Urban Air Pollution Analysis for Ulaanbaatar · Urban Air Pollution Analysis for Ulaanbaatar The...

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Urban Air Pollution Analysis for Ulaanbaatar The World Bank Consultant Report

Washington DC USA

Prepared by

Dr. Sarath Guttikunda

Contact Information:

Email: [email protected] +91 9891315946, New Delhi, India

June 2007

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The analysis and views expressed in this report are entirely those of the authors

and should not be cited without permission. They do not necessarily reflect the

views of the World Bank Group, its Executive Directors, or the countries they

represent. The material in this report has been obtained from sources believed

reliable, but may not necessarily be complete and cannot be guaranteed.

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CONTENTS

Acknowledgements ............................................................................................................ix Read Me...............................................................................................................................x Abstract................................................................................................................................ 1

Mapping the changes .................................................................................................................... 1 Opportunities for pollution reduction ....................................................................................... 3 Road ahead ..................................................................................................................................... 7

Report Structure ..................................................................................................................9 1. Ulaanbaatar and Air Quality .......................................................................................... 10

Air Quality Management Bureau, Mongolia ........................................................................... 13 Master Plan for UB Air Pollution Reduction ......................................................................... 17 Integrated Air Pollution Analysis.............................................................................................. 20

2. Nature of the Problem ................................................................................................... 21 3. Sources of Pollutants in UB ........................................................................................... 31

Cookstoves in Gers..................................................................................................................... 33 Cookstoves in Kiosks ................................................................................................................. 37 Power plants................................................................................................................................. 39 Heat only boilers.......................................................................................................................... 42 Vehicular traffic ........................................................................................................................... 43 Fugitive dust (Transport) ........................................................................................................... 47 Fugitive dust (Non-transport) ................................................................................................... 49 Industry - Brick............................................................................................................................ 51 Garbage burning.......................................................................................................................... 53 Hospital Waste Burning ............................................................................................................. 55 Livestock....................................................................................................................................... 56

4. Emissions Inventory for Primary Pollutants ................................................................. 57 Establishing a Baseline ............................................................................................................... 57 Methodology ................................................................................................................................ 59 Assumptions................................................................................................................................. 61 Emissions Inventory ................................................................................................................... 62 Recommendations....................................................................................................................... 70

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5. Air Pollution Analysis .................................................................................................... 73 Mapping of Emissions................................................................................................................ 74 Dispersion Modeling................................................................................................................... 76 Impact Evaluation ....................................................................................................................... 84

6. Possible Interventions.................................................................................................... 87 Improved Stoves in Ger areas ................................................................................................... 88 Briquettes or smokeless coal...................................................................................................... 90 Power plants................................................................................................................................. 94 Abolish small scale boilers ......................................................................................................... 96 Ash pond maintenance and brick making ............................................................................... 97 Reduction of local garbage burning.......................................................................................... 98 Gasification of Urban and Solid Waste ................................................................................. 100 Paved road dust reduction – wet sweeping........................................................................... 102 Transport Demand Management............................................................................................ 103 Renewables for housing – solar water heaters...................................................................... 104

7. Future Scenario Analysis ............................................................................................. 107 Scenario for 2010 and Results ................................................................................................. 107 Scenario for 2020 and Results ................................................................................................. 110

Annex 1: Data Request Sheets ..........................................................................................113 Annex 2: Urban Air Pollution Resources..........................................................................117

Analytical Studies, Research and Toolkits ............................................................................. 117 World Bank Projects with AQM components ..................................................................... 120

List of Tables:

Table A.1: Examples of technical, institutional, and policy interventions .......................................... 3 Table A.2: Level of impact of interventions on air quality in Ulaanbaatar ......................................... 5 Table 1: Vehicular growth perspectives .................................................................................................. 26 Table 2: Survey results for Kiosks and Food Shops (May, 2007)....................................................... 38 Table 3: Average vehicle kilometers traveled in Ulaanbaatar .............................................................. 45 Table 4: Estimated emissions inventory for Ulaanbaatar in 2006 (in tons) ...................................... 63 Table 5: Estimated emissions inventory for Ulaanbaatar in 2010 (in tons) ...................................... 64 Table 6: Estimated emissions inventory for Ulaanbaatar in 2015 (in tons) ...................................... 65 Table 7: Estimated emissions inventory for Ulaanbaatar in 2020 (in tons) ...................................... 66

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Table 8: Average contribution range to center of Ulaanbaatar........................................................... 81 Table 9: Average Dose-Response functions and willingness to pay for health enpoints ............... 85 Table 10: Estimated health costs incurred in each year due to excess pollution ............................. 86 Table 11: Price of various household fuels ............................................................................................ 92 Table 12: Indicative Carbon Finance Revenue in SWM – Case study of India ............................... 99 Table 13: Estimated emissions inventory for Ulaanbaatar in 2010 with controls (in tons) ......... 108 Table 14: Estimated emissions inventory for Ulaanbaatar in 2020 with controls (in tons) ......... 111

List of Figures:

Figure A.1: Estimated baseline annual emissions and concentrations in 2006 .................................. 2

Figure A.2: Modeled future (2010 & 2020) PM10 concentrations (µg/m3) with controls ................ 6 Figure 1: Geographical Location of Ulaanbaatar .................................................................................. 10 Figure 2: Annual Average Temperature and Precipitation in Ulaanbaatar ....................................... 11

Figure 3: Annual Average SO2 and NO2 concentrations (µg/m3) in Ulaanbaatar .......................... 12 Figure 4: Institutional Framework of AQMB in Mongolia ................................................................. 13 Figure 5: Ulaanbaatar Air Quality Stakeholders Database................................................................... 16 Figure 6: Working groups for master plan for UB air pollution reduction....................................... 17 Figure 7: Framework for integrated air quality management .............................................................. 20 Figure 8: Typical air pollution situation in the Winter (January, 2007).............................................. 21 Figure 9: Population growth in the city of Ulaanbaatar ....................................................................... 22 Figure 10: Total number of households in the city of Ulaanbaatar ................................................... 23 Figure 11: Land Classification in Ulaanbaatar (in ha)........................................................................... 24 Figure 12: Vehicular growth in the city of Ulaanbaatar ....................................................................... 26 Figure 13: Health impacts of particulates ............................................................................................... 27 Figure 14: Forest fire and dust storm imagery for Mongolia .............................................................. 28 Figure 15: Topography and Mixing layer heights for Ulaanbaatar ..................................................... 29 Figure 16: Ger areas and Cookstoves...................................................................................................... 33 Figure 17: Cookstoves and annual fuel usage cycle in Gers................................................................ 34 Figure 18: Unconventional fuels used in Ger areas .............................................................................. 35 Figure 19: Pressed coal in Ulaanbaatar ................................................................................................... 36 Figure 20: Kiosks and food shops in Ulaanbaatar ................................................................................ 37 Figure 21: Power plant locations in Ulaanbaatar................................................................................... 39

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Figure 22: Annual coal consumption cycle at Power plant No.4 ....................................................... 39 Figure 23: Fly ash from power plant ash ponds (May, 2007).............................................................. 40 Figure 24: Location of known HOBs in Ulaanbaatar .......................................................................... 42 Figure 25: Vehicular growth vs. Improved road and Average age ..................................................... 43 Figure 26: Percent of transport modes - Total and Public .................................................................. 44 Figure 27: Number of public transport routes by modes .................................................................... 45 Figure 28: Vehicular fugitive dust examples in Ulaanbaatar................................................................ 47 Figure 29: Trucks and Loads .................................................................................................................... 48 Figure 30: Non-transport fugitive dust ................................................................................................... 49 Figure 31: Mongol Ceramic brick factory in Ulaanbaatar.................................................................... 51 Figure 32: Waste generation and disposal shares in 2005.................................................................... 53 Figure 33: Medical waste burning practices ........................................................................................... 55 Figure 34: Livestock population in Ulaanbaatar (in thousands) ......................................................... 56 Figure 35: Estimated percentage contributions to total PM10 emissions in 2006 ............................ 63 Figure 36: Estimated percentage contributions to total PM10 emissions in 2010 ............................ 64 Figure 37: Estimated percentage contributions to total PM10 emissions in 2015 ............................ 65 Figure 38: Estimated percentage contributions to total PM10 emissions in 2020 ............................ 66 Figure 39: Estimated annual total emissions (tons) .............................................................................. 67 Figure 40: Estimated percentage contributions to coarse and fine mode emissions....................... 69 Figure 41: Ulaanbaatar city map............................................................................................................... 74 Figure 42: Wind Rose functions for city of Ulaanbaatar for 2006 ..................................................... 76

Figure 43: Modeled annual average PM10 concentrations in 2006 (µg/m3)...................................... 77 Figure 44: Modeled percentage of modes in annual PM10 concentrations in 2006 ......................... 78

Figure 45: Modeled total PM10 averages for each season in 2006 (µg/m3) ...................................... 79 Figure 46: Modeled source contributions (%) to annual PM10 concentrations in 2006.................. 80 Figure 47: Modeled source contributions (%) to winter PM10 concentrations in 2006 .................. 82

Figure 48: Modeled future (2010, 2015, 2020) PM10 concentrations (µg/m3) under BAU............ 83 Figure 49: Improved cookstoves and manufacturing in Ulaanbaatar ................................................ 89 Figure 50: Change in PM10 source contributions in 2010 for improved stoves............................... 90 Figure 51: Briquettes in use in Ulaanbaatar and fuel characteristics .................................................. 91 Figure 52: Smokeless coal making process............................................................................................. 92 Figure 53: Change in PM10 source contributions in 2010 for briquettes........................................... 93

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Figure 54: Change in PM10 source contributions in 2010 for power plants ..................................... 95 Figure 55: Applications of solar water heating for housing systems in India................................. 105 Figure 56: New buildings in Ulaanbataar ............................................................................................. 106 Figure 57: Estimated percentage contributions to total PM10 emissions in 2010 with controls . 108

Figure 58: Modeled 2010 PM10 concentrations (µg/m3) with controls........................................... 109 Figure 59: Estimated percentage contributions to total PM10 emissions in 2020 with controls . 111

Figure 60: Modeled 2020 PM10 concentrations (µg/m3) with controls........................................... 112

List of Boxes:

Box 1: Pollution Control Technologies for Power Plants ................................................................... 94 Box 2: Use of flyash for brick making .................................................................................................... 97 Box 3: Example of Solar Water Heaters in Rizhao, China ................................................................ 104 Box 4: Renewable energy trends ............................................................................................................ 104

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Acknowledgements

For this study, the process of air quality review and assessment and the establishment of

baseline data were largely conducted over training and data request sheets (see Annex)

presented to respective departments for information and analysis. This process closely

involved discussions with local experts from ministries, external agencies and bodies, beyond

the provision of raw data. I would specially like to acknowledge Ms. Oyuntsetseg

Dugarsuren1, for her efforts and contribution to this report.

1 Former manager, Improved Household Project. Email: [email protected]; Phone: +976-99115526

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Read Me

1. For the city of Ulaanbaatar, this is an inventory for particulate emissions, baseline

estimates using projection trends, and comes with its limitations in application and

discussion.

2. At large limitation is lack of PM monitoring data in the city. Looking at the photo

evidence from winter and summer months and word of mouth, it can be assumed that

the PM ambient levels in the winter months are at least 2-4 times more than the summer

months. Recently installed nephlometer installed in the middle of the city was measuring

150-200 µg/m3 on a “good” summer day.

3. Estimates for emissions and modeling results are Author’s calculations based on data

collected, data available, and material from discussions with local experts. Every attempt

is made to provide the reader with all the possible references for proper guidance.

4. By no means, the emission inventory presented in this study should be considered final,

but an attempt has been made to quantify all the major contributing sources. The reader

is expected to take this into consideration while making any judgments. Analysis focuses

ONLY on particulate pollution.

5. This report describes the results based on data collected and discussions with a number

of local experts from various technical and ministerial departments for one week in June,

2006, followed by two weeks in May, 2007.

6. One of the major challenges for an exercise this is the availability of local database on

various topics. For example, access to the emission factors (gm of pollutant emitted per

tons of fuel consumed) for various applications (industry, transport, households, etc.,) in

Ulaanbaatar is a major drawback. Where numbers are not available, which is most of the

cases, reference numbers were borrowed from neighboring countries. As and when local

capacity to develop these databases exists, these inventories need updates.

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7. There is nothing magical about the year 2020. Current Master Plan for air pollution

control in Ulaanbaatar has a target year of 2020. This study presents scaled estimates for

2010, 2015 and 2020.

8. Some estimates, especially projections and trends, are based on word of mouth and

discussions with local experts from respective departments. For most cases, it was hard

to pin-point a number to quantify changes and develop an inventory.

9. When interpreting the results from the modeling section, it is important to keep in mind

the limitations of the models and view the results as the general level of contributions

from each source or all sources. In developing countries, there exist a number of sources

and most times these sources are unaccounted during the source profiling. Some might

have been over estimated, some under, and some not all. This is an on-going study to

better understand the source potentials in Ulaanbaatar.

10. All the inputs from this exercise and outputs are available for the reader to review and

PROVIDE inputs.

11. The dispersion modeling was conducted outside of Ulaanbaatar. These models are also

available to the reader to download and apply, with a caution that these models are

technical in nature, working on platforms other than Windows, and there is NO

technical training available (besides web-based services) for the dispersion modeling

applications at this time.

12. Potential for reduction of air pollution sources in Ulaanbaatar is based on two findings –

(a) Identification of sources during the data collection process, including sources that are

previously not accounted for in the emissions inventory. (b) Based on example

applications for similar situations in other developing countries. This list of interventions

and potential for reductions is the result of a two week review of the sources in

Ulaanbaatar and these individual interventions clearly need FURTHER detailed study for

project preparation with proper LOCAL INPUTS.

1

Abstract

Mapping the changes

The objective of this report is to provide an analytical basis to underpin discussions on air

quality in Ulaanbaatar and to discuss possible long-term strategies for reducing air pollution;

given the changing demographics, in terms of increasing population and a growing

urbanization and industrialization. These trends have spurred an increase in the demand for

energy in several sectors including transport, construction, heating, industrial production and

have resulted in challenges related to the secondary effects of growth and industrialization

such as pollution from transport, waste disposal, natural resource mining among others.

Thus the increase in air pollution as a result of growing population and urbanization poses a

significant challenge for rapidly growing city like Ulaanbaatar. A scenario analysis of air

pollution emissions in Ulaanbaatar for the years 2010 and 2020 indicate that unless the

government makes a concerted effort to address the issue at multiple levels, air pollution and

its corresponding health impacts in Mongolia will be significant. While there is no single

solution to reduce emissions, a combination of measures ranging from public education and

awareness to strengthening of monitoring and enforcement, to improving technology is

necessary in order to successfully address the increasing levels of air pollution.

Long term measures such as large scale district heating, building public transportation

infrastructure (paving roads) require action at the institutional level, large capital investments

and have a long gestation period. On the other hand short term actions such as installing

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solar panels, introducing efficient stoves, education and awareness on proper ventilation of

kitchens are less capital intensive and while they require mobilization at the level of the user,

are relatively easier to implement. Hence a successful strategy to address air pollution should

include a combination of short term and long term solutions.

Percent Emissions Total PM10 Concentrations (µg/m3)

HH Stoves23%

HoB16%

Veh2%

UPRD7%

Brick3%

OB4%

HWB0%

UNK8%

Other13%

PP34%

Kiosks1%

PRD2%

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Annual Total PM10 = 98.5 ktons

Annual Total PM2.5 = 43.5 ktons

Annual Total SO2 = 23.3 ktons

Annual Total NOx = 53.2 ktons

Daily Standard = 150 µg/m3

Annual average = 200 µg/m3

Winter average = 265 µg/m3

Summer average = 125 µg/m3

Local authorities need to develop a well defined process for action planning, preferably

based on existing processes and activities, and built on the existing institutional frameworks.

