapshots of household access to non-solid fuels. But the projections presented here are based on access to improved cooking appliances, which are captured in various tiers of the multi-tier framework in figure 2.3. 87 Global tracking framework Box 2.5 GEA investment cost projections to reach universal access The Global Energy Assessment (GEA) of the International Institute for Applied Systems Analysis, which mod- els 41 energy “pathways” (or scenarios designed to meet certain prespecified objectives) has estimated the investment costs associated with reaching near-universal access to electricity and modern cooking solutions by 2030. Six of these pathways are consistent with meeting all three global SE4ALL goals, in addition to achieving emissions reductions consistent with the 2°C climate target, limiting health-damaging air pollution, and improving energy security. The analysis estimates the global cost of reaching universal access with a specific focus on Sub-Saharan Af- rica, Southern Asia, and Pacific Asia, which are home to the bulk of the populations without access today. For modern cooking solutions, the model puts forth critical policy measures—assuming a final transition to LPG (as a proxy for modern cooking solutions) for those who have access to it and can afford it as well as microfi- nance options to enable households to finance new cookstoves. In the scenarios that meet SE4ALL objectives, the model assumes 50 percent fuel subsidies for LPG (70 percent for Sub-Saharan Africa) and microfinancing to purchase cookstoves at a 15 percent interest rate. This model internalizes the demographic and income changes associated with growth in these regions. For electrification, the GEA pathways assume achievement of near-universal power supply through grid-based options. Mini-grid and off-grid options are not included in the model. The SE4ALL scenario assumes a 100 percent electrification rate in all regions and consumption of 420 kWh/household/year arising from the use of 115 watts for 10 hours a day (for television, lighting, refriger- ation, and other small appliances). The GEA model estimates an annual investment requirement of $71.3 billion for modern cooking facilities and $15.2 billion for rural electrification to reach universal access by 2030. These figures are the same across all the six energy pathways. This total of more than $85 billion annual spending is several times higher than the $9.6 billion currently spent annually to expand access. 1200 2250 960 1800 Population (million) Population (million) 720 1350 480 900 240 450 0 0 Total -Baseline Total -50% Scenario Total -Baseline Total -50% Fuel Subsidies Total - 15% Micro Finance SSA SAR EAP SSA SAR EAP Source: Riahi and others 2012. note: SSA = Sub-Saharan Africa; SAR = South Asia; EAP = East Asia and Pacific. $49 billion will need to be invested every year to reach universal access to energy by 2030 chapter 2: universal access 88 Broader implications of universal access, and key barriers If universal access to modern energy services were 2.33). Less than half of the additional energy demand achieved, global primary energy demand would be around would be for fossil fuels, with the remainder coming from 167 million tons of oil equivalent (Mtoe) higher in 2030 than renewables. For cooking, an additional 0.85 million barrels under the NPS, an increase of around 1 percent (figure per day (mb/d) of LPG would be required in 2030. 2,595 million 0.28% percentage change 0.21% 0.14% 990 Million 0.07% $34 billion 199 Mt 167 mto 0.00% CO2-emissions Total primary Annual investment Population Population energy demand in energy-related gaining access gaining access to infrastructure to electricity clean cooking Figure 2.33 Additional global impact of universal access to modern energy services over the New Policies Scenario, 2030 source: IEA 2012. note: Percentages are a share of global energy-related carbon dioxide (CO2) emissions (2030), global primary energy demand (2030), global energy related infrastructure investment (annual average, based on the New Policies Scenario, in 2010 dollars), and global population (2030). Mt = million tons; Mtoe = million tons of oil equivalent. The significant role of renewables in delivering universal people newly provided with modern energy access and to access to electricity means that the impact of increased the significant proportion of renewable solutions adopted, access on global CO2 emissions is projected to be rela- particularly in rural and peri-urban households. The diver- tively small, increasing the total by around 0.6 percent (199 sity of factors involved in these projections means that the Mt) by 2030. Even with such as increase, emissions per estimate of the total impact on greenhouse gas emissions capita in those countries achieving universal access would of achieving universal access to modern cooking facilities still be less than one-fifth of the OECD average in 2030. must be treated with caution. It is, however, widely accept- The small size of this increase in emissions is attributable ed that advanced stoves and greater conversion efficiency to the low level of energy per capita consumed by the would reduce emissions and thus reduce this projection. 89 Global tracking framework Several barriers must be overcome if universal access to energy is to be achieved. As highlighted by SE4ALL (2012), a set of common elements will have to be put in place to overcome those barriers: }} High-level commitments on the part of each country’s political leadership to achieving universal energy access. }} A realistic energy-access strategy and clear implementation plans linked to overall national development and budget processes. }} Strong communication campaigns to inform stakeholders of planned changes and related benefits. }} Sufficient funding to support the delivery of energy services from appropriate sources and at affordable rates. An increase in financing from all sources and in various forms is required, from large projects down to the micro level. }} A robust financial sector, willing to lend to the energy sector and to provide end-user financing. }} A legal and regulatory framework that encourages investment. }} The active promotion of project and business opportunities and a consistent flow of deals or transactions to attract a critical mass of private sector players (such as banks). }} Processes to match actors around specific projects and proposals, particularly in public-private partnerships. }} Energy access for community institutions (for example, rural multifunctional platforms, typically driven by diesel that powers pumps, grain mills, generators etc.). }} The means to support successful small-scale projects and solutions to reach a larger scale. }} Robust and effective public utilities. }} Strong internal capacity, potentially supported by external technical assistance. }} A deliberate effort to improve the availability of accurate and timely information. }} Reconciliation of regional and national interests in energy projects. While some of these solutions are context-specific and barriers are not insurmountable, but they will require the need to be supported by efforts to build the capacity of collective strengths of national governments, the private local institutions, most address generic problems found sector, and civil society. The SE4ALL initiative provides a in all or most countries seeking to deliver access to mod- platform for addressing these barriers in a comprehen- ern energy. They involve financial, planning, and regula- sive manner, offering countries a menu of options based tory measures needed to strengthen the operating envi- on global good practices. ronment of private developers and service providers. The chapter 2: universal access 90 References AGECC (Advisory Group on Energy and Climate Change). 2010. Energy or a Sustainable Future. The Secretary General’s Advisory Group on Energy and Climate Change, Summary Report and Recommendations, United Nations, New York. Barnes, D. F., ed. 2007. The Challenge of Rural Electrification: Strategies for Developing Countries. Washington, DC: RFF Press. Barnes, D. F., S. R. Khandker, and H. A. Samad. 2011. “Energy Poverty in Rural Bangladesh.” Energy Policy 39: 894−904. Bonjour, S, Adair-Rohani, H., Wolf, J., et al. 2012. “Solid Fuel Use for Household Cooking: Country and Regional Esti- mates for 1980-2010.” Environmental Health Perspectives 2012. Cabraal R. A., D. Barnes and S. G. Agarwal. 2005. “Productive Uses of Energy for Rural Development.” Annual Review of Environment and Resources 30: 117−44. Clancy, J. C., M. Skutsch, and S. Batchelor. 2003. The Gender-Energy-Poverty Nexus. Finding the Energy to Address Gender Concerns in Development. Technology and Development Group, University of Twente, Gamos Ltd, DFID Project CNTR 998521. Davis, M. 1998. “Rural Household Energy Consumption: The Effects of Access to Electricity—Evidence from South Africa.” Energy Policy 26 (3): 207−17. Elledge, M. F. 2012. The Enabling Environment: Global Guidelines and National Policies for Indoor Air Quality. R. Press, Editor RTI International, Research Triangle Park, North Carolina. EnDev. 2011. EnDev’s Understanding of Access to Modern Energy Services. GIZ and NL Agency. Germany. ESMAP (Energy Sector Management Assistance Program). 2003. Rural Electrification and Development in the Philip- pines: Measuring the Social and Economic Benefits. ESMAP Report 255/03, World Bank, Washington, DC. EUEI (European Union Energy Initiative). 2011. Productive Use of Energy-PRODUSE: A Manual for Electrification Practi- tioners. Germany. Filmer, D., and L. Pritchett. 1998. The Effect of Household Wealth on Educational Attainment around the World: Demo- graphic and Health Survey Evidence. Washington, DC: World Bank. Government of India. 2011. Key Indicators of Household Consumer Expenditure in India, 2009-10. New Delhi: Ministry of Statistics and Programme Implementation, Government of India. Heltberg, R. 2004. “Fuel Switching: Evidence from Eight Developing Countries.” Energy Economics 26 (5): 869−87. ———. 2005. “Factors Determining Household Fuel Choice in Guatemala.” Environment and Development Economics 10 (03): 337−61. IAEA (International Atomic Energy Agency). 2005. Energy Indicators for Sustainable Development: Guidelines and Meth- odologies. Vienna: IAEA. IEA (International Energy Agency). 2004. World Energy Outlook 2004. Paris: IEA. 91 Global tracking framework ———. 2011. World Energy Outlook 2011. Paris: IEA. ———. 2012. World Energy Outlook 2012. Paris: IEA. IEG (Independent Evaluation Group). 2008. The Welfare Impact of Rural Electrification: A Reassessment of the Costs and Benefits. Washington, DC: World Bank. siteresources.worldbank.org/EXTRURELECT/Resources/full_doc.pdf. Lam, N. L., K. R. Smith, A. Gauthier, and M. N. Bates. 2012. “Kerosene: A Review of Household Uses And Their Hazards in Low- and Middle-Income Countries.” Journal of Toxicology and Environmental Health Part B, Critical reviews 15(6): 396–432. Lim, S. S. et al. 2012. “A Comparative Risk Assessment of Burden of Disease and Injury Attributable to 67 Risk Factors and Risk Factor Clusters in 21 Regions, 1990−2010: A Systematic Analysis for the Global Burden of Disease Study 2010.” The Lancet 380 (9859): 2224−60. http://www.ncbi.nlm.nih.gov/pubmed/23245609 Link, C. F., W. G. Axinn, and D. J. Ghimire. 2012. “Household Energy Consumption: Community Context and the Fuel- wood Transition.” Social Science Research 41 (3): 598−611. Masera, O. R., B. D. Saatkamp, and D. M. Kammen. 2000. “From Linear Fuel Switching to Multiple Cooking Strategies: A Critique and Alternative to the Energy Ladder Model.” World Development 28 (12): 2083−103. Masera, O. R., R. Díaz, and V. Berrueta. 2005. “From Cookstoves to Cooking Systems: The Integrated Program on Sus- tainable Household Energy Use in Mexico.” Energy for Sustainable Development 9 (1): 25−36. Mills, E. 2012. Health Impacts of Fuel-based Lighting. The Lumina Project: California, USA. Nussbaumer, P ., M. Bazilian, V. Modi, and K. K. Yumkella. 2011. Measuring Energy Poverty: Focusing on What Matters. Oxford: University of Oxford, Oxford Poverty and Human Development Initiative. PCIA (The Partnership for Clean Indoor Air). 2012. “International Workshop Agreement on Cookstoves Unanimously Approved.” http://pciaonline.org/news/cookstoves-iwa-unanimously approved. Popalzai, M. 2012. “Landmine Kills 10 Girls Collecting Firewood.” http://edition.cnn.com/2012/12/17/world/asia/afghanistan-girlslandmine/index.html?hpt=wo_c2. PPEO (Poor People’s Energy Outlook). 2010. Rugby, UK: Practical Action. ———. 2012. Poor People’s Energy Outlook 2012. Rugby, UK: Practical Action. ———. 2013. To be published. Poor People’s Energy Outlook 2013. Rugby, UK: Practical Action. Rehfuess, E., S. Mehta, and A. Prüss-Üstün. 2006. Environmental Health Perspectives 114 (3). http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1392231 Riahi, K., F. Dentener, D. Gielen, A. Grubler, J. Jewell, Z. Klimont, V. Krey, D. McCollum, S. Pachauri, S. Rao, B. van Rui- jven, D. P. van Vuuren and C. Wilson. 2012. “Energy Pathways for Sustainable Development.” In Global Energy Assess- ment—Toward a Sustainable Future, Chapter 17, 1203−306. Cambridge, UK and New York, NY: Cambridge University Press; Laxenburg, Austria: International Institute for Applied Systems Analysis. Ruiz-Mercado, I., et al. 2011. “Adoption and Sustained Use of Improved Cookstoves.” Energy Policy 39 (12): 7557−66. http://ehs.sph.berkeley.edu/krsmith/publications/2011/ruiz_adoption.pdf Sanchez, T. 2010. The Hidden Energy Crisis: How Policies are Failing the World’s Poor. London: Practical Action Publishing. chapter 2: universal access 92 SE4ALL (Sustainable Energy for All Initiative). 2012. In Support of the Objective to Achieve Universal Access to Modern Energy Services by 2030. Technical Report of Task Force 1: New York. http://www.sustainableenergyforall.org/about-us. UNDP (United Nations Development Programme)/WHO (World Health Organization). 2009. The Energy Access Situation in Developing Countries: A Review Focusing on the Least Developed Countries and Sub-Saharan Africa. UNDP, WHO. UNDP. 2011. http://esa.un.org/wpp/other-information/pr_faq.htm. WHO. 2006a. WHO Air Quality Guidelines: Global Update 2005. Copenhagen: WHO. ———. 2006b. Fuel for Life: Household Energy and Health. Geneva: WHO. ———. 2009. Mortality and Burden of Disease Attributable to Selected Major Risks. Geneva: WHO. World Bank. 2011. One Goal, Two Paths: Achieving Universal Access to Modern Energy in East Asia and Pacific. Washington, DC: World Bank. 93 Global tracking framework Annex 1: Approaches to defining and measuring access to energy Methodology Name Description Objective Demand-based approach to define an energy poverty line Energy Poverty Line Define a threshold point at at the threshold point at which Single indicator (Barnes, Khandker, which households consume a households consume a bare and Samad 2011) bare minimum level of energy. minimum level of energy needed to sustain life. Set of 30 indicators of sustain- able development aiming to Energy Indicators for measure the current and future Measure the social, economic, Sustainable effects of energy use on human and environmental impact of Development health, human society, air, soil, energy. (IAEA 2005) and water to determine whether current energy use is sustainable and if not how to change it. Measures percentage of popula- Dashboard of tion in developing countries with indicators access (or lack of) to three key Energy access areas of energy supply; electrici- situation in developing Estimate the penetration rate of ty, modern household fuels, and countries modern energy. mechanical power (data limited (UNDP/WHO 2009) to 3 countries); plus measures access to improved cookstoves and analyses overall fuel use. Set of 17 indicators across three Ecosystem Health elements of an energy access Evaluate the health of ener- Indicator (PPEO 2012) ecosystem—financing, policy, gy-access ecosystems. and capacity. Estimate the penetration rate Energy Development of modern energy and levels Tracks progress in a country’s Index of energy consumption across transition to the use of modern (IEA 2004—amended households and community fuels. 2010 and 2012) indicators, compiling a coun- try-level index. Composite index Multidimensional Measure of deprivation of access Measure lack of access to Energy Poverty Index to a range of modern energy energy services by ownership (Nussbaumer and services affecting individuals. of appliances. others 2011) Categorizes five essential energy Total Energy Access Set minimum access stan- access services with quantitative (PPEO 2010) dards for five energy services. minimum standards. chapter 2: universal access 94 Methodology Name Description Objective Categorizes three key areas of Create a multidimensional Energy Supply Index energy supply with qualitative measure of the quality of (PPEO 2010) levels of supply. energy supply. Incremental levels Multilevel access to energy ser- Estimate level of access to en- of access to energy vices: (i) basic human needs, (ii) ergy services through energy services (AGECC productive uses, and (iii) modern usage (kWh/per capita). 2010) society needs. Multi-tier Defines minimum levels for three Minimum levels and key energy services—(i) lighting Measure minimum access to priorities of access (ii) cooking, and (iii) communi- basic energy needs in terms of to energy services cation and information, based quantity, quality, and afford- (EnDev 2011) on quantitative and qualitative ability. indicators. Multi-tier standards Multi-tier standards for house- Establish standards for cook- for cookstoves hold cookstoves (levels not stoves in terms of efficiency, (GACC/PCIA 2012) finalized). safety, and emissions. source: Authors’ compilation. 95 Global tracking framework Annex 2: Compilation of World Bank’s Global Electrification Data- base and World Health Organization’s Household Energy Database An intensive data compilation effort underpins the estab- cluster surveys (MICS), the WHO’s World Health Survey, lishment of the starting point and the analysis of historical and other nationally developed and implemented surveys, evolution presented in this report. Those efforts took form and from various government agencies (for example, min- in the World Bank’s Global Electrification Database and istries of energy, utilities). World Health Organization’s (WHO’s) Household Energy Database. As a first step in the creation of the two databas- This data-gathering effort resulted in 126 data points for es, data on electrification and use of primary fuels for cook- electrification and 142 countries for household energy ing were collected from nationally representative household around the starting point in 2010 (latest year available) (fig- surveys, including the United States Agency for International ure A2.1). For electrification the major sources are the DHS Development’s (USAID’s) demographic and health surveys and LSMS. For cooking solutions, data are primarily from (DHS) and living standards measurement surveys (LSMS), the DHS, national census or national household surveys, the Nations Children’s Fund’s (UNICEF’s) multiple indicator and MICS. 7% 8% 11% 16% 30% 2% 40% 14% 22% 17% 26% 7% Figure A2.1 Distribution of survey sources for original data—latest year available DHS LSMS/IE Census MICS DHS LSMS/IE Census MICS Other Surveys Non Survey Other Surveys WHS source: Authors note: HH = household; DHS = Demographic and health survey; IES = Integrated Expenditure Survey; LSMS = Living stan- dard measurement survey; MICS = Multiple indicator cluster survey; WHS = World Health Survey To develop the historical evolution and starting point of allowed the estimation of access rates for 212 countries electrification rates, a simple modeling approach was over these three time periods. adopted to fill in the missing datapoints – around 1990, around 2000, and around 2010. Therefore, a country can First over, the sample of countries for which there was at have a continuum of zero to three datapoints. There are 42 least one observation the following model was estimated: countries with zero data point and the weighted regional average was used as an estimate for access to electricity in each of the data periods. 170 countries have between one and three data points and missing data are estimated Where R denotes region dummies, t denotes time dummies; by using a model with region, country, and time variables. y denotes percentage with access, C denotes a vector of The model keeps the original observation if data is avail- dummy variables reflecting the country. The , and are able for any of the time periods. This modeling approach unknown parameters and u is an error term. chapter 2: universal access 96 For the sake of constructing the series, the model then uses for 193 countries. Generating time-series curves for coun- the latest access rates available from the above household tries based on available actual data points has several ad- surveys. For those countries with at least one observation vantages. It can derive point estimates for those countries but missing values the study then uses the estimates of , for which there are no data by using regional trends. It also and to make predictions of the missing values. incorporates all the available data to derive point estimates and is not unduly influenced by large fluctuations in survey For predicting access for countries with no observed values estimates from one year to the next. For example, in the for any time period the study estimates the model over the case of household cooking solutions in Namibia, house- following model over the sample which is available. hold survey data for use of solid fuels are available for 1991, 2000, 2001, 2003, and 2006, but not for 2010. Using the mixed model, an estimate of 55 percent was obtained for Namibia in 2010. For Nepal an even greater number of where R denotes region dummies, t denotes time dum- surveys are available (n = 8), some of which report sub- mies; and y denotes percentage with access. The α1 and stantially different estimates. Looking at the Nepal graph β1 are unknown parameters and u1 is an error term. For (figure A2.3), it is evident that the mixed model derives those countries with no observations the study then uses estimates that lie at or near the median of various survey the estimates of α1 and β1 to make predictions. estimates and derives a reasonable estimate of 82 percent for 2010. In the case of WHO Global Household Energy Database, a mixed model was used to derive solid fuel use estimates percentage of population using solid fuels (%) 100 80 60 40 20 0 1990 1995 2000 2005 2010 Year Figure A2.3 Example of model estimates in selected countries namibia survey data model estimate 95% confidence interval nepal survey data model estimate 95% confidence interval source: authors. Finally, the World Bank Global Electrification Database en- Database includes 193 countries, both representing near compasses 212 countries and WHO Household Energy universal coverage of global population (table A2.1). 97 Global tracking framework Country coverage % of population Electricity Household survey data available 126 * 96 * Data from model estimates 212 100 Household cooking fuel Household survey data available 142 * 97 * Data from model estimates 193 99.6 * Refers only to low- and middle-income countries. chapter 2: universal access 98 Annex 3: Matrix for measuring household access to electricity supply and electricity services Supply tiers Tier 0 Tier 1 Tier 2 Tier 3 Tier 4 Tier 5 Quantity (peak — >1 W >50 W >500 W >2,000 W >2,000 W available capacity) Duration of supply — >4 >4 >8 >16 >22 (hours) Attributes Evening supply — >2 >2 >2 4 4 Affordability (of a standard consumption — — Affordable Affordable Affordable Affordable package) Legality — — — Legal Legal Legal Quality (voltage) — — — Adequate Adequate Adequate 99 Global tracking framework Tier 0 Tier 1 Tier 2 Tier 3 Tier 4 Tier 5 Watts Watts Watts Watts Watts Likely feasible Radio 1 Radio Radio Radio Radio applications Task lighting 1 Task lighting Task lighting Task lighting Task lighting (May not be Phone 1 Phone charging Phone charging Phone charging Phone charging actually used) (Wattage is charging General 18 General lighting General lighting General lighting indicative) lighting Air circulation Air circulation Air circulation Air circulation 15 Television Television Television Television 20 Computing Computing Computing Computing 70 Printing Printing Printing Printing 45 Air cooling 240 Air Cooling Air Cooling Etc. Food 200 Food processing Food processing processing Rice cooking Rice cooking Rice cooking 400 Washing Washing Washing 500 machine machine machine Water pump 500 Water pump Etc. Refrigeration 300 Refrigeration Ironing 1,100 Ironing Microwave 1,100 Microwave Water heating 1,500 Water heating Etc. Air conditioning 1,100 Space heating 1,500 Electric 1,100 cooking Etc. Possible Dry cell — — — — — electricity Solar lantern Solar lantern — — — — supply Rechargeable Rechargeable batteries Rechargeable batteries — — — technologies batteries Home system Home system Home system Home system Home system Home system Mini-grid/grid Mini-grid/grid Mini-grid/grid Mini-grid/grid Mini-grid/grid Mini-grid/grid note: — = not applicable Service tiers Tier 0 Tier 1 Tier 2 Tier 3 Tier 4 Tier 5 Tier 2 package Tier 3 package Tier 4 package Task lighting General Actual use of AND AND AND AND lighting indicative light and medium and/or heavy and/or phone AND electricity — discontinuous continuous appli- continuous appli- services charging television application cation cation OR AND (thermal or (thermal or me- (thermal or me- electric radio air circulation mechanical) chanical) chanical) source: Authors’ compilation. note: — = not applicable chapter 2: universal access 100 Annex 4: Technical performance standards for cookstoves In February 2012, the Global Alliance for Clean Cookstoves consensus that not all reductions in emissions are of equal (the Alliance) in collaboration with the World Health Organiza- value to human health and to climate change. The IWA tion (WHO) and International Standards Organization (ISO) multi-tier guidelines provide the basis for measurement of achieved an International Workshop Agreement (IWA) on cookstove performance on the four technical attributes— multi-tier standards for measuring technical performance of efficiency, indoor pollution, overall pollution, and safety. cookstoves. The IWA acknowledges the emerging scientific Technical attributes Tier 0 Tier 1 Tier 2 Tier 3 Tier 4 HPTEa (%) <15 <15 >25 >35 >45 Efficiency LPSCb (MJ/min/L) >0.05 <0.05 <0.039 <0.028 <0.017 CO (g/min) >0.97 <097 <0.62 <0.49 <0.42 Indoor pollution PM (g/min) >40 <40 <17 <8 <2 HPCOc (g/MLd) >16 <16 <11 <9 <8 LPCOd (g/min/L) >0.2 <0.2 <0.13 <0.1 <0.09 Overall pollution HPPMe (mg/MJd) >979 <979 <386 <168 <41 LPPMf (mg/min/L) >8 <8 <4 <2 <1 Safety Iowa protocol <45 <45 >75 >88 >95 source: Authors’ compilation. note: — = not applicable The above guidelines could potentially form the basis for It should be noted that the IWA standards have been de- determining the overall technical performance of the pri- veloped separately for each technical parameter and are mary and secondary cookstoves as the first step in the not designed to be aggregated to obtain an overall rating multi-tier measurement of household access to cooking for the cookstove. The different technical parameters have solutions. In addition to technical performance of primary been kept separate in the IWA to allow programs, donors, and secondary cookstoves (including the use of non-sol- investors, and consumers the ability to distinguish and pri- id fuels), measurement of household access to cooking oritize between different parameters. solutions takes into account the conformity, convenience, and adequacy attributes for the household as a whole, as indicated in figure 2.4 of this document. 101 Global tracking framework Annex 5: Mapping of consumption ranges to proposed multi-tier measurement of access Total Basic Watteq Hours/ Additional access Appliances (kWh/ access per unit day year) Tier 1 Tier 2 Tier 3 Tier 4 Tier 5 Radio 1 2 0.7 0.7 0.7 0.7 0.7 0.7 Task lighting 1 4 1.5 1.5 1.5 1.5 1.5 1.5 Phone charger 1 2 0.7 0.7 0.7 0.7 0.7 0.7 General lighting 18 4 26.3 26.3 26.3 26.3 26.3 Air circulator (fan) 15 4 21.9 21.9 21.9 21.9 21.9 Television 20 2 14.6 14.6 14.6 14.6 14.6 Food processors 200 1 73.0 73.0 73.0 73.0 Washing machine 500 1 182.5 182.5 182.5 182.5 Refrigerator 300 8 876.0 876.0 876.0 Iron 1,100 0.3 120.5 120.5 120.5 Air conditioner 1,100 2 803.0 803.0 3 66 321 1,318 2,121 source: Authors’ compilation. note: Watteq = Watt equivalent; kWh = kilowatt-hour. chapter 2: universal access 102 chapter 3 energy efficiency CHAPTER 3: energy efficiency This chapter proposes a framework for understanding energy efficiency trends, integrating the current approaches to energy efficiency of various international agencies and national institutions, and establishing a methodology to determine the starting point against which future improvements in energy efficiency can be measured at the global and national levels. The chapter begins by identifying the methodological challenges of defining and measuring energy efficiency. After mapping a conceptual framework to address these issues, it goes on to review available global databases and to examine the extent to which those data- bases can be used to address the methodological issues raised. Households and industries use energy sources such as environmental impacts of energy use and production. Yet the electricity to provide goods and so-called end-use services real benefits often come from improved service outcomes: that result in higher levels of economic productivity. Ener- faster journeys, better health from warmer homes, and gy efficiency is measured as the ratio between the useful higher industrial productivity and product performance. output of the end-use service and the associated energy input. In other words, it is the relationship between how In places where the energy needs of consumers are al- much energy is needed to power a technology (for exam- ready met, efficiency improvements primarily translate into ple, a light bulb, boiler, or motor) and the end-use service reduced demand for energy and reduced costs, which (for example, lighting, space heating, or motor power) that can improve competitiveness. On the other hand, many the technology provides. developing countries cannot meet the energy demands of consumers; in places like these, improvements in energy Improving energy efficiency is a means to an end; it is not efficiency are critical to providing more-reliable service an end in itself. The value of energy efficiency policies can and increasing productivity. Both aspects of efficiency— be measured by the social, economic, and environmental reduced energy demand and improved service value—are benefits that they bring. Improved efficiency is an important essential for wealth creation and social development. means of addressing the cost, availability constraints, and Section 1: METHODOLOGICAL CHALLENGES IN DEALING WITH ENERGY EFFICIENCY Measuring and tracking the rate of improvement of energy efficiency in the global energy mix poses various definitional and methodological challenges—chief among them: }} Finding a single headline measure of energy efficiency despite its multidimensional nature }} Dealing with the fact that headline measures of energy intensity are, at best, imperfect proxies for underlying energy efficiency }} Deciding whether to measure economic output in terms of market exchange rate or purchasing power parity }} Deciding whether to measure energy input in terms of primary or final energy. Those challenges are considered individually in the four subsections that follow. chapter 3: energy efficiency 104 Multidimensionality Energy efficiency is most accurately expressed in terms of tween energy processes and the different metrics used to the relationship between energy inputs and end-use out- measure efficiency, the overall energy efficiency of a coun- puts at the level of individual technologies and processes try will not necessarily equal the average efficiency of the (as represented by the base of the pyramid in figure 3.1). component processes. An example of an indicator of such “process efficiencies” would be units of energy input per ton of steel produced To address this problem, aggregate indicators and meth- in a particular type of steel mill using a particular quality or odologies have been developed (represented by the high- type of input material and industrial process. er tiers of the pyramid shown in figure 3.1). Subsectoral indicators trace the relationship between energy input and Operationally, however, such precise indicators present physical or service output in an industry or subsector. This problems as benchmarks for energy efficiency, particularly is done for energy-intensive products (for example, steel, for comparative analyses across countries. First, few coun- cement, pulp and paper) regardless of the differences in tries, if any, consistently track detailed information across the process used among factories. For the residential sec- the full spectrum of energy use in their economies, and, tor, indicators typically track energy used per household even when they do, it is often not possible within a plant and per unit of floor space as well as for each end-use to define exactly how much energy is flowing into differ- (for example, space heating and cooking). For transport, ent processes. (Issues relating to industrial confidentiality indicators include energy per traffic unit (such as passen- pose additional challenges when trying to collect disag- ger kilometers and ton kilometers). At an even higher level gregated data.) Second, even if such data were available, of aggregation, sectoral indicators measure the relation- they would comprise a huge number of process-level in- ship between energy input and associated output in one dicators with different metrics that could not ultimately be broad sector of the economy, such as industry or agricul- aggregated, or, if they could be aggregated, would not be ture. Finally, the highest level of aggregation measures the very informative in evaluating a country’s overall progress relationship between energy input and the output of the on energy efficiency. In fact, owing to the interactions be- economy as a whole. Top-down Bottom-up approach (Energy balances) Total Subsectoral surveys of Top-down (national by sector energy, use, structure accounts, census, etc.) Surveys of users and Top-down Sectoral Intensities equipment, estimates aggregate approach Measurements of Structure: Subsectoral Intensities processes, equipment Attributes: Utilization, Quality, Etc. Process Efficiencies Figure 3.1 Pyramid of energy efficiency indicators source: Martin and others 1995; IEA 1997; Phylipsen 2010. 105 Global tracking framework Intensity versus efficiency As one moves up the pyramid in figure 3.1, the higher de- shifts, and the overall level of activity in the economy. For gree of aggregation across economic activities makes it example, as national income increases, so does car own- increasingly difficult to measure output in physical terms ership and car usage,1 a structural change that has a signif- (for example, tons of steel or units of floor space). Instead, icant effect on energy intensity even if the fuel consumption output is typically measured in monetary units as the value of individual automobiles is no higher than before (and may added of a specific economic sector. even have improved). Several decomposition methods can help to capture changes in the drivers of energy de- Such value-based measures are typically measured in mand and thus to isolate the changes in energy efficiency terms of megajoules (MJ) per U.S. dollar of value added (Ang and Choi 1997; Baksi and Green 2007) (box 3.1). and are technically measures of energy intensity rather than energy efficiency. Energy intensity is at best an im- Despite its limitations, energy intensity has traditionally perfect proxy for energy efficiency. This is because energy been used as a proxy for energy efficiency when making intensity is affected not only by changes in energy demand international comparisons owing to the limited availability but also by shifts in the components that comprise the of disaggregated data and the multidimensional nature of denominator of that ratio, which may have little to do with energy efficiency. energy efficiency. For example, a country that moves rap- idly from subsistence agriculture to industrialization would Energy intensity measures are ratios; trends represent the experience a change in the structure of the economy to- rates of change of those ratios. Therefore, small changes ward more energy-intensive activities rather than a shift in in either the numerator or denominator of energy intensity energy efficiency per se. measures can result in significant shifts in year-to-year trends. The volatility of data trends from one year to the Energy intensity may also be affected by other factors, next can make tracking the evolution of energy intensity such as demographic changes, weather variation, fuel-use difficult. Box 3.1 Understanding what drives change in aggregate variables Changes in energy demand in an economy or sector are influenced by multiple driving forces, including changes in: }} Activity or output. Demand for energy rises with increases in industrial output, the number of people needing housing, or the volume of passengers and distances travelled in the transportation sector. }} Structure. Larger houses and sparser occupancies increase household energy intensity indepen- dent of changes in population; decreases in steel production or increases in financial services lower the energy intensity of the economy as a whole; shifts in transport modes (for example, from public or nonmotorized transport to private cars, or from trains to trucks) alter transport energy consumption. }} Fuel type. A shift from wood to electricity, for example, alters energy demand. }} External/explanatory factors. Cold weather affects the quantity of energy used for residential space heating; changes in income and lifestyle affect consumer preferences, travel, and the use of appliances. }} Technical efficiency. Managerial or technological changes—such as better insulation, process improvements in industry, or innovations in automotive technology—affect the demand for energy. 1 There appears to be an upper limit to car ownership and usage. Policy matters, but it does not cancel out the effect of increased car ownership and usage as incomes increase. chapter 3: energy efficiency 106 A decomposition analysis is typically used to break down the change in an aggregate variable, like energy demand, into its driving factors. Several methodologies can be used for such an analysis, including the Divi- sia-based and Laspeyres-based methods. Since decomposition is a series expansion truncated at first order, a residual usually remains that captures higher-order terms. Most of the methods based on the Divisia index have the advantage of being “residual free,” which comes at the expense of an arbitrary attribution of interac- tion terms. For the purposes of global tracking, the logarithmic mean Divisia index I (LMDI I) method will be used both because it is practical and because it is already widely used to assess energy efficiency progress. The Divisia index was devised by François Divisia and first published in the Revue d’économie politique in 1925 (Divisia 1925). Divisia initially used the index to determine the variable in the equation of exchange. Its application to energy analysis was pioneered by Boyd, Hanson, and Sterner (1988). Source: Authors. Market exchange rate versus purchasing power parity Another difficulty associated with international compari- produced goods tend to be systematically higher in high- sons of value-based measures of energy efficiency is that er-income countries. As a result, MER measures may un- of determining a suitable value measure of output. In par- dervalue output from lower-income countries and therefore ticular, value added can be expressed either in terms of overstate energy intensity. But PPP measures are not as market exchange rate (MER) or purchasing power parity readily available as MER measures because the associ- (PPP). MER measures simply convert the value of output to ated correction factors are updated only every five years a common monetary metric based on standard exchange (box 3.2). rates. The drawback to this approach is that price levels vary significantly across countries, and prices of locally Box 3.2 Purchasing power parity Purchasing power parity (PPP) adjustments are calculated by the International Comparison Program at the World Bank using data from surveys undertaken every five years. A total of 180 countries participate in the surveys. PPP estimates are developed by interpolation for countries that do not participate in the surveys and for years during which surveys are not conducted. For nonparticipating countries, the PPPs are estimated using a price level index adjustment that computes the relative size of the economies in terms of gross domestic product (GDP), imports, and exports in U.S. dollars. PPP series are updated in years between surveys using the most recent nominal GDP and relative GDP deflators (accounting for the rate of inflation) between the country and the United States since the last PPP value was calculated. The current PPP series in use is from the 2005 survey, and the next update will be released in 2013, based on the survey done in 2011. In terms of projections, the International Monetary Fund forecasts country-level annual real GDP through 2017 in the World Economic Outlook. That report (IMF 2012) uses PPP adjusted values and weights for country comparisons and regional aggregations. Source: World Bank International Comparison Program; IMF 2012; UN 2012. 107 Global tracking framework Primary versus final energy Just as energy intensity measures are affected by the mon- capture much of the traditional (that is, noncommercial) etary unit used to capture the value added of output, they energy that accounts for a significant share of energy are also affected by the way that energy consumption2 is demand in lower-income countries. measured. Specifically, energy consumption can be mea- sured either in terms of primary or final energy.3 The use of While it may make sense to use primary energy for high- primary energy as a measure requires selecting a meth- ly aggregated measures of energy intensity, it is less od of accounting for nuclear, hydro, and other renewable useful for measuring energy intensity at the sectoral sources of energy for which there is no distinct process of or subsectoral level. For example, it would be difficult converting final energy (outputs) to primary energy inputs.4 to interpret the results of an analysis that uses primary energy measures to gauge the energy intensity of the When energy intensity is tracked at the primary energy residential sector, because this would confound the ef- level, efficiency improvement trends and potential can ficiency of energy conversion and transformation in the be analyzed on both the supply side and the demand electricity and heating supply sector (which supplies en- side. On the supply side, the conversion from primary ergy to residential buildings) with the efficiency of ener- energy (such as coal) to final energy (such as electricity) gy used within the buildings for end-use services (such can be captured. On the demand side, the conversion as space heating, cooling, and lighting). from final energy (such as electricity used by applianc- es) to useful energy (such as light and heat) can be captured. If only final energy is tracked, the analysis will miss the potential for improvements on the supply side, which could be significant for developing countries. Fur- thermore, analysis at the primary energy level can also 2 Though technically energy cannot be consumed, in this report the term energy consumption means “quantity of energy applied”, following the definition in ISO 50001:2011 and the future standard ISO 13273-1 Energy efficiency and renewable energy sources - Common international terminology Part 1: Energy Efficiency. 3 Final energy can also be expressed in primary terms through the use of dynamic and country-specific conversion factors. This approach is proposed in the ISO standard “Energy Efficiency and Savings Calculation for Countries, Regions and Cities,” currently under development (ISO/TC257). Given the objectives of the UN SE4ALL Global Tracking Framework, data availability issues, and the arguments presented in this section, final energy in primary terms is not used in this report to calculate sectoral intensities. For further discussion on the use of primary or final energy accounting, see the section on methodological issues in chapter 4. 4 As explained further in this chapter, primary energy supply data from the International Energy Agency, which employs the physical energy content method, will be used. chapter 3: energy efficiency 108 Suggested methodology for defining and measuring energy efficiency While it is not possible to fully resolve all of the challenges outlined in the preceding section, SE4ALL’s preferred meth- odological approach is outlined in table 3.1. Challenge Proposed approach Track global performance on energy intensity while also tracking the energy intensity of major economic sectors The multidimensionality of energy efficiency and the efficiency of the energy industry. Move toward better tracking of targets, policies, institutions, and investments. Track energy intensity for countries and major regions and blocks. Where feasible, complement that tracking Intensity versus efficiency with decomposition of changes in energy demand to strip out structural effects. Track energy intensity using the purchasing power parity Market exchange rate versus purchasing power parity measure to capture the value-added of economic output. Track global energy intensity in terms of total primary Primary versus final energy energy supply and sectoral energy intensity in terms of final energy consumption. Volatility of efficiency measures Track a five-year moving average trend. Table 3.1 ADDRESSING METHODOLOGICAL CHALLENGES IN THE GLOBAL TRACKING OF ENERGY EFFICIENCY source: authors. The headline indicator proposed here as a proxy for energy between 1990 and 2010, which is the longest time series efficiency in global tracking is the compound annual growth of data available for this purpose. Going forward, five-year rate of energy intensity at the national level. Energy intensity moving averages will be tracked. is measured as the ratio of total primary energy supply5 to the value-added of the economy measured in terms of pur- To get as close as possible to measuring the underlying chasing power parity to ensure a fairer comparison of en- changes in energy demand, the headline indicator is ergy intensity across developed and developing countries. accompanied by a decomposition exercise of changes in final energy consumption that distinguishes between To address concerns about the year-to-year volatility of en- activity, structure, and underlying efficiency effects.6 The ergy efficiency measures, energy intensity is calculated as proposed methodology uses the logarithmic mean Divisia the compound annual average growth rate for the 20 years decomposition (LMDI I) method for each country. 5 Total primary energy supply is defined as “indigenous production + imports – exports – international marine and aviation bunkers +/- stock changes. It is equivalent to total primary energy demand, and represents inland demand only and, except for world energy demand, excludes international marine and aviation bunkers” (IEA). As discussed later, energy statistics used to calculate indicators in this chapter come primarily from the International Energy Agency. Hence, IEA terminology and definitions are generally used for these variables. When referring to final energy consumption, the equivalent IEA indicator is total final consumption (TFC). 6 Decomposition analysis can also isolate fuel-switching effects, mainly electrification. This was not done in the analysis presented here, however, owing to data constraints. 