THE COST OF COASTAL ZONE DEGRADATION IN WEST AFRICA: BENIN, CÔTE D’IVOIRE, SENEGAL AND TOGO Lelia Croitoru, Juan José Miranda and Maria Sarraf MARCH 2019 © 2019 World Bank Group 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org Email: feedback@worldbank.org All rights reserved. This volume is a product of the staff of the World Bank Group. The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Executive Directors of World Bank Group or the governments they represent. The World Bank Group 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 World Bank Group concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this publication is copyrighted. Copying and/or transmitting portions or all of this work without permission may be a violation of applicable law. World Bank Group encourages dissemination of its work and will normally grant permission to reproduce portions of the work promptly. For permission to photocopy or reprint any part of this work, please send a request with complete information to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA, telephone: 978-750-8400, fax: 978-750-4470, http:///www.copyright.com/. Any queries on rights and licenses, including subsidiary rights, should be addressed to the Officer of the Publisher, World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; fax: 202- 522-2625; e-mail: pubrights@worldbank.org. THE COST OF COASTAL ZONE DEGRADATION IN WEST AFRICA: BENIN, CÔTE D’IVOIRE, SENEGAL AND TOGO Lelia Croitoru, Juan José Miranda and Maria Sarraf With Fadi Doumani and Jia Jun Lee MARCH 2019 Photo Credit: World Bank/Vincent Tremeau. CONTENTS Foreword v Acknowledgments vii Executive Summary ix Chapter One: Introduction 1 Chapter Two: Methodology 5 2.1. Objective and Scope 5 2.2. What Does the COED Measure? 6 2.3. Study’s Limitations 9 Chapter Three: Pollution 13 3.1. Air 13 3.2. Water 16 3.3. Waste 19 Chapter Four: Flooding and Erosion 25 4.1. Flooding 25 4.2. Erosion 28 References 32 BOXES Box 3.3.1: E-waste and Plastics are Growing Concerns in West Africa 19 MAPS Map 1: Coastal Areas of the Four West African Countries Covered by the Study 1 Map 4.1.1: Fluvial Flooding for 1/10 Years Return Period by Country 26 Map 4.2.1: Long-Term Average Erosion Rate (1984–2016) by Country 29 TABLES Table 1: Estimated COED (US$ million, current prices, 2017) x Table 1.1.1:  Socio-Economic Data of the Four West African Countries 2 Table 2.2.1:  Environmental Degradation and Valuation Methods Used 8 Table 3.1.1:  Health Costs Due to Ambient Air Pollution (PM2.5), 2017 16 Table 3.2.1:  Coastal Population and Water-Borne Disease Risk Factors 17 Table 3.2.2: Cost of Untreated Domestic Wastewater 18 Table 3.2.3: Cost of Coastal Water Degradation, 2017 19 Table 3.3.1: Cost of Uncollected Municipal Waste on the Coast 21 Table 3.3.2: Cost of Municipal Waste Disposal on the Coast 22 Table 3.3.3:  Cost of Municipal Waste Mismanagement on the Coast, 2017 22 Table 4.1.1:  Damage Function by Water Depth 27 Table 4.1.2:  Distribution of Flow and Stock Per Land Use Per Year (Percentage) 27 Table 4.1.3: Unit Cost Per Land Use (US$/ha) 27 Table 4.1.4: Economic Cost of Flooding on the Coast, 2017 28 Table 4.2.1: Long-Term Erosion Rate (1984–2016) 29 Table 4.2.3: Economic Costs Associated with Erosion, 2017 30 Table 4.2.2:  Unit Price of Land (US$/m2) 30 Photo Credit: World Bank/Vincent Tremeau. FOREWORD Environmental degradation is costly—to individuals, to societies, and to the environ- ment. In West Africa, coastal degradation takes an important toll on people’s health and quality of life. From Mauritania to Gabon, millions of people on the coast suffer from severe erosion, flooding and pollution. These take away lands, homes and lives. Climate change and variability, characterized by rising sea levels and more frequent and violent storms, are exacerbating their predicaments. How large are the impacts of this degradation? In the past, when government officials asked this simple question, the response was often an emphatic “large!”. This study quantifies in economic terms how large is “large.” As such, it is expected to capture the attention of decision makers to improve coastal policy making in West Africa. Croitoru, Miranda and Sarraf make an important contribution to the literature by making this work available. For the first time in the region, they present a consistent approach to estimating the impacts of environmental degradation in the coastal areas of four countries, namely Benin, Côte d’Ivoire, Senegal and Togo. Their findings show the urgency to find the knowledge, gather the finance, and stimulate the collaboration needed to protect coastal areas and avoid future damages. Benoît Bosquet Director, Environment and Natural Resources World Bank The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo v Photo Credit: World Bank/Vincent Tremeau. The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo ACKNOWLEDGMENTS This report was prepared by a team composed of Lelia Croitoru (Environmental Economist, Consultant) and Juan José Miranda (Environmental Economist), under the guidance of Maria Sarraf (Practice Manager), with valuable contributions from Fadi Doumani (Environmental Economist, Consultant) and Jia Jun Lee (Research Analyst). The team gratefully acknowledges the support of Benoît Bosquet (Director), Peter Kristensen (Lead Environmental Specialist), Dahlia Lotayef (Lead Environment Specialist) and of the peer-reviewers Richard Damania (Senior Economic Adviser) and Raffaello Cervigni (Lead Environmental Economist). Useful comments and inputs were provided by Idriss Deffry (Natural Resources Management Specialist), John Dixon (Lead Environmental Economist, Retired), Abdoulaye Gadiere (Senior Environmental Specialist), Medou Lo (Senior Environmental Specialist), Brigitte Mobongol (Environmental Specialist) and Stefano Pagiola (Senior Environmental Economist). Special thanks are given to Madjiguene Seck (Communications Officer) and Will Kemp (Graphic Designer) for their valuable contribution to the publication. The report was funded by the World Bank’s West Africa Coastal Areas (WACA) management program. Front and back cover photos: World Bank/Vincent Tremeau. The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo vii Photo Credit: World Bank/Vincent Tremeau. viii The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo EXECUTIVE SUMMARY West Africa’s coastal areas host about one third of the region’s population and gener- ate 56 percent of its GDP. They are home for valuable wetlands, fisheries, oil and gas reserves, and high tourism potential. However, these areas are affected by severe pres- sures: rapid urbanization along the coast has increased the demands on land, water, and other natural resources; man-made infrastructure and sand extraction have con- tributed to significant coastal retreat; moreover, climate change and disaster risks are exacerbating these threats. As a result, coastal areas are undergoing alarming envi- ronmental degradation leading to deaths (due to floods, air and water pollution), losses of assets (houses, infrastructure) and damages to critical ecosystems (mangroves, marine habitat). This study estimates in monetary terms the Cost of Environmental Degradation (COED) in the coastal areas of Benin, Côte d’Ivoire, Senegal, and Togo1. Specifically, it values the impacts of degradation that occur during one year, as a result of three major factors: flooding, erosion, and pollution (from water, air and waste). The final results are expressed in 2017 prices. They are reflected in absolute (US$) and in rela- tive terms, as percentage of the countries’ GDP. Overall, the COED of the four FIGURE 1: ESTIMATED COED BY CATEGORY, 2017 countries is estimated at about US$3.8 billion2, or 5.3 per- 2.5% cent of the countries’ GDP 2.1% in 2017. Flooding and erosion 2.0% are the main forms of degrada- % of GDP 1.5% 1.4% 1.3% tion, accounting for more than 60 percent of the total cost (Fig- 1.0% ure 1). Moreover, coastal deg- radation causes over 13,000 0.5% 0.3% 0.3% deaths a year, primarily due to air and water pollution, and to 0.0% floods. Flooding Erosion Water Air Waste Source: World Bank estimates 1 These countries are part of the West Africa Coastal Areas Resilience Investment Project (WACA ResIP), which aims to strengthen the resilience of communities and areas in coastal West Africa. The project covers Benin, Côte d’Ivoire, Mauritania, São Tomé and Príncipe, Senegal and Togo. 2 If we adjust this figure with the countries’ purchasing power parities, we obtain a total loss of 10 billion international $ (PPP-adjusted, 2017). The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo ix FIGURE 2: ESTIMATED COED BY COUNTRY, 2017 8% 7.6% 7% 6.4% 6% 4.9% 5% % of GDP 4% 3% 2.5% 2% 1% 0% Benin Côte d’Ivoire Senegal Togo Flooding Erosion Water Air Waste Source: World Bank estimates At the country level, coastal degradation imposes costs »» Erosion is a result of both natural and human fac- varying between 2.5 percent of GDP in Benin to 7.6 per- tors. Some areas have no erosion at all, others have cent of GDP in Senegal in 2017 (Figure 2 and Table 1). land losses (erosion), and others have land gains (accretion). About 56 percent of the coastline in These estimates are the result of three major factors Benin, Côte d’Ivoire, Senegal and Togo is subject to affecting the coastal area: an average erosion of 1.8 meters per year. Erosion »» Flooding due to high rainfalls (pluvial floods) and is the most damaging factor in Benin, Senegal, and overflowing rivers (fluvial floods) causes deaths Togo, primarily due to losses of high value urban and leads to major damage to houses, infrastruc- land. The highest cost, estimated at US$0.5 billion ture and critical ecosystems, such as beaches and per year, occurs in Senegal. In all countries, the mangroves. Floods are extremely damaging in Côte cost of erosion is expected to increase considerably d’Ivoire, costing society US$1.2 billion per year, in the future, as the phenomenon is likely to affect mainly due to large areas affected by pluvial floods larger urban areas. (Table 1). In the other countries, flooded areas and »» Pollution from air, water and waste mismanage- the associated water depths are smaller, leading to ment imposes an important toll on people’s health comparatively lower flooding costs. TABLE 1: ESTIMATED COED (US$ MILLION, CURRENT PRICES, 2017) Benin Côte d’Ivoire Senegal Togo Flooding 29 1,183 230 10 Erosion 117 97 537 213 Water 53 485 375 36 Air 10 166 