WORLD BANK TECHNICAL PAPER NO. 378 Work in progress for public discussion Dec I o Urban Air Quality ed Management Strategy - in Asia Ku'atlilJ,id Ud//e Repolrt .! ~~~~~~~~~~7, _~ lW hI i?,g , .Jitol/ra.. ShA/ RECENT WORLD BANK TECHNICAL PAPERS No. 313 Kapur, Airport Infrastructure: The Emerging Role of the Private Sector No. 314 Vald6s and Schaeffer in collaboration with Ramos, Surveillance of Agricultural Price and Trade Policies: A Handbookfor Ecuador No. 316 Schware and Kimberley, Information Technology and National Trade Facilitation: Making the Most of Global Trade No. 317 Schware and Kimberley, Information Technology and National Trade Facilitation: Guide to Best Practice No. 318 Taylor, Boukambou, Dahniya, Ouayogode, Ayling, Abdi Noor, and Toure, Strengthening National Agricul- tural Research Systems in the Humid and Sub-humid Zones of West and Central Africa: A Frameworkfor Action No. 320 Srivastava, Lambert, and Vietmeyer, Medicinal Plants: An Expanding Role in Development No. 321 Srivastava, Smith, and Forno, Biodiversity and Agriculture: Implicationsfor Conservation and Development No. 322 Peters, The Ecology and Management of Non-Timber Forest Resources No. 323 Pannier, editor, Corporate Governance of Public Enterprises in Transitional Economies No. 324 Cabraal, Cosgrove-Davies, and Schaeffer, Best Practices for Photovoltaic Household Electrification Programs No. 325 Bacon, Besant-Jones, and Heidarian, Estimating Construction Costs and Schedules: Experience with Power Generation Projects in Developing Countries No. 326 Colletta, Balachander, and Liang, The Condition of Young Children in Sub-Saharan Africa: The Convergence of Health, Nutrition, and Early Education No. 327 Valdes and Schaeffer in collaboration with Martin, Surveillance of Agricultural Price and Trade Policies: A Handbookfor Paraguay No. 328 De Geyndt, Social Development and Absolute Poverty in Asia and Latin America No. 329 Mohan, editor, Bibliography of Publications: Technical Department, Africa Region, July 1987 to April 1996 No. 330 Echeverria, Trigo, and Byerlee, Institutional Change and Effective Financing of Agricultural Research in Latin America No. 331 Sharma, Damhaug, Gilgan-Hunt, Grey, Okaru, and Rothberg, African Water Resources: Challenges and Opportunities for Sustainable Development No. 332 Pohl, DIankov, and Anderson, Restructuring Large Industrial Firms in Central and Eastern Europe: An Empirical Analysis No. 333 Jha, Ranson, and Bobadilla, Measuring the Burden of Disease and the Cost-Effectiveness of Health Interventions: A Case Study in Guinea No. 334 Mosse and Sontheimer, Performance Monitoring Indicators Handbook No. 335 Kirmani and Le Moigne, Fostering Riparian Cooperation in International River Basins: The World Bank at Its Best in Development Diplomacy No. 336 Francis, with Akinwumi, Ngwu, Nkom, Odihi, Olomajeye, Okunmadewa, and Shehu, State, Community, and Local Development in Nigeria No. 337 Kerf and Smith, Privatizing Africa's Infrastructure: Promise and Change No. 338 Young, Measuring Economic Benefitsfor Water Investments and Policies No. 339 Andrews and Rashid, The Financing of Pension Systems in Central and Eastern Europe: An Overview of Major Trends and Their Determinants, 1990-1993 No. 340 Rutkowski, Changes in the Wage Structure during Economic Transition in Central and Eastern Europe No. 341 Goldstein, Preker, Adeyi, and Chellaraj, Trends in Health Status, Services, and Finance: The Transition in Central and Eastern Europe, Volume I No. 342 Webster and Fidler, editors, Le secteur informel et les institutions de microfinancement en Afrique de l'Ouest No. 343 Kottelat and Whitten, Freshwater Biodiversity in Asia, with Special Reference to Fish No. 344 Klugman and Schieber with Heleniak and Hon, A Survey of Health Reform in Central Asia No. 345 Industry and Mining Division, Industry and Energy Department, A Mining Strategyfor Latin America and the Caribbean No. 346 Psacharopoulos and Nguyen, The Role of Government and the Private Sector in Fighting Poverty No. 347 Stock and de Veen, Expanding Labor-based Methods for Road Works in Africa (List continues on the inside back cover) WORLD BANK TECHNICAL PAPER NO. 378 Urban Air Quality Management Strategy in Asia Kathrmandu Valley Report SELECTED WORLD BANK TITLES ON AIR QUALITY Air Pollution from Motor Vehicles: Standards and Technologiesfor Controlling Emissions. Asif Faiz, Christopher S. Weaver, and Michael Walsh. Clean Fuelsfor Asia: Technical Optionsfor Moving toward Unleaded Gasoline and Low-SulftLr Diesel. Michael Walsh and Jitendra J. Shah. Technical paper no. 377. Energy Use, Air Pollution, and Environmental Policy in Krakow: Can Economic Incentives Really Help? Seabron Adamson, Robin Bates, Robert Laslett, and Alberto Ptotschnig. Technical paper no. 308. Taxing Bads by Taxing Goods: Polluttion Control with Presumptive Charges. Gunnar S. Eskeland and Shantayanan Devarajan. Directions in Development Series. Urban Air Qtality Management Strategy in Asia: Kathmandu Valley Report. Edited by Jitendra J. Shah and Tanvi Nagpal. Technical paper no. 378. Urban Air Qtuality Management Strategy in Asia: Jakarta Report. Edited by Jitendra J. Shah and Tanvi Nagpal. Technical paper no. 379. Urban Air Qtality Management Strategy in Asia: Metro Manila Report. Edited by Jitendra J. Shah and Tanvi Nagpal. Technical paper no. 380. Urban Air Quality Management Strategy in Asia: Greater Mumbai Report. Edited by Jitendra J. Shah and Tanvi Nagpal. Technical paper no. 381. Urban Air Quality Management Strategy in Asia: :Guidebook. Edited by Jitendra J. Shah, Tanvi Nagpal, and Carter J. Brandon. Vehicuzlar Air Pollution: Experiencesfrom Seven Latin American Urban Centers. Bekir Onursal and Surhid P. Gautam. Technical paper no. 373. AUTHORS Steinar Larssen Frederick Gram Ivar Haugsbakk Norwegian Institute for Air Research, Kjeller, Norway Huib Jansen Xander Olsthoorn Institute of Environmental Studies at the Free University Amsterdam, the Netherlands Mr. Anil S. Giri Mr. Rishi Shah Royal Nepal Academy of Science and Technology Kathmandu Dr. Madan L. Shrestha Department of Hydrology and Meteorology Kathmandu Dr. Bimala Shrestha Tribhuvan University Kathmandu WORLD BANK TECHNICAL PAPER NO. 378 Urban Air Quality Management Strategy in Asia Kathmandu Valley Report Edited by Jitendra J. Shah Tanvi Nagpal The World Bank Washington, D.C. Copyright © 1997 The International Bank for Reconstruction and Development/THE WORLD BANK 1818 H Street, N.W. Washington, D.C. 20433, U.S.A. All rights reserved Manufactured in the United States of America First printing December 1997 Technical Papers are published to communicate the results of the Bank's work to the development community with the least possible delay. The typescript of this paper therefore has not been prepared in accordance with the proce- dures appropriate to formal printed texts, and the World Bank accepts no responsibility for errors. Some sources cited in this paper may be informal documents that are not readily available. The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s) 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. 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The complete backlist of publications from the World Bank is shown in the annual Index of Publications, which con- tains an alphabetical title list with full ordering information. The latest edition is available free of charge from the Dis- tribution Unit, Office of the Publisher, The World Bank, 1818 H Street, N.W., Washington, D.C. 20433, U.S.A., or from Publications, The World Bank, 66, avenue d'Iena, 75116 Paris, France. Cover illustration by Beni Chibber-Rao. Cover photo by Curt Camemark, "Nepal. Kathmandu," 1993. ISSN: 0253-7494 Jitendra J. Shah is an environmental engineer in the World Bank's Asia Technical Enviromnent Unit. Tanvi Nagpal, a political economnist, is a consultant in the World Bank's Asia Technical Environment Unit. Library of Congress Cataloging-in-Publication Data Urban air quality management strategy in Asia. Kathmandu Valley report / edited by Jitendra J. Shah, Tanvi Nagpal. p. cm. - (World Bank technical paper ; no. 378) Indudes bibliographical references. ISBN 0-8213-4034-4 1. Air quality management-Nepal-Kathmandu Valley. 2. Air- Pollution-Nepal-Kathmandu Vally. I. Shah, Jitendra J., 1952- II. Nagpal, Tanvi, 1967- . III. Series. TD883.7.N352K388 1997 363.739'25'095496-dc2l 97-28977 CIP TABLE OF CONTENTS LETTER OF SUPPORT ................................ ix FOREWORD ................................ x ABSTRACT ................................Xi ACKNOWLEDGMENTS ................................ xii ABBREVIATIONS AND ACRONYMS ............................... 13 EXECUTIVE SUMMARY ................................ 1 1. BACKGROUND INFORMATION ............................... 5 SCOPE OF THE STDY ................. 5 GENERAL DESCRIPTION OF KATHMANDU VALLEY AND THE AIR POLLUTION SITUATION ..........5........... 5 DATA SOURCES ............................................................. 6 Previous studies ............................................................. 6 URBAIR data collection ............................................................. 8 SUMMARY OF DEVELOPMENT IN THE KATHMANDU VALLEY ............................................................. 8 POPULATION ............................................................. 10 FUEL CONSUMPTION ............................................................. 10 INDUSTRIAL DEVELOPMENT ..............................................................11 ROAD VEICLE FLEET ........................... : 12 2. AIR QUALITY ASSESSMENT ........................... 13 AIR POLLUTION CONCENTRATIONS ........................... 13 Concentrations in Kathmandu ........................... 14 AIR POLLUTANT EMISSIONS IN KATHMANDU VALLEY .............................................. 23 DISPERSION MODEL CALCULATIONS .............................................. 27 General description of topography and climate .............................................. 27 Dispersion conditions .............................................. 27 Dispersion model calculations, city background .............................................. 30 Pollution hot spots .............................................. 38 Population exposure to air pollution .............................................. 38 SUMMARY OF AIR QUALITY ASSESSMENT, KATHMANDU VALLEY .............................................. 41 Air pollution concentrations .............................................. 41 Air pollutant emissions inventory .............................................. 44 Population exposure to air pollutants .............................................. 44 Visibility reduction .............................................. 44 IMROVING AIR QUALITY ASSESSMENT .............................................. 45 Main shortcomings and data gaps .............................................. 45 vii viii 3. AIR POLLUTION IMPACTS ................................................................... 47 INTRODUCTION .................................................................. ...... 47 IMPORTANT IMPACTS IN KATlHMANDU VALLEY .......................... ....................................... 48 Mortalitv .................................................... 48 Illness (morbidit.v) .................................................... 49 VALUATION OF HEALTH IMACTS ................................................................. 49 HEALTH IMPACT AND ECONOMIC DAMAGE BY SOURCE CATEGORY ................................................... 50 CONCLUSIONS ................................................................. 52 4. ABATEMENT MEASURES: EFFECTIVENESS AND COSTS ...................................... 53 INTRODUCTION ................................................................. 53 TRAFFIC ................................................................. 53 Implementation of a scheme for inspection & maintenance .................................................... 54 Improvingfuel quality .................................................... 55 Adoption qf clean vehicle emissions standards .................................................... 57 Improved abatement/other propulsion techniques .................................................... 59 Addressing resuspension .................................................... 59 Improvement of traf.fic management .................................................... 59 Construction and improvement of mass-transit systems ..................................................... 60 INDUSTRIAL COMBUSTION (EXCLUDING BRICK MANUFACTURING) ............................ ........................ 60 BRICK MANUFACTURING ................................................................. 60 DOMESTIC EMISSIONS AND REFUSE BURNING ................................................................. 61 CONCLUSIONS ................................................................. 61 5. ACTION PLAN ................................................................... 63 ACTIONS TO IW ROVE AIR QUALITY AND ITS MANAGEMENT ........................ ..................................... 63 Actions to improve air quality ................................................................. 63 Actions to improve the air quality management system ............................................................ 64 6. EXISTING LAWS AND INSTITUTIONS ................................................................... 75 LAWS AND REGULATIONS ON AIR POLLUTION ................................................................................ 75 INSTITUTIONS INVOLVED ................................................................................ 76 RIEFERENCES ........................................................................................................................79 APPENDICES ................................................................... 83 1. AIR QUALITY STATUS, KATHMANDU VALLEY .83 2. AIR QUALITY GUIDELINES ................................................................ 119 3. EMISSIONS INVENTORY ................................................................ 121 4. EMISSION FACTORS, PARTICLES ................................................................ 145 5. SPREADSHEET FOR CALCULATING EFFECTS OF CONTROL MEASURES ON EMISSIONS ................................................................ 149 6. PROJECT DESCRIPTION FOR LOCAL CONSULTANTS ...................................................... 153 viii ENVIRONMENT PROTECTION COUNCIL URBAN ENVIRONMENT MANAGEMENT COMMITTEE LETTER OF SUPPORT 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, URBAIR 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 Government/Nepal, Environment Protection Council, Urban Environment Management Committee is fully 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 Enviroment Management Committee/EPC FOREWORD In view of the potential environmental consequences of continuing growth of Asian metropolitan areas, the World Bank and United Nations Development Programme launched the Metropolitan Environmental Improvement Program (MEWP) in six Asian metropolitan areas-Beijing, Mumbai (Bombay), Colombo, Jakarta, Kathmandu Valley and Metro Manila. The mission of MEIP is to assist Asian urban areas address their environmental problems. Recognizing the growing severity of air pollution caused by industrial expansion and increasing numbers of vehicles, the World Bank through MEIP started the Urban Air Quality Management Strategy (URBAIR) in 1992. The first phase of URBAIR covered four cities- Mumbai (Bombay), Jakarta, Metro Manila and the Kathmandu Valley. 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 for the metropolitan regions. The approach used to achieve this objective involves the assessment of air quality and environmental damage (on health and 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 of this 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 between 1993 and 1995. The 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 costs 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 during the second workshop. NILU and IES carried out cost-benefit analysis of some selected abatement measures, showing the economic viability of many of the technical control options. It is hoped that this analysis will form the basis for further analysis of data, and formulation of strategies for air pollution control. Local institutions may refer to it as a preliminary strategy and use it in conjunction with the URBAIR Guidebook to formulate policy decisions and investment strategies. Maritta Koch Weser Division Chief Asia Environment and Natural Resources Division x ABSTRACT Severe air pollution is threatening human health and the gains of economic growth in Asia's largest cities. This report aims to assist policy makers in the design and implementation of policies, monitoring and management tools to restore air quality in Kathmandu, the political and commercial hub of Nepal. Kathmandu Valleys' population grew by 44 percent from 1980 to 1990. This growth was accompanied by a doubling in the number of vehicles. The number of registered brick kilns, one of the main industries, tripled in the same time period. Atmospheric visibility data show a substantial decrease in the number of clear days and point to particulate pollution as a growing problem in Kathmandu. The brick industry, Himal Cement Plant. domestic fuel combustion, and vehicle emissions are the main sources of particulate pollution. World Health Organization air quality guidelines for TSP and PM10 are often substantially exceeded. TSP concentrations have been measured at above 800 4g/m3. Using dose-response equations developed in the United States, this report states that in 1990 particulate pollution caused 84 excess deaths, 475,298 restricted activity days and 1.5 million respiratory symptom days among other health problems. The monetary value attached to these impacts totaled NRs200,000 million. Applying the essential components of an air quality management system to the pollution problem in Kathmandu Valley, this report suggests an action plan listing abatement measures for the short, medium and long terms. Recommendations fall under two categories: institutional and technical. A single institution with a clear mandate and sufficient resources should be made responsible for air quality management in the city. In addition, data gathering and processing capabilities need vast improvements. Technically, it is crucial that pollution from brick kilns and the cement industry be better monitored. In terms of vehicular pollution, it is crucial that gross polluters be identified and penalized. Diesel quality should be improved and unleaded gasoline made widely available. This is crucial for the enforcement of clean vehicle emissions standards. The regular inspection and maintenance of vehicles is also crucial to ensuring that such standards are maintained. The sulfur content of fuel oil should also be reduced. Awareness raising through public and private organizations, including educational institutions, is key to bringing about policy change on matters related to air pollution. xi ACKNOWLEDGMENTS 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 Affairs, the Norwegian Consultant Trust Funds, and the Netherlands Consultant Trust Funds. Host governments and city administrations provided substantial input. 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 for MEIP-Kathmandu, Guru Bar Singh Thapa, contributed greatly to the successful outcomes. In the World Bank's Environment and Natural Resources Division, Asia Technical Group, URBAIR was managed by Jitendra Shah, Katsunori Suzuki, and Patchamuthu Illangovan, under the advice and guidance of Maritta Koch-Weser, Division Chief, and David Williams, MEIP Project Manager. Colleagues from World Bank Country Departments and Kathmandu Resident Mission offered program assistance and comments on the numerous drafts. Management support at the World Bank was provided by Sonia Kapoor, Ronald Waas, and Erika Yanick. Tanvi Nagpal and Sheldon Lippman were responsible for quality assurance, technical accuracy, and final production. Julia Lutz designed the layout. 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, in addition to the above mentioned, contributed to the URBAIR process and its outcome. • Mr. Murkesh Bhattarai, Ministry of Industry * Mr. M. Dehal, MEIP/MHPP * Mr. Surendra R. Devkota, Industrial Pollution Control Project, Ministry of Industry * Umesh B. Malla, Joint Secretary, vIHPP/Member Secretary UEMC/MHPP • Mrs. Sony Pradhan, Field Expert, URBAIR Project, RONAST * Toran Sharma, NESS-Brick Kiln Contribution to Air Quality * Rohit Thapa, Vehicle Emission Control Program in the Kathmandu Valley * Dr. S.P. Sagar Thapaliya, Kathmandu Valley Traffic Police xli ABBREVIATIONS AND ACRONYMS ADT average daily traffic NH3 ammonia AQG air quality guidelines NIEMP National Industrial Energy AQMS air quality management system Management Program Co carbon monoxide NOx nitrogen oxide EIA environmental impact assessment NPC National Planning Commission ENPHO Environment and Public Health PAH polycyclic aromatic hydrocarbons Organization Pb lead EPC Environmental Protection Council PM10 particulate matter of 10 microns or ERV emergency room visits less g/il grams per liter ppb parts per billion GDP gross domestic product RAD restricted activity days GNP gross national product RHA respiratory hospital admission H hypertension RHD respiratory hospital diseases H2S hydrogen sulfide RON research octane number HC hydrocarbon RONSAT Royal Nepal Academy of Science HMG His Majesty's Government and Technology IES Institute for Environmental Studies, RSD respiratory symptom days Amsterdam SKO kerosene IPCR Industrial Pollution Control SO2 sulfur dioxide Regulation S04 sulfate KVVEPC Kathmandu Valley Vehicle TSP total suspended particles Emission Control Project UNDP United Nations Development LDO light diesel oil Programme LPG liquefied petroleum gas UNEP United Nations Environment pg microgram (10 6 grams) Programme mg milligramns (10 3 grams) URBAIR Urban Air Quality Management Rg/Im3 particulate concentration in Strategy in Asia micrograms per cubic meters USAID United States Agency for MEIP Metropolitan Environmental Intemational Development Improvement Program VOC volatile organic compounds MTBE methyl-tertial-butyl-ether VSL value of statistical life NILU Norwegian Institute for Air WHO World Health Organization Research, Kjeller, Norway WTP willingness to pay NGO nongovernmental organization xiii 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 Himal Cement Plant is one of the major industrial sources of pollution. With the growth in the number of vehicles and industrial expansion, the consumption of coal and automotive fuel has increased. Over the period 1980-93, the increase has been about 150 percent for gasoline, 175 percent 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. 