It is important to associate the process of Action Planning with other activities and functions

such as – establishing a baseline, analyzing the source categories, developing set of options,

considering the necessary indicators (air quality improvements, perceptions and

practicability) then prioritizing the options with the highest marginal benefits in the short

and long term, and draft the Action Plan, involving an array of stakeholders from public,

private, political, and academic backgrounds. Figure A.1 presents the baseline contributions

of identified sources to the PM emissions in the city along with the modeled concentrations

for year 2006. Although this report focuses more on the outdoor air pollution issues, it is

Figure A.1: Estimated baseline annual emissions and concentrations in 2006

Abstract 3

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important to note that the same pollution sources also contribute to indoor air pollution

within the Gers.

Opportunities for pollution reduction

Initiatives aimed at reducing emissions from local sources should be based on assessments

of their relative contributions to the pollution load. The problem of air pollution is complex

for where there are no cookie cutter solutions. Interventions that are tailor made for

Ulaanbaatar should build on existing practices and institutional setup and should include a

large awareness campaign that is implemented at all levels; among citizens and the public,

non-governmental organizations, industry, the municipality, government, and donor

agencies. Some of the ways in which air pollution can be addressed are detailed in Table A.1

(note that there is an overlap between types of interventions) and level of impact of some of

these interventions is presented in Table A.2.

Table A.1: Examples of technical, institutional, and policy interventions

Technical (T)

• Eliminate gas leaks – VOC recovery – primary at least (P)

• Inspection & maintenance for commercial vehicles (P, E)

• Coal briquettes, wood pellet, better solid fuel stove design (P)

• Promote more efficient agricultural burning methods (P, E)

• Less polluting – better ventilated kitchens (A)

• Reduce sulphur content of diesel and gasoline to 500 ppm or lower (P)

• Require new gasoline cars to have three way catalytic converters (P)

Institutional (I)

• Identify, encourage and promote best practices (A)

• Create Clean Air Group which includes industry, fuel provides and NGOs (A)

Road, Transport, Traffic Management (R)

• One way traffic with synchronized signals (T, E)

• Paving roads (T, E)

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• Pavements for pedestrians (A, E)

• Affordable public transportation (A, E, T)

• Train bus drivers about pollution and fuel use (A)

• Discourage SUVs and encourage fuel efficiency goals (T, A)

Policy (P)

• Lead -free gasoline (T)

• Promote only four stroke vehicles (T)

• No burning of garbage, leaves (E)

• Discontinue fuel subsidies

• Lower tax on clean fuels and energy efficient technologies (T)

• Wet sweeping of the roads (R)

Awareness, Media, Educational and social (A)

• Publish and broadcast AQI (T)

• Regular media outlet for AQ stories to keep up interest (T)

• Draw the connections between air quality and health.

• Environment education at primary level, agricultural extension (T)

Enforcement (E)

• Identify gross polluters (T)

• Squealer or complaint phone or text message number to report polluters (P) Examples of Failures

• Too advanced technology – beyond capacity to maintain – parts supply

• I & M for personal vehicles without proper Q & A

• Capital investment without operation and maintenance funds

• Emissions Inventory is wrong which leads to wrong solutions

• Arguing for leaded gasoline against the impacts benzene and other VOCs from unleaded

gasoline

Abstract 5

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Table A.2: Level of impact of interventions on air quality in Ulaanbaatar

Intervention Status Impact on Air Quality in the short term Comments

Monitoring Current capacity to monitor PM pollution in the city is low. Low AQ monitors are very essential to evaluate the impact of air

pollution reduction measures.

Client Capacity Air Quality Management Bureau (AQMB) formed in August 2006 Low Capacity building on integrated air quality management is

necessary to prepare a sound and effective action plan.

Improved Stoves Pilot program in implementation HighHousehold stoves are a low lying source and contributes significantly in the winter months. This intervention is expected to have an immediate impact on ground level concentrations.

Fuel substitution -briquettes

Private and small scale projects in implementation High

Along with the improved stove program, fuel substitution with briquettes from sawdust and coal is expected to further reduce the outdoor air pollution burden. This intervention expands to all coal users.

Pollution control at power plants

Only CHP-4 is using ESP at 95 % PM capture efficiency and no sulfur or NOx controls in place.

HighOne of the largest elevated sources in the city. Technology such as ESPs and FGDs is mature and available internationally.

Public awareness Media, public, and political demands. Low An essential part of the campaign to promote energy efficiency at the household level.

Garbage collection Limited program in place with substantial amount being burnt in-situ Medium This requires institutional set-up for garbage collection and

landfill management.

LPG Limited supply to taxis Low This intervention needs pricing and supply reforms, to make it more widely available.

Paved road dust Manual sweeping in place MediumThis intervention is expected to reduce spring and summer time on-road fugitive source. Heavy-duty vehicles for this purpose are available internationally.

Going unleaded City still imports leaded gasoline HighGasoline is imported and city lacks testing facilities to check lead content in gasoline. This intervention requires a strong resolution to import unleaded gasoline only.

Energy efficiency at heat only boilers

A number of small and medium scale boilers in use High

Nearly 800 small boilers are operated in the city for heating purposes. This intervention can reduce dispersed pollution by abolishing small scale boilers and upgrading them to district heating system.

Solar water heating for housing systems

No activity HighThis is an expensive and possible short term intervention. With the new 40,000 housing system in plan, the solar water heating can reduce the load on district heating system and power plants. Technology is available internationally.

Gasification of urban and solid waste

No activity MediumIn combination with garbage and solid waste management, can supply for small scale energy needs and heating. Technology is well documented and available internationally.

Ash ponds from power plants No activity Medium

This intervention is expected to reduce spring and summer time fugitive source out of power plants ash ponds. Technology for using ash to make bricks and construction material is well studies and available internationally.

Bus Rapid Transport No activity Low

Fleet is small and their effect may be counteracted by growth in the passenger vehicles and barriers such as lack of policy frameworks for inspection and maintenance.

Note: High indicates immediate and large reductions; Medium indicates moderate and sporadic reductions; Low indicates less or non-direct reductions in air quality; Authors interpretations

6 UAPAU

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2010 Assumed improvements from business as usual (BAU): 50 percent shift to improved stoves in the households; 50 percent shift from coal to briquettes in the household stoves; 50 percent abolishment of small heat only boilers operating in the city; 50 percent improvement in the garbage collection and reduction of in-situ burning; Use of fly ash from power plant ash ponds, reducing the unknown

PM10 % Change from BAU

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City central annual average = 195 µg/m3; Avoided health costs = US$ 148 million

2020

Assumed improvements from BAU: 100 percent shift to improved stoves in the households; 100 percent shift from coal to briquettes in the household stoves; 50 percent abolishment of small heat only boilers operating in the city; Halving the growth of small and big heat only boilers and promotion of district heating and solar water heating; 50 percent improvement in the garbage collection and reduction of in-situ burning; Introduction of ESPs for all the power plants without (2 & 3) and improving the efficiency of ESPs with (4 & 5); Introduction of FGD systems reducing SO2 and NOx emissions by 75 percent; Use of fly ash from power plant ash ponds, reducing the unknown; Mechanical sweeping of the paved roads and reducing the silt loading on roads for the spring and summer and conversion of a fraction of unpaved to paved roads in the Ger area.

PM10 % Change from BAU

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City central annual average = 163 µg/m3; Avoided health costs = US$ 690 million

Figure A.2: Modeled future (2010 & 2020) PM10 concentrations (µg/m3) with controls

Abstract 7

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Road ahead

The scenarios and control options for year 2010 and 2020 are based on several assumptions;

however they provide a direction to policy makers and experts and allow them to evaluate

the relative benefits and impacts of different policy strategies, which are discussed in greater

detail in this report. Figure ES.2 presents pollution levels estimated for year 2010 and 2020

with some control measures, expected reduction in concentrations from business as usual

scenarios for 2010 and 2020 and avoided health costs compared to business as usual.

The framework for the Air Quality Analysis for Ulaanbaatar, as detailed in this report, has

been established after consultation and interaction with multiple stakeholders in Ulaanbaatar,

and taking into account the current institutional setup. It is important that stakeholders at all

levels are taken into consideration when establishing a long term air quality strategy.

9

Report Structure

Chapter 1 presents background information on the city of Ulaanbaatar and the current air

quality management program. Chapter 2 provides an overview of air quality problem

including general statistics, air quality, and climate for the city of Ulaanbaatar, followed by

Chapter 3 which describes an inventory for sources of air pollution. Chapter 4 presents

methods used to calculate, results from the emissions inventory exercise, compilation of the

final emission maps and data products. Chapter 5 presents results from air pollution

dispersion modeling for baseline scenarios, contributions from various sectors to ambient

levels. Chapter 6 provides an overview of possible interventions for various sectors, followed

by respective modeling results for two scenarios in Chapter 7.

The main objectives of this study are to review and assess the sources of PM, using a

combination of data collection, surveys, and application of analytical tools. These methods

have the potential to provide an indication of the relative contributions of different sources

to ambient air pollution and potential to reduce emissions and ambient pollution levels. The

analysis covered in this project involves four general tasks:

1. Review of currents trends in air pollution in Ulaanbaatar

2. Review of sources of air pollution, with focus on particulate matter

3. Development of a baseline emissions inventory for primary pollutants

4. Analyze potential for reduction emission sources

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1. Ulaanbaatar and Air Quality

Ulaanbaatar is located at ~1300 meters above sea level, slightly east of the center of

Mongolia on the Tuul River (see Figure 1), a sub-tributary of the Selenge, in a valley at the

foot of the mountain Bogd Khan Uul. Ulaanbaatar (UB) is the coldest national capital in the

world, with an average annual temperature of -1.3°C (29.7°F) (see Figure 2).

106.7 106.75 106.8 106.85 106.9 106.95 107 107.05

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106.7 106.75 106.8 106.85 106.9 106.95 107 107.05

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Figure 1: Geographical Location of Ulaanbaatar

Ulaanbaatar and Air Quality 11

The country averages 257 cloudless days a year, and it is usually at the center of a region of

high atmospheric pressure. Precipitation is highest in the north (average of 20 to 35

centimeters per year) and lowest in the south, which receives 10 to 20 centimeters annually.

Average Air Temperature (oC)

-5.5-5

-4.5-4

-3.5-3

-2.5-2

-1.5-1

-0.50

0.51

1941

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2001

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Total Precipitation (mm/year)

0

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100

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350

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450

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1943

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1947

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1995

1997

1999

2001

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2005

Source: Ulaanbaatar Statistical Year Book, 2006

In this growing city of Ulaanbaatar, air pollution is becoming a top priority issue, mainly

owed to growing population, energy consumption for the cooking and heating, and rapidly

expanding vehicular fleet. The city Air Quality Division (AQD) operates four fixed air

quality monitoring stations and 15 mobile stations for regulatory purposes. These four only

measure sulfur dioxide (SO2) and Nitrogen Oxides (NO2) concentrations. Although PM is

recognized as the main health deterrent, the four stations lack technical support to measure

particulate (PM) pollution. Figure 3 presents station locations and monthly average SO2 and

NO2 concentrations measured at the four stations. Stations UB-2 and UB-4, which are closer

to central Ulaanbaatar, are indicative of urban signature. Specific studies from the

monitoring data indicate rise in the peak SO2 and NO2 concentration. However, SO2

pollution, which has sources similar to PM10, primarily coal combustion, confirms a direct

linkage to growing trend in coal use. Similarly, growing vehicular population is one of the

primary causes for increased NO2 levels, a primary precursor for ground-level ozone

pollution and secondary contributor to PM2.5 pollution.

The World Bank Environmental Monitor 2004 estimates the daily mean concentration of

PM at 131-162 µg/m3 for 2002 which is 2 times higher than internationally accepted

Figure 2: Annual Average Temperature and Precipitation in Ulaanbaatar

12 UAPAU

standards. This number is averaged over intermittent measurements using a high-volume

sampler made over a year and the current levels of PM are expected to be double this

reported value.

Monitoring Station Locations in Ulaanbaatar, Mongolia

UB-1

UB-2UB-3

UB-4

Monthly average SO2 (µg/m3)

0

10

20

30

40

50

60

70

80

Dec-01 Jun-02 Dec-02 Jun-03 Nov-03 May-04 Nov-04 May-05 Oct-05 Apr-06 Oct-06

UB-1

UB-2

UB-3

UB-4

Monthly average NO2 (µg/m3)

0

10

20

30

40

50

60

70

80

Dec-01 Jun-02 Dec-02 Jun-03 Nov-03 May-04 Nov-04 May-05 Oct-05 Apr-06 Oct-06

UB-1

UB-2

UB-3

UB-4

Source: Dr. Enhmaa Sarangerel, CLEM, Ulaanbaatar, Mongolia

Preliminary findings of a study conducted by the World Bank group2 on indoor air pollution

inside Gers indicate that PM and carbon monoxide (CO) are way above WHO standards.

For example, the Mongolian standard for 24 hour suspended particle concentration is 150-

200 µg/m3. This standard is very high considering the standard set by US-EPA for PM2.5 is

65 µg/m3. Yet the mean PM measurements in homes with individual heat stoves measured

at 750 µg/m3.

2 Coulter-Burke, Edwards, Kaufman, and Smith, Impact of Improved Stoves on Indoor Air Quality in Ulaanbaatar, Mongolia, July 6, 2004. http://esmap.org/filez/pubs/31305MongoliaIAP090905forWeb.pdf

Figure 3: Annual Average SO2 and NO2 concentrations (µg/m3) in Ulaanbaatar


Air Quality Management Bureau, Mongolia

Following a multiple stakeholder meeting on air pollution in Ulaanbaatar, at the World Bank

office, Ulaanbaatar, Mongolia, in June 2006, the Air Quality Management Bureau (AQMB)3,

presented in Figure 4, was established under the organizational structure of National Agency

for Meteorology Hydrology and Environmental Agency (NAMHEM) in August 2006 and

under a national air quality council with the Ministry of Nature and Environment (MNE).

Air Quality Management

Bureau

National AQ Council

(with MNE)

Secretary of AQMB

Specialized Organizations

AQ Division of UB

AQ Divisions for

Provinces

CLEM

Ozone

Monitoring

ICC

Inst. Of Meteorology and Hydrology

AQMB acts as focal point for air quality related activities at national and international level

and is expected to expand further in its activities and responsibilities in the near future. This

has major implications for stakeholders at all levels of Government, industry, Academia, and

international agencies. A list of expected stakeholder’s database for Phase-I activities through

2010 is presented in Figure 5. The underlying principle of AQMB is the management of air

quality at various spatial scales, from national, district to local scale. At the provincial level,

AQMB secretariat oversees the activities for individual air quality divisions. It is also

applicable at the level of individual polluters, with an agenda for continuous improvement of 3 Contact person at AQMB is Ms. Oyunchimeg Dugerjav (Email: [email protected])

Figure 4: Institutional Framework of AQMB in Mongolia

14 UAPAU

emission standards and air quality. Main responsibilities4 outlined during the establishment

of AQMB are

• To prepare proposals for standards, regulations and procedures related to

improvement of air quality and establishment of decision making authorities for

implementation

• To prepare proposals for short, medium, and long term programs for air quality

protection and introduce to MNE

• To establish and provide methodology for national air quality monitoring network

unit

• To collect all data and information from air quality monitoring network followed by

creation of a database for analysis and information sharing

• To collect data and information for air quality from local centers and emission

sources

• To summarize all information on air quality for government and public

• In case of an emergency of increased radioactivity levels and diffusion harmful

chemical components, to provide urgent information for government and public

• To establish sub-database for air quality and submit to central environmental

database

• To organize activities for setting emission standards for stationary and mobile

sources

• To conduct assessment for air pollution emission based on measurements and

analysis by air quality divisions and centers for meteorology, hydrology, and

environmental monitoring of Capital city and aimags (provinces).