17 23 Waste 20 53 90 28 Total 229 1,985 1,250 310 Source: World Bank estimates x The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo and quality of life. It can reach as high as US$0.7 real estate on the coastal area). Therefore, the results of billion, in Côte d’Ivoire. In all countries, unsafe this study should be considered conservative estimates, water, sanitation, and hygiene are particularly which capture only partially the full COED. To refine and harmful, causing more than 10,000 deaths per complement these estimates, it would be important that year; they affect primarily Côte d’Ivoire and Senegal, future work cover the above aspects, as well as the effects with more than 4,000 deaths per country. Air pollu- of climate change on floods and erosion, and the com- tion and waste mismanagement are also important bined impacts that erosion and climate change may have forms of degradation, but are considerably under- on water availability. estimated: the cost of air pollution (2,500 deaths) refers only to the impacts of fine particulate matter The study demonstrates that flooding, erosion and pollu- in the countries’ capitals, while the cost of waste tion are major challenges facing the West Africa coastal covers only the effects of insufficient collection and areas. They cause death, decrease the quality of life inappropriate disposal of municipal waste. of citizens and lead to substantial economic damages amounting to over 5.3 percent of the four countries’ GDP. Finally, it should be noted that data limitations pre- Building coastal resilience early on will reduce these dam- vented the estimation of several costs, related to air pollu- ages and save billions of dollars in future damages. The tion (e.g. the impacts of air pollution in other cities than the recently established West Africa Coastal Areas (WACA) countries’ capitals; of air pollutants other ambient PM2.5); management program is designed to build resilient coastal water pollution (e.g. damages caused by the discharge of communities. The program invests in seawalls, breakwa- untreated agricultural and industrial wastewater); waste ters, sand barriers, road protection, mangrove restoration, management (e.g. damages caused by inappropriate or beach replenishment and pollution prevention. insufficient disposal of medical, industrial, construction and demolition, e-waste); floods (e.g. damages caused by Investing in coastal adaptation now will prevent losing bil- flooding from sea level rise and storm surges); and ero- lions of dollars in damages in the future. sion (e.g. slower GDP growth in the future due to less The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo xi Photo Credit: World Bank/Idriss Deffry. CHAPTER ONE INTRODUCTION The West African coast, spanning from Mauritania to Gabon, covers 17 countries,3 with a diversity of economic, political, and conflict situations. The coastal area is home to one third of the population and generates 56 percent of the GDP (UEMOA, 2010). This study covers four countries—Benin, Côte d’Ivoire, Senegal, and Togo—with a total population of 56 million people and a coastline of 1,223 km (Map 1). The coastal areas of these countries—defined as all districts along the coast —are home to 36 percent of the countries’ total population (Table 1.1.1). MAP 1: COASTAL AREAS OF THE FOUR WEST AFRICAN COUNTRIES COVERED BY THE STUDY Source: WBG staff using CIESIN Gridded Population of the World (GPWv4) (2015), ESA Global Land Cover (2015) 3 These are Benin, Cabo Verde, Cameroon, Côte d’Ivoire, Equatorial Guinea, Gabon, Ghana, Guinea, Guinea- Bissau, Liberia, Mauritania, Nigeria, São Tomé and Príncipe, Senegal, Sierra Leone, The Gambia, and Togo. The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 1 TABLE 1.1.1:  SOCIO-ECONOMIC DATA OF THE FOUR WEST AFRICAN COUNTRIES Urban coastal Total Coastal Coastal GDP (US$/ Coastline Coastal population Country population population population capita) (km) districts (#) (% of coastal (million) (million) (% of total) population) Benin 830 10.9 121 5 1.9 17 97 Côte d’Ivoire 1,662 22.7 515 8 8.2 36 57 Senegal 1,033 15.0 531 15 7.8 52 61 Togo 617 7.2 56 2 2.0 28 100 Average/ 1,196 55.7 1,223 30 19.9 36 67 Total Sources: data.worldbank.org; www.cia.gov; CIESIN Gridded Population of the World (GPWv4) (2015) and ESA Global Land Cover (2015). These coastal areas are home to valuable wetlands, rich The four countries were selected due to better data availa- fisheries, oil and gas reserves, and high tourism potential bility on coastal issues compared to other countries of the (UNIDO, 2011). However, they are affected by severe pres- project, given by the multi-hazard risk assessment of the sures: rapid urbanization and migration to the coast have International Marine & Dredging Consultants (IMDC), increased the demands on land, water, and other natural multi-sectoral investment plans, national statistics, etc. resources (World Bank, 2015a); man-made infrastructure Overall, estimating the COED in monetary terms will and sand extraction have contributed to significant coastal provide an indication of the real magnitude of damage retreat, which could reach 10 meters per year in highly and of the urgency of action needed to protect the coastal vulnerable areas (Giardino et al., 2017); moreover, climate areas. Chapter 2 provides an overview of the methods change and disaster risks are exacerbating these threats. used for estimating the COED and the study’s limitations. As a result, coastal areas are undergoing severe environ- Chapter 3 estimates the impacts of pollution, while Chap- mental degradation leading to deaths (due air and water ter 4 addresses the cost of flooding and erosion on the pollution), losses of assets (houses and infrastructure) and coast. of critical ecosystems (mangroves). For example, flooding in Senegal is estimated to affect 200,000 people annu- ally; while the extreme floods in 2009 caused damages of US$104 million in Dakar only.4 Raising awareness on the magnitude of coastal degrada- tion is a critical step towards enacting positive change. This study contributes to this need, by estimating in monetary terms the Cost of Environmental Deg- radation (COED) of the coastal areas in select West African countries5: Benin, Côte d’Ivoire, Senegal and Togo. These countries are part of the six-country West Africa Coastal Areas Resilience Investment Project (WACA ResIP),6 which aims to strengthen the resilience of communities and areas in coastal West Africa. 4 https://www.gfdrr.org/senegal 5 This study updates and expands the earlier work on the cost of environmental degradation in Mauritania (World Bank, 2017) and Togo (World Bank, 2015b). 6 which includes Benin, Côte d’Ivoire, Mauritania, São Tomé and Príncipe, Senegal and Togo. 2 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo Photo Credit: World Bank/Vincent Tremeau. Photo Credit: World Bank/Vincent Tremeau. CHAPTER TWO METHODOLOGY A solid methodological framework is needed to ensure that the costs imposed on soci- ety by environmental degradation are captured as accurately as possible and consist- ently across different environmental impacts. This chapter describes the methodology used for estimating the COED. Section 2.1 presents the objective and scope of envi- ronmental valuation, section 2.2 discusses the methodological consistency and valua- tion methods used, and section 2.3 presents the study’s limitations. 2.1. OBJECTIVE AND SCOPE This study aims at estimating in monetary terms the annual COED of the coastal areas of Benin, Côte d’Ivoire, Senegal, and Togo. It assesses damages at three levels: economic, such as damages to assets (e.g. buildings and roads) due to coastal floods; environmental, for example, reduced aesthetic value in the areas located near unsanitary landfills; and social, such as premature deaths caused by exposure to high levels of air and water pollution. It should be noted that certain activities have short-term impacts: for example, water pollution often causes health problems (such as diarrhea and skin allergy) ranging from a few days to several weeks. Other activities have long-term impacts: for example, erosion of coastal areas often results in losses of assets in the long run. This study estimates the present value (PV) of the current and future impacts caused by activities occurring during the latest year for which data are available. The analysis uses a 3 per- cent discount rate due to the high importance given to the future impacts of erosion, and a time horizon of 30 years.7 The results are expressed in 2017 prices. They are reflected in absolute (US$) and in relative terms, as percentage of the countries’ GDP. The study values the impacts of environmental degradation that occurred in 2017 due to pollution (related to air, water, and waste), flooding and erosion on the coast. It focuses on degradation induced by both human (e.g. air pollution due to industrial activities, 7 Assuming that a person of average age will benefit from environmental services for another 30 years. The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 5 water pollution due to discharges of untreated wastewa- ter) and natural factors (e.g. flooding). As such, the esti- 2.2. WHAT DOES THE COED mated values provide a more comprehensive picture of MEASURE? the situation of environmental degradation compared to other COED work that focused primarily on degradation The COED estimates the annual changes in benefits induced by human actions (Croitoru and Sarraf, 2010). caused by current environmental management practices. For example, knowing that floods might cause high coastal Figure 2.1.1 illustrates these values. At any given time, damages would trigger an urgent call for installing protec- coastal areas provide certain benefits (e.g. industrial and tive measures—which would not have been triggered, had agricultural production, recreational value), depending the COED covered only human-induced losses. on the type of management and socioeconomic context. The first column shows the economic value of these ben- In addition, the valuation of the COED also covers to efits for a given year. a certain degree the impacts of climate change (e.g. increased flooding due to higher rainfall). However, it is The second column presents the value of these benefits in important to note that: (i) the impacts of climate change the future; they are assumed to be lower because of deg- cannot be separated from those of other factors; (ii) since radation, due to either sub-optimal management (e.g. dis- the valuation refers to only one year, these impacts are charge of untreated municipal wastewater, air pollution likely to be minor.8 caused by industrial activities) or natural factors, exacer- bated by climate change (e.g. coastal erosion and flood- ing). The difference in value represents the cost of damage caused by current degradation, namely the COED. FIGURE 2.1.1: ECONOMIC VALUE OF COASTAL ZONES $ Benefit of intervention Cost of degradation Cost of intervention 2017 2018 under 2018 with current improved management management Source: Pagiola et al. (2004). 