109 Global tracking framework To give a more nuanced picture of energy efficiency trends, global or regional comparison because the indicator is dis- the headline indicators are complemented with indicators torted by resource-endowment factors. In a country with a of the energy intensity of three end-use sectors (agricul- significant hydroelectric sector, for example, primary energy ture, industry, and “other sectors”7) and two energy supply and delivered energy are more directly related, while a coun- sectors (electricity and gas8) along with the specific energy try rich in geothermal energy will have a lower ratio owing to consumption of select energy-intensive products.9 In addi- the low thermodynamic quality of the primary resource. tion, the suggested methodology tracks national targets, policies, institutions, and investments in energy efficiency. It is very difficult to determine how much primary energy is needed per unit of final energy or end-use output. The For demand-side sectors, the methodology uses energy electricity system is dynamic, with changing dispatch, intensity measures based on the ratio between final energy outages, and utilization factors. It is not practical to pro- consumption (expressed in joules) and a measure of the scale cess real-time generator data for indicators, and the use of the sector. Finding a suitable measure for the scale of of transformation efficiency assumptions obscures the real the sector can be challenging. But its economic value can changes that occur. Efficiency indicators that focus on the be captured through global statistics on sectoral value added. supply system itself are therefore more informative for sup- ply-side decision makers. It is thus more effective to treat Value added is clearly defined only for industry and ag- the supply side as separate from the demand side for in- riculture. For “other sectors,” a category that includes dicator analysis. transport, some activities related to the residential sector, services, and other residuals, value added is less clearly Supply-side energy efficiency indicators measure the ef- defined.10 Indeed, grouping transport, which has a high en- ficiency of thermal plants in converting primary energy ergy intensity, with services, which has a low energy inten- sources—such as coal, gas, and oil—into electricity. They sity, may not be very meaningful and may complicate the are calculated by dividing gross electricity production from interpretation of results for this category, but the decompo- electricity and cogeneration plants by total inputs of fu- sition analysis can at least give some insight into structural els into those plants. Whether market-based or privately changes occurring in better-defined sectors. owned, self-generating plants that do not export their pow- er should be included in the index assessment. In the case Ideally, it would be desirable to report separately on the en- of cogeneration plants, fuel inputs are allocated between ergy intensity of the residential and transport sectors. In the electricity and heat production in proportion to their shares case of the residential sector, energy consumption would of the annual output. ideally be normalized against the number of households or the size of residential housing units in square meters. Sim- Transmission and distribution (T&D) losses measure pow- ilarly, energy consumption in the transport sector would er lost in the transmission of (high-voltage) electricity from ideally be normalized against freight and passenger traffic power generators to distributors and in the distribution of volumes. Unfortunately, because none of these variables (medium- and low-voltage) electricity from distributors to is widely available, it is not possible at present to report end-users. T&D losses are represented as a percentage separate energy intensity measures for the residential and of gross electricity production. They include both techni- transport sectors. cal and nontechnical (or commercial) losses. Included in the latter are unmetered, unbilled, and unpaid electricity, Overall energy efficiency in the supply sector is captured including theft, which could be significant in developing by the ratio of final energy consumption to total primary countries. Aggregate T&D system indicators may be dom- energy supply. This is a practical indicator, and the data are inated by factors other than losses. The location of primary typically available in country energy balances. While this energy resources (such as hydro lakes and coal seams) indicator can be useful for tracking progress in supply-side and large loads (cities and industries) may be more signifi- energy efficiency within a country, caution is required in a cant factors in T&D efficiency indicators than the losses 7 Owing to data limitations, this report groups transport, residential, services, and others into “other sectors.” The medium- and long-term methodology will consider these sectors separately. 8 For this analysis, transformation losses in oil production are considered negligible and will not be tracked. 9 These include iron and steel, cement, chemicals and petrochemicals, aluminum, pulp and paper, and fertilizers (provided there are sufficient data for tracking). 10 This makes the definition of sectors consistent both in the numerator and the denominator of the intensity calculation. The World Bank’s World Development Indicators (WDI) database considers all of the items classified under the International Standard Industrial Classification (ISIC) 3, including the value of energy for own use, as value added in industry. Therefore, own use of energy by industry (as reported by IEA) was added to the sector’s consumption. This excludes nonenergy uses (such as feedstocks and methanol production). Similarly, energy use in the WDI sector labeled “services” is calculated by adding the consumption of the EIA sectors listed as “services,” “residential,” “transportation,” and “other nonspecified.” chapter 3: energy efficiency 110 or efficiency of the transmission system itself. Properly For gas supply, the efficiency indicator is based on the ra- separating true losses (and hence the efficiency poten- tio of losses to primary energy supply using data available tial of transmission systems) from exogenous location from national energy balances. and scale factors and nontechnical losses would re- quire detailed studies of system-dynamic interactions and real operating requirements that are not practical for global tracking purposes. Global databases for setting the tracking framework A number of agencies have historically collected dis- Table 3.2 summarizes the available databases that are aggregated data on sectoral—and sometimes subsec- consistent across countries and time, three of which are toral—measures of energy intensity and energy efficiency, in the public domain (IEA; the World Bank’s World Devel- although these focus primarily on the developed countries opment Indicators; and UN Energy Statistics). The table of the Organisation for Economic Co-operation and Devel- also includes ODYSSEE, which, although limited in country opment (OECD) (box 3.3). coverage, exemplifies the extent to which energy efficien- cy indicators can be constructed provided that there are At present, disaggregated data are available for few devel- sufficient data. oped countries. Therefore, when constructing energy inten- sity indicators for a wide set of countries, it is necessary to analyze base sectoral and end-use energy and activity data. Box 3.3 Overview of existing data sources for energy efficiency indicators A number of different agencies are doing important work on developing energy efficiency indicators. In gen- eral, these efforts either cover a relatively small number of countries in great depth (e.g. ODYSSEE-MURE) or a large number of countries at a much higher level of aggregation (WEC). While all these sources are relevant and useful for global tracking, none of them are directly suited in their existing form. The International Energy Agency’s (IEA’s) energy efficiency indicators start from the top of the energy efficiency indicator pyramid (recall figure 3.1) and cover as many aggregation levels as possible. The IEA makes efforts to deepen the coverage of energy efficiency indicators to lower levels of disaggregation in OECD-IEA member countries. At lower aggregation levels, data availability limits the number of countries for which detailed indi- cators can be developed to ever-smaller subsets of IEA member countries. The exception is a special effort undertaken for the 2012 World Energy Outlook (WEO), which includes energy efficiency analysis for 25 large countries and global subregions. The ODYSSEE-MURE Project, under the Intelligent Energy Europe Programme of the European Commission, is one of the most ambitious attempts to produce subsectoral and process-level indicators on energy efficien- cy. It focuses on the 27 EU member states plus Norway and Croatia. Through bilateral support—such as the assistance that ADEME (the French Agency for Environment and Ener- gy Management) has provided to several developing countries, and the efforts of individual countries (for ex- ample, China, India, Mexico, South Africa, Turkey, and Vietnam)—Enerdata provides relatively good coverage of sectoral-level energy intensity indicators for 184 countries worldwide, but these are proprietary. The World Energy Council (WEC), with technical support from ADEME/Enerdata, maintains a database of global energy efficiency indicators focusing on a small set of aggregated indicators. The WEC effort covers the entire world at a regional level but provides only relatively aggregated efficiency indicators; this level of aggregation is indicative of what can currently be achieved for most developing countries without substantial additional effort and local involvement. It is important to note that efforts are under way to expand the countries included in the WEC’s database. 111 Global tracking framework The Asia Pacific Economic Cooperation, through capacity building activities on energy efficiency indicators organized by its Energy Working Group, has been forging collaboration and information sharing among its member economies. Additionally, information is collected by various other agencies, including the World Bank, the U.S. Department of Energy’s Energy Information Administration (EIA), the UN Industrial Development Organization (UNIDO), and other UN agencies. National energy agencies also collect data as part of their routine work, but these are limited in scope by coverage (either by country or sector) and often are based on differing methodologies. As a result, care must be taken when using these inputs as part of a tracking framework. ENERGY DEMAND OTHER VARIABLES Sectoral: Primary Number of Subsectoral: Household data Period Sectors (# of Sector Transport activities Source or countries Subsectors (# of covered countries) value added (# of countries) secondary covered (# of countries) countries) Industry, agriculture, 13 industry International services, subsectors, 6 Building Energy Primary 1971–2010 138 residential, transport — — characteristics Agency (IEA) transport, subsectors for (29) fishing, and (138) forestry (138) Industry, 3 industry agriculture, subsectors, 5 UN Energy services, Primary 1950–2009 Over 200 transport — — — Statistics residential, subsectors transport (over 200) (over 200) Air transport, freight in million World Bank, 3 sectors ton-km (169); Air Household World (agriculture, transport, passen- final Development Primary 1980–2011 — — — industry, gers carried (169); consumption Indicators services) railways, goods (172) (WDI) transported in million ton-km (88) Industry (181), 13 industry agriculture subsectors 3 sectors Private (135), services (16–61) 4 (industry, Enerdata Secondary 1970–2010 184 — consumption (167), resi- transport agriculture, (134) dential (184), subsectors services) transport (184) (87–184) 16 industrial Traffic, annual subsectors, distance travelled, Stock of 9 transporta- and stock of dwellings, new Industry, tion modes, 3 sectors vehicles by mode dwellings, agriculture, 4 household (agri- of transporta- floor area of ODYSSEE Primary 1990–2010 29 services, end-uses, 5 culture, tion: road (cars, dwelling, stock residential, appliances, industry, two-wheelers, bus- of appliances, transport (29) 6 branches services) es, light vehicles, equipment rate services, 1 trucks), rail, water, (29) agriculture air (29) sector (29) Table 3.2 Coverage of the few available databases that are consistent across countries and time source: authors. — = data not available. chapter 3: energy efficiency 112 Global and country-level tracking frameworks Immediate and short term The immediate approach for global tracking will make use IEA, the World Energy Council (WEC), the World Bank, the of the most widely available historical data to construct na- Asia Pacific Energy Research Centre (APERC), and the Eu- tional and sectoral indicators of energy intensity. This will ropean Union (EU), as well as country consultations. be done by combining two sets of public domain data: (i) data on total primary energy supply and final energy con- At present there is no established methodology or periodic sumption at the national and sectoral levels from the IEA’s data collection on a global scale for tracking investments national energy balances, complemented with UN data on in energy efficiency. IEA’s recent work for the World Ener- countries for which IEA lacks information; and (ii) data on gy Outlook (WEO) 2012 could lay the foundation for this national and sectoral value added in PPP terms from the purpose. Data sources include the World Bank and other World Bank and International Monetary Fund. Indicators multilateral development organizations. As mentioned pre- will be tracked on a country level and aggregated globally viously, energy intensity indicators should be calculated as and regionally for reporting by SE4ALL. five-year moving averages. For monitoring and evaluation, especially in EU countries, the European Commission Di- The specific energy consumption of selected energy-inten- rective on energy efficiency and the national energy effi- sive products will be tracked using a wide range of avail- ciency action plans may be used. able studies and databases, including those produced by the IEA, Enerdata, UNIDO, and other relevant stakeholders. The question of the entity that should be responsible for In this process, care should be taken to address issues of tracking, monitoring, and evaluating progress on energy comparability between different methodologies. Tracking efficiency is still under discussion. Well-established insti- should include national (and regional when applicable) en- tutions that already collect and analyze the base data, as ergy efficiency policies, targets, institutional frameworks, well as special-purpose entities created under the SE4ALL and investments. Sources of information for the former initiative, are being considered. include databases and compendiums available from the Medium term The development of energy efficiency indicators in many on the residential and transport sectors, for which scaling developing countries is limited by the availability and quali- variables are not readily available at present. In the case ty of data and by a lack of dedicated resources and exper- of the residential sector, data series on floor space, oc- tise to collect, track, and analyze those data. Substantial cupancy and the number of households in each country capacity-building efforts and resources—both human and are needed to calculate more meaningful measures of res- financial—are needed to strengthen existing programs and idential energy intensity than are possible today. The same institutions. Several countries have already established is true for data series on freight and passenger traffic vol- tracking systems and are collecting data and conducting umes in the transport sector. Improved floor space data analysis. In other countries, energy data are limited to sup- could also help to provide more meaningful measures of ply and demand at the national and sector levels, which efficiency in the services sector. makes it difficult both to assess energy efficiency and to target policy interventions. Since SE4ALL envisions the establishment of national track- ing systems, there will be opportunities to invest in coun- Efforts to improve data collection are best directed at in- try-level capacity to collect critical complementary data that creasing the availability of sectoral activity indices that can can cover the spectrum of economic activity. In addition, at be used to convert into energy intensities detailed data on the country level, it may be possible to contemplate more sectoral energy consumption already available from the refined and disaggregated data on energy efficiency at the national energy balances. In particular, the focus should be level of subsectors and technology processes. 113 Global tracking framework Annex 1 illustrates the proposed indicators and their lim- framework needs to be established. Figure 3.2 illustrates itations. For a country to understand key sector-level fac- the levels of data needed to monitor energy efficiency tors driving energy efficiency, a bottom-up data collection and intensity. data source Total • IEA Energy Balances by sector • IEA Energy Balances & • World Bank Value Added (National accounts, Census) Sectoral Intensities • National Surveys • Industry Associations • Measurements • Modelling/Estimates Sub-sectoral IntensitY AND EfficiencY DATA • Public and Private Administrative Sources Degree of Data Required Figure 3.2 Energy indicators pyramid source: Authors. Note: IEA = International Energy Agency. There is no single best approach to collecting country-lev- those data should be handled. This decision can be driv- el data; a country could choose from a number of ways en by existing national administrative laws. Some coun- to compile bottom-up energy demand data. Data collec- tries task statistical departments to undertake national tion could focus on sectors of interest and could include surveys and carry out analysis; in other countries, final a combination of national surveying, metering, modeling, energy end-use analysis and estimates are carried out by and collection of administrative data from existing public ministries responsible for energy and natural resources. and private sources. Figure 3.3 illustrates a data collection Often, different ministries are asked to work together. For framework that could be used for each sector based on example, statistics ministries and ministries tasked with several different sources. The final—and most important— overseeing energy resources and economic output are step of the data collection framework is the bottom-up pro- asked to coordinate to produce a final output together cess of reconciliation and validation with energy balances. with one national organization taking the lead. This is the step in which analysts ensure that energy and activity data are aligned with activity classification defini- More data are not necessarily better. A country must com- tions. In addition, energy end-use data (such as for space mit to maintaining ongoing data collection and assessment heating and cooling), or derived data (obtained, for exam- of efficiency improvements. In order to establish timely and ple, by estimating average fuel consumption of vehicles on effective analysis of energy efficiency improvements, steps roads by relating energy data to vehicle registration dates) should be taken to ensure that sector-level monitoring of are produced from the collated data. energy use is renewed on an annual basis. Resources should be allocated to monitor sectors that constitute a Deciding which organization collects, consolidates, and significant share of the country’s absolute energy demand. analyzes data can be as important as determining how chapter 3: energy efficiency 114 Surveys Sector and Sub-sector Measuring/ Bottom-up energy Metering Modelling consumption by end-users Validation Administrative Sources Energy Balances Figure 3.3 Data collection framework source: Authors. IEA’s forthcoming Manual on Statistics for Energy Efficiency sources. Other international guides are also being prepared, Indicators will be an essential guide for all countries that wish including the Energy Statistics Compilers Manual by the Unit- to establish a national framework. It will provide a list of key ed Nations Statistics Division, and the Manual for Statistics data elements needed to build energy efficiency indicators on Energy Consumption in Households by Eurostat. and describe how countries collect such data. The manual will feature examples of international practices, such as sur- Figure 3.4 summarizes the proposed framework for the imme- veying, metering, modeling, and collecting of administrative diate and medium term, both globally and at the country level. Immediate Medium term National and sectoral energy intensity measures for end-use sectors (industry, agriculture, and Improve integration of data systems on energy other sectors, the latter comprising services, use and associated output measures (for exam- residential and transport) plus an efficiency ple, residential floor space and traffic units for Global measure for electricity and gas supply. transportation). tracking Apply Divisia decomposition method to track Improve data on specific energy consumption of the underlying energy efficiency component of energy-intensive products. energy intensity. Strengthen country-level information systems and capability to collect data on sectoral intensi- ties (and, ideally, subsectoral process efficiency measures). Country-level None Improve data on physical activity drivers (traffic tracking volumes—passenger and freight, number of households, floor space, and so on). Improve data on energy efficiency targets, poli- cies, investments and institutional frameworks. Figure 3.4 Immediate and medium-term tracking across global and country levels source: authors. 115 Global tracking framework Section 2. Global, regional, and sectoral trends in energy intensity This section establishes the starting point for improvement decades from 1990 to 2010 at the global, sectoral, and re- in energy intensity using the approach outlined in the previ- gional levels. ous section. It reviews energy intensity trends over the two Defining the starting point for improvement As described earlier, energy intensity measures the amount of energy used to produce a unit of economic activity (GDP). The 20 years between 1990 and 2010 witnessed an unprec- -1.0% edented growth in both GDP and energy demand across is the compound the globe. World primary energy supply grew from 367 exa- annual reduction joules (EJ)11 in 1990 to 534 EJ in 2010, an annual growth rate in global energy intensity during the of 1.9 percent. Global GDP grew at an even higher rate of decade 2000-2010; significantly lower 3.2 percent per year (from $36 trillion in 1990 to almost $68 than the equivalent figure of -1.6% for trillion in 2010) in PPP terms (constant 2005 U.S. dollars). the decade 1990-2000 Thus, the starting point for the rate of energy efficiency im- provement against which future progress will be measured The magnitude of the deceleration during the decade 2000– under the SE4ALL initiative is a compound annual growth 2010 differs markedly across the MER and PPP measures. rate (CAGR) for global energy intensity of –1.3 percent (in The rate of improvement of energy intensity slowed to only PPP terms) for the period 1990–2010. The SE4ALL global –0.1 percent annually in MER terms, compared to –1.0 objective is a CAGR of –2.6 percent for the period 2010– percent in PPP terms. This divergence between MER and 2030.12 For immediate tracking purposes, energy intensity PPP measures can be attributed to globalization during the is adopted as an imperfect proxy for energy efficiency that 2000s, which led to a large shift in the share of global GDP may be subject to improvement over time. that was produced in non-OECD countries, where prices tend to be relatively low. As a result, the valuation of global As figure 3.5 illustrates, improvements in energy intensi- output in PPP terms (to correct for these lower prices) rose ty were not even across the two decades. Energy inten- steeply relative to MER terms. The rate of improvement in sity decreased more rapidly in the 1990s (–1.6 percent energy intensity thus looks much higher when the true val- per year) than in the 2000s (–1.0 percent per year). This ue of increased output is taken into account. slowdown is mainly attributable to an increasing share of global economic activity during the 2000s in developing Asian countries, which have energy-intensive industries and coal-fired power generation, and thus relatively high energy intensities. 11 1 exajoule (EJ) = 1018 J; 1 terajoule (TJ) = 1012 J; 1 megajoule (MJ) = 106 J. 12 When measured in final energy terms, the compound annual growth rate is –1.5 percent for the period 1990–2010. Thus the goal is –3.0 percent on average for the next 20 years. chapter 3: energy efficiency 116 a. Purchasing power parity b. Market exchange rate 1990–2000 2000–2010 1990–2010 1990–2000 2000–2010 1990–2010 0% 0% -0.04% -0.5% -0.5% -0.8% -1% -1% -1% -1.3% -1.5% -1.5% -1.5% -1.6% -2% -2% c. Evolution of global PPP/MER ratio d. OECD vs. non-OECD share of GDP (PPP) 100% 1.35 100% 80% 1.30 80% 60% 1.25 60% 40% 1.20 40% 20% 1.15 20% 0% 1.10 0%1990 2000 2010 1990 2000 2010 1990 2000 2010 OECD Non-OECD OECD Non-OECD Figure 3.5 Rate of improvement in global energy intensity (compound annual growth rate) source: Based on World Bank World Development Indicators; IEA 2012a. Note: GDP = gross domestic product; MER = market exchange rate; OECD = Organisation for Economic Co-operation and Development; PPP = purchasing power parity. 117 Global tracking framework In absolute terms, global energy intensity fell from 10.2 MJ/$ in 1990 to 7.9 MJ/$ in 2010 when measured in PPP terms (figure 3.6a). The role of major global economic 7.9 MJ/US$ shocks is evident when examining year-to-year rates of im- is the global provement. The impact of steeply rising energy prices is average energy observable in the charts as triggering larger improvements intensity in 2010; compared with 10.2 in energy intensity in the 1990s. With the recession of the megajoules per US$ in 1990 early 2000s and the global financial crisis of the late 2000s, improvements in energy intensity slowed. a. Energy Intensity 1% 10 10.2 9.5 0% MJ/$2005 9 -1% 8.5 8.7 -2% 8 -3% 7.9 7.5 1990 2000 2010 EI Annual % Change (left) Energy Intensity (right) b. INTENSITY FROM DECOMPOSITION 0% 12 10 10.2 -1% 8 MJ/$2005 8.4 7.4 -2% 6 4 -3% 2 -4% 0 1990 2000 2010 EI Annual % Change (left) Energy Intensity (right) Figure 3.6 Evolution of global energy intensity trends at PPP source: Based on World Bank World Development Indicators; IEA 2012a. note: EI = energy intensity; PPP = purchasing power parity. chapter 3: energy efficiency 118 As noted in the previous section, the decomposition of en- of energy intensity with the activity and structure effects ergy demand trends expressed in final energy consumption factored out is –1.6 percent—higher than the CAGR of by sector makes it possible to distinguish among changes energy intensity of –1.3 percent for the same time period, attributable to an expansion in economic activity (the activity illustrating that energy intensity trends underestimate the effect), changes attributable to a shift in the structure of the rate of progress in underlying energy efficiency.13 economy (the structure effect), and changes attributable to improvements in energy intensity (intensity effect). The latter The reason for this difference can be seen in figure 3.7b, provides a first-order approximation of underlying energy which illustrates the variations in each component of energy efficiency (see figure 3.6b). The figure shows that improve- demand from the base year. As the years progressed, the in- ments in the decomposed intensity were consistently higher crease in economic activity in each sector was offset by the than those in the unadjusted intensity, particularly in the last increased efficiency in each of the sectors used in the decom- decade of the period analyzed. position. The change in the structure component is insignifi- cant at the global level because structural shifts in one country Figure 3.7a shows more clearly the changes in the global are to some extent offset by those in another, while the level of energy intensity component of energy consumption for the sector disaggregation is in any case quite coarse. 20 years since 1990. For the period 1990–2010, the CAGR a. Energy intensity improvement by decade 1990–2000 2000–2010 1990–2010 0% -0.5% -1.0% -1.5% -1.4% -1.6% -2.0% -1.9% b. Trends by component 2.5 2.0 1.5 Energy Index (base year 1990) Activity Index 1.0 Structure Index Intensity Index 0.5 0 1990 2000 2010 Figure 3.7 Global rate of energy intensity improvement (decomposition analysis) source: Based on World Bank World Development Indicators; IEA 2012a. 13 The –1.6 percent rate is also a larger improvement than the global compound annual growth rate measured in terms of final energy consumption terms with no decomposition. If taken as a baseline, it would imply average annual growth of –3.2 percent over the next 20 years. 119 Global tracking framework Energy intensity improvements over the two decades 1990– 2010 had a dramatic impact on the reduction of primary energy demand14 globally. As figure 3.8 illustrates, if global 2,300 EJ energy intensity measured in PPP terms had remained at is the cumulative its 1990 level, world energy demand in 2010 would have energy savings been nearly 300 EJ higher. The energy intensity improve- due to decreases in global energy ment that took place over the past 20 years allowed sav- intensity from 1990 to 2010; equivalent ings of nearly 2,300 EJ, equivalent to almost one-quarter of to the combined cumulative primary cumulative global primary energy demand—or the cumu- energy demand of China, India and lative primary energy demand of China, Russia, and India Russia over the same period combined over the same period. 900 600 EJ 300 0 1990 2000 2010 Primary Energy Demand Avoided Energy Demand Figure 3.8 Energy savings from realized intensity improvements (EJ) source: Based on World Bank World Development Indicators; IEA 2012a. Global trends by sector Further insights can be obtained by examining energy terpret given the very different activities included under this intensity trends at the level of major economic sectors— category, which have markedly different drivers and inten- namely, agriculture, industry and other sectors (including sity levels (see box 3.4 for an estimate of the contribution of transportation, residential, and services) (figure 3.9). The the transport sector to improvements in energy intensity). industrial sector is by far the most energy intensive, de- spite having improved at a relatively fast rate of –1.4 per- Although the rate of energy intensity improvement in in- cent annually in PPP terms. The agricultural sector, which dustry and agriculture slowed down in 2000–2010 com- accounts for slightly over 2 percent of global final energy pared to 1990–2000, the opposite was true in the other consumption, showed the fastest rate of improvement, at sectors; once again, however, this result must be consid- –2.2 percent per annum. Improvement in the other sectors ered cautiously. is similar to that in industry, although this is difficult to in- 14 As indicated previously, primary energy demand is equivalent to primary energy supply. chapter 3: energy efficiency 120 a. By sector, 1990–2010 Industry Agriculture Other Sectors 0% 10 MJ/$2005 5 -1.4% -1.4% -2.2% -3% 0 CAGR 1990-2010 (left) EI in 1990 (right) EI in 2010 (right) b. By sector and decade Industry Agriculture Other Sectors 0% -1% -0.9% -1.2% -1.7% -1.7% -1.8% -2% -2.7% -3% 1990-2000 2000-2010 Figure 3.9 Sectoral energy intensity trends at PPP source: Based on World Bank World Development Indicators; IEA 2012a. note: Other sectors include the transportation, residential, and service sectors. CAGR = compound annual growth rate; EI = energy intensity; PPP = purchasing power parity. When looking at energy savings (that is, the difference the percentage contribution of each sector (figures 3.10b between estimated cumulative final energy consumption and 3.10c) matches closely their share of final energy if energy intensity levels had remained constant at 1990 consumption (figure 3.10a). levels and actual cumulative consumption through 2010), 121 Global tracking framework 40% 36% 32% 40% 36% 32% 65% 62% 56% 2% 4% 65% 3% 62% 56% 2% 4% 3% Other sectors agriculture Industry Figure 3.10a Final energy Figure 3.10b Other sectors Energy agriculture Figure 3.10c Energy savings by Industry consumption by sector, savings by sector, sector, 1990–2010 (based on 1990–2010 1990–2010 intensity from decomposition) SOURCE: Based on World Bank World Development Indicators; IEA 2012a. notE: Other sectors include the transportation, residential, and service sectors. Box 3.4 Estimating the contribution of the transport sector to energy intensity improvements Due to limitations in the availability of data on sectoral value added in the World Development Indicators, the main analysis here treats “other sectors” as a residual after industrial and agricultural output have been sub- tracted from GDP . As a consequence of this method, a number of disparate subsectors—including transport, residential, and services—are lumped together. More disaggregated data on value added in the transport sector are available from the United Nations Sta- tistics Division’s National Accounts database, though that database covers 100 countries instead of 116 and only for 2000–10. Despite limitations in data, it is still of interest to explore trends in the transport sector as a supplement to the main analysis. The analysis shows a CAGR of –1.3 percent for the energy intensity of the transport sector in 2000–10. Overall, the transport sector contributed 29 percent of total global energy sav- ings—almost as much as the other service sectors (38 percent) (figure A). Figure A. Economywide extended decomposition: The contribution of sectoral energy efficiency improvements to energy savings, 2000–2010 Transport 29% 30% Industry Agriculture 3% Other Sectors 38% Source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. Note: Other sectors include the residential, and service sectors. chapter 3: energy efficiency 122 While the sectoral indicators reported above give a good many years. New coal-fired power stations dominate re- sense of demand-side energy intensity, it is also important cent load growth, keeping overall efficiency relatively low to consider the efficiency of conversion and transformation despite the availability of higher-efficiency plants, such as from primary to final energy. Figure 3.11a shows a gradual combined-cycle gas generators. loss of global total primary energy to final energy trans- formation efficiency. This ratio decreased from 72 percent Figure 3.11d highlights that again there is inertia in the dy- in 1990 to 68 percent in 2010. The driving forces behind namics of power transmission and distribution systems. this include the growth in coal use for electricity generation, The underlying drivers include the ongoing economic ap- and coal, oil, and gas consumption for heat provision rela- plication of transmission efficiency improvements being tive to other primary resources. countered by increasing network length as new generators are added farther from load centers. Figure 3.11b shows the impact of improvements made in reducing losses in primary gas extraction and processing. The above indicators highlight that it is important to under- Contributing factors include reduced gas flaring, reduced stand the underlying system inertia and dynamics and that leakage, and improved efficiency of pipeline pressurization. disaggregation is key to explaining the status and oppor- tunities of energy systems. Figure 3.11c highlights the inertia in global electricity gen- eration efficiencies, locked in at about 38 percent over a. FINAL TO PRIMARY ENERGY RATIO (%) b. GAS SUPPLY LOSSES (%) 74% 2% 71.7% 72% 1.4% 70.3% 1.0% 70% 1% 0.9% 68.0% 68% 66% 0% 1990 2000 2010 1990 2000 2010 c. THERMAL EFFICIENCY (%) IN POWER SUPPLY d. T&D LOSSES (%) IN POWER SUPPLY 40% 12% 39.0% 39% 10% 9.5% 38.3% 38.3% 9.1% 8.9% 38% 8% 37% 6% 36% 35% 4% 1990 2000 2010 1990 2000 2010 Figure 3.11 Supply-side energy efficiency indicators source: Based on IEA 2012a. Note: T&D = transmission and distribution. 123 Global tracking framework Global trends by region On a regional level, Eastern Europe and the Caucasus and and Northern Africa are among the slowest-performing Central Asia regions exhibited the fastest rate of energy regions in terms of the rate of energy intensity improve- intensity improvement over the past 20 years (figure 3.12). ment, they rank second and third, respectively, in terms Despite this remarkable improvement, however, Eastern of the lowest achieved level of energy intensity in 2010. Europe and the Caucasus and Central Asia regions remain Countries in Europe and North America also steadily im- among the most energy intensive in the world, alongside proved their energy intensities. Southern and Southeastern Sub-Saharan Africa. Western Asia (which includes coun- Asia achieved similar levels of energy intensity, although tries from the Middle East) is the only region to show a sub- the latter showed slower progress, having started from a stantial deterioration in energy intensity, particularly in the relatively lower level. past decade. Although Latin America and the Caribbean 2% 40 0.8% 30 0% -0.1% -0.5% -0.5% MJ/$2005 -1.1% -1.1% 20 -1.3% -1.3% -1.5% -1.7% -2% -2.3% 10 -3.2% -4% 0 m eu ee a ea a sa ia c f a a a w c ss se la a n n c n ea c o CAGR 1990-2010 (left) EI in 1990 (right) EI in 2010 (right) Figure 3.12a Rate of improvement in energy intensity at PPP vs. energy intensity levels in 1990 and 2010, by region note: NAm = North America; EU = Europe; EE = Eastern Europe; CCA = Caucasus and Central Asia; WA = Western Asia; EA = Eastern Asia; SEA = Southeastern Asia; SA = Southern Asia; LAC = Latin America and Caribbean; NAf = Northern Africa; SSA = Sub-Saharan Africa; CAGR = compound annual growth rate; EI = energy intensity; PPP = purchasing power parity. Eastern Asia, North America, and Europe contributed most Western Asia and Northern Africa contributed a 0.6 percent to global energy savings over the 20 years between 1990 decrease in energy savings owing to deterioration or slow and 2010 (figure 3.13).15 Eastern Europe, Southern Asia, progress in energy intensity improvement. and other regions accounted for only 16 percent of energy savings while consuming about 35 percent of global energy. 15 Savings are calculated comparing actual primary energy supply with what it would have been if countries in each region had maintained 1990 energy intensity levels. chapter 3: energy efficiency 124 2% 0% CAGR -2% -4% -6% m eu a ia c f a ee a ea a sa a w c ss se la a n n c n ea c o 1990-2000 2000-2010 Figure 3.12b Rate of improvement in energy intensity at PPP by region and decade source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. note: NAm = North America; EU = Europe; EE = Eastern Europe; CCA = Caucasus and Central Asia; WA = Western Asia; EA = Eastern Asia; SEA = Southeastern Asia; SA = Southern Asia; LAC = Latin America and Caribbean; NAf = Northern Africa; SSA = Sub-Saharan Africa; CAGR = compound annual growth rate; EI = energy intensity; PPP = purchasing power parity. EA (21%) EA (58%) NAM (24%) NAm (17%) EU (15%) EU (10%) EE (11%) EE (6%) SA (7%) SA (4%) CCA (1%) CCA (2%) LAC (6%) LAC (1%) SSA (4%) SSA (1%) Oceania (1%) Oceania (<1%) SEA (4%) SEA (<1%) WA (4%) NAf (1%) Figure 3.13a Primary energy supply by Figure 3.13b Energy savings by region, region, 1990–2010 1990–2010 source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. Note: NAm = North America; EU = Europe; EE = Eastern Europe; CCA = Caucasus and Central Asia; WA = Western Asia; EA = Eastern Asia; SEA = Southeastern Asia; SA = Southern Asia; LAC = Latin America and Caribbean; NAf = Northern Africa; SSA = Sub-Saharan Africa. 125 Global tracking framework Global trends by income level Lower-middle-income countries started from the same level showing solid progress, low-income countries remain by of energy intensity as the upper-middle-income countries far the most energy-intensive income group. Interestingly, in 1990 and made the most rapid progress in energy inten- apart from upper-middle-income countries, all income sity improvement through 2010 (figure 3.14). Even though groups—particularly low- and lower-middle-income coun- high-income countries improved their energy intensity at tries—accelerated their rates of energy intensity improve- the slowest pace, their absolute level of energy intensity ment in the decade between 2000 and 2010. The deceler- remains the lowest in the world; indeed, even their starting ation in the global rate of energy intensity improvement in level of energy intensity in 1990 has not yet been matched this decade can therefore be attributed to the upper-middle by countries of other income levels as of 2010. Despite -income countries. a. By income group HICs UMICs LMICS LICs 0% 20 -1.1% MJ/$2005 -1.4% 10 -1.9% -2.3% -3% 0 CAGR 1990-2010 (left) EI in 1990 (right) EI in 2010 (right) b. By income group and decade HICs UMICs LMICS LICs 0% -1% -2% -3% 1990-2000 2000-2010 Figure 3.14 Rate of improvement in energy intensity at PPP vs. energy intensity levels in 1990 and 2010, by country income group and decade source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. note: CAGR = compound annual growth rate; EI = energy intensity; HICs = high-income countries; LICs = low-income countries; LMICs = lower-middle-income countries; UMICs = upper-middle-income countries; PPP = purchasing power parity. chapter 3: energy efficiency 126 Despite the slowdown of energy intensity improvement only one-third of energy savings (figure 3.15). The rea- in 2000s, upper-middle-income countries accounted for son behind this disparity is that the upper-middle-income more than half of total energy savings over the past 20 countries started with an energy intensity twice as high as years. High-income countries, on the other hand, con- that of high-income countries, and therefore had more op- sumed close to half of global energy but accounted for portunities to introduce energy saving measures. 2% 1% 13% 8% LICs 27% HICs 51% UMICs 34% LMICs 64% Figure 3.15a Primary energy supply by Figure 3.15b Energy savings by income level, 1990–2010 income level, 1990–2010 source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. Note: HICs = high-income countries; LICs = low-income countries; LMICs = lower-middle-income countries; UMICs = upper-middle-income countries. 127 Global tracking framework Section 3. Country performances Country performances varied greatly within and across re- 7, those between 7 and 10, and those above 10 (figure gions, ranging from an energy intensity of 1.0 in Macau, 3.16). There are 45 countries with energy intensities below China, to almost 60 in Liberia. (All energy intensities in this 5; most countries in this category are found in Latin Amer- section are expressed in PPP terms as MJ/$2005.) Overall, ica and Caribbean, Europe, Oceania, and Sub-Saharan 54 out of 181 countries experienced an increase in energy Africa. In the most energy-intensive category, there are 50 intensity over the past 20 years. countries, with many of them in Sub-Saharan Africa and Western Asia. The world can be divided into four country blocks—coun- tries with energy intensities below 5, those between 5 and 100% 2 1 4 1 4 3 1 2 3 80% 6 4 4 25 6 3 60% 12 9 1 3 2 3 3 3 1 40% 1 8 2 1 3 5 15 20% 11 4 3 8 2 3 2 1 1 5 0 m EU EE A A EA A SA ia C f A A W C SS SE LA A n N C N ea c O Figure 3.16 Energy intensity (MJ/$2005) at PPP by region (number of countries), 2010 Below 5 Between 5-7 Between 7-10 Above 10 source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. note: NAm = North America; EU = Europe; EE = Eastern Europe; CCA = Caucasus and Central Asia; WA = Western Asia; EA = Eastern Asia; SEA = Southeastern Asia; SA = Southern Asia; LAC = Latin America and Caribbean; NAf = Northern Africa; SSA = Sub-Saharan Africa. Further insights can be obtained by plotting energy in- uniformly low levels of energy intensity, but vary hugely in tensity against energy consumption per capita. Low- and their energy consumption per capita. For example, North lower-middle-income countries show levels of energy con- America and some of the Gulf states have some of the sumption per capita that are uniformly below the global highest levels of energy consumption per capita, while a average. Yet within these same groups of countries there number of European countries have some of the lowest. is great variation in individual energy intensity, from the The upper-middle-income countries, by contrast, tend to lowest to the highest energy-intensity ranges observed present either both high energy intensity and consumption globally (figure 3.17a). For example, Uzbekistan and per capita, as in the Islamic Republic of Iran and several Ukraine are two of the most energy-intensive countries in countries of the former Soviet Union, or both low energy the world, while the Philippines is one of the least (figure intensity and low consumption per capita, as in Turkey and 3.17b). High-income countries, on the other hand, show a number of Latin American countries. chapter 3: energy efficiency 128 a. By income group Primary energy Supply/GDP (PPP) Primary energy consumption/capita lics b. In 40 largest energy consumers lmics umics Primary energy Supply/GDP (PPP) hics uzbekistan ukraine kazakhstan iraq russia nigeria s. africa saudi arabia china iran Vietnam venezuela canada Primary energy indonesia Pakistan thailand Malaysia S. Korea consumption/capita Belgium Egypt Czech Rep. uae india Algeria Sweden poland Argentina France Australia brazil ITALY japan Netherlands Philippines Mexico Turkey SpAIN germany united states uk figure 3.17 Energy intensity PPP vs. energy consumption per capita, 2010 Source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. Note: Values are normalized along the average. Bubble size represents volume of primary energy supply. GDP = gross domestic product; HICs = high-income countries; LICs = low-income countries; LMICs = lower-middle- income countries; UMICs = upper-middle-income countries; PPP = purchasing power parity. 129 Global tracking framework Lorenz curves 100% 80% Cumulative % 60% Gini 0.53 40% Gini 0.48 20% 0 20% 40% 80% 60% 100% Cumulative % Population Figure 3.18 Distribution of energy demand and GDP by population Energy Demand GDP source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. note: GDP = gross domestic product. High-impact countries Global total primary energy supply is heavily concentrated already achieved relatively low levels of energy intensity. in a relatively small number of high- and middle-income In identifying high-impact opportunities, it is therefore also countries. China and the United States alone account for relevant to consider a country’s starting point in terms of about 40 percent of global primary energy supply. The 20 energy intensity. Countries with relatively high energy inten- countries with the highest levels of energy demand togeth- sity may have a greater potential for improvement, but as er account for 80 percent of the global total, while the top seen previously, the underlying drivers of energy demand 40 countries account for 90 percent. must also be considered. For example, a country with a large mining industry or very cold climate may have high One way of capturing the global inequalities in the distribu- energy intensity, but nonetheless be very energy efficient. tion of energy demand is to calculate a pseudo-Gini coeffi- cient16 based on the cumulative percentage of global energy In reality, there is very little overlap between those countries demand accounted for by a given cumulative percentage of with the highest energy demand and the highest energy global population. The resulting Gini coefficient for energy intensity. The group of 20 countries with the highest ener- demand is 0.48, which represents a high degree of inequal- gy demand is dominated by high-income countries across ity, just slightly lower than the Gini coefficient of 0.53 for in- Europe, Asia, the Middle East, and North America. India, equality in the global distribution of GDP (figure 3.18). Indonesia, and Ukraine are the only lower-middle-income countries among the 20 largest energy consumers (figure While improvements in energy efficiency are valuable and 3.19a). The group of 20 countries with the highest energy important for all countries, achievement of the SE4ALL intensity, on the other hand, is dominated by low-income global objective for energy efficiency will depend on tar- countries from Africa and the former Soviet Union, plus a geting efforts in high-impact countries. The level of a coun- few smaller countries from Latin America and South Asia try’s impact depends in part on its overall energy demand. and Iceland, which is the only European country in the Higher energy demand translates into a greater potential group (figure 3.19b). Ukraine is the only country that is impact of a country’s efforts on the achievement of the both one of the largest energy consumers and one of the global objective. Many high-consuming countries have most energy-intensive economies. 