52906 Urban Air Quality Management Strategy in Asia Kathmandu Valley Report October 1996 ~ Metropolitan Environmental Improvement Program A World Bank Initiative URBAIR URBAN AIR QUALITY MANAGEMENT STRATEGY IN ASIA KATHMANDU VALLEY REpORT Prepared by: Knut Erik Gronskei, Frederick Gram, Leif Otto Hagen, and Steinar Larssen, Norwegian Institute for Air Research, Kjeller, Norway Huib Jansen and Xander Olsthoorn, Instituut voor Milieuvraagstukken (IVM), Vrije Universiteit, Amsterdam, the Netherlands Anil S. Giri Royal Nepal Academy of Science and Technology (RONAST) Kathmandu, Nepal Madan L. Shrestha Dpt. of Hydrology and Meteorology, Min. of Water Resources, Kathmandu, Nepal Bimala Shrestha Tribhuvan University, Kathmandu, Nepal Edited by: Jitendra Shah and Tanvi Nagpal The World Bank, Washington, DC to 1997, The International Bank of Reconstruction and Development/THE WORLD BANK 18]8 H Street, N.W. Washington, D,C. 20433 U.S.A. All rights reserved Printed in the United States of America First printing February] 997 The findings, interpretations, and conclusions expressed in this study are entirely those of the authors of this study and should not be attributed in any manner to the World Bank, to its affiliated organizations, or to members of its Board of Executive Directors or the countries they represent. The World Bank does not guarantee the accuracy of the data included in this publication and accepts no responsibility whatsoever for any consequence of its use. Any maps that accompany the text have been prepared solely for the convenience of the readers; the designations and presentation of material in them does not imply the expression of any opinion whatsoever on the part of the World Bank, its affiliates, or its Board or member countries concerning the legal status of any country, territory, city, or area or of the authorities thereof or concerning the delimitation or its national affiliation. Likewise, the material in this report should not be attributed in any manner whatsoever to governments, non-governmental organizations, any other institutions or individuals who participated in the URBAIR studies and related workshops and meetings. The cover design is by Beni Chibber-Rao, Graphic and Map Design, General Services Department, The World Bank. The layout is by Julia Lutz, Environment and Natural Resources Division, Asia Technical Department, The World Bank. ENVIRONMENT PROTECTION COUNCIL URBAN ENVIRONMENT MANAGEMENT COMMITTEE Foreword Many Asian cities are on the threshold of a major environmental crisis in the form of air pollution. The deteriorating air quality in cities is a result of rapid economic expansion, rise in population, increased industrial output and unprecedented growth in numbers of passenger vehicles. The impacts of air pollution are well known: adverse health effects, rising health costs, damage to ecological and cultural properties, deterioration of built environment. In Kathmandu Valley cities, the main contributor of air pollution comes from the transport sector, followed by power plants, industrial units and burning of garbage. Fuel quality and engine conditions significantly influence the' level of air pollution. To arrest this growing problem, a concerted effort with public involvement is essential. Awareness of the issue, proactive policies, economically affordable standards and technologies and effective enforcement are key elements in an air quality management strategy. A long- run perspective shows that early adoption of policies for environmentally safer technologies can allow developing countries to resolve some of the most difficult problems of industrialization and growth at lower human and economic cost. Kathmandu Valley cities joined the World Bank-executed Metropolitan Environmental Improvement Program (MEIP) in 1993. At the inter-country workshop held in Hawaii in 1990, the cities facing serious air pollution problems sought MEIP intervention to assist in finding solutions. In response to this, l.TRBAIR was conceived and launched in Kathmandu Valley, Nepal in 1993. URBAIR has assisted His Majesty's Government/Nepal, Environment Protection Council, Urban Environment Management Committee to develop a strategy and time- bound action plan for air quality management in Kathmandu Valley. For the first time, it brought together the different stakeholders - sectoral agencies, private sector, NGOs, academics, research bodies and media -- to formulate a strategy. From this group was formed the Technical Committee that deliberated for several months with technical support provided by a team of national and international experts. The outcome is the action plan included in this document. The result is truly impressive and His Majesty's Govemment/Nepal, Environment Protection Council, Urban Environment Management Committee is fuBy committed to the implementation of the plan. We will need the support of the international community in realizing the goals of the plan. I wish to acknowledge with gratitude all those who contributed to the development of the strategy and plan, especially to MEIP for facilitating the process. Umesh Bahadur Malla , Joint Secretary/MHPP Member Secretary Urban Environment Management Committee/EPC Kathmandu, ~epaJ III PARTNERS AND CONTRIBUTORS Many contributed to the URBAIR process. URBAIR core funds were provided by United Nations Development Programme, the Australian International Development Agency, the Royal Norwegian Ministry of Foreign Mfairs, the Norwegian Consultant Trust Funds, and the Netherlands Consultant Trust Funds. Host governments and city administrations provided substantial input City studies were conducted by the Norwegian Institute for Air Research (NILU) and the Institute of Environmental Studies (IES) at the Free University in Amsterdam, with assistance from the selected local consultants: Mr. Anil S. Giri and Mr. Rishi Shah, Royal Nepal Academy of Science and Technology; Dr. Madan L. Shrestha, Department of Hydrology and Meteorology, and Dr. Bimala Shrestha, Tribhuvan University. The city-level technical working groups provided operational support, while the steering committee members gave policy direction to the study team. The National Program Coordinator ofl\.1EIP-Kathmandu, Mr. Guru Bar Singh Thapa, contributed greatly to the successful outcomes. At the World Bank, URBAIR was managed by litendra Shah and Katsunori Suzuki, and under the advice and guidance of Maritta Koch-Weser and David Williams. Colleagues from the World Bank Country Departments and Resident Mission helped with the program. Tanvi Nagpal was responsible for technical accuracy and editing. Management support was provided by Erika Yanick, Sonia Kapoor and Ronald Waas. Nicole Schofer and Sheldon Lippman provided editorial support. Many international institutions (World Health Organization, United States Environmental Protection Agency, United States Asia Environment Partnership) provided valuable contribution through their participation at the workshops. Their contribution made at the workshop discussions and follow-up correspondence and discussions has been very valuable for the result of the project. The following is a list of individuals, based in Kathmandu, who contributed to the URBAIR process and its outcome. · Mr. Murkesh Bhattarai, Ministry ofIndustry · Mr. M. Dehal, l\1EIPIMHPP · Mr. Surendra R. Devkota, Industrial Pollution Control Project, Ministry ofIndustry · Mr. Anil Shankar Giri, URBAIR Project Incharge, RONAST · Umesh B. MalIa, loint Secretary, MHPPlMember Secretary UEMCIMHPP · Mrs. Sony Pradhan, Field Expert, URBAIR Project, RONAST · Mr. Rishi ShahRONAST-Secretary · Toran Sharma, NESS-Brick Kiln Contribution to Air Quality · Dr. Madan Lal Shrestha, Department of Hydrology and Meteorology · Dr. Bimala Shrestha, Teaching Hospital, Maharajgunj · Rohit Thapa, Vehicle Emission Control Program in the Kathmandu Valley · Dr. S.P. Sagar Thapaliya, Kathmandu Valley Traffic Police IV ABBREVIATIONS AND ACRONYMS ADT average daily traffic NIEMP National Industrial Energy AQG air quality guidelines Management Program AQMS air quality management system NOx nitrogen oxide CO carbon monoxide NPC National Planning Commission EIA environmental impact assessment PAH polycyclic aromatic hydrocarbons ENPHO Environment and Public Health Pb lead Organization PM10 particulate matter of 10 microns EPC Environmental Protection or less Council ppb parts per billion ERV emergency room visits RAD restricted activity days gil grams per liter RHA respiratory hospital admission GDP gross domestic product RHD respiratory hospital diseases GNP gross national product RON research octane number H hypertension RON SAT Royal Nepal Academy of Science H2S hydrogen sulfide and Technology HC hydrocarbon RSD respiratory symptom days HMG His Majesty's Government SKO kerosene IES Institute for Environmental S02 sulfur dioxide Studies, Amsterdam S04 sulfate IPCR Industrial Pollution Control TSP total suspended particles Regulation UNDP United Nations Development KVVEPC Kathmandu Valley Vehicle Programme Emission Control Project UNEP United Nations Environment LDO light diesel oil Programme LPG liquefied petroleum gas URBAIR Urban Air Quality Management J.lg microgram (10.6 grams) Strategy in Asia mg milligrams (l0·3 grams) USAID United States Agency for 3 particulate concentration in International Development Ilg/m micrograms per cubic meters VOC volatile organic compounds MEIP Metropolitan Environmental VSL value of statistical life Improvement Program WHO World Health Organization MTBE methyl-tertial-butyl-ether WTP willingness to pay NILU Norwegian Institute for Air Research, Kjeller, Norway Note: Except as indicated, "dollars" NGO non-governmental organization refers to 1992/93 U.S. dollars. NH3 ammoma v TABLE OF CONTENTS FOREWORD ............................................................................................................................. iii PARTNERS AND CONTRIBUTORS ..·.·..·..······································.··········.························· iv ABBREVIATIONS AND ACRONYMS ................................................................................... v PREFACE.....··..······.........................................·......··................................................................ ix EXECUTIVE S UMM.ARY ..........................·······..........................···..·............................................................................... 1 1. BACKGROUND IN"FORMATION ...................................................................................... 5 1 1. SCOPE OF THE STUDy........ .... .. ............... ........ .. .. ........ ....... ................ .. .... ........... ... .......... 5 1.2. GENERAL DESCRIPTION OF KATHMANDU VALLEY AND TIlE AIR POLLUTION SITUATION.... 5 1.3. DATA SOURCES ................................................................................................................ 7 1.3.1. Previous studies ..................................................................................................... 7 1.3.2. URBAIR data collection ......................................................................................... 8 1.4. SUMMARY OF DEVELOPMENT IN THE KATIIMANDU VALLEy ............................................. 8 1.5. POPULATION .................................................................................................................. 10 1.6. FUEL CONSlJMPTION ...................................................................................................... 10 1.7. lNJ)USTRIAL DEVELOPMENT............................................................ .................. ........... .. 11 1.8. ROAD VEHICLE FLEET ................................................................................................... 11 2. Am QUALITY ASSESSl\1:ENT .......................................................................................... 12 2.1. AIR POLLUTION CONCENTRATIONS ................................................................................. 12 2.1.1. Air pollution concentrations................................................................................. 13 2.2. AIR POLLUTANT EMlSSIONS IN KATIIMANDU VALLEy ..................................................... 22 2.3. DISPERSION MODEL CALCULATIONS ............................................................................... 26 2.3.1. General description o/topography and climate .................................................... 26 2.3.2. Dispersion Conditions .......................................................................................... 26 2.3.3. Dispersion model calculations, city background................................................... 32 2.3.4. Pollution hot spots................................................................................................ 37 2.3.5. Population exposure to air pollution .................................................................... 37 2.4. SUMMARY OF AIR QUALITY ASSESSMENT, KATIIMANDU VALLEY ................................... 43 2.4.1. Airpollution concentrations ................................................................................. 43 2.4.2. Air pollutant emissions inventory............ .............................................................. 43 2.4.3. Population exposure to air pollutants ................................................................... 44 2.4.4. Visibility reduction ............................................................................................... 44 2.5. IMPROVING AIR QUALITY ASSESSMENT ........................................................................... 44 2.5.1. Main shortcomings and data gaps ........................................................................ 44 VI URBAIR-Kathmandu VIl 3. AIR POLLUTION IMPACTS ............................................................................................. 47 3.1. INTRODucTION .............................................................................................................. 47 3.2. IMPORTANT IMPACTS IN KATIfMANDU VALLEy ......................................................... .47 3.2.1. Mortality............................................................................................................... 48 3.2.2. Illness (morbidity) ................................................................................................. 49 3.3. VALUATION OF HEALm IMPACTS .................................................................................. 50 3.4. REALm IMPACT AND ECONOMIC DAMAGE BY SOURCE CATEGORy ................................. 50 3.5. CONCLUSIONS ............................................................................................................... 51 4. ABATEMENT MEASURES: EFFECTIVENESS AND COSTS ....................................... 53 4.1. INTRODUCTION .............................................................................................................. 53 4.2. TRAFFIC ......................................................................................................................... 53 4.2.1. Implementation ofa scheme for inspection & maintenance ................................... 54 4.2.2. Improvingfoel quality ........................................................................................... 55 4.2.3. Adoption ofclean vehicle emissions standards ...................................................... 57 4.2.4. Improved abatement/other propulsion techniques ................................................. 59 4.2.5. Addressing resuspension ....................................................................................... 59 4.2.6. Improvement oftraffic management ...................................................................... 59 4.2.7. Construction and improvement ofmass-transit systems ......................................... 60 4.3. INDUSTRIAL COMBUSTION (EXCLUDING BRICK MANUFACTURING) ................................... 60 4.4. BRICKMANUFACTh"'RlNG ........................................................... :............................. 60 4.5. DOMESTIC EMISSIONS AND REFUSE BURNING................ ... ..... ...... .. ............................... 61 4.6. CONCLUSIONS................................................................. ...... .... . . ............... .. ........... 61 5. ACTION PLAN .................................................................................................................... 62 5.1. ACTIONS TO IMPROVE AIR QUALITY AND ITS MANAGEMENT ........................................... 62 5. 1. 1. Actions to improve air quality ............................................................................... 62 5.1.2. Actions to improve the Air Quality Management System ....................................... 63 6. EXISTING LAWS AND INSTITUTIONS .......................................................................... 73 6.1. LAWS AND REGULATIONS ON AIR POLLUTION ................................................................. 73 6.2. INSTITUTIONS INvOLVED ................................................................................................ 74 7. REFERENCES ········...·.·············..·......·..·.·..···········..·..··...·..···.·····.·······.··.·..·····.·..........·......·· 76 APPENDIX 1: AIR QUALITY STATUS, KATHMANDU VALLEY APPENDIX 2: AIR QUALITY GUIDELINES APPENDIX 3: EMISSIONS INVENTORY APPENDIX 4: EMISSION FACTORS, PARTICLES APPENDIX 5: SPREADSHEET FOR CALCULATING EFFECTS OF CONTROL MEASURES ON EMISSIONS APPENDIX 6: PROJECT DESCRIPTIONS, LOCAL CONSULTANTS PREFACE In view of the potential environmental consequences of continuing growth of Asian metropolitan areas, the World Bank and United Nations Development Programme (UNDP) launched the Metropolitan Environmental Improvement Program (MEIP) in five Asian metropolitan areas - Beijing, Mumbai (Bombay), Colombo, Jakarta, and Metro Manila. In 1993, the Kathmandu Valley Urban Area joined the intercountry program as the sixth MEIP city. The mission of MEIP is to assist Asian urban areas tackle their rapidly growing environmental problems. Presently, MEIP is supported by the governments of Australia, Netherlands and Belgium. Recognizing the growing severity of air pollution caused by industrial expansion and increasing vehicle population, the World Bank started the Urban Air QualityManagement Strategy (URBAIR) in 1992 as a part of MEIP. The first phase of URBAIR covered four cities - Mumbai (Bombay), Jakarta, Metro Manila and the Kathmandu Valley Urban Area. URBAIR is an international collaborative effort involving governments, academia, international organizations, NGOs, and the private sector. The main objective of URBAIR is to assist local institutions in these cities to develop action plans which would be an integral part of their air quality management system (AQMS) for the metropolitan regions. The approach used to achieve this objective involves the assessment of air quality and environmental damage (e.g. on health, materials), the assessment of control options, and comparison of costs of damage and costs of control options (cost-benefit or cost-effectiveness analysis). From this, an action plan can be set up containing the selected abatement measures for implementation in the short, medium, and long term. The preparation ofthis city-specific report for Kathmandu is based upon the collection of data and specific studies carried out by the local consultants, and upon workshops and fact finding missions carried out in April and December 1993, June 1994 and March 1995. Norwegian Institute for Air Research (NILU) and the Institute for Environmental Studies (IES) prepared first drafts of the report, before the first workshops. These were based on general and city-specific information available from earlier studies. Later draft reports were prepared before the second workshop, with substantial inputs from the local consultants, and assessment of air quality, damage and control options, and cost analysis carried out by NILU and IES. The report concludes with an action plan for air pollution abatement produced by the local working groups as a result of the deliberations and discussions during the second workshop. NILUIIES carried out cost-benefit analysis of some selected abatement measures, showing the economic viability of ma,ny of the technical control options. It is hoped that, based on this preliminary analysis, local institutions will carry out further analysis of data and develop policy plans as well as investment proposals for air quality management in Kathmandu Valley. IX EXECUTIVE SUMMARY URBAIR-KATHMANDU VALLEY: Larger and more diverse cities are a sign of Asia's increasingly dynamic economies. Yet this growth has come at a cost. Swelling urban populations and increased concentration of industry and automotive traffic in and around cities have resulted in severe air pollution. Emissions from automobiles and factories; and domestic heating, cooking, and refuse burning are threatening the well being of city dwellers, imposing not just a direct cost by impacting human health but also threatening long term productivity. Governments, businesses, and communities face the daunting yet urgent task of improving their environment and preventing further air quality deterioration. Urban air quality management strategy or URBAIR aims to assist in the design and implementation of policies, monitoring and management tools to restore air quality in major Asian metropolitan areas. At several workshops and working group meetings, government, industry, local researchers, non-government organizations, international and local experts reviewed air quality data and designed actions plans. These plans take into account economic costs and benefits of air pollution abatement measures. This report focuses on the development of an air quality management system for Kathmandu Valley and the resulting action plan. THE DEVELOPMENT OF KATHMANDU VALLEY AND ITS POLLUTION PROBLEM Kathmandu Valley's population grew by 26 percent from 1970 to 1980, and another 44 percent between 1980 and 1990. In 1992, the popUlation stood at approximately 1,060,000 of which 56 percent was urban. The growth in population has been accompanied by a doubling in the number of vehicles in the past decade. Within the local brick industry, the number of registered kilns has tripled in the last decade. The Rimal Cement Plant is one of the major industrial Figure ES.1: No. ofdays in January with good visibility (>8,000 m) at sources of pollution. given hours ofthe day. (Ref: ML. Shrestha, 1995). 30~------------------------------------------__- , With the growth January in the number of . .'.-_---- --., --;a~iy-70's-\ , .... .- .. vehicles and industrial : 20 expansion, the .. Vl > · consumption of coal ItS · .. o and automotive fuel 10 has increased. Over the period 1980-93, · · . the increase has been _------_ ..... _.. about 150 percent for 6 8 10 12 14 16 18 gasoline, 175 percent Local time 1 2 Executive Summary for motor diesel, 250 percent for kerosene and 580 percent for fuel oil. The per capita fuel consumption in 1993 was about 27 liters of gasoline, 150 liters of motor diesel, 125 liters of kerosene and 20 liters of fuel oil. Atmospheric visibility data from Kathmandu's airport analyzed onwards from 1970 show that there has been a very substantial decrease in the visibility in the Valley since about 1980 (Figure ES.l). The number of days with good visibility (greater than 8,000 meters) around noon has decreased in the winter months from more than 25 days per month in the 1970s to about 5 days per month in 1992/93. The loss of tourism could not be exactly calculated, but is significant. Air pollution measurements show that particulate pollution is the most significant problem in Kathmandu Valley. Total TSP emissions per year amount to 16,500 tons. PM10 emissions are 4,700 tons/year. The main sources of particulate pollution are the brick industry (28% PM lO , 31 % TSP); domestic fuel combustion (25% PMlO , 14% TSP); the Himal Cement Plant (17% PM lO, 36% TSP); vehicle exhaust (12% PM lO , 3.5% TSP) and resuspension of the road dust (9% PM lO, 9% TSP).WHO air quality guidelines Table ES.l: Impacts ofair pollution (PM1 J on mortality (AQG) for TSP and PM lO are often and health and their valuation in Kathmandu Valley substantially exceeded. There have (1990). been measured 24-hour TSP Number of Value (NRs) --~~~~~~~~ Type of health impact cases Specific Total (1,000) concentrations above 800 llg/m3 , Excess mortality 84 340,000 28,644 while the WHO AQG is 150 Chronic bronchitis 506 83,000' 41,988 230 llg/m 3 . Restricted activity days 475,298 56 26,617 For practical and Emergency room visits 1,945 470-720" 1,167 methodological reasons only a Bronchitis in children 4,847 350 1,697 partial assessment and valuation of Asthma 18,863 45-4,170" 11,318 the health impacts due to PM lO was Respiratory symptom days 1,512,689 50 75,634 Respiratory hospital admissions 99 4,160 415 possible (Table ES.l) In monetary Total 209,051 terms the total impact is about Shrestha's estimate is about NRs146,OOO, based on an undiscounted NRs200,000 million. Impact of total amount over 27 years. Discounting with 5% leads to an estimate of lead pollution due to the use of NRs83,OOO. gasoline which contains lead is not ·· 600 used as average in calculations. included. CONCEPT OF AIR QUALITY MANAGEMENT SYSTEM Assessment of pollution and its control form the two prongs of an Air Quality Management System (AQMS). These components are inputs into a cost-benefit analysis. Air Quality Standards or Guidelines, and economic objectives also guide the cost-benefit calculation (See Figure ES.2) An action plan contains the optimum set of abatement and control measures to be enacted in the short, medium, and long term. Successful air quality management requires the establishment of an integrated system for continual air quality monitoring. Such a system involves an inventory of air pollution activities and emissions; monitoring of air pollution and dispersion parameters; calculation of air pollution concentrations, by dispersion models; inventory of population, URBAIR-Kathmandu 3 materials and urban Figure E8.2: Air Quality Management System development; calculation of the effect of abatement and control measures; and Dispersion Monitoring establishment and modeling improvement of air pollution regulations. In order to ensure than an Emissions Air Quality Air pollution AQMS is having the desired impact, it is also necessary to carry out surveillance and monitoring. This requires the Abatement Control Exposure establishment of an Air measures & options assessment . Quality Information System regulations (AQIS) to inform authorities and the general public about the quality of the air and assess results of abatement. This information system should also provide continuous feedback to the abatememt strategy process. ABATEMENT MEASURES AND ACTION PLANS Measures to reduce air pollution in Kathmandu Valley focus on one important source--traffic. Traffic emissions contribute about 20 percent of total PM lO . A reduction in such emissions has a much larger impact in terms of health than a corresponding reduction in emissions from industries or domestic cooking and refuse burning (Table ES.2). While controlling pollution from industries, especially brick kilns and cement plants, has not been discussed at length, it must also be promoted through enforcement and regulation. It is proposed that the following technical and policy measures be given priority. · Address gross polluters. Reinforce the anti-smoke belching program. Existing smoke opacity regulations and overloading of vehicles should be more strictly enforced. The success of this action depends upon the routine maintenance and adjustment of engines. · Improved diesel quaJity. Domestic refineries could be modified to produce low-sulfur diesel (0.2 percent), or it could be imported. Economic instruments such as taxes and subsidies can Table ES.2: Marginal benefitsfrom emissions reduction in different sources. Source Emissions % Change % Change Change in Change in health Marginal (tons) in Emission in Mortality RSD (1,000) damage (NRs thousand) benefits (NRS/kg) Traffic (exhaust) 440 -10 -6 -108 -150,374 341 Resuspension 400 -10 -2 - 35 - 4,903 122 Domestic emissions 1,160 -10 -9 -155 - 21,360 185 Blick (Bull's trench kilns) 1,250 -10 -3 - 57 - 7,832 62 4 Exeultive Summary be used to differentiate fuel price according to quality. · Inspection and maintenance of vehicles. Annual or biannual inspections are necessary to enforce clean vehicle standards. These can be carried out by government or private entities. · Clean vehicle emissions standard: State-of-the-art emissions standards should be set for new gasoline cars, diesel vehicles, and motorcycles. Lead-free gasoline, a requirement for this standard, should be cheaper than leaded gasoline. · Cleaner fuel oil: A reduction in the sulfur content of heavy fuel oil, initially to 2 percent. · Awareness raising: Public awareness and participation are key to bringing about policy change. Widespread environmental education promotes understanding of linkages between pollution and health and encourages public involvement. Private sector participation through innovative schemes like accepting delivery only from trucks that meet government emissions standards; Adopt-a-Street campaigns, and air quality monitoring displays should be encouraged. Media can also participate in awareness raising by disseminating air pollution related data. RECOMMENDATIONS FOR STRENGTHENING AIR QUALITY MONITORING AND INSTITUTIONS It is crucial that a single coordinating institution with a clear mandate and sufficient resources be made responsible for air quality management. Kathmandu Valley presently lacks an ongoing air quality monitoring program. A comprehensive AQMS can only be designed on sound knowledge. In order to improve air quality data, it is recommended that there be continuous, long-term monitoring in two to five general city sites, one to three traffic exposed sites, and one to five industrial or hot spot sites. Further, an on-line data retrieval system directly linked to a laboratory database either via modem or telephone is recommended for modern surveillance. The determination of population exposure in Kathmandu Valley is based upon a combination of dispersion modeling and pollution measurements. To improve the population exposure calculations beyond what has been developed as part of the first phase of URBAIR for Kathmandu Valley, it is necessary to: · establish dispersion models for the Valley capable of dealing with the complex topographical/temperature/dispersion conditions, in particular dispersion from roads, and · improve the input t.:atabase to such a model, regarding hourly air pollution concentration data, hourly dispersion data, spatial resolution, and hourly emissions data. Prior to 1994, there were no laws pertaining specifically to pollution. An Environmental Protection Council has now been established, together with an Environmental Protection Division that functions within the National Planning Commission. Laws on vehicle pollution control have been proposed according to the recommendations from the Kathmandu Valley Vehicle Emission Control Project (KVVECP). Standards or guidelines for ambient air quality have not yet been passed. The basis for controlling air pollution in Kathmandu Valley needs to be further developed, Clearly, environmental risks are escalating. If pollution sources are allowed to grow unchecked, the economic costs of productivity lost due to health problems will escalate. While working with sparse and often unreliable data, this report sets out a preliminary plan that has the potential of improving the quality of air as well as better managing the air quality monitoring system in the future. 1. BACKGROUND INFORMATION 1.1. SCOPE OF THE STUDY This report on air quality management for the Kathmandu Valley was produced as part of Urban Air Quality Management Strategy in Asia (URBAIR) program. The major objective of URBAIR is to develop Air Quality Management Strategies (AQMS) and action plans for improving air quality in Asia's cities. The AQMS is based on a cost-benefit analysis of proposed actions and measures for air pollution abatement. In general, costs relate to abatement measures, while benefits include a reduction in the estimated costs of health damage resulting from air pollution. This study emphasizes the damage done to the health of those who are exposed to air pollution. Population exposure is based on measured and calculated concentrations of air pollutants, through emissions inventories and dispersion modeling. A general strategy for air quality management is described in the URBAIR Guidebook on Air Quality Management Strategies, published by the World Bank:' s Metropolitan Environmental Improvement Program. Reports based on city-specific analysis have been produced for four URBAIRJMEIP cities: Jakarta, Greater Mumbai (Bombay), Metro Manila, and the Kathmandu Valley urban area. These four reports outline action plans for air quality improvement, including estimated costs and benefits. Action plans are based on comprehensive lists of proposed measures and actions developed by local working groups, in consultation with outside experts. The appendices of the report contain more detailed description of the air quality data, the emissions inventory and emission factors, population exposure calcualtions and local laws and regulations. 1.2. GENERAL DESCRIPTION OF KATHMANDU VALLEY AND THE AIR POLLUTION SITUATION Kathmandu Valley is the administrative, trade and educational center of Nepal, as well as the hub of communications. This densely populated urban area is made up of Kathmandu and Patan. The Bagmati River runs east-west between the two centers. The Tribhuvan International Airport lies just east of this area, which is approximately 7 kilometers in diameter. Villages and housing are scattered outside this area, and the city Bhaktapur is located about 10 kilometers east of Kathmandu City. Figure 1.1 shows the locations of various cities and industrial zones in Kathmandu Valley. Dispersion modeling and population exposure studies were conducted for the area demarcated in this figure. As can be seen, it covers most of the Valley. 5 ~I 0\ ~- · Bull's trench kilns ;: " . . ·,800~_" , ," , ~ 'I '1400 ' .... 160(). .... __ '\ · Hoffmann kilns 20 I i" _ ~ - I ,\'" .. Himal Cement ~ ..... . , ..h. j " .,. ", ,'\ " - : ~ "" "'""V ~.," I / " t····") Industrial areas ' ............. ~ ,,', . \ ... ". '-':.' · Commercial (traffic) sites ::; ... Industrial sites ~ \ ... t I ,\ I\ ",,,, 1BOO." \ '\ \ '" \ f \ -_'" ,. .. Residential sites I::i , i" '--', \1 1', I,: f o Regional background sites ::::: ~ I, " '_'. " ,\61)0 _ I _ '; " , \"' ... "" -"" ~ '-," , 1400 ,, , ... J - \ , " ~ := , 15 ,, ,, ~ ~ , ,, - - ... 1 " '600 ,, \ \ 1400 ,- "'~- ... , .... , ,'~ I::i ~ ...... 1'.... , · · ··· · · ·· \ ~ ..... ··· · , ,- -' I::i , ····· , ~ '''Q:" , ·· \ /'.- _\ ~ 10 ,/ , ,, \ , , I' s. ~ .... '1 , " ' I ,, I ' ....... F \ , := ~ " I '.1600,' \ . . "' . . "J. " -,-<'Cb, ,',"/:, ··· · ,, . ,, ,, "' ""'<'~' , , ,, , " ~ ''''VI', \ "" ... _::~ \ I . . !'".,.,. . . , 1400. ::::: 1'''' -, ,.-~ \ \lQOO \\ I , I ~ , ,, I I , I' \ f~ I ~ "".#,t (' f ........ 1 I , , I I ,, , " \ '---...... " "'... '\ ,- 1600 "I ". .,' ...... , " " I t:!:j ... \ 1',.. .... -, r", _ _ 'I , I _ 1-400 I ...... \ \ " -~, \,,',-' , ~ ~ , , , \ I, , ~ \ i:';" 51;, " \ '" >', " \ \ ... "\ -,..- - -... ... ... ... , < ... I , I " ,I I, , ' \, -' " , --'1"00" \ - 1800 ., (JQ ~F \- .... ~ I I , j \'--' \ ,, (- , 0 '\ \.'): "\ '",_, I "".' \ I ... '" I f f ,, ( " / \ I 1..., ..... - _ .......12000 \ ,, ~ ,, , N = = c.. "\ I I I -,,, ~ t ... 1' ...... ,1 .... "\ ... ...... J J \ = ., """" ( .:: .... - -) ,I I 1- _ , ~ '''00 , , I I , I - , -' 1 , I , "' .... ~I a ~ et_ 0 1 5 = URBAIR-Kathmandu 7 While agricultural activities dominate, substantial parts of the flat valley floor are used for brick production. There are more than a hundred brick production facilities in the Valley, many of them situated in areas immediately south and east of Kathmandu City, within 5 to 10 kilometers of the city's center. Coal and other energy sources are used to fire bricks in these industries, creating significant air polluting emissions. Road traffic is also an important source of air pollution because of exhaust emissions, and the resuspension of particles from dust and refuse on the roads. A substantial portion of the vehicle fleet is in poor condition, overloaded and produces large amounts of visible emissions. Road traffic is quite dense from the city center to the ring road, about 3 kilometers from the center. A cement plant is situated on the banks of the Bagmati river, about 6 kilometers south of the city center. The emissions from this plant affect the air quality in its neighborhood and may contribute to overall air pollution in the city, especially when there are southerly winds during the monsoon season. Domestic emissions from cooking, heating, and refuse burning also contribute to the pollution. In Kathmandu, kerosene and wood are the primary sources of cooking fuel. Kathmandu Valley forms a basin that is approximately 30 by 30 kilometers. It is surrounded by hills that rise 500 to 1,000 meters above the valley floor (approximately 1,300 meters above sea level). Hills completely surround the valley, with the exception of one narrow outlet in the southwest where the Bagmati river flows out of the valley. This bowl-like topography, and generally low wind speeds during the dry (winter) season create poor dispersion conditions, predisposing Kathmandu Valley to serious air pollution problems. Growing populations and an accompanying increase in pollution-generating activities have resulted in a substantial rise in air pollution concentrations in the valley, particularly in the last decade (see Appendix 1 and 2 for details). 