8 To capture the overall impacts of climate change on the coast, a study should use projections of impacts on a much longer time horizon (e.g. 30–50 years). 6 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo It is important to note that the degradation costs only in two instances does the study apply cost-based methods,9 indicate the extent of damage and the areas needing while ensuring that they provide conservative results com- urgent interventions for improvement. They provide no pared to other WTP measures.10 information on the best choice of interventions or their profitability. The third column best reflects this, showing Demand curve approaches include: revealed prefer- that the profitability of interventions should be measured ence methods, based on observation of actual consumer by comparing their benefits with the costs of intervention. behavior in markets for goods and services; and stated preference methods, based on elicitation of consumers’ This study estimates only the COED (the differ- WTP for a benefit or willingness to accept (WTA) a com- ence between the first and the second column). Potential pensation for a loss (Bateman, 1994). Measures based on interventions for environmental improvement are identi- observed behavior are usually preferred to those relying fied and their profitability is assessed in the Cost-Benefit on hypothetical behavior, as the latter can result in biased Analysis of the WACA ResIP project appraisal document responses. In addition, the perception of the value of ser- (World Bank, 2018a). vice/damage differs from the WTP/WTA perspective. The NOAA Panel suggested that WTP should be always used to evaluate a service; it is commonly argued that this 2.2.1 METHODOLOGICAL CONSISTENCY constitutes the most conservative (and therefore, preferred) Estimating the COED involves valuing damages to some option (Arrow, 1993; Carson et al., 1996). This study uses goods and services that have market prices (e.g. houses the WTP approach, derived from the available studies and land lost to erosion), and to some that do not (e.g. pol- in the four countries, or in the West Africa region. lution due to uncollected municipal waste). While valua- While the above discussion provides a quick glimpse on tion of marketable goods tends to be straightforward (e.g. the efforts made to achieve methodological consistency in by using the market price after eliminating distortions), this study, it is important to dedicate additional effort to estimating the value of non-market goods and services is specifically review the methods used in the COED and often challenging. This has been long recognized in the similar studies, rank valuation methods in terms of their environmental literature, and a wide range of valuation consistency with other methods, their relative desirability, methods have been developed (e.g. Dixon et al., 1994; the likelihood that data will be available to apply them, Freeman, 2003; Willis and Garrod, 2012; Johnston et al., and the type of bias the resulting estimates might contain. 2015). In a valuation exercise such as the COED, ensur- ing consistency across the valuation methods is essential for obtaining meaningful results. 2.2.2 VALUATION METHODS The existing valuation methods are commonly divided The COED is estimated based on the valuation methods into demand curve approaches (that seek to estimate the summarized in table 2.2.1 and described below. value of goods and services by explicitly estimating the consumers’ demand, or WTP for them) and non-demand Air pollution. Ambient air pollution is a major contrib- curve approaches (that value environmental damages utor to human mortality and morbidity. Exposure to fine via cost-based methods, such as replacement cost) (Mar- particulate matter (PM2.5) is especially harmful to health, kandya et al., 2002). When no market prices are avail- able to estimate the value of damage itself, this study uses 9 These are forgone income approach (to value the cost of water borne demand curve approaches—WTP measures—to assess morbidity) and cost of wastewater treatment (to value the impact of untreated the impacts of environmental degradation. For exam- wastewater discharge). ple, the cost of uncollected municipal waste is estimated 10 Careful attention should be paid when applying cost-based methods. For through the society’s WTP for improved collection. Only example, when restoration cost is applied, use of actual expenditures can under- estimate the damage, as replacements rarely substitute all the services coming from the original ecosystem; it can also over-estimate, if replacement is under- taken inefficiently. The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 7 TABLE 2.2.1:  ENVIRONMENTAL DEGRADATION AND VALUATION METHODS USED Environmental degradation Methods used for valuation Pollution Air Impact of ambient air pollution (PM2.5) on health: VSL for mortality lower respiratory infections; ischemic heart WTP for morbidity disease; stroke; chronic obstructive pulmonary disease; tracheal, bronchus and lung cancer; and diabetes mellitus type 2 Water Impact of insufficient water supply, sanitation and VSL for mortality hygiene on health: diarrhea Forgone income for morbidity Discharge of untreated wastewater in the Cost of treating wastewater environment Waste Damage due to uncollected municipal waste WTP for improved waste collection Damage due to inappropriate disposal of municipal Hedonic pricing waste Floods Damage to assets and economic productivity Market price Mortality VSL for mortality Erosion Loss of assets, land and economic productivity Market price as it can pass the barriers of the lung and enter the blood years, DALYs) based on the 2017 Global Burden of Dis- stream. This section estimates the impact of exposure to ease (GBD) data. It then estimates the economic cost of ambient PM2.5 on health in the four countries’ capitals. mortality (based on the VSL) and morbidity (based on the Using the latest cause-and-effect relationships developed forgone income approach). In addition, the section values in the epidemiological literature, it estimates the impact the impact of discharging untreated wastewater on the on premature mortality: induced lower respiratory infec- environment through the local cost of treating wastewater in tions; ischemic heart disease; stroke; chronic obstructive the region. pulmonary disease; tracheal, bronchus and lung cancer; and diabetes mellitus type 2 (GBD 2017 Risk factors col- Waste management poses complex challenges, as it laborators, 2018). The cost of mortality is estimated based relates to a wide range of wastes—e.g. municipal, medi- on the VSL, which reflects the society’s WTP to avoid cal, industrial, demolition, electronic waste—which must death. In addition, the cost of morbidity is valued as a frac- be handled in distinct ways. Inappropriate management tion (10 percent) of the cost of mortality, based on avail- of these wastes can result in: reduced tourism opportu- able studies estimating the WTP for reduced morbidity nities, fish contamination, groundwater pollution, and due to air pollution (World Bank, 2016; Hunt et al., 2016). sometimes human deaths. This section addresses only the impact of inappropriate management of domestic waste. Water pollution. Insufficient or inappropriate water First, the damage due to insufficient collection of domes- supply, sanitation, and hygiene (WASH) can affect human tic waste is estimated based on the quantity of uncollected health (e.g. due to water-borne diseases) and the environ- waste and the society’s WTP for improving waste col- ment (e.g. due to discharge of untreated wastewater). This lection. Second, the cost of waste disposal in unsanitary section estimates the impacts on health through the bur- landfills is valued based on the observed depreciation of den of water-borne diseases caused by unsafe WASH in land value located in the proximity of the landfills. coastal urban and rural areas of the four countries. First, the section quantifies mortality (number of premature Floods. West African countries experience fluvial floods, deaths) and morbidity (number of disability adjusted life which occur when rivers burst their banks as a result of 8 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo sustained or intense rainfall, and pluvial floods, which Landsat images with resolution of 30 m (Luijen- occur when heavy precipitation saturates drainage sys- dijk et al., 2018). tems, particularly in flat and urban areas. The analysis »» The unit economic value of eroded land captures: the val- values the impact of both fluvial and pluvial floods that ue of assets (e.g. buildings, roads, other infrastruc- occur along the coast,11 through: (i) the cost of mortality, ture); the present value (PV) of economic flows for estimated based on the number of deaths due to flood- the next 30 years; and the value of bare land. ing and the VSL; and (ii) the damage to assets and economic production, based on: the flooded area for a typical year, a damage factor (coefficient of loss), and the unit economic 2.3. STUDY’S LIMITATIONS value of land. These indicators are derived as follows: »» The flooded area is calculated based on the results of The study was conducted during September 2018–Feb- the SSBN Global Flood Hazard Model applied ruary 2019, based on available secondary information. to West Africa. These results show the maximum Due to time and budget constraints, it was not possible to expected water depth for fluvial and pluvial floods collect primary data. Despite that, every effort was made and their corresponding surface for six different re- to use reliable data and to provide comparable estimates turn periods (between 1-in-5 and 1-in-100 years). across countries. The flooded area is then classified into rural and urban areas. It should be noted that data limitations prevented the »» A damage