• To prepare inventory of greenhouse gases and CFCs (ozone depleting substances)

for submission to MNE

• To initiate registration of air pollution emission sources with MNE for every year

• To renew inventory of emission sources every 5 years for submission to MNE

4 Based on translated list provided by Ms. Oyunchimeg Dugerjav Secretary, AQMB


• To collect information from organizations and companies in import and export

activities

• To prepare information for customers, who requests information for conflict for air

quality

• Rights of AQMB

o To control national air quality monitoring network

o To control air pollution emission sources and collect information

o To control implementation of emission and air quality standards

o To control and assess emissions from mobile and stationary sources

o To control and check all equipment at emission reduction faculties

The program team has a good mixture of experienced professionals pulled from specialized

organizations in the fields of air quality management, industrial processes, training,

information systems, and monitoring.

16 UAPAU

Figure 5: Ulaanbaatar Air Quality Stakeholders Database

Ula

anb

aata

r A

ir Q

ual

ity

Stak

ehol

der

s D

atab

ase

Pha

se I

: 20

06-2

010

Gov

ern

men

t O

rgan

izat

ion

s

State Inspection Authority

MNE and AQMB

Loc

al G

over

nan

ce

Off

ices

Scie

nti

fic

Res

earc

h

and

Un

iver

siti

esP

ub

lic a

nd

Soc

ial

Com

mu

nic

atio

ns

Bu

sin

ess

En

titi

es

National Emergency Board

Related Ministries

–MCUD, MF, MH, MFE

City Environmental Agency

Scientific Research Institute for Urban Development

City Inspection Office

City Emergency Office

City Land Relationship Office

City Air Quality Division

SR Universities & Institutes

SR Academy and Institutes

Institute of Geography of SRA

Institute of Eco-geology of SRA

Botanic Institute

Biological Institute

Social Health Institute

CLEM

School of Geology, Energy, and Construction

Ecological Research Center for Technical University

Professional Organizations for EnvironmentNon-Governmental Org.

Communities

Trade and Services

Industries

Investors and Non-Bank Org.

Information Service Org.

Light

Raw Material Processing

Fuel and Energy

Mining

Construction Material

Inte

rnat

ion

al

Org

aniz

atio

ns

International Conventions and Agreements

International Environmental Research Org.

UN Branches

Foreign Countries

International Monetary

Asian and East Asian Regional Networks

RAMSAR, International Trans-boundary Water Conventions, UNCCD

WWF, Research Center for BaigalLake

UNEP, UNDP, UNCCD, MAB

WB, ADB

NEASPEC, DSS, NEAN

Sou

rce:

Pro

f. G

onch

igsu

mla

a,

Nat

iona

l Uni

vers

ity o

f Mon

golia


Master Plan for UB Air Pollution Reduction

The high levels of air pollutants in urban areas of Ulaanbaatar and similar trends in the

smaller cities of Mongolia, have led to a call for a better understanding of air pollution

sources, improved understanding of how to management options – technical, institutional,

economic, and policy, and to understand the potential for interventions to better air quality.

Parliamentary Working Group

For AP PlanMinistries of Environment,

Energy, Urban Development

Central Government

Air Quality Division – UB City

WG-I WG-II

AQMB &

MNEDirect Interactions and Support

Support for working groups –data and analysisSupport to Parliamentary working group

Source: Author’s interpretation based on discussions with working groups and AQMB

Local institutions were given responsibilities for reviewing and assessing local air quality as

part of the National and City Air Quality Master Plan. Formal review and assessment is a

three-stage process (Local institutions, Municipality, and Parliament as shown in Figure 6)

requiring city municipality to monitor pollution levels of key air pollutants (particulates), and

to prepare a short term and long term action plan to reduce local air pollution levels. The

Mongolian Parliament is discussing a draft resolution on measures for the reduction in air

pollution in Ulaanbaatar City. During the preparation of Master Plan for the reduction of air

Figure 6: Working groups for master plan for UB air pollution reduction

18 UAPAU

pollution, AQMB and the associated teams play a vital role in the monitoring and analysis of

the air pollution.

Together there are three working groups preparing this Master Plan (see Figure 3) – one at

the Parliamentary level, consisting of Member of Parliaments and members from respective

ministries – Nature and Environment, Fuel and Energy, Construction and Urban

Development, Transport, etc. Some of the control features highlighted in the resolution and

stressed upon by Honorable Member of Parliament, Mr. Bakey, Deputy Chairman of the

Parliament WG, during a meeting are

• Ger area re-planning and infrastructure building – city municipality is expected to

convert 80% of the Ger areas into housing complexes by 2020. Plan for

reconstructions of various Ger sections and time frame are discussed in the draft

report by one of the technical working groups (WG-I).

• Conversion of coal to Briquettes (smokeless coal). Plan is to refurbish the CHP-2 to

manufacture smokeless coal and establish similar plant near the Baganuur coal mine

to supply ~70,000 households with better quality coal for cooking and heating.

• Commission a new power plant to the east of the city, to support the new housing

constructions and demand for hot water and heating.

• Institutional reforms to support vehicular pollution reduction - to promote

inspection of vehicles, support LPG conversions for Taxis, retirement of old

vehicles, stricter regulations on imports – for lead free gasoline, and make LPG

available for most of the public transport by end of 2008.

• Legislation for "Polluters Pay". A ten point law is in preparation by MNE for various

industries and individual polluters.

• Plan to promote air quality monitoring and support improvement of local and

national laboratories.

• Need to promote “Short term activities based on long term strategy” with full ecological and

economical analysis of various interventions.


Other two groups are “Technical Working Groups” supporting the preparation of an

action plan and analysis of strategy for reduction of air pollution.

One of the working groups is headed by Prof. Gonchigsumlaa, with the department of

Geoecology and Land Use Management at National University of Mongolia, and other by

Dr. Oyun Ravsal, General Director, JEMR Consulting Co. Ltd., formerly with the remote

sensing group in the Ministry of Environment in Ulaanbaatar. These teams are required to

conduct an integrated analysis consolidating technical, economic, physical and ecological

aspects of air pollution. Main responsibilities5 of the working groups are to:

• Coordinate among departments to establish baseline and action plan

• Conduct analysis to draw the vision for healthy city

• Develop a Master Plan of action incorporating measures to secure political

commitment

• Ensure the participation of community, NGOs and private sectors to mobilize non-

government resources

The Master Plans by both teams is under preparation and they are required to submit for

discussions in June/July, 2007, at which point local authority must declare Air Quality

Management Areas and draw up an Action Plan to reduce air pollution levels.

5 Provided by Dr. Oyun from JMER during the discussions. Her team consists for 30+ members from various departments.

20 UAPAU

Integrated Air Pollution Analysis

One of the key factors in the implementation of a successful air quality management plan is

better understanding of nature of local and regional pollution. The four main elements

which must be considered, both for individual options and Action Plans, are source

strengths, air quality impacts, perceptions and practicability, and cost effectiveness. Air

quality per se cannot be managed. However, air polluting activities and behavior can be

managed. An air quality management system, regardless of the scale, is an integrated system

that assesses input to the atmosphere (emission), determining resultant concentrations in the

ambient environment (measurement/modeling/ analysis), assessment of the impact against

legislation, addressing process of behavior to reduce (mitigation), and reassessment versus

targets on the path of continual improvement. This study aims to promote an integrated

assessment framework for air pollution in Ulaanbaatar.

SourcesSources

Air QualityAir Quality

ImpactsImpacts

Integrated Integrated Air Quality Air Quality ManagementManagementPolicy Policy

OptionsOptionsTechnical Technical OptionsOptions

Economic Economic OptionsOptions

SourcesSources

Air QualityAir Quality

ImpactsImpacts

Integrated Integrated Air Quality Air Quality ManagementManagementPolicy Policy

OptionsOptionsTechnical Technical OptionsOptions

Economic Economic OptionsOptions

Figure 7: Framework for integrated air quality management

21

2. Nature of the Problem

The pictures presented below are growingly common feature for the city of Ulaanbaatar in

the winter seasons. Fossil fuel, mostly coal in the case of Mongolia, (e.g., combustion for

domestic cooking and heating, power generation, industrial processes, and motor vehicles) is

the primary source of air pollution. In addition, the burning of biomass such as firewood,

agricultural and animal waste contributes in the household sector for a large proportion of

the pollution in some urban areas.

Source: Dr. Sarantuya Myagmarjav, MNE

The most typical urban pollutants include suspended particulate matter (SPM), sulfur dioxide

(SO2), volatile organic compounds (VOCs), lead (Pb), carbon monoxide (CO), carbon

dioxide (CO2), nitrogen oxides (NOx) and ozone (O3) (a secondary pollutant formed due to

the chemical interaction of the various pollutants mentioned above). Of all the pollutants

Figure 8: Typical air pollution situation in the Winter (January, 2007)

22 UAPAU

listed above, most of which are well studied and have established ambient air quality

standards under WHO6 to safeguard public health and protect the environment, it has been

shown that particulate matter7 (PM) is one of the most critical pollutants responsible for the

largest health and economic damages. Because of the importance of PM pollution for human

health, visibility and the environment, and due to the expertise and interests of the agencies

and staff involved, this exercise focused primarily on PM pollution as a target pollutant for

interventions and analysis, while attempting to remain general enough to be applicable to a

wider range of pollutants.

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

1930

1935

1940

1944

1950

1956

1960

1965

1970

1975

1980

1985

1990

1995

2000

2001

2002

2003

2004

2005

2006

2010

2015

2020

Tot

al P

opu

lati

on, t

hou

san

ds

10% Growth Rate

8% Growth Rate

5% Growth Rate

Current - 4%


Growing levels of urbanization have resulted in increasing air pollution due to higher activity

in the electricity demand, transportation, energy and industrial sectors, and energy for

6 WHO, 2006 Air Quality Guidelines - http://www.who.int/phe/health_topics/outdoorair_aqg/en/ 7 PM is generally measured in terms of the mass concentration of particles within certain size classes: total suspended particulates (TSP), PM10 (with an aerodynamic diameter of less than 10 micron, also referred as coarse), and PM2.5 (with an aerodynamic diameter of less than 2.5 micron, also referred as fine), and ultrafine particles are those with a diameter of less than 0.1 micron. The distinction between the coarse and fine particles are made due to differences in sources, formation mechanisms, composition, atmospheric life spans, spatial distribution, indoor-outdoor ratios, temporal variability in addition to size, and health impacts.

Figure 9: Population growth in the city of Ulaanbaatar

Nature of the Problem 23

domestic cooking and heating, which are all concentrated in densely packed city of

Ulaanbaatar. Figure 9 presents total population growth for the city. In early 2007, total

urban population reached the milestone of 1 million8. And at the current growth rate of 3.8

percent, which had been constant over the last five years, total urban population is expected

to reach 1.75 million in year 2020 ranging up to an unlikely 4.5 million at a 10 percent

growth in the coming decade.

In the recent years, one of the major causes for total population rise is in-migration. Two

main factors that are fueling the in-migration: 1) higher incomes in towns compared to

villages; and 2) increased employment opportunities, especially in the construction and

mining sectors. Also, a combination of the city’s' relative isolation and government policy

preventing in-migration to cities have spurred the growth in the Ger areas of Ulaanbaatar.

0

35,000

70,000

105,000

140,000

175,000

210,000

245,000

280,000

315,000

350,000

385,000

1930

19351940

19441950

19561960

19651970

19751980

19851990

19952000

20012002

20032004

20052006

20102015

2020

Total Number of Householdsin Ulaanbaatar

4% Growth Rate

0

40,000

80,000

120,000

160,000

200,000

240,000

280,000

2000 2005 2006 2010 2015 2020

Total Number of Gers in Ulaanbaatar

5% Growth Rate


In 2005, total number of Gers was estimated at 120,000, which increased to an estimated

130,000 for year 20069, primarily because of in-migration from the neighboring provinces.

The Ger population is expected to grow increasingly until 2010, after which point the

growth rate is expected to slow down, indicating the limits for growth of some Ger areas. 8 Reader should note that the numbers presented here are from the Statistical Yearbook for Ulaanbaatar. General discussions with local experts reveal that there is a bias in number reporting, and the error could be as large as 30% for the reported numbers. Current population for 2007 is estimated at over 1.2 million. 9 Similar is the case for the households and Gers. The number presented is the number registered and due to in-migration, an unofficial number is expected to be at least 30% higher.

Figure 10: Total number of households in the city of Ulaanbaatar

24 UAPAU

Rapidly growing urban areas are ill equipped to absorb such a fast growing population. The

lack of infrastructure has brought on severe problems such as waste management, lack of

clean water and sanitation, and high levels of air pollution. Figure 11 presents total land

allocated for the city development – settlers, transport, and other activities. Over the last

decade, the land allocation has been very steady compared to the population and vehicular

growths, putting together a congested picture for the municipality. Also, given the natural

constraints in the layout of the city, as a linear city, major transport corridors are along its

east-west axis.

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000Total

Settlements

Transport


With the bludgeoning population in the cities, comes the energy demand - for electricity,

cooking, heating, industrial use, and for running vehicles. Heating is required for almost nine

months of the year and is generated primarily through the combustion of poor quality coal.

Electricity and heating is provided to apartments and commercial buildings from 3 large

Figure 11: Land Classification in Ulaanbaatar (in ha)


combined heat and power plants and around 910 inefficient heat only boilers10 burning 6.0

million tons of domestically produced lignite per year.11

The quality of Mongolia’s reserves covers the full range, from lignite (low-grade coal)

through bituminous and coking coals but most of the current production is low-grade coal.

Three large mines (Baganuur, Shivee Ovoo, and Sharyn Gol) produce most of the lignite

that supports current core energy services in Mongolia. Their production is mainly lignite

with heating values ranging from 2,700 to 4,000 kcal/kg, 18-35% moisture and 12-25% ash.

In addition, small and medium mines produce coal of similar quality with a heating value of

5000 kcal/kg and low moisture. All coals in Mongolia are low in sulfur (less than one

percent).

In the domestic sector, heating in Gers is provided by over 130,000 individual household

stoves using an estimated 0.6 million tons of coal per year. An unofficial survey estimates

this number to be much higher because growing kiosks and food shops that use smaller, if

not similar size, stoves for heating purposes. In the last five years, the number of kiosks is on

the rise along with Ger population. More detailed analysis is presented in the coming

sections. On average, Gers are estimated to consume 5 tons of coal and 3.0 m3 of fuel wood

per year. Most of the coal is consumed during the heating season and fuel wood during the

spring and summer months for cooking and minor heating needs.

The transport sector is the other ever growing sector, with an estimated 15 percent vehicular

growth rate in the last five years, especially private vehicles. In 2006, total in-use vehicular

population is estimated at 80,000 inclusive of public transport system. This number is based

on the statistical report, although one of the latest reports suggests an in-use vehicular

population of ~150,00012, with 60% of the fleet of age more than 11 years. Currently, most

of the heavy duty fleet, especially diesel trucks are old and tend to produce higher emissions

10 Conversation with City Engineers office 11 A more detailed assessment of the Energy sector is available in the 2007 Mongolia Infrastructure Report by the World Bank. 12 http://www.montsame.mn/newsdetail.php?nid=112665

26 UAPAU

compared to the permissible levels. Figure 12 presents statistics on vehicular growth rate in

the past 40 years with the highest growth coming in the last 5 years13.

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

1960

1966

1970

1975

1980

1985

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

-10%

0%

10%

20%

30%

40%

50%Total VehiclesGrowth Rate


Table 1: Vehicular growth perspectives

Category 2004 2005 2006 2010 2015 2020 Passenger vehicles 49,123 54,316 58,541 Trucks 9,658 10,954 12,001 Buses 6,553 6,130 6,303 Tank Cars 702 587 448 Special Vehicles 1,325 1,753 2,247 Sub Total 67,361 73,740 79,540 104,993 146,990 205,786 Motorcycles 333 370 368 Tractors 730 656 708 Trailers 1,190 1,384 1,490 Grand total 69,614 76,150 82,106 108,380 151,732 212,424 Source: Dr. Sereether, Director, Department of Transport, Ulaanbaatar, Mongolia

The current growth is expected to continue in the coming decade (see Table 1), more than

doubling by 2020. A large portion of this increase is expected among passenger vehicles –

13 Please note that these statistics are not without any errors. The dip in the vehicular population in 2003 is very likely an error. Otherwise there was no dramatic cut down in the fleet numbers in 2003 for this drop.