1.3. DATA SOURCES 1.3.1. Previous studies There have been no comprehensive studies that describe air quality, pollution sources, emissions and population exposure in Kathmandu Valley. The following publications provided important background information for this report. · Surendra Raj Devkota (1992) Energy Utilization and Air Pollution in Kathmandu Valley, MS Thesis. · Study of Kathmandu Valley Urban Road Development by Japan International Cooperation Agency (IICA, 1992). · Ram M. Shrestha and Sunil MalIa (1993) Energy Use and Emission of Air Pollutants: Case of Kathmandu Valley, Asian Institute of Technology, Bangkok. · HB. Mathur (1993) Final Report on the Kathmandu Valley Vehicular Emission Control Project (KVVECP), HMG/UNDP. · Nepal Environmental and Scientific Services (1995) Assessment of the Applicability of Indian Cleaner Technology for Small Scale Brick Kiln Industries of Kathmandu Valley, Thapathali, Kathmandu. 8 Background Information Presentations at the first URBAIR workshop in Kathmandu also provided review data on the meteorological conditions (M.L. Shrestha), as well as on industrial and traffic pollution sources in the Valley (M.D. Bhattarai, S. Thapa et al.). United States Agency for International Development (USAID) funded a study on vehicle emission measurements in Asia, using a remote sensing (FEAT) technique. Such measurements were also made in Kathmandu, providing useful data (Steadman and Ellis, 1993). A joint UNDPlWorld Bank Energy Efficiency and Fuel Substitution Study (World Bank, 1993) evaluated options for rationalizing energy use in Nepal, with the aim of developing a coherent strategy for the National Industrial Energy Management Program (NIEMP). 1.3.2. URBAIR data collection The following local consultants provided additional data. · RONAST provided data on popUlation, pollution sources, fuel use, vehicle and traffic statistics, air quality measurements, air quality laws and regulations, and institutions dealing with air pollution. RONAST also generated new traffic data by counting rush hour traffic at 33 locations. · Dr. Madan L. Shrestha collected meteorological and visibility data, and evaluated the dispersion and visibility conditions of the Valley. · Dr. Bimala Shrestha conducted an assessment of the health effects of air pollution, and estimated the costs related to health damage. 1.4. SUMMARY OF DEVELOPMENT IN THE KATHMANDU VALLEY Figure 1.2 provides a summary of population, fuel consumption, vehicles, brick kiln development, and visibility data in Kathmandu Valley (and Nepal) over the past 20 years. Kathmandu Valley's population grew by 81 percent from 1971 to 1991. In 1991, 56 percent of the population was urban. There has been an average annual increase of 0.5 percent in gross domestic product (GDP) per capita between 1965 and 1990. However, the GDP/capita was very low--US$170 in 1990. This has not impacted the development of transport in the region; the number of registered road vehicles has almost doubled in the last decade. Registered brick kilns have grown by 200 percent over this period. Liquid fuel consumption, for Nepal as a whole, has increased dramatically since 1980. The consumption of gasoline and motor diesel (HSD) has increased 150 percent. Kerosene use is 250 percent higher, and fuel oil use is 580 percent higher. Fuel wood consumption appears to be declining by 20 percent from 1984 to 1987 (Devkota, 1992), having been replaced by kerosene (SKO) to a large extent. These growth trends have caused an acute air pollution problem in the Valley, as exemplified by the observed deterioration in visibility conditions. In the four-month period between November and February, the months with lowest visibility, the number of days with fairly good visibility (greater than 8,000 meters at 11 :45 local time) has decreased from 115 days in early 1970s to only about 20 days in 1992/93. URBAIR-Kathmandu 9 Figure 1.2: Development and growth trends over the last two decades, Kathmandu Valley. Population growth in Kathmandu valley. I 6'1400 g 1200 1063 '; 1000 -- C 0 600 :;::: BOO 586 736 III "S 400 Q. 0 200 0.. 0 ... (") ll) ,.... m ... (") se ll) ,.... m ... C') t:: ,.... 0 t:: ~ t:: -:r ,.... t:: co ,.... t:: ,.... (0 - (0 0 (0 (\J (0 (0 :;:: (0 ~ (0 - (0 (0 (0 ~ m - m CIJ ()) Fuel consumption trends, Nepal. -1BO~---------------------------------------------------, :;; 160 - - Gasoline (MS) ~ 140 --Diesel (HSD) (all use) In 120 -Kerosene(SKO) ! 100 5 80 . -..... Fuel oil (FO) - 60 -Fuel wood, Kathmandu Valley g 40 --:::-:: ~ 2g±--+__~1--~~~~;;:;~~~~~~~~~~~~~~::~~~~--J . . ........... ' (\J C') -:r ll) 0 .... (\J C') -:r co ~ ~ se (0 (") (0 ~ -:r (0 ~ m (0 ~ ... ~ m !2: CIJ m ~ (") m Growth tr~nds, Kathmandu valley. -vehicles · brich kilns (Bull's trench) BuU's trench kilns: +200% Cars, jeeps: + 64% Minibuses, buses, trucks: + 93% MC, scooters: + 118% 1980........................................ 1990 Air quality indicator: VISIBILITY at Kathmandu airport. No. of days in Nov - Feb with good visibility (> aOOOm). 120 100 III > 80 III c 60 ,., 40 20 0 ;::. ,.... ... ,.... m a C') ll) ()) (") ll) C') se C;; -- ,.... 0 t:: ,.... (\J t::: -:r ,.... t:: co ,.... t:: ,.... (0 (0 ~ (0 ~ (0 co (0 se (0 (0 -- 0 m !2: CIJ m 10 Background Information 1.5. POPULATION Available Table 1.1: Population data (thousands), Kathmandu Valley (JleA, population data for 1992). 1971, 1981 and 1991 Kathmandu district Lalitpur district Bhaktapur district Total Population are shown in Table 1971 354 122 110 586 1.1 (llCA, 1992). In 1981 427 165 144 736 the Valley as a 1991 668 222 736 1,063 whole, the growth ...............................1??~..~~~~J. ................(?}~~.~.~~~!.............. J??~..~.rP.~~}...................~~~~~..~.rP.~.~L ...... Growth rate % rate has been 3.7 1971-81 1.9 3.1 2.7 2.3 percent per annum. 1981-91 4.6 3.0 1.8 3.7 1.6. FUEL CONSUMPTION Data are not available for every category of fuel consumed in the Kathmandu Valley. Motor diesel (HSD) and kerosene (SKO) by volume are the most used liquid fuels in Nepal, followed by gasoline (MS) and fuel oil (FO). Liquid fuel consumption totals are given in Table 1.2. Table 1.2: Liquidfuel consumption Off kllJ!.r1, Nepal (Gautam, 19941. Gasoline Motor diesel Kerosene Light diesel oil Aviation fuel Fuel oil LPG Years MS HSD SKO LOO FO 1975176 10.5 30.8 32.2 9.4 112 1.8 0.6 1980/81 11.5 57.3 37.8 10.3 16.8 3.0 0.7 1985/86 20.4 80.4 62.2 8.3 23.2 15.8 2.6 1990/91 24.6 135.6 97.7 3.0 19.0 6.3 7.4 1992/93 28.3 156.9 131.1 0.3 28.1 20.3 ? Chan2e (%) 1980-93 +146 +174 +247 --100 +67.3 +576 » The quality of liquid fuel is governed by established specifications. Maximum allowed sulfur contents are: 4 percent in fuel oil, 1 percent in motor diesel, and 0.2 percent in 93-octane gasoline. Maximum lead content is 0.56 gil in 83-octane gasoline, and 0.80 gil in 93-octane gasoline. The actual contents of sulfur and lead are not known, and may be considerably less than the maximum allowed. Fuelwood consumption data for Kathmandu Valley is given in Table 1.3. Because of diminishing resources, fuelwood consumption has declined by close to a factor of 2 between 1983 and 1990. Increased use of kerosene Table 1.3: Fuelwood and agricultural waste has replaced fuelwood as the major consumption, Kathmandu Valley dom estic fueL d:(D"':=:=~=k==o==ta,Ą1=:=9:==92==~=.==:=:====:=.:=:=:=:== 3 3 Coal has replaced fuelwood in the brick industry. In Year 10 tJyr Year 10 tJyr the early 1980s, fuelwood and coal were almost equally 1983184 35.9 198711888 21.2 used in the local brick industry, now the ratio between ~~~:: ~~:~ ~~~~~~:~ ;~:~ 1986/87 29.0 URBAIR-Kathrnandu 11 coal and fuelwood consumption is about 7 to 1 (NESS, 1995). Table 1.4: Coal consumption in the brick and Brick and cement industries use cement industries, Kathmandu Valley (tonslyr). mainly coal. Table 1.4 shows the available Bull's Chinese*" Himal data on coal consumption. In the Hoffman trench* (Hoffman) Cement*" Total# kilns, coal consumption is somewhat kilns kilns factory lower than it was in 1970. In the Himal 1970171 3,300 1975176 2,950 Cement Factory, coal consumption has 1980/81 1,690 6,400 increased dramatically from 1990/91 to 1985186 2,200 5,860 1992/93. The dominant coal consumer in 1990191 2,440 7,980 the Valley is the Bull' s trench kiln 1992193 21,000 4,100 17,100 47000 industry. Shrestha and MalIa's estimate for 1993 43,800 1992/93 appears to underestimate 1994 54,800 Sources: · NESS, 1995 consumption. Although data for past coal ·· Devkota, 1992 # Shrestha and Malia, 1993 consumption in the Bull's trench kilns are not available, coal consumption has most likely increased substantially, especially since it has almost completely replaced fuelwood. 1.7. INDUSTRIAL DEVELOPMENT Industrial growth has been very strong in Kathmandu Valley, especially in the last decade. In 1991192, there were approximately 2,200 industrial establishments with more than 10 employees as compared with 1,504 industries in 1986/87. Brick and cement industries are the main industrial polluters. The number of registered Bull's trench kilns has increased markedly from 102 in 1984 to 305 in 1993. The rise in the number of smaller industries represents an increase in the combustion of such fuels as fuel oil, HSD and agricultural refuse, as well as some process emissions. The exact amount of increase in such industrial combustion and process emissions is not known. It is believed to have less significance for general air pollution than the brick and cement industries, but it has led to increased pollution exposure. 1.8. ROAD VEIllCLE FLEET In 1993, there were an estimated 67,000 registered vehicles in Kathmandu Valley (see Appendix 3 for more details). These included: · 22,000 cars/jeeps (21 per 1,000 inhabitants); · 36,000 motorcycles (34 per 1,000 inhabitants); · 5,000 truckslbuses. Specific vehicle fleet data are not presented for previous years. The KVVECP study reported a 64 percent increase in registered car/jeeps from 1980 to 1990; 118 percent increase for motorcycles, and 93 percent increase for buses and trucks. 2. AIR QUALITY ASSESSMENT This chapter provides estimates of the population's exposure to area air pollutants, and quantifies the contributions of different pollution sources to this exposure. Population exposure is estimated by: · describing existing air pollution concentration measurements, and their variation in time and space; · making an inventory of air pollution sources, and their relative contributions; · calculating concentration distributions in the area, using dispersion modeling; and · calculating population exposure by combining spatial distributions of population and concentrations, and incorporating the exposure on and near roads, and in industrial areas. National air quality standards or guidelines have not yet been proposed for Nepal. In this study the World Health Organization air quality guidelines (WHO AQG) are used to evaluate the air quality in Kathmandu. 2.1. AIR POLLUTION CONCENTRATIONS Overview of air pollution measurements, and observations. Non-scientific observations, especially in the dry season, indicate the following significant air pollution problems: · very high roadside air pollution, especially particles and odor, due to high emission vehicles of all types, and resuspension of street dust and litter; · black smoke plumes from brick kilns; · generally low visibility, especially before noon, and · one large point source, the cement factory, has highly visible particle emissions The air pollution concentrations have only recently been directly measured. The shortness of measurement periods at each site limits the accuracy of the measurements. The study, however, does provide a picture of the variation in space and time. In 1993, measurements were taken in the Environment and Public Health Organization (ENPHO) study (Karmacharya et ai., 1993), the KVVECP study (Devkota, 1993), by the Hydrological and Meteorological Services (HMS) (Shrestha, 1994), and by NESS (1994). · ENPHO study measured TSP, PM lO , S02, NO x, CO and Pb in November 1992 and February 1993, at 20 sites. · KVVECP study measured TSP, PM IO , S02, N0 2 from September to December 1993; a total of 14 sites (traffic, industrial, residential, background) were involved with 4 to 22 days of measurements at each site. Some CO measurements were also made. Locations of the various monitoring stations in the KVVECP study are shown in Table 2.1. · HMS measured TSP at the HMS Building, Babar Mahal, from January-August 1993, for 10 31 days of measurement each month. 12 URBAIR-Kathmandu 13 Table 2.1: Ambient Air Quality Monitoring Stations in the KVVECP study. Category Locations Distance from main Height of the road (mJ station (mJ 1. Commercial Areas: i. Heavy traffic (30,000-40,000 ADT) Singha Durbar, 2 3 GPO 3 3 ii. Medium traffic (20,000-30,000 ADT) Ratnaparl<, 4 3 Lainchaur, 2 2.5 Kalimati 3 3 ......~~.:.~.?~.~!!!?J~!.!g~Q.~9.!.L........................T.~.i.r:~~!.'(~.Ig2.......................................................................?..........................................?.:?.................... 2. Residential Areas Maharajgunj (TUTH), 30 3 Naya Baneswor, 20 7 .................................................................................. }~y.~..~.~~~~~9.~ ............................................................J.?............................................~..................... 3. Industrial Areas Balaju, 15 4 Bhaktapur, 50 3 Patan Industrialized districts, 5 5 ....................................................................................~.i.12!~1.. 9.~.~~.'!!.f~!?!?~.~~!!.9.~D9!.Q~..........................~.QQ..........................................~.Q.................... 4. Regional background/control site Tribhuvan University Kirtipur 50 3 ADT: Average Daily Traffic · NESS (Pvt) Ltd measured PM lO and Pb in air, and Pb in road dust; samples were taken at a total of 19 sites from September to November, 1993. · Visibility observations have been made at the Kathmandu Airport since 1969, through hourly observations of meteorological visibility. These observations and measurements indicate that suspended particles are the primary air pollution problem in the Valley, leading both to potential health risks, and to visibility deterioration. According to the measurements of S02 and N02, these compounds seem to represent little risk at present. The CO concentrations can be fairly high at rush hours along the roads with the heaviest traffic. In Appendix 1, the analysis and evaluation of the results of these air quality measurements and observations have been summarized. An extract of that summary follows. 2.1.1. Airpollution concentrations. The following WHO AQG for TSP, PM lO , and S02 are used in Nepal (Table 2.2). TSP concentrations. TSP concentrations Table 2.2: Applicable WHO AQGfor TSP, measured by ENPHO, KVVECP, and PMuk and S02 in Kathmandu HMS show that the WHO AQG for daily TSP PM10 S02 (lJgfm3) (J.lgfm3) (J.lgfm3) averages (150-230 ~glm3) are substantially Long-term (annual average): 60 - 90 exceeded both in heavily traveled and Short-term (24-houraverage): 150-230 70 100-150 residential areas. In addition, the guideline Source: National Ambient Air Quality Standards for Industrial and for the annual average (60-90 Ilglm3) is Mixed Use Areas, see S.O. 384(E) under APCA, 1981. also exceeded. Results of TSP Note: · = Annual average mean of minimum 104 (24 hourly) measurements, both average and measurements in a year. maximum, are shown in Figures 2.1 and .. = Should be met 98 percent of the time in a year. Should not be exceeded on two consecutive days. 14 Air Quality Assessment 2.2 (average and maximum concentrations). The maximum 24-hour concentrations of TSP measured, 467 l1g/m3 at the Babar Mahal building, and 319-876 l1g/m3 at traffic exposed sites in the KVVECP study, were more than twice the upper level of the 24-hour WHO AQG. In addition, daily TSP guidelines were exceeded on the majority of days at Babar Mahal. TSP ranged between the following values for the different sites of the KVVECP study (near ground level): · Traffic sites: 319-876 l1g/m3 · Residential sites: 273-350 l1g/m3 · Industrial sites: 102-290 l1g/m3 · Near Himal Cement Factory: 560 l1g/m3 · Tribhuvan University (reg. background): 155 l1g/m3 The KVVECP measurements were made from September to December of 1993. Had they been taken in the winter, measurements would have shown higher maximum concentrations. The ENPHO measurements showed a maximum of 555 l1g/m3 and an average of 308 l1g/m3 at 9 sites representing Central Kathmandu City air. At the 11 roadside sites, the measurements showed TSP maximum of 2,258 l1g/m3 and average of 1,397 l1g/m3. These values are based on a 9-hour average and only one sample was taken at each site. The 2,258 l1g/m3 maximum in the E!'-!'PHO measurements represents an estimated 24-hour average value of about 1,100 l1g/m3. HMS measurements indicate an annual average concentration around 180 l1g/m3 at Babar Mahal, 15 meters above ground leve1. This is more than twice the WHO AQG. At more exposed sites, such as heavily trafficked areas and around the Himal Cement Factory, the annual average would be much higher. At KVVECP stations, the WHO AQG values of 150-230 l1g/m3 are exceeded by 70 percent for the lower limit, and by 50 percent for the higher limit. No measurements have been taken in the brick kiln areas. However, the high concentrations at Thimi may be partly the result of contributions from the brick kiln emissions. These measurements point to a severe TSP pollution problem in the Kathmandu Valley, and in Kathmandu City in particular. Figure 2.1: Summary of TSP measurements, Babar Mahal Building. (Ref.: Shrestha, 1995.) 500 50 M c::JTSP (max) .§ 450 Cl ',,,",,,.,,ITSP (mid) 2.400 40 (/) i;' g, 350 r -+- No of rainy '"0 > da s 30 c e 300 250 200 0 20 z - 0 150 100 10 50 0 0 jan feb mar apr may jun jul aug URBAIR-Kathmandu 15 Figure 2.2: Results o/TSP measurements, KVVECP study September-December, 1993. (Relatively short measurement periods at each site.) (Ref: Devkota, 1993.) TSP I 87 I Average value i 102 Max. value Measurement sites, KWECP · Commercial (traffic) sites ... Industrial sites ... Residential sites o Regional background sites PM10 concentrations. PM lO has been measured by ENPHO, KVVECP, and NESS. The results of the KVVECP measurements are shown in Figure 2.3. PM lO concentrations were above the recommended WHO AQG (70 llg/m3) on all the days on which concentrations were measured. The exception were the Balaju and Patan industrial sites, which had the lowest TSP and PMIQ levels, Ratnapark traffic site and at Tribhuvan University. At the University site, PM lO was above the AQG on about half the days. The low values at Balaju and Patan are not representative, since measurements were made only for a few days in September. 16 Air Quality Assessment Figure 2.3: Results ofPM10 measurements, KWECP study September-December, 1993. (Relatively short measurement periods at each site.) (Ref.: Devkota, 1993.) The highest PM IO concentrations were 201 f.lg/m3 in November at the General Post Office, which is the site of heavy traffic and 194 f.lg/m3 at the Rimal Cement Plant site in December. About 50 percent of all the measurements in the KVVECP study were above the recommended guideline. The ENPHO measurements of PM 10 in Kathmandu City gave an average concentration of 89 f.lg/m3, and a maximum concentration of 127 f.lg/m3 at the general sites. The roadside sites were higher with an average concentration of 296 f.lg/m 3 , and a maximum of 498 f.lg/m3 (9-hour average values), ENHPO results support the results of the KVVECP study. URBAIR-Kathmandu 17 PM lO measurements taken by NESS, representing one I-hour average samples during Table 2.3: Ratios between PMlO and TSP, daytime at 9 sites, gave values up to 2, 100 ~g/m3 from KVVECP and ENPHO with an average of 800 ~g/m3. These are much measurements. higher than both ENHPO and KVVECP Based on measurements. Reasons for the apparent Average Max. discrepancies between these results and those from concentration concentration the ENPHO and KVVECP studies may be found KWECP Trafflc sites 0.39 0.34 when comparing the different samplers and ReSidential Sites 0.48 0.48 laboratories used. Industrial sites 0.47 0.51 The ratios between measured PM lO and TSP Himal Cement site 0.39 0.35 are given in Table 2.3. The ratio 0.70 is in the Tribhuvan Univ. 0.70 0.52 range typically found at sites that are not exposed {Background site} to a high degree of resuspension. The low PM IO ENPHO Traffle sites 0.21 0.18-0.25 ratio for the sites (0.4-0.5) indicates that the General sites 0.29 0.23 resuspension pollution is high. In the case of the Himal Cement site, the size distribution of cement factory emissions dominates the low ratio found there. S02 conceutrations. Results from the KVVECP measurements in Figure 2.4 indicate that S02 concentrations from September-December 1993 were low. Kalimati (traffic site) and Jaya Bageshwori (residential) are the exception. At these sites S02 concentrations were above the guideline (100-150 ~g/m3) on several days, and the maximum concentration was 225 ~g/m3. KVVECP measurements indicate that although S02 concentrations are not generally a problem in Kathmandu, area and point sources may create high local concentrations. No measurements have been made in areas exposed to brick kiln emissions. N0 2 concentrations. KVVECP measurements shown in Figure 2.5 indicate that N02 concentrations were generally low, and well below the 24-hour WHO AQG (150 ~g/m3). The Jaya Bageshwori site had elevated N0 2 and S02 concentrations, pointing to a local source. 18 Air Quality Assessment Figure 2.4: Results ofS02 measurements, KVVECP study September-December, 1993. (Relatively short measurement periods at each site.) (Ref: Devkota, 1993.) I 47 · Average value 53 i Max. value Measurement sites, KWECP · Commercial (traffic) sites .. Industrial sites .. Residential sites o Regional background sites URBAIR-Kathrnandu 19 Figure 2.5: Results ofN01 measurements, KVVECP study September-December, 1993. (Relatively short measurement periods at each site.) (Ref.: Devkota, 1993.) [ill. Average value ~ Max.value Measurement sites, KVVECP · Commercial (traffic) sites T Industrial sites .. Residential sites 20 Air Quality Assessment Figure 2.6: No. ofdays in Kathmandu Valley with fair-to-good visibility (>8,000 m) in the winter months. (Ref. ML Shrestha, 1995). 40 October 40 January .... ---v 30 '" 30r ~20 20 c 10~ 10 0 0 70 75 80 85 90 Year 70 75 80 85 90 Year 40 NovelTtler 40 February '" 30 30 "' c " 20 til 20 10 10 0 0 70 75 80 85 90 Year 70 75 80 85 90 Year 40 December 40 March 30 30 '" "' c" til 20 20 ~O 10 0 0 70 75 80 85 90 Year 70 75 80 85 90 Year Visibilityl. Observations point to a clear decline in visibility in Kathmandu Valley in the dry season (November-March), especially beginning in 1980. In the monsoon season, visibility appears to be unaffected. Figure 2.6 shows the number of days in the winter months with fair-to good visibility of greater than 8,000 meters at noon. Before 1980, this was the case on most days. Presently, there are very few days that have good visibility at noon. Figure 2.7 shows the number of foggy mornings (around 9:00 a.m.). This has increased from 35-40 days around 1970, to more than 60 in 1993. The nature of the "lifting" of the morning fog is visualized in Figure 2.8. In the relatively unpolluted air of the early 1970s this normally took place before 10 a.m. Fog dispersal is now typically delayed for 3 hours, and on hazy days, good visibility only occurs after 1:00 p.m. or 2:00 p.m. On some days the haze never lifts. Madan L. Shrestha (1994) analysis of visibility data from the Kathmandu Airport for 1963-1993 is summarized in Appendix 1. URBAIR-Kathmandu 21 Visibility reduction is Figure 2. 7: No. offoggy days at 9 a.m., Kathmandu Valley, 1969-93. mainly caused by (Ref.: M.L. Shrestha, 1995). particles (aerosol) 6'0 , of the size range comparable to the wavelength of light, e.g. 0.2 0.5 !lm diameter. 20 These are combustion aerosols from sources such as cars (diesel and Figure 2.8: No. of days in January with good visibility (>8,000 m) at gasoline), coal, given hours ofthe day. {Ret: M.L. Shrestha, 1995). fuelwood, and 30-,------------------____________________________- , agricultural January residue combustion. This 20 aerosol contains 1992 - 93 hygroscopic ~ ro particles, such as o particles 10 containing sulfate (S04), condensed organIc compounds, etc. I I 6 10 12 14 16 18 Thus, the morning Local time fog is caused by water vapor absorbed in the hygroscopic aerosol. As the temperature rises, the water vapor evaporates. In the afternoon, the still-reduced visibility is caused by the dry aerosol which remains in the air. The relative humidity in Kathmandu Valley is on average over 70 percent throughout the day in the monsoon period (June-September). Even so, day-time visibility is not reduced in these months, indicating that the concentration of hygroscopic aerosol is rather low in the monsoon season. In the winter months, the relative humidity falls below 70 percent between 9:00 to 10:00 a.m .. However, visibility is reduced throughout the morning. It improves gradually until 12:00 to 1.00 p.m. at which time the relative humidity has declined to about 50 percent. This corresponds to the situation in which a typical urban aerosol absorbs water vapor gradually from a relative humidity of 30-40 percent. Sulfate particles have a deliquescence point of 72 percent, which means that the relative humidity must approach 72 percent before such particles grow substantially and cause visibility reduction. Therefore sulfate particles may be a part of the visibility-reducing aerosol, but other types of aerosol, e.g. organic aerosol, make important contributions. 22 Air Quality Assessment 2.2. AIR POLLUTANT EMISSIONS IN KATHMANDU Table 2.4: Total annual emissions in Kathmandu Valley, VALLEY 1993 (tons/yr). TSP Total emissions. An emissions Transport sector inventory covering all source Vehicles exhaust Gasoline Cars/taxis 38.4 categories has been compiled for TC 67.5 4.2-1051 the Kathmandu Valley. It MC 107.5 contains emission data for TSP, Diesel Jeeps 68.4 PM lO and S02. Details of the Minibuses 22.5 emissions inventory Buses 45.0 78-390 1 development are described in Trucks 114 Appendix 4. Calculated and Tractors 21.6 TC ffiB estimated total emissions are Sum vehicle exhaust 570 570 82-495 1 presented in Table 2.4. They are Sum Resuspension from roads 1,530 -400 0 based on the emission factor ··Energyii"nd·usfi:y·s·ector....·....···..··..··················..................................................................... data in Table 2.5, and the fuel Fuel combustion consumption and traffic activity Industrial/commercial (excl. brick/cement) data in Table 2.6. Fuelwood 61.9 31 Coal 48.0 24 172 The inventory covers main Charcoal 20.0 10 source categories. The emissions HSD 1.8 2 from road vehicles are relatively LDOIFO? reliable and are based on fuel Kerosene!LPG 0.1 consumption, traffic activity and Agri. residue 4,50.0 225 emission factors. Emissions Sum industrial/commercial 5,82.0 292 Domestic Fuelwood 18,32.0 916 from industrial and commercial Agri. residue 4,54.0 227 activities, other than brick Anim. waste 30.0 15 combustion, are based on figures Kerosene!LPG 2.3 2.3 and emission factors provided Charcoal 10.0 5 by Shrestha and MalIa (1993). Sum domestic 2328.0 1,165 Emissions from Bull's trench Industrial processes brick kilns have been estimated Brick industry Bull's Trench 5000 1,250 4.8-44652 by NESS (1995). Chinese kiln Chinese 180 45 emissions are based on coal Sum brick 5180 1,295 consumption and on estimated Himal Cement Sum Stack -2000 -400 615 emission factors. Himal Cement Sum Diffuse duS!, -4000 -400 factory has provided numbers on Other emissions from the factory Sum Refuse burning 385 190 Sum Construction (Bhattarai, 1993). 16,565 4,712 Total High value: Based on max. allowable S content Low value: Based on actual S content, according to IOC Ltd. certificate 2 NESS (1995): Estimates based on different methodologies. URBAIR-Kathmandu 23 Table 2.5: Emission factors used (or URBAIR study, Kathmandu Valley. TSP PM101 TSP S02 NOx %Smax. Fuel combustion (kglt) Residual oil (FO) ind.lcomm. 1.25S+O.38 0.85 20-S1) 7 4 Distillate oil (ind.lcomm.) 0.28 0.5 20-S 2.84 HSD: 14) (HSD, LDO) (residential) 0.36 ~ 1.62) 0.5 20-8 2.6 LDO: 1.85) LPG (ind.ldom.) 0.06 1.0 0.007 2.9 0.02 Kerosene (dom.) 0.06 1.0 17-S 2.5 0.25 Natural gas (utility) 0.061 1.0 20-8 11.3· f (irid.ldom) 0.061 20-S 2.5 Wood (dom.) 15 0.5 0.2-A 1.4 Fuelwood (ind.) 3.6 0.5 Coal (dom.lcomm.) 10 0.5 Charcoal dom./comm. 20 0.5 Agri. residue 10 0.5 Anim. waste 10 0.5 ...B~f~~~..~!!!.!)!~.~;..~~~..................................}?...............................Q:J...................9.:!?.:~ ...............~.................................................................................. Road vehicles (glkm) (A) (B) Gasoline (Cars) 0.2 2.7 83 Octane (RON) 0.253) (MCfTC) 0.5 0.07 93 Octane (RON) 0.20 Diesel (Cars, jeeps, tractors) 0.6 0.9 1.4 14) (Minibuses, tempos) 0.9 1.5 13 (Buses, trucks) 2.0 3.0 13 1) A Ash content, in %; S: sulfur content, in % 2) Well ~ poorly maintained fumaces . 3) Actual S content in 87 RON gasoline, according to IOC Ltd quality certificate: 0.009% 4) Actual S content, according to IOC Ltd quality certificate: 0.20% 5) Actual S content, according to IOC Ltd quality certificate: <1 % (A) Used for Manila, Jakarta, Bombay (B) Proposed and used for Kathmandu Valley. 24 Air Quality Assessment Table 2.6: Fuel consumption and traffic activity data/or Kathmandu Valley. Emission source/ fuel type Category Fuel consumption Traffic activity 106 veh. km/yr Vehicles kl/yr Cars Gasoline 28.015 192 Tempos (TC) 135 Motorcycles (MC) 215 542 sUbtotal Jeeps Diesel 22.955 76 Minibuseslbuses 30 Trucks 15 Tractors 38 Tempos ~ 183 sUbtotal 725 total Industry 103 tonslyr Himal Cement Bun's trench kilns CoalNuelwood/rice husk 4215.7/15.8 Chinese kilns Coal 20 Other industry/commercial HSD/LDO ?n Coal/charcoal 4.8/1,0 Wood/agricultural 17.2145 residue SKOILPG ton Domestic Wood/charcoal 12210.5 Agric. res.lanim. waste 45.4/3.0 SKO/LPG 35/4 Refuse burning Refuse 10 For resuspension from roads, a TSP emission factor of 2 glkm is used (the same as was used for Greater Mumbai and Manila). This emission factor is based upon USEPA data. Data on fuel consumption and emission factors are often uncertain. The amount of open refuse burning, not for cooking purposes, is unknown. For Kathmandu the same estimate has been used as was used for Bombay: 1 kg of refuse burned per week, per household (some 200,000 households in Kathmandu Valley), with an emission factor of 37 glkg (Economopoulos, 1993; Semb, 1985). The source contributions in Table 2.7 are derived from estimated emissions given in Table 2.4. The contributions to population exposure may differ substantially from the contributions to total emissions. This difference depends on the height of the emissions Table 2. 7: Source Contributions (ground level or high stack), the distance from the source ofTSP and PMUh to populated areas, and the dominating wind directions. Contribution % Source category TSP PM10 Road vehicles TSP. It is estimated that the total emissions are gasoline t3 4.5 approximately 16,500 tons/year. The brick industry, diesel 2.2 7.6 domestic fuel combustion, and resuspension from roads Resuspension from roads 9.3 8.5 are estimated to be the dominant sources for the Valley as Domestic fuel combustion 14.1 24.7 a whole. Emissions from construction activities have not Brick industry 31.3 27.5 been estimated. Himal Cement 36.2 17.0 Other industry/commercial 3.5 6.2 Refuse buming 3.2 4.0 URBAIR-Kathmandu 25 PM lO. Total estimated emissions are some 4,700 tons/year. For PM lO , the main sources are the brick industry and domestic fuel combustion, followed by vehicles and road resuspension. Himal Cement Factory and other industrial/commercial activities are fairly equal contributors. Spatial distribution of emissions. Total emissions have been distributed within the grid system based on the actual location of point sources, industrial areas, and road links, and the population distribution (as described in Appendix 4). The resulting emissions distribution, summed for all source categories, is shown in Figure 2.9, in the form of isolines. This distribution forms the input of the dispersion calculations. The figure shows high emissions densities, particularly in Kathmandu City, due to a combination of vehicle exhaust, road resuspension, and domestic fuel combustion. High densities are also present in areas that have a concentration of brick kilns, west of Kathmandu and Southeast of Patan. The Himal Cement factory shows the maximum level in the distribution. Figure 2.9 Spatial emissions distribution in Kathmandu Valley, 1993. Total emissions (kg/h, av,erlJ!f!el1 over the 6 winter months) km1, represented as isolines i o 0~ 26 Air Quality Assessment 2.3. DISPERSION MODEL CALCULATIONS 2.3.1. General description oJtopography and climate Kathmandu Valley is located between the Himalayas in the North and the Mahabharat mountains in the South. Kathmandu City is located on a plain, about 1,325 meters above sea level and is surrounded by hills and mountains. The Siwalik Mountains form the border between the Terai and Nepal's central region, and the valleys that run east-west of which Kathmandu Valley is the most important. The Bagmati river runs through the valley, and the river plain is covered with fertile river deposition. The Himalayan range rises north of the central valley, with Mount Everest peaking at 8,846 meters and several others above 8,000 meters. There are large height differences between the valleys and the mountains that surround them. The monsoon circulation determines the climate. In the lowest parts of the country, the climate is subtropical; at higher elevations one finds a cooler temperate climate; and in the high mountain ranges there are tundra and glacial climates. The mean annual temperature in Kathmandu is 18° C. The coldest month is January with a mean temperature of 10° C. The warmest months are July and August, with an average temperature of 24° C. Kathmandu has an annual rainfall of 1,400 mm. The wettest month is July with an average rainfall of about 370 mm. November and December are the driest months; the average rainfall is less than 6 mm. High altitudes, combined with extreme diurnal radiation variations, lead to substantial differences between the day and night temperatures. The days are warm and there is rapid cooling at night. In the dry season, the cooling at night may cause the formation of deep inversion layers, with the air temperature increasing with height. When such an inversion layer is deep enough, it takes time for the insulation to break it up. The atmosphere then acts as a lid over the city, and pollution concentrations can build up considerably 1.3.2. Dispersion Conditions During the winter there is a build-up of a strong high pressure center over central Asia. In the northern parts towards the Himalayas, the prevailing winds come from northwest. In the spring the Asian high pressure weakens, and the northwest monsoon disappears. The summer monsoon is a continuation of the southeast monsoon from the southern hemisphere. After crossing the equator, the airmass turns towards the east, causing the southwest summer monsoon. This monsoon is driven by a low-pressure area located over central Asia. This airflow becomes southeast upon reaching Nepal, due to physical and dynamic reasons. Local wind conditions in the Kathmandu Valley have been measured at Tribhuvan Airport for many years. A wind/stability matrix has been constructed from these data, the distribution of stability classes, and observations of diurnal wind pattern. Such a matrix:, representing the statistics of dispersion climatology, can be used as an input to dispersion models for calculation of long-term average concentrations of pollutants. Figure 2.10 shows selected monthly wind roses for the period 1971-75 and 1993 (Shrestha, 1994). In the summer and early autumn, the prevailing wind regime in Kathmandu Valley is the southwest monsoon. In the winter, the prevailing winds are more westerly. High mountains in the north prevent the entry of cold Siberian winds from the northeast. The pattern is dominated by weak winds. The high occurrence URBAIR-Kathmandu 27 of calm and low wind speeds causes poor dispersion conditions in the Valley. The combined matrix is given in Table 2.8. Table 2.8: Wind/stability frequency matrix for the winter months (Jan-March, Oct-Dec) 1993, Tribhuvan Airport. .8 rnIs 1.8 mts 3.3 rnIs 6.3 rnIs l1 23 4 ~ 2 3 411 2 3 4! 