WORLD BANK TECHNICAL PAPER NO. 380
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Urban Air Quality Management Strategy in Asia Metro Manila Report SELECTED WORLD BANKTITLES ON AIR QUALITY
Air Pollutionfrom Motor Vehicles:Standards and TechnologiesforControlling Emissions. Asif Faiz, Christopher S. Weaver, and Michael Walsh. CleanFuelsfor Asia:Technical Optionsfor Moving towardUnleaded Gasoline and Low-SulfutrDiesel. Michael Walsh and Jitendra J. Shah. Technical paper no. 377. Energy Use,Air Pollution,and EnvironmentalPolicy in Krakow:Can EconomicIncentives Really Help?Seabron Adamson, Robin Bates, Robert Laslett, and Alberto Ptotschnig. Technical paper no. 308. TaxingBads by TaxingGoods: Pollution Control with PresuimptiveCharges. Gunnar S. Eskeland and Shantayanan Devarajan. Directions in Development Series. UrbanAir Quality ManagementStrategy in Asia:Kathmandu Valley Report. Edited by Jitendra J. Shah and Tanvi Nagpal. Technicalpaper no. 378. UrbanAir Quality ManagementStrategy in Asia:Jakarta Report. Edited by Jitendra J. Shah and Tanvi Nagpal. Technical paper no. 379. UrbanAir Quality ManagementStrategy in Asia:Metro Manila Report.Edited by Jitendra J. Shah and Tanvi Nagpal. Technicalpaper no. 380. UrbanAir Quality ManagementStrategy in Asia: GreaterMumbai Report.Edited by Jitendra J. Shah and Tanvi Nagpal. Technicalpaper no. 381. UrbanAir Quality ManagementStrategy in Asia:Guidebook. Edited by Jitendra J. Shah, Tanvi Nagpal, and Carter J. Brandon. VehicularAir Pollution:Experiences from SevenLatin American UrbanCenters. Bekir Onursal and Surhid P.Gautam. Technical paper no. 373. AUTHORS
Steinar Larssen Frederick Gram Leif Otto Hagen Norwegian Institute for Air Research Kjeller, Norway
Huib Jansen Xander Olsthoorn from the Institute for Environmental Studies, Free University Amsterdam, the Netherlands,
Dr. Reynaldo Lesaca Test Consultants Inc.
Dr. Emmanuel Anglo Prof. Elma B. Torres Dr. Ronald D. Subida Dr. Herminia A. Fransisco University of the Philippines
WORLD BANK TECHNICAL PAPER NO. 380
Urban Air Quality Management Strategy in Asia MetroManila Report
Editedby JitendraJ. Shah TanviNagpal
TheWorld 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
TechnicalPapers 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. The World Bank does not guarantee the accuracy of the data in- cluded in this publication and accepts no responsibility whatsoever for any consequence of their use. The boundaries, colors, denomninations,and other information shown on any map in this volume do not imply on the part of the World Bank Group any judgment on the legal status of any territory or the endorsement or acceptance of such bound- aries. The material in this publication is copyrighted. Requests for permission to reproduce portions of it should be sent to the Office of the Publisher at the address shown in the copyright notice above. The World Bank encourages dissem- ination of its work and will normally give permission promptly and, when the reproduction is for noncommercial purposes, without asking a fee. Permission to copy portions for classroom use is granted through the Copyright Clearance Center, Inc., Suite 910, 222 Rosewood Drive, Danvers, Massachusetts 01923,U.S.A.
Cover design by Beni Chibber-Rao. Cover photo, "Philippines, Manila," by Edwin G. Huffman, 1975.
ISSN:0253-7494
jitendra J. Shah is an environmental engineer in the World Bank's Asia TechnicalEnvironment Unit. Tanvi Nagpal, a political economist, 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. Metro Manila report / edited by Jitendra J. Shah, Tanvi Nagpal. p. cm. - (World Bank technical paper; no. 380) Includes bibliographical references. ISBN 0-8213-4036-0 1. Air quality management-Philippines-Manila Metropolitan Area. 2. Air-Pollution-Philippines-Manila Metropolitan Area. I. Shah, Jitendra J., 1952- . II. Nagpal, Tanvi, 1967- . III. Series. TD883.7.P62M368 1997 363.739'25'0959916-dc2l 97-34168 CIP TABLE OF CONTENTS
LETTER OF SUPPORT ...... x F OREWORD...... xi ABST'RACT...... xii ACKNOWLEDGMENTS ...... xiii ABBREVIATIONS AND ACRON YMS ...... xv EXECUTIVE SUM ARY ...... 1 THE DEVELOPMENTOF METROMANILA AND ITS POLLUTIONPROBLEM ...... 1 CONCEPTOF AIR QUALIrY MANAGEMENTSYSTEM ...... 2 ABATEMENTMEASURES AND ACTION PLAN ...... 3 RECOMMENDATIONSFOR STRENGTHENINGAIR QUALITYMONITORING, AND INSTITUTONS ...... 4 1. BACKGROUND INFORMATION...... 5 SCOPE OF THESTUDY ...... 5 GENERALDESCRIPTION OF THEMETROPOLITAN MANILA REGION ...... 5 LAND USE...... 8 DATA SOURCES...... 8 Previous studies ...... 8 URBAIR data collection...... 10 DEVELOPMENTOF METROMANILA, 1980-1992 ...... 10 POPULATION...... I VEHICLE FLEET...... 12 ROAD ANDTRANSPORT ...... 12 INDUSTRIALSOURCES ...... 13 FUEL CONSUMPTION...... 15 2. AIR QU ALITYASSESSMENT ...... 17 AIR POLLUTIONCONCENTRATIONS ...... 17 Overview of database ...... 17 TSP...... 18 PM10...... 2 2 Lead ...... 22
S0 2 summary ...... 23
vii AIR POLLUTANTEMISSIONS ...... 26 Total emissions ...... 26 TSP emission ...... 30 PM, emissiono ...... 32 SO2 emission ...... 32 Lead emission ...... 32 DISPERSIONMODEL CALCULATIONS ...... 33 Dispersion conditions ...... 33 Dispersion model calculations, city background ...... 41 Suspended particles ...... 42 Pollution hot spots ...... 46 POPULATIONEXPOSURE TO AIRPOLLUTION IN METRO MANILA...... 49 SUMMARYOF THE AIR QUALITYASSESSMENT ...... 52 IMPROVINGAIR QUALITY ASSESSMENT ...... 53 Shortcomings and data gaps ...... 53 3. HEALTH IMPACTS OF AIR POLLUTION ...... 57 INRODUCTION...... 57 MORTALrrYAND MORBIDITY ...... 57 Mortality and other health impacts of lead ...... 58 MORTALITYAND MORBIDITY DUE TO PARTICULATES...... 59 VALUATIONOF HEALTHIMPACTS ...... 60 VALUATIONOF NON-HEALTHDAMAGES ...... 62 4. ABATEMENT MEASURES: EFFECTIVENESS AND COSTS .. 63 INTRODUCTION...... 63 TRAFFIC...... 63 Reinforcing the anti-smoke belching program ...... 64 Improving diesel quality ...... 64 Implementing an inspection and maintenance scheme ...... 66 Fuel switching in the transportation sector ...... 67 Clean vehicle emissions standards ...... 69 Other technical measures ...... 71 Resuspension emission ...... 72 Improving traffic management ...... 72 Constructing mass-transit systems ...... 72 POWERPRODUCTION ...... 73 Cleanerfuels in existing plants ...... 73 Treatment offlue gases ...... 74 FUEL COMBUSTIONOTHER THAN FOR POWERPRODUCTION ...... 75 Cleaner fuels ...... 75 Flue gas treatment ...... 75 INDUSTRIALPROCESSES (NON-COMBUSTION SOURCES), REFUSE BURNING AND CONSTRUCTION...... 76
viii 5. ACTION PLAN ...... 77 AcrIONS TO IMPROVEMETRO MANILA AIR QUALITY AND ITS MANAGEMENT...... 77 Actions to improveair quality...... 77 Actions to improvethe Air QualityManagement System (AQMS)...... 78 A COMPREHENSIVELIST OF PROPOSEDMEASURED AND ACTIONS ...... 79 6. INSTITUTIONS,REGULATIONS, AND POLICY PLANS...... 97 INSTITUTIONS...... 97 AIR POLLUTIONLAWS AND REGULATIONS...... 99 POLICYPLANS ...... 100 PRIVATESECTOR PARTICIPATION ...... 102 REFERENCES...... 103 APPENDICES 1: AIR QUALITY STATUS, METRO MANILA ...... 107 2: AIR QUALITY GUIDELINES...... 133 3: AIR POLLUTION LAWS AND REGULATIONS FOR THE PHILIPPINES AND METRO MANILA ...... 139 4: EMISSIONS OF AIR POLLUTANTS, METRO MANILA ...... 147 5: EMISSION FACTORS, PARTICLES ...... 169 6: POPULATION EXPOSURE CALCULATIONS ...... 173 7: SPREADSHEETS FOR CALCULATING EFFECTS OF CONTROL MEASURES ON EMISSIONS AND EXPOSURE ...... 177 8: PROJECT DESCRIPIONS, LOCAL CONSULTANTS ...... 185
ix DEPARTMENTOF ENVIRONMENTAND NATURAL RESOURCES
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 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 Metro Manila, the main contributor of air pollution is 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, econornically 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.
Metro Manila joined the World Bank-executed Metropolitan Environment Improvement Program (MEIP) in 1991. 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, Urban Air Quality Management Initiative (URBAIR) was conceived and launched in Metro Manila, Philippines in 1993.
UJRBAIRhas assisted the Republic of the Philippines, Department of Environment and Natural Resources to develop a strategy and time bound action plan for air quality management in Metro Manila. For the first time, it brought together the different stakeholders - sectoral agencies, private sector, NGOs, local government units (LGUs), academics, research bodies and media - to formulate a strategy. This group was brought together as a Technical Committee and deliberated over several months with technical support provided by a team of national and international experts. The outcome is the Action Plan that is listed ahead. The result is truly impressive and the Philippine Government is fully committed to the implementation of the plan. We would need the support of the international community in realizing the goals of the plan.
I wish to acknowledge with gratitude to all those who contributed to the development of the strategy and plan, especially to MEIP for facilitating the process.
VICTOR 0. RAMOS Secretary Department of Environment and Natural Resources
Visayas Avenue, Diliman, Quezon City FOREWORD
In view of the potential environmental consequences of continuing growth of Asian metropolitan areas, the World Bank and United Nations Development Programme (UNDP) launched the Metropolitan Environmental Improvement Program (MEIP) in 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 environmental problems. Recognizing the growing severity of air pollution caused by industrial expansion and increasing number 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, Jakarta, Kathmandu, and Metro Manila. URBAIR is an international collaborative effort involving governments, academia, international organizations, NGOs, and the private sector. The main objective of URBAIR is to assist local institutions in these cities to develop action plans that 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 was set up containing the selected abatement measures for implementation in the short, medium, and long term. The preparation of this city-specific report for Manila is based on data and specific studies carried out by local consultants, and from workshops and fact-finding missions carried out in August 1993 and May 1994. Consultants from Norwegian Institute for Air Research (NILU), Kjeller, Norway, and Institute for Environmental Studies (IES), Free University, Amsterdam, the Netherlands, prepared first drafts of the report before the first workshop. Prior to the second workshop, a second draft report was prepared with 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. 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 Asian Environment and Natural Resources Division
xi 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 Metro Manila, the political and commercial capital of the Philippines. Annual total suspended particles (TSP) emission in 1992 was 75,020 tons. In the same year PMIo (particulate matter smaller than 10 microns) emission was 42,240 tons. The ambient TSP concentration varies from 115 to 256 jig/m3 at various locations throughout the city. Annual average TSP concentrations are frequently five times higher than the World Health Organization Air Quality Guidelines (WHO AQG). Eighty percent of the population lives in areas where the national standard for air quality is exceeded. Long-term measured lead levels also exceed both national and WHO AQG. Dose-response equations use for 1992 Manila data reveal that PM1 O emissions from various transport sources may be responsible for 1,545 excess deaths and 41.8 million respiratory symptom days at a total cost of 5,373 million pesos. Applying the essential components of an air quality management system to the pollution problem in Manila, this report suggests an action plan containing abatement measures for the short, medium, and long terms. Recommended actions fall into two categories-institutional and technical. A single institution with a clear mandate and sufficient resources should be made responsible for air quality management in Manila. Existing, citywide plans for improving air quality should be implemented. In addition, data gathering and processing capabilities should be improved throughout the city. Technically, it is crucial that gross polluters be identified and existing smoke opacity regulations more strictly enforced. Diesel quality should be improved, and lead free gasoline be made cheaper than leaded gasoline. State-of-the art emissions standards should be set for all vehicle classes; annual or biannual inspections are necessary to enforce such standards. The sulfur content in heavy fuel oil should be reduced. Awareness raising through public and private organizations, including educational institutions, is key to bringing about policy change on matters of air pollution.
xii ACKNOWLEDGMENTS
We would like to acknowledge the groups and individuals who contributed to this URBAIR study. Core funding was provided by the United Nations Development Programme, the Royal Norwegian Ministry of Foreign Affairs, the Norwegian Consultant Trust Funds, and the Netherlands Consultant Trust Funds. Substantial inputs were provided by host govemnmentsand city administrations. The city-level technical working groups provided operational support, while the steering committee members gave policy direction to the study team. The MEIP National Program Coordinator for Metro Manila, Ms. Bebet G. Gozun, contributed substantially to the study. At the World Bank's Environment and Natural Resources Division, 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 commented on numerous drafts. Management support at the World Bank was provided by Erika Yanick, Samual Taffesse, Sonia Kapoor and Ronald Waas. Tanvi Nagpal and Sheldon Lippman were responsible for quality assurance, technical accuracy, and final preparation. Julia Lutz designed the layout. Many intemational institutions including World Health Organization, United States Environmental Protection Agency, and U. S. Asia Environment Partnership provided valuable contribution to the study. The following individuals participated in the Manila URBAIR working groups:
URBAIR Technical Working Group Members, Manila NCR AIRQUALITY ASSESSMENT Engr.Rachel Vasquez EnvironmentalManagement Bureau Engr.Erlinda Gonzales EnvironmentalManagement Bureau Engr.Amadeo Alveyra EnvironmentalManagement Bureau Engr.Emiliano Kempis DENR-NationalCapital Region Atty.Theresa Oledan LagunaLake Development Authority Ms.Adelina Borja LagunaLake Development Authority Engr.Derlyn Gemeniano LagunaLake Development Authority Ms.Eva Liza Mortel LandTransportation Office Ms.Heriberta Domingo LandTransportation Office Engr.Amel Manresa DepartmentofTransportation and Communication Ms.Aida Pujanes DepartmentofEnergy Engr.Lilian Femandez DepartmentofEnergy Dr.Aida Jose Phil.Atmospheric Geophysical and Astronomical Services Administration Engr.FelizardoMagnayon Ms.Cirila Botor Bureauof ProductStandards, Department ofTrade and Industry Prof.Minda Mella Collegeof Public Health, University of Philippines
xiii URBAIR Technical Working Group Members, Manila NCR Dr.Emmanuel Anglo CollegeofMeteorology, University ofPhilippines ECONOMICVALUATION OFAIR POLLUTION DirectorRomy Acosta SpecialConcerns Office, Department ofEnvironment andNatural Resources Dr.Marian Delos Angeles EnvironmentalandNatural Resource Accounting Dir.Celso Diaz DepartmentofEnvironment andNatural Resources, National Capital Region Ms.Rosita Rondilla NationalEconomic and Development Authority-Trade andIndustry Utility Staff Ms.Carol Dela Cruz Dr.Montana Ramos DepartmentofHealth Dr.Ma. Elizabeth Caluag DepartmentofHealth Dr.Edna Francisco Red DepartmentofHealth Dir.Augusto G.Sanchez DepartmentofLabor and Employment SUB-COMMITTEEONATMOSPHERE (Served as TWG for Policy Issues) Ms.Teresita Femandez DepartmentofInterior and Local Government Ms.Ester Peres De Tagle ConcernedCitizen Against Air Pollution Mr.Vicente Lava JR PEN-PIChE Ms.Ma. Ressureccion L.Petel EnvironmentalManagement Department National Power Corporation Mr.Evan Eleazar PIAF-NGO/PO Mr.Gregorio Magdaraog NCPF/APOINGO Mr.Renato P. Olegario PCIERDDepartment ofScience and Technology Mr.Raymundo Punongbayan CommisionerPHILVOCS DOST Ms.Leticia Gloria DepartmentofNational Defense Dr.Raquel V. Francisco Phil.Atmospheric Geophysical and Astronomical Service Administration Mr.Mark Andew C. Quebal Asst.Director. Energy Resource Development Bureau Department ofEnergy Ms.Clarissa Cabacang EnvironmentProtection and Monitoring Division Department of Energy Ms.Zanaida Monsada Chief.Energy Resource Supply Administration Division, Dept. of Energy DirectorGloria Santos Infrastructureand Service-Oriented Industry, Dept. of Trade and Industry Mr.Amel Manresa RoadTransport Planning Div., Dept. of Transportation and Communication Mr.Von Hernandez GreenCoalition Mr.Antonio Claparols EcologicalSociety of the Phils. Ms.Leonora Vasquez de Jesus Undersecretary,Presidential Management Staff, Office of the President. Mr.Leonardo Ablaza Health,Safety Environment & Security Manager, Pilipinas Shell Corporation. Mr.Alexander Lionaz BoardMember FILCAR Dr.William Padolina Undersecretaryfor Research &Tech. Transfer, Dept of Science& Tech. Mr.Henry V. Moran President,Phil. Automotive Federation, Inc. Hon.Manuel F. Bruan - AssistantSecretary. Land Transportation Office Mr.Deo Reloj Chairman,Amptron Group of Companies Mr.Ramon de la Cuesta Manager,Corporate Enviromental, Health & Safety,Caltex (Phils Inc.) Mr.Celso L. Legarda VicePresident, Petron Corporation Mr.Florello Galindo TechnicalServices Manager, Petron Corporation Mr.Nazario C. Vasquez ExecutiveVice President, Phil. National Oil Company-Energy Development Dr.Margarita R. Songco Trade& IndustryUtility Staff, National Economic and Development Authority Ms.Corazon T. Marges AgriculturalStaff, National Economic and Development Authority Dr.Emmanuel T.Velasco Director,Bureau of ImportServices Mr.Renato V. Nacvarette Director,Bureau of ProductStandards
xiv ABBREVIATIONS AND ACRONYMS
AADT annual average daily traffic NILU Norwegian Institute for Air ADB Asia Development Bank Research AQG air quality guidelines NMV non-motorized vehicle AQIS Air Quality Information System NO. nitrogen oxides AQMS Air Quality Management OPSF Oil Price Stabilization Fund Strategy P peso BOF bunker oil, heavy fuel oil PAGASA Philippines Atmospheric CHD coronary heart disease Geophysical and Astronomical CNG compress natural gas Services Administration CO carbon monoxide PAH polycyclic aromatic hydrocarbons CrBr chronic bronchitis PD Presidential Decree CVM Contingent Valuation Method PMio particulate matter less than 10 DENR Department of Environment and microns Natural Resources ppm parts per meter DOF diesel RAD restricted activity days EMB Environment Management RDC Regional Development Councils Bureau RHD respiratory hospital diseases ERV emergency room visits RSD respiratory symptom days g/l grams per liter SO2 sulfur dioxide GDP Gross Domestic Product TGS pararosaniline GNP Gross National Product TOG total organic gases HC hydrocarbon TSP total suspended particles IES Institute of Environmental UNDP United Nations Development Studies, the Netherlands Programme LNG liquefied natural gas UNEP United Nations Environment LPG liquefied petroleum gas Programme MEIP Metropolitan Environmental URBAIR Urban Air Quality Management Improvement Program Strategy in Asia MTBE methyl-tertial-butyl-ether USEPA United States Environment mg milligram Protection Agency jIg microgram VOC volatile organic compounds tg/rm3 particulate concentration per VSL value of a statistical life microgram per cubic meters WHO World Health Organization NAIA Ninoy Aquino International Airport
xv
EXECUTIVE SUMMARY
URBAIR-METRO MANILA. 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 has resulted in severe air pollution. Emissions from automobiles and factories; domestic heating, cooking and refuse burning are threatening the well being of city dwellers, imposing not just a direct economic 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 the 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 action 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 Metro Manila and the Action Plan that resulted from the development of this strategy.
THE DEVELOPMENT OF METRO MANILA AND ITS POLLUTION PROBLEM
Metro Manila's population grew by 38 percent from 1981 to 1992. In 1994, the metropolitan area's population stood at 8.85 million. This growth in population was accompanied by an increase in the per capita gross domestic product. The Philippine Gross Domestic Product (GDP) per capita was US$730 in 1992. The rapid expansion of the vehicle fleet (9.5 percent per annum between 1985 and 1990, and a projected 6 percent between 1990 and 2000) has resulted in increased traffic congestion and fuel use. Industrial combustion of diesel, and small-to-medium- scale power generation during frequent power outages, have contributed to the 287 percent increase in fuel consumption between 1988 and 1992. These developments are reflected in the city's air quality. Annual Total Suspended Particles (TSP) emission in Manila in 1992 was 75,020 tons. PMIo(particulate matter less than 10 microns) emission in the same year was 42,240 tons. The main sources of TSP and PM1 Oare listed in Table ES. 1. The ambient TSP concentration varies from 115 to 256 p.g/m3 at various localities. Annual average TSP concentrations are frequently five times higher than the World Health Organization Air Quality Guidelines (WHO AQG). Eighty percent of the population lives in areas where the national air quality standard for TSP is exceeded. PM1 o concentrations are also exceedingly high. Long-term measured lead levels exceed both the national and WHO guidelines.
1 2 Executive Summary
SO2 pollution is not as serious an issue as Table ES. 1: Main sources of TSP and PM,, particulate pollution. Resuspension from roads and construction, diesel vehicles, and eTissions lative contributions) refusemain sourcesburning of are the ~TSP PMlo refuse burning are the main sources of Highsulfur fuel oil (BOF) combustion 22% 34% particulate pollution. Drivers, commuters, Resuspensionfrom roads (rough estimate)* 33% 15% and roadside residents are the worst Dieselvehicle exhaust 9% 16% affected. In industrial areas, heavy fuel oil Refusebuming (rough estimate) 8% 14% combustion and process emissions result in Industralprocesses (rough estimate) 8% 7% population exposure. *Thecalculation of resuspension from roads may represent an While attaching an economic value to overestimate,as it is basedon anoverall emissions figure of 2 morbidity and mortality stemming from air glkm. pollution can be difficult, there is anecdotal and estimated evidence to suggest that the health of the residents of Metro Manila is under assault. In 1995, dose-response equations used for valuing health impacts reveal that PM,( may cause 1,300 excess deaths and 35 million respiratory symptom days (RSD), among other health impacts, at a total cost of 4,594 million pesos.
CONCEPT OF AIR QUALITY MANAGEMENTSYSTEM
Assessment and control of pollution form two prongs of an Air Quality Management System (AQMS). These components are inputs into a cost-benefit analysis. Air Quality Guideline or Standards, and economic objectives and constraints also guide the cost-benefit calculation. (See Figure ES. 1) An Action Plan contains the optimum set of abatement/control measures for the short, medium, and long term. Successful air quality management requires the establishment of an integrated system for continual air quality management. Such a system Figure ES. 1: Air Quality Management System involves: * An inventory of air pollution activities and _en A Monitoiing emissions; * Monitoring of air pollution and dispersion parameters;E .4irpollution * Calculation of air concentrations pollution concentrations .. by dispersion models; Exposure * Inventory of population, measurt & COntrol assessment materials, and urban regulations development; * Calculationof the effect Dumage of abatement/control Cost analysis assessment measures; and URBAIR-Manila 3
Establishment/improvement of air pollution regulations. In order to ensure that an AQMS is having the desired impact, it is also necessary to carry out surveillance and monitoring. This requires the establishment of an Air Quality Information System (AQIS) that can keep the authorities and the general public well informed about the quality of air, assess the results of abatement measures, and provide continuous feedback to the abatement strategy process.
ABATEMENT MEASURESAND ACTION PLAN
Measures to reduce air pollution in Metro Manila focus on one important source-traffic. This is both because traffic emissions are a clear and major source of air pollution, and measures to address other pollution sources, although addressed briefly, could not be substantiated due to lack of data. Based on these abatement measures, an Action Plan was designed through a consultative process that include Metro Manila URBAIR working groups, local and foreign consultants. (See Table ES.2 for the costs and benefits of these measures.)
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 should 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 be used to differentiate fuel price according to quality. * Inspection anidmraintenance of vehicles. Annual or biannual inspections are necessary to enforce clean vehicle standards. These can be carried out by government or private entities. The basic legislation for this measure, Presidential Decree 1181, is already in place. * 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, is a prerequisite. * Awiareness raising: Public awareness and participation are key to bringing about policy
Table ES.2: Benefits and costs of selected abatement measures, annualfigures Benefits AbatementMeasure Avoidedeffects Reducedcosts Costof measure Timeframe, effect of (US$million) (US$million) measure Addressgross polluters 160deaths 16-20 0.08 Short-term (AntiSmoke Belching Campaign) 4 millRSD Improvingdiesel quality, vehicles 94deaths 10-12 10 2-5 years 2.5mill RSD lnspection/maintenance,vehicles 310deaths 30-40 5.5 2-5 years 8 millRSD Cleanvehicle standards 895deaths 94-116 10-20 5-10years 24mill RSD 4 Executive Summary
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.
RECOMMENDATIONSFOR STRENGTHENINGAIR QUALITYMONITORING, AND INSTITUTIONS
It is crucial that a single coordinating institution with a clear mandate and sufficient resources be made responsible for air quality management. 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. It is necessary to fill the gaps in the emissions inventory, and upgrade the inventory in general. The emissions inventory database must cover both the Department of Energy and Natural Resources, National Capital Region and Laguna Lake Development Authority (DENR- NCR and LLDA) jurisdiction areas. The population exposure calculations used in the first phase of URBAIR should also be improved. This would entail, using better data for distributing the population in km2 grids. In addition, dispersion modeling expertise should be identified in Metro Manila, and such models should be integrated into the air quality management work of control agencies. There are several Action Plans to improve Manila's air quality including: * The OPLAN Clean Air Metro Manila (Presidential Decree 1181) to improve air quality during 1993 to 1998. This is also called the Anti-Smoke Belching Campaign; * The Clean Air 2000 Action Plan for Metro Manila; and * The Air Quality Management Master Plan of the Environmental Management Bureau (EMB) by the (DENR-NCR), finalized in 1994. Most of these policy plans focus on cleaner fuels, inspecting and maintaining vehicles, improving vehicle technology, reviewing fuel pricing mechanisms, and making the public more aware and involved in environmental issues through information, education and communication campaigns. Private sector participation through a company program that does "business with delivery vehicles that meet government emissions standards" has shown good results. The "say no to smoke belching trucks" and "Adopt-a- Street" campaigns are good examples of socially responsible community action. Clearly, environmental risks are escalating. If pollution sources are allowed to grow unchecked, the economic costs of productivity lost to health problems will also rise. While working with sparse and often unreliable data, this report sets out a preliminary plan that has the potential to improve the quality of air as well as better manage the air quality monitoring system in the future. 1. BACKGROUND INFORMATION
SCOPE OF THE STUDY'
URBAIR's main objective is to develop a general Air Quality Management System (AQMS) for use in Asian cities, and to apply this strategy to develop Action Plans for improving air quality in the following cities: DKI Jakarta, Greater Mumbai (Bombay), Kathmandu Valley and Metro Manila. These four cities also participate in the World Bank's Metropolitan Environmental Improvement Program (MEIP). The AQMS is based on an analysis of the costs and benefits of proposed actions and measures for air pollution abatement. Benefits include the reduction in costs of health and other damage due to air pollution, resulting from the implementation of abatement measures. This study emphasizes health damage estimates based on the distribution of population exposed to air pollutants. Population exposure estimates are derived from emissions inventories and dispersion modeling that use measured and calculated air pollution concentrations. The generalized strategy is described in the URBAIR Guidebook on Air Quality Maanagement Strategy. The city reports conclude with prioritized Action Plans for air quality improvement, including costs and benefits figures. These Action Plans are based on a comprehensive list of proposed measures developed by local working groups in each of the four cities and evaluated by the URBAIR consultants.
GENERAL DESCRIPTIONOF THE METROPOLITANMANILA REGION
The Metropolitan Manila Region (MNMR)or Metro Manila is situated on a plain on the south- western coast of Luzon Island, around the mouth of the Pasig river in the Manila Bay. Also called the National Capital Region (NCR), MMVRcovers a total land area of 636 square kilometers, and consists of seven cities and ten municipalities. Figure 1.1 shows a map of the Metro Manila area. The population density grew from 12,500 persons per square kilometer in 1990, to approximately 14,000 persons per square kilometer in 1994. The population is projected to grow at the rate of 2.35 percent per year during the 1990s, leading to a projected 26 percent increase during the decade (Figure 1.2).
1 Exceptas indicated, "dollars" refers to 1992-93U.S. dollars. Exceptas indicated, all figures, tables, and textboxes were created by the authors for thisreport.
5 6 Background Information
Figure 1.1: National Capital Region (NCR) of the Philippines. * Cities and Municipalities * DENR-NCR and LLDA jurisdiction areas * Monitoring stations * Dispersion modeling area
N
* 5 km a
\ X S~~~c QuezonCity< (in}
ManilaBay at os
Jurisdictionareas: Clear:LLDA Shaded:DENR-NCR Lgn |8 . ~~~~Lake
1:- Ermita W1 2: LasPinas '- 4. Pasig l unUna . yD ersi\ 5: QuezonCity T _/ " 4 t modelling 6: CaloocanCity | area\ 7: Valenzuela 8: Makati URBAIR-Manila 7
Figure 1.2: Population, vehicle fleet, fuel consumption and air quality (annual average concentrations), 1981-1992. 9000 8000 POPULATION 7 000 6000 - 0 5000 z 4000 0 .~3000HH 2000 1000 ]l 81 82 83 84 85 86 87 88 89 90 91 92 93 94
1000
800 MC/TC *3Trucks/buses 0 UV[ Cars
7500600 E 400 e 300 200 100 0 , I I I I I I 81 82 83 84 85 86 87 88 89 90 91 92 93 94
45003 - E 4000 FUEL CONSUMPTION 3800 3000 GPasoline
.2 2600 03Diesel (all use) 2000 M*Fueloil
1000,0
Ue 0 , 0 2 81 82 83 84 85 86 87 88 89 90 91 92 93 94
300 0,10 3 1500 +SQeoCbys-00 AIR POLLUTION 0,09 250 --- SEnia0,08 6 Pai- Soo 200 TSP Las Pinas 0,07 200 ~~~TSPParanaque 00 E ~~~~TSPPasigE 150 ~ TSP Quezon City 0,05 ~TSPValenzuela 0,0 ....-W-SO2 Ermrnta00 100~~S0 Paranaque 0,03 soS0 Pasig 0,02 50 ~~~S02Quezon City 0,01
81 82 83 84 85 86 87 88 89 90 91 92 93 94 8 Background Information
EDSA is the principal circumferencial highway. It is a 12-lane highway running in a semi- circle with a radius of about seven kilometers (see Figure 1.3). It was built as an outer ring road, but the growth of city centers such as Makati and Quezon City has changed the city's layout. Commercial and administrative development have shifted from the center to areas outside EDSA, which has become the spine of the city. At Guadalupe, the busiest point, traffic peaks at 11,000 to 12,000 vehicles per hour, and daily volumes exceeding 140,000 to 150,000 vehicles are common. Traffic congestion is frequent along many sections of EDSA with 2.34 million passengers daily, of which 1.43 million travel by bus. With the projected growth in population and traffic, it is expected that there will be a total breakdown in traffic within a few years unless new investments are made in the transport sector. Several proposals have been advanced, including highway improvements and alternative routes. For public transport, a Light Rail Transit System along EDSA or a separate transitway system have been proposed.
LAND USE
About 37 percent of total land area in Metro Manila is used for housing, including single family residences, multiple residential units, slums and squatter areas. Generally, high density, poor housing areas are located around the commercial and tourist centers which provide informal employment opportunities. More affluent residential areas are located along EDSA, at the Southern edge of Quezon City, at Greenhills in San Juan, near Ortigas in Mandaluyong and Pasig, and near the Makati Commercial Center in Makati. About 8 percent of the land in Metro Manila is used for commercial activity. The old commercial areas are located in Ermita, Malate, Quiapo, Divisoria Santa Cruz, and Binondo of Manila. Recent commercial developments have come up in Santa Mesa (Manila), Cubao, Balintawak, and Monumento (Quezon City), Makati, Greenhills (San Juan), and the EDSA- Ortigas-Shaw areas at the confluence of Pasig and Mandaluyong. Industrial development claimed about 15 percent of Metro Manila land in 1990. Factories are concentrated in areas with good transportation links, such as Pasig, Port Area, Paco, Pandacan and Mandaluyong. Other areas of recent industrial concentration are located along MacArthur Highway and Tandang Sora in the north, and along Pasong Tamo and the South Superhighway in the south. Industries are currently expanding in provinces immediately adjacent to Metro Manila (Laguna, Cavite, Batangas).
DATA SOURCES
Previous studies
Several institutions have studied and reported the air pollution situation in Metro Manila. The most important among these have formed part of the background for URBAIR's work. These are: * "Urban Air Pollution in Megacities in the World" from the GEMS/Air-program of WHO/UNEP (WHO/UNEP, 1992). URBAIR-Manila 9
Figure 1.3: Metro Manila main road network Bonlfazi
tS~~~~~~~~S 10 BackgroundInformation
* "Model for Air Pollution Planning", by Dr. P. Manins, a study for the Environmental Management Bureau, presenting dispersion modeling results for Metro Manila (Manins, 1991). * The ADB/EMB project on "Vehicular Emission Control Planning in Metro Manila" (ADB/EMB, 1992). * The DENR/EMB-study "Air Pollution Emission Inventory for Metro Manila, 1990" by P-M. Ayala (Ayala, 1993).
URBAIR data collection
The following local consultants have provided additional data. See Appendix 8 for further details: * Dr. Reynaldo M. Lesaca and colleagues of Test Consultants Inc., provided data on population, pollution sources, fuel vehicle and traffic statistics, and air quality measurements (see Appendix 8 for summary of collected data). * Dr. Emmanuel G. Anglo, Meteorology Department of the University of the Philippines, at Diliman, Quezon City, provided data on meteorological and dispersion conditions, and also on dispersion modeling work (Anglo, 1994). * Prof. Elma B. Torres, and Dr. Ronald D. Subida of the College of Environmental and Occupational Health, University of Philippines, and Dr. Herminia A. Francisco, University of the Philippines, Los Banos, provided data on the health effects of air pollution, and on associated health costs (Torres et al., 1994).
DEVELOPMENTOF METROMANILA, 1980-1992
Figure 1.2 provides a summary of the available data regarding population, vehicles, fuel consumption and air quality, and economic development in the last decade. Changes in air quality during the past decade have not been adequately documented, and the quality of measurements made before 1986 is Table 1.1: World Health Organization and questionable (Lodge, 1992). Since 1986, Metro-Manila Air Quality Guidelines actual measurements show a variable trend WHO Philippines(Metro in TSP pollution. While certain areas such (ig/lm3) Manila)(ig/m3) as Paranaque and Valenzuela have become TSP more polluted, others such as Ermita are Longterm (annual average) 60-90 90 somewhat less polluted. Shortterm (24 hour average) 150-230 230 The WHO AQG and the guidelines PM10 applicable to Metro Manila are shown in Longterm (annual average) - 60 Table 1. 1. ~~~~~~~~Shortterm(24 hour average) 70 150 The TSP concentrations (annual Longterm (annual average 50 80 (0.03ppm) average) are up to five times higher than the Shortterm (24 hour average) 125 180(0.07 ppm) AQG (90 Ig/m3 ) at many of the measuring Lead sites. There has not been a general increase Longterm (annual average) 0.5-1.0 1.0 in S0 -concentrations (see Ch. 2.1), Shortterm (24 hour average) - 2 Source:WHO/UNEP (1992) and DENR (1993). URBAIR-Manila 11
although the AQG for SO2 (24-hour average) is exceeded at times. The population has grown steadily from approximately 6.1 million in 1981, to about 8.4 million in 1992, an increase of 37.7 percent. The total number of vehicles, primarily utility, has grown by 73 percent over the same period. Fuel consumption data for Metro Manila are available only for 1988, 1990 and 1992. The consumption of gasoline and diesel oil has increased substantially. Diesel consumption more than doubled from 1990 to 1992. Diesel is consumed by vehicles, industry and power generation. It is assumed that most of the increase took place in the industrial and small-scale power generation sector. Consumption of gasoline grew by 32 percent between 1985 and 1991. In the same period, diesel use rose by 96 percent, and fuel oil by 43 percent. The years following the EDSA revolution in which President Aquino came to power were characterized by an upswing in the economy. Gross National Product (GNP) growth rates recovered to their high levels. From -4.8 percent average annual growth in 1983-85, growth rates climbed to 5.5 percent in 1986-89. There was another slow down in the economy in the early 1990s, but this too has ended. In 1995, the annual growth rate was 5.8 percent.
POPULATION
Metro Manila's population grew by 33 percent from 1980 to 1990, as shown in Table 1.2. The growth occurred mainly in southern and northern Central Manila, with the largest increase in the southern municipalities of Paranaque, Las Pinas and Muntinlupa, where the population density is the lowest. The average population density was 12,500 per square kilometer in 1990. In the same year, Navotas and Manila had the highest density with about 72,000 and 42,000 per square
Table 1.2: Population and growth rate 1980-1990, NCR Population(thousands) Growthrate (percent) Pop.density (10 3/km=) 1980 1985 1990 1980-1985 1985-1990 1980 1990 NCR 5,926 6,940 7,948 17 14 9.3 12.5 1980-1990(percent) Manila 1,630 1,601 -2 42.5 41.8 Quezoncity 1,998 2,669 43 7.0 10.0 Nearcity, South 996 1,197 20 - SanJuan, 12.5 12.2 - Mandaluyong 7.9 9.5 - Makati 12.5 15.2 - Pasay 20.7 26.5 North 1,016 1,571 55 - Caloocancity 8.4 13.7 - Navotas 48.0 72.0 - Malabon 8.2 12.0 - Valenzuela 4.5 7.2 South 482 884 83 - Paranaque 5.4 8.0 - LasPinas 3.3 7.2 - Muntinlupa 2.9 6.0 12 Background Information kilometer, respectively. The lowest densities in the far North and the far South were 3,000 to 7,000 per square kilometer. Table 1.3: Age distribution Table 1.3 shows the age distribution in Metro Manila in 1990. of the Metro Manila Approximately 33 percent of the population was under 14 years population, 1990 of age. The median age was 22.4 years. The sex ratio was 94 Years % Years % males to 100 females. --
Only two percent of the trips are made on the light rail Table 1.7: Road network andpassenger transport line. The road system has not 1980 1983 1985 1990 Growth been expanded to keep pace Roadnetwork, km 2 647 2,987 1983-90:13% with the increasing demand. Unpavedroads 15.5% 10.8% This has resulted in a Transportdemand, NCR considerable increase in traffic Dailyperson trips (1 06) 10.97 13.08 17.65 198085:19% cons1derable1ntraffic mcrease ~~~~~~~~1985-90:35% congestion.. The main road Modalshare (%) system is depicted in Figure Privatevehicle 25.6 27.5 30.4 1.3. Jeepney 58.5 56.5 44.1 Bus 15.8 15.6 23.6 Commutertrain 0.1 - - Lightrail - 0.4 1.9 INDUSTRIAL SOURCES Table 1.8: Number of industrialfrms in Metro Manila, 1994
Although a complete DENR-NCRjurisdiction LLDA North South West jurisdiction industrialemissions survey No.of firms 282 567 780 1,429 does not exist, Metro Manila No.of air pollutingfirms 95 197 416 430 has a large and diversified withAPCF industrial structure. Table 1.8 -withpermit to operate 26 101 230 gives an overview of the -withoutpermit to operate 13 53 33 number of companies as of withoutAPCF 1994 (DENR-NCR, and -withpermit to operate 30 34 66 Lesaca, 1994). Of the 3,000 industrial companies, 1,100 are listed as air polluting. Many of these operate without a Table 1.9: Number of industries permit. As Table 1.9 shows, industries are located inMetro Manila, DENR-NCR throughout Metro Manila. (Manins, 1991). iurisdiction areas, 1986 According to an industrial emissions survey for the Foodmanufacturing industries 352 DENR-NCR areas (Ayala, 1993), the main air polluting Footwear 351 industrial source categories (not ranked) are: Paperand paper products 73 * Textile mills-sulfur dioxide (SO2 ); Rubberproducts 59 * Food and related products manufacturing-(S02); Chemicaland related industries 372 * Paper and related products-Particulate Matter (PM); Non-metallicmineral industries 91 . Petroleum and coal products-(PM); and, Basicmetal industries 180 * Fabricated metal products-(PM). Metalproducts 2,8618 The locations of more than 1,800 industries in NCR (E. Source:Manins (1991). Anglo, 1994) are shown in Figure 1.4. The database does not include plant, stack, and emissions data. These should be included in the future. 14 Background Information
Figure 1.4: Locations of factories in Metro Manila (1987)
0 4000 8000 12000 16000 20000 24000
36000 _ 3**6000
32000 32000
28000 28000
24000 24000
E 20000 X4* 20000
16000 16000 Manila Bay
12000 12000
8000 * 8000
4000 -* Laguna de Bay 4000
0 0 0 4000 8000 12000 16000 20000 24000 x (m)
Source:Anglo, E. (1994). URBAIR-Manila 15
FUEL CONSUMPTION
Fuel consumption data for Metro Manila are available for 1988, 1990 and 1992. Table 1.10 gives data for gasoline, diesel, fuel oil, kerosene, liquified petroleum gas (LPG) and aviation fuels. The primary data source was the Energy Regulatory Board (Lesaca, 1994).