factor, whose magnitude varies according estimation of several costs, related to: air pollution (e.g. the to water depth, is used to estimate the part of eco- impacts of air pollution in other cities than the country’s nomic value lost to floods (Huizinga et al., 2017). capital; the impacts of air pollutants—other PM2.5—in »» The economic value of land is estimated based on the coastal areas; the impact of indoor air pollution on health); available multi-hazard risk assessment on the West water pollution (e.g. damages caused by the discharge of African coast (IMDC, 2018 a,b,c). It captures the untreated agricultural and industrial wastewater); waste value of assets (e.g. buildings, roads, other infra- management (e.g. damages caused by inappropriate/ structure) and of economic flows (e.g. industrial insufficient disposal of waste other than municipal, such as and agricultural production) for 2017 for both ru- medical, industrial, construction and demolition, e-waste); ral and urban coastal areas. floods (e.g. damages caused by flooding from sea level rise and storm surges); and erosion (e.g. slower GDP growth Erosion. West African coastal areas are affected by ero- in the future due to less real estate on the coastal area). sion due to population growth, economic activity, and sea Therefore, the results of this study should be considered level rise. Estimating the cost of erosion assumes that the conservative estimates, which capture only partially the full land, assets, and economic flows are lost in the long run.12 COED. Despite these limitations, the results are consid- The valuation is based on the following indicators: ered to be reasonable estimates of the magnitude of the »» The eroded area is estimated as an annual aver- COED and to reflect the true environmental priori- age value of land area lost to erosion, based on a ties on the coastal zones in these countries. study which estimated the change in shoreline over 1984–2016, by comparing cloud-free historical Every effort was made to ensure that the environmental damages are estimated by applying consistent valuation 11 It does not address the impacts of floods caused by the sea level rise due to methods, as explained in section 2.2.1. Despite these limited modelling exercises. efforts, the study is affected by some limitations. For 12 In reality, these losses can be replaced through reconstruction of similar example, when data on the society’s WTP was not avail- assets in areas located nearby; however, this is often not possible, for example able for the four countries, valuation was based on ben- due to land scarcity (e.g. driven by high urbanization rate on the coast). Even when reconstruction is possible, it diverts budget from other investments which efits transfer of similar measures from other countries of would have otherwise happened—hence, inducing lost economic opportunities. the region, an exercise which involves a certain degree of The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 9 inaccuracy.13 In addition, despite the considerable recent It should be also noted that the COED captures both improvements of the GBD 2017 compared to the GBD losses of stocks (e.g. losses of buildings to erosion) and 2016,14 use of this method is still affected by some limita- flows (e.g. loss of economic productivity) for the year of tions, e.g. lack of incorporation of smoking and second- analysis, while the GDP is a measure of annual flow. In hand smoke into the proportional burden strategy (GBD this study, expressing the COED as a percentage of GDP 2017 Risk Factor Collaborators, 2018). is meant only to benchmark the damage against a well-known macro-economic indicator, and not to directly compare the two Another limitation is related to the valuation of mortality. values. Valuing life in monetary terms could be controversial. The VSL concept has been developed in the environmental economics literature, using people’s WTP to avoid the risk of death (Viscusi and Aldy, 2003; Viscusi and Masterman, 2017). However, even though this concept is now com- monly used, its application is still subject to challenges, e.g.: (i) in countries where primary surveys have been con- ducted, its application often generated a wide variety of results, depending on the approach used, type of survey, etc.; (ii) in countries with no primary surveys, the VSL has been usually obtained through benefits transfer of a value from a different country. The latter is the case of the present study, where the VSL for the four countries has been obtained through benefits transfer of a base value from OECD countries, following the guidelines of World Bank (2016). It should be noted that the results are very conservative estimates of the VSL and do not capture the real value of life in these countries. 13 In general, the accuracy of benefits transfer depends on several parame- ters, such as reliability of the original study’s techniques, similarity of context between the original site and the site where the value is transferred, population characteristics, and so forth (Johnston et al., 2015). 14 The improvements of GBD 2017 compared to GBD 2016 include: updating the integrated exposure responses to include data from new studies (e.g. studies published after the completion of GBD 2016, systematic reviews of all second- hand smoking cohorts, etc.), inclusion of type 2 diabetes as a new outcome (based on a systematic research of scientific literature), calibration of satellite measurements with ground measurements (using Data Integration Model for Air Quality), refinement of the population attributable fractions by using a proportional approach which reduces the overestimation risks (GBD 2017 Risk Factor Collaborators, 2018). 10 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo Photo Credit: World Bank/Vincent Tremeau. Photo Credit: World Bank/Vincent Tremeau. CHAPTER THREE POLLUTION 3.1. AIR Ambient air pollution is a major contributor to human mortality and morbidity. Glob- ally, ambient particulate matter caused about 2.9 million premature deaths in 2017, or 8.6 percent of total global deaths (GBD 2017 Risk factor collaborators, 2018). In West Africa, it was responsible for about 79,800 premature deaths in the same year (IHME, 2018). In this region, air quality is increasingly degrading in the agglomerated coastal areas, as a result of urbanization, transport, and industrial development. This section estimates in monetary terms the impacts of ambient fine particulate matter15 (PM2.5) on health in the capitals of the four countries: Cotonou (Benin), Abidjan (Côte d’Ivoire), Dakar (Senegal) and Lomé (Togo). The impacts of air pollution on health in other areas could not be estimated due to data limitations. Additionally, the effects of air pollutants other than PM2.5 could not be estimated either, due non-availability of robust methodology linking concentration levels with health impacts. 3.1.1. COST OF URBAN AIR POLLUTION We estimate the impact of PM2.5 exposure on mortality, in terms of premature deaths due to lower respiratory infections; ischemic heart disease; chronic obstructive pulmonary diseases; tracheal, bronchus, and lung cancer; stroke; and diabetes mellitus type 216 (GBD 2017 Risk factor collaborators, 2018); and on morbidity, due to prob- lems such as chronic bronchitis, hospital admissions, work loss days, restricted activity days, and acute lower respiratory infections in children (Hunt et al., 2016; World Bank, 2016). The estimation is conducted in four steps, presented below. Step 1. Measure the PM2.5 concentration. In West Africa, ground air quality monitoring is limited to a few monitoring stations in the most agglomerated urban 15 particulate matter with aerodynamic diameter of less than 2.5 microns. 16 Evidence suggests that exposure to PM₂.₅ can be linked to type 2 diabetes through altered lung function, vascular inflammation, and insulin sensitivity (Rajagopalan and Brook, 2012). The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 13 FIGURE 3.1.1: MORTALITY DUE TO EXPOSURE TO FINE PARTICULATES (PM2.5), BY CITY 1800 1600 1400 1200 1000 Deaths 800 600 400 200 0 Cotonou Abidjan Dakar Lomé LRI Lung cancer COPD IHD Stroke Diabetes mellitus type 2 Source: Authors, based on data from IHME (2018) and GBD 2017 Risk factors collaborators (2018) Notes: IHD = ischemic heart disease; LRI = lower respiratory infections; COPD = chronic obstructive pulmonary diseases. areas. The most recent available ground measurements the population exposed to ambient air pollution are not indicate annual average PM2.5 of 21 μg/m3 in Dakar available for any measurement stations in the cities con- (WHO, 2018b17), 32 μg/m3 in Abidjan and 32 μg/m3 in sidered. As a result, it is assumed that the average level Cotonou (Djossou et al., 201818). of pollutant concentration calculated in the previous step applies to the total population of each city. Population No measurement data for Lomé were available. In its data are drawn from the most recent demographic census absence, satellite-derived data indicate a PM2.5 concentra- of the four countries and reflect the urban population in tion of 75 μg/m3 in 201719. However, it is important to each district: 1.1 million people in Dakar (ANSD, 201721); note that satellite-derived data can provide reliable esti- 601,000 people in Cotonou22, 4.5 million people in Abid- mates at city level only when calibrated against observa- jan23 and 1.5 million people in Lomé. tions from ground-level monitoring (World Bank, 2016). Though this calibration is not possible for Lomé, a com- Step 3. Quantify the health impacts of exposure parison between satellite-derived and ground measured to PM2.5. Several epidemiological studies revealed strong data for Cotonou indicates a proportion of 2.320. Using correlations between long-term exposure to PM2.5 and the same proportion for Lomé, the PM2.5 concentration is premature mortality (e.g. Apte et al., 2015; Cohen et al., roughly estimated at 32 μg/m3. 2017, etc.). Recent research associated PM2.5 exposure with mortality related to five diseases in adults over 25: Step 2. Identify the population exposed. Data on ischemic heart disease; stroke; chronic obstructive pulmo- nary disease; tracheal, bronchus and lung cancer; and dia- betes mellitus type 2; and to lower respiratory infections in 17 based on measurements from three stations (industrial, traffic, urban) in all ages (GBD 2017 Risk factor collaborators, 2018). 2018. 