Figure 12: Vehicular growth in the city of Ulaanbaatar


car and vans. Another major shortcoming in the transport sector, given the land constraints

in a linear city like Ulaanbaatar, is that municipal plans rarely consider how land-use changes

will be effected by such a growth in vehicles.

Particle Size (mm)

9.2 to 30

5.5 to 9.2

3.3 to 5.5

2.0 to 3.3

1.0 to 2.0

0.1 to 1.0

Effect

Visible Pollution

Lodges in nose/throat

Main breathing passages

Small breathing passages

Bronchi

Air sacs

The health impacts of air pollution (asthma, chronic bronchitis, minor respiratory irritations,

etc.,) are also on the rise in the city of Ulaanbaatar, mainly because of prolonged exposure to

high levels of respirable particulate matter from various sources. It is well documented that

particles (PM10, PM2.5, and secondary PM due to SO2 and NOx emissions) cause negative

health effects when inhaled by people working and living in the areas surrounding the

construction sites, indoors where the cooking and heating takes place using coal, and on the

roads where there is a constant exposure to fumes from vehicles and re-suspended dust in

the city. These health effects include premature death, acute respiratory illness, aggravated

asthma, chronic bronchitis and decreased lung function. The poor, undernourished, very

young and very old, and people with preexisting respiratory disease and other ill health, are

more at risk. Especially, in the Ger areas with higher population density and close knit coal

combustion units, the concentrations (both indoor and outdoors) in the winter exceed the

World Health Organization (WHO) standard many times, the incidence rates for various

Figure 13: Health impacts of particulates

28 UAPAU

health effects are much higher. A more detailed assessment of health impacts and incidence

rates for various pollutants can be obtained from HEI14.

In Mongolia, seasonal natural phenomena (spring and summer months) cause a considerable

amount of air pollution. The dust storms from the Gobi deserts (predominantly yellow sand)

and forest fires from the north, contribute substantially to sporadic PM pollution spikes.

Due to the magnitude of the impact of these events, pollution due to natural phenomena is

more of a regional concern than an urban issue. The dust blown from the Sahara desert15 has

been detected in West Indian islands and in the spring time dust blown from the Gobi

desert16 has been detected across the Atlantic Ocean days after passing over the Pacific

Ocean and during Northern American transit raising PM levels above WHO standards.

During these dust storm periods, PM measurements of over 1000 µg/m3 were recorded in

Northeast China and Mongolia.

Source: Information and Computer Center, Ulaanbaatar, Mongolia

14 Health Effects Institute, www.healtheffects.org 15 Africa to Atlantic, Dust to Dust - http://www.gsfc.nasa.gov/feature/2004/0116dust.html 16 In April 1998, one the strongest dust storms, documented at http://capita.wustl.edu/Asia-FarEast/ crossed the Pacific and Atlantic Oceans in a period of 10 days; Haze over Eastern China – Observations of November 6th, 2006 http://earthobservatory.nasa.gov/NaturalHazards/natural_hazards_v2.php3?img_id=13953.

Figure 14: Forest fire and dust storm imagery for Mongolia


During the dry and windy seasons, the impact of dust storms and yellow sand combined

with smoke from forest fires in the North of Mongolia is severe not only for health reasons,

but also esthetic value of the City’s infrastructure. Figure 14 presents total forest and grass

lands burnt in year 2006 and a dust storm passing through the city of Ulaanbaatar in April

2005. In the passing days, secondary effects of these dust storms also include resuspension

of dust settled on buildings, roads, and vehicles. The Information and Computer Center

(www.icc.mn), under the Ministry of Nature and Environment, provides updated

information on forest fires and dust storms on their website.

0

200

400

600

800

1000

1200

1400

1600D

ec-99

Jul-00

Feb

-01

Oct-01

May-02

Jan-03

Au

g-03

Mar-04

Nov-04

Jun

-05

Feb

-06

Sep-06

Ap

r-07

Source: Map by Prof. Gonchigcumlaa, National University of Mongolia and Heights from Assembled Met fields from NCEP Reanalysis data17

In Ulaanbaatar, enhancement of the air pollution and entrapment of pollutants is also due to

its location and topography. Figure 15 presents the map of Ulaanbaatar, which is surrounded

by valley of mountains. Pollution sources tend to be concentrated, and in the weather

phenomenon known as thermal inversion18, a layer of cooler air is trapped near the ground

by a layer of warmer air above not allowing for any dispersion of pollutants – as seen the

Figure 8. When this occurs, normal air mixing almost ceases and pollutants are trapped in

the lower layer. Local topography, or the shape of the land, can worsen this effect, as is the

17 This data is obtained from NCEP/NCAR reanalysis data fields available at http://www.cdc.noaa.gov/cdc/data.ncep.reanalysis.pressure.html 18 A thermal inversion is where cool air is trapped by warm, resulting in an extremely stagnant pocket of air at the earth's surface, and preventing dispersion of pollutants. Thermal inversions are usually most pronounced in valleys and low-lying areas and more prevalent where there is 1) a large temperature variation (25F and 30F degrees) between daytime high and nighttime low temperatures; 2) clear skies and calm winds at night. This allows the surface air to cool more rapidly than the surrounding air which traps or caps the surface air.

Figure 15: Topography and Mixing layer heights for Ulaanbaatar

30 UAPAU

case with Ulaanbaatar - an area ringed by mountains, becoming a pollution trap especially for

the low lying sources such as household stoves used for cooking and heating.

The effects of thermal inversion (as seen in Figure 8) are enhanced further in the winter

seasons because of lower geo-potential or mixing-layer heights. Figure 15 presents daily

average mixing heights for the period of January 2000 to April 2007, with winter season

(November to February) average of 300 m., which is extremely low, increasing the

concentrations at the ground level that many folds19.

Urban air pollution not only has immediate localized impacts on human health and well

being, but also contributes to regional and global air pollution. Emissions of greenhouse

gases (GHGs) resulting from the combustion of fossil fuels in the industrial and

transportation sectors contribute to global climate change and is estimated to grow

significantly in the urban areas of developing countries. Although the carbon foot print for

Mongolia is not comparable to that of the developed and developing countries, the potential

for co-benefits for reducing GHGs along with the harmful local air pollutants is large.

Air quality has become a prime concern and a priority problem for the city of Ulaanbaatar

and informed early action could avert this growing crisis. Amassing an accurate air pollution

management knowledge base is critical and often a constraint in Ulaanbaatar. Developing a

good knowledge base and feel for the critical pollutants and their sources, possible control

options, simple tools to analyze options in an integrated manner, conducting more detailed

studies and developing methodologies as required and eventually prioritizing a feasible set of

options that can be implemented is a necessary step and critically missing with the current

stakeholders group.

19 Mathematically, if we assume that all the pollutants are equally mixed between the ground level and the mixing layer, the volume occupied by this layer is smaller in the winter seasons, hence increasing the observed concentrations (mass/volume). Also, due to the increased coal consumption (mass) for heating, which is not as much in the summer and spring months, the concentrations observed in the winter season almost doubles that of other seasons.

31

3. Sources of Pollutants in UB

Pollutants can be classified as either primary or secondary. Primary pollutants are substances

directly produced by a process, such as ash from coal combustion in a power plant or the

carbon monoxide gas from a motor vehicle exhaust. Secondary pollutants are not emitted.

Rather, they form in the air when primary pollutants react or interact. An important example

of a secondary pollutant is ground level ozone - one of the many secondary pollutants that

make up photochemical smog. Note that some pollutants may be both primary and

secondary: that is, they are both emitted directly and formed from other primary pollutants.

With special focus on PM, secondary PM consists of significant portions of Sulfates and

Nitrates, which due to chemical transformation of SO2 and NOx emissions from various

sources. The mix of sources observed in Ulaanbaatar is closely linked with key factors such

as level of industrialization and motorization.

In Ulaanbaatar, major sources of air pollution remain combustion processes (e.g., burning of

fossil fuels for steam and power generation, heating, and household cooking, and diesel and

petroleum based vehicles) and various industrial processes. As in most of the developing

countries of Asia and Latin America, coal and oil remain the main source of energy in

Ulaanbaatar. Furthermore, pollution control measures are tightly linked with the economic

activities and the feasibility of technology transfer.

It is important to note that the main source of emissions in a city may not necessarily be the

most dominant source of pollution that people breathe. There is a long list of sources

32 UAPAU

besides the traditional sources that are most commonly referred to and some such as garbage

burning and fugitive/resuspended dust are not at all accounted for in the inventories at this

time. This chapter presents an overview of various sources in Ulaanbaatar contributing

significantly to the air pollution problems and has potential to substantially reduce their foot

print on air quality. List of sources analyzed in this study are

1. Cookstoves in Gers

2. Cookstoves in Kiosks and Food shops

3. Power plants

4. Heat only boilers

5. Vehicular traffic

6. Fugitive dust – Transport and Non-transport

7. Construction industry - Bricks

8. Garbage burning

9. Hospital waste burning

10. Livestock


Cookstoves in Gers

In Ulaanbaatar, if there is single largest source at the ground level for air pollutants, that

would be coal and fuel wood combustion in the cookstoves of Gers. Many homes are Gers,

the traditional Mongolian dwellings consisting of a wooden frame beneath several layers of

wool felt. Other homes in these districts are generally wood constructions of variable quality

and levels of insulation. In 2006, sixty percent of the 220,000 registered households in

Ulaanbaatar (presented in Figure 10) approximately 130,000 households live in the Ger

areas. Because of the increasing in-migration trends from neighboring provinces, there is no

clear estimate of total number of households.

General statistics reveal that the total number of Ger households is not a direct estimate of

number of stoves in use. In some wooden households, as seen in Figure 16, it is estimated to

have up to 2 stoves. The total number of stoves in the Ger areas is expected at least 30%

more than the reported number of households.

Traditionally, the residents of Ger areas use coal and fuel wood for their cooking and heating

purposes, which are sold in sacks along the roadside (see Figure 17). Per year, each

household is estimated to use 5 tons of raw coal and 3.0 m3 of fuel wood. Most of the raw

coal is supplied from the local coal mines with high ash content. One complaint by a Ger

resident is that the price per sack of coal and fuel wood has been constant, but the volume

of fuel per sack has gone down over the years ~ 30 kg two years ago vs. 25 kg per sack of

Figure 16: Ger areas and Cookstoves

34 UAPAU

coal now. So, on an average these residents tend to spend more for the same amount of fuel

than they used to.

Annual Fuel Use Cycle

0%

3%

6%

9%

12%

15%

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Most of the coal is used during the heating season, with fuel wood concentrated in the late

spring and summer months. Figure 17 also presents as estimated coal consumption cycle in a

year, with nearly 60 percent of the annual coal consumption coming in the months of

November to February.

Fuel mix used in the stoves very much depends on the local resources. In the Gers, there is

extensive use of conventional and unconventional fuels as resources, which adds to the

uncertainty of total pollutant levels from cookstoves usage. Figure 18 illustrates the use of

unconventional fuels such as rubber tubs and bricks dipped in coal tar. These are generally

Figure 17: Cookstoves and annual fuel usage cycle in Gers


available to the households and are in use for intermittent cooking and heating needs. There

is no clear estimate of the extent of usage of these materials.

Source: Dr. Sarantuya Myagmarjav, MNE

Another commonly used fuel, which is also available at lesser price, is the pressed coal. The

variety of pressed coal available to the public has been scrutinized for its quality – mainly

high percentage of ash content compared to raw coal. This is primarily because the glue used

to press the crushed coal to make briquette shaped pressed coal. Originally, these were sold

under the name of briquettes, but the distinction should be made between pressed coal and

briquette. The latter has higher calorific value and produces less ash. Currently, there are 23

manufacturing groups producing pressed coal, and the production levels have dropped over

the years, because of complaints on ash content.

Figure 18: Unconventional fuels used in Ger areas

36 UAPAU

The technology to make briquettes and charcoal briquettes out of saw dust is slowly building

momentum in Ulaanbaatar, with at least three private manufacturers supplying a limited

amount to select costumers. These briquettes are available at a higher price (details in the

later section) compared to raw coal. There is also limited consumption of Liquefied

Petroleum Gas (LPG) in the Gers, because of the price differences. Most of the LPG is

utilized in the housing complexes.

Figure 19: Pressed coal in Ulaanbaatar


Cookstoves in Kiosks

In Ulaanbaatar, kiosks and food shops are an unaccounted source of pollution. Especially in

the Ger areas, only source mentioned is the household level fuel consumption for cooking

and heating. Since the expansion of the Ger areas in the mid-90’s and increased in-migration

from neighboring districts, the number of food shops have more than doubled in the last

five years – from 1,100 in 2000 to 2,500 in year 2005. Most of these shops use smaller, if not

similar type of cookstoves for cooking and heating.

0500

10001500200025003000350040004500

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Markets Wholesale Centers Food Shops Clothes Shops Mixed Shops Kiosks

In 2000 = 3976

Clothes Shops

5%

Kiosks64%

Food Shops28%

Wholesale Centers

2%

Markets1%

In 2005 = 4015

Clothes Shops

8%

Kiosks27%

Food Shops62%

Wholesale Centers

2%

Markets1%


Figure 20: Kiosks and food shops in Ulaanbaatar

38 UAPAU

Food shops also use a mix of coal and fuel wood for heating. Recent surveys estimate fuel

consumption at the rate higher than that of households at 8 tons of coal per year, which is

completely unaccounted for in the annual emissions inventory.

Table 2: Survey results for Kiosks and Food Shops (May, 2007)

Type District Area, m2 (Stove) Working Hours Fuel Consumption

Coal Wood

Kiosk SB 9 (Standard) 9.00am-23pm 7 ton/yr 9kg/day

SB 12 (Standard) 24 hours 20 kg/day 10kg/day

SKH 4 (Standard) 6am-24pm 20 kg/day 10kg/day

SKH 9 (Standard) 9am-20pm 20 kg/day

SKH 7.5 (Standard) 7am-24pm 30 kg/day

Food Shop SB 56 (Standard with heating wall) 7.00am-23pm 30 kg/day

BG 42 (Water heating) 9am-22pm 8 ton/yr

CH 72 (Water heating) 9am-22pm 10 ton/yr

BG 9 (Water heating) 9am-22pm 5 ton/yr

Average 8.2 ton/yr


Power plants

CHP-3CHP-4

CHP-2

This source of air pollution has been well documented and is one of the major energy (raw

coal) consumers supplying heat and electricity to the city. Three largest coal-fired Combined

Heat and Power (CHP) Plants (shown in Figure 21) are an integral part of the energy sector

that comprise nearly all of the installed power capacity in the city and also are the main

source of district heating (DH) services – space heating and domestic hot water.

0

50,000

100,000

150,000

200,000

250,000

300,000

Jan-06

Feb

-06

Mar-06

Ap

r-06

May-06

Jun

-06

Jul-06

Au

g-06

Sep-06

Oct-06

Nov-06

Dec-06

Jan-07

Feb

-07

Mar-07

Ap

r-07

Baganuur Mine Shevo-Hue Mine Total tons of Coal per Month

Monthly Percentage of Coal Consumption

6.00%

6.50%

7.00%

7.50%

8.00%

8.50%

9.00%

9.50%

10.00%

Jan-06

Feb

-06

Mar-06

Ap

r-06

May-06

Jun

-06

Jul-06

Au

g-06

Sep-06

Oct-06

Nov-06

Dec-06

Source: Mr. D. Battsend, Deputy Director and Chief Engineer, Power Plant No.4

These three CHP’s cover 60 percent of the households in central Ulaanbaatar supplying 80%

of the energy needs. They consume ~3.5 millon tons of coal per year and emitted 33.3 ktons

of PM, 35.7 ktons of NOx and 19.8 ktons of SO2 in 2005. Figure 22 presents annual coal

Figure 21: Power plant locations in Ulaanbaatar

Figure 22: Annual coal consumption cycle at Power plant No.4

40 UAPAU

consumption cycle at power plant No. 4 for a total of 2.42 million tons of coal in 2006.