Table 1.10: Petroleum product sales, Metro Manila (106 n. 1988 1990 Product Total Re-seller Individual Pi US Totala 1992 1990- consumers Govt bases Total 1992 Roadtraffic Premiumgasoline 772 679 62 68 3 812 1,018 42% Regulargasoline 28 10 3 0 41 194 Dieseloilb 1,080 599 583 84 16 1,282(+24) 3,102 138% Powergeneration Fueloil, total 3,669 0 3,508 2 0 3,510(+48) 4,225 19% Fueloil, in powerplants 1,409 1,131 1,662 47% Domestic/Commercial Kerosene 406 110 65 0 0 175 312 78% LPG 334 255 231 0 0 486 682 40% a) Numberin brackets:Intemational sales. b) Usedpartly for road traffic, partly for medium-to-small scale power generation. Source:For 1988: Manins (1993); For 1990, 1992: Lesaca (1994)).
There was a substantial growth in fuel consumption between 1982 and 1992. Gasoline consumption increased by 57 percent, diesel oil by 187 percent, and fuel oil by 5 percent. Kerosene and LPG consumption also increased substantially, but the total amount of air pollution emissions from these fuels is insignificant. There have been power shortage problems in Metro Manila since 1992, resulting in scheduled, periodic power outages. This has resulted in increased use of diesel-run generators for power supply. No estimate is available on the amount of diesel oil used for power generation annually. The substantial increase in consumption from 1990 to 1992 may, however, be partially explained by this use.
2. AIR QUALITY ASSESSMENT
This chapter provides an estimate of the population exposure to area air pollutants, and quantifiesK 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 the concentration distributions using dispersion modeling; and * calculating population exposure by combining spatial distributions of population and concentrations, and incorporating exposure on roads and in industrial areas.
AIR POLLUTIONCONCENTRATIONS
Overviewof database
Air pollution measurement programs reveal that Metro Manila has a substantial particle pollution problem. Measurements of TSP and PM10 frequently exceed air quality guidelines. The SO2 problem is much less pronounced, although guidelines are sometimes exceeded. S02 measurements, however, need further analysis. The emissions inventory indicates that SO2 concentration levels are significantly higher than the measurements indicate. Assessments are based on data from two monitoring networks. The monitoring networks, and results of measurements, are described in greater detail in Appendix 1. The DENR-NCR Air Quality Monitoring Network consists of seven stations that regularly report TSP and S02 data. The stations are divided among area-representative stations (Quezon City, Makati), those located near streets with relatively heavy traffic (Ermita, Paranaque, Las Pinas), and those located in industrial areas (Valenzuela, Pasig). Twenty-four hour average samples are taken a few days per month on a rotational basis. In periods of frequent power outages (1990-1993), one-hour average samples have been taken instead of 24-hour samples. The Asian Development Bank/Environmental Management Bureau (ADB/EMB) monitoring network of five stations operated from August 1991 to March 1992. Oxides of nitrogen (NOx), carbon monoxide (CO), and S02 were monitored continuously at one station. Twenty-four-hour samples of TSP, PMIo, and lead were taken every third and sixth day at some or all stations. Two stations, located on or near streets, had meteorological monitors.
17 18 Air Quality Assessment
Summaries of the TSP, PMIo, lead, and SO2 measurements follow. The measurements of CO, NOx, and ozone, described in Appendix 1, are insufficient to draw conclusions about the prevalence of these pollutants in Metro Manila.
TSP
TSP is a major air pollution problem in most of Metro Manila. It is especially acute near streetsk and industrial areas, and during the dry season. The Philippines has adopted the upper limit valte of the WHO AQG as their National AQG (see Appendix 2). The WHO guideline is 60-90 pL/m3 for long-term (annual) average, and 150-230 1ig/m3for short-term (24 hour) average. These values are clearly exceeded at all DENR-NCR measurement stations in Manila. Figure 2. 1a. gives annual averages for 1992, and Figure 2. lb provides the maximum values measured during 1990- 1992. The annual averages for 1990 and 1991 do not differ much from those in 1992. The highest annual average concentrations were measured at the Valenzuela station, situated in an industrial area dominated by lumberyards and light steel industries. High concentrations have also been measured in Manila (Ermita station). Annual TSP averages at the Ermita and Valenzuela sites are 2.5 to 3 times the guideline. Very high 24-hour average values have been recorded at all stations. Except for one extreme value, 823 gg/m3 at Makati (possibly due to some extraordinary industrial influence), the maximum values are 300-500 ,ug/m3,or twice the AQG. Figure 2.2 shows 24-hour samples of TSP measurements at the Valenzuela and Ermita sites for 1992. These are representative of Metro Manila, and show an annual variation with relatively higher values in the late winter (dry season) than during the wet season (starting July/August). Dry season TSP may be higher than wet season TSP by as much as a factor of two. This is probably because of increased wind speed and turbulence, causing dispersion, decreased resuspension from the ground, and/or increased washout of particles in the rain. The ADB/EMB Vehicular Pollution Control project made measurements near high-traffic Table 2.1: TSP concentrations (ug/m3) measured on sites areas. Table 2.1 shows TSP located on or near streets concentrations at some of these TSPconcentration Period No.of sites. On heavily exposed Station Street Average max.24 h 199111992observations streets such as the EDSA, TSP Ermita,Manila Taft 256 549 Aug.-Feb. 49 concentrationsare generally ADB,EDSA EDSA 497 843 Aug.-Feb. 47 very high; maximum 24-hour Monumento EDSA 400 489 Feb.92 5 concentrations reach 850 pgg/m3. URBAIR-Manila 19
Figure 2. la: Mean annual TSP concentrations for the year 1992 (pg/n)) Air Quality Guideline: 60 - 90 pg/m3 as annualaverage
Stations: 1: Ermita(street, 5 m fromcurb) 2: Las Pinas(street, 10 m from curb) 3: Paranaque(street, 10 m from curb) 4: Pasig(industrial) 5: QuezonCity (area) 6: CaloocanCity 7: Valenzuela(industrial) 8: Makati(area) 20 Air Quality Assessment
3 Figure 2. lb: Maxinmum 24 hours TSP concentrations during the years 1990-1992 (pg/m ) Air QualityGuideline: 150- 230 Vug/m3 as max.24 h. average
Stations: 1: Ermita(street, 5 m from curb) 2: Las Pinas(street, 10 m fromcurb) 3: Paranaque(street, 10 m from curb) 4: Pasig(industrial) 5: QuezonCity (area) 6: CaloocanCity 7: Valenzuela(industrial) 8: Makati(area) URBAIR-Manila 21
Figure 2.2: 24-hour TSP concentrationsgiven by month and dayfor the Ermita and Valenzuelasites (,g/m 3)
400 -
350- Ermita1991
300
250
ISO
150
00
5 8JIi1iO8_9_0 -I2 ;s
Valenzuela1992 450 400 ~350
150
100 50
0 ...... U 0 cor 22 Air Quality Assessment
PM 10
Health impacts caused by air pollution are correlated more to the presence of PMIo than TSP. Because PM1O particles are small they are more likely to penetrate the lungs and cause respiratory illness. The provisional national AQGs for PM,( are 60 ,ug/m3 for long term (annual) average, and 150 pg/m3 for the short-term (24 hour) average. The WHO AQG for PM1 Ois 70 gg/m3 for the short-term average. PM,( has been measured only at the traffic exposed stations of the ADB/EMB project along EDSA, Quezon City, during August 1992-February 1993, in the dry season. PM10 concentrations were high, indicating annual and 24-hour PMIo averages of more than twice the national AQG. The maximum 24-hour averages were more than four times the WHO AQG. PMIOconcentrations at area-representative sites are probably lower than those at the street sites. An estimate of the PM1 Oconcentrations at the DENR-NCR sites can be arrived at by using the average PM10/TSP ratio measured at the ADB stations. Using this ratio, the annual average PMIo concentrations at the DENR-NCR stations are estimated to be in the range 60-130 Vg/m 3 . This is considerably higher than the National AQG (60 [Ig/m3).The calculated PMIO concentration is highest at the Ermita and Valenzuela stations. Using the PM10/TSP ratio to be 0.5, the maximum PM1 O concentrations would, when using the PM,( /TSP ratio of 0.5, be about 150-200 g.g/m3,which is at or above the National AQG (150 pg/m3) and well above the WHO AQG (70 jig/m3). Measurements show that PM10 is a significant air pollution problem Table 2.2: PM,o concentrations (fug/m3)measured on sites throughout Manila, located on or near streets especially on and near the PM,oconcentration Period No.of main road network. Table Station Street Average Max.24 hr 1991/1992 observations 2.2 shows PM,( Ermita,Manila Taft 144 258 Aug.-Feb. 62 concentrations at some ADB,EDSA EDSA 219 321 " 47 sites along road networks. DENR-NCR QuezonAve 227 321 Oct.-Feb. 26 SanLorenzo, 179 206 Jan.-Feb. 10 Makati Monumento EDSA 198 241 Feb.92 5 Lead
Results from lead measurements at the Ermita, ADB, and Monumento sites of the ADB/EMB study are shown in Table 2.3, together with TSP and PM1 Oresults. In general, measured long-term lead levels exceed the national AQG (1.0 ptg/m3), and the WHO AQG (0.5-1 ,ug/m3). Some 24-hour averages of up to 5.5 pt/m3were recorded at the ADB site in 1991/1992. The national standard for lead content
3 Table 2.3: Lead, TSP and PM1 (gg/m ) from ADB/EMB study 1991/1992 Lead PMIO TSP Mean No.of measurements Mean/Max No. of measurements Mean/Max No. of measurements Ennita 1.07 (36) 144/258 (62) 256/549 (49) ADB 2.30 (34) 219/321 (47) 497/843 (47) Monumento 1.00 (4) 198/241 (5) 4001489 (5) Source:ADB/EMB (1992). URBAIR-Manila 23 of gasoline is given in Table 2.4. Table 2.4: Lead Content of gasoline (g/l) Low lead gasoline (0.15 g/l) was introduced Upto 1991 1992 in July 1993. After February 1994 unleaded Regulargasoline (RON 81 min) 0.4 gasoline was available in Premiumgasoline (RON 93 min) 0.84 0.6 key cities. Measurements Source;Rolfe (1992). show that the lead Table 2.5: Ambient concentration of lead: 1993 and 1994, concentration in the air 24-hour sampling time (p/r 3 ) have declinedsubstantially Year/MonthErmita LasPinas Makati Pasig QuezonCity Valenzuela as a result (NEDA, 1994) 1993 (See Table 2.5.) January 0.4 0.7 February 1.28 0.45 0.48 March 1.06 1.18 0.45 SO2 summary August 0.58 0.27 0.28 0.28 0.23 September 0.26 0.27 0.31 0.23 0.48 October 0.33 0.59 0.38 0.37 The sumnmaryof November 0.56 0.49 0.33 0.49 measurements in December 0.57 0.28 0.66 1990/1992, as shown in 1994 Figures 2.3a and 2.3b, January 0.33 0.23 0.37 0.63 0.26 0.45 indicates that the long- February 0.4 0.24 0.29 0.29 0.87 term March 0.42 0.17 0.39 0.42 0.85 averagelemaessgthacnthalfthenconcentration April 0.21 0.14 0.29 0.18 is low, less than half the May 0.2 0.16 0.25 0.17 AQG, and maximum 24- June 0.29 0.35 0.17 hour values occasionally July 0.24 0.24 0.19 exceed the AQG. The TGS Note:April to July 1993 n.a. (Pararosaniline) Source:NEDA (1994). calorimetric method is used to measure this. SO2 monitoring at the Ermita station during the ADBIEMB study gave 24-hour average values up to 0.035 ppm for a one-month period. Considering the amount of high-sulfur fuel oil used in Manila, this measured SO2 concentration level appears to be low. Table 2.6 shows calculated emissions data for SO2 and TSP Table 2.6: Calculated SO2 and TSP emissions, 1992 3 for various Source(s)-10tonslyr MeasuredSO 2fTSP combinations of area- Traffic Traffic+ Traffic+ concentrationratios wide source categories, areawidefuel areawidefuel + at DENR-NCRsites, as well as the S0 2/TSP resuspension+ averages,1992k ratio (see Ch. 2.2). The 258.0 constrn17.0ction measuredS02/TSPS0 2 emission 170 280258.0 measured S02/TSP TSPemission 8.9 25.9 60.9 ratios at DENR-NCR SO)TSP 1.9 10 4.2 0.08-0.14 3 sites are also shown. Note:t An extra-urban background of30 g/im hasbeen subtracted from the TSP measured values. Power plant emissions are not included in this exercise because high stacks do not have a pronounced impact on ground- level concentrations. 24 Air Quality Assessment
Figure 2.3a: Mean annual SO2 concentrationsfor 1992 (ppm)
Air QualityGuideline: Phil. Ntl. Who 0.03ppm 0.02ppm as annual average
Stations: / 1: Ermita(street, 5 m fromcurb) l.- 2: Las Pinas (street,10 m from curb) \ /1 3: Paranaque(street, 10 m from curb) ^/%s 4: Pasig(industrial) \JN\. 5: QuezonCity (area)l_ 6: CaloocanCityI 7: Valenzuela(industrial) / 8: Makati(area) URBAIR-Manila 25
Figure 2.3b: Maximum 24-hour SO2 concentraions during 1990-1992 (ppm) Air QualityGuideline: Phil.Ntl. Who 0.007ppm 0.005ppm as max.24 h. average
Stations: 1: Ermita(street, 5 m fromcurb) 2: Las Pinas(street, 10 m fromcurb) 3: Paranaque(street, 10 m fromcurb) 4: Pasig(industrial) 5: QuezonCity (area) 6: CaloocanCity 7: Valenzuela(industrial) 8: Makati(area) 26 Air Quality Assessment
The measured ratios are much lower than the ones from the emissions survey. The discrepancy may be explained by the following factors: * The TSP emissions inventory is not comprehensive. Resuspension of dust, an important pollution source, is only roughly estimated. No data are available for wood and coal consumption. Industrial process emissions are also significantly underestimated. * S02 emissions standards is not sufficiently precise. The actual sulfur-content of bunker oil/heavy fuel oil might be much lower than the maximum allowed 3.8 percent which was used for the estimates. If the actual sulfur content of bunker oil is actually lower, the modeled SO2 level would also be lower. * The SO2 measurements give suspiciously low concentrations. S02 concentrations reported during 1977-1989, as summarized by UNEP/WHO (1993), may be taken to support these items. Measurements before 1983, reported SO2 concentrations three times higher than the TGS bubbler method used after 1985. This discrepancy should be resolved by better quality assurance and measurement standards.
AIR POLLUTANT EMISSIONS
Total emissions
Many attempts have been made to produce a complete air pollutant emissions survey for Metro Manila. In 1991, P. Manins developed a gridded emissions inventory for S02 in connection with establishing a "model for air pollution planning" (Manins, 1991). In 1993, P. M. Ayala prepared the methodology for carrying out a total emissions survey and completed a total emissions survey for CO, NOx, SO2, TSP, PMIo and total organic gases (TOG) (EMB, 1993). This survey is not gridded and the emissions are not distributed spatially over the city. The results of emissions surveys are summarized in Appendix 4. These surveys have been completed under many constraints, especially the completeness of the input database. The most pronounced shortcoming is that emissions data from industrial plants have not been available from the LLDA jurisdiction areas (Manila, Quezon City, Caloocan, Marikina, Pasig, Pateros, Pasay, Taguig, Muntinlupa). URBAIR calculated total emissions for TSP, PM10 , and SO2, based on the studies mentioned above, the work done within the ADB/EMB Vehicular Emission Control Project (VECP, 1991), and additional data on traffic and fuel consumption provided by Test Consultants Inc. in Manila (Lesaca, 1993). This emissions inventory is presented in Table 2.7, based on the emissions factor data given in Table 2.8, and the fuel consumption and traffic activity data of Table 2.9. The traffic activity data are described in detail in Appendix 4. The fuel consumption data for 1992 were taken from official statistics (Lesaca, 1993). The inventory covers the main source categories. "Generator sets" is not a separate category in the inventory, since data on the fuel consumed by these are not available. Fuel consumption is included under DOF. Source contributions to TSP and PM1 o are shown in Figure 2.4. As described below, and in Appendix 4, the emissions inventory is not completely accurate. Some of the estimates are rough and based on incomplete background information. While the accuracy of the figures has not been estimated, the inventory is considered sufficiently accurate URBAIR-Manila 27 for an initial estimate of source contributions and provides a suitable background for a first stage cost-benefit analysis.
Table 2.7: Total annual TSP and SO2 emissions in Metro Manila, 1992,according to source groups Emissionsources Vehicletype/industry TSP PMIO S02 tons/yr % tons/yr % 103tons/yr TransportSector Exhaust Gasolinevehicles Cars 580 0.8 580 1.4 UV 1,180 1.6 1,180 2.7 MC/fC 290 0.4 290 0.7 Bus/truck 150 0.2 150 0.4 Dieselvehicles Taxies 170 0.2 170 0.4 UV 1,160 1.5 1,160 2.7 17.0 Jeepneys 1,580 2.1 1,580 3.8 TruckWbus 3,800 5.1 3,800 9.0 Sumvehicle exhaust 8,910 11.9 8,910 21.1 Re8ufspe fromroads 25,000 33.4 6,250f 14.9 Energy/industrysector Powerplants 2,120a 2.8 2,01Ob 4.7 101.8
Otherfuel combustion BOF(Bunker) IndustriaVcommercial 14,380 19.2 12,220c 28.9 216.6 DOF(Diesel) IndustriaVdomestic 2,550 3.4 1,280d 3.0 24.2 Kerosene 20 - 20 - LPG 40 0.1 40 0.1 Wood ? - Coal - Sum,fuel combustion (excludingpower plants) 16,990 22.6 13,570 32.0 Industral.rocessess 6,000 8.0 3,000e 7.1
...... Other Refusebumings (<)6,000 (<)8 (<)6,000 14.2 Constructiong 10,000 13.3 2,500f 5.9 Sum (<)75,020 100 (<)42,240 100 359.6+ Notes:a) Emission control: Multicyclone f) PM,= 0.50x TSP(Rough estimate) b) PM,0= 0.95x TSP(Ref.: EPA AP42) g)PM,0 = 0.25x TSP(Rough estimate) c) PM,,= 0.85x TSP(Ref.: EPA AP42) h) Roughestimates d) PM10= 0.50x TSP(Ref.: EPA AP42) i) Estimateby taking maximum sulfur content allowed for each fuel category since = unknownfigure actualsulfur contents were not available .Actual emission would be less. 28 Air QualityAssessment
Table2.8: Emissionfactors for TSP Emissionsource Vehicletype/ Industry Thiswork AyalaADBIEMB Vehicles Gasoline Cars 0.2g/km 0.1 UV 0.33g/km 0.12 MC/TC 0.5g/km 2.0 Diesel Taxies 0.6g/km 0.6 UV 0.9glkm 0.9 Jeepneys 0.9g/km 0.9 Truck/bus 2.0sk .
Fuelcombustion Powerplants 1.5kg/m3 BOF(Bunker) IndustriaVcommercial5.1 0 DOF(Diesel) Industrial/domestic 1.4' Kerosene 0.06kg/ton LPG 0.06kg/ton Refusebuming Residential 37g/kg Source:For a listof references from which emissions factors have been compiled, see Appendix4.
Table2.9: Trafic activityandfuel consumption data, 1992 Emissionsource Vehicletype/ Industry 103m 3/yr 109vehicle km/yr Vehicles Gasoline Cars 292 2.92 UV 536 3.57 MC/TC 28 0.57 Bus/truck 66 0.22 Diesel Taxies 29 0.29 UV 262 1.75 Jeepneys 194 1.29 Truckibus 571 1.90 ...... I...... Fuelconsumption Powerplants 1,410 BOF(Bunker) IndustrialVcommercial 2,830 DOF(Diesel) IndustriaVcommerciaVdomestic1,820 Kerosene 312 LPG 682 Wood notavailable Coal notavailable Source:See Appendix 4 for references. URBAIR-Manila 29
Figure 2.4: Source contributions to TSP and PM1 Oemissions, 1992 TSP
X Largepoint sources
/ ...... UI1 Gasolinevehicles
. Dieselvehicles
El Resusp.
SOMMEM"INnBOF
EDOF
- Fuelcomb.
L Ind. proc.
PM10 Misc. 30 Air Quality Assessment
TSP emission
A rough estimate for industrial processes emission is given in Table 2.7. It is based on the Ayala emissions survey, presenting total emissions from industries by industrial branch. The present work estimates the amount of calculated TSP emission that is associated with fuel consumption based on Ayala's S02 emission. The rest are presumed to be process emissions. The emission figure for construction, based mainly on USEPA emission factors, is also taken from Ayala's work. Total emissions from refuse burning are also approximately estimated. The estimate is based on one million households in Metro Manila, each burning half a kilogram of refuse per day. This is probably an overestimate, especially since refuse burning is not as large a source of TSP as compared to other fuel combustion. In order to estimate road dust resuspension, USEPA suggests the following emissions factors (EPA, AP 42) for different road classes: * local streets (AADT less than 500): 15 g/km * collector streets (AADT of 500-10,000): 10 g/km * major streets (AADT of 10,000-50,000): 4.4 g/km * freeways/expressways (AADT greater than 50,000): 0.35 g/km These factors are suggested for dry road conditions. Much of the traffic activity in Metro Manila takes place on roads with AADT greater than 50,000. Assuming the traffic activity share of these road classes are 5 percent (local), 25 percent (collector), 30 percent (major), and 40 percent (freeway/expressway), and that the roads are wet 50 percent of the time, EPA emissions factors suggest an average factor of slightly more than 2 gram per kilometer. Even this may be an overestimate. However, two grams per kilometer was selected as an average resuspension emissions factor for Metro Manila. TSP concentrations measured at the ADB study street stations support a resuspension factor of close to this magnitude. Also, a recent evaluation of emission rates from roads based on measurements, supports the EPA emissions factors for paved roads, although the study concludes that more investigation is needed (Claiborn et al., 1995). Emission estimates for power plants are based on an emission factor of 1.5 kilogram per cubic meter, assuming multi-cyclone emission control. If the multi-cyclones are out of order, which is sometimes the case, the emissions are about four times greater. Due to tall stacks that disperse the emissions, power plants are not significant contributors to ground-level particle concentrations. The largest contributors to TSP and PMIo are bunker oil (BOF) combustion in small-to- medium industrial and commercial installations, resuspension, and construction activities. (Figure 2.5) Vehicle exhaust contributes about 12 percent of total TSP emissions. The largest contributors are diesel trucks and buses (6.2 percent) and diesel jeepneys (2.7 percent). URBAIR-Manila 31
Figure 2.5: Dispersion modeling area, NCR
N
0 5 km
Jurisdictionoareas:Quezon City
4: Pasig~~ ~~ ~~~~~~~~~ai
|Clear: LLDA 5 Monitoringstations: B i 1llmn 2: LasPinas t il...... 3: Paranaque 77 Mutnl\YlP h 5: QuezonCity ' modelling 6: CaioocanCityaa 7: Valenzuela 8: Makati V 32 Air Quality Assessment PM,, emission PM,( emission estimates are based on TSP emissions, and PM1 o /TSP ratio (see footnotes to Table 2.7). There are approximately 45,000 tons of PMIo emission per year, 60 percent of total TSP emission. Vehicle exhaust particles are more significant for PM1o, comprising 20 percent of the total emissions, compared with 12 percent, relative to total TSP emissions. Resuspension, consisting mainly of coarse particles, contributes 14 percent of PMIo, compared with 33 percent of TSP. SO2 emission S02 emission from fuel combustion is based on the sulfur content of fuel. The following contents are used in the estimates (Lesaca, 1994): BOF (3.8 percent); diesel (0.8 percent), and coal (2.5 percent). Actual sulfur content is probably less than these maximum allowable levels. There is no complete information on S02 emission from industrial processes, or from coal consumption. SO2 emission at times exceeds AQG in the area (1-4 kilometer) near the power plants. Lead emission The total lead (Pb) content in gasoline consumed in Metro Manila in 1992 is Table 2.10: Lead Emission Estimates for 1992 calculated in Table 2. 10. Premiumgasoline 1, 018.1061 @ 0.6 g Pb/I equals 611tons Annual lead emission in Metro Regulargasoline [email protected] g Pb/I equals 78tons Manila in 1992 was 520 tons in TSP, Total 689tons and 240 tons in PM1 O. Since low lead and unleaded gasoline have now been made available, these emissions should diminish substantially. Some of the lead is deposited in vehicles' exhaust systems. Measurements show that during urban driving, about 35 percent of the gasoline lead is emitted immediately as particles in the PM1 O fraction (Haugsbakk and Larssen, 1985). During acceleration, part of the lead deposited in the exhaust system is emitted as larger particles. It is generally assumed that about 25 percent of the lead in gasoline is pennanently deposited in exhaust systems. Spatial emi.ssion distribution of vehicle exhaust particles. In order to conduct a cost-benefit or cost-effectiveness analysis of abatement measures, it is necessary to establish an air pollution exposure base-line, and spatial concentration fields over the urban area. The main air pollution problem in Metro Manila is high particle concentration, and in order to model the spatial distributions, a gridded particle emissions survey was needed. Road traffic was the only source with sufficiently detailed data to produce a gridded emissions inventory. Its background and methodology are given in Appendix 2. A square- kilometer grid system of 18 X 30 grid squares was established, covering Malabon in the north, to Las Pinas in the south, and from Manila in the east to Marikina in the west (see Figure 2.5). Valenzuela and the northern part of Quezon city were not covered by the model area because the basis for the grid system and road network was the I to 25,000 scale map of Metro Manila which does not include Valenzuela. URBAIR-Manila 33 The populationwas distributedover the grid system,based on the municipalityand taking into account residentialand non-residentialareas apparentfrom the map (see Appendix2). Figure 2.6 shows a classificationof the calculatedpopulation density. Figure 2.7 gives the gridded emissionsdata for TSP exhaustfrom road traffic. There are large emissionsin downtownManila and in the grids along EDSA. The largest densitywas calculated for the grid (at coordinates8,15), which includedthe intersectionof EDSA and the South DiversionRoad. The emissiondensity in this grid was 1.28tons per year of exhaust particles. High emissiondensities in downtownManila are typicallyone ton per year. DISPERSION MODEL CALCULATIONS Dispersion conditions (;ertl'c/ description *f lopography/cihmate/dispersion.The Philippines is located in the subtropical climatezone. Air temperatureaverages between 260 and 27°C, and the seasonal variation is only 3-40C. Regionalclimate differences are largely due to rainfall distribution.The western coast of Luzonhas a marked dry seasonand rainy season. There are heavy rains from June to December,when the southwestmonsoon dominates. The winter and spring seasons are dry becausethe coastlineis shelteredfrom the north-easttrade winds. The eastern coast has a more even distributionof rain throughoutthe year. Most of it falls during the north-easttrade wind regimes. In the summerthe southern monsoonwind brings the rain to the eastern coast. The averagerainfall varies from under 1,000millimeters on the valley plains to 4,500 millimetersin the mountains. 34 Air Quality Assessment Figure 2.6: Calculated population distribution, NCR, 1992 U<40 U <60 Note:s kn Aa1,00is sn inFep 260 Note1,0pesn pe k_2 Are isshw iiur URBAIR-Manila 35 Figure 2. 7. Gridded TSP (i.e. exhaust particles) emissions from road traffic, NCR, 1992 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 I8 J=30 49. 70. 69. 185. 114. 147. 196. 260. 442. 442. 452. 338. 196. 196. 303. 192. 65. 82. J=29 98. 33. 190. 115. 220. 539. 395. 26S. 458. 392. 432. 358. 304. 272. 229. 65. 65. 114. J=28 274. 94. 380. 687. 963. 901. 409. 515. 768. 494. 434. 32. 335. 422. 159. . 16. 163. J=27 306. 409. 219. 624. 865. 650. 262. 409. 638. 590. 435. 610. 348. 218. 224. 16. 49. 131. J=26 5. 258. 654. 727. 518. 842. 535. 627. 803. 547. 545. 456. 409. 245. 147. 33. 131. 65. J=25 . 354.1029. 921. 526. 746. 541. 835. 694. 741. 978. 512. 648. 445. 157. 181. 181. 83. J=24 . 663. 894.1037.1254. 948. 832. 512. 516. 663. 709. 939. 619. 327. 128. 184. 177. 67. J=23 . 687.1059.1033.1161. 428. 818. 40S. 652. 804. 334. 834. 570. 358. 49. 109. 203. J=22 . 542.1018.1028.1283.1181.1116. 939. 717. 811. 938. 845. 513. 360. 82. 65. 139. 28. J=21 . 19. 619. 914. 693. 461. 217. 595. 719. 604. 403. 405. 629. 262. 295. 91. 16. 53. J=20 . . 691. 807. 902. 724. 331. 287. 354. 665. 675. 654. 272. 245. 215. 209. 166. 160. J=19 . . . 595.1063.1228. 854. 298. 327. 523. 737. 878. 221. 182. 162. 31. 49. 49. J=18 . . . 193.1119.1289. 912. 717. 698. 576.1199. 321. 357. 266. 160. 49. J=17 . . . 49. 780. 594.1057.1003. 961.1170. 902. 287. 333. 133. 82. 33. J=16 . . . 56. 536. 288. 774.1038.1153. 763. 115. 181. 297. 199. 33. 16. J=15 . . . . 298. 409. 580.1460. 672. 459. 224. 1. 275. 163. 33. 16. J=14 . . . . 269. 330. 290. 620. 529. 76. 74. . 33. 84. . J=13 . . . . 221. 296. . 65. 437. 16. . . . 58. . J=12 . . . . 174. 366. 128. . 174. 347. . 65. 29. 58. 33. J=11 . . . . 192. 202. 16. 49. 82. 255. 147. 131. 26. . 114. J=10 . . . 34. 344. 58. 147. 147. 98. 445. 255. 163. 46. . . J= 9 . . . 227. 191. 67. 33. 131. 126. 218. 410. 99. 54. . . J= 8 . 69. 174. 63. 33. 320. 185. 131. 114. 147. 320. 49. 16. . . J= 7 . 120. 91. 114. 98. 114. 266. 418. 217. 131. 288. 33. . . . J= 6 9. 18. 292. 163. 98. 33. 163. 147. 353. 250. 288. . . . . J= 5 18. . 217. 283. 386. 131. 131. 147. 163. 114. 407. . . . J= 4 9. . 49. 163. 299. 386. 250. 147. 163. 49. 304. . . . . J= 3 . . . 49. 163. 147. 201. 402. 250. 131. 304. . . . . J= 2 . . . . 98. 131. 131. 114. 369. 185. 304. . . . . J= I . . . . 16. 49. 147. 131. 98. 56. 552. . . . . 1 2 3 4 5 6 7 8 9 10 11 12. 13 14 15 16 17 18 Note:Maximum value is 1.4602E+01,in (8,15).Sum is 1.4037E+03.Scale is 1.OE-02.Grid size 1,000meters. Unit: kglh. 36 Air Quality Assessment Manila is located on the mouth of the Pasig River in the Manila Bay, on the western coast of the Luzon Island. The Manila plain is a densely populated agricultural area and is open to the sea (Manila Bay) on the west, and to a freshwater lake to the east (Laguna Lake). Several mountain chains, 1,000 to 1,500 meters high, run parallel with the main axis of the island. In the north the big mountain chain Cordillera Central forms the main ridge of the Luzon island, and consists of several parallel crests with an average height of 1,650 meters. Along the northeast coast runs the Sierra Madre, with a length of about 560 kilometers. The Sierra Madre chain is volcanic and slopes steeply down toward the ocean. Cagayan valley, the main agricultural area, is located between these main mountain chains. The central Manila plain runs parallel to the Cagayan valley but is west of Cordillera Central. Near the coast, the sea breeze dominates. The dominant wind direction in the Metro Manila region is the north/northeastern trade wind, and to a lesser extent the south/southwestern monsoon. The Philippines Atmospheric Geophysical and Astronomical Services Administration (PAGASA) collects hourly spot readings of speed and wind direction in the Metro Manila area at the Ninoy Aquino International Airport (NAIA), the Manila Port area (MCO) and at PAGASA in Quezon City. The Climate Data Section of PAGASA summarizes these as daily averages. PAGASA measures wind speed, wind direction, air temperature, air stability and rainfall. Dispersion conditions. Wind conditions and the vertical stability of the atmosphere determine dispersion of air pollution emissions. An evaluation of wind data from the three Metro Manila measurement sites reveals that the data from NAIA and the Science Garden (SCI) in Quezon City appear less dependable than those from the Port Area site, possibly due to local influences from nearby buildings that disturb the wind flow (Anglo, 1994). The URBAIR analysis, therefore, emphasizes Port Area data. Figure 2.8 shows wind roses for the three stations for January, April, and August 1992, from a database established as a part of the URBAIR work. There are similarities in wind direction distributions at the Port Area and Science Garden (near Quezon City) stations, with lower wind speed expected at Science Garden. The directional wind rose at the NAIA indicates a serious local effect on the sensor, possibly due to nearby buildings. Figure 2.9 gives average wind roses for January, April and Table 2.11: Analysis of the Pasquill/Guifford stability classes based August, as well an on data from Manila Tegen station annual average for Stabilityclasses 1961-1980 (Anglo, Windspeed Very ModeratelySlightly SlightlyModerately 1994).Data on the miles/secondunstable unstable unstableNeutral stable stable 1994).on the Data 0.4-1.7 0 0 1.2 5.2 0.5 0 vertical stability of the 1.8- 3.5 0 0 0 6.0 8.8 0 Metro Manila 3.6 -5.7 0 0.6 0 16.4 9.6 0 atmosphere (Table 5.8-8.4 0 1.6 3.5 17.0 4.3 0 2.1 1) come from the 8.5-10.6 1.2 3.2 3.5 8.2 1.2 0 2.l1)comefromthe ~~>10.7 6 0.9 0 1.1 0 0 Manila (Tegen) station Note:Total frequency of the unstable, neutral and stable conditions are given. near the mouth of the Pasig River. From this data, a combined wind/stability matrix was constructed. Such a matrix representing the statistics of dispersion climatology can be used as input to dispersion models to calculate long-term average concentrations of pollutants. The combined matrix is given in Table 2.12. *1~~~~~~~~~~~~~~~~~~~~~0 P3 rn~~~~~~~~~ <~~~~ X 38 Air Quality Assessment Figure 2. 8b: Wind roses for 1992, Metro Manila meteorological stations TOWrw4 - *4 TOW S2 N Y: N Yw ...... LWb Swt .. S :Frfi W Os W~~~~~~~~~~~~~~~kfmN gS J S~~ SdtN 20 ' ."o'x30s. ' 40140 S S 5-3,4 15-14 mSA357 54-79 0 Sb*m : " Stto I N YS: IIIi2 N Y:i SE ...... ' '' " ...... , .,~~~~~~~~~~~~~Mt Ateg %~~~~~~~~~~~~~~~=.,,.,,,....-. ,.oo S S 35-54 5-7S9WOU.4 -554 SZ-7 7S ..w ______b __, ___._ (n! z z 6 z4f ...... ~~~~~~~~~~~~ [t1WX [|1WW~~~~~~~~ 1' ('1 t"Z *11~~ ~ ~ 1 w I '.i iz i ______ S w S^...... d ., ,.. '" ':, L .. I... . z~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...... URBAIR-Manila 41 Adversedispersion conditionsin Metro Table 2.12: Wind/stabilityfrequency matrix (annual), Metro Manila. Weak and short- Manila lived inversions are typical Sector 0-1.4m/s 1.5-3.4m/s in a tropical, coastal city. degrees U N L S U N L S 45 These inversions generallygenery ~90 2.0 0.30.2 1.51.0 9.59.0 break up with sun rise. 135 0.9 0.1 1.0 4.0 When a land-sea breeze runs 180 0.6 0.4 0.2 1.8 3.0 opposite at greater speed to 225 0.4 0.2 0.1 2.8 0.2 the onson,de to270 0.6 0.4 0.3 4.4 0.3 the monsoon,due to 315 0.1 0.3 0.1 1.8 0.1 atmospheric inversion high 360 0.1 1.1 0.1 0.3 4.5 1.2 ground-level concentrations Sum 1.8 7.3 0.7 0 1.0 18.8 27.3 0 occur, especially during 9.8 47.1 ealSector oinsy 3.5-5.4m/s >5.5m/s early mornings when the sky degrees U N L S U N L S Sum is clear and the inland 45 0.6 1.1 1.2 0.3 15.4 airmass is cooled from 90 0.8 2.2 1.3 0.7 18.3 below by the ground. 135 0.6 2.0 1.4 1.2 11.2 180 0.6 1.2 2.4 0.4 10.6 A combinationof weak 225 0.6 0.9 1.8 3.1 0.1 10.2 wind speed and unstable 270 0.3 5.2 2.5 3.5 17.5 atmospheric conditions 315 0.1 2.3 4.8 during the day may lead to 3Su 0.1 2.9 0.5 0 2 1.0 12.0 vertical turbulent motions, 22.0 21.1 100 and high ground-level Note:U - unstableN - neutralL - lightstable S - stable concentrations near point sources (stack emissions). The plume may not be diluted enough before the downward drafts move it towards the ground, resulting in high short-term, ground-level concentrations. Dispersion model calculations, city background Model description. The dispersion modeling work in this first phase of URBAIR concentrates mainly on the calculation of long-term (annual) average concentrations, representing the average within square-kilometer grids ("city background" concentrations). Contributions from nearby local sources in specific receptor points (e.g. street side, industrial hot spots) must be evaluated separately. The dispersion model is a multisource Gaussian model treating area, point, and volume sources separately. Meteorological input to the model is represented by a joint wind speed/direction/stability matrix representing the annual frequency distributions of these parameters. The dispersion conditions are considered spatially uniform over the model area. For point sources, account is taken of plume rise (Brigg's equations), effects of building turbulence, and plume downwash. For area sources, total emissions in a square-kilometer grid are simulated by 100 ground-level point sources, equally spaced over the land area. The software package used is the KILDER model system developed at NILU (Gram and B0hler, 1992). Secondary particle formation, such as secondary sulfate and organic aerosol, are not taken into account in this modeling exercise which treats only dispersion of primary emission compounds. 42 Air QualityAssessment Further modeling and particle analysis should be done to estimate the extent of secondary particle formation. Suspended particles Vehicle exhaust particles. Dispersion modeling is conducted only for the road vehicle source category, for which reliable data are available. Figure 2.10 shows the isolines of the concentration field, based on the calculated annual average concentrations in each square-kilometer grid. The emissions distributions in Figure 2.7 are modified for different dispersion conditions caused by distinct density and height of buildings in various parts of the area. The isolines show the highest concentrations of emissions in the same area. In general, the emissions are largest in downtown Manila. The highest annual average concentration was 39Rg/m3. Total TSP and PM,O concentrations from area sources. Vehicle exhaust particles account for an estimated 12 Table 2.13: Total TSP and PM, 0 percent of TSP emission and 20 percent of PMIo emissions from area distributed emission in Metro Manila (see Table 2.13). sources (tons/yr) The spatial distribution of emissions from the TSP PMIO various source categories can be separated into two Vehicleexhaust emissions 8,910 8,910 groups: area sources and point and industrialsources. 50%of DOF combustion 1,300 650 groups:area sources and point and industrialsources. * Refuseburning (<)6,000 (<)6,000 Area sources, whose spatial distribution is determined Construction/Resuspension35,000 8,500 by population distribution and the road network, include Total 51,210 24,060 traffic, commercial/domestic fuel combustion, refuse burning, and construction. Point and industrial sources concentrated in industrial areas include power plants, industrial process emissions, and industrial fuel consumption. Particles in vehicle exhaust contribute an estimated 17 percent of total TSP from the area distributed sources, and 37 percent of total area source PM1 o emission. The diesel and BOF not used by buses and other vehicles is probably used by industry. The maximum concentration calculated in downtown Manila (35 pg/M 3) correspon3dsto a total TSP 3 concentration of about 235 ,ug/m , and a total PMIo concentration of 105 ,ug/m . This accounts for the contributions from other area-distributed sources, and an additional 30 pg/M3 (15 pg/m3 for PM1o ) as extra-urban background. TSP: 35g/m +30 ug m3 = 235 ug / m3 0.17 PM10 35 gM3 +lS,uig/m3 =llO g/m 3 PMi~: 0.37 jiLg Table 2.14 shows corresponding vehicle exhaust particle concentrations (Cv) and TSP concentrations (CTsp), when an extra-urban background concentration (Cb) has been added: CV + Ch= CSP C + Cb=CPMO 0.17 0.37 URBAIR-Manila 43 Figure 2.10: Road traffic exhaust particle concentration distribution (,ug/m3), annual average 1992, Metro Manila N~~~~~~~ jq y ' f A 0~~~~~ <~~~~~~~~~~~~ N~~~I 44 Air Quality Assessment Table 2.15 compares measured and calculated TSP. Table 2.14: Corresponding The calculated values represent the average concentrations of vehicle ecxhaust concentrations in the grid squares where the sites are particles (Cr) and TSP and PMIJ located. Local exposure from nearby roads and industries in Metro Manila, Base case, 1990 have also been indicated. Calculations do not account for Cb secondary particle formation. Cv TSP PM1o CTSP C PM1o At Makati, where local exposure seems small, there is 35 30 15 235 110 general agreement between measured and calculated 20 30 15 145 70 annual average TSP. At all other sites, the calculated TSP 10 30 15 90 40 values are lower than measured values. The discrepancies may be accounted for by additional local exposure from roads and industry. Table 2.15: Measured TSP concentrations at Ermita, Las Pinas and Paranaque have DENR-NCR sites, and calculated area-source definite road exposure, and Pasig, average TSP concentrations in thzegrid squares Caloocan and Paranaque have industrial where the sites are located exposure. The "construction" source is C, CTSP CTSP Localexposure from significant, and its distribution over Caic. Caic. Meas. Roads Industry Manila is unknown. This may account Ermita,Manila 30 195 219 + ? for some of the discrepancies. Despite Caloocan 15 113 150 ? + the discrepancies, the dispersion QuezonCity 20 140 178 (+) (+) calculation is a fairly good Pasig 10 85 183 (+) + Makati 23 158 146 - (+) representationof measuredTSP. Las Pinas 11 91 115 + + Paranaque 10 85 166 + + SO2 dispersion. The SO2 emissions NOTE: + Definateinfluence (+)Weaker influence standards (Ch. 2.2) was used as a basis -Noinfluence ? Unknown for calculating a first approximation of the SO2 distribution in Metro Manila. SO2 emission sources are: diesel vehicles (according to the traffic activity pattern described in Appendix 2); power plants calculated as point sources, with stack and fuel data as referenced by Manins (1993), and industrial, commercial, and residential use of diesel and BOF (a first approximation distributed according to population distribution, since the actual spatial distribution of industries is not available.) Calculations of annual average SO2 are shown in Figure 2.11 (the dispersion model as used for TSP). Contributions from various sources, and the total distribution are presented. The main contribution comes from BOF and diesel combustion which is considered a low-level source. The 3 first estimate of total annual average S02 concentration is calculated to be 120-150 pLg/min central Manila. Annual average S0 2 measurements at Ermita, from 1977 to 1983, range between 50-1 1O pg/m3 URBAIR-Manila 45 3 Figure 2.11: Calculated first estimate SO2 concentration distributions (ig/rm , annual average), 1992 POWERPLANTS INDUSTRY TRAFFIC . .. TOTAL 0"0~~~~~~~~~~~~0 / ) -4vof; g X 46 Air Quality Assessment Pollution hot spots Pollution hot spots are characterized by significant pollution sources that emit large concentrations. Such hot spots are located: * along the main road system; and * near industrial areas with significant emissions, especially through low stacks. Examples of hot spot pollution concentrations have been calculated by Anglo, 1994. Metro Manila power plant.. The Metro Manila power plant is a 200-megawatt plant run on Bunker C fuel. It is equipped with 76-meter high stacks. SO2 concentrations are calculated for a ten kilometer radius of this power plant, using an average emission rate of 760 grams per second (corresponding to 24,000 tons per year) and statistical meteorological data for the Port Area meteorological station (Anglo, 1994). The results are given in Figure 2.12, showing isopleths for the following: * monthly average SO2 concentrations for January and August; * maximum 1 hour concentrations for the same months; and, - maximum 24 hour concentrations for August. Maximum one-hour concentrations up to approximately 250 Rg/m 3 are calculated. Concentrations above 200 ig/rM3 occur within four kilometers of the plant during January and August. Maximum 24-hour concentrations reach 140 gg/m 3 in August, about two kilometers northeast of the plant. Monthly average concentrations reach 80 Rg/m3 in August, approximately four kilometers northeast of the plant. The exposure from this plant alone does not exceed national AQG, although the WHO guideline may be exceeded. However, calculations show that 24-hour average national AQG for SO2 may be exceeded particularly northeast of the plant, if city background SO2 from diesel and BOF combustion, and from diesel vehicles is added. PM and S02 exposurenear main roads. Typical hourly concentrations Table 2.16: PM and SO2 exposure near main roads of exhaust particles and SO2 have been Trafficdata (AADT) Emissionfactors (g/km) calculated for selected sections of Taft Taft EDSA ExhaustParticles S0, Avenue and EDSA, both dominated by Cars 21,400 130,500 0.33 0.123 car, bus, and heavy jeepney traffic Taxis 1,050 6,500 0.45 0.634 (Anglo, 1994). Anglo uses Jeepneys 22,800 2,500 0.45 1.268 Trucks 4,450 3,700 0.93 3.38 meteorologicalstatistics from the Port Buses 250 15,150 0.93 2.54 Area meteorological station. Data used Total 49,950 158,350 in this calculation is given in Table 2.16. URBAIR-Manila 47 Figure 2.12: Isopleths of calculated SO2 concentrations (9g/rm3)around the Manila Power Plant Monthlyaverage, January Max1 h average,January |~~~~ N 2 \n S 2 kmn S Monthlyaverage, August Max1 h average,August W ; t t Q t 8 E W X\ E 2 bn S 2 tin S Max24 h average,August N NationalAOG: W . E /f180 - pg/mst +>X (24 hour averege) 80 pg/rn3 (annualaverage) 2h1n S Note:Plant emissions arein the center of the circles. Figures give the calculated concentrations asa function ofdirection and distancefrom the plant. Source:Anglo, E. (1 994.) 