1). 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. 1 2 Executive Summary Air pollution measurements show that Figure ES.1: No. of days in January with good visibility particulate pollution is the (>8,000 m) at given hours of the day most significant problem in 30- Kathmandu Valley. Total January ,' early 70s TSP emissions per year ea y amount to 16,500 tons. PMIo 20 ,.--9 emissions are 4,700 tons/year. The main sources of particulate pollution are 10- the brick industry (28% PM10, 31% TSP); domestic - - fuel combustion (25% PM1o, 0- 14% TSP); the Himal 6 8 L0cltime 16 18 Cement Plant (17% PM1,O Source: M.L. Shrestha (1995). 36% TSP); vehicle exhaust (12% PMIo, 3.5% TSP) and Table ES.): Impacts of airpollution (PMi) on mortality PMIo, 9% TSP).infHO air quality and health and their valuation in Kathmandu Valley guidelines (AQG) for TSP and (199 PMIo are often substantially Number of Value (NRs) PM10eded. ar ere oftenubsanty Type of health impact cases Specific Total (1,000) exceeded. There have been Excess mortality 84 340,000 28,644 measured 24-hour TSP Chronic bronchitis 506 83,000* 41,988 concentrations above 800 gig/m3, Restrcted activity days 475,298 56 26,617 while the WHO AQG is 150- Emergency room visits 1,945 470-720** 1,167 230 ,ug/m3. Bronchitis in children 4,847 350 1,697 For practical and Asthma 18,863 454,170** 11,318 m odological an o Respiratory symptom days 1,512,689 50 75,634 methodological reasons only a Respiratory hospital admissions 99 4,160 415 partial assessment and valuation Total 209,051 of the health impacts due to PM1o * Shrestha's estimate is about NRs146,000, based on an undiscounted was possible (Table ES. 1) In total amount over 27 years. Discounting with 5% leads to an estimate of monetary terms the total impact is NRs83,000. about NRs200,000 million. ** 600 used as average in calculations. Impact of lead pollution due to the use of gasoline which contains lead is not 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 URBAIR-Kathnmandu 3 air pollution activities and emissions monitoring of air pollution and Figure ES.2: Air quality management system dispersion parameters; calculation of air pollution concentrations, by Dispersion dispersion models; inventory of moel/ MonRorilig population, materials and urban development; calculation of the effect of abatement and control Emissions Airpollut70n measures; and establishment and concentrafions improvement of air pollution l regulations. Abatement Control Exposure In order to ensure than an measures & options AQMS is having the desired impact, regulations it is also necessary to carry out surveillance and monitoring. This Cost asessent requires the establishment of an Air Quality Information System (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 PMIo. 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 sho.uld be more strictly enforced. The success of this action depends upon the routine maintenance and adjustment of engines. * Improved diesel quality. 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 benefts from 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 Brick (Bull's trench kilns) 1,250 -10 -3 -57 - 7,832 62 4 Executive 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 database 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 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 U]RBAIR/MEIP 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. 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 l Except as indicated, "dollarse refers to 1992-93 U.S. dollars. Except as indicated, all figures, tables, and textboxes were created by the authors for this report. 5 6 Background Information 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. 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 1 0 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). DATA SOURCES 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 (JICA, 1992). • Ram M. Shrestha and Sunil Malla (1993) Energy Use and Emission of Air Pollutants: Case of Kathmandu Valley, Asian Institute of Technology, Bangkok. URBAIR-Kathmandu 7 Figure 1.1: Air quality management area of Kathmandu Valley _ 2 1 _s 1 1 ,\ 1 1 1 1 i E 1I I .I - I :,, A ,)~~~ I I - I - I ; 0-08v -' -$ 0 W t ts~~I -- - Co I 0 / A~ -~~~~~~~~~~~~~~~~~~~~~ I~ ~~~~~~~~~~~~~~~~~- U ) .....................1 0 - C, LO 04 ~ ~ ~ ~ ~ ~ ~ ~ ~~~~- /-- 8 Background Information * H.B. 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. 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 UNDP/World 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). 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. 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. URBAIR-Kathmandu 9 Figure 1.2: Development and growth trends over the last two decades in Kathmandu Valley Population growth in Kathmandu valley. 1400 1200 1063 x 1000 0 00 -160 60 0 M L r- o - CO) LO t- 0 - C L co~t I. I~ co CD CD 0) 0 180 - ~~Fuel consumption trends, Nepal. n 160 - - Gasoline (MS) 2 140 - Diesel (HSD) (all use) 0 120 - -Kerosene (SKO) c 180 0. . Fuel oil (FO) 2 60 - 4 Fuel wood, Kathmandu Valley 4 40- ID CO O O 0- C%J CO co D I C+J CO I C O 0 0 0 0 0 0 o co 0) 0) 0 0 Growth trends, Kathmandu valley. - vehicles - brich kilns (Bull's trench) Bull's trench kdilns: + 200% Cars, jeeps: + 64%1/ 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 (> 8000m). 120 - 100 *80 U 60- m 40- - 20 - - _ o It -r L 0 I) rv L - cO s fs 0 s s 0 a C 0 0 0 10 Background Information 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 1 15 days in early 1 970s to only about 20 days in 1992/93. POPULATION Available population data for 1971, 1981 Table 1.1: Populaton data (tkousands), Kathmandu Valley and 1991 are shown Kathmandu district Lalitpur district Bhaktapur district Total Population in Table 1.1 (JICA, 1971 354 122 110 586 1992). In the Valley 1981 427 165 144 736 as a whole, the 1991 668 222 736 1,063 growth rate has been (62°!0 uran) (53/ u..an) (35%n u.M an) (56% urban) Growth rate % 3.7 percent per 1971-81 1.9 3.1 2.7 2.3 annum. 1981-91 4.6 3.0 1.8 3,7 Source: JICA (1992). 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. 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 g/l in 83-octane gasoline, and 0.80 g/l in 93-octane gasoline. The actual contents of sulfur and lead are not known, and may be considerably less than Table 1.2: Liquid fuel consumption (I03 klyr), Nepal Gasoline Motor diesel Kerosene Light diesel oil Aviation fuel Fuel oil LPG Years MS HSD SKO LDO FO 1975/76 10.5 30.8 32.2 9.4 11.2 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 ? Change (%) 1980-93 +146 +174 +247 --100 +67.3 +576 ,, Source: Gautam (1994). URBAIR-Kathhmandu 11 the maximum allowed. Fuelwood consumption data for Kathmandu Valley is Table 1.3: Fuelwood given in Table 1.3. Because of diminishing resources, consumption, Kathmandu Valley fuelwood consumption has declined by close to a factor of Year 103 tVyr Year 103 Uyr 2 between 1983 and 1990. Increased use of kerosene and 1983184 35.9 198711888 21.2 agricultural waste has replaced fuelwood as the major 1984/85 40.0 1988/1989 23.7 domestic fuel. 1985/86 23.7 1989/1990 20.0 Coal has replaced fuelwood in the brick industry. In 1986/87 29.0 the early 1980s, fuelwood and coal were almost equally Source: Devkota (1992). used in the local brick industry, now the ratio between coal and fuelwood consumption is about 7 to 1 (NESS, 1995). Brick and cement industries use mainly coal. Table 1.4 shows the available data on coal consumption. In the Hoffman kilns, coal Table 1.4: Coal consumption in the brick consumption is somewhat lower than it was in and cement industries, Kathmandu Valley 1970. In the Himal Cement Factory, coal (tonslyr) consumption has increased dramatically from Bull's Chinese* Himal 1990/91 to 1992/93. The dominant coal trench* (Hoffman) Cement** Total# consumer in the Valley is the Bull's trench kiln kilns kilns factory industry. Shrestha and Malla's estimate for 1970/71 3,300 1992/93 appears to underestimate 1975176 2,950 1980/81 1,690 6,400 consumption. Although data for past coal 1985/86 2,200 5,860 consumption in the Bull's trench kilns are not 1990/91 2,440 7,980 available, coal consumption has most likely 1992/93 21,000 4,100 17,100 47,000 increased substantially, especially since it has 1993 43,800 almost completely replaced fuelwood. 1994 54,800 Sources: * NESS, 1995 -* Devkota, 1992 # Shrestha and Malla, 1993 INDUSTRIAL DEVELOPMENT Industrial growth has been very strong in Kathmandu Valley, especially in the last decade. In 1991/92, 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. 12 Background Information ROAD VEHICLE 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 trucks/buses. 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. 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 and Shrestha, 1993), the KVVECP study (Devkota, 1993), by the Hydrological and Meteorological Services (HMS) (Shrestha, 1994), and by NESS (1994). * ENPHO study measured TSP, PM1o, SO2, NO,, CO and Pb in November 1992 and February 1993, at 20 sites. * KVVECP study measured TSP, PMIO, SO2, NO2 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. 13 14 Air Quality Assessment Table 2.1: Ambient air quality monitoring stations in the KVVECP study Category Locations Distance from main Height of the road (m) station (m) 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) Ratnapark, 4 3 Lainchaur, 2 2.5 Kalimati 3 3 iii. Low traffic (<7,000 ADT) Thimi (NTC) 2 2.5 ........................................... )................................................................................ .................! 2. Residential Areas Maharajgunj (TUTH), 30 3 Naya Baneswor, 20 7 Jaya Bageshwori 15 8 i adusta eas Balaju, 15 4 Bhaktapur, 50 3 Patan Industrialized districts, 5 5 Himal Cement Factory surrounding 100 10 ................................................................. 6 ....... ................................................................................................................................................... 4 Regional background/control site Tribhuvan University Kirtipur 50 3 Note: ADT -- average daily traffic. Source: Mathur (1993). * HMS measured TSP at the HMS Building, Babar Mahal, from January-August 1993, for 1 0- 31 days of measurement each month. D NESS (Pvt) Ltd measured PMIO 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 SO2 and NO2, 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. Table 2.2: Applicable WHO AQGfor TSP, Concentrations in Kathmandu PM, , and SO2 in Kathmandu TSP PM,o S02 The following WHO AQG for TSP, PM10, (,ug/m3) (I.gIm3) (pglm3) and SO2 are used in Nepal (Table 2.2). Long-term (annual average): 60-90 - - Short-term (24-hour average): 150-230 70 100-150 Note: * = Annual average mean of minimum 104 (24 hourly) TSP concentrations. TSP concentrations measurements in a year. measured by ENPHO, KVVECP, and HMS ** = Should be met 98 percent of the time in a year. show that the WHO AQG for daily averages Should not be exceeded on two consecutive days. (150-230 ,ug/m3) are substantially exceeded Source: National Ambient Air Quality Standards for lndustrial both in heavily traveled and residential areas. and Mixed Use Areas, see S.O. 384(E) under APCA, 1981. URBAIR-Kathmandu 15 In addition, the guideline for the annual average (60-90 FLg/m3) is also exceeded. Results of TSP measurements, both average and maximum, are shown in Figures 2.1 and 2.2 (average and maximum concentrations). Figure 2.1: Summary of TSP measurements, Babar Mahal Building 500 50 E- 450 =TSP (max) ' 400 _M_M_TSP (mid) 40 ', cn 350 _ No of rainy 300 30- *E 250 200 -, 20 0 0 .tiA 1 0 .:0 jan feb mar apr may jun jul aug Source: Shrestha (1995). The maximum 24-hour concentrations of TSP measured, 467 ,ug/m3 at the Babar Mahal building, and 319-876 ,Ig/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 pg/m3 * Residential sites: 273-350 ,ug/m3 - Industrial sites: 102-290 ,g/m3 * Near Himal Cement Factory: 560 ,ug/m3 * Tribhuvan University (reg. background): 155 pg/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 gg/m3 and an average of 308 [tg/m3 at 9 sites representing Central Kathmandu City air. At the 11 roadside sites, the measurements showed TSP maximum of 2,258 ,ug/m3 and average of 1,397 zjg/m3. These values are based on a 9-hour average and only one sample was taken at each site. The 2,258 gg/m3 maximum in the ENPHO measurements represents an estimated 24-hour average value of about 1,100 jig/m3. HMS measurements indicate an annual average concentration around 180 gg/m3 at Babar Mahal, 15 meters above ground level. 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 jIg/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. 16 Air Quality Assessment Figure 2.2: Results of TSP measurements, KVVECP study September-December, 1993 (Relatively short measurement periods at each site) TSP . .... [~~~~~~~~j~[1 l \ t 87 \ ~ ~~~~~~ 87 Average value _ ,f > Cr > 9 102 \ _~~~~~~~~~F 102 Max. value_ , 430 , /A \ \ ~~~~~~~~Measurement sites, KVVECP \ 560 t5// \ *~~~~~~~~~~~~ Commercial (traffic) sites V Industrial sites X* Residential sites o Regional background sites Source: Devkota (1993). These measurements point to a severe TSP pollution problem in the Kathmandu Valley, and in Kathmandu City in particular. PM1O concentrations. PMIo has been measured by ENPHO, KVVECP, and NESS. The results of the KVVECP measurements are shown in Figure 2.3. PM1O concentrations were above the recommended WHO AQG (70 p,g/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 PMjo URBAIR-Kathmandu 17 Figure 2.3: Results of PM,O measurements, KVVECP study September-December, 1993 (Relatively short measurement periodis at each site) PM10 I.... .2 1326 l \ X al \ <~~~~~~-4 Average valuje _ f 0 t/> \ > \ | ~~~~~~~~~~~53 |Max. value_ . l/l \ \ ~~~~~~~~~~~Measurement sites, KVVECP < 166 .t // \ *~~~~~~~~~~~~ Commercial (traffic) sites v Industria! sites * Residential sites o Regional background sites -T Source: Devkota (1993). levels, Ratnapark traffic site and at Tribhuvan University. At the University site, PM,( 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. The highest PM1O concentrations were 201 t.g/m3 in November at the General Post Office, which is the site of heavy traffic and 194 gg/m3 at the Himal Cement Plant site in December. About 50 percent of all the measurements in the KVVECP study were above the recommended guideline. 18 Air Quality Assessment The ENPHO measurements of PM1o in Kathmandu City gave an average concentration of 89 g.g/m3, and a maximum concentration of 127 gg/m3 at the general sites. The roadside sites were higher with an average concentration of 296 gg/m3, and a maximum of 498 gg/m3 (9-hour average values). ENHPO results support the results of the KVVECP study. PM1O measurements taken by NESS, representing one 1-hour average samples during daytime at 9 sites, gave values up to 2,100 [ig/m3 with an average of 800 jLg/m3. These are much higher than both ENHPO and KVVECP measurements. Reasons for the apparent discrepancies between these results and those from the ENPHO and KVVECP studies may be found when comparing the different samplers and laboratories used. The ratios between measured PM1o and TSP are given in Table 2.3. The ratio 0.70 is in the range typically found at sites that are not exposed Table 2.3: Ratios between PM10 and TSP, to a high degree of resuspension. The low PM1o from KVVECP and ENPHO ratio for the sites (0.4-0.5) indicates that the measurenents resuspension pollution is high. In the case of the Based on Himal Cement site, the size distribution of cement Average Max. factory emissions dominates the low ratio found concentration concentration there. KWECP Traffic sites 0.39 0.34 SO2 concentrations. Results from the KVVECP Residential sites 0.48 0.48 measurements in Figure 2.4 indicate that S02 Himal Cement site 0.39 0.35 concentrations from September-December 1993 Tnbhuvan Univ. 0.70 0.52 were low. Kalimati (traffic site) and Jaya (Background site) Bageshwori (residential) are the exception. At ENPHO these sites S02 concentrations were above the Traffic sites 0.21 0.18-0.25 guideline (100-150 gg/m3) on several days, and General sites 0.29 0.23 the maximum concentration was 225 jig/m3. KVVECP measurements indicate that although SO2 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. NO2 concentrations. KVVECP measurements shown in Figure 2.5 indicate that NO2 concentrations were generally low, and well below the 24-hour WHO AQG (150 ,g/m3). The Jaya Bageshwori site had elevated NO2 and SO2 concentrations, pointing to a local source. URBAIR-Kathmandu 19 Figure 2.4: Results of SO2 measurements, KVVECP study September-December, 1993 (Relatively short measurement periods at each site) _ ~ ~I I I _l I _ I I I I I 1 , so52 Sour vta ( . Averagevalue _ r > tX \ 1 ~~~~~~~~~~~~~53 1 Max. value_ . 57 ', 1/1 I \ \ ~~~~~~~Measurement sites, KVVECP '.,, 6 .+f/ Commercial (traffc) sites _ _ /z/ I \ ~~~~~~~~~~~~~~~~v Industrial sites_ n \t / > +~~~~~~~~~~~~~4 Residential sites 5 (S) / \ ~~~~~~~~~~~o Regional background sites Source: Devkota (1993). 20 Air Quality Assessment Figure 2.5: Results of NO2 measurements, KVVECP study September-December, 1993 (Relatively short measurementperiods at each site) N02 $~~~~~~~~~~~ ~~~~~~~~~~ )2ndustrial sites M Reasdentl sites, KVV e Regional background sites - "I I I ' I I' I I I I _ Source: Devkota (1993). Visibility2. 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 2 Madan L. Shrestha (1994) analysis of visibility data from the Kathmandu Airport for 1963-1993 is summarized in Appendix 1. URBAIR-Kathmandu 21 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. Figure 2.6: Number of days in Kathmandu Valley with fair-to-good visibility (>8, 000 m) in the winter months 40- October 40- January 30-30 a 20- 20 - 0 O 70 75 80 85 90 Year 70 75 80 85 9.0Year 40- 4November 40 Fruary C>20 - - 20 v 70 75 80 85 90 Year 70 75 80 85 90 Year 40~ -December 40- March Q20- 20- 70 75 80 85 90 Year 70 75 80 85 90 Year Source: Shrestha (1995). The nature of the "lifting" of the morning fog is Figure 2.7: Number offoggy days at 9 am., Kathmandu Valley, 1969- visualized in 9 Figure 2.8. In the 80- relatively unpolluted _ air of the early 60- 1970s this normally _/ took place before 10 40- a.m. Fog dispersal is _ now typically 20- delayed for 3 hours, _ andonhazy days, o l l l l l l l l l l l l l good visibility only 70 75 80 85 90 Year occurs after 1:00 Source: Shrestha (1995). 22 Air Quality Assessment p.m. or 2:00 p.m. On some days the Figure 2.8: Number of days in January with good visibility (>8,000 m) haze never lifts. at given hours of the day, Kathmandu Valley Visibility 30 - reduction is mainly Januarye caused by particles (aerosol) of the 20 size range , 1992 - 3 comparable to the wavelength of light, e.g. 0.2- 10- 0.5 ,um diameter. These are combustion o aerosols from 6 8 10 12 14 16 18 sources such as Local time cars (diesel and Source: Shrestha (1995). gasoline), coal, fuelwood, and agricultural residue combustion. This aerosol contains hygroscopic particles, such as particles containing sulfate (SO4), condensed organic compounds, etc. Thus, the morning 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. URBAIR-Kathmandu 23 AIR POLLUTANT EMISSIONS IN KATHMANDU VALLEY To/al emissions. An emissions inventory covering all source Table 2.4: Total annual emissions in Kathmandu Valley, categories has been compiled for 1993 (tons/yr) the Kathmandu Valley. It TSP PM10 SO2 contains emission data for TSP, Transport sector PM1o and SO2. Details of the Vehicles exhaust emissions inventory Gasoline Cars/taxis 38.4 - development are described in TMC 107.5 - 4.2-105a Appendix 4. Calculated and Diese Jeeps 684 - estimated total emissions are Minibuses 22.5 - presented in Table 2.4. They are Buses 45.0 - 78-390a based on the emission factor Trucks 114 - data in Table 2.5, and the fuel Tractors 21.6 - consumption and traffic activity TC 85.8 - consumption T ande traffc6activity Sum vehicle exhaust 570 570 82-495a data in Table 2.6. Sum Resuspension from roads 1,530 -400 0 The inventory covers main Eniergiy/industry sector .......... source categories. The emissions Fuel combustion from road vehicles are relatively Industral/commercial (excl. brck/cement) reliable and are based on fuel tuelwood 61.9 31 consumption, traffic activity and Coal 48.0 24 172 emission factors. Emissions Charcoal 20.0 10 from industrial and commercial HSD 1.8 2 LDO/FO? activities, other than brick Kerosene/LPG 0.1 combustion, are based on figures Agr. residue 450.0 225 and emission factors provided Sum industriallcommercial 582.0 292 by Shrestha and Malla (1993). Domestic Fuelwood 1,832.0 916 Emissions from Bull's trench Agri. residue 454.0 227 Anim. waste 30.0 15 brick kilns havebeen estimated .Kerosene/LPG 2.3 2.3 by NESS (1995). Chinese kiln Charcoal 10.0 5 emissions are based on coal Sum domestic 2,328.0 1,165 consumption and on estimated Industrialprocesses emission factors. Himal Cement Brick industiy factory has provided numbers on Bull's Trench 5,000 1,250 4.84465b emi n fm tChinese 180 45 emissions from the factory Sum brick 5,180 1,295 (Bhattarai, 1993). Himal Cement Sum Stack -2,000 -400 615 Sum Diffuse dust -4,000 -400 Other Sum Refuse burning 385 190 Sum Construction - - Total 16,565 4,712 a) High value: Based on max. allowable S content. Low value: Based on actual S content, according to IOC Ltd. certificate. b) NESS (1995): Estimates based on different methodologies. 