Power plant No.2 and No.3 consumed 181,800 and 888,000 tons of coal respectively in 2006

(Ministry of Fuel and Energy).

The pollution control technology in the power plants is operated at lower efficiencies. For

the power plants 2 & 3, wet scrubbers operate at an efficiency of 70 and 80 % catchments of

flyash and the power plant 4 operates an Electrostatic Precipitator (ESP) at 95% efficiency.

For reference, ESP’s operate at an efficiency of 99.95%. Similar to the household energy use,

the power plant operates at a higher load in the winter months compared to the spring and

summer months.

Besides the stack emissions from each of power plants, an important source unaccounted for

is the fly ash from the ponds. After the fly ash is removed from the scrubbers and ESP, it is

sent to the settling tanks, where the sedimented dust is collected and sent to the ash ponds.

For CHP-2 and CHP-3, these ash ponds are very close to the plant location and for CHP-4

it is 3 km to the west. These ash ponds are open and continuously subjected to wind erosion

in the dry season as seen in Figure 23. The re-suspended ash is normally fine size and

contributes substantially to the local air quality problems. The snaps in Figure 23 have a 30

minute time difference, and the plume is still visible and traveling towards to the city.

Figure 23: Fly ash from power plant ash ponds (May, 2007)


These stock piles are typically characterized by non-homogeneous surfaces with particles of

various sizes and very dependent on wind erosion to form emission puffs as shown in the

pictures. The emission rates are a function of wind speeds, above the threshold speeds to lift

the particles, particle size, and area exposed, which makes it a very intermittent source and a

hard one to calculate. This is a common sight in the spring and summer months along with

dust storms from deserts. Due to higher moisture content and snow cover, it doesn’t

account much to the pollution sources in the winter months.

42 UAPAU

Heat only boilers

In Ulaanbaatar, households not supplied with DH from the three power plants use

traditional heating stoves for cooking and heating. Smaller heat-only boiler (HOB)-supplied

systems are used in small town centers and are also used in isolated built-up areas, where

extension of DH is not feasible. Alternatives to DH are a major and growing source of

choking winter air pollution in Ulaanbaatar along with low lying heating sources in the Gers.

The 40% of the households living in peri-urban Ger areas use stoves. Use of HOBs in

potential DH territory has started to increase due to urban growth (e.g. connections to

existing installations and expansion of their capacity, and construction of new HOBs in the

city center) and due to problems with the ability of DH to extend its network to pockets of

residential and commercial growth.

Source: Dr. Oyun, JEMR Consulting Co. Ltd., Ulaanbaatar, Mongolia

Figure 24 presents location of known (350) HOBs in the city. A survey conducted by the

City Chief Engineer’s office reveals that this number is as high as 950 with at least 150

boilers of size 0.17 to 3.5 MW and 800 less than 100 kW or less. Of the large boilers, 80

percent are established using older Russian technology currently running at 40-50 percent

efficiency. And the smaller boilers are owned by individuals with possible newer

technologies.

Figure 24: Location of known HOBs in Ulaanbaatar


Vehicular traffic

In Ulaanbaatar, an estimated 80,00020 vehicles are in use in 2006. Rapid growth in the

number of motorized vehicles has overwhelmed city infrastructure. The total number of

vehicles here is not comparable to other capital cities in East Asia, but given the city

infrastructure limitations, this is becoming an increasingly congested problem for the

municipality. Because of limited highway and secondary street capacity, with a high fraction

of car ownership (see Figure 25), city is now experiencing worse traffic congestion and

related pollution. In the last decade, the percent of passenger vehicles (cars, vans, jeeps, etc.)

have increased from ~25 percent to ~65 percent in 2005.

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

192519301933193619571960196619701975198019851990199119921993199419951996199719981999200020012002200320042005

0

50

100

150

200

250

300

350

400

450Total Number of VehiclesImproved Road, km

Vehicular Population in Ulaanbaatar

0%

20%

40%

60%

80%

100%

192519301933193619571960196619701975198019851990199119921993199419951996199719981999200020012002200320042005

Pass. Vehicles Trucks Buses Tank Cars Special Vehicles

0

10000

20000

30000

40000

50000

60000

70000

80000

1998 1999 2000 2001 2002 2003 2004 2005 2006

> 11

7 to 10

4 to 6

<3

Source: Ulaanbaatar Statistical Year Book, 2006, and Dr. Sereether, Department of Transport, Ulaanbaatar

Vehicle ownership is considered a sign of social status in East Asia. Unfortunately, once a

household becomes “motorized,” it is extremely difficult to get its members to use non-

20 Local sources report this number to be as high as 150,000 with aged vehicles still in-use. http://www.montsame.mn/newsdetail.php?nid=112665

Figure 25: Vehicular growth vs. Improved road and Average age

44 UAPAU

motorized modes or public transport, no matter how attractive they are made. There is also

an accompanying degradation of the urban quality of life through conversion of open space

to accommodate auto movement and storage (parking, increases in noise and run-off, etc).

The average age of the fleet, especially for the passenger vehicles has improved, but for the

rest of the fleet, it averages above 10 years.

Vehicular Population in Ulaanbaatar

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

1980

1985

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

OtherPublic TransportPrivate Vehicles

Public Transport in Ulaanbaatar

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Bus-State Bus-Private Bus-Trolley Bus-Micro Taxi


The growth in the public transport sector is at the same rate as passenger vehicles, but the

type of vehicles in use is different. The effects of the trend to increased motorization of all

forms are longer travel times for surface public transport (i.e. bus) which, in turn, induces

more auto and taxi use, poor traffic safety, the economic inefficiency of increased fuel use,

etc. In the last five years, micro-buses (see Figure 26), which can operate at faster speeds

Figure 26: Percent of transport modes - Total and Public


compared to regular buses have increased along with taxis21. These micro-buses operate at

full capacity, take passengers for short distance (within in the city) and long distance (to the

neighboring districts) and charge approximately double the buses.

Table 3: Average vehicle kilometers traveled in Ulaanbaatar

Type of Vehicle Average Vehicle KM Traveled Car/Van/Jeep 40 Bus (regular) 200 Bus (micro) 275 Taxi 140 Truck 150 Source: City Transport Department of Ulaanbaatar

Table 3 present average vehicle kilometers traveled in 2005 by buses and taxies, and

according to the city transport department. Figure 27 presents the share of public transport

routes by various modes. It is clear that there is an increased demand for the smaller and

efficient transport modes, such as micro-bus service. This is also an indicator for the reduced

speeds on the roads making it harder for regular buses to operate at normal speeds and a

steady decline in their numbers. The summer camp trips are mostly out of town in the

summer time.

0

20

40

60

80

100

120

140

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Bus-State Bus-Private Bus-Trolley Bus-Micro Summer Camps


21 The number of taxis listed here is of registered vehicles. In the city, there is also an unofficial taxi culture, which is very prevalent and easy to access at any time of the day. This increases the uncertainty in the estimates of vehicle kilometers traveled and loaded trips.

Figure 27: Number of public transport routes by modes

46 UAPAU

Most of the passenger vehicles are gasoline operated, except for taxis, some of which are in

the process of getting converted to duel modes with LPG. Leaded gasoline from Russia

makes up the majority of supply with a small amount imported from China. There is no

facility in Ulaanbaatar for testing the level of lead in gasoline, which is determined at the

pumping stations in Russia and China. A study conducted in 2006 measured lead in child

blood at 16.5 mkg/dl and this number is expected to even be higher. An estimated 80% of

vehicles do not meet fuel consumption or emission standards22.

Besides the road transport, other significant sources include Railway stations and airports.

Railway station is Ulaanbaatar is estimated to burn 2000 tons of raw coal during the winter

season. For airports, although the source is far from the city limits to west, it is a significant

source of emissions of VOCs, CO, NOx, and (to a limited extent) PM. The aircraft emissions

inventory depends on annual number of landing and takeoffs, taxing times, takeoff and

landing weights, etc. This study includes a simplified estimate of these emissions because of

limited information on these parameters.

22 Environmental Challenges of Urban Development, Mongolia Environment Monitor 2004, World Bank


Fugitive dust (Transport)

One of the most important sources of fugitive dust emissions at congested areas is re-

suspension of already deposited dust on streets due to traffic. Fugitive dust is a relatively

new term for an old problem. Simply put, fugitive dust is a type of non-point source air

pollution - small airborne particles that do not originate from a specific point such as a

gravel quarry or grain mill. Significant sources include unpaved roads, agricultural cropland

and construction sites. In Ulaanbaatar, most of the Ger areas are unpaved and in the dry

spring and summer months, the problem of fugitive dust is very persistent and a very

common sight (see Figure 28).

Dust emission from paved roads is also a growing problem in Ulaanbaatar, because of high

“silt loading” present on the road surface as well as the average weight of vehicles traveling

Figure 28: Vehicular fugitive dust examples in Ulaanbaatar

48 UAPAU

the road. The term silt loading refers to the mass of silt-size material (equal to or less than

75 µm in physical diameter per unit area of the travel surface. The total road surface dust

loading consists of loose material that can be collected by broom sweeping and vacuuming

of the traveled portion of the paved road, which varies between 100-3000 gm/sq.m in

Ulaanbaatar.

Fugitive dust is included in the larger fraction of PM10 and contributes significantly in dry

and arid conditions. Besides causing additional cleaning of homes and vehicles, fugitive dust

can cause low visibility on unpaved roads. Dust particles are abrasive to mechanical

equipment and damaging to electronic equipment such as computers. Although generally not

toxic, fugitive dust can cause health problems, alone or in combination with other air

pollutants. For example, aged loaded trucks as shown in Figure 29 are a common sight in the

Ger areas.

Figure 29: Trucks and Loads


Fugitive dust (Non-transport)

Construction operations are significant source of dust emissions that may have a substantial

temporary impact on local air quality. This emission source category includes both residential

and non-residential construction as well as road construction. Dust emissions during the

construction of buildings or roads are associated with land clearing, drilling and blasting,

ground excavation, and cut and fill operations (i.e., earth moving). Dust emissions can vary

substantially from day to day, depending on the level of activity, the specific operations, and

the prevailing meteorological conditions. A significant amount of the dust emissions result

from construction vehicle traffic over temporary roads at construction sites.

Note that it is not always easy to distinguish between the sources of the pollution. Above

pictures are for illustrative purpose only. Emissions inventory estimation methods do not

accurately account for fugitive dust from unpaved roads. Emission factors are estimated

Figure 30: Non-transport fugitive dust

50 UAPAU

based on structure type and duration of construction. For example, for single family houses,

construction duration is assumed to be 6 months; for apartment buildings, 12-month

construction duration is assumed. The emissions factors vary from approximately 0.011

tons PM10/acre-month to 0.11 tons PM10/acre-month. Of the re-suspended dust, on an

average 20 percent is attributed to the PM2.5 fraction. In Ulaanbaatar, the construction sites

for housing complexes is a common site and are adding to the growing fugitive dust sources.


Industry - Brick

The construction industry is a major source of pollution, more water pollution incidents than

any other industry because of runoffs, and regular noise complaints. Although construction

activities also pollute the soil, the main areas of concern are: air, water and noise pollution.

All construction sites generate high levels of dust (typically from concrete, cement, wood,

stone, silica) as seen in the previous section and this can carry for large distances over a long

period of time. Pre-construction activities include brick and cement industry, which are on

very high demand in Ulaanbaatar. The contribution of these two industries to air pollution

include: land clearing for sand and clay, operation of diesel engines on site, combustion of

fuel for brick burning, and transport of the end product to various sections of the city.

Figure 31: Mongol Ceramic brick factory in Ulaanbaatar

52 UAPAU

With the current housing expansion plans in Ulaanbaatar, there will be an increased demand

for bricks and cement in the coming years. At present 100 percent of the brick demand is

met locally by 20+ large factories and few small factories. Some question the quality of the

bricks, as some of them are being manufactured in a hurry. Where as for cement, 60 percent

is produced locally and 40 percent is imported from China.

As an example, Figure 31 presents pictures of Mongol ceramic brick factory in Ulaanbaatar,

which is one of the biggest brick suppliers in town. Talking to the chief engineer, reveals that

they are currently able to reach the consumer target, but coming year or two, they will fall

short of the demand. Current plant capacity is 12-15 million bricks a year. They operate two

kilns with 48 and 28 burning chambers and consume an estimated 50 tons of coal per week

over a 6-8 month working period. Most of the coal is supplied from Baganuur coal mine and

they operate a Chinese boiler for kilns. This plant also operates 25 pat-pats (shown in Figure

31) which consume 5 liters of diesel every 6 hours. Because of the heavy loads that these pat-

pats carry from the manufacturing site to the kilns, they have a life time of less than 3 years

and produce a lot of black smoke. They also operate 10 units of heavy duty vehicles for

transport of sand and bricks.

Current total demand for bricks stands at 100 million a year. Secondary source of pollution

from these sites include fly ash from the combustion of coal, fugitive dust on-site, and the

open pit sand mining areas which are 10 km from the city limits. In the current emissions

inventory available, this sector of growing brick and cement industry is missing.


Garbage burning

'Backyard burning' of common household trash and garbage emits substantial amount of

pollutants and toxins into the air and a source completely unaccounted for in the emission

inventories. Because of the smoke, air pollution, and odor complaints of backyard burning,

many local governments prohibit residential trash burning, but continue unabated. Many of

these pollutants become widely dispersed and persist for years in the environment,

contaminate the food chain, and accumulate to dangerous levels in our bodies. One of the

immediate dangers of backyard burning, especially near the households, is the indoor air

pollution. These burning problems are also persistent at the landfill sites.

Generation555 ton/day

(100 %)

Self Disposal92 ton/day

(16.6%)

Public Area Cleaning Waste

10 ton/day(1.8%)

Waste from Business Activities

34 ton/day(6.1%)

Household Waste511 ton/day

(92.1 %) Illegal Dumping121 ton/day

(21.6%)

Final Disposal325 ton/day

(58.6%)

Final Recycling18 ton/day

(3.2%)Period: 2005 Winter Season

Generation248 ton/day

(100 %)

Self Disposal23 ton/day

(9.2%)

Illegal Dumping50 ton/day

(20.1%)

Final Disposal156 ton/day

(63.5%)

Final Recycling18 ton/day

(7.2%)Period: 2005 Summer Season

Public Area Cleaning Waste

17 ton/day(6.9%)

Waste from Business Activities

44 ton/day(17.8%)

Household Waste187 ton/day

(75.3 %)

0

200

400

600

800

1000

1200

1400

1600

19471952195719601965196619671968196919701971197219731974197519761977197819791980198119921993199419951996199719981999200020012002200320042005

Garbage Conveyed, thous.m3

According to a survey conducted by JICA in 2005, in Ulaanbaatar, an estimated 555

tons/day in the winter and 248 tons/day of garbage in the summer season – half that of

Figure 32: Waste generation and disposal shares in 2005

54 UAPAU

winter collection – is produced. Households produce most of the waste in the winter season,

more than 90 percent (511 tons/day) compared to 75 percent (187 tons/day) in the summer

months. Vast difference is primarily due to the climatic conditions. Of which 17 percent and

10 percent of is self disposed in the respective seasons and nearly 20 percent in each season

is illegally dumped. In addition to burning garbage, residents are also littering and many parts

of the Ger areas have been turned into makeshift landfill sites. It is assumed that once in a

week, all the illegally dumped garbage is put to fire in the Ger areas. As estimated 1000+

makeshift landfills sites exist in the Ger areas of Ulaanbaatar. Figure 32 also illustrates the

collapse of garbage-collection services that led to an increase in the amount of garbage being

burnt in the Ger areas.


Hospital Waste Burning

Traditionally, city landfills do not except medical waste from the hospitals and hospitals are

required to install incinerators that burn trash and infectious medical waste. In Ulaanbaatar,

this is a very small source of air pollution compared to the rest discussed above. About 35

hospitals practice bio-hazard waste burning, but do not use regulated incinerators. Figure 33

presents a common practice in Ulaanbaatar – use of a common cook stove at high

temperatures, contributing to the air pollution sources.

