TA No. 4415-AFG Kabul Air Quality · PDF file · 2016-09-01TA No. 4415-AFG Kabul Air Quality Management Draft KAQM Strategy Report January 2007 ... SPREADSHEET FOR CALCULATING EFFECTS

2006-1220/KAQM-Report

Asian Development Bank

National Environmental Protection Agency

Islamic Republic of Afghanistan

TA No. 4415-AFG Kabul Air Quality Management

Draft KAQM Strategy Report

January 2007

ENGCONSULT LTD. 21 Queen Street E., Suite 302

Brampton, Ontario, L6W 3P1 Canada Tel: 905 455 7892, Fax: 905 455 2351

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TABLE OF CONTENTS ABSTRACT ACKNOWLEDGEMENTS ABBREVIATIONS AND ACRONYMS EXECUTIVE SUMMARY I. BACKGROUND INFORMATION...........................................................................................1

1.1 SCOPE OF THE STUDY ..............................................................................................1 1.2 GENERAL DESCRIPTION OF KABUL VALLEY AND THE AIR POLLUTION SITUATION ...............................................................................................................................2 1.3 DATA SOURCES..........................................................................................................3

1.3.1 Previous Studies .......................................................................................................3 1.3.2 KAQM Data Collection ..............................................................................................4

1.4 SUMMARY OF DEVELOPMENT IN THE KABUL VALLEY..........................................5 1.5 POPULATION ...............................................................................................................5 1.6 FUEL CONSUMPTION .................................................................................................6 1.7 INDUSTRIAL DEVELOPMENT.....................................................................................6 1.8 ROAD VEHICLE FLEET ...............................................................................................7

2 AIR QUALITY ASSESSMENT...............................................................................................8 2.1 AIR POLLUTION CONCENTRATION...........................................................................8

2.1.1 Concentrations in Kabul ............................................................................................8 2.2 AIR POLLUTANT EMISSIONS IN KABUL VALLEY .....................................................9 2.3 DISPERSION MODEL CALCULATIONS....................................................................11

2.3.1 General Description of Topography and Climate ....................................................11 2.3.2 Dispersion Conditions .............................................................................................12 2.3.3 Dispersion Model Calculations, City Background....................................................17 2.3.4 Pollution Hotspots ...................................................................................................25 2.3.5 Population Exposure to Air Pollution .......................................................................25

2.4 SUMMARY OF AIR QUALITY ASESSMENT, KABUL VALEEY.................................28 2.4.1 Air Pollution Concentrations ....................................................................................28 2.4.2 Air Pollutant Emission Inventory..............................................................................29 2.4.3 Population Exposure to Air Pollutants .....................................................................29 2.4.4 Visibility Reduction ..................................................................................................29

2.5 IMPROVING AIR QUALITY ASSESSMENT...............................................................30 2.5.1 Main Shortcomings and Data Gaps ........................................................................30

3 AIR POLLUTION IMPACTS ................................................................................................32 3.1 INTRODUCTION.........................................................................................................32 3.2 IMPORTANT IMPACTS IN KABUL VALLEY ..............................................................32

3.2.1 Mortality...................................................................................................................33 3.2.2 Morbidity..................................................................................................................33

3.3 VALUATION OF HEALTH IMPACTS..........................................................................33 3.4 HEALTH IMPACT AND ECONOMIC DAMAGE BY SOURCE CATEGORY ..............34 3.5 CONCLUSIONS..........................................................................................................34

4 ABATEMENT MEASURES: EFFECTIVENESS AND COSTS ............................................36 4.1 INTRODUCTION.........................................................................................................36 4.2 TRAFFIC .....................................................................................................................36

4.2.1 Implementation of Scheme for Inspection & Maintenance ......................................36 4.2.2 Improving Fuel Quality ............................................................................................37 4.2.3 Adoption of Clean Vehicle Emission Standards ......................................................39

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4.2.4 Improved Abatement/ Other Propulsion Techniques ..............................................40 4.2.5 Addressing Resuspension.......................................................................................40 4.2.6 Improvement of Traffic Management ......................................................................41 4.2.7 Construction and Improvement of Mass-Transit Systems.......................................42

4.3 INDUSTRIAL COMBUSTION (EXCLUDING BRICK MANUFACTURING).................42 4.4 BRICK MANUFACTURING.........................................................................................42 4.5 DOMESTIC EMISSIONS AND REFUSE BURNING...................................................43 4.6 CONCLUSIONS..........................................................................................................44

5 ACTION PLAN.....................................................................................................................45 5.1 ACTIONS TO IMPROVE AIR QUALITY AND ITS MANAGEMENT ...........................45

5.1.1 Actions to Improve Air Quality .................................................................................45 5.1.2 Actions to Improve Air Quality Management System ..............................................47

6 EXISTING LAWS AND INSTITUTIONS ..............................................................................52 6.1 LAWS AND REGULATIONS ON AIR POLLUTION ....................................................52 6.2 INSTITUTIONS INVOLVED ........................................................................................52

APPENDICES APPENDIX 1: AIR QUALITY STATUS, KABUL VALLEY APPENDIX 2: PROPOSED AMBIENT AIR QUALITY STANDARDS APPENDIX 3: EMISSION INVENTORY APPENDIX 4: EMISSION FACTORS, PARTICLES APPENDIX 5: SPREADSHEET FOR CALCULATING EFFECTS OF CONTROL MEASURES ON EMISSIONS APPENDIX 6: PROEJCT DESCRIPTION FOR LOCAL CONSULTANTS

LIST OF TABLES

Table 1: Vehicle Data of Kabul .....................................................................................................7 Table 2: Summary of NILU Air Quality Data. ................................................................................8 Table 3: Total Estimated Annual Emissions in Kabul, 2005 .......................................................10 Table 4: Mean Monthly Climatic Data of Kabul...........................................................................12 Table 5: Annual Wind Speed/Direction Frequency Matrix of Kabul ............................................13 Table 6: Meteorological Input Parameters for Dispersion Modeling ...........................................17 Table 7: USEPA AQI Classification and Population Exposure ...................................................26 Table 8: Modeled 24 hour average concentrations in µg/m3......................................................29 Table 9: Proposed Actions to Improve Air Quality Assessment..................................................30 Table 10: Estimated increment in annual health effect associated with unit change in PM10 .....33 Table 11: Estimates of Mortality and Health and Their Valuation ...............................................34 Table 12: Source Wise Economic and Health Benefits Due to Emission Reductions ................34 Table 13: Implementation of an Inspection and Maintenance Scheme ......................................37 Table 14: Improving Diesel Fuel Quality .....................................................................................38 Table 15: Adoption of Clean Vehicle Standards .........................................................................39 Table 16: Introduction of CNG to Replace 50% of Gasoline Consumption ................................40 Table 17: Manual Sweeping of Roads. .......................................................................................41 Table 18: Action plan of abatement measures ...........................................................................45 Table 19: Additional measures for short- to medium-term introduction ......................................46 Table 20: Actions to Improve AQMS...........................................................................................47

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LIST OF FIGURES

Figure 1: Air Quality Management System .................................................................................viii Figure 2: Location Map of Kabul ...................................................................................................3 Figure 3: Locations of Air Quality Monitoring Stations (NEEDS CORRECTION) .........................4 Figure 4: Population Growth in Kabul ...........................................................................................5 Figure 5: Annual Fuel Consumption in Kabul ...............................................................................6 Figure 6: PM10 Concentration Variation at Station 1 .....................................................................9 Figure 7: PM10 Concentration Variation at Station 2 .....................................................................9 Figure 8: Contribution of Different Sources to Emissions of PM10, NO2, SO2 and CO................11 Figure 9: Monthly Wind Roses of Kabul, from January to June, 2005........................................14 Figure 10: Monthly Wind Roses of Kabul, from July to December, 2005....................................15 Figure 11: Season and Annual Wind Roses of Kabul for the Year 2005 ....................................16 Figure 12: Distribution of Modeled 24-hr Average PM10 concentrations for all sources. (Below:

PM10 distribution over digital elevation model of Kabul) .....................................................18 Figure 13: Distribution of Modeled 24-hr average PM10 Concentrations from Brick Kilns ........19 Figure 14: Distribution of Modeled 24hr average PM10 Concentrations from Vehicular Traffic. 20 Figure 15: Distribution of Modeled 24-hr average PM10 Concentrations from Residential

Heating ................................................................................................................................20 Figure 16: Distribution of Modeled 24-hr Average NOX Concentrations (all sources)................21 Figure 17: Distribution of Modeled 24hr-average NOX Emissions from Vehicular Traffic. .........22 Figure 18: Distribution of Modeled 24-hr average NOX Concentrations from Residential and

Commercial Generators.......................................................................................................22 Figure 19: Distribution of Modeled 24-hr Average NOX Concentrations from Power Plant........23 Figure 20: Distribution of Modeled 24-hr Average SO2 Concentrations (all sources). ...............24 Figure 21: Distribution of Modeled 24hr Average SO2 Concentrations from Vehicular Traffic ...24 Figure 22: Population Exposure to PM10 ...................................................................................27 Figure 23: Population Exposure to NOX.....................................................................................27 Figure 24: Population Exposure to SO2 ......................................................................................28 Figure 25: Frequency Distribution of PM10 exposure of the Kabul Population (2005).................32

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ABSTRACT

The air quality in Kabul is severely affected by various pollutant sources, the impacts of which often cause acute health problems, particularly among the old, young and those suffering from poor health. The impacts of chronic exposure to air pollutants are also likely to become apparent over time. The purpose of this Air Quality Management Report is to assist policy makers in the design and implementation of policies, and in the development of monitoring and management tools to restore air quality in Kabul. Estimates of various pollutant emissions indicate that that vehicular traffic, windblown and reentrained dust, brick kilns, residential heating during winter season, and domestic and commercial generators are the major sources of air pollution. The estimated total annual emissions in Kabul are 17,363 tons of PM10; 16,183 tons of NOX; 2,484 tons of SO2; 97,068 tons of CO; and 650,846 tons of CO2. Ambient air quality levels of PM10, NOX and SO2 in Kabul routinely exceed USEPA and WHO guidelines. Population exposure has been calculated to assess the costs of morbidity and mortality in the general population. Sixty-four percent of population is exposed to very high concentrations of 1,500 µg/m3 of PM10 and 68 percent of population is exposed to more than 120 µg/m3 of SO2. Using dose-response equations developed in the United States, it is estimated that in 2005 particulate matter pollution caused 2,287 excess deaths, 15 million restricted activity days and 49 million respiratory symptom days, in addition to other health problems. The monetary value attached to all these health impacts totaled 7,547 million Afghans. To address the air pollution problem and development of a coherent air quality management approach, this report suggests an action plan comprised of abatement measures for the short, medium and long terms. Two types of recommendations are made: institutional and technical. A single institution with a clear mandate and sufficient resources should be made responsible for air quality management in the city. In addition, capabilities for data gathering and processing should be improved throughout the city. It is crucial that gross polluters be identified, penalized and brought in to compliance on a reasonable timescale, or forced to close. Vehicle emission standards should be established and strictly enforced. The regular inspection and maintenance of vehicles is also crucial to ensuring that such standards are complied with. Clean fuels should also be used to reduce emissions from residential heating, bakeries and public wash-halls (hammams). Vertical Shaft Brick Kiln technology should be adapted to Kabul’s operating environment to reduce pollution from brick kilns. A systematic raising of awareness through the activities of educational institutions, public and private organizations is also a fundamental component of any plan for bringing about policy changes intended to reduce air pollutant emissions and impacts on human health and welfare.

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ACKNOWLEDGEMENTS

This study was funded by Asian Development Bank Technical Assistance under a grant from the Government of Denmark. Engconsult Ltd., Canada wishes to confer thanks to Dr. Ali Azimi, ADB Afghan Resident Mission for providing extensive support during the whole study period. We would like to thank National Environmental Protection Agency, Islamic Republic of Afghanistan for extending their heartfelt support in undertaking the study. Sincere thanks are due to Mr. Mark Hodges, ADB Individual Consultant for his review and edits on the report and drafting Appendix 2: Proposed Ambient Air Quality Standards and Mr. Ghulam Mohd. Malikyar ADB Individual Consultant for his support in collecting data, organizing and supporting meetings and trainings in air quality orientation and permitting. We are also thankful to Norwegian Institute for Air Research (NILU) for sharing their Kabul Air Quality Monitoring data.

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ABBREVATIONS AND ACRONYMS

ADB - Asian Development Bank NEPA - National Environmental Protection Agency

AERMET - Meteorological Preprocessor Software NGO - Non Governmental Organization

AERMOD - Air Quality Dispersion Modeling Software NILU - Norwegian Institute for Air

Research

AIMS - Afghanistan Information Management Service NOX - Nitrogen Oxides

ANSA - Afghanistan National Standardization Authority NO2 - Nitrogen Dioxide

AQI - Air Quality Index PM -: Particulate Matter

AQIS - Air Quality Information System PM10 - Particulate Matter (less than 10

microns) AQMS - Air Quality Management RAD - Restricted Activity Days CO - - Carbon Monoxide RHD - Respiratory Hospitalization Day

CO2 - Carbon Dioxide RSD - Respiratory Symptoms Day

CNG - Compressed Natural Gas ERV - Emergency Room Visits SO2 - Sulfur Dioxide

GIS - Geographical Information System TOC - Total Organic Carbon

GHG - Greenhouse Gas TSP - Total Suspended Particles

HC - Hydrocarbon URBAIR : Urban Air Quality Management Strategy in Asia

ISAF - International Security Assistance Force USEPA - United States Environmental

Protection Agency

KQAM - Kabul Air Quality Management VOC Volatile Organic Carbon

LPG - Liquefied Petroleum Gas WHO World Health Organization Units

oC - Degree Celsius KW -- Kilowatt

g/kg - Grams per kilogram KWh -- Kilo watt hour

g/kwh - Grams per kilo watt hour % - Percentage

g/km - Gram per kilometer m -- Meter

Kg - Kilogram mm - Millimeter Kg/day - Kilogram per day m/s - meter per second Kg/m3 - Kilogram per cubic meter MW : Mega watt km - Kilometer µg/m3 Micro grams per cubic meter

Currency

USD - US Dollar AFA - Afghanistan Afghani 1 USD = AFA 50 1 AFA = 0.020 USD

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EXECUTIVE SUMMARY The Kabul Air Quality Management Project 1. The government of Afghanistan with Technical Assistance from Asian Development Bank has executed the Kabul Air Quality Management (KAQM) Project. The KAQM Project was designed to assist in the development of a prioritized, phased and sustainable air quality management program and approach for Kabul that can be replicated in other Urban Areas of Afghanistan. Eight air quality monitoring stations were installed under this project, and are located in and around Kabul, to collect 24-hour average ambient air quality samples for subsequent analysis to determine atmospheric loadings of PM10, NOX and SO2. The KAQM report has been prepared based on the format of the World Bank URBAIR Project ‘Urban Air Quality Management Strategy in Asia” reports, and specifically the reports for the Kathmandu Valley, Jakarta, Metro Manila and Mumbai.

The Development of Kabul and Its Pollution Problem 2. The end of more than two decades of war in Afghanistan has resulted in a massive influx of refugees and rural peoples to large cities such as Kabul, the population of which grew by 10% per year during the period 2000 and 2005. The population of Kabul in 2005 is 3 million. 3. The war and resultant impacts; return of refugees, continuous migration from rural areas; and reconstruction activities in Kabul have caused substantial deteriorated of the ambient air quality of Kabul. Air pollution is highly visible in many if not all locations throughout Kabul and is severely impacting public health and welfare. More than 60 percent of the population has been exposed to concentrations routinely exceeding 150 µg/m3 of PM10, 120 µg/m3 of NOX and 20 µg/m3 of SO2. The highest value of 24-hour averaged PM10 recorded in Kabul, was measured in early 2004, is 704 µg/m3, and was measured at the Norwegian Embassy which is located in the heart of the city. Traffic, windblown and reentrained dust, residential heating, portable power generators and brick kilns are the major sources of air pollution in Kabul. 4. Total PM10 emissions in Kabul are estimated at 17,363 tons per year, while total NOX emissions are 16,183 tons/year and SO2 emissions are 2,484 tons/year. The calculated maximum 24-hour average concentrations of PM10, NOX, and SO2,as predicted by atmospheric dispersion modeling are 261, 241 and 37 µg/m3 respectively.

The Concept of Air Quality Management System 5. The World Bank Air Quality Management System (AQMS), as developed for URBAIR projects, is shown in Figure 1. Assessment of pollution and the potential for its control are the two major components used to perform a cost-benefit analysis. The cost-benefit analysis is an integral component of the action plan, which contains a balanced and optimized combination of abatement and control measures for short, medium, and long term enactment. 6. A successful AQMS requires the establishment of an integrated system for continuous collection and updating of air quality-related data. Such data includes:

• An inventory of air pollution activities and emissions • Monitoring of air pollution and dispersion parameters • Calculation of air pollution concentrations by dispersions models • Inventory of population, building materials and planned urban development • Calculation of the effect of abatement/control measures; and • Establishment/improvement of air pollution regulations

7. In order to ensure that an AQMS is having the desired impact, it is necessary to carry out surveillance or monitoring. This requires the establishment of an Air Quality Information System (AQIS) to inform authorities and the general public about air quality and assess results

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of abatement measures. AQIS should also provide continuous feedback to the abatement strategy process.

Abatement Measures and Action Plan 8. Measures to reduce air pollution in Kabul should focus on vehicle traffic and road dust. Traffic emissions are a clear and major source of air pollutants. Abatement measures which address other important pollution sources including windblown and reentrained dust, brick kilns and wood burning for residential heating, bakeries and hammams are also addressed in this report. Focusing on these abatement measures, an action plan was designed based on discussions with various stakeholders in Kabul, KAQM working groups and the consultants. It is proposed that the following technical and policy measures be given priority:

Implementing an inspection/maintenance scheme for vehicles, Addressing excessively polluting vehicles, Improving traffic management, Using cleaner fuel oil, Improving abatement and other propulsion techniques, Improving diesel quality and checking fuel adulteration, Fuel switching in the transportation sector, gasoline to LPG or CNG in vehicles, Adopting clean vehicle emission standard, Development of dust abatement programs and strategies, and Rehabilitating the electric trolley-bus system.

Dispersion Modeling

EmissionsAir Quality Air Pollution

Concentrations

Abatement Measures & Regulations

Control Options

Exposure Assessment

Damage AssessmentCost Analysis

Monitoring

Figure 1: Air Quality Management System

Recommendations for Strengthening Air Quality Monitoring, and Institutions 9. It is essential that institutions dealing with air quality be strengthened through clearer mandates and enforcing powers. A single coordinating institution with a clear mandate and sufficient resources must be made responsible for air quality management. The analyses presented in this report address health impacts based on average dose-effect relations derived from US cities as there is insufficient local data to support such analyses. While dose-response relationships are quite similar across various human populations, local epidemiological data should be collected and improved.

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10. Clearly, environmental risks are escalating. If pollution sources are allowed to grow unchecked, the economic costs of lost productivity resulting directly or indirectly from health impacts will escalate. While working with sparse and sometimes loosely substantiated data, this report sets out a preliminary plan that has the potential to improve the air quality of Kabul and to support the development and implementation of an effective AQMS in the future.

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I. BACKGROUND INFORMATION 1.1 SCOPE OF THE STUDY 11. The National Environmental Protection Agency (NEPA) of Government of Afghanistan with Technical Assistance (TA) of the Asian Development Bank, is preparing Kabul Air Quality Management (KAQM) Project. The KAQM Project will assist in the development of a prioritized, phased and sustainable air quality management program for Kabul that can be replicated in other urban areas in Afghanistan. The components of the Project include:

• Establishing a baseline air quality sampling and reporting system for Kabul through installing air quality monitoring stations for monitoring PM10, SO2 and NO2 at eight locations through out Kabul.

• Development of a baseline air emission inventory for point, area and mobile sources of emissions through dispersions modeling for identification and prioritization of sources and thereby deriving appropriate control measures.

• Establishing a vehicular emissions inventory system, to support development of emissions control measures and for integration with traffic planning efforts.

• Developing the framework and recommendations for an integrated, prioritized, phased and sustainable AQ program.

• Establishing linkages between specific source types, current air pollution levels, and prioritization of mitigation measures based on timing of benefits and cost-effectiveness of measures.

• Development of a draft Kabul AQ Management Plan (KAQMP), with specific policy recommendations for the consideration of National Environmental Protection Agency of Afghanistan (NEPA) and the Kabul Municipality

• Integration of air pollution concerns into the local and national environmental policies.

• Assistance in the development of air quality measurement, control and management training materials targeted specifically for the local operating environment

• Assistance in the development of a vehicle fuels inspection and testing capacity, and; development of a draft Urban Air Quality strategy report, with specific policy recommendations for the consideration of Ministry of Irrigation Water Resources and Environment (MIWRE) and the Kabul Municipality.

• A timely turn-over of all program activities to local counterparts, for continued operation of the air quality monitoring and inventory functions, and continuation of updates and implementation of the KAQM Strategy Report.

12. The KAQM Strategy Report describes the emission inventory of the Kabul, analysis of monitoring data, and the estimating of air quality of Kabul through dispersion modeling. The KAQM report is prepared based on the World Bank URBAIR Project “Urban Air Quality Management Strategy in Asia” and documents produced under this project for Katmandu Valley, Jakarta, Metro Manila and Mumbai. The report prioritizes overall investment needs for AQM at the urban, regional, and national levels, taking into account the expected sources of such investments (i.e. private sector or national government) and the mechanisms through which the polluters-pay principle can be used to eventually transfer costs to the polluters.

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13. The AQMS is based on a cost-benefit analysis of proposed actions and measures for air pollution abatement. In general, costs related to abatement measures, while benefits include a reduction in the estimated costs of health damage resulting from air pollution. This study emphasized the damage done to the health of those who are exposed to air pollution. Population exposure is based on measured and calculated concentrations of air pollutants, through emissions inventories and dispersion modeling. 14. The appendices of the report contain more detailed description of the available air quality data, the emissions inventory, emission factors, proposed regulations and standards, and spread sheets for calculating effects of control measures on emissions.

1.2 GENERAL DESCRIPTION OF KABUL VALLEY AND THE AIR POLLUTION SITUATION

15. Kabul is the capital and largest city of Afghanistan, with a population of about 3 million. Kabul is situated about 1,800 m above mean sea level in a valley, wedged between the Hindu Kush Mountains. The built up area of Kabul is 140 km2 and the city has grown in two adjacent valleys separated by north-south running mountain range. For administrative purposes, the city is divided into 16 districts, of which three districts are peri-urban and sparsely populated. 16. The end of two decades of civil strife, and political conflicts has resulted in the massive influx of refuges and migration from rural areas. Availability of urban services like water, electricity, hospitals and schools in cities like Kabul are attracting almost all the Afghan refuges to return to Afghanistan. There is also a greater sense of security from violence and exploitation as well as more job opportunities is also the major factors attracting the refugees and rural community. 17. The war has not only devastated Afghanistan's infrastructure but has also deprived the country of new investment that will have raised services above pre-war levels. As a result, most Afghans have little or no access to conventional urban services and must either go without or rely on costly alternatives. About 40% of urban streets are damaged and 50% of drains are broken or do not function. Power supply is erratic and irregular as one thermal power station is completely damaged. Limited emergency efforts are on-going to address these deficiencies. 18. Air pollution in Kabul is quite evident even to the naked eye with very high TSP and PM-10 concentrations in high traffic areas. Higher rates of allergies, cough and respiratory problems in children can be found in these areas. The major sources of air pollution in Kabul are:

• Vehicular traffic, usage of old vehicles and adulterated fuels, • Resuspension of dust and wind blown dust, damaged roads, • Residential heating during winter months using fuel wood, coal, diesel and

animal residue, • Enormous usage of privately used generators due to erratic power supply, • Bakeries and public wash halls, which use fuel wood, • Brick Kilns, all of them are old fashioned and unfortunately located in residential

areas, • Asphalt factories, • A thermal power station and small size industries, • Construction activities, and • Stone crushing and carpet cleaning industries.

19. Vehicular traffic and resuspension of dust are the major sources of air pollution in Kabul. The vehicle population of Kabul is 341,047 and most of them are older than 25 years.