18 based on measurements from stations representative for traffic during 2015– 2017. 19 Based on World Bank satellite data. 20 Obtained as 74 μg/m3 (satellite-derived data)/ 32μg/m3 (ground measure- 21 The population is related to the Department of Dakar. ment data) in Cotonou. The same proportion is applied to Lomé, due to simi- 22 http://www.insae-bj.org/population.html. larities between the geographical and environmental contexts of the two cities. 23 http://www.ins.ci/n/templates/Pub/annuaire%20demo.pdf 14 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo FIGURE 3.1.2: MORTALITY BY GROUP OF AGE 95+ 90–94 85–89 80–84 75–79 70–74 65–69 60–64 Groups of age 55–59 50–54 45–49 40–44 35–39 30–34 25–29 20–24 15–19 10–14 5–9 0–4 0 100 200 300 400 500 600 700 Deaths Source: Authors, based on data from IHME (2018) and GBD 2017 Risk factors collaborators (2018) We estimate the number of deaths attributable to air pol- Step 4. Estimate the health impacts of exposure lution (PM2.5) using data on: (i) mortality by disease and to PM2.5. We estimate in monetary terms the impacts of age group, based on the 2017 Global Burden of Disease PM2.5 on health as follows: study (IHME, 2018); (ii) proportion of deaths due to PM2.5 »» The cost of mortality is valued based on the calculated by using the integrated exposure response func- Value of Statistical Life (VSL), which reflects the tions developed by GBD 2017 Risk factors collaborators society’s WTP to reduce the risk of death. The cost (2018), which are available by disease, age and PM2.5 con- of mortality for each country is presented in Table centration24. 3.1.1. »» The cost of morbidity includes resource costs Figure 3.1.1 summarizes the results. In the four cities, (i.e. financial costs for avoiding or treating pollu- exposure to PM2.5 is responsible for about 2,500 deaths tion-associated illnesses), opportunity costs (i.e. in 2017: about 190 in Cotonou, 1,550 in Abidjan, 270 in indirect costs from the loss of time for work and Dakar and 490 in Lomé. The greatest share (62 percent) leisure), and disutility costs (i.e. cost of pain, suffer- of deaths occurred in Abidjan, due to its large population ing, or discomfort). The literature assessing causal exposed to high pollution levels. In all cities, lower respira- relationships between exposure to PM2.5 and mor- tory infections are the leading cause of mortality: they are bidity is much more limited than that for mortality responsible for nearly half of the deaths—half of which (Hunt et al., 2016). affecting children under five (Figure 3.1.2). So far, no commonly accepted method has been devel- oped to value the overall cost of morbidity due to air 24 For more details, see GBD 2017 Risk Factor Collaborators, 2018. Supple- pollution (OECD, 2014). However, results of studies con- ment to: GBD 2017 Risk Factor Collaborators. Global, regional, and national ducted in several OECD countries indicate that morbid- comparative risk assessment of 84 behavioural, environmental and occupa- ity costs account for a small percentage of mortality costs tional, and metabolic risks or clusters of risks for 195 countries and territo- (Hunt et al., 2016; OECD, 2014; World Bank, 2016). On ries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018; 392: 1923–45. doi:  http://dx.doi.org/10.1016/S0140- this basis, OECD proposed a 10 percent markup of mor- 6736(18)32225-6. tality cost to account for morbidity (Hunt et al., 2016). The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 15 TABLE 3.1.1:  HEALTH COSTS DUE TO AMBIENT AIR POLLUTION (PM2.5), 2017 Benin Côte d’Ivoire Senegal Togo (Cotonou) (Abidjan) (Dakar) (Lomé) Mortality* (US$ million) 8.9 150.5 15.3 20.9 Morbidity (US$ million) 0.9 15.0 1.5 2.1 Total (US$ million) 9.8 165.5 16.8 23.0 Total (% of GDP) 0.1% 0.4% 0.1% 0.5% Notes: * Based on a VSL of US$46,100 for Benin; US$97,300 for Côte d’Ivoire; US$78,100 for Senegal and US$31,500 for Togo (very conservative estimates obtained from benefits transfer of results from OECD studies, based on World Bank, 2016). Using this assumption, the cost of morbidity is estimated Management, in partnership with UNEP, is starting an and presented in Table 3.3.1. air quality monitoring program, which is expected to put in place a network of monitoring stations for PM2.5 and other pollutants in Lomé (ANGE, 2018). 3.1.2. CONCLUSIONS Overall, the health cost resulting from exposure to PM2.5 3.2. WATER in the four cities is estimated at about US$215 million, or 0.3 percent of the four countries’ GDP. The The degradation of water resources on coastal zones is greatest share of this cost accrues to Abidjan, due to the often due to human activities—e.g. poor water and sani- largest population exposed, high pollution levels, and sub- tation service provision, mining, tourism, agriculture25— stantially higher VSL compared to other countries. In all and natural factors—e.g. sea level rise leading to salt cities, this cost is due to both anthropogenic (e.g. traffic, water intrusion in groundwater. This degradation affects waste burning) and natural factors (e.g. Saharan dust). both water quality and quantity, with impacts on people’s health and the services provided by ecosystems. Due to Distinguishing between anthropogenic and naturally- data limitation, this chapter quantifies only the impacts of caused PM2.5 is important for guiding policies to improve water degradation on human health and that of untreated air quality and health. However, in lack of source appor- domestic wastewater on the environment. tionment studies, it is not possible to distinguish the con- tribution of each source of pollution to the overall impact. This task is especially challenging for African urban areas, 3.2.1. WATER-BORNE DISEASES where the intensity of each pollution source varies with The burden of water-borne diseases is decreasing glob- season: e.g. pollution linked to domestic fires, traffic and ally26, but remains critically important in Sub-Saharan waste burning most likely occur throughout the year, while Africa27—especially in slums, peri-urban areas and rural transport of biomass burning emissions and Saharan dust areas. It stems from unsafe water, sanitation and hygiene are expected to have impact primarily during dry season as (WASH28), which cover poor water quality, inadequate well as December–January (Djoussou et al., 2018; Doumbia et al., 2012; Liousse et al., 2010). 25 excess pumping and irrigation as well as pesticide, fertilizer and fungicide Overall, ambient air pollution on West African coastal runoff 26 According to IHME, the number of deaths due to unsafe water, sanitation areas is a problem that risks to be aggravated in the and hygiene decreased from 2.8 million in 1990 to 1.6 million in 2017 at the future. Although the present estimates refer only to four global leve (https://vizhub.healthdata.org/gbd-compare/) cities—the only ones for which measurements or estima- 27 http://apps.who.int/gho/data/view.main.INADEQUATEWSHv?lang=en tions could be found—other urban areas also experience 28 UNICEF-WHO Definition: drinking water services refers to the accessibil- ity, availability and quality of the main source used by households for drinking, harmful impacts of air pollution. Aware of this growing cooking, personal hygiene and other domestic uses; sanitation services refer to challenge, Togo’s National Agency for Environmental the management of excreta from the facilities used by individuals, through emp- 16 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo TABLE 3.2.1:  COASTAL POPULATION AND WATER-BORNE DISEASE RISK FACTORS Category Unit Benin Côte d’Ivoire Senegal Togo Coastal Population # million 1.88 8.17 7.84 1.97 Coastal urban population # million 1.79 4.57 4.89 1.71 Coastal rural population # million 0.09 3.60 2.95 0.26 WASH risk factors Mortality lower bound (urban) #/100,000 45.7 38.7 39.5 34.2 Mortality higher bound (rural) #/100,000 86.0 71.3 74.5 67.9 Morbidity lower bound (urban) DALY/100,000 95 106.2 106.7 105.8 Morbidity higher bound (rural) DALY/100,000 139.9 156.1 159.4 155.8 Physical valuation Mortality in coastal area # 899 4,338 4,127 762 Morbidity in coastal area DALY lost 1,833 10,476 9,915 2,216 Economic valuation Estimated VSL US$ 46,100 97,300 78,100 31,500 Annual income, 2017 US$ 1,600 2,700 1,200 1,200 Estimated mortality cost US$ million 41 422 322 24 Estimated morbidity cost US$ million 3 28 12 3 Total US$ million 44 450 334 27 Sources: CIESIN Gridded Population of the World (GPWv4) (2015) and ESA Global Land Cover (2015) for the coastal population; https://vizhub.healthdata.org/gbd- compare/ for WASH risk factors. Notes: To give better context to the above estimates, mortality at the country level due to water-borne diseases was estimated at 7,278 in Benin, 13,237 in Côte d’Ivoire, 7,830 in Senegal and 3,638 in Togo. sanitation status within households, and lack of hygiene pared to rural areas.29 Thus, the estimation of mortality by household members. Over time, climate change will and morbidity uses the GBD lower-bound risk factors for most likely increase the risk of water-borne diseases: for urban areas, and the higher-bound risk factors for rural example, coastal flooding can spread fecal contaminants areas. and increase the risk of cholera outbreak, while water shortages due to droughts could escalate the risks of diar- Similar to the chapter 3.1, the economic valuation of rheal diseases. mortality (deaths due to water-borne diseases) relies on the VSL. The estimation of morbidity (DALY lost) is This analysis relies on the 2017 Global Burden of Dis- based on the forgone income approach—the average ease (GBD) data, which calculates the number of deaths wage per capita in 2017—in lieu of the cost of illness. This and disability adjusted life years (DALYs) associated with approach is conservative, as it does not capture the value unsafe WASH at the country level. Table 3.2.1. shows of medical and transport cost, pain and suffering asso- the coastal population in urban and rural areas and the ciated with the burden of water-borne diseases. Accord- available WASH risk factors for water-borne diseases. It ingly, the cost related to water-borne diseases is estimated is important to note that in the four countries, access to between US$27 million in Togo and US$450 mil- improved WASH is substantially higher in urban com- lion in Côte d’Ivoire. tying and transport of excreta for treatment and eventual discharge or reuse; 29 For example, data for Benin show differences in improved access to water (81 and hygiene refers to the conditions and practices that help maintain health and percent for urban vs. 71 percent for rural), sanitation (59 percent for urban vs. prevent spread of disease including handwashing, menstrual hygiene manage- 15 percent for rural) and hygiene (30 percent for urban vs. 21 percent for rural) ment and food hygiene. (https://washdata.org/data/household#!