Currently, very little information is available on this source.

Figure 33: Medical waste burning practices

56 UAPAU

Livestock

The intensity of animal production and competitive economic factors have sometimes

resulted in poor indoor air quality and emission of air pollutants such as odorous and

hazardous gases, dusts, global atmospheric constituents (e.g., GHGs), and microbiological

pollutants such as bacteria, fungi and toxins into the outdoor environment. Direct emissions

from livestock include CO2 from the respiratory process and methane as part of digestive

process. Besides those two, animal manure is known to emit nitro oxides and ammonia

depending on the way they are produced (solid or liquid) and managed (collection, storage,

and spreading). Figure 34 presents trend in livestock statistics in Ulaanbaatar, with a

population of ~350,000 in 2005. As per particulates are concerned, ammonia is one of the

binding pollutants in the formation of secondary sulfates and nitrates.

0.050.0

100.0150.0200.0250.0300.0350.0400.0450.0

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Camel Horse Cattle Sheep Goat

0%

20%

40%

60%

80%

100%

19801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005

Camel Horse Cattle Sheep Goat


Figure 34: Livestock population in Ulaanbaatar (in thousands)

57

4. Emissions Inventory for Primary Pollutants

The emissions inventory is essentially a planning tool for air pollution abatement measures.

Emission estimates are also a requirement to track changes in response to new developments

and policy measures for air pollution abatement. In Ulaanbaatar, up to date and complete

emission inventory is lacking for various reasons. While it is important to be able to monitor

compliance levels for industries, vehicles, and other sources, it is also important to keep

track of the urban area’s input to ambient pollutant levels. An accurate inventory can be used

for evaluating and comparing the impacts of various policy options on future emission

levels, thus facilitating selecting the most effective control option. Otherwise known as

“Bottom-up” analysis is one of the fields that require serious inputs.

Establishing a Baseline

As with any action planning process, it is important to have a well-defined data baseline

upon which to base the “Action Plan” and against which its success can be measured. In this

context, the most important information will relate directly to air quality, and will include the

following:

• Current air quality status, identified by pollutant;

• Likely future trends, and known developments, over the next five to ten years, under

a business as usual scenario;

• The sources of air pollution and their relative contribution to air quality (source

apportionment);

58 UAPAU

• Annual, weekly and diurnal variations for both emissions and air quality;

• The specific locations affected by poor and impoverished air quality;

• The extent to which the public, and particular sensitive groups within it, are exposed

to predicted air quality objective exceedances.

Most of this information should arise from the air quality review and assessment process.

However, in order to conduct a full scale analysis of pollution sources, there are a number of

problems developing countries have to overcome. These include:

• Existing methodologies usually require significant data, and are “super-specialized,”

expensive, and inflexible within the context of developing countries

• Developing country environmental agencies are often young, with inadequate skills,

interaction, and capacity

• Institutional problems are very common in developing countries (For example,

public, bureaucratic and political interest in environment quality is oftentimes in its

infancy and with competing demands for scarce financial resources; decision-making

is often ad-hoc and crisis-driven and there is often little time to develop a suite of

high-end models for a bewildering array of options.)

• Oftentimes detailed studies are undertaken on a few parameters without

understanding how important these parameters are for the broader problem

• Databases are often inaccessible and not of the required quality and consistency

Emissions Inventory 59

Methodology

Analysis focused primarily on the particulates – primary and secondary (SO2 and NOx)

emissions. The data collection process is on-going and the methods employed for this

analysis will be updated as when newer information is made available by the participating

stakeholders. Methodology employed in this study is simple.

For industrial or household fuel consumption,

Emissions = Activity * Emission Factor

Where, Emissions is tons of pollutant emitted per year; Activity is the amount of fuel used

(e.g., tons of coal burnt per year); and Emission Factor is tons of pollutant emitted per ton

of fuel burnt

For industrial or household sources with controls,

Emissions = Activity * Emission Factor * (1 – Efficiency)

Where, Efficiency is the efficiency of the control technology, such as scrubbers and ESP in

the power plants.

For example for particulate emissions from power plants:

Emissions = Coal use * Ash Content * (1-Ash Retention)

For power plants, scrubbers operate at 80% in wet scrubbers and 95 % in the ESP23. This

gives total TSP emissions. The PM10/TSP ratio of 0.65, 0.5, and 0.6 and PM2.5/PM10 ratio of

0.4, 0.6, and 0.6 were applied for power plants, Ger stoves, and HoBs, respectively, to

calculate the final emission rates of individual fractions exiting at the top of the chimney.

These are based on general observations from various sources listed in this section.

Similarly, PM emissions were calculated for coal use in stoves and HoBs, and other coal

applications. 80% retention of ash is assumed in the stoves and boilers.

For sulfur, similar equations are,

Emissions = coal use * sulfur content

23 These numbers were collected during discussion with Mr. D. Battsend, Chief Engineer at CHP-4

60 UAPAU

Since no sulfur controls measures are in place, it is assumed that all of the sulfur is emitted in

the form of SO2. 1 % sulfur content by weight is assumed for coal used.

For NOx, an emission factor of 750 kg per TJ (1012 joules) is used. This number is obtained

as an average from a variety of sources such as SEI Emissions Inventory study24, GAINS25,

US EPA26. Calorific value of coal used is set at 2700 kcal

Some of these assumptions can be avoided by regular monitoring of emission rates at the

power plants and boilers in use in Ulaanbaatar.

For vehicular sources, similar equation would look like

Emissions = vehicles * VKT * Emission Factor

Where, Emissions is tons of pollutant emitted per year; Vehicles is the number of vehicles

in-use; Emission Factor is grams of pollutant emitted per km and VKT is the vehicle

kilometers traveled per year.

Average VKT, presented in Table 3, were obtained from Dr. Sereether, Department of

Transport. One of the major limitations in this study is the availability of the local specific

emission factors for vehicles. For this purpose, emission factors were borrowed from

situations with similar technology and controls in other developing countries, especially the

older vehicles – given the mix of age of vehicles in Ulaanbaatar. For cars and SUVs

emissions rates are averaged between vehicles of 5 years age and new ones. For buses and

trucks, emission factors of vehicles older than 8 years are assumed. Main sources of

information on emission factors are HEAT27, SEI emission inventory, and US EPA (old

vehicles). The numbers obtained from these databases for old vehicles were adjusted for

some wear and tear, assuming emission factor deteriorating rate of 3 %. Emission factors

used are tabulated in the excel files for review.

24 http://www.sei.se/index.php?section=atmospheric&page=projdesc&projdescpage=99928 25 GAINS - http://www.iiasa.ac.at/rains/gains/index.html 26 US EPA AP-42 - http://www.epa.gov/ttn/chief/ap42/ 27 Harmonized Emissions Analysis Tool - www.iclei.org/heat


The emissions from non-traditional sources, such as fugitive dust from transport and non-

transport activities are calculated using empirical equations, based on US EPA AP-42

manual. These empirical equations are developed for applications in US cities, but are useful

in providing an estimated guidance where no such studies are done, like here in US. For obvious

reasons, these results come with some level of uncertainty in the results. As an example, the

PM10 fugitive dust from paved roads is calculated using an equation as follows

)4NP-(1*C]-))

3W(*)

2sL(*[4.6=E 1.50.65

Where E = fugitive dust emissions factor in gm/VKT; sL is the silt loading on the roads in

gm/sq.m; W is the average weight of vehicles on road in tons; C is a wear and tear factor is

units of E; P is the number of precipitation days; and N is the total number of days for

calculation. This is an empirical equation developed for conditions suitable for US roads, and

used here as a first order approximation for Ulaanbaatar till similar studies can be conducted

here. Parameters were calculated based on vehicular information received from the transport

department.

For Ulaanbaatar, a silt loading of 300 gm/sq.m is assumed, which is typical for dry and dust

areas. These emissions are calculated only for the spring and summer months. Average

weight of the vehicle is set at 10 tons. This is a VKT averaged weight of all the vehicles on

road. Similar methodologies are applied for unpaved roads, and construction dust.

Assumptions

A series of assumptions were made while estimating emissions. In the excel sheet, all these

assumptions are entered in interchangeable fashion. Assumptions are,

• For all the years, 30 percent uncertainty in the household to stoves in use ratio.

• Gers are expected to grow at the current 5 percent until 2010 and 3 percent through

2020. This is not taking into consideration possible demolishing of Gers to construct

housing complexes through 2020, at which time all the stoves are expected to be

LPG.

62 UAPAU

• From household combustion analysis, coal emissions are distributed more over the

winter months and fuel wood over spring and summer months as per in Figure 17.

• Similarly for power plant emissions, annual cycle shown in Figure 22 is followed.

• Emissions from HOB’s are distributed over winter months only.

• Vehicles (especially passenger and taxi) are assumed grow at the current rate of 10

percent through 2015, at which time growth is expected to overlap with vehicle

retirements and better policy measures

• Paved and Unpaved road dust is distributed over the spring and summer months.

• Wind erosion over select spots on the map – locations of ash ponds, sand mines,

brick kilns with open pits, is calculated during the modeling exercise (next chapter),

which depends on the threshold wind speeds.

• Hospital waste rates are assumed based on local discussions.

• Brick kilns operate for only 6-8 months starting March.

• For HOB’s a growth rate of 10 percent till 2010 and 5 percent through 2020 is

assumed. After 2010, it is assumed that some of the Ger sections and housing areas

will have access to DH supply from the new PP No.5 which will be commissioned in

the east side.

• Waste generation is expected to grow at the current population rate of 4 percent.

Emissions Inventory

Tables 4-7 and Figures 35-38 present estimated emissions inventory for Ulaanbaatar under

business as usual scenario with expected growth rates in various sectors.

Following tables and figures are Author’s calculations.


Table 4: Estimated emissions inventory for Ulaanbaatar in 2006 (in tons)

Category PM10 PM2.5 SO2 NOx

Household stoves in Gers 22,281 13,369 4,286 7,150

Kiosks and Food shops 1,439 863 240 361

Power plants 32,370 12,948 13,840 29,847

Heat only boilers 15,563 6,225 3,388 5,099

Vehicles 2,368 1,184 1,354 10,372

Fugitive dust – paved roads 2,138 535

Fugitive dust – unpaved roads 7,056 1,411

Brick industry 2,844 1,138 219 329

Waste – open burning 4,073 3,055

Waste – hospitals 360 180

Unknown 8,000 2,500

Total 98,492 43,407 23,326 53,158

HH Stoves23%

HoB16%

Veh2%

UPRD7%

Brick3%

OB4%

HWB0%

UNK8%

Other13%

PP34%

Kiosks1%

PRD2%

Source: Authors calculations

28 Total is the sum of both particulate bins - coarse (between sizes of 10 to 2.5 µm) and fine (less than 2.5 µm)

Figure 35: Estimated percentage contributions to total28 PM10 emissions in 2006

64 UAPAU




Kiosks and Food shops 2,261 1,357 377 567

Power plants 41,925 16,770 20,000 43,131


Vehicles 3,174 1,587 1,837 13,964



Brick industry 4,164 1,665 320 482



Unknown 10,000 3,500

Total 126,579 55,579 32,123 73,429

HH Stoves21%

HoB15%

Veh3%

UPRD9%

Brick3% OB

4%

HWB0%

UNK8%

Other14%

PP33% Kiosks

2%

PRD2%


Figure 36: Estimated percentage contributions to total PM10 emissions in 2010






Power plants 46,800 18,720 24,000 51,758


Vehicles 4,303 2,151 2,501 18,824



Brick industry 6,705 2,682 516 776



Unknown 12,000 4,000

Total 152,282 66,501 39,127 90,572

HH Stoves21%

HoB16%

Veh3%

UPRD9%

Brick4%

OB4%

UNK8%

Other15%

PP31%

Kiosks2%

PRD2%

HWB0%



66 UAPAU





Power plants 52,650 21,060 28,800 62,109


Vehicles 4,931 2,466 2,894 21,450

Fugitive dust – paved roads 4,508 1,127


Brick industry 8,558 3,423 658 991



Unknown 12,000 5,000

Total 176,276 78,108 46,769 107,337

HH Stoves20%

HoB18%

Veh3%

UPRD8%

Brick5%

OB5%

HWB0%

UNK7%

Other17%

PP29%

Kiosks2%

PRD3%




-

30,000

60,000

90,000

120,000

150,000

180,000

210,000

240,000

PM10 PM2.5 SO2 NOx

2006201020152020

Under the business as usual scenario, total PM10 emissions are estimated to increase ~80

percent from 98 ktons in 2006 to 176 ktons in 2020. Note that PM2.5 (fine fraction) is a

subset of total PM10 emissions presented in Figure 39. This is only the primary PM

emissions, and secondary contribution of SO2 and NOx emissions adds to the total tally and

air quality. With no controls, SO2 and NOx emissions are expected to double the current

2006 levels. NOx emission increase is mainly driven by the high vehicular growth and aged

fleet on roads.

By far, three main sources that dominate are power plants, household stoves, and heat only

boilers. Some of these heat only boilers are industry based, but there is little information

available on the type. The AQMB is in the process of inventorizing all the boilers in the city,

which will help update the emission inventory at a later stage. An unaccounted source is

fugitive road dust from the paved and unpaved roads in the city. For the calculations

purpose, it is assumed that 40-50 percent of the vehicle kilometers traveled occur on the

unpaved roads of Ger areas resulting in ~10 percent of road dust emissions.

Figure 39: Estimated annual total emissions (tons)

68 UAPAU

Starting 2010, a new power plant to the east of the city is added to the inventory. A future

analytical assessment could include change in the heating loads because of increasing average

temperatures (see Figure 2).

Figure 40 presents percent contributions to the coarse and fine modes of PM10 emissions,

which have distinct dispersion characteristics in the atmosphere with a longer resident time

for fine particulates which travel farther distances than the coarse mode. Power, stoves, and

heating sector dominate most of the inventory for ~60 to 70 percent.

It is important to note that a number of sources are still missing from this inventory. One of

the incomplete sources is process industries – cement, iron and steel furnaces, textiles,

leather, etc., all of which use considerable amount of coal for various purposes besides

heating. In 2006, estimated PM10 emissions from brick industry accounted for 3-4 percent

total. With rest of the process industries includes, this is expected to be between 10 -15

percent. Other small sources include agricultural burning, livestock, and natural sources such

as dust storms and forest fires, which can be large scale sporadic events and hard to estimate

on a yearly basis.


COARSE (10 to 2.5 µm) FINE (Less than 2.5 µm)

2006

HH Stoves16%

HoB17%

Veh2%

UPRD10% Brick

3%

OB2%

HWB0%

UNK10%

Other11%

PRD3%

Kiosks1%PP

36% HH Stoves31%

HoB14%

Veh3%

UPRD3%

Brick3%

OB7%

HWB0%

UNK6%

Other16%

PP30%

Kiosks2%

PRD1%

2010

HH Stoves15%

HoB17%

Veh2%

UPRD12% Brick

4%

OB2%

HWB0%

UNK9%

Other11%

PP36%

Kiosks1%

PRD2%

HH Stoves29%

HoB14%

Veh3%

UPRD4%

Brick3%

OB7%

HWB0%

Other16%

UNK6%

PP31%

Kiosks2%

PRD1%

2015

HH Stoves15%

HoB17%

Veh3%

UPRD13% Brick

5%

OB2%

HWB0%

UNK9%

Other13%

PRD2%

Kiosks1%PP

33% HH Stoves29%

HoB15%

Veh3%

Brick4%

OB7%

HWB0%

UNK6%

Other18%

UPRD4%

PRD1%

Kiosks3%

PP28%

2020

HH Stoves14%

HoB19%

Veh3%

UPRD12% Brick

5%

OB2%

HWB0%

UNK7%

Other15%

PP33%

Kiosks2%

PRD3%

HH Stoves28%

HoB16%

Veh3%

Brick4%

OB8%

HWB0%

UNK6%

Other20%

UPRD4%

PP27%

Kiosks3%

PRD1%


Figure 40: Estimated percentage contributions to coarse and fine mode emissions

70 UAPAU

Recommendations

This report has described the methods used to develop an emissions inventory based on

available data and comes with a number of uncertainties which need to be addressed in the

future studies. A number of recommendations have been made for improvements to the

quality. These are listed below in order of priority.