16 The Gini coefficient is a concept most commonly used in economics to measure inequality of income distribution within a population; a value of zero represents perfect equality, and a value of one represents maximum inequality. chapter 3: energy efficiency 130 China 107 107.4 Liberia 60 59.8 USA 93 92.8 Congo, DRC 48 47.6 Russia 29 29.4 Burundi 33 33.3 India 29 29.0 Trinidad & T. 29 28.8 Japan 21 20.8 Sierra Leone 27 26.7 Germany 14 13.7 Turkmenistan 24 23.8 Brazil 11 11.1 Uzbekistan 23 23.3 France 11 11.0 Guinea 22 22.2 Canada 10 10.5 Mozambique 22 22.2 S. Korea 10 10.5 Iceland 22 21.6 Iran 9 8.7 Togo 21 20.8 Indonesia 9 8.7 Ukraine 20 19.8 UK 8 8.5 Zambia 19 18.8 Mexico 8 7.5 Uganda 18 18.2 Italy 7 7.1 Ethiopia 18 18.0 Saudi Arabia 7 7.1 Kazakhstan 18 17.6 S. Africa 6 5.7 Sao Tome & P. 16 16.3 Ukraine 6 5.5 Guyana 16 16.3 Spain 5 5.3 Bhutan 16 16.0 Australia 5 5.2 Swaziland 16 15.9 Figure 3.19a Countries with highest levels Figure 3.19b Countries with highest levels of primary energy demand, 2010 (EJ) of energy intensity PPP, 2010 (MJ/$2005) source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. A combination of relatively high energy demand and rela- tively high energy intensity defines where the highest-im- pact opportunities exist. Table 3.3 lists the countries among x 10 times the 20 largest energy consumers with the highest energy - span of energy intensities overall and within each economic sector. When intensity among the analysis is done in PPP terms, the highest-impact op- the world’s 20 most energy intensive portunities can be found in Ukraine, Russia, Saudi Arabia, economies at 20-30 megajoules per South Africa, and China. Canada, Iran, Brazil, Indonesia, dollar of GDP and the world’s least and the United States also appear when analyzing eco- energy intensive economies at 2-3 nomic sectors. megajoules per dollar of GDP All sectors Industry Agriculture Other sectors 1 Ukraine Ukraine Canada Iran 2 Russia Russia South Africa Ukraine 3 Saudi Arabia Canada Russia Saudi Arabia 4 South Africa Brazil United States Indonesia 5 China South Africa Brazil Russia table 3.3 Highest energy intensities among the 20 largest energy consumers, 2010 source: Based on World Bank World Development Indicators; IEA 2012a.. note: “Other sectors” include the transportation, residential, and service sectors. 131 Global tracking framework Fast-moving countries To reap the substantial potential for reducing energy de- mand, it will be important for countries around the world to learn from one another’s experiences and best practices. In -4.0% that sense, two groups of countries are of particular interest: is the compound those who have already achieved low levels of energy inten- annual growth sity and those who have made the most rapid progress in rate of energy intensity among those improving their energy intensity over the last decades. 20 countries making the fastest prog- ress globally 1990-2010 Most of the 20 countries that experienced the most rapid improvement in energy intensity over the 20 years between 1990 and 2010 are from the former Soviet Union and intensity in 1990 and still remain at above global average Eastern European, with annual rates of reduction ranging levels of energy intensity in 2010. While they therefore can- from 4 percent to 12 percent—several times higher than not be regarded as models for best practice, their experi- the global average of –1.3 percent (figure 3.20a). Many of ence can help to shed light on where and how to begin the these countries started from relatively high levels of energy process of accelerating energy efficiency improvements. Bosnia-Herz. 12 11.9% St. Lucia 4 3.9 Estonia 8 8.4% Botswana 4 3.8 Azerbaijan 8 7.9% Ireland 4 3.7 Armenia 7 7.3% Bahamas 4 3.7 Afghanistan 7 6.8% Switzerland 4 3.7 East Timor 6 6.3% Malta 4 3.7 Sao Tome & P. 6 5.9% Grenada 4 3.6 Belarus 5 5.3% Kiribati 4 3.6 Georgia 5 4.9% Panama 4 3.6 China 5 4.7% Albania 4 3.5 Lithuania 5 4.6% Colombia 3 3.4 Kyrgyzstan 4 4.5% Antigua & Barb. 3 3.4 Albania 4 4.4% Peru 3 3.3 Bhutan 4 4.3% Solomon Isl. 3 3.0 Laos 4 4.2% St. Vincent 3 2.9 Eritrea 4 4.1% Afghanistan 3 2.9 Romania 4 4.0% Vanuatu 3 2.7 Turkmenistan 4 4.0% Dominica 3 2.6 Moldova 4 3.9% Hong Kong 2 2.0 Uganda 4 3.9% Macau 1 1.0 Figure 3.20a Fastest-moving Countries Figure 3.20b Fastest-moving Countries with Lowest CAGR 1990–2010 in PPP terms energy intensity in 2010 in PPP terms (MJ/$2005) source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. chapter 3: energy efficiency 132 The 20 countries exhibiting the lowest energy intensity (less Kingdom, Spain, Italy, and Germany—and Japan show a than 3.9 MJ/$2005 GDP PPP) are a heterogeneous group, strong performance with low energy intensity, both over- with a strong presence of small island countries in which all and across a number of sectors (table 3.4). Curiously, energy costs tend to be exceptionally high (figure 3.20b). countries such as China, Indonesia, and Saudi Arabia— Confining attention to the least-energy-intensive countries which are among the most energy intensive of the large in PPP terms among the 20 largest energy consumers, energy consumers—exhibit relatively low energy intensity a handful of Western European countries—the United for agriculture. All sectors Industry Agriculture Other sectors 1 United Kingdom Japan Saudi Arabia Japan 2 Spain Germany Indonesia United Kingdom 3 Italy United Kingdom India Spain 4 Germany Spain Germany Italy 5 Japan Italy China Germany table 3.4 Lowest energy intensities among the 20 largest energy consumers, 2010 source: Based on World Bank World Development Indicators; IEA 2012a. note: “Other sectors” include the transportation, residential, and service sectors. Perhaps of greater interest is the interaction between a the annual rate of change is clearly evident in the chart. The country’s starting point in energy intensity and its rate of re- country that most clearly stands out is China, which started duction of energy intensity over the two decades between with one of the highest levels of energy intensity among the 1990 and 2010. In principle, those starting out with the high- largest 40 energy users; despite the huge expansion in its est levels of energy intensity had the greatest opportunities industrial sector that took place over the same period, it to reduce it. The cross-plots below attempt to depict that. also experienced the steepest decline in energy intensity The first chart plots the CAGR of energy intensity during in the last 20 years. Indeed, by 2010, China had reached a 1990–2010 against initial energy intensity in 1990; the sec- level of energy intensity comparable to that of other large, ond, against final energy intensity in 2010 (figure 3.21). middle-income, emerging economies. The negative relationship between the starting point and 133 Global tracking framework a. Energy intensity, 1990 (MJ/$2005 PPP) 3% saudi arabia iran uae thailand brazil venezuela energy intensity, 1990 0% cagr 1990-2010 10 20 30 40 50 japan s. africa russia indonesia ukraine canada germany kazakhstan uk nigeria india -3% united states uzbekistan iraq poland china -6% Hics UMIcs lMics Bubble size represents volume of primary energy consumption in 2010 b. Energy intensity, 2010 (MJ/$2005 PPP) 3% Saudi Arabia Iran UAE Thailand Brazil Venezuela energy intensity, 2010 0% cagr 1990-2010 10 20 30 40 50 Japan S. Africa Indonesia Ukraine Russia Canada Germany Kazakhstan UK India Nigeria -3% United States Uzbekistan Iraq Poland China -6% figure 3.21 Energy intensity in 1990 and 2010 vs. CAGR 1990–2010 source: Based on World Bank World Development Indicators; IEA 2012a. note: Bubble size represents the volume of primary energy supply in 2010. CAGR = compound annual growth rate; HICs = high-income countries; LMICs = lower-middle-income countries; UMICs = upper-middle-income countries. chapter 3: energy efficiency 134 The decomposition of energy trends that was undertaken trend in overall energy intensity. Such efforts partially off- globally above (recall figure 3.7) is also of interest at the set increases in energy demand due to expanded activity country level. Figure 3.22 clearly shows that among the levels and structural changes. By contrast, the reduction top 20 energy consumers, the underlying energy efficiency in Ukraine´s energy intensity is attributable to reductions effect for China and India after adjusting for activity levels in all three factors (mainly activity, and to a lesser degree and structural shifts is particularly large at 6 percent and structure and pure intensity). 4 percent respectively, and significantly higher than the 4% a. CAGR for intensity component (1990–2010) 40 2% 30 0% MJ/$2005 CAGR -2% 20 -4% 10 -6% -8% 0 a l ia kr a K a a C lia st ea A SA Ru ia ia Ja o o ny Fr ine Br in In ma K i A an n M ce Sp y zi in U ad S. ic bi l er U ss ic d pa es a U Au or a a ra ra n h fr r In a ex It n n I C a a S. d d G u Sa CAGR 1990-2010 (left) EI in 1990 (right) EI in 2010 (right) 10% b. CAGR for changes in primary energy demand and activity, 8% structure, and intensity components (1990–2010) 6% 4% CAGR 2% 0% -2% -4% -6% l a ia K a kr a C lia a st ea A SA Ru ia ia Ja o Fr ine m K iA n o ny Br in M ce n Sp y zi in S. ic U ad bi l U ic ss d Ira d es pa a U Au or a a ra ra a n h fr In a ex It n n a C a er S. d G In u Sa figure 3.22 DECOMPOSITION ANALYSIS OF ENERGY DEMAND in 1990 and 2010 vs CAGR 1990–2010 Total Energy Activity Structure Intensity source: Based on World Bank World Development Indicators; IEA 2012a. note: CAGR = compound annual growth rate; PPP = purchasing power parity. 135 Global tracking framework Yet another way of identifying countries that made partic- ularly significant progress in reducing energy consump- tion is to look at the extra energy these countries would 1,320 EJ be demanding today if their energy intensity had remained is the cumulative at 1990 levels (figure 3.23). Once again, China stands out energy savings as having achieved by far the largest reductions in energy of China due to reductions in energy consumption, with cumulative energy savings from 1990 intensity from 1990 to 2010; exceeding to 2010 exceeding cumulative energy consumption during China’s own primary energy demand that same period. Overall, actions taken in China, the Unit- over the same period. ed States, Europe, and India accounted for more than 90 percent of the nearly 2,300 EJ of energy saved globally between 1990 and 2010. Largest Energy Consumers, Cumulative 1990-2010 (EJ) Cumulative Energy Savings as a Result of reductions in energy intensity 1990-2010 (EJ) USA 1904 China 1320 China 1269 USA 369 Russia 595 India 114 Japan 435 Germany 69 India 413 UK 47 Germany 297 Poland 46 France 221 Bosnia H. 38 Canada 214 Russia 35 UK 190 Iraq 24 Brazil 168 Canada 23 Korea 155 Belarus 18 Italy 146 Romania 18 Ukraine 138 Estonia 16 Indonesia 134 Mexico 14 Mexico 131 France 14 Iran 118 Australia 13 Spain 103 Kazakhstan 12 S. Africa 101 Argentina 11 S. Arabia 99 Nigeria 11 Australia 93 Czech Rep. 10 Figure 3.23a Largest energy consumers, Figure 3.23b Largest energy savers, cumulative 1990–2010 (EJ) cumulative 1990–2010 (EJ) source: Based on World Bank World Development Indicators; IEA 2012a; UN Energy Statistics Database. Policies, targets, technological developments, and investments There are many underlying factors that explain the trends are being taken—and should be taken—to improve ener- and figures outlined in the previous section. The framework gy efficiency in each country. They also provide a guide of laid out here proposes to track them through a revision where to direct actions to address needs and reveal op- of the policies that affect energy demand, the targets that portunities in a given country. countries and regions (like the EU) give themselves, the technological developments that reduce specific energy Policies include a range of instruments—including mar- consumption, and the flow of energy efficiency investments. ket-based and financial instruments, regulations, informa- tion, and awareness—that can be voluntary or mandatory. Though the global and country-level intensity indicators Of particular relevance in 1990–2010 have been building presented may serve to track progress toward the SE4ALL codes, labeling, and minimum energy performance stan- goal, the complementary indicators described above give dards (MEPS) for appliances and motors, and fuel-efficien- a more complete picture to policy makers of what actions cy standards and fiscal incentives for vehicles. Countries chapter 3: energy efficiency 136 such as Italy and India have implemented market-based nesses in the next 20 years. Meanwhile, India, in its draft cap and trade mechanisms like the white certificates and 12th Five Year Plan, is proposing to reduce the carbon the Perform, Achieve, and Trade (PAT) scheme. Box 3.5 emissions intensity of its economy by 20−25 percent from summarizes the 25 energy efficiency policies that the IEA 2005 levels by 2020. is recommending governments to adopt. The same or- ganization is also starting the process of developing Section 4 and annex 2 provide an overview of policies and a set of governance and policy recommendations for targets for selected countries,17 while annex 3 shows the developing countries. specific energy consumption of selected energy-intensive products, both for current practice and a benchmark of the Targets can take several forms. China aims to decrease its best available practice. energy intensity by 16 percent during the period 2011–15 (its 12th Five-Year Plan). The EU, through its Energy Effi- As noted in section 1, there is no established methodology ciency Directive, mandates a reduction in primary energy to track investments in energy efficiency. One will have to consumption of 20 percent by the year 2020, while Japan be developed for the medium term. This report relies on and Brazil want to reduce electricity demand by 10 per- the work done by IEA’S WEO 2012. The results are pre- cent by 2030. Recently, the United States announced that sented in the following section. it aims to cut in half the energy wasted in homes and busi- Box 3.5 IEA’s 25 energy efficiency policy recommendations To support governments in their implementation of energy efficiency, the International Energy Agency (IEA) recommended the adoption of specific energy efficiency policy measures to the G8 summits in 2006, 2007, and 2008. The consolidated set of recommendations to these summits covers 25 fields of action across seven priority areas: cross-sectoral activity, buildings, appliances, lighting, transport, industry, and power utilities. The fields of action are outlined below. 1. The IEA recommends action on energy efficiency across sectors. In particular, the IEA calls for action on: }} Data collection and indicators }} Strategies and action plans }} Competitive energy markets, with appropriate regulation }} Private investment in energy efficiency }} Monitoring, enforcement, and evaluation 2. Buildings account for about 40 percent of energy used in most countries. To save a significant portion of this energy, the IEA recommends action on: }} Mandatory building codes and minimum energy performance requirements }} Net-zero energy consumption in buildings }} Improved energy efficiency in existing buildings }} Building energy labels or certificates }} Energy performance of building components and systems 17 Further details are provided in IEA 2012b. 137 Global tracking framework 3. Appliances and equipment represent one of the fastest-growing energy loads in most countries. The IEA recommends action on: }} Mandatory minimum energy performance standards and labels }} Test standards and measurement protocols }} Market transformation policies 4. Saving energy by adopting efficient lighting technology is very cost-effective. The IEA recommends action on: }} Phaseout of inefficient lighting products }} Energy-efficient lighting systems 5. To achieve significant savings in the transport sector, the IEA recommends action on: }} Mandatory vehicle fuel-efficiency standards }} Measures to improve vehicle fuel efficiency }} Fuel-efficiency for nonengine components }} Transport system efficiency 6. To improve energy efficiency in industry, action is needed on: }} Energy management }} High-efficiency industrial equipment and systems }} Energy efficiency services for small- and medium-sized enterprises }} Complementary policies to support industrial energy efficiency 7. Energy utilities can play an important role in promoting energy efficiency. Action is needed to promote: }} Utility end-use energy efficiency schemes chapter 3: energy efficiency 138 Section 4. The scale of the energy efficiency challenge Doubling the rate of improvement in energy intensity from been announced, even where the specific measures to im- –1.3 percent to –2.6 percent per annum in the 20 years be- plement these commitments have yet to be introduced. To tween 2010 and 2030 will present an immense challenge. illustrate the outcome of the current course in energy trends, Examining the scale of that challenge is the subject of this if unchanged, the Current Policies Scenario embodies the section. The analysis is based on the scenarios developed effects of only those government policies and measures that by WEO (2012).18 had been enacted or adopted by mid-2012. The Efficient World Scenario is based on the core assumption that all in- The New Policies Scenario is WEO’s central scenario. It vestments capable of improving energy efficiency are made takes into account broad policy commitments and plans so long as they are economically viable and any market bar- that have already been implemented to address energy- riers obstructing their realization are removed. and climate-related challenges, as well as those that have The outlook for efficiency improvements by sector and region According to the WEO 2012, the SE4ALL objective for efficiency policies continued, as assumed in the Current energy efficiency can be met only if countries implement Policies Scenario (figure 3.24). policies beyond those in the New Policies Scenario. That conclusion is highly dependent on the chosen reference Energy efficiency in end uses and in the supply sectors period. For example, doubling the performance of the last accounts for almost three-quarters of the total potential decade, when the pace of improvement in energy intensity for improving energy efficiency by 2030. The New Policies was slow, would be only a moderately ambitious goal. In Scenario projects global energy intensity (where GDP is the New Policies Scenario, energy demand is projected to measured at PPP) to decline at a rate of 2.3 percent per grow from 530 EJ in 2010 to 670 EJ in 2030, equivalent year on average over the period 2010–2030, a significant to an increase of nearly 30 percent. That is about 45 EJ, improvement on the trend seen in 1990–2010, when it was or 6 percent, lower than if only the world’s current energy –1.3 percent per year. 800 750 Efficiency in end-uses 700 Fuel and technology switching 650 Activity EJ 600 Efficiency in energy supply 550 New Policies Scenario Current Policies Scenario 500 450 2010 2020 2030 figure 3.24 Change in global primary energy demand: Current Policies Scenario and New Policies Scenario (EJ) source: IEA 2012b. note: “Activity” reflects a change in the demand for energy services due to a change in end-user prices. The incremental energy savings by 2030 of moving from the Current Policies Scenario to the New Policies Scenario amount to 45 EJ in all. Of these total energy savings, 69% are attributable to improvement in end-use efficiency, 15% to reduced activities, 14% to fuel and technology switching, and 3% to improved efficiency in energy supply. 18 Figures are also compared to those developed by the International Institute for Applied Systems Analysis (IIASA). 139 Global tracking framework When looking at the economically viable potential of energy unit of GDP . Other key elements of China’s strategy include efficiency, it becomes apparent that current and planned innovation and energy savings in 10,000 energy-intensive policies globally would utilize only a third of the economi- enterprises identified by the government, which collective- cally viable efficiency measures. From a sectoral perspec- ly make up 37 percent of the targeted savings by 2015. tive, industry utilizes most of the potential (44 percent), The centerpiece of India’s efforts to save energy is its inno- followed by transport (37 percent), power generation (21 vative PAT scheme, which aims at saving energy in large percent), and buildings (18 percent). The uptake of more energy-intensive industries by imposing mandatory energy efficient technologies is strong in industries in OECD coun- intensity targets. In addition, it allows trading of excess en- tries and China because of the introduction of MEPS and ergy savings with other participants in the form of so-called CO2 pricing, and because rising energy prices strengthen white certificates for compliance. the economic case for improving energy efficiency. In North America, the United States is currently revising its The second-most-important sector in terms of efficiency-re- MEPS for appliances and equipment, a policy initially intro- lated energy savings is transport, where several countries duced in 1978. Twenty-four states have adopted long-term are discussing the introduction of ambitious fuel-economy energy savings targets, which drive utility investments in standards, often with the goal of reducing oil imports or energy efficiency. Another focus is road transport, with the air pollution. Energy savings in the buildings sector are introduction of a 2025 fuel economy target for passenger relatively small because of high transaction costs. Most cars that would exploit much of the known (but so far un- of the savings occur in commercial buildings, where the used) technical potential of conventional vehicles. business case is often stronger and regulation is easier to apply than in residential construction. Some demand reduction also occurs in the residential sector, however, thanks to the assumed reduction in fossil-fuel subsidies 33% in some countries, including India, Russia, and parts of is the share of all the Caspian region. Depending on the region, some of the economically key measures applied in the buildings sector include man- viable energy efficiency opportunities datory energy requirements in building codes and energy that will be harnessed by current or efficiency labels for appliances. planned policies globally An increasing number of countries and regions are focus- ing on energy efficiency and strengthening their respective In Asia Oceania Japan’s Innovative Strategy for Energy policies in this area. Annex 2 tabulates current policies in and the Environment, released in 2012, includes a major selected countries. focus on energy efficiency, with a target to reduce elec- tricity demand by 10 percent in 2030 compared with 2010. Energy efficiency policies in developing Asia, North Amer- This is expected to be backed up by measures to incen- ica, Europe, and Asia Oceania account for more than tivize the introduction of more efficient technologies in the three-quarters of the reduction in global primary energy residential sector and, to a lesser extent, in industry. demand under the New Policies Scenario, compared with the Current Policies Scenario. This reflects the sheer size Because energy resources have been plentiful and prices of the energy markets of these regions and their empha- low, improving energy efficiency has historically not been a sis on energy efficiency. In Europe the EU has established key priority throughout much of the Middle East, though in a comprehensive energy efficiency policy framework with recent years this has begun to change, as fast-increasing targets for 2020, notably a 20 percent reduction in energy domestic demand is restraining oil and gas exports that demand in 2020 against their reference projection. The en- bring much-needed revenue. Saudi Arabia established an ergy efficiency directive enlists energy providers in helping energy efficiency center in 2012, and the United Arab Emir- consumers—industry and households—to increase their ates has launched a national energy efficiency and conser- investment in energy efficiency. vation program to improve efficiency in buildings. With the exception of a few countries, subsidized prices have sig- In developing Asia China has set a goal of reducing energy nificantly hampered the uptake of efficient technologies in intensity by 16 percent between 2011 and 2015. An ongo- the power sector, road transport, and buildings. In much of ing restructuring of the national economy is expected to Africa, with the exception of South Africa and a few countries bring about significant savings in energy consumption per in North Africa, the focus has been on providing access to chapter 3: energy efficiency 140 basic energy services and increasing the availability of ener- The above-mentioned policy efforts are expected to re- gy to boost economic growth rather than on energy efficien- duce primary energy demand in 2030 by almost 45 EJ. cy. Improving energy access is fundamental for economic The biggest contributions come from developing Asia (25 development, but integrating energy efficiency strategies EJ), North America (6 EJ), Europe (4 EJ), Eastern Europe/ into such programs, ideally from the outset, would make it Eurasia (3 EJ), and the Middle East (2.5 EJ) (figure 3.25). possible to widen access faster and more economically. a. Energy intensity levels 15 15 12 12 PPP 9 PPP 9 MJ/$2005, MJ/$2005, 6 6 3 3 0 0 NORTH EUROPE ASIA EASTERN EUROPE DEVELOPING SOUTH AFRICA MIDDLE EAST NORTH AMERICA EUROPE ASIA OCEANIA EASTERN EUROPE DEVELOPING EURASIA ASIA SOUTH AMERICA AFRICA MIDDLE EAST AMERICA OCEANIA EURASIA ASIA AMERICA 2010 2030 2010 2030 b. Primary energy savings in the New Policies Scenario compared with Current Policies Scenario in 2030 0 0 -6 -6 -12 -12 EJ EJ -18 -18 -24 -24 -30 -30 NORTH EUROPE ASIA EASTERN EUROPE DEVELOPING SOUTH AFRICA MIDDLE EAST NORTH AMERICA EUROPE ASIA OCEANIA EASTERN EUROPE DEVELOPING EURASIA ASIA SOUTH AMERICA AFRICA MIDDLE EAST AMERICA OCEANIA EURASIA ASIA AMERICA figure 3.25 Results of the New Policies Scenario source: Based on data/analysis taken from IEA (2012b). 141 Global tracking framework Energy efficiency investments needed to achieve the New Policies Scenario The current status of energy efficiency investments is diffi- To achieve the savings from energy efficiency laid out in the cult to quantify, as investments in energy efficiency are sel- New Policies Scenario, cumulative additional investments dom tracked systematically and there is no comprehensive of $2.3 trillion are needed through 2030 (or $128 billion estimate of current global investment in energy efficiency. per year, on average, above current levels of investment The lack of an estimate is due to the fact that energy ef- in transport, residential, industry, and services) (figure ficiency investments are made by a multitude of agents, 3.26).19 Investment in transport increases by $0.9 trillion households, and firms, often using their own funds. More- (almost 40 percent of the total additional investment for all over, there is no standard definition of what constitutes sectors worldwide), largely to improve fuel economy. Res- an energy efficiency investment, and while investments in idential and service-sector buildings account for another energy efficiency in buildings and industry are tracked in $1.1 trillion from 2012 to 2030, in the form of investments many countries, data for the transport and power sectors in retrofits, insulation, and thermal efficiency, as well as for are more difficult to obtain. Based on a country-by-coun- electrical equipment (appliances and lighting). Additional try survey, however, it is estimated that current global in- investment in industry amounts to $340 billion between vestment in projects aimed principally at improving energy 2012 and 2030, about two-thirds of which is to improve the efficiency amounted to about $180 billion in 2011—signifi- efficiency of heat systems, where much unrealized poten- cantly lower than the investment in expanding or maintain- tial exists. The remainder of the investment is in electrical ing the fossil-fuel supply (nearly $600 billion in the same equipment, mostly industrial motors. year). About two-thirds of the estimated investment in en- ergy efficiency in 2011 was undertaken in OECD countries. 300 240 Billion US Dollars (2011) 180 120 60 0 TRANSPORT RESIDENTIAL INDUSTRY SERVICES TRANSPORT RESIDENTIAL INDUSTRY SERVICES 2020 2030 Energy efficiency investment Additional energy efficiency investment in New in Current Policies Scenario Policies Scenario over Current Policies Scenario figure 3.26 Average annual increase in energy efficiency investment: New Policies Scenario versus Current Policies Scenario source: Based on data/analysis taken from IEA (2012b). 19 Energy efficiency investment denotes spending on a physical good or service that results in energy savings, compared with the energy that would otherwise have been demanded. This section focuses on energy efficiency investment in end-use sectors—transport, residential, industry, and services—as this is where most of the savings and additional investment occur. Through 2030, additional investment in the power sector in more efficient plants and greater use of renewable energy is more than offset by the reduced investment required for new power plants and transmission and distribution (T&D) lines resulting from lower electricity demand, leading to a net decrease of $0.3 trillion, or 2.4 percent of the total investment requirements in this sector. chapter 3: energy efficiency 142 The IEA Efficient World Scenario The New Policies Scenario does not fully exploit the po- In the Efficient World Scenario, oil demand peaks at 91 mil- tential for cost-effective energy efficiency improvements lion barrels per day (mb/d) before 2020 and then declines or achieve the SE4ALL energy efficiency objective. Under to 88.7 mb/d in 2030. Global coal demand also peaks be- the Efficient World Scenario, however, it is possible to im- fore 2020, at around 5,400 million tons of coal equivalent prove energy intensity by 2.8 percent per year, on average, (Mtce), before dropping to about 4,800 Mtce in 2030—19 through 2030, compared with the annual rate of –1.3 per- percent lower than under the New Policies Scenario. Unlike cent achieved from 1990 to 2010. The central assumption for the other fossil fuels, global demand for natural gas still of the Efficient World Scenario is that policies are put in increases under the Efficient World Scenario, as it remains place to allow the market to realize the full potential of all an important fuel in the power, industry, and buildings economically viable energy efficiency measures. Projec- sectors. Total demand reaches 3,700 billion cubic metres tions for energy savings under the Efficient World Scenar- (bcm) in 2020 and almost 4,100 bcm in 2030. io, compared with the Current Policies Scenario and New Policies Scenario, are presented in figure 3.27. 800 750 Efficiency in end-uses 700 Fuel and technology switching 650 Activity EJ Efficiency in energy supply 600 Current Policies Scenario 550 New Policies Scenario 500 Efficient World Scenario 450 2010 2020 2030 figure 3.27 Change in global primary energy demand: Efficient World Scenario versus other scenarios (EJ) source: IEA (2012B) Note: The incremental energy savings by 2030 of moving from the NEW Policies Scenario to the Efficient World Scenario amount to 76 EJ in all. Of these total energy savings, 80% are attributable to improvement in end-use efficiency, 10% to fuel and technology switching, 6% to improved efficiency in energy supply, and 4% to reduced activities. 143 Global tracking framework Two steps were taken to calculate the economic po- -specific considerations (see also figure 10.2 in IEA tential of the Efficient World Scenario, which varies by 2012b). In countries with carbon pricing, these prices are sector and region. lower than in the New Policies Scenario, as energy efficien- cy measures are assumed to contribute to targeted emis- First, technical potentials were determined, identifying key sions reductions. In the Efficient World Scenario, no addi- technologies and measures to improve energy efficiency tional carbon pricing beyond the New Policies Scenario is by sector. This process involved analysis of a substantial assumed. Fossil-fuel subsidies are phased out by 2035 at amount of data and information from varied sources per- the latest in all regions except the Middle East, where they taining to a variety of subsectors and technologies. The are reduced to a maximum rate of 20 percent by 2035. Efficient World Scenario assumes no major or unexpect- Additional efforts toward energy efficiency lead to a lower ed technological breakthroughs. Nor does it assume the energy demand and thereby to lower international energy application of holistic concepts such as prioritizing ener- prices. This again causes a rebound in energy consump- gy efficiency at all levels of urban planning or changes in tion, offsetting roughly 9 percent of the energy savings. consumer behavior (except where induced by lower ener- gy prices). The scenario is, rather, based on a bottom-up On a regional level, the implemented energy efficiency analysis of currently available technologies and practices, measures lead to different conclusions. While the largest and considers incremental changes in the level of energy relative savings potential in terms of energy intensity ex- efficiency deployed. ist in developing Asia, Eastern Europe/Eurasia, and North America, it is developing Asia, North America, and Europe A second step identified those energy efficiency measures that save the most primary energy by 2030 under the Effi- that are economically viable. The criterion adopted was the cient World Scenario (figure 3.28). amount of time an investor might reasonably be willing to wait to recover the cost of an energy efficiency investment The energy savings in the Efficient World Scenario are (or the additional cost, where appropriate) through the achieved by a raft of policy measures across different end- value of undiscounted fuel savings. Acceptable payback use energy demand sectors,20 leading to a significant im- periods were calculated as averages over the 2012–2035 provement in energy intensity (table 3.5). projection period and take account of regional and sector 20 For more detail on policy measures in each sector see chapter 11 in IEA (2012b). chapter 3: energy efficiency 144 a. Energy intensity levels 14 12 10 MJ/$2005, PPP 8 6 4 2 0 NORTH AMERICA EUROPE ASIA OCEANIA EASTERN EUROPE DEVELOPING SOUTH AMERICA AFRICA MIDDLE EAST EURASIA ASIA 2010 2030 b. Primary energy savings in the New Policies Scenario compared with Current Policies Scenario in 2030 0 -7 -14 EJ -21 -28 -35 NORTH AMERICA EUROPE ASIA OCEANIA EASTERN EUROPE DEVELOPING SOUTH AMERICA AFRICA MIDDLE EAST EURASIA ASIA figure 3.28 Changes in energy intensity and primary energy savings under the Efficient World Scenario, by region source: Based on data/analysis taken from IEA (2012b). 145 Global tracking framework Eastern North Asia World Europe Europe/ America Oceania Eurasia 2010 2030 2010 2030 2010 2030 2010 2030 2010 2030 Energy intensity 7.0 3.9 6.2 3.5 4.6 2.8 5.3 3.5 12.0 6.5 (MJ/dollar, PPP) Energy demand per capita 77.9 74.1 242.4 191.3 137.3 115.1 183.4 172.9 141.9 152.8 (GJ/capita) Residential energy intensity 100 75 100 73 100 74 100 73 100 82 (2010 = 100) Service energy intensity 100 62 100 61 100 72 100 69 100 52 (2010 = 100) Fuel consumption, new 7.6 4.1 8.7 4.3 6.2 3.6 6.8 3.7 7.1 3.8 PLDVs, test cycle (l/100 km) Fuel consumption, new heavy trucks on-road 36 22 38 21 31 19 27 16 33 19 (l/100 km) Energy intensity of industries 4.3 2.6 3.8 2.6 2.9 2.2 3.3 2.6 6.2 3.6 (TJ/$1,000 VA industry) Fossil-fuel power plant 43% 48% 42% 49% 51% 59% 43% 50% 60% 68% efficiency (%) Developing South Middle Africa Asia America East 2010 2030 2010 2030 2010 2030 2010 2030 Energy intensity 8.3 3.8 5.2 3.4 9.4 5.3 9.9 5.9 (MJ/dollar, PPP) Energy demand per capita 46.1 55.7 54.4 61.1 28.1 22.6 131.5 119.7 (GJ/capita) Residential energy intensity 100 73 100 93 100 70 100 81 (2010 = 100) Service energy intensity 100 48 100 72 100 64 100 58 (2010 = 100) Fuel consumption, new 7.7 4.0 8.1 4.5 7.4 4.4 11.7 6.4 PLDVs, test cycle (l/100 km) Fuel consumption, new heavy trucks on-road 40 24 36 21 41 25 40 25 (l/100 km) Energy intensity of industries (TJ/$1,000 VA 5.6 2.7 4.1 2.9 3.2 1.9 3.5 2.2 industry) Fossil-fuel power plant 38% 43% 39% 47% 37% 43% 33% 42% efficiency (%) table 3.5 Key energy efficiency indicators for selected regions source: = IEA. note: For the definition of regions and additional detail on indicators, see annex 2. GJ = gigajoules; MJ = megajoules; PPP = purchasing power parity; PLDV = passenger light duty vehicle; TJ = terajoules; VA = value added. chapter 3: energy efficiency 146 Why do we want to achieve the Efficient World Scenario? The Efficient World Scenario requires cumulative addi- lion, freeing up economic resources and stimulating ad- tional investments in energy efficiency of $8 trillion over ditional demand for efficient goods and services. Achiev- the investments already realized under the New Policies ing the Efficient World Scenario would give a $11.4 trillion Scenario from 2012 to 2030 (figure 3.29). The additional boost to the global economy from 2012 to 2030. Countries investment level for the Efficient World Scenario is about that have a competitive advantage in producing less en- three-and-a-half times higher than for the New Policies ergy-intensive goods would see their economy grow the Scenario. The majority of the additional investments under most. This is the case for China, India, the EU, and the the Efficient World Scenario accrue in the transport sector United States. The particularly high growth in China and ($3.0 trillion). The remaining investments are split among India is stimulated both by domestic demand and exports. the residential sector ($2.7 trillion), services sector ($1.4 trillion), and industry ($1.1 trillion). $400 billion Achieving the Efficient World Scenario brings many region- is the annual al and global benefits, including fuel savings, improved investment energy security, health improvements, environmental ben- requirement to meet SE4ALL objective efits, and reduced energy import bills. For example, the for energy efficiency; around triple required investment of $8.2 trillion in energy efficiency is historical levels more than offset by fuel expenditure savings of $10.6 tril- 500 400 Billion US Dollars (2011) 300 200 100 0 TRANSPORT RESIDENTIAL INDUSTRY SERVICES TRANSPORT RESIDENTIAL INDUSTRY SERVICES 2020 2030 ADDITIONAL ENERGY EFFICIENCY INVESTMENT ADDITIONAL ENERGY EFFICIENCY INVESTMENT IN NEW POLICIES SCENARIO OVER CURRENT IN EFFICIENT WORLD SCENARIO OVER NEW POLICIES SCENARIO POLICIES SCENARIO figure 3.29 Average annual increase in energy efficiency investment: Efficient World Scenario versus New Policies Scenario source: Based on data/analysis taken from IEA (2012b). 147 Global tracking framework From the perspective of mitigating climate change, a rapid or is under construction emits, in normal use, about 80 per- and widespread adoption of energy-efficient technologies cent of the cumulative emissions allowed over the period to can reduce CO2 emissions in the short term. Energy-relat- 2035 in a 2°C world. If infrastructure investments continue ed CO2 emissions under the Efficient World Scenario peak in line with the New Policies Scenario and are operated as before 2020 at 32.4 gigatons (Gt) before beginning a steady projected in that scenario, infrastructure in existence in 2017 decline to 31.0 Gt in 2030. Owing to the faster development would emit 100 percent of the allowed cumulative emis- of energy-efficient technologies, emissions in 2030 are 5.2 sions. Energy efficiency can delay by five years (to 2022) Gt lower than under the New Policies Scenario. the complete locking in of all CO2 emissions allowed in a 2°C world. This additional time is crucial in the immediate An analysis of the global capital stock in place in all energy future, because a new climate agreement is expected to be sectors shows that the infrastructure that either exists today reached by 2015 and to take effect by 2020. Box 3.6 Overview of the energy intensity projections of the Global Energy Assessment The figures below present the main energy intensity projections from the Global Energy Assessment (GEA) de- veloped by the International Institute for Applied Systems Analysis (IIASA). The bases and regional groupings on which the IIASA scenarios are constructed are different from those of the International Energy Agency (IEA). It is outside the scope of this report to make them compatible. The baseline scenario is consistent with the annual rate of improvement of energy intensity observed over the last 20 years (–0.8 percent). The SE4ALL scenario—a scenario that meets the access, renewables, and effi- ciency targets—assumes an annual improvement in energy intensity of –2.7 percent, which is actually greater than the needed rate of improvement of –1.5 percent if measured at market exchange rate (MER). The six GEA “pathways”—each of which assumes the future availability of various key technologies—do not differ much in actual energy intensity or in the rate of improvement. All meet the SE4ALL energy efficiency target and assume faster energy intensity improvement as compared to SE4ALL. chapter 3: energy efficiency 148 Projections of global primary energy intensity by scenario, 2010 vs. 2030 (MJ/$2005), MER 9.45 8.08 6.39 5.48 4.97 5.10 5.09 5.09 5.06 4.93 4.93 2010 Baseline SE4ALL GEA1 GEA2 GEA3 GEA4 GEA5 GEA6 Min (2C) Max (2C) Projected annual rate of improvement in global primary energy intensity by 2030, by scenario (MER) Baseline SE4ALL GEA1 GEA2 GEA3 GEA4 GEA5 GEA6 Min (2C) Max (2C) -0.8% -1.9% -2.7% -3.0% -3.0% -3.1% -3.1% -3.2% -3.2% -3.2% Looking at the world’s regions, substantial reductions in the absolute level of energy intensity are expected from the former Soviet Union, centrally planned Asia (including China), and South Asia. These regions are projected to decrease their current energy intensity levels by more than 60 percent and to meet the SE4ALL target—reflecting that the SE4ALL target is not that far off from the business-as-usual, or IIASA’s baseline, scenario in these regions. By contrast, an effort far beyond that of the baseline scenario would be needed from those regions that have already achieved low levels of energy intensity, such as North America and Western Europe. Substantial effort would also be required in the former Soviet Union and Middle East. Some improvements are expected in Afri- ca, but they do not go far beyond the business-as-usual projection. 149 Global tracking framework Primary energy intensity: 2010 versus 2030 baseline and SE4ALL scenarios (MJ/$2005), MER 35 28 MJ/ $2005, MER 21 14 7 0 WEU PAO NAM World LAM EEU PAS MEA AFR CPA SAS FSU 2010 BASELINE SE4ALL Primary energy intensity annual rate of improvement: Baseline versus SE4ALL scenario (CAGR 2010–30), MER NAM WEU PAO MEA World AFR EEU LAM FSU PAS SAS CPA 0% -1% -2% -3% -4% -5% -6% NAM WEU PAO MEA World AFR EEU LAM FSU PAS SAS CPA BASELINE SE4ALL source: International Institute for Applied Systems Analysis (IIASA). note: Primary energy presented on the charts above is measured using direct equivalent method as opposed to the physical content method used in the rest of the report. AFR = Sub-Saharan Africa; CPA = Centrally planned Asia and China; EEU = Central and Eastern Europe; FSU = Former Soviet Union; LAM = Latin America and Caribbean; MEA = Middle East and North Africa; NAM = North America; PAO = Pacific OECD; PAS = Other Pacific Asia SAS = South Asia; WEU = Western Europe. chapter 3: energy efficiency 150 Overcoming the barriers The energy savings identified in the Efficient World Scenar- needed to address the various principal–agent barriers io will not be realized if market actors are left to their own and other split incentives where investors may not directly devices. For that reason, the Efficient World Scenario rests reap the return on investments to energy efficiency, includ- on a raft of policy measures taken to overcome market ing short asset-ownership periods vis-à-vis payback peri- barriers. Various countries have successfully implemented ods for building retrofits (Hilke and Ryan 2012). Perception policies that were effective in saving energy. It is important of financial risk is another barrier to energy efficiency in- to learn from those experiences and the approaches used. vestment and can be overcome by lowering the risk premi- ums applied to lending for energy efficiency projects and Because the nature of the barriers to energy efficiency dif- by providing risk guarantees, credit lines, mechanisms to fers by the end use and economy considered, a portfolio standardize and bundle project types, and awareness and of measures is needed. But, whatever the specifics of the capacity-building efforts among the finance community. sector or economy being addressed, certain key principles need to be adhered to. Make it standard. Energy efficiency needs to be standard- ized if it is to endure. Once a high-efficiency technology or Make it visible. The energy performance of each energy service solution has been widely adopted, there is rarely a end-use and service needs to be made visible to the mar- step backwards: the less-efficient technology or approach ket. Governments need to ensure that the energy perfor- is rapidly forgotten, and the cost differentials for higher-ef- mance of all major energy services and end-uses is mea- ficiency technologies decline substantially as adoption sured and reported to consumers, clients, and statistical rates increase. Under the Efficient World Scenario, a mix agencies in a consistent, accessible, timely, and reliable of regulations is deployed to prohibit the least-efficient ap- manner. Increased visibility lowers information costs, an proaches and to impose MEPS for equipment, vehicles, important element of transaction costs. buildings, and power plants. Make it a priority. The profile and importance of energy ef- Make it real. Monitoring, verification, and enforcement ac- ficiency needs to be raised. Visibility stimulates market ac- tivities are needed to verify claimed energy efficiencies. tors to consider energy efficiency, but is often not enough Without such efforts, experience has shown that savings to motivate them to demand it. Governments need to take will turn out to be less than expected, undermining policy additional steps to ensure that the full value of higher en- objectives. Under the Efficient World Scenario, there is a ergy efficiency is made clear to individuals and to society substantial increase in the scale of such activities. at large and integrated into decision-making processes in government, industry, and society. Make it realizable. Achieving the supply and widespread adoption of energy-efficient goods and services depends Make it affordable. It is essential to identify and support on an adequate body of skilled practitioners in government business models, financing vehicles, and incentives that and industry and requires improved energy efficiency gov- provide those who invest in energy efficiency an appropri- ernance, including legislative frameworks, funding mecha- ate share of the rewards that flow from efficiency improve- nisms, institutional arrangements, and coordination bodies ments. Tailored economic instruments such as tax policies, that work together to support the implementation of energy loans, grants, trading schemes, white certificates, public efficiency strategies, policies, and programs (IEA 2010). procurement, and investment in R&D or infrastructure are 151 Global tracking framework References Ang, B. W., and K.-H. Choi. 1997. “Decomposition of Aggregate Energy and Gas Emission Intensities for Industry: A Refined Divisia Index Method.” The Energy Journal 18: 59–73. Baksi, S., and C. Green. 2007. “Calculating Economy-Wide Energy Intensity Decline Rate: The Role of Sectoral Output and Energy Shares.” Energy Policy 35: 6457–66. Boyd, G.A., D.A. Hanson, and T. Sterner. 1988. “Decomposition of Changes in Energy Intensity: A Comparison of the Divisia Index and Other Methods.” Energy Economics 10 (October): 309–12. Hilke, A., and L. Ryan. 2012. Mobilising Investment in Energy Efficiency. OECD/IEA: Paris. Available at http://www.iea.org/publications/insights/Mobilising_investment_EE_FINAL.pdf. IEA (International Energy Agency). 1997. The Link between Energy and Human Activity. International Energy Agency, Paris, France. ———. 2010. Energy Efficiency Governance. OECD: Paris. Available at http://www.iea.org/publications/freepublications/publication/eeg-1.pdf. ———. 2012a. IEA World Energy Statistics and Balances. Paris. ———. 2012b. World Energy Outlook. OECD: Paris. IMF (International Monetary Fund). 2012. WEO2012 Statistical Appendix, http://www.imf.org/external/pubs/ft/weo/2012/01/pdf/statapp.pdf. IIASA (International Institute for Applied Systems Analysis). 2012. Global Energy Assessment—Toward a Sustainable Future, Cambridge University Press, Cambridge, UK and New York, NY, USA and IIASA, Laxenburg, Austria. Martin, N., E. Worrell, L. Schipper, and K. Blok. 1995. Workshop Proceedings: International Comparisons of Energy Efficiency. Conference Presentation, Utrecht University: Utrecht, The Netherlands. Phylipsen, G. 2010. Energy Efficiency Indicators: Best Practice and Potential Use in Developing Country Policy Making. World Bank. UN (United Nations). 2012. Millennium Development Goals Indicators: PPP conversion factor, local currency unit to international dollar series. http://mdgs.un.org/unsd/mdg/Metadata.aspx?IndicatorId=0&SeriesId=699 UNIDO. 