48 Air Quality Assessment Figure 2.13: Calculated average daily variation of car exhaust concentrations (PM and SO,) near selected roads in Metro Manila Predicted meanhourly TSP conc at Taft Ave (USEPAEmission factors) 70 January April August 60 -- -A - -. _ so 20 __ ...... , _.. 06 08 11 14 t7 20 23 02 Hour 0) Predictedmean hourly S02 concat EDSA 20 (USEPAEmission factors) 20010 January April August o ,>10 ___X__._____._ 2 S0 08 11 14 17 20 23 02 Hour Source:Anglo E. (1994.) URBAIR-Manila 49 The results of the CALINE model that was used are shown in Figure 2.13. Using USEPA emission factors, maximum exhaust particle concentrations at Taft were calculated to be about 65 pLg/m3. For jeepneys, trucks, and buses, these emission factors should be almost doubled to correspond with those selected for this study. Anglo's calculations would thus indicate typical rush hour concentrations of about 150 ,ug/m3, and an estimated annual average exhaust particle concentration of 50-60 1.g/m3. Contribution from resuspension has not been included in this calculation. Using selected emission factors, this would minimally double the particle concentration at Taft Avenue. The resulting TSP contribution from Taft Avenue traffic would be at least 100 ,ug/m3. With a city background TSP contribution of about 150 Zg/ m3 (as calculated in Chapter 2.3.2), annual average TSP concentration at Taft would be about 250 ,ug/ m3 . The average concentration- 219 ,ug/ m3 for 1992 (see Figure 2.1 a)- measured at Ermita station, near Taft, agrees with the above. S02 concentration calculated for EDSA during typical rush-hour concentration is about 120- 170 p.g/m3 and about 40 ug/m3 annual average. POPULATION EXPOSURE TO AIR POLLUTION IN METRO MANILA Population exposure is defined as the number of persons exposed to ambient concentrations that exceed the standards or guidelines. The cumulative population exposure distribution gives the percentage of the total population exposed to concentrations above standard values. People are exposed to air pollutants at home, during commuting on roads, at work and other places. In order to correctly map population exposure, data is needed on: * Concentration distributions and variation with time, in homes (general city air pollution or "city background"); along the main road network; and near other hot spots such as near industrial areas. * Population distribution (residences and workplace) and the number of commuters, along with time-dependent travel habits. Databases for population exposure calculations are often incomplete, and a methodology must be developed for each city based on its available database. The methodology used for Metro Manila, more fully described in Appendix 4, includes calculation of the concentration distribution of vehicle exhaust per square kilometer grid. This distribution is adjusted upwards to account for all area-distributed sources. Residence exposure is calculated from this concentration distribution and the square kilometer population distribution. Added exposure near industrial areas is calculated by giving 50 percent of the inhabitants an extra concentration value. Added exposure near roads is calculated for commuters, drivers, and roadside residents. Exposure to TSP. Metro Manila's main pollution problem is TSP. Calculations of population exposure to annual average concentrations of TSP are used in health damage analysis. While exposure to high short-term concentrations of suspended particles and other pollution compounds in hot spots is very important, calculating such exposure requires a more extensive database than was available for Metro Manila. In addition, comprehensive dose-response relationships for the impact of high short-term concentrations on human health have not been developed. Annual average TSP population exposure calculations in Metro Manila (1992) are shown in Table 2.17. They represent the dispersion modeling area which includes 65,000 inhabitants, but 50 Air Quality Assessment Table2.17: Calculatedpopulation exposureto TSP (annualaverage), 1992 C Population traffic areasourcesa Population Additionalexposure, exposure,area Additional Resulting g/rm3 +background exposure dueto industryb sources+ exposuredue to population ptg/m3 areasources 103inh. industry roadsidec exposure 103inh. 103inh. 103inh. 103inh. 275 A= 65 65 >40 205-225 50 50 B = 300 350 35-40 180-205 210 140 370 670 C/3=800 1,470 30-35 160-180 550 370 250 1,030 -D 570 25-30 140-160 1,470 250 240 1,220 -D 760 20-25 115-140 1,010 240 250 750 C/3-D 1,090 15-20 95-115 940 250 460 C/3-D 800 10-15 75-95 1,000 1,000 -D 540 <10 30- 75 1,470 1,470 -D 1,010 Sum 6,650 6,650 6,655 Note: a) Areasources: Traffic + ind./comm.fuel combustion + refuse buming + construction. Trafficemissions = 23% of total area source emissions. b) 25%of inhabitants ineach km 2 is givenan additional 20 jlg/m 3. 25%of inhabitants ineach km 2 is givenan additional 40 jig/m 3. c) A:no. of roadside residents = 65 000, exposed to anestimated 275 Rg/m3 B:no. of chauffeurs/policemen= 300000, exposed to an estimated 220 ig/rn3 C:no. of road commuters =2 400000, exposed to anestimated 185/135/1 00jig/m3 (33%of the 2 400000 in eachof the three concentration levels). D:D = (A+B+C)/6 TheA, B, and C inhabitantsare moved from the lower to the higher exposure classes. excludes much of Valenzuela and the northern parts of Quezon City. Population exposure distributions, annual averages and present conditions are shown in Figure 2.14. At present (1992) about 65 percent of Metro Manila's population lives in areas where the air 3 quality guideline (90 gg/m ) is exceeded. General exposure (at homes) to TSP and PM1 o comes from resuspension from roads and construction, diesel vehicles, and refuse burning. When industrial and road exposure is added, about 80 percent of the population is exposed to levels above the AQG. About 3 percent of the population is exposed to levels double the AQG, while they are in their homes. When industrial exposure is added, 11 percent are exposed to twice the AQG, and with road exposure added, this number rises to 29 percent. Additional exposure in industrial areas stems from BOF combustion, and process emissions. Roadside residents, numbering 65,000 or one percent of the Manila population, public transport drivers, policemen, and other roadside workers, estimated at 300,000 or 4.5 percent of the population, are the most severely exposed. URBAIR-Manila 51 Figure 2.14 Calculatedpopulation exposure distribution,Metro Manila Modeling Area, TSP, annual average,present conditions (1992) 20 S 4 04 20 7 ,5 4 100 170 190 210 230 250 'a 70- 160Total exposure, Conc n residence,ndusty 8 ~~~~~~~~~~~~~~~~~~androadhot spot -0* ""o()Exposure at residences, d -*40 - dueto areasources, w Industryhot spot added 0. 300 0. 2 Exposureat residences 'O dueto areasources * 10 *~~~~~~~~~~~~ 0 50 ~~~~100 150 200 250 Concentration(pg/rn 3) o(z) Exposureat residences, due to areasources -- un.o+q (z) As above, with exposure due to industry added w (z) Total exposure,i.e. as above,with roadexposure added 52 Air Quality Assessment Exposure to PMo. Table 2.18: Corresponding area (km2) concentrations of vehicle Long-term (annual) and exhaust particles, TSP, PM1 oand lead (ggl(m3), 1992 maximum short-term Annualaverage concentration Max.24 hour (24-hour) population concentration exposure has also been Trafficexhaust TSP(1) PMIO(2) Lead(3) A B estimated for PM1O. particles PM1, (4) PM10 (5) Table 2.18Table givesgives40 2.18 35 205180 10090 1.301.50 135155 175200 averagesof vehicle 30 160 75 1.10 115 155 exhaust particles, TSP, 25 140 65 0.95 100 130 PM1 o,and lead, as well 20 115 55 0.75 80 105 as estimated maximum 15 95 40 0.55 65 80 24-hourPM lo 10 75 30 0.35 45 60 24-hour PM10 <10 30-75 5-30 <0.35 10-45 10-60 concentration,based on NationalAQG 90 60 150 stated assumptions. Note: The valuesin Table I Vehicleexh. particle emission = 23%of totalarea distributed TSP emission. 2.18 indicatethat the 2 Vehicleexh. particleemission = 42%of totalarea distrbuted PM1 0 emission. long-term TSP AQG 3 Theratio between vehicle PM1o leadand particle emissions = 0.33/8.9= 0.037. 3 (90 ,ug/m ) is exceeded 4 Max.24-hour PM 10 = 1.5x annualaverage PMIO. to a larger extent than 5 Max.24-hour PMIo = 2.0 x annualaverage PM10. the corresponding PM1 o 3 guideline of 60 Jlg/m . Thus, TSP is the limiting parameter for long-term exposure to particles. Table 2.18 also shows that a comparison of the calculated concentrations to the AQGs reveals 3 that the Philippine short-term PM1o guideline of 150 gg/m is less restrictive in Metro Manila than the long-term TSP guideline. The WHO short-term PMIo guideline of 70 gg/m3 is about as restrictive in the Metro Manila as the TSP long-term guideline. SUMMARY OF THE AIR QUALITYASSESSMENT Metro Manila air quality: * Concentrations of TSP and SO2 have been measured regularly at eight fixed locations for a few days per month for many years. The locations are composed of street-side, area- representative stations, and industrial areas. * In addition to these measurements, a network of five street-side stations was introduced in 1991/1992. This program included NOx, CO, PM1 o, lead, TSP and some SO2 measurements. * TSP frequently exceeds WHO and national AQG. Concentrations near the main streets are sometimes extremely high, exceeding the AQG by a factor as high as five. * Measurements in industrial areas (e.g. Valenzuela) indicate high TSP concentrations. * TSP and PMIo are the most important pollution parameters in the Metro Manila relative to their respective AQG. * SO2 calculations indicate that AQG are exceeded, although not as markedly as for particles. There is a large discrepancy between calculated results and the results of actual SO2 measurements. * Metro Manila's air quality monitoring system, and data base need substantial improvement. URBAIR-Manila 53 Emissions sources. According to fuel consumption data, a large quantity of high sulfur BOF is combusted in Metro Manila annually. Road traffic-exhaust and resuspension of road dust-is an important source of emissions. Little is known about industrial process emissions, and estimates of emissions from refuse burning, construction, and resuspension are rough. There are no data on the use of wood and coal. Estimatedcontributions from main sourcesare as follows: * TSP: BOF combustion (22 percent, including 3 percent from power plants); resuspension of road dust (33 percent); diesel vehicle exhaust (9 percent); refuse burning and industrial processes (both roughly 8 percent). * PM1 o: BOF combustion (34 percent, including 5 percent from power plants); diesel vehicle exhaust (16 percent); resuspension from roads (15 percent); and refuse burning (14 percent). * SO2: BOF combustion (88 percent, including 28 percent from power plants); DOF combustion (5 percent); and diesel vehicle exhaust (4 percent). An improved emissions inventory is needed, especially for industrial emissions, refuse burning, resuspension, and construction. IMPROVINGAIR QUALITYASSESSMENT Shortcomings and data gaps Air quality. The measurement system operated by DENR-NCR has the following shortcomings: * 24-hour samples of TSP and SO2, are collected infrequently (2-4 days per month). - PM1o, lead, NO2, CO, ozone, and other compounds are not measured routinely. - Many measurement sites do not clearly represent typical areas such as city background stations (commercial, industrial, residential); traffic exposed (street side) stations; or industrial hot spot stations. It is clear that DENR-NCR operates under considerable financial constraints that affect its methodological and manpower capacities. Nevertheless, it is important to improve air quality monitoring in Manila. A comprehensive monitoring system would include: * two to five city background sites; * one to three traffic exposed sites; * one to five industrial area/hot spot sites; * continuous monitors for PM1o, CO, NOx, SO2, or ozone, depending upon the site; and, * on-line data retrieval system directly linked to a laboratory database via telephone/modem. Ozone measurements should begin as soon as possible in order to determine whether there is a photochemical air pollution problem. Such measurements should be carried out continuously, over a one-year period, at sites inside and outside Metro Manila. Emissions inventory: shortcomings and improvements. The main shortcomings of the emissions inventory are as follows: * industrial emissions (use and combustion of fuel, process emissions); * resuspension from roads; * other coarse particle sources, such as construction; and 54 Air Quality Assessment * domestic refuse burning. Additional shortcomings include a lack of detailed traffic distribution data, which forms the background for car exhaust emissions distribution, and the use and distribution of fuel in the commercial and domestic sector, including generators. It is necessary to fill the inventory data gaps, and upgrade the inventory. In this regard, a comprehensive emissions database should be developed, covering both the DENR-NCR and LLDA. Population exposure. Population exposure to air pollution, and source contributions to this exposure, is determined by a combination of dispersion modeling, and air pollution monitoring. A good quality population exposure distribution is important because it forms the basis for estimating health damage costs; and assessing the health benefits of measures to reduce exposure. To improve population exposure calculations that have been developed in the first phase of URBAIR, the following are needed: * Improved data for distributing the population in square kilometer grids (Barangay data already exist, and should be used); and * Dispersion modeling expertise in Metro Manila should be identified. Such expertise, and appropriate models for air pollution management and control strategies, should be based in EMB and DENR-NCR. URBAIR-Manila 55 Table 2.19: Proposed Actions to inrove Air Qualit Assessment Actions Timeschedule AirQualif Monitoring Designand establish a modified and improved, Thisactivity should begin immediately. A proposed schedule is as extendedambient air monitoring system: follows: * evaluatesites (number and locations); * By30 June, 1996. Finalize plan for an upgraded air quality * selectschedule for parameters, methods, monitoringsystem, including laboratory upgrading; monitors,and operation; * Newmodem monitoring stations were put into operation in 1994. * upgradelaboratory facilities, and manpower Evaluationsforfinal upgrading will follow. capacities. Designand establish a quality control, and quality Thisshould commence immediately, parallel to the establishment of assurancesystem. animproved monitoring system, and upgrading oflaboratories. Designand establish an Air Quality Information Thisactivity should begin as soon as modem,on-line monitoring System(AQIS), including; stationshave been established. Tobe operative by the end of 1996. * database, * informcontrol agencies, law makers, and generalpublic. Emissions Improveemissions inventory: Thisshould start immediately, by establishing a unit which will have a - Produceinventory of industrialemissions long-termresponsibility foremissions inventory work in MetroManila. (location,process, emissions, stack data); Priorityto: - Betterinventory of roadand traffic data; * industrialemissions inventory - Improveinventory of domesticemissions; * studyof resuspensionfrom roads - Studyresuspension from roads and other . thedevelopment ofan emissions inventory procedure surfaces. Developan integrated and comprehensive emissions inventoryprocedure, including emission factor review,update, and QA procedures. Must cover both MetroManila and LLDA areas. Improvemethods and capacity for emission measurements. Populationexposure Assesscurrent modeling tools/methods, and Beginimmediately byestablishing a unit which will have long-term establishappropriate models for controlstrategy in responsibilityfor performing such modeling in MetroManila. MetroManila. 3. HEALTH IMPACTS OF AIR POLLUTION INTRODUCTION This chapter presents an overview of major air pollution impacts in Metro Manila, including an estimation of the monetary value of these damages. Concern about air pollution stems mainly from high concentrations of suspended particles and lead, both exceeding national and WHO health guidelines (See, Chapter 2). Problems arising from S02, NOx and ozone (photochemical air pollution) do not appear to be as serious. Therefore, this chapter concentrates on PM1 O and lead. Health impact estimates are based on air pollution dose-response research conducted in the United States (Ostro, 1994). The methodology for deriving these estimates are described in the URBAIR Guidebook. Although damage to human health is not the only adverse effect of air pollution, lack of appropriate data prevented us from quantifying other impacts such as a reduction in the economic life of capital goods, damage to the ecosystem, tourism, crop production, and other intangible impacts. MORTALITY AND MORBIDITY Health impacts are divided into mortality (excess deaths) and morbidity (excess cases of illness). Mortality and morbidity are derived from air quality data using dose-response relationships. In principle, such relationships are found by statistical comparison of death rates and morbidity in urban areas with different air quality. Ostro (1994) has summarized and estimated appropriate dose-response relationships. Admittedly, these dose-response relationships are derived from studies in U.S. cities, and it is speculative to apply them to Metro Manila. But until specific dose- response relationship for tropical conditions are derived, Ostro's calculations are useful for preliminary analyses. Further, while it is clear that indoor pollution, such as that caused by cooking, also causes damage health, this analysis was limited to outdoor air pollution. 57 58 Health Impacts of Air Pollution Mortality and other health impacts of lead Mortality due to lead. Diastolic blood pressure (DBP) is an important part of the dose-response function of mortality caused by lead. Pb in blood indicates the concentration of lead in blood, expressed in Jlg/dl. The relationship between lead concentration and change in DBP is: A DBP = 2.74 (In [Pb in bloodlold - In [Pb in bloodinew), The relationship between lead in blood, and lead in the air is complex. A close approximation of the relationship between change in DBP and lead concentration in air, where [PbA] indicates the concentration of lead in the air, expressed in ,g/rm3 , is empirically stated as follows: A DBP = 2.74 (In [PbA]old - In [PbAlnew), There is little evidence on a threshold level of [PbA], and the threshold might well be zero. However, WHO guidelines suggest a [PbA]old benchmark of 0.5 gg/dl. Change in DBP can be derived using this threshold. The change in the 12-year probability of death, related to change in blood pressure due to lead, where, DBPold can be the average U.S. value of 76, is: Pr (M) = (1+ exp-(-5.315 + 0.03516 DBPold))-l - (1+ exp-(-5.315 + 0.03516 DBPnew)) 1 It was not possible to make an estimate of the distribution of people exposed to different levels of lead concentration and, therefore, we have a very rough mortality estimate. 3 About 700,000 people live in areas where lead concentration is 1.2 gg/M or higher, and approximately one million people who live along the roadside are also exposed to that concentration. If the lead concentration that these 1,700,000 people were exposed to was reduced 3 to 0.5 gg/m , the mortality would decrease yearly by 770 people. This damage figure of 770 cases of excess yearly mortality is actually an underestimate, as the population exposed to concentrations between 0.5 and 1.2 gg/m3 is not included in calculating this impact. In addition, a portion of the 1,700,000 people are exposed to 3 concentrations above 1.2 jig/ m . It is expected that Table 3.1: Impact of PM10 air with a reduction in the lead content of gasoline, there pollution on health in 1992 will be a corresponding decline in the airborne lead Typeof impact Numberof pollution in Manila. casesin 1992 Chronicbronchitis 12,000 Restrictedactivity days 11,006,000 Morbidity due to lead. The main effects of lead are Emergencyroom visits 45,000 hypertension, coronary heart disease and decreased Bronchitisinchildren 112,000 intelligence in children. The relationship between Asthma 436,000 Respiratorysymptom days 35,028,000 cases of hypertension(H) and a change in air qualityis Respiratoryhospital admissions 2,000 estimated as the following formula in which [PbA]2 is Note:Figures are presented in detail for reasons of the ambient lead concentration in the air, and [PbA]j consistency,not to suggestlarge reliability. is the WHO benchmark lead concentration guideline of 0.5 jg/m 3. The results are in Table 3.1. URBAIR-Manila 59 AH = (I + exp - (- 2.744 + 0.793 In 2[PbA]J))-l - (I + exp - (- 2.744 + 0.793 In 2[PbAJ2))-l The dose-effectrelationship with coronaryheart disease (CHD)and DiastolicBlood Pressure (DPB) indicatesthat the increasein the 10-yearsprobability of a case A Pr(CHD)is calculatedby the following: A Pr(CHD)= (1+ exp - (-4.996 + 0.030365DBPI))- 1 -(I+ exp - (- 4.996 + 0.030365DBP2))- The decreasein IQ points in childrenuses the followingformula in which the WHO [PbA]1 3 guidelineof 0.5 ,ug/m, can be used and [PbA]2 is the ambientlead concentrationin air: A IQ = 0.975x ([PbA]2- [PbA]fA, For the benchmarkconcentration, we used the WHO guidelineof 0.5 ,ug/m3. It can be argued that a no-effect levelis lower, possibly zero, becausethe lead intake from air is in additionto other intakes. MORTALITYAND MORBIDITY DUE TO PARTICULATES Mortalitydue to PMIo.The relationshipbetween air qualityand mortalityis show in the following equationwhere P representsthe number of people exposedto a specificconcentration; c stands for the crude mortalityrate which is 0.0061 in Metro Manila (Subidaand Torres, 1994);and PM,o 3 is the annual averageconcentration in gg/m . The PM1o benchmarkis 41. Above this benchmark mortalityincreases corresponding to the WHO AQG for long-termannual averageconcentration, and taking accountof PM1o concentrationswhich are typicallyabout 55 percentof TSP. From this relationshipand the exposuredata, it calculatesthat excess mortalitywas 1,300in 1992. Excessdeath = 0.00112x ([PMjo] - 41) x P x c Morbidity due to PM,0 . Many cases of chronic bronchitis, restrictedactivity days (RAD),respiratory hospital diseases (RHD),emergency room visits (ERV),bronchitis, asthma Table 3.2: Health impact of lead attacks,and respiratorysymptoms days (RSD) can be air pollution (1992) attributed to particulate pollution. Dose-response Coronaryheart disease 762 cases relationships for particulate concentrations are described in Hypertension 91,207cases the URBAIR Guidebook. Their relevance to environmental 10points loss 403,000points benefit/damageassessment is mentionedin Chapter4. See results in Table 3.2. * The change in yearly cases of chronic bronchitisper 100,000persons is estimatedat 6.12 per 3 ,ug/m PM1o. The total number of yearly cases of chronicbronchitis per 100,000persons is calculatedat 6.12 x ([PM,0] -41). * The change in RAD per person, per year, per pg/m3 PMjo is estimatedat 0.0575. If we use the WHO guideline,the change is 0.0575x ([PM,0] - 41). 3 * The change in RHD per 100,000persons is estimatedat 1.2per gg/m PM1o. Usingthe WHO standard,RHD per 100,000persons is estimatedat 1.2 x ([PM,o] -41). 60 Health Impacts of Air Pollution 3 * The change in the number of ERV per 100,000 persons is estimated at 23.54 per ,ug/m PM10, and the total number per 100,000 persons at 23.54 x ([PM1o] - 41). • Children under the age of 18 comprise an estimated 35 percent of the total population. Change in the annual risk of bronchitis for these children is estimated at 0.00169 x ([PM1 0] - 41). * Change in daily asthma attacks per asthmatic person is estimated at 0.0326 x ([PM1oJ - 41). There is no definite count of asthmatic persons. * The number of respiratory symptom days (RSD) per person, per year, is estimated at 0.183 x ([PM1o] - 41). VALUATION OF HEALTH IMPACTS Mortality. Placing a monetary value on mortality is debatable. Many argue that such a valuation cannot be made on ethical grounds. By not valuing mortality, however, we would seriously underestimate the total damage caused by air pollution. A case (single instance) of mortality can be valued in two ways. The first is based on "willingness to pay," the other on "income potential." The willingness to pay approach is described in detail in the URBAIR Guidebook. In the United States, a value of about US$3 million per statistical life is often used. Although such a valuation is not readily transferable from one country to another, an approximation can be derived by correcting the U.S. figure by a purchasing power parity factor: Philippines purchasing power parity, divided by the U.S. purchasing power. This factor is 2,1 10 divided by 21,900 equaling 0.096 (Dikhanov, 1994). At an exchange rate of Pl.0 equal to US$0.03, this suggests a value of P11 million per statistical life in the Philippines. The second approach is based on income lost due to mortality. The value of a statistical life is estimated as the discounted value of expected future income at the average age. If the average age of the population is 26 years and the life expectancy at birth is 65 years, the formula used for calculating value of a statistical life is: 38 VSL = W, V =E(I + d)' In the formula: w = average annual income, and d = discount rate (Shin et al., 1992). In this approach, the value of people without a salary (e.g. housewives) is the same as the value of people with a salary. The minimum wage in Manila is P145 per day, but very often a lower wage is paid. A reasonable estimate is PI00 per day, which corresponds to P20,000 per year. At a discount rate (d) of 5 percent, VSL equals P0.35 million. In both approaches to the valuation of premature death from PMIo, the cost of air pollution, in 1992, ranges from P0.5 billion to P14.3 billion. Methodological note on morbidity and mortality. The URBAIR Guidebook presents estimated costs of morbidity (medical treatment, lost earnings), based on U.S. values. In order to obtain city- specific figures, the U.S. figures were corrected with a factor of 0.096, to reflect the difference in purchasing power parity between the United States and the Philippines (Dichanov, 1994). These URBAIR-Manila 61 initial estimates are supplemented by estimates based on specific data for Manila (Subida, 1994). Table 3.3: Valuationof health impacts (in The data sets are presented in Table 3.3. Pesos) Tables 3.4 and 3.5 summarize the present Estimatefrom USA damage due to PM1 o and lead pollution, Manila derived respectively. For some of the effects the figures Effectsof PM10 derived from the United States are higher. This is Restrictedactivity day 160 190 Emergencyroom visit 1,790 856 explainedby the high valuationof a statisticallife Bronchitis 1,840 1,069 in the willingness-to-pay method (US$98,400), Asthmaattacks 1,190 328 whereas for the Manila, the low valuation (loss of Respiratorysymptoms day 40 49 income method) of a statistical life was used Hospitaladmission 11,900 92,378 (US$11,124). In contrast, the valuation of illness Effectsof lead in the Manila figures is higher than in the U.S.- Hypertension 722 Coronaryheart disease 160,700 derived figures. For the valuation of health Lossof IQpoints 15,000 damage due to lead, data for Manila were not available. We used morbidity cost figures derived from the United States with the lower estimate Table 3.4: Costs (million Pesos) of health being used for the valuation of a statistical life. impacts of PM1o calculatedfrom Manila data Summary: mortality and morbidity. In an URBAIR 1992 study, Valuation of Air Pollution Damages in Manila US- Metro Manila, conducted by H.A. Francisco in derived 1994,the monetaryvalue of damageto health due Mortality 500 14,500 air4pollutonewasy estmatueofdange toheaContiuen Restrictedactivity days 1,800 2,118 to air pollutionwas estimatedusmg the Contigent Emergencyroom visits 81 39 Valuation Method (CVM). CVM is a survey Bronchitisinchildren 210 122 method in which respondents are asked about their Asthmaticattacks 526 145 willingness-to-pay to reduce damage. The total Hospitaladmissions 1,518 1,738 estimate of damage to health amounted to P300- Respiratorysymptom days 28 215 450 million. This figure is low compared to the Total 4,594 18,727 earlier estimates. This may partly be explained by the fact that the respondents were not aware of dose-response relationships. However, the estimate might also indicate that the value of Table 3.5: Costs (mi7lion statistical life as derived from the USA studies may not be Pesos) of health impacts applicable to Manila, even if corrected for differences in from lead pollution (1992) purchasing power parity. This estimate was based on the Mortality 283 averagewillingness to pay to reduce general health damages. Coronaryheart disease 40 Therefore, it cannot be related to specific illnesses or to H0pointloss 2,000 exposure to specific concentrations. Total 2,300 62 Health Impacts of Air Pollution VALUATION OF NON-HEALTH DAMAGES Although there is no figure for the damage that air pollution causes to buildings and materials, Francisco (1994) indicates that there are indications of substantial damage. Interviewed households reported perceived damage due to air pollution to be in the range of P3,233 to P5,500 per year, per house. The sample of interviewed homeowners was, however, not representative of Manila. Information on other damage categories is lacking. It can be estimated that each household would receive a benefit of US$2.7, in reduced soiling, if pollution was reduced by 1 ,ug/m3 (Freeman's estimate, URBAIR Guidebook, Appendix 4). Corrected for differences in purchasing power parity, this figure amounts to US$0.26. If the average number of persons per household is 8, cleaning costs can be estimated at US$2 million or P60 million. Traffic congestion is very severe in Metro Manila. It may be reasonable to assume that Table 3.6: Air pollution impacts attributed to source one-third of the population (9 categories (1992) million persons in 1994) loses Sourcecategory Mortality# RSD Costs an average of two hours each ofpeople millions millionpesos day, 300 days a year sitting in Gasolinecars 44 1.2 151 traffic. Calculating at an hourly Motorcycles 22 0.6 75 wage rate of PI12,this results in Jeepneys12 3039 Utilityvehicles (diesel & gasoline) 177 5.0 614 over P20 billion of damage. Trucksand buses (diesel & gasoline) 555 15.0 1,924 Table 3.6 presents the results of Combustionof heavy fuel oil (BOF) 200 5.0 695 calculations aimed at attributing Refuseburning 435 12.0 1,519 air-pollution (PMIo) impacts, to source categories. The valuation is based on the Manila data. 4. ABATEMENT MEASURES: EFFECTIVENESS AND COSTS INTRODUCTION This chapter outlines measures for reducing air pollution in Metro Manila, and for drafting an action plan that would translate these measures into practice. Information is organized by source category: traffic, power plants, fuel combustion other than in power plants; non-combustion sources, construction, and refuse burning. For the main source categories, characteristics of abatements measures are described in terms of: *ffectivene,ss in terms of both emissions reduction and reduced exposure impacts in the year 1995 (according to the methodology used in Chapter 3); the reference data include mortality (1,700, due to PM,0 ) and number of RSD (50 million in 1995); * costs of measures in order to prioritize implementation; fbenefits including reduced excess deaths (mortality), reduced number RSD, and the economic benefits based on Manila data; see Chapter 3. * policy instruments and institutions that may be used to implement the measures; and * term,for emissions reduction: short- (2 years), mid- (2-5 years), or long-term (more than 5 years). Identifying measures to address traffic emissions, for example, is straightforward because the major causes of the air pollution are commonly known. Although it is possible to list other measures (for source other than traffic), the lack of specific information regarding those sources prevented elaborating costs and benefits to some degree. For industrial process emissions, construction, and refuse burning it was not possible to present measures due to lack of information The list of measures is derived from the information presented by the local working groups, from the URBAIR Guidebook and from earlier plans for addressing pollution in Metro Manila (See Chapter 2). All figures for emissions, costs, and benefits, represent annual estimates. TRAFFIC This section describes the effectiveness (abated emissions) and the benefits of selected measures such as: 63 64 AbatementMeasures: Effectiveness and Costs * enhancing effectiveness of the anti-smoke belching program; * improving diesel fuel quality; * implementation of a scheme for inspection and maintenance; * switching fuel (low-sulfur diesel, and unleaded gasoline) in the transportation sector, induced by price-shifts; and * adoption of clean vehicle emissions standards. Reinforcing the anti-smoke belching program Effectiveness.According to rough estimates, about 25 percent of Table 4.1: Reinforcing the anti-smoke belching program jeepneys, utility vehicles, and Effectiveness: 2,000tons PM,O avoided. other diesel-engine powered Costs: Costsof annual inspection per jeepney/utility vehicles are smoke belchers. The vehicle:P200 (at the expense of the vehicle owner). anti-smoke belching program Totalcosts: P2.5 million. specifically targets these vehicles. Benefits Mortalityavoided: 158, RSDavoided: 4 million, A successful campaign would Benefits:P550 million. reduce overall emissions of all Instrument/institution:Enforcement authorities. diesel-engine vehicles by 50 Term: Oneyear. percent (an estimated reduction of Targetgroups: Vehicleowners/drivers. 2,000 tons of PMIo). See summary in Table 4.1. Cost. It is difficult to assess the costs of stricter enforcement of regulations addressing smoke- belching vehicles, possibly including a mandatory improvement of engine controls (fuel injection/timing). A proposal (Baker et al, 1993) below summarizes an inspection and maintenance scheme for Metro Manila, addressing all vehicles. The anti-smoke belching program could be integrated into such an inspection and maintenance scheme. It is estimated that the cost of once-per-year inspection would be about P200 for each vehicle. In addition to this cost, jeepney owners may face increased maintenance costs. The latter costs are expected to be partly compensated by improved energy efficiency. Improving diesel quality Effectiveness.Ignition and combustion properties of diesel, including volatility2, viscosity3, and 4 cetane number , are important parameters in explaining PM1 o emission by diesel engines 2 Volatilityisdefined as theease with which a productbegins to vaporize. Volatile substances have relatively high vapor pressuresand, therefore, boil at relativelylow tempreatures. Viscosityisthe property of a fluidwhich determines its rate of flow. As the temperature ofa fluidis increased its viscosity decreasesand, therefore, itflows more readily. Thephysico-chemical properties ofdiesel fuel, as expressedin the cetane number, influence the magnitudeofemissions of exhaustparticles from diesel vehicles. The relationship between these properties (such as volatilityand viscosity) and the producitonofexhaust particles in a dieselmotor is not straighfforward; thecharacteristics ofthe diesel motor, its load and injectiontiming plan are other important parameters. URBAIR-Manila 65 (Hutcheson and van Paassen, 1990; Tharby et al, 1992). In Manila, the cetane number and volatility of diesel are less important in explaining particle pollution than age, lack of maintenance, and poor motor settings of vehicles. While data on the cetane number of fuel used in Manila are not available, the typical cetane number in Southeast Asia is 47. The corresponding number in Europe is 50. Reducing the sulfur content leads to a proportional decline in sulfur dioxide emission (approximately 17,000 tons in 1992). Reducing the sulfur from 0.7 percent to 0.5 percent reduces the sulfate particulate matter by approximately 30 percent. Further reduction from 0.5 percent to 0.2 percent reduces the sulfate particulate matter an additional 60 percent (Ruby, 1994). PMIo emission also decrease because a part of the particulates comes from sulfur in the fuel. It is assumed that improving properties of diesel fuel by increasing the cetane number, and adding detergents would result in a 10 percent decline in PM10 emission. A proposal to set quality requirements for diesel, including a further reduction in the sulfur content is shown in Table 4.2. Another Table 4.2: Current and proposed quality requirement may be to add detergents and standards for diesel.fuel dispersants. These additives keep injection Fuelcharacteristic Current Proposed systems clean and have discernible efficiency Distillation20 vol. % min. 'C none 210 effects (Parkes, 1988). 90vol.%max. °C 357 338 Viscosity(@ 40 °C)centistokes 1.9-5.0 1.8-4.1 Cost.The costs of reducing sulfur in diesel Sulfur(weight percent) 0.7 0.20 fuel stem from more extensive desulfurization Source:Mehta K.H. et al. (1993). activity at the refinery. For reducing the sulfur content from 0.7 percent to 0.2 percent, it would cost about US$0.01 or P0.3 per liter. Combustion of sulfur in diesel fuel also leads to the formation of corrosive sulfuric acid. Therefore, reducing the sulfur content lowers the cost of vehicle maintenance and repair. Improving the quality of diesel fuel, given the current product mix, requires either importing low-sulfur diesel fuel or adjusting the refineries to produce lighter distillates, and Table 4.3: Product mix of increase their hydrodesulfurization capacity. The current Philippine refineries. output-mix (different products from crude oil, Table 4.3) of Typeof fuel Output Share refineries does not match the demand structure. Demand for (MTOE) (%/) diesel fuel is much higher than the demand for gasoline (see Gasoline 1,363 14 Table 2.9). The quality of diesel may improve if the price Kerosene 1,027 10 structure of all transportation fuels was altered. Total required Diesel 3,972 40 investments in refinery adjustments are P11.5 billion, of which Other(elg LPG, 549 7 P1.0 billion would go to hydrodesulfurization equipment. Aviationfuel) Expenditures for diesel fuel, assuming other factors not Source:Mehta K.H. et al. (1993). changing, might increase to P300 million. These costs might be absorbed by the Oil Price Stabilization Fund or may be shifted to the vehicle owners. Policy instruments and target groups. Diesel quality requirements are set by the Energy Regulatory Board. The petroleum industry is responsible for improving quality. The system of diesel-fuel subsidies, managed by the Oil Prize Stabilization Fund, provides an opportunity to tie 66 Abatement Measures: Effectiveness and Costs implementation and enforcement quality standards with the subsidy scheme. If subsidies can be linked to fuel quality, clean fuel can be introduced using market instruments. Term. Improved diesel can be made widely Table 4.4: Summary. Improving dieselfuel available in two to five years. It is estimated that quality refineries can be extended in about 3 years Effectiveness: 1,200tons PM1 0 (1995). (Mehta et al, 1993). A summary of the measure Costs: P300million. for improving diesel fuel quality is in Table 4.4. Benefits: AvoidedMortality: 94, AvoidedRSD : 2.5million, BenefitsP350 million, ReductionofSO2 emission. Implementing an inspection and Instruments&Institution: Energy Regulatory Board, maintenance scheme OilPrice Stabilization Fund. Tern: Two-fiveyears. Poor vehicle maintenance is a Targetgroups: Petroleumindustry. major cause of harmful emissions. Implementing a scheme for inspection and Table 4.5: Implementation of an inspection and maintenance, as proposed by the maintenance scheme Asian Development Bank (ADB, Effectiveness: 4,000tons PM 10 (1995)avoided annually. Baker et al, 1993) (summarized Costs: US$5.5million for vehicle owners-inspection costs. in Table 4.5), includes annual Maintenancecosts saved by improved fuel efficiency. inspection for all vehicles, with Benefits: AvoidedMortality: 316, AvoidedRSD: 8 million, high-mileage vehicles being BenefitsP1.1 billion. inspected twice a year. The ReductionofCO, VOC emissions, improvement ofroad scheme, to be implemented safety(if roadworthiness isincluded in the scheme). during 1993-2002, would include Instruments/institution:LandTransportation Office, DENR-NCR authorities. 