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The road system in Kabul was originally designed to accommodate only 10% of present vehicle population. The concentration of population in the centre of the city and tremendous increase in traffic has caused congestion in the city, further degraded by hawkers, pedestrians, security walls and illegal construction around the main roads. The residential localities, roads and major traffic areas are shown in Figure 2. The residential localities are also the major sources of pollution during winter months. About 82 tons of wood and 123 tons of coal/charcoal are being consumed annually for residential heating, bakeries and public wash-halls. This effect and impacts are compounded during the winter, when Kabul (and many other cities) experiences more frequent and severe atmospheric inversions and stagnation of air masses for prolonged periods – trapping air pollutants below a low mixing height.

Figure 2: Location Map of Kabul

1.3 DATA SOURCES 1.3.1 Previous Studies

20. Short-term air quality studies were conducted in Kabul during 2003 by an Environmental and Industrial Health Hazard (EIHH) Special Support Team (SST) deployed by the Canadian ISAF contingent and by Norwegian Institute for Air Research (NILU) on behalf of the Norwegian ISAF contingent during 2004. 21. NILU has collected SO2 and NO2 data, for the first three months of 2004, at three sites in Kabul. PM10, elemental and organic carbon, and several metals are measured for two sites.

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1.3.2 KAQM Data Collection 22. A preliminary inventory of air pollution sources was developed for the first time in Kabul during 2005 under the KAQM Project. The inventory data consists of type of source, its location, type of fuel used, fuel usage, operation time and product output. 23. The ADB supported air quality monitoring system, installed in various locations started in May 2006. Based on 24 hours sampling data collection for NO2, SO2 and PM10 through the system is continuing. Since the KAQM program a very new initiative, laboratory analysis of the samples has been difficult. The locations of the monitoring stations are given below and shown in Figure 3. Air samples as collected on filters for PM-10 and passive diffusion wafers for SO2 and NO2, are being sent to the laboratories of Research Triangle Institute (RTI), International, Inc., in USA.

Thermal Power Station (up wind, northwestern part) Bagrami District Compound (downwind, southeastern part) National Archive Compound (center city, north) Kabul Zoo Compound (center city, south) Qalacha area (centre city, south) Kalakan District Compound (upwind, north) Ministry of Energy and Water Compound (centre city, south) Kabul Serina (central city, main part)

Figure 3: Locations of Air Quality Monitoring Stations (NEEDS CORRECTION)

24. Additional samples for CO and O3, and wind speed & direction measurements may also be collected in the near future at four sites, if resources are available. at a subset of four sites maybe collected in future. At present, hourly meteorological data from Kabul

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Airport ((OAKB) 34-38N 069-12E), as provided at: http://weather.noaa.gov/weather/current/OAKB.html has been used for the present study.

1.4 SUMMARY OF DEVELOPMENT IN THE KABUL VALLEY 25. Kabul is experiencing tremendous growth, after two decades of war, in terms of population, industry, construction and transport. Population of Kabul in 2005 is 3 million. During 2000 and 2005, the population grew at rate of 10 percent per year and predicted to grow at a rate of 5% percent in next ten years. 80 small size factories, 521 brick kilns, 280 asphalt plants and 662 bakeries are located in Kabul. A 5 % increase in these industries is noticed from 2005 to 2006. In addition, several State Owned Industries are in the process of rehabilitation. Government has recently built an industrial park and planning to develop one more. Construction activities and construction materials industry is expanding rapidly. Vehicle population in Kabul is 341,047 and is estimated to increase 11 percent annually. About 500 million liters of diesel and gasoline, 86 million kg of wood and 123 million kg of coal/charcoal is being used annually in Kabul.

1.5 POPULATION 26. Kabul has experienced massive population growth since the late 1990s primarily due to repatriation from other countries and continuous migration from rural areas. According to the estimates of United Nations the population of Kabul in 2005 is 3 million. Between 2000 and 2005 the city’s population grew at 10% per year and is projected to grow in future at 5% per year (2% migrants and 3% natural growth). The historical and predicted population data of Kabul is shown in Figure 4.

171369 472

674

978

1,4321,616

2,994

4,666

3,753

1,240

285221

1,963

0

1,000

2,000

3,000

4,000

5,000

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015Year

Popu

latio

n (in

thou

sand

s)

Source: Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat, World Population Prospects: The 2004 Revision and World Urbanization Prospects: The 2005 Revision, http://esa.un.org/unup.

Figure 4: Population Growth in Kabul 27. Kabul’s average population density is about 215 persons per hectare (p/Ha). While this is a high density by world standards it is quite average for a large Asian city. This density is similar to Bangalore or Hyderabad and lower than Shanghai (286 p/Ha), Seoul (322 p/Ha), or Hong Kong (367 p/Ha). In addition, Kabul population densities are higher in

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the periphery than in the city center; thus, Kabul is more dispersed than other cities in Asia with similar built-up densities.

1.6 FUEL CONSUMPTION 28. The major consumers of fuel in Kabul are vehicles, residential heating, bakeries, and generators. Fuel consumption data for vehicles are not available and are therefore estimated using the results of the emissions inventory survey. The estimated annual usages of fuels for various types of sources are given in Figure 5. The approximate annual fuel usage in Kabul is:

• 400 million liters of diesel • 99 million liters of gasoline • 86 million kg of wood • 123 million kg of coal/charcoal and animal residue

53

265

99

300.8 10 0.7

284

5143

123

400

9986

123

0

100

200

300

400

Fuel

Use

(milli

on li

tres

or k

g)

PowerStation

Vehciles Generators PublicWash-Halls

Bakeries Brick Kilns Heating Total Use

DieselGasolineWood Coal/ Charcoal

Figure 5: Annual Fuel Consumption in Kabul

1.7 INDUSTRIAL DEVELOPMENT 29. More than two decades of war has devastated Kabul’s industrial sector. Most of the industries are not functioning or partly functioning. Thermal Power Station located in Badam Bagh area is the only big working industry in Kabul. To support power supply in Kabul, the Power supply department of the Ministry of Energy and Water (MEW) has installed around 25 small scale power generators in different parts of the city, where transmission lines and or junctions have been destroyed. Erratic and irregular power supply in Kabul has resulted into enormous usage of independently owned portable electricity generators. 30. According to the emission inventory conducted during early 2005, Kabul has about 521 Brick Kilns and 280 asphalt plants, 662 bakeries, 22 carpet cleaning factories, 85 small size factories and several stone crushing factories. A follow up emission inventory conducted during mid 2006 indicated a 5% increase in the number of factories, bakeries and stone crushing factories. 31. The government is developing an industrial park in Bagrami area. A 9 hectares industrial complex is recently completed and another 11 hectares complex is proposed for construction. The government is also planning to rehabilitate several State Owned damaged industries in Kabul, viz. Marble Company, Janglak Industrial Co., Metal Mining Co., Afghan Carpentry Co., Bagrami Textile Co., Bread Baking Company, Bagrami Brick

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Co., Housing Construction Plant, Afghan Construction Co., Azadi Printing Co., Ariana Printing Co., Iron Components Co., Power Construction Co, Brishna Electric Power Co. 32. Construction has been a main driving force behind Afghanistan’s recovery and the construction materials industry is expanding rapidly. The variety, quality and quantity of production materials are increasing. The continued reconstruction process, increasing income, and increasing population imply that construction will remain strong over the next years. Selected state construction projects in Kabul over the next two years are:

• Rehabilitation of the Historic Old Town of Kabul • Ten thousand housing units in Qasaba, Kabul • Construction of 12 thousand houses in Dah Sabz • Review and update of Kabul Master Plan 1978 with Kabul Municipality • Rehabilitation of historical Kharabat Gozar in old city of Kabul • Rehabilitation of Hendo Gozar in Kabul • Rehabilitation of Balahesar Park in Kabul • Rehabilitation of the buildings around Kabul rivers • Technical infrastructure for the old city of Kabul

1.8 ROAD VEHICLE FLEET 33. The total number of vehicles registered in Kabul as of December 2005 is 341,047. The details of vehicle type and their share to the total vehicle type are given in Table 1. Table 1 also gives the type of the vehicles based on the fuel usage. 66 percent of the vehicles used in Kabul are small cars, 73 percent of which are gasoline. Vehicle population is estimated to increase approximately 11 percent annually. While majority of these vehicles are not road-worthy, interestingly large sections of roads are not vehicle worthy. Most of the vehicles in Kabul are older than 25 years, which are largely imported illegally. Kabul has its own public buses (Millie Bus) that take commuters on daily routes to many destinations throughout the city. The service currently has approximately 200 buses but is gradually expanding and upgrading with more buses being added. Poor standard of vehicle maintenance; and limited use of fuel-efficient technologies are the major factors that contributed to the overall air pollution.

Table 1: Vehicle Data of Kabul

Vehicle Type

Total Vehicles

% of Share in Total Vehicles

% of Diesel

Vehicles

% of Gasoline Vehicles

Small Cars 225,692 66.2 26.6 73.4

Taxi 29,270 8.6 31.7 68.3

Tractors 162 0.05 100.0 0.0 Trucks 42,422 12.4 0.0 100.0

Buses 32,323 9.5 0.0 100.0 Two Stroke MCs 11,178 3.3 100.0 0.0

Total 341,047 100 24 76

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2 AIR QUALITY ASSESSMENT 34. This Chapter provides measured and estimated annual air quality emissions and the estimated contribution of the various sources of pollution to these emissions. Ambient air quality concentrations are calculated through Gaussian atmospheric dispersion modeling, results of which are then used to estimate population exposure.

2.1 AIR POLLUTION CONCENTRATION 35. Initial air quality samples collected under KAQM from the monitoring stations of Kabul Have been analyzed. Very high TSP concentrations are visible around district 11, district 9, district 7 and district 18 during day time (early morning and evening). High levels of air pollutants can be seen at various intersections in the evening after 6 pm. The high concentrations SO2 and NO2 can be noted at these places. In fact pollutants such as SO2, NOX, and PM10 (respirable) from vehicular exhaust are palpable. People living near traffic intersections report a sour taste in the mouth and stinging sensations in the nose and throat, which are most probably due to high atmospheric loadings of air pollutants.

2.1.1 Concentrations in Kabul 36. Norwegian Air Research Institute (NILU) has collected air quality data from four stations (at the Norwegian military camp, Norwegian Embassy, near the Administration Building, and a background (upwind) site) during first three months of 2004. The air quality data is given in Annexure 2 and summary is given in Table 2. The average PM10 (24-hr average) concentration is 198 µg/m3 at Station 1 and 328 µg/m3 at Station 2. The 7 day average maximum NO2 and SO2 concentrations are 87 µg/m3 and 46 µg/m3. Metal concentrations are found to be within the limits of WHO guidelines except for Cadmium.

Table 2: Summary of NILU Air Quality Data.

24-hour average concentrations (µg/m3) 7 day average

concentrations (µg/m3) PM10 OC EC TC NO2 SO2

Maximum 12 36 11 47 70 46 Minimum 486 8 2 10 38 11 Station 1

(Camp) Average 198 21 6 27 61 28 Maximum 63 109 27 138 87 34 Minimum 704 55 20 74 34 14 Station 2

(Embassy) Average 328 81 23 104 60 21 Maximum 63 32 Minimum 29 <2 Station 3

(Admin.) Average 48 15 Maximum 41 16 Minimum 5 5 Station 4

(Background) Average 32 10

37. The variation of 24-hour average PM10 concentrations through out the monitoring period at stations 1 and 2 are given in Figure 6 and Figure 7 respectively. 24-hour average PM10 concentrations at station 1 vary from 12 µg/m3 to 296 µg/m3 (only one sample shows very high concentration of 486 µg/m3), while PM10 concentrations at station 2 vary from 63 µg/m3 to 704 µg/m3.

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Figure 6: PM10 Concentration Variation at Station 1

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2.2 AIR POLLUTANT EMISSIONS IN KABUL VALLEY 38. Air emissions inventories are prepared based on a pollutant source inventory survey conducted during 2005 and USEPA emission factors. The methodology of estimating emissions for various sources and their spatial distribution is given in Appendix 3. The estimated annual emissions for PM10, NOX, SO2, CO, CO2 and TOC are given in Table 3. Contribution of various sources for the total emissions is given for PM10, NOX, SO2, and CO in Figure 8. 39. Though some estimates are rough and based on incomplete information, the emissions inventory may be considered adequate for a first estimate of source contributions and a background for first stage cost-benefit analysis. 40. Total annual emission of PM10 is estimated to 17,363 tons. The major emission sources of PM10 are vehicles and dust (52%), fuel combustion for residential heating (31%) and brick kilns (12%). The major sources of NOX are portable generators (19%) and residential heating (8%) and the major sources of SO2 are space heating (15%) and generators (8%). The major sources of CO emissions are gasoline vehicles (36%) and space heating (39%).

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Table 3: Total Estimated Annual Emissions in Kabul, 2005

PM10 NOX SO2 CO CO2 TOCVehiclesGasoline Vehicles 310 1,700 113 34,450Diesel Vehicles 1,387 9,475 1,625 9,615Resuspension 7,278

Total Vehicles 8,976 11,175 1,739 44,065Residential SourcesResidential/ Commercial Heating 5,403 1,241 381 38,077 511,833 7,333

Residential/ Commercial Generators 223 3,131 207 3,028 120,822 324

Bakeries 463 44 7 3,492 736Hammams 160 15 2 1,209 255

Total Residential Sources 6,249 4,431 597 45,807 632,655 8,648Industrial SourcesThermal Power Plant 35 347 110 32 16Industrial Generators 12 185 10 7,121 17,629 239Brick Kilns 2,030 44 25 44 30 0.19Asphalt 62 2 3 0.10 532 0.64

Total Industrial Sources 2,138 578 148 7,197 18,191 256Grand Total 17,363 16,183 2,484 97,068 650,846 8,903

SourceAnnual Emission (Tons)

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Industrial Generators1%

Thermal Power Plant2%

Residential/ Commercial Heating

8%

Residential/ Commercial Generators

19%

Diesel Vehicles59%

Gasoline Vehicles11%Brick Kilns

11.7%

Resuspension41.9%


31.1%

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Gasoline Vehicles1.8%


1.3%

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Industrial Generators0.1%

Thermal Power Plant0.2%

Hammams0.9%

Asphalt0.4%

Brick Kilns1.0%

Bakeries0.3%


Hammams0.1%

Thermal Power Plant4.4%


8.3%


Diesel Vehicles65.4%


15.3%


39.2%


Diesel Vehicles9.9%


Hammams1.2%

Bakeries3.6%


3.1%

PM10 NO2

SO2 CO

Figure 8: Contribution of Different Sources to Emissions of PM10, NO2, SO2 and CO

2.3 DISPERSION MODEL CALCULATIONS 2.3.1 General Description of Topography and Climate

41. Topography of Kabul is of valley type surrounded by hills and mountains. Average elevation of Kabul is 1,800 meters above the mean sea level. The city has a continental climate with four distinct seasons, winter from December to February, spring from March to April, summer from May to September, and autumn from October to November. The mean monthly temperature of Kabul is 12.5oC. The coldest month is January with a mean temperature of -1.9oC and the warmest month is July with a mean temperature of 25.1oC. The average annual precipitation is 316 mm with maximum rainfall occurring during February to April. June to October are the driest months with mean monthly precipitation of less than 7mm. The average monthly climatic data of Kabul for 12 years is given in Table 4.

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The data in Table 4 include monthly averages of precipitation, potential evaporation, temperature, wind speed, sunshine and global radiation.

Table 4: Mean Monthly Climatic Data of Kabul

Month Precipiation1 PET1 PET2 Mean Temp3

Min Temp3

Max Temp3

Night Temp3

Wind Speed4 Sunshine5 Global

Radiation6

Jan 34 14 0.47 -1.9 -7.4 1.4 -2.7 1.3 0.56 9.1Feb 57 24 0.8 -0.3 -4.8 3.1 -0.5 1.3 0.6 12.1Mar 64 53 1.77 6.6 1.4 9.5 5.6 1.8 0.53 14.2Apr 82 83 2.77 13.3 5.5 14.2 10 1.7 0.57 17.9May 23 152 5.07 17.8 8.6 19 13.6 2.3 0.71 22.9Jun 1 207 6.9 23 12.1 23.9 17.7 2.4 0.81 26Jul 7 227 7.57 25.1 14.8 26.6 20 2.6 0.8 25.3Aug 1 184 6.13 24.4 14 26.2 19.2 1.8 0.83 24Sep 2 126 4.2 20 9.2 22.4 14.7 1.5 0.81 20.3Oct 2 64 2.13 13.7 4 16.5 8.9 1.2 0.81 16.4Nov 20 26 0.87 6.7 -1.2 9.5 2.9 1.3 0.77 12.2Dec 23 13 0.43 1.2 -5.1 3.9 -1.7 1.2 0.64 9.1Avg. 26 98 3.26 12.5 4.3 14.7 9 1.7 0.7 17.51 Long-term average mean monthly value in mm2 Long-term daily mean value in mm3 Long-term mean monthly value in degrees Celsius4 Long-term mean monthly value in m/s (12 years data)5 Long-term mean monthly ratio 6 Long-term daily value in mJ/m2/daySource: Department of Meteorology, Department of Transport and Tourism, Islamic Republic of Afghanistan 42. Generally, substantial differences between the day and night temperatures occur due to extreme diurnal variations in the high altitude areas. The days are warm and there is rapid cooling at night. In the dry season, the cooling at night may cause the formation of deep inversion layers, with air temperature increasing with height. When such an inversion layer is deep enough, it takes time for the insulation to break it up. The atmosphere then acts as a lid over the city, and pollution concentrations can build up considerably. 43. Meteorological data of Kabul is measured by a weather station (OAKB, 34-38N 069-12E) located at Kabul airport. The station records hourly observations of the following parameters

• air temperature; • air humidity; • wind speed; • wind direction; • visibility; • barometric pressure; and • dew point

2.3.2 Dispersion Conditions 44. USEPA developed meteorological preprocessor AERMET, has been used to calculate dispersion conditions and boundary layer parameters. AERMET preprocessed hourly meteorological data for the year 2005 of Kabul has been used as input to AERMOD. Wind roses for all the months of the 2005 and the four seasons are given Figures 9, 10 and11, respectively. Wind directions are predominantly from northwestern directions except in summer months. During summer months, the wind directions are predominantly from northern directions. The annual wind speed/direction frequency table is given in Table 5.

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Table 5: Annual Wind Speed/Direction Frequency Matrix of Kabul

<1.54 1.54-3.09 3.09-5.14 5.14-8.23 8.23 -10.8 >10.8

0 2.17 1.07 2.29 3.31 1.52 0.46 10.8222.5 1.58 0.82 1.19 1.26 0.72 0.24 5.80

45 1.44 1.27 1.07 0.23 0.03 0.01 4.0567.5 1.45 1.40 1.30 0.10 0.00 0.00 4.26

90 1.70 1.13 1.15 0.42 0.06 0.01 4.47112.5 1.35 0.74 0.58 0.19 0.01 0.00 2.88

135 1.42 1.08 0.37 0.06 0.00 0.00 2.92157.5 1.94 0.88 0.31 0.01 0.00 0.00 3.14

180 1.88 0.97 0.38 0.05 0.01 0.00 3.29202.5 1.38 0.50 0.38 0.11 0.00 0.00 2.37

225 1.32 0.61 0.34 0.05 0.00 0.00 2.32247.5 1.97 1.19 0.47 0.11 0.01 0.01 3.77

270 2.73 1.83 0.86 0.03 0.02 0.00 5.47292.5 4.01 3.31 1.64 0.02 0.01 0.01 9.01

315 4.45 5.00 4.43 0.19 0.03 0.00 14.11337.5 2.75 2.79 4.84 1.85 0.31 0.01 12.55Total 33.54 24.59 21.60 8.00 2.74 0.75 91.22

Calms 6.56Missing 2.21

Total 100.00

Direction TotalSpeed (m/s)

45. AERMET processes the meteorological data in three stages:

• The First Stage (Stage 1) extracts meteorological data from archive data files and processes the data through various quality assessment checks.

• The Second Stage (Stage 2) merges all data available for 24 hr periods (surface data, upper air data, and onsite data) and stores these data together in a single file.

• The Third Stage (Stage 3) reads the merged meteorological data and estimates the necessary boundary layer parameters for use by AERMOD.

46. Out of this processes two files are written for AERMOD: (i) A surface file of the following hourly boundary layer parameter estimates

(minimum and maximum values of some of these parameters for each month are given in Table 6). • wind speed, • wind direction, • ambient temperature, • lateral and vertical turbulences with their associated measurement heights, • sensible heat flux, • friction velocity, • Monin Obukhov length, and • convective and mechanical mixing heights

(ii) A profile file of multiple level observations of wind speed, wind direction, temperature and standard deviation of the fluctuations of wind components.

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Figure 9: Monthly Wind Roses of Kabul, from January to June, 2005

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Figure 10: Monthly Wind Roses of Kabul, from July to December, 2005

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Figure 11: Season and Annual Wind Roses of Kabul for the Year 2005

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Table 6: Meteorological Input Parameters for Dispersion Modeling

Month

Min Max. Min Max. Min Max. Min Max. Min Max.January -64 215.5 0.045 1.111 0.154 2.215 72 2428 50 2440February -64 267.4 0.045 1.861 0.261 2.480 72 3259 49 3879March -64 337.1 0.045 1.679 0.164 3.142 72 3498 50 3998April -64 384.4 0.045 2.425 0.161 2.999 72 4328 49 4000May -64 401.0 0.045 3.168 0.194 3.361 49 4928 49 4000June -64 414.0 0.045 2.515 0.347 3.828 72 5000 49 4000July -64 413.1 0.045 2.425 0.195 3.329 49 4527 50 4000August -64 404.2 0.045 2.425 0.174 3.444 49 4717 49 4000September -64 373.7 0.045 3.912 0.215 2.985 88 5000 49 4000October -64 317.4 0.045 2.425 0.130 2.667 49 3670 49 4000November -64 240.4 0.045 1.685 0.128 2.286 49 3880 49 4000December -64 188.5 0.045 1.588 0.198 2.052 72 2625 49 2999

Mechanical Mixing Height (m)

Sensible Heat Flux (W/m2)

Frictional Velocity (m/s)

Convective Velocity (m/s)

Convective Mixing Height (m)

.

2.3.3 Dispersion Model Calculations, City Background 47. USEPA regulatory dispersion model AERMOD is used in the present study. AERMOD is a steady-state plume model that incorporates air dispersion based on the planetary boundary layer turbulence structure and scaling concepts, including treatment of both surface and elevated sources, and both simple and complex terrain. 48. Pollutants considered for dispersion modeling in the present study are PM10, NOX and SO2. Where ever emissions for PM10 are not estimated directly, they have been derived by converting from total PM emissions as explained in Appendix 3. Digital Elevation Model of Kabul is created by digitizing AIMS printed topographic map of Kabul and converted using xyz2dem software. AERMET preprocessed hourly meteorological data from January 1, 2005 to December 31, 2005 has been used as meteorological input to the model. GIS shape files have been used for locating point and area sources. Effective emission heights are considered for area sources, for example, an emission height of 0.25m is considered for vehicles and 0.5 m is considered for generators. A 24 hour averaging period is selected for modeling.

a) Particulate Matter 49. Particulate Matter (PM) is a complex mixture of extremely small particles and liquid droplets. PM is made up of a number of components, including acids (such as nitrates and sulfates), organic chemicals, metals, and soil or dust particles. The size of particles is directly linked to their potential for causing health problems. The particles that are 10 micrometers in diameter or small are of general health concern as they easily pass through the throat and nose and enter the lungs. Once inhaled, these particles can affect the heart and lungs and cause serious health effects. PM is categorized into two groups, (i) “Inhalable coarse particles,” such as those found near roadways and dusty industries, are larger than 2.5 micrometers and smaller than 10 micrometers in diameter (known as PM10); and (ii) “Fine particles,” such as those found in smoke and haze, are 2.5 micrometers in diameter and smaller (known as PM2.5) and these particles can be directly emitted from sources such as forest fires, or they can form when gases emitted from power plants, industries and automobiles react in the air. The USEPA ambient air quality standard for 24-hr average PM10 is 150 µg/m3 and for 24-hr average PM2.5 is 35 µg/m3 (effective December 17, 2006) WHO air quality guideline for 24-hr average PM10 is 50 µg/m3 (WHO, 2005). 50. The modeled 24 hour average PM10 concentration distribution of all combined sources is shown in Figure 12. The highest averaged concentration for all sources is 267 µg/m3. A maximum concentration of more than 225 µg/m3 is predicted in two small areas: near ‘Tahwil-Khane-Abrasani’ and ‘Sayed Nurm Mohamod Sha Min’ areas in District 8 and

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near ‘Qala-i-Shada’ area on the western part of the city at the borders of districts 3, 5 and 6. These high concentrations are possibly due to the presence of brick kilns in these areas.