1. Domestic fuel use

Inclusion of updated fuel consumption data, preferably at a higher spatial

resolution than is currently available (xopoos)

An update of the households by geological location of households would

improve the mapping of emissions

An updated survey of domestic heating and cooking patterns

2. Point sources – power plants and HoBs:

Access to annual fuel consumption and emissions reports data

Reporting of fuel use by fuel type by installation in the Environment

Agencies Pollution Inventory

Consolidate emissions data for Local Authority regulated processes. This

would also assist in the air pollution modeling.

3. Industrial and commercial area sources:

Better data on fuel specific fuel consumption in the commercial and public

services sectors would allow more accurate fuel intensity calculations for

various sectors.

Improved spatially resolved data on boiler locations, type of boiler, fuel

efficiency could also be made available to improve the emission inventory

and intervention assessment.

4. Road transport:

Development of local specific emission factors.

Additional traffic census data along the major corridors will help analyze the

miss of vehicles in in-use during the day and would significantly improve

the emissions distribution schemes.


Census of vehicular ages by type will improve the emissions calculation

procedures by varying emission factors by age, retirement rates, and

registration of new vehicles.

Vehicle idling periods on the roads because of congestion will improve

analysis of interventions such as promotion of public transport and

possible fuel savings.

Measurements of silt loading on the roads and composition of fine and

coarse fraction of road dust.

5. Railways:

Census of mix of railway engines and fuel consumption while idling at the

stations, etc.

6. Agriculture:

Update of livestock and poultry distributions used for mapping.

7. Airports:

Update of the take off and landing patterns.

8. Landfills:

Better data on the locations and sizes of landfill sites – active, closed,

unofficial.

9. Accidental fires:

At the national level, the land cover data could be augmented using regional

fire statistics to improve the distribution of emissions.

73

5. Air Pollution Analysis

Three important steps in this analysis are

1. Emissions mapping

2. Dispersion modeling

3. Impacts assessments – Health outcomes

One barrier is the large amount of uncertainty inherent in these analyses. It is important to

note to keep these limitations in mind, while we use the results accordingly. Areas of

uncertainty include mapping systems, air-quality modeling, population demographics and

heterogeneity, health and exposure baselines, validity and precision of concentration-

response functions and use of alternative models (linear, nonlinear), estimation of these

functions as relative effects, relative toxicity of mixture components, and applicability of

these functions to target populations of regulatory concern. These uncertainties are rooted in

incomplete scientific knowledge. When benefits are estimated for future target populations,

please note that these are cumulative and subjective assessments. Many of them can be

reduced by further research, but on the whole, they are likely to remain high.

74 UAPAU

Mapping of Emissions

Geographical distribution of emissions to the Ulaanbaatar city map was conducted based on

map presented in Figure 41.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

Main city center is divided into a 30 x 20 grid at a resolution of 0.9 min, ~1 km.

Approximate placement of the grid over the city map is presented in Figure 41.

• The power plant emissions are allocated to the source location.

• An inventory of over 350 HoBs exists with location information. Rest of the small-

scale boilers are distributed based on density in the Ger areas – highest close to the

center and lowest to the north of the city.

Figure 41: Ulaanbaatar city map

Air Pollution Analysis 75

• Of the vehicular emissions, 50 percent is assumed to occur in the central urban area

and 50 percent in the Ger areas, more concentrated towards the center

• Paved road dust is distributed over the central urban parts of city and unpaved road

dust to the Ger areas.

• Garbage burning of illegally disposed waste is distributed to the Ger area

distribution.

• Emissions from stoves and power plants are distributed over the months as

presented in Figures

Note that the distribution to the grids is subjective, because of lack of real geographical

information of sources. Gridding process included geographical maps from the city council

– Ger areas and road maps, and industrial location information from local experts – by

circling areas on the map and estimating percentage of sectors in various sections of the city.

As the detailed information on sources and industries is made available – with the on-going

inventorization of boilers by AQMB, this methodology can be improved in the future

assessments. At this point, goal was to get an approximate spatial pattern on emissions on

ground.

76 UAPAU

Dispersion Modeling

For this exercise, we utilized ATMOS dispersion model29. Meteorological data was

obtained from NCEP Reanalysis fields (also explained in the manual) for the grid

containing Ulaanbaatar. Wind rose functions for this data are presented in Figure 42. All

the simulations were conducted using meteorological data for year 2006 presented in the

figure below.

Winter (DJF) Spring (MAM)

Summer (JJA) Fall (SON)

For the modeling purposes, each of the sources is simulated separatly and added to the

totals and this process is repeated for all the scenarios presented in the report. Figure 43

presents modeled annual average total PM10 concentrations for year 2006. This includes the 29 Details of the model and a manual are available here http://www.cgrer.uiowa.edu/ATMOS/atmos-urbat-linux/

Figure 42: Wind Rose functions for city of Ulaanbaatar for 2006


primary PM emissions and secondary contributions from SO2 and NOx emissions. For the

formation of secondary concentrations, a simplified chemical conversion is assumed,

detailed on the chemical process are presented in the model manual. Lines in black represent

major road networks in Ulaanbaatar.

106.7 106.75 106.8 106.85 106.9 106.95 107 107.0547.8

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Clearly, the total PM10 concentrations exceed the standards set by WHO for health

guidelines and Mongolian standard for 24 hours of 150 µg/m3. NOTE that these are annual

average concentrations calculated using estimated emission inventory and meteorology from

a global dataset. So, uncertainties are high and a lot of room for improvement. This still

needs to be validated with local measurements, preferably temporal, to make full use of the

results. There is only one nephlometer in operation since March, 2007, for validation, which

is located in the center of the city. During a visit in May, 2007, equipment measured 170

µg/m3. Assuming that winter concentrations are at least double that of the summer months,

an annual average concentration of 250 µg/m3 over the center of the city seems reasonable.

For the domain circled in the figure, modeled annual average is 200 µg/m3, with winter

maxima of 265 µg/m3 (November to March) and summer minimum of 125 µg/m3 (May to

August).

Figure 43: Modeled annual average PM10 concentrations in 2006 (µg/m3)

78 UAPAU

Given the differences in the dispersion characteristics, the particulates are binned and

modeled separately. Figure 44 presents contributions from the coarse and fine modes.

Because of smaller size and longer resident times in air, fine mode tends to travel farther and

contribute to regions away from the sources. For the domain circled in Figure 43, coarse

mode averages 45% and fine mode 55%. Secondary components (sulfates and nitrates) are

generally less than 2.5 µm in size and are included in the fine mode. Of the total PM10,

secondary pollution averages 15%.

Coarse Mode Fine Mode (incl. Sec)

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Most of the year, winds are Northwesterly, with the pollution moving West of East. Seasonal

average total PM10 concentrations for year 2006 are presented in Figure 45. The difference

between the seasons is very prominent. For winter months, wind speeds are generally low,

westerly direction dominating for most of the season, which pushes emissions from Gers in

the West and power plant emissions in the south towards the city center. It is also important

Figure 44: Modeled percentage of modes in annual PM10 concentrations in 2006


to note that the coal consumption in the winter months is higher than the spring and

summer months. For household stoves, it is approximately 7:1 ratio for winter to summer

months, see Figure 17. Same is true for the power plants, which operate at a higher load in

the winter months and the heat only boilers operating mostly in the winter months.

Winter (DJF) Spring (MAM)

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For summer months, wind rose is more even with faster winds, which is scattering most of

the emissions out of the city limits. Never the less, concentrations on an average range are

over 100 µg/m3 through out the year, with source contributions changing significantly. In

the summer and spring months, the paved and unpaved road dust contributes more than

other seasons because of dry temperatures and faster wind speeds to sustain suspension of

dust longer. For the fall season, on set of winter takes its effect and changing southerly wind

speeds pushes some of the power plant emissions to the center.

Figure 45: Modeled total PM10 averages for each season in 2006 (µg/m3)

80 UAPAU

Household Stoves Heat only Boilers

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Figure 46: Modeled source contributions (%) to annual PM10 concentrations in 2006


Once again, besides the sources modeled in this study, there are a number of sources still

missing in the inventory. The sources listed and modeled are the major sources identified

and each contributes differently because of their location and size. Figure 46 presents annual

average contribution of various sources for year 2006 and Table 8 presents averages over the

central domain circled in Figure 43.

Table 8: Average contribution range to center of Ulaanbaatar

Source Type Percentage Range Household stoves 25-40 Heat only boilers 15-25 Power plants 15-30 Vehicles 6-8 Vehicles + Road dust 18-21 Brick industry - Open waste burning 4-6

The ground level sources contribute significantly more than the elevated sources such as

power plants and large heat only boilers. Note that figure represents average percentages and

the real concentration contributions are much higher in number. For example, the high

patch of 30 percent or more for the power plants contribution is mainly because of the

lower concentrations in the south originating from other sources and location of power

plants. In general, the low lying sources, for obvious reasons contribute the most to the

central domain of Ulaanbaatar. The household stoves and heat only boilers contribute to an

estimated 40-60 percent. Road dust is one of the unaccounted sources and is more

prominent in the dry seasons. Currently contribution by the brick industry is small in the east

(10 factories) and west (11 factories), but given the current demand for construction

material, this contribution is expected to grow in the coming years. In case of open waste

burning, these sources are distributed along the Ger locations and shows 3-6 percent

contribution, which is also high in real numbers. Similar to the coal consumption, waster is

generated in more in the winter months and expected to get burn the most (see figure 32).

In Winter, these contributions are much higher than the annual averages, given increased

coal consumption for heating in the households and power sector. Figure 47 presents

82 UAPAU

percent contributions for four main sources for the winter months – December, January,

and February.

Household Stoves Heat only Boilers

106.7 106.75 106.8 106.85 106.9 106.95 107 107.0547.8

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106.7 106.75 106.8 106.85 106.9 106.95 107 107.0547.8

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Contributions from the main households and heat only boilers increase at least 10 percent

over the central Ulaanbaatar. Change in the contribution of the power plants in the winter is

not as pronounced as the other two sectors, mainly because of the inversion layer. Because

of high stack heights, the emissions are above the inversion layer and contributing less at the

ground level. This is also evident in Figure 8 where the plumes can be clearly seen above the

inversion layer and moving over the city.

Under business as usual scenario, simulations were conducted for years 2010, 2015, and

2020, suing the emissions inventory presented in the previous section. All the simulation

used meteorological fields from 2006, so the dispersion patterns are the same compared to

year 2006. NOTE that these are business as usual scenarios, assuming growth rates and no

Figure 47: Modeled source contributions (%) to winter PM10 concentrations in 2006


new controls introduced for most of the source categories. Figure 48 present annual average

concentrations for total PM10 concentrations for 2010, 2015, 2020.

Concentrations (µg/m3) % increase from 2006

2010

106.7 106.75 106.8 106.85 106.9 106.95 107 107.0547.8

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In the future baseline scenarios, there is a new power plant (CHP-5) planned to the east of

the city, is gradually expected to come fully online and operational in 2010. Assumptions for

this baseline estimates are explained in the previous chapter. Figure 48 also presents the

percent increases with respect to the total PM10 concentrations in 2006. Under business as

usual, it is expected to have a minimum of 20, 40, and 70 percent increase in total PM10

concentrations.

Figure 48: Modeled future (2010, 2015, 2020) PM10 concentrations (µg/m3) under BAU

84 UAPAU

Impact Evaluation

A large number of studies were conducted and are being conducted around the world to

document a consistent association between elevated ambient PM10 and PM2.5 levels to an

increase in mortality rates, respiratory infections, number and severity of asthma attacks and

the number of hospital admissions30. Actual health impacts of air pollution are determined

by two factors, i.e., by sufficiently high concentrations of pollutants in the atmosphere and

the presence of people in the region affected by these pollution levels. In Ulaanbaatar, both

are true, especially in the winter season, with high ambient PM concentrations and people in

high density areas of Gers being constantly exposed to them. Latest information on

epidemiological studies and health impacts of air pollution can be obtained from HEI31

website.

In this study, health impacts are estimated in the following way: First, the corresponding

changes in ambient concentrations are estimated - such as exceedances to WHO guidelines

or thresholds to health impacts or in case of scenario analysis, changes in number of cases,

subsequently combined with the population at risk of exposure. Based on dose-response

functions32 from the literature, health impacts are derived using the equation below.

)(**)( arg ettCCPOPPOP −= βδ

Where δ(POP) is the population exposed and effected because of the excess of

concentrations (C-Ctarget). β is the dose response function of the health endpoint. Some

examples are presented in Table 9. POP is the total population of the region or the grid.

30 OECD.: 2000, ‘Ancillary Benefits and Costs of Greenhouse Gas Mitigation’, Proceedings of an IPCC co-sponsored workshop, Washington, DC, USA 31 HEI – Health Effects Institute – www.healtheffects.org 32 Dose-response functions measure the relationship between exposure to pollution as a cause and specific outcomes as an effect. They refer to damages/production losses incurred in a year, regardless of when the pollution occurs, per unit change in pollution levels. In this table, the function is defined as number of effects incurred per unit change in concentrations (µg/m3) per capita.


Table 9: Average Dose-Response33 functions and willingness to pay for health endpoints

Health Endpoint Dose response function (effects/1µg/m3 change/per capita)

Willingness to Pay (US $) per effect34

Mortality 0.0001400 16,667.00 Adult Chronic Bronchitis 0.0000612 3,333.00 Child Acute Bronchitis 0.0005440 1,667.00 Respiratory Hospital .Admission 0.0000120 83.00 Cardiac Hospital Admission 0.0000050 5,000.00 Emergency Room Visit 0.0002354 2.00 Asthma Attacks 0.0326000 1.00 Restricted Activity Days 0.0570000 1.00 Respiratory Symptom Days 0.1830000 1.00

For this study, health impacts were evaluated for the city center based on the population

distribution. For year 2006, 2010, and 2020, estimates of city average annual concentrations

were evaluated using annual PM10 WHO standard of 80 µg/m3 as a threshold value for

occurrence of heath impacts.

Besides mortality, morbidity end points were also considered, such as - adult and child

chronic bronchitis, respiratory hospital admissions, cardiac hospital admissions, emergency

room visits, asthma attacks, restricted activity days, and respiratory symptom days. Table 10

presents results of health impact analysis using city average PM10 concentration in the center

of the city and possible incurred health costs based on willingness to pay studies. For further

details on the methodology refer to Lvovsky et al., 200035. The willingness to pay is a

33 Reference material for dose response functions and case studies. (1) WHO, 1999, Air Quality Guidelines, http://www.who.int/peh/air/Airqualitygd.htm; (2) Ostro, B.: 1994, ‘Estimating the Health Effects from Air Pollutants: A Method With an Application to Jakarta.’ World Bank Policy Research Working Paper #1301; (3) Xu, X., D.W. Dockery, J. Gao, and J. Chen.: 1994, ‘Air Pollution and Daily Mortality in Residential Areas of Beijing, China.’ Archives of Environmental Health, 49, pp. 216-222; (4) SAES.: 2000, ‘Shanghai Energy Option and Health Impact.’ Report prepared by Shanghai Academy of Environmental Sciences and Shanghai Medical University (5) ECON study, East Asia and Pacific region, Contact person: Mr. Jostein Nygard, The World Bank, Washington DC 34 These willingness to pay values are averaged and adjusted to Mongolian rates based on local GDP. A GDP of US$ 600 is assumed for Mongolia. Reference case study is US mortality and morbidity health costs for the listed health endpoints. This is a conservative estimate and needs local studies to corroborate. 35 Lvovsky, K., G. Hughes, D. Maddison, B. Ostro, and D. Pearce. 2000. “Environmental Costs of Fossil Fuels: A Rapid Assessment Method with Application to Six Cities.” Environment, Department Paper 78, The World Bank, Washington, DC. USA.