17 inspection and maintenance Term: Twoto fiveyears. stations in Metro Manila, run by Targetgroups: Thescheme could be carried out by the private sector. private contractors. The scheme might be supplemented with roadside spot-checks. Effectiveness. Maladjusted fuel injection systems or carburetors, and worn out motor parts present a threat to traffic safety, increase fuel consumption and thus costs, and lead to large emissions. The semi-annual inspection and maintenance of vehicles will probably result in a substantial reduction in PM1O,VOC, and CO. An accurate assessment of emissions reduction, associated with an inspection and maintenance scheme, requires statistical data about emission characteristics of the Manila vehicle fleet relative to its state-of-maintenance. Such information is not available. From a survey of emission characteristics of the Bangkok vehicle fleet (McGregor & Weaver, 1992) it can be inferred that diesel-powered jeepneys and pickup trucks tend to fail smoke tests more than other vehicles. It is assumed that the proposed inspection and maintenance scheme would reduce PM10 , VOC, and CO emissions by 35 percent. This is in line with a World Bank estimate (Mehta, 1993). The benefits associated with a 35 percent reduction in PM1 Oemission include 316 fewer deaths (avoided mortality) and 8 million fewer RSD. The associated economic benefits are US$41 million (using U.S. data) or US$33 million (using Manila data; see Chapter 3). URBAIR-Manila 67 Costs of an inspection and maintenance scheme. Total investment cost for an inspection and maintenance scheme is US$63 million, as estimated in the ADB study. Costs per test (operating costs and depreciation expenses) increase from an initial P181 to P233. The costs will be covered by vehicle owners. The average test fee would decline from an initial P215 to P194 in 2002. Costs are expected to be fully compensated by a reduction in fuel consumption resulting from the necessary maintenance and repair. If this scheme were linked with the current roadworthiness inspection scheme (not yet fully developed), increased road safety would constitute a second benefit. The ADB study elaborates a scheme in which inspection and maintenance is carried out by the private sector at no cost to the government. A lack of financial resources has prevented this scheme from becoming operational. Policy instruments and target groups. The Land Transportation Office is responsible for inspecting vehicles for roadworthiness. Due to a lack of finances and personnel, however, inspection is not fully implemented. Current legislation (PD 1181) allows environmental spot- check inspections of vehicles by the DENR-NCR authorities. In order to avoid further financial strain, an inspection and maintenance scheme, operated by the private sector, has been proposed. (Baker et al, 1993) Tern. An inspection and maintenance scheme can be implemented within two to five years. A summary of abatement measures for inspection and maintenance implementation is in Table 4.5. Fuel switching in the transportation sector Diesel to gasoline. Diesel-engine jeepneys Table 4.6: Transportation fuel price (Pesos per liter) effective and utility vehicles are a July 1, 1992 major sources of PM1o. Fuel DirectCo. Specific OilPrice Other Pump Diesel is popular because Recovery tax StabilizationFund price it costs less than gasoline. Premiumgasoline 5.52 2.52 1.39 1.57 11.00 Fuel prices are regulated Regulargasoline 4.97 2.28 1.70 1.55 10.50 by the Philippine Dieseloil 5.58 0.45 -0.58 1.55 7.00 Govemment and diesel Source:Mehta et al(1993). prices are kept low by the Oil Price Stabilization Fund. The components of at-the-pump prices are presented in Table 4.6. By changing the tax and subsidy structure, the gasoline/diesel price ratio could be reduced. This would be an incentive for vehicle operators to switch to gasoline. Such a change may be cost-neutral for the government. The subsidy regime could be changed gradually, over a period of five years. A transitional period would allow all participants, including refineries and other fuel suppliers, the gasoline distribution system, jeepney owners, and mechanic shops, to make necessary adjustments. The lower maintenance cost of gasoline engines (P6,000 against P12,000 for diesel) is an added reason to change to gasoline (Baker/ADB, 1992). A primary obstacle to this measure is that jeepney owners lack the funds to invest in gasoline engines, at an estimated replacement cost of P15,000. A change in fuel pricing would have to be complemented by an additional measure, such as a budget neutral scheme for subsidies or loans for engine replacement. 68 Abatement Measures: Effectiveness and Costs LPG as an alternative to diesel and gasoline. LPG can be used as a clean fuel alternative for both gasoline and diesel. PM1 Oemission from LPG is very low. Adapting gasoline cars to LPG requires investments in an LPG-fuel tank and an adapted carburetor. By the same token, marketing LPG requires investments by fuel retailers. LPG can be an attractive alternative to gas if taxes and excises on it are lower than those on gasoline. LPG can also be used in diesel engines, but the investments for adaptation are higher. Several European cities have started using LPG in city buses. The environmental benefits include the virtual elimination of PMIo emission, no Polycyclic Aromatic Hydrocarbons (PAH) or sulfur emission, low NOx emission, and nuisances from smell. These benefits justify the higher investments (about US$40,000 or P1.2 million per bus). Effectiveness. Gasoline-powered utility vehicles (UV), which are technically similar to a diesel- powered jeepney, expel about a third of PMIo emission. If all jeepneys and UVs were equipped with gasoline engines, PMIo emission would be reduced by 60 percent. The associated health benefits include mortality reduction by 100, and a 2.5 million fewer RSD. However, these figures underestimate health benefits because the PAH content of particulates is larger in diesel fuel than in gasoline. The environmental drawback of changing to gasoline is an increase in VOCs and CO, unless legislation requires state-of-the-art emissions abatement control such as exhaust catalysts. A shift toward using LPG in these vehicles would virtually eliminate PMIo and SO2 emissions. In addition, NOx emission from LPG-fueled vehicles are about 50 percent lower than equivalent gasoline-powered vehicles. The benefits of a large-scale introduction of LPG would be 567 fewer mortalities, and 15 million fewer RSD. The associated economic benefit from improved health ranges from P1.9 billion (Manila specific data) to P7.5 billion (based on U.S.-derived data, see Tables 3.3 and 3.4). ('osts. An appropriate fuel tax and subsidy scheme, could make the changeover budget-neutral for the government. A subsidy or loan scheme could also be financed by fuel taxes. Costs for jeepney owners and operators depend on the transition period and, whether subsidies or loans are offered. Eventually, jeepney owners would benefit from the scheme, depending on the final gasoline market price. The initial costs for replacing the engine, and for diesel fuel, required before engine replacement would be compensated by lower maintenance and fuel costs. Information about availability of LPG for automotive purposes is lacking and its market costs and feasibility might be low. Policy instruments and target groups. The tax and subsidy scheme is operated by the Energy Regulatory Board. The groups involved are government agencies, the petroleum industry (supplying gasoline or LPG), jeepney owners, service stations and mechanical shops (engine replacement), and jeepney passengers. The last group is a major stakeholder. Therefore, a scheme must not increase jeepney fares substantially. The possibilities of using LPG are strongly dependent on local availability of LPG, and associated fiscal policies. Term. Provided there is a strong and determined political will, compliance would take five to ten years. A summary of measures to shift from diesel towards gasoline or LPG is in Table 4.7. URBAIR-Manila 69 Clean vehicle Table 4.7: Shiftingfrom diesel towards the use of gasoline or LPG emissionsfgsl standards Effectiveness: Jeepney/UVusing gasoline avoid 2,000 tons PM, 0annually, byintroduction ofLPG. Costs: Inconclusive,because ofregulated fuel market, but negative Many countries have costsin terms of world pnces, as gasoline ischeaper. adopted standards for AvailabilityofLPG not known at the present. permissible emissions Benefits: AvoidedMortality: upto 600, from vehicles.These AvoidedRSD: up to 15 million, ftandaromveh uices.e Benefits:P 550 million. standardsrequire ReductionofSO, emission. vehicles with four- InstrumentsandInstitutions: Energy Regulatory Board, Oil Price Stabilization Fund. stroke gasoline engines Term: Fiveto ten years, or longer. to be equipped with Targetgroups: Petroleumindustry, Fiscal Authorities. exhaust gas control devices based on the use of three-way catalysts (closed-loop systems). A few countries, including Austria and Taiwan, have also set standards for motorcycle emissions, requiring that two-stroke engine-powered vehicles be equipped with open-loop catalysts. The latter devices control emissions of VOCs, PMIOand CO, but not NOx. The catalyst technology uses unleaded gasoline, the sulfur content of which should be less than 500 PPM. Therefore, introducing such a standard requires infrastructure for producing and distributing unleaded gasoline5 . Two-strokeengines (motorcycles) are not yet as common as in Metro Manila as in other Southeast-Asiancities like Bangkok, Jakarta, and Taipei. Therefore, associated problems are not as pressing. The experience in these other cities indicates that it is very likely that economic growth in Manila will be accompanied by a large increase in the number of motorcycles. Diesel-poweredvehicles may be made subject to regulations. Emission requirements are met by adjusting the motor's design. Tailpipe emission treatment may also be used, and existing buses can be retrofitted with abatement equipment. If this last method is to be used, the diesel much be of a much better quality than is currently used (sulfur content below 0.02 percent). Such a standard is being introduced in some parts of the world. Effectiveness. Catalytic devices for treating exhaust gases require the use of unleaded gasoline. Closed-loop catalytic treatment in gasoline-engine vehicles (three-way catalysts) reduces all exhaust NOx, CO, and VOC emissions by about 85 percent. In addition, lead emission is reduced by 100 percent. Open-loop catalytic treatment of exhaust gases from two-stroke motorcycles reduces CO, VOC and PM1O(oil mist) emissions by as much as 90 percent. Two-stroke engines are a major source of this exhaust. Successful use of these catalysts also requires unleaded gasoline. In case of diesel-engine powered vehicles, "clean vehicle" standards are currently enforced in Europe, Japan, and the United States. Such standards require the use of "clean" diesel fuel as discussed above, in combination with improved maintenance. Overall effectiveness at reducing NO,, CO, VOC emissions is estimated at 35 percent. Oxidation filters may be used to remove more particulates from diesel-engine exhaust gases. Low-sulfur diesel (sulfur content less than 0.02 percent) is required for such devices resulting in emission reductions by 80 percent. However, these devices are not yet common. 5 Tomaintain the operation ofthe catalyst, it is absolutely necessary that leaded fuel not be used. Asingle gram of lead will contaminatethecatalyst and render it useless. Inaddition, lead destroys the oxygen sensor ofthe fuel injection system. 70 Abatement Measures: Effectiveness and Costs If in 1995 all vehicles were "clean," mortality would have been reduced by 895, and RSD would have been reduced by 24 million. In addition, airborne lead would be dramatically reduced. Associated health benefits from eliminating lead are about P2 billion (Chapter 2). Removing lead from gasoline requires reformulation of gasoline to maintain ignition. This can be done by increasing the content of aromatics6 in gasoline or by adding oxygenated compounds such as MTBE (methyl-tertial-butyl-ether). Aromatics, however, include benzene, a carcinogenic compound. This would result in an environmental concern, both from benzene exposure due to evaporation of gasoline (during production, storage, and handling) and from the expectation that benzene in exhaust may increase (Tims et al, 1981; Tims, 1983). A limit for benzene content in gasoline may be necessary. A decision would be based on current air quality data on benzene. Experience in other countries indicates that this problem can be resolved. Catalytic converters destroy benzene in exhaust, which leads to less benzene emission. A small increase in exhaust emissions from "dirty" cars using unleaded gasoline is possible. Unleaded gasoline with a high RON-number7 is usually produced by adding MTBE, the preferred lead substitute. MTBE must be imported into the Philippines. Costs. The cost of closed-loop catalytic treatment of exhaust gases stems 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, the associated costs are compensated by an increase in the lifetime of replacement parts such as the exhaust system. Due to methodological difficulties it is not possible to calculate the total costs for introducing standards for Metro Manila. However, costs can be estimated on a vehicle-by-vehicle basis. The costs of open-loop catalytic treatment of exhaust gases from two-stroke motor cycles are related to increased purchasing costs of the equipment, and decreased fuel costs due to improved engine operation. Taiwan adopted standards requiring the use of open-loop catalytic devices resulting in increased costs of US$60 to US$80, which were offset by fuel savings (Binnie & Partners). Other costs are the higher price of unleaded gasoline due to increased production cost and modifying pump nozzles. A very rough estimate of the cost is US$100 or P3,000 annually per car (P1,500 depreciation of the control system and P1,5.00for increased fuel costs, depending on the possible subsidies or levies on gasoline). Policy instruments and target groups. A regulation may be included in the revision of implementing rules and regulations under PD 1181 which is now under review by the DENR/EMB Standards Committee. In order not to discourage the use of unleaded gasoline, and prevent misfueling, it is important that unleaded gasoline be cheaper at the pump than the leaded alternative. This can be ensured through taxes. The groups involved in the introduction of "clean" vehicles are vehicle import firms, service garages, the petroleum industry and gasoline retail suppliers, and vehicle owners who will pay the price for the vehicle, fuel, and maintenance. 6 Aromaticsarea groupsofhydrocarboms ofwhich benzene isthe parent. They are called 'aromatics" because many of their derivativeshave sweet odors. These hydrocarbons areof of relatively high specific gravity and possess good solvent properties.Certain aromatics have valuable anti-knock (octane) characteristcs. Typical aromatics arebenzene, toluene, and xylene. Theoctane number ofgasoline isa measureofits anti-knock value. The higher the octane, the higher isthe anti-knock qualityof gasoline. URBAIR-Manila 71 Term. In practice, standards can be set only for new cars as Table 4.8: Adoption of clean vehicle standards catalysts in case of it is too expensive to gasoline engines, best practical means for diesel engines equip existing Effectiveness: 80%effectiveness pervehicle for gasoline and 35% for diesel. vehicles with the Costs: P3,000per car (including costs of unleaded fuel) necessary devices. TotalP1.3 billion. The effect of these Benefits: AvoidedMortality: 485, standards will be AvoidedBenefits:RSD:P1.75 13billion. million, shown gradually, Additionalbenefit due to virtual elimination of lead pollution. reflecting the rate of Reductionof CO, NOx and VOC emissions-the main justification replacement of ofintroduction ofthese systems in other countres. existing vehicles. A Instrumentsand Institutions: DENRI National Capital Region. summaryof OilPrice Stabilization Fund. suatemeanofasure Term: Twoto five years. The result of such measures tums up with the abatementmeasure renewalof the carfleet. to adopt clean Targetgroups: Petroleumindustry making available unleaded fuel vehicle standards is Carimporters in Table 4.8. Other technical measures The measures discussed above can be regarded as the state-of-the art measures or Best Practical Technical measures. Other measures discussed below are considered viable but are not yet widely used. Fuel switch to compressed natural gas (CNG). Although it is technically feasible to use CNG as a fuel for diesel engines, it is not a common practice. CNG use has been contemplated for buses in downtown areas, particularly to address PM10 emission. The required supply structure is an obstacle to the introduction of CNG. CNG can be used only in areas where a system for supplying natural gas to industries, commercial and domestic users, already exists. CNG use would lead to a decline in PM10, NOx, and SO2 emissions, but also to an increase in methane ( a greenhouse gas) emissions Fuel switch to alco-fuels and other agro-fuels. In various parts of the world fuels made from agricultural products, such as ethanol and vegetable oils, are being used and studied. Energy policies advocate their use as an alternative to imported fossil fuels. Other benefits include the use of otherwise useless agricultural resource and prevention of greenhouse gas emission. These fuels do not perform well with respect to emissions of NOx, CO, and PM1 o, but they do not contain PAH or sulfur. Improvements in abatement/other propulsion techniques. The United States and European Union are considering further tightening of standards to improve current techniques for abatement; 72 AbatementMeasures: Effectiveness and Costs inspection and maintenance, as a small number of maladjusted or worn-out cars cause disproportionately large emissions; and enforce the use of "zero-pollution" vehicles, such as electric vehicles in downtown areas. Although diesel engines emit less C02, they are still a bottleneck in decreasing automotive air pollution because exhaust gas treatment similar to that for gasoline cars is not available. Resuspension emission Although resuspension is a high priority issue in Manila, there is a lack of quantitative information about appropriate abatement measures. Further analyses should give priority to measures dealing with resuspension. In general, all methods of reducing entrainment should be evaluated and applied. Controlling resuspension of road dust may be the most cost effective way of reducing TSP exposure. Improving trafflc management Traffic management includes a variety of measures including: traffic control by police or traffic lights; one-way streets, new roads, and road-pricing systems. One of the main aims of traffic management is to solve congestion problems. Curbside traffic management may improve air quality8, but it may also increase air pollution because it usually results in increased use of the transport system. In terms of exposure, traffic management leads to an improvement in the downtown air quality, and a reduction in road-exposure. In terms of total exposure, however, the net result may be small. It is noted that improved traffic management may have other environmental benefits such as less noise and congestion. More detailed analysis is needed, but traffic management appears to be a cost-effective policy. Constructing mass-transit systems Mass-transit systems, such as light-rail transport, may constitute a part of the solution to environmental problems due to traffic, and increase transport capacity. Building such systems is a long-term process requiring large investments Assessing the costs and effectiveness of measures to improve the Metro Manila public transport system involves: * describing a future system appropriate for Metro Manila; * assessing the performance of such a system (passenger-kilometers); * estimating the construction costs; * describing the baseline (future situation without such system); * estimating avoided emissions; * assessing non-environmental benefits; and * designing a scheme to identify costs and benefits to impute to the environmental aspects. 8 Acceleratingvehicles, a feature ofcongested traffic, emit disproportionately largeamounts ofpollutants. URBAIR-Manila 73 The costs of mass-transitsystems are high, and projectscannot be justified from an air pollution point of view alone. One way of calculating the environmental benefit of a mass-transit system is to consider that the current light-rail system in Manila handles 300,000 passengers daily. This roughly translates to 30,000 vehicular trips by bus and jeepney traffic, assuming an average occupancy of 10 passengers per vehicle. Using a PM1o emission factor of 2 g/km (exhaust particles plus resuspension, see Chapter 2), the light-rail line takes away some 20 tons of particles annually, a very small amount compared to the total emissions. It can be argued that the light-rail line does, however, protect 300,000 passengers or 12 percent of 2.4 million daily commuters, from road exposure. It can be concluded that, although mass-transit systems have a smaller effect on air quality than other measures mentioned above, they also have additional benefits, including reducing congestion. POWER PRODUCTION Cleaner fuels in existing plants The three Metro Manila power plants use BOF (Bunker C fuel oil, grade 6). The smallest power plant is equipped with multicyclones to reduce PMIo emission. A technically feasible measure is to switch to low sulfur fuel, as the SO2 emission is proportional to the sulfur content of the fuel. In addition, reducing the sulfur content of fuel leads to a decrease in PM,o particles9 . Another fuel-switch option is to use less heavy fuel oil, for instance grade 5 or grade 4 oil, with lower PM1 o emission factors. Effectiveness. Reducing the sulfur content of BOF from 3.12 to 2 percent will reduce the emissions from power plants by 40 percent. Using lighter types of fuel oils will be more effective, according to the emission factors given above. Use of grade 5 fuel oil will reduce emissions by 70 percent, and grade 4 fuel oil by about 80 percent. Power plants in Manila do not contribute as much to poor air quality because of their high stacks. Costs. Cleaner fuel oil could be imported or produced in Philippine refineries. This would require either changing to low-sulfur crudes as feedstocks, or extending the equipment for desulfurization and perhaps other secondary treatments, such as visbreaking. The precise costs are, however, unknown. Final cost estimates are derived from the sulfur premium, the increase in the world market price of fuel oil with decreasing sulfur content. The sulfur premium is US$5-10 per ton per percentage sulfur. Fuel consumption in power plants was about 1.4 million tons. Buying similar oil with a sulfur content of 2 percent instead of 3 percent would involve a cost of US$10 million annually. Of course, S02 emission would decrease. 9 Theemission factor for TSP is proportional tothe sulfur content ofBunker-C fuel oil (grade 6), according toEFTsp (kg.m 3) = 1.25* S (%w) + 0.36(EPA 42). Two other factors are for Grade 5fuel oil: EFTsp(kg.m-3) = 1.25 and in case of Grade 4 fueloil: EFTSp (kg.m3) = 0.88. 74 Abatement Measures: Effectiveness and Costs Policy instruments and target groups. Fuel quality and emissions standards Table 4.9: Use of 2% sulfur fuel oil in power plants are enforced through legislation. Effectiveness: 500ton PM, 0 (1995). Target groups other than Costs: US$10million. environmental institutions are, the Benefits: Onlyminor avoided health effects; National Power Corporation, the ReductionofSO 2 emission. PhilippinesNational Oil Company InstrumentsandInstitutions: DENR, Energy Regulatory Board. Term: Immediate. and relevant energy policy authorities. Targetgroups: NationalPower Corporation, Philippine NationalOil Company. Term. From a technical viewpoint, low-sulfur fuels can be in use within a year. A summary of measure for using of 2 percent sulfur fuel oil is in Table 4.9. Treatment offlue gases Power plants are not the dominant causes of air Table 4.10: Commontechniques for cleaningofflue gases pollution in Metro Manila Pollutant Flue-gascleaning technique (see chapter2), therefore, PM,o Electrostaticprecipitators, fabrc filters, (multi)cyclones measures to reduce their SO2 Wetscrubbers, flue gas desulfurization, drysorbent injection techniques emissionshave a low NO, Selectivecatalytic reduction priority. Treatments aim at 0 removing PMIo, SO2 and NOXfrom flue gasesl . Common techniques are listed in Table 4.10. Removing 02 from flue gases results in waste material, such as gypsum. Wet scrubbers also partially remove PM,o from flue gases. Effectiveness. Selective catalytic reduction and dry sorbent injection is 80 to 85 percent effective, flue gas desulfurization is 90-95 percent effective, and electrostatic precipitators and fabric filters are 95-99 percent effective. Multicyclones are less effective, capturing only about 50 percent of the large particles from fuel oil combustion. The small, harmful particulates (less than 5 microns) are barely separated. Costs. Preliminary estimates include an investment of US$10 million for electrostatic precipitators with an annual cost of US$3-5 million. SO2 removal, which involves reduction of the 80,000 tons of emissions with 90 percent flue gas desulfurization, has an estimated requirement of US$100 million annually. Policy instruments and target groups. Legislation concerning allowable emissions and prescriptions to use a specific flue gas treatment. The National Power Corporation and environmental institutions are the target groups. 1o Airpollution due to CO 2 isnot an urbanpollution problem and is, therefore, outside the scope of thisstudy. URBAIR-Manila 75 FUEL COMBUSTIONOTHER THAN FORPOWER PRODUCTION Cleanerfuels Switching to cleaner fuels includes options ranging from lowering the sulfur content of Table 4.11: Cost-effectiveness of clean fuel, BOF, to switching to natural gas, results in and fuel shifts less PMIo emission. The measures are Characteristic Effectiveness Cost summarized in Table 4.11. Reductionofsulfur content 40% US$10-20per There is a lack of data on the use of the inheavy fuel oil to 2% tonfuel fuel oil (number of plants factored by annual Switchingtonatural gas 99% Unknown fuel consumption), therefore, our estimates of the effectiveness and costs of abatement are only preliminary. Estimates of reductions are as follows: * emissions: 5,000 tons (1995); * mortality: 100; and * RSD: 2.5 million. Industry's total consumption of heavy fuel oil is, according to our estimates, about twice that of power plants. It might be inferred that costs of firing clean fuel (heavy fuel oil with 2 percent sulfur) is about US$10-20 annually. Policy instruments and target groups. Reductions in the sulfur content of fuels can be achieved by adopting standards, and having the petroleum industry, including importers of oil products, supply clean fuels. Switching to natural gas might be a long-term possibility, although this implies a radical change in the energy supply structure. Such change will require the use of energy-policy instruments. Term. From a technical point of view, low- sulfur fuels can be implemented in the short Table 4.12: Summary. Reduction of the term. See summary in Table 4.12. maximum sulfur content of heavy fuel oil (BOF) to 2% (weight) Effectiveness: 5,000tons PM., (1995). Flue gas treatment Costs: US$10-20million for industry. Benefits: AvoidedMortality:100, AvoidedRSD : 2.5million. The optionsfor flueThe gasoptions reductionfor flue are similar Benefits:P327 million to those for power plants. Multicyclones are Renof P32 mission Reductionof S02 emission. cheap and reliable devices to abate PM10. Instruments/institution:DENR, Energy Regulatory Board. However, they are only effective in case of Term: Shortterm. large (greater than 5 microns) particles. Flue Targetgroups: Petroleumindustry, Industry ingeneral. gas treatments like multicyclones are only 50 percent effective for suspended particulate matter from heavy-fuel oil combustion; smaller, more harmful, particulates are not controlled. 76 Abatement Measures: Effectiveness and Costs INDUSTRIAL PROCESSES (NON-COMBUSTIONSOURCES), REFUSE BURNINGAND CONSTRUCTION The lack of data about process emissions,estimated at 3,000 tons of PMio (annually),does not allow for listing an appropriateset of measures.Refuse burning results in PMIoemission estimatedat 6,000tons annually.More informationis required on the source characteristicsof these emissionsbefore measurescan be suggested. PM1o emissionresulting from constructionis estimated at 3,500 tons. A part of the emissions comes from demolitionactivities. There are several means for controllingconstruction emissions includingscreens alongsidedemolition works, the use of chutes to remove rubble,etc. 5. ACTION PLAN The following action plan is based on the cost-benefit analysis of various measures that reduce air pollution and the damages that result from it. This 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" fall into two categories: 1. Technical and other measures that will reduce exposure and damage; 2. Improving the data collection, as a basis for establishing an AQMS in Metro Manila. ACTIONS TO IMPROVEMETRO MANILA AIR QUALITY AND ITS MANAGEMENT Actions to improve air quality Actions and measures have been formulated and proposed by the Manila URBAIR working groups, through other World Bank projects, and by consultants. Proposed actions and measures are categorized as follows: 1. Improved fuel quality; 2. Technology improvements; 3. Fuel switching; 4. Traffic management; and, 5. Transport demand management. The Action Plan, composed of priority short-term measures, is given in Table 5.1. The full list of proposed measures is presented below. For all measures, except cleaner fuel in power plants, the calculated benefits are substantial-in the tens of millions of U.S. dollars annually. The benefits, as a rule, are much higher than the estimated costs. Lower lead in gasoline is an important measure, already initiated through current agreements. Lead-free gasoline is a prerequisite for clean vehicle standards and is not listed as a separate measure. The success of these measures rests with enforcement. It is important to ensure that necessary technical improvements and adjustments, such as workshop capacity and capability for adjusting engines, and the assurance of available reasonably priced spare parts. 77 78 Action Plan Table 5.1: Action Plan of piority abatement measures, for proposed immediate introduction in NCR, based on costlbenefit analysis Benefits Timeframe Abatementmeasure Avoided emissions 2, Avoidedhealth Costsof measure Introduction of Effectof tonsPM1i1yr damage measure! measure Vehicles Addressinggross p ...... Effectivesmoke- 2,000 US$16-20million, US$0.08million Immediate Short-term belchingcampaign 158deaths, 4 millionRSD. Improvingdiesel 1,200 US$1012 million, US$10milion Immediate 2-5years quality 94deaths, 2.5million RSD. Inspection/ 4,000 US$30-40million, US$5.5million Immediate 2-5 years maintenance 316deaths, ...KW ...... I...... Fuelswitching: 2,000 US$5973million, Immediate 5-10years diesel-4 gasolinein 600deaths, vehicles 15million RSD. Cleanvehicle 7,000 million, US$5-20million Immediate 5-10years standards 895deaths, 24million RSD. Fuelcombustion Cleanerfuel oil 5,000 US$10-20million US$10-20million Immediate 1-2years 100 deaths ...... 6 ;...... I...... 2.5million RSD ...... Powerplants Cleanfuel 500 small US$10million Immediate 1-2years Notes: i Timeframe for starting the work necessary to introduce measure. 2 Thevarious abatement measures are not necessarily independent ofeach other. Thus, the 'decided emissions" stated in this tablefor each measure separately may not simply be added, if one wants an estimate of thetotal effect of a packagesof measures. Table 5.2 lists abatement measures for which cost-benefit analysis has not been performed. These could also be introduced in the short term, and would benefit air quality. Actions to improve the Air Quality Management System (AQMS) Actions to improve the AQMS include the following: * improving air quality assessment, * improving the assessment of damage and its costs, * improving the institutional and regulatory framework, and * building awareness among the public and policymakers. URBAIR-Manila 79 Table 5.2: Additional measures for short- to medium-term introduction Timeframe Abatementmeasure Action Introductionof Effectof measure measure Vehicles Addressdilution and adulteration offuel, Shortterm Shortterm Restrictlife time of public UVs and buses. Shortterm Med.term Trafficmanagement Improvecapacity ofexisting road network, - improvesurface Shortterm Med.term - removeobstacles -improvetraffic signals Extend/developroadnetwork: Improve/eliminate Shortmed.term Med.term bottlenecks, MakingStreets safer for NMV's and Pedestrians and - bicyclepaths Shortterm Shortterm notonly for more motor vehicles. Transportdemand management Improveexisting bus system, - improvetime schedules Shortterm Med.term - improvejunctions/stations - makeintegrated plan Developparking policy, - restrictionsincentral area Shortterm Shortterm - parkingnear mass transit terminals Shortterm - car-pooling Shortterm Non-motorizedvehicles (NMV), - bicyclepaths Shortterm Shortterm Improveroad access toNMV. - improvedaccess - enforcement Chapter 2.6 presents necessary actions to improve air quality assessment. They are summarized in Table 5.3. Table 5.3: Actions to improve Air Quality Assessment. AirQuality Monitoring * Improvethe ambient air monitoring system; * Upgradelaboratory facilities and manpower capacities; * Establishand improve a quality control system; * Establisha database suitable for providing airquality information tothe public, control agencies, and ...... lawmakers. Emissions . Produceaninventory ofindustrial emissions; * Developintegrated, comprehensive, emissions standards procedure; ...... * ...... i onon roads. Populationexposure * Establishappropriate dispersion modeling tools for control strategy inMetro Manila. A COMPREHENSIVE LIST OF PROPOSEDMEASURED AND ACTIONS. Table 5.4 presents the complete list of proposed measures to improve the Metro Manila air quality 00 0 Table 5.4: Urban Air Quality Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks TRAFFICMANAGEMENT 1.1mprovetraffic flow a.Improve existing Removeobstnuctions (basketball 1994-onwardsLGUs, PNCC, MMA bettertraffic flow Improvedriver-friendliness roadnetwork courts,vehicles, parking, repair ofroads shops) EnsureUmely coordination of all 1994 UtilitiesCoordinating digging Council(MMA), LGUs LGUsstudy imposition ofordinance 1994 onwards LGUs onnuisances Repairroads (with cooepration of 1994-onwardsDPWH, PNCC privatesector) Passgridlock laws, ordinance 1995 LGU, MMAshould have a Congress,MMA transport,land use study b.Extend/develop -Analysesituation (bottlenecks, S/M DPWH,LGUs, DOTC C3& C6completion should roadnetwork etc.) bea priority -Supportresponsible agencies Note:10 pt. problem of -Activateother plans like C5 PMAsubmitted to FVR c. Improve/co-ordinateSystematize traffic signals S/M TEC/DPWH,MMLTCC, trafficsignal systems (implement PD 207) LGUs,PNP d.Segregate mass Strictlyimplement bus lanes ASAP MMA,LGUs, PNP transportfrom other modes. e.Improve facilities for Constructpedestrian overpasses 1994- DPWH,Private Sector non-motorizedtraffic andsecond layer roads. Establish onwards PNCC,DOTC sidewalks f. ImplementTransport Study the implementation ofa 1995 DOTC,LGU MMLTCC Serv.Rationalization private car utilization restraint policy Programs -setup bus terminals, etc. (park 1994 LGU,MMA andride) limit entry within metropolis -defineand mark the lanes 1995 TEC/MMA (expresslanes, HOV, and enforce bicyclelanes) -studystaggering ofwork and 1995 DOLE,PCCI, Employers' studyhours/days & day-off Assoc.Unions Note:S, < 2yrs; M,2-5 yrs; L, 5-10 yrs; VL, > 10yrs; P, priority item. Table 5.4: Urban Air Ouality Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks -encouragecarpooling through 1994 MMA,LGU,DOTC demandmanagement measures likeparking regulations (higher fee, restrictedparking areas, etc.) -useeco instruments to influence 1995 DTI/BOI,BPS,DOTC vehicledesign and fleet air and quality -designatewhere PUVs (buses, 1994onwards MMLTCC, MMA, LGUs, taxis,jeepneys) can stop and PNP strictlyimplement this policy (*P)g. Immediate Rationalize/standardizetrafficlaws, 1994 Congresstoinclude Improvementof rulesand regulations bypassing creationw/in LTO of Enforcement/Traffictraffic code & usestandard form trafficcourt Laws Studyimplementation ofcolor 1995 DOTC/LTO vehiclecoding for PUVs Provideproper training to 1994onwards MMLTCC, LGUs PNP enforcers/driversandrequire them topass exams Putin place more stringent drivers 1995onwards MMLTCC, LTO licensingsystem Setup monitoring and evaluation 1995onwards MMLTCC LTO for drivers systemfor enforcers and for MMA,DILGfor enforcers violators -moresanctions/stiffer penalties 1995onwards LTO (re-educationand suspension of driverslicense) - incentiveprogram for enforcers 1995onwards MMLTCC, PNP, DILG Authorizedlicense plates should be 1995 LTO,Private sector immediatelyavailable toall who register,through expansion ofplate makingplant (proper specs) Computerizedriver/vehicle info r to 1994 DOTC,LTO determinehistory of violation Reactivatedemerit system for 1995 LTO,Insurance driversand link this to insurance commissioner system 00 Table 5.4: Urban Air Quality Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks Seriouslyenforce anti-jay walking 1994 AllLGUs, MMA, PNP law (*P)h. Reactivate and Createtechnical group to evaluate1994 DOTC/LTO expandcomputerized existing IS and prepare plans informationsystem at LTO i. StrengthenTraffic Effecttraffic safety seminars on 1994 MMA,DOTC, LTO, SafetyProgram trafficrules and regulations (re- NCTS,DILG, PNP, LGU, education) Phil.Motorist Assn. Immediatelystrengthen MMLTCC fortraffic improvement CreateMM Traffic Safety and MMLTCC AdvisoryCommittee Havevisible traffic policemen 1994 PNP,MMA,LGU,DILG presentall thetime. Involve barangayofficials Usemass media for information 1994 PIA,LTO, MMLTCC dissemination Establishmentofsidewalk network S-M MMA,LGUs, DPWH Developnetwork of Designatespecific truck terminals S LGUs,DILG, MMA, truckterminals, as part HLURB of a schemefor efficienttransport of goods. TRANSPORTDEMAND MANAGEMENT 1.Expansion ofbus Advocate&Support S-M DOTC,MMLTCC, NGOs system 2. (*P)Provide/ Accelerate(expansion/extension) of 1994 DPWH,NGOs,DOTC,Decline in personal Acceleratemass transit implementpara transit LRT and use of railwaysand PNR,LRTA, PNCC vehicletravel and systemand other improvedMetro Ferry increasein mass environmentfriendly transit transportation Studyfeasibility of electricvehicles ASAP DOST,NGO, Academe, Less vehicular OP,DOE emissions Table 5.4: Urban Air Quality Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks 3.Survey present MMLTCC& DOTC to create team S MMLTCC,DOTC Thereshould be a Metro mass-transitsituation, to evaluateand make ManilaTransport /Land anddevelop recommendations. UseStudy comprehensive/ integratedplan on existingcomponents: -improvetime DPWHshould consider schedules,co- drverfrendliness of roads, ordination islands,etc. - improve junctions/stations, especiallywhere severalmodes meet 4. Surveynew Evaluateexperiences ofother S-M DOTC conceptsfor person countries,and use the ones that transport(APM, areapplicable guidewaybus system, pointto point buses, etc.)and evaluate its possibleuse in MM. 5.Promote non- Putin place necessary S-M MMLTCC,LGUs, DPWH motorized infrastructure. PIA,DOTC transport(NMT). Encouragethrough media S-M Improve,construct facilities,such as lanesand roads for NMT 6.(*P) Use parking MMLTCC&LGUs to provide 1994-1995 LGUs,MMA Considerplans for policyto influence guidelinesLGUs, MMA to impose emergencysituation trafficmode mix, e.g., higherfees higherparking fees, parkingrestrictions in centralareas, parking facilitiesnear mass transitterminals, carpoolguidance system,designate park& rideareas 00 Table 5.4: Urban Air Quality Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks IMPROVEDFUEL QUALITY 1.Address dilution a.Strictly enforce existing law on continuing DOE,BPS, Oil indu- 10%reduction Canbe minimized through andadulteration of fuels activity stres,truckers, assns of theuse of marker dyes and fuel gasstations testkits. b.Deputize NGOs as inspectors ASAP DOE TSP Legalbasis is being studiedby DOE c. Frequentlyinspect esp. in MM On-going DOE d. Increasepenalties through June-Dec DOE,COCAP,Congress legislation 1994draft DTI/BOI,ERB, other legislation NGOs e. Propedylabel gas pumps, cars, S BPS,DOE etc. f. informpublic how to detect S DOE,PIA adulteratedand diluted fuel, and its effect 2.