Figure 12: Distribution of Modeled 24-hr Average PM10 concentrations for all sources. (Below: PM10 distribution over digital elevation model of Kabul)

.

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Figure 13: Distribution of Modeled 24-hr average PM10 Concentrations from Brick Kilns

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Figure 14: Distribution of Modeled 24hr average PM10 Concentrations from Vehicular Traffic.

. Figure 15: Distribution of Modeled 24-hr average PM10 Concentrations from Residential Heating

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b) Nitrogen Oxides 52. Nitrogen oxides (NOX), is the generic term for a group of highly reactive gases, all of which contain nitrogen and oxygen in varying amounts. Many of the nitrogen oxides are colorless and odorless. However, one common pollutant, nitrogen dioxide (NO2) along with particles in the air can often be seen as reddish-brown layer over many urban areas. Nitrogen oxides form when fuel is burned at high temperatures, as in a combustion process. The primary manmade sources of NOX are motor vehicles, electric utilities, and other industrial, commercial, and residential sources that burn fuels and natural gas. The main causes for concern of NOX pollution are: (i) formation of ground-level ozone, which can trigger serious respiratory problems, (ii) formation of acid rain, (iii) nutrient overload that deteriorates water quality, and (iv) visibility impairment most noticeable in national parks. NOX and the pollutants formed from NOX can be transported over long distances, following the pattern of prevailing winds. The USEPA ambient air quality standard for NO2 (annual average) is 100 µg/m3 and the Indian standard for 24-hour average NO2 is 120 µg/m3. WHO air quality guideline for NO2 concentrations are 40 µg/m3 for annual mean and 200 µg/m3 for 1-hour mean.

Figure 16: Distribution of Modeled 24-hr Average NOX Concentrations (all sources).

53. The modeled 24 hour average NOX concentration distribution of all sources is shown in Figure 16. The maximum concentration found is 246 µg/m3. Higher concentrations of more than 200 µg/m3 are predicted in two areas, one in the heart of the city around city square, the main traffic junctions and the other is near ‘Khwaja Bughra and Gala-i-Nagar’ areas on northern side of the city in District 15. 54. Traffic is the major contributor for NOX with a maximum concentration of 180 µg/m3 followed by domestic/commercial generators, 50 µg/m3. The contribution of NOX from vehicles is higher because of high number of diesel vehicles in Kabul. The contour maps of NOX concentrations for traffic, domestic/commercial generators and power plant are given in Figures 17, 18 and 19, respectively.

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Figure 17: Distribution of Modeled 24hr-average NOX Emissions from Vehicular Traffic.

Figure 18: Distribution of Modeled 24-hr average NOX Concentrations from Residential and Commercial Generators

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5 10

Figure 19: Distribution of Modeled 24-hr Average NOX Concentrations from Power Plant.

c) Sulfur Dioxide 55. Sulfur dioxide (SO2) belongs to the family of sulfur oxide gases (SOx) and these gases dissolve easily in water. Sulfur is prevalent in all raw materials, including crude oil, coal, and ore that contains common metals like aluminum, copper, zinc, lead, and iron. SOx Gases are formed when fuel containing sulfur, such as coal and oil, is burned, and when gasoline is extracted from oil, or metals are extracted from ore. SO2 dissolves in water vapor to form acid, and interacts with other gases and particles in the air to form sulfates and other products that can be harmful to people and their environment. SO2 contributes to (i) respiratory illness, particularly in children and the elderly, and aggravates existing heart and lung diseases, (ii) the formation of acid rain, and (iii) the formation of atmospheric particles that cause visibility impairment, most noticeably in national parks. SO2 and the pollutants formed from SO2 , such as sulfate particles, can be transported over long distance and deposited far from the point of origin. The USEPA standard for 24-hour average Sulfur Oxides is 0.14 ppm (365 µg/m3) and WHO air quality guideline for 24-hour average is 20 µg/m3. 56. The modeled 24 hour average SO2 concentration distribution of all the sources is shown in Figure 20. The concentration distribution of SO2 is found to be similar to the concentration distribution of NOX. Traffic is the major contributor for SO2 with a maximum concentration of 28 µg/m3 followed by Power Plant, 5 µg/m3. The high concentrations of SO2 from traffic are due to high quantity of diesel vehicles with 0.11 percent of sulfur present in the diesel. The contour map of SO2 concentration for traffic is shown in Figure 21.

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Figure 20: Distribution of Modeled 24-hr Average SO2 Concentrations (all sources).

A

Figure 21: Distribution of Modeled 24hr Average SO2 Concentrations from Vehicular Traffic

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2.3.4 Pollution Hotspots 57. Pollution hot spots are characterized by significant pollution sources that emit large concentrations. Major hot spots are generally located along the main road system; and near large industrial establishments with significant emissions, especially through low stacks. 58. The general distribution of pollution concentration indicates that the pollution problem in Kabul is mainly an urban-scale resulting from many distributed sources. However, very high concentrations are observed around city centers and brick kilns. Emissions from brick kilns expose nearby areas with very high short-term concentrations, depending upon the wind and dispersion conditions. In addition, Kabul City is surrounded by mountains and has valley topography, emissions are entrapped within shallow heights and pollution is further deteriorated by frequent inversions during winter season.

2.3.5 Population Exposure to Air Pollution 59. A study was conducted under the KAQM project to assess the impact of air pollution on the population of Kabul. The study revealed a strong correlation between exposure to air pollution and health risk. The higher rates of allergies, cough and respiratory symptoms in children are found living with in 50 m from the roads. In every minute, about 24 different vehicles pass a street in Kabul, while in heavy traffic areas, about 34,600 vehicles pass in 24 hours. Physical abnormality, tension, and high blood pressure can be found in the community living around central traffic intersections (districts 1, 2, 3, 4, 10,and 11). The people making livelihood near these traffic sections complained serious respiratory problems and infections. 5 of 20 hawkers interviewed have complained permanent cough and cold, 6 hawkers complained eye and nose irritation and the rest though didn’t complain any thing, feeling sad. 60. A two stage study was conducted to further assess the impact of air pollution. The first stage is ‘hazard identification’, in which a number of doctors were interviewed about the diseases of their patients. Many of the patients are found to have problems like headache, nausea, eye or nose or throat irritation. In the second stage of the study, ‘exposure assessment’, the data of patients who are visiting the doctor more than once are collected. 61. Children who attend school near a heavily trafficked areas are found to have increased respiratory infections and symptoms of increased inflammatory markers. It was also found that in some maternity hospitals in Kabul, a number of babies were delivered with defective heart valves, cleft lips and palates possibly due to mother’s exposure to hazardous air pollution during their pregnancy. 62. Population exposure is defined as the number of persons exposed to pollutant concentrations within given concentration ranges. 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, on roads, at work, and other places. In order to correctly map population exposure, data are needed on:

Time activity patterns to establish geometrical concentration distribution, and variation with time in homes/commercial buildings (ambient air quality or city background), along the main road network, and near other spots such as industrial areas, and

Population distribution (residences and workplaces), the number of commuters, and their time-dependent travel habits.

63. Databases for population exposure calculations are often incomplete. A methodology must be developed for each city based on the available data. In the present study, the

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population exposure to different levels of concentrations is estimated by measuring the area of exposure in each district and multiplied it with population density assuming that population is equally distributed within the district. 64. Air Quality Index (AQI) is a tool that state to issue public reports about daily levels of actual levels of particles, ground-level ozone, and sulfur dioxide, carbon monoxide and nitrogen dioxide. USEPA determines the index number on a daily basis for each of the five pollutants; it then reports the highest of the five figures and identifies which pollutant corresponds to the figure that is reported. The AQI classification with its equivalent PM10 concentrations, its health impact and related health advisory are given in Table 7. The percentage of Kabul’s population exposed to these concentrations is also given in Table 7.

Table 7: USEPA AQI Classification and Population Exposure AQI

Range Equivalent

PM10 Range (µg/m3)

EPA Descriptor

Health Effects Health Advisory Percentage of Kabul

Population Exposed

0 - 50 0-54 Good None 0% 51 to 100 55-154 Moderate Respiratory symptoms

possible in unusually sensitive individuals, possible aggravation of heart or lung disease in people with cardiopulmonary disease and older adults

Usually sensitive people should consider reducing prolonged or heavy exertion.

35.69%

101 to 150 155 to 254 Unhealthy for Sensitive Groups

Increasing likelihood of respiratory symptoms in sensitive individuals, aggravation of heart or lung disease and premature mortality in people with cardiopulmonary disease and older adults.

People with heart or lung disease, older adults, and children should reduce prolonged or heavy exertion.

64.19

151 to 200 255 to 354 Unhealthy Increased aggravation of heart or lung disease and premature mortality in people with cardiopulmonary disease and older adults; increased respiratory effects in general population

People with heart or lung disease, older adults, and children should reduce prolonged or heavy exertion.

0.13

201 to 300 355 to 424 Very Unhealthy Significant aggravation of heart or lung disease and premature mortality in people with cardiopulmonary disease and older adults; significant increase in respiratory effects in general population.

People with heart or lung disease, older adults, and children should avoid all physical activity outdoors. Everyone else should avoid prolonged or heavy exertion

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Everyone should avoid all outdoor exertion.

Figure 22: Population Exposure to PM10

Figure 23: Population Exposure to NOX

d) Estimating Population Exposure in Kabul 65. Population exposure calculations have been carried out for 24 hour average concentrations of PM10, NOX and SO2. The calculations have been used to further assess the costs of health damage. The results of population exposure to 24 hour average concentrations of PM10, NOX and SO2 are shown in Figures 22, 23 and 24, respectively. 66. 64 percent of the population is exposed to more than 150 µg/m3 (USEPA standard) of PM10. 36 percent of the population is exposed to PM10 concentrations between 100 – 150 µg/m3.

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average Indian ambient air quality standard for NO2). 7.7 percent of the population is exposed to very high concentrations of more than 200 µg/m3 of NOX. 68. 62 percent population is exposed to a concentration above the WHO standard of SO2. 20 µg/m3. The maximum concentration of SO2 found is 37 µg/m3.

Figure 24: Population Exposure to SO2

2.4 SUMMARY OF AIR QUALITY ASESSMENT, KABUL VALEEY 2.4.1 Air Pollution Concentrations

69. The modeled maximum 24 hour average concentrations of PM10, NOX and SO2 for all sources independently and the concentrations for all sources are shown in Table 8. Air quality monitoring stations have been established to collect air quality data of Kabul. Due to lack of monitoring data, the modeling results could not be validated. Therefore, model outcome in Table 8 is indicative only.

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Table 8: Modeled 24 hour average concentrations in µg/m3 Source PM10 NOX SO2

All Sources 267 241 37Vehicles 144 180 28Generators - Residential 4 50 4Generators - Industrial 2 31 1Residential Heating 101 23 1Bakeries 10 1 1Asphalt Plants 12 1 1Power Plant 2 15 5Brick Kilns 116 3 2

2.4.2 Air Pollutant Emission Inventory 70. The estimates of various pollutant concentrations in Kabul indicate that vehicular traffic, dust, brick kilns, generators and residential heating are the major sources of air pollution. Emissions are estimated based on statistical data on pollution-producing activities, and on emission factors described by USEPA and the World Bank URBAIR reports. The estimated total annual emissions are:

• 17,363 tons of PM10 • 16,183 tons of NOX • 2,484 tons of SO2 • 97,068 tons of NO • 650,846 tons of CO2 • 8,903 tons of TOC

71. Further investigation is vitally important to improve these rough estimates and to the development of a control strategy. Road traffic, dust and brick kilns are the major sources of particulate emission. Traffic and independently owned domestic generators are the major sources of NOX emissions.

2.4.3 Population Exposure to Air Pollutants 72. The number of residents exposed to different pollutant levels is used to calculate health impacts of air pollution. 64 percent of the population is exposed to more than 150 µg/m3 of PM10 and 68 percent of the population is exposed to more than 120 µg/m3 of NOX.

2.4.4 Visibility Reduction 73. Visibility is defined as the degree to which the atmosphere is transparent to visible light and the clarity and color fidelity of the atmosphere. Visible range is the farthest distance a black object can be distinguished against a horizontal sky. Visibility impairment is associated with airborne particle properties, including size distributions and aerosol chemical composition Visibility in Kabul is mainly affected by sub-micrometer particles, mainly from fuel combustion, resuspension of dust and wind blown dust from the surrounding mountains. Hygroscopic particles like sulfate, nitrate and organic aerosols, cause strong visibility reduction at relative humidity above 70 percent. Combustion aerosols absorb water, which causes reduced visibility, at 30 to 40 percent relative humidity.

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74. Visibility in Kabul is generally low during winter months due to snow and haze. According to the visibility data collected during July to September 2006 from the meteorological station at Kabul airport,

visibility is more than 11 km during 33 percent of time, visibility is between 5 to 8 km during 58 percent of time, and visibility is less than 3 km during 9 percent of the time.

75. The major sources of particles, which are directly responsible for visibility reduction in Kabul, are:

Residential heating during winter months Vehicles Brick kilns Thermal power plant Bakeries and public wash-halls

2.5 IMPROVING AIR QUALITY ASSESSMENT 2.5.1 Main Shortcomings and Data Gaps

76. Emission estimates derived in this report are rough and based on incomplete information, which are to be further modified. However, the emissions inventory may be considered adequate for a first estimate of source contributions and a background for first stage cost-benefit analysis. 77. Additional sources identified during second round of emission inventory survey during end of 2006 (viz. stone crushing factories, carpet cleaning industries and generators being used by the Kabul electricity department, etc.) are not included in the emission estimates. Construction activities, one of the major source of particulate emissions in Kabul, are not considered in emission estimates. It is necessary to fill all these data gaps and upgrade the inventory. 78. The emission inventory is to be improved by giving the special attention to the following:

• Industrial emissions • Resuspension from roads • Other coarse particle sources, such as construction • Domestic refuse burning • Consumption patterns for domestic and commercial fuel use; and • Absence of local emission factors

79. Population exposure is determined by the results of only dispersion modeling. It should be developed by the combination of monitoring data and dispersion modeling results. It is vital that the population exposure distribution is reliable, since it forms the basis for assessing damage to health and estimating costs from such damages. Further, it feeds into the cost-benefit analysis of measures to reduce exposure. Proposed actions to improve air quality assessment are summarized in Table 9

Table 9: Proposed Actions to Improve Air Quality Assessment Actions Time Schedule

Air Quality Monitoring • Air samples collected from the monitoring

stations are to be analyzed. • Developing laboratory facilities and man

power capacities

Immediate Medium Term

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Actions Time Schedule • Design and establish Air Quality Information

System, including o Database, o Information to

Control agencies Law makers General public

Short term

Emissions • Improve emission inventory for Kabul

including o Industrial emission inventory (location,

process, emissions, stack data); o Road and traffic data inventory; o Domestic emissions inventory

• Study dispersions from roads and surfaces • Estimate contribution from construction and

refuse burning • Establish emission factors for Kabul

conditions • Develop an integrated and comprehensive

emissions, inventory procedure, include emission factor review, update and quality assessment procedure.

• Improve methods and capacity for emission measurements

Priority • Industrial emissions inventory • Study of resuspension from roads, • Start developing an emission inventory

procedure

Population Exposure Assess current modeling tools/methods, and establish appropriate models for control strategy in Kabul

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3 AIR POLLUTION IMPACTS 3.1 INTRODUCTION 80. This Chapter presents an overview of major impacts of air pollution in Kabul, including a rough estimation of the monetary value of these damages, based on PM10 levels alone. Health impact estimates are prepared based on a research conducted in the United States (Ostro, 1994) and according to the methodology described in the URBAIR Guidebook. A frequency distribution of PM10 exposure of Kabul’s population is presented in Figure 25.

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3.2 IMPORTANT IMPACTS IN KABUL VALLEY 81. The study conducted under this project revealed a significant correlation between air pollution and health risks. Higher rates of allergies, cough and respiratory symptoms are found in people living very close to the heavy traffic areas and main roads. Physical abnormalities and high blood pressures can also be found in these people. 82. A research conducted in United States (Ostro, 1994) has been used to assess the impact of air pollution on Kabul population. Although US research relates to TSP concentrations, in this study it has been adapted and applied to PM10, since these particles are considered a more serious threat to health in Kabul Valley. The US study considered annual average concentrations of TSP and compared it with corresponding annual WHO guideline to assess the health damage, but in the present study 24-hour average PM10 concentrations are used and compared with 24-hour average WHO guideline. PM10 concentrations are calculated from dispersion models using actual PM10 emissions. TSP dose-response relationship is converted to PM10, using a ratio of 0.55 between PM10 and TSP concentrations.

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3.2.1 Mortality 83. Health impacts are divided into mortality (excess deaths) and morbidity (excess cases of illness). Mortality and morbidity rates are derived from air quality data using dose-effect relationships. In principle such relationships are derived by statistical comparisons of death rates and morbidity in (urban) areas with different air quality. Dose-effect relationships for different pollutants for cities in the United States, have been compiled by Ostro (1994). Although the use of these relationships for Kabul may be speculative, until specific dose-effect relations are derived for valley-like conditions, Ostro’s dose-effect relations are the best available. This analysis is limited to outdoor concentrations, though indoor air pollution also causes significant health damage. 84. The relationship between air quality and mortality is:

Excess death = 0.00112 x ([PM10]-50) x P x C

Where, ‘P’ equals the number of people exposed to a specific concentrations; ‘C’ equals the crude rate mortality (0.0076 in Kabul, assumed equal to Mumbai,

India); and PM10 stands for its 24-hour average concentrations (µg/m3). A PM10 bench mark of

50 (WHO guideline for PM10) is used. It is assumed that mortality increases when concentrations exceed this number.

3.2.2 Morbidity 85. Inhaling of particles can lead to chronic bronchitis, restricted activity days (RAD), respiratory diseases that requires hospitalization (RHD), emergency room visits (ERV), bronchitis, asthma attacks, and respiratory symptoms days (RSD). The impact coefficients of these diseases are given in Table 10. Multiplication of these coefficients with ([PM10]-50) and population will give the total morbidity cases Table 11.

Table 10: Estimated increment in annual health effect associated with unit change in PM10

Morbidity Cases Impact co-efficient Hospital Admissions/100000 1.2 Emergency Visit/100000 23.54 Restricted Activity Days/person (RAD) 0.0575 Lower Respiratory Illness/child 0.0016 Asthma cases 0.0326 Symptoms of Respiratory Disorders/person (RSD) 0.183 Chronic Bronchitis/100000 6.12

3.3 VALUATION OF HEALTH IMPACTS 86. Mortality: Though it is difficult to estimate monetary value of mortality, it is a vital component in estimating the health damages caused by air pollution. Mortality can be estimated by two methods, (i) “willingness to pay”, and (ii) “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 US figure by a factor based on purchasing power parity in Afghanistan divided by the purchasing power in the United States. 87. The second approach is based on income lost due to mortality. The value of a statistical life (VSL) is then estimated as the discounted value of expected future income at

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the average age. If the average age of population is 24 years and the life expectancy at birth is 62 years, the VSL formula is

VSL = Σ w/(1+d)t , where t = 0-38

In the formula, ‘w’ is the average annual income, and ‘d’ is the discount rate (Shin et al., 1992). In this approach, the value of persons without a salary (e.g. housewives) is taken to be the same as the value of those with a salary. 88. Morbidity: the valuation of illness should be interpreted with care as it is based on dose-response relations derived in other parts of the world. More research is needed to derive relations that are specific for Kabul Valley. Unit health costs of morbidity derived for Mumbai in 1997 by URBAIR report have been considered equal to present Kabul scenario and are used to estimate valuation of heath impacts. The estimated impact of mortality and morbidity due to PM10 emissions and their valuation in Afghan currency are given in Table 11.

Table 11: Estimates of Mortality and Health and Their Valuation

Type of Health Impact Cases Unit Cost*, USD

Total cost, million AFA

Mortality 2,287 8,000 915Restricted Activity Day 15,447,233 0.90 695Respiratory Symptoms Day (RSD) 49,162,497 0.64 1,573Emergency Room Visit 63,240 0.64 2Bronchitis 208,847 10.24 107Asthma Attacks 613,054 0.64 20Chronic Bronchitis 16,441 5,152 4,235*Unit health costs are taken from URBAIR Report of Mumbai, 1997

3.4 HEALTH IMPACT AND ECONOMIC DAMAGE BY SOURCE CATEGORY 89. Source wise assessment of health and economics impact is necessary in targeting and prioritizing action plan for air quality management. Vehicular traffic including road dust, residential heating in winter months, brick kilns, fuel combustion for bakeries and wash-halls, and domestic generators, in that order, are the major sources of the particulate pollution. Table 12 gives the economic and health benefits for 25% reduction in the emissions from the major sources.

Table 12: Source Wise Economic and Health Benefits Due to Emission Reductions

Source Emisssions (Tons)

Emissin Reduction

(%)

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(Tons)

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(million)

Avoided Health Costs (million AFA)

Traffic 8,976 25 2,244 296 6.35 975Heating 5,403 25 1,351 178 3.82 587Brick Kilns 2,030 25 508 67 1.44 221Bakeries and wash-halls 623 25 156 21 0.44 68Generators 223 25 56 7 0.16 24 3.5 CONCLUSIONS 90. The mortality and morbidity resulting from excess atmospheric loadings of PM10 have been estimated using dose-effect relationships derived for U.S. cities. However, air pollution impacts on vegetation and crops, buildings and monuments, ecosystems and tourism could not be assessed. 91. The estimated annual mortality due to PM10 exposure is 2,287 and the total cost of mortality in terms of monetary value is 915 million Afghans. The estimated annual

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respiratory symptoms days are 49 million and asthma attacks are 0.6 million. The total monetary value of all health damages are assessed as 7,547 million Afghans. 92. Traffic is the major sources of health impacts and economic damage followed by residential heating in winter months and brick kilns. A 25 percent reduction in emissions from traffic could result in a reduction in mortality of 296 persons and a reduction in total health-related costs of 975 million Afghans.

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4 ABATEMENT MEASURES: EFFECTIVENESS AND COSTS 4.1 INTRODUCTION 93. This Chapter highlights the mitigation measures for reducing air pollution in Kabul and for developing an action plan that would translate these measures into practice. They are chosen based on their effectiveness in controlling emissions, the benefits associated with the reduction in emissions, and cost of implementing the measure. The measures are described in terms of their:

• effectiveness in emissions reduction and reduced exposure impacts; • costs of measures in order to prioritize implementation; • benefits including reduced excess deaths (mortality, reduced number of Respiratory

Symptoms Days, and economic benefits); • policy instruments and institutions that may be used to implement the measures; and • term, a time schedule in which a particular measure can result in emissions reduction:

short term (2 years), mid-term (2-5 years), long term (more than 5 years). 94. It is evident from emission estimates that PM10 is the main contributor to the air pollution in Kabul. The major sources of PM10 are traffic, road and wind blown dust, brick kilns and wood combustion for residential uses, bakeries and public wash-halls. Vehicles alone contribute to 70 percent of both NOX and SO2 emissions. Identifying measures to address traffic emissions, for example, is straight forward because the major causes of traffic pollution are commonly known. Policy measures that are especially cost efficient include: an inspection and maintenance scheme, and the introduction of low sulfur diesel and low-smoke lubricating oil. Other measures with less cost-benefit ratios (due to lack of data or methodological problems) are: improving automotive diesel fuel quality; stringent vehicle emission standards; introduction of natural gas; and improving public transportation system. The list of measures is derived in consultation with various government agencies, information presented by the local consultants, the URBAIR Guidebook and NEPA’s action plan for addressing pollution in Kabul. All figures for emissions, costs, and benefits represent annual estimates for 2005, unless otherwise stated.

4.2 TRAFFIC 95. This section describes the effectiveness (abated emissions) and, to the extent possible, the benefits of measures such as

• Implementation of a scheme for inspection and maintenance; • Improving diesel fuel quality; • Adoption of clean vehicle emissions standards; • Improved Abatement/other Propulsion Techniques • Addressing Resuspension • Improvement of Traffic Management • Construction and Improvement of Mass Transit Systems.