/ben). The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 17 3.2.3 UNTREATED WASTEWATER (WTP measures), actual damages to productivity (e.g. due to irrigation with wastewater of insufficient quality), or Untreated domestic, agricultural and industrial waste- cost of wastewater treatment (UNEP, 2015). Examples of water pollutes the environment and affects the carry- studies estimating the society’s WTP for wastewater treat- ing capacity of the marine environment, notably lakes, ment provide annual WTP of US$53 per household in lagoons and the sea. Due to limited data availability, this Hanoi, Vietnam (Trang et al., 2018); US$10 per house- section only estimates the impact of untreated domestic hold in Nairobi, Kenya (Ndunda and Mungatana, 2013) wastewater on the environment in urban and rural coastal and US$1.3 per household in Chandernagore munici- areas. pality, located on the banks of the River Ganga in India (Birol and Das, 2010). The wide range of estimates illus- Table 3.2.2 presents the calculations. For both urban and trates the difficulty of transferring them to our analysis. rural areas, the quantity of untreated domestic waste- Accordingly, we prefer to use an estimate based on the water is estimated as the difference between: the total local cost of treating wastewater. This was valued at about quantity of wastewater, derived from the average water US$0.32/m3, based on Dodane et al. (2012), adjusted to consumption per capita and coastal population; and the 2017. The estimate is similar to the unit cost of treating treated wastewater quantity, estimated based on the share domestic wastewater in Morocco (Khattabi and Croitoru, of population using safely managed sanitation services.30 2015). Accordingly, the cost of untreated domestic waste- water varies between US$8 million in Benin to US$41 The economic value of wastewater can be estimated million in Senegal. through the benefits of improved wastewater treatment TABLE 3.2.2: COST OF UNTREATED DOMESTIC WASTEWATER Category Unit Benin Côte d’Ivoire Senegal Togo Amount of water consumed liters/capita/day 38 37 59 40 Urban Quantity of wastewater generated million m3/year 24 62 105 25 Quantity of treated wastewater million m3/year 0.1 0 25 0 Quantity of untreated wastewater million m3/year 24 62 80 25 from urban area (1) Rural Quantity of wastewater generated million m3/year 1 49 63 4 Quantity of treated wastewater million m3/year 0 0 14 0 Quantity of untreated wastewater million m3/year 1 49 49 4 from rural area (2) Total Estimated untreated wastewater from million m3/year 26 111 129 29 coastal area (1 + 2) Average cost of wastewater treatment US$/m3 0.3 0.3 0.3 0.3 Cost of untreated domestic US$ million 8 35 41 9 wastewater Source: https://data.worldbank.org and Dodane (2012). Figures may not add exactly due to rounding. 30 “Safely managed sanitation” is defined as the use of an improved sanitation facility which is not shared with other households and where : (i) excreta is safely disposed in situ or (ii) excreta is transported and treated off-site (https://www. who.int/water_sanitation_health/monitoring/coverage/explanatorynote-sdg- 621-safelymanagedsanitationsServices161027.pdf ?ua=1 ). 18 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo TABLE 3.2.3: COST OF COASTAL WATER DEGRADATION, 2017 Benin Côte d’Ivoire Senegal Togo Water-borne diseases (US$ million) 44 450 334 27 Untreated wastewater (US$ million) 8 35 41 9 Total (US$ million) 53 485 375 36 Total (% of GDP) 0.6% 1.2% 2.3% 0.7% 3.2.4 CONCLUSIONS BOX 3.3.1: E-WASTE AND PLASTICS ARE The total cost due to water degradation is estimated GROWING CONCERNS IN WEST AFRICA between US$36 million in Togo and US$485 million in E-waste. The rapid growth of information technology Côte d’Ivoire (Table 3.2.3). When aggregated across coun- and communication has brought many socio-economic tries, the cost of water degradation along the coastal areas benefits, but it has also caused environmental problems related to electronic waste, or e-waste. E-waste contains a amounts to US$949 million, which is equivalent to variety of substances that are toxic to human and environ- 1.3% percent of the four countries GDP in 2017. mental health, such as brominated flame retardants, heavy metals (e.g., lead, nickel, chromium, mercury), and per- As noted earlier, this analysis is limited to only a few cat- sistent organic pollutants (e.g., polychlorinated biphenyls, egories for which data was available. Multiple aspects such PCBs). Ghana, Kenya, and Nigeria have the highest levels as: ballast water and oil spills, untreated industrial waste- of e-waste in the Sub-Saharan Africa. In Senegal, inappro- water, agricultural seepage and waste leachate were not priate e-waste management has caused severe health prob- lems in recycling sites around Dakar, e.g. 10,000 cases of quantified. As a result, the above estimates represent an lead poisoning due to discharge of used batteries in Thiar- underestimate of the true cost of water degradation in oye sur Mer; 745 cases of tuberculosis and fatal respiratory the coastal area. failure in Mbeubeusse; and multiple cases of dioxin and lead poisoning in Colobane. E-waste production in West 3.3. WASTE Africa countries is steadily increasing,1 calling for a special- ized management system to be put in place. Waste management is a complex challenge, as it relates Plastic. With increased urbanization and economic to a wide range of wastes, which require distinct ways of growth, Africa is developing large consumer markets for plastic goods and plastic packages. Inadequate waste man- handling: municipal, medical, industrial, transport, agri- agement around river basins—such as the Niger, Congo, cultural, construction, demolition waste, etc. Inappro- and Senegal rivers—also means that these rivers are likely priate management of these wastes can result in serious to transport a large quantity of land-based waste, including consequences. In coastal and marine areas, it can cause plastic pollution, as they make their way to the ocean. Sen- problems such as deterioration of marine water qual- egal, Gambia, Côte d’Ivoire, and Nigeria have high levels ity, reduced tourism opportunities, fish contamination, of mismanaged plastic waste in Africa, of more than 0.8 groundwater pollution, and sometimes human deaths. kg per person per day. In many countries of the region, more than 80 percent of plastic waste is inadequately dis- Moreover, the problem of inappropriate waste manage- posed of. This has multiple impacts: when discarded plastic ment has recently become even more acute at the global bags fill with rainwater, they can attract malaria-carrying level, due to growing concerns related to other types of mosquitoes; when they are dumped, they can choke and waste, such as plastic and e-waste. These waste streams kill marine life and livestock;2 plastic trash can block storm pose increasing challenges also in West Africa, where (continued) countries typically do not have the resources or infrastruc- 1 In Côte d’Ivoire, e-waste production has almost doubled from 7,400 ture to manage them (Box 3.3.1). tons in 2010 to an estimated 14,000 tons in 2019. 2 An estimated 70 percent of cattle and sheep deaths in Nouakchott, Mauritania, are from ingesting plastic bags. https://earthpolicyinstitute. This section estimates the cost of degradation associ- wordpress.com/page/2/ ated with insufficient or inadequate municipal waste The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 19 improved waste collection in Africa, with varying results: drains and cause flooding—a devastating 2015 flood in US$3.1 per capita to improve solid waste management Ghana caused by plastic-blocked drains killed 150 people.3 The harmful effects of plastics continue as they photo- in Mekele City, Ethiopia (Hagos et al., 2012); US$2.7 degrade: microplastics have been found in tap and bottled per capita to improve solid waste collection in Kampala water, milk, fish and other food—as well as in human city, Uganda (Banga et al., 2011); US$0.9 per capita to stool—thus posing toxicity risks to the global food chain improve solid waste collection in Akinyele Local Govern- and to human health. ment, Nigeria (Olojede and Adelayo, 2014). Despite the Sources: World Bank (2015c); World Bank (2014a and b); Jambeck et al. available examples, it is difficult to transfer these estimates (2018); Andrady (2011); Kosuth et al. (2018); Schwabl et al. (2018). to the four countries, due to differences in geographical, environmental and socio-economic situations. Thus, the 3 https://www.plasticpollutioncoalition.org/pft/2017/4/11/how-coun- valuation uses the World Bank benchmark of 1.25 per- tries-in-africa-are-winning-the-fight-against-plastic-pollution cent (1 to 1.5 percent) of the annual disposable income as a proxy for the people’ WTP for improved collection (Raich, 2009). collection and inappropriate disposal on the coast. Due to data limitations, it does not tackle: the impacts of coastal Based on the proportion of population not covered by the and marine waste on the tourism industry; the untreated service, and 1.25 percent of their disposable annual income, leachate that could contaminate water bodies; the lost the cost of municipal waste collection in urban and rural opportunity of collecting and reusing recyclables and of areas is estimated to vary from about US$7 million in capturing methane and generating energy from landfill,31 Benin to US$63 million in Senegal. and the effects of waste other than municipal waste.32 3.3.2 MUNICIPAL WASTE DISPOSAL 3.3.1 UNCOLLECTED MUNICIPAL WASTE Inappropriate disposal of municipal waste can result in Insufficient collection of municipal waste on West African many negative externalities, such as groundwater pollu- coastal areas is a major challenge, leading to bad odors, tion, air pollution and depreciation of the value of land pollution of environment (e.g. water) and potential health and houses surrounding the unsanitary landfills. This sec- problems. In the four countries, lack of municipal waste tion estimates the impacts of unsanitary landfills located collection affects 