(*P) Decrease lead Enforcemandatory regulation S/M DOE,Petrol Industry Lowerblood lead Programfor lead phase- levelin leaded levels downhas been done. gasoline 3.(*P) Market Establishvoluntary-use taxsystem unleadedgasoline. Identify/Evaluateother additives. a.Issue an E.O. to accelerate DOE,Petrol Industry 100%reduction of Additivesshould be phasein ofunleaded gasoline leadby year 2000 registeredsince some additivesare not approved foruse in USAand other countries. Standardsfor underground storagetanks should be determine. DOEsubject to the results ofthe study on the move to certainsectors. b. IECon proper use of unleaded 1994onwards PIA, DECS, DOE Petrol increaseuse of ULG Industry Table 5.4: UrbanAir Quality Management(URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks 4. Phase-outof leaded Mandatory regulation Jan.1, '98- DOE,Petrol Industry tobe Considersuper low lead gasoline.Time urbanareas deter- (.05%)since this may lower schedule. Jan.1, 2000 - mined thetotal lead emission wholecountry soonerthan an all-leaded scenario 1. Identifysectors who will beaffected and identify safetynets. 2. Notethat COCAP's objectsto phase-out dates andbelieves it should be in Jan.1996 3. DOEagreed with the schedulesubject to the resultof the study on the impactof this move to certainareas Needto defineurban areas. 5. (*P)Decrease Regulation,phasing 0.5% by 1996 S/M DOE/petroleum reductionofTSP maximumallowable companies 0.5%sulfur by 1996 sulfercontent in diesel Decreasemaximum 3%by 1996 allowablesulfer 1%by 2001 contentin fuel oil 6.Upgrade diesel-fuel Alter fuel quality standards S/M DOE,Petrol industry, Studyimpacts, Reviewof environmental quality(viscosity, BPS,NEDA DENR esp.on equity standard sulfurcontent and volatility) Correctlabeling through dyes Requiresrefinery *Rigorously study the im- restructufingl pactsof allthese proposals upgrading (#2to #6) 7. Reviewenergy a.Createtechnical group to study 1994onwards DOE,ERB,DENR,OP pricingpolicy consider the issue. Recommend removal of impactsto pricedistortions and incorporate all environment environmentalcosts (petroleumproducts andelectricity) 00 Table 5.4: Urban Air Qualitv Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks encourageconservadon, through ERB,MERALCO,electric feestructures and including coops. environmentalcosts examples i. Removesubsidies on diesel, LPG 1996-2007 ERB/DOF ii. Pollutiontax (recommend to ASAP DOF/DENR/BIRIDOE RRPfor inclusion in legislation ERB-leadagency reviewof leaded gasoline b.Studyimpacts of the removal of 1994onwards DOE,ERB,DOF,NEDA subsidyfor diesel (phase out of existingsubsidy) c.Improvethe regulators DOE/ERB mechanismtomake petroleum' industrymore competitive d.nlormpublic about the impacts of ASAP DOE/ERB deregulationonprices of diesel gasoline,etc. FUELSWITCH 1.(*P) Gasoline for Tax/subsidymodification 1995 DOF,Tax Research Taskforce consisting of dieselin UVs Center,ERB, DOE DOFand Tax Research Centershould study restructuringoftaxes vis-a- visdiesel and gasoline. Studypossibility tostop registrationof new diesel engines. Conductstudy on technical 1994 FILCAR,DOTC, DOE, Samegroup to studyprice/ requirements,health and safety DENR,DOH marketimplications. Action andprice/ market implications. Planto depend on outcome of thestudy. Sub-committeeonexcise taxheaded by NTRCis currentlyreviewing the proposedoil tax restructuring. 2. LPGfor transport Studythe use of LPG 1994-1995 Pricedisparity between (buses,PUV) homeLPG & automotive. Table 5.4: Urban Air Quality Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks Createa Technical Task Force to June30, 1994 DOE/DOTC/ DOF/ ERB LPGshould be considered. studyLPG utilization for transport LIVECOR,FILCAR Revive& developinfrastructure for 1995-1996 Oilcompanies/DOE/DTI- Todepend on findings of theuse of LPG BPS/NGO study. 3.(*P) CNG, coco-oil, Updating R&D study 1995-1997 DOE/DOST alcohol 4. Naturalgas in Studypossibilities (resources) 1998 DOE industry AIRQUALITY MONITORING 1.Design and set up Evaluateexisting monitorng S DOST,DENR Thereshould be bi-monthly modified,improved, system;improve it, andseek or,if possible,weekly andextended fundingfor implementation adviceon air quality monitoringsystem conditions 2. Designand Prepareproposal, ask funding S DENR,LLDA, DOST, establish support BPS Quality/Control/ QualityAssurance System -evaluationofsites; numberand location -selectionof methods, parametersmonitored, frequencyofoperation 3.(*P) Increase and Encouragecollaboration with Endof 1994 DENR/NGO/Private upgradeDENR- LLDA NGOs, private sector in setting up, Sector/Donor monitoringcapability privatesector in settingup, Community operatingand maintaining monitoringstations Tapfunding agency support ASAP community Rehabilitatethe air pollution index ASAP EMB/MEIP/ADB boardalong EDSA Setup additional index boards 1995onwards EMB/donors 4.Appropriate budget Conduct appropriate researches S-M DOST,Academe, to environmental andstudies which will relate to accreditationofprivate agencyfor the morerational emission standards firmsand laboratories following: 00 00oc Table 5.4: Urban Air Quality Management (URB3AIR)Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibilitf Remarks Strengthenthe capability of the S-M DENR,donors DENRpersonnel inthe stationary sourcemonitoring and measurements Provisionofa standardized S-M DENR,donors monitoringequipment to support thesetting up of standards 5.(*P) Solicitactive participation of S-M Consultingfirms and Estimatecost if NGOswill Encouragethird party consultingfirms and laboratories by laboratoriesDENR, operate& maintain participationin accreditation(which will act as a DOH,DOST, Academe monitoringstations environmental thirdparty) in theconduct of monitoring compliancemonitoring to encouragecompliance and resolve reservationsof some sectors on reliabilityof data 6. (*P)Establish Improvepresent database on S-M PAG-ASADENR, LLDA computerized meteological,airquality data databaseofall MM dataregarding - airquality - meteorology (dispersion)and share databasewith all concemed 7. Minimizere- Encourageplanting and care of ASAP LGUs,MMA, DENR suspensionofdust trees,shrubs etc. Practiceturfing? ASAP LGUs,MMA Waterroads mosre frequently asneeded LGUs,MMA, NPCC, duringthe dry months (water from Citizens industrialtreatment plants may be usedfor this purpose) Table5.4: UrbanAir QualityManagement (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks INVENTORY/DISPERSIONMODELING 1.(*P) Develop an Requirethru EIS System for new S-M DENR integratedand plantsBy Administrative Order for comprehensive oldplants emissioninventory procedure,including emissionfactor review,update and QAprocedures. (Ensuresmoke stacks have ASAP DENR/LLDA samplingports to enable monitorng) 2. (*P)Improve DENR-LLDAcoordination and startby End DENRILLDA Includequantity of lead, emissioninventory for collaboration of 1994on- numberof facilities that use MM. Tapfunding support for this going volatilecompounds Developprocedures & costestimates a. Produceinventory Requirefirms to submit data S DENR,LLDA of industrialemissions DENR/LLDA tocollect and collate (location,process, data emissions,stackdata) b. Improveinventory Improvepresent data gathering S TEC,DOTC, MMLTCC of roadand traffic data c. Conductinventory SeekUSEPA assistance S DENR,LLDA ofdomestic emissions d. Studyresuspension Set procedure todo this and S DENR,LLDA of dusts conductstudy -fromroads -fromother surfaces 3. (*P)Strictly DENR- LLDA/3rd party monitoring mid 1994 DENRILLDA/ NGOs implementand enforcethe requirementforfirms to submitdata on emissions(Promote self-monitoringby firmsthrough responsiblePCOs) 0' V Table 5.4: UrbanAir Quality Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks Providetraining for PCOs ASAP DENR/LLDA/ PCAPI Increasesanctions for misreporting ASAP DENRILLDNlProf. RegulationCommission 4.Assess current Addappropriate stations to M PAGASA,UP College of modeling measuremeteorological data (in Meteorology tools/methods,and AQmonitoring) establishappropriate modelsfor control strategyin MM 5. Inventoryoflead Bureauof Customscollate data on S-M Bureauof Customs, importsby oil importations& DENR can monitor DENR companies&correlate thru declarations based on touses implementationofRA 6969 Inventoryof paint TapNSO census S-M NSO,DTI companies&motor shopsand car manufacturers INS77TUTIONALANDREGULATORY FRAMEWORK 1.(*P) Implement Passbills (Clean Air Act, Phil. 1994-1995 Congress,DENR, "polluter'spay EnvironmentalCode) imposing DOTC,LTO, NGOs prnciple"thru higherpenalties increasedpenalties for violatorsof PD 1181 andPD 984 and other measures Strengthenenforcement 1994 DENR,LLDA, DOTC, capabilitiesfor industrial and LTO,MMA, LGUs transportemission control Studyways to strenghten legal ASAP DENR,LLDA mechanismfor compensationof victims Considerincorporation ofroad user 1994-1995 DOTC/LTO chargein the registration fees Improvethe insurance policy 1994-1995 InsuranceCompanies, requirementforvehicle registation- LTO tiedto vehicle inspection. Require as partof mandatory insurance. Table 5.4: Urban Air Quality Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks Cancelfranchises ofviolators ASAP- LTFRB continuing 2. Increaseand Tapexisting academic institutions ASAP NGOsIAcademe/ upgradethe technical to providetraining DENR/LLDA capabilityof Encouragecommunity participation govemment,industry throughNGOs andNGOs in AQM -preparesimple to understandlists S DENR/EMB of whatto monitor - disseminateesp. through schools S DENR/DECS - IEClike komiks??, primer S DENR,DECS, PIA Upgradesalary scale of technical ASAP DENR/DBM/LLDA staffat regulatoryagency Allowthe use of fees and fines to S DENR& NGOsto push strenghtengovemment capability to forthis/ Congress monitorand enforce through passageof appropriate legislation - CleanAir Act & Phil.Env. Code ReviewQS for technical positions S DENR,CSC, DBM Encourageprivate sector S DENR,LLDA, NGOs, involvementinair pollution Phil.Motorist Assn., monitoringand control PCCI,MAP Accreditprivate laboratories for S DOTC/LTO testing,private group for MVIS and monitoring 3.Improve the Proposeone Traffic Management 1994 - draft Congress,MMA, DOTC coordinationof Authority-long term bill differentgovemment agenciesinvolved in airpollution control Strengthenexisting MMLTCC 1994 MMA,PNP, LGUs, LTO, TEC,MM Pollution ControlAssn. Preparecommon monitoring ASAP DENR/LLDA guidelinesfor LLDAand DENR (for industries)and strengthen co- ordinationbetween the two .O Table 5.4: Urban Air Quality Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks Studycreation of one S DENR,LLDA, Congress environmentalbody/ agency 4. ImproveLGU Providetraining Sonwards DENR,MEIP, LLDA, technicalcapability for MMA,LGUs, Local environmental GovemmentAcademy management 5. Providemore funds Provide more budget 1995onwards DBM/Congress/LGUs forenvironmental Allowuse of environmental fees M Congressto passlaw monitoringand andestablish a trust fund which will (revisedEnvironment enforcement trainexisting staff, get more Code,Clean Air Act) equipment,etc. Passordinance setting aside a S-M LGUs,MMA portionof thecollections from the anti-smokebelching campaign for useto strenghten the air pollution controlcapability 6.Analysis of Requirethe tachograph for all S-M Allconcemed agencies regulationsby all vehicles,esp. commercial vehicles concemedagencies PassOdometer Law S-M Congress,DOTC/LTO Requiretotal disclosure Requirethe sealing of the control S-M DOTCguidelines rodby authorized manufacturer or servicecenter authorized by manufacturer. Encourageimportation and use of S-M BPSto issue guidelines certifiedstandard spare parts NEDA-TRM,Tariff (definespare parts to avoidchop- Commission chop) 7. Passageof Billon Houseand Senate Committee on S-M Congress AntiPilferage Ecologyto supportthis bill Infocampaign include schools& S DECS,PIA churchesfor awarenessbuilding andvalue formation Table 5.4: Urban Air Qualitv Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks 8. Studypossible Evaluateexisting salary scale for S-M DBM,DENR, DILG, Civil incentivesfor mertincreases ServiceCommission enforcersand other staffinvolved in environmental management Tap"Environmental Trust Fund" to M DENR provideincentives once it is setup 9.Remove issues on Providedetailed implementing 1994 DENR,Inter-Agency jursdictional guidelinesof an EO-making LLDA GroupLLDA boundaresbetween asattached agency of DENR with LLDAand DENRas chair of LLDA Board DENR(whichcauses "grayareas" in the implementationof relatedrules and regulabons) 10.(*P) Strenghten Trainmore people ASAP DOTC/LTO,DENR, enforcementcapability LGUs,MMA ofLTOIDOTC, MMA, PNP,LGUs TapNGOs to assist ASAP COCAP,LGUs, civic groupslike Rotarans Setup "hot line' for publicto report ASAP LTO,MMA, MMLTCC violators Usemass media (social) pressure ASAP PIA,all concemed 11.Strictly and Updatecommon manual, which ASAP DENR,MMA, LTO, uniformlyimplement specifiesstandard procedures LGUs anti-smokebelching campaign Prepareand publicize conversion 1994 DENR,LTO chartre comparability oflyasaka, Hartridge& Boschtype equipment Studyqualifications oftechnicians ASAP DENR/EMB & provideclear training procedures forLGUs, MMA, LTO & PNCC teams Table 5.4: Urban Air Qualito Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks EncourageNGOs to join teams ASAP COCAP,other NGOs, LGUs Encouragegarage testing of public ASAP DENR,MMA, LGUs, utilityvehicles NGOs,PNCC, private operators,owners assn. Encourageprivate companies, ASAP NGOs,industry groups, schools,offices to starttheir anti- DECs,DENR, LTO, smokebelching projects with PNCC,LGUs, PCCI, technicalassistance from MAP govemment EncourageLGUs to buy their own ASAP LGUs smokemeters from fines/fees collected TECHNOLOGYIMPROVEMENT 1.State-of-the-art ExtendPD 1181 set time schedule M-L DOTC,DTI/BPS emissioncontrol for newcars, gasoline 2. State-of-the-art ExtendPD 1181 settime schedule M-L DOTC,DTI/BPS emissioncontrol for newmotorcycles 3. State-of-the-art ExtendPD 1181 set time schedule M-L DOTC,DTI/BPS emissioncontrol for newlight duty diesel vehicles(cars) 4. State-of-the-art ExtendPD 1181 set time schedule M-L DOTC,DTI/BPS emissioncontrol for Setlevels for smoke DENR heavyduty diesel M-L vehicles(UV, buses, trucks) 5. (*P)Address highly pollutingvehicles; a.Upgradejeepney Enforceexisting regulation, I/M S-M DOTC,LTO, ADB Lesspollution from engines enginesto system, replacement of jeepneys complywith new emission regulations?.Financing scheme. Table 5.4: Urban Air Ouality Management (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks Discourage Requirecompliance with emission 1994 TariffCommis-sion/ IAC- Studyphase-out of importationof dirty standards,either from the country- UTE importationof2nd hand and/oruncertified whicheveris more stringent vehiclesthru the repeal of enginesand vehicles EO782, EO 361, EO 354 Limitnumber of years for PUVsby 1994-1995 LTO Highmileage vehicles regulation degradefaster Createstudy group on how 1994 NEDA-TRM Resultsof study should uncertifiedimportation ofengines guidedecision makers on couldbe stopped necessarysteps to be taken. (*P)b. Inspection/ Expandoperations/coverage of on-going LTO Pollutivevehicles will Tocertify remanufacture of maintenancescheme MVIS nolonger be allowed usedengines to "as new" Strictlyimplement Encourageprivate sector onthe streets specification requirementthat all investmentinl&M program through on-going LTOfor guidelines vehiclespass economicincentives, and credit DTI/BOIfor incenfives emissiontests prior to ADBfor credit registration(once a yeartesting for private vehiclesand twice a yeartesting for public utlities Studypossible accreditation of on-going DOTC-LTO/DTI privateentities for motor vehicle inspectionsystem emission testing withclear sanctions and provision fortraining without conflict of nterest Re-activatecomputerized database ASAP LTO,PNCC, LGUs, Easiermonitoring & onall vehiclesand include law PNP,MMA enforcement enforcementdata Studyshift to 2-year Reviseregulations on vehicle 1995 LTO registrationfornew registration privatevehicles C. studyincome Preparemeasures to carry this out. 1994 LTOOffice of Transport enhancementof Coop jeepneydrivers Table 5.4: UrbanAir QualitvManagement (URBAIR) Action Plan Issue ActionRequired TimeFrame Agencies Impacts Cost Feasibility Remarks d. passthe DOTC/LTOregulations. Draft Bills S-M DOTC/LTO,Congress odometerlaw, truth in beprepared mileageAct; use of speedometerlenforce speedlimits; non- removalof tachometers 6.(*P) Industrial Sources Useof emission Licensing(emission reg's) 1994 Industryassociations controlequipment Chargeson emissions/ citizens& NGO,DENR Processmodifications/ Promote good environmental 1994 PCAPI,PICHE, PCCI, improvement practices MAP Encourage ASAP citizen/NGOaction vs. industrialpolluters 6. INSTITUTIONS, REGULATIONS, AND POLICY PLANS INSTITUTIONS" The main governmentagency responsible for environmentalprotection and managementis the Departmentof Environmentand Natural Resources(DENR). The EnvironmentalManagement Bureau (EMB) of DENR is chargedwith developingenvironmental management strategies and programs. EMB main tasks consistof recommendinglegislation, policies, programs,and projects regardingenvironmental management and pollutioncontrol; formulatingenvironmental quality standards;recommending rules and regulationsfor environmentalimpact assessment,and providingtechnical assistance for implementingenvironmental education and information campaigns.DENR Regional Officesimplement laws, rules and regulations,policies, plans, programs,and projectsat the local level.The PollutionAdjudication Board (PAB) cooperates with EMB and DENR RegionalOffices, and adjudicatespollution cases that are referredto it. The Laguna Lake DevelopmentAuthority (LLDA) has a mandateto manageand control the resourcesand environmentalconcerns of the Laguna de Bay and its region. It has jurisdictionover four cities and five municipalitiesin Metro Manila.Although the division of responsibilities betweenDENR and LLDA is well defined,the existenceof two separatejurisdictions may complicatethe performanceof regulatorywork. The Land TransportationOffice (LTO)inspects vehicles,and conductsemissions tests as a prerequisitefor registration.There are overlappingresponsibilities between DENR and LTO in testing motor vehicle emissions.The institutionsinvolved have very limited budgetsfor environmentalmanagement and protection,leading to a shortageof well-trainedpersonnel. Equipmentfor measuringemissions and monitoringneeds to be upgraded.Current fuel pricing and tariff policiesstimulate the use of dirty fuels and inefficientengines. Local GovernmentUnits (LGU)have the responsibilityof protectingthe local environment, and imposingappropriate penalties for acts that endangerthe environment.With the implementationof the Local GovernmentCode (1991),the environmentalfunctions of the Metro Manila Authority(MMA), which is supposedto be the coordinatingbody for Metro Manila, became less clear and are being redefined. Institutionsaremore fully described inPhilippines Environmental Sector Study. Toward Improved Environmental Policies and Management,World Bank Report 11852-PH (Mehta etal., 1993) 97 98 Institutions,Regulations, and Policy Plans The Inter-Agency Committee on Environmental Health has a coordinating function, formulates programs and policies, and promulgates guidelines for environmental health protection. The Board of Investments within the Department of Trade and Industry identifies priority areas for investments, and registers industries. Prior to registering, companies are required to secure either an Environmental Clearance Certificate (ECC) or an exemption. The National Economic and Development Authority (NEDA) has the task of integrating the concept of sustainable development in the country's economic development plans. The NEDA Director General is the Chairman of the Philippine Council for Sustainable Development (PCSD). NEDA serves as the secretariat of the PCSD, as well as all the Regional Development Councils (RDC). The Oil Price Stabilization Fund (OPSF) plays a role in setting oil and oil product prices. The Energy Regulatory Board (ERB) allocates costs across all refined products. Environmental considerations are not taken into account in either OPSF or ERBs pricing policies. The conceptual framework of the Philippine Strategy for Sustainable Development was accepted in 1989. It is a very general strategy with the achievement and maintenance of acceptable air quality as one of its objectives. DENR tasks are defined in the proposed Clean Air Act of 1993. It states that DENR has jurisdiction over all aspects of air pollution. Presidential Decree (PD) 1181 of 1977 provided for the prevention, control, and abatement of air pollution from motor vehicles. PD 1586 of 1978 established the Environmental Impact Assessment System. The Philippine standards for ambient air concentrations are as shown in Table 6.1. Table 6.1: National ambient air qualityguidelines for criteriapollutants Pollutant Shortterm ' Averaging Longterm Averaging g.g/Ncm3 ppm time glNcm3 ppm time Suspendedparticulate matter TSP' 230 24hrs. 90 - 1yr.c PM1o 150 24hrs. 60 1yr.' Sulfurdioxide' 180 0.07 24hrs. 80 0.03 1yr. Nitrogendioxide 150 0.08 24hrs. - - Photochemicaloxidants 140 0.07 1 hr. - - - asozone 60 0.03 8 hrs. Carbonmonoxide 35mg/Ncm 3 30 1hr. 10mg/Ncm 3 9 8 hrs. Leadd 1.5 - 3 months 1.0 - 1 yr. Notes: a. Maximumlimits represented byninety-eight percentile (98%) values not be exceeded more than once a year. b. ArithmeticMean. c. AnnualGeometric Mean. d. Evaluationofthis guideline iscarried out for 24-hour averaging time and averaged over three moving calendar months. The monitoredaverage value for three months shall not exceed the guideline value. e. SO,and TSP are sampled once every six days when using the manual methods. Aminimum number of12 sampling days perquarter or48 sampling days each year is required forthese methods. Daily sampling may be done in the future once continuousanalyzers are procured and available. f. Limitsfor TSP with mass median Jiameter less than 1O microns until sufficient monitoring data are gathered tothe proper guideline. Source:DENR (1992). URBAIR-Manila 99 AIR POLLUTION LAWS AND REGULATIONS A comprehensive set of air pollution laws and regulations has been enacted in the Philippines. Appendix 3 contains a summary of Air Pollution Laws and Regulations in the Philippines, and Metro Manila. The Philippines National AQGs are described in Appendix 2, together with the WHO Guidelines. The laws and regulations which provide the basis for improving air quality in Metro Manila are summarized below. * The Philippine Clean Air Act, adopted in 1994, and formulated as an umbrella Action Plan is pending in Congress. It includes plans for regulating the work of managing and improving air quality at the national scale. * Air quality standards have been set for major pollutants including TSP, PM1o, S02, NO 2, photochemical oxidants (such as 03), CO and lead (DENR AO No. 14, 1993). Elevated concentrations of other toxic compounds may exist near specific sources. The standards are comparable to those set by USEPA, but they are less stringent than WHO Guidelines. * The emissions standards for stationary sources are comprehensive. They also require monitoring activities (emissions and ambient air near the plant), and set requirements for good practices in operating process and control equipment (DENR AO No. 14, 1993). Permissible particle emission levels have recently been made more stringent (1993). The permissible SO2 emission will be more stringent in 1996. * Fuel specifications for sulfur and lead are still quite high, but are under consideration. Allowable contents of Table 6.2: Pollution reduction targets for Metro various pollutants in 1994, and the Manila aimed reduction are presented below. Present Aimedreduction Reducing sulfur and lead in fuels was (1994) the subject of voluntary agreements Sulfur(%, by weight) involving industries, DENR, and the (Ref.:DENR AO 14,1993) Congress, in 1994. as.summarized in - Fuel oil (BOF) 3.5 3.0 (byJan. 1996) Cbongress,i 1994,as summarizedi -Industrialdiesel (DOF) 0.7 0.5(by Jan. 1996) Table 6.2. - Motordiesel 0.5(by Jan. 1995) * An Environmental Impact 0.3(by Jan 1997) Assessment System (PD No. 1586, 0.05(by Jan. 2000) with last revised implementingrules - Coal 2.5 1.0(by.Jan: ..... of 1992) requires that all planned Lead(g PbAfuel) projects that are environmentally - premiumgasoline 0.8 0.15(by July 1995) critical,or located in an - regulargasoline 0.4 0.15 (by July 1995) critical,or located in an -unleadedgasoline 25%(by July 1994) environmentally critical area, must (marketshare) 50% (byJan. 1995) obtain an Environmental Compliance 100%(by Jan. 2000) Certificate before undertaking actual construction. For all projects falling within the scope of Environmentally Critical Projects, a complete environmental impact assessment must be made. Projects to be located in environmentally critical areas need to submit a Project Description to EMD. An outline/guideline for preparing an Environmental Impact Assessment for a Project Description, including a full description of the project's effects on local air pollution has been prepared by EMB. * Motor vehicle emissions standards (PD 1182, with implementing rules of 1980) correspond to standards enforced in Europe during 1975-1979. Subsequently, the regulations of European 100 Institutions,Regulations, and Policy Plans and other countries have become considerably stricter. However, a DENR Standard Review Committee is currently revising 1980 standards. The 1980 Philippine standard only covers CO and HC emissions from gasoline-powered vehicles during idling, and smoke opacity during a free acceleration test for diesel-powered vehicles. Modem vehicle emissions standards should cover CO, NOx, HC, and particles emission limits during driving, according to a standard test cycle. * Prohibitive regulations are in place regarding miscellaneous air polluting activities, such as activities causing fugitive particle emissions; handling of volatile organic components; open burning; and operating miscellaneous equipment such as furnaces, smoke ovens, bake ovens, coffee heaters, and paint booths. * Traffic regulations have been set with the aim to improve traffic flow on Metro Manila's main roads, reducing congestion and air pollution emissions per vehicle. Some of these measures include bus/PUJ lanes ("yellow lanes"); truck ban during rush hours on main thoroughfares; towing illegally parked vehicles obstructing traffic; prohibiting pedicabs/tricycles on main roads, and clearing obstructions on sidewalks and roads. These rules and regulations are considered judicially sufficient to forrn a basis for improving Metro Manila's air quality, if adequately implemented. The most aggressive enforcement campaign is the Anti-Smoke Belching Campaign, which has been active since 1977. Up to 18,000 smoke-belchers have been apprehended per year, which means about 1 out every 20 vehicles, if all utility vehicles and trucks/buses are counted. The actual effect of this effort on average smoke emissions from these vehicles has not been evaluated. With the DENR AO 14 and ELAsystem, it is expected that air pollution from stationary sources will decline. However, improvements will be small and slow, and may be easily offset by the present rate of development in population and activities. The same is true for motor vehicle- related air pollution. Lowering and removing lead and sulfur from gasoline is the only decisive regulatory action, and it must be followed up strongly to be successful. Present vehicular emission regulations are lax, compared to present state-of-the-art emission control, and are inadequate to curb emissions, although the Anti-Smoke Belching Campaign is being carried out rigorously. Rapid technical improvement of the diesel vehicle fleet, in particular, is necessary. POLICYPLANS Under PD 1181, the "OPLAN Clean Air Metro Manila" has been formulated with the aim to improve the quality of the air within five years, starting January 1993. Key to its strategy are the following activities: * an intensive information, education, and communication campaign; * networking with all national government agencies, NGOs, and other organizations which can play a role in this campaign; * enforcement in two phases: a 'benign' phase in the first six months in which everyone is given the chance to maintain their vehicles in good operating condition, and only excessive smoke- belchers are apprehended; and a punitive phase in the second six months in which all smoke- belchers will be punished; * promotion of cleaner fuels; URBAIR-Manila 101 * an inspectionand maintenanceprogram requiring emissions testing of all public utility vehicles,initially focused on buses and trucks; * reviewingthe pricing mechanismfor petroleumproducts, in particularthe subsidyfor diesel fuel and low tariffs and duties on importingsecond-hand engines; * finalizinga Clean Air 2000 ActionPlan for Metro Manila. The preliminaryClean Air 2000 Action Plan for Metro Manila has formulatedstrategies along three lines: policyreforms; institutional linkages and networking;and public information, education,and communication.The policy reformsaddress five fields: * reducinglead in gasolineand sulfurin diesel; * mandatoryinspection and maintenanceprogram of all vehicles; * clean jeepneys; * adoptingclean vehicleemissions standards and phase-outtwo-stroke motorcycle engines; and * traffic management. EMB'sAir Quality ManagementMaster Plan were targeted to be finalizedin 1994.Its ten major measuresare: * remove the price subsidyon diesel; * introduceunleaded gasoline; * encourageor mandatethe use of unleaded gasoline; * improvediesel quality; * introducea strengthenedair pollution control licensingsystem; * require all new gasolinevehicles to use unleaded gasoline; * encouragereplacing diesel engines with gasolineengines; * require all new motor vehiclesto meet emissionsstandards in country of design origin; * mandatoryinspection and maintenanceprogram for all vehicles;and * introduceadvanced emission control systemsfor new dieselengines. In DENR's Anti-SmokeBelching Program,a continuinginformation, education and communicationprogram plays an importantrole, in order to encouragepeople's active participation.A number of policies need to be developed,especially incentivesto driversto behave in a less-pollutingway. MEIP'sEnvironment Management Strategy contains an AQMS which aims to reducepollution below the proposedEMB air quality guidelines.The strategycontains policies for phasing out lead in gasoline,and sulfur in bunker fuels; a programfor making vehiclescomply with emissions standards,coupled with an informationcampaign of the advantagesof proper vehicle maintenance;a ban on large scale importationof used engines which do not meet the standards; strengtheningmonitoring capabilities; and monitoringso that a more specificindustrial emission control strategycan be developed. ADB carriedout a study on vehicularemission control in Metro Manila is now developinga US$50million investmentproject. The strategycontains six measures: * reducinglead in gasoline; * low sulfur diesel fuel; * inspectionand maintenanceprogram; * clean vehicleemissions standards; * cleanjeepneys; and * public information,education and communication. 102 Institutions, Regulations, and Policy Plans PRIVATE SECTOR PARTICIPATION Although strong legislation and government implementation are crucial, public awareness of the problem and private sector accountability are equally vital, as exemplified by the action of one company in Manila which announced that it would only accept deliveries from trucks which passed the government standards (Box 6.1). The company started testing trucks entering its premises and rejected vehicles which were in violation of the government emissions standards. Such action improved the environment and provided a model for private sector involvement. "Adopt-a-Street" is another example of how to promote private sector participation in socially responsible environmental management and awareness raising. Environmental education, outreach via television and newspaper should be promoted vigorously to improve public participation in the regulatory process in overall air pollution management of the city. Box 6.1: Pollution Reduction by the San Miguel Corporation The Philippines' first multinational company, the San Miguel Corporation, used its clout to influence its suppliers and employees to meet vehicular emissions standards. The pollution control officer of San Miguel's brewery in Polo, Valenzuela, Metro Manila, was alarmed by the air quality monitoring reports issued by the DENR. He recommended to his management that the company conduct business only with suppliers whose trucks or delivery vehicles meet the government emissions standards. Management supported and immediately implemented the recommendation. After all, they were the ones directly breathing the emissions from the smoke- belching trucks. DENR trained the staff on emissions testing and initially lent the Brewery a smoke meter. Only vehicles that passed the emissions test drove inside the brewery's premises. With an average of 200 truck and other commercial vehicles in and out of the area every day, the firm decided to purchase two smoke meters costing P400,000 each. San Miguel requires that vehicles be tested every six months and issues stickers to trucks that pass the test. The administrative cost for each vehicle tested is about P150. San Miguel does not expect or intend to recover its investment . This company is willing to spend its funds to help clean the environment even if this does not result in immediate or direct corporate profits. When the testing first started, some 30 percent of the vehicles failed the test. Today that figure is down to 5 percent or less. This program has expanded and now San Miguel is encouraging its employees to test their personal vehicles. Some 80 companies, 3 schools and a subdivision have adopted the San Miguel model. One of the country's largest financial institutions, the Far East Bank and the Trust Company, has even donated a smoke meter to be used by the City of Makati and other local governments running similar programs. Source:Local Environmental Action in Metro Manila, Models ofCommunity Govemance, MEIP 1996. REFERENCES Anglo, E. (1994). "Impact of the Manila Thermal Plant on Short and Long-term SO2 Ambient Concentrations. A Preliminary Report, and Line Source Modeling for Metro Manila." Progress Report for URBAIR. Univ. of Philippines, Dept. of Meteorology and Oceanography, Quezon City. Asian Development Bank (ADB)/Environment Management Bureau (EMB) (1992). "Vehicular Emission Control Planning in Metro Manila." Prepared by Engineering-Science Inc. in association with Basic Technology and Management Corp, Published by Asian Development Bank, Manila. Ayala, P.M. (1993). "Air Pollution Emissions Standards for Metro Manila 1990." Department of Environment and Natural Resources (DENR)/Environmental Management Bureau (EMB), Manila. Baker et al. (1992). "Final Report for Vehicular Emission Control Planning in Metro Manila." Asian Development Bank T.A. No. 1414 - PHI, Manila. Baker, J., R. Santiago, T. Villareal, and M. Walsh. (1993) "Vehicular Emission Control in Metro Manila." Asian Development Bank PPTA 1723, Manila. Binnie & Partners (1992). "Modernization of Environmental Monitoring Facilities and Capabilities in Response to Philippines' Energy Development Project." Report to EMB. Binnie & Partners, Consulting Engineers, Manila. Birk, M.L. (1992). "The Effects of Transportation Growth on Energy Use, the Environment and Traffic congestion: Lessons from Four Case Studies." Paper presented at the Transportation Research Board Conference, January 12-16, Washington, D.C. Claiborn, C. et al. (1995). "Evaluation of PMIo Emission Rates from Paved and Unpaved Roads Using Tracer Techniques." Atmospheric Environment. 29: 1075-1089. Department of Environment and Natural Resources (DENR) (1993). Revised Air Quality Standards of 1992, Revising and Amending the Air Quality Standards of 1978. DENR Administrative Order No. 14 and 14-A, Series of 1993. Govt. of Philippines, Manila. Department of Transportation and Communications (1991). "Metro Manila Urban Transport Development Plan (1990-2000) project." EDSA Mass Transit Study SS 1/1991, Manila. 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 WHO/PEP/GETNET/93.1-A. Geneva: World Health Organization. Engine, Fuel and Emissions Engineering Inc. (1993). "Motorcycle Emissions Standards and Emission Control Technology." Engine, Fuel and Emissions Engineering, Inc., Sacramento, CA. Fuentes, R.U. (1993). "Draft Clean Air Act of 1992." Paper prepared for URBAIR Workshop in Manila, June 26-28, 1993. 103 104 References Francisco, H.A. (1994). "Valuation of Air Pollution Damages in Metro Manila." Paper prepared for URBAIR, Manila. Hutcheson, R. and C. van Paassen. (1990). Diesel Fuel Quality into the Next Century. London: Shell Oil Company Public Affairs. Shah, Jitendra, Tanvi Nagpal, and Carter Brandon (eds.) 1997. Urban Air Quality Management StrategyforAsia: Guidebook: Washington, D.C.:The World Bank. Lave, L.B. and E.S. Seskin. (1977). Air Pollution and Human Health. Baltimore/London: Johns Hopkins University Press. Lesaca, R.M. (1993). "Air Quality Related Rules, Regulations and Standards, their Enforcement, Effectiveness and Necessary Items for Further Improvement." Paper prepared for the First Urban Air Quality Management Workshop, June 26-28, Manila. Lesaca, R.M. (1994). "Urban Air Quality Management in the Philippines. Final report. TEST Consultants Inc., Manila. Lloyd's Register (1991). Marine Exhaust Emissions Research Programme; Steady State Operation and Slow Speed Addendum. London:Lloyd's Register Engineering Services. Lodge, J.P.Jr. (1992). "Air Quality in Metropolitan Manila: Inferences from a Questionable Data Set." Atmospheric Environment. 26A: 2673-2677. Manins, P. (1991). "Model for Air Pollution Planning." Environmental Management Bureau, Manila. McGregor, D.B. and C.S. Weaver. (1992). "Vehicle I/M Test Procedures and Standards." Engine, Fuel and Emissions Engineering, Sacramento, California. Midgely, P. (1993) Urban transport in Asia: An operational agenda for the 1990s. World Bank technical paper number 224). National Economic and Development Authority (NEDA). (1994). "Study on the Impact of the Phase-out of Leaded Gasoline." NEDA, Manila. Ostro, B. (1992). "Estimating the Health and Economic Effects of Air Pollution in Jakarta: A Prelirninary Assessment." Paper presented at the Fourth Annual Meeting of the International Society of Environmental Epidemiology, Cuernavaca, Mexico, August 1992. Ostro, B. (1994). Estimating the Health Effects of Air Pollution: A Methodology with an Application to Jakarta. Policy Research Working Paper 1301, Washington, DC: World Bank. Paassen, C.W.C. van, et al. (1992). The Environmental Benefits and Costs of Reducing Sulfur in Gas Oils. Brussels: Oil Companies' European Organization for Environmental Protection and Health (CONCAWE). Parkes, D. (1988). Matching Supply and Demandfor Transportation in the Pacific Rim Countries Post 1990. London: Shell Oil Company. Perissich, R. (1993). "Auto Emissions 2000, "Stage 2000" of the European Regulations on Air Polluting Emissions of Motor Vehicles." Proceedings of the symposium. Brussels - Luxembourg: Commission of the European Communities. Rolfe, K.A. (1992). "Collaboration on the Preparation of Air Quality Management Master Plan for the Philippines." Report no. EHE/ICPIRUD/001, World Health Organization Western Pacific Region, Environmental Health Centre, Kuala Lampur. Shin, E., R. Gregory, M. Hufschmidt, Y-S Lee, J.E. Nickum, and C. Umetsu. (1992). Economic Valuation of Urban Environmental Problems. Washington D.C.: World Bank. URBAIR-Manila 105 Subida, R.D. and E. B. Torres. (1994). "Impact of Vehicular Emissions on Vulnerable Populations in Metro Manila." University of the Philippines/World Health Organization, Manila. Subida, R.D. (1994) Medical Treatment Costs calculated for URBAIR. Communication to World Bank. Tharby, R.D., W. Vandenhengel, and S. Panich. (1992). "Transportation Emissions and Fuel Quality Specification for Thailand." Monenco Consultants Pvt. Ltd., Oakville, Canada. Tims, J.M. (1983). Benzene Emissions from Passenger Cars. Brussels: Oil Companies' European Organization for Environmental Protection and Health (CONCAWE). Tims, J.M. et al. (1981). Exposure to Atmospheric Benzene Vapor Associated with Motor Gasoline. Brussels: Oil Companies' European Organization for Environmental Protection and Health (CONCAWE). Torres, E.B. and Subida, R.D. (1994) "Health Assessment for Metro Manila." Paper written for URBAIR Metro Manila-report. U.S. Environmental Protection Agency (USEPA). (1986). "Fuel oil combustion." In: Compilation of air pollutant emission factors, 4th ed., Suppl. A. Research Triangle Park, NC: EPA. West Japan Engineering Consultants, Inc. (1992). "Manila Thermal Power Plant Rehabilitation. Study on Environmental Pollution Control." National Power Corporation (NAPOCOR), Manila. World Health Organization (WHO) /United Nations Environment Programme (UNEP). (1992). Urban Air Pollution in Megacities in the World. Oxford, UK:Blackwell Publishers. Williams, D.J., J.W. Milne, D.B. Roberts, and M.C. Kimberlee. (1989). "Particulate Emissions from 'In-Use' Motor Vehicles -1. Spark Ignition Vehicles." Atmospheric Environment. 23: 2639-2645. Williams, D.J., J.W. Milne, D.B. Roberts, and M.C. Kimberlee. (1989). "Particulate Emissions from 'In-Use' Motor Vehicles -II. Diesel Vehicles." Atmospheric Environment. 