4.2.1 Implementation of Scheme for Inspection & Maintenance a) Effectiveness

96. Maladjusted fuel injection systems or carburetors and worn-out motor parts pose a threat to traffic safety. They also increase fuel consumption and costs, and lead to large emissions. Annual inspection and maintenance of vehicles would probably result in substantial reductions in PM10, VOC, and CO. It is assumed that an inspection and maintenance scheme would reduce tail pipe emissions of PM10, VOC, and CO by 35

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percent, as is the case for the World Bank estimate for Manila (Mehta, 1993) and the Association of Indian Automobile Manufacturers (AIAM, 1994). Drive Clean Program (I/M) found about 15.2% reductions in GHGs and smog causing pollutants in Ontario, Canada (Karim, M. M., 2003).

b) Costs 97. Kabul presently has no capacity to test vehicles for emissions. In order to circumvent capacity problems in government agencies, testing can be done by private firms. Such a scheme, involving all vehicles may require a total cost of approximately AFA 60 million (AFA 200 per test, 0.3 million vehicles). A reduction in fuel costs, associated with improved engine performance, would offset the maintenance costs. 98. The scheme involving inspection by private firm might include the following actions

• private firms would be licensed to carryout inspections • government authorities would spot-check the private firms to oversee inspections • government can regulate repair technicians certification, train inspectors and

regulate test price • vehicles that pass the test would get a sticker valid for a specific period, and

drivers would show the test report on request • emission test sticker will be a pre-requisite for annual vehicle licensing renewal • vehicles would be spot-checked

c) Policy Instruments and Target Groups 99. Government should develop a regulation for maintaining emission testing for all vehicles complying with standards and inspection scheme. This scheme should be combined with mandatory requirement of annual renewal of license plate. The requirements for a regular inspection have two significant impacts. First, the inspection requirements discourage tampering and act as a stimulus for the majority of motorists to improve or continue the proper maintenance of their vehicles. Second, those vehicles that fail the inspection will be required to undergo some level of repair. Term 100. An inspection and maintenance scheme can be implemented within 5 years. A summary of this measure is given in Table 13.

Table 13: Implementation of an Inspection and Maintenance Scheme Effectiveness: 35% reduction, 594 tons PM10 Costs: AFA 60 million; maintenance costs are expected to be offset by

improved fuel efficiency. Benefits: Reduced mortality, 76; reduced RSD 1.68 million; avoided health

costs, AFA 258 million; reduction of CO; VOC emissions; safer automobiles (if roadworthiness is included in the scheme).

Instruments/institutions: Implementation of existing rules; arrangement for involvement of private firms.

Term: Two to five years Target groups: Private sector.

4.2.2 Improving Fuel Quality 101. Diesel's ignition and combustion properties are important parameters for explaining PM10 emission from diesel engines (Hutcheson and van Paassen, 1990, Tharby et al., 1992). These properties include: volatility (boiling range), viscosity, and cetane number (an indicator of its ignition properties). Diesel quality is also determined by the presence of

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detergents and dispersants in diesel fuels. These additives keep injection systems clean and have a discernible impact on efficiency (Parkes, 1988).

a) Effectiveness 102. An improvement in the properties of diesel fuel, as expressed by a higher cetane number and the addition of detergents results in a 10 percent reduction in PM10 emission. Reducing the sulfur content from fuel also leads to a proportional decline in SO2 emission. PM10 emission also decreases because a part of the particulates comes from sulfur in the fuel as secondary pollutant.

b) Costs 103. The cost of improving diesel fuel, especially improving the cetane number, is determined by the oil-product market, the refinery structure (capacity for producing light fuels, visbreaking, hydrotreating etc.), and government involvement in the national market. The latter finally determines the price of fuels at the pump. 104. The cost of reducing the sulfur content of diesel stems from the requirement for extensive desulfurization at the refinery. The cost of reducing sulfur from 0.7 percent to 0.2 percent is US$ 0.01 per liter, which is a huge investment to set-up a refinery in Afghanistan. The alternative is to make arrangement in fixing maximum sulfur content while importing diesel fuel. Afghanistan National Standardization Authorization (ANSA) proposed a maximum of 0.1% sulfur for diesel and 0.05% in gasoline. Ministry of Commerce should maintain these standards while importing petroleum fuel. This is the easiest way to control SO2 emissions from petroleum fuel. When combusted, the sulfur in diesel fuel forms corrosive sulfuric acid. Therefore, lowering the sulfur content leads to a financial benefit, as there is a parallel reduction in the cost of vehicle maintenance and repair.

c) Policy Instruments and Target Groups 105. Recommendations to improve the quality of diesel fuel would affect the energy policy of Afghanistan and therefore authorities dealing with energy and fuel standards need to be involved, especially Afghanistan National Standardization Authority (ANSA). Mean while, the adulteration of diesel and gasoline to be checked by collecting and testing samples at retail outlets. At present only one laboratory, under Department of Thermal Power, has such facility. KAQM Project is attempting to assemble manual densitometers and blotter pads, similar to those used in India at service stations, for field screening of diesel and gasoline.

Table 14: Improving Diesel Fuel Quality Effectiveness: 10% Reduction139 tons PM10 Costs: Low. Benefits: Reduced morality, 18; reduced RSD, 0.39 million; avoided health costs,

AFA 60 million; reduction of SO2 emission. Instruments/institutions: Energy authorities Term: Three-five yeas. Target groups: Petroleum industry.

d) Term 106. The required adjustment in fuel standardization, such as ascertaining the sulfur content in diesel, would take about 3-5 years. A summary of benefits, for improving diesel fuel quality is given in Table 14.

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4.2.3 Adoption of Clean Vehicle Emission Standards 107. Many countries have adopted standards for permissible emissions from vehicles. These standards require vehicles with four-stroke gasoline engines to be equipped with exhaust gas control devices based on the use of three-way catalysts (closed-loop systems). A few countries, including Austria and Taiwan, have also set standards for motorcycle emissions, requiring that two-stoke engine-powered vehicles to be equipped with open-loop catalysts. Such catalysts control VOCs, PM10, and CO emissions, but not NOx. The catalysts technology uses unleaded gasoline, the lead content of which should be less than 0.05 percent. Therefore, introducing such standards requires the infrastructure for producing and distributing unleaded gasoline. 108. Diesel-powered vehicles are also subject to regulations. The emission requirements are met by adjusting the motor design and management plan. Tailpipe emission treatment may also be used, and existing buses can be retrofitted with abatement equipment like diesel filter.

a) Effectiveness 109. Closed-loop catalytic treatment of exhaust gases in gasoline engine vehicles (three-way catalysts) reduces exhaust emissions of NOx, CO, and VOC by about 85 percent. In addition, lead emissions are reduced by 100 percent, as unleaded fuel is prerequisite for this type of standards. 110. Open-loop catalytic treatment of exhaust gases in two stroke motorcycles reduces CO, VOC and PM10 (oil mist) emissions by, as much as 90 percent. Successful use of these catalysts also requires unleaded gasoline. An alternative is using well designed and adequately maintained four stroke engines. A similar emission reduction can be obtained following this approach. These measures would not be effective to the majority of vehicles in Kabul as they are old and poorly maintained. However, government can take policy measures on import ban of vehicles without catalytic converter.

b) Costs 111. Due to methodological difficulties, it is not possible to calculate the total costs of introducing these standards in Kabul. However, costs can be estimated on a vehicle-by-vehicle basis. 112. The cost of closed-loop catalytic treatments of exhaust gases stems from the increased purchasing cost of vehicles. In the United States, this increase averages US$400, ranging from US$300 to US$500 (Wang et al., 1993). While catalytic devices have a minor adverse effect on fuel economy, the associated costs are compensated by an increase in the lifetime of replacement parts such as the exhaust system. The total annual cost per automobile is estimated at US$ 100 (US$50 depreciation per car and US$50 extra fuel costs) or AFA 5,000. 113. The cost of open-loop catalytic treatment of exhaust gases is related to increased equipment costs and decreased fuel costs due to improved engine operation. Taiwan has adopted standards requiring the use of open-loop catalytic devices. The increased cost of US$60-80 is offset by fuel savings (Binnie & Partners, 1992). Total annual costs are estimated at US$75 or AFA 3,750 per vehicle (depreciation plus increased fuel costs). It is assumed that the cost for two-stroke engines or motorcycles is similar to the cost for four-stroke engines. A summary of measures for adoption of clean vehicle standards is given in Table 15.

Table 15: Adoption of Clean Vehicle Standards Effectiveness: 80% effectiveness per gasoline vehicle (248 tons)

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Costs: AFA 5,000 per vehicle (AFA 805 million) Benefits: Reduced mortality, 33; reduced RSD, 0.70 million; avoided heath costs, AFA

108 million; reduction of emissions of CO, NOx, VOC; the main justification for the introduction of these systems in other countries.

Term Two to Five Years Target Groups Oil industry – the first move to make unleaded fuel available, vehicle imports,

vehicle manufacturers

4.2.4 Improved Abatement/ Other Propulsion Techniques 114. The other possible improved abatement techniques include: • Alternative Fuel: Using gaseous fuels such as LPG (Liquefied Petroleum Gas) and CNG

(Compressed Natural Gas) for addressing PM10 emissions from vehicles. LPG is widely used in areas where supply is abundant and fuel taxes are favor to use. The effectiveness of this option, if 50 percent of gasoline in passenger cars is replaced by CNG, is given in Table 16.

Table 16: Introduction of CNG to Replace 50% of Gasoline Consumption Effectiveness: 90% reduction of PM10 (140 tons) Costs: Costs for vehicle owner depends on the price differential between gasoline

and CNG (generally natural gas is cheaper) Benefits: Reduced mortality, 20; reduced RSD, 0.4 million; avoided heath costs, AFA

61 million. Trade-off Increased emissions of methane (greenhouse gas), the main constituent of

natural gas Target Groups Energy authorities

• Vehicle Specifications: All imported vehicles should comply with the road design conditions and driving pattern in Kabul.

• The United States and the European Union are discussing ways to tighten standards by enforcing the use of “zero-pollution’ vehicles (for example, electric vehicles in downtown areas).

115. Diesel engines are a bottleneck in decreasing automotive emissions because, unlike gasoline engines, it is not possible to treat their exhaust gases with easily available devices such as catalytic converters, diesel engines, however, are better with respect to CO emissions.

4.2.5 Addressing Resuspension 116. Road dust and wind blown dust are the high-priority issues to address particulate matter in Kabul. Unfortunately, there is a lack of quantitative information about control measures appropriate for Kabul. In general, all possible methods for reducing entrainment should be evaluated and applied on experimental basis to assess their adaptability to Kabul situation. Controlling resuspension of road dust may be the most cost effective way of reducing PM10 exposure. Kabul municipality should consider the following dust control strategy

• Strict enforcement of good construction practices and proper transportation of material.

• Better coordination in construction work on any particular road among utility companies and Kabul municipality.

• Pave or greening of road shoulders, side walks and median. • Manual sweeping of the roads regularly. • Application of biodegradable polymer sprays.

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• Permanent vegetation around Kabul on the exposed areas to arrest wind erosion.

117. Manual sweeping of roads with brooms, at least along the main roads, is an immediate measure to address dust control in Kabul. The total length of main roads in Kabul is 204 km (15.3% of the total road length in Kabul). Assuming the cost of sweeping one kilometer length of road is 6 USD/day and frequency of cleaning is twice in a week, the annual cost of sweeping is AFA 6.4 million. In a study conducted at Thailand (Wongpun, 2001), it was reported that 38 percent of road dust was removed with a similar exercise. The cost benefit analysis of road sweeping is given in Table 17. Care should be taken for the proper disposal of dust instead of sweeping it off of the road in to drainage.

Table 17: Manual Sweeping of Roads. Effectiveness: 38% reduction of PM10 (106 tons) from resuspension of main road dust Costs: Annual cost is AFA 6.0 million Benefits: Reduced mortality, 14; reduced RSD, 0.30 million days; avoided heath costs,

AFA 46 million. Institutions: Municipal authorities Terms: 1-3 years Target Groups: Building and road contractors, material transporters

118. Vacuum assisted street sweeping is more common in USA for the management of storm water pollution. In a study conducted by University of California in 1995, it was found that the vacuum-based street sweeping is 80 percent more efficient than routine street sweeping with brooms in reducing road dust. The study also documented that the PM10-efficient street sweepers removed 99 percent of street surface silt loading. Vacuum assisted street cleaning programs require a significant investment of capital and a yearly operation and maintenance budget. Sweepers have a useful life of about four years, and proper maintenance can greatly improve sweeping efficiency. Arrangements for disposal of the swept material collected must also be made, as well as accurate tracking of the streets swept and the frequency of sweeping. The approximate cost of a vacuum assisted sweeper and its four years operation and maintenance will be about 24 million AFA. However adoptability of this equipment to Kabul road is to be tested. The Kabul municipal authorities may consider to purchase a sweeper and operate in one district for demonstration purpose and to assess its efficiency. 119. Chemical adhesives like advanced polymer emulsions are also very effective in controlling dust emissions. Advanced emulsion formulas improve and stabilize unpaved road surfaces. They work by saturating, penetrating and bonding dust and aggregate particles together, creating a hard, durable surface that offers good longevity and load bearing qualities. The treated surfaces can look like paved roadways, sometimes after only one application. When considering chemical application to suppress dust, consideration should be taken as to whether the chemical is biodegradable or water-soluble and what effect its application could have on the surrounding environment, including water bodies and wildlife. 120. Chemical dust control measures can vary widely in cost, depending on specific needs of the site and level of dust control desired. The approximate cost of unpaved shoulders using a polymer emulsion, as noticed in a study at San Joaquin Valley in California, USA, is about $4,224 per curb mile.

4.2.6 Improvement of Traffic Management 121. 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

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of traffic management is to solve congestion problems. Stopping of public transport close to the immediate vicinity of the intersection must be avoided and drivers will be encouraged to stop at designated areas only. Curbside traffic management may improve air quality, but it may also increase air pollution because it usually results in the increased use of the transport system. In terms of exposure, traffic management leads to improvement in downtown air quality and reduction in road exposure. In terms of total exposure, however, the net result may be small. Improved traffic management has other environmental benefits such as less noise and congestion. Although more detailed analysis is needed, traffic management appears to be a cost-effective policy.

4.2.7 Construction and Improvement of Mass-Transit Systems 122. Promotions of better public transportation services like increased fleet and better network design of Millie buses, the rehabilitation of electric trolley-bus services and better coordination among the services in Kabul to avoid route conflict of various transit modes. The exponential growths in traffic and population activities in Kabul have virtually reduced the efficiency of transportation systems. The existing transportation infrastructure in Kabul could not bear the current traffic loads. The level of services and options of transportation modes are not at all convenient for the passengers and either for the environment. After a preliminary investigation and consultation with various stakeholders in August 2006 it has led to recommend measures to increase transportation infrastructures. The most cost effective option is to rehabilitate the decades old electric trolley-bus system in Kabul. In 1979, the trolley bus used to carry 21 million passengers per year. The rolling stock consisted of 80 trolley-buses and Czech Republic provided technical assistance for the establishment of a large depot in the Khushal Khan area. Currently some of the infrastructures are in place and it can reduce extensively traffic congestion and pollution after the rehabilitation. The total investment cost for this system is estimated to be approximately US$23 million. This is a balancing package of investment to increase the capacity, convenience, and reliability of public mass transport, which is environmentally less damaging. The result of these measures should improve access and a better quality of life in Kabul City. However due to present power shortages at Kabul, this measure to be implemented in long term.

4.3 INDUSTRIAL COMBUSTION (EXCLUDING BRICK MANUFACTURING) 123. Major industries in this category include thermal power plant and asphalt plants. The use of cleaner fuel such as low sulfur oil, cleaner coal, or natural gas may be used to reduce emissions of NOX and CO2.

4.4 BRICK MANUFACTURING 124. Brick manufacturing is a major source of pollution in Kabul. As fuel costs are a significant portion of the cost of brick production, measures to improve the energy efficiency of kilns are beneficial to both the environment and the economy of brick manufacturing. De Lange (1989) suggested a number of simple technological improvements such as improved thermal insulation, mechanical draft, etc, to improve the energy efficiency of kilns. A decrease in fuel consumption would reduce emissions as well. Replacement of coal and biomass with electricity would also be an option if consistent electricity supply is available. 125. Vertical Shaft Brick Kiln (VSBK) is a new environment friendly and socially benign technology can be adapted to Kabul. The VSBK technology saves energy between 40 to 50%, reduces emissions by 80 to 90 %, improves drastically working conditions, and is economically viable. Swiss Agency for Development and Corporation (SDC) conducted a feasibility study in November/ December 2005 to assess the need for cleaner brick production and a potential for overall improvement of the brick manufacturing sector in

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Afghanistan. The study revealed a booming Afghan construction sector due to large numbers of public and private post-war reconstruction initiatives resulted in a significant increase in demand for bricks and therefore in a growing brick making industry. A detailed assessment of the current brick production sector with regard to technological, environmental, economic, social, and institutional aspects confirmed a high need for improvement. The existing brick making technologies generate serious air emission. Ongoing inefficient firing methods include the burning of tires and scarcely available wood. 126. As a technology shift does not only concern the firing method but also the entire production system, a technology transfer is only effective and sustainable if a holistic approach is applied. A holistic approach considers besides the technology and environment also economic, institutional, and social aspects. Experiences in India and Nepal have shown that a pilot project approach is most appropriate to adapt and optimize the technology to the local context and to anchor know-how and expertise within the existing institutional set up. 127. In 2006 the VSBK Technology Transfer to Afghanistan was launched through Swiss Resource Centre and Consultancies for Resource and Development (SKAT). This includes the active involvement of key stakeholders such as pilot entrepreneurs, support service providers, government departments, etc. SKAT has implemented first knowledge sharing and capacity building activities which have been organized by the ongoing VSBK Programs in Nepal and India. Stakeholders receive and exchange tangible information about the VSBK technology for informed decision making as well as to be enabled to arrange for the required pilot project preparations. 128. In a case study in India, the advantages of VSBK found are: (i) Improved energy efficiency 20 percent more efficient than Bull’s Trench Kilns (BTKs) and 50 percent more efficient than clamps. Other important advantages are uniformity of quality and lower breakage levels; (ii) Reduced air pollution: SPM emissions from VSBKs are very low and both obvious and fugitive emissions are significantly lower.

4.5 DOMESTIC EMISSIONS AND REFUSE BURNING 129. In developing countries, the problem of indoor air pollution far outweighs the ambient air pollution. There are four principal sources of pollutants of indoor air; (i) combustion, (ii) building material, (iii) the ground under the building, and (iv) bio-aerosols. Domestic emissions from stoves and refuse burning, together with resuspension, are the main sources of air pollution in Kabul. Majority of the households cook their food using biomass fuels like crop residues and wood. The stoves used for cooking are not energy efficient. The fuels are not burned completely. The incomplete combustion of biomass releases complex moisture of organic compounds, which include suspended particulate matter, carbon monoxide, poly organic material etc. Domestic emissions are also caused by generators and space heating in winter posing special threat to the health of women and children. 130. Immediate intervention is needed avoid high degree of morbidity and mortality due to indoor air pollution in Kabul. The intervention program should include (i) educating people and promoting awareness, which may lead to people finding ways of minimizing exposure through better kitchen management and infant protection; (ii) use of particulate filtration masks by sensitive groups like young, old and ill; (iii) changes in pattern of fuel use, like using cleaner fuels or switching to LPG or solar cooking; (iv) modification in stove design to make them fuel efficient and provide them with a mechanism (e.g. chimney) to remove pollutants from the indoor environment.; (v) Improvement in the ventilation such as putting a window above the cooking stove and providing cross ventilation through the door may help in diluting the pollution load; and (vi) collaboration and commitment between agencies responsible for health, energy, environment, housing and rural development.

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131. Refuse burning can be avoided by extending the public refuse collection system. This may require an increase in municipal taxes, or overall management.

4.6 CONCLUSIONS 132. This Chapter describes a number of measures that are appropriate for improving the air quality in Kabul and explains their effectiveness, costs, benefits, implementation, and the institutions and authorities that would be responsible for each of the measure. A comparison of the costs and benefits leads to the prioritization of the measures. 133. Traffic emissions are a major cause of air pollution. Measures that stand out from a cost-benefit point of view are:

• Inspection and maintenance of vehicles • Improving diesel quality • Adoption of clean vehicle emission standards • Improved abatement/other propulsion techniques • Improvement of traffic management • Improved public bus services and rehabilitation of electric trolley bus system • Introduction of alternative Fuels • Dust suppression.

.

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5 ACTION PLAN 5.1 ACTIONS TO IMPROVE AIR QUALITY AND ITS MANAGEMENT 134. The proposed action plan is based on the cost-benefit analysis of various measures that reduce air pollution and resulting damages. This plan is based on available data, the shortcomings of which have been identified throughout this study. Improving the database is necessary in order to extend the action plan to include additional measures. The "actions" fall into two categories:

Technical and other measures that will reduce the exposure and damage; and Improving the database, and the regulatory and institutional basis for establishing an

operative AQMS in Kabul.

5.1.1 Actions to Improve Air Quality 135. Actions and measures have been compiled based on the discussion with various stakeholders in Kabul, action plan proposed by the KAQM working groups and the Consultants. The action plan incorporates the following measures.

Implementing an inspection/maintenance scheme for vehicles, Addressing excessively polluting vehicles Improving traffic management Using cleaner fuel oil Improving abatement and other propulsion techniques Improving diesel quality and checking fuel adulteration, Introducing low-smoke lubrication oil for 2-stroke and mixed lubricant engines, Fuel switching in the transportation sector, gasoline to LPG or CNG in vehicles Adopting clean vehicle emission standard Better management and increased fleet of Mini buses to cover an extended network

and rehabilitating electric trolley-bus system. Dust abatement

136. Proposed actions and measures that can be introduced in the short term are given in Table 18. Success of these measures rests with enforcement. It is important to ensure those technical improvements and adjustments such as workshop capacity and capability for tuning engines, and the availability of reasonably priced spare parts. Maintaining low lead content in gasoline is an important measure as it leads to reduction in lead concentrations. In addition it is also a prerequisite for clean vehicle standards.

Table 18: Action plan of abatement measures

Introduction of measure

Effect of measure

Inspection/Maintenance 594 78 1.68 258 60 0.101 Immediate 2-5 years

Improved Diesel Quality 139 18 0.39 60 Immediate 2-5 years

Clean Vehicle Standards 248 33 0.70 108 805 3.242 Immediate 2-5 years

Introduction of CNG 140 20 0.40 61 Immediate 2-5 years

Sweeping of Main Roads 106 14 0.30 46 6.4 0.061 Immediate 2-5 years

Time Frame

Abatement MeasureAvoided

Emissions (tons PM10/yr)

Mortality Reduction

Reduced RSD

(million days)

Annual health

benefits (million AFA)

Annual costs

(million AFA)

Cost of control per

ton emission (million AFA)

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137. Table 19 lists abatement measures for which cost-benefit analysis has not been performed. These measures could also be introduced in the short term, and would benefit air quality. The rehabilitation of electric bus system has tremendous traffic benefits.

Table 19: Additional measures for short- to medium-term introduction Time Frame Abatement Measure/Action Benefits

Introduction of Measure

Effect of Measure

Vehicles Address dilution and adulteration of fuel:

Short-term Short-term

Restrict life time of public utility vehicles and buses

Short-term Medium-Term

Better network design and increased fleet of Millie buses

- improve congestion Short-term Short-term

Traffic management Improve capacity of existing road network

-improve surface Short-term Medium-Term

-remove obstacles -improve traffic signals Extend/develop road network: Improve/eliminate bottlenecks

Short-/medium-term

Medium-Term

Transport demand management Improve existing bus system -improve time schedules Short-term Medium-Term -improve

junctions/stations

-make integrated plan Develop parking policy -restrictions in central

area Short-term Short-term

-parking near mass transit terminals

Short-term

-car-pooling Short-term Rehabilitation of Electric Bus Trolley

-Rehabilitation of existing electric bus trolley system

Medium-term Medium-term

Windblown dust Vegetative cover -Vegetative cover on

exposed areas Medium term Long-Term

Best Construction Practices - Solid waste management by construction workers

Short-term Short-term

Consolidation of dust and soil through application of biodegradable polymers

Immediate reduction in TSP and PM10 levels

Short-term Short-term and sustained

Industries Brick Kilns ‘ – Using of cleaner fuels

and adoption of newer technology


Bakeries and Public Wash-halls ‘- Introduction of cleaner burning stoves and ovens


Domestic Emissions

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Time Frame Abatement Measure/Action Benefits Introduction of Measure

Effect of Measure

Emission from wood combustion ‘- Introduction of chimneys to traditional stoves


‘ – Using of cleaner fuels and switching to LPG or solar cooking

Medium-term Medium-Term

- Educating people and promoting awareness

Short-term Long-term

Population Growth Population influx from rural areas ‘- Development of rural

areas to arrest inflow into Kabul

Long-term Long-Term

5.1.2 Actions to Improve Air Quality Management System 138. A successful AQMS requires putting into action the best possible air quality assessment, damage and cost assessment, institutional and regulatory framework, and awareness building among the public policy makers. A summary of actions to improve the AQMS in Kabul are listed in Table 20.