2010. Global Industrial Energy Efficiency Benchmarking—An Energy Policy Tool Working Paper. United Nations Industrial Development Organization, Vienna, Austria. chapter 3: energy efficiency 152 Annex 1: Proposed energy efficiency indicators for the medium term Challenges Medium associated with Rationale for Energy intensity -term and energy efficiency increasing the indicator preferred energy Data Sector monitoring, using scope of proposed in this indicators to sources the proposed monitoring and baseline report track energy energy intensity data collection efficiency indicators Residential Included under other Does not permit track- MJ/floor area Floor area is a better Activity data such as sectors ing of the sector, as it MJ/number of house- proxy to identify floor area and number also includes trans- holds changes in the resi- of households can be port, residential, and MJ/total dential sector. obtained from existing others. population national census. MJ/end use (for ex- Household number ample space heating, can be informative, but Floor area measure- cooking, cooling, size of each household ments should follow appliances) may also be relevant. UN census guidelines. End-use energy National household consumption such surveys also track total as for space heating, floor area on a more cooling, and cooking frequent basis. These needs is of importance surveys are essential to the residential sector to capture physical main activities. building and equip- ment characteristics and total annual ener- gy consumption. Energy consumption by end use can be estimated by com- bining output from household surveys, metering/measuring of household activity, and modeling techniques. The final breakdown needs to be validated against total residential energy consumption from energy balances. 153 Global tracking framework Challenges associated with Medium-term and Rationale for Energy intensity energy efficiency preferred energy increasing the indicator Data Sector monitoring, using indicators to scope of proposed in this sources the proposed track energy monitoring and baseline report energy intensity efficiency data collection indicators Services MJ/service sector GDP There has been little MJ/floor area Total floor area is one Services sector floor evidence that the two of the key physical vari- area can be derived MJ/floor area by type of variables are directly ables essential to track from a number of service linked (that is, correlated). overall improvement sources such as national in the service sector building surveys and Because of data disag- efficiency. business tax offices. gregation limitations, services value added Long-term monitoring Some monitoring may includes residential, of the service sector be essential to capture transport, and others. by type of service (or the behavioral aspect of Therefore, the indicator type of building where energy consumption in combines sectors with service is provided) buildings. very different intensities such as government Finally, bottom-up and drivers. and public buildings, modeling and estima- education, hospitals, tion techniques will be Using physical parame- lodging, and so on. needed as the sector is ters is a better indicator of energy efficiency In some sectors such highly heterogeneous improvements. as hospitals, number of and some assumptions hospital beds may be need to be made. a better indicator of the activity in the building. Challenge will remain as some countries may choose to cut off sur- veying of small entities and only focus on large institutions. Industry Total industry MJ/GDP The variable is highly Industry subsector MJ/ Where possible use The existing IEA energy aggregated, missing value added of industry physical output in the balances structure the information at subsector GDP following sectors: provides industry subsector level. aluminum, cement, iron subsector information MJ/output volume and steel, pulp and according to the UN Literature points to poor paper, fertilizers, and ISIC code definitions. correlation in monitor- others. National energy ing energy efficiency improvements industry consumption industry based on value added surveys. alone. Physical activity data exist in international organizations. Bottom-up modeling validated at the aggregate level against energy balances. chapter 3: energy efficiency 154 Challenges associated with Medium-term and Rationale for Energy intensity energy efficiency preferred energy increasing the indicator Data Sector monitoring, using indicators to scope of proposed in this sources the proposed track energy monitoring and baseline report energy intensity efficiency data collection indicators Transport Included under other Does not permit track- MJ/vehicle-kilometers The need to split National mobility sectors ing of the sector, as it passenger and freight surveys. MJ/passenger- also includes services, transport energy Tax offices where kilometers residential, and others. consumption in MJ. actively used vehicles MJ/freight kilometers Currently there are no are registered with data MJ/total passenger publicly available global such as vehicle vehicles data that properly split kilometers and age of MJ/total freight passenger and freight vehicle. vehicles transportation energy Monitoring using the consumption. latest GPS data logger Within domestic bound- technology. aries, the IEA energy Modeling to estimate balances reports these mode split and average data in aggregate form fuel consumption of by road, rail, marine, existing vehicle stock by and domestic aviation. mode type. Age of vehicles would Bottom-up modeling be another important validated at the parameter to capture, aggregate level especially in countries against energy where used vehicles balances. are imported. source: Authors. note: GDP = gross domestic product; GPS = global positioning system; IEA = International Energy Agency; ISIC = International Standard Industrial Classification; MJ = megajoule. 155 Global tracking framework Annex 2: Overview of energy efficiency policies and targets by country and sector EU member New United Australia Canada Japan Korea states Zealand States Cross-sectoral Energy Clean Energy Moving Forward National Energy Innovative The National New Zealand Target: Cut in efficiency Future Plan on Energy Efficiency Action Energy Savings Energy Master Energy half the energy strategy Efficiency in Plans Plan September Plan and Energy Efficiency wasted in homes National Strategy or target Canada: 2012 Use Rationaliza- and and businesses on Energy Effi- Achieving tion Master Plan Conservation over the next 20 ciency (NSEE) Results to 2020 Strategy years. and Beyond Energy efficiency action plans at state level. Buildings and appliances Building Mandatory for Voluntary Mandatory for Voluntary Mandatory for Mandatory for Mandatory for energy new and existing national Energy new and existing guidelines. residential new residential new residential codes residential and Code for new buildings when buildings and and commercial and commercial commercial and existing renovation is commercial buildings. buildings, and buildings. Codes residential and undertaken. buildings major renova- updated in 2011. commercial 500–300 m². tions, with some buildings, Codes updated exceptions. published in in 2010. Variation of 2011 for stringency adoption by across states. subnational regulators. Energy National frame- Mandatory Energy Voluntary build- Labeling system Eight products Mandatory labeling work replacing EnergyGuide performance ing labeling expanded from covered. EnergyGuide seven state and label for eight certificates program and 26 products in labeling for most major house- territory legisla- mandatory for all Energy Star for 2011 to 35 household tive frameworks. hold appliances new buildings. office products in 2012. appliances. and light bulbs. Labeling in place equipment. Voluntary energy Seven appliances International for household star labeling for covered by the ENERGY STAR appliances. over 60 mandatory symbol categories of Energy Rating promoted in appliances, Labeling Canada. equipment, and Scheme. buildings. Mandatory disclosure of commercial building energy efficiency. chapter 3: energy efficiency 156 EU member New United Australia Canada Japan Korea states Zealand States Buildings and appliances (continued) Appliance, 20 products 47 products 15 product Top Runner: 26 products 16 products 45 products equipment covered. covered. groups covered 23 products covered. covered. covered. and by EcoDesign covered. lighting Directive. MEPS Transport Fuel- LDV: Implemen- LDV: published LDV: 130 g/CO2 LDV: 16.8 km/l LDV: 17 km/l by None LDV: 34.1 mpg efficiency tation from 2015. October 2010 per km by 2015.* (45.1 mpg). 2015; 140 g/CO2 by 2016 (6.90 standards for model years per km by 2015. l/100 km); large HDV: Included HDV: under HDV: starting MY 2011–2016. increases by in carbon price consideration. 2015. HDV: starting 2025. mechanism from HDV: under after 2015 *Switzerland 2014. consideration. HDV: starting MY is also imple- 2014. menting these standards. Fuel- LDV: Yes LDV: EnerGuide LDV: Yes LDV: Yes LDV: Yes LDV: Yes LDV: Yes efficiency Label HDV: None HDV: None HDV: Yes HDV: None HDV: None HDV: None labeling HDV: None Fiscal None Several provinces Most countries Registration tax- None None Tax at federal incentives and territories align vehicle es according to level; 20 states for new offer incentives taxes with CO2 CO2 emissions plus DC offer tax efficient or rebates for emissions. and fuel econ- incentives, vehicles the purchase of omy. rebates, or fuel-efficient voucher vehicles, programs for including EVs. advanced vehicles (EVs, PHEVs, HEVs, and/or fuel cell vehicles) 157 Global tracking framework EU member New United Australia Canada Japan Korea states Zealand States Industry Energy Energy Efficiency ecoEnergy Voluntary Energy managers Voluntary Energy Energy Voluntary energy man- Opportunities Efficiency for agreements in required for large Saving through management management agement (EEO) Program Industry place in Belgium industries. Partnership diagnostic tools, certification programs mandatory for program, which (Flanders), program. training for program, corporations supports the Denmark, energy implementation using more than early implemen- Finland, Ireland, managers and of ISO 50001. 0.5 PJ of energy tation of the Netherlands, other support. Technical per year. Expan- new ISO 50001 Sweden. support sion of program Energy Manage- programs in announced. ment Systems place, especially standard. for SMEs. MEPS for IE2 for three- Must meet or IE3 (premium Adding three- IE2 (high MEPS are in IE3 (premium- electric phase industrial exceed the efficiency). phase induction efficiency) three- place at level II efficiency) MEPS motors electric motors. efficiencies MEPS to Top phase electric Standards. for three-phase MEPS for three- outlined in either Runner program. motors. Investigation induction motors. phase induction table 2 or table under way to motors <7.5kW 3 of CAN/CSA advance to level by 2015; all IE3 C390-10. III. (IE2+Variable Speed Drive) in 2017. chapter 3: energy efficiency 158 South Russia China India Brazil Mexico Africa Cross-sectoral 2009 Federal 12th Five Year 11th Five-Year 2011 National Energy 2008 Law on Law Plan (2011–2015): plan Energy Efficiency Sustainable target to reduce Strategy of the Energy Use No. 261-FZ on (2007–2012): Efficiency Plan: energy intensity Republic of Goal: reduce energy saving target to improve reduce projected by 16 percent by South Africa: electricity and improving energy efficiency power consump- 2015. sets a national demand 12 energy by 20 percent. tion by 10 percent target of percent by efficiency; An “Approach by 2030. energy 2020 and 18 reduce energy to the 12th Five- efficiency percent by intensity by Year” has been improvement 2030. 40 percent by published. of 12 percent 2020. by 2015. Buildings and appliances Building Mandatory Mandatory codes Energy Conser- Voluntary National National energy building codes for all new large vation Building guidelines in Building Thermal codes (but not yet fully residential build- Code (2007), place. Regulation Insulation implemented). ings in big cities. with voluntary with voluntary and Lighting guidelines for guidelines for Standards for commercial new buildings. commercial and residential buildings. buildings. Energy Information on Labeling Voluntary Star Voluntary for Voluntary Green labeling energy mandatory for Ratings for office residential and Green Star Building efficiency new, large, buildings. commercial South Africa Labeling classes for commercial and buildings. label. System. appliances governmental required since buildings in big January 2011. cities. Appli- Phaseout of 46 products Mandatory S&L 13 products Standards Standards ance, incandescent covered by for room air covered by under for freezers, equip- >100 watt labeling schemes. conditioners voluntary labels. development refrigerators, ment and bulbs. and refrigerators, for lighting; washing lighting voluntary for 5 planned for air machines, MEPS other products. conditioners, and fluores- solar water cent lamps; heaters, heat 186 products pumps, and covered by shower heads. mandatory labels. 159 Global tracking framework South Russia China India Brazil Mexico Africa Transport Fuel- None PLDV: 6.9l/100 km LDV: Under None None LDV: Average efficiency by 2015, development new car fleet standards 5.0 l/100 km by average fuel HDV: None 2020; trucks: economy of proposed MY 14.9 km/l (35 2015. mpg) in 2016 HDV: None HDV: None Fuel- None LDV: Yes None None None None efficiency HDV: None labeling Fiscal None Acquisition tax Registration None None None incentives based on taxes by vehicle for new and engine size, efficient sales incentives vehicles for advanced vehicles. Industry Energy Periodic energy Top 10,000 PAT in force None. Voluntary man- audits required program setting since 2011. “Energy agement for some energy savings Audits mandated Efficiency programs industries. targets by 2015 for for designated and Energy the largest 10,000 consumers. Demand industrial consum- Management ers. Flagship Programme” involving 24 major indus- trial energy users and associations. MEPs for None High-efficiency None High-efficiency None Premium electric (IE2) MEPs for (IE2) MEPs for efficiency (IE3) motors three-phase three-phase for output induction motors induction motors power ratings in place. in place. of 0.75−150 kW source: IEA. note: CAN/CSA = Canadian Standards Association; CO2 = carbon dioxide; EV = electric vehicle; HDV = heavy-duty vehi- cle; HEV = hybrid-electric vehicle; IE2 = high-efficiency motor; IE3 = premium efficiency motor; MEPS = minimum energy performance standards; ISO = International Organization for Standardization; kW = kilowatts; LDV = light-duty vehi- cle; mpg = miles per gallon; PAT = Perform, Achieve, Trade; PHEVs = plug-in hybrid electric vehicle; PJ = petajoule; PLDV = passenger light-duty vehicle; S&L = standards and labeling; SME = small and medium enterprise. chapter 3: energy efficiency 160 Annex 3: Specific energy consumption of energy-intensive products The tables below list the status of energy consumption in major industries, along with the existing best practices and their savings potential. Sector or Current practice Best available practice benchmarks process Iron and steel 90 percent of the production of crude Practical minimum energy consumption for a blast steel is in the range of 14–30 GJ final furnace is 10.4 GJ/t iron. energy/ton. Includes total energy con- sumption for steel production—from coke making to furnace firing to steel finishing—and refers to crude steel production. Electricity consumption is not corrected for the efficiency of power generation. Cement Dry-process kilns thermal energy consumption: 2.9–3.3 GJ/t clinker. Dry-process kilns electricity consumption: 95–100 kWh/t cement. Chemicals and Olefin production from steam cracking: petrochemicals 12 GJ/t olefin (excluding feedstocks). Ammonia production from natural gas: 11 GJ/t ammonia (excluding feedstocks). Methanol production from natural gas: 9 GJ/t methanol (excluding feedstocks). Aluminum Total fuel and electricity consumption of Bayer process: 9.5–10 GJ/t alumina. The current best practice of Hall–Heroult electrolysis cells (using currents of 300–315 kA) is estimated at 12.9–13 MWh/t aluminum. Pulp and paper Large modern chemical pulp mills are Mechanical pulping 7.5 GJ elec/t. largely self-sufficient in energy terms, Chemical pulping 12.5 GJ/t + 2.08 GJ elec/t. using only biomass and delivering sur- plus electricity to the grid. Steam con- Waste paper pulp 0.5GJ/t + 0.36 GJ elec/t. sumption of 10.4 GJ/ adt and an excess De-inked waste paper pulp 2.0 GJ/t + 1.6 GJ elec/t. of electricity production of 2 GJ/adt. Depending on final paper quality energy intensities vary from 3.7 –5.3 GJ/t + 1.8–3.6 GJ elec/t. source: : IEA. note: GJ/adt = gigajoule/air dry ton pulp; kA = kilo ampere; kWh = kilowatt-hour; MWh/t = megawatt-hour/ton. 161 Global tracking framework Comparison of estimated short-term potential for industrial energy savings in industrialized and developing countries, 2007 Share of Total savings potential Improvement potential (%) energy (EJ/year) costs (%) Industrializing Developed Developed and develop- countries countries Industrializing Industrializing ing countries Sectors and products (including (including countries countries (including economies in economies in economies in transition) transition) transition) Petroleum refineries 10–25 40–45 0.7 2.9 50–60 Chemical and petrochemical 0.5 1.8 Steam cracking (excl. feedstock) 20–25 25–30 0.4 0.3 50–85 Ammonia 11 25 0.1 0.3 Methanol 9 14 0.0 0.1 Nonferrous 0.3 0.7 30 Alumina production 35 50 0.1 0.5 35–50 Aluminum smelters 5–10 5 0.1 0.15 — Copper smelters 45–50 0.0 0.1 — Zinc 16 46 0.0 0.1 10–30 Iron and steel 10 30 0.7 5.4 Nonmetallic minerals 0.8 2.0 25–50 Cement 20 25 0.4 1.8 40 Lime 7–20 Glass 30–35 40 0.4 0.2 30–50 Ceramics 15–35 Pulp and paper 25 20 1.3 0.3 5–25 Textile 5–25 Spinning 10 20 0.1 0.3 5–15 Weaving Food and beverages 25 40 0.7 1.4 1–10 Total of all sectors 15 30–35 7.6 23 – (excl. feedstock) source: UNIDO 2010. chapter 3: energy efficiency 162 chapter 4 renewable energy CHAPTER 4: renewable Energy One of the three objectives of the UN Secretary General under the Sustainable Energy for All (SE4ALL) initiative is to double the share of renewable energy in the global energy mix by 2030, with an emphasis on promoting sustainable forms of renewable energy. This chapter proposes a methodology for establishing a starting point against which future global progress can be measured and provides an indicator framework for tracking that progress. The chapter also describes global trends in renewable energy and discusses market growth, barriers, high-impact opportunities, as well as future scenarios and the scale of the challenge. Section 1: Methodological challenges in defining and measuring renewable energy There are various definitional and methodological challenges in measuring and tracking the share of renewable energy in the global energy mix: }} Defining renewable energy, taking into account sustainability considerations }} Data availability, collection, and management issues }} Determining what convention to use for measuring the share of renewables in the global energy mix }} Measuring other relevant indicators Defining renewable energy While there is a broad consensus among international ocean, hydropower, biomass, geothermal resources, and organizations, government institutions, and regional com- biofuels and hydrogen derived from renewable resources” missions on what constitutes renewable energy, these (IEA 2002). groups employ legal or formal definitions that vary slightly in the types of resources and sustainability considerations These definitions vary in the type of sources included and included. in whether sustainability considerations are explicitly incor- porated. These differences illustrate the fact that there is The International Renewable Energy Agency (IRENA) has a no common or global definition of renewable energy. statutory definition, ratified by 108 members (107 states and the European Union) as of February 2013: “renewable en- For the purposes of the SE4ALL tracking framework, it ergy includes all forms of energy produced from renewable is recommended that the definition of renewable energy sources in a sustainable manner, including bioenergy, geo- specify the range of sources to be included, embrace the thermal energy, hydropower, ocean energy, solar energy notion of natural replenishment, and espouse sustainabili- and wind energy.” ty. But data are not currently available to distinguish wheth- er renewable energy – notably biomass – has been sus- The International Energy Agency (IEA) defines renew- tainably produced. Until adequate data become available, able energy resources as those “derived from natural it is thus recommended that renewable energy be defined processes” and “replenished at a faster rate than they are and tracked without the application of specific sustainabili- consumed” (IEA 2002, OECD, IEA and Eurostat, 2005). ty criteria. The SE4ALL initiative will support the strengthen- The IEA definition of renewable energy includes the follow- ing of methodologies for tracking sustainability across all ing sources: “electricity and heat derived from solar, wind, renewable energy sources. chapter 4: Renewable energy 164 Ensuring sustainability It is clear that the SE4ALL initiative should encourage pronounced in the case of bioenergy and hydropower, renewable energy where this contributes to overall but are also relevant to the widespread deployment of sustainable development, taking into account all three other technologies. Assessment methodologies and pillars of sustainability—environmental, economic, and best practice guidelines that can be used to manage social. In general, the renewable technologies score high in these impacts are often available at the national level. terms of sustainability criteria, but energy production from But there are no internationally accepted sustainability these sources inevitably has both positive and negative criteria covering the major technologies, and it is therefore environmental, economic, and social impacts, which must very difficult to distinguish between sustainable and less- be carefully managed. These considerations are most sustainable deployment. Bioenergy Bioenergy is a very complex field; concerns associated But biomass can also be used to produce household-level with the sustainability of its production and use require a energy more efficiently via improved cooking and heating case-by-case assessment, considering feedstock, loca- appliances. It can also be used to produce heat efficiently tion, production methods, land use, conversion pathways, for commercial and industrial needs, as well as electricity infrastructure, and so on. These concerns span all types of and transport fuels. Ambitious renewable energy scenarios bioenergy, from traditional uses of biomass in the residen- rely heavily on these “modern” forms of bioenergy use to tial sector to bioenergy used in the transport sector and meet their goals, but some also recognize that traditional power generation, across the three pillars of sustainability. uses of biomass will continue to be an important energy For example, the greenhouse gas (GHG) balance needs source for many people for some time to come. Indeed, to be carefully evaluated on a case-by-case basis with it is not possible to distinguish, using available data, the proper assessment of the full life cycle of GHG emissions, extent to which bioenergy is used by modern or traditional from land use conversion to end use. There are some un- conversion methods, at least as far as the residential sec- resolved methodological issues, such as how to account tor is concerned. For example, in some IEA analysis it is for the indirect impacts of bioenergy production on land assumed that the use of bioenergy in the residential sector use (that is, indirect land use change, ILUC). Potential eco- of non-OECD (Organisation for Economic Co-operation and nomic and social impacts, including on food security, must Development) countries is made up of “traditional biomass,” also be carefully considered. Substantial progress has whereas in the OECD countries it counts as modern bio- been made in identifying the key sustainability issues and energy. This is obviously a simplification given the fact that creating methodologies for impact assessment, notably informal use of wood fuels in low-efficiency appliances through the work of UN Energy 1 and the Global Bioenergy also occurs in many OECD countries.3 Clearer criteria are Partnership (GBEP).2 The GBEP has established interna- needed. For example, should the use of biomass in an im- tional consensus around sustainability indicators for bioen- proved stove be counted as “sustainable” use? In addition, ergy. While the inclusion of sustainability considerations for data on household use of biomass for fuel is difficult to bioenergy is still under development in the legal and reg- establish with any precision, with different methodologies ulatory regimes of many countries, improved frameworks and estimates providing a range of differing results. are beginning to emerge. Within the monitoring process associated with the SE4ALL Bioenergy provides around 14 percent of global energy initiative, it would clearly be desirable to distinguish be- consumption. Some 70 percent of this biomass energy is tween “sustainable” and “unsustainable” bioenergy use. believed to be consumed in developing countries for cook- While the GBEP framework of sustainability indicators ing and heating with open fires and very inefficient stoves, would provide a good basis for making this distinction, no the traditional uses of biomass. It is widely recognized that internationally accepted standards based on these indica- these uses, including the inefficient production and use of tors have yet been developed. Given the additional difficul- charcoal, lead to deforestation and are closely linked to ties of collecting appropriate information in the field, such indoor air pollution (Goldemberg 2004). distinctions are not feasible at this stage. 1 UN Energy Bioenergy Decision Support Tool at http://www.bioenergydecisiontool.org. 2 http://www.globalbioenergy.org. 3 Note that it is possible to estimate traditional biomass use based on data from national household surveys. But this approach require assumptions on a set of issues; for example, these surveys report on what is the primary fuel being used by households but do not provide volume or quantity or the actual total level of fuel household consumption. Thus, the proportion of primary fuel could vary widely depending on the number and extent of consumption of other fuels used. Also, the actual household consumption needs to be assumed. 165 Global tracking framework Since it is not currently possible to distinguish consistently initiative will track all types of bioenergy uses. But progress between the sustainable and less-sustainable ways of us- toward the target should be monitored in as disaggregated ing bioenergy (including traditional biomass) the SE4ALL a manner as the data allow so that trends can be assessed. Hydropower There is a degree of international consensus around sus- management. In 2010 the International Hydropower Asso- tainability considerations for hydropower. For example, ciation published the “IHA Sustainability Assessment Pro- the IEA Hydropower Agreement published guidelines on tocol” based on a multistakeholder development process “Hydropower and the Environment” in 2000, which were involving representatives from social and environmental updated in 2010 (IEA 2000; 2010). The World Commission nongovernmental organizations (NGOs), governments, on Dams also produced a “Decision Making Framework” commercial organizations, development banks (including to guide planners in protecting people from the negative the World Bank), and the hydropower sector (International impacts of water and energy projects. Brazil has produced Hydropower Association 2010). a detailed manual for river basin inventory studies and Other technologies For other technologies, guidelines are established on a na- and unsustainably produced renewable energy—in line tional or regional basis in the absence of international con- with the overall aim of the initiative—this is not possible in sensus. To encourage the highest levels of sustainability the short term, based on existing data and protocols. The in the deployment of all renewables, a necessary first step SE4ALL initiative presents a unique opportunity to improve is to establish internationally accepted indicators and pro- existing methods of data collection and enhance the avail- tocols for the sustainability of each technology. Although able knowledge base as a step toward the ability to track it would be desirable to differentiate between sustainably progress on sustainability. Data availability, collection, and measurement Availability Tracking progress toward the renewable energy SE4ALL The IEA compiles a comprehensive and comparable set of objective requires accurate, consistent data on both over- energy data that is used as the reference source for most all energy production and use of energy from all sources. reporting of global energy demand and renewable ener- gy production. The IEA database contains comprehensive Many organizations and companies generate reports on and accurate data for OECD countries and also covers global energy statistics. But only three organizations collect about 75 non-OECD countries that provide their national primary global and country-level data on energy consump- energy balances to the IEA. For 10 other countries, tertia- tion and production: ry sources and estimations are used to compile the data. Data from some smaller developing countries are not in- }} IEA dividually reported in the IEA statistics and are based on extrapolations of country data provided by the UN Statis- }} UN tics Division. }} World Health Organization (WHO) (focusing particularly on household energy use) The UN database contains long-time series data for almost all countries, but is more heterogeneous and not available Many other institutions and companies use these IEA, UN, until sometime after the IEA information is reported. The and WHO databases, and complement them with both WHO collects primary data on energy use but mainly at the primary data and secondary information to create customized household level. databases and analyses (for example, Enerdata, US-EIA, BP , and REN21; see table A1.1 in annex 1). chapter 4: Renewable energy 166 Collection and measurement As discussed above, the major issue affecting the }} Direct production of heat (for example, by solar contribution from renewable energy to the global energy water heaters). Contribution of direct use of solar mix relates to the use of biomass for heating and cooking. heat is often estimated based on installed capacity In many countries this is an informal sector, and data of solar collectors, but there are inconsistencies in availability and accuracy are acknowledged to be poor how the data is collected and reported. and subject to large errors. Different data sources and methodologies produce varying estimates. This makes }} Waste fuels, where the methodologies do not it very difficult to establish the starting point and to track consistently differentiate between renewable (bio- progress toward the goal with any precision. So there genic) and other waste fractions. is an urgent need to improve the overall quality of data }} The treatment of heat pumps within the statistics on bioenergy use, particularly in regard to heating and is somewhat complex, and there are inconsistencies cooking, and to refine the definitions and classifications in how the net energy produced by the heat pump relating to this sector. is accounted for, and whether this is classified as renewable. There are some other categories of renewable energy pro- duction that are not fully or consistently represented in the }} “Passive solar” energy makes a substantial con- data. While these data gaps may not significantly affect the tribution to energy needs, both in industrial process- overall proportion of renewables within the current energy es (salt production, food processing, and drying) mix, as new technologies are more widely deployed their and buildings (passive solar heating and lighting). shares may become more significant and would need to This contribution can be further optimized by careful be better monitored in any comprehensive tracking sys- design, reducing the need for fossil fuels. But it is tem. These categories include: difficult to explicitly identify the contribution from passive solar, and so it is usually excluded. }} Small, distributed grid-connected generation, such as small-scale photovoltaic (PV) or wind and }} Interregional integration of electricity or biomass solar water heating. These may not be included trade. in statistical reports, and a correction based on installed capacity may be needed. Indeed, current Given the need to develop a comprehensive and compa- practice is inconsistent across countries. rable analysis at a global level, we recommend that the IEA energy statistics—complemented with UN data for the }} Renewable energy production that is estimated smaller non-OECD countries—be used as the basis for based on installed capacities may be inaccurate, tracking progress toward the target. Furthermore, a review particularly because some systems may be installed of the methodologies for collecting data and reporting on but not producing energy effectively. the sources listed above is needed to ensure that the share of energy from these sources is accurately represented in }} Biofuels are currently measured at final, not the energy statistics as their importance grows. primary, energy levels. }} Off-grid and mini-grid electricity generation, which are often not captured by energy statistics. Primary and final energy To track the share of renewables in the global energy mix it basis of final energy.4 Each of the choices has different ad- is necessary to define at which level of the energy balance vantages and disadvantages. the measurement must be taken. The choice has a mate- rial impact on the starting and target levels of deployment. Tracking can be done at the primary energy level or on the 4 In some countries, such as the United States, the term “delivered energy” is used, which is defined as the energy value of the fuel or electricity that enters the point of use (for example, a building). 167 Global tracking framework Primary energy accounting Many energy production statistics (for example, those }} The physical energy content method (used by used by the IEA, Eurostat, and the U.S. Energy Information IEA and Eurostat) Administration [EIA]) are based on a physical energy con- tent or primary energy accounting method. In these sys- }} The partial substitution method (used by EIA) tems, energy is accounted for in the form in which it first }} The direct equivalent method (used in some appears. For fossil fuels and bioenergy, the energy content Intergovernmental Panel on Climate Change [IPCC] in the fuels before conversion is used as the measure. For reports) nuclear and renewable energy, the primary energy content is calculated based on a number of different conventions. Table 4.1 provides a comparison of total world energy sup- The comparison between the roles of renewables and oth- ply in 2010 that illustrates the differences in the proportion er sources is obscured by assumptions about the efficien- of renewables in the energy mix estimated using these cies of the various processes in these conventions. Wher- methodologies. ever high efficiencies are used, the share of renewables in the overall system is underrepresented in terms of the The advantage of estimating primary energy is that figures useful energy produced. are based directly on the physical measurement of the energy content in fossil fuels. The disadvantages are There are, in fact, three different conventions for presenting that for low-carbon electricity sources the primary energy the primary energy data, which can affect the overall size content has to be calculated and the result depends on of the global energy mix and of the renewable share within the accounting convention used. It is difficult to make a it. These are:5 clear comparison between the contribution of renewable and nonrenewable sources because this is obscured by assumptions about efficiencies. The resulting figures tend to underrepresent the share of electricity-producing renewables. RE contribution to world RE contribution to total world primary energy supply final energy consumption % renewables in Physical Direct Substitution global energy mix content equivalent method method method EJ % EJ % EJ % EJ % 2010 69 13 68 13 91 17 60 18 Table 4.1 Comparison of primary and final energy consumption methodologies source: Source: IEA analysis. (2010) Note: RE = renewable energy. Final energy accounting The data for this methodology come from the Total Final are reported directly in the form ready for consumption. Energy Consumption (TFEC) figures within the IEA statis- Although other primary energy sources (for example, fos- tics (these exclude nonenergy uses of fossil fuels such as sil fuels and bioenergy used for heating in the residential their use as raw material for the production of plastics and sector) are still reported in terms of their fuel content, this chemicals). Within the TFEC figures, heat and electricity methodology comes closer to representing the energy in 5 Definitions of the methods as well as more details on how to calculate primary and final energy can be found in annex 1. chapter 4: Renewable energy 168 the forms useful to users. To establish the contribution of The advantage of using TFEC as the basis for monitoring is each technology, the aggregated figures for electricity and that it allows a straight comparison (in GWh) of electricity- commercial heat have to be allocated to the relevant tech- producing renewables (or nuclear sources) as well as of nology. This can be done based on the proportions exhibit- commercial heat—and gets closer to measuring useful ed in production data, attributing the losses proportionally. energy. Table A1.5 in annex 1 shows the breakdown of final con- The merits and disadvantages of using primary and final en- sumption figures for 2010 before and after allocation of ergy as the basis for tracking are summarized in table 4.2. electricity and heat. Primary energy supply Final energy consumption • Heat and electricity in form ready for consumption. • Widely used. Advantages • Closer to useful energy output valued by • Based on physical measurement of fuels. end-users • Better balance for directly produced RE. • Different conventions for assumptions on efficiencies means that contribution of RE Disadvantages depends on calculation procedure. • Losses need to be allocated. • Underrepresents directly produced RE. Table 4.2 Advantages and disadvantages of primary and final energy consumption methodologies Note: RE = renewable energy. Given the decarbonization efforts under way around the at the secondary energy level). Because the aim is to track globe, we can expect that more and more energy will be the contribution of renewables to the global energy mix, we delivered by noncombustible energy sources. These are suggest using progress measurement at the final energy precisely the sources that are measured in the energy bal- consumption level of the energy balance. ance only once they have produced power or heat (that is, Measuring additional indicators In addition to tracking deployment levels, it will be useful energy markets. These could include trends in deployment to track some supplementary indicators to improve the diversification, policy developments, evolution of technology overall analysis of the global evolution of renewable costs, and investment. Deployment diversification In order to meet the SE4ALL goals it will be important for }} Number of countries exceeding threshold an increasing number of countries to develop significant capacity levels for key technologies, which would renewable energy portfolios. This diversification trend is identify only those countries with a larger absolute already in progress; for example, the recent IEA Medium and globally significant level of production. Term Renewable Energy Market Report shows an increas- ing number of countries reaching a 100-megawatt (MW) }} Number of countries reaching threshold levels threshold level of installed renewable energy capacity (IEA of renewable energy as a proportion of final energy 2012b). Tracking such diversification could be based on the: consumption, which would identify countries that made significant efforts. 169 Global tracking framework Renewable energy policy It will also be useful to track the adoption of formal renew- }} Number of countries with specific legislation or able energy targets and the introduction of fiscal, financial, regulations supporting the development of re- and economic incentives for the purposes of future analy- newables within the electricity, heat, and transport ses and tracking of renewable energy development across sectors countries and regions. At present, there is no common basis for the way that The IEA has a policy database that covers policies within a countries establish renewable energy targets; some are wide range of countries. This is now being expanded as a based on technology capacities, others on a percentage joint database with IRENA, and will eventually cover all the that is based on primary energy production, and some member countries of both organizations. The data will be on final energy consumption. This makes it impossible regularly updated and validated by the responsible organi- to establish the extent to which, taken together, country zations in the countries. Other international organizations, targets are aligned with the overall SE4ALL goal. We such as REN 21 in its annual Renewables Global Status recommend that countries establish goals based on final Report,6 also track renewable energy policies. The tracking energy consumption, and that a target for 2030 be included could include: along with intermediate targets to improve the consistency of tracking efforts. }} Number of countries with renewable energy targets Technology cost Tracking the evolution of technology costs will also be es- }} Equipment cost sential to future analyses of the development of renewable energy markets. Many institutions, including IRENA and }} Total installed project cost, including fixed the IEA, are playing an important role in collecting data financing costs and reporting on costs for a range of renewable energy }} The levelized cost of energy (LCOE) technologies. The cost of equipment at the factory gate and installed Cost estimates are not always consistent due to the differ- project costs are often available from market surveys or ent conventions and assumptions applied in their calcula- from other sources, such as the IRENA. tion (for example, different cost allocation rules for com- bined heat and power plants may be applied, or different The LCOE is the price of electricity required for a project grid connection costs and rules). where revenues would equal costs, including making a re- turn on the capital invested equal to the discount rate, as Considering the advantages and disadvantages of differ- measured by a discounted cash flow analysis. ent cost analyses, we suggest that a number of different cost indicators are used for the analysis, including: Investment Tracking global trends in renewable energy investment Finance (BNEF) and UNEP have been reporting data on will help to identify emerging trends and to highlight bot- investment on an annual basis from 2004 (BNEF, UNEP, tlenecks. It will be particularly important to track private and Frankfurt School 2012). sector investment, the role of development banks, and the extent to which public and concessional finance is lever- aged with other sources of finance including asset finance, venture capital, and private equity. Bloomberg New Energy 6 http://www.ren21.net/gsr chapter 4: Renewable energy 170 Suggested methodology for defining and measuring renewable energy While it is not possible to fully resolve all of the methodological challenges outlined in the preceding section, the preferred approach for tackling them is summarized in table 4.3. Challenge Proposed approach Energy from natural sources that are replenished at a faster rate than they are Definition of renewable energy consumed, including hydro, bioenergy, geothermal, aerothermal, solar, wind and ocean Develop sustainability protocols for different forms of renewable energy over time, Sustainability of renewable so that sustainability considerations can be incorporated to the definition in the energy medium term Primary versus final energy ac- Track renewable energy as a share of total final energy consumption, and as a counting subsidiary indicator the share of renewable energy in electricity generation Track complementary indicators such as deployment diversification, renewable Measuring additional indicators energy policy, technology cost and diversification Table 4.3 Addressing methodological challenges in global tracking of renewable energy source: authors. Definition of renewable energy For the purposes of the SE4ALL tracking framework, we But since it is also important that the SE4ALL initiative em- recommend that renewable energy be defined broadly as: phasizes and promotes the sustainable use of renewable energy resources, we recommend that, in parallel, the “Energy from natural sources that are replenished at a SE4ALL initiative promotes or commissions a formal as- faster rate than they are consumed, including hydro, sessment to tackle the methodological aspects necessary bioenergy, geothermal, aerothermal, solar, wind, and for tracking sustainability in the long term. This will require ocean.” the development of a consensus around sustainability in- dicators and criteria for each of the main technologies con- We also propose that, in the short term, sustainability crite- sidered. These efforts will need to be introduced in tandem ria not be applied so as to exclude any of these resources with strong capacity building at the country level, especial- or associated technologies, given the difficulties of making ly in less-developed economies. these distinctions based on currently available data. This implies that the traditional uses of biomass would be in- cluded in the definition of renewable energy. Method for accounting and measuring renewable energy For the purposes of the SE4ALL initiative, we recommend previously, particularly relating to bioenergy use. We there- that the estimation of the proportion of the global energy fore propose that the SE4ALL initiative promote or com- mix from renewable energy be based on the TFEC data. mission the assessments necessary for improving mea- surement and data collection in those categories. To improve the tracking of the contribution of renewable energy to TFEC, it will be necessary to enhance measure- ment and data collection to improve the issues identified 171 Global tracking framework Measuring and tracking complementary indicators In tracking the contribution of renewable energy to TFEC }} Policy development, including number of coun- under the SE4ALL initiative, the analysis of complementary tries with a policy target and level of target in each indicators will be necessary to understand patterns and country for an aggregated global baseline; and overall market evolution at the global, regional, and country adoption of fiscal, financial, and economic incen- levels. tives at the country level We recommend monitoring the following additional }} Technology costs for each of the renewable indicators: energy technologies considered, initially in terms of LCOE, but if suitable procedures can be developed }} Deployment diversity, including threshold levels this should be complemented by manufacturing of installed capacity for key renewable energy cost data where possible technologies or resources and number of countries reaching threshold levels of renewable energy as a }} Investment in renewable energy (by asset class, proportion of final energy consumption country, and region) Baseline year Given the availability of data, we propose that the baseline year should be established as 2010, providing a 20-year period for reaching the target. Data sources We recommend using the IEA data as the main source for The use of IEA statistics as a basis for tracking should also measuring the starting point and for tracking the contribu- be supplemented by enhanced efforts to track direct use tion of renewable energy to TFEC, complemented with the of renewable energy for heat, improve data on bioenergy UN data for the case of smaller non-OECD countries. use (particularly relating to the traditional uses of biomass), and identify small-scale and off-grid electricity generation (as well as other sources not currently measured or includ- ed in the energy statistics described earlier). Global baseline and tracking Immediate and short term In the immediate and short term (that is, for establishing The tracking of TFEC will be conducted primarily based the starting point and for tracking progress within the next on the statistics already produced by the IEA. These are five years), the SE4ALL initiative will track TFEC of different based on country information gathered through annual renewable energy resources used for heating, electricity, questionnaires