23, 2647- 2661. APPENDIX 1: AIR QUALITY STATUS, METRO MANILA DESCRIPTIONOF PAST AND PRESENTMEASUREMENT PROGRAMS Stations and parameters Air qualitymonitoring in Metro Manila was started in 1971by the then NationalWater and Air PollutionControl Commission(NWAPCC). The NWAPCCestablished six monitoringstations, primarilytraffic oriented,and used mechanizedsamplers for measuringoxidant (ozone), sulfur dioxide,nitrogen dioxide, carbon monoxide, suspended particulates and lead. Monitoringwas conductedintermittently on a weeklybasis, except at one stationwhere samplingwas done daily for an eight-hourperiod using a mobileand a stationarylaboratory. In 1974,the mechanizedequipment was replacedby automaticinstruments, also at six traffic- oriented, stationarysites. Then, hourly concentrationsof carbon monoxide,total hydrocarbons, nitric oxide, nitrogendioxide, total oxidants,sulfur dioxideand suspendedparticulates were continuouslyrecorded, along with such meteorologicalfactors as temperature,humidity and wind speed and direction. In addition, a mechanizedhigh-volume sampler was providedat four stationsin order to determinethe concentrationof suspendedparticulates beyond the measuring range of the automaticdust analyzer. The mechanizedhigh-volume samplers had been operated 24 hours daily but their use was discontinueddue to maintenanceproblems. By 1978,there was a need for spare electricalparts for the automaticinstruments (NPCC, 1978). In 1981 the equipmentmanufacturer in Japan discontinuedmanufacturing the types of monitorsused in Metro Manila,thus limitingthe availabilityof spare parts. The lack of spare parts and high maintenancecosts in the ensuingyears forcedthe NationalPollution Control Commission(NPCC) to stop monitoringNO 2, hydrocarbons,and oxidants,leaving only TSP, CO, and SO2 as the parametersmeasured. The remainingequipment began to break down in 1983,and in 1984 the number of stationswas reducedto three. All monitoringoperations were shut down by the end of 1985. A comparativestudy made on the automaticinstrument and the high-volumesampler for particulatematter showed a significantrelationship between the 24-houraverage concentrations from the high-volumesampler and the automaticinstruments with the high volumesampler givingabout 2.6 times higher concentrations(Pecache, G.A., 1979). For other pollutants 107 108 Appendix I measured during that period, Dr. Lodge, in reviewing data for the Montgomery report, noted serious problems with the methodology and calibrations for all the pollutants measured with these systems. DENR-NCR long term monitoring network The DENR-NCR monitoring resumed again in 1986 using high volume samplers for TSP and manually operated bubblers for SO2. The sites are variously exposed to road and industrial emissions. The location of the stations is shown in Figure 1, and a complete listing and description of the stations are presented in Table 1 and Table 2. Table 1: Description and classification of the DENR-NCR air quality monitoring network in Manila Stations Siteof SO and TSP Classificationof Approximate Sampler monitoringstation monitoringsite sampling heightabove ground meters Ermita TaftAve, corner Pedro Gil R,C,I,T 3.0 TSP/high-volumeandmidget St.Ermita, MM impinger/S02 LasPinas CasimiroVillage, Bo. 1,R 3.0 TSP/high-volume Bamplona,LasPinas, MM Paranaque ElordeSports CC., Sucat 1,C 3.5 TSP/high-volumeandmidget Rd.Paranaque impinger/SO2 Pasig ValleVerde Phase 1 R,1 3.5 TSP/high-volumeandmidget Bo.Ugang, Pasig MM impinger/SO2 QuezonCity PAGASACompound i 3.0 TSP/high-volumeandmidget ScienceGarden, impinger/S02 BIRRd, Quezon City Navotas SampaquitaSt.,Merville R 3.0 TSP/high-volume Subdiv.Navotas, MM Valenzuela ValenzuelaMun. Hall, 1,C 3.5 TSP/high-volumeandmidget Valenzuela,MM impinger/SO, Makati: a.Poblacion PalmaSt., Poblacion R,1 3.0 Midgetimpinger/80 2 Makati,MM b.Bel Air Bel-AirPark Ph. 111, Makati, R,1 3.0 TSP/high-volumeandmidget MM impinger/S02 c.Viejo GumamelaSt.,Guadalupe R, 1 3.0 TSP/high-volumeandmidget Viejo,Makati, MM impinger/SO, Note:R, residential; C,commercial; 1,institutional; T,traffic-oriented; MM,Metro Manila. URBAIR-Manila 109 Figure 1: National CapitalRegion (NCR) of the Philippines: * Cities and municipalities; * DENR-NCR and LLDA jurisdictional areas; * Monitoringstations; and * Dispersionmodeling areas. N 0 5 km ao Jurisdiction areas:uezon City, Clear: LLDA( ar , t Manila \ ; - ManilaBayR-NCR 0 tT') ~~aguig Jurisdiction areas: ;}J /// Clear: LLDA 1:- 1z Shaded: DENR-NCR -:LfHns:-( ||i Laguna --. - y 111, Lake Monitoring stations: 1: Ermita 2: LasPinas 3: Paranaque MuntinJ 4: Pasig lp 5: QuezonCity modemng 6: CaloocanCity area 7: Valenzuela 8: Makati 110 Appendix1 Table2: FurtherDENR-NCR site description Sitedescription Nearestroad Distance(m) Annualaverage dailytraffic Ermita Thesite has high volume and S02 sampler, located at 5 40,000-50,000 TaftAve., corner Pedro Gil, Ermita, Manila. Itis a residential,commercial, industrial and traffic orientedarea. It is on a main road. Other sources nearby:Manila Thermal Plant (2 km north of station). ParanaqueThe site has high volume and SO, sampler. Itis located 10 30,000-40,000 atElorde Sports Complex Compound, Sucat Road, Paranaque,MMand it isan industrial and commercialarea. It isalong a mainroad. Other sourcesnearby: Sucat Power Plant (5 km west of station). QuezonCity Thesite has high volume and SO, sampler. Itis located 30 10,000-15,000 atPAGASA Compound atScience government site (withgovernment office around it)and classified as anindustrial area. It is along a mainroad. No other nearbysources. ValenzuelaThe site has high volume and SO, sampler. Itis located 50 40,000-50,000 atthe Valenzuela Municipal Hall, Valenzuela, MM. Itis classified asan industrial and commercial area. Nearbysources: rubber company (1km southeast), manysmall lumber yards (1 km radius around station). Makati Thesite has high volume and SO, sampler. It is located 5 <5,000 (Viejo) at GumamelaSt.,Guadalupe, Viejo, Makati, MM. It isa residential and industrial area. It isabout 10 metersfrom the main road. Other nearby sources: RockwellPower plant (2 km south). Pasig Thesite has high volume and S0 sampler.It is located 5 10,000-15,000 atVelle Verde Phase I,Bo, Ugong, Pasig, MM and isin a residentialand industrial area. About 5 metersfrom a main road. Other nearby sources: FRcement, bagging operations (1km east); Resins, Inc.(500 meters east); Union Ajinomoto (1km east);Union Glass Co. (1 km east); Coca Cola Plant,CO, (1.5 km east); Phoenix Steel Co. (5 km east). LasPinas Thesite has high volume and SO, sampler. Itis located 10 30,000-40,000 atCasimiro Village, Barrio Pamplona, Las Pinas. It isan industrial and residential area. It is about 20 metersfrom the main road. No other nearby sources. Source:Lesaca, 1994. URBAIR-Manila 111 Both Dr. Mage, a WHO Adviser, and Dr. Lodge in the Montgomery Engineers study, pointed out the problems with the equipment and the operation of the monitoring system. Dr. Mage explained that the orifices for calibrating the high volume samplers had not been recalibrated for over ten years, and that only two of the high volume samplers operating were flow controlled, i.e. equipped with controllers to maintain a constant flow rate even as the filters load up and become more resistant to airflow. The report (Environmental Management Bureau, 1990) stated that "...manual samplers had to be utilized for sulfur oxides and particulates through improvised monitors using materials from the discarded equipment. The lack of uniformity in the frequency and methods of collection and analysis have limited the amount of data which could be used to completely define the metropolis' air pollution problems". A tour of several of the existing monitoring stations by project staff confirmed the above. The results of the visits to the monitoring sites indicated poor equipment conditions, and also, except for the Ermita site, inappropriate location to characterize the more severe air pollution conditions resulting from motor vehicle operation in Metro Manila. ADB/EMB 1991/92monitoring network During the Vehicle Emission Control Planning Project in Metro Manila funded by the Asian Development Bank (ADB) a more detailed air quality monitoring study was made in the period 1991-92. This again was concerned mainly with potential pollution problems associated with vehicle emissions. This project set up five monitoring stations on major streets in Metro Manila. All five stations measured particulate matter and three included lead analyses. One station-in Ermita monitored carbon monoxide and nitrogen dioxide continuously. For a short period, total oxidants, sulfur dioxide and hydrocarbons were measured. Another station monitored carbon monoxide and nitrogen oxides continuously for a two-month period. This monitoring equipment remains at the Ermita station but is not used except for the carbon monoxide equipment. This monitoring program used equipment that would be regarded as "state of the art" for air quality monitoring programs undertaken in the UK. The Table 3: Air quality monitoring equipment types used are summarized in Table 3. equipment usedfor the 1991-92 The ADB 1991/92 project team in conjunction with survey the Environmental Management Bureau and the Pollutant Equipmenttype DENR-NCR staff selected five monitoring sites. Nitrogendioxide Chemiluminescentdetector Selection criteria included location on major Carbonmonoxide Non-dispersive infrared thoroughfares, a geographic distribution and Hydrocarbons Flameionization detector availabilityof public buildings for actual monitor Particulates(PM,.) BetaRadiation gauge placement. The following describes these stations and Highvolume sampler their locations: Ermita. The project team refurbished the existing DENR-NCR monitoring station on Taft Avenue corner Pedro Gil Street and measured nitrogen oxides and carbon monoxide continuously from August 1991 through December 1991. These monitors were moved to the DENR-NCR office location on Quezon Avenue for the months of January and February 1992, and were then retumed to Ermita. The Ermita station measured TSP matter and PM1 Oon a once every-three-day basis from August, 1991, until the end of the project sampling period in early March 1992. There 112 Appendix1 was also measured sulfur dioxide using wet chemistry methods. This station was equipped with a meteorological station measuring wind speed, direction, and air temperature throughout the project period. The Ermita station represented a busy intersection with slow traffic of all types of vehicles. Asian Development Bank (EDSA). This station started operation in early August 1991, and continued operation through the remaining project monitoring period. It monitored PM1o and TSP, and also the meteorological parameters of wind speed, wind direction, and temperature. This station represented an area of high bus and truck traffic near a busy intersection on a major beltway thoroughfare of Metro Manila. The actual sampler was located near the tennis court on Asian Development Bank property along EDSA. In addition, an Air Quality Index Display Board has been installed on the center island of EDSA to characterize suspended particulate air quality levels as "good," "fair," or "unhealthy.". The PM1 o sensor, a Horiba Model APDA-350E beta instrument located on the ADB property, was designed to send air quality indicator data to the display board receiver by remote control every half hour for display to the public. Quezon Avenue. At this site PM1 Owas monitored; the monitor was located on a second floor ledge of a government office almost directly across the street from the DENR-NCR office on Quezon Avenue. This site started operation in October 1991, and continued throughout the project sampling period. Quezon Avenue is an extremely busy street, heavily traversed by Jeepneys. Traffic moves relatively slow in the area of the monitor, and traffic frequently gets tied up at traffic signals. Because the monitor was located on a ledge, there was some concern that it was too sheltered from the street. Manila Central University Hospital. At this site, located on EDSA near the Monumento Intersection, both PM1 Oand TSP were monitored. The monitor location represented an area of heavy bus and jeepney traffic, and it also is an area of many pedestrians. Numerous pedestrians wait for buses or jeepneys in the area, go to or from the Light Rail Transit station, and use the major shopping areas there. San Lorenzo Village. Start-up of this station was delayed due to difficulty in siting: this station therefore operated only for two months of the project sampling period. At this station PMIOwas monitored on a once-every-three-day basis. Monumento/MCU. There was also a delay in siting at this station. This station operated only the last month of the project period, with equipment measuring PMIo and TSP on a once-every-three- day basis with lead analyses of alternate day TSP filters. The 1991/92 project sampling station locations and parameters measured are shown in Figure 2. ADB/EMB 1991/1992monitoring network This network is described in Figure 2. PM1 Oand TSP were measured on an every third day basis, providing TSP filters for lead analyses on a once every 6 days basis. Nitrogen oxides, carbon URBAIR-Manila 113 monoxide and SO2 were Figure2: Projectsampling station locations andparameters measured by measured months at each location (1991-92) continuously. Total oxidants Aug Sep Oct Nov Des Jan Feb Mar Apr were sampled Emita continuously at TSP one of the NO2 stations for co only three days HC near the end of Lead the overall SO2 project period. Oxidants ADB/EDSA PMO- Data TSP presented in Lead this report DENR-NCR As several PMNo reportshave co pointed out poor equipment San LorenzoVillage conditions, PMo0 only recent data Monumento/MCU (1988-92) are PMont- presented in TSP this report to Lead characterize the over all air pollution situation in Manila. Total suspended particles (TSP) and PMlo Annual arithmetic averages of total suspended particles in Metro Manila from the DENR-NCR network are shown in Figure 3 (1992) and in Figure 4 (1990-92). The maximum 24-hour concentrations for the same periods are given in Figure 5 (1992) and in Figure 6 (1990-92). 114 Appendix1 Figure 3: Mean annual TSP concentrations, 1992 (igIm 3 ) Air QualityGuideline: 60 -90 uPg/m3 as annualaverage Stations: 1: Ermita(street, 5 m fromcurb) 2: LasPinas (street, 10 m fromcurb) 3: Paranaque(street, 10 m fromcurb) 4: Pasig(industrial) 5: QuezonCity (area) 6: CaloocanCity 7: Valenzuela(industrial) 8: Makati(area) URBAIR-Manila 115 3 Figure 4: Mean annual TSP concentrationsfor the period 1990-92 (pg/rm) Air QualityGuideline: 3 60 - 90 pg/m as annualaverage Stations: 1: Ermita(street, 5 m fromcurb) 2: LasPinas (street, 10 m from curb) 3: Paranaque(street, 10 m from curb) 4: Pasig(industrial) 5: QuezonCity (area) 6: CaloocanCity 7: Valenzuela(industrial) 8: Makati(area) 116 Appendix 1 Figure 5: Maximum 24-hour TSP concentrationsfor the year 1992 (pg/m3) Air QualityGuideline: 150- 230pg/m 3 - as max.24 h. average Stations: 1: Ermita(street, 5 m fromcurb) 2: Las Pinas(street, 10 m from curb) 3: Paranaque(street, 10 m fromcurb) 4: Pasig(industrial) 5: QuezonCity (area) 6: CaloocanCity 7: Valenzuela(industrial) 8: Makati(area) URBAIR-Manila 117 Figure 6: Maximum 24-hour TSP concentrationsduring 1990-92 (pg/m3) Air QualityGuideline: 150- 230pg/mr 3 as max.24 h. average Stations: 1: Ermita(street, 5 m fromcurb) 2: Las Pinas(street, 10 m fromcurb) 3: Paranaque(street, 10 m from curb) 4: Pasig(industrial) 5: QuezonCity (area) 6: CaloocanCity 7: Valenzuela(industrial) 8: Makati(area) 118 Appendix 1 In the DENR-NCR network, only the Ermita station represents a high traffic area. Ermita represents an area of a busy intersection with slow traffic of all types of vehicles. The new Philippine air quality standards for TSP were exceeded at all stations except for the 24-hour maximum value at Navotas in 1992. At the Valenzuela station the annual average values for the years 1989, 1990, 1991 and 1992 were almost 3 times the standard, and the maximum 24-hour value in 1992 was twice the standard. Figure 7 shows the observed 24-hour TSP concentrations at selected stations for the years 1991 and 1992. Even though very high concentrations are measured throughout the year, there is a tendency for a higher frequency of lower concentrations during the rainy season. Figure 8 shows the air quality TSP trend for the period 1988-1992 for the stations Ermita, Las Pinas, Paranaque, Pasig, Quezon City and Valenzuela. Except for the Paranaque station, which shows slightly increased annual average values, the TSP levels seem fairly constant at all stations. The levels are well above the new Philippine national ambient air quality guideline. At the Pasig station the maximum 24-hour TSP concentrations have decreased during the last years, but the annual average value has changed very little. TSP data from the 1991/1992 ADB/EMB project are shown in Table 4. The Ermita station is the same as in the DENR-NCR network, but new measuring equipment was put in. The measurements in the period August 1991-February 1992 showed an annual geometric average of 260 Pg/lm3, a maximum 24-hour value of 549 Pg/m3 and a minimum 24-hour value of 79 pg/im3. At the ADB stations which represents an area of high bus and truck traffic near a busy intersection on a major highway through Metro Manila, the TSP concentrations were well above the Ermita stations level. The geometric mean value of 480 Pg/M3 (more than 5 times the standard) and the maximum 24-hour value was 843 Pg/M3 (3-4 times the standard). In the ADB/EMB project also PMIo was measured. Results from 5 stations are shown in Table 5. The results show that the Philippine national ambient air quality quidelines of 60 .tg/m3 as an annual geometric mean value and 150 pg/mi3 as a 98 percentile 24-hour value were clearly exceeded at all five stations. All of them represent areas with high traffic intensity. Data from the Ermita, ADB and Monumento stations show the TSP levels are about twice the PMIo levels. This means that about 50% of the particle mass have a diameter of 10 PM. Table 4: TSP concentrations from the 1991/1992 ADB/EMB project (pg/rm3 ), 24-hour sampling Station MeasurementArithmetric Geometric Maximum24-hr Minimum24-hr Numberof period meanvalue meanvalue value value observations Ermita Aug91-Feb 92 256 260 549 79 49 ADB Aug91-Feb 92 497 480 843 213 47 MonumentoFeb 2 400 413 489 244 5 Table 5: PM,oconcentrationsfrom the 1991/92 ADB/EMB project (pg/ 3 ), 24-hour sampling Station MeasurementArithmetric Geometric Maximum Minimum Numberof period meanvalue mean value 24-hrvalue 24-hrvalue observations Ermita Aug91- Feb 92 144 143 258 54 62 ADB Aug91- Feb 92 219 212 321 139 47 DENR-NCR Oct91-Feb 92 227 221 321 142 26 SanLorenzo Village Jan92-Feb 92 179 185 206 135 10 Monumento Feb92 198 201 241 150 5 URBAIR-Manila 119 Figure 7: 24-hour TSP concentrations given by month and day for Ermita (1991), Quezon City (1991), Navotas (1991) and Pasig (1992) (,ug/m3) MsO EmslaI991 I . 201 201 tM4 ozonciyi 401 20D 301 Na Cts 19S1 01 301 20D 4. 350tPoSig 1991 101 201 20 H - -01, 101 g<_w_~ego o-~^°°e 120 Appendix 1 Figure 8: Annual average values and maximum 24-hour TSP concentrationsfor the years 1988-92 at 6 stations (pg/m3) I E-cm 4001 ,.. 45 !- - ..- Mc .e. I 1ie t 50 300t _350f | i tiXt19 19O 1l99 1 r Praitq_ . ._ t200t 1' i * 201 ' Itooo * , *_ I!3.0-,~ --. 5C; I-s low 1990 A1992 2 0...... 500 too _ ------l _t _ _ Y | 5CCiTi tOilCet tii2 2,50i100 i I ItS INS5 ffO 1lMt 199 i ______URBAIR-Manila 121 Figure 8 continued: Annual average valuesand maximum 24-hour TSP concentrationsfor the years 1988-92 at 6 stations (pg/rm3) So Erm Mean 4500 Maxnum gm e-aftU 400 40 Omm_m 350 440 E 300 I3 T 250 I 5200 0 100 19 1 1988 1989 1990 1991 1992 Soo Las Pmnas 5 4500 400~~~~~~~~~~~~~~~~~~~~~~~0 350 2uo I 5300- _. ---. 200 I g~250 190 ISO______1OD Ism 130 130 131 1913 50 1968 1989 1990 1991 1992 500 - Pamanaqu. 450 400 3500 200Pu. 1E | 1S1ME ISO~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 0 1986 1989 1990 1991 199 122 Appendix 1 Lead In the 1991/1992 Table 6&Lead concentrationsfromthe 1991/1992ADB/EMB project ADB/EMB project, (Og/m3), 24-hoursampling FSPfilters were also Station MeasurementArithmetric Maximum Minimum Numberof analyzed for lead. penod meanvalue 24-hrvalue 24-hrvalue observations The results are given Emita Aug91- Feb 92 1.07 2.18 0.10 36 in Table 6. The mean ADB Aug91- Feb 92 2.30 5.45 0.44 34 values ranged from 1 MonumentoFeb 92 1.00 1.44 0.65 4 pg/m3 at the Monumento station to 2.3 Jig/m3 at the ADB station. The Philippine national ambient air quality 3 3 guidelines are 1.5 pg/m as a 3-month mean value and I Jg/M as a year mean value. The guidelines may be exceeded at all stations, and the ambient concentrations seem to be well above the WHO guidelines for 1 year which is 0.5-1 ,g/m 3. There are also some lead data available for major thoroughfares in metropolitan Manila for the year 1987 (or maybe 1988). Annual arithmetic mean value ranged from 0.26 at the Pasig station to 4.35 Jig/M3 at the Valenzuela station. At the Ermita station the annual lead concentration was 0.63 Jig/m3 which is well below the 1991/92 value of 1.07 Pg/m 3. Sulfur dioxide (SO2 ) Annual arithmetric averages of 202 in Metro Manila from the DENR-NCR network are shown in Figure 9 (1992) and in Figure 10 (1990-92). The maximum 24-hour concentrations for the same periods are given in Figure 11 (1992) and in Figure 12 ( 1990-92). In 1991, the highest values were measured at the Ermita stations with an annual average of 0.013 ppm (about 35 Jig/M3) and 24-hour maximum value of 0.091 ppm (about 240 pg/M3 ). The maximum 24-hour value at the Ermita station in 1992 was above the Philippine national ambient air quality guideline of 180 pg/M3 and well above the WHO standard of 125 Jig/M3 . The annual mean value was below the Philippine and WHO standards. Figure 13 shows observed 24-hour S02 concentrations from selected stations for the years 1991 and 1992. Most of the 24-hour S02concentrations at the Quezon City and Makati stations were very low (below 0.02 ppm). During the months of June, July and August 1992, much higher concentrations were observed at the Ermita station suggesting the influence of a strong source not far away, may be the power station. Figure 14 shows the S02 air quality trend at the stations Ermita, Paranaque, Pasig and Quezon City in the period 1988-1992. The annual average values are well below the new Philippine ambient air quality guideline of 0.003 ppm (80pg/lm3), and the measurements show slightly decreased values the last years. The 24-hour guideline of 0.08 ppm (150 pg/m3) was exceeded at the Ermita and Pasig stations during the 1988-1992 period, but the 1992 maximum value at the Pasig station was well below the guideline value. URBAIR-Manila 123 Figure 9: Mean annual SO2 concentrations, 1992 (ppm) Air QualityGuideline: Phil. Ntl. WHO 0.03 ppm 0.02ppm as annualaverage 0,006 Stations: 1: Ermita(street, 5 m from curb) 2: LasPinas (street, 10 m fromcurb) 3: Paranaque(street, 10 m fromcurb) 4: Pasig(industrial) 5: QuezonCity (area) 6: CaloocanCity 7: Valenzuela(industrial) 8: Makati(area) 124 Appendix1 Figure 10: Mean annual SO2 concentration for the three-year period 1990-92 (ppm) Air Quality-Guideline: Phil. Ntl. WHO > 0.03 ppm 0.02ppm as annualaverage Stations: 1: Ermita(street, 5 m fromcurb) 2: LasPinas (street, 10 m fromcurb) 3: Paranaque(street, 10 m from curb) 4: Pasig(industrial) 5: QuezonCity (area) 6: CaloocanCity 7: Valenzuela(industrial) 8: Makati(area) 125 URBAIR-Manila (ppm) Figure 11: Maximum 24-hour SO2 concentrationsfor the year 1992 Air Quality Guideline: Phil.Ntl. WHO __ 0.007ppm 0.005ppm as max.24 h. average 2: LasPinas (street, 10 m from curb) /l, 3: Paranaque(street, 10 m from curb) . 4: Pasig(industrial)V \ 5: QuezonCity (area) 6: CaloocanCity K 7: Valenzuela(industrial)\J 8: Makati(area)v 126 Appendix 1 Figure 12: Maximum 24-hour SO2 concentrations during the years 1990-92 (ppm) AirQuality Guideline: Phil. Ntl. WHO 0.007ppm 0.005ppm as max.24 h. average Stations: 1: Ermita(street, 5 m fromcurb) 2: Las Pinas(street, 10 m from curb) 3: Paranaque(street, 10 m from curb) 4: Pasig(industrial) 5: QuezonCity (area) 6: CaloocanCity 7: Valenzuela(industrial) 8: Makati(area) URBAIR-Manila 127 Figure 13: 24-hour concentrations given by month and day for Ermita (1992), Quezon City (1992), and Makati Poblacion (1991) (ppm) 0.10 0.140 vEfnita 1992 0.120 1UlS 0.100 E ooao-4 AO Standard,Phill. '-R0.070 ~ 0.061 0.040+ __-- - S°E °° Ow 0.160 - 0.140 Quezon City 1991 0.120 0.100 - o.00 - 0.040 2 01020 0.100 0.040 0.020 1 0.020 Ir0 || ,' !riI 11ll1 ILtl l^l v!s^! I#IIlilIIi| 128 Appendix 1 Figure 14: Annual average values and maximum 24-hour SO2 concentrations for the years 1988-92 at 4 stations (ppm) 0.12 Ermna Mean 0.10 ..... Maximum i0.06. 0.08 '-. - ' .- 0.04 0.02 0.00 1988 1989 1990 1991 1992 0.12 Paranaque 0.10 0.06 - -- 0.02 0.00 1988 1989 1990 1991 1992 0.08 '0.06 0.12 Qszon ilg y 0.10 0.00 0.04 ,,,,%s . 0.02 1988 1989 1990 1991 1992 URBAIR-Manila 129 Figure 14 continued:Annual averagevalues and maximum 24-hour SO2 concentrationsfor the years 1988-92 at 4 stations (ppm) 0.12- Ermita Mean 0.10 . Maximum 0.08- 0.04- 0.02 w 0.00 - 1988 I'~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~1989 1990 1991 1992 0.12 Pmranaque 0.10 0.08 :-,,r-~0.06 0.04 0.02 0.00 1988 1989 1990 1991 1992 0.12 PaQIg 0.10 0.06 0.06 0.04 0.02 0.00 198. 1980 1990 1991 1992 0.12 Oue.on City 0.10 0.08. 0.06 0.04 0.00 1088 1989 1990 1001 1992 130 Appendix1 Carbon monoxide (CO) Table 7: Measuredaverage daily maximumone-hour and eight-hour CO was monitored carbonmonoxide concentrations (August 1991-February1992) in Manila at four sites Statonand Aug91 Sep91 Oct91 Nov91 Dec91 Jan92 Feb92 from 1977 to 1983. averagingtime Annual mean Ermita concentrations were 1-hr(ppm) 20.6 13.7 9.8 6.9 7.3 between 1.5 mg/mr3 8-hr(ppm) 11.3 9.0 6.7 5.1 4.0 and 10mg/in. The 1-hr(ppm) 14.0 14.1 highest concentrations 8-h4(ppm) 8.5 7.7 were measured at the Ermita in 1983. The only CO measurements since 1983 were during the 1991/92 ADB/EMB project. CO was then measured for five months at Ermita and two months at Quezon Avenue (DENR-NCR). The results of this monitoring are shown in Table 7. At Ermita the maximum one hour CO value was 20.6 ppm, well below the national standard of 30 ppm. The maximum 8-hour value was 11.3 ppm which is above the standard of 9 ppm. At the Quezon Avenue (DENR-NCR) CO concentrations were lower than at Ermita. As shown in Figure 15 mean CO concentrations at Ermita in November 1991 Figure 15: CO diurnal concentrationvariations, Ermita ranged from about 0.5 ppm station, November 1991 (ppm) during the night hours to about CO ppm 3 ppm during rush hour traffic in the morning and afternoon. The monthly mean value in 3 - November 1991 seems to be about 2-2.5 ppm. 2 Oxides of nitrogen 1 Oxides of nitrogen include 0 both nitric oxide (NO) and l l l l nitrogen dioxide (NO2 ). Until 01 06 12 18 24 the 1991/92 ADB/EMB project there were no data available on N02 air pollution levels in Manila. NO, NOx and NO2 were then measured together with CO at the Ermita and Quezon Avenue (DENR-NCR) stations. Table 8 shows maximum one hour and monthly average NO2 data. The highest values were measured at Ermita in October 1991 with maximum one hour value of 0.240 ppb (about 450 ,g/m 3) and a monthly value of 0.026 ppb (about 50 pg/m3 ) The Philippine guideline value is 0.08 ppm/150 pg/m for 24 hours. The data does not show if this guideline is exceeded or not. URBAIR-Manila 131 The daily NO,, NO and N02 concentration Table 8: Maximum one-hour and monthly average NO2 data variation is shown in (August 1991-January 1992) Figure 16. As for CO, the Station Aug91 Sep91 Oct91 Nov91 Dec91 Jan92 highest values were Ermita measured during rush 1-hr(ppm) 0.044 0.039 0.240 0.110 0.160 hours in the morning and Monthlyaverage (ppm) 0.006 0.007 0.926 0.009 0.050 in the afternoon. The 1DENR-NCR-hr (ppm) 0.240 lowest values are Monthlyaverage (ppm) 0.016 measured during night hours. N02 data are very limitedin Manila. Figure 16: NON, NO and NO2 diurnal concentration variation, Ermiita Peak concentrations Station (November 1991) (ppb) may be well above nationaland WHO NOX,NO, NO 2 standards,especially ppb in heavilytrafficked 200 areas. There is a need for more N02 150 monitoring. 100 -N Ozone so NO2 03 was measured J only for three days I at Ermita in April 01 06 12 18 24 1992 during the Timeof day 1991/92 ADB/EMB project. The measured levels were below 0.01 ppm. The very low values may be caused by high levels of oxides of nitrogen from the traffic in the area. Chemical reactions between NO and 03 reduce 03 and increase N02. More 03 monitoringis needed,especially in areas well away from heavily traffickedareas. APPENDIX 2: AIR QUALITY GUIDELINES AIR QUALrrY GUIDELINES National Ambient Air Quality Standards In 1992 the Department of Environment and Natural Resources (DENR) has revised and amended the air quality standards of 1978. The new National ambient air quality guidelines (NAAQG) and standards are given in Table 1. Table1: Nationalambient air qualit guidelinesfor criteriapollutants Shortterm' Longtermb Pollutant pg/m3 ppm averagingtime pg/m' ppm averagingtime Suspendedparticulate matter -TSP' 230' 24hrs 90 1 yr - PM10 150, 24hrs 60 1ye Suffurdioxide 180 0.07 24hrs 80 0.03 1yr Nftrogendioxide 150 0.08 24hrs - - Photochemicaloxidants 140 0.07 1hr - asozone 60 0.03 8 hrs Carbonmonoxide 35mg/m3 30 1hr 3 10mg/m 9 8 hrs - - Leadd 1.5 - 3 monthse 1.0 1yr. Notes: a. Maximumlimits represented byninety eight percentile (98%) values not to be exceeded more than once a year. b. Arithmeticmean. c. AnnualGeometric Mean. d. Evaluationofthis guideline iscarried out for 24-hour averaging time and averaged over three moving calendar months. The monitoredaverage value for any three months shall not exceed the guideline value. e. SO,and Suspended Particulates aresampled once every six days when using the manual methods. Aminimum number of twelvesampling days per quarter orforty eight sampling days each year is required forthese methods. Daily sampling may bedone in the future once continuous analyzers are procured and become available. f. Limitsfor TSP mass median diameter less than 25-50 pm. Source:DENR (1992). 133 134 Appendix 2 The national Ambient Air Quality Guidelines in Table 1 are established "for the purpose of protecting the public health and welfare and reducing damage to property, as well as providing an air quality management control strategy for emission limitation from mobile and stationary sources, location of commercial, industrial and residential facilities, and to assist in the promotion and use of an improved transportation system". The applicable methods for sampling and measurement of the pollutants listed in Table 1 are as follows: * Sulfur dioxide-Gas Bubbler and Pararosaniline Method (West and Gaeke Method), or Flame Photometric Detector; * Nitrogen dioxide-Gas Bubbler Griess-Saltzman, or Chemiluminescence Method; * Ozone-Neutral Buffer Potassium Iodide (NBKI), or Chemiluminescence Method; * Total suspended particulates (PMio)-High volume with 10 micron particle-size inlet (Gravimetric); * Carbon monoxide-Non-dispersive Infra-red Spectrophotometry (NDIR); and * Lead-High Volume and Atomic Absorption Spectrophotometry (NDIR). Other equivalent methods approved by the DENR may be adopted. WHO Air Quality Guidelines and Standards WVHOAir Quality Guidelines and Standards are listed in Table 2. The Philippine guidelines for TSP are within the 1979 WHO guideline range. The national PMIo guidelines for 24 hours is well above the WHO guidelines. The guidelines for S02 are also higher than the WHO guidelines. The N02 guideline follows the 1987 WHO guideline. The Philippine guidelines for 03 are below the WHO values. CO guidelines follow WHO guidelines, while the lead guideline is above the WHO guideline. URBAIR-Manila 135 Table 2: WHO air quality guidelines/standards(WHO 1977a, 1977b, 1978,1979,1987) Parameter 10 15 30 1 8 24 1 year Yearof standards minutesminutes minutes hour hours hours 3 SO2 pg/m 500 350 125' 50' 1987 S0 . pg3/ 100-150 40-60 1979 BSb pg/m3 125' 50' 1987 BSb pg/m3 100-150 40-60 1079 TSP pg/M3 120' 1987 TSP pg/M3 150-230 60-90 1979 3 TP(PM...... O) ~~~~. p./rn .....0...... I...... 70Q ...... 1987 Lead p./r3 0.5-1 1987,1977a ~~~~~~3...... CO mg/r3 100 60 30 10 1987 ~ ~ ~~~~~v ...... I...... I...... I...... 3 NO2 pg/M 400 150 1987 NO...... 9/r ...... 190,320c ...... 1977b...... Ol pg/mr 150-200100-120 1987 03 pg/m3 100-200 1978 Notes: a. Guidelinevalues for combined exposure tosulfur dioxide and suspended particulate matter (they may not apply to situations whereonly one of the components ispresent). b. Applicationofthe black smoke value is recommended onlyin areas where coal smoke from domestic fires is the dominant componentofthe particulates. It does not necessarily apply where diesel smoke isan important contributor. c. Notto be exceeded more than once per month. Suspendedparticulate matter measurement methods: BS:Black smoke as concentration ofa standard smoke with an equivalent reflectance reduction tothat of the atmosphericparticles ascollected ona filter paper. TSP: Totalsuspended particulate matter; the mass of collected particulate matter by gravimetric analysis divided by total volumesampled. PM;M:Particulate matter less than 10 pm in aerodynamic diameter, the mass of particulate matter collected bya samplerhaving aninlet with 50 percent penetration at10 pm aerodynamic diameter determined gravimetrically divided by the total volume sampled. TP:Thoracic particles (as PMj). IP: Inhalableparticles (as PM,O). Source:WHO/UNEP (1992). National Air Quality Indices The DENR has also adapted and promulgated national air quality indices. The following describes the levels of air quality for suspended particulates, sulfur dioxide, photochemical oxidants or ozone and carbon monoxide anywhere in the Philippines. 136 Appendix 2 During serious or alert conditions different actions are to be taken. All these actions are Table3: National air qualityindices specified in DENR (1993). A short summary Totalsuspended particulates 24-houraverage of actions is given below: Good 0 -80 pg/m3 Fair 81 - 230pg/M 3 Very unhealthful air quality (alert level): .Poor 231- 350pg/m 3 SeriousorAlert Conditions: * elderly and sick persons should stay VeryUnhealthful (Alert Level) 350pg/m 3 ( ppm) indoors and reduce physical activity, Hazardous(Warning Level) 600pg/M 3 (15 ppm) * pedestrians should avoid heavy traffic ExtremelyHazardous 900 pg/m3 (15ppm) areas, EmergencyLevel ...... * voluntary restrictions on the use of SulfurDioxide 24-houraverage vehicles, vehicles, ~~~~~~~FairGood 81-_1800 -80pg/Mr pg/rn 3 * open burning should be prohibited, and Poor 181- 650pg/m 3 * preparations for reducing industrial Seriousor Alert Conditions: emissions. VeryUnhealthful (Alert Level) 650 pg/M3 (0.25ppm) Hazardous(Warning Level) 1,570pg/m 3 (0.60ppm) Hazardous air quality (warning level): ExtremelyHazardous 2,360pg/m 3 (0.90 ppm) * all previous restrictions and in addition, - ...... -.-----.-----.------.- the general population should, avoid Photochemicaloxidants or 1 hour ozone outdoor activity, Good 0-80pg/m 3 * motor vehicles should avoid areas under Fair 81-160 pg/rm 3 alert, Poor 161-350 pg/m 3 D main thoroughfares should be closed for Seriousor AlertConditions: traffic, and VeryUnhealthful (Alert Level) 350pg/r 3 (350ppm) selective1 curtailment of industrial Hazardous(Waming Level) 780pg/m 3 (0.40ppm) aselctivities. curtailmentofindustr'Extremely Hazardous 1,180pg/m 3 (0.90ppm) activities. EmergencyLeve. Carbonmonoxide 8-hraverage Extremely hazardous air quality (emergency Good o- 5 mg/m3 level): Fair 5.1-10 mgim 3 * all previous restrictions and in addition, Poor 10.1-17 mg/m 3 Seriousor Alert Conditions: * all persons should remain indoors keeping VeryUnhealthful (Alert Level) 17mg/m 3 (15ppm) windows and doors closed, Hazardous(Waming Level) 34mg/m 3 (34ppm) * use of motor vehicles shall be prohibited ExtremelyHazardous 46 mg/m3 (40ppm) except in emergencies, EmergencyLevel * major curtailment of all activities in the Source:DENR (1993). affected area, and * industrial pollution producing operations shall be curtailed as directed by the Department. National ambient air quality standardsfor source specific air pollutantfrom industrial sources/operations DENR has also established national ambient standards for source specific pollutants. The discharge of air pollutants that results in peak airborne concentrations (averaging time 5-60 minutes) in excess of the National Ambient Air Quality Standards shown in Table 4 shall not be permitted for any industrial establishment or operation. Sampling shall be done at an elevation of URBAIR-Manila 137 at least 2 meters abovethe ground level and conductedeither at the propertyline or at a downwinddistance of 1.5 to 20 times the stack height, whicheveris more stringent. Table 4: National ambient air quality standards for source specific air poUlutantsfrom industrial sources/operations Concentration' Averagingtime Averagingmethod of (min) analysis/measurementb Pollutants' pg/m3 ppm Ammonia 200 0.28 30 Nesselarization CarbonDisuHfide 30 0.01 30 TischerMethod Chlorineand Chlorine compounds 100 0.03 5 MethylOrange expressedasCl, Formaldehyde 50 0.04 30 Chromotropicacidmethod orMBTH-Colorimetric method HydrogenChloride 200 0.13 30 VolhardTitration with Iodine solution Hydrogensulfide 100 0.07 30 MethyleneBlue Lead 20 30 MSb Nitrogendioxide 375 0.20 30 Griess-Saltzman 260 0.14 60 Phenol 100 0.03 30 4-Aminoantipyrine Sulfurdioxide 170 0.06 30 Colorimetric-Pararosaline 340 0.13 60 Suspendedparticulate matter TSP 300 - 60 Gravimetric - PM10 200 - 60 Gravimetric Notes: a. Pertinentambient standards forAntimony, Arsenic, Cadmium, Asbestos, Nitric Acid and Sufuric Acid Mists in the 1978 NPCCRules and Regulations maybe considered asguides indetermining compliance. b. Otherequivalent methods approved bythe Department may be used. c. Ninety-eightpercentile (98%) values of 30-min. sampling measured at25'C and one atmosphere pressure. Source:DENR (1993). APPENDIX 3: AIR POLLUTION LAWS AND REGULATIONS FOR THE PHILIPPINES AND METRO MANILA INTRODUCTION The laws and regulations regarding the control of air pollution in the Philippines and in Metro Manila have been reviewed previously in several reports (e.g. WBIDENR, 1993.; ADBJDENR, 1992). The actual texts of the laws and regulations have not been available to the authors of this report, except the DENR AD no. 14 of 1993 (see below). Traffic regulations and enforcement of these are also important for emissions from the road traffic. A summary of these was described in the recent Traffic and Transportation Management Plan (1993-1998). In addition to these the Anti-Smoke Belching-Campaign which started in 1977 should be mentioned as a specific provision to reduce the particle emissions for diesel vehicles. SUMMARYOF EXISTING LAWS AND REGULATIONS Republic Act No. 3931 * 1964: Establishment of the National Water and Air Pollution Control Commission (NWAPCC). The work re. air pollution concentrated first on industrial emissions. Presidential Decree (PD) No. 984: Air quality standards, etc. * 1976: National Pollution Control Commission (NPCC, renaming of NWAPCC); * Air QualityStandards and Rules. * 1978: Implementing Rules and Regulations * 1993: DENR Adm. Order (AO) No. 14: The AD 14 is further described below. * Revised Air Quality Standards of 1992 revising and amending the Air Quality Standards of 1978 139 140 Appendix 3 Presidential Decree No. 1181: Prevention, control and abatement of AP from motor vehicles. * 1977: Provisions * 1980: Implementing rules and regulations * Emission standards currently in effect Presidential Decree No. 1586: Environmental impact assessment system * 1978: Provisions * 1982: Implementing Rules and Regulations * 1992: Revised Rules and Regulations, enforced by EMB Executive Order (EO) No. 927: * 1983: Laguna Lake Development Agency (LLDA) vested responsibility to implement and enforce PD 984 in the Laguna Bay Region Republic Act 6969: * 1990: Control of toxic substances and hazardous and nuclear wastes The most important ones, relative to air pollution control in Manila, are the PD 984/DENR AD 14, the PD I 1 81 (1980 implementing rules and regulations) and the PD 1586 (1992 revision). PD 984/DENR ADMINISTRATIVEORDER No. 14 (1993) Revised air quality standards of 1992 Sections 8 and 12 of this order regard National Ambient Air Quality Guidelines and Air Quality Indices, revising and amending the air quality standards of 1978. This is described in Appendix 2. Emissions from stationary sources are treated in other sections, and outlined in the following: Table1: Particulatematter emission limits (mg/N m 3) * Section4: National NewSource ExistingSource EmissionStandards for 1993 After1978 Before1978 Smokeand Particulate Fuelburning steam generators * 50 300 500 matterforStationary a(a) urban/industrialarea 200 300 500 Matter for Stationary (b)other areas 200 300 - Sources (Table 1). Visible Incinerators 200 300 500 Smokeemission: Not darker Cementplants (kilns, etc.) 150 300 500 than Shade 1 on the Smeltingfurnaces 150 300 500 Ringelmann chart. Otherstationary sources 200 300 500 * 12%CO 2 (volume) Source:DENR (1993). URBAIR-Manila 141 Exceptions for short-term emissions. * Section 5: National Emission Standards for Source Specific Air Pollutants (NESSAP). Emission Table 2: NO, standards standards are given for Sb, As, Cd, NOI Maximumemissions (mglN in) CO, Cu, HF, Pb, Hg, Ni, NO., P205 , NitricAcid Plants 2,000(acid+NO,, caic. as NO2) Zn, with analytical methods specified. Fuelbuming steam generators The NO,, standards are shown in Table -existingsource 1,500as NO2 -newsource 2: coal-fired 1,000as N02 * Section 6: Control of Sulfur oil-fired 500as NO2 Compound Emissions (Table 3). Anyother source -existingsource 1,000as N02 These are the initial specifications for -newsource 500as N02 1993-96. After January 1, PbAny source 10 1996, all operators shall be Source:DENR (1993). required to install appropriate SO2 control Table 3: Sulfur contents in fossilfuel, existing sources equipment to meet the SO2 Max.S (%by weight) emissionlimits specified MetroManila OutsideMetro Manila below, unless the above S- July1993 January1996 July1993 January1996 Fueloil 3.5 3.0 3.8 3.0 in-fuel regulationsare Industrialdiesel 0.7 0.5 0.8 0.5 revised so as to represent an Coal 2.5 1.0 2.5 1.0 alternative approach to Source:DENR (1993). control the S02 emissions (Table 4). If these standards are not met by an operator, Table 4: Emission limits for S02 to be met the following corrective measures may be by January 1, 1996 required: gm/Nm3as SO, -To use fuel with a specified sulfur content. New Existing -To erect a stack sufficient to reduce the Existingsources ground level concentrationof SO, to below - Sulfuricacid plants 2.0 1.5 8Vg/M3 average) above'24-hour the - Fuelbuming steam generators 1.5 1.0/0.7* 80 pg/nd (24-houraverage) abovethe Otherstationary sources 1.0 0.2 backgroundlevel. Note:* ByJan. 