Table 20: Actions to Improve AQMS

Air Quality Monitoring

• Improve the ambient air quality monitoring system, • Upgrade laboratory facilities and man-power capacities, • Establish a quality control system, • Establish database, suitable for providing Air Quality information

to the public/control agencies/law makers

Emissions

• Produce inventory of industrial emissions, • Develop integrated, comprehensive emissions inventory

procedure, • Study resuspension from roads.

Population exposure • Establish appropriate dispersion modeling tools for control strategy

139. High levels of urban air pollution have created growing tension between the government, people and civil societies in Afghanistan. Poor air quality not only impacts human health, welfare and quality of life, but causes a wide range of environmental damage. Overpopulation of urban centers will undoubtedly affect an increasing percentage of the population in the years to come. Yet, many government departments appear to continue to adhere to the old systems for planning and development, rather than adapting to the needs for urban planning and new growth management strategies. 140. A number of government departments could undertake additional measures to substantially improve air quality. The Ministry of Commerce could take a more aggressive role in issuing licenses to import gasoline, diesel, vehicles and industrial machinery. Banning substandard fuels, used vehicles in poor condition, and old or inefficient machinery would go far to improve air quality and in the end, the economy. The Ministry is also in position to solicit investigation of creation of incentives for use of CNG as a fuel, to further reduce consumption of other imported fuels. 141. Recommended measures for each of these departments are given below.

Traffic Department

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142. The Traffic Department is responsible for vehicle operation nationwide. This department is in a position to establish a system for testing vehicles fro emissions and general safety. They can also stop or restrict registration of used vehicles, especially ones with worn out engines, poor performance and high pollutant emissions. Many of large vehicles and buses are said to be up to 60 years old. It is also claimed, and is likely true, that emissions of older heavy duty vehicles can be 20 times, or more, that of ones less than 10 years old.

Municipalities 143. Municipal Departments are responsible for urban planning, management and land use. They also engage in transportation planning and mapping of roadways and pedestrian routing as well as waste management and disposal. It is essential that the municipality consider all issues in developing, zoning and approving new housing and urban development. As such, the Department is de facto in many regards responsible for greening and cleaning the cities. Reforestation and regreening can also be tools for improving air quality when properly designed and implemented. Kabul is mushroomed by spotted security areas numbering hundreds, which has resulted in closure of roads indefinitely with virtually no access to through traffic. These causes traffic congestion in other alternative routes. The municipality should initiate negotiation with international organizations to slowly relocate them from the urban centers. 144. Environmental authorities and municipalities have a broad range of means and policy instruments at their disposal to prevent and combat air pollution in Kabul. Such efforts and policies might include:

1. Better developed legal and institutional framework 2. Improvement of technical capacities 3. Improvement of administrative capacities 4. Improved knowledge of use of environmental management equipment 5. Public education and promotion of public support 6. Development of natural resource management and reclamation, and associated

economic incentives for sustainable development

Ministry of Agriculture, Animal Husbandry and Food 145. In past the Ministry was responsible for reforestation and urban greenery through its already existed tree nurseries. The department of Forestry and Range Management was responsible for environmental matters. Most recently the National Environmental Protection Agency (NEPA) has been established to address and manage environmental issues. Participation of the Ministry and NEPA in an air quality management program will be critical to development of workable and sustainable strategies for improvement of air quality in Kabul and other cities of Afghanistan.

Ministry of Commerce 146. Mixed vehicle specifications are growing concerns in Kabul. NEPA should coordinate with the Ministry of Commerce on specifications of all vehicles imported to Afghanistan. All imported vehicles should comply with the road design conditions and driving pattern in Afghanistan. 147. Fuel adulteration is widespread in Afghanistan. Differences between the prices of gasoline and diesel and the price of adulterants such as kerosene and industrial solvents for vehicles and non-vehicle fuels have led to adulteration of more than 55% of vehicle fuels by some estimates. This adulteration of vehicle fuel can significantly increase harmful vehicle emissions. While adulteration of diesel fuel with small amounts of kerosene does not cause

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increased emissions, other adulterants of gasoline and diesel fuels typically cause increased emissions of hydrocarbons, carbon monoxide, and oxides of nitrogen. Emissions of other toxic substances such as benzene and polycyclic aromatic hydrocarbons may also occur, and engine malfunctions or failure may follow sustained use. The primary barrier to resolving this pervasive problem is the lack of adequate testing facilities to monitor fuel supplies and compliance and enforcement measures. The Ministry of Commerce consists of various Departments that deal with the import-export and quality control. The Department of Statistics collects all data of the commodities import to Afghanistan. Department of Gasoline Monopoly is also in a key position to enforce quality control of the gasoline imported to and distributed in Afghanistan. In past a quality control laboratory in the Department was responsible for the imported fuel and the standardized test of the fuel. The laboratory is no longer operational. Reinstitution of this capacity is vital to the effective control of fuel quality in Afghanistan. In the interim, samples can be sent offshore to Pakistan, India or Dubai – but this is not a satisfactory or cost-effective long-term solution.

Ministry of Public Health 148. Air pollution has been associated with a variety of adverse health effects. These include impairments of lung function, increased incidence of chronic bronchitis, exacerbation of chronic respiratory disease (asthma) or indications of coronary disease such as angina, and premature mortality from respiratory and cardiovascular disease. The less serious effects include increased incidence of acute respiratory illnesses (colds and sinus problems and sub-clinical effects such as Inflammation of the nasal mucous membranes and itchy, watery eyes. 149. The Department of Environmental Health and Hygiene will play an essential role in providing baseline data on disease, effects on humans and changes in the health of the general population as a result of changes in air pollutant exposures. Such data will substantiate the intuitive and serve as reinforcement for changes in activities that result in increased air pollutant emissions. Cleaner air results in better health.

Ministry of Housing and Urban Development 150. The role of Ministry of Urban Planning is to mange the spatial organization of cities for efficient allocation of urban infrastructure and land use. Depending on how it is applied, urban planning can improve air quality in the long run by strategic location and control of sources of air pollution, reducing the number of persons exposed, and encouraging a city structure that will minimize accumulation of pollutants. 151. Most cities in Afghanistan have been damaged or destroyed by war and internal conflict. Effective and satisfactory rehabilitation of such cities requires basic urban planning. The Ministry of Housing and Reconstruction has been responsible for urban planning, and to prohibit the misallocation of land use and growth in urban areas that are nor conductive to environmentally sound economic development. The Ministry is empowered to ban the siting of new industries in metropolitan areas and require industrial zoning to be established in proper directions and at proper distances from metropolitan or other sensitive areas. Moreover, the Ministry could translate the issue of reconstruction into an effective urban planning tool to improve overall environmental conditions.

Ministry of Transport

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152. Policies to support the increase of development and use of clean public transport systems would result in reduced use of private vehicles – and reduced emissions of air pollutants in the urban environment. Regardless of success in that area, An additional objective should to minimize the direct air pollution impacts of current and future public transport systems. 153. The Department of Private Sector in the Ministry of Transport, and the government Urban Transportation System is supervised by the Ministry. It is also responsible for overall management of the road transportation system. The Ministry can and must play a very important role in the improvement of urban air quality – and energy efficiency. in the transportation sector

Ministry of Energy and water 154. Forest, air, and other environmental resources are affected by energy policies. The energy sector is already causing environmental impacts throughout the energy supply chain, including air pollution from the combustion of fossil fuels, soil and water pollution resulting from oil and gas leaks, and poor refinery and production process. The Ministry of Energy will play fundamental role in air quality control by introduction and encouragement of environmentally friendly and energy efficient technologies, including renewable energy. Enforcement of reduced fuel consumption through energy efficiency measures would reduce per capita consumption of fuels, resulting in likely improvements in air quality. Such measures would also include increased use of all renewable energy resources, including wind, solar, hydroelectric and biogas. Utilization of the most appropriate technologies is essential to rebuilding a secure and self-sufficient the energy sector – and to improving air quality in Afghanistan.

Ministry of Mines and Industries 155. Poorly managed industrial development, can lead to significant, long-term social and environmental impacts. Afghanistan has a culturally strong and vigorous private sector but almost no significant industrial development. The situation may deteriorate further as future reconstruction places additional demands on the resource endowments. Effective environmental management will require the support of the Ministry, to integrate environmental considerations into industrial development and mining practices. Such controls are most readily implemented through a well-defined construction and operation permitting, and compliance and enforcement system. The Ministry is also empowered to prevent illegal trade in hazardous waste. Further development of best environmental practices in the private sector, subjected to economic instruments including taxes, permits, emissions fees, performance of EIAs and demonstration of environmental regulatory compliance relevant regulations should be considered by the ministry.

NGOs and Civil Societies 156. Lack of information is one of the critical factors impeding introduction and implementation of sound air pollution control policies. Residents may observe black smoke, but may not recognize the toxicity of invisible pollutants. Some may note that smoke from biomass combustion causes their eyes to water, but not link smoke to much more damaging health effects. The government is in the position to inform civil society about why it is taking what may, on occasion, be unpopular actions to reduce air pollution. Conversely, civil society and particularly NGOs can bring pressures on people to think for themselves and take actions in reducing pollution. NGOs can also contribute by raising public awareness through many channels. Information dissemination is one of the most important roles that NGOs and the media can play. NGOs can also be effective in data collection, to support informed decision on environmental management.

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Private Sector 157. Many of the entities engaged in activities that affect urban air quality are in the private sector. For an air quality policy to be effective there must be an incentive for the private sector to comply – if not support – environmental management policies. The incentive may be financial, in the form of emission fees, liabilities, permit fees, costs of noncompliance (fine, restricted operation or closure). More incentives can also be identified and advertised for peer pressure to influence behavior, and to guide consumer preferences that may affect market share. In all of these dimensions, the incentives are likely to be more powerful if the agents themselves have been involved in the formulation of the policies.

Formation of a Consultative Committee 158. Air quality management is complex because a large number of stakeholders, often in different sectors, driven by objectives and motives other than environmental improvement, are involved. Setting emission standards can easily involve a number of key ministries in prioritizing and adopting policies that can improve air at small incremental cost. Air quality management requires sustained and cooperative actions over a long period. Forging cross-sectoral coordination is essential. To ensure proper development of a responsive program for Air Quality Control in Kabul, many activities must be initiated – some dependent others independent – to start to address the current air quality problems. To address the issue of air quality in Kabul – and beyond – it is recommended that a standing consultative committee comprised of key decision makers from relevant ministries and institutions be formed. It is proposed that members of the committee include representatives from the following ministries and institutions

1. National Environmental Protection Agency (NEPA) 2. Ministry of Commerce (Department of Gasoline Supply) 3. Ministry of Justice (legislative divisions) 4. Kabul Municipality (Sanitation and Greenery Department) 5. Traffic Department 6. Kabul Police Department 7. Ministry of Urban Development and Housing 8. Ministry of Transport 9. Ministry of Health 10. Kabul University 11. ADB 12. UNDP 13. ISAF 14. An NGOs coordination council in Kabul

159. The Consultative Committee members would initially meet once a month. The committee would:

• Review concise briefing notes for use by policy makers, non-governmental organizations, industry, academics, and researchers, highlighting issues, policy considerations, proposed approaches and soliciting comments from potentially affected parties.

• Commission reviews and studies to evaluate the current state of knowledge and practices, and to make recommendations for improvement

• Work together for successful implementation of the project and environmental regulatory measures

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6 EXISTING LAWS AND INSTITUTIONS 6.1 LAWS AND REGULATIONS ON AIR POLLUTION 160. The government of Afghanistan has developed Environmental Act in 2005 and presently making efforts to develop regulations and policies for various environmental components. At present there is no existing regulation/policy that directly addresses air pollution in Afghanistan. A phased Ambient Air Quality Standards for Afghanistan is proposed based on WHO Air Quality Guidelines and is included in Appendix 2.

6.2 INSTITUTIONS INVOLVED National Environmental Protection Agency 161. The National environmental Protection Agency (NEPA) is responsible for implementation of the Environmental Act of Afghanistan and develops policies, laws and regulations in Afghanistan. The functions of NEPA include:

1. maintain environmental integrity and promote the sustainable use of natural resources;

2. promote conservation and rehabilitation of the environment; 3. coordinate environmental affairs at the international, national and local levels; 4. develop and implement national environmental policies and strategies in order to

integrate environmental issues and sustainable development approaches into the legal and regulatory frameworks;

5. provide environmental management services in the areas of environmental impact assessment, air and water quality management, waste management, pollution control, and permitting related activities;

6. establish communication to outreach for environmental information to ensure improved awareness of environmental issues;

7. implement bilateral or multilateral environmental agreements to which Afghanistan is a Party;

8. in cooperation with relevant ministries and public bodies and on a periodic basis, gather information, including baseline data, on national environmental conditions and on the changes affecting the environment, publish such information and assessment reports and evaluate and utilize it is in environmental management and planning;

9. coordinate the preparation and implementation of a national program for environmental monitoring and effectively utilize the data provided by that program;

10. prepare every two years in relation to urban areas and every five years in relation to rural areas a State of the Environmental Report for Islamic Republic of Afghanistan for submission to the President’s office;

11. prepare an interim State of Environmental report on emerging issues relevant to the environment in Afghanistan not less than every two years;

12. periodically compile and publish reports on significant environmental indicators; 13. develop and implemental plans for environmental training, environmental education

and environmental awareness-raising in cooperation with relevant ministries and public bodies;

14. actively coordinate and cooperate with ministries, Provincial Councils and District and Village Councils, public bodies and the private sector on all issues related to

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sustainable use of natural resources and conservation and rehabilitation of the environment.

15. fulfill any other function that may be assigned by the Council of Ministers.

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REFERENCES Association of Indian Automobile Manufactures (AIAM), (1994). “Letter from Association of

Indian Automobile Manufacturers to Various Indian Ministries 28/02/1994”. AIAM, New Delhi

Binnie and Partners. (1992). “Modernization of Environmental Monitoring Facilities and capabilities in Response to Philippines’ Energy Development Project.” Interim Report to EMB, Binnie and Partners, Mumbai

Hutcheson, R. and C. van Passen. (1990). “Diesel Fuel Quality into the Next Century.” Shell Public Affairs, London.

Karim, M. M. (2003) “GHG Reduction by Vehicle I/M Program in Ontario, Canada: Application to Developing Countries, International Workshop on CDM/JI in the Transport Sector, Ministry of Land, Infrastructure and Transport, Tokyo, Japan.

Mehta, K.H. (1993). Urban Transport in Asia: An Operational Agenda for the 1990s. Technical Paper No.224. Asia Technical Department Series. Washington D.C.: World Bank

Ostro, Bart. (1994). Estimating the Health Effects of Air Pollutants: A Method with Applications to Jakarta.” Policy Research Working Paper 1301, The World Bank, Washington, D.C.

Parkes, D. (1998) “Matching Supply and Demand for Transportation in the Pacific Rim Countries post – 1990.” Selected Papers. Shell Oil Company, London

Tharby, R.D., W. Vandenhengel, and S. Panich (1992). “Transportation Emissions and Fuel Quality Specifications for Thailand.” Draft Report, Monenco Consultants Ltd., Oakville, Canada

USEPA (2006). “National Ambient Air Quality Standards (NAAQS)” (http://epa.gov/air/criteria.html)

WHO (2005) “WHO Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide”, Global update 2005 (http://www.who.int/phe/air/aqg2006execsum.pdf)

Wang, Q., C.Kling and D. Sperling. (1993). “Light-duty Vehicle Exhaust Emission Control Cost Estimates Using a Part-pricing Approach.” Journal of Air Waste Management Association, 43: 1464-1471

Wongpun L. (2001). “Control of Road Dust”. Regional Workshop Fighting Urban Air Pollution: From Plan to Action. Feb 12-14. 2001. United Nations Conference Centre, Bangkok, Thailand.

C:\Documents and Settings\owner\My Documents\Masud\Projects\2006\2006-1220\Report\KAQM Report\KAQM-Report-Main.doc

Asian Development Bank

National Environmental Protection Agency Islamic Republic of Afghanistan

TA No. 4415-AFG Kabul Air Quality Management

Appendices

January 2007

ENGCONSULT LTD. 21 Queen Street E., Suite 302

Brampton, Ontario, L6W 3P1 Canada Tel: 905 455 7892, Fax: 905 455 2351

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TABLE OF CONTENTS

APPENDIX 1: AIR QUALITY STATUS, KABUL VALLEY...............................................55 APPENDIX 2: PROPOSED AMBIENT AIR QUALITY STANDARDS .............................60 US National Ambient Air Quality Standards (NAAQS)....................................................63 APPENDIX 3: EMISSION INVENTORY .........................................................................65

A. Introduction......................................................................................................65 B. Distribution of Emission Sources.....................................................................65 C. Thermal Power Stations ..................................................................................65 D. Generators ......................................................................................................66 E. Fuel Combustion for Heating, Wash-Halls and Bakeries ................................67

1. Residential Heating .........................................................................................67 2. Public Wash-Halls ...........................................................................................68 3. Bakeries ..........................................................................................................68

F. Brick Kilns.............................................................................................................69 G. Asphalt Plants .................................................................................................70 H. Vehicles and Traffic.........................................................................................70 I. Total Emission Inventory ......................................................................................72

APPENDIX 4: EMISSION FACTORS, PARTICLES ......................................................77 A. Introduction......................................................................................................77 B. Motor Vehicles.................................................................................................77

1. Gasoline ..........................................................................................................77 2. Diesel ..............................................................................................................77

C. Fuel Consumption ...........................................................................................78 D. Generators, Brick Kilns and Asphalt Plants.....................................................79 E. References ......................................................................................................79

APPENDIX 5: SPREADSHEET FOR CALCULATING EFFECTS OF CONTROL MEASURES ON EMISSIONS.........................................................................................80 APPENDIX 6: PROEJCT DESCRIPTION FOR LOCAL CONSULTANTS .....................87

A. Air Quality Assessment in other Cities ............................................................87 B. Damage Assessment and Economic Valuation ..............................................88

1. Physical Impacts .............................................................................................88 2. Economic Valuation.........................................................................................89 3. Other impacts ..................................................................................................90 4. Technological Reduction Options....................................................................90

LIST OF TABLES

Table A1: Details of Measuring Stations and Measured Parameters. ............................55 Table A2: Measured concentration of SO2......................................................................56 Table A3: Measured concentration of NO2 .....................................................................56 Table A4: Measured concentration of PM10 at Station1 .................................................57 Table A5: Measured concentration of PM10 at Station 2 ................................................58 Table A6: Analytical Results of Carbon..........................................................................58 Table A7: Concentration Meal Element in Air ................................................................59 Table A8: WHO Air Quality Guidelines and Interim Targets for Particulate Matter: Annual

Mean Concentrations...............................................................................................60

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Table A9: WHO Air Quality Guidelines and Interim Targets for Particulate Matter: 24-hour Concentrations.a ..............................................................................................61

Table A10: WHO Air Quality Guidelines and Interim Targets for SO2: 24-Hour and 10-Minute Concentrations.a...........................................................................................61

Table A11: WHO Air Quality Guidelines and Interim Targets for Nitrogen Dioxide (NO2).................................................................................................................................62

Table A12: WHO Air Quality Guidelines for Carbon Monoxide (CO) ..............................62 Table A13: WHO Air Quality Guideline and Interim Target for Ozone: 8-Hours

Concentration...........................................................................................................62 Table A14: National Ambient Air Quality Standards .......................................................63 Table A15: Summary Inventory of Emission Sources....................................................65 Table A16: Annual Emissions from the Thermal Power Plant .......................................66 Table A17: Inventory of Portable Power Generators .....................................................66 Table A18: Annual Emissions from the Generators .......................................................67 Table A19: Inventory of Heating Sources ......................................................................67 Table A20: Emissions from Heating Sources................................................................68 Table A21: Annual Emissions from Public Wash-Halls..................................................68 Table A22: Annual Emissions from Bakeries .................................................................69 Table A23: Inventory of Brick Kilns and their Fuel Usage..............................................69 Table A24: Annual Emissions from Brick Kilns ..............................................................70 Table A25: Annual Emissions from Asphalt Plants ........................................................70 Table A26 : Vehicle Population and their Annual Travel Times ......................................71 Table A27: Annual Emissions from Vehicles .................................................................71 Table A28: Population Distribution in Different Districts of Kabul ...................................72 Table A29: Total Emission Inventory ..............................................................................73 Table A30: Percentage Contributions to Emission Inventory..........................................73 Table A31: Emission Factors (g/km) for Particulate Emissions from Motor Vehicles .....78 Table A32: Selected emission Factors (g/km) for Particulate .........................................78 Table A33: Emission factors for oil combustion ..............................................................78 Table A34: Emission factors for oil combustion ..............................................................79

LIST OF FIGURES

Figure A1: Location Map of Kabul (Source: AIMS, Kabul) ..............................................74 Figure A2: Locations of Residential and Industrial Areas in Kabul (Source: AIMS, Kabul)

.................................................................................................................................75 Figure A3: Road Network of Kabul (Source: AIMS, Kabul).............................................76 Figure A4: KAQM Spreadsheet for Emission Calculation ..............................................82 Figure A5: Spreadsheet for Emissions Calculation........................................................84 Figure A6 : Spreadsheet for Emissions Calculation........................................................86

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APPENDIX 1: AIR QUALITY STATUS, KABUL VALLEY 1. Eight air quality monitoring stations have been installed in Kabul under this Project and collection of 24-hour average samples for PM10, NO2 and SO2 from these stations started from May 2006. As appropriate laboratory facilities do not yet exist in Afghanistan, the samples are currently sent to a laboratory in USA for analysis. 2. Short-term air quality studies were conducted in Kabul in the past during 2003 and 2004 by an Environmental and Industrial Health Hazard (EIHH) Special Support Team (SST) deployed by the Canadian ISAF contingent and Norwegian Institute for Air Research (NILU) on behalf of the Norwegian ISAF contingent. 3. The EIHH SST team has collected 337 air samples during June and October 2003 at various locations in Kabuli to characterize the general air quality and to measure the concentrations of potentially harmful pollutants. Detailed analysis of the air samples collected in the Canadian AOR (area of responsibility) indicated that no contaminants of concern were present at concentrations high enough to present significant health risks to the deployed troops. However, EIHH identified elevated levels of PM10 and vehicle hulks in the air. It was observed that airborne PM originated from camp construction activities, activities of local population, and naturally occurring sources like sand storms. The results of this study are not available to present in the report. 4. NILU has collected air quality data for PM10, SO2, NO2, various metals and carbon compounds during January to March, 2004 to study the air pollution in Kabul exposed by Norwegian military. Four air quality stations are installed in Kabul to monitor the variations of the air quality. Three stations are installed inside Kabul (near Norwegian military camp, Norwegian embassy and behind the administration building) and the fourth station was installed, outside Kabul on upwind direction, to study the background concentrations. The stations located in a military camp and assy are used to measure all pollutants while the other two stations are used to study the concentrations of NO2 and SO2 only. Operating period of each monitoring station and the parameters measured at each station are given in Table A1.

Table A1: Details of Measuring Stations and Measured Parameters. Measuring

Station Location Measuring Period NO2 SO2 PM10 Metals Carbon

Kabul 1 Norwegian Military Camp

10.01.01-14.03.04 x x x x x

Kabul 2 Norwegian Embassy

12.01.04-08.03.04 x x x x x

Kabul 3 Behind Administration Building

10.01.04-14.03.04 x x

Kabul 4 Background location

10.01.04-14.03.04 x x

5. The concentrations of SO2 and NO2 are found to be very high. The maximum concentrations observed for SO2 is 46 µg/m3 and for NO2 is 70 µg/m3. Air quality data for SO2 and NO2 are presented in Table A2 and Table A3, respectively. Average concentration of SO2 at barracks is 29 µg/m3, which is comparatively higher than average SO2 concentration at embassy, 21 µg/m3, located in the centre of the city. The high concentrations at barracks are may be due to the excessive use of fossil fuels like diesel for vehicles and generators. During the entire sampling period, only two times the

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concentrations of PM10 found to be less than 50µg/m3. Average background concentration of SO2 is 10 µg/m3.