that the IEA designed to ensure consis- and transport on a global basis. tency of reporting variables (for example, use of the same reporting conventions and definitions, use of the interna- These resources include: hydro (all sizes), bioenergy (all tional standard industrial classification, application of the types, but including only the estimated biodegradable same definitions for different categories, and so on). This fraction of products or waste), geothermal, aerothermal, information is supplemented with other data sources in solar (including PV and solar thermal), wind, and ocean. countries that have not signed data-reporting conventions with the IEA. The IEA aggregates the country-level data and reports on an annual basis. chapter 4: Renewable energy 172 During the first five years, the SE4ALL initiative will seek These new procedures and the necessary country-leve- to complete the recommended assessments for improv- training will be introduced before the end of the fifth year ing methodological issues and to enhance data collection after the SE4ALL initiative is launched. to cover identified data gaps. Once the assessments are completed, these new concepts, definitions, and ques- The SE4ALL initiative will track four additional indicators: tions will be integrated into the procedures for collecting and reporting the energy statistics. }} Deployment diversity A parallel review of sustainability indicators and criteria }} Policy developments for each of the main technologies will be carried out and }} Technology costs used as the basis for developing internationally accepted standards that can be used to assess the degree to which }} Investment in renewable energy deployment meets the highest sustainability standards. All indicators will be tracked on a country level and ag- gregated globally for the purposes of reporting under the SE4ALL initiative. Medium term In the medium term, we recommend that the SE4ALL initia- In addition, we recommend that countries adopt a consis- tive move toward a working definition of renewable energy tent targeting approach, setting targets in terms of the pro- that includes only renewable energy produced in a sustain- portion of energy in their energy mix based on TFEC, which able manner. To do this it will be necessary to develop and would allow for the calculation of an aggregate figure that promote methodologies for tracking sustainability across would provide a measure for the cumulative ambition for the use of all types of resources; improving definitions and comparison with the SE4ALL goal. data on bioenergy use, particularly relating to traditional vs. modern uses of biomass; organic versus inorganic fraction Toward the fifth year of the SE4ALL implementation, these of waste and products; output and use of heat pumps; use additional aspects could be incorporated into the reporting of small-scale renewable energy in distributed generation; systems on an annual basis. and use of renewable energy in off-grid schemes. Country-level tracking At this stage there is no attempt to disaggregate the in- Also in the medium term, the revised information-gathering creases in the share of renewable energy to the individual systems and definitions will need to be implemented at the SE4ALL commitments (that is, the impact of particular UN country level, along with the application of sustainability cri- SE4ALL measures is not considered). Nor does the report teria for bioenergy and other technologies as appropriate. attempt to address the allocation of the SE4ALL objective on a regional or country level. A summary of the strategy for tracking is provided in table 4.4. In the medium term it would be beneficial for country-lev- el targets to be reformulated in line with the proposed SE4ALL methodology—that is, as the percent of renew- able energy in TFEC. 173 Global tracking framework Immediate Medium term • TFEC. • Improved definitions and data associated with bioenergy. • Electricity (MW, GWh). • RE in distributed generation. • Number of countries exceeding threshold levels of installed capacity for key RE • RE in off-grid (including micro-grids). technologies and exceeding threshold • Harmonized approach to target setting. Global tracking levels as a proportion of final energy consumption. • Number of countries with policy targets and incentives. • Technology costs. • Investment levels. • Nil. • Development of consistent targets expressed in terms of renewable energy share of TFEC by 2030. • Support and implementation of revised information gathering systems aimed at improving coverage of the full range of Country-level renewable energy technologies in selected tracking countries. • Piloting of the application of sustainability criteria in bioenergy in selected countries. • Developing sustainability criteria for other renewable energy technologies and piloting their application in selected countries. Table 4.4 Tracking framework source: authors. Note: GWh = gigawatt-hours; MW = megawatts; RE = renewable energy; TFEC = total final energy consumption. chapter 4: Renewable energy 174 Section 2. Global trends in renewable energy This section establishes the initial conditions of the share and income groupings. It also discusses trends in renew- of renewable energy in global final energy consumption able energy policy, technology progress, investment and, using the methodology described in section 1, and presents deployment diversification. global trends including breakdowns for different regions Total final energy consumption and electricity Based on existing data sources (with their associated sta- It is estimated that traditional biomass accounts for about tistical limitations), the share of renewable energy in TFEC half of the renewable energy total (figure 4.1).8 A further is estimated to be 18 percent at the starting point in 20107. quarter of the renewable energy total relates to modern This implies a SE4ALL objective of 36 percent for the year forms of bioenergy, and most of the remainder is hydro- 2030. For immediate tracking purposes, it is not possible power. Other forms of renewable energy—including wind, to take sustainability considerations into account, so as solar, geothermal, waste, and marine—together contribute to exclude any unsustainable forms of renewable energy; barely 1 percent of global energy consumption. though it is recommended that these considerations be in- corporated over time. As a result, the starting point of 18 percent as well as the associated target can be regarded as upper bounds. traditional biomass (9.6%) modern biomass (3.7%) liquid biofuels (0.8%) fossil fuels (79.1%) wind (0.3%) Nuclear (2.5%) 18.0% solar (0.2%) renewable energy (18%) biogas (0.2%) geothermal (0.2%) waste (0.1%) marine (<0.01%) hydro (3.1%) Global Share of Renewable Energy in TFEC, 2010 Figure 4.1 Global share of Renewable Energy in TFEC, 2010 SOURCE: source: Authors’ IEA analysis based on IEA 2012d Indeed, although the consumption of traditional biomass Nonetheless, as mentioned previously, the methodology increased in terms of volume between 1990 and 2010, its for collecting data on biomass (both traditional and mod- share of TFEC declined from 10.2 percent in 1990 to 9.6 ern) must be enhanced for a more accurate disaggrega- percent in 2010. This trend may be partially attributed to a tion of sources and uses and a better understanding of the slow shift toward the use of more modern energy sources degree to which these sources are being utilized sustain- at the global level. The modern biomass share of TFEC ably. increased slightly from 3.5 in 1990 to 3.7 percent in 2010. 7 During the 2012 Year of Sustainable Energy for All a provisional estimate of 15 percent was used for the share of renewable energy in the global energy mix, with an associated target of 30 percent. This was based on 2005 data and a slightly different methodological approach to that finally agreed in this report. 8 The UN Food and Agriculture Organization defines traditional biomass as “woodfuels, agricultural by-products, and dung burned for cooking and heating purposes.” In developing countries, traditional biomass is still widely harvested and used in an unsustainable and unsafe way. It is mostly traded informally and non- commercially. So-called modern biomass, by contrast, is produced in a sustainable manner from solid wastes and residues from agriculture and forestry. 175 Global tracking framework increasing at a compounded annual growth rate (CAGR) of 3.0% growth only 1.2 percent, the share of all other renewable sources (including hydro) grew at 3.0 percent CAGR, with the last - the compound annual growth rate of renewable five years marked by an unprecedented 4.9 percent CAGR. energy other than traditional biomass over the period 1990-2010, two The renewable energy sources other than traditional bio- times the rate of global total final mass and hydropower grew at an even higher annual rate, energy consumption in the same period on the order of 11 percent between 1990 and 2010. Thus, the incremental increase in the share of renewable energy in The renewable energy sources other than traditional bio- TFEC during that period was to some extent driven by wind, 59,513 mass and hydropower (including modern solid biomass, biofuels, biogas, solar, waste, and geothermal sources biofuels, biogas, waste, geothermal, wind, solar, and ma- (figure 4.2). rine energy) contributed only 5.4 percent to TFEC in 2010. In the same year, the global consumption of hydropower 5,637 Marine reached a comparatively high share of 3.1 percent of TFEC. use of different sources has evolved at contrasting The Waste rates. While the share of traditional biomass in the global Marine energy mix steadily declined between 1990 and 2010, Geothermal Waste Geotherma Others Biogas Biogas Hydro Solar 1,467 Solar Biomass Modern Wind Traditional Biomass 26% 59,513 694 5,637 Liquid Biofu Marine Wind 2010 Waste 17% 47,109 1990 2000 2010 Liquid Biofuels Marine 010 40,412 Geothermal Waste Geothermal Biogas Biogas 1,467 Solar Solar Wind Others 694 Liquid Biofuels Hydro Wind Modern Biomass 1990 Traditional 2000 Biomass 2010 Liquid Biofuels 1999 2000 2010 Figure 4.2 Evolution of renewable final energy consumption (PJ) source: Authors’ analysis based on IEA 2012d. Indeed, over the past ten years the use of renewable energy (as illustrated in figure 4.3). The impressive scale-up in the sources other than biomass and hydro almost quadrupled use of these sources is largely attributed to the provision of at the global level. Wind, biogas, and solar exhibited the sustained policy incentives that triggered high investment most dramatic growth in both absolute and relative terms, volumes and remarkable reductions in technology costs. growing at 25, 16.7, and 11.4 percent CAGR, respectively chapter 4: Renewable energy 176 25.0% 16.7% 11.1% 11.4% 6.6% 5.1% 1.9% 2.3% 1.2% 0.0% d r e ro e s s l la st a n in ss el ss a g ri yd m W a a So fu o a a W er m m H Bi M o o o th Bi Bi Bi eo n l er a G n d io o it M d a Tr Figure 4.3 Compounded annual growth rates (CAGR) of renewable energy TFEC by source, 1990–2010 source: Authors’ analysis based on IEA 2012d. Renewable energy sources are used for heating, electricity, other sources combined accounted for about 10 percent and transport. Renewables for heating (cooking, space, of total renewable-source-based electricity supply in 2010 and water heating) accounted for 75 percent of all renew- (figure 4.4a). able energy use in 2010, with biomass contributing 96 per- cent of this share.9 Commercial-scale heating, in particular, increased rapidly between 1990 and 2010, although it still represented only 1 percent of total heating consumption 25% growth by the end of 2010. Indeed, the use of modern renewable - the compound energy technologies for heating and cooling is still limited annual growth rate relative to their potential for meeting global demand. of wind energy over the period 1990-2010 Despite its significant share, renewable energy for heating declined 7.5 percent over the period 1990-2010. This trend While the historic share of renewable energy in electricity may be also partially attributed to substitution of traditional production was relatively flat through 2010, more recent for more modern sources of energy. The CAGR associated trends suggest that it may be increasing. Renewables with the global use of biomass for heating between 1990 accounted for almost half of the estimated 208 gigawatts and 2010 is estimated at only 1.3 percent, while those of (GW) of new electric capacity added globally during 2011. geothermal and solar thermal for heating reached 6.7 and Wind and solar photovoltaic (PV) accounted for almost 40 10.6 percent respectively. percent and 30 percent of new renewable capacity, re- spectively, followed by hydropower (nearly 25 percent). By The share of renewable energy in electricity production the end of 2011, total renewable power capacity worldwide fluctuated between 1990 and 2010, decreasing from 19.5 exceeded 1,360 GW, up 8 percent over 2010; renewables percent in 1990 to a low of 17.5 percent in 2003, and then comprised more than 25 percent of total global pow- rebounding to 19.4 percent in 2010. The reason for the er-generating capacity (estimated at 5,360 GW in 2011) decline between 1990 and 2000, despite the absolute and supplied an estimated 20.3 percent of global electric- growth, is that electricity demand grew at a faster pace ity. Renewable technologies are also expanding into new than renewable energy. Hydropower contributed 83 per- markets. In 2011, around 50 countries installed wind power cent to this global share, followed by wind-based gener- capacity, and solar PV capacity is moving rapidly into new ation, which accounted for a little more than 8 percent. All regions and countries. Solar hot water collectors are used 9 Traditional biomass alone contributed approximately 70 percent to the share of renewable energy sources used for heating. 177 Global tracking framework a. Technology breakdown by renewable b. Renewable energy contribution to global TFEC energy application (2010) in electricity, transport, and heat (2010) 19.4% Others Others biomass 5% Other Biofuels 15% wind 8% biodiesels 26% biomass 96% hydro 83% biogasoline 3.9% 59% 2.4% Heat (75%) Electricity (21%) Transport (4%) Commercial Heat Electricity Transport Figure 4.4 Renewable energy applications Contribution of RE to global electricity, transport and commercial heat. Note: Biogasoline includes bioethanol, biomethanol, bioETBE and bioMTBE. Note: Biomass includes primary solid biofuels and charcoal. Biogasoline includes bioethanol, biomethanol, bioETBE, and bioMTBE and “other biofuels” includes those that cannot be specified as either biogasoline or biodiesel due to lack of data. Commercial heat refers to heat produced for sale by combined heat and power (CHP) and heat plants. TFEC = total final energy consumption. SOURCE: Authors’ analysis based on IEA 2012d. tricity by more Transport than 200 million households, as well as in many But despite the remarkable growth of wind, biogas, so- public and commercial buildings around the world. Interest lar, geothermal, and smaller renewable-source-based in geothermal heating and cooling is also on the rise glob- developments, the overall share of renewable energy in ally, as is the use of modern biomass for energy purposes. TFEC remained relatively stable between 1990 and 2010 because of the central role of traditional biomass, which The contribution of renewable energy to global final con- accounted for about 53 percent of the renewable energy sumption in commercial heat—mainly combined heat and share of TFEC in 2010 (figure 4.5). power—and transport reached 3.9 and 2.4, respectively, in 2010 (figure 4.4b). Renewable energy is used in the transport sector in the 50% form of gaseous and liquid biofuels; liquid biofuels pro- of newly installed vided about 3.3 percent of global road transport fuels in power generation in 2011 came from renewable sources 2010-11, more than any other renewable energy source in the transport sector.10 Electricity powers trains, subways, and a small but growing number of passenger cars and Global TFEC increased from 243 to 330 exajoules (EJ) motorized cycles, and there are limited but increasing ini- over that period, at a CAGR of 1.5 percent. Meanwhile, the tiatives that link electric transport with renewable energy. consumption of renewable energy increased from 40 to about 60 petajoules (PJ), at 2 percent annually. 10 Road transport is a subcategory of total transport shown on figure 4.4b, with the latter also including rail, pipeline, navigation, aviation, and other nonspecified transport categories. It is important to note that most biofuels are used in road transport. chapter 4: Renewable energy 178 70 18.0% 17.2% 17.4% 17.0% 16.6% 60 50 Other RE 40 Hydro 30 Modern Biomass Traditional Biomass 20 RE share in TFEC 10 - 1990 1995 2000 2005 2010 Figure 4.5 Global TFEC (PJ) vs. share of renewable energy (%) Note: TFEC = total final energy consumption. SOURCE: Authors’ analysis based on IEA 2012d. Global trends by region The evolution of the share of renewable energy in regional At the same time, the analysis of the data by income group TFECs has been influenced by a number of factors, includ- reveals that traditional biomass is being consumed pre- ing growth in overall energy consumption, trends in the dominantly by middle-income economies, while renew- use of traditional biomass, and growth in the production able energy sources other than hydro and traditional bio- of renewable energy other than traditional biomass and mass are primarily being consumed by upper-middle- and hydropower per se. high-income countries (figure 4.6). The regional share of renewable energy between 1990 and If we confine attention to power generation only, the region- 2010 increased in Europe, North America, and Sub-Saha- al picture for the share of renewable energy in the electric- ran Africa but decreased in Latin America, Northern Africa, ity mix looks quite different. Latin America and Caribbean and most subregions of Asia (table 4.5). emerges as the region with by far the highest share of re- newable energy in the electricity generation portfolio of 56 The increased share of renewables in Europe has been percent, which is more than twice the level in the next high- attributed to the adoption of bold and sustained policy est regions – Caucuses and Central Asia, Europe, Oceania measures that triggered a large volume of investments and Sub-Saharan Africa – all of them above 20 percent. primarily in renewable source-based initiatives other than Globally, 80 percent of renewable electricity generation is hydropower, although this trend has also been influenced found evenly spread across just four regions: East Asia, by a low growth in overall energy demand. In Europe re- Europe, Latin America and Caribbean and North America. newables have directly displaced other sources of energy, most notably fossil fuels. The share of renewables in Southern Asia and Sub-Saha- 65% vs 20% ran Africa is particularly high due to the use of traditional - the share of biomass, especially in the residential sector. But the share global total final of renewables in Southern and Southeastern Asia declined energy consumption significantly over the 1990–2010 period, in part owing to from renewable sources including decreased reliance on traditional biomass for cooking and traditional biomass contributed by wider adoption of non-solid cooking fuels. Africa and Asia versus Europe and North America in 2010 179 Global tracking framework Region Share of RE in each region Contribution to global share 1990 2000 2010 1990 2000 2010 North America 6.0 7.1 9.0 8.1 9.8 9.7 Europe 8.1 9.4 14.1 7.6 8.2 10.0 Eastern Europe 3.0 4.2 5.4 2.9 2.3 2.4 Caucasus and Central Asia 3.1 5.2 4.4 0.5 0.4 0.3 Western Asia 8.2 5.8 4.3 1.1 0.9 0.9 Eastern Asia 22.2 19.1 15.3 23.2 20.8 19.9 Southeastern Asia 52.2 37.9 31.1 8.8 8.5 7.7 Southern Asia 50.9 43.4 34.8 18.1 17.5 16.4 Oceania 15.0 15.6 15.1 1.1 1.2 1.0 Latin America and Caribbean 32.3 28.2 29.0 10.7 10.4 10.7 Northern Africa 6.5 6.2 5.0 0.3 0.3 0.3 Sub-Saharan Africa 72.5 74.6 75.4 17.7 19.8 20.7 World 16.6 17.4 18.0 100.0 100.0 100.0 Table 4.5 Regional contribution to the share of renewables in TFEC (after allocation) (%) source: Authors’ analysis based on IEA 2012d. 18% 13.3% hics 9.6% umics 8.5% lmics LICS 5.4% 3.7% 3.1% 1.7% Total RE RE (excl. RE (excl. RE (excl. biomass Trad. Modern Hydro trad. trad. all biomass biomass biomass) biomass biomass & hydro) & hydro) figure 4.6 Contributions to the Share of Renewable Energy in TFEC by Source and Income Group, 2010 source: Authors’ analysis based on IEA 2012d. Note: HICs = high-income countries; LICs = low-income countries; LMICs = lower-middle-income countries; UMICs = upper-middle-income countries. chapter 4: Renewable energy 180 Trends in relevant indicators Policies and dramatic technology cost reductions have general trends in renewable energy policy, technology driven renewable energy investment and market develop- progress, investment, and deployment diversification. ment in unanticipated ways. This subsection discusses Policies to promote renewable energy development Policy makers are increasingly aware of renewable energy’s chain have driven the remarkable growth of renewable en- wide range of benefits, including energy security, reduced ergy other than hydropower. Policy instruments include tar- import dependency, reduction of GHG emissions, preven- gets and a combination of economic, fiscal, and financial tion of biodiversity loss, improved health, job creation, rural incentives. development, and energy access, leading to closer inte- gration of renewable energy policy with policies in other Renewable energy targets have increasingly been adopt- economic sectors in some countries. Globally there are ed around the world over the past few years. Today, about more than 5 million jobs in renewable energy industries, 120 countries have a national target on renewable energy, and the potential for job creation continues to be a main more than half of which are developing countries (REN21 driver of renewable energy policies (REN21 2012). 2012). To a large extent, policy incentives targeting different stag- es of the technology innovation and market development 12 10 8 high income upper middle income 6 lower middle income low income 4 2 0 1990-2000 2001-2005 2006-2010 1990-2000 2001-2005 2006-2010 FITP RPS / AUCTIONS figure 4.7 Number of countries introducing price and quantity setting instruments source: REN21 2012. Note: FITP = feed-in tariff policy; RPS = renewables portfolio standard. 181 Global tracking framework Indeed, developed and emerging economies have accu- to develop renewable energy, with the intention of lowering mulated years of experience with the design and imple- domestic consumption of fossil fuels and developing in- mentation of various types of policy instruments, including dustrial capacity for the manufacture of renewable energy price-setting mechanisms and policies that impose a quo- equipment. ta and introduce competitive bidding or auctions. In partic- ular, feed-in tariff policies have been necessary to lower the Most recently, however, policy support for renewable en- range of risks associated with the introduction of capital- ergy weakened in Europe due to the economic crisis and intensive technologies and the development of new markets. associated austerity measures. As a result, efforts have increased to improve the effectiveness and economic ef- Increasingly, low- and middle-income countries are adopt- ficiency of policy incentives, especially in countries with a ing price/quantity setting instruments in combination with long track record of their implementation (box 4.1 discuss- fiscal and financial incentives to promote different seg- es the issue of policy performance). ments of the renewable energy market (figure 4.7). Even oil- and gas-exporting economies such as Saudi Arabia and the Gulf States are beginning to introduce incentives Box 4.1 Policy effectiveness and economic efficiency Between 1990 and 2010, many countries, especially developed and emerging economies, introduced a com- bination of economic, fiscal, and financial incentives to promote renewable energy development. Policy mak- ers and regulators have gradually learned that the choice of policy mechanism, the features of policy design, the setting of tariff levels, and the compatibility of different instruments are all crucial aspects of an effective and economically efficient regime. Indeed, policy and regulatory frameworks have been repeatedly reformed and adjusted in most countries that have introduced renewable energy policies. For example, almost all countries using feed-in tariffs to promote one or many segments of the renewable energy market–– different types of technologies, project scales, or geographic areas–– have successively adjusted the tariff levels to avoid high infra-marginal rents and policy costs or subsidy volumes. In this process, countries have introduced automatic adjustment mechanisms and other design features to ensure that the cost to taxpayers or consumers is acceptable while also lowering regulatory uncertainty for potential investors. The design of auction mechanisms to competitively determine the price of renewable energy has also required adjustments to avoid speculative behavior and ensure the construction of plants (for example, bid bonds, guarantees on project completion, penalties on construction delays, and so on). The use of price- and quota-based instruments is necessary in the absence of externality pricing. Today, many countries have adopted emissions trading frameworks and have also learned many lessons in the process of establishing carbon markets. Ultimately, it is clear that a policy package needs to be not only effective in terms of the capacity deployed and electricity generated but also economically efficient—that is, delivered at the lowest possible cost while remaining sustainable and socially inclusive. Source: Jacobs 2012; Elizondo-Azuela and Barroso 2011; IEA 2008. chapter 4: Renewable energy 182 Technology progress On the technology development front, there has been About 30 GW of solar PV was installed globally every year continuous progress in efficiency, and cumulative experi- between 2010 and 2012, bringing the total installed PV ence has translated into increasingly cost-effective solu- capacity from 40 GW to more than 100 GW (EPIA 2013). tions. For instance, the investment cost of wind energy fell In addition, total wind power capacity reached over 282 from $2,500/kilowatt (kW) in the mid-1980s to $630-1,270/ GW globally in 2012, representing an increase of almost 20 kW in 2012, while the cost of PV systems fell from about percent from 2011 (GWEC 2013). The market expansion of $7,000/kW to $750–$1,100/kW over the same period (IRE- renewable technologies in many regions of the world has NA 2013b) (figure 4.9). Similar trends occurred in the sug- also brought considerable cost reductions. For instance, arcane-based bioethanol industry (see learning curve in the cost of solar PV modules dropped by 42 percent in 2011 annex 2). while the cost of onshore wind turbines fell by 10 percent. Today, many countries manufacture solar PV modules, although China, the United States, Japan, Canada, and Norway have the largest market shares (China supplies 30 percent of the global market volume). Wind turbines, on the other hand, are manufactured mainly by China, Denmark, the United States, Spain, Germany, and India. 100.00 global average turbine/module selling price (2011 usd/w) 1979 2006 c-si price increase 1992 due to polysilicon shortage 10.00 1998 2002 2004 1984 2009 2010 2011 1.00 2012 22% price reduction for each doubling of cumulative volume 0.10 1 10 100 1,000 10,000 100,000 1,000,000 cumulative volume installed capacity (wind) / production (solar)(mw) FIGURE 4.8 Learning curves for wind and solar PV modules solar thin film panel - cdte (irena 2012) solar panel crystaline c-si - cdte (irena 2012) onshore wind power plants (us) (ipcc 2011) Source: IRENA analysis with data from EPIA and Photovoltaic Technology Platform (2011), IPCC (2011), Bazilian and others (2012), and Sologico (2012). Note: PV = photovoltaic. 183 Global tracking framework Critical for the widespread integration of renewable energy Technology innovation has played a critical role in the sources into power systems will be the introduction of development and commercialization of renewable energy technologies, operational protocols, and practices to solutions. According to BNEF, UNEP , and Frankfurt School manage the issue of variability. This can involve a number (2012), despite the fact that corporate research and devel- of options, including more flexible generation from opment (R&D) in renewable energy has decreased over nonvariable sources (renewable and fossil), grid extension, the past few years, venture capital and government R&D demand-side management, and storage. Although energy increased substantially between 2004 and 2011 (with CA- storage solutions are in different stages of development, GRs of 30 and 14 percent, respectively). they are quickly progressing along the technology development path (IRENA 2012, Chen and others 2009) (box 4.2). Box 4.2 Electricity storage At present, the only commercial storage option is pumped hydro power by which surplus electricity (for exam- ple, electricity produced overnight by base-load coal or nuclear power) is used to pump water from a lower to an upper reservoir. The stored energy is then used to produce hydropower during daily high-demand periods. Pumped hydro plants are large-scale storage systems with a typical efficiency between 70 percent and 80 percent, which means that a quarter of the energy is lost in the process. Other storage technologies with different characteristics (that is, storage process and capacity, conversion back to electricity and response to power demand, energy losses and costs) are currently in demonstration or pre-commercial stages, including compressed air energy storage (CAES), flywheels, electrical batteries and vanadium redox flow cells, super capacitors, and superconducting magnetic storage. In addition, thermal en- ergy storage is under demonstration in concentrating solar power (CSP) plants where excess daily solar heat is stored and used to generate electricity at sunset. No single electricity storage technology scores high in all dimensions. The technology of choice often depends on the size of the system, the specific service, the electricity sources, and the marginal cost of peak electricity. For example, pumped hydro currently accounts for 95 percent of the global storage capacity and still offers a considerable expansion potential but does not suit residential or small-size applications. CAES expansion is limited due to the lack of suitable natural storage sites. Electrical batteries have a large potential with a number of new materials and technologies under development to improve performance and reduce costs. Heat stor- age is practical in CSP plants. The choice between large-scale storage facilities and small-scale distributed storage depends on the geography and demography of the country, the existing grid and the type and scale of renewable technologies entering the market. While the energy storage market is quickly evolving and expected to increase 20-fold between 2010 and 2020, many electricity storage technologies are under development and need policy support for further commercial deployment. Electricity storage considerations should be an integral part of any plans for electric grid expan- sion or transformation of the electricity system. Storage also offers key synergies with grid interconnection and methods to smooth the variability of electricity demand (demand-side management). Source: IRENA 2012. chapter 4: Renewable energy 184 Evolution of investment BNEF reports that global investments in renewable in 2010. This increase in investment and capacity came -source-based power generation and fuels reached a re- at a time when the cost of renewable power equipment cord of $277 billion in 2011 (figure 4.10) (BNEF database was falling rapidly. Furthermore, renewable energy tech- 2012).11 This was more than six times the figure for 2004 nologies continued to attract investments despite overall and almost twice the total investment in 2007, the last year uncertainty about economic growth and policy priorities in before the acute phase of the recent global financial crisis. developed countries. In 2011 renewable-source-based power generation capacity (excluding large hydro) accounted for 44 percent of new generation capacity added worldwide, up from 34 percent 25 23 20 300 277 17 15 250 10 228 5 US dollars (billions) 200 0 2011 170 154 150 143 other developing 97 brazil 100 india 65 china other developed 50 39 united states europe 0 2004 2005 2006 2007 2008 2009 2010 2011 Figure 4.9 Global investments in renewable energy by country, 2004–2011 (US$ billion) Source: BNEF database 2013; BNEF, UNEP, and Frankfurt School 2012. Note: Data include investments in hydropower plants with capacities in the range of 1-50 MW. Investment data in- clude the following categories: asset finance, public markets, venture capital and private equity, investments in small distributed capacity, government R&D, and corporate R&D Developing countries, especially emergent economies, economies, most notably in Thailand, Indonesia, Ukraine, made up 35 percent of this total investment, compared to Romania, Bulgaria, Turkey, and Costa Rica. 65 percent for developed economies. Indeed, Brazil, China, and India together accounted for about $74 billion, or 27 Overall, developed countries led the way in investments percent of the total new investments in renewable energy in solar initiatives, while developing economies had the globally in 2011 (BNEF, UNEP , and Frankfurt School 2012). upper hand in new investments in wind-based generation. Renewable energy markets are also expanding into middle- and lower-income developing nations. In 2011 an estimated 8.4 percent of total new investments in renewable energy took place in developing countries outside large emergent 11 Almost 90 percent of this investment went to either solar (57 percent) or wind-based projects (33 percent). 185 Global tracking framework Deployment diversification Development of newer renewable deployment—other increased from 23 in 2005 to 38 in 2010. Solar has also than traditional biomass and hydropower—is becom- seen a significant increase in terms of the number of coun- ing increasingly widespread, with growth shifting beyond tries that reached this threshold in these five years, grow- traditional support markets in the developed world. The ing from 3 to 15 countries in total. Biomass and waste also number of countries with cumulative renewable source– achieved a high level of capacity deployment, expanding based electricity capacities above 100 megawatts (MW) in- by another 5 countries in 2005–2010. creased significantly in the period 2005–2010. The number of countries with wind-based capacity above this threshold 40 9 32 9 8 24 3 16 27 29 1 23 20 8 5 5 14 6 6 3 0 2005 2010 2005 2010 2005 2010 2005 2010 solar geothermal biomass & Waste wind Figure 4.11 Number of countries whose cumulative installed capacity exceeded 100 MW as of 2010 OECD NON-OECD Source: EIA database (2012). Note: OECD = Organisation for Economic Co-operation and Development. chapter 4: Renewable energy 186 Section 3. Country performance Key drivers for country support to renewable energy development The introduction of renewable energy brings multiple bene- the production of ethanol from sugarcane to decrease de- fits to society. Indeed, most countries deploying renewable pendency on imported fossil fuels for transport. Also, in energy are motivated by a combination of social objectives many fuel-dependent countries where the avoided cost that vary depending on their economic conditions, re- of power generation or heating is high, renewable ener- source endowments, and strategic priorities. This combi- gy represents a competitive alternative that comes without nation of objectives may include reducing greenhouse gas an incremental cost or additional burden on taxpayers or emissions and local environmental impacts, enhancing consumers. energy security, stimulating economic and industrial devel- opment, and increasing access to reliable, affordable, and Indeed, the justification of renewable energy deployment clean modern energy services. on economic grounds, including a solid understanding of the full range and valuation of benefits, is essential to policy Many countries have strongly supported renewable energy making and regulatory design. as part of an environmental and climate change policy in addition to other social objectives. For instance, renew- ables play a key role in the climate change mitigation strat- egies of all EU member states, Norway, Australia, Mexico, $277 billion invested in renewable India, and many others. energy in 2011, more than six times the investment in 2004 The overall contribution of renewable energy to local envi- ronmental sustainability has also driven many countries to introduce specific renewable energy policies, especially in A few high- and middle-income economies have also nations where the consumption of traditional biomass or strongly focused on renewable energy to support economic the use of fossil fuels results in acute air pollution levels, growth and job creation. Denmark, Germany, China, and biodiversity loss, or deforestation. In Nepalese villages, for India among others have provided specific incentives to example, modern renewable energy systems have been stimulate technology innovation, promote the domestic deployed to mitigate the negative impacts on biodiversity manufacture of renewable energy equipment, and create and deforestation resulting from the unsustainable use of a local market for companies installing and developing biomass. China, in particular, has explicitly aimed at renewable energy projects. Germany, for instance, has increasing renewable energy to lower and avoid the regional spent more on PV R&D than any other country in Europe, and local environmental impacts of coal-based power gen- with the aim of growing a competitive export industry of eration. Many other countries have also explicitly supported components, final products, and manufacturing equipment renewables to reduce local environmental impacts. (IPCC 2011). At the same time, energy security is a key strategic prior- Renewable energy can also contribute to increasing energy ity of almost all nations. Renewable energy can improve access in peri-urban and rural areas. Many developing security of supply in a variety of ways, including reducing countries (including, for example, Argentina, Bolivia, Brazil, dependence on imported fuels, contributing to technological Bangladesh, China, India, Sri Lanka, Tonga, and Zambia) and fuel diversification, hedging against fuel price volatility, have introduced energy access programs and policies to and enhancing the national trade and fiscal balances. increase access to energy services with renewable-energy Since the early 1970s, for example, Brazil has promoted -based solutions. 187 Global tracking framework Growth of renewable energy markets Fast-moving countries Renewable energy sources beyond traditional biomass percent of this volume was produced and consumed by and hydropower, including modern solid biomass, biofu- high-income and emerging economies, most notably the els, biogas, waste, geothermal, wind, solar, and marine United States, Europe, Japan, Brazil, China, and India. energy, contributed 5.4 percent to TFEC in 2010. About 97 share of re in tfec hics 40% UMICS LMICS 35% Sweden LICS 30% Finland Brazil 25% Congo, DRC Sri Lanka 20% Chile Sudan Tanzania Ghana Cambodia 15% Philippines Thailand India Turkey Spain Germany 10% France Haiti Benin Mexico Poland Zimbabwe Nigeria Colombia Canada Vietnam 5% Indonesia n.Korea Pakistan Italy China, PRC Russian Argentina USA Myanmar Japan s. Africa Federation 0% Ethiopia compound annual -5% -2% 1% 4% 7% 10% 20% 30% 40% growth rate, -5% 1990-2010 Figure 4.11 Renewable energy’s share (excluding traditional use of biomass and hydropower) of country TFEC and CAGR, 1990–2010 Source: Authors’ analysis based on IEA 2012d. Note: Figure includes the use of modern biomass. (DRC and Tanzania appear due to their high use of modern biomass in the industrial sector). Bubble size depicts volume in terms of PJ of final energy consumption. The negative CAGRs exhibited in Turkey, Mexico, Indonesia, Colombia, Russia, and Benin are primarily due to reduction in the use of non- traditional solid biomass (most notably in industry). TFEC = total final energy consumption; CAGR = compound annual growth rate; DRC = Democratic Republic of Congo. Indeed, the development of these renewable energy mar- In hydropower Mozambique, China, Vietnam, Iceland, and kets has been led by a small group of pioneering countries Albania increased their consumption rapidly between 1990 that consistently introduced innovation on the technology, and 2010, while China, Brazil, the United States, Canada, policy, and financing fronts in 1990–2010. Norway, India and Russia maintained very high volume of consumption (figure 4.12). China, Germany, Italy, and Spain have rapidly increased their renewable-source-based consumption, while Swe- den, Finland, and Brazil have achieved high shares of renewable energy in their total domestic consumption (as illustrated in figure 4.11).12 12 Bubble charts for each of the technologies considered are included in annex 3. chapter 4: Renewable energy 188 share of re in tfec hics 60% Tajikistan UMICS Norway LMICS 50% LICS 40% Iceland 30% Georgia Brazil Kyrgyzstan Albania 20% Sweden Costa Rica Uruguay Mozambique Canada 10% China, PRC compound annual Russian Venezuela Vietnam growth rate, Federation 1990-2010 0% usa India -10% -3% -1% 1% 3% 5% 7% 9% 13% 15% Figure 4.12 Share of hydro in country TFEC and CAGR, 1990–2010 Source: Authors’ analysis based on IEA 2012d. Note: HICs = high-income countries; LICs = low-income countries; LMICs = lower-middle-income countries; UMICs = upper-middle-income countries; TFEC = total final energy consumption; CAGR = compound annual growth rate. In 2010 the volume of renewable energy sources other than traditional biomass and hydropower consumed by Brazil, China, and India represented 76 percent of the vol- 1,000 EJ ume consumed in the United States and European coun- is the cumulative tries combined. When including hydro, these three emerg- amount of renewable energy supplied globally ing economies are among the top five renewable energy between 1990 and 2010; equivalent to consumers in the world (as shown in figure 4.13). the cumulative final energy consumption of China and France over the same period. China, in particular, has rapidly increased its hydro base in electricity and introduced bold industrial and renewable energy policies and strategies to promote the scale-up of wind-based electricity generation and solar PV. The United States also stands out for the volume of renew- able energy consumed, mainly due to its high consump- tion of biofuels (most in the form of corn-based bioetha- nol) and wind-based electricity generation. Brazil is ranked third in renewable energy consumption for its aggressive and pioneering support of sugarcane-based bioethanol production, its use of bagasse-based combined heat and power, and its high share of hydropower in electricity. 189 Global tracking framework Table 4.6 lists the top five countries by region in terms of annual capacity additions in electricity from 2009 to 2010. Incremental renewable energy consumption in the period 1990-2010 (PJ) 94 wind Venezuela marine Pakistan 95 solar Chile 112 geothermal Congo, DRC 118 hydro United Kingdom 142 liquid biofuels Finland 138 biogas Austria 139 modern biomass Nigeria 159 waste Poland 198 Canada (0) 204 France (1) 209 Thailand 214 Sweden (4) 221 Spain 297 Italy 340 India 546 Germany 730 Brazil 1,719 United States 2,274 China, PRC 2,804 -500 200 900 1600 2300 3000 Figure 4.13 Top 20 countries: Incremental renewable energy consumption in the period 1990-2010 (PJ) Source: Authors’ analysis based on IEA 2012d. Note: Figure excludes traditional biomass. DRC = Democratic Republic of Congo. 