1 2 30 ~ .6 .1 1.0 .6 1.1 .0 .1 .1 l.O .0 .0 .0 1.0 .0 60 j .5 .1 1.0 .5 ~ .1 .0 .2 .1 Lo .1 .0 .0 1.0 .0 90 j 1.6 .3 2.8 1.6 L1 .0 .2 .1 ~.O .1 .1 .0 LO .1 . ··120·····Ts....······j·..········z:s........Ts·..·..···Tij"""·..···..·..··:o··....·······j·····..···.. ·:z·········ro..·....·········:O···············:O········..·..:O··..······TO'·..·······..·:0········..1 150 ~ 1.9 .6 6.3 3.8 ~ .2 .1 .6 .4 j .0 .2 .1 .0 j .0 .0 j 180 ! 1.6 .5 5.4 3.2 i .3 .1 1.0 .6 i .1 .8 .3 i .0 .1 .3 l ··2·1O'·····T4'}········'1":O········3T····..{s..·······Tg················.'Z'···········j··..······..··j..·..····T:4················Di·············:2"·..········j··········To·········..··:6··········1 240 ~3.5 .8 2.3 1.1 ~.9 .2 .6 .3 ~.5 1.6 .3 .3 j.O .3 j ..?!Q.......U:.~........:.~.........}:?.........~.:~..........L~...............:.1.............:~.............:.?..........L~................~.:~.............:.I?............:.~...........L9.............:.~. . . ...J 300 j.7 .1 1.3 .7 j.3 .1 .5 .3 j.2 .6 .2 .2 ~.O .5 ~ 330 ~ .8 .2 1.5 .8 j .2 .0 .3 .2 l.1 .2 .1 .1 ! .0 .1 ~ 360 L7 .1 1.1 .5 ~ .1 .0 .1 .1 1.0 .0 .0 .0 ) .0 .1 ~ Stability 1 2 3 4 Windprof. exponent .20.28 .36 .42 Mixing height 1,200. 1,000. 400. 200. Stability classes Velocity classes (rnls) I: Unstable 0.3-1.5 (0,8 rnls average) N: Neutral 1.5-2.0 (1.8 rnls average) SS: Weakly stable 2.5-4 (3.3 rnls average) S: Stable >4 (6.3 rnls average) The frequencies of calm are distributed in the direction sectors within each of the stability classes of the 0.3-1.5 mls velocity class, proportional to the joint occurrence of wind and stability. 28 Air Quality Assessment Figure 2.10: Wind roses/or 1971-75 and 1993, Tribhuvan Airport (Shrestha, 1995). 1971-75 1993 February ~ ... .' . ,;.*<1 , . 'f May August November % calm Jan Feb Mar Apr May Jun Dec 1971175 71 66 69 68 69 63 70 70 77 74 74 79 1993 62 56 47 41 48 62 67 68 65 62 60 65 URBAIR-Kathmandu 29 Figure 2.11 a: TSP concentrations in Kathmandu Valley. Calculated winter average concentrations (km2 averages), 1993. Total distribution and contributions from various source categories. / TSP, total distribution /00 30 Air Quality Assessment Figure 2.11h TSP Concentrations in Kathmandu Valley car exhaust 'C , .0 ,i ",- , : GiJ I' , ~ . I .... -... , 0 .. " ~ , , , I ,' ... _ ...' , . .. ," ... ...... .:-,----- ... , , , " \ .' Road resuspension " I .l Domestic fuel , , URBAIR-Kathmandu 31 Figure 2.11 c TSP Concentrations in Kathmandu Valley Bull's trench brick Chinese brick " ... _-, .' , /' '. , I ,I ,, ... .., .. ' -.... , ...... " , .. ,:.. ............ "'" o ! ! ,," t I 32 Air Quality Assessment 2.3.3. Dispersion model calculations, city background Model description. In the first phase of URBAIR, dispersion models concentrate on the calculation of long-term (winter) average concentrations, representing the average within km2 grids ("city background" concentrations). Contributions from local sources, in specific receptor points such as industrial hot spots, is evaluated separately. The dispersion model used here is a multisource, Gaussian model, which treats area, point and volume sources separately. Such a model is sufficient for calculating a first approximation of the contribution from various source groups to long-term average air pollution concentrations. Meteorological input to the model is represented by a joint wind speed/ direction/stability matrix, representing the frequency distributions of these parameters for the winter months. The dispersion conditions are assumed to be spatially uniform over the model area. For point sources, plume rise (Brigg's equations), the effects of building turbulence, and plume downwash are taken into account. For area sources, total emissions in a km2 grid is simulated by 100 ground level point sources, equi-spaced over the km2 grid, using the actual height of the emissions. For example, for a traffic source, a 2 meters emission height is used. Total suspended particles (TSP). Calculated, average TSP concentration distributions in the winter months, are shown in Figures 2.11a, b and c. A regional background value of 10 Jlg/m3 has been added. Emissions from refuse burning and other commercial/industrial fuel combustion can be estimated. The following sources are covered: · Road vehicle exhaust (gasoline and diesel). · Resuspension from roads. · Domestic fuel combustion (including estimated emissions from cottage-scale pottery). · Bull' s trench brick kilns. · Chinese (Hoffmann-Bhatta) brick kilns. · Himal Cement Factory. TSP, total distribution. Calculated TSP source contribution for Kathmandu City and the brick kiln area given in Table 2.9. There are distinct peaks in the distributions from the various sources: · due to road traffic (vehicle exhaust and resuspension) and domestic fuel combustion in Kathmandu City; Table 2.9: TSP contributions (llglm1, winter average) calculated/or certain grids and maximum grid contribution. Maximum Source Kathmandu City Brick area maxima From each source in grid no. maxima (grid 11,14) (grid 14,7) Vehicle exhaust 22 2.5 22 (11.14) Resuspension from roads 57 5.0 57 (11.14) Domestic fuel combustion 35 17.0 41 (13.16) Bull's trench kilns 47 238.0 238 (14,7) Chinese kilns 2 19.0 24 (16,7) Himal Cement 1 0.5 23 (9.9) Regional background 10 10.0 TOTAL 174 292 URBAIR-Kathmandu 33 Figure 2. 12a: PM10 concentrations in Kathmandu Valley. Calculated winter average concentrations (km2 averages) 1993. Total distribution and contributions from various source categories. 50 ,, . ,. /", ( . , - ...... ... " ., , , . , 34 Air Quality Assessment Figure 2.12h PMlO concentrations in Kathmandu Valley Car exhaust ,, , , ,, ., , , ... .... ,.t ..... "''''''''''''- .. ,: .., , ,, . : ,: ,, ,,~~ Domestic fuel ( J' o ". " . -. ~ j , ,, '" (J ,, ,, , .., . , ,., ," URBAIR-Kathmandu 35 Figure 2.12c PMJO concentrations in Kathmandu Valley Bulf's trench brick " Chinese brick / ,....... .,' -~ .., . , , '. ,, , , , ....#... " ..... !. ... - - . - ... o Himal Cement, diffuse dust Himal Cement, Stack , , , , / " \ ,, , t , /' .... -... *' 1 )~,),:::~:,:: l t 1 1 1 ,, , iii I I i , I 36 Air Quality Assessment · in the brick kiln areas, especially southeast of Patan, and · near Himal Cement factory. The tJimal Cement Factory, despite its large emission, makes a small overall contribution to the total TSP levels in Kathmandu City and popUlation exposure because of its tall stack, and the sparse population close to the factory. Estimated additional contribution from refuse burning is 5 ~g/m3 at the Kathmandu City maximum, with a spatial distribution similar to domestic fuel combustion (comments on source contributions). The contribution from commercial/industrial fuel combustion (in addition to brick kilns) is about the same as the refuse burning. These calculated concentrations can be compared with Shrestha's measurements at Babar Mahal Building (in grids 11,12 and 12,12): · Calculated winter average: 160-170 jlg/m3 · Measured average, Jan-March, 1993: 255 jlg/m3 It can be seen that the calculated value is lower than that measured. The calculated value represents the km2 grid average, while the Babar Mahal Building (at which the actual measurements were taken) is affected by heavy traffic. This site is situated approximately 100 meters downwind from the Arniko Rajmarg Road which carries close to 31,000 vehicles each day. The measurement site thus experiences emissions from vehicles on the road, and thus actual measurements are higher than the calculations. Nevertheless, the dispersion calculations may underestimate the actual TSP concentration in Kathmandu City to a small degree. Comparison with KVVECP measurements can only be indicative, since the measurements were taken only in short autumn periods. As expected, however, measurements close to roads (2 2 30 meters from roads), give much higher concentrations than those calculated as km grid square averages. PM lO· Calculated PM lO distributions, and the source contributions, are shown in Figures 2.12a,b and c. The PM lO calculations are based on TSP calculations, using the PM10/TSP ratios given in Tables 8 and 9 in Appendix 3. As was the case for TSP, the PM lO measurements from the KVVECP sites close to roads show considerably higher concentrations than those calculated. Calculated PM lO contributions in selected grids are given in Table 2.10. Table 2.10: PM10 contributions (p/m3 , winter average), calculated/or certain grids, and maximum grid contribution. Kathmandu City (grid 11,14) Brick area maxima (grid 14.7) From each source In grid no. Vehicle exhaust 22 2,5 22 (11,14) Resuspension from roads 15 1 15 (11,14) Domestic fuel combustion 18 8 21 (13,16) Sufi's trench kilns 12 60 60 (14,7) Chinese kilns 0,5 5 6 (16,7) Himal Cement -0 -0 10 (9,9) Reg. background 10 10 TOTAL 78 87 URBAIR-Kathmandu 37 S02 and N0 2. Dispersion calculations have not been carried out for S02 and NO x (or N0 2). In general, actual measurements indicate fairly low values. The emissions inventory indicates that the ratio between S02 and PM IO for road traffic (vehicle exhaust plus resuspension) is within the range 0.1-0.6 flg/m3 The numbers differ depending on whether the maximum sulfur content in fuel or the lac certificate value sulfur content is used. For total S02 emission, the corresponding range is 0.2-1.4 J.lg/m3. The measurements give an S02IPMlO ratio of 0.3-0.6 flg/m3 near road sites, indicating that the actual sulfur content in RSD is close to the maximum value of 1 percent sulfur. 2.3.4. Pollution hot spots Significant pollution sources contribute to large concentrations in their neighborhoods, adding to the general city background. Such pollution hot spots are generally located along the main road system, and near industrial areas with significant emissions through low stacks. Industrial pollution hot spots in Kathmandu Valley include the areas near Rimal Cement Factory that are exposed to the diffuse dust source associated with quarrying, transport, and other handling of materials. The brick kiln areas are also pollution hot spots. Emissions from each low chimney (10 meters), expose nearby areas with very high short-term concentrations, depending upon the wind and dispersion conditions. In the dispersion calculations of long-term averages, however, the kilns are represented as area sources, and the calculated concentrations represent the average of each square kilometer. The KVVECP measurements of S02 and N0 2, such as at the Jaya Bageshwori site, indicate that other sources in the Valley may also create pollution hot spots. Undoubtedly, the entire main road system which has a daily traffic higher than 15-20,000 vehicles, represents pollution hot spots. Such hot spot areas contribute significantly to the health damage caused by air pollution. 2.3.5. Population exposure to air pollution Population exposure is defined as the number of people experiencing pollution compound concentrations within established concentration ranges. The cumulative population exposure distribution gives the percentage of the total population exposed to concentrations above standard accepted values. People are exposed to air pollutants at home, in transit, at work and other places. More often than not, complete data are not available to make population exposure calculations. The methodology used must be adapted to the data available in each country. In order to correctly map population exposure, data are needed on: · concentration distributions and their variation with time, in homes (general city air pollution or "city background"), along main road network and near other hot spots, such as industrial areas; and · population distribution (residences and workplace), the number of commuters, and time dependent travel habits. Exposure to TSP and PM lO . Population exposure calculations have been carried out for winter concentrations of TSP and PM IO , which are the major air pollution problems in Kathmandu Valley. These calculations used to assess the costs of health damage. Although exposure to high, short-term concentrations of particles or hot spot exposure to other pollutants is very important, these calculations have not been made because of the lack of 38 Air Quality Assessment data for Kathmandu Valley. In addition, comprehensive dose-effect relationships regarding health have not yet been developed for short-term exposure, although there are established air quality guidelines for such exposure. The calculation of population exposure is based on the calculated km2 -grid average concentrations. All the people who live within a grid square are assumed to be exposed to the same concentration, whether they live close to a hot spot, such as a road, or near a park. The exposure of drivers and commuters while they are on the road is also not taken into consideration. Thus, the calculation underestimates actual exposure. Calculations for Manila and Greater Mumbai reveal that approximately 5 percent of the population, residing near roads, and taxi, bus, or tempo drivers, are exposed to 25-50 ~g TSP/m 3 more than is calculated by the km2 average method. The results of the population exposure calculations for winter average TSP and PM 10 are shown in Figure 2.13. An annual average exposure is estimated, based on the ratio between annual average and winter average TSP of 0.75, measured at the Babar Mahal Building (Figure 2.1). The same ratio is used for PM 1O . The exposure situation in Kathmandu Valley can be summarized as follows: · Approximately 50 percent of the population is exposed to a TSP concentration above the WHO AQG--90 ~g!m3, annual average. · 3 to 4 percent of the population is exposed to TSP greater than twice the WHO AQG (180 ~g/m3). These are residents in the brick kiln areas, drivers, and those who live near the most heavily traveled roads. Indoor air pollution exposure is not taken into account in these calculations. Undoubtedly, such pollution is a very important source of exposure and greatly impacts human health, especially that of women and children who are most directly exposed. During cooking, the indoor exposure may significantly exceed the outdoor concentrations, increasing total exposure considerably. This drawback must be corrected in future analyses. General exposure at residences is mainly caused by the following (in approximate order of importance): · For TSP: Resuspension from roads, brick kilns, domestic fuel combustion, diesel vehicles, gasoline vehicles (See Table 2.9.) · For PM lO : Diesel vehicles, gasoline vehicles, resuspension, domestic fuel, brick kilns. (See Table 2.10.) Additional exposure because of proximity to roads is significant for part of the population. This additional roadside exposure is accounted for in the following way. 1. Considering the high TSP and PM lO measurements at roadside sites, average roadside TSP exposure concentration is estimated to be 500 ~g/m3 (winter average). 2. Half the population, 200,000 people, living in the most highly exposed areas in Kathmandu City within the 75 ~g!m3 PM lO isoline on Figure 2.13, are assumed to be subjected to additional roadside exposure. 3. These 100,000 people are assumed to spend half their time at the roadside and the other half at home. The total exposure resulting from this calculation is 350 ~g/m3 TSP, corresponding to about 130 ~g/m3 PM lO in Kathmandu. URBAffi-Kathmandu 39 Figure 2.13: Population exposure distributions for TSP and PM10 (winter average concentrations, Ilg/mJ), Kathmandu Valley, 1993, based on calculated average km2 concentrations. 100~------------------------------------------------, 90 · .TSP 80 · o PM10 o _ 70 if. · - 60 ~ · i 50 'S § 40 · o · · · 50 100 150 200 250 300 350 400 450 500 uglm3 40 .TSP 35 DPM10 30 25 if. 20 15 10 5 o ~.I j , ,I ; n '7 7 I / j ·· ··· 'j · 'j j J ] o C\l 0 '<;t o co o co o o ,... to ,... C\l 0 ,... 1.0 o o 0 1.0o o o o g C\l C\l C'? o::t to uglm3 40 Air Quality Assessment 4. Thus, these 100,000 people are moved from the 60-80 llg/m3 exposure level (see Figure 2.13, PM IO) to 130 llg/m3. The effect of increased and reduced emissions from each source category has been calculated. These calculations reveal that in order to reduce TSP and PM IO exposures, reductions in the brick kiln emissions are crucial, followed by reductions in domestic fuel combustion, road resuspension and vehicle exhaust. The results are shown in Figures 2.14 and 2.15 for TSP and PM lO , respectively. Calculations were made for ± 25 percent change in emissions from each source, on the number of people experiencing exceedance of the following pollution levels: · TSP: Exceedance of 100 llg/m3 as winter average, corresponding to approximately 75 llg/m3 as annual average in Kathmandu Valley (which is within the WHO AQG range 60-90 llg/m3). Exceedance of 175 llg/m 3 as winter average, corresponding to an annual average of 130 llg/m 3. · PM lO : Exceedance of 60 llg/m 3 as winter average, corresponding to about 45 llg/m3 as annual average in Kathmandu Valley. Exceedance of 100 llg/m3 as winter average, corresponding to about 75 llg/m,3 as annual average. URBAIR-Kathmandu 41 Figure 2.14: Change in population exposure to TSP as a result of ±25 percent change in the total emissions from each source category. TSP, exceedance of winter average> 100 IJg/m 3 No. of people (x 1000) + 97 + 90 Change in total emissions from + 58 each source +60 +39 +25% + 30 +23 + 14 +2 544 -7 -7 -7 - 30 -24 -40 -25% -60 - 90 ·98 TSP, exceedance of winter average> 175IJg/m3 + 120 +90. + 60 ! +25% + 30 ~ 155---~~~----~~----~~-----r-r-----r-r-----+-+------+---- 72 n I ~ I 30_ -25% 60 + 90 -120 Source: Car Road Dom. BuU's Hoffman Himal exhaust resusp comb. brick brick Cement 42 Air Quality Assessment Figure 2.15: Change in population exposure to PMLO os a result of ±25 percent change in the total emissions from each source category. PM 10 · exceedance of winter average> 60 ~g/m3 No. of_ people (x 1000) +90 Change in total emissions from r +60 each source ~ +25% + 30 476 + 19 ,..- n Yo ~ ~ r--1 '-.J -30 ~ ·25% -60 _ :s6 - 65 ·90 - PM 10 · exceedance of winter average > 100 ~g/m3 + 120j +,J.13 +90 +60 ~7 +25% +30 68 --+'~-----+-r----~+-----~-----t~----~+-----~'--r------ I -30 I I :--r2 U 13 - -25% -60_ i i i t i i I I I I I I Source: Car Road Dam. Bull's Hoffman Himal Himal exhaust resusp comb. brick brick stack diffuse URBAIR-Kathmandu 43 2.4. SUMMARY OF AIR QUALITY ASSESSMENT, KATHl\UNDU VALLEY 2.4.1. Airpollution concentrations Air pollution concentrations have not been fully measured. At KVVECP's 14 sites, TSP, PM lO , S02 and N0 2 were been measured for 5 to 30 days during the autumn of 1993. One fairly long series of TSP measurements, from Babar Mahal Building, was taken from January to August 1994. These measurements, as well as subjective observations, reveal that the main air pollution problem in the Valley is associated with suspended particles, such as TSP, PM lO and combustion particles. Concentrations exceed WHO AQG on more than 50 percent of the days. The highest 24-hour concentrations, compared with the WHO AQG are given in Table 2.11. The 8-month average TSP at Babar Mahal was 20 I llg/m3, compared to the WHO AQG of Table 2.11: Highest 24-Hour Concentrations in 60-90 llg/m3. The highest Kathmandu concentrations occurred in the Max. concentration WHO Guidelines most heavily trafficked sites and TSP, KWECP (traffic exposed) 8671JgJm 3 150.230 IJg/m 3 at the site near the Himal Cement TSP, Babar Mahal (residential) 467 j.JgJm3 150-230 IJgJm 3 factory. No measurements were PM 10 , KWECP (traffic exposed) 201 IJgJm3 70 j.JgJm3 made in the areas most exposed to brick industry emissions. High levels measured at the Thimi site may partly be due to such emissions. 2.4.2. Airpollutant emissions inventory The main particle emission sources are smoking vehicles (diesel and gasoline), brick kilns, and the Himal Cement Factory. Based on available emissions data and estimates, a first approximation of an emissions inventory for suspended particles has Table 2.12 Main Emissions Sources in been worked out. Kathmandu (l993) In terms of total emissions in 1993, TSP the main sources are given in Table 2.12. Himal Cement 36% Brick industry 28% Diesel vehicles contributed about 60 Brick industry 31% Domestic fuel 25% Domestic fuel combustion 14% Himal Cement 17% percent of the particles and gasoline Road resuspension 9% Vehicle exhaust 12% vehicles about 40 percent. The actual Vehicle exhaust 3.5% Road resuspension 9% impact of these emissions on human health depends on the emission conditions such as the height of emissions, and their position relative to population centers. There are significant uncertainties in the emission figures for the sources. This may be especially important for road resuspension and Bull's trench kilns, which are the predominant polluters in the brick industry. The PMIO/TSP ratios used for various source categories are also uncertain. 44 Air Quality Assessment 2.4.3. Population exposure to air pollutants Table 2.13: Average Winter A first approximation of the population exposure Concentrations in Kathmandu Ci(y is based on the emissions inventory, a multisource TSP !-191m3 PM10 !-191m3 Gaussian dispersion model for long-term Vehicle exhaust 22 22 averages, and meteorological statistics from Road resuspension 57 15 Tribhuvan Airport. The calculated contributions Domestic fuel combustion 35 18 BUll's trench kilns 47 12 to the winter average concentrations in Background ? ? Kathmandu City are given in Table 2.13. Total ? ? The calculated winter average TSP concentrations underestimate the actual concentrations in Kathmandu City (Babar Mahal Building). The indoor air pollution, which is very significant in rural areas, has not been taken into account in these calculations The present TSP exposure situation to the population in Kathmandu Valley is as follows: · about 50 percent is exposed above the upper limit of the WHO AQG (90 llg/m3), and · approximately 3 to 4 percent is exposed to concentrations that are more than twice this level (180 llg/m3 ), which include residents in the brick kiln areas, drivers and roadside residents. 2.4.4. Visibility reduction Visibility in the Valley has been very significantly reduced in the dry season since early 1980s. Visibility is mainly affected by sub-micrometer particles, mainly from fuel combustion. Hygroscopic particles like sulfate, nitrate and organic aerosols, cause strong visibility reduction at relative humidities above 70 percent. Combustion aerosols absorb water, which causes reduced visibility, at 30 to 40 percent relative humidity. Location and height of the emission source is of little importance for visibility reduction. The main sources of combustion particles in Kathmandu Valley cannot be ranked because the emissions and, consequently, exposure estimates are not very accurate. The main sources are: · Domestic fuel combustion · Road vehicles · Brick industry · Himal Cement Factory 2.5. IMPROVING AIR QUALITY ASSESSMENT 2.5.1. Main shortcomings and data gaps Air pollution concentrations. There is a need for a comprehensive air pollution monitoring program in Kathmandu Valley. Such a program should encompass the following items: · Compounds 1st priority -- TSP, PM IO , submicron particles, black smoke, chemical composition, CO. 2ndpriority -- S02, N02, P AH, benzene, lead. · Air quality sites -- roadside, background, brick kiln area, rural, valley outskirts (hilltop). · Meteorological data -- 3 to 5 measurement sites, wind, relative humidity, stability, visibility. URBAIR-Kathmandu 45 · Measurement methods -- continuous monitors for PM lO , combustion aerosol, CO, meteorological data, visibility. Emissions. It is important to improve the emissions inventory. Special attention must be given to the following: · comprehensive fuel statistics, · emission factors for vehicles, · measurement of emissions from Bull's trench kilns, · emission factors for domestic fuel combustion, · determination of resuspension emission factors, and · particle size distribution for different source emissions. Population exposure. The determination of population exposure in Kathmandu Valley is based on a combination of dispersion modeling and pollution measurements. A reliable population exposure estimate is crucial for estimating health damage, and assessing the beneficial health impacts of measures to reduce the exposure, as part of a cost-benefit analysis. In order to improve the population exposure calculations, it is necessary to: · establish dispersion models that are capable of dealing with complex topographical, temperature, dispersion conditions, and also for dispersion from roads; and · improve the input database especially hourly air pollution concentration data, hourly dispersion, emissions and spatial resolution data. A list of proposed actions to improve the air quality assessment in Kathmandu are given in Table 2.14 46 Air Quality Assessment Table 2.14: Proposed actions to improve the Air Quality Assessment Actions Time Schedule Air Quality Monitoring Design and establish a modified, improved, and This activity should start immediately, and a proposed schedule is extended ambient air, meteorological, and dispersion as follows: monitoring system · By 31 June 1996: Rnalize plan for an upgraded air quality · evaluate sites (at least 10 locations); monitoring system, including plans for laboratory upgrading. · select parameters, recommended ones are CO, · During 1996: NOx, 03, HC, TSP and PM10 - Establish of 1to 2 modem monitoring stations; and · select methods/monitors/operation schedule; and - Carry out first phase of laboratory upgrading. · upgrade laboratory facilities, and manpower capacities. Design and establish a Quality Control/Quality This activity should start immediately, phased in with the improved Assurance System monitoring system, and the laboratory upgrading. Design and establish an Air Quality Information System, including · database; and · information to control agencies; lawmakers; and ..~.......J?~~!.i.9................................................................................................................................................................................................................................. Emissions Improve emissions inventory for Kathmandu Valley, First priority: including · industrial emissions inventory; · industrial emissions inventory (location, process, · study of resuspension from roads, emissions, stack data); · start developing an emissions inventory procedure · road and traffic data inventory; · domestic emissions inventory. Study resuspension from roads and surfaces Estimate contribution from construction and refuse buming. Establish emission factors for Nepal conditions. Develop an integrated and comprehensive emissions inventory procedure, include emission factor review, update and quality assessment procedures. Improve methods and capacity for emission ..!!'.~~.~.~~~.r:!')!::~!~:....................................................................................................................................................................................................................... Population exposure Assess current modeling tools/methods, and establish This activity should be started without delay.. appropriate models for control strategy in Kathmandu Valley. 3. AIR POLLUTION IMPACTS 3.1. INTRODUCTION This chapter presents an overview of the major impacts of air pollution in Kathmandu Valley and estimates of the monetary value of these damages. Concern about air pollution focuses on the high concentrations of suspended particles, especially PM IO , which regularly exceed the WHO AQG (See Chapter 2). Figure 3.1 summarizes the information presented in Chapter 2 in a frequency distribution of population exposure to PM IO . The WHO AQG for PM IO (41 ~g/m3) is derived by multiplying the WHO AQG for TSP (70 ~g/m3) with a factor 0.55 which expresses the typical fraction of PM 10 in TSP. Health impact estimates are based on air pollution dose-response research conducted in the United States (Ostro, 1994). The methodology for deriving these estimates is described in the URBAIR Guidebook. The dose response equation~ used here are based on Ostro's work. Guidelines for acceptable pollution concentrations, also known as "no-damage benchmarks," have been proposed by WHO. Although damage to human health is not the only adverse impact of air pollution, the lack of appropriate data prevents the quantification of other impacts, such as a reduction in tourism, a particularly important source of earnings for Nepal. 3.2. IMPoRTANT Figure 3.1: Frequency distribution ofPM1 0 exposure (annual IMPACTS IN KATHMANDU average). Kathmandu Valley, situation 199211993. VALLEY Health. Although U.S. research relates to TSP concentrations, in this study it has been adapted and applied to PM lO , since these '0 particles are considered a " more serious threat to health W ~ 20,00 in Kathmandu Valley. a. The conversion from TSP to PM lO was done as follows: · PM lO concentrations are calculated from 8 22 38 52 68 82 98 112 128 microgram 1m3 (PM10) dispersion models using 47 48 Air Pollution Impacts actual PM lO emissions, and measurements of PM IO as control. · TSP dose-response relationship is converted to PM lO , using a ratio of 0.55 between PM lO and TSP concentrations. · WHO AQG, which is used as a "no-damage benchmark," is converted from TSP to PM IO , using the same ratio, 0.55. Tourism. An October] 993 article in Newsweek painted a pessimistic, but accurate image of the air pollution situation in Kathmandu Valley. Such negative publicity could have an adverse impact on tourism. In the early 1990s, foreign currency revenues amounted to approximately US$60 million a year. Although no "dose-effect" relationships of air pollution and tourism are available, it can be assumed that an approximate 10 percent decrease in tourism could lead to a loss of close to US$6 million for Nepal. This is a very significant amount of foreign exchange for a country that has a negative balance of trade. Moreover, indirect effects may have the same impact. This leads us to a tentative estimate ofUS$] 0 million, or NRsO.5 billion per year, in tourism losses due to pollution. The following sections deal with the impacts on death rates and illness, and their economic valuation in Kathmandu Valley. 3.2.1. Mortality Health impacts are divided into mortality (excess deaths) and morbidity (excess cases of illness). Mortality and morbidity rates are derived from air quality data using dose-effect relationships. In principle such relationships are derived by statistical comparison of death rates and morbidity in (urban) areas with different air quality. Dose-effect relationships for different pollutants for cities in the United States, have been compiled by Ostro (1994). Although the use of these relationships for Kathmandu may be speculative, until specific dose-effect relations are derived for Valley-like conditions, Ostro's dose-effect relations are the best available. While indoor air pollution such as that caused by cooking also damages health, this analysis is limited to outdoor concentrations. Mortality due to PM10 · The following relation between air quality and mortality is used: Excess death 0.00112 x ([PMJO] - 41) x P x c where P equals the number of people exposed to a specific concentration; c equals crude rate mortality = 0.0091 in Kathmandu (Shrestha, ] 995); PM]o is its annual average concentration ().lglm 3). A PMlO benchmark of 41 is used. It is assumed that mortality increases when concentrations exceed this number. From this relationship and the data presented in Chapter 2, it 2 can be concluded that excess mortality due to PM IO was about 85 cases, in a population of approximately 1 million. 3.2.2. Rlness (morbidity) Particles. The following health impacts can be attributed to particles: chronic bronchitis, restricted activity days (RAD), respiratory hospital diseases (RHO), emergency room visits (ERV), bronchitis, asthma attacks, and respiratory symptoms days (RSD). Results of calculations are detailed for reasons of consistency and not accuracy. URBAIR-Kathmandu 49 The following dose-effect relationships are used: · Chronic Bronchitis--Change in yearly cases of chronic bronchitis per 100,000 persons is estimated at 6.12 per mg/m3 PM lO . The total number of yearly cases of chronic bronchitis per 100,000 persons is 6.12 x ([PM IO ] - 41). 3 · RAD--Change in restricted activity days per person per year per mg/m PM lO is estimated at 0.0575. Ifwe use the WHO standard, the change is 0.0575 x ([PM lO ] - 41). · RHD--The change in respiratory hospital diseases per 100,000 persons is estimated at 1.2 per 3 mg/m PM lO . Using the WHO standard, the respiratory diseases requiring hospital treatment per 100,000 persons are estimated at 1.2 x ([PM lO ] - 41). · ERV--The change in the number of emergency room visits per 100,000 persons is estimated 3 at 23.54 per mg/m PM 10 , and the total number per 100,000 persons at 23.54 x ([PM lO ] - 41). · Bronchitis--Change in the annual risk of bronchitis in children below 18 years is estimated at 0.00169 x ([PM) 0] - 41). It is estimated that 46 percent of the population is composed of children under 18 years of age. (estimate based on communication with Professor Bimala Shrestha). · Asthma--Change in daily asthma attacks, per asthmatic person, is estimated at 0.0326 x ([PMlOl - 41). It is estimated that 20 percent of the population suffers from asthma (estimate based on communication with Professor Bimala Shrestha). · RSD--The number of respiratory symptoms days, per person, per year, is estimated at 0.183 x ([PM lO ] - 41). Table 3.1 combines dose-response relationships with the frequency distribution ofPM lO exposure (given in Figure 3.1) to derive total numbers of people impacted by various types of pollution and the economic valuation of these impacts. 3.3. VALUATION OF HEALTH IMPACTS Mortality. Attaching a monetary value to mortality is often the subject of ethical debate. However, the damage caused by air pollution would be grossly underestimated if mortality was omitted from the calculations. Two approaches can be used to estimate a monetary value for Table 3.1: Impact on mortality and health and their valuation (NRs) ofhealth impact in Kathmandu Valley. Value (NRs) Type of health impact Number of cases Specific Total (10 3) Excess mortality 84 340,000 28,644 Chronic bronchitis 506 83,000' 41,988 Restricted activity days 475,298 56 26,617 Emergency room visits 1,945 470·720 (600 in calculations) 1,167 Bronchitis in children 4,847 350 1,697 Asthma 18,863 450-4,170 (600 average in calculations) 11,318 Respiratory symptom days 1,512,689 50 75,634 Respiratory hospital admissions 99 4,160 415 Total 209,051 Shrestha's (1995) estimate is approx. NRs146,000, but this is not based on a discounted sum over 27 years. Discounting at a 5% rate leads to an estimate of NRs83,OOO. 50 Air Pollution Impacts mortality. The first approach is based on willingness to pay (WTP). The WTP approach is described in detail in the URBAIR Guidebook. In the United States, a value of approximately US$3 million per statistical life is often used. Although such a valuation is not readily transferable from one country to another, an approximation can be derived by correcting the U.S.figure by a factor of the purchasing power parity in Nepal, divided by the purchasing power in the United States. This factor is 930121,900 = 0.0425 (Dichanov, 1994). At an exchange rate of INR = US$0.02, the value of a statistical (VSL) life in Nepal is estimated at NR6.4 million (US$0.1275 million). The second approach is based on income lost due to mortality. VSL is estimated as the discounted value of expected future income, at the average age. If the average age of population is 23 years, and the life expectancy at birth is 60 years, VSL is: 36 VSL= L w/(l+d)t t 0 where, w equals average annual income (Shin et at, 1992) and d equals discount rate. In this method, the value of those persons who do not earn a salary, for example women who work in their homes, is taken to be the same as the value of those with a salary. With a yearly wage of NRs20,000 and a discount rate of 5 percent, the VSL is NRs340,000. Considering both approaches to the valuation of premature death, the cost figure associated with increased mortality due to PM lO air pollution in 1990 (84 cases) ranges from NRs28.3 million to NRs540 million. Morbidity. The valuation of illnesses should be interpreted with care as it is based on dose response relations derived in other parts of the world. More research is needed to derive relations that are specific for Kathmandu Valley. 