Table A2: Measured concentration of SO2 From To Measuring

Period Position µg/m3

2004.01.10 2001.01.17 7 Kabul 1 46 2004.01.17 2004.01.24 7 Kabul 1 34 2004.01.24 2004.02.06 13 Kabul 1 31 2004.02.06 2004.02.22 16 Kabul 1 31 2004.02.22 2004.02.29 7 Kabul 1 26 2004.02.29 2004.03.07 7 Kabul 1 11 2004.03.07 2004.03.14 7 Kabul 1 21 2004.01.12 2004.01.19 7 Kabul 2 34 2004.01.19 2004.01.26 7 Kabul 2 24 2004.01.26 2004.02.02 7 Kabul 2 19 2004.02.02 2004.02.09 7 Kabul 2 24 2004.02.09 2004.02.16 7 Kabul 2 26 2004.02.16 2004.02.23 7 Kabul 2 15 2004.02.23 2004.03.02 8 Kabul 2 14 2004.03.02 2004.03.08 6 Kabul 2 14 2004.01.10 2004.01.17 7 Kabul 3 32 2004.01.17 2004.01.24 7 Kabul 3 18 2004.01.24 2004.02.06 13 Kabul 3 23 2004.02.06 2004.02.22 16 Kabul 3 18 2004.02.22 2004.02.29 7 Kabul 3 <2 2004.02.29 2004.03.07 7 Kabul 3 7 2004.03.07 2004.03.14 7 Kabul 3 16 2004.01.10 2004.01.17 7 Kabul 4 2004.01.17 2004.01.24 7 Kabul 4 16 2004.01.24 2004.02.06 13 Kabul 4 10 2004.02.06 2004.02.22 16 Kabul 4 11 2004.02.22 2004.02.29 7 Kabul 4 12 2004.02.29 2004.03.07 7 Kabul 4 5 2004.03.07 2004.03.14 7 Kabul 4 5

Table A3: Measured concentration of NO2 From To Measuring

Period Position Concentration

(µg/m3) 2004.01.10 2001.01.17 7 Kabul 1 70 2004.01.17 2004.01.24 7 Kabul 1 63 2004.01.24 2004.02.06 13 Kabul 1 62 2004.02.06 2004.02.22 16 Kabul 1 72 2004.02.22 2004.02.29 7 Kabul 1 69 2004.02.29 2004.03.07 7 Kabul 1 38 2004.03.07 2004.03.14 7 Kabul 1 65 2004.01.12 2004.01.19 7 Kabul 2 67 2004.01.19 2004.01.26 7 Kabul 2 60 2004.01.26 2004.02.02 7 Kabul 2 59 2004.02.02 2004.02.09 7 Kabul 2 56 2004.02.09 2004.02.16 7 Kabul 2 87 2004.02.16 2004.02.23 7 Kabul 2 61 2004.02.23 2004.03.02 8 Kabul 2 34 2004.03.02 2004.03.08 6 Kabul 2 59

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From To Measuring Period

Position Concentration (µg/m3)

2004.01.10 2004.01.17 7 Kabul 3 63 2004.01.17 2004.01.24 7 Kabul 3 60 2004.01.24 2004.02.06 13 Kabul 3 44 2004.02.06 2004.02.22 16 Kabul 3 54 2004.02.22 2004.02.29 7 Kabul 3 38 2004.02.29 2004.03.07 7 Kabul 3 29 2004.03.07 2004.03.14 7 Kabul 3 50 2004.01.10 2004.01.17 7 Kabul 4 Fails 2004.01.17 2004.01.24 7 Kabul 4 41 2004.01.24 2004.02.06 13 Kabul 4 26 2004.02.06 2004.02.22 16 Kabul 4 42 2004.02.22 2004.02.29 7 Kabul 4 41 2004.02.29 2004.03.07 7 Kabul 4 5 2004.03.07 2004.03.14 7 Kabul 4 11

6. The maximum concentration observed for PM10 is 704 µg/m3, which is very high compared to the daily average Norwegian standard of 50 µg/m3. The average PM10 concentration at barracks is 198 µg/m3 while the average PM10 concentration at embassy is 328 µg/m3. The variation of PM10 concentrations at monitoring stations 1 and 2 are given in Table A4 and Table A5 respectively.

Table A4: Measured concentration of PM10 at Station1

From To Ave. Time (h) Conc.

From To

Ave. Time (h)

Conc.

2004.01.10 2004.01.11 24 12 2004.02.08 2004.02.09 24 2004.01.11 2004.01.12 24 163 2004.02.09 2004.02.10 24 54 2004.01.12 2004.01.13 24 148 2004.02.10 2004.02.11 24 111 2004.01.13 2004.01.14 24 155 2004.02.11 2004.02.12 24 140 2004.01.14 2004.01.15 24 198 2004.02.12 2004.02.13 24 139 2004.01.15 2004.01.16 24 77 2004.02.13 2004.02.14 24 189 2004.01.16 2004.01.17 24 43 2004.02.14 2004.02.15 24 304 2004.01.17 2004.01.18 24 157 2004.02.15 2004.02.16 24 286 2004.01.18 2004.01.19 24 217 2004.02.16 2004.02.17 48 2004.01.19 2004.01.20 24 251 2004.02.18 2004.02.19 24 165 2004.01.20 2004.01.21 24 200 2004.02.19 2004.02.22 72 2004.01.21 2004.01.22 24 2004.02.22 2004.02.23 24 229 2004.01.22 2004.01.23 24 2004.02.23 2004.02.24 24 111 2004.01.23 2004.01.24 24 2004.02.24 2004.02.25 24 254 2004.01.24 2004.01.25 24 2004.02.25 2004.02.26 24 209 2004.01.25 2004.01.26 24 2004.02.26 2004.02.27 24 124 2004.01.26 2004.01.27 24 2004.02.27 2004.02.28 24 151 2004.01.27 2004.01.28 24 2004.02.28 2004.02.29 24 159 2004.01.28 2004.01.29 24 2004.02.29 2004.03.01 24 278 2004.01.29 2004.01.30 24 2004.03.01 2004.03.02 24 208 2004.01.30 2004.01.31 24 108 2004.03.02 2004.03.07 120 2004.01.31 2004.02.01 24 96 2004.03.07 2004.03.09 48 2004.02.01 2004.02.02 24 126 2004.03.09 2004.03.10 24 283 2004.02.02 2004.02.03 24 2004.03.10 2004.03.11 24 240 2004.02.03 2004.02.04 24 135 2004.03.11 2004.03.12 24 279

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From To Ave. Time (h) Conc.

From To

Ave. Time (h)

Conc.

2004.02.04 2004.02.05 24 157 2004.03.12 2004.03.13 24 259 2004.02.05 2004.02.06 24 199 2004.03.13 2004.03.15 48 2004.02.06 2004.02.07 24 2004.03.15 2004.03.16 24 296 2004.02.07 2004.02.08 24 102 2004.03.16 2004.03.17 24 486

Table A5: Measured concentration of PM10 at Station 2

From To Ave. Time (h) Conc. From To Ave.

Time Conc.

2004.01.13 2004.01.14 24 609 2004.02.09 2004.02.10 24 145 2004.01.14 2004.01.15 24 704 2004.02.10 2004.02.11 24 96 2004.01.15 2004.01.18 72 2004.02.11 2004.02.12 24 169 2004.01.18 2004.01.19 24 612 2004.02.12 2004.02.15 72 2004.01.19 2004.01.20 24 625 2004.02.15 2004.02.16 24 338 2004.01.20 2004.01.21 308 2004.02.16 2004.02.17 24 405 2004.01.21 2004.01.22 63 2004.02.17 2004.02.18 24 174 2004.01.22 2004.01.25 72 2004.02.18 2004.02.19 24 155 2004.01.25 2004.01.26 24 298 2004.02.19 2004.02.23 96 2004.01.26 2004.01.27 24 425 2004.02.23 2004.02.24 24 549 2004.01.27 2004.01.28 24 312 2004.02.24 2004.02.25 24 689 2004.01.28 2004.01.29 24 98 2004.02.25 2004.02.26 24 283 2004.01.29 2004.02.01 72 2004.02.26 2004.02.29 72 2004.02.01 2004.02.02 24 227 2004.02.29 2004.03.02 48 2004.02.02 2004.02.03 24 567 2004.03.02 2004.03.03 24 120 2004.02.03 2004.02.04 24 481 2004.03.03 2004.03.04 24 416 2004.02.04 2004.02.05 24 192 2004.03.04 2004.03.07 72 2004.02.05 2004.02.08 72 2004.03.07 2004.03.08 24 699 2004.02.08 2004.02.09 24

7. The air quality data of organic carbon (OC), elemental carbon (EC) and total carbon (TC) are given in Table A6. EC/TC ratio is estimated to assess whether the source of carbon is from anthropogenic or natural. Concentrations of metals in the Kabul air quality are given in Table A7. It is observed that about 20% of the carbon is anthropogenic (by product of combustion processes). Only cadmium concentrations have exceeded the WHO guideline of 5 µg/m3.

Table A6: Analytical Results of Carbon

Station Start Date Stop Date OC µg/m3

EC µg/m3

TC µg/m3

EC/TC ratio

PM10

µg/m3 Kabul 1 2004-01-18 2004-01-19 23.07 7.47 30.54 0.245 217Kabul 1 2004-01-19 2004-01-20 36.15 10.47 46.63 0.224 251Kabul 1 2004-02-03 2004-02-04 18.68 6.98 25.66 0.272 135Kabul 1 2004-02-23 2004-02-24 8.31 2.16 10.49 0.207 111Kabul 1 2004-02-24 2004-02-25 16.86 3.94 20.83 0.19 254Kabul 1 2004-03-07 2004-03-09 30.74 10.62 41.36 0.257 475Kabul 2 2004-01-18 2004-01-19 101.63 25.52 127.15 0.201 612Kabul 2 2004-01-19 2004-01-20 108.6 26.27 137.87 0.195 625Kabul 2 2004-02-03 2004-02-04 71.49 19.8 91.3 0.217 418Kabul 2 2004-02-23 2004-02-24 77.12 20.32 97.44 0.209 549

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Station Start Date Stop Date OC µg/m3

EC µg/m3

TC µg/m3

EC/TC ratio

PM10

µg/m3 Kabul 2 2004-02-24 2004-02-25 72.03 25.49 97.53 0.261 689Kabul 2 2004-03-07 2004-03-08 80.15 23.01 103.15 0.223 699Kabul 2 2004-03-08 2004-03-09 54.57 19.62 74.19 0.264 506

Table A7: Concentration Meal Element in Air

2004.01.18

2004.01.19

2004.02.03

2004.02.23

2004.02.24

2004.03.07

2004.01.18

2004.01.19

2004.02.03

2004.02.23

2004.02.24

2004.03.07

2004.03.07

2004.01.19

2004.01.20

2004.02.04

2004.02.24

2004.02.25

2004.03.09

2004.01.19

2004.01.20

2004.02.04

2004.02.24

2004.02.25

2004.03.08

2004.03.09

PM10 (µg/m3) 217 251 135 111 254 475 612 625 481 549 689 699Echelon ng/m3 ng/m3 ng/m3 ng/m3 ng/m3 ng/m3 ng/m3 ng/m3 ng/m3 ng/m3 ng/m3 ng/m3 ng/m3

PB (µg/m3) 17 24.4 -11.6 -11.2 11.7 30.7 99.6 112.8 53.1 62.8 92.5 77.9 53.7Cd (5 µg/m3) 0.3 0.62 0.26 0.14 0.26 0.63 2.2 3.05 1.11 1.35 7.48 2.03 1.22CU -9.8 26.2 -9.1 -8.7 -9.1 20.8 31.4 28.6 22.3 64.5 53.9 38.9 30.2ZN 59.2 57.5 30.4 20.2 39.1 96.7 154.9 183.8 119.9 145.2 212 226.8 138.7Cr 16.2 16.7 15.2 36.2 53.4 65.3 31.8 31.9 28.8 50.6 63.1 69.1 57.1Ni 15 29.8 7.3 7.3 15.2 35.6 32.6 30.3 27.6 44 58.3 47.5 39Co 2.8 2.6 1.4 1.2 3.2 7.1 5.7 5.5 5 6.7 9.2 8.5 6.9Mn (0.15µg/m3) 102.5 90.2 56.1 44.5 128.9 299.9 260.2 242 207.8 260.5 369.1 388.7 311.5V (20 µg/m3) 13.6 11 7.6 6.5 18.6 41.4 29.8 25 27.4 32 36.8 41.2 37.3Fe 5932 5720 3031 2561 6937 14262 10488 10211 10944 14756 13365 16901 14316As 3.6 5.2 1.9 0.8 2.6 5.1 6.3 6.2 5.6 8.3 10.7 9.5 7.1

Kabul 1 Kabul 2

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APPENDIX 2: PROPOSED AMBIENT AIR QUALITY STANDARDS 8. It is easily recognized that ambient air quality in Kabul is quite often poor, and it is generally accepted that establishment of ambient air quality standards (AAQS) that are as stringent as those currently in place in the developed and industrialized World would be meaningless. It is therefore proposed that AAQS that are initially less stringent, but still sufficient to protect and improve human health and welfare, be adopted for Kabul. Formalization of AAQS for Kabul, and the rationale employed, could also serve as the basis for AAQS throughout Afghanistan. Over time, initial standards would be replaced by more stringent standards. The schedule for increased stringency would be based on the ability and feasibility of meeting the more stringent standards. 9. The AAQS proposed for Kabul are based on the recently published “World Health Organization (WHO) Air Quality Guidelines for Particulate Matter, Ozone, Nitrogen Dioxide and Sulfur Dioxide Global Update 2005 - Summary of Risk Assessment”, Executive Summary: (http://www.who.int/phe/air/aqg2006execsum.pdf) 10. The full report, “WHO Air Quality Guidelines”, scheduled for release during late 2006 has yet to be released. Updates to the Kabul AAQS will be made if necessary, following release and review of the full WHO report. The current full report, the “WHO Air Quality Guidelines for Europe: Second Edition (WHO Regional Publications. European Series: No. 91) will serve as the comprehensive technical basis in the interim, and can be viewed and downloaded at: http://www.euro.who.int/document/e71922.pdf 11. It is proposed that the least stringent (interim) standards presented in the 2005 WHO report provide the basis for initial AAQS for Kabul. The rationale for this approach is as succinctly stated in the current WHO as cited above: 12. “In addition to guideline values, interim targets are given for each pollutant. These are proposed as incremental steps in a progressive reduction of air pollution and are intended for use in areas where pollution is high. These targets aim to promote a shift from high air pollutant concentrations, which have acute and serious health consequences, to lower air pollutant concentrations. If these targets were to be achieved, one could expect significant reductions in risks for acute and chronic health effects from air pollution. Progress towards the guideline values should, however, be the ultimate objective of air quality management and health risk reduction in all areas.” 13. Proposed standards and brief statements of rationale, by pollutant, follow. Proposed standards are in bold type and are in rows that have been highlighted in italic. Particulate Matter of Aerodynamic Diameter Less Than 10 Microns (µm) (PM10)

Table A8: WHO Air Quality Guidelines and Interim Targets for Particulate Matter: Annual Mean Concentrations

Targets PM10

(µg/m3) PM2.5

(µg/m3) Basis for the selected level

Interim target-1 (IT-1)

70 35 These levels are associated with about a 15% higher long-term mortality risk relative to the AQG level.


50 25 In addition to other health benefits, these levels lower the risk of premature mortality by approximately 6% [2–11%] relative to theIT-1 level.

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Targets PM10

(µg/m3) PM2.5

(µg/m3) Basis for the selected level


30 15 In addition to other health benefits, these levels reduce the mortality risk by approximately 6% [2-11%] relative to the -IT-2 level.

Air quality guideline (AQG)

20 10 These are the lowest levels at which total, cardiopulmonary and lung cancer mortality have been shown to increase with more than 95% confidence in response to long-term exposure to PM2.5.

a The use of PM2.5 guideline value is preferred.

Table A9: WHO Air Quality Guidelines and Interim Targets for Particulate Matter: 24-hour Concentrations.a

Targets PM10

(µg/m3) PM2.5

(µg/m3) Basis for the Selected Level


150 75 Based on published risk coefficients from multi-centre studies and meta-analyses (about 5% increase of short-term mortality over the AQG value).


100 50 Based on published risk coefficients from multi-centre studies and meta-analyses (about 2.5% increase of short-term mortality over the AQG value).

Interim target-3 (IT-3)*

75 37.5 Based on published risk coefficients from multi-centre studies and meta-analyses (about 1.2% increase in short-term mortality over the AQG value).


50 25 Based on relationship between 24-hour and annual PM levels.

a 99th percentile (days/year).

* For management purposes. Based on annual average guideline values; precise number to be determined on basis of local frequency distribution of daily means. The frequency distribution of daily PM2.5 or PM10 values usually approximates to a log-normal distribution. Sulfur Dioxide (SO2)

Table A10: WHO Air Quality Guidelines and Interim Targets for SO2: 24-Hour and 10-Minute Concentrations.a

Targets 24-hour average (µg/m3)

10-minute

average (µg/m3)

Basis for selected level

Interim target-1 (IT-1)a

125

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50 – Intermediate goal based on controlling either motor vehicle emissions, industrial emissions and/or emissions from power production. This would be a reasonable and feasible goal for some developing countries (it could be achieved within a few years) which would lead to significant health improvements that, in turn, would justify further improvements (such as aiming for the AQG value).


20 500

a Formerly the WHO Air Quality Guideline (WHO, 2000). Nitrogen Dioxide (NO2)

Table A11: WHO Air Quality Guidelines and Interim Targets for Nitrogen Dioxide (NO2)

NO2 (µg/m3 annual)

NO2 (µg/m3 1-hour)

Basis for the Selected Level

40

200

Guideline values for NO2 remain unchanged in comparison to the existing WHO AQG levels, i.e. 40 µg/m3 for annual mean and 200 µg/m3 for 1-hour mean.

Carbon Monoxide (CO) 14. No carbon monoxide (CO) standards are provided in the WHO Global Update 2005. However, effects of CO are well-known from occupational and urban exposure studies. Recommended standards presented in the “WHO Air Quality Guidelines for Europe: Second Edition (WHO Regional Publications. European Series: No. 91) represent recognized standards and are as follow. 15. The following guidelines are based on the Coburn-Foster-Kane exponential equation, which takes into account all known physiological variables affecting carbon monoxide uptake (16). The following guideline values (mg/m3 values rounded) and periods of time-weighted average exposures have been determined in such a way that the Carboxyhemoglobin (COHb) level of 2.5% is not exceeded, even when a normal subject engages in light or moderate exercise.

Table A12: WHO Air Quality Guidelines for Carbon Monoxide (CO) 15 minutes (mg/m3) 30 minutes (mg/m3) 1 hour (mg/m3) 8 hours (mg/m3)

100 60 30 10 Ozone (O3)

Table A13: WHO Air Quality Guideline and Interim Target for Ozone: 8-Hours Concentration.

Targets Daily maxi-mum 8-hour

mean (µg/m3) Basis for selected level

High levels 240 Significant health effects; substantial proportion of vulnerable

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Targets Daily maxi-mum 8-hour

mean (µg/m3) Basis for selected level

populations affected.


160 Important health effects; does not provide adequate protection of public health. Exposure to this level of ozone is associated with: • Physiological and inflammatory lung effects in healthy

exercising young adults exposed for periods of 6.6 hours; • Health effects in children (based on various summer camp

studies in which children were exposed to ambient ozone levels).

• An estimated 3–5% increase in daily mortalitya (based on findings of daily time-series studies).


100 Provides adequate protection of public health, though some health effects may occur below this level. Exposure to this level of ozone is associated with: • An estimated 1–2% increase in daily mortalitya

(based on findings of daily time-series studies).

• Extrapolation from chamber and field studies based on the likelihood that real-life exposure tends to be repetitive and chamber studies exclude highly sensitive or clinically compromised subjects, or children.

• Likelihood that ambient ozone is a marker for related oxidants.

a Deaths attributable to ozone. Time-series studies indicate an increase in daily mortality in the range of 0.3–0.5% for every 10 µg/m3

increment in 8-hour ozone concentrations above an estimated baseline level of 70 µg/m3.

US National Ambient Air Quality Standards (NAAQS) 16. The Clean Air Act, which was last amended in 1990, requires EPA to set National Ambient Air Quality Standards (40 CFR part 50) for pollutants considered harmful to public health and the environment. The Clean Air Act established two types of national air quality standards. Primary standards set limits to protect public health, including the health of "sensitive" populations such as asthmatics, children, and the elderly. Secondary standards set limits to protect public welfare, including protection against decreased visibility, damage to animals, crops, vegetation, and buildings. 17. The EPA Office of Air Quality Planning and Standards (OAQPS) has set National Ambient Air Quality Standards for six principal pollutants, which are called "criteria" pollutants. They are listed below. Units of measure for the standards are parts per million (ppm) by volume, milligrams per cubic meter of air (mg/m3), and micrograms per cubic meter of air (µg/m3).

Table A14: National Ambient Air Quality Standards

Pollutant Primary Standards

Averaging Times

Secondary Standards

9 ppm (10 mg/m3)

8-hour(1) None Carbon Monoxide 35 ppm

(40 mg/m3) 1-hour(1) None

Lead 1.5 µg/m3 Quarterly Average Same as Primary

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Pollutant Primary Standards

Averaging Times

Secondary Standards

Nitrogen Dioxide 0.053 ppm (100 µg/m3)

Annual (Arithmetic Mean)

Same as Primary

Revoked(2) Annual(2) (Arith. Mean) Particulate Matter (PM10) 150 µg/m3 24-hour(3) 15.0 µg/m3 Annual(4) (Arith. Mean) Same as Primary Particulate Matter (PM2.5) 35 µg/m3 24-hour(5) 0.08 ppm 8-hour(6) Same as Primary

Ozone 0.12 ppm 1-hour(7) (Applies only in limited areas)

Same as Primary

0.03 ppm Annual (Arith. Mean) ------- 0.14 ppm 24-hour(1) ------- Sulfur Oxides ------- 3-hour(1) 0.5 ppm

(1300 µg/m3) (1) Not to be exceeded more than once per year. (2) Due to a lack of evidence linking health problems to long-term exposure to coarse particle pollution, the agency revoked the annual PM10 standard in 2006 (effective December 17, 2006). (3) Not to be exceeded more than once per year on average over 3 years. (4) To attain this standard, the 3-year average of the weighted annual mean PM2.5 concentrations from single or multiple community-oriented monitors must not exceed 15.0 µg/m3. (5) To attain this standard, the 3-year average of the 98th percentile of 24-hour concentrations at each population-oriented monitor within an area must not exceed 35 µg/m3 (effective December 17, 2006). (6) To attain this standard, the 3-year average of the fourth-highest daily maximum 8-hour average ozone concentrations measured at each monitor within an area over each year must not exceed 0.08 ppm. (7) (a) The standard is attained when the expected number of days per calendar year with maximum hourly average concentrations above 0.12 ppm is < 1, as determined by appendix H. (b) As of June 15, 2005 EPA revoked the 1-hour ozone standard in all areas except the fourteen 8-hour ozone non-attainment Early Action Compact (EAC) Areas.

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APPENDIX 3: EMISSION INVENTORY A. Introduction 18. Emission estimates of Kabul are prepared first time during this project. No previous studies have been conducted to assess the emission estimates in Kabul. A preliminary inventory of emission sources in Kabul was prepared based on a survey conducted during 2004 and 2005 under the KAQM Project. The summary inventory of the emission sources and fuel consumption are given in Table A15.The major emission sources identified in Kabul are vehicles, brick kilns, asphalt plants, bakeries, industries, fuel combustion for heating of residential and commercial places during winter, and thousands of independently owned generators. The geographic area considered for air emission inventory and air quality modeling is given in Figure A1. The methodology of calculating emissions for all these sources and their distribution have been described in this Appendix.

Table A15: Summary Inventory of Emission Sources Approximate Daily Fuel Usage

Source Quantity Diesel (litres)

Gasoline (litres)

Wood (kg)

Coal/ Charcoal (kg)

Thermal Power Stations 1 144,000 Vehciles 329,869 Generators 173,755 304,257 7,882 Public Wash-Halls 222 69,833 Bakeries 662 2,275 94,415 Brick Kilns 521 20,710 Asphalt Plants 280 Other Industries (small size) 85 Residential/Commerical Heating

338,898 286,555 817,444

B. Distribution of Emission Sources 19. The locations of industries and residential areas are given in Figure A2. The residential areas, which also include commercial localities, are the major sources of emission resulting from fuel combustion for heating in winter, operations of generators, bakeries and public wash-halls. Industrial locality includes small and medium sized factories and asphalt plants. The brick kilns are concentrated in three areas within the residential areas. Thermal power station is located on north-western part of the city. 20. For the purpose of air quality modeling, the emissions from all the residential sources (bakeries, public wash-halls, heating, domestic and commercial generators) are considered equally distributed within the residential localities and considered as areas sources. While the emissions from the asphalt plants and industrial generators are equally distributed within the industrial area. Similarly emissions from other sources are distributed within the area of the source. The emissions from the power station are considered as a large point source.