1, 1994/byJan 1. 1996. - Alter the process/method of operations. Source:DENR (1993). * Section 9: Prohibited Acts. Fugitive particulates. Prohibition to cause emissions of fugitive particles from any source without taking reasonable precautions, such as: - dust control during demolition/constructions; - dust control on unpaved road; - use of hoods, fans and filters to contain or vent handling of dusty materials; - covering of open loaded trucks. Volatile Organic Compounds. Requirements for handling and disposal, such as: - maximum tank volume: 150,000 liters, unless leakage of gas is prevented; 142 Appendix 3 - maximum emissions from ethylene source: 7 kg per day, unless emissions are burned; and - maximum emissions of organic solvent: 1.5 kg/hour or 7 kg/day from any process. Nuisance. Prohibition to cause emissions creating nuisance. Open burning. Prohibition of any open fire, except, for instance, for: - cooking; - recreational or ceremonial purposes; - fires for prevention of decease/pests; - disposal of hazardous materials, when no alternative is available, if approved by DENR; or - recognized agricultural, forest management practices. General restrictions, among others. - The capacities and capabilities of control devices shall not be exceeded; - No source should be installed if it results, together with the contributions from other sources, in exceeding air quality standards; - All pollution control devices shall be properly and consistently maintained and operated. No facilities shall be operated without the control equipment in proper- operation, except with permission from DENR; - Erection or alteration/resiting of a chimney shall be applied for, giving the following information: D site plan including buildings within 1,000 m from chimney, and height of the highest building within 50 m, D data on emissions (compounds, amounts and concentrations). * Section 10: Source monitoring, Record Keeping, Testing - Any owner/operator may be required to install monitoring equipment, both for emissions and ambient air quality, to keep records and file periodic reports. - For each major source, it shall be the responsibility of the owner/operator to do so, without notice from DENR. - Analysis and tests to be conducted as specified by DENR. - DENR has the right to inspect. * Section 11: Miscellaneous Provisions. For stationary fuel-burning equipment, the following applies: - Person-in-charge shall be able to inspect smoke plume, without leaving the control room. - The following major industries are required to install stack monitoring devices for smoke opacity and S02 emissions: * Fossil-fuelfired PowerPlant (also NO,,), * PetroleumRefinery, * PrimaryCopper Smelter, * Steel/Ferro-alloyplants (opacityonly). - The equipment is to be installed within 24 months after the effective date of the regulation. URBAIR-Manila 143 For miscellaneousequipment, the followingapplies: - Reheatingfurnaces, smoke ovens, bakingovens, coffee heaters,varnish kettles, paint booths and similarequipment shall be so designedthat there is no free flow of objectionablegases into the atmosphere.Preventive devices shall be used. PD 1181: PREVENTION,CONTROL AND ABATEMENTOF AIR POLLUTIONFROM MOTORVEHICLES PD 1181 was passed on 19 August, 1977. The implementingrules and regulationof this PD were publishedin the officialGazette on 6 October, 1980. The National PollutionControl Commissionwas chargedwith the administrationand enforcementof these rules. Enforcement proceduresinclude the right to apprehendvehicles not complyingwith the emissionstandards, after testing the emissions. The emissionstandards to be enforcedafter January 1, 1981 are shown in Table 5. Table 5: Emission standards enforced after Januar 1, 1981 Vehiclecategory Standards Diesel Registeredvehicles Smokeopacity not to exceed 2.5 per m. (light absorption coefficient), atfree acceleration test. Non-registeredvehicles, for registration after Jan. 1, Mustcomply with existing smoke opacity rules of either British, ECE, 1982 Australia,USA or this PD 1881 Standard. islon-req!steredvehicles with recondioned ...... engines...... Samerule as for re..stered vehicles. Gasoline EmissionatIdle: Registeredvehicles Modelyear CO(%) HC(ppm) 1976-81 4.5 1,000 1971-75 5.0 1,000 1965-70 5.5 2,000 1964-older 6.0 2,000 2-stroke 6.0 7,800 ...... Unregisteredvehicles, forregistration after Jan.1, 1982 Emissionlimits, for either US82 (CVS) or ECE test cycle: WeightGW(kg) CO(g_km) HC(gVf) <1,000 25 2.5 1,001-1,500 30 3.0 1,501-3000 35 3.5 Source:PD 1181. These standardsimply that the presentcar fleet in Manila shouldcomply with regulations similarto those of ECE-RI5/01and 74/290/EWG,valid in the EuropeanCommunity between 1975 and 1979. At present, the followingmeasures are also being undertakenunder PD 1181: Public Awareness. An inter-agencycommittee chaired by DENR has been created to enhance public awarenessof vehicularair pollution. NGOs are co-operatingin this task. 144 Appendix 3 * Roadside Inspection and Re-inspection (the Anti Smoke-Belching Campaign). (See below). * Periodic Inspection. "AO No. 40-91-005 issued by the Land Transportation Office (LTO) of DOTC, established the New Motor Vehicle Inspection System (NMVIS), under which all new vehicles shall be inspected, to be registered. Due to limited inspection facilities and equipment, the initial implementation of NMVIS is confined to areas where motor vehicle inspection stations are assigned to certain classes or types of motor vehicle." * Retrofitting. Conversion of vehicle engines to run on less polluting fuels is encouraged (e.g. gasoline-LPG). One taxi fleet has been converted to LPG. * "Greening of MM". Planting of trees. * Traffic control. Truck ban and bus lanes (see below). * Infrastructure approach. Construction of flyovers to enhance traffic flow. * Voluntary approach. Encouragement to adopt flexible working hours, to relieve rush hour traffic. PD 1586: ENVIRONMENTAL IMPACT ASSESSMENTSYSTEM The Environmental Impact Assessment System (EIS) was established by PD 1586 on June 11, 1978. Implementing rules and regulations of the EIS were adopted on December 14, 1981, and amended by the DENR Administrative Order No. 21, series of 1992. DENR is the leading agency of the EIS. The Environment Management Bureau (EMB) of DENR is responsible for processing the EIS documents on Environmentally Critical Projects (ECP). The DENR Regional Offices shall be responsible for projects that fall within the scope of Environmentally Critical Areas (ECA). All planned projects within an ECA need an Environmental Compliance Certificate. This is obtained after a review process by DENR/EMB. This review process includes the preparation, by the proponent, of an Environmental Impact Assessment, unless a 1. phase review establishes that the project has no or insignificant impact on the environment. The 1. phase review is based on a specific project description to be prepared by the proponent. The AO 21/1992 contains an "Annotated Environmental Impact Statement Outline" which is to serve as a general guideline for proponents as to the contents of an EIS. Summary of the outline is as follows. For the parts regarding air pollution the entire contents of the outline is presented. 1.0 Name and address of project proponent 2.0 Type of project 3.0 Overview Summary 4.0 The project setting - - objective, need, alternatives, associated projects 5.0 The proposal - - general layout, pre-construction details, operation/maintenance 6.0 A brief history of past environmental conditions and a description of the existing environmental and resource use - climate, terrain, hydrology, oceanography, - atmosphere (the following items should be described in this section): a. historical trends in air quality of the project area; URBAIR-Manila 145 b. existing air qualityand types and levels of air pollutantsalready existent in the area of concern;and c. existing ambientair qualitystandards and emission standardset by EMB should be appended. - vegetation,fish and wildlife,land and resourceuse, socio-economicaspects. 7.0 Future environmentalconditions without the project (an averageof 5 years projection). 8.0 Predictionand assessmentof impacts -physical/chemicaleffects - water,ground water, - atmosphere: a. Air Characteristics.Changes in air characteristicsresulting from the project may have implicationsfrom the standpointof public health, temperaturemodification, humiditychange. b. Wind. Occurrenceof wind modification(valley, barrier or funnel effect), creation of localized wind disturbancessuch as those resulting from the establishmentof high rise buildingcomplexes and highways. c. Inversion.Development of inversionconditions which result in the entrapmentof air remittancecausing high impingementconcentrations of air pollutants. 9.0 Contingencyplans. 10.0 Environmentalbriefing and monitoring. 11.0 Mitigationmeasures. 12.0 Residual/unavoidableeffects. 13.0 Informationdeficiencies. 14.0 Appendices. 16.0 Consultationand commentsincluding public recommendations. 17.0 Other documentsto be attached. The outlineindicates that a full descriptionof the effects of the projecton air pollutionhas to be developed,based on necessarycollection and compilationof data, measuredor calculated. Traffic regulations Trafficregulations may have a significanteffect on air pollution emissionsfrom vehicles,to the extent that they influencethe total traffic activityin an area, the traffic count in a particularroad section,or the speed and flow of the traffic. The followingregulations may have such effects in Metro Manila: MMA Ordinance19 (1991): * Trucksand buses on major roads 6-9 AM and 4-8 PM; * Designatedtruck routes during rush hours. MMA Ordinance78-03-A (1992): * Towingof illegallyparked and stalled vehicles 146 Appendix3 MMC Ordinance 3 (1989): * Yellow Lane Rule. Designates and regulates the use of bus and PUJ lanes in main thoroughfares. MMC Ordinance 6 (1990): * Prohibiting pedicabs and tricycles on highways and major thoroughfares, and limiting their operation to tertiary roads and within subdivisions. PD of November 6, 1992: * Clearing of Obstruction on Sidewalks and other Roadways in order to effect the smooth flow of traffic. * To identify, develop and use alternative routes to ease the traffic situation in Metro Manila. The Anti smoke-belching campaign This project started in August 1977 with the issuance of PD 118 1. The project was first managed by NPCC, then by DENR-NCR, then by a committee of representatives from Metro Manila Authority, Land Transportation Office and the Constabulary Highway Group. After this group disbanded in 1991, DENRINCR/MVPCC resumed responsibility. This enforcement activity consists of 1) stopping smoke-belching vehicles and testing their emissions using the Ringelmann Chart as a guide, 2) issuing subpoenas to owners for testing, and 3) confiscating license plates. Failing in the test results in fines of P200 for the first offense, P500 for the second and P1000 for the third and succeeding offenses. At the peak of the campaign, 18,000 vehicles were apprehended in 1982, but it lost momentum to only about 1,500 vehicles in 1988. After revitalization, again about 18,000 vehicles were apprehended in 1989, and 80% of them reported for testing. Seventy percent of the tested vehicles were then issued a certificate of compliance. APPENDIX 4: EMISSIONS OF AIR POLLUTANTS, METRO MANILA GENERAL DESCRIPTION OF THE CITY AND ACTIVITIES Manila is the capital of The Republic of the Philippines. Table 1: Land area, population and population density of the It is situated in a plain on the NCR in 1990 south-western coast of the City/municipalityArea (km2) Population(x1,000) Populabondensity Luzon Island, around the 1. Manila 38.3 1,599 41,749 mouth of the Pasig river in 2. Caloocan 55.8 761 13,638 the Manila Bay. The 3. PasayCity 13.9 367 26,403 166.2 1,667 10,030 MetropolitanMetroolitnManilaManla RegionRgion 5.4. MalabonQuezonCity 23.4 278 11,880 (MMR), henceforth to be 6. Navotas 2.6 187 71,923 referred to as the National 7. Makati 29.9 453 15,150 Capital Region (NCR) covers 8. Valenzuela 47.0 340 7,234 a total land area of 636 km2 9. LasPinas 41.5 297 7,156 and consists of 4 cities 10.San Juan 10.4 127 12,211 11.Paranaque 38.3 308 8,042 (Manila,Caloocan, Pasan and 12.Mandaluyong 26.0 245 9,423 Quezon City) and 13 13.Pasig 13.0 397 30,538 municipalities. Figure I 14.Taguig 33.7 266 7,893 shows a map of the NCR 15.Muntinlupa 46.7 277 5,931 area. The population density 16.Pateros 10.4 51 4,904 for the NCR is 12,468 17.Marikina 38.9 310 7,969 persons per km2, 60 times Total,NCR 636.0 7,930 12,468 denser than the national Source:MMR (1990). average. The population is projected to grow at the rate of 2.35% annually during the 1990s, corresponding to a 26% increase during the decade. Table I shows the land area, population and population density in the 4 cities and 13 municipalities that comprised the NCR in 1990. Around Metro Manila runs EDSA, the principal circumferential highway. It is a 12-lane highway running in a demi-circle with a radius of about 7 km. It was built as an outer ring road, but development of city centers such as Makati and Quezon City has changed the structure of the 147 148 Appendix4 city. Commercial and administrative development has shifted strongly from the Center to areas outside EDSA, and it has become the spine of the city. At Guadalupe, the busiest point, peak traffic is around 11-12,000 vehicles per hour and daily volumes exceeding 140-150,000 vehicles are observed. Traffic congestion appears regularly along large sections of EDSA. Daily, more than 2 million passengers are passing along EDSA, out of which 1.43 million by bus. With the projected increase in population and traffic it is expected that there will be a total breakdown in the traffic within a few years unless something is done. Several proposals have been made during the last few years: highway improvements, alternative routes and for public transport a Light Rail Transit System (LRT) along EDSA or a transitway system. About 37% of NCRs total land area is used for housing which includes single family residences, multiple residential units, slums and squatter areas. Generally, poor housing areas with higher density are located around the commercial and tourist areas which provide informal employment opportunities. The better housing areas are located along EDSA at the Southern edge of Quezon City, at Greenhills in San Juan, near Ortigas in Mandaluyong and Pasig and near the Makati Commercial Center in Makati. About 8% of the MMR is commercial area. The old commercial areas are located in Ermita, Malate, Quiapo, Divisoria Sta. Cruz and Binondo of Manila. Recent commercial developments occur in Sta. Mesa, (Manila), Cubao, Balintawak, and Monumento (Quezon City), Makati, Greenhills (San Juan), and EDSA-Ortigas-Shaw areas at the confluence of Pasig and Mandalugy. Industrial development took about 15% of the NCRs land in 1990. The factories are concentrated in strategic areas that provide easy access to transportation such as Pasig, Port Area, Paco, Pandacan and Mandaluyong. Other areas of recent industrial concentration are along McArthur Highway, Tandung Sora in the north and along Pasong Tamo and the South Superhighway in the south. Current expansion of industries is now occurring in the municipalities immediately adjacent to the NCR (Laguna, Cavite, Batangas). This is a normal pattern for megacities where new industries are built in areas with lower pollution control than in the Metropolitan Area. Reference map, grid area and population distribution The region selected for an emission survey and for modeling must be large enough to extend towards localities with negligible emissions, or localities where a constant small value of ground- level emissions can be assumed. For MMR this gives the area stretching to the north beyond Kalookan City, south beyond Muntinlupa, west into Manila Bay, and east towards Laguna de Bay and the eastern borders of Marikina and Quezon City. This covers an area of about 22x50 km2 For emission and model calculations the number of grid squares is of importance for the computer time consumption. For Manila it seems that a grid size of 1 km would be appropriate. For the calculation of the pollution load in different parts in the NCR, it is essential to have correct data for the population within each kmn2 of the area, preferably split into different social classes. This is of importance since a significant part of an emission survey is connected with domestic activities. This may be calculated on the basis of data for the population within subdistricts within the municipalities, a detailed map with the subdistrict borders and some local knowledge. Land Use maps from National Mapping and Resource Information Authority (NAMRIA) could be a good basis for an emission survey. URBAIR-Marila 149 Pollution sources The main source groups in Manila are: * Power stations, * Industrial/stationary sources, * Area sources, * Motor vehicles. Several attempts have been made to produce total emission inventories for Metro Manila. Ayala has made emission calculations for Manila for 1987 and 1990 (Ayala, 1993), and Manins has tried to adjust the figures with additional data (Manins, 1991). The original intention of the inventory by Ayala was to cover the entire Metro Manila Region. However, the emission inventory team had no access to the facility records of stationary sources located in the cities and municipalities of the Laguna de Bay Region which were under the LLDA jurisdiction. Ayala's emission estimates cover thus only the sources in the shaded area of Figure 1. In order to complete Ayala's emission survey for 1987/88 Manins examined the Metro Manila 1:10,000 Land Use Maps and counted the number of "industry" symbols within each grid cell. The total was 1,838 factories. The number of factories registered in the emission data base for the same cells was subtracted from the counts, to give an estimate of the number of factories "missing" from each cell in the data base for Metro Manila. Most of the identified missing factories (1689) are in the Valenzuela-Kalookan city (North) and Makati-Pateros regions, but this number can be only indicative and should be corrected by field survey work. Ayala calculated emissions of six criteria pollutants for 1987 and 1990: total organic gases (TOG), carbon monoxide (CO), oxides of nitrogen (NO,), oxides of sulfur (SOx), particulate matter (PM) and particulate matter less than 10,u(PM' 0), as shown in Table 2 for 1990. She also calculated emissions of lead, benzene, ethylene dibromide (EDB), ethylene dichloride (EDC) and asbestos. Table 2 shows that the dominant source of pollutants in Manila is mobile sources for Table 2: Summary of emissions from aU sources in Metro TOC, CO and NO,. SO. is Manila regon, 1990 emitted mainly from Power Source Pollutants,tons per year Stations using high sulfur (3- category TOG CO NO, SO, PM PM0 4% S) fuel, whereas area source Mobile 100,954 572,626 66,216 10,350 13,220 11,450 resuspension of dust from roads Powerplants 103 684 9,118 68,331 4,850 3,265 is the main particle source. Stationarysources 1,713 3,362 4,301 9,762 4,473 4,229 Areasources 5.162 525 276 12 102,386 51,042 Total 107,932 577,197 79,910 88,456 124,929 69,986 Note:Benzene, 4,713 tons; EDB, 2 tons;EDC, 56 tons; Pb, 407 tons; asbestos, Power stations 45 tons. Source:Ayala (1993). There are three power stations in Metro Manila: Sucat (Gardner) Power Station on the edge of Laguna de Bay in Muntinlupa, a four-boiler, two-stack base-load station with a capacity of 150+200+200+300 MW. 150 Appendix 4 Figure 1: Metro Manila region with EDSA and the three power stations f ''' ' ,~~0R,...... :.. * 7t Legend: * . . \W.rk IlillW Emission source inventory area * Power plants URBAIR-Manila 151 * Manila (Tegen) Power Station on Isla de Provisor in the Pasig River, a boiler, two-stack base- load station with a capacity of 2xlOO MW. * Rockwell Power Station south of the Pasig River in Makati, a three-boiler, three-stack base- load station of 3x30 MW. The positions Table 3: Emissionsfom the power stations in Manila of the power Staton Stack Fuelconsumption Emission(tons/year) stations are shown height(m) (MI) TSP SO, NO, CO TOC in Figure 1. Table 1987/88(Manins) 3%S 3 shows emission Sucat 122 949 3,796 53,751 6,263 569 28.5 data and some other Manila 76 310 1,240 17,558 2,046 186 9.3 Rockwell 79 150 600 8,496 990 90 4.5 data for the power oji405;3 5,636 79,8057985 9,299,2 stations....Totalote+;,5o~~ ~ ~ ~ ~~~~~~ki~ ...... 1,409 845 42.3 Total 4,850 68,331 9,118 684 102.6 Industrial/stationary sources Information about stationary sources is the province of two authorities, National Capital Region, Department of Environment and National Resources (DENR/NCR) and Laguna Lake Development Authority (LLDA). Unfortunately, data from the sources within LLDA have not been available. Of the several hundred emitters in the DENR/NCR database, 149 more significant ones are included in the data base used for model calculations. Manins has studied the fuel sales statistics for 1988. When the consumption in the power stations and the stationary sources in the data base is subtracted, 58% of all FO0(Bunker C fuel oil, 4%S) imported to Metro Manila is unaccounted for (or 93% of all non-power station sale). As mentioned above, the stationary sources which fall under the Laguna Lake Development Authority are not included in the data base, but the oil consumption in these will not account for the whole difference. This is a normal problem when making the first emission estimates for capital cities. Many companies have their main offices in the capital and factories elsewhere in the country, but the sale figures are often assigned to the company address instead of the consumption address. The OEA statistics show that 74% of the EFOsold in the Philippines in 1987 was sold in Metro Manila. Out of the total sale of 3,669 Ml IFO in Manila in 1987, 1,409 Ml were used in the power stations. Manins shows that the difference is too big to be accounted for only by the consumption in the stationary sources in the Manila region. It is clear that the existing basis for emission calculations for Manila is inadequate. The oil companies have to deliver correct data about their customers. including delivery addresses, and the Office of Energy Affairs should have the responsibility for correct sale figures. 152 Appendix 4 Motor vehicles The estimates of the emissions from motor vehicles in the NCR may be divided as follows: Overall vehicle emissions and spatial distribution of the emissions. The overall vehicle emissions are calculated as the sum Qveh,j =Ni X Td1 x Q where QvehJ is the total emission of component j (g/year), N; is the number of vehicles of category i, Tdi is an average annual travel distance for the vehicles (km/year), QiJ3 is emission factor for component j from vehicle category i (g/lkm). In earlier emission surveys the only emission factors available have been USEPA factors, as shown in Table 4. It has been pointed out that it Table 4: Emission factors (g/km)from is necessary to take local emission measurements Philipeine vehicles from actual Philippine vehicles. Poorly CO TOC NO, SO, TSP maintained diesel jeepneys and buses are Petrol common, no emission controls are used by petrol Cars 33.0 3.04 2.70 0.123 0.33 vehicles, and many motorcycles are used for Utilityvehicles 33.0 3.04 2.70 0.134 0.33 public transport. In a project initiated by the Truck 117.0 12020 7.80 0.246 0.68 Asian Development Bank, a measuring program Diesel to give a new set of Philippine emission factors Cars 1.1 0.20 0.99 0.634 0.45 has been developed, as shown in Table 5 by Utilityvehicles 1.1 0.30 0.99 3.380 0.93 Vehicular Emission Control Planning (VECP). Truck 17.8 2.90 13.00 3.380 0.93 These have been applied in the latest emission Buses 13.2 2.90 13.00 2.535 0.93 calculations by Ayala, but the figures she Source:USEPA (no date). presents do not correspond to the equation above. Table 6 shows the results from different emission estimates for Manila. For some Table 5: Emission factors for vehicles in the Philippines Numberof 1,000km/ glkm vehiclesx 1,000 vehicle CO HC NO, SO, Pb PM Gasoline Cars 292.6 12 49.5 6.00 2.7 0.011 0.073 0.10 UV 137.4 30 60.0 8.00 3.0 0.014 0.092 0.12 MC 66.6 10 26.0 18.60 0.2 0.004 0.028 2.00 Bus/Truck 6.3 50 36.24 1.68 3.93 0.05 Diesel Taxi 14.4 30 1.9 0.65 2.0 0.081 0.60 Jeepney 50.0 50 2.5 0.70 1.4 0.121 0.90 UV 64.3 40 2.5 0.70 1.4 0.115 0.90 Bus/Truck 54.4 50 12.4 3.70 12.5 0.374 1.50 Note:Number of vehicles 1990. Source:VECP (1992). URBAIR-Manila 153 components in some vehicle types there are similar values, but in most cases there are substantial differences. The methods should be approximately the same, and the calculations should be based upon the same statistical data. It is of no value to start an argument about the most correct emission figures. For SO2 the values are based upon different assumptions regarding sulfur content, in other cases the vehicle groups may include different vehicle types. The jeepneys seem to appear like a dark horse in these calculations, in most of the estimates they are included in the Diesel Utility Vehicles. Although buses are very visible sources of pollution, they contribute little to the total emissions. Spatial distribution of vehicular emissions For model calculations in an area it is not enough to have figures for the total emission from vehicles, a correct spatial distribution is also necessary. This may be achieved in a three-stage procedure: primary roads, secondary roads and local roads. The co-ordinates for the crossings in the primary road network should be measured on the reference map. Based upon counts of the number of vehicles of different types on 'the main roads, values for Annual Average Daily Traffic (AADT) may be estimated. It will often be necessary to extrapolate counts from one intersection to the nearest crossings with local experience about the traffic flow. This is a time consuming procedure, but in this way it is possible to calculate the traffic work (vehicle-km) for each vehicle type within each km2 . The next problem is to obtain correct emission factors for the driving conditions on the main roads, but as the first estimate the results of the emission measurement programs may be used. In this way emission distributions of different pollutants may be calculated. For the secondary roads it is necessary to measure the length of the primary and secondary roads within each km2 , and subtract the length of the primary roads from the calculations above. Values for the AADT for each vehicle group on the secondary roads should be estimated to give distributions of secondary traffic activity, and from these the emissions may be calculated. As for the traffic on the local roads, it is necessary to start with figures for the total sale of petrol and diesel in the area. It is normal to assume that there is no net export of gasoline across the borders of the study area. The consumption of petrol and diesel by the traffic on the primary and secondary roads is calculated, and the difference has to be distributed in some way, usually according to the population distribution. 154 Appendix 4 Table 6: Differentemission estimates of vehicleemissions in Manila sO N Manins Ayala Ayala VECP Manins Ayala Ayala VECP ______1987 1990 1987 1990 Gasoline Cars 786 750 43 17 239 7 497 11556 10440 UV 249 319 64 5 005 3189 14641 16 588 Truck 54 12 121 1 721 116 1 276 Buses 1 7 12 76 MCITC 51 130 3 78 1 305 306 147 Sub-tot 1140 1 212 238 24042 12 120 27 855 Diesel Cars 206 756 846 321 1 862 956 Jeepny 4 952 UV 2 516 7 284 6 695 1 965 17 941 7 193 Truck 6 267 2 289 2 285 24 103 5 639 26 841 41 029 Buses 1 959 329 287 10353 811 3 371 MC/TC 64 158 Sub-tot 10 948 10722 10 113 36 742 26 411 38 361 Total 12 088 11934 10 350 - 60 785 38 531 66 216 73 156 CO TSP Manins Ayala Ayala VECP Manins Ayala Ayala VECP 1987 1990 1987 1990 Gasoline Cars 210 694 134992 213672 191399 2 107 750 866 387 UV 61174 57414 280442 277603 612 319 1107 2456 Truck 25 811 2 095 11770 19 064 150 12 84 1 466 Buses 218 696 1 17 MC/TC 17 592 73 502 22 025 217 131 1 512 4 923 Sub-tot 315271 218221 528605 3 086 1 212 3 586 Diesel CarsfTaxi 357 672 938 146 1 260 345 Jeepny 40 701 2 857 UV 2 184 6 475 13112 893 12141 5 155 Truck 33 003 1 908 26 626 1 724 3 816 3 272 Buses 10 198 293 3 344 719 549 461 MC/TC 57 _ 107 Sub-tot 45 742 9 405 44 020 3 482 17 873 9 633 Total 361 013 227626 572 626 536814 6 568 19 084 13220 12089 TOC Manins Ayala Ayala VECP 1987 1990 Gasoline Cars 19409 22 742 30040 23 200 UV 5 635 9 672 42 049 37 792 Truck 2 691 353 577 Buses 37 32 MCITC 10 452 3 959 15425 13 638 Sub-tot 38 188 36 763 88 124 Diesel Cars/Taxi 94 94 314 Jeepny 2 309 UV 596 12 141 3 573 Truck 5 377 3 816 7 945 12 145 Buses 2 241 549 998 Sub-tot 8 308 17872 12830 Total 46495 54 635 100954 89 084 URBAIR-Manila 155 Ayala has estimated the fuel consumption with respect to vehicle type in Table 7: Fuel consumption in MMR, 1990 MMR for 1990 as shown in Table 7. The Vehicletype Gasoline(10 liters) Diesel(10f liters) consumption is distributed according to the Cars 414.3 50.4 number of registered vehicles, without any UtilityVehicles 194.5 399.4 consideration of different consumption per Buses 0.5 17.1 vehicle. This is obviously not correct, as Trucks 8.4 136.3 for instance the MC/TCs, which are 13% of Total 712.0 603.3 the total number of gasoline vehicles, should account for less than 13% of the fuel consumption. In addition to the vehicular emissions in NCR, it is important not to forget emissions from the traffic outside the study area, but inside the emission grid. At least the emissions from the main roads should be estimated. Ayala has also calculated other motor vehicle emissions in addition to the running exhaust emissions: incremental cold start exhaust emissions, incremental hot start exhaust emissions, and the evaporative emissions consisting of hot soak, diurnal and evaporative running losses. The major road network of Metro Manila (Figure 2) consists of 10 radial and five circumferential roads: * R-1: Roxas Boulevard, * R-2: Taft Avenue, * R-3: South Superhighway, * R-4: J. P. Rizal Street, * R-5: Shaw Boulevard, * R-6: Ortigas Avenue, * R-7: Quezon Avenue, * R-8: A. Bonifacio Avenue, - R-9: Rizal Avenue, - R-l0: Honorio Lopez Boulevard, * C-1: Taft Avenue, * C-2: Pres. Quirino Avenue, * C-3: G. Aretana Avenue, * C4: Epifanio de los Santos Avenue (EDSA), * C-5: Katipunan (under construction). Most of the roads are traveled by both gasoline and diesel fueled vehicles, except for R-2 and R-9 where the Light Railway Transit (LRTA-1) operates. Public transport consists mainly of jeepneys, buses (including mini-buses) and taxis. Motorcycles/tricycles are also used for short distance trips. Private transport is mainly by car and five-setae jeepneys, pick-ups and vans, school and office service buses. The National Capital Region has about 4, 900 km of roads for its interurban travel, classified into 720 km of National Roads, 554 km of Municipal Roads, 1,274 km of City Roads, 318 km of Barangay Roads, and 1,827 km of Private Roads (inside subdivisions). 156 Appendix4 Figure 2: Major road corridors in Metro Manila ~~~~I al\P\ < SA ~~/6SA l it;&0 0i I /\ \SoExpressway/ 10tt URBAIR-Manila 157 Area sources Area sources are small sources individually emitting relatively Table 8: Area source emissions in Metro Manila region, insignificant amounts of 1990 emissions, but when considered TOG CO NO, SO, PM collectively with other similar Pavedroad travel 80,507 sources, they become significant. Structuralfires 9.25 113.08 2.57 7 Ayala estimated emissions from Automobilefires 0.09 2.87 0.09 2 Roadconstruction 8,479 12 differenttypes of area sources Buildingconstruction 13,380 as shown in Table 8. Surfacecoatings 381.80 Adhesiveand sealants 1,332.87 In addition, there will be some Drycleaning 80.75 emissions from the traffic at the Industrialdegreasing 773.30 harbor of Manila. No ResidentialFuel Combustion 11.61 29.74 145.98 0.18 5 information,however, iS GasolineCommercialDispensing Aircraft 2,410.92161.54 378.93 127.17 12.09 4 available about the consumption Facilities of coal in Metro Manila. Total 5162.13 524.62 275.81 12.27 102,384 Emission from residential fuel Source:Ayala (1993). combustion includes the use of LPG. Normally there should be appreciable emissions from domestic cooking, especially from low-standard dwellings using different cheap fuels. These are not included in official statistics, but has to be taken into account. For each of the source groups there will be a separate key to distribute the emissions over the area. This may follow the distribution of roads, the number of gasoline stations, the population distribution or even a different distribution key for different regions is possible. Emission survey for Metro Manila, road traffic emissions This emission survey has been prepared as input for model calculations for the Metro Manila area, as a tool in developing an AQMS for the area. An emission inventory should cover source groups such as industrial point sources, small industry and domestic emissions and emissions from main road and local road traffic. Using representative emission factors for each source category will normally give good estimates. However, this survey is not a complete emission survey for Manila. Many source groups are not included yet, and for others the calculations are based upon secondary information, especially for the spatial distribution. This means that many basic input data are still missing, and we have had to use other data to estimate the distribution. Information about stationary sources in Metro Manila is divided between two authorities: National Capital Region, Department of Environment and National Resources (DENR/NCR) and Laguna Lake Development Authority (LLDA). Figure 3 shows the two regions within our model area. In the DENR/NCR database there are data for several hundred emitters, but the actual emission data are not available to us. 158 Appendix 4 Map and emission grid The emission calculationsare Figure 3: Metro Manila region and the model calculation area made for a 1 km2 grid of 18x30, N according to "Map, of Metro Manila" 1:25,000, and all co-ordinates and references are given relative to this map. The National Capital (NCR) covers a total land area of 636 km2 and \\ Calooca QuezonCity, consists of 4 cities (Manila, Caloocan, Pasay and Quezon City) and 13 municipalities. Pasi Figure 3 shows the Metro Manila Region and the Mnl a calculation area. The calculation Tag, g area covers 540 kmM2 of this is about 140 km2 sea or areas outside NCR. Large (but less H inhabited) areas of Jurisdictionareas: NCR are situated Clear:LLDA outside the grid Shaded:DENR-NCR Lk area, mainly the Monitoringstations: northern part of 1:Ermita NCR. Table 9 2: Las Pinas shows the land area 4: Pasig lupalin and the population 5: QuezonCity modellin in the regions in 6: CaloocanCity area 1980, 1990 and 8: Makati 1995. _ URBAIR-Manila 159 Table 9: Area and population in the Manila regions Region Areakm 2 Cov.% InhabitantsInhabitants InhabitantsBarangays Zone 1980(10) 1990(10') 1995(103) 1 Manila 38.3 100 1,630 1,601 1,587 900 1 2 CaloocanCity 55.8 50 468 763 975 188 2 3PasayCity 13.9 100 288 368 417 200 3 4 QuezonCity 166.2 90 1,166 1,670 1,999 140 2 5 Malabon 23.4 60 191 280 339 21 3 6 Navotas 2.6 80 126 187 229 14 2 7 Makati 29.9 100 373 453 500 32 2 8 Valenzuela 47.0 10 212 340 430 32 3 9 LasPinas 41.5 90 136 297 438 20 3 10 SanJuan 10.4 100 130 127 125 21 2 11Paranaque 38.3 100 209 308 375 16 3 12 Mandaluyong 26.0 100 205 248 273 27 2 13 Pasig 13.0 100 269 398 484 30 3 14 Taguig 33.7 100 134 267 376 18 3 15 Muntinlupa 46.7 40 137 278 397 9 3 16Pateros 10.4 100 40 51 58 10 3 17 Mankina 38.9 70 212 310 376 14 3 Total 636.0 5,926 7,948 9,378* 1,692 Note:*The total is reportedas 9,205,422, but the sum of the population in all regionsgive 9,378,665. Source:DENR/NCR. Population distribution For each region there was estimated a coverage factor to account for the fraction of the population within the grid area. For each km there was estimated another factor, "built-up-area," to distribute the population within each region, and also to estimate the traffic on minor roads (see later). With more detailed data these factors may be estimated later. The population in grid (I,J) within region K will be POP(I,J)= FACT(K)xINH(K)xCOV(I,J,K)/[)COV(IJ,K)], where FACT(K) is the coverage factor for region K, INH(K) is the number of inhabitants in the region K, COV(I,J,K) is the coverage of grid (1,J) in region K. Figure 4 and Annex 1 show maps of the population distribution in Manila, 1990. This covers 6,652,600 of the 7,948, 000 inhabitants. The highest population density is estimated for grid (2,27), with 76,952 inh/km2 . 160 Appendix 4 Figure 4: Population distribution in Manila (1990) <10 < 20 U_;1<40 E-<<60 EX_ >60 1 _Unit: lil 4 ~~~~~~~~1000inhabitantsJkm3 URBAIR-Manila 161 Each regionin Manila is divided into a number of "barangays,"as shown in Table 9. To give a correctpopulation distribution for Metro Manila,the populationin each barangayshould be distributedto the grid squares it covers. On the averageeach barangayis approximately0.4 km2, and in this way the errors in the populationdistribution will be small. For this method it is necessaryto have data for the barangaypopulation, and a detailedmap with the barangayborders. The same proceduremay be used for other types of data, using demographicor socio- economicparameters. For examplethe use of differentfuels may be a functionof socialstanding. Emission from traffic The estimatesof the emissionsfrom motor vehiclesin the NCR may be divided into two: The overall vehicleemissions and the spatial distributionof the emissions. The overallvehicle emissionsare calculatedas the sum Qveh,j = £x; x Tdix Qj,, where Qveh, j is the total emissionsof componentj (g/year), N1 is the numberof vehiclesof categoryi, Td;is an averageannual drivingdistance (AADD)for the vehicle category, Qi j is averageemission factor for componentj from vehiclecategory i (g/km). Table 10 gives the calculated Table10: Trafficactivity andfuel consumptionin Manila total traffic Noof vehicle AADD Trafficactivity ConsumptionFuel consumption activity and (10') (10'km) (lOkmlyr) (I/m) (1tel) fuel Gasoline consumption Cars 292.3 10.0 2.92 0.10 292 for traffic Utility 137.4 26.0 3.57 0.15 536 for traffic MC 66.6 8.5 0.57 0.05 28 in Manila, Bus/truck 6.3 35.0 0.22 0.3 66 based on an Sumgasoline 502.6 71.85 7.28 .60 922 assumptionof Diese Td,. Taxi 14.4 20 0.29 0.10 29 The fuel Jeepney 50.0 35 1.75 0.15 262 s&lestatistics Utily 64.3 20 1.29 0.15 194 Truck/bus 54.4 35 1.90 0.30 571 for Metro Sumdiesel 183.1 110 5.23 .70 1,056 Manila for the Total 685.7 181.85 12.51 .130 1,978 year 1990give a total sale of 855 x 106liters of gasolineand 1,307x 106liters of diesel oil. This is less gasolinethan the consumptioncalculations above give, and it indicatesthat either the averagemileage of the vehiclesor the specificconsumption (1/km) is overestimated,or both are. The total sale of diesel oil is higher than the calculatedconsumption from the traffic. This is probablyexplained by the significantamounts of diesel oil used for industrialheating processes. 162 Appendix4 In the VECPproject funded by the Asian DevelopmentBank, a Table 11: kmissions of NO, and TSPfrom traffic in measuringprogram to give a set of Manila Philippineemission factors was Trafficactivity NO, TSP carriedout. These are used together 10'km/yr g/km 10't/yr glkm tVyr with EPA/WHOemission factors to Gasoline give the emissionfactors used in the Cars 2.92 2.70 7.89 0.20 584 Utilityvehicles 3.57 2.70 9.64 0.33 1,178 calculationsof emissionsof NOxand MC 0.57 0.07 0.04 0.5 285 TSP from traffic in Manila,as shown Bus/truck 0.22 8.00 1.76 0.68 150 in Table 11. Sumqasoline 7.28 13.47 19.33 1.71 2,197 ...... On the average,this gives an Diesel emissionfactor of 3.9 g NOx,/kmand Taxi 0.29 1.0 0.29 0.6 174 0.7 g TSP/km. Jeepney 1.75 1.4 2.45 0.9 1,575 Utilityvehicles 1.29 1.4 1.81 0.9 1,161 Truck/bus 1.90 13.0 24.70 2.0 3,800 Sumdiesel 5.23 16.8 29.25 4.4 6,710 Spatial distribution of the jTta 12.51 30.2 48.59 6.11 8...90 traffic emissions Source:VECP (1992) Main roads. For the spatial distributionof the traffic,a main road net for Manila was defined accordingto a report from the Manila TrafficManagement Center (MTMC). For many of the roads the AnnualAverage Daily Traffic (AADT)was given, for others the data was measuredfrom a map in the report. The road net was not completeand had to be extended and supplemented,mainly for the areas outside EDSA,but also to someextent for the central parts of Manila. For these roads the AADTwas estimatedby extrapolationor other means. In this way a main road net for Manila was defined with straight links from one crossingto another,as shown in Figure 5. The total length of the road net is 434.5 km, and the total traffic work on these roads was estimatedto 15,418x 106km/yr. This gives an averageAADT of about 35,000 cars/dayon the main roads. Using the average fuel consumptionfigure of 0.158 1/km calculatedabove, this will give a yearly consumptionof 889 x 1,061of fuel. Annex 2 shows the distributionof the main road traffic activity. The vehiclecomposition was given for about 20 countingpoints in Manila,mainly along the radial and circumferentialroads. This is valuableinformation, but in this study it was not possibleto extrapolatethese data to the adjacentroads, and we were forced to use composite emissionfactors based upon the averagetraffic compositionfigures (as in Table 11). URBAIR-Manila 163 Figure 5: Main road net in Manila ( 1I \ I I Ttl _X _l_I.