3.4. HEALTH IMPACT AND ECONOMIC DAMAGE BY SOURCE CATEGORY In targeting and prioritizing actions, it is useful to know which pollution sources are the most harmful and the extent to which they have contributed to health damage. Given the present data, it ~s impossible to identify the relative contributions of all the source categories; however, we do gain some insight into the relative importance of each by estimating their marginal contributions to total particulate pollution. Table 3.2 presents the results of these calculations. The first two columns summarize emissions data as presented in the emissions inventory (see Appendix 3). The third column indicates the assumed changes in emissions which were evaluated in the air quality model (see chapter 2). The fourth, fifth and sixth columns summarize the additional damages caused by pollution, for example change in respiratory symptom days, and the estimated costs associated with these changes. The last column presents the estimated marginal "damage costs" and "benefits" of changes in emissions (change in health damage costs divided by the change in emissions). URBAIR-Kathmandu 51 Table 3.2: Marginal impacts (rom different sources. Source Emissions Change in Change in Change in Change in health Marginal (ton) Emissions (%) Mortality RSD (1,000) damage (NRs costslbenefits thousand) (NRslkg) Traffic (exhaust) 440 25 20 354 48,952 10 10 180 25,351 576 -10 -6 -108 -15,037 341 ...................................................................................................:??......................:~....................:.1.?9................................. ::?~!.1.~.~........................................., Resuspension 400 25 12 219 30,273 10 9 165 22,842 571 -10 -2 -35 -4,903 122 ....................................................................................................:??......................:!....................:.~.?.~..................................:!!.!.?~.?.......................................... Domestic 1160 25 23 407 56,238 10 13 227 31,367 270 -10 -9 -155 -21,360 185 ....................................................................................................:??................... ::!~....................~??.~.................................::?.~!.Q~.? .......................................... Brick (Bun's trench kilns) 1250 25 25 443 61,199 10 13 229 31,688 253 -10 -3 -57 -7,832 62 ....................................................................................................:??................... :.~.~....................:.?.?.~..................................:?!.!.~?1.........................................., Hoffman brick kilns 25 45 0-3 446 -25 0 -6 ·765 These calculations are based on an earfier version of an air quality damage model in which roadside air exposure is not taken into account. Therefore, this model tends to under estimate the impacts or the air pollution, e.g, mortality is estimated at 65 instead of 84, as mentioned in the section above. It can be seen from the data in the last column of the above table that changes in traffic sources (exhaust emissions and resuspension) may have the largest impact on health. An increase in emission of 1 kg increases health damage by NRs570. This is followed by domestic sources and Bull's trench brick kilns (NRs270 and NRs250, respectively). These results are generally reflected in the ranking of marginal benefits of emissions reduction. Reduction of vehicle exhaust emissions is the most effective in terms of reduced health damage (NRs341 per kg emission reduction). Next in order of importance is "reduction of domestic emissions" (NRs185 per reduced kg of PM IO emission). In absolute terms, however, the reduction in domestic emissions yields the greatest benefits. Preliminary calculations (not shown here) indicate that a reduction of the diffuse (non-stack) emissions of the Himal cement plant will have marginal benefits of similar magnitude to domestic emissions, up to NRs300 per kilogram emission reduction .. 3.5. CONCLUSIONS Damage caused by air pollution has many components: human and ecosystem health, physical materials, vegetation and crops, buildings and monuments, visibility reduction and tourism. In theory, all this damage can be assessed. In practice, however, the absence of empirical dose effect relations makes this assessment difficult. Health damage consists of mortality and morbidity. If the human capital approach (i.e. lost earnings due to premature death) is used, the value of a statistical life amounts to approximately NRs340,OOO. The total excess mortality is then valued at NRs28.3 million. 52 Air Pollution Impacts The willingness-to-pay approach yields a "damage value" ofNRs540 million. Health impacts are assessed using dose-response relations derived in the United States, and the air quality model developed for Kathmandu Valley (Chapter . Key data are excess mortality totaling 85 cases, and the number of respiratory symptom days at about 1.5 million. Cost estimates of morbidity are more reliable than the estimates for mortality. These consist of foregone wages and costs of medical treatment. The costs of morbidity resulting from PMlO were assessed specifically for Kathmandu Valley. Morbidity costs are valued at about NRs180 million, and total health damage at NRs21 0 million (with lost salary as the value of statistical life). This valuation of damage approach to human health tends to be underestimated, as suffering due to illness or premature death is not included. An analysis of the marginal impacts of emissions increase and reduction by source categories showed that the health impacts are mostly affected by developments in the transport sector, while domestic sources and brick manufacturing rank second in this respect. It is difficult to value the damage to Kathmandu's cultural assets such as its temples and monuments. However, there is a good reason to believe that tourism has ben negatively affected by pollution. The yearly revenue from tourism is US$60 million. If we assume a reduction of 10 percent, and if the indirect economy-wide impact of a reduction in tourism is of the same magnitude, the total economic loss related to pollution can be estimated at roughly NRsO.5 billion. 4. ABATEMENT MEASURES: EFFECTIVENESS AND COSTS 4.1. INTRODUCTION This chapter outlines measures that are appropriate for reducing air pollution in Kathmandu Valley. They are chosen based on their effectiveness in controlling emissions, the benefits associated with the reduction in emissions, and the cost of implementing the measure. The same criteria may be used in drafting an action plan. The chapter is organized by the source categories: traffic; fuel combustion in industries or homes, construction, and refuse burning. For these source categories, measures are described in terms of their: · effectiveness in reducing emissions and associated impacts in the year 1992/1993 (according to the methodology used in Table 3.2); the reference data are mortality 85 (due to PM lO), and number ofRSD 1.5 million in 1990 (Table 3.1); · cost; · benefits, including reduced mortality, RSD, and other economic benefits; · policy instruments and institutions that would be needed to implement these measures; · time schedule in which a particular measure can result in emissions reduction (short term, 2 years; mid-term, 2- years; long term, more than 5 years). All emission figures, costs, and benefits represent annual estimates for 199211993, unless otherwise stated. The list of measures is derived from the information presented by local consultants, URBAIR Guidebook, and from earlier plans that have addressed segments of the air pollution problems in Kathmandu Valley. Measures to address process emissions, construction and open burning, were not addressed because of the lack of data specific to Kathmandu. 4.2. TRAFFIC This section describes the effectiveness (abated emissions) and, to the extent possible, the benefits of measures such as: · implementing an inspection and maintenance scheme and, addressing excessively polluting vehicles, · improving fuel quality, adulteration of fuel, improving diesel fuel quality, introducing unleaded gasoline, improving the quality of lubricating oil in two-stroke engines; and · adoption of clean vehicle emissions standards. 53 54 Abatement Measures: Effectiveness and Costs 4.2.1. Implementation ofa scheme for inspection & maintenance Effectiveness. Maladjustment of fuel injection or carburetors and worn-out parts not only pose a hazard to traffic safety and increase fuel consumption, they also cause large emissions. A scheme requiring annual inspection and maintenance (I&M) would result in a reduction in the emissions ofPM IO, VOC (unburned hydrocarbonsIHC), and co. A 1993 study titled, "Pollution control of motor vehicles by introducing effective maintenance/repair works" (Thapathali Campus, Institute of Engineering, 1993), conducted within the framework of the Kathmandu Valley Vehicular Emission Control Project (KVVECP), evaluated the effects of maintenance and repair on smoke levels in exhaust gases of a sample of diesel vehicles by measuring with Hartridge Smoke meters. The results suggest that simple maintenance leads to radical improvements in fuel efficiency, and smoke levels can be reduced by 20 to 50 percent in a very cost efficient manner. The results of this research support an estimate (Mehta, 1993) for Manila, and one made by the Indian Automobile Manufacturers (AIAM, 1994) for the situation in India. The KVVECP study also studied gasoline vehicles, measuring the amounts of CO and HC (VOC) in exhaust gases. The results indicate possibilities for reducing emissions at no cost. Local measurements, therefore, support the Table 4.1: Recommended steps in an Inspection & Maintenance assumption that the scheme (Tuladhar, 1993). proposed, Diesel engine Gasoline engine comprehensive, Air filter Air filter inspection and Fuel filter, tappet settings Fuel filter, tappet settings maintenance scheme Injector Nozzle pressure Ignition system (Spark plugs, Contact pOints, distributor etc.) would reduce Injector pump calibration Carburetor emissions ofPM lO , Engine compression check up Engine compression check up VOC, and co by a Engine overhaul Engine overhaul third (35 percent reduction in tail-pipe emissions). From Table 3.2 it can be inferred that the benefits of such a scheme exceed NRs25 million. Costs. Vehicle-emission testing capacity is presently insufficient. The lack of capacity among 3 government agencies can be compensated if testing is done by private firms. The cost of a single test is estimated to be 1\~100. This estimate is based on proposals (tests, including, roadworthiness) which have been made for Indonesia (Budirahardjo, 1994), and Manila (Baker et aI, 1992). Based on the findings of the KVVECP study, it is assumed that maintenance costs will be off-set by the reduction in fuel costs associated with improved engine performance. Policy instruments and target groups. A study of Thapathali Campus (1993) revealed a lack of awareness of the adverse environmental and economic effects of poor maintenance (breakdown A set-up of such scheme might be: firms are licensed to cany out inspection; authorities spot-check the firms whether inspections are made properly; vehicles which pass the test get a sticker valid for a specific period, drivers show test report upon request; vehicles are spot-checked. l.JRBAIR-Kathmandu 55 maintenance). This was true for both private owners, as well as fleet owners (government). This suggests the need for an awareness program which can convey the message that it pays to maintain vehicles. Eventually, inspection and maintenance could be made mandatory through a legislation which sets emissions standards (and road safety standards). The enforcement of emissions standards is the most critical component of this measure. Spot-checks by the traffic police may be the most practical approach (Mathur, 1993, Garrat, 1993). Term. An awareness program could be designed and developed within one year. A mandatory inspection and maintenance scheme could be implemented within five years. 4.2.2. /mprovingfuel quality This measure has four components. They include addressing adulteration of gasoline, introducing low-lead and unleaded gasoline, "clean H diesel, and improving the quality of lubricating oil in two-stroke engines. 4.2.2.1.Adulteration of fuel The adulteration of gasoline by adding diesel is believed to be a common practice in Nepal. The government pricing policy has led to a large gap between the prices of diesel and gasoline, making the former much cheaper. Adulterated fuel used in motorcycles and other gasoline vehicles results in increased emissions, as well as increased wear and tear of the engines. The exact extent of this practice and its adverse environmental effects have not been quantified. 4.2.2.2.Introduction of unleaded gasoline Unleaded gasoline not only removes the problem of lead pollution in emissions, it is also a prerequisite for the introduction of strict emissions standards. An "intermediate" approach to removing all lead is to lower the lead content of gasoline. Fuel distribution systems must ensure that unleaded and leaded fuels are not mixed. Retailers usually sell both types of fuel. This is crucial in the phase when unleaded gasoline is being introduced. The catalytic converters on new cars would be ineffective if leaded gasoline is used. Older engines may continue to use leaded fuel because of the lubrication needed for their valve seats and/or because they require a higher RON-number fuel. Effectiveness. Emissions are proportional to the eventual market shares of unleaded/low-lead gasoline and, in the case of low-lead gasoline, the content of lead. Costs of the measure. Gasoline, diesel oil, and fuel oils are not produced in Nepal. The Nepal Oil Corporation imports all fuel through India (Indian Oil Corporation). Therefore, there is little to no possibility of importing clean fuels until such time as clean fuels are more widely marketed in India. Recently, unleaded gasoline has been introduced in India. Gasoline that has a lower amount of lead needs to be reformulated so that it retains the required properties (RON number). In order to obtain gasolines with sufficiently high RON numbers, the lead compound is substituted with oxygenated compounds. MTBE (Methyl-tertiary butyl-ether) is a preferred substitute. These changes lead to an increase in production costs, 56 Abatement Measures: Effectiveness and Costs typically in the range of NRsO.5-1 per liter of gasoline, depending on the local market for refinery products, required gasoline specifications and the costs ofMTBE (Turner et ai, 1993). It is expected that similar costs would result if the Indian petroleum industry were producing unleaded gasoline. Policy instruments and target groups. Considering the supply situation, the appropriate measure would be to support the production and distribution of unleaded gasoline in India so that it can be imported to NepaL Term. Widespread availability of unleaded fuel could be implemented within five years, provided it becomes available in India. 4.2.2.3.Improving diesel quality Diesel's ignition and combustion properties explain PM IO emission from diesel engines (Hutcheson and van Paassen, 1990, Tharby et ai, 1992). Volatility (boiling range) and viscosity (including its cetane number, an indicator of the ignition properties) of fuel determine ignition and combustion and, consequently, PM IO emission. In Nepal, the specified cetane number of diesel used for automotive purposes is 42. In the United States, Western Europe, and Japan the corresponding quality requirement varies from 48 to 50. Detergents and dispersants added to the fuel also determine its quality. These additives keep injection systems clean and have discernible effects on efficiency (Parkes, 1988). 4 Effectiveness. Improving the quality of fuel by increasing the cetane number and adding detergents, results in a decrease of 10 percent in PM 10 emission, about 25 tons as an order of magnitude (AlAM, 1994, Mehta et ai, 1993). A reduction in the sulfur content leads to a proportional fall in emission of SOz. In addition, PM IO emission declines because a part of the particles emitted consist of sulfates that originate from the sulfur in the fueL Costs. The cost of improving diesel fuel, particularly by increasing the cetane number, is determined by the oil-product market, refmery structure (capacity for producing light fuels, visbreaking, hydro treating etc.), and the government's role in the national market. The government sets the price-at-the-pump for fuels. Desulfurization of fuel at the refinery contributes the main cost. The costs per liter for a reduction from 0.7 percent to 0.2 percent are in the order of magnitude ofNRsO.5 per liter. At combustion, sulfur in diesel fuel forms corrosive sulfuric acid. Therefore, a reduction in the sulfur content has a financial benefit because it reduces the costs of vehicle maintenance and repaIr. The benefit of improving diesel quality is about NRs7.5 million. Policy instruments and target groups. The barriers to the introduction of low sulfur fuel are similar to those that are encountered in the introduction of low-lead gasoline: an improvement in The physico-chemical properties - as expressed in the cetane number - of diesel fuel influence the magnitude of the emissions of TSP of diesel powered vehicles. The relation between these properties (such as volatility, viscosity) and the production of TSP in a diesel motor is not straightfOlward; the characteristics of the diesel motor, its load and its injection timing plan are parameters that complicate the picture. URBAIR-Kathmandu 57 the quality of diesel fuel depends on energy policy in India. The India Oil Corporation must make the necessary investments to expand the capacity for producing improved quality diesel. Term. The typical period for a required adjustment of Indian refmeries (such as extension of visbreaking capacity) is about 3 to 5 years. 4.2.2.4.lntroduction of low-smoke lubricating oil for two-stroke, mixed-lubrication engines There are a large number of motorcycles and tricycles, both equipped with two-stroke mixed lubrication engines in Kathmandu Valley. These vehicles contribute about 100 tons of the PM IO emission (through exhaust gases) from road traffic. The particles emitted by these vehicles take the form of small droplets of unburned lubrication oil. According to Shell (private communication, 1993) the lubricating oil used in most Southeast Asian countries is cheap and has poor combustion properties. Effectiveness. It is assumed that using better quality lubrication oil could halve emissions (50 tons reduction). A 50 ton emissions reduction corresponds to NRs 15 million (order of magnitude, data from Table 3.2). Costs. Introduction of these oils will in the first estimation double the costs of lubricating oil. We 5 estimate the annual consumption of these oils at 250 kg. The total cost of low-smoke oil would be NRs12,500. The benefit would be NRs2.5 million. (Table 3.2) Policy instruments and target groups. The importers of lubrication oil are the main target groups. 4.2.3. Adoption ofclean vehicle emissions standards Many countries with severe air pollution problems have adopted standards for allowable vehicular emissions. Current standards require vehicles which have four-stroke gasoline engines to be equipped with exhaust gas control devices, based on the use of three-way catalysts (closed loop systems). A few countries, including Austria and Taiwan, have also set standards for motorcycle emissions, requiring two-stroke engine powered vehicles to be equipped with open loop catalysts. The latter devices control emissions ofVOCs (PMIO) and CO, not NO".6 Regular inspection and maintenance and the availability and use of unleaded gasoline for automobiles, are prerequisites for the successful adoption of clean vehicle standards. The catalyst technology cannot be used in conjunction with leaded gasoline. The fuel's sulfur content should also be low (less than 500 ppm). Therefore, the introduction of clean vehicle standards involves a 7 structure for producing and distributing unleaded gasoline. 5 Gasoline consumption is estimated at 28.3 x103 kllyr. (Table 1.2). Assuming that about half is used in two-stroke engines and there is an average content of 2 to 5% lubricating oil in gasoline, brings an estimate of roughly 250 kg. of lubricating oil 6 Weaver, C.S. and Ut-Mian Chan, P.E. (1993) Motorcycle emission standards and emission control technology. Draft report. Report to the World Bank and the Thai Govemment. Sacramento, EF &EE. To maintain the operation of the catalyst, it is absolutely necessary to avoid the use of leaded fuel. A single gram of lead will contaminate the catalyst and render it useless. In addition lead destroys the oxygen sensor of the fuel injection system. 58 Abatement Measures: Effectiveness and Costs Diesel engine-powered vehicles can also be regulated. Emissions standards commonly imposed in many industrialized countries can be met by adjusting the maintenance plan and the design of motors. Tail-pipe emission treatment, as well as retrofitting buses with abatement .equipment are also options. Further reduction of diesel engine emissions requires the use of exhaust gas control equipment. In addition, the quality of diesel must also be improved .. 4.2.3.1.Effectiveness Closed-loop catalytic treatment of exhaust gases (three-way catalysts) from gasoline-engine typically reduces all exhaust emissions, including NO l' , CO and VOC by 85 percent. In addition, lead emissions are eliminated, because unleaded fuel is a prerequisite for the use of three-way catalysts. Open-loop catalytic treatment of exhaust gases of two-stroke motorcycles generally reduces CO, VOC and PM lO (oil mist) emissions by 90 percent. These catalysts also require the use of unleaded gasoline. An alternative would be to use well-designed and maintained four-stroke engines. We estimate that a similar emissions reduction could be obtained, If all gasoline vehicles (including motorcycles) had been equipped with catalytic converters, the emissions would be lower by 150 tons, mortality would be reduced by about 10 lives, there would be 200,000 fewer RSD, and the overall health costs avoided would total US$75,000 (Estimated from Table 3.2). Health improvements as a result of reduced lead pollution should also be added to these benefits. Costs. Due to methodological difficulties, it is not possible to calculate the total cost of introducing these standards in Kathmandu Valley. However, costs can be estimated on a vehicle by-vehicle basis. · The cost of closed-loop catalytic treatments of exhaust gases arises from the extra purchasing costs of vehicles. In the United States, this increase averages about US$400, ranging from US$300 to US$500 (Wang et al, 1993). While catalytic devices have a minor adverse effect on fuel economy, this cost is offset by an increase in the lifetime of replacement parts such as the exhaust system. The total annual cost per automobile is estimated at NRs5,000 (NRs2,500 depreciation per car, and NRs2,500 extra fuel costs). · The cost of open-loop catalytic treatment of exhaust gases is related to increased purchasing costs of the equipment. Benefits include lower fuel costs due to improved operation of the engine. Taiwan adopted standards that require the use of open-loop catalytic devices which result in US$60-80 costs increase. This is offset by fuel savings (Binnie & Partners, 1992). The total annual cost is estimated at NRs3,500 per vehicle (depreciation plus increased fuel costs). It is assumed that the cost of motorcycles is similar to the cost of four stroke engines. The higher price of unleaded gasoline, due to increased costs of production, and the adjustment of the logistic system (modification of pump nozzles) should also be considered here. A very rough estimate of the cost is US$100 annually per vehicle (NRs2,500 depreciation of control system plus increased fuel costs in the amount of NRs2,500, depending on the subsidies/levies on gasoline). URBAIR-Kathmandu 59 Policy instruments and target groups. The groups involved in the introduction of "clean" vehicles are: · petroleum industry and gasoline retailers (introduction of clean cars requires the availability of unleaded gasoline); · Indian car and motorcycle industry; · workshops that must acquire the skill for maintaining clean vehicles; and · vehicle owners who have to pay the price. Term. In practice, standards are set only for new models of cars and motorcycles. It is too expensive to equip existing vehicles with the necessary devices. Practically all new vehicles currently sold in the world market are equipped with catalytic control systems. The effect of these standards becomes apparent gradually, reflecting the rate of replacement of existing vehicles. 4.2.4. Improved abatementlother propulsion techniques The United States and Europe are considering the tightening of standards. Possibilities are: · improving current techniques for abatement; · improving inspection and maintenance, because a small numbers of maladjusted/worn-out cars cause disproportionally large emissions; and · enforcing the use of "zero-pollution" vehicles (for example, electric vehicles in downtown areas.) Diesel engines are a bottleneck in decreasing automotive emissions because, unlike gasoline engines, it is not possible to treat their exhaust gases with easily available devices such as catalytic converters. Diesel engines, however, are better with respect to CO emission. 4.2.5. Addressing resuspension Resuspension is clearly a high priority·issue. Unfortunately, there is no quantitative information about measures appropriate for Kathmandu. Possible measures to tackle resuspension include improving the surfacing and periodical cleaning of roads. 4.2.6. Improvement o/traffic management Traffic management includes a variety of measures such as traffic control by police or traffic lights, one-way streets, construction of new roads, and road-pricing systems. Traffic management addresses the problem of congestion. Curbside management of traffic also may improve air qUality8. At the city level, traffic management may actually increase air pollution because it usually results in increased use of the transport system. Although downtown air quality improves with traffic management, leading to a decline in "road-exposure," in terms of total exposure the net result may be small. Improved traffic management may have other environmental benefits such as a lessening of noise and congestion, and safer roads. &Accelerating vehicles, a dominating feature of congested traffic, emit disproportionately large amounts of pollutants. 60 Abatement Measures: Effectiveness and Costs 4.2. 7. Construction and improvement ofmass-transit systems A methodology to assess the costs and effectiveness of improving the Kathmandu Valley public transport system involves: · describing a future system appropriate for Kathmandu Valley; · assessing the performance of such a system - (passenger times kilometer); · calculating the costs of construction; · describing the baseline (future situation without such a system); · estimating avoided emissions; · outlining the non-environmental benefits; and · designing a scheme to identify the environmental costs and benefits. The cost of constructing a mass-transit system is high, and projects cannot be justified from an air pollution point of view alone. If proposals to build mass-transit systems are initiated from a non-environmental point of view, they should be supported in the environmental policy. Trolleybuses are operated in Kathmandu. These are electrically powered and do not emit exhaust pollutants. This system could be expanded to provide increased public transport. 4.3. INDUSTRIAL COMBUSTION (EXCLUDING BRICK MANUFACTURING) Major industries in this category include carpet manufacturers, the food industry, and metal products. These industries operate boilers that are fired with fuel oil (HSD) and agricultural wastes (e.g. rice husks). Very little information is available about emissions from this category. Therefore it was not possible to evaluate measures such as good housekeeping practices, fuel substitution, and encouraging energy efficiency in greater detail. 4.4. BRICK MANUFACTURING Brick manufacturing is a major source of pollutants in Kathmandu Valley (see Table 13 in the emissions inventory, in Appendix 3). Currently two brick producing technologies are used. The most important is the Bull's trench kiln technology (Chimney Bhatta) which accounts for about 80 percent of the brick production, and for over 95 percent of the PM lO emission from the brick industry. The other technology is the Hoffmann (Chinese) kiln type. A third brick manufacturing technology (Vertical Shaft Brick Kiln) is currently being tested (NESS, 1995). This type of brick manufacturing is relatively clean from the air pollution point of view, but it has a high rate of brick breakage (NESS, 1995). NESS (1995) extensively studied the economic situation of the brick industry and the problems that factory owners face. The study concluded that the availability of land and fuel are primary problems. As fuel costs are a significant portion of the cost of brick production, measures to improve the energy efficiency of kilns are beneficial to both the environment and the economy of brick manufacturing. The NESS study (1995) proposes simple techniques to scrub the flue gases in the chimneys of the Bull's trench kilns. These proposals do not fully elaborate the expected effectiveness of the device, its power consumption, the availability of scrubbing water and its effect on the draft of the chimney. URBAIR-Kathmandu 61 De Lange (1989) suggested a number of simple technological improvements such as improved thermal insulation, mechanical draft, etc., to improve the energy efficiency of kilns. A decrease in fuel consumption would reduce emissions as welL Replacement of coal and biomass with electricity would also be an option if consistant electricity supply was available. 4.5. DOMESTIC EMISSIONS AND REFUSE BURl\'JNG Local stoves, also known as chullas, are the main cause of domestic emissions. The amount of emissions from these stoves is second only to brick manufacturing (see emissions inventory in Appendix 3). Traditional cooking with chullas is problematic from several perspectives. It constitutes a threat to public health (indoor pollution), particularly for women; it wastes energy; it depletes natural forest resources" and it has an adverse effect on outdoor air quality. Traditional cooking with fuelwood and agricultural waste is extremely energy inefficient. Improved cooking stoves that have an energy-efficiency of 20 percent, as compared to traditional stoves that are 12 percent efficient (Malla and Shrestha, 1993), constitute part of a solution. The introduction of improved cooking stoves is, from an environmental viewpoint, a highly effective approach to improve air quality. There is little information about the improved stoves attractiveness to traditional households that are usually low-income, therefore no cost effectiveness estimates have been presented here An alternative approach to reducing the emissions from cooking is to foster the use of kerosene as a cooking fuel. A scheme for subsidizing the use of kerosene, if feasible, might be an appropriate instrument to reduce the use of fuelwood. Refuse burning can be avoided by extending the public refuse collection system. 4.6. CONCLUSIONS This chapter describes a number of measures that are appropriate for improving the air quality in Kathmandu Valley. It deals with several aspects of the measures: effectiveness, costs, benefits, implementation, and the institutions involved. The benefits in terms of reduced health impacts and other damages, together with the costs of implementing each measure, provide information on how to prioritize these measures. The quantitative information presented is often characterized in order of magnitude. Measures to address traffic emissions are dealt with in greatest detail because the traffic related causes of pollution are clearly recognized and documented. An abatement measure that stands out from a cost-benefit point of view is the routine maintenance of vehicles. The costs to vehicle owners are offset by benefits in terms of reduced fuel costs. The benefits from reduced health damage costs should also be added. Due to a lack of data, cost estimates are not made for measures other than those in the transport sector. This is a serious drawback because some of these sources -- particularly Bull's Trench brick kilns, and domestic use of fuelwood and agricultural waste -- are almost equally important sources of PM 10 exposure in the Kathmandu Valley. 5. ACTION PLAN The following action plan is based on the cost-benefit analysis of various measures that reduce air pollution and its damages. The Plan is based on available data, the shortcomings of which have been identified throughout the text. Improving the database is necessary in order to extend the action plan to include additional measures. The "actions" consists of two categories: 1. Technical and other measures that reduce the exposure and damage. 2. Improvement of the data base, and the regulatory and institutional basis for establishing an operative AQMS in Kathmandu Valley. The time frame in which the actions or measures could be implemented, and would be effective, is indicated: short term (fewer than 5 years), medium term (5-10 years), long term (more than 10 years). 5.1. ACTIONS TO IMPROVE Am QUALITY AND ITS MANAGEMENT 5.1.1. Actions to improve air quality Actions and measures have been proposed by the Kathmandu Valley URBAIR working groups, The list of measures proposed by the URBAlR working group is presented in Table 5.3. The proposed actions/measures have been put in the following categories: 1. Air quality monitoring 2. Inventory/dispersion modeling 3. Institutional and regulatory framework 4. Traffic management 5. Transport demand management 6. Land use planning 7. Fuel switch 8.. Improved fuel quality 9. Technology improvement 10. Awareness raising 11. Further studies 12. Water supply and sanitary management 13. Solid waste management and recycling The following sources are of equal importance both in terms of health impacts, and in reduction in visibility. · Vehicle exhaust (diesel and gasoline) · Domestic fuel combustion · Resuspension from roads 62 URBAIR-Kathmandu 63 · Bull's Trench brick kilns. Vehicle exhaust is the most Table 5.1: A list oftechnical pollution abatement important source in terms of measures, important for the reduction ofthe air pollution reducing health damage. e.ffects in Kathmandu Valley (.x.:o: more important than Xl. Uncontrolled emissions from Abatement measure Short· Medium- Long· Himal Cement Factory are term term term important determinants of Technical measures, vehicles visibility. 11M scheme, comprehensive xxx Improved motorcycle technology xx xx Table 5.1 presents a list of Clean vehicle standards xx xx technical measures, with an Improved abatement/new propulsion techniques xx indication of the importance of Fuel quality the measure to reduce pollution, Control adulteration xxx Introduction in the short, Low·lead gasoline xx medium, and long term is Unleaded gasoline xx indicated. Proposed measures are Improved diesel quality xx xx Low-smoke lub. oil, 2·stroke engines xxx economically feasible in the Road resuspension indicated time frame. The Road cleaning, garbage collection xxx measures are not described in Domestic emissions great detail. The list does not Improved cooking stoves )( xx represent a ranking based on Switch to kerosene )( xx Brick industry cost-benefit ratios. Improved technology )( xx The success of abatement measures rests with the enforcement of the action. It is important to ensure that conditions are met for carrying out the necessary technical improvements/adjustments. This may mean ensuring sufficient workshop capacity and capability for efficient adjustment of engines, the availability of spare parts at a reasonable price, environmental education and outreach via television, newspapers and other media. Additional measures include traffic managment and transport demand management, including land use planning. Expansion of the trolley bus system and electric vehicles in Kathmandu can also be supported from a local environmental point of view. Additionally, "Adopt-a-Street" could be used to promote private sector participation in socially responsible environmental management and awareness raising. Making streets safer for non-motorized vehicles, and pedestrians and not only for more motor vehicles is another priority. 5.1.2. Actions to improve the Air Quality Management System Actions to refine air quality management include improving the following: · Air quality assessment, · Assessment of damage and its costs, · Inventory of abatement measures, · Institutional and regulatory framework and · Awareness among the public and policy makers. 64 Action Plan Actions to improve air quality management are summarized in Table 5.2, together with other necessary improvements. Table 5.2: Actions to improve the Air Quality Management System ofKathmandu Valley. Air pollution monitoring Establish a monitoring system, covering: · compounds such as TSP, PM10, combustion particles, black smoke, CO, visibility, etc. · sites, such as traffic exposed, city background, brick kiln area, rural, hilltop, etc. · long term operation · continuous monitors, where available Indoor air pollution study. ...............................................................................~p.:9.~~~~.!~~~!9EY.~.~~!~.~!!~~..g~~ll~.p.~~!!.9!..~Y.~!~.r:~!;.................................................................... Emissions Improved, comprehensive fuel statistics. Establish/improve emission factors for vehicles, brick kilns, domestic fuel combustion, resuspension. Study particle size distribution of emissions from various sources, as well as for the ...............................................................................