24 Air Quality Assessment Table 2.5: Enission factors used for URBAIR study, Kathmandu Valley TSP PMiod TSP S02 NOx %S max. Fuel combustion (kg/t) Residual oil (FO) ind./comm. 1.25S+0.38 0.85 20-Sa) 7 4 Distillate oil (ind./comm.) 0.28 0.5 20-S 2.84 HSD: Id) (HSD, LDO) (residential) 0.36 -- 1.6b) 0.5 20-S 2.6 LDO: 1.80) LPG (ind./dom.) 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-S 11.3 . f (ind./dom) 0.061 20-S 2.5 Wood (dom.) 15 0.5 0.2-A 1.4 Fuelwood (ind.) 3.6 0.5 Coal (dom./comm.) 10 0.5 Charcoal dom./comm. 20 0.5 Agri. residue 10 0.5 Anim. waste 10 0.5 Refuse buming, open 37 0.1 0.5-A 3 Road vehicles (gilkm) (A) (B) Gasoline (Cars) 0.2 1 2.7 83 Octane (RON) 0.250) (MC/TC) 0.5 1 0.07 93 Octane (RON) 0.20 Diesel (Cars, jeeps, tractors) 0.6 0.9 1 1.4 1d) (Minibuses, tempos) 0.9 1.5 1 13 (Buses, trucks) 2.0 3.0 13 a) A: Ash content, in %; S: sulfur content, in %. b) Well -+ poory maintained fumaces. c) Actual S content in 87 RON gasoline, according to IOC Ltd quality certificate: 0.009%. d) Actual S content, according to IOC Ltd quality certificate: 0.20%. e) Actual S content, according to IOC Ltd quality certificate: <1%. (A) Used for Manila, Jakarta, Bombay. (B) Proposed and used for Kathmandu Valley. URBAIR-Kathmandu 25 Table 2.6: Fuel consumption and traffic activity data for Kathmandu Valley Emission sourcel fuel type Category Fuel consumption Traffic activity 106 veh. km/yr Vehicles kl/yr Cars Gasoline 28.015 192 Tempos (TC) 4 135 Motorcycles (MC) 215 542 subtotal Jeeps Diesel 22.955 76 Minibuses/buses 30 Trucks 15 Tractors 38 Tempos 24 183 subtotal 725 total Industry 103 tonslyr Himal Cement Bull's trench kilns Coallfuelwoodtrce husk 42V5.7/15.8 Chinese kilns Coal 20 Other industry/commercial HSD/LDO ?/M Coal/charcoal 4.8/1.0 Woodlagncultural 17.2/45 residue SKOALPG 1.0/? Domestic Wood/charcoal 122/0.5 Agnc. res./anim. waste 45.4/3.0 SKO/LPG 35/4 Refuse buming Refuse 10 For resuspension from roads, a TSP emission factor of 2 g/km 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 g/kg (Economopoulos, 1993; Semb, 1985). The source contributions in Table 2.7 are derived Table 2.7: Source Contributions from estimated emissions given in Table 2.4. of TSP and PM,0 The contributions to population exposure may differ Contribution % substantially from the contributions to total emissions. Source category TSP PMIp This difference depends on the height of the emissions Road vehicles (ground level or high stack), the distance from the source gasoline 1.3 4.5 to populated areas, and the dominating wind directions diesel 2.2 7.6 Resuspension from roads 9.3 8.5 Domestic fuel combustion 14.1 24.7 TSP. It is estimated that the total emissions are Brick industry 31.3 27.5 approximately 16,500 tons/year. The brick industry, Himal Cement 36.2 17.0 domestic fuel combustion, and resuspension from roads Other industry/commercial 3.5 6.2 are estimated to be the dominant sources for the Valley as Refuse buming 3.2 4.0 a whole. Emissions from construction activities have not been estimated. 26 Air Quality Assessment PM10. Total estimated emissions are some 4,700 tons/year. For PMIo, 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. Figure 2.9: Spatial enmssions distribution in Kathmandu Valley, 1993 (Total emissions-kg/h, averaged over the 6 winter months-per kmi, represented as isolines) _ I I I l IiI I I I I I I I I I I I I I I_ L ' ':~c '0: 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. URBAIR-Kathmandu 27 DISPERSION MODEL CALCULATIONS General description of topography 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 180 C. The coldest month is January with a mean temperature of 100 C. The warmest months are July and August, with an average temperature of 240 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. 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 28 Air Quality Assessment 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 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 matrixfor the winter months (Jan-March, Oct-Dec) 1993, Tribhuvan Airport .8 mIs 1.8 m/s 3.3 mls 6.3 mls_i 1 2 3 4 1 2 3 4 1 2 3 4 1 2 30 3.6 1 1.0 .6 1 .0 .1 .1 0 .0 .0 .0 0 0 60 .5 1 1.0 .5 .1 .0 .2 .1 .0 .1 .0 .0 .0 .0 90 1.6 .3 2.8 1.6 .1 .0 .2 .1 0 .1 .1 .0 .0 .1 120 8 .3 2.6 16 .0 0 .3 2 0 .0 0 .0 * 0 150 j 1.9 .6 6.3 3.8 *.2 .1 .6 .4 0 .2 .1 .0 0 .0 180 1.6 5 5.4 3.2 .3 .1 1.0 .6 .1 .8 .3 .1 .0 .3 ........ ..................................... ......... ......i............ .......... ........................................... ................ 210 4.7 1.0 3.1 16 9 .2 .6 .3 4 1.4 .2 .2 0 6 240 . 3.5 .8 2.3 1.1 9 .2 .6 .3 .5 1.6 .3 .3 .0 .3 270 .1.8 .4 3.2 1.8 5 .1 .8 .5 ..4 1.4 .6 .4 ..0 .8 00 ' i i i3 7 '.1 1. 3 .2 .6 .2 .2 . 330 j.8 .2 1.5 .8 i2 .0 .3 .2 j.1 .2 .1 .1 ..0 .1 360 ..7 .1 1.1 .5 .1 .0 .1 .1 .0 .0 .0 .0 .0 .1 Stability: 1 2 3 4 Windproof. .20 .28 .36 .42 exponent: Mixing height: 1,200.0 1,000 400.0 200.0 Stability classes Velocity classes (mis) I: Unstable 0.3-1.5 (0.8 m/s average) N: Neutral 1.5-2.0 (1.8 m/s average) SS: Weakly stable 2.5-4 (3.3 n/s average) S: Stable >4 (6.3 m/s average) The frequencies of calm are distributed in the direction sectors within each of the stability classes of the 0.3-1.5 m/s velocity class, proportional to the joint occurrence of wind and stability. URBAIR-Kathmandu 29 Figure 2.10: Wind roses for 1971-75 and 1993, Tribhuvan Airport 1971-75 1993 * _ I February A4 ft~ ~ ~ .,,.,_ ~~91. ~ 10 + ~~~~~~August _ , + _ ~~~~November _ %/ calm Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1971/75 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 Source: Shrestha (1995). 30 Air Quality Assessment Dispersion model calculations, city background Model description. In the first phase of URBAR, 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 2.1 la, b and c. A regional background value of 10 lug/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: Table 2.9: TSP contributions (,ug/m3, winter average) calculatedfor 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 31 Figure 2. Ha: TSP concentrations in Kathmandu Valley * 1 1 1 § I I I I I I I I I I _~ /TSP, total distribution Note: Calculated winter average concentrations (km2 averages), 1993. Total distribution and contributions from various source categories. 32 Air Quality Assessment Figure 2.1lb: TSP concentrations in Kathmandu Valley Car exhaust -~~~~~~ Road resuspension so 10~~~~~~~~~~~~~~~ 0 - ~ ~ ~ I TI X,,,,~~( - ' ' ' ' | | I ,,,,,,,, _~I f g W SG URBAIR-Kathmandu 33 Figure 2. 1Ic: TSP concentrations in Kathmandu Valley Bull's trench brick I I I I I I I I I I I I I I I Chinese brick i r * r w -r-rE* , , . . . . . . . . . . . . . . . . . Himal Cernent, diffuse dust \Himal Cernent, Stack f~~~~~~ ~~~~~~~~~~~~~~ -- . * S so ~ ~ ~ ~ ~ .*S- 34 Air Quality Assessment * due to road traffic (vehicle exhaust and resuspension) and domestic fuel combustion in Kathmandu City; * in the brick kiln areas, especially southeast of Patan, and * near Himal Cement factory. The Himal 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 ,ug/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 gg/m3, * Measured average, Jan-March, 1993: 255 [ig/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- 30 meters from roads), give much higher concentrations than those calculated as km 2 grid square averages. PM1O. Calculated PMIo distributions, and the source contributions, are shown in Figures 2.12a,b and c. The PM1o 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 PM1O measurements from the KVVECP sites close to roads show considerably higher concentrations than those calculated. Calculated PMIo contributions in selected grids are given in Table 2.10. Table 2.10: PM1O contributions (,U/M3, winter average), calculatedfor 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 fromroads 15 1 15 (11,14) Domestic fuel combustion 18 8 21 (13,16) Bull'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 35 Figure 2.12a: PM1O concentrations in Kathmandu Valley SO _ I I I . I 1. 1 1 1 1 1 1 1 I I I I I | I I , I V tA+ 100 pg/m3 No. of people (x 1000) + 97 + 90 - Change in total emissions from + 60 - + se ~~~~~~~~~~~~~~~~each source + 39 F + 30 -+23 + 25 II ~~~~~~+14 +2 -7- L . - 30 -24 - 40 -25% - 60 -90 TSP, exceedance of winter average > 175 pg/rn3 + 120- +117 + 94 + 90 +64 +7 + 60 + 25% + 30 -+19 + 9 -60_ -4 56 1 5 5 go - _ -73_ - _ _ _ _ _ _ _ _ 5 -1i20 -119 Source: Car Road Dom. Bull's Hoihan Himal exhaust resusp comb. brick brick Cemfent URBAIR-Kathmandu 43 Figure 2.15: Change in population exposure to PMIO as a result of ±25 percent change in the total emissions from each source category PM10, exceedance of winter average > 60 pg/M3 No. of people (x low) +90- Change in total emissions from + 60 - + 45 each source + 30 +19 16+18 +2 476-' E 3 -90 PMIn, exceedance of winter average > 100 upg/m3 + 124 + 120 13 +115 + 90- + 66 + 60 -l 47 113H +25% 68 -- __ _ _ _ - 30 I-12 -13 2% - 60 - 9 -9 -39 -59 Source: Car Road Dom. Bull's Hoffman Himal Himal exhaust resuap comb. brick brick stack diffuse 44 Air Quality Assessment Air pollutant 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 been worked out. In terms of total emissions in 1993, the main sources are given in Table 2.12. Diesel vehicles contributed about 60 Table 2.12: Main emissions sources in Kathmandu percent of the particles and gasoline (1993) vehicles about 40 percent. The actual TSP PM10 impact of these emissions on human Himal Cement 36% Brck industry 28% health depends on the emission Brck industty 31% Domestic fuel 25% conditions such as the height of Domestic fuel combustion 14% Himal Cement 17% emissions, and their position relative to Road resuspension 9% Vehicle exhaust 12% population centers. There are significant Vehicle exhaust 3.5% Road resuspension 9% 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. Population exposure to air pollutants A first approximation of the population exposure is based on the emissions inventory, a multisource Table 2.13: Average winter Gaussian dispersion model for long-term averages, concentrations in Kathmandu Cit and meteorological statistics from Tribhuvan TSP pglm3 PM10 pglm3 Airport. The calculated contributions to the winter Vehicle exhaust 22 22 average concentrations in Kathmandu City are Road resuspension 57 15 given in Table 2.13. Domestic fuel combustion 35 18 The calculated winter average TSP Bull's trench kilns 47 12 concentrations underestimate the actual Background 171 10 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 ,ug/m3), and * approximately 3 to 4 percent is exposed to concentrations that are more than twice this level (180 ,ug/m3 ), which include residents in the brick kiln areas, drivers and roadside residents. 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 URBAIR-Kathmandu 45 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 IMPROVING AIR QUALITY ASSESSMENT 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 Ist priority-TSP, PM1O, submicron particles, black smoke, chemical composition, CO. 2nd priority- SO2, NO2, PA, 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. D Measurement methods-continuous monitors for PM10, 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. 46 Air Quality Assessment A list of proposed actions to improve the air quality assessment in Kathmandu are given in Table 2.14 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: Finalize 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 PMlo - Establish of 1 to 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 Informaton System, including * database; and * information to control agencies; lawmakers; and * public. .... y t .............................................................................................................................................................................................................................. 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 condibions. Develop an integrated and comprehensive emissions inventory procedure, include emission factor review, update and quality assessment procedures. Improve methods and capacity for emission measurements. ......................................................................................................................................................................................................................................... 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 INTRODUCTION This chapter presents an overview of the major Figure 3.1: Frequency distribution of PM1o exposure (annual impacts of air pollution in average), Kathmandu Valley, situation 1992/1993 Kathmandu Valley and estimates of the monetary so,oo value of these damages. WHO standard PM1O Concern about air pollution 40,00 focuses on the high concentrations of suspended . particles, especially PMIO, Oa30,00 - which regularly exceed the WHO AQG (See Chapter 2). Figure 3.1 summarizes the information presented in Chapter 2 in a frequency 10,00 distribution of population exposure to PMIo. The WHO AQG for PM10 000 8 22 38 52 68 82 98 112 128 (41 gg/m3) is derived by microgramlm3 (PM10) multiplying the WHO AQG for TSP (70 pig/m3) with a factor 0.55 which expresses the typical fraction of PM10 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 equations 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. 47 48 Air Pollution Impacts IMPORTANT IMPACTS IN KATHMANDU VALLEY Health. Although U.S. research relates to TSP concentrations, in this study it has been adapted and applied to PM1O, since these particles are considered a more serious threat to health in Kathmandu Valley. The conversion from TSP to PM1O was done as follows: * PM1O concentrations are calculated from dispersion models using actual PM1O emissions, and measurements of PMIo as control. * TSP dose-response relationship is converted to PM1O, using a ratio of 0.55 between PM1o and TSP concentrations. * WHO AQG, which is used as a "no-damage benchmark," is converted from TSP to PMIo, using the same ratio, 0.55. Tourism. An October 1993 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$6 million for Nepal. This is a very significant amount of foreign exchange for a country that has a negative balance of trade. Moreover, indirect effects may have the same impact. This leads us to a tentative estimate of US$ 10 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. 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 PM1O. The following relation between air quality and mortality is used: Excess death = 0.00112 x ([PM,0] - 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, 1995); PM,O is its annual average concentration (AgIm3). A PM1o 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 URBAIR-Kathmandu 49 can be concluded that excess mortality due to PM1o was about 853 cases, in a population of approximately I million. Illness (morbidity) Particles. The following health impacts can be attributed to particles: chronic bronchitis, restricted activity days (RAD), respiratory hospital diseases (RHD), emergency room visits (ERV), bronchitis, asthma attacks, and respiratory symptoms days (RSD). The following dose-effect relationships are used: * Chronic Bronchitis-Chane in yearly cases of chronic bronchitis per 100,000 persons is estimated at 6.12 per mg/m PM1o. The total number of yearly cases of chronic bronchitis per 100,000 persons is 6.12 x ([PM10] - 41). * RAD-Change in restricted activity days per person per year per mg/m3 PM10 is estimated at 0.0575. If we use the WHO standard, the change is 0.0575 x ([PM10] - 41). * RHD-The change in respiratory hospital diseases per 100,000 persons is estimated at 1.2 per mg/m3 PMIo. Using the WHO standard, the respiratory diseases requiring hospital treatment per 100,000 persons are estimated at 1.2 x ([PM10] - 41). * ERV-The change in the number of emergency room visits per 100,000 persons is estimated at 23.54 per mg/m3 PM1o, and the total number per 100,000 persons at 23.54 x ([PM10] - 41). * Bronchitis-Change in the annual risk of bronchitis in children below 18 years is estimated at 0.00169 x ([PM10] - 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 ([PM1 o] - 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 ([PM10] - 41). Table 3.1 combines dose-response relationships with the frequency distribution of PM1o 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. 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 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 3 Results of calculations are detailed for reasons of consistency and not accuracy. 50 Air Pollution Impacts Table 3.1: Impact on mortality and health and their valuaton (NRs) of health impact in Kathmandu Valley Value (NRs) Type of health impact Number of cases Specific Total (103) Excess mortality 84 340,000 28,644 Chronic bronchitis 506 83,000- 41,988 Restrcted 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 Note: * Estimate is approx. NRsI46,000, but this is not based on a discounted sum over 27 years. Discounting at a 5% rate leads to an estimate of Nrs83,000. Source: Shrestha (1995). 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 930/21,900 = 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=E w/(l+d)t .1=0 where, w equals average annual income (Shin et al., 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 PM10 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. 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 is impossible to identify the relative contributions of all the source categories; however, we do URBAIR-Kathmandu 51 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). Table 3.2: Marginal impacts from different sources Source Emissions Change in Change in Change in Change in health Marginal (ton) Emissions (lo) Mortality RSD (1,000) damage costs/benefits (NRs thousand) (NRslkg) Traffic (exhaust) 440 25 20 354 48,952 10 10 180 25,351 576 -10 -6 -108 -15,037 341 -25 -9 -160 -22,118 ........................................................................................................................................................................... ............................................................... Resuspension 400 25 12 219 30,273 10 9 165 22,842 571 -10 -2 -35 -4,903 122 -25 -7 -125 -17,382 .............................................................. ........................ ~ 6............................... ............................................................ Domestic 1160 25 23 407 56,238 10 13 227 31,367 270 -10 -9 -155 -21,360 185 -25 -13 -239 -33,056 Bick (Bull's trench kilns) 1250 25 25 443 61,199 10 13 229 31,688 253 -10 -3 -57 -7,832 62 -25 -15 -274 -37,921 ........................................................................ ....................... 6 .............................................................................................................. Hoffman brick kilns 45 25 0 -3 446 -25 0 -6 -765 Note:These calculations are based on an earlier 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" (NRs 185 per reduced kg of PM1o 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.. 52 Air Pollution Impacts 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 N-Rs340,000. The total excess mortality is then valued at NRs28..3 million. The willingness-to-pay approach yields a "damage value" of NRs540 million. Health impacts are assessed using dose-response relations derived in the United States, and the air quality model developed for Kathmandu Valley (Chapter 2). 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 PM10 were assessed specifically for Kathmandu Valley. Morbidity costs are valued at about NRs 180 million, and total health damage at NRs210 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 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: - e;ffectiveness 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 PM0o), and number of RSD 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, 2-5 years; long term, more than 5 years). All emission figures, costs, and benefits represent annual estimates for 1992/1993, 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. 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, 53 54 Abatement Measures: Effectiveness and Costs - improving diesel fuel quality, - introducing unleaded gasoline, - improving the quality of lubricating oil in two-stroke engines; and adoption of clean vehicle emissions standards. Implementation of a scheme for inspection & maintenance Effectiveness. Maladjustment of fuel Table 4.1: Recommended steps in an inspection & maintenance injection or scheme carburetors and worn- Diesel engine Gasoline engine out parts not only Airfilter Air filter pose a hazard to Fuel filter, tappet settings Fuel filter, tappet settings traffic safety and Injector Nozzle pressure Ignition system (Spark plugs, Contact points, distributor etc.) increase fuel Injector pump calibration Carburetor Engine compression check up Engine compression check up consumption, they Engine overhaul Engine overhaul also cause large Source: Tuladhar (1993). emissions. A scheme requiring annual inspection and maintenance (I&M) would result in a reduction in the emissions of PMIo, VOC (unburned hydrocarbons/HC), and CO. See summary in Table 4.1. 