- /- 4- -4-4+ 1 -4-1 J -4 -I- It -r- 1 I I} ! 1 Ill I _ 1_1\ Ki7 z1 1-1-l _1__ -_ T--tt T-I 7IJLI i IJLLJJffiLlriKLJTF- t-1 4-- _ 4- 4- ___ 4 TT1 -1- T -I'I - - -I- r 7 -7 _ 1 r |~~~jI ii e I]e I , A II _III\ I 1 I 1,I_ , 1_4 L4 ,+, 't -1 \ i-- -, 164 Appendix4 Local roads. In addition to the traffic on the main roads there is a considerable amount of traffic activity on the local roads in the area. The average traffic on the main roads was estimated to 35,000 vehicles/day, and for the main road data there seems to be a lower limit of about 10,000. The National Capital Region has a total of about 4,900 km roads for its interurban travel. Most of these will have low traffic, but there will also be roads with heavy traffic, and the emissions are considerable. To estimate the traffic activity on the small roads, the Metro Manila area was divided into 3 zones: zone I is Manila, zone 2 the surrounding regions inside and around EDSA, and zone 3 the regions outside. The zone codes are listed in Table 9. For each km2 the small road traffic activity was calculated as TRAF(I,J) = COV(I,J,K)xTRW[ZONE(K)], where COV(I,J,K) is the coverage of grid (I, J) in region K, defined above, ZONE(K) is the zone listed in Table 9, TRW[ZONE(K)] is the traffic activity in zone ZONE(K), as listed below; 200,000 vehicle-km in zone 1, 130,000 vehicle-km in zone 2, 40,000 vehicle-km in zone 3. These estimates of local road traffic activity were set so that the total fuel consumption for road traffic in Manila would correspond to the fuel consumption statistics. The increase from zone 3 towards zone 1 reflects the increase in traffic activity towards the central areas of Metro Manila. The actual ratio of increase was chosen somewhat arbitrarily. Based upon these assumptions the traffic activity on the small roads was estimated to 18,706x 106 veh-km/day or 6.83x 109 km/yr. With the fuel consumption factor of 0.158 1/km calculated in Table 10 this gives a fuel consumption of 1,077x106 I/year for the local road traffic. The total fuel consumption is then 889+1,077 (gasoline+diesel):= 1,968 x 106I/year, which corresponds well with the estimated fuel consumption of 1979x1061/year in Table 10. The estimates for the traffic in Manila give a total of 34 124x106veh-km/dayor Table 12: Traffic activity and total emissions from traffic in 12.46x109 km/yr. Using the Metro Manila average emission factors of Trafficactivity Fuelconsumption 3.9 g NO,/km and 0.70 g 10'veh-km/day 10' kmtyr 10 Ilyr TSP/km as defined above, Mainroads 15,418 5,628 889 this gives total emissions Localroads 18,706 6,832 1,079 from road traffic in Manila Total 34,124 12,460 1,968 shown in Table 12. Totalemissions from traffic NO, 10TSP Annex 3 and 4 show 133.15.54t/dt/dh 23.91.9 t/dVh maps of average hourly 48,578t/yr 8,719t/yr emissions of NOx and TSP from traffic in Manila 1990. URBAIR-Manila 165 ANNEX 1: POPULATION DISTRIBUTION 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 J=30 900. 600.1200.1346.1831. 823. .1156.2312.2312.2312.1927.1156.1156. 771.. 771. 385. 632. J=29 1800. 600.2700.1800.1500.2546. 771.1542.2698.2312.2312.1927.1542. 77i. 385. 385. 385.1726. J=28 3840. 900. 300. .2244.1732. 771.1156.2698.1927.1927. . 385.1542. 771. . 247.2466. J=27 3520.7695.4039.4039.3142.1542.1542.1927.3083.1927. 385.1156.1542.1156.1156. 247. 740.1973. J-26 .3986.5799.4039.1346.3083.2698.3083.3083.1542.1156.2312.2312.1156.1017. 493.1973. 986. J=25 .3591.4039.2465. 771.3468.2312.2312.3083.2698.2698.2312.3083.1542. 740.1973.1973. 493. J=24 2010.6699.4689.1340. 385.2698.2312.1156.1927.2312.2698.2698.2312.1927.1233.1726.2219. J=23 4019.5359.5359.6029.2010. .1927.1542.2222.2539.1542.2312.2312.1927.1057. 704.2465. J=22 4019.6699.5359.5359. 670.3349. . 771.2041.2426.2268.2744.1927.1927. 385. 352.2465. J=21 2679.6029.5359.4689.6029.6029.2679. .1056.2041.1510.1127.2698.1542.1542. 704. 352. J=20 .2679.2679.3349.1340.1340.3349.2010.1879.3006.3006.1503.2489.2818. 352. 704.1409. 352. J219 .3349. 670.4689.2679.2010.1340.1185.1667.3006.3382.2231.2465.2465.1409. 352.1057.1057. J18 . .1340.5359.4689.5629.1888.2427.2157.2582.2475.2078.3170.1761.1057.1057. J-17 . . .4689.6029.3088.2427.2427.1888.2427.2696. 809.1596.2113.1761. 704. J=16 . .1284.5005.2140. .1618.2427.2157.2157. 270. 539.1389.1882. 522. 352. J=15 . .1284.2995.3851.1712.1070.2427.2427.1888. 539. .1899.1190. 703. 351. J=14 . . . 856.4279.2995. 266.1348.1512. 351. 703. . 703. 703. . Js13 . . . .1712.3556. 561. . 351. 351. . . . 703. . J=12 . . . .1712. 133.1844.1416. 398. 664. 266.1671. 351. 703. 703. Jail . . . . 856.1416. 133.1195.1195.1850.3256.3209. . .2459. J=10 . . . . 268. 133. 266. 266.1062. 797.1897.3646. 703. . . J. 9 . . . . 136. 271. 398. 398.1062. 929.1546. 968. 703. . . J- 8 . . . 271. 950. 814. 941.1062.1195. 664.1413.1187. 351. . . Js 7 . . . 950.1357. 814. 268.1328.1195. 664. 929. 835...... J. 6 . . . 678.1221. 950.1085.1080.1195.1328. 929. . . . . J- 5 . . 407.1357.1357. 950. 950.1201.1704. 398. 454. . . . Ja 4 . . . . 407.1357.1221. 543.1083.1589.1816. 454. . . . . J= 3 . . . . . 814.1085.1085.1041.1362. 681. 454. . . . . J- 2 . . . . . 136. 407.1221.1633.1362. . 454. . . . . 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Note:Unit:, 10 persons. Maximujm value is 7.6953E+04in (227). Sum - 6.65260E+06.Scale: 1.OE+01. Gridsize, 1,000 meters. 166 Appendix 4 ANNEX 2: MAIN ROAD TRAF'FICWORK 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 14 IS 1 6 17 1 8 J=30 .114. 12. 315. .300. .195. 153. 153. 18. 35. . .52.7. 188. . J-29 . .132. 50. 422. 449. 207. 10. . .121. 94. 129. 433. 500. . J=28 37. 138. 312. 302.1145.1156. 851. 974. 947. 510. 326. 97. 825. 491. 87. . . J=27 137. . 71. 110. 846. 586. . 251. 351. 804.1132.1264. 265. 65. 85. . . J=26 15. 189. . 423. 485. 975. 236. 318. 854. 872.1066. 194. 51. 151. . . . J-25 .181. 146. 718. 609. 482. 454.1355. 524. 867.1592. 366. 383. 561. 330. 153. 152. 152. J=24 .226. 335. 771. 935. 600.1345. 964. 578. 826. 767.1470. 693. . 141. 212. 92. 204. J-23 .302. 240. 760.1151.1008. . 439. 593.1058. 221.1351. 545. 94. . 232. 269. J-22 .457. 414. 743.1824. 912. 712.1271. 393. 479. 868. 584. 569. 100. 50. IS0. 76. 87. i=21 .59. 694.1595. 620. 809. 64. 321. 499. 48. 32. 640. 523. . 102. 179. . 163. i=20 . .613.2168. 659.1015. 113. 278. 82. 432. 464.1200. 331. 350. 607. 539. 307. 438. J=l9 . . .1220. 851.1656. 213. 112. . . 455.1635. 326. 205. 297. 43. J=18 . . .591.1322.1043. 488. 394. 533. 161.2068. 230. 641. 565. 341 . J=17 . . . .1136. 765.1431.1268.1538.1777. 758. 278. 468. 108. . . . J=16 . . .21.1288. 430. 966.1373.1925. 734. 152. 152. 257. 108. . . J=15 . . . .810. 752.1024.2665. 254. 4. 284. 3. 40. 149 . J=14 . . . .822. 610. 487. 845. 916. 183. 128. . .157. . . J-13 . . . .677. 605. . .1135. . . . .79.. J-12 . . . .481. 969. 242. .531.1061. . .39. 79. . . . Jull . . . .536. 568. . . . 531. . .79. . . . . J-10 . . 104.1002. 127. . . .1061. 531. .39. . . . J= 9 . . .595. 533. 106. . .85. 217.1155. 203. 65. . . . . J- 8 .212. 531. 144. .830. 415. . . .830...... J= 7 .368. 178. . . .415. 830. 415. .830...... J= 6 27. 54. 543...... 830. 415. 830...... J= 5 54. .415. 415. 830...... 1244...... J= 4 27. . . .415. 830. 415. . . .830...... J- 3 ...... 415. 830. 415. .830...... J5 2 ...... 830. 415. 830...... J- I 170.1589. . .. I 2 3 4 S 6 7 8 9 10 11 12 13 14 1S 16 17 18 Note:Unit:, 100 car-kmlday. Maximum value is2.6653E+05 in(8,15). Sum - 1.54178E+07.Scale: 1.OE+02. Gridsize, 1,000 meters. URBAIR-Manila 167 ANNEX3: TRAFFICNO, EMISSIONS 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 J-30 35. 49. 49. 130. 81. 104. 138. 183. 312. 312. 319. 239. 138. 138. 214. 135. 46. 58. J=29 69. 23. 134. 81. 155. 380. 278. 187. 323. 277. 304. 252. 214. 192. 161. 46. 46. 81. J=28 193. 66. 268. 484. 679. 635. 288. 363. 541. 348. 306. 22. 236. 298. 112. . 12. 115. J=27 216. 288. 155. 440. 610. 458. 184. 288. 450. 416. 307. 430. 246. 153. 158. 12. 35. 92. J=26 3. 182. 461. 512. 365. 594. 377. 442. 566. 385. 384. 321. 288. 173. 104. 23. 92. 46. J-25 . 249. 725. 649. 371. 526. 381. 589. 490. 523. 690. 361. 457. 314. 111. 128. 127. 58. J=24 . 467. 630. 731. 884. 668. 587. 361. 364. 467. 500. 662. 436. 230. 90. 130. 125. 47. J-23 . 485. 747. 728. 818. 301. 576. 286. 459. 567. 235. 588. 402. 252. 35. 76. 143. J=22 . 382. 718. 724. 904. 833. 786. 662. 506. 571. 661. 596. 362. 254. 58. 46. 98. 20. J=21 . 14. 436. 644. 489. 325. 153. 420. 507. 426. 284. 286. 443. 184. 208. 64. 12. 38. J=20 . . 487. 569. 636. 510. 233. 202. 249. 468. 476. 461. 192. 173. 151. 147. 117. 112. J=19 . . . 420. 749. 866. 602. 210. 230. 369. 520. 619. 156. 128. 114. 22. 35. 35. J=18 . . . 136. 789. 909. 643. 506. 492. 406. 845. 226. 252. 188. 113. 35. J=17 . . . 35. 550. 418. 745. 707. 677. 825. 636. 202. 235. 94. 58. 23. J=16 . . . 39. 378. 203. 545. 731. 813. 538. 81. 127. 209. 140. 23. 12. J=15 . . . . 210. 289. 409.1029. 473. 324. 158. 1. 194. 115. 23. 12. J=14 . . . . 190. 233. 205. 437. 373. 54. 53. . 23. 59. J=13 . . . . 156. 209. . 46. 308. 12. . . . 41. J=12 . . . . 122. 258. 90. . 122. 245. . 46. 21. 41. 23. J=11 . . . . 135. 142. 12. 35. 58. 180. 104. 92. 18. . 81. J=10 . . . 24. 243. 41. 104. 104. 69. 314. 180. 115. 32. J= 9 . . . 160. 134. 47. 23. 92. 89. 154. 289. 70. 38. J= 8 . 49. 122. 45. 23. 226. 130. 92. 81. 104. 226. 35. 12. J3 7 . 85. 64. 81. 69. 81. 188. 295. 153. 92. 203. 23. J- 6 6. 12. 206. 115. 69. 23. 115. 104. 249. 176. 203. J= 5 12. . 153. 199. 272. 92. 92. 104. 115. 81. 287. J= 4 6. . 35. 115. 211. 272. 176. 104. 115. 35. 214. J- 3 . . . 35. 115. 104. 142. 283. 176. 92. 214. - . . . . J= 2 . . . . 69. 92. 92. 81. 260. 130. 214. J= 1 . . . . 12. 35. 104. 92. 69. 39. 389. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Note: Unit:, kglh. Maximum valueis 1.0293E+02 in (8,157). Sum - 9.89485E+03. Scale: 1.OE.01. Grid size, 1,000 meters. 168 Appendix 4 ANNEX4: TRAFFICEXHAUST PARTICLE EMISSIONS 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 156 17 18 J=30 49. 70. 69. 185. 114. 147. 196. 260. 442. 442. 452. 338. 196. 196. 303. 192. 65. 82. J=29 98. 33. 190. 115. 220. 539. 395. 265. 458. 392. 432. 358. 304. 272. 229. 65. 65. 114. J=28 274. 94. 380. 687. 963. 901. 409. 515. 768. 494. 434. 32. 335. 422. 159. . 16. 163. J-27 306. 409. 219. 624. 865. 650. 262. 409. 638. 590. 435. 610. 348. 218. 224. 16. 49. 131. J=26 5. 258. 654. 727. 518. 842. 535. 627. 803. 547. 545. 456. 409. 245. 147. 33. 131. 65. J.25 . 354.1029. 921. 526. 746. 541. 835. 694. 741. 978. 512. 648. 445. 157. 181. 181. 83. J-24 . 663. 894.1037.1254. 948. 832. 512. 516. 663. 709. 939. 619. 327. 128. 184. 177. 67. J=23 . 687.1059.1033.1161. 428. 818. 405. 652. 804. 334. 834. 570. 358. 49. 109. 203. J=22 . 542.1018.1028.1283.1181.1116. 939. 717. 811. 938. 845. 513. 360. 82. 65. 139. 28. J=21 . 19. 619. 914. 693. 461. 217. 595. 719. 604. 403. 405. 629. 262. 295. 91. 16. 53. J=20 . . 691. 807. 902. 724. 331. 287. 354. 665. 675. 654. 272. 245. 215. 209. 166. 160. 3=19 . . . 595.1063.1228. 854. 298. 327. 523. 737. 878. 221. 182. 162. 31. 49. 49. J=18 . . . 193.1119.1289. 912. 717. 698. 576.1199. 321. 357. 266. 160. 49. J=17 . . . 49. 780. 594.1057.1003. 961.1170. 902. 287. 333. 133. 82. 33. J=16 . . . 56. 536. 288. 774.1038.1153. 763. 115. 181. 297. 199. 33. 16. J=15 . . . . 298. 409. 580.1460. 672. 459. 224. 1. 275. 163. 33. 16. J=14 . . . . 269. 330. 290. 620. 529. 76. 74. . 33. 84. . J=13 . . . . 221. 296. . 65. 437. 16. . . . 58. . J=12 . . . . 174. 366. 128. . 174. 347. . 65. 29. 58. 33. Jail . . . . 192. 202. 16. 49. 82. 255. 147. 131. 26. . 114. J310 . . . 34. 344. 58. 147. 147. 98. 445. 255. 163. 46. . . J= 9 . . . 227. 191. 67. 33. 131. 126. 218. 410. 99. 54. . . J= 8 . 69. 174. 63. 33. 320. 185. 131. 114. 147. 320. 49. 16. . . J3 7 . 120. 91. 114. 98. 114. 266. 418. 217. 131. 288. 33. . . . J= 6 9. 18. 292. 163. 98. 33. 163. 147. 353. 250. 288. . . . . J= 5 18. . 217. 283. 386. 131. 131. 147. 163. 114. 407...... J= 4 9. . 49. 163. 299. 386. 250. 147. 163. 49. 304...... J- 3 . . . 49. 163. 147. 201. 402. 250. 131. 304. . . . . J3 2 . . . . 98. 131. 131. 114. 369. 185. 304. . . . . J3 1 . . . . 16. 49. 147. 131. 98. 56. 552. . . . . 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18FELT FOR Pa Nots:Unit, kg/h. Maximrm value is 1.4602E+01in(8,15). Sum - 1.40374E+03.Scale: 1.0E.02. Gridsize, 1,000 meters. APPENDIX 5: EMISSION FACTORS, PARTICLES EMISSION FACTORS,PARTICLES Introduction Emission factors (emitted amount of pollutant per quantity of combusted fuel, or per km driven, or per produced unit of product) are important input data to erosion inventories, which again are essential input to dispersion modeling. The knowledge of emission factors representative for the present technology level of Asian cities is limited. For the purpose of selecting emission factors for the URBAIR study, references on emission factors were collected from the open literature and from studies and reports from cities in Asia. This appendix gives a brief background for the selection of emission factors for particles used in the air quality assessment part of URBAIR. Motor vehicles The selection of emission factors for motor vehicles for use in the URBAIR project to produce emission inventories for South-East Asian cities, was based on the following references: * WHO (1993); * US EPA (EPA AP42 report series) (1985); * VECP, Manila (Baker, 1993); * Indonesia (Bosch, 1991); * Williams et al. (1989); * Motorcycle emission standard and emission control technology (Weaver and Chan,1993). Table 1 gives a summary of emission factors from these references for various vehicle classes. From these, the emission factors given in Table 2 were selected, for use as a basis for 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; 169 170 Appendix 5 * Utility trucks, diesel; * 2-stroke 2- and 3-wheelers. Table 1: Emission factors (g/km) for particle Thus, the emission factors for these emissions from motor vehicles vehicle classes are the most important ones. Fueland Vehicle Particles(gkm) Reference Gasoline Passengercars 0.33 USEPA/WHO Comments 0.10 VECP,Manila 0.16 Indonesia(Bosch) 0.07 Williams It is clear that there is not a very solid basis Trucks,utility 0.12 VECP,Manila in actual measurements on which to estimate 0.33 USEPA particle emission factors for vehicles in Trucks,heavy duty 0.33 USEPA South-East Asian cities. The given MCw2/4stroke 0.21/ USEPAMHO references represent the best available basis. 2 00/ VECP,Manila Comments are given below for each of the 0.21/0.029 IndonesiaVWS vehicle classes. 0.28/0.08 Weaverand Chan Diesel Gasoline: Car,taxi 0.6 VECP,Manila • Passenger cars: Fairly new, normally* 1T 0.37O~~~~~~045 WilliamsUSEPA/WHO well maintained cars, engine size less Trucks,utility 0.9 VECP,Manila than 2.5 1, without 3-way catalyst, 0.93 EPA running on leaded gasoline (0.2-0.3 g Trucks,heavy/bus 0.75 WHO Pb/1), have an emission factor of the 1.5 VECP,Manila order of 0.1 glkm. Older, poorly 0.93 USEPA maintained vehicles may have much 1.2 Bosch larger emissions.larger The emissions.US EPA/WHOEPA/WHO2.1 Note:relevant as a basisfor selection of factors Williamsto be usedin factor of 0.33 g/km can be used -as an South-EastAsian cities. estimate for such vehicles..-..-- ....-- ..--- ..---...... ---..--....- - * Utility trucks: Although the VECP study (Manila) uses 0. 12 g/km, the EPA factor of 0.33 g/km was selected for such vehicles, taking into account generally poor maintenance in South-East Table 2: Selected emission factors Asian cities. (glkm) for particles from road * Heavy duty trucks: Only the USEPA has given an vehicles used in URBAIR estimate for such vehicles, 0.33 glkm, the same as Vehiclesclass Gasoline Diesel for passenger cars and utility trucks. Passengercars/taxies 0.2 0.6 * 3-wheelers, 2-stroke: The USEPA and WHO Utilityvehicles/light trucks 0.33 0.9 suggest 0.2 g/km for such vehicles. Motorcycles/tricycles 0.5 * Motorcycles, 2-stroke: The Weaver report supports 2.0 the 0.21 9/km emission factor suggested by USEPA/WHO. In the VECP Manila study a factor of 2 g/km is suggested. This is the same factor as for heavy duty diesel trucks, which seems much too high. Visible smoke emissions from 2-stroke 2- and 3-wheelers is normal in South-East Asian cities. Low quality oil as well as worn and poorly maintained engines probably both contribute to the large emissions. The data base for selecting a representative emission factor is small. In the data of Weaver and Chan (1993), the highest emission factor is about 0.55 g/km. URBAIR-Manila 171 For URBAIR, we choose a factor of 0.5 g/km. Realizing that this is considerably higher than the factor suggested by USEPA, we also take into consideration the factor 2 g/km used in the VECP study in Manila, which indicates evidence of 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 9/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 glkm. 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% 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) Emissionfactor Oil. The particle emission factors Uncontrolled Controlled suggested by USEPA (AP 42) are taken Utilityboilers as a basis for calculating emissions from Residualoil' combustion of oil in South-East Asian Grade6 1.25(5)+0.38x 0.008(ESP) cities. The factors are given in Table 3. Grade 5 1.25 x 0.06 (scrubber) Grade4 0.88 x 0.2(multicyclone) IndustrialVcommercialboilers Residualoil (asabove) x 0.2(multicyclone) Distillateoil 0.24 REFERENCES Residentialfurnaces Distillateoil 0.3 Baker, J., R. Santiage, T. Villareal, and Note:S --Sulfurcontent in % byweight. M.Walsh. 1993. "Vehicular a) Anotheralgorithm for calculating the emission factors is as M.Walsh. 1993. "Vehicular follows:7,3xA kg/m 3, whereA is the ash content of the oil. emission control in Metro Source:USEPA, AP 42 (1985). 172 Appendix 5 Manila." Asian Development Bank. PPTA 1723. Manila. Bosch, J. 1991. "Air quality assessment in Medan." Extract from Medan urban transportation study. Washington D.C., World Bank. 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. World Health Organization (WHO). (WHO/PEP/GETNET/93. I -A). Geneva. Larssen, S. and J. Heintzenberg. 1983. "Measurements of emissions of soot and other particles from light duty vehicles." (NILU OR 50/83). Lillestrom. (In Norwegian.) Rajbahak, H.L. and K. M. Joshi. 1993. "Kathmandu Valley vehicular transportation and emission problems." Metropolitan Environment Improvement Program. Urban Air Quality Management Workshop (URBAIR), December 2, 1993. Manila. U.S. Environmental Protection Agency. 1985. "Compilation of air pollutant emission factors" Fourth edition, Supplement A, EPA (Environmental Protection Agency, AP-42). Research Triangle Park, NC. 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." Atmospheric Environment., 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. Atmospheric. Environment, 23, 2647-2662. APPENDIX 6: POPULATION EXPOSURE CALCULATIONS POPULATIONEXPOSURE CALCULATIONS Methodology An estimate of the exposure of the population of Metro Manila to air pollution concentrations can be arrived at only through application of dispersion models, and on the basis of an emissions survey and the results of air pollution monitoring. The data base for making an exposure estimate for Metro Manila, under present conditions, is not quite complete. The most important shortcoming is that there are virtually no data on emissions from industrial processes and from refuse burning. Also, the data base on meteorological measurements in Metro Manila is not entirely consistent. There is a substantial data base on air quality measurements. However, more frequent measurements would be desired, and also a more stringent definition and location of measurement sites (city background/street site/industrial hot spot site). However, the existing data base is sufficient for producing an exposure estimate. We use the survey of emissions from road vehicles ("traffic") as a basis (see Appendix 1). Based on the traffic data supplied, and the population distribution, we consider the spatial distribution of traffic emissions which has been produced, as being of sufficiently good quality. The methodology used is as follows: 1. Emissions of car exhaust were distributed in the km2 grid net, based on: * road vehicle and traffic data, * total fuel consumption, * population distribution in the km2 grid net. 2. Annual average concentrations of car exhaust compounds were calculated for each km2. based on meteorologicaldata for the Port Area meteorologicalstation. These calculated concentrationsrepresent the general "city background"concentrations in each km2. 3. The car exhaust concentrationfield was adjustedupwards, applying a factor equal to the ratio betweenthe total emissionsof all known area sources (traffic,fuel combustion,construction, refuse burning) and the traffic emissions. A backgroundvalue of extra-urbanpollution concentrationswas added: 173 174 Appendix 6 Carea= C(traffic, fuel, refuse, construction) + Cbackgr Ctrafflc The same factor was applied over the entire area. 4. Each inhabitant is given, as his "exposure value," the concentration calculated for the km2 grid square where his home is situated. Based on this, a basic exposure curve (number of people exposed to concentrations higher than certain values) is constructed. 5. Measurements at the DENRINCR sites indicate increased concentrations in industrial areas (e.g. Valenzuela, Pasig). Industrial areas are dispersed throughout the Metro Manila region. This additional industrial pollution exposure is accounted for by giving 50% of the people in each concentration interval an added concentration value. 6. The increased concentrations close to the main road system are taken into account in the exposure curve by giving roadside residents, commuters and "workers on the road" (drivers, policemen, etc.) an additional concentration value, estimated on the basis of the VECP/ADB measurements at roadside sites. Calculation of population exposure to air pollution in Metro Manila The methodology described above is followed and gives the results shown in Table 1. The table gives: Table 1: Calculated population exposure to TSP (annual average) in Metro Manila, present conditions (1992) C C Population Additional Populationexposure Additional Resulting traffic areasourcesa + exposure,area exposuredue to areasources + industry exposure due to population pg/l3 background sources industryW 10'inhab. roadside exposurec 3 plmg 10' inhab. 10'inhab. 10'inhab. 10'inhab. 275 A = 65 65 >40 205-225 50 50 B = 300 350 35-40 180-205 210 140 370 670 C/3= 800 1,470 30-35 160-180 550 370 250 1,030 -D 570 25-30 140-160 1,470 250 240 1,220 -D 760 20-25 115-140 1,010 240 250 750 C/3-D 1090 15-20 95-115 940 250 460 C/3-D 800 10-15 75-95 1,000 1,000 -D 540 <10 30-75 1,470 1,470 -D 1,010 Sum 6,650 6,655 Note: a) Areasources: Traffic + industriaVcomm.fuelcombustion + refuse buming + construction. Trafficemissions = 23% of total area source emissions. b) 25%of inhabitants ineach km 2 is givenan additional 20 pg/m3. 25%of inhabitants in each kM2 is givenan additional 40 pg/m3. c) A: No.of roadside residents = 65,000, exposed to an estimated 275 pg/rm 3; B: No.of drivers/policemen = 300,000, exposed to anestimated 220 pg/m3; C: No.of road commuters = 2,400,000, exposed to anestimated 185/135/100 pg/rm3 (33% of the 2,400,000 ineach of the threeconcentration levels); D= (A+B+C)/6:The A, B,and C inhabitantsare moved from the lower to the higher exposure classes. URBAIR-Manila 175 1. The number of inhabitants living in grid squares with average TSP concentrations (C) within various ranges. 2. The estimation of additional exposure due to industrial emissions and road exposure, and the resulting total exposure. Additional exposure due to roadside exposure (on and near roads) is calculated by the following method: 1. The average on-the-road TSP concentration (annual average) is estimated to be 350 ,g/m 3 based on the road and TSP data in Table 2. 2. The following categories of people are given the following exposure: Drivers/policemen: - Working hours (8 hrs): 350 ,ug/m3 - Rest of day (16 hrs): 150 pg/M3 - Average: 220 ua/M3 Road commuters: While commuting Rest of day Average (2 hrs.) (22 hrs.) 3 - High exposure (plg/m) 570 150 185 3 - Medium exposure (pg/M ) 300 120 135 3 - Low exposure (pg/m ) 220 90 100 Residents near roads: 3 - Average road side exposure: 350 Pg/M - Average city background: 1501pg/m3 The average resident near roads is given the Table 2: Estimated on-the-road TSP average exposure between road side and city concentration(annual average) as a background,i.e. 275 pg/m3. functionof AADT (ehicles/day) 3. The number of individuals in each category of AADTon Manila people exposedto or near the main road MainRoad Network Estimatedon-the-road network is estimated as described in Table 3. It AADT km TSPconcentration (pg/r') is obvious that these are very rough estimates, 120-140,000 11 570 but they are believed to be of a realistic order of 100-120,000 6 500 magnitude. 80-100,000 16 430 60-80,000 30 360 With addition of Policemen and other drivers, the 40 60,000 69 290 no. of "road workers" daily exposed to road <20,000 150 concentrations for several hours is estimated to be 300,000. Table 3: Estimated number of drivers/policemen exposed Commuters to or near main road network Numberof vehicles Numberof drivers Numberof persons * No. of person trips daily: on roaddaily exposed 17.7 million (TTMM, 1993), Jeepneys 50,000 2.0 100,000 * Traffic activity on the main Buses 5,000 2.0 10,000 road network: 50% of total, UVs 200,000 0.5 100,000 * On the average each person Tricycles 20,000 1.0 20,000 does 3-4 trips per day. Total 325,000 255,000 176 Appendix 6 This gives an estimate of 2-3 million people commuting on the main road network every day, spending a total of some 1-2 hours per day "on the road". In the exposure calculation model for Table 2, the figure of 2.4 million was used as an estimate of the number of road commuters, distributed equally between high, medium and low road exposure, as previously calculated. Roadside residents * Length of main roads with AADT <40,000: 130 km, * Length of main roads with residents alongside: 50% of the above, with 50% roadside house coverage, * residents per 10 meter roadside. This gives an estimate of 65,000 roadside residents. APPENDIX 7: SPREADSHEETS FOR CALCULATING EFFECTS OF CONTROL MEASURES ON EMISSIONS AND EXPOSURE EMISSION SPREADSHEET The spreadsheet is shown in Figure 1 and 2. (Examples: TSP and PMIOemissions, Metro Manila, Base Case Scenario, 1992.) Table I gives explanation for the rows and columns in the spreadsheet. Figure 3 shows emission contributions for TSP, in absolute and relative terms. The purpose of the spreadsheet is to calculate modified emission contributions, due to control measures, such as: * new vehicle technology; * improved emission characteristics, through measures on existing technology; * reduced traffic activity/fuel consumption; and * other. The emissions are calculated separately for large point sources (with tall stacks) and for area sources and smaller distributed point sources. The reason is that air pollution concentrations and population exposures are calculated differently for these two types of source categories. Columns: 1. 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. 2. F, T: Amount of "activity"- - T (vehicle km) for traffic activity; - F (m3 or ton) for fuel consumption in industrial production. 3. qT, qF: Base case emissions, tons, calculated as product of columns a) and b). 4. fq, fF, fT, f-: Control measures. Relative reduction of emission factor (fq), amount (fF, fl) or other (f-) resulting from control measures. 5. qF fq fF f-: Modified emissions, due to control measures. 6. d (qF fq fF f-): Relative emission contributions from each source, per source category: - vehicles - fuel combustion - industrial processes 177 178 Appendix 7 Figure 1: URBAIR spreadsheetfor annual emission calculations, TSP scenario, 1992 t i_ ut _ ce _k _"M11601 ao LARGEPOINT SOUJRC q F qF ^ F t. qF1qVft QF4F t qF VW6q O_W1 m_ _ 1-0 1410 2.12 10 1.00 1.00 2.12 1000 _~ t P" _w L eta ~oat Lt:1 iu. AREASOURCES AND DISTRIBTED POSITSOURCE_ VehkAe 4 T qT ffT t. qTtqfml1 qTf mT IdT f4ftI t Pi V re__ _ _ .2 Et l O - 1 Onsbw cmw c-in Emt 020 2.92 am 1 1 0 t$ 1.0 NOW 0.05 0.00 0.0 1 1 I 0. 0.0 0.0 UV ___ OM 315 1.15 1 1 1 1.1 112 2.0 NMw 0.05 0. 0. 1 o o0. 1 s 0.00 tC,rc E 2 0.50 0S 02t 1 I 1 025 32 01 4 0.10 O. 0. 1 1I0. 0. Mm 2 ODD O I 1 1 . 0.0 0.0 4 0mot 1 1 1 0. 0.o 'frhdLbA EtE .6M 022 0.l5 1 1 1 0.1 1.7 02 NM 0o.0 1 1 1 0a 0.0 0.0 Swgmbw 220 220 3.6 ~~domkwen~~~~~fl~~emna. ______~~~~~~~~~1.00______ Tamd Est 0.5 02S 0.1 1 1 1 01 2 0.3 NM 02 am 0. 1 1 1 0.a 0. 0.0 Ep11 0.9 1. t E10 1 1 1 1S 17.7 2.6 NM 0.5 G O 1 1 1 o a 0A UV 0i. 116 1.16 1 1 1 1.16 1I s1 NM 01 0. 0O. I 1 I 0o 0 Tnradolo EAI 2.0 1A 30 1 1 1 42.7 l I NOW 0.7 C0 0. 1 1 1 0 0.0 00 9uinnusI l6.71 6.7 11.1 Ihte sN I&m m _ diesl _ .___ _ _ 1__.a _ _ sum 1W .N.miU OSt U1 100.0 17 NoSe ewffomoi few "neaa N Wl ei d ii ______1 ______tt_os. T 1.0 1251 12S1 1 1 1 12S51 20.7 am be "mWin .zt.eA24 2ttA:* 21A* _ omeooloomwm.)II . tow lddes -______1.. FUhIedoluautO 4 F qF fq f 1. f4qfr t FqqF1qhaei qdq FVW h,djm.t_tm 5.10 2a 143 1AC 1.0100 1 141 54.7 23S 140 ISO 22 1JO 1AI0C 220 1.t 42 Kermos 0.06 312 0.02 1.00 1C00 1 002 0.1 0.0 UtO 0.06 tt2 0.04 10 100 1.Q 004 02 0.1 Wed . o. 1.00o 1.00 1 o0 0. 0.0 cow am 1.00 120 I a 0. 0.4 Dung ______0.00 1.00 1.00 1.M 0. 0. 0.4 suam Maes00 0.06 0.4 al1 t_t m_ Sm N.im~~~~~~~~~~~~~m_ d___ 15~~~~a_ __ *A1.0 _ _ ¶00.0 as Wt_-~~~~ -=- 1lt- - 0 1 1 1 00. O.0 1 1 1 0st O,t 0.1 Xt ~~ ~ ~ ~ ~ ______1 1 1 6t 10o.Z 9. _ _ _ 4 tUt6 100t.l _ _t_ _~iedomp. ___ __ Mlaeslimib_ug q U OM IQ OA . qiAqUI "iqMfneo j,PqM 1qEf4t 6t 1 1 1 6Ct 37 its t______1 1 1 1 10,t ______li IsWm ttut tlLo .Nuw _ __ gm GMSwoonauuuse, g3aoL'Sacr.GaS A Note:The emission factor for resuspension was set to 1.0glkm, while 2.0 glkm has been assumed to be more realistic, and hasbeen used throughout the URBAIR study. thus, emission figures in thisexample spreadsheet deviates from those in other placesin theManila report. URBAIR-Manila 179 Figure 2: URBAIR spreadsheetfor annual emissions calculations, PMIo scenario, 1992 Emi"won AmoAn Bm Cnlrol mes 11_ted ta hl factor cx_ _Mbam _ mhbnsu ______S _ _ __d h _ _ _ LARGEPOINT SOURCES_ _ q F qF Sq F F- qF qtFf (dqFiqfFt) pdqFltq Fit %k9f3) s11E3m (IrE3e91 10E31s) Ip-M) 0w..1 Powerpanbt 1.40 1662 2.33 1.00 1.00 1.00 2.33 100.0 0.00 0.0 &n pdnt t 2 . 235 100.0 tad.dph t_ 1.00 AREASOURCES AND DISTRIBUTED POINT SOURCES Vehicles q T qT - q tT F qTtq flf (dqTtq f) (dqTtq f) _ rghm~~~~~~~~~~~~k)(1EOfm) 310E3 S) (10UE3) %W"e) p"X ~eahe.zlmst Cars Exist 0.20 2.92 0.8 1 1 1 0.58 6.6 1.5 New 0.05 0.00 0.00 1 1 1 0.00 0.0 0.0 UV Exist 0.33 35 1.18 1 1 1 t.18 132 2.9 Now 0.05 0.00 0.00 1 1 1 0.00 0.0 0.0 MC/TC Exit 2 0.50 0.57 0.29 1 1 1 0.29 3.2 0.7 4 0.10 0.00 0.00 1 1 1 0.00 0.0 0.0 New 2 0.00 0.00 1 1 1 0.00 0.0 0.0 4 0.00 0.00 1 t t 0.00 0. 0.0 Trudobue ExisL 0.68 0.22 0.1S 1 1 1 0.15 1.7 0.4 NOw 0.00 1 1 1 0.00 0.0 0.0 Sum g9xoln 2.201 2.20 5.6 %Siied*mfissionuahmiasions,gne _ _ __ 1.00 Dieel extatat~ Tax Exiwt 0.6 029 0.17 1 1 1 0.17 2.0 0.4 New 0.2 0.00 0.00 1 1 1 0.00 0.0 0.0 J epney Exist. 0.9 1.75 1.58 1 1 1 1SI 17.7 3.9 New 05 0.00 0.00 1 1 1 0.00 0.0 0.0 V Exist 0.9 1.29 1.16 1 1 1 1.16 13.0 2.9 New 0.5 0.00 0.00 1 1 1 0.00 0.0 0.0 Tnwdchua Exist 2.0 1.90 3.80 1 1 1 3.80 42.7 95 New 0.7 0.00 0.00 1 1 1 0.00 0.0 0.0 Sum cl 6.71 6.71 16.7 Moddied*mhonsoeeions, diel 1G00 Sumtotl vetile exhaust 6.91 8.91 100.0 22.2 Mailed .nissioherWm"aao , totl vehildh exhaust ______1.00 ______fleeuwpeaednn 0.60 12.51 626 1 1 6.26 15.6 Sn td vahkke xhemp.) 151 15.16 37.8 imbd egdinlmwiamhds, :,tb r_alo.s) 1.00 FuelCombwtlon q F qF tq fF F- qF tq fi f dqFfq WfoI pcqFlq fFfiot ______3) l1 E3 lndJiomurcial 4.30 2820 12.13 1.00 1.00 1.00 12.1a 90.1 30.2 DOF SndJcommldoemsL 0.70 1820 127 1.00 1.00 100 127 95 3.2 O_lc Krosrne 0.06 312 0.02 1.00 1.00 1.00 0.02 0.1 0.0 LPG 0.06 682 0.04 100 1.00 1.00 0.04 0.3 0.1 Wood 0.0 1.00 1.00 1.00 0.00 0.0 0.0 Coal 0.00 100 100 1.00 0.00 0.0 0.0 Durq_ 0.0 1.00 1.00 1.00 0.00 0.0 0.0 Sum domestic 0.06 0.0 0.4 0.1 Modied en*ihaslenjeissiondomatsic 1.0l S tsum _ 13A6 1S3AS 100.0 3t5 lait__ .halmw,_ .h.u,tmuI 1.00 ______1 Industrlal proc.aas q F qF bq F t. qF q fFt dqF q tF)ind. (dqFSq fF*td t 1 1 O.Ot O,t 0-~ O.<~~0~1 0 1 1 1 0.00 0.0 0.0 TOW 3 1 1 1 3.00 100.0 75 UM eduatmi Procesede 3 "a 100.0 7.5 1111ed I" p_ _ 1.00 lao.lwmsous q .A qM Sq SM t- q 1Mft dqMtqfMtnsao pdqMtq 1MMt" *mh _ 6 1 1 1 6.00 70.6 150 Camb_JeUal 2.5 1 1 1 2.50 29.4 62. barn.dmauluseogm 6.5 8.55 100.0 21.2 b_dmhdm adrnImms,n,Smgv 1.00 ' 3acIcpm und ______6 ______6 00 ______00 unrmwn .. ____ .______Sumtotal ama acurcaw,mcl. "Bakgr." 4. 40.1 1Ait Uo4fl.d amlestonernimieons.totl am sourcs 1.00 180 Appendix7 Figure 3: Emission contributionsfrom various source categories 16 14 OUdiisd 12 ;10 Large o1Xfim FDiesel Rewasp. F F Fuel w. Prsent Mod WLarg poit mams DIGasolin *Diesel O Roea~p EDOF El kw.Pr -miscellaneous 7. d (qF fq fF f-): Relative emiissioncontributions, all categories summed. Rows: 1. Separate rows for each source type and category, "existing" and "new" technology. 2. "Background"-Fictitious emissions, corresponding to an extra-uirbanbackground concentration 3. Modified emission/emissions-Ratio between modified and base case emissions. ExposuRE CALCULATIONS Figure 4 shows the spreadsheet for calculating population exposure to air pollutants. The spreadsheet gives both base case exposure, and modified exposure due to control measures. (Example shown: TSP exposure, Metro Manila, base case scenario, 1992). The exposure calculation takes into account residence exposure due to area distributed emissions, additional exposure due to industrial process emissions, and additional road/roadside exposure. The methodology is described in Appendix 6. The columns and rows of the spreadsheet are as follows: Figure 4: Spreadsheetfor population exposure calculations, annual average TSP (pg/r3), extra urban background(30 pg/m3) ROAD EW. _ Cawao Conc. Contiro measures Mod. conc. Exposuroe,% of tow poption Base case Modlied Vehicles+ Industial Vehicles+ Vehices+ Vehicles+ fue pwocesses fuel+ fuel+ backgr.fuel + backgr. badaround Base case Modified t1 12 Roadside residents: 65000 65000 275 1 1 275 1.0 1.0 WRoad workerg": 300000 300000 220 1 1 220 4.5 4.5 Commuters C1: 800000 800000 185 1 1 155 12.0 12.0 C;2: 800000 800000 135 1 1 135 12.0 12.0 C3: 800000 800000t 00 1 1 100 12.0 12.0 RESIDENCEEXP. Total popultion: 6655000[ Base case Concentratlon Conlroi measures Moi. conc. Exposre % totalpopulation Vehices Vehicles+ Vehicles+ Industral Vehices+ Vehicles+ Add,due to industrial Adddue toroadside Combined Combinedcumutative fuel+ fuel processesfuel + fuel+ backgr.pmcsses exposme badnround I _backoround Base case Base case Modified Base case Modilied Base case Modified Base case Modiiied x v t1 f2 z o P q r s t u v w 250 1 1 250 1.0 1.0 1.0 1.0 1.0 1.0 225 1 225 0 0 0.0 0.0 0.0 0.0 1.0 1.0 40 205 1 1 205 0.0 0.8 0.8 4.5 4.5 5.3 5.3 6.3 6.3 35 180 1 1 180 3.2 6.9 6.9 12.0 12.0 22.1 22.1 28.4 28.4 30 160 1 1 160 8.2 7.3 7.3 -6.9 -6.9 8.6 8.6 37.0 37.0 25 140 1 1 140 22.1 -3.8 -3.8 -6.9 -6.9 11.4 11.4 48.4 48.4 20 115 1 1 115 15.2 -3.9 -3.9 5.1 5.1 16.4 16.4 64.8 64.8 15 95 1 1 95 14.2 -7.3 -7.3 5.1 5.1 12.0 12.0 76.7 76.7 10 75 1 1 75 15.0 0.0 0.0 -6.9 -6.9 8.1 8.1 84.8 84.8 0 30 1 1 30 22.1 0.0 0.0 -6.9 -6.9 15.2 15.2 100.0 100.0 _ - - - -~~~~~~~~~~~~~~~~~o 182 Appendix 7 Road exposure: 1. Categories: - Roadside residents-people livingclose to the main road system. - Road workers-public transportand truck drivers,.policemen, etc. spendingseveral hours on the road every day. - Commuters-people travelingon roads to work, shoppingetc., spendingI2 hours on the road daily The number of people in each categoryis estimatedfor base case and other scenario ("Modified"). 2. Concentration:Estimated average concentration that the categoryis exposedto. Base case 3. Control measures: relative reductionof emissionsfrom - area distributedsources (vehicles- fuel combustion+ construction),f 1; - industrialprocesses, f2. 4. Modifiedconcentrations: Base case concentrationx fl x f2. 5. Exposure:Percent of the total populationexposed on the road, for each category - base case - other scenario ("Modified"). Residence exposure: 1. Base case concentration x: Vehicles: Calculated concentration, from traffic emissions y: Area distributed sources: y = x total area distributed emissions + Cb traffic emissions 2. - f 1: Relative reduction in area distributed source emissions. -f2: Relative reduction in industrial processes emissions. 3. Modified concentrations: - z= [y-Cb]fJ +Cb 4. Exposure: - o. Exposure due to area distributed sources and background; percentage of total population with residence in the grids squares with calculated concentration, due to area-distributed sources + background. within the given concentration ranges. - p,q: Added exposure due to emissions from industrial processes (see Appendix 6). - p: base case; - q: scenario ("modified"): q=pxf2, i.e. the number of people given extra exposure due to industrial emissions is reduced proportionally to the industrial emission reduction. - r,s: Added exposure, due to road/roadside exposure. (Values are taken from the "road exposure" table). r: base case - s: scenarios ("modified"). - t,u: Combined exposure, area + industrial + roadside - t: base case: t = o+p+r, - u: scenario: u = o+q+s. - v,w: Combined exposure as above. Figure 5 shows the cumulative population exposure curves, as follows: * base case total exposure curve (v vs y) * for the given scenario: - residentialexposure curve due to area distributedsources (o vs z) URBAIR-Manila 183 Figure S: Cumulative population exposure, Metro Manila 20 90~-- ~ ~ ~ 2 100- _*, s .0~~~~~~~~~~~~~~~~~~~~~~~~~. : 80- 4-9 ;> ~~~ ~ ~~170190 210 230 250 70-- 10--~~ ~ ~~~~~1 \ 60 - * \ h~~~~~~~~~~~~Ttalexposure, a) *+*,* x ~~~~~~~~~~~~~residence,idustry Y 50- /+ **X/ ~~~~~~~~~~~~androadhot spot 2 ~~~~~~~Exposureat rsdnw, * ^ - 40 -- dueto areasoure, * C ~~~~~~~~industryhot spotadd* =3 30--."/o. 0L 2 Exposureat residences t l 20O dueto areasources o ig 0 so 100 150 200 250 L ~~~~~~~~~~~Concentrabon(lig/M3)l -residential exposure curve due to area distributed sources + industrial process emissions (o+q vs z) - total exposure curve (w vs z). The insert in Figure 5 shows the details at the high exposure end of the curves. APPENDIX 8: PROJECT DESCRIPTIONS, LOCAL CONSULTANTS PROJECT DESCRIPTION REGARDING AIR QUALITYASSESSMENT 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 Metro Manila: * Meteorological measurements in and near the city. * Activities/population data for Metro Manila: - 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. 185 186 Appendix 8 * Air pollution emissions - Emission inventory data (annual emissions) 1. per compound (SO2, NO,, particles in size fractions: <2 pg, 2-10 pg, >10 pg, 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 Metro Manila. 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-Manila 187 PROJECTDESCRIPTION REGARDING DAMAGE ASSESSMENT AND ECONOMIC VALUATION URBAIR:TOPICS FOR RESEARCH Physical Impacts 1. Describe available studies on relations between air pollution and health. 2. Decide on the acceptability of dose-effect relationships from the United States. a) Mortality: 10 Pg/M3 TSP leads to 0.682 (range: 0.48-0.89) percentage change in mortality. b) Work loss days (WLD): 1 pg/m3TSP leads to 0.00145 percentage change in WLD. c) Restricted activity days (RAD): 1 pg/m3 TSP leads to 0.0028 percentage change in RAD per year. d) Respiratory hospital diseases (RHD): 1 pg/m3 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 pg/m3 TSP leads to 12.95 (range: 7.1-18.8) cases of ERV per 100,000 persons per year. f) Bronchitis (children): 1 pg/M3 TSP leads to 0.00086 (range: 0.00043-0.00129) change in bronchitis. g) Asthma attacks: 1 pg/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 pg/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]old-[Pb in blood]new) with [Pb in blood] is blood lead level (pg/dl). j) Coronary heart disease (CHD): change in probability of a CHD event in the following ten years is: [1 + exp - (-4.996 + 0.030365(DBP)})j- 11 + exp - (-4.996 + 0.030365(DBP2 )11- i) Decrement IQ points: IQ decrement = 0.975 x change in air lead (pg/M3) Calculation example: * Let population be 10 million people. * Let threshold value of TSP be 75 pg/r 3 (the WHO guideline). * Let the concentration TSP be 317 pg/rm3. =* Concentration-threshold = 317 - 75 = 242 = 24.2 (10 pg/m3). > Change in mortality = 24.2 x 0.682 = 16.5%. * Let crude mortality be 1 % per year. X 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. 188 Appendix 8 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 ca. 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 ca. 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 U.S. 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 235 pg/m3 to 115 Pg/m3. This would imply a benefit of US$0.35 per household per Pg/m 3 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-Manila 189 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. a 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. GERMANY ISRAEL NEPAL PORTUGAL SWEDEN AB Distributors of COLOMBIA UNO-Vedag YozmotLiterature Ltd. EverestMedia Intemational Services (P) Lt. 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