~!!!~!~.~~.P.9]]~.~9!!.: ....................................................................................................................................... ..~9!?~l~.~.~~..~P.??~.~...................................... ~~!~.~l!~~..~p.p.!'!?P.~~!~..~!?~~!!?~.!!!99.~!.!.~~..~~!~.'!!~.r:!~.y.~!!~y.;.................................................... Assessment of damage and cost Epidemiological research, assessment of specific health costs. Empirical study of tourism and environment (tourists attitudes). ...............................................................................!9.~~y~~~y.~~..~!.!.r:!!~:.~?~.~f..~!!~~.p.~~~~.!~.~.~!~~::.~.::.~~r.~~!!!~.~.!:._ .......................................... Inventory of abatement measures Effectiveness (abated/avoided emissions). Costs. u ...............................h Non-environmental environmental. . . . . . . . . . . . . . . . . . . ,.. . . . . . . . . u n. . . . . . . . . . . . . . ~~d . . . . . . . . ~_ · · · a.. . . . . . . n ..u . . . . .n u . . . . . . . u " u u ...... u . u .... n . . . . .~ . . . . . . . . . . . . . . . . . . . . . . u ·· n~u . . u ....'" . . . . . . . . . . . . . . . . .u n. . . . . . u . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .n n. . . .u u Institutional and regulatory framework Involvement of the Nepal Oil Corporation. Tax differentiation between clean and dirty diesel, if there areways of importing clean diesel ...............................................................................!..~~..~h~..~~.?~.~~~~~!'Y.!..~~~.'::~~P...~!~~~.~~~!:!~!99.~~~........................................................................... Awareness building Publicity campaigns on billboards and in the media to raise attention to issues, e,g. smoke-belching, health damage, and expected developments if no actions are taken). Environmental education in schools. Organization of environmental education courses. Setting up an environmental information center. Support of environmental NGOs. ~ Table 5.3. Propf!sed actions andlnea.'mres to i'!!J!!ove the ai,- quality olJ(ath",andu Valley. ~ What How Category 1. Ambient Air Quality Monitoring, Inventory and Dispersion Modeling When Who Remarks ~ I. Air Quality Monitoring ~ 1. A. Design naUonal air quality - Review national air polluUon status and assessment ASAP NPC/EPC, DOHM, DOTM Monitoring ambient air quality will be ;. monitoring program. capabilities; trusted to DOHM with close cooperation a ~ · Establish field stations and base laboratory 1995 with MOl and MOWT and NGOs = c. B. Design and establish - Tap funding agency support; 1995 NPC/EPC/DOTM, DOHM = quality assurance system ·Identify needs, and gaps in the existing facilities; ASP Donors, community, NOG, (evaluation of sites, number and -Determine air pollution impact on health DOHM consultants, academic location) 1995 MOH, consultants II. Inventory and dispersion modeling 1.. Design/Develop a - Coordination with academic, policy-making body, ASAP DOHM, MOl, Academic comprehensive emission implementing agencies such as MOWr. MOl, consultants, NPC/EPC inventory procedure including DOHM, DOTM. emission factor review and · Funding support such as MEIP 1995 on DOHM, NPC consultants update, (all sources) and cost going 2. Improve emissions inventory - mass balance approach 1995 on Consultants, DOHM, MOl, of both mobile and stationary going DOTM sources. 3. Conduct inventory of - Coordinate with indoor-air pollution program SIS academic consultants Coordinating with donors domestic emission Category 2. Traffic Demand Management and Infrastructure Improvement 1. Improve traffic flow - Remove obstructions (unloaded building materials, 1995 - DOR, DOTM municipalities, MOWT/MLD/MHPP will develop a a. Improve existing road roadside vendors, altemate parking facilities, repair onwards Traffic police comprehensive plan and traffic police as network and service shops, etc.) well as municipalities will serve as b. Introduce traffic man- enforcing agencies agreement concept · Synchronize and optimize repair roads 1995 · DOR, DOTM municipalities onwards · Ensure proper coordination among different units of - DOR, DOTM, NEA, NTC, govemment for digging. NWSC, municipalities, NEA, NTC, NWSC · Radial roads and public transportation facilities. DOR,UCC c. Extend/develop road network Implement the recommendation of Urban Road 1993 DOR, MOWT, DOTM, MHPP, Development Master Plan (JICA study report onward municipalities 0\ VI 01 01 Table 5.3. Proposed actions anti measures to improve the air qu,l!lity 0/ Katl'man.t!u,Yl!I!~. What How When Who Remarks d. Improve facilities for non- Construct pedestrian overpasses and sidewalks 1994 DOR, municipalities, DOTM motorized traffic onwards e. Implement Transport Service Study the implementation of a private car utilization DOTM, Traffic Police, DaR Rationalization Program restraint policy which would include: - limit entry within certain areas; - define and mark the lanes and enforce the rules; 1994 - encourage carpooling through demand 1995 management measures like parking regulations by onwards charging a higher parking fee; - designate where public utility vehicles (buses, taxis, 1994 etc.) can stop. f. Immediate Improvement of Rationalize/standardize traffic laws, rules and 1994 MOWT, DOR, DOTM, Traffic EnforcementlTraffic Laws regulations by enacting traffic code and use standard police form; Provide proper training to enforcers drivers and 1994 DOTM, Traffic Police require them to pass exams; onwards Set up monitoring and evaluation system for 1995 DOTM, Traffic police enforcers and for violators; onwards Effect traffic safety seminars and traffic rules and 1994 DOTM, Traffic Police regulations re-education Use mass media for information dissemination 1995 DOTM, Traffic Police, All Media onwards 2. Introduce and expand Create technical group to evaluate existing Action Traffic Police, MOH computerized information information system and prepare plans. Result system at traffic police 1994 3. Strenathen Traffic Safety Establishment of wide walk network 1995 DOR, DOTM Organize traffic safety seminars/weeks and also re 1994 education of traffic rules and regulation. onward > .... / ") Immediately strengthen traffic police/traffic DaR, Traffic Police o· 4. Expansion of public lights/zebra crossing for traffic improvement Advocate and support 1995 MOWT, DOTM = ~ ~ transport/system 5. Provide environment friendly Extend trolley bus network 1994 MOWT, NTC = transportation onwards ~ Table 5.3. Propl!~~d actions and measures to;,11tprove the ai,.quality ofKathmandu Val~ey. ~ What How When Who Remarks ~ 6. Survey present mass transit Implement survey results situation and improve: - time schedules, - junctions and stations 1994 onwards DOTM - ~ ::r !3 I» Category 3. Land Use Planning and Management = c.. 1. Land use planning to reduce Workout strategy for dispersing facilities (shopping, SIS MHPP,OOB,OHUO,OOTM MHPP/MLP are the key actors = transport demand etc.) so that these are closer to users and generate less traffic 2. Update land use Update land use and pass new zoning SIS MHPP,DHUD plans/GLOP for Kathmandu ordinances Valley and revise zoning ordinates raise awareness through training and education SIS OHUO, NGOs, campaigns to make people realize the benefits of municipalities planning Extend GLOP to areas where environmental standard is low 3. Conservation of open Ensure buffer zones parks and other public amenities ASAP MLO,OHUO spaces by strict enforcement of land use policy municipalities, NGOs 4. Land use policy for Industrial Develop and enforce inter and intra-industrial land ASAP MHPP, MOl establishments use zoning Category 4. Fuel Switch/Quality Control 1, Switch on to less DoliutinQ Tax or subsidy modification. ASAP MOS, MOF Leading role should be played by MOS vehicles in various and NOC. organizations Study restructuring of taxes on diesel vis-a-vis petrol with aview to encourage the use of petrol over diesel. Study market implications of such modifications. 2. Address the problems of Strict enforcement of laws relating to quality control ongoing NOC,DAO dilution and adulteration of fuel of petroleum products: - frequent inspection of petrol pumps or dealers and tankers; - stiffer penalties for Violations; - start mobile laboratory van or testing fuels. 0\ --l 0\ 00 Table 5.3. Proposeti flcti()1'Is flltll1t1.easures to improve the air qllaliljl()IJfflth.1t1.fl1'l(/1l Valley. What How When Who Remarks Inform public about ways to detect adulterated and ASAP NOC diluted fuel and its effect. Use filter paper or thermometer for testing fuels. NOC has introduoed a system of thermometer but it needs to be made aocessible and its existence known to the oonsumer. Use NGOs and consumer Droteotion oounoils for SIS NGOs educating the 3. Phasing out of lead in petrol Study its feasibility, possibility of revision of supply to ASAP NOC some extent, the additional oost to the oonsumers. 4.. Review energy pricing Study the issue and feasibility of removing all price ASAP MOS, MOF, NOC, NPC/EPC, policy. Consider impaots to distortions. Consider environmental oosts. DOTM environment (petroleum produots and electricity or other fuels) Study impacts of removal of subsidies on diesel; Study the possibility of introduoing pollution tax. Category 5. General Awareness Raising 1. Awareness/information on air Use tn-media ASAP, MECSW, NPC/EPC, MHPP, MCI Target groups: public through CBO, pottution 1995 NGOs, government units Start pollution information forum. Publish bulletin/newsletter. MOH, NGOs, EPC - Improve indoorl outdoor air Launch antismoke campaign MECSW, MHPP, MOH,NGOs quality Arrange talk programs in publio places (HaaUBazar, schools, restaurants, etc.) Indoor ventilation/improved cooking stoves MCI, MOH Designate smoke-free zones - Promote oorreot value Include in school curriculum MECSW > system Media campaign to create awareness ·. Il - Care for the environmentlfellowmen = = Amend/Revise rules to ensure effectiveness ~ I» Follow-up KWECP campaign Train enforcers and drivers ASAP MCI, NGOs, MOWT Traffic Police = 2. Traffio Management Proper tuning of vehicles. DOTM ~ Table 5.3. Proposed actions ami measures to imp!'ove the air quality ofKathmandu Valley. ~ What How Organize traffic week regularly When SIS Who MECSW, TP, DOTM Remarks ~ Use mass media for public awareness SIS MCI, DOTM ~ 3. Supply quality fuel Information to detect diluted fuel and its effect SIS NOC ~ Introduce an appropriate system of fuel testing at SIS NOC 8 ~ petrol pum!'s. = Q. CategolY 6. Further Studies = 1. Air Quality Monitoring Conduct appropriate studies which will relate to more ASAP NPC/EPC NPC/EPe will handle every item for rational emission standards further study in detail in consultation with line agencies and NGOs 2. Inventory Dispersion Study re-suspension from roads and other sources 1995 Modeling 3. Institutional and Regulatory Study ways to strengthen legal mechanism for 1995 Framework introducing "polluters pay" principle. Study possible incentives for enforce and other staffs 1995 involved in environmental management Study the possibility of accrediting private entities for 1995 vehicle inspection and emission inspection system. Study the feasibility of phasing out importation of 1995 secondhand and reconditioned vehicles. 4. Traffic Demands/ Study the implementation of aprivate car utilization 1995 Management restraint policy. Study staggering of work and study hours/days and 1995 days off. Study and update feasibility of extending trolley bus 1995 network 5. Land Use Planning Study and update land use plans to facilitate 1995 transport demand 6. Fuel Switch/Quality Control Study the feasibility of using LPG in public transport. 1995 Study of market implication of taxes on diesel vis-a 1995 vis petrol with a view to encourage the use of petrol. Study the feasibility of marketing unleaded petrol and 1995 identify/evaluate other additives. Study impacts of removal or phasing out of existing 1995 subsidy for diesel. Study the possibility of introducing pollution tax. 1995 0\ \0 --..l o Table 5.3. Propo:,ed !,:cti.Qns ami measures to improve the air quality ofKathmandu Valley. What How When Who Remarks 7. Research on Air Pollution Effects of decrease in lead/lead-free petrol and other 1996 Effects on Health concomitant pollutant Study on air pollution effects on cardio-vascular and 1996 respiratory diseases 8. Study the possibility of Start R&D 1995 alternative fuel such as LPG, CNG, electric vehicles, etc. 9. Review the policies of Analyze present policies in comprehensive ways and 1995 vehicle import to the correlate with the realities Kathmandu Valley, Nepal 10. Study the economic aspect Explore the economic loss due to air pollution 1995 of the effects of air pollution in the Valley Category 7_ Institutional and Regulatory Framewor/( 1. Introduce "polluters pay" Plug and amend existing environmental legislation. SIS MLD, MHPP. MOwr, 8SM. MOl Ahigh level coordinating and monitoring principle through appropriate unit at NPC/EPC will be constituted with regulatory measures and serve representation from govemment and penalties against violators private sector to supervise the overall managerial activities. Impose penalties to violators SIS EPC, Traffic Police, DOTM Ensure regulation from the practical point of view Amend and pass bill ASAP NPC/EPC, DOTM Introduce mandatory third party insurance ASAP SWMRMC/MLD Incorporate users charge. 1995 Municipality, Formulate pollution standard ASAP NPC/EPC/DOTM Give pressure for the localization of industries ASAP MOl Introduce quality drainage management ASAP DWSS 2. Strengthen technical Establish and promote training institutions SIS MLD ~ capabilities relevant ~ government agencies, industry, .... Q municipality, SWMRMC and NGOs for environmental = :! ~ management Promote technical and economic capabilities SIS EPC = Encourage community/people participation ASAP MLD. TOC Table 5.3. Proppsed aclif!!1.!Jlml!!,~ure~!2 imJ!!'ovelh~aj!'Jlualj!J ofKath!!f,a]!du Valley. What How Increase economic benefit of the staffs. Encourage private sector involvement When 1995 ASAP Who Relevant Govt. Agencies, NGOs Remarks !. ~ Promote private lab for testing ASAP ~ 3. Coordinate efforts among Strengthen existing traffic management SIS MLD, Traffic Police, DOTM a Il) different government and non = Q. government agencies involved = in air pollution control Execute common monitoring guidelines ASAP DWSS, RONAST, DOTM Creation of one environmental body 1995 EPC/NPC 4. Analysis of regulation by all Pass odometer law ASAP MLD,EPC concerned agencies. Require total disclosure and technigraph for all ASAP DWSS, SWMRMC, NGOs vehicles. Encourage to import standard spare parts SIS Fixing parameters on air, water, noise and land SIS EPC pollution control. 5. Study possible incentive and Analyze existing salary scales for merit ASAP EPC, MLD, DWSS, MSS, funding for enforcer and other SWMRMC, municipalities, staffs involved in environmental NGOS monitoring management Create a fund to provide and support economic ASAP benefit. Allocate more budget Launch antismoke belching campaign. Create environmental fees/fines and setup a trust fund.. 6. Remove jurisdictional Duplication of jurisdictional boundaries and SIS MLD, MHPP, EPC boundaries between different responsibilities be avoided. institutions. Play vital role with O&M activities SIS Provide detailed guidelines and strengthen SWMRC SIS and municipalities. 7. Strengthen enforcement Train people or staffs and maintain coordination. ASAP MLD, MHPP capabilities of concerned authorities - :-.l -...J IV Table 5.3. Proposell actif!!ls and meas"res to improve the air q"ality o[Kathmandu Valley. What How When Who Remarks Tap NGO to assist. Use media pressure. Setup SIS EPC hotline to report violators. 8. Strictly and uniformly Prepare a manual, strengthen implementation 1995 EPC, MOWT, MHPP, MLL>, implement antismoke belching capability of traffic police, among others. Traffic police, DOTM campaign Encourage NGOs relevant govemment agencies to ASAP EPC,MHPP,MLD,MOE launch awareness campaigns. Encourage garage testing ASAP DOTM Encourage school, office to start this campaign ASAP MOE 9. Strict emission control for Policy, translation into implementation procedure, set 1995 on· NPC/EPe Traffic Police, MOWT, cars, motorcycles, heavy-duty time schedule going DOTM vehicle, tempos 10. Address highly polluting: Enforce existing lawsllegislation ASAP NPC, MOl, Traffic Police, DOTM, vehicles DOR. citizen groups, NGO industries consulting firms road maintenance construction on laws; use of emission control equipment/improvement Replacement of engines on-going Follow-up of industrial EIA procedure > II C;. = I>"CI ;" = 6. EXISTING LAWS AND INSTITUTIONS 6.1. LAWS AND REGULATIONS ON AIR POLLUTION The development of environmental and air pollution legislation in Nepal is in its first phase. Prior to 1994, there were no laws or regulations pertaining specifically to air pollution. Economic development in Nepal has been accompanied by worsening environmental problems and there is now a growing awareness of this relationship. Statements on the need to protect the environment have been included in Five-Year Plans. An Environment Protection Council had been established under the Chairmanship of the Prime Minister, and an Environmental Protection Division exists within the National Planning Commission (NPC). The government's environmental policies and actions were set out in the Eighth Five-Year Plan document. These may be summarized as follows: 1. adopt an integrated approach to environmental policy, with sustainability as the overall goal; 2. develop strategies for sustainability, and provide for their implementation directly through regional and local planning; 3. require proposed development projects, program, and policies to include environmental impact assessment and extended economic appraisal; 4. establish a comprehensive system of environmental law and provide for its implementation and enforcement; 5. recognize the legitimacy of local controls, implementation, and enforcement mechanisms in local environmental planning and management; 6. ensure that all national policies, development plans, budgets and decisions on investments take full account of their effects on environment; 7. provide economic incentives for conservation and sustainable use; 8. strengthen the knowledge base, and make information on environmental matters more accessible; and 9. ensure that strategies for sustainability include actions to motivate, educate and create conditions for individuals to lead their lives in a sustainable environment. In its"Approach to the Eighth Five-Year Plan," the Government has specified policies and actions to ensure that all national policies, development plans, budgets and decisions on investments take full account of their environmental impacts. In particular, the Eighth Plan specifies that the urban environment will be improved through the control of waste, and through the establishment of water, air and noise standards. According to His Majesty's Government, Ministry of Industry, Nepal, two basic activities for the formulation of legislation on air pollution have been recently completed and forwarded for approval by the cabinet: 73 74 Existing Laws and Institutions a) Environmental Impact Assessment (EIA) guidelines for the industrial sector have been forwarded for approval by the cabinet. The guidelines include measures for mitigating the increased pollution generated by new industrial establishments in Nepal; and b) Industrial Pollution Control Regulation (IPCR) for air and water discharges was drafted as an outcome of a workshop conducted by HMGlMinistry of Industry in June 1994. Concerned sectors, agencies and NGOs were involved. According to the Ministry, the draft was expected to become a regulation by November 1994. Laws on Vehicle Pollution Control have been proposed according to recommendations from the KVVECP study. They include limits on diesel smoke from diesel vehicles (65 Hartridge Smoke Units, HSU, free acceleration test) and CO emission from gasoline vehicles (3 percent at idle). To our knowledge, standards or guidelines for air pollution concentrations have not yet been passed. 6.2. INSTITUTIONS INVOLVED The following is a listing of the institutions responsible for environment. Coordination · HMGlNational Planning Commission (NPClEnvironment Protection Council (EPC); and · Metropolitan Environment Improvement Program (MEIP)/wodd Bank. Monitoring · Department of Hydrology and Meteorology, Babarmahal, Kathmandu; · Royal Nepal Academy of Science & Technology (RONAST), Naya Baneshwor, Kathmandu; and · HMG J Bureau of Standards. Emissions Inventories · Department of Hydrology and Meteorology, Babarmahal, Kathmandu; st · Kathmandu Valley Vehicle Emission Control Project (the 1 phase), funded by UNDP, under Department of Transport Management, Naya Baneshwor, Kathmandu; and · Royal Nepal Academy of Science & Technology (RONASn, Naya Baneshwor, Kathmandu. Legislation · HMG J Ministry of Law, Babarmahal, Kathmandu. Enforcement · Department of Traffic Management, Naya Baneshwor, Kathmandu; and · Kathmandu Valley Traffic Police, Singhadurbar, Kathmandu. The above mentioned departments are basically funded by the Government of Nepal, except for the 'Kathmandu Valley Vehicle Emission Control Project (I st phase)' which was financed by UNDP and MEIP. URBAIR-Kathmandu 75 Manpower, expertise, and equipment data for the organizations are are listed in Table 6.1. Table 6.1: Institutions and Equipment Needfor Kathmandu, Nepal. Name of Dept. Manpower Expertise Equipment 1. Dept. of Transport 255 26. 10 smoke meters, analyzers and 4 High Volume Samplers Management of Envirotech Co., India, and 2 COIHC analyzers of Horiba Co., Japan 2. KTM Valley Traffic Police 455 44 · Shares the equipment from the Dept. of Management 3. Thapathali Campus 90 42 · Technical vocational school owns most of the equipment for repair and maintenance of machinery and also shares equipment for vehicle emissions check from the Dept. of Transport Management. 4. Dept. of Hydrology and 300 50 · Meteorological station at Babarmahal. Meteorology 5. Vehicle Emission Control Project, 2nd phase (under formulation) 6. Dept. of Civil Aviation N.A. Fully equipped meteorological station for aviation pur · poses at the airport, Kathmandu. 7. RONAST 180 108 · High Volume and Handy Samplers one each, and a fully equipped meteorological station at Sundari Ghat, Kirtipur, Kathmandu. 8. HMG/Bureau of Standard 80 6 8 . Laboratory for quality control of all kinds of products Note: The equipment owned by HMG/Department of Transport Management is rotated among the enforcing organizations in the Valley. 7. REFERENCES AIAM (1994) Letter from Association ofIndian Automobile Manufacturers to various Indian Ministries 28/0211994. Baker et al. (1992) Final report for vehicular emission control planning in Metro Manila. Asian Development Bank (T.A. No. 1414 - Pill). Baker, J., Santiago, R., Villareal, T. and Walsh, M. (1993) Vehicular emission control in Metro Manila. Draft final report. Asian Development Bank (PPTA 1723). Bhattarai, M.D. (1993) Urban air quality workshop (URBAJR). Paper on industrial contribution to air quality. Kathmandu, Ministry of Industry. Binnie & Partners, (1992) Modernization of environmental monitoring facilities & capabilities in response to Philippines' Energy Development Project. Interim report. Binnie & Partners, Consulting Engineers. Report to the EMB. Devkota, S.R. (1992) Energy utilization and air pollution in Kathmandu Valley, Nepal. Bangkok, Asian Institute of Technology. (Thesis EV-9209). Devkota, S. R. (1993) Ambient air quality monitoring in Kathmandu Valley. A report submitted to Kathmandu Valley Vehicular Emission Control Project. (HMGIUNDPINEP/92/034). Dichanov, Y. (1994) Sensitivity of PPP-based income estimates to choice of aggregation Procedures. World Bank, Washington D.C. Economopoulos, A. P. (1993) Assessment of sources of air, water and land pollution. A guide to rapid source inventory techniques and their use in formulating environmental control strategies. Part L Rapid inventory techniques in environmental pollution. Geneva, World Health Organization (WHOIPEP/GETNET/93.1-A). Garratt, K. (1993) Vehicular emission control: Kathmandu Valley discussion paper, Mimeography. HMGIUNDP joint project. Kathmandu, Kathmandu Valley Vehicular Emission Control Project. Gautam and associates (1994) Study report on automobile fuels, its import, supply, distribution and quality assurance in Nepal. Kathmandu, Gautam and associates, Consulting Engineers. Gram, F. and Behler, T. (1993) User's guide for the "KILDER" dispersion modeling system. Lillestmm (NILU TR 5/92). Hutcheson, R. and Paassen, C. van (1990) Diesel fuel quality into the next century. London, Shell Public Affairs. JICA - Japanese International Cooperation Agency (1992) The study on Kathmandu Valley urban road development. His Majesty's Government of Nepal. Kathmandu, Ministry of Works and Transport. Joshi, K.M. (1993) Report on the works of monitoring of vehicular emissions in Kathmandu Valley. HMGIUNDP Joint project for environmental protection, KVVECC-project. Kathmandu. Karmacharya, A. P. and Shrestha, R. K. (1993) Air quality assessment in Kathmandu City 1993. Kathmandu, Environment & Public Health Organization. 76 URBAIR-Kathmandu 77 Lange, D.F. de (1989) Brick industry in Kathmandu Valley. Options for energy saving in Bull's trench kilns. Enschede, the Netherlands, University of Twente, Technology and Development Group. Larssen, Steinar et al. (1996) URBAIR Guidebook for Urban Air Quality Management in Asia. MEIP, The World Bank. Lave, L.B. and Seskin, E.S. (1977) Air pollution and human health. Baltimore/London, Johns Hopkins University Press. Mathema, M.B., Joshi, A.R., Shrestha, S.L. and Shrestha, c.L. (1992) Environmental problems of urbanization and industrialization: the existing situation and the future direction. Report submitted to UNDP/Nepal, Environmental Management Action Group, Kathmandu. Mathur, H.B. (1993) Final report on the Kathmandu Valley vehicular emission control project. HMGIUNDP Joint project for environmental protection, KVVECP-project. Kathmandu. McGregor, D.B. and Weaver, C.S. (1992) Vehicle IIM test procedures and standards. Draft interim report. Sacramento, Engine, Fuel and Emissions Engineering. Mehta, KH. et al., (1993) Philippines. Environmental sector study. Toward improved environmental policies and management. Worldbank (Report No. 1 I 852-PH). NESS - Nepal Environmental and Scientific Services (P) Ltd. (1995) Assessment of the applicability of Indian cleaner process technology for small scale brick kiln industries of Kathmandu Valley. Thapathali Kathmandu, NESS. Ostro, B. (1992) Estimating the health and economic effects of air pollution in Jakarta: A preliminary assessment (draft). Paper presented at the Fourth annual meeting of the International Society of Environmental Epidemiology, Cuernavaca, Mexico, 1992. Ostro, B. (1994) Estimating Health Effects of air pollution, a methodology with application to Jakarta. PRDPE's Research Project (676-43). Otaki, K, Sharma, T. and Upadhyaya, N. P. (undated) Respirable air particulate (PM lO ) potential in Kathmandu municipality. Sapporo, Yagai-Kagaku Co. Ltd.! Kathmandu, NESS (pvt) Ltd. Paassen, C.W.C. van et aL (1992) The environmental benefits and costs of reducing sulfur in gas oils. Brussels, Concawe (Concawe report 3/92). Parkes, D. (1988) Matching supply and demand for transportation in the Pacific Rim countries post 1990. Selected papers. London, Shell. Perissich, R. (1993) "Auto emissions 2000", "Stage 2000" of the European regulations on air polluting emissions of motor vehicles. Written proceedings of the symposium. Brussels.Commission of the European Communities, UCSC-EEC-EAEC. Sharma, T., Upadhyaya, N. P. and Shahi, K B. (undated) Extent and dimension of lead pollution through leaded emission in the Kathmandu municipality. Kathmandu, NESS (Pvt) Ltd. Shin, E.R., Hufschmidt, G.M., Lee, Y-S., Nickum, lE. and Umctsu, C. (1992) Economic valuation of urban environmental problems. Washington D.C., World Bank. Shrestha, B. (1995) Health assessment URBAIR. Kathmandu. Shrestha, B. (1994) Health assessment (URBAIR). Interim report. HMGIUNDP joint project. Kathmandu, Kathmandu VaHey Vehicular Emission Control Project. Shrestha, B. (1994) Health assessment (URBAIR). Final draft report. Kathmandu. Shrestha, B. (I 993) Health effects of air pollution due to vehicular emissions. HMGINDP joint project. Kathmandu, Kathmandu Valley Vehicular Emission Control Project. 78 References Shrestha, M. L. (1994) Meteorological aspect and air pollution in Kathmandu Valley. Final report. Kathmandu, Dept. of Hydrology and Meteorology, His Majesty's Government in Nepal. Shrestha, R.M. and Malla, S. (1993) Energy use and emission of air pollutants: Case of Kathmandu Valley. Bangkok, Asian Institute of Technology. Stedman, D. H. and Ellis, G. (1993) Summary of findings - five nation Asia. Motor vehicle sampling tour August, 1993. University of Denver. Thapathali Campus. Institute of Engineering (1993) Report on pollution control of motor vehicles. HMGIUNDP joint project. Kathmandu, Kathmandu Valley Vehicular Emission Control Project. Tharby, R.D., Vandenhengel, W. and Panich, S. (1992) Transportation emissions and fuel quality specification for Thailand (draft report Febr. 1992). Monenco Consultants. Tims, lM. (1983) Benzene emissions from passenger cars. Brussels, Concawe (Concawe report 12/83). Tims, I.M. et al. (1981) Exposure to atmospheric benzene vapor associated with motor gasoline. Brussels, Concawe (Concawe report 2/81). Tuladhar, A.M. (1993) Progress report on technical intervention of diesel vehicles. KVVECP HMGfUNDP joint project. Kathmandu. Turner et al. (1993) Cost and emissions benefits of selected air pollution control measures for Santiago, Chile. Report to the Worldbank. Sacramento, EF & EE. UNDPfESMAP (1993) Nepal. Energy efficiency and fuel substitution activity. Activity completion report. Washington D.C., World Bank. (Confidential). WHO (1993) Assessment of sources of air, water, and land pollution. A guide to rapid source inventory techniques and their use in formulating environmental control strategies. Part One: Rapid inventory techniques in environmental pollution. By A.P. Economopoulos. Geneva (WHOIPEP/GETNET/93.1-A). Wang, Q., Kling, C. and Sperling, D. (1993) Light-duty vehicle exhaust emission control cost estimates using a part-pricing approach. J Air Waste Manage. Assoc., 43, 1461-1471. Weaver, C.S. and Lit-Mian Chan, P.E. (1993) Motorcycle emission standards and emission control technology. Draft report. Report to the Worldbank and The Thai Government. Sacramento, EF & EE. WHOfUNEP (1992) Urban air pollution in megacities of the world. Earthwatch: Global environmental monitoring system. Oxford, Blackwell. APPENDICES PREFACE APPENDIX 1: AIR QUALITY STATUS, KATHMANDU VALLEY APPENDIX 2: AIR QUALITY GUIDELINES APPENDIX 3: EMISSIONS INVENTORY APPENDIX 4: EMISSION FACTORS, PARTICLES APPENDIX 5: SPREADSHEET FOR CALCULATING EFFECTS OF CONTROL MEASURES ON EMISSIONS APPENDIX 6: PROJECT DESCRIPTIONS, LOCAL CONSULTANTS 79 PREFACE In view of the potential environmental consequences of continuing growth of Asian metropolitan areas, the World Bank and UNDP launched the Metropolitan Environmental Improvement Program (MEIP) in five Asian metropolitan areas - Beijing, Bombay, Colombo, Jakarta, and Metro Manila. In 1993, Kathmandu joined the intercountry program as the sixth MEIP city. The mission of MEIP is to assist Asian urban areas in tackling their rapidly growing environmental problems. Presently, MEIP is supported by the governments of Australia, Netherlands and Belgium. Recognizing the growing severity caused by industrial expansion and increasing vehicle population, the World Bank started the Urban Air Quality Improvement (URBAIR) initiative in 1992 as a part of the MEIP. The first phase ofURBAIR covered four cities - Bombay, Jakarta, Kathmandu, and Metro Manila. URBAIR is an international collaborative effort involving governments, academia, international organizations, NGOs, and the private sector. The main objective of URBAIR is to help local institutions in these cities to develop action plans which would be an integral part of their air quality management system (AQMS) for the metropolitan regions. The approach used to achieve this objective involves the assessment of air quality and environmental damage (e.g. on health, materials), the assessment of control options, and comparison of costs of damage and costs of control options (cost-benefit or cost-effectiveness analysis). From this, an action plan can be set up containing the selected abatement measures, for implementation within the short/medium/long term. The preparation of this city-specific report for Kathmandu Valley is based upon the collection of data and specific studies carried out by the local consultants, and upon workshops and fact-finding missions carried out in April and August 1993, and May 1994. A first draft of the report was prepared by Norwegian Institute for Air Research (NILU) and Institute for Environmental Studies (IES) before the first workshop, based upon general and city-specific information available from earlier studies. A second draft report was prepared before the second workshop, with substantial inputs from the local consultants, and assessment of air quality, damage and control options, and cost analysis carried out by NILU and IES. This report contains the appendices to the main report. 80 APPENDIX 1: AIR QUALITY STATUS, KATHMANDU VALLEY OUTDOOR (AMBIENT) CONCENTRATIONS Past measurements. Prior to 1993, only scattered measurements of air pollution concentrations have been performed. The KVVECP (Kathmandu Valley Vehicle Exhaust Control Program) (Mathur, 1993) study identified 7 previous studies, which included some measurements (Table 1). In these studies, measurements were confined to roadside sites. Thus, the results are not representing the status of general population exposure. Mathema et al. (1992) describes some results from measurements done, in the following manner: "A 1980-study carried out by Bhattarai and Shrestha (1981) on dust pollution at Kathmandu concludes that at 18 spots where the data was collected, lead content was far in excess of the reasonably acceptable level of 0.6 parts per million. At busy street and cross-roads the lead content was found to be in the range of 544 ppm (Maitighar) to 153 ppm (Tripureswor). A 1987 study on pollution in the Kathmandu City carried out experiments to determine "particulate loading" (extent of dust present in the air) in the month of September when dust pollution is expected to be low. It was found that at the three locations where measurements were recorded (Jochhen Tole, Singha Durbar, and Lazimpat) the amounts of dust particles per cubic meter of air were between 6 and 11 times the relevant US standard (MHPP, 1991 (b). Similar experiments carried out by CEDA (1990) in Pokhara, Kathmandu, and Biratnagar have led to similar conclusions, during the 1989/90 India-Nepal trade impasse when vehicular traffic volume was considerably lowered due to shortage of gasoline/petrol. Davidson and Pandey (1986/p 115-119) have shown that the concentration of S04, N03 and C (organic) and lead at the curb of a busy street of Kathmandu is comparable to those in urban areas in industrialized countries." Measurements of particles and their content of mycoflora in Kathmandu City were performed in June, October and November, 1992 (U. Sharma et aI., 1992). 16 samples were collected at 16 different locations near roads, using a Millipore pump and filters (6-8 hours of sampling). The sampling method indicates that the measurements are related to measurements of Total Suspended Particle (TSP), as measured with a high volume sampler. The particle concentration was within the range 197-524 Jlg/m3, averaging 304 Jlg/m3 . The corresponding Air Quality Guideline of WHO is 120 Jlg/m 3 . Thus, the measured concentrations 81 82 Appendix 1 Table 1: Air quality related studies in Kathmandu Valley prior to 1993 (Ref.: KVVECP study). Reference of study Year Conclusions 1. Bhattarai and Shrestha 1980 Kathmandu: Pb Maitighar: 544 ppm Tripureshwor: 153 ppm 2. MHPP Pollution study 1987 Kathmandu: Road side dust: 6 to 11 times of U.S. Std. 3. CEDA study 1989190 Pokhara, Kathmandu, Biratnagar, road side dust: (SPM) higher than WHO standards. 