56% of electricity generation in Latin America comes from renewable sources - higher than any other region of the world chapter 4: Renewable energy 190 Solar and Geo- Biomass Hydro Wind Total marine thermal and waste Canada United States United States United States United States United States North America United States Canada Canada Canada Canada Germany Spain Germany Italy Germany Germany Switzerland Germany Italy Germany Austria Italy Europe Italy France Spain Italy Spain Sweden UK France UK France Croatia Italy Belgium Netherlands UK Bulgaria Poland Slovakia Czech Rep. Poland Ukraine Bulgaria Bulgaria Poland Bulgaria Eastern Europe Slovakia Hungary Hungary Slovakia Hungary Romania Czech Rep. Poland Hungary Slovakia Czech Rep. Romania Romania Romania Armenia Azerbaijan Armenia Caucasus and Kazakhstan Azerbaijan Central Asia Kazakhstan Turkey Turkey Israel Turkey Turkey Turkey Western Asia Israel Cyprus Israel Israel Cyprus Cyprus China China Japan Japan China China Eastern Asia Japan Japan China S. Korea Japan S. Korea S. Korea S. Korea S. Korea Philippines Vietnam Philippines Philippines Laos Thailand Indonesia Laos Southeastern Myanmar Myanmar Asia Vietnam Indonesia India India Bangladesh India India Iran Iran Iran Southern Asia Nepal Bangladesh Nepal Maldives Oceania Australia Australia Australia N. Zealand Australia N. Zealand N. Zealand 191 Global tracking framework Solar and Geo- Biomass Hydro Wind Total marine thermal and waste Brazil Brazil Mexico Brazil Brazil Ecuador Mexico Chile Ecuador Latin America Peru Chile Peru and Caribbean Guatemala Dominica Chile Panama Nicaragua Guatemala Algeria Egypt Egypt Morocco Morocco Northern Africa Tunisia Tunisia Algeria Ethiopia Kenya Uganda Ethiopia Sierra Leone S. Africa Sierra Leone Sub-Saharan Uganda Eritrea Uganda Africa Kenya Kenya Guinea Guinea China China Germany N. Zealand Brazil China Brazil United States Italy Italy China Germany World Turkey India Japan United States Germany United States India Spain Spain Turkey Austria Italy Ethiopia Germany France Philippines India India Table 4.6 Top five countries in annual capacity additions, 2009–2010, by region Source: U.S. Energy Information Administration database 2012. In addition to these pioneering countries, many others have begun to introduce renewable energy for several rea- sons, most notably energy security and local environmen- 62% tal sustainability. of total final energy consumption In Africa, for instance, countries such as Kenya, Uganda, in Africa comes from renewable sources Ethiopia, Mali, and Tanzania are consistently progressing including traditional biomass - higher than any other region of the world toward the deployment of renewable energy. Other devel- oping nations, such as Bangladesh, Honduras, Nepal, and Maldives, are also working toward assessing the magni- tude of their renewable energy resource potential. chapter 4: Renewable energy 192 100,000 MIN/MAX RANGE GLOBAL TECHNICAL POTENTIAL (EJ/YR, LOG SCALE) 10,000 1,000 GLOBAL HEAT DEMAND 2010, 167 EJ 100 GLOBAL PRIMARY ENERGY SUPPLY, 2010 534 EJ GLOBAL ELECTRICITY 10 DEMAND 2010, 64 EJ 1 Geothermal Hydropower Ocean Wind Geothermal Biomass Direct Energy Energy Energy Energy Solar ELECTRICITY HEAT PRIMARY ENERGY figure 4.14 Estimated global technical RE potential Source: IPCC 2011. High-impact opportunities 75% Technical potential of the world’s un- Technical studies have consistently found that total global exploited potential in hydropower is located in Africa, Asia technical potential for renewable energy is substantially and South America. higher than global energy demand projected to 2050 (IPCC 2011) (figure 4.14). Technical potential for solar energy is the highest among renewable energy sources, challenges. For instance, scaling up the use of renewable but substantial potential also exists for biomass, geothermal, energy will require the proactive planning of transmission hydro, wind, and ocean energy. systems, often on a broader regional scale, to allow for optimization of sources and balancing of variability. In fact, Available data suggest that most of this technical potential regional integration can allow increased resource use effi- is located in the developing world (figure 4.15 and table ciency due to seasonal and dispatching complementari- 4.7). For instance, at least 75 percent of the world’s unex- ties (for example, among hydro, wind and solar resources). ploited potential in hydropower is located in Africa, Asia, This can be particularly important in regions with a high and South America, and about 65 percent of total geother- potential for large hydropower (for example, South Asia), mal potential is found in non-OECD countries (IJHD 2011; or regions where resource endowments exhibit high com- IPCC 2011). Also, many developing nations are located plementarities (for example, East Africa). in the solar belt, the area with the highest solar irradiance across the globe. At the same time, the parallel deployment of energy effi- ciency measures that reduce peak demand on the grid Clearly, the challenge will be to capture and utilize a sizable while easing transmission losses and bottlenecks will share of this vast global technical potential in a cost-effec- help make renewable energy objectives more attainable. tive and environmentally and socially sound manner. Indeed, energy systems will need to be planned and oper- ated with both the use of renewable sources and deploy- Meeting a higher share of global consumption with re- ment of energy efficiency measures in mind. newable energy sources will pose important technical 193 Global tracking framework figure 4.15 Hot spots: Potential for hydro, solar, wind, and geothermal Source: MAP PREPARED BY AUTHORS with data from Ásmundsson 2008; IJHD 2011; IPCC 2011; McCoy-West and others 2011; UNEP and NREL/U.S. DOE 2012. The following table lists countries with high potential for renewable energy development by region and source. Large Small Region Solar Wind Geothermal hydropowera hydropowerb EUR Greece, southern Iceland, Baltic Austria, France, Italy, Norway, Bosnia and Her- Italy, southern Countries, Corsica, Germany, Iceland, Sweden zegovina, Croatia, Portugal and Spain northern Spain, Italy, Portugal Estonia, Finland, northern Europe, Greece, Ireland, Scandinavia, Latvia, Luxembourg, southern France, Macedonia (FY- southern Italy, ROM), Montenegro, Switzerland, the Norway, Poland, United Kingdom Serbia, Spain EEU Balkan countries, Russia Hungary, Ukraine, Russia, Ukraine Romania, Russia, Slovak Republic, Bulgaria, Czech Republic CCA Kazakhstan, Georgia, Kyrgyz- Armenia, Azer- Tajikistan, stan, Tajikistan, baijan, Georgia, Turkmenistan, Kazakhstan, Tajiki- Uzbekistan stan, Uzbekistan WAS Central China, Iraq, Black Sea coun- Tonga, Turkey Iraq, Turkey Israel,Turkey Arabian Peninsula, tries (Turkey), Urals India, Turkey region (Russia), EAS Southwestern China, Japan Japan, China, Japan, Taiwan China, northeast- Mongolia ern China, Japan, Mongolia chapter 4: Renewable energy 194 Large Small Region Solar Wind Geothermal hydropowera hydropowerb SEA Parts of Indonesia Indonesia, Philip- Cambodia, Indone- Philippines, pines, Thailand sia, Laos, Malaysia, Thailand Myanmar, Vietnam SAS Eastern Iran, India, Nepal, Afghanistan, India, Iran, Paki- southern Pakistan Pakistan Bhutan, India, Iran, stan, Sri Lanka Nepal, Pakistan, NAF Algeria, Egypt, Algeria, Egypt Egypt Lybia, Morocco SSA Saharan countries Central Chad, Ethiopia, Kenya Angola, Ethiopia, Burkina Faso, (particularly Mau- eastern Africa, Cameroon, Congo, Burundi, Cameroon, ritania, Mali, Niger, Madagascar, Gabon, Guinea, Central African Chad, Sudan), Namibia, western Madagascar, Republic, Chad, eastern Africa Sahara, Somalia, Mozambique, Ethiopia, Ghana, (Somalia and South Africa, Zimbabwe Guinea, Mauritius, Ethiopia), southern Sudan Mozambique, Africa (particularly Namibia, South Namibia, South Africa, Sudan, Africa, and Uganda, Zambia Botswana) NAM Southwestern Alaska, central Mexico, United Canada, Mexico, Mexico, United North America (the North America States United States States U.S. Southwest, (the United States, the northwest and Canada), Green- Yucatan Peninsula land, northeastern of Mexico) North America (the United States, Canada) LAC Andean region Central America, Costa Rica, Domi- Argentina, Bolivia, Belize, Brazil, (Peru, Bolivia, northeastern Brazil, nica, El Salvador, Brazil, Chile, Colombia, Domi- Ecuador, northern Patagonia Guatemala, Nica- Colombia, Costa nica, El Salvador, Chile), Caribbean (Argentina, Chile) ragua, St. Kitts and Rica, Ecuador, Grenada, Honduras, islands, El Salvador, Nevis, St. Vincent Paraguay, Peru, Nicaragua, Guatemala, Nicara- and the Grenadines Venezuela Panama, Suriname, gua, northeastern Uruguay Brazil Oceania Australia, Indonesia, Australia and New Australia, Fiji, Australia, New New Caledonia, Philippines Zealand (south- French Polynesia, Zealand French Polynesia, west, northeastern New Zealand, Papua New Guinea coastal zones, and New Caledonia, Tasmania), parts of northern Mariana Papua New Guinea Islands, Papua New Guinea, Samoa, Solomon Islands, Vanuatu Table 4.7 Hot spots: Countries with high potential in renewable energy (as suggested from available data) Source: Ásmundsson 2008; IJHD 2011; IPCC 2011; McCoy-West and others 2011; UNEP and NREL/U.S. DOE 2012. Note: CCA: Caucasus and Central Asia; EAS: Eastern Asia; EEU: Eastern Europe; EUR: Europe; LAC: Latin America and Ca- ribbean; NAF: Northern Africa; NAM: North America; OCEANIA: Oceania; SAS: Southern Asia; SEA: Southeastern Asia; SSA: Sub-Saharan Africa; WAS: Western Asia. a. Total hydropower for countries with technical potential greater than 100,000GWh/yr. b. Definitions of small hydropower vary by country but are generally in the range of 5–30 MW. 195 Global tracking framework Economic potential Renewable energy is becoming increasingly competitive it competitive costs, especially in non-OECD countries. In when compared to fossil-fuel-based alternatives (figure particular, a recently dominant feature of renewable energy 4.16). For instance, the levelized costs of small- and large- market dynamics has been the falling price of photovoltaic scale hydropower and on-shore wind are already in the modules, which are making this technology more com- same cost range as fossil-fuel-fired electricity generation. petitive. Solar PV is on grid-parity in areas with very high When the resource potential or quality is high, biomass solar irradiance, such as North Africa, Saudi Arabia and and geothermal-based power generation may also exhib- Australia. 0.5 diesel-fired electricity cost range 0.4 0.3 2011 USD/kWh 0.2 0.1 fossil fuel-fired electricity cost range in oecd 0.0 Onshore wind CSP Solar PV: large Solar PV: small Offshore wind Biomass Hydro Small Hydro Large Geothermal Onshore wind CSP Solar PV: large Solar PV: small Biomass Hydro Small Hydro Large Geothermal OECD non-OECD figure 4.16 Levelized costs of power generation, 2012 Source:IRENA 2013b Note: Levelized cost represents the per kilowatt-hour cost of building and operating a generating plant over an assumed financial life and duty cycle. While levelized costs are a convenient summary measure of the overall competitiveness of different generating technologies, the measure does not cover the overall system costs. The full cost of introducing different generation options (especially variable) depend on the specific conditions of the system; for example, the extent to which variable sources match the demand profile and complement the mix of existing sources and technologies. At the same time, renewables are competitive in countries oil price levels and changes on power generation costs vulnerable to high and volatile oil prices or those with high is significant in these countries, and so electricity tariffs electricity prices; this is especially true in net-oil-importing are very high. For example, the average residential tariff in countries particularly landlocked countries and SIDS. For Central America for consumption of 100 kWh reached 15 instance, all countries in Central America and the Carib- cents/kWh in 2010 (CEPAL 2011). In this subregion, only bean are net oil importers. In both subregions, oil provides 9 percent of power generation is supplied by renewables more than 90 percent of primary energy needs and sup- other than hydropower, mainly geothermal, but also wind plies more than half of power generation. The impact of (CEPAL 2011). chapter 4: Renewable energy 196 In West Africa, where many countries are net oil importers, at just $88 billion (IEA 2012c). Phasing out fossil fuel sub- residential electricity tariffs are in the range of 15–30 cents/ sidies while incorporating carbon-pricing mechanisms that kWh (for consumption of 100 kWh), mainly due to high oil fully reflect the externality cost of fossil-fuel-based energy prices and the need to use emergency thermal genera- would be critical steps toward accelerating the scale-up of tion (Briceño-Garmendia and Shkaratan 2011). In Uganda renewable energy. the levelized cost of diesel-HFO-based thermal generation is roughly 20–25 cents/kWh, much higher than the costs Nevertheless, levelized cost comparisons between variable of biomass, small hydropower, or wind-based generation sources of renewable energy (notably wind and solar) and (estimated at 8 cents, 10 cents, and 12.4 cents per kWh, others (such as large hydro, geothermal and fossil fuels) respectively). In countries with such problems, renewable are not straightforward. The full cost of introducing different energy has the potential to play a key role in hedging generation options (especially variable) depends on the against high and volatile fuel oil prices. specific conditions of the system—for example, the extent to which variable sources match the demand profile and Indeed, more than 55 developing economies exhibit high complement the mix of existing sources and technologies. oil dependencies with imports supplying at least 50 per- cent of their domestic consumption needs. At the same Ultimately, attaining the SE4ALL target for renewable en- time, almost all of the 53 small island developing states ergy depends to a large extent on the efforts of countries (SIDS) are completely dependent on oil and gas.13 Even with high energy demand and consumption. These coun- when considering the diversity of available fuels and ener- tries (including most developed and emerging economies) gy sources, developing countries are more vulnerable (see would have to significantly increase their efforts to scale Figure 4.17). up renewables, introducing effective and efficient policy mechanisms across all segments of the energy sector and The competitiveness of renewable energy still depends on strengthening the overall business environment to attract its relative cost vis-à-vis fossil fuels. Today, fossil fuels ben- and leverage different sources of finance. efit from huge subsidies of around $523 billion annually around the world, while renewable energy support stands figure 4.16 DIVERSITY INDEX OF PRIMARY ENERGY MIX (BASED ON HERFINDAHL-HIRSCHMAN INDEX HHI) Source: Prepared by authors from IEA data following Bacon and Kojima (2008), Kojima (2012) Note: The energy sources considered in the primary energy mix are natural gas, oil and oil products, coal (coal and peat), hydropower, other renewables (biofuels, waste, geothermal, solar, wind, other), and nuclear. Higher index values indicate lower diversity in primary energy mix, and therefore, increased vulnerability to changes. 13 A notable exception is Trinidad and Tobago, an island country that produces both oil and gas. 197 Global tracking framework Section 4. The scale of the renewable energy challenge This section looks at the scale of the challenge to double scenarios, and attempts to draw some lessons about the the proportion of renewable energy in the global energy conditions needed to achieve the target. Finally, it high- mix. It does this by comparing current trends with the tra- lights some of the main challenges associated with this jectory required to meet the target. It then looks at projec- ambitious target, discusses opportunities, and concludes tions of the proportion of renewable energy under various with general policy recommendations. Current trends in the use of renewable energy As shown in section 2 of this chapter, there have been rapid But as shown in figure 4.18, overall global energy con- rises in the deployment of several renewable energy sectors sumption has also been rising at nearly the same rate in recent years. Generation from wind and solar has grown (1.5 percent). As a result, despite the sustained growth in at double-digit annual percentage rates, and the transport renewable energy production, the overall level of renew- fuel sector has also grown strongly. Overall, the level of ables as a proportion of global energy needs has essen- energy generation from renewables has been growing tially remained stable, at close to 18 percent. steadily, at a 2 percent CAGR (in terms of TFEC), and has increased in absolute terms by 36 percent since 1990. 500 Total Energy Consumption Total Energy Renewables Consumption Consumption - Trends Continued 400 300 200 Renewables - SE4ALL Target Growth 100 Renewables - Current Trends Continued 0 1990 2000 2010 2020 2030 figure 4.18 Global trends in renewable energy and total final energy consumption, 1990–2030 Source: Authors’ analysis based on IEA 2012d. chapter 4: Renewable energy 198 Figure 4.18 also shows that if current trends continued to 2030, renewable energy consumption would rise by 56 percent to around 95 EJ. But if trends in TFEC were also to 19.4 % is the share of continue to 2030, this would increase by 48 percent to 490 EJ, and the share of renewables in the global energy mix renewable energy expected to 2030 if current global would increase only to 19.4 percent. trends were to continue- barely one percent higher than in 2010 If overall energy consumption were to stabilize, doubling the contribution of renewables would imply consumption of around 118 EJ by 2030, requiring an annual growth rate This highlights how challenging it will be to meet this goal, of 3.5 percent (a 50 percent increase over current levels). If and underscores the importance of the link between the current overall growth in energy demand continues, meet- SE4ALL goals for renewable energy, energy efficiency, and ing the target would require the consumption of renew- energy access. Achieving the renewable energy goal is ables to triple to around 177 EJ by 2030, an annual growth likely to depend both on rapid expansion of deployment rate of 5.9 percent, which is 2.5 times the current growth rates for renewables as well as on considerable progress rate. Given the likely reduction in the “traditional” use of being made in reducing overall global energy consumption biomass, the increase in sustainable renewable produc- via energy efficiency improvements. tion would have to be even larger. Future scenarios There are a wide range of energy scenarios that consider such as Greenpeace and the World Wide Fund for Nature how energy demands may evolve in the future and what (WWF), as well as major oil companies, such as BP , Exxon, the role of renewable energy in the global energy mix will and Shell, develop and publish projections for global ener- be. These scenarios use different approaches: some are gy demand and supply. based on policy considerations; others are based on a least-cost modeling approach, given a portfolio of technol- A detailed review of all the relevant modeling exercises is ogy options; others are goal-oriented exercises that place not attempted here, but a short summary of major projec- constraints on future scenarios (for example, by setting tions for energy demand and supply in 2030, which high- global emission limits). Scenario analysis also uses differ- lights the wide range of projections of total final energy ent assumptions about many of the essential parameters, consumption and the renewable energy share (from 18 including those relating to population and economic devel- percent to 45 percent), is given in table 4.8. opment and how these are coupled with energy demand, the availability and costs of technologies, and so on. Several national and international organizations, such as the IEA, the EIA, the International Institute for Applied Sys- tems Analysis (IIASA), the European Union, and NGOs 199 Global tracking framework Renewables Renewables Organization Scenario TPED (EJ) TFEC (EJ) (%) (%) 2010 Energy Bal- IEA Statistics 2010 533 13 324 18 ances NPS 2030 687 17 425 21 IEA 2012c a 450 ppm 2030 605 23 384 27 EWS 2030 380 22 IEA 2012 a 2D 600 Reference 684 13.9 EIA 2011 b High oil case 733 13.6 Low oil case 655 13.9 ReMind 590 32 IPCC 2011c MINICAM 608 24 MESAP/PlaNet 474 39 GEA 1 446 29.8 312 36.7 GEA 2 458 29.7 321 36.3 GEA 3 457 27.9 311 34.4 IIASA 2012d GEA 4 443 33.3 303 40.7 GEA 5 456 28.1 324 34.6 GEA 6 454 34.7 314 40.9 ExxonMobil 2011e 618 14 478 24% BP 2012 f 683 14 Mountains 749 14 Shell 2013 Oceans 777 17 Greenpeace/EREC/ Revolution 340 45% GWEC 2012 WWF, Ecofys/OMA 319 42% 2012 Table 4.8 Energy demand projections and renewable energy share in major energy scenarios, 2030 Source: : IEA 2010, 2011, 2012a, 2012c; IPCC 2011; IIASA 2012; ExxonMobil 2012; BP 2012; Shell 2013; Greenpeace, EREC, and GWEC 2012; WWF, Ecofys, and OMA 2011. Note: TPED = total primary energy demand; TFEC = total final energy consumption. a. TPED is based on the physical energy content method, which assumes 33 percent efficiency for nuclear; 100 percent efficiency for renewable energy resources like hydro, wind, and solar PV; 50 percent for CSP; and 10 percent for geothermal. b. TPED is based on the substitution method. c. In all scenarios, the direct equivalent method is used to measure primary energy demand. d. TPED is based on the direct equivalent method, assuming 100 percent efficiency for both non-biomass renewables and nuclear. e. The data are based on interpolations between the data points for 2025 and 2040. f. The primary energy values of nuclear and hydroelectric power generation, as well as electricity from renewable sources, have been derived by calculating the equivalent amount of fossil fuel required to generate the same volume of electricity in a thermal power station, assuming a conversion efficiency of 38 percent (that is, the average for OECD thermal power generation). chapter 4: Renewable energy 200 The following subsections summarize the major conclu- modeling work carried out in support of the IEA’s World sions of three major modeling exercises: the IPCC analysis Energy Outlook (IEA 2011); and the IIASA’s Global Energy described in its Special Report on Renewable Energy; the Assessment scenario analysis. United Nations Framework Convention on Climate Change’s (UNFCCC’s) analysis The IPCC Special Report on Renewable Energy reviewed a low-carbon options to be deployed. Where carbon wide range of modeling exercises, covering 164 scenarios capture and storage (CCS) or nuclear generation is from 16 different large-scale integrated models, and drew constrained, renewable energy plays a larger role. some general lessons that provide a relevant context for understanding the SE4ALL goal: }} The range of figures for the proportion of renew- ables in the global energy mix also varies widely. }} The models differ widely (by a factor of three) More than half the scenarios show a contribution of in terms of the anticipated growth of overall global over 17 percent, with the highest renewable energy energy production and demand. share reaching 43 percent. }} Renewable energy deployment plays a substan- }} The scenarios show that growth in renewable tially higher role in scenarios associated with ambi- energy will be worldwide and not constrained to tious GHG emission targets. For scenarios targeting particular regions, although renewable energy will atmospheric carbon dioxide concentrations (CO2) become most significant in emerging and develop- at levels below 440 ppm, the median deployment ing economies, where growth in energy demand is level for 2030 is 139 EJ with the highest level of likely to be focused. The scenarios also show that 252 EJ. But these low-emission scenarios exhibit the full spectrum of renewable energy technologies a wide range of renewable energy deployment will be deployed, with no dominant technology, levels, depending on assumptions about the mix of although modern bioenergy, wind, and solar energy will make the largest contributions. The IEA’s World Energy Outlook scenarios Table 4.7 shows the primary energy demand today and in vigorous policy action is taken in the years up to 2020 and 2030 according to the three IEA scenarios developed in that, thereafter, OECD and other major economies set the World Energy Outlook (IEA 2011). The Current Policies economy-wide emissions targets consistent with a trajec- Scenario (CPS) assumes that current policy commitments tory in which greenhouse gas levels are stabilized at a level are maintained. In this scenario, the level of renewables of 450 ppm of CO2 equivalent. In this scenario, the overall continues to grow sharply. But given the continuing rise level of renewables rises to 27 percent, which is still sig- of overall energy demand, the proportion of renewables nificantly below the 36.1 percent SE4ALL target. The emis- rises only slightly by 2030, to 18.4 percent. The New Poli- sions trajectory associated with the WEO 450 Scenario is cies Scenario (NPS) factors in the impacts of announced consistent with the 2°C Scenario (2DS) developed in the policy commitments to improving energy efficiency and context of IEA’s Energy Technology Perspectives 2012. In deploying low-carbon energy technologies. In this sce- the 2DS, renewables make up around 50 percent of elec- nario, the modeling indicates that the proportion of renew- tricity generation in 2030, and their share of total average ables would increase more rapidly, reaching 21.1 percent world electricity generation increases to 57 percent by by 2030. This is still significantly below the SE4ALL goal, 2050. however, highlighting that current policy commitments are insufficient to promote the type of change that the initiative The WEO 450 Scenario foresees a higher share of renew- envisions. ables and increased energy efficiency, and also includes ambitious deployment of CCS technology, assuming The WEO 450 Scenario sets out an energy pathway that is around 35 percent of CCS in coal-fired power generation consistent with a 50 percent chance of meeting the goal by 2030. Other scenarios use higher levels of renewable to limit the increase in average global temperature to 20C power generation instead of CCS technologies to reduce compared with preindustrial levels. It assumes that more global CO2 emissions. 201 Global tracking framework The IIASA’s Global Energy Assessment scenarios Within the suite of IIASA’s Global Energy Assessment -side policies to enhance efficiency, leading to pathways of (GEA) scenarios, a number of different energy pathways comparatively low energy demand (GEA-Efficiency), inter- explore alternative combinations of energy efficiency im- mediate demand (GEA-Mix), and high demand (GEA-Supply). provements and supply-side transformations to achieve ambitious targets for sustainable development (table 4.9). The second level of differentiation considers what dominant These include the goals of: transportation fuels and technologies might emerge, dis- tinguishing between systems in which conventional liquid }} Providing almost universal access to affordable fuel systems remain important and those where advanced clean cooking and electricity for the poor systems based on electricity/hydrogen take on a major role. For each combination, the diversity of the portfolio }} Limiting air pollution and health damages from of supply-side options is then considered: first, allowing energy use for the unconstrained deployment of the full range of tech- nology options (including renewables, nuclear, and CCS), }} Improving energy security throughout the world then looking at a range of ten options where deployment }} Limiting climate change of one or more these technology options is constrained. The main aim is to provide a better understanding of The third level of differentiation considers feasible supply what is needed to achieve these goals in terms of the -side transitions (for example, use of CCS) as well as combination of measures, time frames, and costs. This demand-side measures. involves consideration of the extent to which changes in the demand for energy services together with demand-side efficiency measures can reduce the energy consumed to provide mobility, housing, and industrial services. Alternatively, if there is less emphasis on reducing energy 21%–45% demand, then a more rapid expansion of a broader portfolio is the range in of low-carbon supply-side options is needed; the success- the share ful implementation of demand-side policies increases the of renewable energy in TFEC by 2030 flexibility of supply-side options (and vice versa). estimated by leading global energy models The scenarios are grouped in terms of three levels of differ- entiation. First, the level of energy demand is considered via three GEA pathway groups, which represent differ- ent emphases in terms of demand-side and supply-side changes. Each group varies, in particular, with respect to assumptions about the comprehensiveness of demand chapter 4: Renewable energy 202 % RE in Pathway Characteristics TFEC, 2030 Assumes limited potential of land-based mitigation options, including low po- tential for biomass; no negative emissions technologies (Bio-CCS) and limited GEA 1 potential for afforestation/reforestation measures. Transportation sector follows 36.7 an “advanced” trajectory (allowing for rapid expansion of, for example, electric vehicles). Assumes the phase-out of nuclear power generation in the medium term, and GEA 2 no CCS. Transportation sector follows an “advanced” trajectory (allowing for 36.3 rapid expansion of, for example, electric vehicles). Assumes limited potential for bioenergy and intermittent renewables (solar and GEA 3 wind). Transportation sector follows a “conventional” trajectory (future vehicles 34.4 continue to reply predominantly on liquid fuels). Assumes limited potential of land-based mitigation options, including low po- tential for biomass; no negative emissions technologies (Bio-CCS) and limited GEA 4 potential for afforestation/reforestation measures. Transportation sector follows 40.7 a “conventional” trajectory (future vehicles continue to reply predominantly on liquid fuels). Assumes no CCS. Transportation sector follows a “conventional” trajectory GEA 5 34.6 (future vehicles continue to reply predominantly on liquid fuels). Assumes the phase-out of nuclear power generation in the medium term, and GEA 6 no CCS. Transportation sector follows a “conventional” trajectory (future vehicles 40.9 continue to reply predominantly on liquid fuels). Table 4.9 Characteristics of the six GEA pathways that meet the SE4ALL target for renewable energY Source: IIASA 2012. Note: CCS can also be used in combination with bioenergy (BioCCS) to produce net negative carbon dioxide (CO 2 ) emissions. GEA = Global Energy Assessment; CCS = carbon capture and storage; TFEC = total final energy consumption ALL OF THE SIX PATHWAYS CORRESPOND TO THE EFFICIENCY SCENARIO OF THE GLOBAL ENERGY ASSESSMENT (GEA). A general conclusion of the analysis is that the role of re- GEA sustainability objectives. But the specific SE4ALL re- newables and other low-carbon supply-side technologies newable energy goal is not achieved in all the scenarios. is greater in the scenarios where restricting overall growth In the scenarios where the renewable energy proportion in energy demand is less successful, because of added equals or exceeds the doubling target, liquid transport pressure to decarbonize the supply side. The role of re- fuels are still an important part of the mix (and the most newable technologies (particularly for power generation) advanced transport technologies are not deployed). This will increase substantially, and renewable energy will play opens up greater opportunities for biofuels, and so in- a significant role in achieving all the scenarios meeting the creases the overall share of renewable energy. Conclusions from scenarios These three exercises indicate several conclusions: constraining increases in energy demand. As a result, the achievement of this target is intimately }} Current deployment growth rates are not high linked to success in achieving the complementary enough to achieve the SE4ALL target on renew- SE4ALL energy efficiency goal. ables (see figure 4.19). The level will need to rise by 50 percent–250 percent, depending on trends }} Exercises show a wide range of potential energy in overall global energy demand. The scale of the futures, depending on the aims and constraints challenge depends equally on the success in applied within different models and scenarios. stimulating the deployment of renewables and The IPCC ‘s review of modeling exercises (Special 203 Global tracking framework Report on Renewable Energy Sources and Climate energy deployment, although the overall level does Change Mitigation) shows the share of renewables not reach the SE4ALL goals in every case. in the global energy mix to range between 17 and 43 percent (in terms of primary rather than final Overall the scenarios show how important renewables energy consumption). are in any future sustainable energy mix, and at the same time highlight their links with energy efficiency and other }} Consideration of the IEA’s CPS and NPS indi- low-carbon technologies. The SE4ALL target falls within cate that neither current policy commitments nor the scope of many scenarios that aim to constrain climate those under consideration will be enough to stimu- change and meet other sustainability goals (although, as late sufficient deployment of renewables to meet the shown in figure 4.19, it falls at the upper end of the spec- SE4ALL goals. trum of results from the scenarios).14 Strong policy action is needed in the short term to stimulate deployment of the }} The six IIASA GEA scenarios concerned with technologies and to improve energy efficiency if the goal is meeting sustainability targets for energy access, to be achieved. limiting air pollution and health damages from energy use, improving energy security, and limiting climate change all include high levels of renewable 60% Greenpeace 50% GEA6 & GEA 4 40% GEA1 & GEA 2 GEA3 & GEA 5 30% WEO 450 WEO NPS & EM 20% WEO CPS 10% 0% 1990 2000 2010 2020 2030 % RE - Historical % RE - Trends Continued % RE - SE4ALL Target Growth Rate figure 4.19 Share of renewable energy in global total final energy consumption: Current trends and scenarios Source: IEA 2012c; ExxonMobil 2012; IIASA 2012; Greenpeace, EREC, and GWEC 2012. Note: WEO = World Energy Outlook; CPS = Current Policies Scenario; NPS = New Policies Scenario; GEA = Global Energy Assessment; EM = ExxonMobil; RE = renewable energy. 14 Based on available data sources (with their associated statistical limitations), the share of renewable energy in TFEC is estimated to be 18 percent as the starting point in 2010. This implies an SE4ALL objective of 36 percent for year 2030. Because the inclusion of sustainability considerations would lower this initial condition and target, they should be regarded as an upper bound. chapter 4: Renewable energy 204 Barriers and opportunities related to the SE4ALL This section discusses the main barriers and opportunities For the non-OECD countries, we can see several observed for attaining the SE4ALL objective of doubling the share of and expected trends, depending on the patterns of overall renewable energy in the global energy mix. energy growth and the opportunities for using renewables and switching away from inefficient biomass use. For re- The challenges of achieving SE4ALL targets vary across gions with a continuing high share of renewables in the regions. They are influenced by a number of factors: power sector (from hydro) and lower use of traditional bio- mass, we can expect a trend in which the overall share }} Expected growth in renewable energy production of renewables continues to increase (for example, in the non-OECD Americas). In regions where the use of tradi- }} Expected growth in overall TFEC tional biomass is widespread (that is, in Africa and Asia), a }} Expected trends in the use of traditional biomass transition to more efficient biomass fuels does not increase the proportion of renewables even when biomass is used Table 4.10 shows historical trends in the share of renew- more efficiently, since “raw” fuels determine the statistics. ables for different regions around the world, and compares But more efficient uses of biomass potentially free up re- this with the projected data from the WEO 450 Scenario. sources for other applications. Within the OECD the share of renewable energy has been In the WEO 450 Scenario, the Middle East also sees a rising due to successful policy efforts and low growth in substantial increase in the share of renewable energy (5.4 overall energy demand, as well as the low share of tra- percent). ditional biomass. These trends are expected to continue, and the OECD countries are expected to significantly in- crease renewables’ share of TFEC. 2030 2030 2030 1990 2000 2010 WEO 450 GEA 1-6 All GEA OECD34 6.9 7.7 10.0 28 Africa 62.2 63.1 61.7 65 Non-OECD Americas 38.0 32.7 34.5 47 Asia excluding China 51.1 43.6 36.7 37 China (region) 33.2 28.9 19.3 23 Non-OECD Europe 3.3 4.8 5.4 10 and Eurasia Middle East 1.0 0.5 0.6 6 World 16.6 17.4 18.0 28 34−41 23−41 Table 4.10 Share of renewables in total final energy consumption by region (after allocation) Source: Authors’ analysis based on IEA 2012d; IEA 2011; and IIASA (2012). Note: WEO = World Energy Outlook; GEA = Global Energy Assessment; OECD = Organisation for Economic Co-operation and Development. 205 Global tracking framework Economic and market opportunities and barriers The costs of many renewable energy technologies have In addition, there are large market opportunities, especial- been a major barrier to their adoption, a problem com- ly in growing countries in Asia, Africa, and Latin America. pounded in many cases by market issues, such as subsi- In its CPS, the IEA estimates that 75 percent of total new dies for competitive energy supply, and by a lack of costing capacity additions in electricity will be added in non-OECD methods to include social and environmental costs such countries by 2030 (IEA 2012c). This scenario also foresees as those related to carbon emissions. Strong growth in re- the addition of 60 percent of total new renewable energy newable deployment has led to significant reductions in capacity and 88 percent of total new hydroelectric capacity the costs of some of the principal technologies. Renew- in non-OECD countries (these relative shares are very simi- ables can now provide a cost-competitive solution in many lar under the IEA’s NPS). circumstances. For mini-grid and off-grid markets, renewable energy tech- nologies are competitive or cheaper than other energy $250-400 sources in many cases (depending on available sources billion and fuels). For grid-integrated projects, renewable energy is the annual technologies are increasingly competitive in a substan- financing requirement for renewable tial number of countries. This cycle of increased deploy- energy through 2030 to meet SE4ALL ment and reduced costs is likely to continue and will be objectives. an important driver for the accelerated renewable energy deployment needed to achieve the target. But in many markets economic barriers still need to be addressed by With regard to biofuels, the IEA estimates in both the CPS policy measures that make up for the lack of a level playing and NPS that about 40 percent of the expected incremen- field, support market introduction, foster the development tal consumption projected to 2030 will originate in non- of local supply chains and infrastructure, and stimulate OECD countries. the deployment that will lead to further cost reduction and competitiveness. Noneconomic opportunities and barriers Section 3 has already discussed a number of important of adequate funding opportunities and financing drivers for renewable energy, including energy security, cli- products for renewable energy technologies mate change, and local environmental conditions. The pro- spective analysis using global energy models shows that }} Infrastructure and integration issues that mainly scenarios aimed at reducing CO2 emissions have higher center on the flexibility of the energy system (for shares of renewables, although this share depends also example, the power grid) to integrate/absorb renew- on how other low-carbon solutions like CCS are deployed. able energy technologies On the other hand, several scenarios highlight noneco- }} Lack of knowledge about the availability and performance of renewable energy technologies as nomic barriers related to: well as lack of skilled workers }} Policy uncertainty and risk from ineffective policy }} Environmental barriers linked to experience design, discontinuity, or insufficient transparency of with planning regulations and public acceptance of policies and legislation renewable energy technologies }} Institutional and administrative issues, including The relative importance of these barriers differs for each a lack of strong, dedicated institutions; lack of clear technology and market, and the priority changes as a tech- responsibilities; and complicated, slow, or nontrans- nology matures along the commercialization and deploy- parent permitting procedures ment path. Also, as one barrier is overcome, others may }} Financial barriers associated with the absence become apparent. chapter 4: Renewable energy 206 Policy requirements Effective policies designed to tackle these barriers are a }} Establishing a predictable renewable energy key requirement to facilitate renewable energy deploy- policy framework, integrated into an overall energy ment. This is the case even when renewables can provide strategy with clear targets a cost-competitive energy source, given the nonfinancial regulatory issues that can inhibit deployment. }} Implementing a portfolio of incentives based on technology and market maturity where these are Policy makers need to be able to deploy policy portfolios necessary that have maximum impact in stimulating deployment and are as cost-effective as possible. Key issues include: }} Adopting a dynamic policy approach based on monitoring of policy impacts in the context of national and global market trends. Broadening the geographic base and the need for capacity building To meet the SE4ALL goal for renewable energy, countries }} Awareness of the potential contribution of that have already started to deploy renewables need to renewable sources to national energy needs among continue along this path and maintain or accelerate prog- decision and policy makers ress. But achieving this challenging goal will depend on a much broader range of countries taking steps to stimulate }} Awareness of internationally accepted best deployment of renewables as a major component of their policy practices overall energy mix. It is likely they can do this in the light of }} Development of appropriate regulatory frame- accumulated experience with policy portfolios and techno- works and institutions logical deployment gained elsewhere. They can also ben- efit from the significant and continuing cost reductions that }} Information and data gathering (for example, on are making renewables cost-competitive with other energy resource potentials and infrastructure needs) sources in a much broader range of circumstances. }} Technology skills, supply chain and installation But in order to effectively diversify deployment there is a and maintenance capabilities. need to build capacity in these new countries in the areas of: }} Provision of finance from local and international sources.Public information Conclusions In the two decades between 1990 and 2010, the family of Given the significant scale of the challenge posed by the renewable energy technologies has matured and estab- SE4ALL renewables target, a concerted effort will be need- lished a strong foothold in global energy supply. The range ed from governments––both those that have already start- of technologies that can be considered commercially ed along the path of renewable energy deployment and proven has grown, and costs have been reduced signifi- those still exploring the options––to make renewables a cantly. With new pressures on energy supply and security, key component of their future sustainable energy mix. It will along with the need to reduce global emissions, the case also require a major coordinated effort from a wide range for deployment is now stronger than ever. Growing ener- of relevant international organizations to track progress, to gy demand, higher fossil-fuel prices, and the continually identify and promote best practices in policy making and diminishing costs of key technologies like wind and solar project implementation, and to assist in necessary capac- open up new opportunities for renewables as affordable ity building to facilitate the diffusion of these technologies and sustainable options in each sector (electricity, heat, into global energy markets. and transport). 207 Global tracking framework References Ásmundsson, R. K. 2008. South Pacific Islands Geothermal Energy for Electricity Production. ÍSOR-2008/032, compiled for the Icelandic International Development Agency. http://www.edinenergy.org/pdfs/pacific_islands_geothermal.pdf. Bacon, R., and M. Kojima. 2008. Coping with Oil Price Volatility. Washington, DC: Energy Sector Management Assistance Program (ESMAP), the International Bank for Reconstruction and Development / World Bank Group. http://esmap.org/sites/esmap.org/files/8142008101202_coping_oil_price.pdf Bazilian, Morgan, I. Onyeji, M. Liebrich, I. MacGill, J. Chase, J. Shah, D. Gielen, D. Arent, D. Landfear, and S. Zhengrong. 2012. “Re-considering the Economics of Photovoltaic Power.” Bloomberg New Energy Finance, https://www.bnef.com/. BNEF (Bloomberg New Energy Finance), UNEP (United Nations Environment Programme), and Frankfurt School. 2012. Global Trends in Renewable Energy Investment 2012. Frankfurt School of Finance and Management, Franfurt, Germany. BNEF Renewable Energy Investment Data Base, 2013. https://www.bnef.com/Renewables/ BP (British Petroleum) 2012. BP Energy Outlook 2030. London. Briceño-Garmendia, Cecilia, and Maria Shkaratan. 2011. “Power Tariffs: Caught between Cost Recovery and Affordability.” Policy Research Working Paper 5904, World Bank, Washington, DC. Chen, H., T. N. Cong, W. Yang, C. Tan, Y. Li, and Y. Ding. 2009. “Progress in Electrical Energy Storage System: A Critical Review.” Progress in Natural Science 19: 291-312. CEPAL (Comision Economica para America Latina y el Caribe). 2011. Centroamerica: Estadisticas del Subsector Electrico, 2010. Mexico: UN CEPAL. DOE (U.S. Department of Energy). 2001. “Renewable Energy: An Overview.” http://www.nrel.gov/docs/fy01osti/27955.pdf. EIA (U.S. Energy Information Administration). 2011. International Energy Outlook 2011. Washington, DC. Elizondo-Azuela, Gabriela, and Luiz Barroso. 2011. “Design and Performance of Policy Instruments to Promote the Development of Renewable Energy: Emerging Experience in Selected Developing Countries.” Energy and Mining Sector Board Discussion Paper No. 22, World Bank, Washington, DC. EPIA (European Photovoltaic Industry Association). 2013. “World’s Solar Photovoltaic Capacity Passes 100-Gigawatt Landmark after Strong Year.” http://www.epia.org/index.php?eID=tx_nawsecuredlandu=0andfile=/uploads/tx_epiapre- ssreleases/130211_PR_EPIA_Market_Report_2012_FINAL_01.pdfandt=1363974656andhash=51671f0c9b602ecae6cc5 acc83b17506dcc0d4ef. European Photovoltaic Industry Association (EPIA) and Photovolatic Technology Platform, 2011, Solar Europe Industry Initiative Implementation Plan 2010-2012, EPIA, Brussels. ExxonMobil. 2012. ExxonMobil—The Outlook for Energy: A View to 2040. Irving, Texas: ExxonMobil. Goldemberg, J. 2004. “The Case for Renewable Energy.” Thematic Background Paper, International Conference for Re- newable Energy, Bonn. http://www.ren21.net/Portals/97/documents/Bonn%202004%20-%20TBP/The%20case%20of%20 Renewable%20Energies.pdf. Greenpeace International, EREC (European Renewable Energy Council), and GWEC (Global Wind Energy Council). 2012. Energy [R]evolution: A Sustainable World Energy Outlook. Greenpeace International, EREC, and GWEC. Amsterdam. chapter 4: Renewable energy 208 GWEC. 2013. “Global Wind Statistics 2012.” http://www.gwec.net/wp-content/uploads/2013/02/GWEC-PRstats-2012_english.pdf. IEA (International Energy Agency). 2000. “Implementing Agreement for Hydropower Technologies and Programmes, Annex III: Hydropower and the Environment: Present Context and Guidelines for Future Action.” IEA, Paris. http://www. ieahydro.org/reports/HyA3S5V2.pdf. ———. 2002. “Renewable Energy Working Party 2002.” IEA, Paris. http://www.energy.anetce.com/2002_iea_renewables54.pdf. ———. 2007. “Renewable Energy Consumption and Electricity Preliminary 2006 Statistics.” IEA, Paris. http://www.eia.gov/cneaf/solar.renewables/page/prelim_trends/rea_prereport.html. ———. 2008. “Deploying Renewables Principles of Effective Policies.” OECD/IEA, Paris. ———. 2010. “Implementing Agreement for Hydropower Technologies and Programmes, Update of Recommendations for Hydropower and the Environment: Briefing Document.” IEA, Paris. http://www.ieahydro.org/uploads/files/finalan- nexxii_task2_briefingdocument_oct2010.pdf. ———. 2011. World Energy Outlook 2011. Paris: IEA, OECD Publishing. ———. 2012a. Energy Technology Perspectives 2012: Pathways to a Clean Energy System. Paris: IEA, OECD Publishing. ———. 2012b. Medium Term Renewable Energy Market Report. Paris: IEA. ———. 2012c. World Energy Outlook 2012. Paris: IEA, OECD Publishing. http://www.worldenergyoutlook.org/publica- tions/weo-2012/. ———. 2012d. IEA World Energy Statistics and Balances. Paris: IEA, OECD Publishing. http://www.oecd-ilibrary.org.libproxy-wb.imf.org/statistics. IEA, OECD, EUROSTAT. 2005. Energy Statistics Manual, International Energy Agency, Organisation for Economic Co- Operation and Development and Eurostat, Paris, France. IIASA (International Institute for Applied Systems Analysis). 2012. Global Energy Assessment—Toward a Sustainable Future. Cambridge, U.K. and Laxenburg, Austria: Cambridge University Press and IIASA. http://www.iiasa.ac.at/web/home/research/researchPrograms/Energy/Home-GEA.en.html. IJHD (International Journal of Hydropower and Dams). 2011. World Atlas and Industry Guide. Wallington, Surrey: IJHD. International Hydropower Association. 2010. Hydropower Sustainability Assessment Protocol. London: International Hydropower Association. http://www.hydrosustainability.org/getattachment/7e212656-9d26-4ebc-96b8-1f27eaebc2ed/ The-Hydropower-Sustainability-Assessment-Protocol.aspx. IPCC (Intergovernmental Panel on Climate Change). 2011. IPCC Special Report on Renewable Energy Sources and Cli- mate Change Mitigation. Prepared by Working Group III of the Intergovernmental Panel on Climate Change. Cambridge, England, and New York, NY: Cambridge University Press. IRENA (International Renewable Energy Agency). 2012. Electricity Storage Technology Brief. Bonn, Germany: IRENA. http://www.irena.org/DocumentDownloads/Publications/IRENA-ETSAP%20Tech%20Brief%20E18%20Electricity-Storage.pdf. ———. 2013a. Doubling the Share of Renewable Energy: A Roadmap to 2030. Bonn, Germany: IRENA. http://irena.org/DocumentDownloads/Publications/IRENA%20REMAP%202030%20working%20paper.pdf. 209 Global tracking framework ———. 2013b. Renewable Power Generation Costs in 2012: An Overview. Bonn, Germany: IRENA. http://irena.org/Docu- mentDownloads/Publications/Overview_Renewable%20Power%20Generation%20Costs%20in%202012.pdf. Jacobs, David. 2012. Renewable Energy Policy Convergence in the EU: The Evolution of Feed-in Tariffs in Germany, Spain and France. Surrey, England: Ashgate. Kojima, M. 2012. Notes on Diversity Indices. Personal communication. McCoy-West, A. J., S. Milicich, T. Robinson, G. Bignall, and C. C. Harvey. 2011. “Geothermal Resources in the Pacific Islands: The Potential of Power Generation to Benefit Indigenous Communities.” Proceedings, 36th Workshop on Geo- thermal Reservoir Engineering, Stanford University, Stanford, California, January 31. http://www.geothermal-energy.org/pdf/IGAstandard/SGW/2011/mccoy.pdf. REN21. 2007. Renewables 2007 Global Status Report (GSR). Paris: Ren21. http://www.ren21.net/gsr. ———. 2012. Renewables 2012 Global Status Report (GSR). Paris: Ren21. http://www.ren21.net/gsr. Shell (2013): New Lens Scenarios: A Shift in Perspective for a World in Transition Sologico, 2012. Sologico market price data, Sologico/pvXchange GmbH, Cologne. See www.sologico.comUN Energy Statistics Database, 2012. http://data.un.org/Explorer.aspx?d=EDATA UN Energy Statistics Database. http://data.un.org/Explorer.aspx?d=EDATA UNEP (United Nations Environment Program) and NREL/U.S. DOE (National Renewable Energy Laboratory, U.S. Depart- ment of Energy). 2012. “Solar and Wind Energy Resource Assessment (SWERA).” Data from the National Renewable Energy Library and the United Nations Environment Program (UNEP). http://maps.nrel.gov/SWERA. Van den Wall Bake, J. D., M. Junginger, A. Faaij, T. Poot, and A. Walter. 2009. “Explaining the Experience Curve: Cost Reductions of Brazilian Ethanol from Sugarcane.” Biomass and Bioenergy 33 (4): 644-58. WWF (World Wide Fund for Nature), Ecofys, OMA (Office for Metropolitan Architecture). 