C. Thermal Power Stations 21. Two thermal power stations, having a total capacity of 45 MW, are located in Kabul, one in Badam Bagh village, in the north western part of the city and the other one in Hodkheil village, in the eastern part of the city. The plant located in Hodkheil was damaged and presently inoperative and hence not considered during the present study. The Badam Bagh plant is operating with two turbine generators with each consuming

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about 9,000 liters of fuel oil per hour. This plant is operating 8-hours a day and primarily used as to offset the hydroelectric power shortages in Kabul. 22. The approximate annual fuel oil use of the thermal power station is 52,560 m3. Emissions from the thermal power plant, calculated using US EPA emission factors are given in Table A16. PM10 emissions are estimated assuming PM10 / PM ratio 0.55 (a typical ratio for most urban environments).

Table A16: Annual Emissions from the Thermal Power Plant Pollutant EF (kg/m3) Annual Emission

(Tons) PM (Filterable) 1.2 63.07 PM10 34.69 NOx 6.6 346.90 SO2 19 S 109.85 CO 0.6 31.54 TOC 0.299 15.72

Source: US EPA, 1995. Compilation of Air Pollutant Emission Factors, AP-42, Vol.1, Fifth Edition (Table 1.3-1)

D. Generators 23. Erratic and irregular power supply in Kabul especially during winter and early spring (December to March) resulted into enormous usage of privately owned portable electricity generators for residential, commercial and industrial uses. Approximately 171, 795 diesel and gasoline powered generators of wide range of capacities are being operated through out the city. The total number of generators and their average daily fuel usage are given in Table A17. However for calculating the emissions from generators, the emissions factors are considered based on the generator capacities. The assumed generators capacities used for calculating the emissions are also given in Table A17. The residential and commercial generators are assumed to operate for 100 days in the whole year, during December to March. While the generators in the industries and factories are assumed to operate 300 days in a year. The resultant emissions from the usage of these generators are calculated using EPA emissions factors and are given in Table A18. 24. Emissions from the residential and commercial sources are equally distributed to the residential area and emissions from industrial sources are equally distributed within the industrial area. PM10 emissions for diesel and coal are estimated assuming a PM10 /PM ratio of 0.55.

Table A17: Inventory of Portable Power Generators

Gasoline Diesel Gasoline Diesel

Household 171,305 1563 3.5 0.5 2.5 100 149.89 1.37Institutions and NGOs 325 175 14 0.9 25 100 11.38 6.13Garages and Mechanical works 195 7 1 10 100 0.00 1.37Shops and Photo Studios 1,165 3.5 0.9 5 100 2.04 0.00Total 172,795 1933 163.31 8.86

Small scale industries and Factories 127 14 2.5 50 300 26.67

Average KW

Operating days in a

year

Type Fuel Type

Surveyed Data Assumed DataTotal Usage in

million KWh

Residential and Commercial

Industrial

Daily operating

Hours

Hourly Fuel Consumption

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Table A18: Annual Emissions from the Generators

Pollutant EF (g/kwh)

Annual Emission

(Tons)

EF (g/kwh)

Annual Emission

(Tons)

PM10 1.34 219 0.439 4 223NOX 18.8 3,070 6.92 61 3,131SO2 1.25 204 0.359 3 207CO 4.06 663 267 2,365 3,028CO2 704 114,967 661 5,855 120,822TOC 1.5 245 8.96 79 324

PM10 0.439 12 12NOX 6.92 185 185SO2 0.359 10 10CO 267 7,121 7,121CO2 661 17,629 17,629TOC 8.96 239 239

Total Annual Emission

(Tons)

Residential and Commercial Sources

Industrial Sources

Gasoline Diesel

Source: US EPA, 1995. Compilation of Air Pollutant Emission Factors, AP-42, Vol.1,

Fifth Edition (Table 3.3-1) .

E. Fuel Combustion for Heating, Wash-Halls and Bakeries 25. Residential heating in winter, bakeries and public wash-halls are the major sources of fuel consumption from the residential and commercial localities and hence considered as residential area sources.

1. Residential Heating 26. During the cold and chilly seasons (November to March, 150 days) all households, institutions, shops, hotels and restaurants use fuel wood, coal, diesel and animal residue for heating purpose. An inventory of the residential heating sources and their approximate fuel usage is shown in Table A19. Annual emissions calculated for these sources are given in Table A20.

Table A19: Inventory of Heating Sources

Diesel 37634 3,567 725 132 21,885 Litres 6 4.5 12 4 6 382,394 150 57,359Fuel wood 282,258 985 654 63 2595 Kg 7 6.5 14 4 6 2,007,187 150 301,078Charcoal 37634 360 Kg 8 8 303,952 150 45,593Coal 141,128 121 5463 Kg 3.5 14 3 512,031 150 76,805Animal Residues

5,645 Kg 8 45,160 150 6,774

Total 504,299 4,552 1,500 5,658 24,840

Total Daily Fuel

Consumption

Average Daily Fuel Consumption Days of use in a

year

Total Annaul Fuel

Consumption, 10E3

Unit Shops Government buildings

Type of Fuel

Type of Users

house holds

Instit-utions

Hotels Shops Government buildings

house holds

Instit-utions

Hotels

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Table A20: Emissions from Heating Sources

EF* (kg/m3)

Annual Emission

(Tons)

EF** (g/kg)

Annual Emission

(Tons)

EF** (g/kg)

Annual Emission

(Tons)PM 0.3 17 2.6 336 353PM10 9 17.3 5,209 185 5,403NOX 2.2 126 1.3 391 5.6 723 1,241SO2 1.87 107 0.2 60 1.7 220 387CO 0.6 34 126.3 38,026 0.13 17 38,077CO2 1700 511,833 511,833TOC 0.299 17 24.3 7,316 7,333

PollutantDiesel Fuel Wood Total Annual

Emission (Tons)

Coal/Residue

Source: US EPA, 1995. Compilation of Air Pollutant Emission Factors, AP-42, Vol. 1, Fifth

Edition, (* Table 1.3-1; ** Table 1.9-1, *** Table 1.7-1&3).

2. Public Wash-Halls 27. Multiple and single wash-halls (Hammams and Saqawa) use fuelwood based boilers to heat water. Some wash-halls also use plastic, rubber and waste oil as energy sources. All these sources are located within the residential areas. The fuel consumption rates for Hammams and Saqawa are 49,960 and 19,873 kg/day. The total annual fuel wood consumption for both of these wash-halls, considering 150 days of use (from October to February), is 10,475 tons. The calculated emissions from these sources are given in Table A21. 28. There is no proper disposal mechanism of ash resulting from the operation of these wash-halls. Some of this ash is being collected by local farmers to use as fertilizers. The waste waters from wash-halls are discharged either into open lands or roadside drainages. Waste waters from these drainages are distributed to open land during rainy season and later became dry and again enter into the air.

Table A21: Annual Emissions from Public Wash-Halls Pollutant EF (g/kg) Annual Emission (Tons) PM10 15.3 160 NOx 1.4 15 SO2 0.2 2.10 CO 115.4 1209 TOC 24.3 255

Source: US EPA, 1995. Compilation of Air Pollutant Emission Factors, AP-42, Vol.1, Fifth Edition (Table 1.10-1).

3. Bakeries 29. About 635 bakeries are located throughout Kabul and all of them use fuel wood, except 48 bakeries which use diesel oil. The total daily fuel consumption for all the bakeries is 94,415 kg of wood and 2,275 liters of diesel. In addition about 43 small sized silos and sweet bakeries use about 150 kg/day of fuel wood. Considering 300 working days, the annual consumption of wood for bakeries is 30,260 tons and diesel is 682 m3. The calculated emissions from bakeries and silos are given in Table A22. The ash produced after combustion is normally dumped behind the bakeries, which again enters to air.

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Table A22: Annual Emissions from Bakeries

EF* (Kg/m3)

Annual Emission,

Tons

EF** (g/Kg)

Annual Emission

(Tons)PM 0.3 0.20PM10 0.11 15.3 463 463NOX 2.2 1.50 1.4 42 44SO2 1.87 1.28 0.2 6.1 7CO 0.6 0.41 115.4 3,492 3,492TOC 0.299 0.204 24.3 735 736

Fuel Wood Total Annual

Emission (Tons)

DieselPollutant

Source: US EPA, 1995. Compilation of Air Pollutant Emission Factors, AP-42, Vol.1, Fifth Edition,

(* Table 1.3-1; ** Table 1.10-1).

F. Brick Kilns 30. Three types of Brick Kilns are currently operating in Kabul, viz. traditional type, Indian type and Chinese type. Traditional kilns normally use wood, plastic waste, rubber, old tires, reeds and other woody bushes as fuel. Indian style factories (Batti), an underground type, use coal, wood and rubber. The Chinese type brick kiln use imported coal from northern Afghanistan. Most of the brick kilns are located very close to the residential areas. The brick kilns are distributed as three area sources, two on the eastern side with (15 and 50 percent of brick kilns), and the other area on western side (with 35 percent of brick kilns). The emissions are also distributed in the same ratio for air quality modeling. The inventory of brick kilns are given in Table A23 and their annual emissions are given in Table A24. PM10 emissions estimated from total particulate emissions assuming a PM10 /PM ratio of 0.55.

Table A23: Inventory of Brick Kilns and their Fuel Usage

AmountProduction rate (bricks/week)

Fuel Consumption (kg/day)

W t. of brick (kg)

W t. of total bricks/week

No. of working weeks

Traditional factories-active

225 80,000 5,710 2.75 220,000 30 6,600

Indian type 135 300000 15,000 2.75 825,000 30 24,750

Chinese type 1 70,000 2.75 192,500 30 5,775

Total 361 450,000 20,710 1,237,500 37,125

Total wt of bricks/year

(tons)

Survyed Data Assumed Data

Brick Kiln Type

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Table A24: Annual Emissions from Brick Kilns

EF (gm/kg)

Annual Emission

(Tons)

EF (gm/kg)

Annual Emission

(Tons)

EF (gm/kg)

Annual Emission

(Tons)PM 99.42 656 99.42 2,461 99.42 574 3,691PM10 361 1,353 316 2,030NOX 1.18 8 1.18 29 1.18 7 44SO2 0.667 4 0.667 17 0.667 4 25CO 1.19 8 1.19 29 1.19 7 44CO2 0.81 5 0.81 20 0.81 5 30

Total Annual

Emissions (Tons)

Pollutant

Traditional Type Indian Type Chinese Type

Source: US EPA, 1995. Compilation of Air Pollutant Emission Factors, AP-42, Vol.1, Fifth Edition

(Table 11.3-1)

G. Asphalt Plants 31. About 280 Asphalt plants are located in the industrial areas of Kabul. Assuming an average production of asphalt per day is 500 kg and number of working days in a year is 200, the total annual production of all the plants will be 28,000 tons. The annual emissions resulting from this quantity of asphalt production are given in Table A25. In addition emissions will also result from burning of asphalt tars, which are highly malodorous and contain high levels of carcinogenic compounds.

Table A25: Annual Emissions from Asphalt Plants

Pollutant EF (g/kg) Annual Emission (Tons)

PM10 2.2 61.6 NOX 0.084 2.35 SO2 0.12 3.36 CO 0.0035 0.10 CO2 19 532

Source: US EPA, 1995. Compilation of Air Pollutant Emission Factors, AP-42, Vol.1, Fifth Edition (Table 11.1-1 and 11.1-7).

H. Vehicles and Traffic 32. Most of the vehicles in Kabul are older than 25 years, which are largely imported illegally. The road system was originally designed to accommodate only about 30,000 vehicles a day, about 10 times lower than the present vehicle population. The tremendous increase in traffic has caused congestion all around Kabul city, which is further degraded by blockade of roads by hawkers, pedestrians, security walls and illegal construction around main roads. The average vehicle movement is very slow and thereby causing much pollution. 33. The total number of vehicles registered in Kabul as of December 2005 is given in Table A26. Though all these vehicles may not be operated in Kabul, for the present study it is assumed that most of the vehicles, except trucks and buses, are being operated in Kabul. About one fourth of the buses and trucks are assumed to be travel in Kabul city.

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Table A26 : Vehicle Population and their Annual Travel Times

Total Gasoline Diesel Gasoline DieselSmall Cars 225,692 59,962 165,730 30 657 1,815Taxi 29,270 9,270 20,000 60 203 438Tractors 162 162 50 3Trucks 42,422 10,000 60 219Buses 32,323 10,000 50 183Two Stroke MCs 11,178 11,178 30 122

Total 341,047 80,572 205,730 985 2,654

Annual Travel Distance (million km)Vehicle Type

Approx. Daily travel distance

(km)

Total Vehicles

34. In addition to the US EPA emission factors the World Bank published Urban Air Quality Management Strategy in Asia reports for Katmandu, Mumbai, Jakarta and Manila are also reviewed. Emission factors are chosen for vehicles of 1977 models and 100,000 kilometers traveled. The approximate travel distance for each type of vehicle is assumed based on a traffic study in Dhaka, Bangladesh (DITS, 1993). The emission factors and the estimated emissions are given in Table A27 . The World Bank URBAIR reports considered PM10 from vehicle emissions is equivalent to TSP and hence same analogy is used in the present report. For resuspension of dust, the URBAIR reports assumed that the PM10 is equivalent to 1/4th of TSP, but in the present study PM10 from resuspension is considered equivalent to TSP due to the current road conditions in Kabul. Windblown soil and dust from open arid terrains and open construction practices around Kabul generate huge dust on road which ground into smaller particles by vehicle tires, abrasion and other processes and considered in resuspension.

Table A27: Annual Emissions from Vehicles

Cars/ Taxies Tractors Motor

CyclesCars/

TaxiesTrucks/ Buses

Cars/ Taxies Tractors Motor

Cycles Total Cars/ Taxies

Trucks/ Buses Total

TSP* 0.33 0.33 0.21 0.45 0.93 284 0.98 26 310 1,014 373 1,387 1,697Resuspension* 2.00 2.00 2.00 2.00 2.00 1,719 5.91 245 1,970 4,505 803 5,308 7,278NOX** 1.92 2.58 0.35 1.12 17.32 1,650 7.63 43 1,701 2,523 6,954 9,477 11,178SO2* 0.13 0.00 0.014 0.57 0.85 112 0 1.71 113 1,284 341 1,625 1,739CO** 36.07 168.14 24.11 1.83 13.66 31,006 497 2,951 34,454 4,123 5,484 9,607 44,061HC** 1.41 7.28 2.19 1.04 5.97 1,212 22 268 1,502 2,343 2,397 4,740 6,241

PollutantDieselGasoline

Total annual

emissions (Tons)

Emission Factors (g/km) Annual Emissions (Tons)

Gasoline Diesel

(*Source: US EPA, 1998. Compilation of Air Pollutant Emission Factors, AP-42, Vol.2, Fifth Edition -Tables H6,1B.2; H217 5.1.2; H259 7.1.2 and ** Urban Air Quality Management Strategy in Asia (1997), World Bank Reports of Mumbai, Kathmandu and Jakarta)

35. The road network of Kabul and the district locations is shown in Figure 3. It is assumed that 20 percent of emissions from the vehicles are distributed along the major roads. The balancing 80 percent of the emission is distributed based on the percentage of population distribution in each district. Population distribution of Kabul is given Table A28.

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Table A28: Population Distribution in Different Districts of Kabul

District Code Percentage Distribution

1 4.80% 2 4.21% 3 5.29% 4 10.31% 5 8.46% 6 11.49% 7 9.47% 8 5.58% 9 8.38% 10 8.75% 11 4.89% 12 1.03% 15 13.53% 16 3.82%

Total 100.00%

I. Total Emission Inventory 36. The summary emission inventory of all sources is given in Table A29. The percentage contribution of each source to the total emissions is given in Table A30. The major emission sources of PM10 are vehicles and dust (52%), fuel combustion for residential heating (31%) and brick kilns (12%). The major sources of NOX are vehicles (69%) and domestic generators (19%). Higher NOX emissions are due to presence of a very high number of diesel vehicles in Kabul. About 76 percent of total vehicles in Kabul are diesel, a very high number compared to the other cities of Asia. Vehicles alone are contributing 70% of total SO2.

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Table A29: Total Emission Inventory

PM10 NOX SO2 CO CO2 TOCVehiclesGasoline Vehicles 310 1,700 113 34,450Diesel Vehicles 1,387 9,475 1,625 9,615Resuspension 7,278

Total Vehicles 8,976 11,175 1,739 44,065Residential SourcesResidential/ Commercial Heating 5,403 1,241 381 38,077 511,833 7,333

Residential/ Commercial Generators 223 3,131 207 3,028 120,822 324

Bakeries 463 44 7 3,492 736Hammams 160 15 2 1,209 255

Total Residential Sources 6,249 4,431 597 45,807 632,655 8,648Industrial SourcesThermal Power Plant 35 347 110 32 16Industrial Generators 12 185 10 7,121 17,629 239Brick Kilns 2,030 44 25 44 30 0.19Asphalt 62 2 3 0.10 532 0.64

Total Industrial Sources 2,138 578 148 7,197 18,191 256Grand Total 17,363 16,183 2,484 97,068 650,846 8,903

SourceAnnual Emission (Tons)

Table A30: Percentage Contributions to Emission Inventory

PM10 NOX SO2 CO CO2 TOCVehiclesGasoline Vehicles 1.8% 10.5% 4.6% 35.5%Diesel Vehicles 8.0% 58.5% 65.4% 9.9%Resuspension 41.9%

Total Vehicles 51.7% 69.1% 70.0% 45.4%Residential SourcesResidential/ Commercial Heating 31.1% 7.7% 15.3% 39.2% 78.6% 82.4%

Residential/ Commercial Generators 1.3% 19.3% 8.3% 3.1% 18.6% 3.6%

Bakeries 2.7% 0.3% 0.3% 3.6% 8.3%Hammams 0.9% 0.1% 0.1% 1.2% 2.9%

Total Residential Sources 36.0% 27.4% 24.1% 47.2% 97.2% 97.1%Industrial SourcesThermal Power Plant 0.2% 2.1% 4.4% 0.0% 0.2%Industrial Generators 0.1% 1.1% 0.4% 7.3% 2.7% 2.7%Brick Kilns 11.7% 0.3% 1.0% 0.0% 0.0% 0.0%Asphalt 0.4% 0.0% 0.1% 0.0% 0.1% 0.0%

Total Industrial Sources 12.3% 3.6% 5.9% 7.4% 2.8% 2.9%Grand Total 100% 100% 100% 100% 100% 100%

SourcePercentage Contributon

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.

Figure A1: Location Map of Kabul (Source: AIMS, Kabul)

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Figure A2: Locations of Residential and Industrial Areas in Kabul (Source: AIMS, Kabul)

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Figure A3: Road Network of Kabul (Source: AIMS, Kabul)

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APPENDIX 4: EMISSION FACTORS, PARTICLES A. Introduction 37. Emission factors (mass of specific pollutants emitted per quantity of combusted fuel, per kilometer traveled or unit of product produced) are important input data to emissions inventories, which again are essential input to dispersion modeling. The knowledge of emission factors representative for the present technology level of Asian cities is limited. For the purpose of selecting emission factors for the KAQM study, references on emission factors were collected from US EPA, the World Bank Urban Quality Management Strategy Reports (URBAIR) in other Asian Cities, and literature. This appendix gives a brief background for the selection of emission factors for particulates used in the air quality assessment part of KAQM.

B. Motor Vehicles 38. The emission factors for motor vehicles are taken from the following references:

• WHO (1993), • US EPA (EPA AP42 report series, Volumes I and II) (1995 and 1998), • Vehicles Emissions Control Project (VECP), Manila (Baker, 1993), • Indonesia (Bosch, 1991) • Williams et al. (1989), • Motorcycle emission standard and emissions control technology (Weaver and

Chan, 1993) 39. Table A31 gives a summary of emission factors from these references for various vehicle categories. The emission factors considered for this study are provided in Table A32. 40. Taking into account the typical vehicle/traffic activity composition, the following vehicle classes contribute the largest to the overall particulate emissions from vehicles:

• Small cars and taxis (diesel and gasoline) • Heavy duty diesel trucks, • Diesel buses, • 2-stroke motor cycles.

41. Thus, the emission factors for these vehicle classes are the most important ones. It is clear that there is no solid basis without actual measurements on which particulate emission factors for vehicles in Asian cities are associated. The given references represent the best available basis. Comments are given below for each of the vehicle classes.

1. Gasoline 42. Small cars and taxis: Fairly new, normally well maintained cars, engine size less than 2.5, without 3-way catalyst, running on leaded gasoline (0.2-0.3 g Pb/1), have an emission factor of the order of 0.1 g/km. Older, poorly maintained vehicles may .have much larger emissions. The US EPA/WHO factor of 0.33 g/km can be used as an estimate for such vehicles. 43. Utility/Heavy 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 Kabul. 44. Motorcycles, 2 stroke engines: The Weaver and Chan (1993) supports the 0.21 g/km emission factor suggested by US EPA/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.

2. Diesel 45. Small Cars: The 0.45 g/km of US EPA/WHO was taken for small cars.

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46. Heavy duty trucks/buses: The factors in the table range from 0.75 g/km to 2.1 g/km. An emission factor suggested by US EPA, 0.93 g/km, was considered.

Table A31: Emission Factors (g/km) for Particulate Emissions from Motor Vehicles

Fuel and Vehicle Particles, g/km Reference Gasoline Passenger cars 0.33 US EPA/WHO 0.10 VECP, Manila 0.16 Indonesia (Bosch) 0.07 Williams Trucks, utility 0.12 VECP, Manila 0.33 US EPA Trucks, heavy duty 0.33 US EPA 3-wheelers, 2 stroke 0.21 US EPA/WHO MC 2/4 stroke 0.21/ US EPA/WHO 2.00/ VECP, Manila 0.021/0.029 Indonesia VWS 0.28/0.08 Weaver and Chan Diesel Car, taxi 0.6 VECP, Manila 0.45 US EPA/WHO 0.37 Williams Trucks, utility 0.9 VECP, Manila 0.93 EPA Trucks, heavy/bus 0.75 WHO 1.5 VECP, Manila 0.93 US EPA 1.2 Bosch 2.1 Williams

Table A32: Selected emission Factors (g/km) for Particulate Vehicles class Gasoline Diesel

Passenger cars/taxies 0.33 0.45Trucks/Buses 0.33 0.93Motorcycles/tricycles 0.21

C. Fuel Consumption 47. The emission factors suggested by US EPA are taken as a basis for calculating particulate emissions from combustion of fuel oil, diesel, fuel wood and coal. The emission factors are given in Table A19.

Table A33: Emission factors for oil combustion Emission factor Fuel Oil (kg/m3) 1.2 Diesel (kg/m3) 0.3 Fuel wood (g/kg) 17.3 Coal (g/kg) 2.6 Residential Stoves (g/kg) 15.3

Source: US EPA, 1995. Compilation of Air Pollutant Emission Factors, AP-42, Vol.1, Fifth Edition.

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D. Generators, Brick Kilns and Asphalt Plants 48. The emission factors suggested by US EPA are taken as a basis for calculating emissions from combustion from diesel and gasoline generators, brick kilns and asphalt plants. The factors are given in Table A34.

Table A34: Emission factors for oil combustion Emission factor Generators, Diesel (g/kwh) 0.439 Generators, Gasoline (g/kwh) 1.34 Brick Kilns, (g/kg) 9.42 Brick Kilns, material handling ( g/kg) 90.0 Asphalt Plants(g/kg) 16.0

Source: US EPA, 1995. Compilation of Air Pollutant Emission Factors, AP-42, Vol.1, Fifth Edition.

E. References Baker, J., R. Santiage, T. Villareal, and M. Walsh. 1993. "Vehicular emission control in Metro

Manila." Asian Development Bank (PPT A 1723). Manila. Bosch. J. 1991. "Air quality assessment in Medan." Extract from Medan Urban Transportation

Study. The World Bank. Washington D.C. DITS, 1993. Working Paper 25, Vehicle Population, Government of Bangladesh. 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). World Health Organization. Geneva.