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 assumption that the proposed, comprehensive, inspection and maintenance scheme would reduce emissions of PM,0, VOC, and CO by a 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 government agencies can be compensated if testing is done by private firms.4 The cost of a single test is estimated to be NRs 100. This estimate is based on proposals (tests, including, 4 A set-up of such scheme might be: - firms are licensed to carry 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. URBAIR-Kathmandu 55 roadworthiness) which have been made for Indonesia (Budirahardjo, 1994), and Manila (Baker et al, 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 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. Improvingfuel quality This measure has four components. They include addressing adulteration of gasoline, introducing low-lead and unleaded gasoline, "clean" diesel, and improving the quality of lubricating oil in two-stroke engines. 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. 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. 56 Abatement Measures: Effectiveness and Costs 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, 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 of MTBE (Turner et al, 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. Imnproving diesel quality Diesel's ignition and combustion properties explain PM1O emission from diesel engines (Hutcheson and van Paassen, 1990, Tharby et al, 1992). Volatility (boiling range) and viscosity (including its cetane number, an indicator of the ignition properties) of fuel determine ignition and combustion and, consequently, PM10 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). Effectiveness. Improving the quality of fuel by increasing the cetane number5 and adding detergents, results in a decrease of 10 percent in PM,0 emission, about 25 tons as an order of magnitude (AIAM, 1994, Mehta et al, 1993). A reduction in the sulfur content leads to a proportional fall in emission of SO2. In addition, PM1o 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, refinery structure (capacity for producing light fuels, visbreaking, hydrotreating etc.), and the government's role in the national market. The government sets the price-at-the-pump for fuels. 5 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 straightforward; the characteristics of the diesel motor, its load and its injection timing plan are parameters that complicate the picture. URBAIR-Kathmandu 57 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 of NRsO.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 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 refineries (such as extension of visbreaking capacity) is about 3 to 5 years. Initroduction of low-smoke lubricating oilfor 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 PM10 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. E.ffectiveness. It is assumed that using better quality lubrication oil could halve emissions (50 tons reduction). A 50 ton emissions reduction corresponds to NRs15 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 estimate the annual consumption of these oils at 250 kg.6 The total cost of low-smoke oil would be NRs 12,500. 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. Adoption of clean 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 6 Gasoline consumption is estimated at 28.3 x103 kl/yr. (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 58 Abatement Measures: Effectiveness and Costs motorcycle emissions, requiring two-stroke engine powered vehicles to be equipped with open- loop catalysts. The latter devices control emissions of VOCs (PM1o) and CO, not NOX.7 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 structure for producing and distributing unleaded gasoline.8 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.. Effectiveness. * Closed-loop catalytic treatment of exhaust gases (three-way catalysts) from gasoline engines typically reduces all exhaust emissions, including NO,, 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 PM1O (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). 7 Weaver, C.S. and Lit-Mian Chan, P.E. (1993) Motorycde emission standards and emission control technology. Draft repoit Repoit to the Wodd Bank and the Thai Government Sacramento, EF & EE.. K 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. URBAIR-Kathmandu 59 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). 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. Improved- abatement/other 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/wornout 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. 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. Improvement of 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 60 Abatement Measures: Effectiveness and Costs addresses the problem of congestion. Curbside management of traffic also may improve air quality9. 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. Construction and improvement of mass-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); a 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. 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. 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 9 Accelerating vehicles, a dominating feature of congested traffic, emit disproportionately large amounts of pollutants. URBAIR-Kathmandu 61 80 percent of the brick production, and for over 95 percent of the PMlo 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. 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. DOMESTIC EMISSIONS AND REFUSE BURNING 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 (Shrestha and Malla, 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. 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 62 Abatement Measures: Effectiveness and Costs 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 PM1o 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. Inprovement 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). ACTIONS TO IMPROVE AIR QUALITY AND ITS MANAGEMENT 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 URBAIR 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. 63 64 Action Plan 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, * Bull's Trench brick kilns. Vehicle exhaust is the most important source in terms of reducing health damage. Uncontrolled emissions from Himal Cement Factory are important determinants of visibility. Table 5.1 presents a list of technical measures, with an indication of the importance of Table 5.1: A list of technicalpollution abatement the measure to reduce pollution. measures, importantfor the reduction of the air pollution Introduction in the short, effects in Kathmandu Valley medium, and long term is Abatement measure Short- Medium- Long- indicated. Proposed measures are term tern term economically feasible in the Technical measures, vehicles indicated time frame. The I/M scheme, comprehensive xxx measures are not described in Improved motorcycle technology xx xx Clean vehicle standards xx xx great detail. The list does not Improved abatement/new propulsion techniques xx represent a ranking based on Fuel quality cost-benefit ratios. Control adulteration xxx The success of abatement Low-lead gasoline xx measures rests with the Unleaded gasoline xx enforcement of the action. It is Improved diesel quality xx xx Low-smoke lub. oil, 2-stroke engines xxx important to ensure that Road resuspension conditions are met for carrying Road cleaning, garbage collection xxx out the necessary technical Domestic emissions improvements/adjustments. This Improved cooking stoves x xx may mean ensuring sufficient Switch to kerosene x xx workshop capacity and capability Brick industWy for efficient adjustment of IImproved technology x xx foreffiien,th adjusabiitm of spare Note: xxx = most important; x =least important. 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" campaigns 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. Actions to improve the air quality management system Actions to refine air quality management include improving the following: URBAIR-Kathmandu 65 * 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. 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 of Kathmandu 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. Up-grade laboratory, establish quality control system. ................................................................................ ..................... . ...... .........................................................................I................................................................................ .missions 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 ambient pollution. P 'opulation exposure Establish appropriate dispersion model for Kathmandu Valley. ................. ......................................... . .................... ...................................................................................................... .......................................................................... Assessment of damage and cost Epidemiological research, assessment of specific health costs. Empirical study of tourism and environment (tourists attitudes). Identification of interest of other parties in a cleaner environment. .... ..I.................................................................................................. ...................I........................................................................................................... Inventory of abatement measures Effectiveness (abated/avoided emissions). Costs. Non-environmental environmental. Institutional and regulatory framework Involvement of the Nepal Oil Corporation. Tax differentiation between clean and dirty diesel, if there areways of importing clean diesel For the brick industry, develop clean technologies ... ............................................................................................................................................... ................................................................... ! 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. Proposed actions and measures to improve the air quality of Kathmandu Valley What How When Who Remarks Category 1. Ambient Air Quality Monitoring, Inventoly and Dispersion Modeling I. Air Quality Monitoring 1. A. Design national air quality - Review national air pollution status and assessment ASAP NPC/EPC, DOHM, DOTM Monitoring ambient air quality will be monitoring program. capabilities; trusted to DOHM with close cooperation - Establish field stations and base laboratory 1995 with MOI and MOWT and NGOs 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, MOI, Academic comprehensive emission implementing agencies such as MOWT, MOI, 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, MOI, of both mobile and stationary going DOTM sources. 3. Conduct inventory of - Coordinate with indoor-air pollution program S/S academic consultants Coordinating with donors domestic emission Category 2. Traffic DemandManagementandinfrastructure 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 Table 5.3. Proposed actions and measures to improve the air qualit of Kathmandu Valley 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, DOR Rationalizaton 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 Enforcement/Traffic 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 infommation information system and prepare plans. Result system at traffic police 1994 3. Strengthen Traffic Safety Establishment of wide walk network 1995 DOR, DOTM Program Organize traffic safety seminars/weeks and also re- 1994 education of traffic rules and regulation. onward Immediately strengthen traffic police/traffic DOTM, DOR, Traffic Police lights/zebra crossing for traffic improvement 4. Expansion of public Advocate and support 1995 MOWT, DOTM transport/system 5. Provide environment friendly Extend trolley bus network 1994 MOWT, NTC transportation onwards Co 00 Table 5. 3. Proposed actions and measures to improve the air quality of Kathmandu Valley What How When Who Remarks 6. Survey present mass transit Implement survey results 1994 DOTM situation and improve: onwards - time schedules, - junctions and stations Category 3. Land Use Planning and Management 1. Land use planning to reduce Workout strategy for dispersing facilities (shopping, S/S MHPP, DOB, DHUD, DOTM 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 plan and pass new zoning S/S MHPP, DHUD plans/GLDP for Kathmandu ordinances Valley and revise zoning ordinates raise awareness through training and education S/S MHPP, DHUD, NGOs, campaigns to make people realize the benefits of municipalities planning Extend GLDP to areas where environmental standard is low 3. Conservation of open Ensure buffer zones parks and other public amenities ASAP MHPP, MLD, DHUD spaces by strct enforcement of land use policy municipalities, NGOs 4. Land use policy for lndustdal Develop and enforce inter and intra-industral land ASAP MHPP, MOI establishments use zoning Categoty 4. Fuel Switch/Quality Control 1. Switch on to less polluting Tax or subsidy modification. ASAP MOS, MOF Leading role should be played by MOS utility vehicles in various and NOC. organizations Study restructuring of taxes on diesel vis-a-vis petrol with a view to encourage the use of petrol over di&W.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. Table 5.3. Proposed actions and measures to improve the air qualit of Kathmandu 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 introduced a system of thermometer but it needs to be made accessible and its existence known to the consumer. Use NGOs and consumer protection councils for S/S NOC, NGOs educating the public. 3. Phasing out of lead in petrol Study its feasibility, possibility of revision of supply to ASAP MOS, NOC some extent, the additional cost to the consumers. 4.. Review energy pricing Study the issue and feasibility of removing all prce ASAP MOS, MOF, NOC, NPC/EPC, policy. Consider impacts to distortions. Consider environmental costs. DOTM environment (petroleum products and electicity or other fuels) Study impacts of removal of subsidies on diesel; Study the possibility of introducing pollution tax. Categoty 5. General Awareness Raising 1. Awareness/information on air Use tb-media ASAP, MECSW, NPC/EPC, MHPP, MCI Target groups: public through CBO, polluton 1995 NGOs, govemment units Start pollution information forum. Publish bulletin/newsletter. MOH, NGOs, EPC - Improve indoor/ outdoor air Launch antismoke campaign MECSW, MHPP, MOH, NGOs quality Arrange talk programs in public places (HaatVBazar, schools, restaurants, etc.) Indoor ventilation/improved cooking stoves MCI, MOH Designate smoke-free zones - Promote correct value Include in school cuniculum MECSW system - Care for the Media campaign to create awareness environmentlfellowmen Amend/Revise rules to ensure effectiveness Follow-up KWECP campaign MCI, NGOs, MOWT 2. Traffic Management Train enforcers and drivers ASAP Traffic Police Proper tuning of vehicles. DOTM Table 5.3. Proposed actions and measures to improve the air quality of Kathmandu Valley What How When Who Remarks Organize traffic week regularly S/S MECSW, TP, DOTM Use mass media for public awareness S/S MCI, DOTM 3. Supply quality fuel Information to detect diluted fuel and its effect S/S NOC Introduce an appropriate system of fuel testing at S/S NOC petrol pumps. Category 6. Fuwler Studies 1. Air Quality Monitoring Conduct appropriate studies which will relate to more ASAP NPCIEPC NPC/EPC 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 a private 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 Table 5.3. Proposed actions and measures to improve the air quality of Kathmandu 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 altematve 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 corTelate 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. Institutonal and Regulato,y Framework 1. Introduce 'polluters pay" Plug and amend existing environmental legislation. S/S MLD, MHPP, MOWT, BSM, MOI A high level coordinating and monitoring prnciple 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 S/S 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 MOI Introduce quality drainage management ASAP DWSS 2. Strengthen technical Establish and promote training institutions S/S MLD capabilities relevant govemment agencies, industry, municipality, SWMRMC and NGOs for environmental management Promote technical and economic capabilities S/S EPC Encourage community/people participation ASAP MLD, TDC Table 5.3. Proposed actions and measures to improve the air qualit of Kathmandu Valley What How When Who Remarks Increase economic benefit of the staffs. 1995 Relevant Govt. Agencies, NGOs Encourage private sector involvement ASAP Promote private lab for testing ASAP 3. Coordinate efforts among Strengthen existing traffic management S/S MLD, Traffic Police, DOTM different govemment and non- govemment 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 concemed agencies. Require total disclosure and technigraph for all ASAP DWSS, SWMRMC, NGOs vehicles. Encourage to import standard spare parts S/S Fixing parameters on air, water, noise and land S/S 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. Removejurisdictional Duplication of jurisdictional boundaries and S/S MLD, MHPP, EPC boundaries between different responsibilities be avoided. institutions. Play vital role with O&M activities S/S Provide detailed guidelines and strengthen SWMRC S/S and municipalities. 7. Strengthen enforcement Train people or staffs and maintain coordination. ASAP MLD, MHPP capabilities of concemed authorities Table 5.3. Proposed actions and measures to improve the air quality of Kathmandu Valley What How When Who Remarks Tap NGO to assist. Use media pressure. Setup S/S EPO hotline to report violators. 8. Strictly and uniformly Prepare a manual, strengthen implementation 1995 EPC, MOWT, MHPP, MLD, 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/EPC Traffic Police, MOWT, cars, motorcycles, heavy-duty time schedule going DOTM vehicle, tempos 10. Address highly polluting: Enforce existing laws/legislation ASAP NPC, MOI, 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 I 6. EXISTING LAWS AND INSTITUTIONS 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. 75 76 Existing Laws and Institutions 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: 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 HMG/Ministry 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. INSTITUTIONS INVOLVED The following is a listing of the institutions responsible for environment. Coordination * HMG/National Planning Commission (NPC/Environment Protection Council (EPC); and * Metropolitan Environment Improvement Program (MEIP)/World Bank. Monitoring * Department of Hydrology and Meteorology, Babarmahal, Kathmandu; * Royal Nepal Academy of Science & Technology (RONAST), Naya Baneshwor, Kathmandu; and * HMG/Bureau of Standards. Emissions Invenwories * Department of Hydrology and Meteorology, Babarmahal, Kathmandu; * Kathmandu Valley Vehicle Emission Control Project (the Ist phase), funded by UNDP, under Department of Transport Management, Naya Baneshwor, Kathmandu; and * Royal Nepal Academy of Science & Technology (RONAST), Naya Baneshwor, Kathmandu. Legislation * HMG / Ministry of Law, Babarmahal, Kathmandu. Enforcement * Department of Traffic Management, Naya Baneshwor, Kathmandu; and * Kathmandu Valley Traffic Police, Singhadurbar, Kathmandu. URBAIR-Kathmandu 77 The above mentioned departments are basically funded by the Government of Nepal, except for the "Kathmandu Valley Vehicle Emission Control Project (1st phase)" which was financed by UNDP and MEIP. Manpower, expertise, and equipment data for the organizations are are listed in Table 6.1. Table 6.1: Institutions and equipment need,for 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 CO/HC analyzers of Horba Co., Japan 2. KTM Valley Traffic Police 455 44 a 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. 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"Summary of Findings-Five Nation Asia Motor Vehicle Sampling tour." University of Denver, Colorado. Tharby, R.D., W. Vandenhengel, and S. Panich. (1992). "Transportation Emissions and Fuel Quality Specification for Thailand." Draft Report February 1992, Monenco Consultants Ltd. Oakville, Canada. Tims, J.M. (1983). Benzene Emissionsfrom Passenger Cars. CONCAWE Report 12/83. Brussels: CONCAWE. Tims, J.M. et al. (1981). Exposure to Atmospheric Benzene Vapor Associated with Motor Gasoline. CONCAWE Report 2/8 1, Brussels: CONCAWE. Tuladhar, A.M. (1993). "Progress Report on Technical Intervention of Diesel Vehicles." HMG/UNDP joint project, KVVECP, Kathmandu. Turner et al. (1993). "Cost and Emissions Benefits of Selected Air Pollution Control Measures for Santiago, Chile." Engine, Fuel and Emissions Engineering, Sacramento, California. United Nations Development Programme/World Bank. (1993). "Nepal. Energy Efficiency and Fuel Substitution Activity. Activity Completion Report." Confidential Report. World Bank, Washington, D.C. Wang, Q., C. Kling, and Sperling, D. (1993). "Light-duty Vehicle Exhaust Emission Control Cost Estimates Using a Part-pricing Approach." Journal ofAir Waste Management Association. 