4. Davidson and Pandey 1986 Kathmandu: S02, NOx and Pb higher than WHO std. 5. Sharma and 1992 Kathmandu: Milipore pump & micro flora SPM range: 197-524IJglm3. Pradhanang 6. NILU Team observation 1993 Kathmandu: Low visibility and haze, road side SPM high 7. RONAST 1993 Kathmandu: Road side SPM 197-775 IJglm3 higher than international stds. were all above this guideline. It can be expected that the TSP concentrations are considerably higher in the dry season, especially during the January-April period. Various species of fungi were isolated from the particle samples described above. The fungi may be agents of different diseases, and some of them are allergens. The source of this mycoflora in the particles is resuspended dust on the roads. This dust is composed of dust from dirt roads and construction sites, as well as scattered refuse from human activities. The latest study before the KVVECP measurements, the ENPHO (NGO) study, confirmed the very high TSP concentrations roadside in the Valley, with daytime concentrations up to 2258 ).lg/m3 (at Kuleswore). This study also included PM IO measurements giving concentrations within 50-130 ).lglm3 . Measurements of CO, S02 and N0 2 gave rather low values, within WHO standards. NILU observations, April 1993. During a field trip to Kathmandu 18-21 April, 1993, the CO concentrations were monitored along some road routes (Figure 1). Generally, the recorded CO concentrations in highly trafficked areas were in the range 15-20 ppm, with peaks up to 60 ppm. URBAIR-Kathmandu 83 Figure 1: CO measurements performed by NILU in Kathmandu, traveling on roads by taxi, April 1993. Kathmandu 19. april 1993 PI''' 6Q.g+---L--4---L--~--~'--~--~~r-~--~--~--r'B.g J I ! .\ I n ii I l\ i~ 48.a~I--~I~.--~----~~-----r--~II--r------r------r 49.11 If) il . 1 , I r' t t I n It I ! I !~ " II 36.a21--T-~~----~-------r--,r,.--r------r~----t 36.11 I I ! ,i (, I I 11 '\ I, () · fit ! ill id I;,j ,1 I, (> , 1 v Q ! !H , !> in, I, 24.i*-~1~'~'-4------~------r-~"~"r-r------r-rr.---r 24.11 , 1 I !i \ (! ·t l .. r~ , I, , '!'.I 1 ,! I ! l I. \ I 0J'\ 'I r It itA rh rdl\\ itt i Ii .11 ~, ~ 12.Q I a·g'I---r--~--.-~--~--~--.---r--.---r--,---rg.g 16:4'3 18:2& 211:83 21:4Q Central European Time PPM Kathmandu 20. april 1993 PI''' 48.11 40.8 ~ I i\ 1\ . · J ! i './ \ I , I \ 32.11 I, 32.a I! \, r'/~ i", /\ ; ( ,. , \ \ 1 f '\ if 1 I !:\ Ii fA 24.& I , t~ ~ \.' I \ 1/ !, I / ~ \ I : "\ ..i}:; -,. ' v ~ ./\ \ j,.JI ~ . \ o .., f'~ .~ \ I! f /I' i : ! \\ ir 16.& 4;J'U\ .'h ~ '1 '.: \ -{ Ii . Y i \ j I. I '/ 8.& "V' e.g I J I g.1I I 1 I I I ra,8 3/16 19:3a 211:94. 211:38 21:12 Central European Time' 84 Appendix 1 Results of measurements after 1992. The following measurement campaigns have been carried out after 1992 (in chronological order): · Environment & Public Health Organization (ENPHO) carried out TSP, PM lO , NO x , CO, S02 and lead measurements at a total of20 sites in Kathmandu City, in November 1992 and February 1993 (Karmacharya and Shrestha, 1993). · The Kathmandu Valley Vehicle Exhaust Control Program (KVVECP) carried out a measurement campaign of TSP, PM lO , ~02, S02, CO and lead at 14 sites during September December 1993 (Devkota, 1993). · Measurements by NESS (pvt) Ltd. of PM 10 and lead at a number of sites in Kathmandu City during September-November, 1993 (Sharma et at, 1994). · Measurements of TSP by the Hydrological and Meteorological Service at the HMS building at Babar Mahal, starting from January 1993, In addition, visibility observations have been made at Tribhuvan International Airport since the early 1970' s (see Chapter 3 of this Appendix). Results from the ENPHO measurements. The measurements were carried out in two phases (Karmacharya et al., 1993): · In November 1992, at 9 sites of various height and distance from roads, to get a general picture of the air quality of the area. 24-hour averages. · In February, 1993, at 11 roadside sites, to get a picture of roadside exposure, 9-hour averages. Monitoring sites are shown in Figure 2, and described in Table 2. The methods are given in Table 6. The description of the project indicates that only one sample was taken at each site. Results are given in Table 3 and 4 for phase 1 and 2 respectively. The results indicate that TSP is the main problem compared to the WHO guideline. The measurements from phase 1 (24 hour averages) averaged 308 llg/m3, with maximum concentration of 555 llg/m3, at ChabahiL PM IO also exceeded the guideline at many of the sites, but to a lesser extent than TSP. Maximum PM IO concentration was 127 llg/m3 (WHO guideline: 70 llg/m3). The S02, NO" and CO measurements indicated rather low concentrations. The lead measurements also indicated fairly low concentrations, with a maximum 24-hour value of 0.53 llg/m3, against a long-term WHO guideline of 0.5-1 llg/m3. URBAIR-Kathmandu 85 Figure 2: ENPHO campaign measurement sites (Karmacharya et al., 1993). TO . : OAKSIWI'J(AI,.I, 86 Appendix 1 Table 2: Descril!.tion o[ENPHO campais.n measurement sites (Karmacha~a et al., 19931. Sampling station Height Distance from Distance from Direction from the Type of area Traffic em) closest road (m) popular junction em) popular junction (m) density 1. Chabahil 3 5 100 North-East Residential! Busy Market 2. Indrachowk 12 5 50 North-West Residential! Busy Market 3. Maharajgunj (Ring 5 15 30 South-East Residential Moderate Road) 4. Thapathali 3 5 75 North-West Residential! Busy Market 5. Putalisadak 6 8 75 South Residential! Busy Market 6. Kalimati 10 5 25 North Residential! Busy Market 7. Royal Palace 5 8 30 South-West Market Busy 8. Balaju (Ring 6 15 35 North-West Residential! Busy Road) Market 9. Bir Hospital 3 5 25 North-West Residential! Busy Market 10. Kuleswor 0.75 2 Right at the junction West Residential Busy !Market 11. Thamel 0.75 0 Right at the junction East Residential! Busy Market 12.Ason 0.75 0 Right at the junction South-West Residential! Low Market 13. Nachghar 0.75 0 Right at the junction North Residential! Busy (Jamal) Market 14. Kasthamandap 0.75 2 Right at the junction South-East Residential! Moderate Market 15. Kalanki (Ring 0.75 2 Right at the junction North-West Residential Busy Road) (outskirt) 16. Singha Durtlar 0.75 2 Right at the junction South-West Office Busy Complex 17. Dillibazar 0.75 2 Right at the junction North Residential! Moderate (Pipalbot) Market 18. Swayambhoo 0.75 2 Right at the junction South-West Residential Moderate (Ring Road) (outskirt) 19. Ratna Park (Bus 0.75 2 Right at the junction North-West Residential Busy park) 20. Tripureswor 0.75 2 50 South-East Residential/ Busy Market URBAIR-Kathmandu 87 The phase 2 measurements at roadside Table 3: Concentration ofthe pollutants (first part - 24 hour sites gave much higher averaging timel, ENPHO stud)!: concentrations. Also here, Stations TSP PM10 S02 NOx CO Pb TSP and PM IO, presented fJg/m3 fJg/m 3 fJ9 /m3 fJg /m3 mg/m3 I:!g/m3 the largest problem 1. Chabahil 555 127 <13.0 28 <11 0.35 compared to guidelines. 2. Indrachowk 194 59 <13.0 24 <11 0.21 3. Maharajgunj (Ring Road) 233 64 <13.0 17 <11 0.18 TSP-concentrations 4. Thapathali 206 74 <13.0 12 <11 0.31 (9-hour day-time average) 5. Putalisadak 267 92 <13.0 28 <11 0.37 averaged almost 6. Kalimati 232 76 <13.0 24 <11 0.30 1400 IJ.glm3 , with max. 7. Royal Palace 182 93 <13.0 25 <11 0.53 concentration 2258 IJ.glm3, 8. Balaju 465 102 <13.0 24 <11 0.23 at Kuleswor. PM lO 9. Bir Hospital 438 116 <13.0 36 <11 0.43 Average 308 89 ·6.5 24.2 <11 0.32 averaged almost WHO Standard 120 70 125 150 0.5 300 IJ.glm3, with 1.0 maximum 498 IJ.glm 3 at Thamel. Table 4: Concentration ofthe pollutants (Second part - 9 hour Again S02, NO x and averaginG. timel, ENPHO study. CO concentrations were Stations TSP PM10 S02 NOx CO Pb low, while the lead fJg/m 3 1:!9/m3 "'9 1m3 ",g/m3 mg/m 3 ",g/m3 concentrations were up to 10. Kuleswor 2258 415 19 59 <11 0.7 1.2 IJ.glm 3, averaging 11. Thamel 1978 498 <13 48 <11 1.2 0.54 IJ.glm3 . Still fairly low, 12. Ason 1772 281 <13 28 <11 0.5 but increased compared to 13. Nachghar (Jamal) 1283 257 <13 32 <11 0.9 the phase I sites. 14. Kasthamandap 1056 182 <13 17 <11 0.4 These measurements, 15. Kalanki (Ring Road) 1201 239 22 40 <11 0.2 16. Sinha Durbar 789 225 20 69 <11 0.2 covering a number of sites 17. Dillibazar 1077 240 18 30 <11 0.5 in general Kathmandu City 18. Swayambhu (Ring Road) 1161 258 <13 26 <11 0.3 atmosphere and the roadside 19. Bus Park (Ratna Park) 1709 355 17 41 <11 0.6 atmosphere, can be used to 20. Tripureswor 1090 313 <13 30 <11 0.4 give a rough estimate of a Average 1397 296 12.3 38 <11 0.54 long-term average TSP and · S02 - <13 has been arbitrarily considered half of 13, i.e. 6.5. PM lO concentration which might represent a typical exposure value for the population in central Kathmandu City, based on the following assumptions: · Consider that the average 24 hour average roadside concentration is ·50 percent of the 9 hour average, i.e. 700 IJ.glm 3 for TSP and 150 IJ.glm3 for PM lO . · Consider that the average person spends 25 percent of the time roadside. · Consider that the summer (monsoon) season average is 50 percent of the winter season average. This results in an annual average of 300 IJ.glm3 for TSP and 75 IJ.glm3 for PM lO for an average person living in central Kathmandu City spending 25 percent of his time roadside. Results from the KVVECP study. As part of the Kathmandu Valley Vehicle Exhaust Control Program (KVVECP), measurements of TSP, PM IO , N0 2, S02, CO and Ph were made at a 88 Appendix 1 number of sites (roadside, residential, industrial). Results have been reported for the period September-December, 1993 (Devkota, 1993). The measurement sites are shown in Figure 3 and described in Table 5. Individual results, as reported by Devkota, are annexed to this appendix. Methods are listed in Table 6. Table 5: Ambient Air Quality Monitoring Stations, KVVECP study. Category Locations Distance from main Height of the station road (m) (m) 1. Commercial Areas: i. Heavy traffic (30-40,000 ADT) Singha Durbar, 2 3 GPO 3 3 ii. Medium traffic (20-30,000 ADn Ratnapark, 4 3 Lainchaur, 2 2.5 Kalimati 3 3 iii. Low traffic «7000ADT) Thimi (NTC) 2 2.5 2. Residential Areas Maharajgunj (TUTH), 30 3 Naya Baneswor, 20 7 Jaya Bageshwori 15 8 3. Industrial Areas Balaju, 15 4 Bhaktapur, 50 3 Patan Industrialized districts, 5 5 Himal Cement Factory surrounding 100 10 4. Regional background/control site Tribhuvan University 50 3 KirfipUl ADT: Average Daily Traffic Table 6: Monitoring methods, ENPHO and KVVECP study. Sampling: En Envirotech APM 451 Respirable Dust Sampler (Indian produce) was used as sampler for TSP, PM1O. S02 and N02. The flow rate for TSP/PM10 was 0.8-1.2 m3/min, and for S02 and NOx 1l1min. The samples were partly 24 hour samples (midnight-te-midnight), and partly 8 hour samples during peak daytime traffic (9-10 a.m. to 5-6 p.m.). Analysis: S02: Pararosaniline method N02: Jacobs-Hochheiser Arsenite, Modified method TSP: Gravimetric analysis, Whatman GF/A filter (PM10) and ceramic thimble (non-respirable fractions). CO: Roadside spot measurements with Kitegava Precision Gas Detector, Model APS. Gas Detector tubes, 5 50 ppm. Heavy metals AAS analysis (Perkin Elmer - 2380) of the glass fibre filters. (Cr, Fe, Pb): URBAm-Kathmandu 89 Figure 3: Measurement sites, KVVECP study. · Commercial (traffic) sites ., Industrial sites 20 -II Residential sites o . Regional background sites I · I _ I ,, I I '" \"""'\, t_ ~eoo-- I ,: , . ", - . , -.:.,-'.... .. r ..... - , "I , _- ... I . . -- 15 , ' '- , ',," .......... -',' ......... - ' .... 'J.400- _ _ ,I ...... ".... -- --... ",- ::; I , ........ , .. ~, ,, , ,, , , ,- , I~ ... \ 10 , ."'.. , I I, , ", , , , .... 1400 ___ ' , ,"''' \ , .- I ,', \ " " -;000.. " ,, ,\ I ........ ..... t "I ....... " . \- - \ ". ::' . ~ '':''', \ ... \ N t I , ,_ '. I , , '." , " _ t , I:'"~ ~ . 1... __, \ ... ' ... "", -' i i l"'~ :,.: 1 5 10 15 20 The results of the 24-hour measurements are summarized in Table 7. Figures 4-7 show the average and maximum concentrations at the measurement sites for TSP, PM lO, S02 and N0 2 respectively. 90 Appendix 1 Table 7: Summary o[AQ measurements, KVVECP studl..' Average/max 24 h conc. (... ~Jm3~ TSP PM10 S02 N0 2 No. of days Commercial (traffic) sites Singha Durbar (heavy traffic) 303/375 142/175 491 64 37/ 64 22 (Nov.lDec,) GPO (heavy) 380/474 137/201 37/ 64 11 / 16 16 (Nov.) Ratnapark (medium) 1871319 671 86 32/102 18/ 28 16 (Sept.) Lainchaur (medium) 228/386 103/146 171 26 191 40 13 (Nov,) Kalimati (medium) 391/441 135/154 77/202 19/ 31 12 (Nov.) Thimi (low) 337/867 115/117 491 65 19/ 24 20 (Dec.) Residential sites Maharajgunj 191/350 72 / 126 19/ 34 121 14 13 (Nov.) New Baneswor 200/270 113/161 131 13 14/ 25 5 (Sept./Nov.) Jaya Bageshwori 228/273 112/132 110/225 491126 10 (Dec.) Industrial areas Balaju 108/137 40/ 77 151 21 311 71 9 (Sept.) Patan 87/102 471 53 131 13 401 83 5 (Sept.) Bhaktapur 213/290 105/131 581 79 201 24 6 (Dec.) Himal Cement surrounding 430 1560 166/194 571 65 381 58 5 (Dec.) Regional background site Tribhuvan Univ. 94/155 661 81 381 77 181 35 19 (Nov.lDec.) URBAIR-Kathmandu 91 Figure 4: TSP measurements, KVVECP study. TSP N t 2km 92 Appendix 1 Figure 5: PM10 measurements, KVVECP study. Measurement sites, KWECP · Commercial (traffic) sites ... Industrial sites · Residential sites o Regional background sites N t 2km URBAIR-Kathmandu 93 Figure 6: S02 measurements, KVVECP study. Measurement sites, KVVECP · Commercial (traffic) sites ... Industrial sites N t 2km 94 Appendix 1 Figure 7: NO] measurements, KVVECP study. Measurement sites. KWECP · Commercial (traffic) sites '" Industrial sites .. Residential sites N t 2km For TSP, the concentration ranges for average and maximum values are 94 (background value)-430 llg/m3 and 102-867 llg/m3, respectively. Granted that the measurement periods differ from site to site, the traffic sites have generally higher TSP concentrations than the other sites (except Himal Cement). However, differences between the traffic sites reflect also other parameters than just the amount of traffic. Thimi, with low traffic, has very high TSP concentrations. Local sources/conditions seem important. For PM lO , the traffic and residential sites seem to have similar levels, higher than the industrial sites (again except Himal Cement). Actually, the Balaju and Patan sites have values similar to the regional background at Tribhuvan Univ., as was also the case for TSP. S02 and N0 2 concentrations were generally low, according to the measurements, except at Kalimati (S02) and Jaya Bageshwori (S02 and NO z). URBAffi-Kathmandu 95 The very short measurement periods at some sites reduce to some extent the general nature of these conclusions. The measurements at the Tribhuvan Univ. indicate that the general background level ofTSP was on the average some 90-100 llg/m3 in the autumn of 1993, with maximum concentrations up towards 150 llg/m3. The similar figure for PM IO was some 50 llg/m3 (average) and 80 llg/m3 (maximum). On top of this, sources nearby the monitoring sites gave higher concentrations. The variation from site-to-site does not seem to be explained simply by amount of traffic, or being in an industrial area. The Himal Cement site had the highest average concentrations ofTSP and PM IO , being close to the cement factory. Relative to WHO guidelines, the TSP and PM IO concentrations both rise to twice the guidelines. For TSP, about 70 percent of all the measurement days were above the lower guideline value (150 llg/m3), and about 50 percent of the days were above the higher guideline value (230 llg/m3). About 50 percent of the total days of measurement had PM IO above the guideline of 70 llg/m3 . The results of the KVVECP CO measurements gave typical values below 5 ppm, and the highest value measured was 7.5 ppm, using detector tubes with range 0-50 ppm. Morning wind speeds were reported generally below 0.5 m/s. These are very low CO values considering the heavy traffic at some of the roads, and they are considerably lower than the results from the NILU measurements. Results from TSP measurements on the Hydrology and Meteorology Service Building. TSP measurements were performed on the roof of the building at Babar Mahal, some 15 m above ground, from January to August 1994 (Shrestha, 1994). Results are given in Table 8, and shown in Figure 8. The highest TSP concentrations occurred in February-April, the dry season, as expected. The TSP levels are substantially reduced on rainy days. The results are at the same level as the KVVECP data for New Baneswar residential site from September and November 1993 (aver.: 200 llg/m3 ; max: 270 llg/m3 ; 5 sampling days). The WHO guidelines were exceeded on the majority of the days. The highest concentration, 467 llg/m3, was more than twice the upper level of the 24-hour guideline range, 230 llg/m3 . The 8-month average concentration was 200 llg/m3, compared to the WHO guideline for annual average, 60-90 llg/m3 Table 8: TSP measurements at Babar Mahal, 1994 (Hydr. and Met. Service Building) (Shrestha, 1994l' Jan. Feb Mar April May June July Aug Avg. Jan-April Avg. May-Aug Average 226 227 312 310 185 137 100 106 269 132 Max. 363 422 384 467 437 302 138 192 No. of days above AQG: -150 !-Ig/m3 21 14 10 18 15 9 0 2 63' 26' -230 !-Ig/m3 12 4 10 15 6 1 0 0 41' r No. of rainy days 2 2 6 1 10 18 25 22 11' 75' No. of samples 24 15 10 19 25 25 23 16 68' 89' , Total no. of days. 96 Appendix 1 Figure 8: TSP measurements at Babar Mahal, 1994 (HMS building) (Shrestha, 1994). 500 500 Jan. Feb. 400 400 300 200 100 1\ "r." \ P Ivy '\ 300 200 100 11 11 ~t. a ....". 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 1 3 5 7 9 11 13 15 17 19 21 23 25 27 0 AJtPr. 500 500 Mar. 400 11 11 400 300 200 t.:. J 11 / 300 200 11 11 WO 100 lL 0 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 500 500 May. Jun. 400 400 300 300 200 100 tfr! A \ '\A Lf 200 100 0 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 500 500 Jul. Aug. 400 , 400 300 300 200 200 11 100 f'rlA ~ '\J\~ 100 a .. A -" . ~ ..... ..t.. a 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 Results from the NESS (Pvt) Ltd campaign. The following samples were taken in 1993: · Dust samples from roads, for lead analysis, at 10 road sites on September 10, 22 and 23, and 21 road sites on October 27 and 28. URBAIR-Kathmandu 97 · PM lO samples from air at 4 sites on September 5-6, and at 9 sites on October 27 and November 1-2, using a Sibata high-volume air sampler HVS-500-5, with a 10 !lm cut off slotted impactor in front. · Monitoring of particle concentration by a Laser Dust Monitor (Japanese Table 9: Lead content in street dust ofKathmandu City, make) at 59 sites during 1993 (NESS study, T. Sharma et aL, undated). November 3-19. ppm Pb in dust The measured road dust Samples No. of sites Average Range Average Range lead content is given in Table September 10, 22, 23 10 275 50-1,187 140 81-344 9. October 27-28 21 160 1-965 Lead, assuming mainly from lead in gasoline, is clearly present in roadside dust. The concentration of lead is typically 200-300 ppm in the >2 mm fraction, and somewhat less in the <0.2 mm fraction. The measured PMlO and lead concentrations in air are presented in Table 10. The values represent typical one- hour averages during daytime hours. Table 10: PMlf) and lead in air analyzed from samples drawn with The PM 10 the Sibata high-volume sampler. concentrations are very PM10 (mg/m3) Lead (f.lg/m3) high (up to Period No. of sites Average Range Average Range 2,100 !lg!m 3 ), much September 5-6 3 3.5 0.23-6.08 higher than those from October 25 and 9 0.80 0.23-2.11 1.1 0.65-2.60 November 1-2 the ENPHO and KVVECP studies. The Sibata sampler has a slotted 10 !lm impactor in front of the filter where particles are collected. The function of the impactor is to hold back particles of diameter above 10 /lm from the filter. It is possible, as knO'WIl from experience with similar impactors, that dry dust particles are not collected with full efficiency. However, it is still difficult to explain the high PM lO concentrations measured, when compared to those of the other studies. The lead concentrations are also substantially higher than those measured in the ENPHO and KVVECP studies. Based on these results, and the Laser dust monitor samples from 59 roadside sites, Otaki et a1. (undated) has plotted PM 10 and lead pollution indicator values for the road network of Kathmandu City, and also a dust deposit map. INDOOR AIR POLLUTION EXPOSURE High indoor air pollution exposure due to cooking practices is recognized as a potentially significant environmental health impact in Nepal (e.g. Pandey, 1984; Reid et.aL, 1986; Pandey et at, 1989). The cooking practices undoubtedly also create localized outdoor air pollution problems in settlements in meteorologically shielded locations. Extremely high TSP and CO concentrations have been measured in village houses, and a pronounced positive effect of improved cooking practices has been detected. Table 11 shows results obtained by Reid et a1. (1986). Pandey et a1. (1990) obtained similar results. 98 Appendix 1 This situation in Kathmandu is described by Mathema et.aL (1992) as Table 11: Mean personal exposures to TSP and follows: CO area concentrations by village and stove type (Reid et.al. 1986). "About 82 percent of the urban Traditional Improved households depend on fuel-wood for n x n x P (%) cooking purposes. If Kathmandu is a TSP(mglm3) typical example then very few urban Gorkha 11 3.17 (2.2) 13 0.87 (0.71) <5 families have the provision of a Beni 11 3.11 (2.9) 14 1.37 (1.3) <2.5 Mustang 2 1.75 2 0.92 >10 smokeless chulo and chimney. They CO (ppm) are increasingly becoming more Gorkha 13 280 (230) 14 70 (35) <0.5 dependent on kerosene. A recent study Beni 14 310 (220) 12 64 (39) <0.1 found that only 0.6 percent of families Mustang 2 64 2 41 >20 in the Kathmandu City have a Note that there is a statistically significant «5%) difference smokeless chulo, 47 percent have no between the levels for both pollutants, experienced by women cooking with improved stoves compared to traditional ones in chimney, and 6.97 percent of those both Middle Hill villages. There are too few samples in who have a chimney felt that their Mustang. kitchen is still "full of smoke" n = sample size (REGMI & JOSHI, 1988/p45-47). X = mean (geometric mean) P = level of significance, Le. probability that observed difference Furthermore, about 36.5 percent use a between the averages of improved and combined traditional Kerosene stove for cooking. The stoves has occurred by chance based on a two-tailed t-test. All calculations are based on sample standard deviations (n-I). smokeless chulo, chimney and use of kerosene when used in absence of good ventilation are potential sources of indoor pollution. The fact that almost one-third of the households have their kitchen on the ground floor, a preference which is becoming very common with the advent of modem one-story house constructions, suggests that the problem of indoor smoke could spread over the rest of the house. The composition of major pollutant emissions from different types of traditional fuel sources, based on an Indian study, is shown in Table 4811: . From the table it is seen that, measured in terms of pollutants emitted from firewood, the most common form of fuel source in urban areas, appears to be the worst among the three sources shown. Assuming a 6 hours cooking period per day, an average urban household is subjected to 16 mg/cu.m. of particulate per day - a figure which is extremely high when seen in terms of its impacts on health. Shrestha states that a traditional Nepali chulo emits a high dose of Carbon Monoxide and "working in such an environment for more than ten minutes is considered poisoning" (SHRESTHA, 1986/p42)." VISIBILITY The meteorological visibility of the Kathmandu Valley has been recorded at the Kathmandu airport since 1969. Shrestha (1994) has made a thorough and valuable analysis of the visibility data for the period 1969-1993, based on hourly meteorological observations and 3-hourly synoptic reports at the airport. The following text is a brief summary of Dr. Shrestha's findings. x Not shown here. URBAIR-Kathmandu 99 Diurnal and annual Figure 9: Fraction ofdays (percent) withfair-to-good visibility (>8,000 m), variation of Kathmandu Valley, November-February, 1993. (Ref: Shrestha, 1994). visibility. The ~ 6 present visibility situations is 8 such that L:}9o during the period November February the · · .. ·. visibility is · ·. , very poor '.' ~ - -=- T- 7- - ;- O~-" - - ,-i before 9:00 a.m., with only 10 percent of the ::j-+--I--'--1---'-1--'--,1J,--'----;--I--'--1---'-1 - ---1 Jan. Feb. March April May June July Aug. Sept. Oct. Nov. Des. day with visibility >8,000 m (Figure 9). The visibility improves generally during the day, with typically good visibility in the afternoon. During the monsoon season and early fall, the visibility is generally good. This annual variation, with improved visibility during the summer months, reflects several of the following conditions: · generally better dispersion during summer, · reduced resuspension during summer (wet surface), · increased rain-out of particles, · reduced fine particle emissions in summer (no brick industry). Trend of reduced visibility. The trend towards reduced visibility in the Valley is quite dramatic for the months November-March, and particularly for December-February (Figure 10). While in the early 70's, visibility greater than 8,000 meters prevailed (at 11:45 a.m.) for 25-30 days per month, there has been a steep downwards trend since about 1980. Today, the number of days per month in December-February with good visibility at noon approaches zero! The nature of the worsened visibility situation in the winter (dry season) is also shown by the example of Figure 11. For the month of January, this figure shows how the natural lifting of the fog and haze during the morning hours, which in the early 70's occurred around 9:00-10:00 a.m., is typically delayed until noon or early afternoon at present. The relative humidity (RH) is an important parameter for visibility variation. Figure 13 shows the average RH as a function of time at Tribhuwan Airport in 1993. 100 Appendix I Figure 10: No. ofdays per month withfair-to-good visibility (>8,000 m), Kathmandu Valley, 1969-93. (Ref: Shrestha, 1994). 40 January 40 July 30 30 rn >- C!l 20 20 10 10 0 0 70 75 80 85 90 Year 70 75 80 85 90 Year 40 February 40 August rn > <0 30 30 - -, 020 20 10 10 0 0 70 75 80 85 90 Year 70 75 80 85 90 Year 40 March 40 September (f) 30 30 1;' 020 20 10 0 0 70 75 80 85 90 Year 70 75 80 85 90 Year 40 April 40 October (f) 30 30 > C!l 20 20 10 10 0 0 70 75 80 85 90 Year 70 75 80 85 90 Year 40 May 40 1 November (f) 30 30 '" C!l 20 20 10 10 0 0 70 75 80 85 90 Year 70 75 80 85 90 Year 40 June 40 December rn 30 30 '" m 020 20 10 10 0 0 70 75 80 85 90 Year 70 75 80 85 90 Year URBAIR-Kathmandu 101 Figure 11: No. offoggy days at 9 a.m.for the period November-February, Kathmandu Valley, 1969-93. (Ref.: Shrestha, 1994). 80 60 til > 8,000 In, at given hours, 1970 (full line) and 1993 (dotted line) (Shrestha, 1994). 30-.----------------------------------------------, January ~, .. .. .. --.-------.~ .' .' .. . 1*' ~~ ~ ' .·. 20 , .· ·· 10 .·,· ·· · ," .. --- .. --- .... "'~ 6 8 10 12 14 16 18 Local time 102 Appendix 1 Figure 13: Temporal variation ofRelative Humidity at Tribhuwan Airport, 1993 (per cent). ~ "" \ \ \ t"'I \ "" I "" "" / " ,-- ,, ,r / "" '10 r 0'1, 0 "" c:n CD t' r \l) ..n :! t"'I II.> E "" t oU r- 0 ...J 0 0'1 , co " "- , 0 (J'l "- "- , " " 'I. , - "" \ I , ~ / I U> I I I r ..n I I I I I I . · I \ .,pI I "" (1'\ \ -4' i:S' I I I I""> I I I ,, I "" , I I -\ \ ,, I \. c:: .0 ... ... >- c:: 01 0- .., > u , a II.> ll... 0 ~ 0- a 41UOW URBAIR-Kathmandu 103 Trend of foggy days. Further description of the visibility situation is given in Figure 12 which shows that the number of foggy days, at 08:45 a.m., during the four winter months November February has increased from 35-40 around 1970 to more than 60 in 1992-93. Dr. Shrestha's analysis clearly shows the dramatically worsened visibility situation in the Kathmandu Valley. It seems clear that the reason is the increased particle concentration in the atmosphere, particularly in the fine particle fraction (diameter <1 fJ.m). It is probable that this increase has taken place in the regional atmosphere in general, as well as for sure in the local Valley atmosphere, due to the increased industrial and commercial activities in the Valley as well as increased population, resulting in increased fine particle emissions and concentrations. REFERENCES Devkota, S. R (1993) Ambient air quality monitoring in Kathmandu Valley. A report submitted to Kathmandu Valley Vehicular Emission Control Project. (H1VIGfUNDPINEP/92/034). Karmacharya, A P. and Shrestha, R K (1993) Air quality assessment in Kathmandu City 1993. Kathmandu, Environment & Public Health Organization. Mathema, M.B., Joshi, AR., Shrestha, S.L. and Shrestha, c.L. (1992) Environmental problems of urbanization and industrialization: the existing situation and the future direction. Report submitted to UNDPINepal, Environmental Management Action Group, Kathmandu. Mathur, H.B. (1993) Final report on the Kathmandu Valley vehicular emission control project. H1VIGfUNDP Joint project for environmental protection, KVVECP-project. Kathmandu. Otaki, K, Sharma, T. and Upadhyaya, N.P. (undated) Respirable air particulate (PM lO ) potential in Kathmandu municipality. Kathmandu, NESS (Pvt) Ltd. Pandey, M.R (1984) Prevalence of chronic bronchitis in a rural community of the Hill Region of Nepal. Thorax, 39, pp. 331-336. Pandey, M.R, Neupane, RP., Gautam, A. and Shrestha, LB. (1989) Domestic smoke pollution and acute respiratory infections in a rural community of the hill region of NepaL Environmentallnternational, Vol. 15, pp-337-340. Pandey, M.R, Neupane, R.P., Gautam, A and Shrestha, LB. (1990) Mountain Research and Development, Vol. 10, No.4, pp. 313-320. Reid, H.F., Smith, KR and Sherchand, B. (1986) Indoor smoke exposures from traditional and improved cookstoves. Comparisons among rural Nepali women. Mountain Research and Development, Vol. 6, No.4. pp. 293-304. Sharma, T., Upadhyaya, N. P. and Shahi, K B. (undated) Extent and dimension of lead pollution through leaded emission in the Kathmandu municipality. Kathmandu, NESS (Pvt) Ltd. Sharma, U, Shahi, RR., Shrestha, A, Thapa, J., Sijapati, 1., Rana, P. and Pradhananga, M. (1992) Atmospheric Pollution in Kathmandu City I: Particulate Matter in the Kathmandu City and study of Mycoflora in it. J.Nep.Chem.Soc., Vol. 11, pp. 1-8. Shrestha, M. L. (1994) Meteorological aspect and air pollution in Kathmandu Valley. Final report. Kathmandu, Dept. of Hydrology and Meteorology, His Majesty's Government in Nepal. 104 Appendix 1 ANNEX: COpy OF THE KVVECP AIR QUALITY MEASUREMENTS (REF.: DEVKOTA, 1993). Table 2. Ambient Air Quality Monitoring in Commercial Area - Heavy Traffic (GPO Complex) Date Pollutants Sampling Remark hour ug/m3 TSP NO z S02 PM10 Particle TOTAL 3/11/93 201 273 474 16 29 24 5/11/93 157 213 370 15 18 8 6/11/93 152 590 742 29 13 8 Holiday 7/11/93 172 414 586 30 13 8 8/11/93 200 527 727 22 46 8 Holiday 9/11/93 168 632 800 25 14 7 10/11/93. 99 267 366 10 46 22 11/11/93 172 665 837 19 35 8 12 8.30 12/11/93 121 79 200 17 13 8 8.30-4.30 12/11/93 173 1399 1572 17 13 8 5-12 pm 12/11/93 138 257 395 23 13 7 13/11/93 106 527 633 12 13 8 Holiday 14/11/93 129 367 496 25 13 8 Hoi 1day 16/11/93 108 229 337 9 13 24 17/11/93 152 431 583 41 13 7 18/11/93 142 179 321 11 35 24 19/11/93 179 409 588 22 81 8 :20/1.2/93 1.35 265 403 1.1. 64 24 Ho11day 21/11./93 179 697 876 35 162 8 i (I) Range SPM 321 - 474 (24 h) 200 - 1572 (8 h) PM 1Q 99 201 (24 h) 106 - 200 (8 h) NO z 9 16 (24 h) 12 41 (8 h) S02 13 - 64 (24 h) 13 - 162 (8 h) (Ill Average : SPM 380 (24 h) , 682 (8 h) PM 10 137 (24 h) , 157 (8 h) NO z 11 (24 h) , 24 (8 h) 802 37 (24 h) , 33 (8 h) URBAIR-Kathmandu 105 Table 3 Ambient Air Quality Monitoring in Commcercial Area - Heavy Traffic, Singha Durbar pollutants Sampling Remark Date hour ug/m 3 SPM N02 S02 PM10 Particle TOTAL 23/11/93 146 236 382 31 93 19 24/11/93 180 419 599 52 99 8 25/11/93 123 252 375 27 46 24 26/11/93 152 713 865 45 51 8 27/11/93 112 105 217 29 31 19 Holiday 28/11/93 113 161 274 49 13 8 5-12 pm 29/11/93 132 957 1089 , 39 67 8 30/11/93 127 107 234 26 64 24 01/12/93 102 201 303 75 188 20 02/12/93 167 208 375 88 61 24 03/12/93 112 219 331 52 69 10 04/12/93 120 292 412 34 80 8 Holiday 05/12/93 134 216 350 41 95 8 06/12/93 165 97 262 24 35 24 07/12/93 170 341 511 45 93 8 08/12/93 119 120 239 20 51 24 09/12/93 143 332 475 40 85 8 10/12/93 121 137 308 22 45 24 11/12/93 128 241 369 33 74 8 Holiday 12/12/93 164 213 377 68 59 8 13/12/93 175 256 331 55 41 24 14/12/93 214 169 383 101 37 20 I. Range: TSP 234 375 (24 hl 274 1089 (8 hl PM10 119 175 (24 hl 113 - 180 (8 hl N0 2 20 - 88 (24 hl 33 - 686 (8 hl SO. 35 - 64 (24 hl 13 - 99 (8 hl II. Average: TSP 303 (24 h) , 532 (8 hi PM10 142 (24 hl, 144 (8 hl N0 2 37 (24 h), 45 (8 h) S02 49 (24 h) , 72 (8 h) 106 Appendix 1 Table 4 Ambient Air Quality Monitoring in Commercial Area - Medium Traffic Kalimati Date Pollutants Sampl Remark hour ug/m 3 ,. TSP N0 2 SO. PM10 Particle TOTAL 20/11/93 114 241 355 22 64 24 21/11/93 110 492 602 40 57 8 Holiday 22/11/93 134 243 377 27 45 14 23/11/93 164 533 697 48 103 8 24/11/93 154 282 436 31 24 24 25/11/93 179 861 1040 51 35 8 26/11/93 137 194 331 12 202 24 27/11/93 170 469 639 45 23 8 Holiday 28/11/93 122 450 572 28 131 8 29/11/93 133 308 441 12 16 24 30/11/93· 168 534 702 26 100 8 01/12/93 165 721 886 9 163 8 I. Range: TSP 331 -441 377 - 1040 (24 h) (8 h) PM 10 114 - 154 ( 24 h) 110 - 179 (8 h) N0 2 12 - 31 (24 h) 10 - 51 (8 h) S02 16 - 202 (24 h) 13 - 163 (8 h) II. Average: TSP 391 (24 h) t 734 (8 h) PM lO 135 (24 h) t 154 (8 h) N0 2 19 (24 h) t 35 (8 h) S02 77 (24 h) , 71 (8 h) URBAm-Kathmandu Table 5 Ambient Air Quality Monitored in Commercial Area- Medium Traffic (Ranipokhari Traffic Complex) . Date Pollutants Sampling Remark hour ug/m3 .", TSP NO. S02 PM10 Particle TOTl'-L 10/9/93 67 252 31.9 17 13 24 15/9/93 59 87 146 6 16 24 Rainfall 13/9/93 57 91 148 28 102 19 Rainfall 05/9/93 46 10 56 24 13 16 Rainfall 17/9/93 86 181 267 15 16 24 18/9/93 76 307 383 30 20 10 Holiday 08/9/93 100 139 239 29 13 8 Rainfall 09/9/93 114 386 500 32 13 8 11/9/93 56 156 212 35 13 8 Holiday 12/9/93 78 212 290 28 14 8 06/9/93 n.a n.a. n.a. 29 13 7 Rainfall 14/9/93 67 115 182 33 21 7 16/9/93 75 30.9 384 25 13 8 19/9/93 78 242 320 21 13 8 Rainfall 20/9/93 100 211 321 20 17 8 Rainfall 21/9/93 109 59 168 11 22 10 NepalBanda I. Range: TSP 56 - 319 (24 h) 182 - 500 (8 h) PM '0 57 - 86 (24 h) 67 114 (8 h) 5°2 13 102 (24 h) 13 - 22 (8 h) N0 2 6 - 28 (24 h) 11 - 3S (8 h) II. Average SPM 187 (24 h) I 300 (8 h) PM,o 67 (24 h) I 74 (8 h) SO. 32 (24 h) I 27 (8 h) N02 18 (24 h) , 19 (8 h) 108 Appendix 1 Table 6 Ambient Air Quality Monitoring in commercial Area - Medium Traffic (Lainchaur DOMG) Date Pollutants Sampling Remark hour ug/m3 TSP "T/,,\ "'/"\ PM"o Particle TOTAL 6/11/93 78 129 207 19 13 24 Holiday 7/11/93 82 201 283 18 13 8 8/11/93 100 74 174 14 26 24 Holiday 9/11/93 82 261 343 18 13 7 10/11/93 146 240 386 12 23 24 11/11/93 115 242 357 36 13 8 12/11/93 103 91 194 40 13 24 13/11/93 116 221 337 12 13 8 Holiday 14/11/93 64 157 221 14 13 8 Holiday 16/11/93 67 96 163 10 13 24 17/11/93 87 158 245 23 13 8 18/11/93 121 125 246 19 13 24 19/11/93 151 630 781 27 178 6 !I! Range TSP 163 - 386 (24 h) 221 - 781 (8 h)' PM 10 67 - 146 (24 h) 64 - 151 (8 h) N0 2 10 - 40 (24 h) 12 - 36 (8 h) SO, 13 - 26 (24 h) 13 - 178 (8 h) (II) Average : TSP 228 (24 h), 367 (8 h) PM10 103 (24 h), 100 (8 h) N02 19 (24 h) I 25 (8 h) S02 17 (24 h) I 38 (8 h) URBAIR-Kathmandu 109 Table 7 Ambient Air Quality Monitoring in Low Traffic - Thimi .. Date Pollutants Sampling Remark hour ug/m' TSP NO, SO, PM10 Particle TOTAL 20/11/93 114 241 355 n.a n.a 24 Holiday 21/11/93 115 70 185 24 35 22 22/11/93 138 273 411 32 87 8 23/11/93 117 102 219 19 49 24 24/11/93 136 233 369 43 23 8 25/11/93 111 66 177 24 45 24 26/11/93 141 192 333 48 15 8 28/11/93 158 203 361 32 70 8 5 12 pm 29/11/93 104 381 485 '. 13 118 8 30/11/93 115 104 219 10 65 24 01/12/93 124 327 451 36 132 8 02/12/93 115 752 867 20 45 24 04/12/93 81 94 175 30 57 18 05/12/93 263 288 551 116 69 8 Holiday 06/12/93 243 274 517 77 184 8 07/12/93 208 165 373 18 79 16 08/12/93 214 669 883 58 73 8 09/12/93 118 561 679 31 59 8 10/12/93 132 351 483 32 72 8 11/12/93 132 594 726 22 70 8 Holiday I. Range: TSP 185 - 867 (24 hl I 333 - 883 (8 h) P~'110 111 - 117 (24 h) I 104 - 263 (8 h) NO, 10 - 24 (24 h) 13 - 116 (8 h) SO, 35 65 (24 h) 15 184 (8 h) II. Average: TSP 337 (24 hl. 521 (8 h) PM 10 115 (24 h) 159 (8 hl I NO, 19 (24 h) I45 (8 h) S02 49 (24 h), 81 (8 h) 110 Appendix 1 Table 8 Ambient Air Quality Monitoring in Residential Area (TUTH, Maharajgunj) Date Pollutants Sampling Remark hour ug/ml TSP N0 2 S02 PM10 Particle TOTAL 3/11/93 126 224 350 16 13 24 4/11/93 36 50 86 n.a n.a 8 5/11/93 32 54 86 14 8 Saturday 6/11/93 51 84 135 14 13 24 7/11/93 55 49 104 19 34 8 Holiday 8/11/93 68 52 120 20 13 16 9/11/93 60 98 158 55 13 5 10/11/93 56 106 162 9 13 24 1l/11/93 76 42 118 16 16 8 12/11/93 56 59 115 10 13 24 Hoilday 13/11/93 67 35 102 16 13 6 Holiday 14/11/93 44 19 63 12 13 8 16/11/93 39 19 58 11 13 16 (1) Range TSP 115 - 350 (24 hl 63 - 118 (8 h) PM 1Q 51 - 126 (24 h) 32 76 (8 h) NO. 9 14 (24 h) 12 19 (8 h) SO, 13 34 (24 h) 13 - 13 (8 hl (II) Average SPI"! 191 (24 h) , 93 (8 hl PM lO 72 (24 h) , 49 (8 h) N02 12 (24 hl , 15 (8 h) S02 19 (24 hl, 13 (8 hl URBAIR-Kathmandu III Table 9 Ambient air Quality Monitoring in Residential Area - Naya Baneshwor. Date Pollutants Sampling Remark hour ug/ml . SPM N02 S02 PM~o Particle TOTAL 01/9/93 27 48 7S 25 13 24 Rainfall 02/9/93 19 16 35 57 14 8 Rainfall 03/9/93 43 21 64 66 13 8 Rainfall 11/11/93 150 120 270 9 13 24 13/11/93 161 161 254 9 13 24 I. Range: TSP 7S 270 (24 h) 35 64 (8 h) PM10 27 161 (24 h) 19 43 (8 h) S02 o 13 (24 h) 13 14 (8 h) N02 0 2S (24 h) 57 66 (8 h) II. Average SPM 200 (24 h) . 