Larssen, S. and J. Heintzenberg. 1983. "Measurements of Emissions of Soot and Other Particles from Light-duty Vehicles." (NILU OR 50/83). (In Norwegian.) Lillestrom, Norway.

United States Environmental Protection Agency. 1995. "Compilation of Air Pollutant Emission Factors." 5th edition. Volumes I and II, 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. Kimber1ee. 1989. "Particulate Emissions from 'In-use' Motor Vehicles: Part I. Spark ignition vehicles." Atmospheric Environment 23, 2639-2645.

Williams, D.J., J. W. Milne, S. M. Quigley, D. B. Roberts, and M. C. Kimber1ee. 1989. "Particulate Emissions from 'In-use' Motor Vehicles: Part II. Diesel Vehicles.

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APPENDIX 5: SPREADSHEET FOR CALCULATING EFFECTS OF CONTROL MEASURES ON EMISSIONS

49. The spread sheets for calculating emissions of PM10, NOX and SOX are shown in Figures A4, A5 and A6, respectively. The purposes of these spreadsheets are to calculate modified emission contributions in absolute and relative terms. These spreadsheets can be used to calculate modified emission scenario due to control measures, such as new vehicle technology, improved emission characteristics, achieved by measures on existing technology, reduced traffic activity by traffic management and introduction of alternate fuel. 50. The emissions are calculated separately for large point sources (with tall stacks), while smaller distributed point sources and line sources are considered as area sources with intensity proportional to the population distribution in the city. The columns and rows of the worksheet are as follows

Columns (a) q Emission factor, g/km for vehicles, kg/m3 or g/kg for fuel combustion

and process emission; and g/kwh for generators • for vehicles, emission factors are given for “existing’ and “new

technology” (b) F,T Amount of “activity”

• F (m3 or ton or kwh) for fuel combustion or power output of generators

• T (million vehicle km) for traffic activity (c) qF, qT Base case emissions, tons, calculated as product of columns (a) and

(b) (d) fq, fF, fT, f- Control measures. Relative reduction of emission factor (fq), amount

(fF,fT) or other (f-) resulting from control measures (e) qF fq fF f- Modified emissions, due to control measures (f) d(fq, fF, fT,

f-) Relative emissions contributions from each source category such as vehicles, fuel combustion, and industrial processes

(g) d(fq, fF, fT, f-)

Relative emissions contributions, sum of all categories

Rows (a) Separate rows for each source type and category (b) “Background”: Fictitious emissions, corresponding to extra-urban

background concentrations

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Spreadsheet for Emission CalculationsTOTAL ANNUAL EMISSIONS, KABULPM10 Scenario: 2005

Emission Factor

Amount Base- case emissions

Modified emissions

Relative emissions per category

Relative emissions total

q (kg/m3) F (10E3m3) qF (10E3kg) fq fF f- qF fq fF f- (10E3 kg)

d(qF fQ fF f-) (percent)

d(qF fq fF f-) tot (percent)

Power Plants 1.2 52.56 34.69 1 1 1 34.69 100.034.69 34.69 100

Modified emissions/emissions, point sources 1.00

Vehiclesq (g/km) T (10E6

km/y)qT (10E3

kg/y)fq fT f- qT fq fT f- (10

E3kg)d(qT fq fT f-)

(percent)d(qT fq fT f-) tot (percent)

GasolineCars 0.33 656.58 216.67 1.00 1.00 1.00 216.67 2.4 1.3Taxis 0.33 203.01 66.99 1.00 1.00 1.00 66.99 0.7 0.4Trucks 0.33 0.00 0.00 1.00 1.00 1.00 0.00 0.0 0.0Tractors 0.33 2.96 0.98 1.00 1.00 1.00 0.98 0.0 0.0Motor Cycles 0.21 122.40 25.70 1.00 1.00 1.00 25.70 0.3 0.1Sum gasoline 984.95 310.35 310.35 3.5 1.8

1.00

DieselCars 0.45 1,814.74 816.63 1.00 1.00 1.00 816.63 9.1 4.7Taxis 0.45 438.00 197.10 1.00 1.00 1.00 197.10 2.2 1.1Trucks 0.93 219.00 203.67 1.00 1.00 1.00 203.67 2.3 1.2Buses 0.93 182.50 169.73 1.00 1.00 1.00 169.73 1.9 1.0Tractors 0.93 0.00 0.00 1.00 1.00 1.00 0.00 0.0 0.0

Sum diesel 2,654.24 1,387.13 1,387.13 15.5 8.01.00

Resuspension 2 3,639.20 7,278.39 1.00 1.00 1.00 7,278.39 81.1 42.01.00

Sum total vehicles 8,975.87 8,975.87 100.0 51.8Modified emissions/emissions, total vehicles 1.00

Generators q (g/kwh) F (10E3 kwh/yr)

qF (10E3kg/yr)

fq fF f- qF fq fF f- (10E3kg)



Residential and CommercialGasoline 1.34 163.31 218.83 1.00 1.00 1.00 218.83 93.3 1.3Diesel 0.439 8.86 3.89 1.00 1.00 1.00 3.89 1.7 0.0IndustrialDiesel 0.439 26.67 11.71 1.00 1.00 1.00 11.71 5.0 0.1Sum Generators 198.83 234.43 234.43 100.0 1.4

modified emission/emissions, generators 1.00

Fuel combustionq (g/kg or

kg/m3)F (10E3m3/yr) qF

(10E3kg/yr)fq fF f- qF fq fF f-

(10E3 kg)d(qF fQ fF f-)

(percent)d(qF fq fF f-) tot (percent)

Fuel wood

Residential heating 17.3 301.08 5,208.65 1.00 1.00 1.00 5,208.65 86.4 30.1

Public Baths 15.3 10.47 160.27 1.00 1.00 1.00 160.27 2.7 0.9Bakeries 15.3 30.26 462.97 1.00 1.00 1.00 462.97 7.7 2.7Sum fuel wood 540.65 5,831.89 5,831.89 96.8 33.7modified emissions/emissions, fuel wood 1.00DieselResidential heating 0.3 57.36 9.46 1.00 1.00 1.00 9.46 0.2 0.1

Bakeries 0.3 0.68 0.11 1.00 1.00 1.00 0.11 0.0 0.0Sum diesel 58.04 9.58 9.58 0.2 0.1

1.00Coal & OthersCharcoal for heating

2.6 45.59 65.20 1.00 1.00 1.00 65.20 1.1 0.4

Coal for heating 2.6 76.80 109.83 1.00 1.00 1.00 109.83 1.8 0.6Animal residue 2.6 6.77 9.69 1.00 1.00 1.00 9.69 0.2 0.1Refuse 37 0.00 1.00 1.00 1.00 0.00 0.0 0.0Sum coal & others 129.17 184.72 184.72 3.1 1.1modified emission/emissions, coal and others 1.00Sum fuel combustion 6,026.18 6,026.18 100.0 34.8Modified emissions/emissions, fuel combustion 1.00

Sum large point sources

Control measures

LARGE POINT SOURCES

AREA SOURCES AND DISTRIBUTED POINT SOURCES

Modified emissions/emissions,

Modified emissions/emissions, diesel

Modified emissions/emissions, gasoline

modified emission/emissions, diesel

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Industrial processe q (g/kg) F (10E6 kg/yr)

qF (10E3kg/yr)




Brick Kilns 99.42 37.13 2,030.03 1.00 1.00 1.00 2,030.03 97.1 11.7Asphalt Plants 2.2 28.00 61.60 1.00 1.00 1.00 61.60 2.9 0.4

0.00 1.00 1.00 1.00 0.00 0.0 0.00.00 1.00 1.00 1.00 0.00 0.0 0.0

Sum industrial processes 2,091.63 2,091.63 100.0 12.11.00

Othersq (g/kg) M qM fq fM f- qM fq fM f- d(qM fQ fM f-)

(percent)d(qM fq fM f-) tot (percent)

0.00 1.00 1.00 1.00 0.00 #DIV/0! 0.00.00 1.00 1.00 1.00 0.00 #DIV/0! 0.00.00 1.00 1.00 1.00 0.00 #DIV/0! 0.0

Sum others 0.00 0.00 #DIV/0! 0.01.00

"Background"Unknown

17328 17328 100.01.00

Modified emissions/emissions, others

Modified emissions/emissions, total

Modified emissions/emissions, ind. Proc.

Sum total, excl.

Figure A4: KAQM Spreadsheet for Emission Calculation

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Spreadsheet for Emission CalculationsTOTAL ANNUAL EMISSIONS, KABULNOX Scenario: 2005

Emission Factor


Modified emissions



q (kg/m3) F (10E3m3) qF (10E3kg) fq fF f- qF fq fF f- (10E3kg)



Power Plants 6.6 52.56 346.90 1.00 1.00 1.00 346.90 100.0346.90 346.90 100



km/y)qT (10E3

kg/y)fq fT f- qT fq fT f-

(10E3kg)d(qT fq fT f-)


GasolineCars 1.92 656.58 1,259.71 1.00 1.00 1.00 1,259.71 11.3 8.0Taxis 1.92 203.01 389.50 1.00 1.00 1.00 389.50 3.5 2.5Trucks 2.58 0.00 0.00 1.00 1.00 1.00 0.00 0.0 0.0Tractors 2.58 2.96 7.63 1.00 1.00 1.00 7.63 0.1 0.0Motor Cycles 0.35 122.40 43.36 1.00 1.00 1.00 43.36 0.4 0.3Sum gasoline 984.95 1,700.19 1,700.19 15.2 10.7

1.00

DieselCars 1.12 1,814.74 2,030.17 1.00 1.00 1.00 2,030.17 18.2 12.8Taxis 1.12 438.00 489.99 1.00 1.00 1.00 489.99 4.4 3.1Trucks 17.32 219.00 3,793.37 1.00 1.00 1.00 3,793.37 33.9 24.0Buses 17.32 182.50 3,161.14 1.00 1.00 1.00 3,161.14 28.3 20.0Tractors 1.51 0.00 0.00 1.00 1.00 1.00 0.00 0.0 0.0

Sum diesel 2,654.24 9,474.67 9,474.67 84.8 59.81.00



qF (10E3kg/yr)




Residential/CommercialGasoline 18.8 163.31 3,070.15 1.00 1.00 1.00 3,070.15 92.6 19.4Diesel 6.92 8.86 61.29 1.00 1.00 1.00 61.29 1.8 0.4IndustrialDiesel 6.92 26.67 184.56 1.00 1.00 1.00 184.56 5.6 1.2Sum Generators 172.16 3,131.44 3,316.00 100.0 20.9Modified emissions/emissions, generators 1.00

Fuel combustionq (g/kg or

kg/m3)F (10E3m3/yr) qF

(10E3kg/yr)fq fF f- qF fq fF f-

(10E3kg)d(qF fQ fF f-)

(percent)d(qF fq fF f-) tot (percent)

Fuel wood

Residential heating 1.3 301.08 391.40 1.00 1.00 1.00 391.40 30.1 2.5

Public Baths 1.4 10.47 14.66 1.00 1.00 1.00 14.66 1.1 0.1Bakeries 1.4 30.26 42.36 1.00 1.00 1.00 42.36 3.3 0.3Sum Fuel wood 513.98 448.43 448.43 34.5 2.8

1.00DieselResidential heating 2.2 57.36 126.19 1.00 1.00 1.00 126.19 9.7 0.8

Bakeries 2.2 0.68 1.50 1.00 1.00 1.00 1.50 0.1 0.0Sum diesel 58.04 127.69 127.69 9.8 0.8

1.00Coal & OthersCharcoal for heating

5.6 45.59 255.32 1.00 1.00 1.00 255.32 19.6 1.6

Coal for heating 5.6 76.80 430.11 1.00 1.00 1.00 430.11 33.1 2.7Animal residue 5.6 6.77 37.93 1.00 1.00 1.00 37.93 2.9 0.2Refuse 3 0.00 1.00 1.00 1.00 0.00 0.0 0.0Sum coal & others 129.17 723.36 723.36 55.7 4.6modified emission/emissions, coal & others 1.00Sum fuel combustion 1299.48 1299.48 100.0 8.2Modified emissions/emissions, fuel consumption 1.0

Control measures

LARGE POINT SOURCES


modified emission/emissions, fuel wood




Modified emissions/emissions, gasoline

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qF(10E3kg/yr)




Brick Kilns 1.18 37.13 43.81 1.00 1.00 1.00 43.81 94.9 0.3Asphalt Plants 0.084 28.00 2.35 1.00 1.00 1.00 2.35 5.1 0.0

0.00 1.00 1.00 1.00 0.00 0.0 0.00.00 1.00 1.00 1.00 0.00 0.0 0.0

Sum industrial processes 46.16 46.16 100.0 0.31.00

Othersq M qM fq fM f- qM fq fM f- d(qM fQ fM f-

)(percent)d(qM fq fM f-) tot (percent)

0.00 1.00 1.00 1.00 0.00 #DIV/0! 0.00.00 1.00 1.00 1.00 0.00 #DIV/0! 0.00.00 1.00 1.00 1.00 0.00 #DIV/0! 0.0

Sum others 0.00 0.00 #DIV/0! 0.01.00

"Background"Unknown

15652 15837 100.01.00


Modified emissions/emissions, total

Modified emissions/emissions, ind. proc.

Sum total, excl.

Figure A5: Spreadsheet for Emissions Calculation

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Spreadsheet for Emission CalculationsTOTAL ANNUAL EMISSIONS, KABULSO2 Scenario: 2005

Emission Factor


Modified emissions



q (kg/m3) F (10E3m3) qF (10E3kg) fq fF f- qF fq fF f- (10E3kg)



Power Plants 2.09 52.56 109.85 1.00 1.00 1.00 109.85 100.0109.85 109.85 100



km/y)qT (10E3

kg/y)fq fT f- qT fq fT f-

(10E3kg)d(qT fq fT f-)


GasolineCars 0.13 656.58 85.36 1.00 1.00 1.00 85.36 4.9 3.6Taxis 0.13 203.01 26.39 1.00 1.00 1.00 26.39 1.5 1.1Trucks 0.00 0.00 1.00 1.00 1.00 0.00 0.0 0.0Tractors 2.96 0.00 1.00 1.00 1.00 0.00 0.0 0.0Motor Cycles 0.01 122.40 1.71 1.00 1.00 1.00 1.71 0.1 0.1Sum gasoline 984.95 113.46 113.46 6.5 4.8Modified emissions/emissions, gasoline 1.00

DieselCars 0.57 1,814.74 1,034.40 1.00 1.00 1.00 1,034.40 59.5 43.6Taxis 0.57 438.00 249.66 1.00 1.00 1.00 249.66 14.4 10.5Trucks 0.85 219.00 186.15 1.00 1.00 1.00 186.15 10.7 7.8Buses 0.85 182.50 155.13 1.00 1.00 1.00 155.13 8.9 6.5Tractors 0.85 0.00 0.00 1.00 1.00 1.00 0.00 0.0 0.0

Sum diesel 2,654.24 1,625.34 1,625.34 93.5 68.51.00



qF (10E3kg/yr)

fq fF f- qF fq fF f- (10E3 kg)



Residential/CommercialGasoline 1.25 163.31 204.13 1.00 1.00 1.00 204.13 94.12 8.60Diesel 0.36 8.86 3.18 1.00 1.00 1.00 3.18 1.47 0.13IndustrialDiesel 0.36 26.67 9.57 1.00 1.00 1.00 9.57 4.4 0.4Sum Generators 172.16 207.31 216.89 100.0 9.1modified emissions/emissions, generators 1.00

Fuel combustion 0.2 F (10E3m3/yr)

qF (10E3kg/yr)

fq fF f- qF fq fF f- (10e6kg)



Fuel Wood

Residential heating 0.2 301.08 60.22 1.00 1.00 1.00 60.22 15.4 2.5

Public Baths 0.2 10.47 2.09 1.00 1.00 1.00 2.09 0.5 0.1Bakeries 0.2 30.26 6.05 1.00 1.00 1.00 6.05 1.6 0.3Sum fuel wood 513.98 68.36 68.36 17.5 2.9

1.00 1.00DieselResidential heating 1.87 57.36 107.26 1.00 1.00 1.00 107.26 27.50 4.5

Bakeries 1.87 0.68 1.28 1.00 1.00 1.00 1.28 0.33 0.1Sum diesel 108.54 108.54 27.83 4.6

1.00 1.00Coal & OthersCharcoal for heating

1.65 45.59 75.23 1.00 1.00 1.00 75.23 19.3 3.2

Coal for heating 1.65 76.80 126.73 1.00 1.00 1.00 126.73 32.5 5.3Animal residue 1.65 6.77 11.18 1.00 1.00 1.00 11.18 2.9 0.5Refuse 0.00 1.00 1.00 1.00 0.00 0.0 0.0Sum coal & others 129.17 213.13 213.13 54.6 9.0

1.00 1.00Sum fuel combustion 390.03 390.03 100.0 16.4Modified emissions/emissions, fuel combustion 1.00



modified emission/emissions, coal &

modified emission/emissions, fuel wood


Control measures

LARGE POINT SOURCES


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qF fq fF f- qF fq fF f- (10E3kg)



Brick Kilns 0.67 37.13 24.75 1.00 1.00 1.00 24.75 88.0 1.0Asphalt Plants 0.12 28.00 3.36 1.00 1.00 1.00 3.36 12.0 0.1

1.00 1.00 1.00 0.00 0.0 0.01.00 1.00 1.00 0.00 0.0 0.0

Sum industrial processes 28.11 28.11 100.0 1.21.00

Othersq M qM fq fM f- qM fq fM f- d(qM fQ fM f-)

(percent)d(qM fq fM f-) tot (percent)

0.00 1.00 1.00 1.00 0.00 #DIV/0! 0.00.00 1.00 1.00 1.00 0.00 #DIV/0! 0.00.00 1.00 1.00 1.00 0.00 #DIV/0! 0.0

Sum Others 0.00 0.00 #DIV/0! 0.01.00

"Background"Unknown

2364 2374 100.01.00Modified emissions/emissions, total

Modified emissions/emissions, ind. Proc.

Sum total, excl.


Figure A6 : Spreadsheet for Emissions Calculation

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APPENDIX 6: PROJECT DESCRIPTION FOR LOCAL CONSULTANTS A. Air Quality Assessment in other Cities 51. Information should be collected regarding the following items, and other items of interest of Air Quality Management System Development in other cities in Afghanistan.

• Meteorological measurement in and near by the city. • Activities/population data for the City

- 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: o number of vehicles in each class (passenger cars, small/medium/large trucks,

buses, motorcycles (2-and 3- wheels, 2- and 4-stroke) o age distribution o Average annual kilometer travel per vehicle class

- Traffic data: o Definition of the main road network marked on map o Traffic data for the main roads o Annual average daily traffic (vehicles/day) o Traffic speed (average, and during rush hours) o vehicle composition (passenger cars, motorcycles, trucks/buses)

- Population data: o Per city district (as small districts as possible) o Total population; o Age distribution

• Air pollutant emissions - Emissions inventory data (annual emissions)

o per compound (SO2, NOx, particles in size fractions: < 2µg, 2-10µg, >10µg, VOC, Lead);

o emission per sector (industry, transport, domestic, etc) • Air pollution data

- concentration statistics per monitoring station o annual average, 98 percentile, maximum concentrations (24-hour, 1 hour); o pollution trend; o 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. Drafting of

Regulation on Air Pollution based on regulation in other countries. • Institutions:

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- description of existing institutions working in and with responsibilities within the air pollution sector, regarding: o monitoring o emission inventories o law making o enforcement

- the information shall include o responsibilities and tasks of the institutions o authority o manpower; o expertise; o equipment (monitoring, analysis, data, hard/software) o funds

52. It is important that the gathering of information is as complete as possible regarding each of the items, so that there is a basis of data which is as updated and complete as possible. Make sure that this updated completed information database is to form the basis for an action plan regarding Air Quality Management in the City. 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.

B. Damage Assessment and Economic Valuation 1. Physical Impacts

53. (a) Describe available studies on relations between air pollution and health, and (b) Decide on the acceptability of dose-effect relationships from the United States

a. Mortality: 10 µg/m3 TSP leads to 0.682 (range: 0.48-0.89) percentage change in mortality

b. Work loss days (WLD): 1 µg/m3 TSP leads to 0.00145 percentage change in WLD.

c. Restricted activity days (RAD): 1µg/m3 TSP leads to 0.0028 percentage change in RAD per year

d. Respiratory hospital diseases (RHD): 1 µg/m3 TSP leads to 5.59 (range: 3.4e-7.71) cases of RHD per 100,000 persons per year

e. Emergency room visits (ERV): 1µg/m3 TSP leads to 12.95 (range: 7.1-18.8) cases of ERV per 100,000 persons per year

f. Bronchitis (children): 1 µg/m3 TSP leads to 0.00086 (range: 0.00043-0.00129) change in bronchitis.

g. Asthma attacks: 1 µg/m3 TSP leads to 0.0053 (range 0.0027-0.0079) change in daily asthma attacks per asthmatic person

h. Respiratory symptoms days (RSD): 1 µg/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)

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j. Coronary heart disease (CHD): change in probability of a CHD event in the following ten years is: [I + exp – {-4.996+0.030365(DBP1)}]I - [I + exp – {-4.996+0.030365(DBP2)}]I

k. Decrement IQ points: IQ decrement = 0.975 x change in air lead (µg/m3)

Calculation example: • Let population be 10 million people • Let threshold value of TSP be 75 µg/m3 (the WHO guideline) • Let the concentration TSP be 317 µg/m3. • Concentration – threshold = 317 – 75 = 242 = 24.2 (10µg/m3) • Change in mortality = 24.2 x 0.682 = 16.5% • Let crude mortality be 1% per year • Crude mortality = 100,000 peoples per year • Change in mortality due to TSP = 16.5% of 100,000 people = 165,000 people per

year 54. For those dose-effect relationships that are acceptable, base values must be gathered, e.g.: crude mortality and present work days lost.

2. Economic 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 (1/100th of a %, or 1,000th) of change in risk of mortality leads to a wage difference of about US$1,000. if this figure applicable to all persons of large population (10 million), the whole population values 1 promille change in risk of mortality at US$1,000 x 10 x 106 = US$ 10 billion. An increase in risk of 1 promille will lead to approximately 10,000 death cases, so per death case the valuation is US$ 1 million. It should be decided if in other countries, e.g., 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 sued for valuation of a lost working day. Moreover, the hospital costs of the 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

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pay for risk to human health, be corrected for wage differences. The acceptability of such a procedure is perhaps, somewhat lower.

4. IQ points. Loss of IQ of children may lead to a lower earning capacity. A United States estimate is approximately US$4,600 per child, per IQ point, summed over the child’s lifetime. If this is acceptable, the figure could be corrected for wage differences between the United States and the city.

3. Other impacts 1. Buildings. An estimate by Jackson et al is that prevented cleaning costs per household

per year are US$42 per a reduction in TSP concentrations, from 235 µg/m3 to 115 µg/m3. This would imply a benefit of US$0.35 per household per µg/m3 reduction. This figure could be corrected for wage differences between the United States and the city. If that acceptable, the information needed is the number of households in the city.

2. Monuments. It is difficult to say which value is attached to monuments, as they are often unique and their value is of a subjective character. Nevertheless, the restoration and cleaning costs of monuments could be an indication of the order of magnitude of damage to monuments. Revenue of tourism might also give a certain indication of valuation of future damage to monuments.

Remark 1. In most cases, the valuation of damage is not very precise, and currently not more than

an indication of the order of magnitude.

4. Technological Reduction Options 55. To give a reliable estimate of the costs of technological reduction options, one needs a reliable emission inventory in which is included the currently used technologies and the age and replacement period of the installed equipment. In the absence of this, the study by the city team might wish to concentrate on a case study (e.g. traffic, fertilizer industry, large combustion sources.) • The first step is to identify options. Cooperation with IES is possible, once a case study

is identified • The second step is to estimate the costs, i.e. investment costs and O&M (operation and

maintenance) costs. Based on the economic lifetime of the invested equipment, the investment costs can be transformed to annual costs, using writing-of procedures. Costs will often depend to a large extent on local conditions.

• The third step is to estimate the emission reductions of the various reduction options • The fourth step is to rank the options according to cost-effectiveness. For this purpose

the various types of pollution have to brought under a common denominator. A suggestion could be to calculate a weighted sum of the pollutants, using as weights the amount by which ambient standards are exceeded on average, however this does not take in to account the differences in impacts of pollutants, or increased impacts per unit increase beyond a certain threshold level.

56. The calculation of the cost-effectiveness consists 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.