36-60 percent of urban coastal popu- close to the countries’ capitals on the value of land. lation and 55–85 percent of the rural one (Table 3.3.1). It focuses only on the large disposal sites, and does not This section focuses on the cost of insufficient collection address the effects of small dumps on rural coastal areas. of municipal waste in the four countries’ coastal urban and rural areas. The estimation is based on hedonic pricing, by compar- ing the average land prices in similar urban or peri-urban Valuing the cost of insufficient municipal waste collec- locations with those around the landfills. Usually, a prop- tion is based on the society’s willingness to pay (WTP) for erty has a collection of attributes: physical characteristics improving waste collection. Contingent Valuation Method (e.g. surface, construction material, etc.), location (e.g. has been often applied to estimate the people’s WTP for proximity to businesses, schools, hospitals, etc.), and other environmental features (e.g. clean air, nice view). The price of the property depends on the levels of its attributes. If 31 When municipal waste is not collected appropriately, it is common practice to burn it in the street to get rid of it, which causes air pollution—this is cap- the quality of the environment surrounding the property tured under the air section. declines, the value of the property is also expected to 32 Medical waste, industrial waste, transport waste (boats, trains and planes), decrease. agricultural waste, slaughterhouse waste, construction and demolition waste, tires, oils, hazardous waste, e-waste, ash and sludge should receive specific forms We estimate the impact of unsanitary landfills through the of treatment, but due to poor management, regulation, and enforcement, often find their way into the formal and informal municipal waste streams. depreciation of land value in areas located in the proxim- 20 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo TABLE 3.3.1: COST OF UNCOLLECTED MUNICIPAL WASTE ON THE COAST Category Unit Benin Côte d’Ivoire Senegal Togo Urban Urban coastal population million 1.79 4.57 4.89 1.71 - of which, without service % 50 52 60 36 Disposable income in urban areas US$/capita 578 810 1,387 1,043 - of which WTP for improved collection % 1.25 1.25 1.25 1.25 Cost of uncollected urban waste (1) US$ million 6.4 24.0 50.8 8.0 Rural Rural coastal population million 0.09 3.60 2.95 0.26 - of which, without service % 85 65 72 55 Disposable income in rural areas US$/capita 272 553 459 482 - of which WTP for improved collection % 1.25 1.25 1.25 1.25 Cost of uncollected rural waste (2) US$ million 0.3 16.2 12.1 0.9 Total cost (1 + 2) US$ million 6.7 40.2 62.9 8.9 Sources: IIS (2015); INSEED (2017); IMF (2017); IMF (2018); World Bank (2018b); World Bank (2018c) and Raich (2009). ity of the landfills.33 Banna and Asermet (2018) study in FIGURE 3.3.1: LAND DEPRECIATION Senegal assessed the level of depreciation of such areas, ASSOCIATED WITH WASTE DISPOSAL based on their distance to landfills: 15 percent deprecia- tion in land prices in the areas located within a radius up to 30 meters around the disposal sites (considered to have A2 a view on the sites); and 10 percent depreciation within a second radius from 30 to 100 meters (Figure 3.3.1). A1 Table 3.3.2 illustrates the surface of each selected landfill, R1 = 30m at 15% Dump area A1 (within 30 m radius), and area A2 (within 30–100 m radius) (columns 2–4). It also estimates the losses of R2 = 70m at 10% land value, based on the above depreciation parameters applied to the average urban prices of each location (col- umns 5–7). Accordingly, the total cost of inappropriate waste disposal is valued between US$13 million in Côte d’Ivoire to US$27 million in Senegal. Source: Adapted from Banna et Ansermet (2018). 3.3.3 CONCLUSIONS estimated at about US$192 million, or 0.3 percent The total cost due to waste mismanagement is estimated of the four countries’ GDP. In absolute terms, the great- between US$20 million in Benin and US$90 million in est cost accrues to Senegal, particularly due to the high Senegal (Table 3.3.3). proportion of population not receiving municipal waste collection (60 percent in urban and 72 percent in rural Overall, the insufficient collection and inappropriate areas) and to the impacts of the unsanitary landfill close to disposal of municipal waste generates an economic cost Dakar. Côte d’Ivoire also contributes significantly to this cost mainly because of a large population exposed to low collection coverage. 33 Linear distance is the most common measure of proximity (Chèze, 2008). The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 21 TABLE 3.3.2: COST OF MUNICIPAL WASTE DISPOSAL ON THE COAST Loss in land Loss in land Landfill Area (A1) Area (A2) value (A1) value (A2) Total loss Landfill name area (m2) (m2) (m2) (million US$) (million US$) (million US$) Benin - Cotonou Ouesse 800,000 97,900 250,500 2.9 5.0 7.9 - Porto-Novo Takon 400,000 70,100 169,700 2.1 3.4 5.4 Sub-total Benin 13.3 Côte d’Ivoire - Cocody Akouedo 1,000,000 109,200 276,700 2.8 4.8 7.6 - Abidjan Kossihouen 33,000 22,100 73,700 1.7 3.8 5.5 Sub-total Côte d’Ivoire 13.2 Senegal - Dakar Sindia 1,040,000 111,300 281,600 8.7 14.6 23.3 - Saint Louis 25,000 44,600 112,500 0.7 1.5 2.2 - Thies 12,000 14,500 55,800 0.5 1.3 1.7 Sub-total Senegal 27.2 Togo - Lomé Akepe 800,000 97,900 250,500 7.0 12.0 19.0 Sub-total Togo 19.0 Sources: Banna et Ansermet (2018); Brisoux and Elgorriaga (2018); Rodrigue et al. (2018); and World Bank (2018b). As previously noted, these figures cover only a part of emissions from dumps), and the impacts of other types the impacts of municipal waste mismanagement in these of waste (e.g. e-waste, micro-plastics, etc.), the final results countries. As they do not include other effects related to underestimate substantially the true cost of waste man- municipal waste (e.g. groundwater pollution, methane agement in the four countries.34 TABLE 3.3.3:  COST OF MUNICIPAL WASTE MISMANAGEMENT ON THE COAST, 2017 Type of cost Benin Côte d’Ivoire Senegal Togo Uncollected waste (US$ million) 7 40 63 9 Waste disposal (US$ million) 13 13 27 19 Total (US$ million) 20 53 90 28 Total (% of GDP) 0.2% 0.1% 0.6% 0.6% 34 Better waste management could help increase coastal tourism, as Benin, Côte d’Ivoire and Senegal have signed the Charte africaine du tourisme durable et responsable at the COP22 in Marrakech in November 2016 (AfDB, https://www.afdb.org/en/news-and-events/la-charte-africaine-du-tourisme-durable-et-responsable-voit-le-jour- a-la-cop22-a-marrakech-16562/) 22 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo Photo Credit: World Bank/Vincent Tremeau. Photo Credit: World Bank/Vincent Tremeau. 24 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo CHAPTER FOUR FLOODING AND EROSION 4.1. FLOODING Globally, the shocks most frequently reported are natural hazards, especially floods. Immediate impacts of flooding include loss or damage to property, loss of human life, destruction of crops, and deterioration of health conditions owing to waterborne diseases. As communication links and infrastructure such as power plants, roads and bridges are damaged and disrupted, some economic activities may come to a standstill, people are forced to leave their homes and normal life is disrupted35. Coastal low- lying areas are prone to natural flooding. Coastal flood-prone areas are dynamic, as daily erosion and accretion affect the contours of the coast, which are exacerbated by human activities through land use and land cover. West African countries are severely affected by floods. Flood frequency has increased in the past 50 years and are expected to increase in the future (Niang et al., 2014). This section estimates in monetary terms the impacts of floods in Benin, Côte d’Ivoire, Sen- egal and Togo. It focuses on fluvial and pluvial floods in coastal areas. Fluvial floods occur when rivers burst their banks as a result of sustained or intense rainfall. Pluvial floods occur when heavy precipitation saturates drainage systems, particularly in flat and urban areas. Coastal flooding caused by seawater is not included in the analysis, due to data limitations36. 4.1.1. COST OF COASTAL FLOODING When translated into socioeconomic and environmental terms, coastal floods affect livelihoods (forgone economic activity), public and private assets (infrastructure, busi- nesses and properties), welfare (injuries, drowning, psycho-physical stress, migration, coping, social dislocation, etc.) and ecosystem services. In this study, we address the 35 Queensland Government (2011), Understanding Floods: Questions and Answers, July 2011.Link: https://www. chiefscientist.qld.gov.au/publications/understanding-floods/flood-consequences/ (retrieved on March 1, 2019). 36 Available modelling exercises are mostly relevant for long-term planning. The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 25 MAP 4.1.1: FLUVIAL FLOODING FOR 1/10 YEARS RETURN PERIOD BY COUNTRY Senegal Côte d’Ivoire Togo and Benin Source: SSBN Global Flood Hazard Model. impact of fluvial and pluvial flooding according to three and 1-in-100 years)37. Model inputs include past floods, main categories: forgone economic activity, damage to precipitation, as well as geographic characteristics to assets, and mortality. The estimation is conducted in three model future floods.38 Map 3.1.1 shows the estimated flu- steps, presented below. vial flood for 1/10 years return period by country and its corresponding flooded area. Step 1. Measure flood areas. The flooded area in coastal districts was calculated based on the results 37 Flooding could be measured in terms of speed (extraordinary event catching of SSBN Global Flood Hazard Model applied to West the population off-guard or natural event that determines the rapidity of the Africa. These results show the maximum expected water flooding phenomena), duration (number of days) and depth (water level rise depth for fluvial and pluvial floods and its corresponding that will determine the affected coastal area given the morphology of the area). surface for six different return periods (between 1-in-5 This exercise is based on the latter approach. 38 Information on past flood events for West Africa is limited and biased toward extreme events. 