50 (8 h) PM 10 113 (24 h) . 31 (8 h) S02 13 (24 hl. 14 (8 h) N0 2 25 t24 h) I 61 (8 h) 112 Appendix 1 Table 10 Ambient Air Quality Monitoring in Residential Area Jaya Bageshwori (Chabahi 11 ) Date Pollutants Sampling Remark hour ug/m) SPM NO" SO" PM~o Particle TOTAL 07/12/93 131 230 361 28 71 8 08/12/93 108 125 233 20 23 24 09/12/93 123 231 354 34 164 8 10/12/93 95 76 171 17 23 8 12/12/93 132 468 600 126 225 24 13/12/93 132 141 273 11 41 5 15/12/93 109 193 302 30 65 24 17/12/93 93 142 235 23 49 20 18/12/93 145 118 265 27 55 20 19/12/93 115 292 307 53 121 20 a I. Range: TSP 171 - 273 (24 h) 307 - 361 (8 h) PM~o 95 - 132 (24 h) 123 - 131 (8 h) N0 2 17 - 341 (24 h) 28 - 53 (8 h) S02 23 41 {24 hl 71 - 164 (8 h) II. Average: TSP 22S(24 h} , 341 (8 l1) , 267 (20 h) PM 10 112(24 h) , 116 (8 h) , 123 (20 h) N0 2 49 (24 hl, 38 (8 h) , 37 (20 h) S02 29 (24 h) , 119 (8 h) , 56 (20 h) URBAIR-Kathmandu 113 Table 11 Ambient Air Quality Monitoring in Industrial Area - Balaju (BID). Date Pollutants sampling Remark hour ug/ml , TSP N0 2 S02 PM10 Particle TOTAL 01/9/93 21 50 71 71 13 24 . Rainfall 10/9/93 77 60 137 11 13.4 24 13/9/93 32 81 113 14 21 24 16/9/93 30 79 109 28 13 22 17/9/93 46 116 162 34 26 8 18/9/93 35 75 110 21 21 8 02/9/93 42·' 14 56 63 13 8 Rainfall 09/9/93 35 72 107 8 13 8 05/9/93 n.a. n.a. n.a. 42 13 6 Rainfall I. Range: TSP 71 - 137 (24 h) 56 - 162 (8 h) PM 10 21 - 77 (24 h) 35 - 46 (8 h) SO. 13 - 21 (24 h) 13 - 26 (8 h) N0 2 11 - 71 (24 h) 8 - 63 (a h) U· Average TSP 108 (24 h) I 109 (8 h) PM 10 40 (24 h), 40 (8h) S02 15 (24 h), 17 (8 h) N0 2 31 (24 h) , 34 (8 h) 114 Appendix 1 Table 12 Ambient Air Quality Monitoring in Industrial Area - Patan (PID) Date Pollutants Sampling Remark hour ug/ml TSP N0 2 S02 PM10 Particle TOTAL 01/9/93 53 37 90 83 13 24 Rainfall 10/9/93 36 33 69 26 13 24 13/9/93 53 49 102 12 13 21 Rainfall 02/9/93 64 61 125 69 13 8 Rainfall 05/9/93 n.a n.a. n.a. 80 13 8 Rainfall I. Range: TSP 69 - 102 (24 h) 0 - 125 (8 h) PM 10 36 - 53 (24 h) 0 64 (8 h) S02 13 - 13 (24 h) 13 - 13 (8 h) N0 2 12 - 83 (24 h) 69 - 80 (8 h) II. Average TSP 87 (24 h) , 125 (8 h) PM 10 47 (24 h) , 64 (8 h) S02 13 (24 h) , 13 (8 hJ N0 2 40 (24 h) , 75 (8 hJ URBAIR-Kathmandu 115 Table 13 Ambient Air Quality Monitoring in Bhaktapur Industrial Areas Date Pollutants Sampling Rema hour rk ug/ml SPM NO a S02 PM10 Particle TOTAL 12/12/93 104 186 290 19 79 20 13/12/93 122 107 229 21 59 8 14/12/93 95 64 159 19 38 20 15/12/93 94 74 168 18 48 20 18/12/93 131 104 235 24 67 20 19/12/93 169 625 794 78 101 8 :t. Range: TSP 159 - 290 (20 .h) 229 - ?94 (8 h) PM10 94 - 131 (20 h) 122 - 169 (8 h) N0 2 18 - 24 (20 h) 21 - 78 (8 h) S02 38 - 79 (20 h) 59 - 101 (8 h) II. Average: TSP 213 (20 h) 512 (8 h) I PM 10 137 (20 h) , 146 (8 h) N0 2 20 (20 h) I 50 (8 h) SOl 58 (20 h) , 80 (8 h) 116 Appendix 1 Table 14 Ambient Air Quality Monitoring in Around Himal Cement Factory Date Pollutants Sampling Remark hour ug/m 3 SPM N0 2 S02 " PM10 Particle TOTAL 15/12/93 157 373 560 ' 38 45 24 16/12/93 147 158 305 17 61 24 17/12/93 127 1093 1220 131 238 3 18/12/93 215 329 544 54 120 8 19/12/93 194 230 424 58 65 24 1:. Range: TSP 305 - 560 (24 h) PM10 147 - 194 (24 h) 17 - 58 (24 h) 45 - 65 (24 h) 1: I:. Averag:e: TSP 430 (24 h) PM 10 166 (24 h) N0 2 38 (24 h) S02 57 (24 h) URBAIR-Kathmandu 117 Table 15 Ambient Air Quality Monitoring in Regional Background Control site - Tribhuvan University, Kirtipur. r ~i Dace ! Pc>l: utants Sc.r.:~-: l: :~:-"":. :: .::::.. :-.; :'-f: II i ~-::.: ~ Ii I ! ug/m~ - SPM NO: .sO: J ! PM ,O Particle TOTAL , 18/11/93 75 17 92 14 13 24 21/11/93 39 38 77 23 21 8 22/11/93 35 23 68 50 35 8 23/11/93 41 39 80 26 35 8 24/11/93 64 53 117 16 20 8 25/11/93 19 55 74 17 26 8 26/11/93 59 19 78 19 63 5 27/11/93 83 18 103 9 13 8 Holiday. 29/11/93 64 13 77 11 35 24 i 01/12/93 29 16 45 10 77 24 02/12/93 06/12/93 57 75 03 2:<: 60 97 20 20 40 32 8 L:4 I 07/12/93 58 46 104 38 76 8 08/12/93 69 12 81 82 70 8 09/12/93 52 31 83 45 80 8 . 12/12/93 73 24 97 35 39 24 14/12/93 81 74 155 20 33 24 16/12/93 113 169 282 90 260 3 19/12/93 136 96 232 83 285 3 I I. Range: TS? 45 155 (24 h) 68 117 (8 h) PI'1 ,o 64 81 (24 h) 19 83 (8h) NO: 10 35 (24 h) 9 82 (8 h). SO: 13 77 (24 h) 13 80 (8 h) II. A"\rerage: TSP 94 (24 h) , 84 (8 h) PM 10 66 (24 h) , 52 (8 h) N0 2 18 (24 h) , 33 (8 h) S02 38 (24 h) , 42 (8 h) APPENDIX 2 AIR QUALITY GUIDELINES Nepalese air quality guidelines/standards have not yet been established. WHO air quality guidelines and standards are listed in Table 1. Table 1: WHO Air Quality Guidelines/Standards (WHO, 1977a, 1977b, 1978, 1979,1987) 10 15 30 minutes Year of standard Parameter minutes minutes 1 hour 8 hours 24 hours 1 year 802 l-l-g/m3 500 350 125a 50 a 1987 802 f.Lg/m' 100-150 40-60 1979 B8 b ~/m' 125a 50 a 1987 B8 b ~/m3 100-150 40-60 1979 T8P Jlg/m' 120a 1987 T8P J..I.9/m3 150-230 60-90 1979 PM 10 f.Lg /mJ 70 a 1987 Lead f.L9/m3 0.5-1 1987, 1977b CO mglm3 100 60 30 10 1987 N02 f.Lg/m3 400 150 1987 N02 j.l.g/m3 190-320C 1977b 3 03 Jlg/m 150-200 100-120 1987 03 f.L9 fm3 100-200 1978 Notes (WHO/UNEP1992): a Guideline values for combined exposure to sulfur dioxide and suspended particulate matter (they may not apply to situations . where only one of the components is present). b Application of the black smoke value is recommended only in areas where coal smoke from domestic fires is the dominant component of the particulates. It does not necessarily apply where diesel smoke is an important contributor. c Not to be exceeded more than once per month, Suspended particulate matter measurement methods (WHO/UNEP 1992) as (Black smoke) - a concentration of a standard smoke with an equivalent reflectance reduction to that of the atmospheric particles as collected on a filter paper. TSP (Total suspended particulate matter) - the mass of collected particulate matter by gravimetric analysis divided by total volume sampled, PM10 (Particulate matter less than 10 ~ in aerodynamic diameter) - the mass of particulate matter collected by a sampler having an inlet with 50 per cent penetration at 10 Jlm aerodynamic diameter determined gravimetrically divided by the total volume sampled. TP {Thoracic particles, as PM10 IP (Inhalable particles, as PM10), 118 APPENDIX 3 EMISSIONS INVENTORY INTRODUCTION Two fairly comprehensive emissions inventories have been previously worked out for Kathmandu Valley, namely by Devkota (1992) and by Shrestha and Mana (1993). Both investigations covered emissions from most of the main air pollution sources in the Valley: road vehicles, brick and cement industry, households, other industries (e.g. potters), aircraft. Shrestha only considered the emissions from "energy use", and not industrial process emissions. None of them considered resuspension from roads and other open surface construction, or refuse burning. Both treated the compounds TSP, CO, S02, NO x, VOC and CO 2. Devkota attempted also to estimate emissions of benzene specifically, and ofPAH from road traffic. The following comprehensive emission survey is based on the works of Devkota (1992) and Shrestha and Malia (1993). The nCA Study on Kathmandu Valley Urban Road Development (nCA, 1992) gave valuable data on the distribution of traffic on the road network of the Valley. RONAST, through the URBAIR contract on data collection, also provided data on traffic, fuels, production etc. used in the following. In addition, the following investigations of the industry and its emissions have been used: · Bhattarai (1993): Paper on Industrial Contribution to Air Quality, presented at the URBAIR Workshop in December, 1993. · Thapa, Shrestha and Karki (1993): A Survey of Brick Industries in the Kathmandu Valley. · NESS Ltd. (1995): Assessment of the Applicability of Indian Cleaner Process Technology for Small Scale Brick Kiln Industries of Kathmandu Valley. Gridded emission fields (emissions distributed in a km2 grid net) were produced using the supporting software programs for the KILDER dispersion modeling program system, developed by NILU (Gram and B0hler, 1992). The. km2 distribution of area source emissions was based on traffic distribution and population distribution data. The area selected for air pollution modeling, and thus for emission inventorying, is shown in Figure 1. It consists of a 27x21 km2 grid, covering the full area of the Valley. 119 120 Appendix 3 Figure 1: Kathmandu Valley air quality modeling area. · Bulrs trench kilns · Hoffmann Idlns 20 o A Himal Cement Industrial areas / 1\1',' , ...... , , ' "- \, \_\60).- I \ I' I_I "', ;;': , , ,-:~ .. - f~ , ,. ..... --" '\ 15,' :" , ,. .... '\ ".. . . . '''0 " "", ""- .......... 1400_ .. _' ~ ~ ,," - .... "" I \ \ ~~~ ... ' ... "'- ... " -, . : .. :...-. ·· · ·· 1 5 10 15 20 25 POPULATION DISTRIBUTION The spatial distribution of the population within the grid system is important information when the fuel consumption, especially domestic fuel consumption, is to be distributed within the grid system. The total population of the URBAIR modeling area for Kathmandu Valley is 1,063,000 inhabitants for the year 1991. This is the number used by JICA in the transportation study. The basis for distributing the population into km2 grids is given by Table I and Figure 2, with reference to the JICA transportation study. The further distribution into km2 grids was done subjectively, based on the distribution of villages within each square kilometer. The resulting distribution of the total population is given in Figure 3. URBAIR-Kathmandu 121 Figure 2: "Traffic zones" ofKathmandu Valley. (Ref: JleA, 1992). N 1 122 Appendix 3 Figure 3: Distribution ofthe Kathmandu Valley population within the km2 grids ofthe modeling area, 1990191. (In tens ofinhabitants.) 7 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 68. 118. 186. 169. 169. 105. 105. 174. 140. 105, 70. 52. 106. 71. 71. 158. lB. 34. 85. 102. 135. 135. 174. 209. 209. 174. 174. 105. 35. 71. 106. 141. 79. 108. 79. 79. 79. J=19 35. lB. 18. lB. lB. 35. 65. 51. 85. 220. 174. 105. 315. 157. 123. 141. 71. 106. 71. 156. 102. 88. 158. 79. IS8. J=18 35. 53. 35. 35. 35. 35. 35. 272. 406. 278. 271. 464. '46. 158. 814. 43B. 177. 247. 114. 102. 117. 158. 158. lSS. 237. J=17 18. 88. 8B. 71. ea. 8B. 35.433.406.779.490.446.446.220.673. 332. 141. 106. 117. 117. 117. 97.167.158.316. 79. Jld6 71. 71. 53. 71. 106. 71.292. 893.1049. 913. 769. 560. 561. 112. 141. 177. 129. 117. 138. 63. 54. 16. 18'. 97. 97. J=15 62. 124. BO. 66. 124. 141. 106. 98.2716.4546. 415.1231. 585. 522. 298. 526. 156. 117. 120. 72. 72. B1. 63. 45. 63. 72. J=14 · 155. 155. 124. 186. 133. 141. 371. 902.1164.2671.1329.1008. 710. 497. 3.,. 142. 154. 197. 236. 126. Bl. 72. 72. 90. 89. 102. J=l3 . 124. 155. 155. 24B. 239. 176. 276. 902.1219. 559. 910. 989. 824. 785. 106. 146. 316. 373. 290. 144. 90. 90. 35B. 134. 63. 125. Jel2 155. 186. 24B. 248. 191. 456. 162. 162. 694. 519. 648. 758.1385. 302. 110. 261. 448. 299. 251. 419. 319. 277. 693. 186. 78. 93. J=l1 62. IB6. 193. 197. 216. 323. 216. 296. 732. 944.2477.1121. 256. 125. 144. 272. 267. 229. 479. 864.1233. 976. 49B. 55. 62. 109. J=10 11. 112. 108. 216. 269. 112. 201. 148. 428. 506.1004. 841. 228. 228. 182. 171. 171. 149. 256. 128. 273. 64. 86. 62. 93. 125. J= 9 54. 54. 162. 81. 25. 9B. 94. 219. 287. 181. 383. 171. 285. 228. 185. 214. 171. 171. 85. 53. 85. 41. 93. 125, 93. Je 8 12. 39. 39. 52. 17. 49. 73. 67.179. 27.201.155. 86.157.342. 8'.121. 64. 64. 43. 53. 12. 31. 31. 16. J= 7 12. 12. 25. 49. 25. 37. 73. 90.170.1&1. 323. 414. 123.189. 86.114. 96. 21. 32. 32. 41. 21. 8. 23. 8. J. 6 25. 25. 17. )1. 37. 49. 74. 22.202.188.269.115.289.101. 57. 57.142. 53. 21. 21. 21. 21. 19. H. J= 5 12. 49. 25. 49. 49. 49. 121. 2<2. 161. 99. 210. 109. 54. 72. 61. 29. 11. 11. 11. J= 4 25. 17. 37. 37. 25. 37. 69.215. 94. lOB. 63. 72. 72. 109. 54. J= 1 6. 25. 12. 25. 3l. 37. 67.188.161. 81. 54. 36. 36. 16. J= 2 12. lB. 17. 12. lB. 17. lL 161. 81. S4. 81. 18. J= 1 S. 2'5. 25. lS. 18. 22. 13. 27. 27. 10 11 12 13 14 15 16 17 18 19 20 21 22 21 24 25 26 27 The distribution between urban/rural populations is 62-38 percent for Kathmandu district, 53-47 percent for Lalitpur district, and 35-65 percent for Bakthapur. URBAIR-Kathmandu 123 Table 1: POl!.ulation oC'tra[fj,.c zones", as given in Fi8,.ure 2. (Ref:.: JICA 19921. Zone 1991 Zone 1991 Zone 1991 Zone 1991 Zone 1991 Zone 1991 101 6,691 ! 201 25,925 ! 301 16,099 ! 401 10, 985 1 501 21,273 ! 601 31,919 102 8, 288 1 202 11,757! 302 9,794 l 402 15,015 ~ 502 32,270 ! 602 29,991 103 29,749 j 203 15,300 ! 303 18,752 1 403 26,878j 503 21, 148 1 603 24,282 104 8,592 ! 204 28,019 ! 304 404 29,291 ~ 504 604 25,783 105 37,380 ~ 205 15,856 ~ 405 36,807 i 106 24,831 j 206 406 25,886 1 107 41,2131 407 24,868j 108 9, 983 1 408 31,633 j 109 20, 329 1 409 33,674 1 110 30,07( 410 111 19,4911 112 20,281 [ 113 28,813 j 114 45,330 ~ 115 19,1901 116 19,208 i 117 12,753 1 118 32,068 ; . SUM all zones 1,175,197 FUEL CONSUMPTION The fuel sale and consumption data for Kathmandu Valley in the available references are given in Tables 2 and 3. There are wide discrepancies between the various reported numbers. Gasoline (MS) is considered to be used almost exclusively for road traffic. The amount varies between about 11,000 and 28,000 kl/yr. It appears that Shrestha arrived at his number by asking a Table 2: Fuel sale and consumption data (Liquid fuels) , kl, for Kath11l1lndu Valley. Gasoline Sector HSO Sector LOO Sector SKO Sector (MS) Shrestha and Malia (1993) 28,015 T 22,955 T 359 T 35,000 H Estimated 564 I 315 I Consumption, 1992193 702 C ..!~~!..........,................................................??!9.~.? ..................................?~!§.1~.....................................}~...................................}§.~gi?...................... Oevkota (1992) 20,093 T 70,317? 60,826 ? "Consumption" ("Diesel") NOC, 1990/91 Gautam et al. (1994) 11,098 T 21,825 T? 1,320 38,600 NOC sales, 1992193 ("Fuel oil") KWEep final report 14,250 T 27,000 T? 1990 ("Diesel") T Traffic H Household HSD High speed diesel SKO Kerosene I Industrial C Commercial LDO Light diesel oil 124 Appendix 3 number of vehicle operators about how much gasoline they use annually, and Table 3: Fuel consumption data (solidfuels), using the average number thus arrived Kathmandu Valley (10' tlyr). Commercial, at for the entire operating vehicle fleet. industrial (excL brick and cement) and household. He arrived at the operating vehicle fleet Shrestha and Malia (1993) Devkota (1992) by assuming that a certain fraction of 1992193 1990191 the registered vehicles in each category Fuel wood 122.0 H is actually in normal operation (Table 17.2 I 0.5 C 6). On the basis of fuel efficiency Coal 4.8 I figures, he also arrived at average Charcoal 0.5 H vehicle-kilometers traveled annually 0.6 C (and daily) per vehicle (see Table 7), Agricultural residue 45.4 H 35-60 I which seems reasonable. Shrestha's Animal waste 3.0 H gasoline consumption data was used in the following analysis. Motor diesel (HSD) may be used for other purposes than for road vehicles. Table 4: Estimated Annual Per Capita Consumption ofFuels in Three of the Urban and Rural Areas ofKathmandu Valley in 1992/93. (Ref: references give Shrestha and Malia, 1993). figures which agree Area Fuelwood Kerosene (I) Agricultural Animal Char- LPG fairly closely with (kg) Residues (kg) Waste (kg) coal (kg) HSD consumption for (kg) traffic. Urbani 93.5 34.5 7.5 0.0 0.8 6.3 Rural 2 115.0 23.7 75.74 5,7 0,0 0.0 Devkota's much 1 Source: Malia (1993) 2 Source: Shrestha (1993) higher total number may reflect, if correct, that HSD is used to a large extent also for other purposes, e.g. industrial/commerciaL Shrestha does not report much use of HSD in industry. Table 5: Fuel consumption in the cement and brick industry (tons/year) Kathmandu Valley. Brick Cement Bull's trench (NESS, 1995) Chinese 2 Himal ave/kiln no. of kilns Total (Shresta, '93) (Shrestha, '93) 1994 1992/93 1992193 Coal 318.8 130 41.444 4.0931 17.096 Lignite 4.5 585 Fuel wood 43.9 5.707 Saw dust 20.5 2.665 Rice husk 101.0 13.130 Tire scrap 0,3 39 1 Consumption in HHBF and BBF brick factories. 2 Devkota reports 1 ton of coal per 8,000 bricks. URBAm~Kathmandu 125 Table 6: ReG"istered vehicle 1!.01!.ulation, Bagmati. Shrestha and Malia 92193 RONAST JICA Devkota Gasoline! Reg. Operating Operating Reg. April Reg. 90/91 "No. of Diesel number fraction vehicles 93 vehicles" Car G 16,522 0.61 10,105 20,273 18,000 19,535 Jeep G 5,522 0.61 3,368 +883 (CD/UN) Minibus D 1,322 ? 372 1,333 Bus D 715 ? 110 773 7,069 7,397 Truck D 3,114 0.44 693 3,231 Tractor D 1,917 0.50 959 1,587 1,729 1,864 3 wheeler G 3,175 0.50 1,588 3 wheeler D 669 0.50 335 2 wheeler G 35,002 0.80 28,000 36,129 24,211 26,121 Table 7: Estimated Annual Average Fuel Consumption and Average Number ofKilometers Traveled Per Vehicle in Transport Sector by Vehicle Types in 1992/93. Ref.: Shrestha and Malia, 1993. Vehicle Type Fuel Type Sample Mean of Average Fuel Fuel Efficiency Average km traveled per Size Consumption vehicle (I) (kmll) (1/10 km) Annualll Daily Truck Diesel 15 8,704 4.5 2.2 39,168 107 Bus Diesel 10 8,418 3.0 3.3 25,254 69 Minibus Diesel 17 7,373 4.5 2.2 33,178 91 Jeep Diesel 20 2,315 8.0 1.25 18,520 51 Tractor Diesel 4 4,785 4.4 2.3 21,054 58 Car Gasoline 61 1,595 10.6 0.94 16,907 46 3-Wheeler Diesel 9 2,592 12.5 0.8 32,400 89 3-Wheeler Gasoline 16 1,479 11.0 0.9 16,269 45 2-Wheeler Gasoline 42 341 45.5 0.22 15,515 43 As for HSD for road traffic, Shrestha's estimation is selected here for use in the emissions survey of this study. We leave the question open that there also may be a substantial use of HSD for other purposes. Diesel oil (LDO) is reported to be used only to a small extent, in industry. Only Shrestha is reporting this, based on CBS (1993). Cottage industries with less than 10 employees are, however, not included in that survey. The consumption of kerosene seems to be around 37,000-39,000 kl annually, as reported by Shrestha and Gautam. Devkota's much larger SKO number is not taken into account in the following analysis. Data reported on consumption of solid fuels is given in Table 3 (cement and brick industry excluded, which is shown in Table 5). Regarding fuel consumption in households, the estimate of per capita consumption for rural and urban populations as estimated by Shrestha and Malia (1993) is given in Table 4. Devkota (1992) has given somewhat higher domestic fuel consumption data, based on investigation of the fuel use in 10 families living near Thankot: 175 kg of fuelwood per capita and 157 kg of agricultural residue per capita. 126 Appendix 3 Shrestha (1993) is used in this study as the main source of information on solid fuel consumption. One figure from Devkota (1992) is added, which concerns the estimated amount of fuel used by local potters (12-15 tons per potter per year, 3 000-4000 units). For fuel consumption in the Bull's Trench brick kiln industry, NESS (1995) is used as the primary source, while for the Chinese kilns and Rimal cement, Shrestha has reported consumption figures. For the Chinese kilns, the reported number from Shrestha concerns two of the 6 factories. Devkota reports the use of 1 ton of coal per production of 8 000 bricks, based on data from the Harisidhhi factory. TRAFFIC ACTMTY AND ITS SPATIAL DISTRIBUTION The total traffic activity of Kathmandu Valley has been calculated here, based upon the data reported by Shrestha (1993) on average fuel consumption and average kilometers traveled annually per vehicle class, and the number of operating vehicles in the Valley. Traffic data reported by the flCA Urban Road Development Study (flCA, 1992) and by RONAST (1994) have been used here to distribute the traffic activity spatially, in the km2 grid net. The various data reported on the total number of registered vehicles in the Valley are given in Table 6. Table 8: Traffic Activity in Shrestha's estimate ofthe fraction of vehicles actually Kathmandu, 1992-93 operating is also given. Vehicle fuel veh- km/yr Considering that the data represent different years, (millions) there is fair agreement between the sources. One notable Gasoline discrepancy is that Shrestha and RONAST give a Cars, taxis 170.8 3-wheelers (TC) 25.8 substantially lower number of registered buses and trucks 2-wheelers (MC) 434.4 than flCA and Devkota. The former are the most recent Subtotal 631.0 data. Diesel Table 7 gives Shrestha's data on average fuel Jeeps 62.4 consumption, fuel efficiency and resulting average Minibuses 12.3 kilometers traveled per vehicle class. Shrestha's figures Buses 2.8 Trucks 27.1 in Table 8 give the traffic activity data for the year Tractors 20.2 1992/93. This total traffic activity corresponds to the 3-wheelers (TC) 10.9 total consumption of gasoline and motor diesel in traffic Subtotal 135.7 as given in Table 2 (Shrestha and MalIa 1993). Total 766.7 The average vehicle composition of the traffic has also been reported by others (Table 9). There may be some discrepancy between the various authors regarding the classification of vehicles. The main discrepancy in the results of Table 7 is that Shrestha has a very high relative number for MC activity, at the expense of Tempo (3-wheelers) activity. His sum for Tempo and MC is, however, in fair agreement with other sources. The problem seems to be that Shrestha has based himself on a too low average driving distance for the Tempos and too long distance for the MC's. URBA1R-Kathmandu 127 Table 9: Composition ofvehicle categories in Kathmandu traffic. JICA (1992) Daily Giri (1993) Devkota (1992) Shrestha (1993) Rush-hour Rush-hour Daily PC/taxi (G) 32.5 (20.0+12.5) 20.4 25 22.3 Jeep (Pickup) (0) 7 8.1 Minibusltrolley (0) 8.1 14.6 8 2.0 Trucks/tractors (D) 4.9 2.3 (incl. bus) 4 6.2 Tempo (G/D) 21.8 62.6 22 4.8 MC (G) 30.0 22 56.6 JICA: Based upon 29 counting locations, 1992. Giri: Based upon 33 counting locations, 1993. Oevkota: Based upon 22 counting locations, 1992. Shrestha: Based upon an analysis of total traffic activity based on fuel consumption, annual average driving distance and number of operating vehicles. The data give basis for the estimates in Table 10 of average vehicle composition of Kathmandu Valley traffic. The vehicle composition in the traffic varies substantially Table 10: Average between roads. Streets in the center have very high tempolMC Vehicle Composition percentage, while the proportion of trucks is high on the Ring Road ofKathmandu Valley (10-15 percent). Traffic In this study, account is not taken of this variation. The average Car/taxi 25% Jeep/minibus/tractor 15% composition is used as a basis for calculating composite vehicle Bus 2% emission factors for gasoline and diesel separately. Truck 5% The traffic data has been used to distribute the traffic on the main Tempo {TCI 25% road system as shown in Figure 4, which gives the estimated annual Motorcycle (MC) 28% average daily traffic (AADT) numbers on some of the main roads. 128 Appendix 3 Figure 4: The main road system ofKathmandu Valley with some ofthe traffic data used in this study. N t 2km EMISSION FACTORS The selection of the emission factors used in this URBAIR calculation for fuel combustion and road vehicles in Kathmandu Valley was based on the following data sources: · USEPA emission factors of AP42 publication. · Emission factors of the WHO publication: "Assessment of Sources of Air, Water and Land Pollution", Part I: Rapid inventory techniques in Environmental Pollution (Geneva, 1993). · Particle emission factors described in Appendix 5. URBAIR-Kathmandu 129 · Particle emission factors for road vehicles, as deduced from smoke meter measurements in the KVVECP study. The selected emission factors for fuel combustion, road vehicles and industry are shown in Tables 11 and 12. The emission factors for Nepali Kathmandu conditions may differ substantially from those Table 11: Emissionfactors usedfor URBAIR, Kathmandu Valley. Fuel combustion, refuse burning and road vehicles. TSP PM101TSP S02 NOx %S max. Fuel combustion (kg!t) Residual oil (OF): ind.fcomm. 1.258+0.381) 0.85 208 7 4 Distillate oil: ind./comm. 0.28 0.5 208 2.84 H8D: 14) (H8D. LDO): residential 0.36 ~ 1.62) 0.5 208 2.6 LDO: 1.85) LPG: ind.ldom. 0.06 1.0 0.007 2.9 0.02 Kerosene: dom. 0.06 1.0 178 2.5 0.25 Natural gas: utility 0.061 1.0 208 11.3· f ind.ldom. 0.061 208 2.5 Wood: dom. 15 0.5 0.2 1.4 Fuelwood: indo 3.6 0.5 Coal: dom.1comm. 10 0.5 1.86) Charcoal: dom/comm. 20 0.5 Agri. residue 10 0.5 Anim. waste 10 0.5 Refuse burning. open 37 1 0.5 3 Road vehicles (glkm) A B Gasoline: Cars 0.2 1 2.7 83 Octane (RON) 0.253) MCffC 0.5 1 0.07 93 Octane (RON) 0.20 Diesel: Cars, jeeps, tractors 0.6 0.9 1 1.4 14) Minibuses, tempos 0.9 1.5 1 13 Buses, trucks 2.0 3.0 13 1) 8: sulfur content. in % 2) Well ~ poony maintained furnaces 3) Actual S content in 87 RON gasoline, according to IOC Ltd quality certificate: 0.009% 4) Actual S content, according to IOC Ltd quality certificate: 0.20% 5) Actual S content, according to IOC Ltd quality certificate: <1% 6) NESS (1995) A Used for Manila, Jakarta. Bombay B Proposed and used for Kathmandu Valley. given in the tables. For road vehicles, observations of vehicle exhaust in the Valley indicate that a substantial part of the fleet has very high emissions. There are indications that this is partly due to fuel adulteration. Steadman et al. (1993) have made exhaust measurements with a remote sampling technique on Kathmandu vehicles, also finding large emission factors. It should be mentioned that the measurement site was on a slightly uphill road. The fraction of "grass polluters" was 16 percent and 25 percent for HC and CO respectively. Also, their measurements showed high opacity readings, i.e. particle emissions. Very high opacity readings have also been measured for the Kathmandu vehicle fleet as part of the KVVECP study. These measurements cannot be used 130 Appendix 3 to calculate exhaust particle Table 12: Emission factors (kg/ton) for brick and cement industries (US emISSIOn EPAAP42). factors. They TSP co %S F Pb indicate, Brick industries however, that Bull's trench the real particle per ton of bricks 9.42 0.25 6.06S 1.18 1.19 0.5 per ton of fuel emission factors - coal (bituminous) for Kathmandu wood and bali< vehicles may be -lignite substantiall y Chinese (Hoffman Bhatta) higher than Portland Cement those given in Dry process, uncontrolled Dry process, kiln 128 0.42 5.41+3.6S 2 1.4 0.06 Table 11. Clinker cooler 4.6 0.09 Also, the Dryers, grinders, etc. 48 particle 1. From mineral source. 2. From coal. emission factors for the various uses of solid fuels in Kathmandu, such as fuelwood, coal, charcoal, agricultural residue and animal refuse are not well determined. Particle emissions from Kathmandu diesel vehicles. The particle emission factors for diesel vehicles used in the URBAIR study for Manila, Bombay and Jakarta, are, as described in Appendix 5, based upon available literature, especially the measurements made on diesel vehicles in Manila. The emission factor for trucks, 2 gIkm, was based upon some 20 percent of the trucks being "smoke belchers", with an emission factor up to 8 glkm. Observations in the Kathmandu traffic and the smoke testing results from the KVVECP study (Table 13) indicate that more than 75 percent of the vehicles in each class have smoke emissions of more than 75 HSU, and some 55 percent have emissions over 85 HSU. The test is done for free acceleration of the engine and does not represent the smoke emissions during driving. However, there is a correlation between smoke emissions during free acceleration and during normal driving. In Table 14, emissions in glkm are Table 13: Summary ofdiesel vehicle smoke estimated from HSU units, based on certain test results (Ref.: KVVECP study). conditions. These g/km figures represent Vehicle type Distribution (%) of tested vehicles in estimates of emissions during "smoking smoke (HSU) level ranges conditions." <65 66-75 76-85 86-95 96-100 For loaded buses and trucks in the Tempo 2 14 16 55 13 Car 19 6 6 62 6 Kathmandu topography, it may be a valid Jeepslst.wgn. 2 7 25 59 6 estimate that smoking conditions for the Mini buses 4 5 28 56 7 vehicle occur more than 50 percent of the time Mini trucks 13 14 24 44 4 of operation. Buses 4 13 44 39 a Trucks 4 8 40 44 4 Average 7 10 26 51 6 HSU: Hartridge Smoke Units. URBAIR-Kathmandu 131 Combining data from Tables 13 and 14, the average particle emission Table 14: Particle emission factor (g/km) for diesel during "smoking conditions" for trucks, estimated from HSU data. Kathmandu trucks is 4.3 gIkm for light Particle emissions truck (0.21 fuel/km) and 8.6 glkm for glkml) glkm2) a heavy truck (0.4 I fuel/km). Hartridge g/m3 40 I engine Light truck Heavy truck Assuming that the average specific Smoke Units 2000 rpm 0.2 Ilkm O.411km 40krnJh fuel consumption by trucks and buses 30 0.13 1.6 0.8 1.6 in Kathmandu Valley is 0.3 lIkm, that 65 0.42 5.0 2.5 5.0 "smoking conditions" for the total 75 0.55 6.6 3.3 6.6 traffic activity of the Valley occur for 85 0.72 8.6 4.3 8.6 25-50 percent of the time, and that the 95 1.0 12.0 6.0 12.0 emission factor for the rest of the time 1) Based upon 12 m3 airlkm (41 engine, 2000 rpm, 40 kmlh). is 1 glkm, the average trucklbus 2) Based upon 0.03 g fuel/g air. emission factor for Kathmandu is calculated to 2.5-3.7 gIkm. This figure is supported by the emission factor presented by Dr. Mathur of ITT New Delhi in the KVVECP Summary Report, namely 11 kg particlesll,OOO liters of diesel, corresponding to 3.7 glkm for a fuel consumption of 0.22 I/km. Table 13 shows that the RSU distribution is nearly the same for all diesel vehicle types, showing that all the vehicle types are dominated by smoking vehicles. The reason for this condition in the Kathmandu Valley is probably two-fold: i) old, poorly maintained vehicles, and ii) poor fuel quality. The above considerations are a basis for increasing the emission factors for particles from diesel vehicles in Kathmandu Valley, relative to those used for Manila, Jakarta and Bombay. Both factors are shown in Table 11. EMISSIONS FROM INDUSTRY The locations of the Bull's Trench kilns, the Chinese kilns and Rimal Cement factory are shown in Figure 1. The brick industry. The brick production data used in this study is shown in Table 15. Table 15: Brick Production Data Area No. of Total production Typical stack Bull's Trench kilns. The emissions units million bricks heighUdiam 1993 1994 (m) from these kilns have been estimated Bull's Trench (Thapa et al. 1993; NESS, 1995) most recently by the NESS study Kathmandu 15 24.75 (1995). The emissions originate mainly Lalitpur 74 209.5 10/0.5 from the combustion of the fuel used, Bhaktapur 41 127.0 the most important of which are coal, Total 130 361.0 450 fuelwood and rice husk. Handling of the Chinese (Thapa et al., 1993) bricks gives rise to particle emissions Lahtpur 5 53.00 65/1.65 Bhaktapur 1 20.00 (resuspension). All fuels give Total 6 73.00 132 Appendix 3 substantial particle emissions, due to the inefficient combustion conditions in the kiln. The coal also gives rise to emissions of sulfur and other trace elements. Coal analysis results from 1994 gave an average ash and sulfur content of 18 percent and L 77 percent respectively (Table 16). Table 16: Coal analysis results, 1994 (NESS, 1995). Moisture Volatile Ash Fixed carbon (%) Sulfur Calorific value (%) (%) (%) (%) (kcallkg) Range (n=6) 0.3-6.2 7.3-37 1.9-73 20-60 0.3-4.4 5,750-7,460 Average 4.15 27.12 18.02 50.72 1.77 6,708 The emissions were calculated by 3 methods: · Based on brick production, using Table 17: Total emissions from Bull's Trench kilns in Kathmandu USEPAAP42 Valley 1994 (tons/yr) (NESS, 1995). emission factors (the Method Particles (SP) S02 CO VOC F weight of a brick is A Based on brick 15,862 6,435 1,442 405 631 451 approx. 2 kg). production B. Based on fuel 5,144 1,536 2,547 524 119 · Based on fuel combustion consumption, using C. Based on emission 4,438 4.8 16,384 2,373 0.8 USEPAAP42 measurements, India emission factors. · Based on emission measurements from Bull's Trench kilns in India. The AP42 emission factors are given in Table 12. The emission results (Table 17) show wide discrepancies between the methods: · Particles: Methods B and C agrees fairly well while method A gives very large emissions. Incidentally, using the AP42 factor for method A (9.42 kg/ton, 450 mill bricks and 2 kg/brick) gives 8,478 tons of particles, while 15,876 tons is reported by the NESS study. · S02: The methods disagree basically. Method C results indicate that the sulfur released from the coal is absorbed on the brick surfaces. · . NOx : The methods disagree basically. Method C results (together with high CO emissions) indicate poor combustion conditions. Based on this, we use an estimate of 5,000 tons of particles emitted annually from Bull's trench kilns. The emission of S02 cannot be estimated with confidence, due to the available data. Chinese (Hoffmann Bhatta) kilns. No specific information is available on the emissions from these kilns in Kathmandu Valley. Also, total fuel and other input consumption data are not available. Shrestha (1993) has reported coal consumption for two of the factories, namely HHBF and BBF (4,093 tons in 1992/93). Devkota (1992) reports that 1,000 kg of coal is required to produce 8,000 bricks (data from the HHBF factory). In addition, 15 tons of fuelwood is used annually for firing, which is URBAIR-Kathmandu 133 negligible. Using the 1,000 kg/8,000 bricks figure, it is calculated that the Chinese kilns use a total of some 9,100 tons of coal annually. The Hima) Cement Factory. The factory has a production capacity of 360 tons per day (Bhattarai, 1993), by 2 vertical shaft kilns. Stack data are as follows (Bhattarai, 1993): · Number of stacks: 2 · Height: 33.5 m · Flue gas velocity: 5.7 mls · Flue gas temperature: 120°C · Stack diameter: unknown The production has normally been some 45,000-50,000 tons annually in the period 1986-91 (Devkota, 1992), with a coal consumption of some 6,000-8,000 tons annually. In the most recent years, production has increased, and Shrestha (1993) reports a coal consumption of some 17,000 tons for 1992/93. According to Bhattarai (1993) the Himal Cement Co estimated that prior to the planned installation of effective particle emission control equipment in 1994, there was an average particle emission of 2.85 tons daily from the stack, and around 10 tons from lime stone handling at the quarry. In addition, there were substantial dust emissions from material handling and transport within the factory area. The pollution control equipment, which includes bag filters and wet scrubbers, was planned to be in operation as of December 1994. Other industries. There is a total of 2, 174 industrial establishments in Kathmandu Valley, presumably with more than 10 employees. Devkota (1992) has described the level of industrialization in the Valley. There are 3 designated "industrial districts" in the Valley: Balaju (0.35 km2), the oldest one, Patan (0.14 km2) and Bhaktapur (0.04 km2). Besides these districts, the emergence of new industries along the "Ribbon zones", i.e. Kathmandu-Thankot and Kathmandu-Bhaktapur transportation corridors, and also in the southern part of Lalitpur district, is a matter of concern (see Figure 1 for location). Devkota reported the following numbers of industrial establishments: in Balaju, 71 units; in Patan, 103 units, and in Bhaktapur, 27 units. He included the Table 18: Cottage Industries numbers of cottage industries shown in "Cottage industries" Kathmandu Lalitpur Bhaktapur (at mid-91) Table 18. Plastic and rubber 79 5 4 Another major cottage industry in Metal crafting 409 97 7 terms of number is backyard pottery, of AI, brass, Cu 32 9 which there may be several thousand in operation during the dry season. Bhattarai (1993) describes briefly the dying industry (carpet and textile) in terms of air pollution emissions. They use boilers to generate steam. Previously, rice husk was mainly used as feed stock for the boilers, but now there is a transition towards the use of diesel oil (HSD). A recent survey of 19 industries gave that 12 of them used diesel. Boilers are also used in other industries such as flour mills and leather mills. Presumably, there is a transition towards diesel also in such industries. 