43: 1461-1471. Weaver, C.S. and P.E. Lit-Mian Chan. (1993). "Motorcycle Emission Standards and Emission Control Technology." Report to the World Bank and Thai Government. Engine, Fuel and Emissions Engineering, Sacramento, California. World Bank. (1993). "Philippines Environmental Sector Study: Toward Improved Environmental Policies and Management." Sector Report No. 11852, East Asia, Country Department 1, World Bank. World Health Organization (WHO)/United Nations Environment Programme (UNEP). (1992). Urban Air Pollution in Megacities of the World. Oxford, U.K.: Blackwell Publishers. APPENDIX 1: AIR QUALITY STATUS, KATHMANDU VALLEY OUTDOOR (AMBIENT) CONCENTRATIONS Past measurements. Prior to 1993, only scattered measurements of air pollution concentrations had been performed. The KVVECP (Kathmandu Valley Vehicle Exhaust Control Program) study identified seven 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: Table 1: Air quality related studies in Kathmandu Valley prior to 1993 Reference-of study Year Conclusions 1. Bhattarai and Shrestha 1980 Kathmandu: Pb Maitighar: 544 ppm Trpureshwor: 153 ppm 2. MHPP Pollution study 1987 Kathmandu: Roadside dust: 6 to 11 times that 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 Pradhanang 1992 Kathmandu: Milipore pump & micro flora SPM range: 197-524 pg/M3. 6. NILU Team observation 1993 Kathmandu: Low visibility and haze, road side SPM high 7. RONAST 1993 Kathmandu: Road side SPM 197-775 pg/m3 higher than intemational stds. Source: Mathur (1993). "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 83 84 Appendix 1 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 SO4, NO3 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 al., 1992). Sixteen 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 ,tg/m3, averaging 304 4g/m3. The corresponding Air Quality Guideline (AQG) of WHO is 120 tg/m3. Thus, the measured concentrations 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 ptg/m3 (at Kuleswore). This study also included PMIo measurements giving concentrations within 50-130 [.g/m3. Measurements of CO, SO2 and NO2 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. 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, PM1o, NOR, CO, SO2 and lead measurements at a total of 20 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, PM10, NO2, SO2, CO and lead at 14 sites during September- December 1993 (Devkota, 1993). * Measurements by NESS (Pvt) Ltd. of PM10 and lead at a number of sites in Kathmandu City during September-November, 1993 (Sharma et al., 1994). * Measurements of TSP by the Hydrological and Meteorological Service at the HMS building at Babar Mahal, starting from January 1993. URBAIR-Kathmandu 85 Figure 1: CO measurements performed by NIL U in Kathmandu, traveling on roads by taxi, April 1993 Kathmandu 19. april 1993 pp# 689 4 8.-L-- .. .. .... .L 0 Ii 41 1 I a__ 3.9 * S 0 X 2 4 T -r-- . 16:49 n: 2e:e3 21: 4e Central European Time yppi Kathmandu 20. april 1993 PP,, "' ' 32.9---32.8 S. ., 1. ~ A 4I 0.0 0.13~ SI A 19:3 20 _42 _3_211 16.9 * *~~~~~~Cnta 16.9 en im 86 Appendix 1 Results ftom the ENPHO measurements. The measurements (Karmacharya and Shrestha, 1993) were carried out in two phases: * 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; and * 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. Table 2: Description of ENPHO camaign measurement sites Sampling station Height Distance from Distance from Direction from the Type of area Traffic (m) closest road (m) popular junction (m) popular junction (m) density 1. Chabahil 3 5 100 North-East Residential/ Busy Market 2. lndrachowk 12 5 50 North-West Residential/ Busy Market 3. Maharajgunj (Ring 5 15 30 South-East Residential Moderate Road) 4. Thapathali i 3 5 75 North-West Residential/ Busy Market 5. Putalisadak 6 8 75 South Residential/ Busy Market 6. Kalimati 10 5 25 North Residentiall Busy Market 7. Royal Palace 5 8 30 South-West Market Busy 8. Balaju (Ring 6 15 35 North-West Residentiall 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 i 1. 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 Durbar 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. Trpureswor 0.75 2 50 South-East Residential/ Busy Market Source: Karmacharya and Shrestha (1993). URBAIR-Kathmandu 87 Figure 2: ENPHO campaign measurement sites TO-KAKAMh i - .. //'TOSM4.LKANa.A T'IL~~~~~~~~~~~~~~~~9 PAXI.AJO SW*ThM~~~~~~~41~~~~JIEATh~~le __S_IMT * ' A~3UIJX;Pw= Z / ' .* Source: Karmacharya and Shrestha (1993). 88 Appendix 1 The results indicate that TSP is the main Table 3: Concentration of the pollutants (first part-24 hour problem compared to the averaing time), ENPHO stud WHO guideline. The Stations TSP PM,0 S02 NO, co Pb measurements from phase ,ug/mr3 pgglr3 pgMl3 pgIM3 mgIm3 JgIm3 1 (24 hour averages) 1. Chabahil 555 127 <13.0 28 <11 0.35 averaged 308 [tg/m3, with 2. Indrachowk 194 59 <13.0 24 <11 0.21 3. Maharajgunj (Ring Road) 233 64 <13.0 17 <11 0.18 maximum concentration 4. Thapathali 206 74 <13.0 12 <11 0.31 of 555 ,ig/m3, at Chabahil. 5. Putalisadak 267 92 <13.0 28 <11 0.37 PMIo also exceeded the 6. Kalimati 232 76 <13.0 24 <11 0.30 guideline at many of the 7. Royal Palace 182 93 <13.0 25 <11 0.53 sites, but to a lesser extent 8. Balaju 465 102 <13.0 24 <11 0.23 than TSP. Maximum PMIo 9. Bir Hospital 438 116 <13.0 36 <11 0.43 concentration was Average 308 89 *6.5 24.2 <11 0.32 concentration was ~~WHO Standard 120 70 125 150 0.5-1.0 127 [tg/m3 (WHO Source: Kannacharya and Shrestha (1993). guideline: 70 ,ug/m3). The S02, NO, and CO measurements indicated rather low concentrations. Table 4: Concentration of the pollutants (Second part-9 The lead measurements hour averaging time), ENPHO study also indicated fairly low Stations TSP PM10 SO2 NOX CO Pb concentrations, with a pg/Ml3 pg/rM3 jg/Ml3 pgIM3 mg/M3 pg/M3 maximum 24-hour value of 10. Kuleswor 2258 415 19 59 <11 0.7 0.53 Fig/m3, against a long- 11. Thamel 1978 498 <13 48 <11 1.2 term WHO guideline of 0.5- 12. Ason 1772 281 <13 28 <11 0.5 1 ,ug/m3. 13. Nachghar (Jamal) 1283 257 <13 32 <11 0.9 The phase 2 14. Kasthamandap 1056 182 <13 17 <11 0.4 meaureet at r15. Kalanki (Ring Road) 1201 239 22 40 <11 0.2 measurements at roadside 16. Sinha Durbar 789 225 20 69 <11 0.2 sites gave much higher 17. Dillibazar 1077 240 18 30 <11 0.5 concentrations. Also here, 18. Swayambhu (Ring Road) 1161 258 <13 26 <11 0.3 TSP and PMIo, presented the 19. Bus Park (Ratna Park) 1709 355 17 41 <11 0.6 largest problem compared to 20. Tfipureswor 1090 313 <13 30 <11 0.4 guidelines. Average 1397 296 12.3 38 <11 0.54 TSP-concentrations (9- * S02 - <13 has been arbitrarily considered half of 13, i.e. 6.5. hour day-time average) Source: Karmacharya and Shrestha (1993). averaged almost 1400 1ig/m3, with max. concentration 2258 gug/m3, at Kuleswor. PMIo averaged almost 300 Rig/m3, with maximum 498 ,ug/m3 at Thamel. Again SO2, NO, and CO concentrations were low, while the lead concentrations were up to 1.2 1LgIm3, averaging 0.54 gg/m3. Still fairly low, but increased compared to the phase 1 sites. These measurements, covering a number of sites in general Kathmandu City atmosphere and the roadside atmosphere, can be used to give a rough estimate of a long-term average TSP and PMIo 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 gg/m3 for TSP and 150 jg/m3 for PM,0. URBAIR-Kathmandu 89 * 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 ,ug/m3 for TSP and 75 Vlg/m3 for PMIo for an average person living in central Kathmandu City spending 25 percent of his time roadside. Resultsfrom the KVVECP study. As part of the Kathmandu Valley Vehicle Exhaust Control Program (KVVECP), measurements of TSP, PMIo, NO2, S02, CO and Pb were made at a 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 (3040,000 ADT) Singha Durbar, 2 3 GPO 3 3 ii. Medium traffic (20-30,000 ADT) 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 Bageshwod 15 8 3. Industrial Areas Balaju, 15 4 Bhaktapur, 50 3 Patan Industrialized districts, 5 5 Himal Cement Factory surrounding 100 10 4. Regionalbackground/control site Tribhuvan University 50 3 Kirtipur Source: Mathur (1993). Table 6: Monitoring methods, ENPHO and KVVECP Sampling: En Envirotech APM 451 Respirable Dust Sampler (Incian produce) was used as sampler for TSP, PMIo, SO2 and NO2. The flow rate for TSP/PM10 was 0.8-1.2 m3/min, and for SO2 and NO, 1 I/min. The samples were partly 24 hour samples (midnight-to-midnight), and party 8 hour samples during peak daytime traffic (9-10 a.m. to 5-6 p.m.). Analysis: SO2: Pararosaniline method NO2: Jacobs-Hochheiser Arsenite, Modified method TSP: Gravimetric analysis, Whatman GF/A filter (PMIO) 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): Sources: Karmacharya and Shrestha (1993) and Mathur (1993). 90 Appendix 1 Figure 3: Measurement sites, KVVECP study . ' " ~~ -7 - E *a Commerdal (traffic) sites - *'o...- -,~ VIndustrial sites 20 14* 4- '- ' / ", "Resldential sHes I t tt'\ ' *- A S /o/ -' ''; oa Regional background sites 5t o , t~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~AO-- 15~~~~~~~~~~~~~~/ 10 pur n T Brtpur '_ -7~~~~~~~~~~~~~~~~~~~~~~~~- ~~~I ~ ~ ~ ~ ~ ~ - - --~~~~~40- 5 10 1520 25 Source: Mathur (1993). 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, PM1o, SO2 and NO2, respectively. URBAIR-Kathmandu 91 Table 7. Summary of air qualit measurements, KVVECP study Average/max 24 h conc. (jig/mr) TSP PM1o SO2 NO2 No. of days Commercial (traffic) sites Singha Durbar (heavy traffic) 303/375 142/175 49 /64 37 /64 22 (Nov./Dec.) GPO (heavy) 380 / 474 137 201 37 / 64 11/16 16 (Nov.) Ratnapark (medium) 187/319 67 86 32 /102 18/28 16 (Sept.) Lainchaur (medium) 228/386 103/ 146 17 /26 19/40 13 (Nov.) Kalimati (medium) 391 /441 135/154 77 /202 19 /31 12 (Nov.) Thimi (low) 337/867 115 /117 49 /65 19 / 24 20 (Dec.) Residential sites Maharajgunj 191 /350 72 /126 19/34 12 /14 13 (Nov.) New Baneswor 200 / 270 113/161 13 /13 14 / 25 5 (Sept./Nov.) Jaya Bageshwor 228/273 112 /132 110 /225 49/ 126 10 (Dec.) Industrial areas Balaju 108/137 40 /77 15121 31171 9 (Sept.) Patan 87 /102 47/53 13 /13 40 /83 5 (Sept.) Bhaktapur 213/290 105/131 58/79 20 /24 6 (Dec.) Himal Cement surrounding 430 /560 166/194 57 / 65 38 /58 5 (Dec.) Regional background site Trbhuvan Univ. 94/ 155 66 /81 38/77 18 / 35 19 (Nov./Dec.) Source: Mathur (1993). 92 Appendix 1 Figure 4: TSP measurenents, KVVECP study _ I I I I I I II I _ []87 Average value TSP l o91 Max. value _108 lwl v \\\\ \ Z \ Measurement sites, KWECP . -371 J \ / ) *Commercial (traffic) sites V Industiial sites Source: Ma thu (1993). Residential sies /< f \ A1 \ ~~~~~~~~~o Regional background sites (J / X } 0 1 2km~~22 (;Tj~~~~~~~27 Source: Mathur (1 993). URBAIR-Kathmandu 93 Figure 5: PM,o measurements, KVVECP study _ i_ I _L I _ 1 I l I _ F[4 7Y\ Average value PMY10 / '. \ 9 \ LS75Max. value F40 Measurement sites, KVVECP J1~ ' 0 / * Commercial (traffic) sites v Industrial sites Source:_ h ( ).i/ Residential sites / , \. ER o~~~~~~~~~~~ Regional background sfes 0~~~~~~~~~~~~~~~~~~~~ 1 2Xk [Suc: ahr (1 993)I 94 Appendix 1 Figure 6: SO2 measurements, KVVECP study _ ' I I ' I I I _,1 1 I I I _ >fl _vAverage value S°2 / x, \ / / 153 Max. value _15 Measurement sites, KVVECP EE\j| * Commerdal (traffic) sites v Industrial sites Source: Mat,ur\(1993). Residential sies / , \ + ~~~~~~~~~~~o Regional background sRtes X (k) I / \ | 0 1 2 km| l~~~~~~~~~~~~I R~125 U URBAIR-Kathmandu 95 Figure 7: NO2 measurements, KVVECP study _ I ' I _l I I I _z1 1 , ~~~ ~~~~~~~~~~~~~~~~~~~I I I _ _ NO2 --.f. 12;\ W4 Average value N 2 . . Max. value Measurement sites, KWECP 7Ml J / / I * Commerdal (traffic) sites v Industrial sites For TSP, the concentration ranges for averagO Regional background s nes value), 430 p...... an40-69~gm,rspciey 00121 nS~~~~~~~~~~~:16 I~~~~~~~~~~~~~~~~~ I 1, k Source: Mathur (1 993). For TSP, the concentration ranges for average and maximum values are 94 (background value), 430 ,ug,/m3, and 102-867 ,ug/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 PM1), 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. 96 Appendix 1 SO2 and NO2 concentrations were generally low, according to the measurements, except at Kalimati (SO2) and Jaya Bageshwori (SO2 and NO2). 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 of TSP was on the average some 90-100 ,ug/m3 in the autumn of 1993, with maximum concentrations up towards 150 ttg/m3. The similar figure for PMIo was some 50 [ig/m3 (average) and 80 ,ug/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 of TSP and PMIo, being close to the cement factory. Relative to WHO guidelines, the TSP and PMIo concentrations both rise to twice the guidelines. For TSP, about 70 percent of all the measurement days were above the lower guideline value (150 Rg/m3), and about 50 percent of the days were above the higher guideline value (230 Rg/m3). About 50 percent of the total days of measurement had PMIo above the guideline of 70 pg/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. Resulas 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. Table 8: TSP measurements at Babar Mahal, 1994 (Hydr. and Met Service Building Jan. Feb Mar April May June July Aug Avg. Jan-April Avg. May-Aug Ave. measure (,ug/m3): 226 227 312 310 185 137 100 106 269 132 Max. measure (pglm3): 363 422 384 467 437 302 138 192 No. of days above AQG: Total number of days -150 pgIm3 21 14 10 18 15 9 0 2 63 26 -230 pg1m3 12 4 10 15 6 1 0 0 41 7 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 Source: Shrestha (1994). 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 p,g/m3; max: 270 pig/m3; 5 sampling days). The WHO guidelines were exceeded on the majority of the days. The highest concentration, 467 ,ug/m3, was more than twice the upper level of the 24-hour guideline range, 230 gg/m3. URBAIR-Kathmandu 97 Figure 8: TSP measurements at Babar Mahal, 1994 (HMS building) 500 500 Jan. Feb. 400 400 300 AA & 300 200 200 A &A A 100 100 0 ' I '' II III I 11 1 1 1 1 1 . . . . . . 1 O - 4 1 ' 1 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 27 500 500 400 Mar. 400 -Apr. A~~~A 300 P A 300 AA~~~~~~~~~~~ 200 200 100 100 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 29 500 500 400 May. 400 Jun. 300 300 200 200 100 ' AAt % AA100 A*& A j @ -i:-, &4 O' I1^ I 1I %1 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 c annual Jul. 40 -,ug.Aug. 300 300ff 200- 200 100 A 100 A 0- 'A-4A 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 311 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 Source: Shrestha (1 994). The 8-month average concentration was 200 Rig/M3, compared to the WHO guideline for annual average, 60-90 jig/M3. Results from the NESS (Pvt) Ltd campaign. The following samples were taken in 1993: 98 Appendix 1 * 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. * PM,( 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 gm cut off slotted impactor in front. * Monitoring of particle concentration by a Laser Dust Monitor (Japanese make) at 59 sites during November 3-19. The measured road dust lead content is given in Table 9. Lead, assuming mainly from Table 9: Lead content in street dust of Kathmandu City, lead in gasoline, is clearly 1993 present in roadside dust. The ppm Pb in dust concentration of lead is typically Samples No. of sites Average Range Average Range 200-300 ppm in the >2 mm September 10, 22, 23 10 275 50-1,187 140 81-344 fraction, and somewhat less in October 27-28 21 160 1-965 - - the <0.2 mm fraction. Source: Sharma, Upadhya and Shahi (undated). The measured PM1o and lead concentrations in air are presented in Table 10: PM,0 and lead in air analyzedfrom samples drawn with Table 10. The values the Sibata high-volume sampler represent typical one- PM10 (mglm3) Lead (,uglm3) hour averages during Period No. of sites Average Range Average Range daytime hours. September 5-6 3 3.5 0.23-6.08 The PMIo October25 and 9 0.80 0.23-2.11 1.1 0.65-2.60 concentrations are very November 1-2 high (up to 2,100 ,ug/m3), much higher than those from the ENPHO and KVVECP studies. The Sibata sampler has a slotted 10 jim impactor in front of the filter where particles are collected. The function of the impactor is to hold back particles of diameter above 10 jim from the filter. It is possible, as known from experience with similar impactors, that dry dust particles are not collected with full efficiency. However, it is still difficult to explain the high PM1O 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 al. (undated) has plotted PMIo 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 al., 1989). The cooking practices undoubtedly also create localized outdoor air pollution problems in settlements in meteorologically shielded locations. URBAIR-Kathmandu 99 Extremely high TSP and CO concentrations have been measured in Table 11: Mean personal exposures to TSP and village houses, and a pronounced positive CO area concentrations by village and stove type effect of improved cooking practices has Traditional Improved been detected. Table 1I shows results n x n x P (%) obtained by Reid et al. (1986). Pandey et TSP(mg/m3) al. (1990) obtained similar results. Gorkha 11 3.17 (2.2) 13 0.87 (0.71) <5 This situation in Kathmandu is Beni 11 3.11(2.9) 14 1.37 (1.3) <2.5 Mustang 2 1.75 2 0.92 >10 described by Mathema et.al. (1992) as CO (ppm) follows: Gorkha 13 280 (230) 14 70 (35) <0.5 Beni 14 310 (220) 12 64 (39) <0.1 "About 82 percent of the urban Mustang 2 64 2 41 >20 households depend on fuel-wood for Note: There is a statistically significant (<5%) difference between cooking purposes. If Kathmandu is a the levels for both pollutants, experenced by women cooking with typical example then very few urban improved stoves compared to traditional ones in both Middle Hill typical example then very few urban .' families have the provision of a villages. There are too few samples in Mustang. families have the provision of a n = sample size; smokeless chulo and chimney. They X = mean (geometric mean); are increasingly becoming more P = level of significance, i.e. probability that observed difference dependent on kerosene. A recent study between the averages of improved and combined traditional found that only 0.6 percent of families stoves has occurred by chance based on a two-tailed t-test. in the Kathmandu City have a All calculations are based on sample standard deviations (n-I). Source: Reid et.al. (1986). smokeless chulo, 47 percent have no chimney, and 6.97 percent of those who have a chimney felt that their kitchen is still "full of smoke" (Regmi and Joshi, 1988, pp. 45-47). Furthermore, about 36.5 percent use a Kerosene stove for cooking. The 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 modern one-story house constructions, suggests that the problem of indoor smoke could spread over the rest of the house. Based on an Indian study, pollutants emitted from firewood appear to be the most common, and the most highly polluting fuel source. Assuming a 6-hour cooking period per day, an average urban household is subjected to 16 mg/m3 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 chula emits a high dose of carbon monoxide and "working in such an environment for more than ten minutes is considered poisoning" (Shrestha, 1986, p. 42). 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 100 Appendix 1 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 Shrestha's findings. Diurnal and annual Figure 9: Fraction of days (percent) with fair-to-good visibility (>8,000 m), variation of Kathmandu Valley, November-February, 1993 visibility. The 6 present 6 visibility situations is 8_ such that during the 10- period _ 90 November- February the visibility is 14- very poor before 9:00 a.m., with 16 only 10 _ 70 percent of the 18- I I day with Jan. Feb. March April May June July Aug. Sept. Oct. Nov. Des. visibility Source: Shrestha (1994). >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. URBAIR-Kathmandu 101 Figure 10: Number of days per month with fair-to-good visibility (>8,000 m), Kathmandu Valley, 1969-93 40- January 40- July D20- \t20 . 70 75 80 85 90 Year 70 75 80 85 90 Year 40 - February 40- August 30C'--V S 30- - 20 20- 10- ~~~~~~~~~~~~10- 70 75 80 85 90 Year 70 75 80 85 90 Year 40 - March 40 - Septemberi 30-- 300- 20O 70 75 80 85 90 Year 70 76 80 85 90 Year 40 -April 40- October 30- ~~~~~~~~~~~30- 20- Ji 20- O'- g111|l llW1 1|{z1tlll18 1O- 70 75 80 85 90 Year 70 75 80 85 90 Yea 70.. 75 80 8 O. 5 90 Year 70 75 80 85 90 Year 40- May 40- November |20- 20--~20 10 - 10 \ O-,,,,,,,,,,,, O-,........... 40- June 40- Decenmber Ct20- 20 _ 70 75 80 85 90 Year 70 75 80 85 90 Year Source: Shrestha (1994). 102 Appendix 1 Figure 11: Number offoggy days at 9 am for the period November-February, Kathmandu Valley, 1969-93 80- 80- 40- 20- 0- I I I I I I 70 75 80 85 90 Year Figure 12: Number of days in January with visibility >8,000 m, at given hours, 1970 (full line) and 1993 (dotted line) 30- January 20- o- IIIIIIII 0 6 8 10 12 14 16 18 Local tire Source- Shrestha (1994). UJRBI3R-Kathmandu 103 Figure 13: Temporal variation of relative humidity at Tribhuwan Airport, 1993 (percent) tn~~~~~~~~~~~~~i r.J 0~~~~~~~~~~ 0~~~~~~~ Ln~~~~~~~~~~~~~~~~I tn~~~~~~~~~~i U~~~~~~~ .~~~J 00 01~ ~ ~ ~~~~zo 104 Appendix 1 Trend offoggy 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 rim). 