2011. The Energy Report, 100% Renewable Energy by 2050. Gland, Switzerland. Yepez-Garcia, R., and J. Dana. 2012. Mitigating Vulnerability to High and Volatile Oil Prices: Power Sector Experience in Latin America and the Caribbean. World Bank: Washington, DC. chapter 4: Renewable energy 210 Annex 1: Concepts, data, and methodology Primary Secondary Coun- Time Data Source data Source data and Reports tries series gaps source analysis Annual Statistical 1965– No BP X Review of World 67 2011 gaps Energy International Energy EIA X X Outlook Enerdata Global Energy and 1970– No X 184 Information Services CO2 Database 2010 gaps Wood fuel data and FAO X analysis Country 1960– No IEA X IEA Energy Statistics 138 surveys 2010 gaps Annual Global IIASA X Energy Assessment Report Renewable Energy IRENA X Country Profiles Annual OECD Fact OECD X Book Platts Biofuels capacity Network of over Annual Global Sta- REN 21 400 data X tus Report contribu- tors Data gaps in Country 1950– UN Data X UN Data Over 220 some surveys 2009 time series UN Stats Monthly UN Stats X Bulletin of Stats Online Annual World WEC X Energy Trilemma Report Country WHO Household WHO X surveys energy Database World Development World Bank X Indicators Table A1.1 Comparison of energy data sources Source: Authors’s compilation. This section provides descriptions of different primary en- and final energy are calculated following different methods. ergy accounting methods and an illustration of how primary 211 Global tracking framework Primary energy accounting The IEA energy production statistics are based on a physi- }} The physical energy content method (used by cal energy content primary energy accounting method. IEA and Eurostat) There are in fact three main ways of presenting the primary energy data, which can affect the overall size of the global }} The partial substitution method (used by EIA) energy mix and of the renewable share within it. These are: }} The direct equivalent method (used in some IPCC reports) A description of these methods is found in the table A1.2. Description Examples Users Physical energy content Adopts the principle that the primary energy The primary energy equivalent of hydro- OECD form should be the first energy form used power and solar PV assumes 100% conver- IEA downstream in the production process for sion efficiency to “primary electricity” (that Eurostat which multiple energy uses are practical. is, 1 kWh of electricity converts into a gross Enerdata energy input of 3.6 MJ) This leads to the choice of the following primary energy forms: (a) heat for nuclear, The primary energy equivalent of nuclear geothermal, and solar energy, and (b) elec- assumes 33% thermal conversion efficiency tricity for hydro, tide/wave/ocean and solar (average for nuclear plants in Europe) to PV energy. “primary electricity” (that is, 1 kWh equals 10.9 MJ of primary energy). The method counts the power plant input for fossil fuels (and biomass), but counts For geothermal, the primary energy equiva- power plant output for nuclear, wind, solar, lent is calculated using 10 % conversion hydro and geothermal. efficiency for electricity (in this case, 1 kWh equals 36 MJ) and 50% for geothermal Thus, it uses conversion efficiencies to heat. calculate the primary energy equivalent of renewable energy output. Substitution method Reports primary energy from noncombusti- BP applies 38% conversion efficiency to Used in slightly different ble sources as if they had been substituted electricity generated from nuclear and variants by: for combustible energy. In other words, it hydro. BP counts the equivalent primary energy of WEC applies 38.6% to electricity from fossil fuels needed to generate a given vol- US EIA nuclear and all other noncombustible ume of renewable-source-based electricity. renewable sources. WEC The method uses different conversion fac- IIASA (GEA) tors for different types of renewable energy output. The share of renewables under this method is thus considerably higher than in the “physical energy content” method. chapter 4: Renewable energy 212 Description Examples Users Direct equivalent method Counts one unit of secondary energy pro- The primary energy equivalent of noncom- UN Statistics vided from noncombustible sources as one bustible or renewable-source-based elec- IPCC Reports unit of primary energy. tricity assumes 100% conversion efficiency to “primary electricity” (that is, 1 kWh of IIASA (IPCC) In this method, secondary energy means electricity converts into 3.6 MJ of primary at the point of end use; that is, as electricity energy) or heat. It counts all forms of electricity equally regardless of origin and does not use con- version efficiencies. Table A1.2 Methods to account for the primary energy of noncombustible sources Source: IPCC 2011; REN21 2007. Note: different variants of the substitution method use different conversion factors. Table A1.3 shows the figures for total primary energy sup- the calculated contribution from renewables to the global ply calculated by the three methods for 2010 along with energy mix. Physical content Direct equivalent Substitution method method method EJ % EJ % EJ % Fossils 433 81% 433 85% 433 79% Nuclear 30 6% 10 2% 26 5% Renewables: 69 13% 68 13% 91 17% Hydro 12 2.32% 12 2.42% 33 5.92% Wind 1 0.23% 1 0.24% 3 0.59% Bioenergy 52 9.78% 52 10.21% 52 9.49% Solar 1 0.14% 1 0.14% 1 0.17% Geothermal 3 0.51% 1 0.11% 1 0.17% Ocean 0 0.00% 0 0.00% 0 0.00% Other 1 0.25% 1 0.26% 1 0.24% Total 534 100% 511 100% 550 100% Table A1.3 Total world primary energy supply in 2010 (EJ) Source: IEA 2012d. 213 Global tracking framework To illustrate the effect of the different methodologies when The advantage of the primary methodology is that figures renewables play a more significant role in the energy mix, are based directly on the physical measurement of energy table A1.4 shows the equivalent analysis based on the content for fossil fuels. The disadvantages are that for low- IEA’s WEO 450 Scenario, in which stringent climate goals carbon electricity sources the primary energy content has are met through the application of the full range of low- to be calculated and the resulting figures depend on the carbon energy technologies including renewables. In this accounting convention used and are not always directly scenario the proportion of renewables can range between related to useful energy production. 23 percent and 29 percent, depending on the methodol- ogy used, and the ratio between the 2010 and 2030 figures range from 1.70 for the substitution method to 1.78 for the other two methodologies. Physical content Direct equivalent Substitution method method method EJ % EJ % EJ % Fossils 408 67% 408 73% 408 62% Nuclear 61 10% 20 4% 53 8% Renewables: 141 23% 129 23% 192 29% Hydro 20 3% 20 4% 54 8% Bioenergy & wastes 86 14% 86 15% 86 13% Other renewables 34 6% 22 4% 52 8% Total 610 100% 557 100% 653 100% Table A1.4 Total world primary energy supply in 2030 in WEO 450 Scenario (EJ) Source: IEA 2012d. Final energy accounting The data for this methodology come from the total final implies losses due to efficiency of conversion. The TFEC energy consumption (TFEC) figures within the IEA statis- level therefore does not represent only useful energy, or tics (these exclude nonenergy uses of fossil fuels such as energy service, but for direct uses of combustible sources those for plastics and chemicals). The TFEC figures for it only represents inputs into a transformation process that power and commercial heat are lower than the figures for will ultimately deliver useful energy. The final energy service their supply because of the energy used within power and is not reported in energy statistics because it is not practi- heat plants and transmission and distribution losses. cal to measure.15 Within the TFEC figures, heat and electricity (secondary In order to establish the contribution of each technology energy sources) represent energy commodities ready to the figures for electricity and commercial heat have to be be used for energy consumption. Other primary energy allocated to the relevant technology. This can be done sources can be directly used for energy consumption (for based on the proportions of production, attributing the example, fossil fuels and bioenergy used for heating in the losses proportionally (although this penalizes the renew- residential sector), and these are still reported in terms of ables’ share since both internal energy losses and trans- their fuel content. These sources need to go through fur- mission and distribution losses tend to be smaller, at least ther transformation processes (for example, combustion) for distributed renewable sources). in order to provide energy services. Such transformation 15 A household will know how much biomass/gas/electricity it used for its heating system but will not measure how much heat the heating system produced. It would be possible to make country/use-specific assumptions on conversions in the final energy sector and estimate useful energy service—but this is a topic for an analytical study, not a statistical assessment. chapter 4: Renewable energy 214 Table A1.5 shows the breakdown of final consumption fig- and heat, using final energy consumption figures based on ures for 2010, before and after the allocation of electricity the IEA’s WEO 450 Scenario. total final energy total final total final energy consumption after consumption consumption allocation EJ % EJ % EJ % Fossils 243 66% 209 63% 263 79% Nuclear 0 0% 0 0% 8 3% Renewables: 47 13% 47 14% 61 18% Hydro 0 0.00% 0 0.00% 10 3% Wind 0 0.00% 0 0.00% 1 0.35% Bioenergy 46 12.61% 46 13.91% 48 14% Solar 1 0.17% 1 0.19% 1 0.27% Geothermal 0 0.08% 0 0.09% 0 0.15% Ocean 0 0.00% 0 0.00% 0 0.00% Other renewables 0 0.00% 0 0.00% 0.02% Electricity 64 18% 64 19% x x Heat 12 3% 12 3% x x Total 366 100% 332 100% 332 100% Table A1.5 Total final energy consumption in 2010 Source: IEA 2012d. The advantage of using the TFEC as the basis for moni- from these sources depends on the conversion efficiency. toring is that it allows a straight comparison in GWh for Non-energy uses are excluded. The disadvantage is that electricity-producing renewables/nuclear and for commer- the energy in the electricity and commercial heat sectors cial heat and gets closer to measuring the useful energy. has to be allocated to the relevant technology based on But bioenergy and direct use of fossil fuels for heat are the production proportions, and the losses are dispropor- still reported in terms of energy inputs, and the useful heat tionally allocated to the renewable technologies. total final energy consumption after allocation EJ % Fossils 256 67% Nuclear 17 5% Renewables: 109 28% Hydro 18 5% Bioenergy & wastes 72 19% Other renewables 20 5% Total 382 100% Table A1.6 Total final energy consumption in 2030 in WEO 450 scenario Source: IEA 2012d. 215 Global tracking framework Annex 2. Global trends in renewable energy cummulative ethanol production in brazil (106 m3) 10 20 40 80 160 320 640 1000 average production cost of ethanol [usd(2005)/m3) 1975 1985 1995 2004 100 1975 1985 1995 2004 10 1 1,000 10,000 cummulative sugarcane production in brazil (106 tonnes sugarcane) figure A2.1 Learning curve for sugarcane-based bioethanol sugarcane production ethanol: sugarcane-based production Source: Van den Wall Bake. and others 2009. Annex 3. Country performance hics Tajikistan Norway UMICS 55% LMICS Sweden LICS 45% Brazil share of re in tfec Paraguay 35% Finland Chile 25% Kyrgyzstan Canada Sudan Sri Lanka Colombia Congo, DRC India Tanzania Mozambique 15% Turkey Philippines Spain France Nigeria North Korea Venezuela Italy Germany Mexico ZimbabweVietnam Pakistan compound annual 5% Argentina Thailand China Indonesia Myanmar growth rate, Egypt USA Russia Japan Ethiopia 1990-2010 (%) 0% -5% -2% 2% 4% 6% 8% 10% 12% 14% figure A3.1 Share of renewable energy (excluding traditional use of biomass) in country TFEC and CAGR, 1990–2010 Source: Authors’ analysis based on IEA 2012d. chapter 4: Renewable energy 216 hics Sweden 30% UMICS Finland LMICS Brazil 25% LICS share of re in tfec Congo, DRC Sri Lanka 20% Chile Sudan Tanzania Ghana Cambodia 15% Philippines Thailand India Poland 10% Turkey Mexico France Haiti Germany Benin Zimbabwe Nigeria Spain Colombia Mozambique Italy Vietnam Canada China, PRC compound annual 5% Indonesia North Argentina Myanmar growth rate, Pakistan Korea United States Russian South Africa 1990-2010 (%) Federation Japan Ethiopia 0% -5% -5% 1% 4% 7% 10% 40% figure a3.2 Share of renewable energy (excluding traditional use of biomass and hydropower) in country TFEC and CAGR, 1990–2010 Source: IEA 2012d. 10% lower-middle income high income economies share of re in tfec 8% low income 6% 4% upper-middle income 2% compound annual growth rate, 0% 1990-2010 (%) 0% 2% 4% 6% figure a3.3 Share of NCRE in TFEC vs. CAGR Source: Authors’ analysis based on IEA 2012d. 217 Global tracking framework a. Share in TFEC hics 60% UMICS Norway Tajikistan LMICS 50% LICS share of re in tfec Iceland 40% 30% Georgia Kyrgyzstan Albania Brazil 20% Sweden Uruguay Mozambique Canada Costa Rica 10% Venezuela China, PRC Vietnam compound annual Japan India 0% growth rate, Russian usa 1990-2010 (%) Federation -10% -3% -1% 1% 3% 5% 7% 9% 13% 15% b. Share in total electricity consumption hics UMICS LMICS LICS share in total electricty consumption 120% Norway Paraguay 100% Zambia Mozambique Albania Tajikistan Georgia 80% Brazil 60% Venezuela Sweden Canada 40% Russia 20% India usa China, PRC compound annual 0% Japan growth rate, 1990-2010 (%) -20% -1% 1% 3% 5% 7% 9% 11% figure a3.4 Share of hydro in country TFEC and electricity consumption vs. CAGR, 1990–2010 Source: Authors’ analysis based on IEA 2012d. chapter 4: Renewable energy 218 25% hics share in total electricity consumption UMICS LMICS 20% Denmark Portugal 15% Spain 10% Ireland United States Germany 5% Greece Italy New Zealand Australia France compound annual India Austria growth rate, United Kingdom Poland Turkey Canada 1990-2010 (%) 0% Brazil Japan China, PRC 10% 20% 30% 40% 50% 60% 70% 80% 90% -5% figure a3.5 Share of wind in electricity consumption vs. CAGR, 1990—2010 Source: Authors’ analysis based on IEA 2012d. 2.5% hics share in total electricity consumption Spain UMICS 2.0% 1.5% Germany 1% Italy .5% Japan USA compound annual South Korea Portugal Czech Republic growth rate, China Canada 1990-2010 (%) 0% France Australia Belgium 35% 40% 45% 50% 55% 60% 65% -0.5% figure a3.6 Share of solar PV in electricity consumption vs. CAGR, 1990—2010 Source: Authors’ analysis based on IEA 2012d. 219 Global tracking framework 11% hics UMICS 9% share of re in tfec Brazil 7% 5% USA 3% Italy Germany Austria Sweden Poland 1% Portugal Thailand Spain France compound annual United Kingdom Canada growth rate, China, PRC 0% 1990-2010 (%) -1% -20% 20% 40% 60% 80% 100% 120% 140% figure a3.7 Share of biofuels in electricity consumption vs. CAGR, 1990-2010 Source: Authors’ analysis based on IEA 2012d. 40% Iceland hics UMICS 30% LMICS LICS share of re in tfec 7% N. Zealand 5% El Salvador Philippines 3% Turkey Costa Rica 1% Switzerland Kenya China compound annual USA Germany Italy Indonesia growth rate, 0% 1990-2010 (%) Mexico -1% -5% 5% 10% 15% 30% 50% 70% 90% figure a3.8 Share of geothermal energy in country TFEC vs. CAGR, 1990–2010 Source: Authors’ analysis based on IEA 2012d. Note: Bubble size represents volume of final renewable energy consumption in 2010. TFEC = total final energy consumption; CAGR = compount annual growth rate. chapter 4: Renewable energy 220 chapter 5 conclusions Section 1. methodical conclusions The Global Tracking Framework has built a robust data platform capable of monitoring global progress toward the SE4ALL objectives (table 5.1). This framework draws primarily on household surveys for data on energy access and on national energy balances for data on renewable energy and energy efficiency. Based on a comprehensive review of sources, it has been possible to cover between 126 and 181 countries depending on the indicator, which is equivalent to between 96 and 98 percent of the world’s population. Category Data sources Country coverage (% of global population) Electrification Global networks of household surveys plus some censuses 212 (100) Cooking fuels Global networks of household surveys plus some censuses 193 (99) IEA and UN for energy balances Energy intensity 181 (98) WDI for GDP and sectoral value added IEA and UN for energy balances Renewable energy 181 (98) REN 21, IRENA, and BNEF for complementary indicators Table 5.1 Overview of data sources and country coverage under global tracking NOTE: IEA = International Energy Agency; UN = United Nations; REN 21 = Renewable Energy Network for the 21st Century; IRENA = International Renewable Energy Agency; BNEF = Bloomberg New Energy Finance; WDI = World Development Indicators (World Bank); GDP= gross domestic product. Looking ahead, the Global Tracking Framework will be global household survey networks to gather specific and updated on a biannual basis to provide the international unambiguous information about the use of electric lighting community with a regular report on the status of progress and the presence or absence of an electricity connection, toward the SE4ALL objectives. as well as sharpening questions about the cooking fuels and cookstoves used in the household, in part to deter- While the methodology here developed provides an ad- mine whether the latter may be considered “improved” equate basis for basic global tracking, there are a num- even where solid fuels continue to be used. This work will ber of significant information improvements that would be require dialogue and close coordination with the Interna- desirable to implement in the medium term (table 5.2). To tional Household Survey Network among others. Second, effectively monitor progress through 2030 incremental in- the full multi-tier frameworks for access to electricity and vestments in energy data systems will be essential over cooking solutions described in chapter 2 need to be pi- the next five years, both at the global and national levels. loted in a number of SE4ALL opt-in countries to validate These represent relatively cost-effective high-impact im- them for wider application. The pilot process would require provements, whose implementation would be contingent preparation of survey questionnaires capable of capturing on the availability of financial resources. the attributes necessary for classifying households with- in the multi-tier frameworks. Third, upon validation of the With regard to energy access, the first task will be to in- multi-tier methodology, the survey questionnaires could troduce the capability for medium-term global tracking potentially be administered at the national level by all opt- using a simplified two-threshold framework. This would in countries. require modifying energy-related questions in the major chapter 5: conclusions 222 Recommended targeting of effort over next five years Work to improve energy questionnaires for global networks of household surveys. Pilot country-level surveys to provide more precise and informative multi-tier measures Energy access of access to electricity and clean cooking Develop suitable access measures for heating. Integrate data systems on energy use and associated output measures. Strengthen country capacity to collect data on sectoral (and ideally subsectoral process) intensities. Energy efficiency Improve data on physical activity drivers (traffic volumes, number of households, floor space, etc.). Improve data on energy efficiency targets, policies, and investments. Improve data and definitions for bio-energy and sustainability. Capture renewable energy used in distributed generation. Renewable energy Capture renewable energy used off-grid and in micro-grids. Promote a more harmonized approach to target-setting. Table 5.2 Medium-term agenda for the improvement of global energy databases source: Authors. Thereafter, the feasibility of applying such a multi-tier ener- volumes, residential and commercial floor space, and pro- gy access survey at the global level could be addressed. duction volumes of energy-intensive products, which at One way to address this challenge would be to commis- present are available for only a few countries. These tech- sion a globally active survey agency to conduct the survey nical indicators will need to be complemented with other across all relevant countries. Another would be to enlist indicators more relevant to policy makers, including na- the support of various development agencies in conduct- tional energy efficiency targets, policies, and investments. ing the standardized survey as a part of their operations in countries where they have significant engagement. It With regard to renewable energy, the first task will be to would be best to explore both possibilities at this stage. In conduct assessments for the purpose of devising defi- addition, new methodologies would need to be developed nitions and methods that will permit energy statistics to and piloted to measure access to energy for community capture more accurately the full spectrum of existing re- and productive uses, and for heating purposes. Funding newable energy sources and applications. These assess- would be needed to implement the pilots, to carry out reg- ments would cover the following areas: small, distributed, ular energy surveys in opt-in countries, to develop new grid-connected electricity generation; off-grid and mini-grid methodologies, and to prepare periodic tracking reports. power generation systems; direct production of heat and net energy from heat pumps; waste fuels; and renewable With regard to energy efficiency, the main concern is to energy production in general. In a second stage, the new strengthen countries’ capacity to produce more disaggre- definitions, categories, and methodologies will have to be gated data on sectoral, subsectoral, and process energy integrated into the questionnaires and procedures used use, as well as the associated output measures. This will to collect and report energy statistics at the country level. entail ensuring consistency in sectoral definitions and meth- This exercise will necessarily involve the commitment and odologies to facilitate country comparisons and regional participation of the international organizations that main- aggregations. Moving from value-based to physical-based tain the primary data repositories in energy—notably the indicators will permit a better tracking of improvements in International Energy Agency, the International Renewable energy efficiency. Such a move will require data on drivers Energy Agency, the United Nations, and the World Health of physical activity such as passenger and freight traffic Organization. 223 Global tracking framework In parallel, a review of methodological approaches—in- Finally, while many countries have already set national tar- cluding definitions, indicators, and criteria—for assessing gets for renewable energy, these are expressed in such a the sustainability of the main renewable energy technolo- wide range of units that they do not permit ready aggre- gies, and in particular modern and traditional uses of bio- gation or comparison across countries. Going forward, it mass, will have to be carried out and used as the basis is proposed that countries express their renewable energy for internationally accepted standards. Implementing the targets as a percentage of their total final energy consump- new methodologies and procedures will require capacity tion for consistency with the global tracking framework. building efforts and should be preceded by piloting at the country level. Section 2. SUBSTANTITIVE CONCLUSIONS The Global Tracking Framework presented in this report of some 20 high-impact countries that have a particularly has made it possible to establish the following starting large weight in aggregate global performance. Overlapping points against which progress will be measured under the groups of 20 high-impact countries in Asia and Africa ac- SE4ALL initiative (table 5.3). The rate of access to electric- count for about two-thirds of the global electrification defi- ity and primary non-solid fuel will have to increase from cit and four-fifths of the global deficit in access to non-solid 83 and 59 percent, respectively, in 2010 to 100 percent by fuels (figure 5.1). Meeting the universal access objective 2030. The rate of improvement of energy intensity will have globally will depend critically on the progress that can be to double from –1.3 percent for 1990–2010 to –2.6 percent made in these countries. A third group of 20 high-income for 2010–30. The share of renewable energy in the global and emerging economies accounts for four-fifths of global energy mix will have to double from an estimated starting energy consumption. The efforts of this group of countries point of at most 18 percent in 2010, implying an objective to develop renewable energy and accelerate improve- of up to 36 percent by 2030. ments in energy efficiency will ultimately determine the global achievement of the corresponding targets. Global progress toward the achievement of each of the three SE4ALL objectives depends critically on the efforts Objective 1 Objective 2 Objective 3 Doubling share Doubling global of renewable Universal access to modern energy services rate of improvement energy in global of energy efficiency energy mix Percentage of Percentage of population with Rate of improvement Renewable energy Proxy indicator population with primary reliance on in energy intensity* share in TFEC electricity access non-solid fuels Historic reference 1990 76 47 16.6 –1.3 Starting point 2010 83 59 18.0 Objective for 2030 100 100 –2.6 36.0 Table 5.3 SE4ALL historic references, starting points, and global objectives (%) Source: Authors. Note: TFEC = total final energy consumption *Measured in primary energy terms and GDP at purchasing power parity chapter 5: conclusions 224 Electricity access Electricity access deficit non-solid fuel Non-solid fuel access access deficit Primary Primary energy energy demand demand deficit (million) (millions of people) deficit (million) (millions of people) (exajoules) (exajoules) India 306 306.2 India 705 705 China 107 107.4 Nigeria 82 82.4 China 613 612.8 USA 93 92.8 Bangladesh 67 66.6 Bangladesh 135 134.9 Russia 29 29.4 Ethiopia 64 63.9 Indonesia 131 131.2 India 29 29 Congo, DR 56 55.9 Nigeria 118 117.8 Japan 21 20.8 Tanzania 38 38.2 Pakistan 111 110.8 Germany 14 13.7 Kenya 31 31.2 Ethiopia 81 81.1 Brazil 11 11.1 Sudan 31 30.9 Congo, DR 61 61.3 France 11 11 Uganda 28 28.5 Vietnam 49 49.4 Canada 10 10.5 Myanmar 25 24.6 Philippines 46 46.2 S. Korea 10 10.5 Mozambique 20 19.9 Myanmar 44 44 Iran 9 8.7 Afghanistan 18 18.5 Tanzania 42 42.3 Indonesia 9 8.7 Korea, DR 18 18 Sudan 34.6 UK 8 8.5 Madagascar 18 17.8 Kenya 32.6 Mexico 8 7.5 Philippines 16 15.6 Uganda 32.2 Italy 7 7.1 Pakistan 15 15 Afghanistan 26.7 S. Arabia 7 7.1 Burkina Faso 14 14.3 Nepal 24.6 S. Africa 6 5.7 Niger 14 14.1 Mozambique 22.2 Ukraine 6 5.5 Indonesia 14 14 Korea, DR 22.2 Spain 5 5.3 Malawi 14 13.6 Ghana 20.4 Australia 5 5.2 figure 5.1 Overview of high-impact countries Source: IEA, WB Global Electrification Database, WHO Global Household Energy Database. Note: DR = “Democratic Republic of.” FIG o.27 overview of high-impact countries SOURCE: WB, WHO, IEA In charting a course toward the achievement of the SE4ALL (table 5.4). With regard to universal access, business as objectives, it will also be important to learn from the expe- usual would leave 12–16 percent and 31–36 percent of the rience of fast-moving countries that made particularly rapid world’s population in 2030 without electricity and modern progress on the three energy indicators between 1990 and cooking solutions, respectively. With regard to energy effi- 2010 (figure 5.2). In the case of electrification and cooking, ciency, implementing all currently available measures with even the fastest-moving countries have not been able to reasonable payback periods would be enough to meet expand access by more than 3–4 percentage points an- or even exceed the SE4ALL objective. However, barriers nually. In the case of energy efficiency, the most rapid im- prevent wider adoption of many of those measures, with provements in energy intensity, amounting to a compound the result that their current uptake ranges from around 20 annual growth rate of 4–8 percent, have been achieved in percent for power generation and building construction to countries that began with high levels of energy intensity, around 40 percent for manufacturing and transportation. where efficiency gains were relatively easy to make. In the With regard to renewable energy, few scenarios point to case of renewable energy, the fastest-moving countries renewable energy shares above 30 percent by 2030. have experienced compound annual growth rates of 10–15 percent (excluding traditional biomass). On all three aspects of energy sector development, China and India, stand out as being both high-impact and fast-moving countries. Global energy model scenarios that gauge the scale of the global challenge implied by the achievement of these three objectives make it plain that business as usual will not remotely suffice to deliver the three SE4ALL objectives 225 Global tracking framework Cumulative population connected to Cumulative population gaining electricity (million) access to non-solid fuels (million) India 474 473.7 India 402 402.5 India 474 473.7 India 402 402.5 China 258 258.1 China 318 318.4 China 258 258.1 China 318 318.4 Indonesia 103 102.6 Brazil 62 62.5 Indonesia 103 102.6 Brazil 62 62.5 Pakistan 92 92 Pakistan 49 49 Pakistan 92 92 Pakistan 49 49 Bangladesh 59 59.3 Indonesia 47 47.1 Bangladesh 59 59.3 Indonesia 47 47.1 Brazil 55 55.4 Vietnam 36 36.3 Brazil 55 55.4 Vietnam 36 36.3 Philippines 37 37.4 Mexico 34 34.4 Philippines 37 37.4 Mexico 34 34.4 Nigeria 35 35.2 Thailand 30 30.1 Nigeria 35 35.2 Thailand 30 30.1 Mexico 32 32.3 Egypt, Arab Rep. 28 28.4 Mexico 32 32.3 Egypt, Arab Rep. 28 28.4 Egypt 26 26.5 Turkey 27 27.4 Egypt 26 26.5 Turkey 27 27.4 Vietnam 25 25.3 Iran, Islamic Rep. 26 25.5 Vietnam 25 25.3 Iran, Islamic Rep. 26 25.5 Iran 21.5 Philippines 22.5 Iran 21.5 Philippines 22.5 Morocco 19.4 South Africa 20.1 Morocco 19.4 South Africa 20.1 Turkey 18.6 Iraq 16.2 Turkey 18.6 Iraq 16.2 South Africa 17.5 Colombia 15.1 South Africa 17.5 Colombia 15.1 Thailand 15.7 Nigeria 14.8 Thailand 15.7 Nigeria 14.8 Iraq 15.1 Malaysia 14.2 Iraq 15.1 Malaysia 14.2 Colombia 14.8 Korea, Rep. 13.9 Colombia 14.8 Korea, Rep. 13.9 Ethiopia 14.2 Algeria 13.7 Ethiopia 14.2 Algeria 13.7 Saudi Arabia 11.8 Argentina 13.2 Saudi Arabia 11.8 Argentina 13.2 Cumulative energy saved through Cumulative renewable energy consumed, reductions in energy intensity (exajoules) excluding traditional biomass (exajoules) China 1320 1,320 USA 62 62 China 1320 1,320 USA 62 62 USA 369 369 Brazil 50 50 USA 369 369 Brazil 50 50 India 114 114 India 32 32 India 114 114 India 32 32 Germany 69 Canada 29 29 Germany 69 Canada 29 29 UK 47 China 24 24 UK 47 China 24 24 Poland 46 France 13 13 Poland 46 France 13 13 Bosnia H. 38 Russia 11 11 Bosnia H. 38 Russia 11 11 Russia 35 Sweden 11 11 Russia 35 Sweden 11 11 Iraq 24 Japan 10 10 Iraq 24 Japan 10 10 Canada 23 Mexico 9 9 Canada 23 Mexico 9 9 Belarus 18 Norway 9 9 Belarus 18 Norway 9 9 Romania 18 Germany 9 9 Romania 18 Germany 9 9 Estonia 16 Turkey 8 8 Estonia 16 Turkey 8 8 Mexico 14 Indonesia 8 8 Mexico 14 Indonesia 8 8 France 14 Nigeria 7 7 France 14 Nigeria 7 7 Australia 13 Spain 6 6 Australia 13 Spain 6 6 Kazakhstan 12 Finland 6 6 Kazakhstan 12 Finland 6 6 Argentina 11 Italy 6 6 Argentina 11 Italy 6 6 Nigeria 11 Austria 5 5 Nigeria 11 Austria 5 5 Czech Rep. 10 Chile 5 5 Czech Rep. 10 Chile 5 5 figure 5.2 Overview of fast moving countries (1990-2010) Source: IEA, UN, WB Global Electrification Database, WHO Global Household Energy Database. Note: Bosnia H. = Bosnia and Herzegovina. Actual global investment in the areas covered by the three The global energy models also help to clarify the kinds of SE4ALL objectives has been estimated at around $400 policy measures that would be needed to reach the three billion in 2010 (table 5.5). The additional investments re- sustainable energy objectives. The IEA’s World Energy quired to achieve the three objectives are tentatively es- Outlook (WEO) and the Global Energy Assessment (GEA) timated to be at least $600–800 billion per year, entailing of the International Institute for Applied Systems Analysis a doubling or tripling of direct financial flows over current (IIASA) coincide in highlighting the importance of phasing levels. The bulk of those investments are associated with out fossil fuel subsidies, adopting measures to provide the energy efficiency and renewable energy objectives, transparent price signals for carbon, embracing stringent with access-related expenditures representing a relatively and consistent technology standards for energy efficiency, small percentage of the incremental costs (10–20 percent). and carefully designing targeted subsidies to increase ac- cess to electricity and clean cooking fuels. chapter 5: conclusions 226 Global models also serve to clarify the likely pattern of ef- annually—are projected for Asia (particularly China) and forts across geographical regions toward the achievement the countries of the former Soviet Union. For renewable en- of the three objectives, based on their starting points, their ergy, Sub-Saharan Africa and Latin America emerge as the potential for improvement, and their comparative advan- regions projected to reach the highest share of renewable tage. On energy access, greatest efforts are needed in energy in 2030—in excess of 50 percent, while much of the Sub-Saharan Africa and South Asia. For energy efficiency, rest of the world falls in the 20–40 percent range (table 5.6). the highest rates of improvement—around –4 percent Objective 1 Objective 2 Objective 3 Doubling share Doubling global of renewable Universal access to modern energy services rate of improvement energy in global of energy efficiency mix Population with Global rate of Renewable energy Population with Percentage in 2030 primary reliance on improvement in share in total final electricity access non-solid fuels energy intensity* energy consumption IEA scenarios   New policies 88 69 –2.3 20   Efficient world 88 69 –2.8 22  450 n.a. n.a. –2.9 27 GEA scenarios Baseline 84 64 –1.0 12   GEA Pathways 100 100 –3.0 to –3.2 34 to 41  2 Celsius 0 n.a. n.a. –1.8 to –3.2 23 to 41 Table 5.4 Overview of projected outcomes for 2030 from IEA World Energy Outlook and IIASA Global Energy Assessment Source: IEA (2012) and IIASA (2012). n.a. = not applicable. * IEA scenarios are presented in primary energy terms while GEA scenarios in final energy terms (GDP at purchasing power parity in both cases) Objective 1 Objective 2 Objective 3 Average annual Doubling global rate Doubling share Universal access to investment 2010–30 of improvement of of renewable Total modern energy services (US$ billion) energy efficiency energy in global mix Electrification Cooking Energy efficiency Renewable energy Actual for 2010 9.0 0.1 180 228 417.1 Additional from WEO 45.0 4.4 393 >>174 >>616.4* Additional from GEA 15.0 71.0 259–365 259–406 604–858** Table 5.5 Overview of projected annual investment needs for 2010–2030 from World Energy Outlook and Global Energy Assessment Source: IEA (2012) and IIASA (2012). * WEO estimates are taken to be those closest to the corresponding SE4ALL objective: the Energy for All Scenario in the case of universal access, the Efficient World Scenario in the case of energy efficiency, and the 450 Scenario in the case of renewable energy. The 450 Scenario corresponds to a 27 percent renewable energy share, which is significantly below the SE4ALL objective. The Efficient World Scenario corresponds to a –2.8 percent CAGR for global energy intensity, which is significantly above the SE4ALL objective. ** GEA estimates that a further $716–910 billion would be needed annually for complementary infrastructure and broader energy sector investments not directly associated with the three objectives. 227 Global tracking framework Objective 1 Objective 2 Objective 3 Doubling global rate Doubling share Universal access to modern of improvement of of renewable energy energy services energy efficiency in global mix Percentage of Percentage of Renewable energy population with Rate of improvement population with share in total final primary reliance on in energy intensity* electricity access energy consumption non-solid fuels 2010 SE4ALL 2010 SE4ALL 1990–2010 SE4ALL 2010 SE4ALL Sub-Saharan Africa 32 100 19 100 1.1 2.2–2.4 56 60–73 Centrally Planned Asia 98 100 54 100 5.2 3.6–3.9 17 27–31 Central and Eastern Europe 100 100 90 100 3.1 2.6–3.0 8 28–36 Former Soviet Union 100 100 95 100 2.4 3.7–4.3 6 27–48 Latin America and Caribbean 95 100 86 100 0.7 2.6–3.0 25 49–57 Middle East and North Africa 95 100 99 100 -0.9 1.8–2.1 3 13–17 North America 100 100 100 100 1.7 2.4–2.6 8 26–34 Pacific OECD 100 100 100 100 0.7 2.9–3.4 6 30–41 Other Pacific Asia 89 100 57 100 1.2 3.6–4.0 18 30–37 South Asia 74 100 38 100 2.9 2.7–2.9 47 25–32 Western Europe 100 100 100 100 1.1 3.2–3.5 11 27–43 World 83 100 59 100 1.5 3.0–3.2 17 34–41 Table 5.6 Global Energy Assessment: Regional projections under SE4ALL scenarios Source: IIASA (2012). Access to electricity for 2010 is from WB Global Electrification Database, 2012. Access to non-solid fuel for 2010 is from WHO Global Household Energy Database, 2012. * Measured in final energy terms and GDP at purchasing power parity Moreover, the global energy models clarify how the three and others 2013). The achievement of the universal access SE4ALL objectives interact with each other and contribute objective for modern cooking, which would increase reli- to addressing global concerns such as climate change. ance on typically fossil-based non-solid fuels for cooking, The IEA finds that neither energy efficiency nor renewable would have a small offsetting effect, reducing the share of energy measures alone will be sufficient to contain global renewable energy in the global mix by some two percent- warming to two degrees Celsius, but that the two, in tan- age points, with a negligible impact on the probability of dem, take us much closer to the target. Achieving universal achieving the two degree Celsius target. access to modern energy would have a negligible effect on global carbon dioxide emissions, adding only 0.6 percent. In conclusion, the Global Tracking Framework has con- The GEA estimates that the probability of limiting global structed a robust data platform capable of monitoring warming to two degrees Celsius increases to between 66 global progress toward the SE4ALL objectives. Looking and 90 percent when the SE4ALL objectives for renewable ahead, the consortium of agencies that has produced this energy and energy efficiency are simultaneously met— report recommends a biannual update on the status of the higher than if either objective were met individually (Rogelj three SE4ALL objectives that will build on this framework. chapter 5: conclusions 228 The methodology of the SE4ALL Global Tracking Frame- Finally, given the scale of the challenge of meeting the three work provides an adequate basis for basic global tracking, SE4ALL objectives for energy, it is apparent that bold poli- but that tracking effort could be vastly improved if sever- cy measures, combined with a regulatory and institutional al measures were implemented over the next five years. environment that supports innovation and encourages in- These cost-effective, high-impact improvements to global vestment, will be required to produce the requisite increas- energy databases will be contingent on the availability of es in the energy sector’s capacity to widen access, boost financial resources. For energy access, the focus will be the output derived from a given unit of energy, and raise to move beyond binary measures of energy access to a the share of renewable energy in the overall energy mix. multi-tier framework that better captures the quantity and A detailed analysis of the policy environment at the coun- quality of electricity supplied, as well as the efficiency, safe- try level lies beyond the immediate scope of this Global ty and convenience of household cookstoves, including Tracking Framework, which has focused on the monitoring those that make use of biomass. For energy efficiency, the of global progress toward the stated SE4ALL objectives. main concern is to strengthen countries’ capacity to pro- However, it will be an important focus for future work in duce disaggregated data on sectoral and subsectoral en- support of the critical social, economic, and environmental ergy consumption that are fully integrated with measures goals that the SE4ALL initiative addresses. of the output of those same sectors. In the case of renew- able energy, the main priority will be to improve the ability to gauge the sustainability of different forms of renewable energy, particularly traditional biomass. 229 Global tracking framework References IEA (International Energy Agency). 2012b. World Energy Outlook. Paris. http://www.worldenergyoutlook.org/publications/weo-2012/. IIASA (International Institute for Applied Systems Analysis). 2012. Global Energy Assessment—Toward a Sustainable Future. Cambridge, England, and Laxenburg, Austria: Cambridge University Press and IIASA. http://www.iiasa.ac.at/web/home/research/researchPrograms/Energy/Home-GEA.en.html Rogelj, Joeri, David L. McCollum, and Keywan Riahi. 2013. “The UN’s ‘Sustainable Energy for All Initiative’ Is Compatible with a Warming Limit of 2°C.” Perspective DOI 10.1038/NCLIMATE1806, Nature Climate Change, February 24. chapter 5: conclusions 230 data annex energy access energy efficiency RENEwable energy DATA ANNEX: ENERGY access Access to Electricity (% of population ) Access to Non-Solid Fuel (% of population) Total Rural URban Total Rural Urban Latest available Latest available Region Country 1990 2000 2010 2010 2010 1990 2000 2010 2010 2010 Source/year Source/year SA Afghanistan 35 37 41 29 81 NRVA 2007/08 <5 9 15 5 66 Other2007 DEV Albania 100 100 100 100 100 DHS 2008 36 50 61 49 89 DHS2008 NA Algeria 94 98 99 98 100 COMELEC 2007 86 > 95 > 95 > 95 > 95 MICS2006 Oceania American Samoa 49 53 56 43 57 Estimate DEV Andorra 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption SSA Angola 28 31 35 6 55 DHS 2011 <5 16 45 11 84 DHS2006 LAC Antigua and Barbuda 81 85 88 74 100 Estimate 86 > 95 > 95 > 95 > 95 Other2007 LAC Argentina 81 85 88 74 89 Estimate 83 94 > 95 > 95 > 95 Other2001 CCA Armenia 94 98 100 100 100 DHS 2005 15 50 81 51 > 95 NatSur2008 LAC Aruba 81 85 88 74 100 Estimate DEV Australia 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption DEV Austria 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption CCA Azerbaijan 93 96 100 99 100 DHS 2006 48 72 93 81 > 95 DHS2006 LAC Bahamas 81 85 88 74 91 Estimate > 95 > 95 > 95 > 95 > 95 Estimate WA Bahrain 87 91 94 90 95 Estimate > 95 > 95 > 95 > 95 > 95 Estimate SA Bangladesh 22 32 55 43 88 HIES 2010 9 11 9 5 37 DHS2007 LAC Barbados 81 85 88 74 100 Estimate > 95 > 95 > 95 > 95 > 95 NatCen2000 DEV Belarus 100 100 100 100 100 HBS 2009 81 92 > 95 94 > 95 MICS2005 DEV Belgium 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption LAC Belize 81 85 88 74 100 Estimate 71 81 88 82 > 95 NatCen2010 SSA Benin 22 25 28 9 52 DHS 2006 <5 6 9 5 14 DHS2006 DEV Bermuda 100 100 100 100 100 Assumption SA Bhutan 66 68 72 50 100 DHS 2007 22 42 60 45 > 95 MICS2010 LAC Bolivia, Plurinational State of 74 77 80 55 93 DHS 2008 55 64 71 27 94 DHS2008 DEV Bosnia and Herzegovina 94 99 100 98 100 HBS 2007 42 50 55 31 83 MICS2005 SSA Botswana 37 40 43 43 43 BAIS III 2008 35 50 63 38 90 NatSur2007 LAC Brazil 92 97 99 94 100 NatCen2009 81 89 94 64 > 95 WHS2003 SEA Brunei Darussalam 66 69 73 64 75 Estimate > 95 > 95 > 95 > 95 > 95 Estimate DEV Bulgaria 100 100 100 100 100 HIS 2007 77 87 93 Estimate 232 Global tracking framework Access to Electricity (% of population ) Access to Non-Solid Fuel (% of population) Total Rural URban Total Rural Urban Latest available Latest available Region Country 1990 2000 2010 2010 2010 1990 2000 2010 2010 2010 Source/year Source/year SSA Burkina Faso 6 7 13 1 47 DHS 2010 <5 <5 8 5 23 NatSur2007 SSA Burundi 0 4 5 1 41 DHS 2010 <5 <5 <5 <5 5 MICS2005 SEA Cambodia 19 17 31 19 81 DHS 2010 <5 6 11 5 45 DHS2010 SSA Cameroon 29 46 49 14 82 NatCen2006 6 17 25 5 41 MICS2005 DEV Canada 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption SSA Cape Verde 58 59 67 44 81 DHS 2005 51 61 68 33 90 NatSur2007 LAC Cayman Islands 81 85 88 74 88 Estimate SSA Central African Republic 3 6 9 5 16 Estimate <5 <5 <5 <5 5 MICS2006 SSA Chad 0 2 4 0 15 DHS 2004 <5 <5 12 6 27 Other2005 DEV Channel Islands 100 100 100 100 100 Assumption LAC Chile 95 98 100 98 100 ENEMDU 2010 76 86 94 53 > 95 N atCen2002 EA China 94 98 100 98 100 Electric Company 36 47 54 19 70 NatCen2005 2010 EA China, Hong Kong SAR 100 100 100 100 100 Estimate EA China, Macau SAR 86 90 93 90 93 Estimate LAC Colombia 90 93 97 91 99 NatCen2010 74 81 86 49 > 95 DHS2010 SSA Comoros 42 45 48 37 77 Estimate 11 21 29 15 58 Other2004 SSA Congo 24 21 37 9 53 DHS 2009 <5 14 23 5 33 DHS2009 SSA Congo, Dem. Rep. of the 6 7 15 3 39 DHS 2007 <5 <5 7 5 14 DHS2007 LAC Costa Rica 93 95 99 98 100 ENCOVI 2010 77 87 94 86 > 95 NatSur2009 SSA Cote d'Ivoire 37 51 59 37 80 DHS 2005 13 19 22 5 35 MICS2005 DEV Croatia 100 100 100 100 100 Assumption 73 84 92 82 > 95 WHS2003 LAC Cuba 94 97 100 93 100 Estimate 93 94 91 77 94 Other2008 LAC Curacao 81 85 88 74 88 Estimate DEV Cyprus 96 100 100 100 100 Assumption > 95 > 95 > 95 Assumption DEV Czech Republic 100 100 100 100 100 HBS 2009 82 94 > 95 > 95 > 95 WHS2003 DEV Denmark 100 100 100 100 100 Assumption > 95 > 95 > 95 Assumption SSA Djibouti 43 46 50 10 61 PRSP 2004 84 87 87 21 90 NatSur2006 LAC Dominica 85 88 91 100 87 Estimate 58 80 > 95 > 95 > 95 NatCen2001 ANNEX: energy access 233 Access to Electricity (% of population ) Access to Non-Solid Fuel (% of population) Total Rural URban Total Rural Urban Latest available Latest available Region Country 1990 2000 2010 2010 2010 1990 2000 2010 2010 2010 Source/year Source/year LAC Dominican Republic 78 92 98 94 100 NatCen2010 63 80 93 85 > 95 DHS2007 SEA East Timor 32 34 38 24 74 DHS 2010 <5 8 8 <5 21 DHS2009 LAC Ecuador 90 93 97 93 100 NatCen2010 73 87 > 95 87 > 95 NatCen2006 NA Egypt 96 98 100 99 100 DHS 2008 93 > 95 > 95 > 95 > 95 DHS2005 LAC El Salvador 77 88 92 82 97 INE 2010 50 65 78 49 93 NatSur2007 SSA Equatorial Guinea 22 26 29 14 52 Estimate 18 21 23 Estimate SSA Eritrea 23 32 33 9 79 Estimate 14 28 40 15 73 DHS2002 DEV Estonia 100 100 100 100 100 Assumption 72 82 89 69 > 95 WHS2003 SSA Ethiopia 10 13 23 5 85 DHS 2011 7 6 <5 <5 27 DHS2005 DEV Faeroe Islands 100 100 100 100 100 Assumption Oceania Fiji 49 53 56 43 68 Estimate 45 56 63 Other1996 DEV Finland 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption DEV France 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption Oceania French Polynesia 49 53 56 43 68 Estimate SSA Gabon 73 74 82 35 89 CWIQ 2005 50 64 74 25 86 Other2006 SSA Gambia 18 34 31 23 37 Estimate <5 <5 9 5 12 MICS2005 CCA Georgia 97 100 100 100 100 HBS 2009 45 51 54 15 88 MICS2005 DEV Germany 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption SSA Ghana 31 45 61 38 82 DHS 2008 <5 9 16 5 28 DHS2008 DEV Greece 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption DEV Greenland 100 100 100 100 100 Assumption LAC Grenada 81 85 88 74 100 Estimate 69 89 100 100 100 NatCen2001 Oceania Guam 49 53 56 43 57 Estimate LAC Guatemala 76 79 82 68 96 NatCen2006 36 41 43 18 73 WHS2003 SSA Guinea 14 16 20 3 53 DHS 2005 <5 <5 <5 <5 <5 DHS2005 SSA Guinea-Bissau 51 54 57 19 100 Estimate <5 <5 <5 <5 <5 MICS2006 LAC Guyana 72 75 78 72 91 DHS 2009 74 85 93 91 > 95 DHS2009 LAC Haiti 31 31 34 12 54 DHS 2006 <5 6 9 5 16 DHS2005 LAC Honduras 75 77 81 64 97 NatCen2010 32 42 49 14 81 DHS2005 234 Global tracking framework Access to Electricity (% of population ) Access to Non-Solid Fuel (% of population) Total Rural URban Total Rural Urban Latest available Latest available Region Country 1990 2000 2010 2010 2010 1990 2000 2010 2010 2010 Source/year Source/year DEV Hungary 100 100 100 100 100 HBS 2007 > 95 > 95 > 95 > 95 > 95 Assumption DEV Iceland 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption SA India 51 62 75 67 93 NSSO 2009 13 29 42 14 77 NatSur2006 SEA Indonesia 67 88 94 89 99 DHS12 2010 33 41 45 23 80 DHS2007 SA Iran, Islamic Republic of 94 98 98 95 100 Ministry of Energy 88 > 95 > 95 > 95 > 95 Natcen2006 2006 WA Iraq 92 94 98 94 100 IAU Iraq / UN 89 > 95 > 95 91 > 95 MICS2005 Factsheet 2011 DEV Ireland 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption DEV Isle of Man 100 100 100 100 100 Assumption DEV Israel 96 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption DEV Italy 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption LAC Jamaica 70 87 92 84 99 Ministry of Energy, 62 77 89 NatCen2001 2008; DEV Japan 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption WA Jordan 95 100 99 99 100 DHS 2009 88 > 95 > 95 > 95 > 95 DHS2009 CCA Kazakhstan 94 97 100 98 100 HBS 2008 71 83 91 77 > 95 MICS2005 SSA Kenya 11 15 23 8 71 DHS 2008 18 20 20 5 61 DHS2010 Oceania Kiribati 49 53 56 43 73 Estimate 34 45 54 Estimate EA Korea, Dem. People’s Rep. of 20 22 26 10 37 Fund for Peace <5 7 9 5 11 NatCen2008 2008; IEA est EA Korea, Republic of 86 90 93 90 94 Estimate 80 > 95 > 95 > 95 > 95 Other1998 DEV Kosovo 100 100 100 100 100 HBS 2009 WA Kuwait 87 91 94 90 94 Estimate > 95 > 95 > 95 > 95 > 95 Estimate CCA Kyrgyzstan 97 100 100 100 100 HBS 2008 49 59 66 47 90 MICS2005 SEA Lao People’s Dem. Rep. 52 46 66 52 94 LECS4 2008 <5 5 <5 <5 11 NatSur2007 DEV Latvia 100 100 100 100 100 Assumption 77 87 95 78 > 95 WHS2003 WA Lebanon 93 95 100 99 100 Other 92 > 95 > 95 > 95 > 95 Other1996 SSA Lesotho 6 5 17 7 43 DHS 2009 37 39 39 20 94 DHS2009 SSA Liberia 0 1 4 1 7 DHS 2011 <5 <5 <5 <5 5 DHS2009 ANNEX: energy access 235 Access to Electricity (% of population ) Access to Non-Solid Fuel (% of population) Total Rural URban Total Rural Urban Latest available Latest available Region Country 1990 2000 2010 2010 2010 1990 2000 2010 2010 2010 