26 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo TABLE 4.1.1:  DAMAGE FUNCTION BY WATER TABLE 4.1.3: UNIT COST PER LAND USE DEPTH (US$/HA) Water depth (meters) Damage function (%) Urban Rural 0 0 Benin 190,100 11,700 0.5 0.22 Côte d’Ivoire 347,800 23,900 1 0.38 Senegal 260,700 12,800 1.5 0.53 Togo 96,000 11,500 2 0.64 Sources: Adapted from IMDC (2018a, b, c) and World Bank estimates. 3 0.82 4 0.9 5 0.96 6 1 Step 3. Quantify flood impacts. The impacts of Source: Huizinga et al. (2017). floods are estimated in terms of damages to assets and economic production; and cost of mortality. Each return period informs about the probability of flood The damages to assets and economic production are estimated occurrence. For instance, a 20-year return period event based on the flooded area (derived from Step 1), the dam- indicates a 5 percent chance of occurrence per year, while age function (derived from Step 2) and the unit value of a 100-year return period suggests a 1 percent chance of land. The latter was derived by IMDC (2018a, b and c) occurrence per year. By combining the probability of for a one-hectare grid cell for Benin, Côte d’Ivoire and flood occurrence with the associated affected areas, we Togo. It was obtained by combining the value of eco- estimate the total flooded areas for each return period, nomic flows (i.e., GDP per hectare, based on the value- for a typical year. These areas are then classified into rural added per employee per hectare) with that of stocks (i.e., and urban areas. About 99 percent of the flood events value of assets per hectare) for one year. We applied a occur in rural areas. similar approach for Senegal. Table 4.1.2 shows the dis- tribution of the economic flows and stocks for urban and Step 2. Translate flood events into asset losses. rural land. In rural areas, stock values are more impor- Not all flood events are severe floods. Flood water depth tant than flow values (82 percent vs. 18 percent); while and its corresponding area are translated into losses, using in urban areas, flow values are slightly higher than stock flood damage functions. To reflect the damage functions values (58 percent vs. 42 percent). for West African countries, we use Huizinga et al. (2017), who conducted a review of worldwide literature on flood Based on the above distribution, Table 4.1.3 estimates the damage functions. Table 4.1.1 shows these damage func- unit value of land for the four countries. These values are tions, according to water depth. used to estimate the damages to assets and economic pro- duction due to fluvial and pluvial floods, and the results are reported in Table 4.1.4. TABLE 4.1.2:  DISTRIBUTION OF FLOW AND STOCK PER LAND USE PER YEAR (PERCENTAGE) Rural/Urban Flow/Stock Côte d’Ivoire Benin Togo Senegal Average Rural Flow 15 19 26 12 18 Stock 85 81 74 88 82 Urban Flow 59 53 63 57 58 Stock 41 47 37 43 42 Sources: IMDC (2018a,b,c) and World Bank estimates. The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 27 TABLE 4.1.4: ECONOMIC COST OF FLOODING ON THE COAST, 2017 Benin Côte d’Ivoire Senegal Togo Damages* due to pluvial floods (US$ million) 9 760 77 4 Damages* due to fluvial floods (US$ million) 18 398 134 5 Mortality due to pluvial and fluvial floods (US$ million) 3 25 20 2 Total (US$ million) 29 1,183 230 10 Total (% of GDP) 0.3% 2.9% 1.4% 0.2% Source: World Bank estimates. Note: * Refers to damages to assets and economic production. Cost of mortality. Following IMDC (2018a, b, c), there are concentration of economic activity39, and sea level rise. 0.16 expected deaths per 1000 people exposed, based on This section estimates in monetary terms the impact of the average number of deaths in the floods of 2009 and erosion on the four countries’ coastal areas. 2010 in Togo (0.25) and Benin (0.07). We use this damage function to estimate the number of victims from coastal 4.2.1. COST OF EROSION floods in the four countries. Accordingly, the total number of deaths is estimated at 640 per year, on average. Similar The valuation of the cost of erosion assumes that the land, to chapter 3.1, the cost of mortality is estimated based on assets, and economic flows are lost in the long run. The the VSL, which reflects the society’s WTP to reduce the estimation is conducted in three steps, presented below. risk of death. The results are presented in Table 4.1.4. Step 1. Estimate the erosion rate. The eroded area 4.1.2. CONCLUSIONS is estimated as an annual average value of land area lost to erosion, based on a study which quantified the change in Adding up the damages to assets, economic production shoreline over 1984–2016, by comparing cloud-free his- and mortality, the total cost of floods in coastal districts is torical Landsat images with resolution of 30 m (Luijendijk estimated between US$10 million in Togo to US$1.2 bil- et al., 2018)40. For each 500 m transect, the authors com- lion in Côte d’Ivoire. This corresponds to a range between puted the rates of shoreline change (m/year) by applying 0.2 percent and 2.9 percent of the countries’ GDP (Table linear regression to all shoreline positions at that location. 4.1.4). Each country is subject to land erosion. However, the Overall, damages due to flooding account for US$1.45 coastline is differently affected. Map 4.2.1 shows for each billion, or 2.1 percent of the four countries’ GDP. country the level of erosion and its heterogeneity from a location to another. Some areas have no erosion at all, others have lost land (erosion) and some have gained land 4.2. EROSION (accretion). Table 4.2.1 estimates the long-term erosion rates only for areas subject to land loss (500 m spaced Coastal erosion is a major environmental problem transects). Column 2 provides the average erosion rates, throughout West Africa. Globally, 24 percent of coastal expressed in m/year. As noted in the table, average ero- areas are eroding at rates exceeding 0.5 m per year (Lui- sion rates, per transect, are much higher in Benin (nearly jendijk et al., 2018). As a result, trees and infrastructure 4 meters/year) and Togo (2.4 meters/year) compared to have been disappearing gradually; towns and villages Côte d’Ivoire (1.4 meters/year) and Senegal (1.6 meters/ located close to the shoreline, where most of the eco- nomic activity takes place, are likewise threatened. West 39 Coastal areas are home to most capitals, major industries, including agro- African coastal areas are further exposed to erosion due to industry, fisheries, offshore petroleum exploration and production, and tourism. higher population growth and migration to coastal areas, 40 Luijendijk et al. (2018) is the only study that measure erosion globally, allow- ing cross-country comparisons. 28 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo MAP 4.2.1: LONG-TERM AVERAGE EROSION RATE (1984–2016) BY COUNTRY Senegal Côte d’Ivoire Togo and Benin Source: SSBN Global Flood Hazard Model. TABLE 4.2.1: LONG-TERM EROSION RATE (1984–2016) % of coastline subject Long-term Erosion Rate Country to erosion Average (m/year) Total (ha/year) Benin 65 –4.06 –29.0 Côte d’Ivoire 47 –1.40 –33.4 Senegal 65 –1.60 –50.6 Togo 52 –2.40 –7.8 Source: Luijendijk et al. (2018) The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo 29 year). Column 3 indicates that total eroded area varies TABLE 4.2.2:  UNIT PRICE OF LAND (US$/M2) from 8 ha (Togo) to 50 ha (Senegal) on average. We use Urban Rural these estimates in the next steps of the valuation. Benin 200 5 Côte d’Ivoire 200 50 Step 2. Classify the eroded land into urban and Senegal 515 20 rural areas. Urban land has higher intrinsic economic Togo 460 15 value than rural land, and not all coastal areas are urban- Source: World Bank Estimates. ized. We divide the eroded coastal land into urban and rural areas, using the land cover classification of the Euro- pean Space Agency’s Global Land Cover database41, and To estimate the value of bare land in coastal areas, we the European Commission’s definition of urban areas (i.e. conducted a rapid assessment of coastal land prices in the areas with population greater than 300 people per km2). four countries. Table 4.2.2 shows the results. The value of Accordingly, coastal urban land is predominant in Togo bare land is estimated as a PV of annual rents for the next (70 percent), compared to the other three countries: Benin 30 years, based on the following assumptions: a rent-to- (16 percent), Côte d’Ivoire (2 percent) and Senegal (17 price ratio of 8 percent42; an average annual increase of percent). 8 percent of urban land value and of 5 percent of rural land value43; a 3 percent annual increase of GDP; and Step 3. Estimate the impacts of erosion. Similar to annual growth of urbanization for the period 2014–2050, the estimation of flood damages (chapter 4.1), we use the as estimated by the United Nations44; and a discount rate annual value of land per hectare also to estimate the cost of 3 percent, to account for the high importance of the of erosion. It should be noted that the flooding valuation erosion impacts in the future. focuses on what is on the land, without considering the value of the land itself. However, this section includes also 4.2.2. CONCLUSIONS the value of bare land, considering that it is lost perma- nently. Thus, the cost of erosion captures: (i) the value of The total cost of erosion is estimated between US$97 lost assets (e.g. buildings, roads, other infrastructure); (ii) million in Côte d’Ivoire and US$537 million in Senegal the PV of economic flows during the next 30 years; and (Table 4.2.3). Overall, the cost of erosion in the four coun- (iii) the value of bare land. tries is US$964 million, or 1.4 percent of their GDP. TABLE 4.2.3: ECONOMIC COSTS ASSOCIATED WITH EROSION, 2017 Benin Côte d’Ivoire Senegal Togo Assets lost (US$ million) 1 1 1 0.2 Production lost* (US$ million) 35 16 103 25 Land lost (US$ million) 81 80 432 188 Total (million US$) 117 97 537 213 Total (% of GDP) 1.3% 0.2% 3.3% 4.4% Source: World Bank estimates. *Analysis based on 30-year return. 42 This value corresponds to one of the lowest in the US (see, e.g., here https:// smartasset.com/mortgage/price-to-rent-ratio-in-us-cities) and half of the ratio in a South American developing country, like Peru (BCRP, 2018). 43 While there is no systematic data on these values, in Peru it is estimated the annual increase in urban land in 9 percent (BCRP, 2018). 41 Link: https://www.esa-landcover-cci.org/ 44 United Nations (2014). World Urbanization Prospects: The 2014 Revision. 30 The Cost of Coastal Zone Degradation in West Africa: Benin, Côte D’Ivoire, Senegal and Togo Photo Credit: World Bank/Vincent Tremeau. 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