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." Report submitted to Kathmandu Valley Vehicular Emission Control Project (KVVECP). (HMGIUNDP/NEP/92/034). Karmacharya, A. P. and R. K. Shrestha. (1993). Air Quality Assessment in Kathmandu City 1993. Environment & Public Health Organization, Kathmandu. Mathema, M.B., A. R. Joshi, S. L. Shrestha, and C. L. Shrestha. (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. Joint Project for Environmental Protection." KVVECP, Kathmandu. Otaki, K., T. Sharma,and N. P. Upadhyaya. (undated). "Respirable Air Particulate (PM1o) Potential in Kathmandu Municipality." NESS (Pvt) Ltd., Kathmandu. Pandey, M.R. (1984). "Prevalence of Chronic Bronchitis in a Rural Community of the Hill Region of Nepal." Thorax 39: 331-336. Pandey, M.R., R. P. Neupane, A. Gautam, and I.B. Shrestha. (1989). "Domestic Smoke Pollution and Acute Respiratory Infections in a Rural Community of the Hill region of Nepal." Environment International 15:337-340. Reid, H.F., K.R. Smith, and B. Sherchand. (1986). "Indoor Smoke Exposures from Traditional and Improved Cookstoves. Comparisons Among Rural Nepali Women." Mountain Research and Development 6(4):293-304. Sharma, T., N.P. Upadhyaya, and K. B. Shahi. (undated). "Extent and Dimension of Lead Pollution through Leaded Emission in the Kathmandu Municipality." NESS (Pvt) Ltd., Kathmandu. Sharma, U., R.R. Shahi, A. Shrestha, J. Thapa, J. Sijapati, P. Rana, and M. Pradhananga. (1992). "Atmospheric Pollution in Kathmandu City I: Particulate Matter in the Kathmandu City and Study of Mycoflora in it." J.Nep.Chem.Society 11 1-8. Shrestha, M. L. (1994) "Meteorological Aspect and Air Pollution in Kathmandu Valley. Final Report." Dept. of Hydrology and Meteorology, His Majesty's Government in Nepal, Kathmandu. URBAIR-Kathmandu 105 ANNEX: COPY OF THE KWECP AIR QUALITY MEASUREMENTS (SOURCE FOR ALL TABLES: DEVKOTA, 1993) Table 1: Ambient air quality monitoring in commercial area, heavy traffic (GPO Complex) Date Pollutants Sampling Remark gig/(m hour TSP N02 802 PM1o 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 1111/93 172 665 837 19 35 8 12-8:30 12/11/93 121 79 200 17 13 8 8:30-4:30 12/11/93 173 1,399 1,572 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 Holiday 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 20/11/93 135 265 403 11 64 24 Holiday 21/11/93 179 697 876 35 162 8 (I) Range SPM: 321-474 (24 hr) 200-1,572 (8 hr) PM10: 99-201 (24 hr) 106-200 (8 hr) N02: 9-16 (24 hr) 12-41 (8 hr) S02: 13-64 (24 hr) 13-162 (8 hr) (II) Average: SPM 380 (24 hr), 682 (8 hr) PMio: 137 (24 hr), 157 (8 hr) N02: 11 (24 hr), 24 (8 hr) S02: 37 (24 hr), 33 (8 hr) 106 Appendix 1 Table 2: Ambient air quality monitoring in commercial area, heavy traffic (Singha Durbar) Date Pollutants Sampling Remark jig/m3 hour SPM N02 S02 PMio 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 29/11/93 132 957 1,089 39 67 8 30/11/93 127 107 234 26 64 24 1/12/93 102 201 303 75 188 20 2/12/93 167 208 375 88 61 24 3/12/93 112 219 331 52 69 10 4/12/93 120 292 412 34 80 8 Holiday 5/12/93 134 216 350 41 95 8 6/12/93 165 97 262 24 35 24 7/12/93 170 341 511 45 93 8 8/12/93 119 120 239 20 51 24 9/12/93 143 332 475 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 hr) 274-1,089 (8 hr) PM1o: 119-175 (24 hr) 113-180(8 hr) N02: 20-88 (24 hr) 33-686 (8 hr) SO2: 35-64 (24 hr) 13-99 (8 hr) (II) Average: TSP: 303 (24 hr), 532 (8 hr) PM10: 142 (24 hr), 144 (8 hr) NO2: 37 (24 hr), 45 (8 hr) SO2: 49 (24 hr), 72 (8 hr) URBAIR-Kathmandu 107 Table 3: Ambient air quality monitoring in commercial area, medium traffic (Kalimati) Pollutants Sampling Remark Date ,ug/m3 hour TSP NO2 S02 PMio Particle Total 20111/93 114 241 355 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 25111193 179 861 1,040 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 1/12/93 165 721 886 9 163 8. (I) Range TSP: 331-441 (24 hr) 377-1,040 (8 hr) PM1o: 114- 154 (24 hr) 110-179 (8 hr) N02: 12-31 (24 hr) 10-51 (8 hr) S02: 16-202 (24 hr) 13-163 (hr) (II) Average: TSP: 391 (24 hr), 734 (8 hr) PM10: 135 (24 hr), 154 (8 hr) NO2: 19 (24 hr), 35 (8 hr) SO2: 77 (24 hr), 71 (8 hr) 108 Appendix 1 Table 4: Ambient air quality monitoring in commercial area, medium traffic (Ranipokhari traffic complex) Pollutants Sampling Remark Date pg/rn3 hour TSP N02 S02 PM10 Particle Total 10/9/93 67 252 319 17 13 24 15/9/93 59 87 146 6 16 24 Rainfall 1319/93 57 91 148 28 102 19 Rainfall 5/9/93 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 8/9/93 100 139 239 29 13 8 Rainfall 9/9/93 114 386 500 32 13 8 11/9/93 56 156 212 35 13 8 Holiday 12/9/93 78 212 290 28 14 8 6/9/93 n.a. n.a. n.a. 29 13 7 Rainfall 14/9/93 67 115 182 33 21 7 16/9/93 75 309 384 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 Nepal Banda (I) Range TSP: 56-319 (24 hr) 182-500 (8 hr) PMi0: 57-86 (24 hr) 67-114 (8 hr) S02: 13-102 (24 hr) 13-22 (8 hr) N02: 6-28 (24 hr) 11-35 (8 hr) (II) Average: TSP: 187 (24 hr), 300 (8 hr) PM10: 67 (24 hr), 74 (8 hr) S02: 32 (24 hr), 27 (8 hr) N02: 18 (24 hr), 19 (8 hr) URBAIR-Kathmandu 109 Table 5: Ambient air quality monitoring in commercial area, medium traffic (Lainchaur DOMG) Pollutants Sampling Remark Date gIj/m3 hour TSP NO2 S02 PM10 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 16/111/93 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 SPM: 163-386 (24 hr) 221-781 (8 hr) PM10: 67-146 (24 hr) 64-151 (8 hr) NO2: 10-40 (24 hr) 12-36 (8 hr) S02: 13-26 (24 hr) 13-178 (8 hr) (II) Average: SPM 228 (24 hr), 367 (8 hr) PM1o: 103 (24 hr), 100 (8 hr) NO2: 19 (24 hr), 25 (8 hr) SO2: 17 (24 hr), 38 (8 hr) 110 Appendix 1 Table 6: Ambient air quality monitoring in low traffic (Thimi) Pollutants Sampling Remark Date ug/m3 hour TSP NO2 S02 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 1/12/93 124 327 451 36 132 8 2/12/93 115 752 867 20 45 24 4/12/93 81 94 175 30 57 18 5/12/93 263 288 551 116 69 8 Holiday 6/12/93 243 274 517 77 184 8 7/12/93 208 165 373 18 79 16 8/12/93 214 669 883 58 73 8 9/12/93 118 561 679 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 hr) 333-883 (8hr) PM1o: 111-117 (24 hr) 104-263 (8 hr) N02: 10-24 (24 hr) 13-116(8 hr) S02: 35-65 (24 hr) 15-184 (8 hr) (II) Average: TSP: 337 (24 hr), 521 (8 hr) PM1o: 115 (24 hr), 159 (8 hr) N02: 19 (24 hr), 45 (8 hr) S02: 49 (24 hr), 81 (8 hr) URBAIR-Kathmandu 111 Table 7: Ambient air quality monitoring in residential area (Maharajgunj) Pollutants Sampling Remark Date jigr3 hour TSP N02 SO2 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 7111/93 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 11/11/93 76 42 118 16 16 8 12111/93 56 59 115 10 13 24 Holiday 13/11/93 67 35 102 16 13 6 Holiday 14/11/93 44 19 63 12 13 8 16111/93 39 19 58 11 13 16 (I) Range TSP: 115-350 (24 hr) 63-118 (8 hr) PM1o: 51-126 (24 hr) 32-76 (8 hr) N02: 9-14 (24 hr) 12-19 (8 hr) SO2: 13-34 (24 hr) 13-13 (8 hr) (II) Average: SPM: 191 (24 hr), 93 (8 hr) PM10: 72 (24 hr), 49 (8 hr) NO2: 12 (24 hr), 15 (8 hr) SO2: 19 (24 hr), 13 (8 hr) 112 Appendix I Table 8. Amnbient air quality monitoring in residential area (Naya Baneshwor) Pollutnts Sampling Remark Date ug/m hour SPM NO2 S02 PM1o Particle Total 1/9/93 27 48 75 25 13 24 Rainfall 2/9/93 19 16 35 57 14 8 Rainfall 3/9/93 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: 75-270 (24 hr) 35-64 (8 hr) PM1o: 27-161 (24 hr) 19-43 (8 hr) S02: 0-13 (24 hr) 13-14 (8 hr) N02: 0-25 (24 hr) 57-66 (8hr) (II) Average: SPM 200 (24 hr), 50 (8 hr) PM10: 113 (24 hr), 31 (8 hr) S02: 13 (24 hr), 14 (8 hr) N02: 25 (24 hr), 62 (8 hr) URBAIR-Kathmandu 113 Table 9: Ambient air quality monitoring in residential area (Jaya Bageshwori, Chabahill) Pollutants Sampling Remark Date jig/1n hour TSP NO2 SO2 PMio Particle Total 7/12/93 131 230 361 28 71 8 8/12/93 108 125 233 20 23 24 9/12/93 123 231 354 34 164 8 10/12/93 95 76 171 17 23 8 12/9/93 132 468 600 126 225 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 (I) Range TSP: 171-273 (24 hr) 307-361 (8 hr) PM1o: 95-132 (24 hr) 123-131 (8 hr) NO2: 17-341 (24 hr) 28-53 (8 hr) SO2: 23-41 (24 hr) 71-164 (8 hr) (11) Average: TSP: 228 (24 hr), 341 (8 hr), 267 (20 hr) PMIo: 112 (24 hr), 116 (8 hr), 123 (20 hr) N02: 49 (24 hr), 38 (8 hr), 37 (20 hr) SO2: 29 (24 hr), 119 (8 hr), 56 (20 hr) 114 Appendix 1 Table IO: Ambient air quality monitoring in industrial area (Balaju, BID) Pollutants Sampling Remark Date _____ hour TSP NO2 S02 PMio Particle Total 1/9/93 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 17/9193 46 116 162 34 26 8 18/9/93 35 75 110 21 21 8 2/9/93 42 14 56 63 13 8 Rainfall 9/9/93 35 72 107 8 13 8 5/9/93 n.a. n.a. n.a. 42 13 6 Rainfall (I) Range TSP: 71-137 (24 hr) 56-162 (8 hr) PM10: 21-77 (24 hr) 35-46 (8 hr) S02: 12-21 (24 hr) 13-26 (8 hr) NO2: 11-71 (24 hr) 8-63 (8 hr) (II) Average: TSP: 108 (24 hr), 109 (8 hr) PM10: 40 (24 hr), 40 (8 hr) S02: 15 (24 hr), 17 (8 hr) NO2: 31 (24 hr), 34 (8 hr) URBAIR-Kathmandu 115 Table 11: Ambient air quality monitoring in industrial area (Patan, PID) Pollutants Sampling Remark Date ,u/m3 hour TSP N02 SO2 PM1o Particle Total 1/9/93 53 37 90 83 13 24 Rainfall 10/9/93 36 33 69 26 13 24 13t9193 53 49 102 12 13 21 Rainfall 2/9/93 64 61 125 69 13 .8 Rainfall 5/9/93 n.a. n.a. n.a. 80 13 8 Rainfall (I) Range TSP 69-102 (24 hr) 0-125 (8 hr) PMio: 36-53 (24 hr) 0-64 (8 hr) S02: 13-13 (24 hr) 13-13 (8 hr) N02: 12-83 (24 hr) 69-80 (8 hr) (II) Average: TSP: 87 (24 hr), 125 (8 hr) PM10: 47 (24 hr), 64 (8 hr) S02: 13 (24 hr), 13 (8 hr) N02: 40 (24 hr), 75 ( 8 hr) Table 12: Ambient air quality monitoring in Bhaktapur industrial area Pollutants Sampling Remark Date ig/n3 hour SPM N02 SO2 PM,o Particle Total 12/12/93 104 186 290 19 79 20 13/112/93 122 107 229 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 19/12193 169 625 794 78 101 8 (I) Range TSP: 159-290 (20 hr) 229-794 (8 hr) PM10: 94-131 (20 hr) 122-169 (8 hr) N02: 18-24 (20 hr) 21-78 (8 hr) S02: 38-79 (20 hr) 59-101 (8hr) PI) Average: TSP: 213 (20 hr), 512 (8 hr) PMio: 137 (20 hr), 146 (8 hr) NO2: 20 (20 hr), 50 (8 hr) S02: 58 (20 hr), 80 (8 hr) 116 Appendix 1 Table 13: Ambient air quality monitoring around Himal cementfactory Pollutant Sampling Remark Date jg'm3 hour SPM N02 SO2 PM1c Particle Total 15/12/93 157 373 560 38 45 24 16/12/93 147 158 305 17 61 24 17/12/93 127 1,093 1,220 131 238 3 18/12/93 215 329 544 54 120 8 19/12/93 194 230 424 58 65 24 (I) Range TSP: 305-560 (24 hr) PM,o: 147-194 (24 hr) N02: 17-58 (24 hr) S02: 45-65 (24 hr) (II) Average: TSP: 430 (24 hr) PM1o: 166 (24 hr) N02: 38 (24 hr) S02: 57 (24 hr) URBAIR-Kathmandu 117 Table 14: Ambient air quality monitoring in regional background control site (Tribhuvan Universit, Kirtipur) Pollutants Sampling Remark Date pgIma hour SPM NO2 SO2 PM1o 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 1112193 29 16 45 10 77 24 2/12/93 57 3 60 20 40 8 6/12/93 75 22 97 20 32 24 7/12/93 58 46 104 38 76 8 8/12/93 69 12 81 82 70 8 9/12/93 52 31 83 45 80 8 12/12/93 73 24 97 35 39 24 14/12/93 81 74 155 20 33 24 16/22/93 113 169 282 90 260 3 19/22/93 136 96 232 83 285 3 (I) Range TSP: 45-255 (24hr) 68-117 (8hr) PMio: 64-81 (24 hr) 19-83 (8 hr) N02: 10-35 (24 hr) 9-82 (8 hr) SO2: 13-77 (24 hr) 13-80 (8 hr) (II) Average: TSP: 94 (24 hr), 84 (8 hr) PM1o: 66 (24 hr), 52 (8 hr) N02: 18 (24 hr), 33 (8 hr) S02: 38 (24 hr), 42 (8 hr) I APPENDIX 2: AIR QUALITY GUIDELINES National air quality guidelines/standards have not yet been established in Nepal. WHO air quality guidelines and standards are listed in Table 1. Table 1: WHO air quality guidelines/standards Parameter 10 15 30 minutes 1 hour 8 hours 24 hours 1 year Year of standard minutes minutes S02 Pg/Mr 500 350 125d 50 1987 SO jg/m3 100-150 40-60 1979 BSb 4g/rm3 125a 50a 1987 BSb jig/m3 100-150 40-60 1979 TSP jg/m3 120a 1987 TSP ig/rni3 150-230 60-90 1979 PM1o jg/m3 70a 1987 Lead jig/m3 0.5-1 1987, 1977b CO mg/m3 100 60 30 10 1987 NO2 jig/M3 400 150 1987 NO2 jIg/M3 190-320c 1g77b 03 Fjg/M3 150-200 100-120 1987 0 jig/rM3 100-200 1978 Notes: 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. SPM measurement methods (WHO/UNEP 1992) BS (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 pjm in aerodynamic diameter): the mass of particulate matter collected by a sampler having an inlet with 50 per cent penetration at 10 jm aerodynamic diameter determined gravimetrically divided by the total volume sampled. TP (Thoracic particles, as PMio IP (Inhalable particles, as PMio). Source: World Health Organization/United Nations Environment Programme (1992). Urban Air Pollution in Megacities of the World. Oxford: Blackwell Publishers. 119 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 Malla (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,, VOC and CO2. Devkota attempted also to estimate emissions of benzene specifically, and of PAH from road traffic. The following comprehensive emission survey is based on the works of Devkota (1992) and Shrestha and Malla (1993). The JICA Study on Kathmandu Valley Urban Road Development (JICA, 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 Bohler, 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. 121 122 Appendix 3 Figure 1: Kathmandu Valley air quality modeling area 20 , ,^, ,, ( ,,, / ,s,, ,, ;,; ^~~~~~~~~~~~~~ Br bec H ldlunids _ 20 * - 5I s _* 5U ,* it / § .'' | Industrial amas _% 8 4' ,Ktndu '--':_ S " -; - - *5 1 5 10 15 20 1 I 1 125r 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 1 and Figure 2, with reference to the JICA transportation study. Further distribution into km2 grids was done subjectively, based on the distribution of villages within each square kilometer. URBAIR-Kathmandu 123 Table _ Populaion of "tafc zones as given inFiure 2 Zone 1991 Zone 1991 Zone 1991 Zone 1991 Zone 1991 Zone 1991 101 6,691. 201 25,925. 301 16,099- 401 10,985 501 21,273-. 601 31,919 102 8,288. 202 11,757- 302 9,794 402 15,015 502 32,270. 602 29,991 103 29,749. 203 15,300. 303 18,752. 403 26,878 503 21,148- 603 24,282 104 8,592. 204 28,019 304 16,477 404 29,291 504 29,626. 604 25,783 105 37,380 205 15,856 405 36,807- 106 24,831 206 20,346. 406 25,886 107 41,213 I 407 24,868 108 9,983. I 408 31,633. 109 20,329.* 409 33,674. 110 30,074 410 19,304. 111 19,491. 112 20,281 113 28,813 114 45,330 115 19,190. 116 19,208. 117 12,753. 118 32,068 _ _ _ _ SUM all zones 1,175,197 Source: JICA (1992). The resulting distribution of the total population is given in Figure 3. 124 Appendix 3 Figure 2: "Traffic zones" of Kathmandu Valley Sure: 408 JIA604 (1992). ] > 410 1,192~~~~~~~~~~~0 !~~~~~0 10 604-( | <= t~~~~~~~~~~0 Isource: JICA (1992). URBAIR-Kathmandu 125 Figure 3: Distribution of the Kathmandu Valley population within the km2 grids of the modeling area, 1990/91 (in tens of inhabitants) 1 2 3 4 5 6 7 a 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 J=21. .. . 68. 118. 186. 169. 169. 105.. 105. 174. 140. 105. 70. 52. 106. .. 71. 71. .158. J=20 Is. 1634. 65. 102. 135. 135. 174. 209. 209. 174. 174. 105. 35. 71. 106. 141. 79. 106. 79. 79. 79. 3=19 .35. 16. 16. 16. 16. 35. 65. 51. 85. 220. 174. 105. 315. 157. 123. 141. 71, 106. 71. 156. 102. 66. 156. 79. 158. J=18 .35. 53. 35. 35. 35. 35. 35. 272. 406. 278. 271. 464. 446. 156. 614. 438. 177. 247. 114. 102. 117. 156. 156. 156. 237. J=17 la1. 66. 88. 71. 68. 88. 35. 433. 406. 779. 490. 446. 446. 220. 673. 332. 141. 106. 117. 117. 117. 97. 167. 156. 316. 79. J316 . . 71. 71. 53. 71. 106. 71. 292. 693.1049. 913. 769. 560. 561. 112. 141. 177. 129. 117. 136. 63. 54. 16. 16'. 97. 97. J=15 .62. 124. 60. 64. 124. 141. 104. 98.2716.4546. 415.1231. 585. 522. 296. 526. 156. 117. 120. 72. 72. 81. 63. 45. 63. 72. J=14 . 155. 155. 124. 184. 133. 141. 371. 902.3164.2671.1329.1008. 710. 497. 369. 142. 154. 197. 236. 126. 61. 72. 72. 90. 69. 102. J=13 .124. 155. 155. 248. 229. 176. 276. 902.1219. SS9. 930. 969. 824. 785. 106. 146. 316. 372. 290. 144. 90. 90. 356. 134. 63. 125. J=12 .155 1866 246. 246. 191. 456. 162. 162. 694. 519. 646. 756.1365. 302. 110. 261. 448. 299. 251. 419. 319. 277. 693. 184 79. 93. J=11 .62. 1066 193. 197. 216. 323. 216. 296. 732. 944.2477.1121. 256. 125. 144. 272. 267. 229. 479. 664.12233 976. 498. 55. 62. 109. J310 .31. 112. 106. 216. 269. 132. 201. 146. 426. 506.1004. 841. 226. 228. 162. 171. 171. 149. 256. 126. 273. 64 866 62. 93. 125. 3= 9 . 54. 54. 162. 61 25. 96. 94. 219. 267. 383. 383. 171. 265. 226. 185. 214. 171. 171. 65 53. 65. 43. 93. 125. 93. 3. 6 12. 39. 395 52. 37. 49. 73. 67. 179. 27. 203. 155. 866 157. 342. 86 121. 64. 64. 43. 53. 32. 31. 31. 16. J.7 . 12, 12. 25. 49. 25. 37. 73. 90. 170. 161. 323. 434. 123. 189 866 114. 96. 21. 32. 32. 43. 21. B. 23. 6. 3= a 2S. 25 37. 31. 37. 49. 74. 22. 202. 166. 269. 136. 269. 101. 57. 57. 142. 53. 21. 21. 21. 21. 19. 16. 3= 5 .12. 49. 25. 49. 49. 49. .121. 242. 161. 99. 230. 109. 54. 72. 61. 29 1. 11 1 J34 . . .25. 37. 37. 27. 25. 37. .69. 215. 94. 106. 63. 72. 72. 109. 54. J-32 . . 6. 25. 12. 25. 31. 37. .67. 166. 161. 61. 54. 26. 36. 36. 3= 2 .,.12. 16. 37. 12. 36. 17. .11. 161. a1. 54. 61. 16. 3=1 I 6. 25. 25. 18. 18. 22. . 3. 27. 27. 1 2 3 4 5 6 7 6 9 10 11 12 13 14 15 16 17 16 19 20 21 22 23 24 25 26 27 The distribution between urban/rural populations is 62-3 8 percent for Kathmandu district, 53-47 percent for Lalitpur district, and 3 5-65 percent for Bakthapur. 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 amnount varies between about 1 1,000 and 28,000 kl/yr. It appears that Shrestha arrived at his number by asking a number of vehicle operators about how much gasoline they use annually, and using the average 126 Appendix 3 Table 2: Fuel sale and consumption data (liquid,fuels) , kl, for Kathmandu Valley Gasoline Sector HSD Sector LDO Sector SKO Sector (MS) Shrestha and Malla (1993) 28,015 T 22,955 T 359 T 35,000 H Estimated 564 1 315 1 Consumption, 1992/93 702 C Total 28,015 23,519 359 36,045 ...................... .............................................. .............. ........................... ............. ............................................................................. ............. Devkota (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, 1992/93 ('Fuel oil") Mathur (1993) 14,250 T 27,000 T? 1990 ("Diesel") Note: T,traffic; H, household; HSD, high speed diesel; SKO, kerosene; I, industrial; C, commercial; LDO, light diesel oil. Sources: Shrestha and Malla (1993); Devkota (1992); Gautam et al. (1994); Mathur (1993). number thus arrived at for the entire operating vehicle fleet. He arrived at the operating vehicle fleet by assuming Table 3: Fuel consumption data (solidfuels), theopratngvehcl fletbyassuming Kathmandu Valley (1O' tlyr) that a certain fraction of the registered Shrestha ale (103 tJyr) vehicles in each category is actually in 1992h93 D19e9vot normal operation (Table 6). On the 1992w93d1920/91 basis of fuel efficiency figures, he also 17.2 1 arrived at average vehicle-kilometers 0.5 C traveled annually (and daily) per Coal 4.81 vehicle (see Table 7), which seems Charcoal 0.5 H reasonable. Shrestha's gasoline 0.6 C consumption data was used in the Agricultural residue 45.4 H 35-60 1 followng anaysis.Animal waste 3.0 H following analysis. Note: C, commercial; H, household; I, industrial (excl. brick and Motor diesel (HSD) may be used cement). for other purposes than for road Sources: Shrestha and Malla (1993); Devkota (1992). vehicles. Three of the references give figures which agree fairly closely with HSD consumption Table 4: Estimated annualper capita consumption of fuels in Urban Devkota's much and rural areas of Kathmandu Valley in 1992/93 higertotal number Area Fuelwood Kerosene (I) Agricultural Animal Char- LPG higher total number (kg) Residues (kg) Waste (kg) coal (kg) may reflect, if (kg) correct, that HSD is Urbana 93.5 34.5 7.5 o.o 0.8 6.3 used to a large extent Ruralb 115.0 23.7 75.74 5.7 0.0 0.0 also for other Source: (a) Shrestha and (b) Malia (1993). purposes, e.g. industrial/commercia 1. Shrestha does not report much use of HSD in industry. URBAIR-Kathmandu 127 Table 5: Fuel consumption in the cement and brick industry (tons/year) Kathmandu Valley Brick Cement Bull's trench (NESS) Chineseb Himal avel kiln no. of kilns Total (Shresta) (Shrestha) 1994 1992/93 1992193 Coal 318.8 130 41.444 4.093a 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 a Consumption in HHBF and BBF bnck factores. b Devkota reports 1 ton of coal per 8,000 bncks. Source: Shrestra (1993); NESS (1995). Table 6: Registered vehicle population, Bagmati Shrestha and Malla RONAST JICA Devkota Gasoline/ Reg. Operating Operating Reg. April Reg. 90191 "Number 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 Sources: Shrestha and Malla (1993); RONAST (1993); JICA (1992); Devkota (1992). 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 Malla (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. 128 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, 3,000-4,000 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 Himal 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 ACTIVITY 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 JICA Urban Road Development Study (JICA, 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. Shrestha's estimate of the fraction of vehicles actually operating is also given. Considering that the data represent different years, there is fair agreement between the sources. One notable discrepancy is that Shrestha and RONAST give a substantially lower number of registered buses and trucks than JICA and Devkota. The former are the most recent data. Table 7 gives Shrestha's data on average fuel consumption, fuel efficiency and resulting average kilometers traveled per vehicle class. Shrestha's figures in Table 8 give the traffic activity data for the year 1992/93. This total traffic activity corresponds to the total consumption of gasoline and motor diesel in traffic as given in Table 2 (Shrestha and Malla 1993). The average vehicle composition of the traffic has also been reported by others (Table 9). Table 7: Estimated annual average fuel consumption and average number of kilometers traveled per vehicle in transport sector by vehicle types in 1992/93 Vehicle type Fuel type Sample Mean of average fuel Fuel efficiency Average km traveled per size consumption vehicle (I) (km/l) (1110 km) Annually 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 Source: Shrestha and Malla (1993). URBAIR-Kathmandu 129 There may be some discrepancy between the various authors regarding the classification of vehicles. The main discrepancy Table 8: Traffic activity in in the results of Table 7 is that Shrestha has a very high Kathmandu, 1992-93 relative number for MC activity, at the expense of Tempo (3- Vehicle fuel veh- km/yr (millions) wheelers) activity. His sum for Tempo and MC is, however, Gasoline in fair agreement with other sources. The problem seems to Cars, taxis 170.8 be that Shrestha has based himself on a too low average 3-wheelers (TC) 25.8 , . . ,. ^ . > . ~~~~~~~~~2-wheelers (MC) 434.4 driving distance for the Tempos and too long distance for the Subtotal 631 0 M C s. ........................................ ...................... Diesel The data give basis for the estimates in Table 10 of Jeeps 62.4 average vehicle composition of Kathmandu Valley traffic. Minibuses 12.3 The vehicle composition in the traffic varies substantially Buses 2.8 between roads. Streets in the center have very high Trucks 27.1 tempo/MC percentage, while the proportion of trucks is high Tractors 20.2 on the Ring Road (10-15 percent). Subtotal 1357 In this study, account is not taken of this variation. The Total 766.7 average composition is used as a basis for calculating composite vehicle emission factors for gasoline and diesel separately. The traffic data has been used to distribute the traffic on the main road system as shown in Figure 4, which gives the estimated annual average daily traffic (AADT) numbers on some of the main roads. Table 9: Composition of vehicle categories in Kathmandu traffic (JICA) (Girl) (Devkota) (Shrestha and Malla) Daily Rush-hour Rush-hour Daily PC/taxi (G) 32.5 (20.0+12.5) 20.4 25 22.3 Jeep (Pickup) (D) 7 8.1 Minibus/trolley (D) 8.1 14.6 8 2.0 Trucks/tractors (D) 4.9 2.3 (ihcl. bus) 4 6.2 Tempo (G/D) 21.8 62.6 22 4.8 MC (G) 30.0 22 56.6 Sources: JICA (1992), based upon 29 counting locations, 1992.; Giri (1993), based upon 33 counting locations, 1993; Devkota (1992), based upon 22 counting locations, 1992; Shrestha and Malla (1993), based upon an analysis of total traffic activity based on fuel consumption, annual average driving distance and number of operating vehicles. Table 10): Average vehicle composition of Kathmandu Valley traffic Car/taxi 25% Jeep/minibus/tractor 15% Bus 2% Truck 5% Tempo (TC) 25% Motorcycle (MC) 28% 130 Appendix 3 Figure 4- Main road system of Kathmandu Valley with some traffic data used in this study 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 131 * 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. Table 11: Emissionfactors usedfor URBAIR, Kathmandu Valley, forfuel combustion, refuse burning and road vehicles TSP PM1oJTSP S02 NOx %S max. Fuel combustion kgIt) Residual oil (OF): ind./comm. 1.25S+0.38a 0.85 20S 7 4 Distillate oil: ind./comm. 0.28 0.5 20S 2.84 HSD: ld (HSD, LDO): residential 0.36 -+ 1.6b 0.5 20S 2.6 LDO: 1.8e LPG: ind./dom. 0.06 1.0 0.007 2.9 0.02 Kerosene: dom. 0.06 1.0 17S 2.5 0.25 Natural gas: utility 0.061 1.0 20S 11.3 . f ind./dom. 0.061 20S 2.5 Wood: dom. 15 0.5 0.2 1.4 Fuelwood: ind. 3.6 0.5 Coal: dom./comm. 10 0.5 1.8f Charcoal: dom/comm. 20 0.5 Agn. residue 10 0.5 Anim. waste 10 0.5 Refuse buming, open 37 1 0.5 3 Road vehicles (glkm) A B Gasoline: Cars 0.2 1 2.7 83 Octane (RON) 0.25c MC/TC 0.5 1 0.07 93 Octane (RON) 0.20 Diesel: Cars, jeeps, tractors 0.6 0.9 1 1.4 1d Minibuses, tempos 0.9 1.5 1 13 Buses, trucks 2.0 3.0 13 a) S: sulfur content, in % b) Well -* poorly maintained fumaces c) Actual S content in 87 RON gasoline, according to IOC Ltd quality certificate: 0.009% d) Actual S content, according to IOC Ltd quality certificate: 0.20% e) Actual S content, according to IOC Ltd quality certificate: <1% 0 NESS (1995) A Used for Manila, Jakarta, Bombay B Proposed and used for Kathmandu Valley. The emission factors for Nepal/ Kathmandu conditions may differ substantially from those 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 to. calculate exhaust particle emission factors. They indicate, however, that the real particle 132 Appendix 3 emission factors for Kathmandu Table 12: Emission factors (kg/ton) for brick and cement industries. vehicles may be TSP PMioITSP SO2 NO, CO %S F Pb substantially Brick industries higher than Bull's trench those given in per ton of bricks 9.42 0.25 6.06S 1.18 1.19 0.5 Table 1 1. per ton of fuel Also, the - coal (bituminous) Also, the - wood and bark particle - lignite emission factors Chinese (Hoffman Bhatta) for the various Portland Cement uses of solid Dry process, uncontrolled fuels in Dry process, kiln 128 0.42 5.4a+ 3.6Sb 1.4 0.06 Clinker cooler 4.6 0.09 Kathmandu, Dryers, grinders, etc. 48 such as a) From mineral source. b) From coal. fuelwood, coal, Source: USEPA (1985). 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 g/km, was based upon some 20 percent of the trucks being "smoke belchers", with an emission factor up to 8 g/km. Observations in the Kathmandu traffic and the smoke testing results from the KVVECP study (Table 13) indicate that more than 75 Table 13: Summary of diesel vehicle smoke percent of the vehicles in each class have test results (Ref: KVVECP study) smoke emissions of more than 75 HSU, and Vehicle type Distribution (%) of tested vehicles in some 55 percent have emissions over 85 HSU. smoke (HSU) level ranges The test is done for free acceleration of the <65 6675 76-85 8695 96-100 engine and does not represent the smoke Tempo 2 14 16 55 13 emissions during driving. However, there is a Jeepsst.wgn. 2 7 265 59 6 correlation between smoke emissions during Mini buses 4 5 28 56 7 free acceleration and during normal driving. Mini trucks 13 14 24 44 4 In Table 14, emissions in g/km are Buses 4 13 44 39 0 estimated from HSU units, based on certain Trucks 4 8 40 44 4 conditions. These g/km figures represent Average 7 10 26 51 6 estimates of emissions during "smoking HSU: Hartridge Smoke Units. conditions." Source: KWECP (1992). For loaded buses and trucks in the Kathmandu topography, it may be a valid estimate that smoking conditions for the vehicle occur more than 50 percent of the time of operation. URBAIR-Kathmandu 133 Combining data from Tables 13 and 14, the average particle emission during "9smoking conditions" for Kathmandu trucks Table 14: Partcle emissionfactor (glkmJ "smoingconitins"for athand trcks for diesel trucks, estimated from HSU data is 4.3 g/km for light truck (0.2 1 fuel/km) Particle emisonS and 8.6 g/km for a heavy truck (0.4 1 Particle emissions fuet/km). gnkMa g1kMb fuel/kin). ~~~~~~~~~~~~Hartridge gIm3 40 I engine Light Heavy Assuming that the average specific fuel Smoke 2,000 rpm truck truck consumption by trucks and buses in Units 40 kmlh 0.2 1/km 0.4 Ilkm Kathmandu Valley is 0.3 1/km, that 30 0.13 1.6 0.8 1.6 "smoking conditions" for the total traffic 65 0.42 5.0 2.5 5.0 activity of the Valley occur for 25-50 75 0.55 6.6 3.3 6.6 percent of the time, and that the emission 85 0.72 8.6 4.3 8.6 factor for the te, an th time is I g/kn the 95 .o 12.0 6.0 12.0 factor ftrsa) Based upon 12 m3 air/km (4 1 engine, 2000 rpm, 40 average truck/bus emission factor for km/h). Kathmandu is calculated to 2.5-3.7 g/km. b) Based upon 0.03 g fuel/g air. This figure is supported by the emission factor presented by Mathur in the KVVECP Summary Report, namely 11 kg particles/1,000 liters of diesel, corresponding to 3.7 g/km for a fuel consumption of 0.22 1/km. Table 13 shows that the HSU 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 Himal Cement factory are shown in Figure 1. The brick industry. The brick production data used in this study is shown in Table Table 15: Brick production data 15. Area No. of Total production Typical stack units million bricks heightWdiam Bull's Trench kilns. The emissions from 1993 1994 (m) these kilns have been estimated most Bull's Trench (Thapa et al. 1993; NESS, 1995) recently by the NESS study (1995). The Kathmandu 15 24.75 recently bthNELalitpur 74 209.5 10/0.5 emissions originate mainly from the Bhaktaur 41 127.0 combustion of the fuel used, the most Total 130 361.0 450 important of which are coal, fuelwood Chinese (Thapa et al., 1993) and rice husk. Handling of the bricks Lahtpur 5 53.00 65/1.65 gives rise to particle emissions Bhaktapur 1 20.00 Total 6 73.00 Sources: Thapa (1993); NESS (1995). 134 Appendix 3 (resuspension). All fuels give 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 1.77 percent respectively (Table 16). Table 16: Coal analysis results, 1994 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 Source: NESS (1995). The emissions were calculated by 3 methods: * Based on brick production, using USEPA AP42 emission factors (the weight of a brick is approx. 2 kg). * Based on fuel consumption, using USEPA AP42 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: Total emissions from Bull's Trench kilns in (Table 17) show wide Kathmandu Valley 1994 (tonslyr) discrepancies between the Method Particles (SP) S02 CO VOC NOX F methods: A. Based on bnck 15,862 6,435 1,442 405 631 451 * Particles: Methods B production and C agrees fairly well B. Based on fuel 5,144 1,536 2,547 524 119 while method A gives combustion C. Based on emission 4,438 4.8 16,384 2,373 0.8 very large emissions. measurements, India Incidentally, using the Source: NESS (1995). 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. * SO2: The methods disagree basically. Method C results indicate that the sulfur released from the coal is absorbed on the brick surfaces. * NO,: 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 (Hoffinann 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 HIHBF 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 HBBF factory). In addition, 15 tons of fuelwood is used annually for firing, which is URBAIR-Kathmandu 135 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 Himal 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 m/s * Flue gas temperature: 1200C * 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 Table 18: Cottage industries in Bhaktapur, 27 units. He included the "Cottage industries" Kathmandu Lalitpur Bhaktapur numbers of cottage industries shown in (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 Al, 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. 136 Appendix 3 Devkota estimated the amount of rice husk used by potters in up-draft kilns. The annual demand per potter may be 12,000-15,000 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 of 7.83 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 HMG/Ministry of Industry, RONAST (1994) reports the TSP emissions from distributed industries in Table 19. Table 19: Industrial TSP enmssions Type of industry No. of units TSP in tonslyr Beverages distilledes 3 5 Textile processing 85 8 TOTAL EMISSIONS Knitting mills 25 5 Carpetandrugs 1109 144 Table 20 gives the estimated emissions of TSP, Animal feed 13 063 PMIO, S02 and NO, associated with the various Plastic products 38 8 source categories, fuels, vehicle types and Soap and detergents 4 5 industries. Marbles 1 67 In the previous text, the quality of the data Dry battery 1 880 sources and the emission numbers have been Source: RONAST (1994). 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 PMIo (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 137 The emissions inventory of Table 20 Table 20: Estimated emissionsfrom air itself, together with observations in the pollution sources in Kathmandu Valley1 1992/93 Valley, indicate the most important sources (tnslyr as shown in Table 21. TSP PM,. S02 Vehicles Gasoline: Cars/taxis 38.4 TC 67.5 - 4.2-105' SPATIAL EMISSION DISTRIBUTION MC 107.5 Diesel: Jeeps 68.4 Minibuses 22.5 The total emissions from each source Buses 45.0 78-390' category have been distributed within the Trucks 114 km2 grid net based on: Tractors 21.6 * the actual location of point sources (e.g. TC 85.8 Hinial Cement Fac y bSum vehicle exhaust 570 570 82495 Hima CeentFacory,brik klnsand Resuspension from roads 1,530.0 -400 0 industrial areas; see Figure 1) Fuel combustion ---------------- * the population distribution Industral/commercial - the cooking practices of the urban and (excl. brick/cement): 61.9 31 rural population Fuelwood - the traffic activity distribution. Coal 48 24 172 Charcoal 20 10 The traffic activity was distributed as LDOFO? 1.8 2 follows: Kerosene/LPG 0.1 * The traffic activity (veh.km/yr) on the Agri. residue 450.0 225 roads with known traffic count was Sum industrial/commercial 582.0 292 calculated (vehicles x road length), and Domestic: Fuelwood 1,832.0 916 distributed in the grid system according Agri. residue 454.0 227 to the actual location of the road Anim. waste 30.0 15 KerosenelLPG 2.3 2.3 sections. Charcoal 10.0 5 3 This traffic activity accounted for about Sum domestic 2,328.0 1,165 50 percent of the total traffic activity, as Brick industry calculated from the fuel consumption Bull's Trench 5,000.0 1,250 4.8- (Shrestha and Malla, 1993). 4,465b * The difference was distributed within Chinese 180.0 45 the grid net, proportional to the HiSum bck 5,180.0 1295 Himal Cement: Stack -2,000.0 -400 615 population distribution, with an Diffuse dust -4,000.0 -400 additional weight put on the highly 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 a) High value: Based on max. allowable S content composite emission factors for gasoline Low value: Based on actual S content, accordng to IOC Ltd. and diesel vehicles respectively, by certificate and diesel vehicles respectively, by b) NESS (1995): Estimates based on different methods. combining the emission factors of Table 11 and the average vehicle composition in Table 10. 138 Appendix 3 Those composite emission factors were calculated to be as Table 21: Important parficulate sources follows: TSP PM1p * gasoline: 0.39 g/km, Roadside * Resuspension * Gasoline exhaust * diesel: 1.65 g/km. pollution * Diesel exhaust * Resuspension The esnGeneral * Domestic fuel combustion * Domestic fuel combustion The emissions from the Bull's population * Brick industry (mainly Bull * Brick industry (mainly Bull's trench kilns were distributed in exposure Trench) trench) the grid net according to their . Resuspension * Vehicle exhaust actual location. An average . Resuspension emission figure for each kiln Reduced * Bull's trench brick kilns was calculated, and the visibility * Domestic fuel combustion emissions from each grid Vehicle exhaust square calculated by multiplying this average emission figure by the number of kilns in the square. Figures 5-9 give the resulting TSP emission distributions from each of the area-distributed source categories, as kg/h (averaged over the winter half-year, October-March, 1992/93. The following ratios are used for PM1o/TSP: 3 Vehicle exhaust -- 1.0, - Resuspension from roads -- 0.25, - Fuel/refuse combustion -- 0.5, - Brick industry -- 0.25, 3 Himal Cement, stack -- 0.2, D Himal Cement, diffuse -- 0.1. c Z 4 - 4 (4 4" to 0% 4 o to 0 4 (4 (4 t. (4 4 4j 4 to 4 - °~~~~~~~~~~ (, .4 .% (4 @ ( U4 V. W4 N4 75 i- _ ^ N N w a~~~~~~ * a4 4 :o 0 44 m w _a Ma_ . r N r ^ N ^ N ^ m m w 0 (4 .4r(4 (4 (4 (4 (4 ( a (4 . 4 . 4 ( No mo to C to .4 fl ( 0 m4 oo 44 w o N _ No to We a to a Wo U W > (4 a ,o (4 (4 S w W 0 ^ ^ w < q W . Qa (4 to to O -J to a U t o4 8 ~ ~ ~ ~ £ U4 (4 ( w o w4 q5 U 0W U o u (4 to a r a - 4 -a (4 to to (4 a to a a £4 to (4 . . tD ~ ~ ~ ~~( _4 (4 a, (4 a _o to t , - -o " (4 (4 " > (0 q 4 (4 a to o (4 4 to .* to to w to * (4 to t ' a ro a O _ " " w " ~~~~(4 4 (4 to (4 (4_ w 8 W a ~~ ~ ~ £4 n a a 4 .4 (4 (4 to (4 a Uo a O4 _4 ( o .o .4 . .o .. to to to 0 -4 r4 0 to to (4 a . bJ . . . . . N WA , - - 9(4r U. ro _ (4 (4 (4r N (4 (4 (4 (4 .o eo (4 (4 W4 aC (i W(4V _ (4- - (4 (4 .o (4 c. . . a . . . . . . * * .* t - . . . . 0 t. . £. . 5. 5. t. . C. . . C. . C. C. 0. . . C. . C. %~~~~~~ . . . . . . . . . . . . . . , . . . . . . - - . - . . . . . . . . . .4 - . a . . . .3 .- Ca r . - - ^ r3 a r o - a . . - ^ r . . . . . . . . . . o * r r r r rr - - a r.- a - - .3 tO . .*.i .3... . - .O.S. .~~~~~ - - - a a -J r - - ,O .0 - t o 4 r 43 4 a .3 .3 * - a a .. r . .3 UI . ., a - . . a . . . 4 . U . - a 3 . . . . . . . . 4 , a £ o .3 r r - .3 '. .3 .3 a .4 o 4 r 4… ……… .4 0) . . . a r . .i " s e , , "~ ~ ~ ~~~~~0 . . .i .30.* .a.. W~ rrW> 9) . .3 .. .3 .3 r r, a a o a -3 a. .3 .3 . , , ,.. . o . o . s . a 0 a r -, > w "~~~~~~~~4 .3 .0 .3 .i . r a ? ° .3~ re, N Nl r3 ID 44 a .4 a a a w '0 r5 .3 '. .3 .3 .4 .3 . ) .3 .3 .3..r~r-,"WwS".- .l 5. a r 3 - .3 .3 i ,x URBAIR-Kathmandu 141 Figure 7: TSP emission from domestic and industrialfuels, (excl. brick and cement industry), Kathmandu Valley 1 2 3 4 5 6 7 a 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 J-21 .302. 529. 831. 755. 755. 467. 467. 779. 623. 467. 312. 233. 473. . . 315. 315. . 706. J.-20 . 78 .151. 378. 453. 604. 604. 779. 934. 934. 779. 779. 467. 156. 315. 473. 630. 353. 483. 353. 353. 353. J.-9 . 158. 79. 79. 79. 79. 154. 381. 227. 378. 984. 779. 467.1406. 703. 590. 629. 315. 473. 315. 696. 45S. 391. 706. 353. 706. J718 . 158. 236. 158. 158. 159. 158. 158.1214.1811.1242.1209.2070.1992. 704.1817.1956. 798.1103. 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. 521. 521. 433. 746. 706.1412. 353. J.-16 . 315. 315. 236. 315. 472. 315.1305.1993.2341.2038.3431.2500.2503. 500. 630. 789. 575. 521. 616. 281. 241. 90. 80. 433. 433. J.15 . 277. 554. 355. 296. 551. 630. 472. 435.2693.4510.1854.2748.2612.2332.1330.2346. 698. 521. 536. 321. 321. 361. 291. 200. 281. 321. J.14 . 692. 692. 554. 831. 592. 630.1657.2014.3138.2649.2966.2249.3170.2217.1647. 633. 689. 877.1052. 562. 361. 321. 321. 401. 396. 457. J.13 . 554. 692. 692.1109.1067. 788.1231.2014.2721.2495.2076.2207.1840.3503. 475. 650.1413.1667.1296. 642. 401. 401.1S98. 600. 369. 556. .J-12 . 692. 831.110.1108. 854.2036. 721. 721.3096.2315.2893.3385.3091.1346. 492.1167.2000.1333.1121.1872.1425.1238.3094. 929. 347. 417. J-31 . 277. 831. 860. 879. 962.1443. 962.1322.3269.210D.5530.2502.1142. 558. 643.1215.1191.1024.2137.1928.2752.2179.2221 243. 278. 487. J-10 . 139. 499. 481. 962.1203. 591. 899. 658.1912.2258.2240.1876.1017.1017. 911. 763. 763. 667.1144. 572.1218. 286. 383. 278. 417. 556. J. 9 . . 241. 241. 721. 361. 110. 439. 420. 978.1283.1709.1708. 763.1272.1017. 826. 953. 763. 763. 381. 238. 391. 191. 417. 556. 417. J. . . . 55. 175. 175. 230. 165. 220. 327. 300. 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. 721.1441.1937. 548. 844. 382. 508. 429. 95. 143. 143. 191. 95. 35. 104. 35. J. 6 . . 110. 110. 165. 137. 165. 220. 329. 100. 900. 840.1200. 604.1291. 450. 254. 254. 636. 239. 95. 95. 95, 95. 83. 70. J. 5 . . . 55. 220. 110. 220. 220. 220. . 540.1080. 721. 441.1028. 484. 242. 323. 271. 127. . 48. 48. 48. J. 4 . . . 110. 165. 165. 165. 110. 165. . 310. 960. 420. 490. 282. 323. 323. 484. 242. J. 3 . . . 27. 110. 55. 110. 137. 165. . 300. 840. 721. 360. 240. 162. 162. 162. J. 2 . . . 55. 92. 165. s5. 160. 77. . 50. 721. 360. 240. 360. 91. J. 1 . . . 27. 110. 110. 82. 82. 100. . . . 60. 120. 120. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 l 19 20 21 22 23 24 25 26 27 Note: Winter half year emission, 1992/93. Constant emission, calculated as kg/hour. Unit: kg/hour per km2 grid. 142 Appendix 3 Figure 8: TSP emission.from Bull's trench brick kilns, Kathmandu Valley 1 2 3 4 5 6 7 8 9 10 11 12 13 14 IS 16 17 18 19 20 21 22 23 24 25 26 27 . 1=21 .............. J.20 3=19 J.1S J=15 J=14 .1740. J=13 J312 .2610. .2610.1740. .2610.4350. 870. .3480.1740. J.11 .5220. 870.. . .4350. 870. 870.1740. .3480. J=10 .2610. J. 9. .2610. .4350.1740.1740. .1740. 870. .3480.1740. J= B .2610.3480. 870.5220. 870. .1740. J. 7 . . . . . . . . .2610.6960.2610.5220.6960. J3 6 .2610.8700. J. S .2610. 870. j- 4 870. 870. 3. 2 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Note: Winter half year emission, 1992/93. Constant emission, calculated as kg/hour. Unit: kg/hour per km2 grd. URBAIR-Kathmandu 143 Figure 9: TSP emission from Chinese (Hoffman Bhatta) brick kilns, Kathmandu Valley 1 2 3 4 5 6 7 a 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 J.21 J.20 J-18 J=17 J7-16 J=15 J314 J713 J712 J.11 J7.10 J- 9 595. J. 8 J. 7 595. 1190. J. 6 595. J' J3.3 J.72 J.1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Note: Winter half year emission, 1992/93. Constant emission, calculated as kg/hour. Unit: kg/hour per km2 gnd. REFERENCES Bhattarai, M.D. (1993). "Industrial Contribution to Air Quality." Paper presented at the Urban Air Quality (URBAIR) Workshop, Kathmandu. Devkota, S.R. (1992). "Energy Utilization and Air Pollution in Kathmandu Valley, Nepal." Thesis EV-9209, Asian Institute of Technology, Bangkok. Gautam and Associates. (1994). "Study on Automobile Fuel, its Import, Supply, Distribution and Quality Assurance in Nepal." Gautam and Associates, Consulting Engineers, Kathmandu. 144 Appendix 3 Gram, F. and T. B0hler. (1992). "User's Guide for the "Kilder". Supporting Programs." Norwegian Institute for Air Research (NILU), Lillestr0m. Japanese International Cooperation Agency (JICA). (1992). "Kathmandu Valley Urban Road Development." Study for His Majesty's Government of Nepal. Kathmandu, Ministry of Works and Transport, Kathmandu. Nepal Environmental and Scientific Services (NESS). (1995). "Assessment of the Applicability of Indian Cleaner Process Technology for Small Scale Brick Kiln Industries of Kathmandu Valley." NESS, Kathmandu. Royal Nepal Academy of Science and Technology (RONAST). (1994). "Reports from the Data Collection for the URBAIR Kathmandu project." RONAST, Kathmandu, and NILU, Kjeller. Shrestha, R.M. and S. Malla. (1993). Energy Use and Emission of Air Pollutants: Case of Kathmandu Valley. Asian Institute of Technology, Bangkok. Thapa, S., S.S. Shrestha, and D. Karki. (1993). "A Survey of Brick Industries in the Kathmandu Valley." ENPHO, Kathmandu. APPENDIX 4 EMISSION FACTORS, PARTICLES INTRODUCTION Emission factors (amount of pollutant emitted per quantity of combusted fuel per kilometer driven, or per produced unit of product) are important input data to emissions inventories, which again are essential input to dispersion modeling. There is limited information on emission factors for Asian cities. For the purpose of the URBAIR study, references on emission factors were collected from the 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 VEHICLES 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 emissions standard and emissions 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 URBAIR 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. 