Source/year Source/year NA Libya 97 100 100 99 100 Estimate 89 > 95 > 95 > 95 > 95 Estimate DEV Liechtenstein 100 100 100 100 100 Assumption DEV Lithuania 100 100 100 100 100 HBS 2008 77 87 93 Assumption DEV Luxembourg 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption DEV Macedonia, Former Yugoslav Rep. of 93 95 99 98 100 HBS 2006 52 61 67 48 78 MICS2005 SSA Madagascar 9 11 14 9 25 DHS 2011 <5 <5 <5 <5 5 NatCen2009 SSA Malawi 3 5 9 4 37 DHS 2010 <5 <5 <5 <5 11 DHS2010 SEA Malaysia 93 96 99 98 100 HIS/BA 2009 78 92 > 95 > 95 > 95 WHS2003 SA Maldives 94 96 100 100 100 DHS 2009 36 65 92 91 > 95 DHS2009 SSA Mali 12 17 17 3 42 DHS 2006 <5 <5 <5 <5 5 DHS2006 DEV Malta 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption Oceania Marshall Islands 49 53 56 43 61 Estimate 80 76 68 8 92 Other2007 SSA Mauritania 12 15 18 2 42 EPCV 2005 20 32 42 21 66 MICS2007 SSA Mauritius 97 99 100 100 100 Estimate 81 93 > 95 > 95 > 95 NatSur2004 LAC Mexico 95 98 99 98 100 NatCen2010 75 82 86 61 > 95 NatCen2010 Oceania Micronesia, Federated States of 49 53 56 43 100 Estimate 45 53 59 NatCen2005 DEV Moldova, Republic of 92 95 99 98 99 DHS 2005 72 82 89 79 > 95 DHS2005 DEV Monaco 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption EA Mongolia 80 83 86 67 100 LSMS 2005 19 25 28 5 43 MICS2005 DEV Montenegro 100 100 100 100 100 Assumption 56 65 72 46 85 MICS2005 NA Morocco 49 71 99 97 100 DHS 2003 81 91 > 95 87 > 95 DHS2004 SSA Mozambique 6 7 15 2 45 DHS 2009 <5 <5 5 5 10 MICS2008 SEA Myanmar 43 47 49 28 92 IHLCA 2010 <5 <5 8 5 17 Other2004 SSA Namibia 26 37 44 15 92 DHS 2006 26 37 45 14 83 DHS2006 SA Nepal 70 73 76 72 100 DHS 2011 26 23 18 10 67 DHS2006 DEV Netherlands 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption Oceania New Caledonia 49 53 56 43 64 Estimate DEV New Zealand 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption LAC Nicaragua 72 73 74 43 96 ENAHO 3 2005 23 36 46 9 71 NatSur2006 236 Global tracking framework Access to Electricity (% of population ) Access to Non-Solid Fuel (% of population) Total Rural URban Total Rural Urban Latest available Latest available Region Country 1990 2000 2010 2010 2010 1990 2000 2010 2010 2010 Source/year Source/year SSA Niger 6 7 9 2 46 DHS 2006 <5 <5 <5 <5 6 DHS2006 SSA Nigeria 42 45 48 35 62 DHS 2010 26 28 26 10 54 DHS2008 DEV Norway 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption WA Oman 87 91 94 90 96 Estimate > 95 > 95 > 95 > 95 > 95 Estimate SA Pakistan 60 80 91 88 98 PSLM 2010-11 12 26 36 11 71 NatSur2006 Oceania Palau 49 53 56 43 58 Estimate 90 > 95 > 95 Other1997 LAC Panama 81 85 88 74 93 Estimate 75 80 82 73 > 95 LSMS2008 Oceania Papua New Guinea 8 11 15 8 63 LSMS 2006 5 17 27 11 72 LSMS1996 LAC Paraguay 90 92 97 94 99 NatCen2010 46 50 51 20 68 NatSur2009 LAC Peru 69 72 85 60 93 NatCen2010 38 52 64 25 92 NatSur2010 SEA Philippines 65 71 83 73 94 DHS 2008 40 47 50 34 76 DHS2008 DEV Poland 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption DEV Portugal 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption LAC Puerto Rico 81 85 88 74 88 Estimate WA Qatar 87 91 94 90 94 Estimate 92 > 95 > 95 > 95 > 95 NatCen2010 DEV Romania 100 100 100 100 100 HBS 2009 65 75 83 63 > 95 Other2002 DEV Russian Federation 100 100 100 100 100 HBS 2009 91 > 95 > 95 92 > 95 MICS2005 SSA Rwanda 2 6 11 4 40 EICV 3 2011 <5 <5 <5 <5 5 NatSur2007 LAC Saint Lucia 81 85 88 74 100 Estimate 63 86 100 100 100 Estimate Oceania Samoa 80 89 100 90 100 Estimate 30 40 47 25 73 DHS2009 DEV San Marino 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption SSA Sao Tome and Principe 50 53 57 44 65 DHS 2008 9 20 29 15 42 DHS2008 WA Saudi Arabia 87 91 94 90 95 Estimate > 95 > 95 > 95 > 95 > 95 Estimate SSA Senegal 26 37 57 27 97 DHS 2011 19 35 49 17 86 NatSur2008 DEV Serbia 100 100 100 100 100 Estimate 49 60 68 41 89 MICS2005 SSA Seychelles 22 26 29 14 42 Estimate 80 93 > 95 > 95 > 95 Other2002 SSA Sierra Leone 6 9 12 1 29 DHS 2008 7 5 <5 <5 5 DHS2008 SEA Singapore 66 69 73 64 73 Estimate > 95 > 95 > 95 > 95 > 95 Estimate DEV Slovak Republic 100 100 100 100 100 Assumption 81 93 > 95 > 95 > 95 WHS2003 ANNEX: energy access 237 Access to Electricity (% of population ) Access to Non-Solid Fuel (% of population) Total Rural URban Total Rural Urban Latest available Latest available Region Country 1990 2000 2010 2010 2010 1990 2000 2010 2010 2010 Source/year Source/year DEV Slovenia 100 100 100 100 100 Assumption 76 88 > 95 > 95 > 95 WHS2003 Oceania Solomon Islands 13 16 19 10 57 Estimate 10 12 10 5 43 NatSur2007 SSA Somalia 22 26 29 14 54 Estimate <5 <5 <5 <5 5 MICS2005 SSA South Africa 65 66 83 64 94 GHS 2011 61 75 85 63 94 NatSur2010 SSA South Sudan 0 0 2 1 5 NatCen2010 DEV Spain 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 WHS2003 SA Sri Lanka 78 81 85 83 96 HIES 2009 11 20 25 15 66 NatSur2009 LAC St. Kitts and Nevis 81 85 88 74 100 Estimate 73 81 86 Estimate LAC St. Martin (French part) 81 85 88 74 100 Estimate LAC St. Vincent and the Grenadines 67 70 73 29 100 Estimate 31 65 > 95 > 95 > 95 NatSur2007 SSA Sudan 23 25 29 15 57 Other HH 2010 <5 7 21 13 24 NatCen2008 LAC Suriname 97 100 100 100 100 Estimate 70 81 88 MiCS2006 SSA Swaziland 29 32 35 22 85 DHS 2006 22 35 45 25 87 DHS2006 DEV Sweden 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption DEV Switzerland 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption WA Syrian Arab Republic 85 87 93 78 100 Other HH 2010 84 > 95 > 95 > 95 > 95 MICS2005 CCA Tajikistan 95 99 100 99 100 LSMS 2003 14 41 66 53 94 MICS2005 SSA Tanzania, United Republic of 7 9 15 4 46 DHS 2010 <5 <5 6 5 16 DHS2010 SEA Thailand 93 96 100 97 100 Household Energy 37 57 74 57 90 MICS2005 Consumption Survey 2010 SSA Togo 10 17 28 6 64 QUIBB 2006 <5 <5 6 5 7 NatSur2006 Oceania Tonga 80 86 92 80 100 Estimate 28 44 57 53 92 NatCen2006 LAC Trinidad and Tobago 93 95 99 98 100 Other HH 2009 81 93 > 95 > 95 > 95 MICS2006 NA Tunisia 93 95 100 99 100 COMELEC 2007 82 94 > 95 > 95 > 95 MICS2006 WA Turkey 100 100 100 100 100 HBS 2009 79 90 > 95 > 95 > 95 Other1999 CCA Turkmenistan 95 100 100 100 100 HBS 2009 86 > 95 > 95 > 95 > 95 DHS2000 LAC Turks and Caicos Islands 81 85 88 74 89 Estimate Oceania Tuvalu 35 37 41 29 53 Estimate 33 58 81 Other2002 238 Global tracking framework Access to Electricity (% of population ) Access to Non-Solid Fuel (% of population) Total Rural URban Total Rural Urban Latest available Latest available Region Country 1990 2000 2010 2010 2010 1990 2000 2010 2010 2010 Source/year Source/year SSA Uganda 7 9 15 5 67 DHS 2011 <5 <5 <5 <5 11 DHS2009 DEV Ukraine 93 96 100 100 100 DHS 2007 79 90 > 95 89 > 95 DHS2007 WA United Arab Emirates 87 91 94 90 95 Estimate 86 > 95 > 95 > 95 > 95 WHS2003 DEV United Kingdom of Great Britain 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption and Northern Ireland DEV United States of America 100 100 100 100 100 Assumption > 95 > 95 > 95 > 95 > 95 Assumption LAC Uruguay 92 96 99 93 100 SEDLAC 2009 89 > 95 > 95 87 > 95 NatSur2006 CCA Uzbekistan 97 100 100 100 100 Estimate 69 80 89 80 > 95 MICS2005 Oceania Vanuatu 18 19 24 15 50 Estimate 17 18 16 6 49 MICS2007 LAC Venezuela, Bolivarian Rep. of 99 100 100 100 100 SEDLAC 2010 85 > 95 > 95 > 95 > 95 NatCen2001 SEA Vietnam 88 89 96 95 99 LSMS 2006 <5 24 44 29 78 NatCen2009 LAC Virgin Islands (U.S.) 81 85 88 74 89 Estimate WA West Bank and Gaza 87 91 94 90 96 Estimate WA Yemen 38 41 45 31 75 Estimate 52 61 67 49 > 95 MICS2006 SSA Zambia 13 17 19 3 43 DHS 2007 5 13 17 5 39 DHS2007 SSA Zimbabwe 28 34 37 13 75 DHS 2011 32 34 34 6 84 DHS2006 Aggregated by income level Access to Electricity (% of population ) Access to Non-Solid Fuel (% of population) Total Rural URban Total Rural Urban Latest available Latest available Region Country 1990 2000 2010 2010 2010 1990 2000 2010 2010 2010 Source/year Source/year High income: non-OECD 88 90 92 89 93 71 74 81 77 86 High income: OECD 99 100 100 100 100 99 100 100 99 100 Low income 20 24 32 19 64 7 9 9 6 25 Lower middle income 58 68 77 69 91 25 37 46 21 75 Upper middle income 93 96 98 96 99 53 64 71 36 85 ANNEX: energy access 239 Aggregated by region Access to Electricity (% of population ) Access to Non-Solid Fuel (% of population) Total Rural URban Total Rural Urban Latest available Latest available Region Country 1990 2000 2010 2010 2010 1990 2000 2010 2010 2010 Source/year Source/year CCA Caucasus and Central Asia 95 99 100 99 100 58 73 85 74 98 DEV Developed Countries 100 100 100 100 100 95 98 99 96 100 EA Eastern Asia 93 96 98 97 98 37 48 55 35 76 LAC Latin America and Caribbean 88 92 95 84 98 73 81 86 57 94 NA Northern Africa 85 92 99 99 100 88 96 100 99 100 Oceania Oceania 21 23 25 14 65 14 24 31 21 73 SA Southern Asia 52 63 75 67 94 16 30 40 23 78 SEA Southeastern Asia 71 81 88 80 97 29 40 48 27 77 SSA Sub-Saharan Africa 23 26 32 14 63 14 17 19 6 42 WA Western Asia 89 89 91 78 97 83 90 95 86 99 WORLD 76 79 83 70 95 47 54 59 35 84 Note: The source field gives either (a) the name and date of the household survey from which the figure is taken; or (b) indicates that the figure is an estimate based on the statistical model described in Annex 2 of Chapter 2; or (c) is based on the assumption of universal access in countries classified by the United Nations as developed. Note: Developed countries (DEV) are considered to have access rates of 100 percent. CCA = Caucasus and Central Asia; EA = Eastern Asia; LAC = Latin America and Caribbean; NA = Northern Africa; SA = Southern Asia; SEA = South-Eastern Asia; SSA = Sub-Saharan Africa; WA = Western Asia; BAIS=Botswana AIDS Impact Survey III; COMELEC= Maghreb association of the electricity sector; CWIQ= Core Welfare Indicators Questionnaire Survey; DHS = Demographic and Health Survey; EICV=Integrated Household Living Conditions Survey in Rwanda; EPCV=permanent living conditions; GHS=General household survey; HBS = Household Budget Survey; IES = Integrated Expenditure Survey; HIES=Household income and expenditure surveys; HIS = Integrated House- hold Survey; HIS/BA= Household Income and Basic Amenities Survey Report; LECS=Lao Expenditure and Consumption Survey; LSMS = Living Standard Measurement Survey; MICS=Multiple Indicators Cluster Survey; NRVA=National Risk and Vulnerability Assessment; NSSO=National Sample Survey Organization; QUIBB=Questionnaire des Indicateurs de Base du Bienetre; WHS=World Health Survey. 240 Global tracking framework DATA ANNEX: ENERGY efficiency Decom- Rate of final Rate of primary Level of primary energy Final to Cumulative Data position Country energy intensity energy intensity, intensity primary energy sourcea analysis, improvement, energy ratio savings (PJ) improvement, CAGR (%) (MJ/$2005 PPP) CAGR (%) CAGR (%) 1990–2000 2000–2010 1990–2010 1990 2010 1990–2010 1990–2010 1990 2010 1990–2010 Afghanistan UN/WDI –15.81 3.12 –6.83 11.8 2.9 8.93** –2.04 — — 2,993 Albania IEA/WDI –5.28 –3.49 –4.39 8.7 3.5 -2.88* –3.84 84.0 94.2 1,227 Algeria IEA/WDI 0.30 0.34 0.32 5.9 6.3 — 1.10 57.4 67.0 –909 Angola IEA/WDI 1.68 –4.41 –1.41 7.7 5.8 -0.29 –1.23 77.0 79.9 184 Antigua and Barbuda UN/WDI –1.49 3.44 0.94 2.8 3.4 — –2.83 — — 6 Argentina IEA/WDI –1.63 –2.19 –1.91 7.9 5.4 -1.83 –1.43 65.3 72.0 11,171 Armenia IEA/WDI –9.13 –5.49 –7.33 30.9 6.8 -11.22 –7.97 84.0 73.1 3,756 Aruba UN/WDI — — — — — — — — — — Australia IEA/WDI –1.07 –1.56 –1.32 8.9 6.8 -1.27 –1.73 65.6 60.4 13,162 Austria IEA/WDI –1.25 0.16 –0.55 5.3 4.8 -0.36 –0.40 79.4 81.7 1,774 Azerbaijan IEA/WDI –2.93 –12.70 –7.95 32.2 6.1 -8.47* –8.22 61.2 57.6 10,415 Bahamas UN/WDI –2.75 3.78 0.46 3.4 3.7 — 8.38 — — 66 Bahrain IEA/WDI –2.38 –0.64 –1.51 20.6 15.2 — –1.51 54.5 54.6 1,535 Bangladesh IEA/WDI –0.89 –0.54 –0.71 6.8 5.9 -1.36 –1.48 86.2 73.8 1,558 Barbados UN/WDI –1.10 2.36 0.61 3.6 4.1 0.59 –3.36 — — 11 Belarus IEA/WDI –4.80 –5.80 –5.30 29.1 9.8 -4.63 –5.55 75.7 71.9 17,682 Belgium IEA/WDI –0.28 –0.98 –0.63 8.1 7.1 -0.84 –0.48 66.4 68.5 2,489 Belize UN/WDI 0.49 –6.34 –2.98 9.7 5.3 — –3.17 — — 78 Benin IEA/WDI –2.87 2.22 –0.36 13.0 12.1 — –0.28 86.4 87.8 282 Bermuda UN/WDI — — — — — — — — — — Bhutan UN/WDI –2.66 –5.83 –4.26 38.3 16.0 — 0.04 — — 528 Bolivia, Plurinational State of IEA/WDI –0.11 3.00 1.43 5.3 7.1 — 1.19 82.6 78.7 –371 Bosnia and Herzegovina IEA/WDI –22.25 –0.12 –11.87 119.7 9.6 -0.80** –13.37 69.7 49.6 37,653 Botswana IEA/WDI –1.79 –1.90 –1.84 5.5 3.8 -2.13 –1.14 71.4 82.4 426 Brazil IEA/WDI 0.39 –0.06 0.17 5.5 5.7 0.42 0.15 79.5 79.3 –4,973 British Virgin Islands UN/WDI — — — — — — — — — — Brunei Darussalam IEA/WDI 1.10 1.67 1.38 5.8 7.6 — 6.29 19.9 51.3 –257 Bulgaria IEA/WDI –2.99 –4.35 –3.67 18.2 8.6 -3.81 –4.55 61.0 50.8 7,280 ANNEX: energy efficiency 241 Decom- Rate of final Rate of primary Level of primary energy Final to Cumulative Data position Country energy intensity energy intensity, intensity primary energy sourcea analysis, improvement, energy ratio savings (PJ) improvement, CAGR (%) (MJ/$2005 PPP) CAGR (%) CAGR (%) 1990–2000 2000–2010 1990–2010 1990 2010 1990–2010 1990–2010 1990 2010 1990–2010 Burkina Faso UN/WDI –5.54 0.47 –2.58 21.2 12.6 -3.35* –3.01 — — 1,738 Burundi UN/WDI 2.15 2.30 2.23 21.4 33.3 — 8.81 — — –652 Cambodia IEA/WDI –2.97 –3.75 –3.43 13.7 7.6 — –4.20 0.0 84.8 –2,635 Cameroon IEA/WDI 1.01 –2.07 –0.54 8.2 7.4 -2.30** –1.30 95.4 81.9 –189 Canada IEA/WDI –1.00 –1.82 –1.41 11.7 8.8 -1.15 –1.31 76.3 77.8 23,448 Cape Verde UN/WDI 1.62 0.16 0.88 3.7 4.4 — –0.56 — — –16 Cayman Islands UN/WDI — — — — — — — — — — Central African Republic UN/WDI –4.09 –0.11 –2.12 18.3 11.9 — –3.57 — — 218 Chad UN/WDI 0.89 –5.70 –2.46 12.9 7.9 — 5.90 — — 488 Chile IEA/WDI –0.34 –1.73 –1.04 6.4 5.2 -1.10 –1.18 79.2 77.0 2,391 China IEA/WDI –7.07 –2.18 –4.65 30.5 11.8 -6.48 –5.64 76.0 61.6 1,319,738 China, Hong Kong SAR IEA/WDI 0.52 –3.59 –1.56 2.7 2.0 — –1.54 60.1 60.3 773 China, Macao SAR UN/WDI 2.83 –8.56 –3.04 1.8 1.0 — –4.13 — — 71 Colombia IEA/WDI –1.97 –1.76 –1.86 5.0 3.4 -2.50 –2.43 78.1 69.5 5,746 Comoros UN/WDI 2.45 2.50 2.47 2.9 4.7 — 7.69 — — –9 Congo IEA/WDI –0.92 1.38 0.22 3.8 4.0 — –0.04 77.8 73.9 16 Congo, Dem. Rep. of the IEA/WDI 9.66 –1.26 4.06 21.5 47.6 — 4.38 89.8 95.6 –7,220 Cook Islands UN/WDI — — — — — — — — — — Costa Rica IEA/WDI –1.31 0.29 –0.51 4.4 4.0 -1.55 –1.41 89.2 74.5 254 Cote d'Ivoire IEA/WDI 2.18 2.47 2.32 7.6 12.0 1.90 1.33 66.6 54.8 –1,645 Croatia IEA/WDI 0.10 –1.68 –0.80 5.9 5.0 -0.32 –0.23 72.1 80.7 138 Cuba IEA/WDI — — — — — — — 79.7 56.7 — Cyprus IEA/WDI 0.43 –1.44 –0.51 5.4 4.9 0.01 –0.04 64.2 70.5 –5 Czech Republic IEA/WDI –2.30 –2.57 –2.44 12.2 7.4 -3.05 –3.02 69.2 61.3 10,499 Denmark IEA/WDI –1.84 –0.24 –1.04 5.6 4.5 -0.83 –0.92 75.9 77.7 1,919 Djibouti UN/WDI 2.81 –0.26 1.26 5.2 6.7 — 4.03 — — –42 Dominica UN/WDI 3.96 –0.02 1.95 1.8 2.6 — –0.18 — — –8 Dominican Republic IEA/WDI 0.55 –4.40 –1.96 6.2 4.2 -5.53** –1.80 65.8 68.0 462 242 Global tracking framework Decom- Rate of final Rate of primary Level of primary energy Final to Cumulative Data position Country energy intensity energy intensity, intensity primary energy sourcea analysis, improvement, energy ratio savings (PJ) improvement, CAGR (%) (MJ/$2005 PPP) CAGR (%) CAGR (%) 1990–2000 2000–2010 1990–2010 1990 2010 1990–2010 1990–2010 1990 2010 1990–2010 Ecuador IEA/WDI 1.10 –0.40 0.35 4.5 4.9 -0.29 –0.18 87.5 78.8 –591 Egypt IEA/WDI –1.89 1.16 –0.38 7.4 6.8 -0.33* –0.61 70.8 67.6 1,860 El Salvador IEA/WDI 0.24 –1.31 –0.54 5.3 4.7 -3.27 –1.97 82.1 61.3 –8 Equatorial Guinea UN/WDI –11.08 6.53 –2.67 11.0 6.4 — –11.87 — — 808 Eritrea IEA/WDI –7.26 –1.45 –4.08 25.6 12.1 — –4.30 0.0 69.2 –640 Estonia IEA/WDI –14.62 –1.77 –8.42 60.8 10.5 -9.26 –9.10 60.6 52.3 15,850 Ethiopia IEA/WDI –0.45 –2.25 –1.36 23.6 18.0 -2.68 –1.39 95.1 94.3 1,668 Falkland Islands (Malvinas) UN/WDI — — — — — — — — — — Fiji UN/WDI –1.04 –3.67 –2.36 7.9 4.9 — –1.13 — — 52 Finland IEA/WDI –0.76 –0.55 –0.66 10.3 9.0 -1.04 –0.99 78.4 73.3 1,178 France IEA/WDI –0.77 –0.70 –0.73 6.6 5.7 -0.74 –0.87 63.9 62.1 13,508 French Guiana UN/WDI — — — — — — — — — — French Polynesia UN/WDI — — — — — — — — — — Gabon IEA/WDI 0.49 1.54 1.02 3.6 4.4 -0.13* 1.17 85.4 88.0 –136 Gambia UN/WDI 0.65 –0.03 0.31 6.5 7.0 — 0.80 — — –8 Georgia IEA/WDI –4.73 –5.08 –4.91 17.6 6.4 -4.82 –4.20 72.3 83.9 1,552 Germany IEA/WDI –2.32 –1.20 –1.76 7.2 5.0 -1.81 –1.71 68.6 69.3 69,126 Ghana IEA/WDI –0.41 –3.74 –2.09 16.5 10.8 -3.17 –2.18 81.7 80.2 1,003 Gibraltar IEA/WDI — — — — — — — 78.1 83.8 — Greece IEA/WDI 0.02 –1.90 –0.94 5.1 4.2 — –0.73 67.6 70.5 1,431 Grenada UN/WDI 1.68 2.20 1.94 2.5 3.6 -0.29** –1.48 — — –12 Guadeloupe UN/WDI — — — — — — — — — — Guatemala IEA/WDI 0.65 0.46 0.55 6.2 6.9 -0.33 0.05 91.4 82.7 –94 Guinea UN/WDI –1.74 –4.20 –2.98 40.6 22.2 — –3.31 — — 1,645 Guinea-Bissau UN/WDI –0.68 1.37 0.34 8.6 9.2 — 1.73 — — 1 Guyana UN/WDI –1.18 –2.10 –1.64 22.7 16.3 0.49 –2.45 — — 137 Haiti IEA/WDI 2.94 1.21 2.07 6.4 9.7 — 2.77 79.1 90.6 –556 Honduras IEA/WDI –0.95 0.25 –0.35 7.7 7.2 — –1.22 98.1 82.2 106 ANNEX: energy efficiency 243 Decom- Rate of final Rate of primary Level of primary energy Final to Cumulative Data position Country energy intensity energy intensity, intensity primary energy sourcea analysis, improvement, energy ratio savings (PJ) improvement, CAGR (%) (MJ/$2005 PPP) CAGR (%) CAGR (%) 1990–2000 2000–2010 1990–2010 1990 2010 1990–2010 1990–2010 1990 2010 1990–2010 Hungary IEA/WDI –1.64 –1.67 –1.65 8.8 6.3 -1.85 –1.74 71.8 70.6 3,906 Iceland IEA/WDI 1.44 3.41 2.42 13.4 21.6 0.57 0.58 78.6 54.7 –450 India IEA/WDI –1.72 –2.98 –2.35 12.5 7.8 -4.09 –3.25 79.5 66.0 114,220 Indonesia IEA/WDI 0.40 –2.15 –0.88 11.2 9.3 -1.73 –1.24 80.9 75.3 9,891 Iran, Islamic Rep. of IEA/WDI 2.10 0.96 1.53 8.5 11.6 1.63 1.30 78.9 75.4 –22,350 Iraq IEA/WDI –10.76 4.80 –3.29 30.2 15.5 — –4.81 75.7 55.2 23,829 Ireland IEA/WDI –1.16 –1.87 –1.52 5.1 3.7 -0.93 –1.25 74.0 78.1 2,155 Israel IEA/WDI –1.60 –0.14 –0.88 5.8 4.8 — –0.57 60.7 64.6 1,963 Italy IEA/WDI –0.01 –0.45 –0.23 4.6 4.4 -0.14 –0.37 78.4 76.2 1,220 Jamaica IEA/WDI 1.42 –3.05 –0.84 8.0 6.8 -0.62 –0.97 70.3 68.5 –90 Japan IEA/WDI 0.55 –1.17 –0.31 5.6 5.3 -0.45 –0.54 68.3 65.3 –2,328 Jordan IEA/WDI –1.04 –2.16 –1.60 13.1 9.5 -2.27 –2.13 71.1 64.0 714 Kazakhstan IEA/WDI –3.51 –0.52 –2.02 26.5 17.6 -3.26* –3.63 81.2 58.3 12,434 Kenya IEA/WDI 0.66 –0.48 0.09 13.4 13.6 -0.82 –0.23 70.2 65.8 –424 Kiribati UN/WDI 1.54 3.49 2.51 2.2 3.6 — 12.22 — — –1 Korea, Dem. People’s Rep. of IEA/WDI — — — — — — — 82.3 86.6 — Korea, Republic of IEA/WDI 1.14 –1.22 –0.05 8.0 7.9 -1.36 –0.55 69.7 63.0 –5,171 Kuwait IEA/WDI 5.46 0.57 2.99 6.2 11.2 — 2.56 43.4 39.9 –5,800 Kyrgyzstan IEA/WDI –7.04 –1.97 –4.54 28.3 11.2 — –4.69 92.2 89.4 2,131 Lao People’s Dem. Rep. UN/WDI –3.20 –5.12 –4.16 13.4 5.7 -4.95 –5.83 — — 814 Latvia IEA/WDI –4.56 –1.85 –3.21 12.3 6.4 -2.87 –2.45 81.6 95.4 1,853 Lebanon IEA/WDI 2.78 –2.26 0.23 4.8 5.1 — 0.46 58.2 61.0 –598 Lesotho UN/WDI 1.28 –2.59 –0.67 12.2 10.6 — –3.58 — — 10 Liberia UN/WDI 0.42 –2.40 –1.00 73.1 59.8 — 0.97 — — –125 Libya IEA/WDI 3.10 –2.82 0.09 7.7 7.9 — 0.92 48.5 57.1 –2,712 Lithuania IEA/WDI –4.73 –4.46 –4.60 14.6 5.7 -4.75 –3.69 64.8 78.2 3,839 Luxembourg IEA/WDI –5.04 –0.28 –2.69 8.8 5.1 -1.86 –2.13 82.1 92.0 1,533 Macedonia, Former Yugoslav Rep. of IEA/WDI 1.66 –1.62 0.01 6.4 6.4 0.65 0.16 60.9 62.9 –361 244 Global tracking framework Decom- Rate of final Rate of primary Level of primary energy Final to Cumulative Data position Country energy intensity energy intensity, intensity primary energy sourcea analysis, improvement, energy ratio savings (PJ) improvement, CAGR (%) (MJ/$2005 PPP) CAGR (%) CAGR (%) 1990–2000 2000–2010 1990–2010 1990 2010 1990–2010 1990–2010 1990 2010 1990–2010 Madagascar UN/WDI 2.31 0.55 1.43 10.3 13.7 — 0.54 — — –721 Malawi UN/WDI –2.03 –2.43 –2.23 16.8 10.7 — –2.96 — — 536 Malaysia IEA/WDI 0.96 –0.18 0.39 7.5 8.1 -1.12* –0.02 64.7 59.6 –4,062 Maldives UN/WDI 8.17 4.64 6.39 2.7 9.3 — 5.53 — — –132 Mali UN/WDI –1.25 –3.41 –2.34 10.6 6.6 — –3.48 — — 445 Malta IEA/WDI –5.30 0.64 –2.38 6.0 3.7 — –1.82 38.4 43.0 262 Martinique UN/WDI — — — — — — — — — — Mauritania UN/WDI –7.19 –0.35 –3.83 20.3 9.3 -1.99* –1.77 — — 839 Mauritius UN/WDI –0.37 –0.79 –0.58 7.3 6.5 -2.40 –1.95 — — 81 Mexico IEA/WDI –1.70 0.30 –0.71 6.1 5.3 -0.58 –1.08 68.7 63.7 13,954 Moldova, Republic of IEA/WDI –3.33 –4.52 –3.92 24.4 11.0 -4.13 –3.72 67.4 70.4 893 Mongolia IEA/WDI –3.46 –3.10 –3.28 26.8 13.7 -5.21 –4.34 87.0 69.7 1,020 Montenegro IEA/WDI n.a –1.30 –1.30 5.7 5.4 — –4.18 0.0 53.8 –193 Montserrat UN/WDI — — — — — — — — — — Morocco IEA/WDI 1.56 –0.04 0.76 4.3 5.0 0.92 1.01 71.9 75.6 –1,076 Mozambique IEA/WDI –3.33 –3.88 –3.61 46.3 22.2 -3.51 –3.59 80.3 80.6 3,587 Myanmar IEA/WDI — — — — — -5.60* — 88.0 92.1 — Namibia IEA/WDI 1.08 0.40 0.74 4.3 5.0 -0.67* 0.55 98.3 94.5 –116 Nepal IEA/WDI –1.49 –1.52 –1.50 17.9 13.2 -2.49 –1.52 99.5 99.1 1,315 Netherlands IEA/WDI –2.01 –0.06 –1.04 7.0 5.7 -1.07 –0.85 74.8 77.6 10,284 Netherlands Antilles IEA/WDI — — — — — — — 42.9 48.4 — New Caledonia UN/WDI — — — — — — — — — — New Zealand IEA/WDI –0.05 –1.65 –0.85 8.3 7.0 -1.18 –1.34 77.4 70.2 1,236 Nicaragua IEA/WDI –0.71 –1.44 –1.08 11.3 9.1 -1.21 –1.27 73.8 71.0 139 Niger UN/WDI 1.57 –8.58 –3.64 16.6 7.9 0.21** –3.65 — — 394 Nigeria IEA/WDI –0.24 –3.92 –2.10 21.4 14.0 — –1.92 89.1 92.4 11,078 Norway IEA/WDI –1.46 0.69 –0.39 6.4 5.9 -1.08 –1.53 83.0 65.9 3,339 Oman IEA/WDI 2.01 4.53 3.26 6.4 12.3 — 2.53 44.5 38.6 –2,035 ANNEX: energy efficiency 245 Decom- Rate of final Rate of primary Level of primary energy Final to Cumulative Data position Country energy intensity energy intensity, intensity primary energy sourcea analysis, improvement, energy ratio savings (PJ) improvement, CAGR (%) (MJ/$2005 PPP) CAGR (%) CAGR (%) 1990–2000 2000–2010 1990–2010 1990 2010 1990–2010 1990–2010 1990 2010 1990–2010 Pakistan IEA/WDI 0.11 –1.62 –0.76 9.9 8.5 -1.09 –0.90 84.8 82.6 2,196 Palau UN/WDI 2.14 4.98 3.55 5.9 11.8 — 4.58 — — –16 Panama IEA/WDI 0.54 –2.31 –0.90 4.3 3.6 -2.52** –1.05 82.5 80.0 88 Papua New Guinea UN/WDI –2.17 –2.66 –2.42 11.4 7.0 -2.01 –4.02 — — 585 Paraguay IEA/WDI 0.49 –1.72 –0.62 7.6 6.7 — –0.91 95.3 89.9 0 Peru IEA/WDI –1.61 –0.89 –1.25 4.2 3.3 -1.76 –1.92 87.9 76.8 2,749 Philippines IEA/WDI 0.50 –4.40 –1.98 7.6 5.1 -2.98 –2.77 69.2 58.8 3,660 Poland IEA/WDI –5.04 –2.49 –3.77 13.8 6.4 -3.17 –3.09 59.6 68.7 46,298 Portugal IEA/WDI 0.96 –1.10 –0.07 4.3 4.3 0.57 –0.02 79.7 80.5 –1,178 Puerto Rico UN/WDI — — — — — — — — — — Qatar IEA/WDI 3.79 –0.99 1.37 7.9 10.3 — 1.25 54.1 52.8 –3,106 Reunion UN/WDI — — — — — — — — — — Romania IEA/WDI –3.63 –4.46 –4.05 14.3 6.3 -4.04 –4.18 69.3 67.5 17,593 Russian Federation IEA/WDI 0.46 –3.39 –1.49 19.7 14.6 -2.12 –2.04 71.1 63.5 34,769 Rwanda UN/WDI 4.50 –6.04 –0.91 10.3 8.6 — –1.18 — — –364 Saint Kitts and Nevis UN/WDI –1.66 5.82 2.01 3.5 5.1 — –1.34 — — –9 Saint Lucia UN/WDI 4.31 1.14 2.71 2.3 3.9 — –3.61 — — –29 Saint Pierre and Miquelon UN/WDI — — — — — — — — — — Saint Vincent and the Grenadines UN/WDI 3.09 0.40 1.74 2.0 2.9 — –2.84 — — –12 Samoa UN/WDI –0.85 –1.70 –1.27 5.7 4.4 — 15.76 — — 9 Sao Tome and Principe UN/WDI –9.71 –1.96 –5.92 55.2 16.3 — –4.78 — — 120 Saudi Arabia IEA/WDI 2.63 1.90 2.27 8.0 12.6 1.93 2.45 60.1 62.2 –27,204 Senegal IEA/WDI 0.48 –0.54 –0.03 6.6 6.6 0.05 0.16 64.1 66.6 –9 Serbia IEA/WDI 2.17 –1.98 0.07 9.2 9.3 -0.15 –0.03 62.7 61.4 –2,344 Seychelles UN/WDI 12.83 1.44 6.99 2.3 9.0 — 10.06 — — –139 Sierra Leone UN/WDI 6.72 –5.61 0.37 24.8 26.7 — 0.03 — — –1,071 Singapore IEA/WDI –2.02 0.13 –0.95 6.3 5.2 -1.49 1.61 43.5 72.4 1,790 Slovakia IEA/WDI –2.01 –4.51 –3.27 13.3 6.8 -3.72 –3.95 73.9 64.1 5,047 246 Global tracking framework Decom- Rate of final Rate of primary Level of primary energy Final to Cumulative Data position Country energy intensity energy intensity, intensity primary energy sourcea analysis, improvement, energy ratio savings (PJ) improvement, CAGR (%) (MJ/$2005 PPP) CAGR (%) CAGR (%) 1990–2000 2000–2010 1990–2010 1990 2010 1990–2010 1990–2010 1990 2010 1990–2010 Slovenia IEA/WDI –0.62 –1.48 –1.05 7.3 5.9 -2.05* –0.57 64.7 71.3 365 Solomon Islands UN/WDI –1.82 –2.65 –2.24 4.7 3.0 — –3.46 — — 24 Somalia UN/WDI — — — — — — — — — — South Africa IEA/WDI 0.03 –1.19 –0.58 13.6 12.1 -1.43 –1.69 56.1 44.9 229 Spain IEA/WDI 0.27 –1.57 –0.65 4.9 4.3 0.01 –0.23 67.3 73.3 1,031 Sri Lanka IEA/WDI –0.96 –3.28 –2.13 6.7 4.3 -3.02* –2.43 96.1 90.4 1,529 Sudan IEA/WDI –3.28 –4.12 –3.70 16.3 7.7 -2.26 –3.00 57.1 66.1 5,749 Suriname UN/WDI 0.44 –2.74 –1.17 13.3 10.5 4.54 0.64 — — 14 Swaziland UN/WDI 7.43 –1.09 3.08 8.7 15.9 -4.12 1.75 — — –442 Sweden IEA/WDI –1.97 –1.33 –1.65 9.4 6.7 -1.78 –1.61 68.0 68.7 6,984 Switzerland IEA/WDI –0.78 –1.18 –0.98 4.5 3.7 -0.71 –0.75 76.7 80.3 1,413 Syrian Arab Republic IEA/WDI –0.86 –1.57 –1.21 12.0 9.4 -1.71 –1.94 72.7 62.7 2,033 Tajikistan IEA/WDI 0.61 –7.04 –3.29 14.2 7.2 -3.14 –3.35 88.2 87.1 250 Thailand IEA/WDI 1.09 0.62 0.85 7.8 9.3 0.08 1.08 68.8 72.0 –6,918 Timor-Leste UN/WDI n.a –6.29 –6.29 7.9 4.7 — –5.08 — — –61 Togo IEA/WDI 3.02 0.33 1.66 15.0 20.8 — 1.26 67.0 61.9 –414 Tonga UN/WDI 2.35 2.55 2.45 3.6 5.9 — 1.32 — — –11 Trinidad and Tobago IEA/WDI 2.70 1.46 2.08 19.1 28.8 — 3.00 62.0 74.2 –2,185 Tunisia IEA/WDI –0.70 –1.57 –1.14 5.6 4.5 -1.41 –1.11 73.6 74.1 744 Turkey IEA/WDI 0.13 –0.60 –0.23 5.0 4.8 -0.68 –0.38 76.0 73.8 2,360 Turkmenistan IEA/WDI 0.64 –8.35 –3.96 53.5 23.8 -4.52 –4.93 70.2 57.3 5,128 Turks and Caicos Islands UN/WDI — — — — — — — — — — Uganda UN/WDI –3.64 –4.11 –3.87 40.1 18.2 -5.55** –4.00 — — 6,622 Ukraine IEA/WDI 2.04 –4.34 –1.20 25.2 19.8 -0.94 –1.47 59.6 56.5 –3,410 United Arab Emirates IEA/WDI 0.53 1.89 1.21 6.4 8.2 — 0.77 79.3 72.7 –3,685 United Kingdom of Great Britain IEA/WDI –2.06 –2.59 –2.32 6.7 4.2 -1.99 –2.24 66.9 68.1 47,052 and Northern Ireland United Republic of Tanzania IEA/WDI 0.19 –2.64 –1.24 19.2 14.9 — –1.40 89.8 86.8 837 ANNEX: energy efficiency 247 Decom- Rate of final Rate of primary Level of primary energy Final to Cumulative Data position Country energy intensity energy intensity, intensity primary energy sourcea analysis, improvement, energy ratio savings (PJ) improvement, CAGR (%) (MJ/$2005 PPP) CAGR (%) CAGR (%) 1990–2000 2000–2010 1990–2010 1990 2010 1990–2010 1990–2010 1990 2010 1990–2010 United States of America IEA/WDI –1.65 –1.78 –1.71 10.1 7.1 -1.67 –1.70 67.5 67.7 368,527 Uruguay IEA/WDI –0.17 0.07 –0.05 4.2 4.1 0.21 –0.01 85.8 86.6 78 Uzbekistan IEA/WDI 1.11 –7.85 –3.47 47.3 23.3 -3.91 –3.76 75.4 71.0 3,859 Vanuatu UN/WDI 2.27 –0.51 0.87 2.3 2.7 — 7.96 — — –2 Venezuela, Bolivarian Rep. of IEA/WDI 0.53 –0.04 0.25 9.7 10.2 0.78* –0.12 63.2 58.7 –799 Viet Nam IEA/WDI –2.52 0.22 –1.16 12.5 9.9 -2.39 –1.61 89.9 81.9 7,495 Western Sahara UN/WDI — — — — — — — — — — Yemen IEA/WDI 0.84 –0.05 0.39 4.9 5.3 0.47* 0.41 72.1 72.2 –470 Zambia IEA/WDI 0.79 –2.80 –1.02 23.0 18.8 -1.67 –1.18 79.5 76.9 5 Zimbabwe IEA/WDI — — — — — — — 85.7 87.8 — Decom- Rate of final Rate of primary energy Level of primary energy Final to Cumulative Data position Aggregated by region intensity improvement, energy intensity, intensity primary energy source analysis, improvement, energy ratio savings (PJ) CAGR (%) (MJ/$2005 PPP) CAGR (%) CAGR (%) 1990–2000 2000–2010 1990–2010 1990 2010 1990–2010 1990–2010 1990 2010 1990–2010 Northern America IEA/WDI –1.59 –1.78 –1.68 10.2 7.3 –1.62 –1.66 68.4 68.7 391,975 Europe IEA/WDI –1.41 –1.10 –1.25 6.5 5.0 –1.12 –1.21 69.6 70.2 223,096 Eastern Europe IEA/WDI –1.26 –3.34 –2.30 18.7 11.8 –2.65 –2.65 68.2 63.4 140,558 Caucasian and Central Asia IEA/WDI –0.84 –5.59 –3.24 30.3 15.7 –3.55 –4.15 76.3 63.2 39,526 Western Asia IEA/WDI 0.55 1.00 0.77 7.1 8.3 0.41 0.42 67.1 62.6 –10,469 Eastern Asia IEA/WDI –1.84 –0.35 –1.10 11.8 9.5 –2.11 –1.89 73.2 62.3 1,314,102 South Eastern Asia IEA/WDI 0.17 –1.16 –0.50 9.1 8.2 –1.48 –0.66 74.2 71.8 9,718 Southern Asia IEA/WDI –0.86 –2.11 –1.49 11.1 8.2 –2.71 –2.16 80.3 70.1 101,857 Oceania IEA/WDI –0.95 –1.60 –1.27 8.8 6.8 –1.33 –1.73 68.5 62.4 15,038 Latin America and Caribbean IEA/WDI –0.52 –0.38 –0.45 6.1 5.6 –0.44 –0.56 73.6 72.1 27,714 Northern Africa IEA/WDI –0.18 0.07 –0.06 6.4 6.4 –0.46 0.20 64.0 67.4 –2,093 Sub-Saharan Africa IEA/WDI 0.03 –2.19 –1.08 15.5 12.4 –1.36 –1.18 76.8 75.4 24,624 World IEA/WDI –1.61 –0.99 –1.30 10.0 7.7 –1.63 –1.53 71.7 68.0 2,275,646 248 Global tracking framework Decom- Rate of final Rate of primary energy Level of primary energy Final to Cumulative Aggregated by Data position intensity improvement, energy intensity, intensity primary energy income level source analysis, improvement, energy ratio savings (PJ) CAGR (%) (MJ/$2005 PPP) CAGR (%) CAGR (%) 1990–2000 2000–2010 1990–2010 1990 2010 1990–2010 1990–2010 1990 2010 1990–2010 High income IEA/WDI –1.03 –1.25 –1.14 7.9 6.3 –0.61 –1.18 68.4 67.8 608,778 Upper middle income IEA/WDI –2.59 –1.13 –1.86 14.1 9.7 –2.62 –2.47 72.5 64.1 1,462,534 Lower middle income IEA/WDI –1.92 –2.70 –2.31 14.0 8.8 –3.15 –2.62 75.0 70.3 191,629 Low income IEA/WDI –0.79 –1.97 –1.38 16.2 12.2 –2.50 –1.40 89.0 88.6 12,706 Source: IEA World Energy Statistics and Balance (2012); UN Energy Statistics (2012); World Development Indicators (2012). a. The IEA World Energy Statistics and Balances provides country level data for 138 countries that account for more than 99 percent of global energy consumption. The rest of the countries are lumped together in three regional groups and reported in an aggregated manner. To increase the country-level coverage, UN Energy Statistics are used for the 68 countries not reported separately by the IEA. However, a number of differences between the two data sources —namely, the application of different methodologies to estimate the use of primary solid biofuels (biomass) and the fact that the UN data were available only through 2009, at the latest—called for an adjustment of the UN data to allow for a fair comparison of energy intensity levels among countries. For some countries for which energy data were available but GDP data were not, no energy intensity figure is shown. (Energy intensity is a derivative of both energy consumption and GDP.) First available data were used for some countries for which 1990 were not available: Cambodia (1995), Eritrea (1992), Montenegro (2005), and Timor-Leste (2002). GDP data were estimated to fill gaps in time series for the following countries: Afghanistan, Barbados, Bosnia and Herzegovina, Djibouti, Estonia, Haiti, Iraq, Iran (Islamic Republic of), Ireland, Kuwait, Libya, Maldives, Palau, Qatar, and Sao Tome and Principe. * Country has less than 20 years of historical data available. Caution should be used when comparing CAGRs of decomposition analysis and energy intensity for country. ** Country has less than 10 years of historical data available. Caution should be used when comparing CAGRs of decomposition analysis and energy intensity for country. ANNEX: energy efficiency 249 DATA ANNEX: renewable ENERGY Total final Data Share (%) of RE share (%) in energy Country Share (%) in TFEC in 2010 source RE in TFEC 2010 of: consumption (PJ) in 2010 Tradi- Modern Liquid Geo- Electricity Electricity 1990 2000 2010 tional Hydro Wind Solar Other biomass biofuels thermal capacity generation biomass Afghanistan UN 42.4 56.5 19.3 12.2 — 7.0 — — — — — 76.5 87.2 72 Albania IEA 24.9 41.0 37.9 9.7 1.4 26.4 — — 0.4 — — 90.1 100.0 77 Algeria IEA 0.2 0.6 0.3 0.3 0.0 0.0 — — — — — 2.5 0.4 1,044 Angola IEA 72.3 75.5 54.9 51.3 1.3 2.4 — — — — — 43.1 67.3 451 Antigua and Barbuda UN — — — — — — — — — — — — — 4 Argentina IEA 8.9 11.0 9.0 0.6 2.0 5.3 1.1 0.0 — — — 27.8 28.6 2,052 Armenia IEA 1.9 6.2 9.0 — 0.1 8.9 — 0.0 — — — 33.5 39.5 74 Aruba UN 0.8 0.1 0.1 0.1 — — — — — — — 11.3 — 6 Australia IEA 8.0 8.4 7.3 — 4.6 1.3 0.4 0.5 0.4 — 0.1 18.7 8.9 2,940 Austria IEA 25.2 26.5 30.6 — 15.1 11.5 2.0 0.6 0.7 0.1 0.6 72.9 66.4 1,083 Azerbaijan IEA 0.3 1.6 3.1 — — 3.1 — 0.0 — — — 15.5 18.4 263 Bahamas UN — — 0.9 — 0.9 — — — — — — — — 29 Bahrain IEA — — — — — — — — — — — 0.0 — 221 Bangladesh IEA 72.0 59.5 42.0 41.4 0.0 0.6 — — — — — 4.0 3.9 883 Barbados UN 18.9 13.6 9.8 0.7 9.1 — — — — — — — — 13 Belarus IEA 0.8 4.9 7.0 2.9 3.9 0.0 0.2 0.0 — — 0.0 0.3 0.4 719 Belgium IEA 1.3 1.5 5.3 — 3.2 0.1 1.2 0.3 0.2 0.0 0.4 16.9 6.9 1,425 Belize UN 37.0 24.1 35.6 — 20.1 15.5 — — — — — 48.9 92.3 9 Benin IEA 93.7 70.3 51.5 42.9 8.7 — — — — — — 1.6 0.7 134 Bermuda UN — — — — — — — — — — — — — 9 Bhutan UN 96.5 95.2 91.7 81.3 0.4 10.0 — — — — — 98.9 100.0 54 Bolivia, Plurinational State of IEA 37.4 29.1 31.7 13.1 15.8 2.9 — — 0.0 — — 30.1 34.0 240 Bosnia and Herzegovina IEA 7.3 19.4 19.9 5.9 0.1 13.9 — — — — — 49.2 46.9 126 Botswana IEA 47.1 35.7 26.4 26.4 0.0 — — — 0.0 — — — — 77 Brazil IEA 49.8 42.8 47.0 4.0 20.3 15.2 7.3 0.1 0.2 — — 78.7 84.8 8,108 British Virgin Islands UN 100.0 1.6 1.1 1.1 — — — — — — — — — 1 Brunei Darussalam IEA 0.7 — — — — — — — — — — — — 70 Bulgaria IEA 1.9 8.3 14.4 8.3 2.0 3.0 0.2 0.4 0.1 0.4 0.0 26.7 12.6 360 250 Global tracking framework Total final Data Share (%) of RE share (%) in energy Country Share (%) in TFEC in 2010 source RE in TFEC 2010 of: consumption (PJ) in 2010 Tradi- Modern Liquid Geo- Electricity Electricity 1990 2000 2010 tional Hydro Wind Solar Other biomass biofuels thermal capacity generation biomass Burkina Faso UN 92.4 86.5 85.3 84.1 0.8 0.4 — — — — — 12.7 18.9 125 Burundi UN 82.6 93.2 96.8 95.7 0.4 0.7 — — — — — 98.1 98.4 84 Cambodia IEA 82.5 81.1 73.3 57.6 15.6 0.1 — — 0.0 — — 5.2 4.9 178 Cameroon IEA 81.6 84.5 78.6 66.7 6.7 5.2 — — — — — 72.2 73.2 243 Canada IEA 20.6 20.5 19.9 — 5.3 13.5 0.6 0.4 0.0 — 0.1 58.9 60.9 7,266 Cape Verde UN — 1.7 1.5 1.0 — — — 0.5 — — — 3.1 1.7 3 Cayman Islands UN — — — — — — — — — — — — — 4 Central African Republic UN 93.9 86.0 81.0 47.1 31.2 2.6 — — — — — 56.8 99.9 17 Chad UN 95.1 97.9 92.3 91.1 1.2 — — — — — — — — 82 Chile IEA 34.0 31.4 27.0 — 19.4 7.4 — 0.1 — — — 38.0 40.2 954 China IEA 32.3 27.7 18.8 13.5 0.0 3.6 0.1 0.2 0.6 0.3 0.5 25.1 17.5 59,740 China, Hong Kong SAR IEA 1.1 0.6 0.7 0.7 0.0 — — 0.0 — — — 0.0 0.0 338 China, Macao SAR UN 0.7 0.2 0.2 — 0.2 — — — — — — — — 17 Colombia IEA 38.3 28.0 28.6 8.2 6.6 13.7 0.1 0.0 — — — 67.1 72.1 894 Comoros UN 1.0 1.0 1.3 — — 1.3 — — — — — 16.7 11.6 1 Congo IEA 66.7 72.7 50.6 47.5 0.0 3.1 — — — — — 80.4 76.9 45 Congo, Dem. Rep. of the IEA 92.0 97.2 96.2 74.1 19.7 2.4 — — — — — 98.6 99.6 950 Cook Islands UN — — — — — — — — — — — 1.1 — 0 Costa Rica IEA 55.7 32.7 41.9 9.0 13.1 16.3 — 0.8 — 2.6 — 67.6 93.3 144 Cote d'Ivoire IEA 80.2 64.7 75.4 65.7 7.8 1.9 — — — — — 49.4 28.8 218 Croatia IEA 13.5 17.5 19.4 0.1 5.9 12.9 0.0 0.2 0.1 0.1 0.1 47.0 60.7 263 Cuba IEA 44.3 35.7 16.3 0.8 11.5 0.1 3.9 — 0.0 — — 1.3 3.2 252 Cyprus IEA 0.5 3.1 6.4 0.5 0.9 — 0.9 0.1 3.7 0.0 0.2 5.8 1.3 69 Czech Republic IEA 2.7 4.9 9.5 — 7.0 0.7 1.0 0.1 0.2 — 0.6 10.4 6.9 1,019 Denmark IEA 7.3 10.9 21.4 — 14.4 0.0 0.2 3.8 0.1 0.0 2.9 37.0 32.1 615 Djibouti UN — — — — — — — — — — — — — 5 Dominica UN 23.6 11.3 9.1 4.2 — 4.9 — — — — — 80.4 25.0 1 Dominican Republic IEA 34.3 22.3 25.9 16.1 7.5 2.4 — — — — — 9.4 11.4 237 ANNEX: renewable energy 251 Total final Data Share (%) of RE share (%) in energy Country Share (%) in TFEC in 2010 source RE in TFEC 2010 of: consumption (PJ) in 2010 Tradi- Modern Liquid Geo- Electricity Electricity 1990 2000 2010 tional Hydro Wind Solar Other biomass biofuels thermal capacity generation biomass Ecuador IEA 23.2 19.6 12.4 4.0 1.8 6.6 — 0.0 — — — 44.7 51.6 372 Egypt IEA 8.6 8.2 6.1 1.8 1.9 2.2 — 0.3 — — — 12.4 9.9 1,792 El Salvador IEA 67.1 50.9 34.8 16.0 8.7 5.9 — — — 4.3 — 47.4 65.1 107 Equatorial Guinea UN 82.0 53.2 15.4 15.2 — 0.2 — — — — — 2.6 7.0 10 Eritrea IEA 88.3 71.2 77.2 73.8 3.3 — — — 0.0 — — 1.3 0.6 21 Estonia IEA 3.3 19.9 25.1 — 24.5 0.0 — 0.4 — — 0.1 6.6 8.1 120 Ethiopia IEA 95.6 94.3 94.5 92.7 0.7 1.0 — — — 0.0 — 90.1 99.4 1,310 Falkland Islands (Malvinas) UN — — — — — — — — — — — 10.0 — 1 Fiji UN 16.4 13.0 15.5 2.6 — 12.8 — — — — — 51.0 57.4 12 Finland IEA 24.6 31.7 33.5 — 27.6 4.6 0.6 0.1 0.0 — 0.6 31.5 30.1 1,051 France IEA 10.4 9.3 12.3 — 6.7 2.8 1.6 0.4 0.1 0.1 0.6 21.5 13.8 6,314 French Guiana UN 12.5 8.0 34.4 7.9 2.1 24.3 — — — — — 90.1 90.1 9 French Polynesia UN 100.0 9.2 8.6 0.5 — 8.1 — — — — — 25.3 28.7 9 Gabon IEA 78.3 74.5 63.0 48.4 11.8 2.8 — — — — — 41.0 44.2 78 Gambia UN 58.9 50.3 41.0 41.0 — — — — — — — — — 10 Georgia IEA 12.8 47.3 39.9 12.6 1.9 23.5 — — — 1.9 0.0 62.8 92.5 103 Germany IEA 2.1 3.8 10.8 — 4.6 0.7 1.8 1.4 0.6 0.2 1.4 36.3 16.7 8,504 Ghana IEA 80.6 74.7 66.5 44.1 15.7 6.7 — — — — — 59.4 83.6 311 Gibraltar IEA — — — — — — — — — — — — — 5 Greece IEA 7.8 7.5 11.1 — 4.7 3.2 0.7 1.2 1.1 0.1 0.1 26.7 18.3 769 Grenada UN 6.4 7.0 8.8 8.1 0.7 — — — — — — 1.4 — 3 Guadeloupe UN 7.8 0.6 5.5 0.5 — 1.0 — 3.7 0.3 — — 11.0 15.0 18 Guatemala IEA 75.0 62.7 67.0 59.7 4.1 3.0 — — — 0.2 — 43.5 66.9 354 Guinea UN 92.6 89.6 88.9 87.3 0.5 1.1 — — — — — 31.6 52.4 114 Guinea-Bissau UN 70.8 50.1 37.4 7.1 30.3 — — — — — — — — 6 Guyana UN 28.1 41.5 46.7 26.6 20.1 — — — — — — 4.0 — 31 Haiti IEA 81.1 76.0 70.5 60.2 10.0 0.3 — — — — — 20.7 30.2 87 Honduras IEA 70.1 55.1 49.8 41.7 3.0 5.1 — — — — — 36.3 46.1 157 252 Global tracking framework Total final Data Share (%) of RE share (%) in energy Country Share (%) in TFEC in 2010 source RE in TFEC 2010 of: consumption (PJ) in 2010 Tradi- Modern Liquid Geo- Electricity Electricity 1990 2000 2010 tional Hydro Wind Solar Other biomass biofuels thermal capacity generation biomass Hungary IEA 3.9 5.2 9.1 — 6.7 0.1 1.1 0.3 0.0 0.6 0.3 9.8 8.1 674 Iceland IEA 62.2 66.1 76.7 — — 38.5 — — — 38.2 0.0 95.3 100.0 108 India IEA 57.5 52.6 42.4 31.7 8.5 1.7 0.0 0.3 0.1 — — 27.0 14.2 17,569 Indonesia IEA 58.7 44.7 37.4 31.6 4.4 0.9 0.0 — — 0.5 — 17.8 16.0 6,177 Iran, Islamic Republic of IEA 1.3 0.4 0.7 0.0 0.2 0.5 — 0.0 — — 0.0 13.8 4.2 5,983 Iraq IEA 1.6 0.3 1.6 — 0.1 1.5 — — — — — 24.9 9.5 855 Ireland IEA 2.3 2.0 5.2 — 1.7 0.4 0.8 2.0 0.1 — 0.3 20.2 13.1 460 Israel IEA 5.8 6.0 8.5 — 0.1 0.0 0.0 0.0 8.4 — 0.0 1.9 0.2 562 Italy IEA 3.8 5.1 10.0 — 3.2 3.7 1.5 0.7 0.2 0.5 0.3 24.7 25.8 5,033 Jamaica IEA 7.6 11.5 12.1 8.4 3.0 0.5 — 0.2 — — — 5.2 6.4 86 Japan IEA 4.4 3.9 4.2 — 1.3 2.2 — 0.1 0.2 0.1 0.1 10.6 10.1 11,915 Jordan IEA 2.8 2.1 3.0 0.1 0.0 0.1 — 0.0 2.8 — 0.0 0.6 0.5 188 Kazakhstan IEA 1.4 2.5 1.2 0.1 0.0 1.1 — — — — — 11.8 9.7 1,816 Kenya IEA 77.7 81.8 77.1 74.2 0.2 1.9 — 0.0 — 0.8 — 58.1 69.5 529 Kiribati UN 39.5 30.9 1.1 1.1 — — — — — — — — — 1 Korea, Dem. People’s Rep. of IEA 7.7 9.8 12.0 — 6.6 5.4 — — — — — 52.6 61.9 672 Korea, Republic of IEA 1.6 0.7 1.3 — 0.2 0.2 0.3 0.1 0.1 0.0 0.4 3.4 1.2 4,982 Kuwait IEA 0.2 — — — — — — — — — — — — 513 Kyrgyzstan IEA 7.9 37.3 22.5 — 0.1 22.3 — — — — — 79.9 91.0 106 Lao People’s Dem. Rep. UN 96.7 91.3 90.1 80.6 — 9.0 — — 0.5 — — 97.4 92.3 66 Latvia IEA 17.6 35.8 35.3 17.7 9.7 6.9 0.6 0.1 — — 0.2 72.8 54.9 173 Lebanon IEA 11.5 5.0 5.0 2.6 0.2 1.8 — — 0.4 — — 12.1 5.3 161 Lesotho UN — 100.0 100.0 — — 100.0 — — — — — 100.0 100.0 1 Liberia UN 95.4 90.5 92.5 92.5 — — — — — — — — — 74 Libya IEA 3.1 2.1 2.1 2.1 0.0 — — — — — — — — 347 Lithuania IEA 3.1 17.6 22.6 12.7 6.2 1.7 1.0 0.7 — 0.0 0.2 8.2 19.2 189 Luxembourg IEA 1.7 6.8 3.7 — 1.2 0.5 1.1 0.2 0.1 — 0.5 7.8 8.3 162 Macedonia, Former Yugoslav Rep. of IEA 2.4 19.4 23.0 10.1 1.0 11.0 0.3 — — 0.6 — 35.9 33.5 75 ANNEX: renewable energy 253 Total final Data Share (%) of RE share (%) in energy Country Share (%) in TFEC in 2010 source RE in TFEC 2010 of: consumption (PJ) in 2010 Tradi- Modern Liquid Geo- Electricity Electricity 1990 2000 2010 tional Hydro Wind Solar Other biomass biofuels thermal capacity generation biomass Madagascar UN 86.4 78.5 82.8 53.5 27.6 1.8 — — 0.0 — — 34.4 58.2 114 Malawi UN 86.1 76.9 81.3 38.5 36.4 6.4 — — — — — 99.7 85.5 59 Malaysia IEA 14.0 8.6 6.2 4.6 0.3 1.3 0.0 — — — 0.0 8.3 6.2 1,557 Maldives UN — — — — — — — — — — — 0.1 — 2 Mali UN 91.6 88.9 88.3 85.4 1.4 1.5 — — — — — 51.6 55.2 62 Malta IEA — — 0.3 — — — — — 0.3 — — 0.3 — 15 Martinique UN 2.3 1.6 1.6 0.2 0.8 — — 0.0 0.6 — — 0.3 2.8 23 Mauritania UN 40.9 42.6 35.1 35.1 — — — — — — — 36.9 — 33 Mauritius UN 51.9 14.6 6.9 0.5 5.4 1.1 — 0.0 — — — 24.3 4.8 33 Mexico IEA 14.3 12.5 10.0 — 7.0 2.3 — 0.1 0.1 0.4 0.0 21.6 17.6 4,408 Moldova, Republic of IEA 0.8 4.6 4.3 — 4.0 0.3 — — — — — 11.6 2.2 75 Mongolia IEA 1.8 4.9 3.7 2.6 1.1 — — — — — — 0.1 — 96 Montenegro IEA n.a. n.a. 48.9 5.6 0.4 42.9 — — — — — 75.8 66.0 18 Montserrat UN — — — — — — — — — — — — — 1 Morocco IEA 8.5 6.7 7.2 3.4 0.6 2.7 — 0.5 — — — 23.7 18.5 500 Mozambique IEA 93.1 92.5 89.6 71.2 7.8 10.7 — — — — — 89.7 99.9 344 Myanmar IEA 90.9 80.2 84.9 79.5 2.6 2.8 — — — — — 46.7 67.7 535 Namibia IEA 38.9 38.2 30.2 13.8 0.0 16.4 — — 0.0 — — 63.4 84.9 63 Nepal IEA 95.1 88.3 88.3 84.3 1.0 2.3 — — — — 0.6 92.1 99.9 424 Netherlands IEA 1.2 1.5 3.6 — 1.5 0.0 0.5 0.6 0.1 0.0 0.8 14.5 9.5 2,064 Netherlands Antilles IEA — — — — — — — — — — — 9.4 — 29 New Caledonia UN 40.2 15.9 8.0 0.2 0.0 7.0 — 0.7 — — — 23.2 23.1 19 New Zealand IEA 29.2 28.9 31.5 — 8.8 15.7 0.0 1.0 0.1 5.6 0.2 68.3 73.4 497 Nicaragua IEA 70.4 62.4 53.8 44.4 6.9 1.3 — 0.4 — 0.8 — 31.6 37.0 92 Niger UN 86.8 93.9 73.7 71.0 2.8 — — — 0.0 — — — 0.0 39 Nigeria IEA 88.4 86.9 88.8 79.6 8.8 0.4 — — — — — 32.9 24.4 4,373 Norway IEA 59.3 60.3 56.9 — 6.2 49.2 0.6 0.4 — — 0.5 93.6 95.8 796 Oman IEA — — — — — — — — — — — — — 265 254 Global tracking framework Total final Data Share (%) of RE share (%) in energy Country Share (%) in TFEC in 2010 source RE in TFEC 2010 of: consumption (PJ) in 2010 Tradi- Modern Liquid Geo- Electricity Electricity 1990 2000 2010 tional Hydro Wind Solar Other biomass biofuels thermal capacity generation biomass Pakistan IEA 57.5 51.1 46.0 37.9 4.7 3.4 — — — — — 29.6 33.7 2,777 Palau UN — — 6.8 — — 6.8 — — — — — n.a. 11.8 1 Panama IEA 43.7 34.4 24.1 11.3 2.9 10.0 — — — — — 47.4 57.0 126 Papua New Guinea UN 70.4 66.4 66.7 56.9 6.6 3.3 — — — — — 38.9 27.3 89 Paraguay IEA 78.5 70.4 64.1 23.1 25.9 13.8 1.2 — — — — 99.9 100.0 179 Peru IEA 39.4 32.2 30.2 17.7 1.5 10.4 0.6 0.0 0.0 — — 39.9 57.9 610 Philippines IEA 51.0 34.9 28.8 15.1 7.5 2.3 0.9 0.0 0.0 3.0 — 33.1 26.3 988 Poland IEA 2.5 6.9 9.5 — 7.5 0.3 1.4 0.2 0.0 0.0 0.1 6.5 6.9 2,718 Portugal IEA 27.1 20.0 27.9 — 13.5 7.5 1.9 4.3 0.4 0.2 0.2 45.5 52.8 722 Puerto Rico UN 1.8 0.7 0.7 — — 0.7 — — — — — 2.8 0.7 67 Qatar IEA — — — — — — — — — — — — — 397 Reunion UN 38.9 16.5 17.6 1.1 10.8 5.1 — 0.7 — — — 38.7 40.0 41 Romania IEA 3.4 16.5 24.0 16.2 1.9 5.3 0.5 0.1 0.0 0.1 0.0 30.9 33.1 914 Russian Federation IEA 3.8 3.5 3.3 0.3 0.4 2.6 — 0.0 — 0.0 — 20.5 16.1 16,133 Rwanda UN 84.4 89.4 87.9 86.8 0.5 0.6 — — 0.0 — — 47.6 40.0 51 Saint Kitts and Nevis UN 67.4 23.3 — — — — — — — — — — — 2 Saint Lucia UN — — — — — — — — — — — — — 3 Saint Pierre and Miquelon UN — — 1.7 — — — — 1.7 — — — 2.3 3.5 0 Saint Vincent and the Grenadines UN 18.0 10.6 7.9 3.1 — 4.8 — — — — — 14.9 17.1 2 Samoa UN 100.0 49.6 44.5 32.5 3.1 8.9 — — — — — — 45.1 2 Sao Tome and Principe UN 62.2 35.7 35.4 33.5 — 1.9 — — — — — 42.9 35.7 2 Saudi Arabia IEA 0.0 0.0 0.0 0.0 0.0 — — — — — — — — 3,005 Senegal IEA 55.6 47.7 42.5 41.5 0.2 0.8 — — 0.0 — — 0.3 10.4 91 Serbia IEA 15.5 23.5 20.3 11.0 0.7 8.6 — — — 0.1 — 26.6 31.8 367 Seychelles UN — — — — — — — — — — — — — 8 Sierra Leone UN 95.6 90.6 71.2 52.2 18.9 0.1 — — — — — 52.9 31.8 58 Singapore IEA 0.2 0.3 0.4 — — — — — — — 0.4 0.2 1.3 532 Slovakia IEA 2.2 3.7 10.9 — 5.2 3.8 1.6 0.0 0.0 0.0 0.2 23.0 21.6 433 ANNEX: renewable energy 255 Total final Data Share (%) of RE share (%) in energy Country Share (%) in TFEC in 2010 source RE in TFEC 2010 of: consumption (PJ) in 2010 Tradi- Modern Liquid Geo- Electricity Electricity 1990 2000 2010 tional Hydro Wind Solar Other biomass biofuels thermal capacity generation biomass Slovenia IEA 12.4 15.9 18.8 — 11.2 5.8 0.9 — 0.1 0.5 0.3 35.5 29.2 207 Solomon Islands UN 68.4 87.0 75.3 75.3 — — — — — — — — — 4 Somalia UN 100.0 96.3 94.8 67.0 27.8 — — — — — — — — 89 South Africa IEA 16.6 18.2 18.7 15.1 3.2 0.3 — 0.0 0.1 — — 2.0 1.0 2,405 Spain IEA 10.5 8.0 14.8 — 4.7 3.6 1.7 3.8 0.8 0.0 0.2 38.8 32.5 3,628 Sri Lanka IEA 78.1 64.2 62.0 36.9 20.4 4.7 — 0.0 0.0 — — 52.0 52.5 370 Sudan IEA 73.3 81.6 66.6 43.3 20.8 2.5 — — — — — 69.3 49.0 437 Suriname UN 36.0 17.1 18.3 6.4 0.6 11.2 — — — — — 46.1 53.9 25 Swaziland UN 84.3 46.8 35.7 24.6 6.4 4.7 — — — — — 40.3 47.3 35 Sweden IEA 34.1 40.9 47.4 — 27.3 15.4 1.7 0.8 0.0 — 2.1 62.1 55.3 1,368 Switzerland IEA 16.9 18.5 21.2 — 4.4 13.7 0.0 0.0 0.2 1.3 1.6 68.9 56.7 858 Syrian Arab Republic IEA 2.4 1.9 1.4 — 0.0 1.3 — — — — — 10.8 5.6 505 Tajikistan IEA 29.6 62.4 57.3 — — 57.3 — — — — — 91.2 96.6 84 Tanzania, United Republic of IEA 94.8 94.3 90.7 70.6 19.0 1.1 — — — — — 66.8 58.0 729 Thailand IEA 33.6 22.0 22.8 10.2 10.9 0.7 1.0 — 0.0 0.0 0.0 8.9 5.6 2,780 Timor-Leste UN n.a. n.a. 43.1 43.1 — — — — — — — — — 3 Togo IEA 78.7 77.1 76.1 64.3 9.2 2.6 — — — — — 78.8 76.2 69 Tonga UN — 0.4 2.0 2.0 — — — — — — — — — 2 Trinidad and Tobago IEA 1.2 0.5 0.2 0.2 0.0 — — — — — — 0.3 — 232 Tunisia IEA 14.5 14.2 14.6 13.9 0.4 0.1 — 0.1 — — — 3.2 1.2 291 Turkey IEA 24.6 17.3 14.2 — 6.3 5.1 0.0 0.3 0.4 2.0 0.0 35.1 26.4 2,948 Turkmenistan IEA 0.3 0.0 0.0 — — 0.0 — — — — — 0.0 0.0 511 Turks and Caicos Islands UN — — — — — — — — — — — — — 1 Uganda UN 96.1 94.6 88.8 85.5 2.6 0.7 — — — — — 68.5 58.6 390 Ukraine IEA 0.7 1.3 2.9 1.4 0.4 1.2 — 0.0 — — — 10.1 7.2 2,856 United Arab Emirates IEA — 0.1 0.1 — 0.1 — — — — — — 0.0 — 1,799 United Kingdom of Great Britain IEA 0.7 1.0 3.2 — 0.9 0.2 0.9 0.6 0.1 0.0 0.6 10.0 6.8 5,435 and Northern Ireland 256 Global tracking framework Total final Data Share (%) of RE share (%) in energy Country Share (%) in TFEC in 2010 source RE in TFEC 2010 of: consumption (PJ) in 2010 Tradi- Modern Liquid Geo- Electricity Electricity 1990 2000 2010 tional Hydro Wind Solar Other biomass biofuels thermal capacity generation biomass United States of America IEA 4.2 5.4 7.6 — 3.2 1.4 1.9 0.5 0.1 0.1 0.3 12.9 10.1 57,173 Uruguay IEA 44.8 38.8 52.3 8.3 26.3 17.7 — 0.1 — — — 60.2 89.0 148 Uzbekistan IEA 1.3 1.2 2.6 — 0.0 2.6 — — — — — 14.9 21.0 1,226 Vanuatu UN 100.0 68.9 41.6 39.7 — 1.1 — 0.8 — — — 10.7 19.0 2 Venezuela, Bolivarian Rep. of IEA 11.8 14.1 12.5 1.1 1.0 10.5 — — — — — 61.5 64.9 1,853 Viet Nam IEA 76.1 58.0 34.8 24.5 5.6 4.7 — — — — — 36.4 29.1 1,924 Western Sahara UN — — — — — — — — — — — — — 2 Yemen IEA 2.1 1.2 1.0 — 1.0 — — — — — — — — 211 Zambia IEA 82.9 89.9 90.7 68.0 12.0 10.8 — — — — — 99.6 99.7 260 Zimbabwe IEA 64.1 70.2 80.8 69.2 5.2 6.4 — — — — — 33.4 50.2 352 Total final Aggregated by Data Share (%) of RE in RE share (%) in energy Share (%) in TFEC in 2010 region source TFEC 2010 of: consumption (PJ) in 2010 Tradi- Modern Liquid Geo- Electricity Electricity 1990 2000 2010 tional Hydro Wind Solar Other biomass biofuels thermal capacity generation biomass Northern America IEA 6.0 7.1 9.0 — 3.4 2.8 1.7 0.5 0.1 0.1 0.3 18.2 16.3 64,439 Europe IEA 8.1 9.4 14.1 0.3 6.0 4.1 1.3 1.1 0.3 0.3 0.8 33.6 26.0 42,078 Eastern Europe IEA 3.0 4.2 5.4 1.1 1.8 2.1 0.3 0.0 0.0 0.0 0.0 17.5 13.8 25,902 Caucasian and Central Asia IEA 3.1 5.2 4.4 0.4 0.1 3.9 — 0.0 — 0.0 0.0 28.6 28.2 4,184 Western Asia IEA 8.2 5.8 4.3 0.0 1.6 1.5 0.0 0.1 0.6 0.5 0.0 11.4 7.4 11,697 Eastern Asia IEA 22.2 19.1 15.3 10.4 0.3 3.2 0.1 0.2 0.5 0.2 0.4 20.8 14.8 77,743 South Eastern Asia IEA 52.2 37.9 31.1 23.4 5.5 1.5 0.3 0.0 0.0 0.4 0.0 15.9 14.1 14,741 Southern Asia IEA 50.9 43.4 34.8 26.7 6.1 1.6 0.0 0.2 0.0 — 0.0 24.4 14.0 28,007 Oceania IEA 15.0 15.6 15.1 4.3 4.8 4.0 0.3 0.5 0.3 0.7 0.1 24.2 22.2 3,867 Latin America and Caribbean IEA 32.3 28.2 29.0 5.1 11.5 9.3 2.9 0.1 0.1 0.1 0.0 52.5 56.5 22,000 Northern Africa IEA 6.5 6.2 5.0 2.5 1.0 1.4 — 0.2 — — — 9.6 7.2 3,974 Sub-Saharan Africa IEA 72.5 74.6 75.4 65.3 8.5 1.6 — 0.0 0.0 0.0 — 26.0 22.7 16,368 World IEA 16.6 17.4 18.0 9.6 3.7 3.1 0.8 0.3 0.2 0.2 0.3 23.9 19.4 329,834 ANNEX: renewable energy 257 Total final Aggregated by Data Share (%) of RE in RE share (%) in energy Share (%) in TFEC in 2010 income level source TFEC 2010 of: consumption (PJ) in 2010 Tradi- Modern Liquid Geo- Electricity Electricity 1990 2000 2010 tional Hydro Wind Solar Other biomass biofuels thermal capacity generation biomass High income IEA 6.2 7.0 9.3 0.0 3.9 2.8 1.3 0.6 0.2 0.2 0.4 20.7 16.6 138,623 Upper middle income IEA 18.8 19.6 16.7 8.4 2.6 4.1 0.6 0.1 0.3 0.2 0.2 27.0 22.1 120,299 Lower middle income IEA 45.1 47.6 43.2 34.2 6.7 2.0 0.0 0.1 0.0 0.1 0.0 26.5 20.7 48,666 Low income IEA 61.9 73.7 74.2 63.9 6.7 3.4 — 0.0 0.0 0.1 0.0 56.3 59.1 7,410 Sources: IEA World Energy Statistics and Balances (2012), UN Energy Statistics. Note: Owing to unavailability of data for 1990, the first available data were used for the following countries: Cambodia (1995), Eritrea (1992), Kosovo (2000), Montenegro (2005), and Namibia (1991). The latest available UN data are for 2009. World is greater than the sum of countries because world includes marine and aviation bunkers. — = data not available. 258 Global tracking framework The report’s framework for data collection and analysis will enable us to monitor progress on the SE4ALL objectives from now to 2030. It is methodologically sound and credible. It produces findings that are conclusive and actionable. In many respects, what you measure determines what you get. That is why it is critical to get measurement right and to collect the right data, which is what this report has done. It has charted a map for our achievement of sustainable energy for all and a way to track progress. Let the journey begin! —Kandeh Yumkella Secretary General’s Special Representative for Sustainable Energy for All The SE4ALL Global Tracking Framework full report, overview paper, executive summary, powerpoint presentation and associated datasets can be downloaded from the following website: www.worldbank.org/se4all Funding from ESMAP and DFID is gratefully acknowledged Coordinators For sustainable energy.