134 Appendix 3 Devkota estimated the amount of rice husk used by potters in up-draft kilns. The annual demand per potter may be 12,000-l5,000 kg of biomass. These "other" industries definitely represent air pollution problems localized to the areas immediately adjacent. In addition, they represent a total emissions from combustion of diesel and rice husk, and to some extent of process emissions, which should be taken into account in the total emission survey for the Valley. Their contribution to the background pollution of the Valley, and thus their effect on visibility, should be considered. RONAST (1994) reports a total diesel consumption of7.83 mill liters by these smaller industries in the Valley in 1992. Dairy products, textile processing and carpet/rugs were the largest industrial users. With reference to the HMGlMinistry of Industry, RONAST (1994) reports the TSP emissions from distributed industries in Table 19. Table 19: Industrial TSP Emissions Type of industry No. of units TSP in tons/yr Beverages/distilleries 3 5 TOTAL EMISSIONS Textile processing 85 8 Knitting mills 25 5 Carpet and rugs 1109 144 Table 20 gives the estimated emissions of TSP, Paper and products 3 0.3 PM IO , S02 and NOx associated with the various Animal feed 13 65 source categories, fuels, vehicle types and Plastic products 38 8 industries. Soap and detergents 4 5 In the previous text, the quality of the data Marbles 1 67 sources and the emission numbers have been Dry battery 880 briefly discussed. It is clear that the estimated emission figures given in Table 14 have a limited accuracy. For instance, brick industry emissions are not well determined. However, they are believed to be useful to give the first estimate of the importance of the various source categories, as contributors to the various air pollution problems of the Kathmandu Valley, such as: · roadside pollution by suspended particles and PM lO (respirable particles), · general air pollution exposure of the population, · reduced visibility. Dispersion modeling will clarify which sources contribute most to these problems. One important point in this respect is the fact that the brick industry is in operation only during the October to March period, i.e. half the year, while the other sources are in operation during the whole year. For the reduced visibility problem, this means that the brick industry is even more important, may be twice as important relatively, than indicated by the emission figures of Table 20. URBAIR-Kathmandu 135 The emissions inventory of Table 20 Table 20: Estimated emissions from air itself, together with observations in the pollution sources in Kathmandu Valley, 1992193 Valley, indicate the most important sources (tonslyr). as shown in Table 21. TSP Vehicles Gasoline: Cars/taxis 38.4 SPATIAL EMISSION DISTRIBUTION TC 67.5 4.2.105 1 MC 107.5 Diesel: Jeeps 68.4 The total emissions from each source Minibuses 22.5 category have been distributed within the Buses 45.0· 78.390 1 km2 grid net based on: Trucks 114 · the actual location of point sources (e.g. Tractors 21.6 Himal Cement Factory, brick kilns and TC 85.8 Sum vehicle exhaust 570 570 82.495 1 industrial areas; see Figure 1) · the population distribution ,..~~~.~.~p.~~~!~.~..fr.~~..~9.~~.~..................~.~~~:g..........:~Q~.............Q........... Fuel combustion · the cooking practices of the urban and Industrial/commercial rural popUlation (excl. brick/cement): 61.9 31 · the traffic activity distribution. Fuelwood Coal 48 24 172 The traffic activity was distributed as Charcoal 20 10 HSD 1.8 2 follows: LDO/FO? · The traffic activity (veh.km/yr) on the KerosenelLPG 0,1 roads with known traffic count was Agri. residue 450,0 225 calculated (vehicles x road length), and Sum industrial/commercial 582.0 292 distributed in the grid system according Domestic: Fuelwood 1,832.0 916 to the actual location of the road Agri. residue 454.0 227 Anim. waste 30.0 15 sections. Kerosene/LPG 2,3 2,3 · This traffic activity accounted for about Charcoal 10.0 5 50 percent of the total traffic activity, as ...§.~~..~.~~.~~!? .....................................?~~.?~:g......... !!.~.~~.......................... calculated from the fuel consumption Brick industry (Shrestha and Malla, 1993). Bull's Trench 5,000.0 1,250 4.8.4,4652 · The difference was distributed within Chinese 180.0 45 the grid net, proportional to the ...~.':!~..~~.?~.............................................. ?~~.?g;.~ ..........~?~~.......................... Himal Cement: Stack -2,000.0 -400 615 population distribution, with an additional weight put on the highly .....................g!.~~~.~.~.~~~......................:~&~Q:.9. .........:~Q~.......................... Miscellaneous populated city center areas. Refuse burning 385 190 · The emissions from the total traffic Construction activity in each grid square were Sum 16,565.0 4,712 calculated by first calculating High value: Based on max. allowable S content composite emission factors for gasoline Low value: Based on actual S content, according to IOC Ltd. certificate and diesel vehicles respectively, by NESS (1995): Estimates based on different methods. combining the emission factors of Table 11 and the average vehicle composition in Table 10. Those composite emission factors were calculated to be: 136 Appendix 3 · gasoline: 0.39 glkm · diesel: 1.65 gIkm Table 21: Important particulate sources TSP The emissions from the Bull's Roadside · Resuspension · Gasoline exhaust trench kilns were distributed pollution · Diesel exhaust in the grid net according to · Resuspension General · Domestic fuel combustion · Domestic fuel combustion their actual location. An population · Brick industry (mainly Bull · Brick industry (mainly Bull's average emission figure for exposure Trench) trench) each kiln was calculated, and · Resuspension · Vehicle exhaust the emissions from each grid · Resuspension square calculated by Reduced · Bull's trench brick kilns multiplying this average visibility · Domestic fuel combustion emission figure by the number · Vehicle exhaust of kilns in the square. Figures 5-9 give the resulting TSP emission distributions from each of the area-distributed source categories, as kglh (averaged over the winter half-year, October-March, 1992/93. The following ratios are used for PMIO/TSP: · Vehicle exhaust: 1.0 · Resuspension from roads: 0.25 · Fuel/refuse combustion: 0.5 · Brick industry: 0.25 · Himal Cement, stack: 0.2 · Himal Cement, diffuse: 0.1 URBAIR-Kathmandu 137 Figure 5: TSP emission from road vehicle exhaust, Kathmandu Valley. Winter half-year emission, 1992/93. Constant emission, calculated as kglhour. Unit: kglhour per km2 grid. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 2. 25 26 27 12. 14. 17. 27. 2·. 24. 15. 15. 2B . 93. 15. 10. 7, 15. 10. 10. 23. .:1·21 J. 10. S. 12. 15. 19. 19. 25. 30. 10·. 2S. 25. IS. S. 10. 15. 20. 11. 15. 1l 1l 11, J~20 s. 3. 3. 3. 13. 14. 12. 7. 12. 32. 25. 40. 94. 23. 1$. 20. 10. 15. 10. 22. 15. 13. 23. 11 23. ..1=19 J=lS 5. B. 5. 5. 5. 9. 19. 41. sa. 40. 123. 140. 64. 23. 116. 63. 25. 35. 16 .. 15. 17. 23. 23. 23. 34. 3. 13. 13. 10. 13. 13. 5. 122. 176. 252. 217. 253. 6'. 31. 96. 48. 20. 15. 17. 17. 17. 14. 24. 23. 45. 11. J=17 J=16 10. 10. B, 10. 15. 10, 325. 135.1344 .1013, 845. ao. 80, 16, 20. 25. 18. 17. 20. 9. 8. 3. 3. 14. 14. 9. IB, lI. 9. 1$. 193. 187. 15.1236.4978. 641.1401. 275. 166. 100, 110, 22. 17. 17. 10. 10. 12. 9. 6. 9. 10. J=15 22. 22. lB. 27. 19. 164. 167. 220.5381.4385. 1956.1B27 . 306. 71 53. 20. 22. 28. 34. 18. 12. 10. 10. 13. 13. 15. J=14 oJ=13 18. 22. n. 36. 34. 169. 80.1020.3383.2936.1226. 65!. 548. 352. 15. 21, 45. 53. 42. 21, 13. 13. 51. 42. 12. lS. J=12 82. 125. 114. 36. 55. 111. 488. 525. 690.1237 .2031.11B7. 564 .1072. 97. 16. 37. 64. '3. 36. 60'. 46. '0. ll2. 27. 11. 13. 9. 42. 130. 149. 11B. 46. 196. 559. 399.1107.2363.1490. 743. 68. 89. 103. 74. 66. 69. 124.1176. 954. 71. 8. 9. 16. J=ll 4. 16. 15. 31 39. 39. 138. 216. 340. 974. 195. 30. 2B3. 160. 153. 14B. 137. 153. 179. 98. 146, 9. 12. 9. 13. 18. J=10 J. 9 8. 8. 23. 12. 4. 12B. 13. 306. 335. 360. 55. 2'. 41. 33, 26. 31. 2 ·. 52. 76. 58. 66. 33. 13. 18. 13. . J. 8 2. 6. 6. 7. 5. 79. 10. 10, 227. 215. 29. 22. 12. 22. 09. 12. 17. 9, 9. 6, 8. 39. 29. O. 2. J. 7 2. 2. , 7. 41. 7, 10. 13, 20. 92. 128. 62. 18. 27. 12. 16. 14. 3. 5. 5. 6. 3. 31. 37. 14. J. 6 O. 4. 5, O. 21 7, 11, 3. 29. 27, 147, 19. 01 14. 8. s. 20. 8, 3. 3. 3, 3. 3. 2. 19. J. 5 2. 7, .. 19, 19, 7, 17. 35. 34, 112. 3), 16. S, 10. 9, 4. 2. 2. 2, J. 4 4. 5. 34. 29. 4. 5. 10, 3L 13. 117, 16. 10. 10. 16, S, :1= 3 1 0, IS. .. o. s. 10 . 21, 23, 12, 101, 5. 5, 5, J. 2 2. 3, 12, 2. 5. 2, 2, n, 12. B. 35, 63. 12. 5, 03= 1 1. 4. O. J, 3, 3, 2, t, 4. lB, 25. 1 2 3 4 5 6 7 S 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 138 Appendix 3 Figure 6: TSP emission from resuspension from roads, Kathmandu Valley. Winter halfyear emission, 1992/93. Constant emission, calculated as kglhour. Unit: kglhour per km2 grid. 10 11 12 13 a 15 16 17 16 19 20 21 22 23 2. 25 26 27 J=21 3. .. ·. 7. 6. 6. ·. 4. 7. 24. ·. ). 2. ·. 3. 3. 6. J=20 1. ). 1. 3. 4. S. 5. 7. 8. 27. 7. 7. ·. 1. 3. ·. 5. 3. ·. 3. 3. 3. J=19 1. 1. 1. 1. 4. 4. 3. 2. 3. 8. 7. 10. 25. 6. 5. 5. 3. 4. 3. 6. ·. l. 6. 3. 6. J=IB 1. 2. 1. I. 1. 2. 5. 11. IS. 10. 32. 37. 17. 6. 31. 16. 7. 9. ·. ·. 4. 6. 6. 6. 9. 1. 3. 3. 3. 3. 3. 1. )2. 46. 66. 57.66.17. 8. 25. 12. 5. 4. 4. ·. 4. ·. 6. 6. 12. 3. 3. 3. 2. 3. 4. 3. 85. 35.352.265. 221. 21. 21. ·. 5. 7. 5. 4. 5. 2. 2. 1. 1. 4. ·. J=15 2. S. 3. 2. 5. 50. 49. 4.324.130'.168. 3.7. n. 44. 26. 29. 6. ·. 4. 3. ). ). 2. 2. 2. 3. 6. 6. 5. 7. S. '3. 44. 58.1410.1149.513.479. 80. 19. 14. S. 6. 7. 9. 5. 3. ). 3. 3. 3. 4. J=13 5. 6. ·. 9. 9. 44. n. 2.7. 8a·. 7.9. 321. 171. 143. ,.. 4. 5. 12. 14. 11. 5. l. 3. 1). 11. 3. 5. J=12 21. 33. 30. 9. 14. 29.128. 139.181. 324. 5)2. 311. 148.281. 25. .. 10. 17. 11. 9. 16. 12. 10. 32. 7. 3. 4. J=ll 2. ll. 3t. 39. 31. 12. 51. 147. 105. 290. 619. 39Q. 195. 18. 23. 27. 19. 17. 18. 32. 308. 250. 19. 2. 2. 4. 1. 4. ·. S. 10. 10. 3·. 57. 89. 255. 51. 91. 74. 42. 40. 39. 3·· 40. 47. 26. 38. 2. 3. 2. ·. 5. J= 2. 2. 6. 3. 1. 33. ·. ao. SB. 94. H. ·· 11. 9. 7. B. ·. 14. 20. 15. 17. 9. ·. S. ·. J= 1. 1. 2. 1. 21. 3. ). 59. 56. 8. 6. 3. 6. 13. 3. 5. 2. 2. 2. 2. 10. 7. 1. 1. 1. 2. 11. 2. 3. 3. 6. 24. 33. 16. 5. 7. 3. ·. 4. 1. 1. 1. 2. 1. 8. 10. ·. J= 1. 1. 1. 1. ·. 2. 3. 1. a. 7. 39. 5. 11. 4. 2. 2. S. 2. 1. 1. 1. 1. 1. 1. S. J= 5 2. 1. S. S. 2. S. 9. 9. 29. 9. 4. 2. 3. 2. 1. 1. 1. 9. 8. 1. 1. 3. 8. 4. 31. 4. 3. 3. 4. 2. J= 3 1. 5. 1. 1. 1. 3. 7. 6. 3. 27. 1. 1. 1. J= :: 1. 3. 1. 1. 6. 3. 2. 9. 16. ), 1. J= 1 1. 1. 1. 1. 1. 1. 1. 1. 5. 7. 10 11 12 13 14 IS 16 17 18 19 20 21 22 23 24 25 2. 27 URBAm-Kathmandu 139 Figure 7: TSP emission from domestic and industrial fuels, (excl. brick and cement industry), Kathmandu Valley. Winter halfyear emission, 1992193. Constant emission, calculated as kglhour. Unit: kglhour per km2 grid 1 2 3 « 5 6 7 8 9 10 11 I. II 14 15 16 17 18 19 20 21 22 2l 24 25 26 27 J;;:21 302. 529. 83L 755. 755. U7. 467. 779. 623. 467. 312. 233. 473. 315. 315. 706. 03=20 79. lSI. 378. 453. 604. fiOf. 779. 934. 934. 779. 779. 467. 156. 315. 473. 630. 353. 483. 353. 353. 353. ..1=19 158. 79. 79. 79. 79. 154. 38I. 227. 37S . 984. 779. 467.1406. 703. 550. 629. 315. 473. 315. 696. 455. 391 706. 353. 706. .j=18 158 . 236. 15e. 158. 158. 158. 158.1214 .1811.1242 .1209.2070.1992. 704.1817 .1956. 788.1103. 510. 455. 521 706. 706. 706.1059. J:;:17 79. 394. 394. 315. 394. 394. 158.1933.1811.3478.2186.1992.1992 . 983.3004.1483. 630. 473. 521. 52l. 52!. 433. 7U. 706.1412. 353. J;:16 315. 315. 236. 3l5. 472. 315.1305.1993.2341.2038.3431.2500.2503. 500. 630. 789. 575. 521. U6. 281. 241. 80. 80. 433. 433. 03=15 277. 554. 355. 296. 551. 630. 472. 435.2693.4510.1854.2748.2612.2332.1330.2346. 698. S2I. 536. 321. 32l. 361. 28!. 200. 281. 321. 03=14 692. 692. 554. 8ll. 592. 630.1557.2014 .3138 .2649.2966. 2249 .3170.2217 .1647. 633. 688. 877 .1052. 562. 361. 321. 32l. 401. 396. 457. .:r-l) 554 . 692. 692.1108.1067. 788.1231.2014.27:/.1. 2U5 .2076. 2207 .1840.3503. 475. 650.1413.1667.1296. 642. 401. 401.1598. 600. 369. 556. J:12 692 . 831.110S.110S. 854.2036. 721. 721. 3096.2315.2893.3385.3091.1346. 492.1167.2000.1333.1121.1872.1425.1238.3094. 829. 347. 411. ..1=11 277 . 8ll. 860. 878. 962.1443. 962.1322.3269.2108.5530.2502.114l. sss. 643 .1lls .1191.1024 .2137 .1928 .2752 .2179.l221. 243. 278. 487 . ,j;:!lO 138. 499. 481. 962.1203. 59L 899. 658.1912.225S .2240 .1876.1017.1011. 811. 763. 763. 667.n". 572.1218. 286. 383. 27S. 417. 556. J= 9 241. 241 72L 36I. 110. 439. 420. 978.1283.1708.1708. 753.1272.1017. 926. 953. 763. 763. 381. 238. 38l. 19l. 417. 556. 417. J. 8 55, 175. 175. 230. 165. l20. n7. JOO. 800. 120. 907. 692. 382. 700.1526. 382. 540. 286. 286. 191. 238. 143. 139. 139. 70. J. 7 55. 55. 110. 220. 110. 165. 327. 400. 760. 721.1Ul. 1937. SU. 844. 382. 50S. 429. 95. 143. 143. 19l. 95. )5. 104. 35. J. 6 no. 110. 165. ll7. 165. 220. 329. 100. 900. 840.1l00. 604.1291. 450. 254. 254. 636. 238. 95. 95. 95. 95. 83. 70. J. 5 55. 2l0. 110. 220. 220. 220. 540.1080. 721. Hl.1028. 484. 242.' 323. 27l. 127. 48. 48. 48. J. 4 110. 165. 165. 165. 110. 165. 310. 960. 420, 460. 282. 323. 323. ~84 . 242. J. 3 27. 110. 55. 110. 137. 165. 300. 840. 721 360. 240. 162. 162. 162. J. 2 55, 82. 165. 55. 160. 77. 50. 721 360. 240. 360. 8L 03= 1 27. 110. 110. S2. 82. 100. 60. 120. 120. 1 2 3 · 5 6 7 · 9 10 11 12 II H 15 16 17 18 19 20 21 2l 23 24 25 26 27 140 Appendix 3 Figure 8: TSP emission from Bull 's trench brick kilns, Kathmandu Valley. Winter haIfyear emission, 1992/93. Constant emission, calculated as kglhour. Unit: kglhour per km2 grid. 10 11 12 13 14 15 16 17 IS 19 20 21 22 23 24 2S 26 27 J:20 .1=19 J:lB 3:::17 J·16 .1740. J=12 . 2610. . 2610.1740 · .2610.4350. 870. .3480.1740 . J=l1 . 5220. 870. · 4350. 810. 870.1740 . .3480 . .2610 . J= 9 . 2610. . 4350.1740.1740. .1740. 870. .3480.1740 . .2610.3480. 870.5220. · 870 . .1'740, J= 7 . 2610.6960.2610.5220.6960. J= 6 .2610.8700. J= 5 .2610. 870. . 870. 87Q. J= 3 J= 2 J= 1 9 10 11 12 13 14 15 16 17 18 19 20 21 22 21 24 25 26 27 URBAIR-Kathmandu 141 Figure 9: TSP emissionfrom Chinese (Hoffman Bhatta) brick kilns, Kathmandu Valley. Winter halfyear emission, 1992/93. Constant emission, calculated as kglhour. Unit: kglhour per km2 grid , 10 11 12 1) 14 15 16 17 18 15 20 21 22 2) 24 25 26 27 J=17 J=16 . j J=10 J= 9 · 595. J= 8 J. 7 · 595. J= S J. 4 .1190. J. 2 J= 1 ;: 10 11 12 13 14 15 16 1'7 18 U 20 21 22 23 24 25 26 27 REFERENCES Bhattarai, M.D. (1993) Urban air quality workshop (URBAIR). Paper on industrial contribution to air quality. Kathmandu, Ministry ofIndustry. Devkota, S.R. (1992) Energy utilization and air pollution in Kathmandu Valley, Nepal. Bangkok, Asian Institute of Technology. (Thesis EV-9209). Gautam and associates (1994) Study report on automobile fuels, its import, supply, distribution and quality assurance in Nepal. Kathmandu, Gautam and associates, Consulting Engineers. 142 Appendix 3 Gram, F. and B0hier, T. (1992) User's Guide for the "Kilder". Supporting programs. Lillestmm (NILU TR 6/92). flCA - Japanese International Cooperation Agency (1992) The study on Kathmandu Valley urban road development. His Majesty's Government of Nepal. Kathmandu, Ministry of Works and Transport. NESS - Nepal Environmental and Scientific Services (P) Ltd. (1995) Assessment of the applicability of Indian cleaner process technology for small scale brick kiln industries of Kathmandu Valley. Thapathali Kathmandu, NESS. RONAST (1994) Reports from the data collection for the URBAIR Kathmandu proj ecl. Available from RONAST (Royal Nepal Academy of Science and Technology), Kathmandu, and from NILU, Kjeller. Shrestha, R.M. and MalIa, S. (1993) Energy use and emission of air pollutants: Case of Kathmandu Valley. Bangkok, Asian Institute of Technology. Thapa, S., Shrestha, S.S. and Karki, D. (1993) A survey of brick industries in the Kathmandu Valley. Prepared for E1\i-rHO (Environment and Public Health Organization. APPENDIX 4 EMISSION FACTORS, PARTICLES INTRODUCTION Emission factors (emitted amount of pollutant per quantity of combusted fuel, or per kilometer driven, or per produced unit of product) are important input data to emissions inventories, which again are essential input to dispersion modeling. The knowledge of emission factors representative for the present technology level of Asian cities is limited. For the purpose of selecting emission factors for the URBAIR study, references on emission factors were collected from the open literature and from studies and reports from cities in Asia. This appendix gives a brief background for the selection of emission factors for particles used in the air quality assessment part of URBAIR. MOTOR VEIllCLES The selection of emission factors for motor vehicles for use in the URBAIR project to produce emissions inventories for South-East Asian cities, was based on the following references: · WHO (1993) · USEPA (EPA AP42 report series) (1985) · Vehicles Emission Control Project (VECP), Manila (Baker, 1993) · Indonesia (Bosch, 1991) · Williams et al. (1989) · Motorcycle emission standard and emission control technology (Weaver and Chan, 1993) Table 1 gives a summary of emission factors from these references for various vehicle classes. From these, the emission factors given in Table 2 were selected, for use as a basis for llRBAIR cities. Taking into account the typical vehicle/traffic activity composition, the following vehicle classes give the largest contributions to the total exhaust particle emissions from traffic: · Heavy duty diesel trucks · Diesel buses · Utility trucks, diesel · 2-stroke 2- and 3-wheelers. Thus, the emission factors for these vehicle classes are the most important ones. 143 144 Appendix 4 COMMENTS Table 1: Emission factors (g/km) for particle It is clear that there is not a very solid basis in emissions from motor vehicles, relevant as a actual measurements on which to estimate basis for selection offactors to be used in particle emission factors for vehicles in South South-East Asian cities. East Asian cities. The given references Fuel and Vehicle Particles (glkm) Reference represent the best available basis. Comments Gasoline are given below for each of the vehicle Passenger cars 0.33 USEPAfWHO classes. 0.10 VECP, Manila 0.16 Indonesia (Bosch) 0.07 Williams Gasoline: Trucks, utility 0.12 VECP, Manila · Passenger cars: Fairly new, normally well 0.33 USEPA maintained cars, engine size less than 2.5 USEPA 1, without 3-way catalyst, running on Trucks, heavy duty 0.33 USEPA leaded gasoline (0.2-0.3 g Pb/l), have an 3-wheelers, 2 stroke 0.21 USEPAfWHO MC 214 stroke 0.21/ USEPAfWHO emission factor of the order of 0.1 g/km. 2.00/ VECP, Manila Older, poorly maintained vehicles may 0.21/0.029 Indonesia VWS have much larger emissions. The 0.2810.08 Weaver and Chan US EPNWHO factor of 0.33 g/km can be Diesel used as an estimate for such vehicles. Car, taxi 0.6 VECP, Manila · Utility trucks: Although the VECP study 0.45 USEPAfWHO 0.37 Williams (Manila) uses 0.12 g/km, the EPA factor Trucks, utility 0.9 VECP, Manila of 0.33 g/km was selected for such 0.93 EPA vehicles, taking into account generally Trucks, heavylbus 0.75 WHO poor maintenance in South-East Asian 1.5 VECP, Manila cities. 0.93 USEPA · Heavy duty trucks: Only the USEPA has 1.2 Bosch 2.1 Williams given an estimate for such vehicles, 0.33 g/km, the same as for passenger cars and utility trucks. Table 2: Selected emission factors · 3-wheelers, 2 stroke: The USEP A and 'WHO (g/km) for particles from road vehicles suggest 0.2 g/km for such vehicles. used in URBAIR. · Motorcycles, 2 stroke: The Weaver report Vehicles class Gasoline Diesel supports the 0.21 g/km emission factor suggested Passenger cars/taxies 0.2 0.6 by USEP NWHO. In the VECP Manila study a Utility vehiclesllight trucks 0.33 0.9 factor of 2 g/km is suggested. This is the same Motorcycles/tricycles 0.5 factor as for heavy duty diesel trucks, which Truckslbuses 2.0 seems much too high. Visible smoke emissions from 2-stroke 2- and 3 wheelers is normal in South-East Asian cities. Low-quality oil as well as worn and poorly maintained engines probably both contribute to the large emissions. The data base for selecting a representative emission factor is small. In the data of Weaver and Chan (1993), the highest emission factor is about 0.55 g/km. For URBAIR, we choose a factor of 0.5 g/km. Realizing that this is considerably higher than the factor suggested by US EPA, we also take into consideration the factor 2 g/km used in the URBAm-Kathmandu 145 VECP study in Manila, which indicates evidence for very large emissions from such vehicles. · Motorcycles, 4-stroke: The emission factor is much less than for 2-stroke engines. The Weaver report gives 0.08 g/km, while 0.029 g/km is given by the VWS study in Indonesia (Bosch, 1991). Diesel: · Passenger cars, taxis: The factor of 0.6 g/km given by the VECP Manila is chosen, since it is based on measurements of smoke emission from vehicles in traffic in Manila. The 0.45 glkm of USEP AfWHO was taken to represent typically maintained vehicles in Western Europe and USA, as also measured by Larssen and Heintzenberg (1983) on Norwegian vehicles. This is supported by Williams' factor of 0.37 g/km for Australian vehicles. · Utility trucks: The USEP A and the VECP Manila study give similar emission factors, about 0.9 g/km. · Heavy duty truckslbuses: The factors in the table range from 0.75 g/km to 2.1 g/km. It is clear that "smoking" diesel trucks and buses may have emission factors even much larger than 2 g/km. In the COPERT emission data base of the European Union factors as large as 3 5 g/km are used for "dirty" city buses. Likewise, based on relationships between smoke meter reading (e.g. Hartridge smoke units, HSU) and mass emissions, it can be estimated that a diesel truck with a smoke meter reading of 85 HSU, as measured typically on Kathmandu trucks and buses (Rajbahak and Joshi, 1993), corresponds to an emission factor of roughly 8 g/km! As opposed to this, well maintained heavy duty diesel trucks and buses have an emission factor of 0.7-1 g/km. As a basis for emission calculations for South-East Asian cities we choose an emission factor of 2 g/km. This corresponds to some 20 percent of the diesel trucks and buses being "smoke belchers". A larger fraction of "smoke belchers", such as in Kathmandu, will result in a larger emission factor. FUEL COMBUSTION Table 3: Emission/actors/or oil combustion (Ref.: US EPA, AP 42). (kglm3) Oil. The particle emission factors Emission factor suggested by USEP A (AP 42) are taken Uncontrolled Controlled as a basis for calculating emissions Utility boilers from combustion of oil in South-East Residual oila) Grade 6 1.25(8)+0.38 xO.008 (ESP) Asian cities. The factors are given in 1.25 xO.06 (scrubber) Grade 5 Table 3. Grade 4 0,88 xO.2 {multicyclone} Industrial/commercial boilers Residual oil (as above) xO.2 (multicyclone) REFERENCES Distillate oil 0.24 Residential furnaces Distillate oil 0.3 Baker, 1., Santiage, R., Villareal, T. and S: Sulfur content in % by weight Walsh, M. (1993) Vehicular a}: Another algorithm for calculating the emission factors is as emission control in Metro follows: 7,3xA kg/m 3, where A is the ash content of the oil. 146 Appendix 4 Manila. Draft final report. Asian Development Bank (PPT A 1723). Bosch, l (1991) Air quality assessment in Medan. Extract from Medan urban transportation study. Final Report. Washington D.C., World Bank. Larssen, S. and Heintzenberg, 1. (1983) Measurements of emissions of soot and other particles from light duty vehicles. Lillestmm (N1LU OR 50/83). (In Norwegian.) Rajbahak, H.L. and Joshi, K.M. (1993) Kathmandu Valley vehicular transportation and emission problems. Metropolitan Environment Improvement Program. Urban Air Quality Management Workshop (URBAIR), December 2, 1993. U.S. Environmental Protection Agency (1985) Compilation of air pollutant emission factors, 4th ed. Supplement A Research Triangle Park, NC, EPA (Environmental Protection Agency; AP-42). Weaver, C.S. and Chan, L.-M. (1993) Motorcycle emission standards and emission control technology. Draft report. Sacramento, CA, Engine, Fuel, and Emissions Engineering, Inc. WHO (1993) Assessment of sources of air, water, and land pollution. A guide to rapid source inventory techniques and their use in formulating environmental control strategies. Part One: Rapid inventory techniques in environmental pollution. By AP. Economopoulos. Geneva (WHOIPEP/GETNET/93.1-A). Williams, D.l, Milne, 1.W., Roberts, D.B. and Kimberlee, M.C. (1989) Particulate emissions from 'in-use' motor vehicles - I. Spark ignition vehicles. Atmos. Environ., 23, 2639 2645. Williams, D.l, Milne, Quigley, S.M., 1.W., Roberts, D.B. and Kimberlee, M.C. (1989) Particulate emissions from 'in-use' motor vehicles - II. Diesel vehicles. Atmos. Environ., 23, 2647-2662. APPENDIX 5: SPREADSHEET FOR CALCULATING EFFECTS OF CONTROL MEASURES ON EMISSIONS EMISSIONS SPREADSHEET The spreadsheet is shown in Figure 1. (Example: TSP emission, Kathmandu Valley, Base Case Scenario, 1993.) Figure 2 shows emission contributions in absolute and relative terms. The purpose of the spreadsheet is to calculate modified emission contributions, due to control measures, such as: · new vehicle technology · improved emission characteristics, through measures on existing technology · reduced traffic activity/fuel consumption · other. The emissions are calculated separately for large point sources (with tall stacks) and for area sources and smaller distributed point sources. The reason is that air pollution concentrations and population exposures are calculated differently for these two types of source categories. The columns and rows of the worksheet are as follows: Columns a) q: Emission factor, gIkm for vehicles, kg/m 3 or kg/ton for fuel combustion and process emissions. For vehicles, emission factors are given for "existing" and "new" technology. b) F,T: Amount of "activity" T (vehicle-km) for traffic activity F (m3 or ton) for fuel consumption in industrial production. c) qT,qF: Base case emissions, tons, calculated as product of columns a) and b). d) fq, fF, IT, f-: Control measures. Relative reduction of emission factor (fq), amount (fF, IT) or other (f-) resulting from control measures. e) qFfqfFf-: Modified emissions, due to control measures. f) d(qFfqfFf-): Relative emission contributions from each source, per source category: - vehicles - fuel combustion - industrial processes - miscellaneous 147 148 Appendix 5 Figure 1: URBAIR spreadsheet/or emissions calculations, Kathmandu Valley, TSP, base case 1993 Emission Amount Bas& Control measures _iIIod Relative Relative factor case emissions emissions emissions EmIssIons e, ...teQOfV tolal POINT SOURCES Q F qF fq IF f- QFfqfFf (dqFfqfFl) (dqFfq fF1)tot I I.... (loa"". {\qMo'1 {10E3bfYW1os) -I (pelWnlJ Him,1 Cemenl Drylciln 2000 1.00 1.00 1.00 2000 33.3 C~nker Cooler 0 1.00 1.00 1.00 0 0.0 Dryers. gri_ etc. 4000 1.00 1.00 1.00 4000 66.7 Quarry 0 1.00 1.00 1.00 0 0.0 0 1.00 1.00 1.00 a 0.0 0 1.00 1.00 1.00 0 0.0 Sum large point sources 6000 6000 100.0 Modified emi...ionslemiulcns. point SOUI'C. 1 DISCRETE AREA SOURCES L....IBriclc !ChI""""IdI". 146.0 1.00 1.00 1.00 0.00 0.0 0.0 Coal 20.00 9.1 182.00 1.00 1.00 1.00 182.00 3.5 1.7 IBUIIT_1d1n$ Coal 42.0 5000.00 1.00 1.00 1.00 1.00 1.00 5000.00 0.00 96.5 0.0 47.3 1.00 0.0 Fuel wood 5.7 1.00 1.00 1.00 0.00 0.0 0.0 .Other (mainly rice husk) 15.8 1.00 1.00 1.00 0.00 M 0.0 SUm discrete area sources 5182.00 5182 100.0 49.0 ModifieG emlssionsiemissions. dlscr. area sourc. 1 DISTRIBUTED AREA SOURCES Vehicles Q T TSP 'Q IT f· qTfqm (dqTfq!Tl) (dqTlQ ITQ .J9"m1 \l~whtlmesIic 1.00 Sum fuel r:omIIWItion 2907.82 2907.82 100.0 27.5 i Modillod emiulonslemi""ion., fuel 1.00 S q M qM Iq 1M t qMlqfM! (dqM tQ 1Mf)njsc I (dqM fq IMQlot II''''"'''> I",,'"""" ,_burning 37 10.4 384.8 I 1 I 384.8 100.0: 3.6 iConstruction ResuSpensiOh. open surfaces SUm miscellaneous 384.6 I 1 1 384.80 100.0 3.6 ssloM, mise. 1.00 ISum total distributed area sources 10579.02 1 10579.02 100.00 Modified emissions/emissions distr. area sources 1.00 URBAIR~Kathmandu 149 Figure 2: Emission sources Present 6000 ., Q) 5000 c: c: .9 4000 C') w 0 :::. '" c: .2 3000 '" (/) 'E CD Q) 2000 (j 'E 10 Ilg, VOC, lead) 2. emissions per sector (industry, transport, domestic, etc.) · Air pollution data: - concentration statistics per monitoring station: 1. annual average, 98 percentile, maximum concentrations (24-hour, 1 hour) 2. trend information; 3. methods description, and quality control information on methods. · Dispersion modeling: Reports describing studies and results. · Air pollution laws and regulations: Summary of existing laws and regulations. · Institutions: - Description of existing institutions working in and with responsibilities within the air pollution sector, regarding: 1. monitoring; 2. emission inventories 3. law making; 4. enforcement. - The information shall include: 1. responsibilities and tasks of the institution; 2. authority; 3. manpower; 4. expertise; 5. equipment (monitoring, analysis, data, hard/software) 6. funds. It is important that the gathering of information is as complete as possible regarding each of the items, so that we have a basis of data which is as updated and complete as possible. Remember that this updated completed information database is to form the basis for an action plan regarding Air Quality Management in DKI Jakarta. Such an action plan will also include the need to collect more data. In that respect, it is very important that the gathering of existing data is complete. PROJECT DESCRIPTION REGARDING DAMAGE ASSESSMENT AND ECONOMIC VALUATION URBAIR: TOPICS FOR RESEARCH Physical Impacts 1. Describe available studies on relations between air pollution and health. 2. Decide on the acceptability of dose-effect relationships from U.S.A. URBAIR-Kathmandu 153 3 a) Mortality: 10 llg/m TSP leads to 0.682 (range: 0.48-0.89) percentage change in mortality. 3 b) Work loss days (WLD): 1 llg/m TSP leads to 0.00145 percentage change in WLD. 3 c) Restricted activity days (RAD): 1 llg/m TSP leads to 0.0028 percentage change in RAD per year. 3 d) Respiratory hospital diseases (RHD): 1 llg/m TSP leads to 5.59 (range: 3.44-7.71) cases ofRHD per 100,000 persons per year. e) Emergency room visits (ERV): 1 llg/m3 TSP leads to 12.95 (range: 7.1-18.8) cases of ERV per 100,000 persons per year. 3 f) Bronchitis (children): 1 llg/m TSP leads to 0.00086 (range: 0.00043-0.00129) change in bronchitis. 3 g) Asthma attacks: 1 Ilg/m TSP leads to 0.0053 (range: 0.0027-0.0079) change in daily asthma attacks per asthmatic persons. 3 h) Respiratory symptoms days (RSD): 1 llg/m TSP leads to 1.13 (range:0.90-1.41) RSD per person per year. i) Diastolic blood pressure (DBP): change in DBP = 2.74 ([Pb in blood]old-[Pb in blood]new) with [Pb in blood] is blood lead level (Ilg/dl). j) Coronary heart disease (CHD): change in probability of a CHD event in the following ten years IS - i [1 + exp - {-4.996 + O.030365(DBP)}f - [1 + exp - (-4.996 + O.030365(DBP2 )}J 3 i) Decrement IQ points: IQ decrement 0.975 x change in air lead (llg/m ) Calculation example: · Let population be 10 million people. 3 · Let threshold value ofTSP be 75 llg/m (the WHO guideline). 3 · Let the concentration TSP be 317 llg/m . => Concentration - threshold 317 - 75 = 242 = 24.2 (10 J..lg/m\ => Change in mortality 24.2 x 0.682 = 16.5%. · Let crude mortality be 1% per year. => Crude mortality = 100,000 people per year. => Change in mortality due to TSP = 16.5% of 100,000 people = 16,500 people per year. 3. For those dose-effect relationships that are acceptable, base value must be gathered, e.g.: a) crude mortality b) present work days lost c) etc. Valuation 1. Mortality. a) Willingness to Pay. In U.S.A research has been carried out on the relation between risks ofjobs and wages. It appeared that 1 promille of change in risk of mortality leads to a wage difference of ca. $1,000. If this figure is applicable to all persons of a large population (10 million), the whole popUlation values 1 promille change in risk of mortality at $1,000 x 10 x 6 10 = $10 billion. An increase in risk of 1 promille will lead to ca. 10,000 death cases, so per death case the valuation is $1 million. It should be decided if in other countries, c.q. cities, 154 Appendix 6 this valuation should be corrected for wage differences (e.g. if the average wage is 40 times lower than in US.A. the valuation of 1 death case is $25,000). If this approach is acceptable, the only information needed is average wage. b) Production loss. If the approach of willingness to pay is not acceptable, the alternative is valuing human life through production loss, i.e. foregone income of the deceased. Again. the information needed is average wage. Moreover, information is needed on the average number of years that people have a job. However, those without a job should also be assigned a value. An estimate of the income from informal activities can be an indication. Otherwise a value derived from the wages (e.g. half the average wage) can be a (somewhat arbitrary) estimation. 2. Morbidity. Estimates are needed for all cases of morbidity of the duration of the illness, so as to derive an estimation of foregone production due to illness. Just as in the case of mortality (B.1.b) wages can be used for valuation of a lost working day. Moreover, the hospital costs and other medical costs are to be estimated. These costs still do not yet include the subjective costs of illness, which can be estimated using the willingness-to-pay approach to pay to prevent a day of illness. 3. Willingness to Pay to prevent a day of illness. Valuation in US.A., based on surveys among respondents, indicate that the willingness to pay to prevent a day of illness is ca. $15. This amount could, just like the amount of willingness to pay for risk to human health, be corrected for wage differences. The acceptability of such a procedure is, perhaps, somewhat lower. 4. IQ Points. Loss ofIQ of children may lead to a lower earning capacity. A US.A. estimate is ca. $4,600 per child, per IQ point, summed over the child's lifetime. If this is acceptable, the figure could be corrected for wage differences between US.A. and the city. Other Impacts. 1. Buildings. An estimate by Jackson et al is that prevented cleaning costs per household per year are $42 for a reduction in TSP concentration, from 235 llg/m3 to 115 llg/m3. This would imply a benefit of $0.35 per household per Ilg/m3 reduction. This figure could be corrected for wage differences between US.A. and the city. If that is acceptable, the information needed is the number of households in the city. 2. Monuments. It is difficult to say which value is attached to monuments, as they are often unique and their value is of a subjective character. Nevertheless, the restoration and cleaning costs of monuments could be an indication of the order of magnitude of damage to monuments. Revenue of tourism might also give a certain indication of valuation of future damage to monuments. Remark · In most cases, the valuation of damage is not very precise, and certainly not more than an indication of the order of magnitude. Technological Reduction Options. To give a reliable estimate of the costs of technological reduction options, one needs a reliable emission inventory in which is included the currently used technologies and the age and replacement period of the installed equipment. In the absence of this, the study by the city team might wish to concentrate on a case study (e.g. traffic, fertilizer industry, large combustion sources.) URBAIR-Kathmandu 155 · The first step is to identify options. Cooperation with IES is possible, once a case study is identified. · The second step is to estimate the costs, i.e. investment costs and O&M (operation and maintenance) costs. Based on the economic lifetime of the invested equipment, the investment costs can be transformed to annual costs, using writing-of procedures. Costs will often depend to a large extent on local conditions. · The third step is to estimate the emission reductions of the various reduction options. · The fourth step is to rank the options according to cost-effectiveness. For this purpose the various types of pollution have to be brought under a common denominator. A suggestion could be to calculate a weighed sum of the pollutants, using as weights the amount by which ambient standards are exceeded on average. The calculation of the cost-effectiveness consists then of the calculation of the ratio of reduction over annual cost (RIC). The options with the highest ration RIC are the most cost effective ones. 156 Appendix 6 Norsk institutt for luftforskning (NILU) P.o. Box 100, N-2007 Kjeller - Norway REPORT SERIES REPORT NO. OR 55/95 App. ISBN-82-425-0716-3 OPPDRAGSRAPPORT DATE SIGN. NO. OF PAGES PRICE 110 NOK 165, lTILE PROJECT LEADER URBAIR Urban Air Quality Management Strategy in Asia NILU PROJECT NO. 0-92117 KATHMANDU VALLEY Appendices AUTHOR(S) CLASSIFICATION '" Prepared by A Steinar Larssen, Frederick Gram and Ivar Haugsbakk: Norwegian Institute for Air Research (NILU), Kjeller. Norway Huib Jansen and Xander Olsthoorn Instituut voor Milieuvraagstukken (IVM) Vrije Universiteit, Amsterdam, the Netherlands Anil S. Giri, Royal Nepal Academy of Science and Technology (RONAST) CONTRACT REF. Kathmandu, Nepal Mr. Jitendra Shah Madan L. Shrestha, Dpt. of Hydrology and Meteorology, Min. of Water Resources, Kathmandu, Nepal REPORT PREPARED FOR: International Bank for Reconstruction and Development (the World Bank) Asian Techn. Dept., 1818 NW, Wash. D.C., 20433 USA ABSTRACT The main report describes the development of an action plan for air quality improvement in Kathmandu Valley, based upon the assessment of emissions and air quality in the metropolitan area, population exposure and health effects (damage), the assessment of costs related to the damage and to a number of proposed abatement measures, and a cost-benefit analysis. This report contains appendices on air quality measurements, emission factors and inventory, exposure calculations, etc. NORWEGIAN TITLE KEYWORDS Air Pollution Management Kathmandu Vallev ABSTRACT (in Norwegian) * Classification A Unclassified (can be ordered from NILU) B Restricted distribution C Classified (not to be distributed) II The World Bank Metropolitan Environmentallmrrovement Program Environment and Natura Resources Division Asia Technical Deportment, The World Bonk 1818 HStreet, NW Washington, DC 20433 telephone: (202) 458·2726 facsimile: (202) 522-1664