145 146 Appendix 4 COMMENTS Table 1: Emissionfactors (g/kmJ)forparticle It is clear that there is not a very solid basis of emissions from motor vehicles actual measurements on which to estimate Fuel and Vehicle Particles (glkm) Reference particle emission factors for vehicles in South- Gasoline East Asian cities. The given references Passenger cars 0.33 USEPAMWHO represent the best available basis. Comments 0.10 VECP, Manila 0.16 Indonesia (Bosch) are given below for each of the vehicle 0.07 Williams classes. Trucks, utility 0.12 VECP, Manila 0.33 USEPA Gasoline: USEPA * Passenger cars: Fairly new, normally well Trucks, heavy duty 0.33 USEPA maintained cars, engine size less than 2.5 3-wheelers, 2 stroke 0.21 USEPAIWHO . without 3-wycaalyt,rnMC 214 stroke 0.21/ USEPA/NHO l, without 3-way catalyst, running on 2.00/ VECP, Manila leaded gasoline (0.2-0.3 g Pb/l), have an 0.21/0.029 Indonesia VWS emission factor of the order of 0.1 g/km. 0.28/0.08 Weaver and Chan Older, poorly maintained vehicles may Diesel have much larger emissions. The Car, taxi 0.6 VECP, Manila US EPA/WHO factor of 0.33 g/km can be 0.45 USEPAMWHO used as an estimate for such vehicles. 0.37 Williams 3 Utility trucks: Although the VECP study Trucks, ulity 0.93 VECP, Manila (Manila) uses 0.12 g/km, the EPA factor Trucks, heavy/bus 0.75 WHO of 0.33 g/km was selected for such 1.5 VECP, Manila vehicles, taking into account generally 0.93 USEPA poor maintenance in South-East Asian 1.2 Bosch cities. 2.1 Williams Note: Relevant as a basis for selection of factors to be used * Heavy duty trucks: Only the USEPA has inSuhEs Asa cte. In Soutni-East Asian cibies. given an estimate for such vehicles, 0.33 g/km, the same as for passenger cars and utility trucks. * 3-wheelers, 2 stroke: The USEPA and WHO suggest 0.2 g/km for such vehicles. * Motorcycles, 2 stroke: The Weaver report Table 2: Selected emission factors supports the 0.21 g/km emission factor suggested . (g/km) for particles from road vehicles by USEPAIWHO. In the VECP Manila study a used in URBAIR factor of 2 g/km is suggested. This is the same Vehicles class Gasoline Diesel factor as for heavy duty diesel trucks, which Passenger cars/taxies 0.2 0.6 seems much too high. Utlity vehiclesAight trucks 0.33 0.9 Visible smoke emissions from 2-stroke 2- and 3- Motorcycles/tricycles 0.5 wheelers is normal in South-East Asian cities. Trucks/buses 2.0 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. URBAIR-Kathmandu 147 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 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 g/km of USEPA/WHO 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 USEPA and the VECP Manila study give similar emission factors, about 0.9 g/km. * Heavy duty trucks/buses: 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. Table 3: Emission factors for oil combustion FUEL COMBUSTION (kg/m3) Emission factor Uncontrolled Controlled Oil. The particle emission factors Utlity boilers suggested by USEPA (AP 42) are taken Residual ola) as a basis for calculating emissions from Grade 6 1.25(S)+0.38 xO.008 (ESP) combustion of oil in South-East Asian Grade 5 1.25 xO.06 (scrubber) cities. The factors are given in Table 3. Grade 4 0.88 xO.2 (multicyclone) Industrial/commercial boilers Residual oil (as above) xO.2 (multicyclone) Distillate oil 0.24 Residential fumaces REFERENCES Distillate oil 0.3 S: Sulfur content in % by weight. Baker, J., R. Santiago, T. Villareal, and a): Another algorithm for calculating the emission factors is as M. Walsh. (1993). "Vehicular follows: 7,3xA kg/m3, where A is the ash content of the oil. Source: USEPA (1985). 148 Appendix 4 Emission Control in Metro Manila." Draft final report. Asian Development Bank (PPTA 1723). Bosch, J. (1991). "Air Quality Assessment in Medan." From Medan Urban Transportation Study. 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 One: Rapid Inventory Techniques in Environmental Pollution. Geneva: World Health Organization (WHO). Larssen, S. and J. Heintzenberg. (1983). "Measurements of Emissions of Soot and other Particles from Light Duty Vehicles." NILU, Lillestrom. Rajbahak, H.L. and Joshi, K.M. (1993) "Kathmandu Valley Vehicular Transportation and Emission Problems. Metropolitan Environment Improvement Program (MEIP)." Urban Air Quality Management Workshop (URBAIR). U.S. Environmental Protection Agency (1985) Compilation of Air Pollutant Emission Factors, 4th ed. Supplement A. Research Triangle Park, NC: Environmental Protection Agency AP-42. Weaver, C.S. and L-M. Chan. (1993). "Motorcycle Emission Standards and Emission Control Technology." Engine, Fuel, and Emissions Engineering, Inc., Sacramento, CA. Williams, D.J., J.W. Milne, D.B. Roberts, and M.C. Kimberlee. (1989). "Particulate Emissions from 'In-Use' Motor Vehicles - I. Spark Ignition Vehicles." Atmos. Environ. 23:2639- 2645. Williams, D.J., J. W. Milne, S.M. Quigley, D.B. Roberts, and M.C. Kimberlee. (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 (TSP emissions, 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 by modifying existing technology, - reduced traffic activity/fuel consumption. 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, g/km for vehicles, kg/m3 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, fT, f-: Control measures. Relative reduction of emission factor (fq), amount (fF, I) 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 149 150 Appendix 5 Figure 1: URBAIR spreadsheetfor emissions calculations Emissiorn Amount Base. Control measures Modiftied Relative Rebative fctor case emissions emissions emisions [Emnsslons I per category total _____ __ _ _ POINT SOUR CES q F qF fq fF f- qFfqF f (dqFiqfFi) (dqFfq Fftot (kgut) (IDE3 t.) tnt-) -10E3 t-) lPe.ot) otoM) Himal Cement Dry kiln 2000 1.00 1.00 1.00 2000 33.3 Chokr Cooler 0 1.00 1.00 1.00 0 0.0 Dryers, grinders, etc. 4000 1.00 1.00 1.00 4000 66.7 Quany 0 1.00 1.00 1.00 0 0.0 1.00 1.00 1.00 0 0. ( 1.00 1.00 1.00 t _ 0.0 Sum large point sources 6 M000 10.0 Moditied emlsaons/emlssons, point sourc. DISCRETE AREA SOURCES Local Brick Chinese kilns 146.0 1.00 1.00 1.00 0.00 0.0 0.0 coat 20.00 9.1 182.00 1.00 1.00 1.00 182.00 3.5 1.7 Bull Trench klltns 500.00 1.00 1.00 1.00 5000.00 96.5 473 Coal 42.0 1.00 1.00 1.00 0.00 0.0 0.0 Fuel wood 5.7 1.00 1.00 1.00 0.00 0.0 0.0 Other (mainty rice husk) 15.8 1.00 1.00 1.00 0.00 0.0 0.e Sum discrete area sources 5182.00 5121 100.0 49.0 Modified emissionslemissions, discr. rea soure. I1 I I DISTRIBUTED AREA SOURCES Vehicles q T TSP fq IT f- qTiqrm (dqT iq fTo (dqT bO f) (WSe) (tOtrtindeee (Vol (10ES tel_) (toMe) (rfevJ Gasaoine exhaust Cars, taxs 0.20 192 38.4 1 1 1 38.4 6.7 0.4 3-whealem (rT) 0.50 135 67.5 1 1 1 67.5 11.8 0.6 2-wheiers (MC) 0.50 215 107. 1 1 1 107.5 18.8 1.0 Sum gasoline 542 213.4 213.4 2.0 |Modified errisionssemissions, gasoline 1.0 Diesel exhaust Jeeps 0.9 78 68.4 1 1 1 68.4 12.0 0.6 Minibuses 1.5 15 22.5 1 1 1 22.5 3.9 0.2 Buses 3.0 15 45.0 1 1 1 45.0 7.9 0.4 Trucks 3.0 38 114.0 1 1 1 114.0 20.0 1.1 Tractors 0.9 24 21.6 1 1 1 21.6 3.8 0.2 3-wheelers (TC) 1.5 57 85.5 1 1 1 85.5 15.0 0.8 Sum diesel 225 357.0 357.0 3.4 Modified emissionstemissiorns, diesel _ 1.0 Sum total vehicle exhaList 767 570.4 570.4 100.0 5.4 Mocofted emissdonts/emissions, total vehicie exhaust I_I_I 1.00 Resuspenslontromroads 2.0 767 1534.0 1 1 1 1534.0 14.5 Sum toted vehicles (exh.+resusp.) 2104.4 2104. 199 Modifled emri2sonsemoisslona, totai vehicles (exh. + resusp.) I _ 1.a Fuel combustion q F qF fq iF f- qF1qtF1 (dqFiq1F-)tue (dqF'qfFfltot ikav (tceM.) |o ) l l1u.l (cot () llndustrifacomnrercila Diesel HSD | 028 0.00 1.00 1.00 1.00 0.00 0.0 0.0 Fueioil LDO 0.00 1.00 1.00 1.00 0.00 0.0 0.0 Coal 10.00 4.8 48.00 1.00 1.00 1.00 48.00 1.7 0.5 Charcoal 20.00 1.0 20.00 1.00 1.00 1.00 20.00 0.7 0.2 Fuelwood 3.60 17.2 61.92 1.00 1.00 1.00 61.92 2.1 0.8 Agri. residue 10.00 45.0 450.00 1.00 1.00 1.00 450.00 15.5 4.3 Kerosenw&PG 0.06 1.0 0.06 1.00 1.00 1.00 O.06 0.0 0.0 Sum Wndustriil 579.98 579.98 5.5 Modtled enmisdosn/einssionrs, lndustrlal __ _u1.00 Domestic Fuelwood 15.00 122.1 1831.50 1.00 1.00 1.00 1831.50 63.0 17.3 Agri. residue 10.00 45.4 454.00 1.00 1.00 1.00 454.00 15.6 43 Anhm. waste 10.00 3.0 30.00 1.00 1.00 1.00 30.00 1.0 0.3 Kerosene 0.06 35.0 2.10 1.00 1.00 1.00 2.10 0.1 0.0 LPG 0.06 4.0 0.24 1.00 1.00 1.00 0.24 0.0 0. Charcoal 20.00 0.5 10.00 1.00 1.00 1.00 10.00 031 0.1 Sum doffestic 2327.84 2327.84 22.0 Modied emiss2onsemnilssions, domestic _ _ 1.0 Sum fuel combustion 2907.82 2907.82 100.0 27.5 Modaed emislons emassions, fuel |_._____ 1.00 Miscellaneous q M qM fq WM f. qMfqWfM (dqMfqiMfmilsc (dqMfqWMf)tot befus ning | 37 10.4 384.8 1 1 1 384.8 100.0 3.6 |coilarrciionII I qtesualpeosioan, oPen surfaces |________I_ Sum miaceBaneous 384.8 1 1 384.98 100.0 3.6 oodIif sionskerdsionsf rrt5 _ j_j 1.00 Sum total distributed area sources 110575.02 lOS79s02 100.0t Modified emisslonslemissions, distr. area sources 1.00 I - URBAIR-Kathmandu 151 Figure 2: Emission sources Present 6000 5000 04000 w . 3000 200 co EL 100 e 2000 . Cs~ ~ . 100 0~~~~~~~~~~~~~~~~~~~~ E U) 0 ai 6 2 E Present 2% 3% 1 37% d) 0 l ~ | W | |_ *0 Large point sources F 7 I i l S - _ z~~~~~~~~~~~~~~1 Brick kilns . ~~~~~~~~~~~~~~~Gasoline 9% l Diesel 0 O Resusp. IZ Ind. fuel comb. _ _ . Pre tEl Domestic fuel comb. 2% °'\ Misc. 32% -~~~~ ag on ore 152 Appendix 5 - miscellaneous g) d(qFfqfFf): Relative emissions contributions, all categories summed. Rows a) Separate rows for each source type and category, "existing" and "new" technology. b) Modified emission/emissions: Ratio between modified and base case emissions. APPENDIX 6: PROJECT DESCRIPTION FOR LOCAL CONSULTANTS PROJECT DESCRIPTION REGARDING AIR QUALITY ASSESSMENT Information should be collected regarding the items described below. The information to be collected shall go beyond the information contained in the material referenced in the Draft Report from NILU and Institute of Environmental Studies (IES) of the Free University of Amsterdam prepared for the Workshop, and summarized in that report. Available information shall be collected regarding the following items, and other items of interest for Air Quality Management System Development in Kathmandu Valley: * Meteorological measurements in and near the city. * Activities/population data for Kathmandu Valley: - Fuel Consumption data: Total fuel consumption (1) per type (high/low sulfur oil, coal, gas, firewood and other biomass fuels, other) and (2) per sector (industry, commercial, domestic) - Industrial plants: Location (on map), type/process, emissions, stack data (height, diameter, effluent velocity and temperature) - Vehicle statistics: 1. number of vehicles in each class (passenger cars, small/medium/large trucks, buses, motorcycles (2- and 3-wheels, 2- and 4-stroke); 2. Age distribution; 3. Average annual driving distance per vehicle class. - Traffic data: Definition of the main road network marked on map. Traffic data for the main roads: 1. annual average daily traffic (vehicles/day) 2. traffic speed (average, and during rush hours) 3. vehicle composition (passenger cars, motorcycles, trucks/buses). - Population data: Per city district (as small districts as possible) 1. total population; 2. age distribution. 153 154 Appendix 6 * Air pollution emissions -Emission inventory data (annual emissions) 1. per compound (SO2, NOx, particles in size fractions: <2 rig, 2-10 ,ug, >10 [.g, 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 Kathmandu Valley. 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. URBAIR-Kathmandu 155 PROJECT DESCRIPTION REGARDING DAMAGE ASSESSMENT AND ECONOMIC VALUATION URBAIR: TOPICS FOR RESEARCH Physical impacts I.Describe available studies on relations between air pollution and health. 2. Decide on the acceptability of dose-effect relationships from the United States. a) Mortality: 10 [g/m3 TSP leads to 0.682 (range: 0.48-0.89) percentage change in mortality. b) Work loss days (WLD): 1 jg/r3 TSP leads to 0.00145 percentage change in WLD. c) Restricted activity days (RAD): 1 jtg/m3 TSP leads to 0.0028 percentage change in RAD per year. d) Respiratory hospital diseases (RHD): 1 jg/m TSP leads to 5.59 (range: 3.44-7.71) cases of RHD per 100,000 persons per year. e) Emergency room visits (ERV): 1 jig/mr TSP leads to 12.95 (range: 7.1-18.8) cases of ERV per 100,000 persons per year. f) Bronchitis (children): 1 ig/m3 TSP leads to 0.00086 (range: 0.00043-0.00129) change in bronchitis. g) Asthma attacks: 1 jig/M3 TSP leads to 0.0053 (range: 0.0027-0.0079) change in daily asthma attacks per asthmatic persons. h) Respiratory symptoms days (RSD): 1 [tg/m3 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]L,d-[Pb in blood]new) with [Pb in blood] is blood lead level (gig/dl). j) Coronary heart disease (CHD): change in probability of a CHD event in the following ten years is: [I + exp - (-4.996 + 0.030365(DBP)}f' - [1 + exp - {-4.996 + 0.030365(DBP2)}fl' i) Decrement IQ points: IQ decrement = 0.975 x change in air lead (jg/M3) Calculation example: * Let population be 10 million people. * Let threshold value of TSP be 75 jig/M3 (the WHO guideline). * Let the concentration TSP be 317 jig/M3. => Concentration - threshold = 317 - 75 = 242 = 24.2 (10 gig/mi). => 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 156 Appendix 6 Valuation 1. Mortality. a) Willingness to Pay. In the United States, research has been carried out on the relation between risks of jobs and wages. It appeared that 1 promille of change in risk of mortality leads to a wage difference of about US$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 US$1,000 x 10 x 106 = US$10 billion. An increase in risk of 1 promille will lead to approximately 10,000 death cases, so per death case the valuation is US$1 million. It should be decided if in other countries, c.q. cities, this valuation should be corrected for wage differences (e.g. if the average wage is 40 times lower than in the United States, the valuation of 1 death case is US$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 the United States, based on surveys among respondents, indicate that the willingness to pay to prevent a day of illness is approximately US$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 of IQ of children may lead to a lower earning capacity. A United States estimate is approximately US$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 the United States and the city. Other impacts. 1. Buildings. An estimate by Jackson et al is that prevented cleaning costs per household per year are US$42 for a reduction in TSP concentration, from 23 5 pig/m3 to 115 Rg/m3. This would imply a benefit of US$0.35 per household per ,pg/m3 reduction. This figure could be corrected for wage differences between the United States 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. URBAIR-Kathmandu 157 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.) * 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 (R/C). The options with the highest ration R/C are the most cost- effective ones. Distributors of COLOMBIA GERMANY ISRAEL NEPAL PORTUGAL SEE Intoenlace Uda. UNO-VedAg Yomot Literature Ltd. Everest Media Inltemational Services (R) Ud. Livrada Portugal Wennergren-William AB W orld Bank Carrera6 No.51-21 PoppelsdolerAlleebS PO. Box 56055 GPO Box 5443 Aparlado 2681, Rua Do Camno 70-74 P 0. Box 1305 Apartado Aereo 34270 53115 Bonn 3YohananHasandlarStreet Kathmandu 1200 Lisbon S-171 25Solna Publications Santafe de Bogo, D.C. 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Toriello Guerra Intemational Publishing Service Lake House Bookshop Southeton Telg (86610)6333-8257 ane dna OtigantSoLthair 14050 Me)oo, D.Fi UO, Piekna31/37 100, SirChittampalamiGardinerMawatha Harare Fax: (86 18) 6401-7365 75116 Paris 4-5 Hsrcourn Rood Tel: (52 5(624-2800 00-677 Warzowa Colomobo 2 Tl 234 261 Tel: (33 1) 40-69-30-56/57 Dublin 2 Fax: (52 5) 624-2822 Tel: (48 2) 628-8089 Tel: (94 1) 32105 Fax: (263 4) 621670 Fax: (33 1)40-69-30-68 Tel: (353 1) 661-3111 E-mail: infotec@rn.net.mx Fax: (48 2)621-7255 Fax: (94 1) 432104 Fa: (353 1)475-2670 URL: http://rtn.neo.mx E-mail: books%ipo@ikp.atm.corm.pl E-mail: LHL@sri.lanka.oet URL: http://www.ipscg.wawpVips/export/ O8,7 RECENT WORLD BANK TECHNICAL PAPERS (continued) No. 348 Goldstein, Preker, Adeyi, and Chellaraj, Trends in Health Status, Services, and Finance: The Transition in Central and Eastern Europe, Volume II, Statistical Annex No. 349 Cummings, Dinar, and Olson, New Evaluation Proceduresfor a New Generation of Water-Related Projects No. 350 Buscaglia and Dakolias, Judicial Reform in Latin American Courts: The Experience in Argentina and Ecuador No. 351 Psacharopoulos, Morley, Fiszbein, Lee, and Wood, Poverty and Income Distribution in Latin America: The Story of the 1980s No. 352 Allison and Ringold, Labor Markets in Transition in Central and Eastern Europe, 1989-1995 No. 353 Ingco, Mitchell, and McCalla, Global Food Supply Prospects, A Background Paper Prepared for the World Food Summit, Rome, November 1996 No. 354 Subramanian, Jagannathan, and Meinzen-Dick, User Organizations for Sustainable Water Services No. 355 Lambert, Srivastava, and Vietmeyer, Medicinal Plants: Rescuing a Global Heritage No. 356 Aryeetey, Hettige, Nissanke, and Steel, Financial Market Fragmentation and Reforms in Sub-Saharan Africa No. 357 Adamolekun, de Lusignan, and Atomate, editors, Civil Service Reform in Francophone Africa: Proceedings of a Workshop Abidjan, January 23-26, 1996 No. 358 Ayres, Busia, Dinar, Hirji, Lintner, McCalla, and Robelus, Integrated Lake and Reservoir Management: World Bank Approach and Experience No. 360 Salman, The Legal Frameworkfor Water Users' Associations: A Comparative Study No. 361 Laporte and Ringold. Trends in Education Access and Financing during the Transition in Central and Eastern Europe. No. 362 Foley, Floor, Madon, Lawali, Montagne, and Tounao, The Niger Household Energy Project: Promoting Rural Fuelwood Markets and Village Management of Natural Woodlands No. 364 Josling, Agricultural Trade Policies in the Andean Group: Issues and Options No. 365 Pratt, Le Gall, and de Haan, Investing in Pastoralism: Sustainable Natural Resource Use in Arid Africa and the Middle East No. 366 Carvalho and White, Combining the Quantitative and Qualitative Approaches to Poverty Measurement and Analysis: The Practice and the Potential No. 367 Colletta and Reinhold, Review of Early Childhood Policy and Programs in Sub-Saharan Africa No. 368 Pohl, Anderson, Claessens, and Djankov, Privatization and Restructuring in Central and Eastern Europe: Evidence and Policy Options No. 369 Costa-Pierce, From Farmers to Fishers: Developing Reservoir Aquaculturefor People Displaced by Dams No. 370 Dejene, Shishira, Yanda, and Johnsen, Land Degradation in Tanzania: Perceptionfrom the Village No. 371 Essama-Nssah, Analyse d'une repartition du niveau de vie No. 373 Onursal and Gautam, Vehicular Air Pollution: Experiencesfrom Seven Latin American Urban Centers No. 374 Jones, Sector Investment Programs in Africa: Issues and Experiences No. 375 Francis, Milimo, Njobvo, and Tembo, Listening to Farmers: Participatory Assessment of Policy Reform in Zambia's Agriculture Sector No. 376 Tsunokawa and Hoban, Roads and the Environment: A Handbook No. 378 Shah and Nagpal, eds., Urban Air Quality Management Strategy in Asia: Kathmandu Valley Report No. 377 Walsh and Shah, Clean Fuels for Asia: Technical Options for Moving toward Unleaded Gasoline and Low-Sulfur Diesel No. 382 Barker, Tenenbaum, and Woolf, Governance and Regulation of Power Pools and System Operators: An International Comparison No. 383 Goldman, Ergas, Ralph, and Felker, Technology Institutions and Policies: Their Role in Developing Technological Capability in Industry No. 384 Kojima and Okada, Catching Up to Leadership: The Role of Technology Support Institutions in Japan's Casting Sector No. 385 Rowat, Lubrano, and Porrata, Competition Policy and MERCOSUR No. 386 Dinar and Subramanian, Water Pricing Experiences: An International Perspective No. 387 Oskarsson, Berglund, Seling, Snellman, Stenback, and Fritz, A Planner's Guidefor Selecting Clean-Coal Technologies for Power Plants No. 388 Sanjayan, Shen, and Jansen, Experiences with Integrated-Conservation Development Projects in Asia No. 389 International Commission on Irrigation and Drainage (ICID), Planning the Management, Operation, and Maintenance of Irrigation and Drainage Systems: A Guidefor the Preparation of Strategies and Manuals No. 395 Saleth and Dinar, Satisfying Urban Thirst: Water Supply Augmentation and Pricing Policy in Hyderabad City, India (.a~ THE WORLD BANK 18 I X I I St,-..t N \V \\lishingizton I).(. 2(0433 t S.\ Icl.plhorlc: 202-477-1234 IF.csimilc: 2042-477-6391 IClcx: \I(I 64145 NWORI) D \VNK \1(C1 248423 NN\OIRI I)Il-VNls \\Wor-ld \\i.lc \\Ch: lttp: '\\x \.\\ orldhank. ,- E-ma il hoIks (\\ orldh1d lkn r. METROPOLITAN ENVIRONMENTAL IMPROVEMENT PROGRAM El mil-olilillcilt 1,1nd N Itur,-l 1~slr.zt,c.s I)i\isl(iz \sia lIT.cl,hicul ID)partlniclt 'IBlic \\I,,-ld 1ankl 1IS ISI St,-cct N.\\ W\ shiFgtof. 1).C. 2(0433 'SA\ ICl.plchonc: 202-458-1598 F'acsimile: 20)2-522-1664 111111 111 110111 9 780821 340349 ISBN 0-8213-4034-4