86 UAPAU

methodology used to present monetarized version of health impacts and can be useful in the

cost benefit analysis of interventions.

Table 10: Estimated health costs incurred in each year due to excess pollution

Model Year City center average PM10 concentration (µg/m3)

Total Mortality costs (US$, in millions)

Total Morbidity costs (US$, in millions)

Total health costs (US$, in millions)

2006 200 182.0 110.0 292.0 2010 247 296.3 179.0 475.3 2020 327 648.7 392.0 1,040.7

87

6. Possible Interventions

Several methods of controlling emissions are practiced in most developing country urban

areas, including fuel switching to gas and low-sulfur coal, the more wide-scale use of district

heating systems, use of flue-gas desulphurization, emission control equipment, energy-

efficient installations, and the use of advanced combustion technologies. But there are often

large numbers of combustion sources that may be difficult to control, and the efficiency of

these technologies and levels of emission control remain low.

List of possible interventions are

1. Improved stoves for Ger areas

2. Briquettes or smoke-less coal

3. Improve efficiency of power plant scrubbers

4. Improve efficiency of PP-4 ESP

5. FGD for sulfur control in power plants

6. NOx control in power plants

7. Ash pond maintenance - brick making

8. Reduction of local garbage burning

9. Gasification of urban and solid waste

10. Paved road dust reduction – sweepers

11. Renewables for housing – solar heaters

12. Abolish small scale boilers for heating

13. Promotion of public transportation

14. Inspection and maintenance of older vehicles

88 UAPAU

Current list is not final and these interventions were selected based on the discussions with

local groups, current control strategies, and sources analyzed. In this section, a little

background on each of the interventions is presented along with expected reductions upon

implementation and estimated changes to the concentrations in Ulaanbaatar city. Results are

based on back of the envelope calculations and further detailed study is a necessity for each

of the interventions. Note that the scenarios are not being overlapped for analysis, which is a

very plausible scenario as none of these interventions will be acted upon individually. At this

time, these interventions are being treated and pollution analyzed on an individual basis to

evaluate their level of impact upon implementation.

Improved Stoves in Ger areas

Under a pilot program, approximately 20,000 improved stoves have been disseminated in

Mongolia since 2001, most of them installed in UB. Figure 49 presents an installation in

Ulaanbaatar, where the stove is being used in a modernized kitchen to use the heat from

stove on two floors. The advantage of this program was inclusion of kitchen improvement

strategy along with stove, which adds to the aesthetics of some houses, as shown below. This

pilot study also included indoor air pollution assessments, results of which are published36

and available for review.

Surveys conducted after piloting the program, it is estimated to save up to 2 tons of coal (40

percent of saving compared to standard stove) and 1.5 m3 of fuel wood (50 percent) per

stove per year. Even though savings of up to $50 per year on cost of coal are possible (retail

price of coal at $25 per ton), a key barrier to uptake identified is that the cost of an improved

stove is nearly double that of a traditional stove, costing MNT 70,000 ($70) as opposed to

MNT 40,000 ($40). There are currently more than 10 private manufacturers who are trained

and financed under this program to supply these stoves and looking for means to scale-up

the program. Program also promotes use of scrap metal from ship yards as stove material,

36 www.esmap.org

Examples of Interventions 89

which is aimed at bringing the stove cost down. Contact person for this program in

Ulaanbaatar is Ms. Oyuntsetseg (Email: [email protected], Phone: +976 99115526)

The Municipality is considering a policy to subsidize the cost of more efficient stoves for

poor households but the impact is too early to judge. While demonstrated effective in

reducing emissions, dissemination would have to increase significantly to have a measurable

impact on air quality. Assuming that all the stoves will be converted to improved stoves by

2010, expected changes in emission contributions are presented in Figure 50. This

intervention is expected to reduce as estimated 10,973 tons of total PM10 emissions in 2010

or 9% of the 2010 BAU.

Figure 49: Improved cookstoves and manufacturing in Ulaanbaatar

90 UAPAU

Business as Usual Improved Stoves

HH Stoves21%

HoB15%

Veh3%

UPRD9%

Brick3% OB

4%

HWB0%

UNK8%

Other14%

PP33% Kiosks

2%

PRD2%

HH Stoves14%

HoB17%

Veh3%

UPRD9%

Brick4% OB

4%

HWB0%

UNK9%

Other15%

PP36%

Kiosks2%

PRD2%

Briquettes or smokeless coal

Charcoal, made out of wood chunks, saw dust, and some low grade coals, is a desirable fuel

because it produces a hot, long-lasting, virtually smokeless fire. Combined with other

materials and formed into uniform chunks called briquettes, it is popularly used for outdoor

cooking in the developed countries. In Ulaanbaatar, given the usage of coal in the stoves and

stoves contribution to the ground level pollution, this is also a viable solution to reduce

outdoor and indoor air pollution. Main difference between this scenario and the introduction

of improved stoves is the central control of fuel manufacturing and use. In this case, there

will be a centrally located industry, which is responsible for manufacturing the clean fuel,

with improved emission standards compared to the regular raw coal being burnt in Gers.

Currently, there are three private factories (partly funded by the local Xac Bank)

manufacturing briquettes out of saw dust. Their conclusion is that the demand for these

briquettes is high, even though the price is higher than the local raw coal, mainly because of

better fuel characteristics. Figure 51 presents results for fuel testing conducted for product

from one of the private manufacturers. One of the manufacturers, presented in the picture

(Contact information: Mr. Dash Ulzii, Email: [email protected]; Phone: +976 9111

Figure 50: Change in PM10 source contributions in 2010 for improved stoves


3536), has a plant capacity of 2,000 tons a year and interests in expanding the production

20,000 tons in the coming years.

Ash (%)

0

10

20

30

40

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BC-1 BC-2 BC-3 SD-B C-B PC

Calorific Value

01,0002,0003,0004,0005,0006,0007,0008,000

BC-1 BC-2 BC-3 SD-B C-B PC

In the figure BC is the standard brown coal, three different types. The lowest is the

commonly available for household use. And the rest are SD-Saw dust briquette, C-B is the

charcoal briquette and PC is the pressed coal (see Figure 19).The calorific value of the

briquettes is 2-3 times higher than locally available coal, and 2-5 % Ash content compared to

20+ percent in the raw coal. These briquettes are also available in the pellet form (shown in

the packet in the picture), with higher burning efficiency. Although the price of briquettes

(see Table 11) is currently 5 times higher than locally available raw coal, the energy content

(2-3 times more) and ash content (5-10 times lower) make up the rest. Mr. Dash expects this

price to come to down to 60,000 MNT with the production capacity going up.

Figure 51: Briquettes in use in Ulaanbaatar and fuel characteristics

92 UAPAU

Table 11: Price of various household fuels

Fuel Type Price (MNT) per tonRaw coal 21,000 Pressed coal 40,000 Sawdust briquette 100,000 Charcoal briquette 200,000 to 300,000 Sawdust + Charcoal 100,000 Sawdust pellets 100,000

The municipality of Ulaanbaatar is planning to expand the production of smoke-less

(charcoal) fuel from coal - one at the baganuur coal mine location and other by converting

the CHP-2 with a combined capacity of 300,000 tons per year. There is pilot project in place

to produce 5,000 tons a year near the town of baganuur, details of this are presented in the

“Parliamentary resolution for air pollution reduction – English translation.” Production cycle

for this process is presented in Figure 52.

Currently, the private manufacturers are supplying to smalls scale industries (heat only

boilers). Assuming that these briquettes will be made available to household users at

marketable prices by 2010, with a fifty percent households covered under this program,

expected changes in emission contributions is presented in Figure 53. This intervention is

expected to reduce as estimated 12,415 tons of total PM10 emissions in 2010 or 10% of the

2010 BAU.

Figure 52: Smokeless coal making process


Business as Usual Briquettes for households

HH Stoves21%

HoB15%

Veh3%

UPRD9%

Brick3% OB

4%

HWB0%

UNK8%

Other14%

PP33% Kiosks

2%

PRD2%

HH Stoves13%

HoB17%

Veh3%

UPRD10%

Brick4% OB

4%

HWB0%

UNK9%

Other15%

PP36%

Kiosks2%

PRD2%

Note that the introduction of briquettes into the market, will also affect the consumption

patterns at the heat only boilers, which is not simulated here.

Figure 53: Change in PM10 source contributions in 2010 for briquettes

94 UAPAU

Power plants

In Ulaanbaatar, CHP-2 and CHP-3 operate wet scrubbers and CHP-4 operates an

Electrostatic Precipitator (ESP) for particulate pollution capture. Currently, the wet

scrubbers are running at an efficiency of 70 - 80 percent capture rate. CHP-4 is operating at

95 percent capture rate, which is very low compared to a typical efficiency rate of 99.8

percent for an ESP. Discussions with the plant Chief Engineer, presents the main problems

for are smoke and maintenance and operation. The power plants do not employee any sulfur

controls, which adds to the particulate pollution in the form of secondary from SO2 and

NOx emissions. Especially, with the power plants, there is a large potential to reduce

emissions.

One possible intervention is installation of an ESP for CHP-3, which consumes

approximately 1 million tons of coal a year, help control the ash collection and also reduce

the water run-offs by improving the collection efficiency. Similarly, finding ways to improve

the efficiency of current ESP operation at CHP-4 from 95 to 99 percent.

Box 1: Pollution Control Technologies for Power Plants

There are a number of technologies that can be applied to existing and new plant that can reduce particulate emissions by as much as 99.5%, these include:

• Electrostatic Precipitators (ESPs) • Fabric Filters • Hot Gas Filtration Systems • Wet Particle Scrubbers

Electrostatic precipitators are the most widely used particulate emissions control technology in coal-fired power generating facilities. Particulate/dust laden flue gases are passed horizontally between collecting plates, where an electrical field creates a charge on the particles. The particles are then attracted towards the collecting plates, where they accumulate.

Flue gas desulphurisation (FGD) technologies are used to remove sulphur emissions post-combustion. FGD technologies can be classified into six main categories:

• wet scrubbers • spray dry scrubbers


• sorbent injection processes • dry scrubbers • regenerable processes • combined SO2/NOx removal processes

Wet scrubbers tend to dominate the global FGD market. The technology uses alkaline sorbent slurry, predominantly lime or limestone based. A 'scrubbing vessel' or scrubber is located downstream of the boiler and flue gas cleaning plant, in which the sulphur dioxide in the flue gases reacts with the limestone sludge, forming gypsum. Low NOx burners control the way that coal and air mixes at each burner within a power station in order to reduce the maximum flame temperature. This in-turn limits the formation of NOx and improves the efficiency of the burner. Low NOx burners can reduce NOx emissions by 30-55%. Currently there are over 370 coal-fired units (125 GWe) worldwide that use low NOx burners. http://www.worldcoal.org/pages/content/index.asp?PageID=417

Although the percent contribution of power plants to the ambient levels in the city center is

not proportional to their emissions contributions, this is bound to reduce 10-15 percent of

the total PM10 emissions from there power plants. This intervention of improving efficiency

at CHP-2 and CHP-3 from 80 to 90 percent, and at CHP-4 from 95 to 99 percent is

expected to reduce as estimated 26,520 tons of total PM10 emissions in 2010 or 21% of the

2010 BAU.

Business as Usual Improving PM Capture Efficiency

HH Stoves21%

HoB15%

Veh3%

UPRD9%

Brick3% OB

4%

HWB0%

UNK8%

Other14%

PP33% Kiosks

2%

PRD2%

HH Stoves28%

HoB20%

Veh3%

UPRD11%

Brick4%

OB5%

HWB0%

UNK10%

Other18%

PP15% Kiosks

2%

PRD2%

Figure 54: Change in PM10 source contributions in 2010 for power plants

96 UAPAU

Abolish small scale boilers

Current inventory for heat only boilers include ~150 boilers with 0.7 to 3.5 MW capacity and

~800 of boilers of capacity less than 100 kW, scattered in and around the city of

Ulaanbaatar. In some cases, these are commercial applications, which municipality can

mandate by banning small boilers and improved fuel use. Some examples options for small

scale boilers are listed below.

Emission control options Targeted activities Readiness of fuel and/or technology, main constraints, and development potential

Briquettes

Residential cooking and space heating

No apparent constraints, except for the availability of briquettes. A short- to mid-term option, especially for cooking.

LPG replacing coal Residential/commercial cooking and water heating

Widely available in major urban areas. Can be costly to low-income households and high-volume commercial users. Most readily option to replace coal in cooking in the housing sector.

Natural gas replacing coal

Residential/commercial cooking, water heating, and space heating

Limited by availability of natural gas. Lack of distribution facilities. Costly to high-volume applications such as space heating. National development interest. Large potential for growth.

CFBC boilers Replacement of old heating boilers or new centralized district heating facilities

Domestic manufacturers are able to produce up to 100 ton-steam/hour sizes. Current costs are relatively high. Could be good candidate for large district heating facilities. Cogeneration installation would further improve energy efficiency and financial returns.

Sources: Feng Liu, The World Bank, Washington DC.


Ash pond maintenance and brick making

Flyash produced at the power plants is separated, sedimented, and collected in ash ponds

which are located close to the city. For power plants 2 and 3, these ponds are located near

the plant and for the power plant-4 it is located 3 kms from the plant to the West. During

the summer and spring months, these ash ponds act as one of the fugitive dust sources (see

Figure 23) and it is not an easy source to estimate as it is also dependent on the local wind

speeds for lifting and carrying the ash into the atmosphere. Currently, there are no plans to

utilize this fly ash, because of concerns for radiation effects. Similar concerns were put forth

in other countries, in India for example, and after testing it was cleared for brick making and

embankment use.

Similar cases were registered and cleared in the other parts of the world, which can be

piloted and implemented in Ulaanbaatar. Some example cases are presented in Box 2.

Box 2: Use of flyash for brick making

50% increase in compressive strength by using fly ash to make clay bricks in Tamil Nadu, India http://www.tifac.org.in/do/fly/proj/brick1.htm

Flyash based components for construction industry http://www.tifac.org.in/do/fly/proj/const.htm

Use of Fly Ash in Roads & Embankment Sector Gains Momentum http://www.tifac.org.in/do/fly/proj/road1.htm

Reclamation of fly ash dykes - out of the ashes http://www.teriin.org/tech_flyash.php

Carbon Finance project: India: FaL-G Brick and Block: Micro Industrial Plants http://carbonfinance.org/Router.cfm?Page=Projport&ProjID=9597

Superio quality brick making from pond ash http://www.ias.ac.in/matersci/bmsoct2002/443.pdf

98 UAPAU

Reduction of local garbage burning

Including material provided by: Sanjay Srivastava, The World Bank, Delhi, India

Solid Waste Management, here referring mainly to the residential garbage, is one of the

critical urban services, both for the impacts that it can have on the air quality and because it

is a clear measure of the capacity of a municipality to deliver effective and efficient service

delivery. The present poor standards for garbage burning are reflected in the inadequate

service that is provided to residents, and the environmental impacts of dumps of untreated

wastes. There is often an attitude that SWM will improve once urban centers are richer and

better managed while, in practice, SWM can also be seen as a core example of municipal

service delivery and that efforts applied and improvements made in this sector are likely to

be foundation stones for general upgrading of municipal services. The current practice of

waste management has potentially serious health problems and environmental degradation.

In many cases, uncollected waste, is disposed of in uncontrolled dumpsites and/or burnt,

polluting water resources and air, defeating the objective to achieve environmental safe

collection and disposal of municipal waste, which is enshrined in regulation.

In 2005, in Ulaanbaatar, illegal disposal of waste accounts for 73 and 200 tons per day (see

Figure 32) in summer and winter months respectively, most of which is burnt approximately

once a week contributing to ~ 5% of the total PM10 emissions.

Carbon Finance37 can potentially support the operational costs of an efficient SWM system.

There is growing interest in seeking Carbon Finance for controlling methane, especially

given the lack of other revenue sources typically associated with landfilling. The principle is

straightforward: capturing and destroying methane, or changing systems to prevent its

generation, can be the basis for claiming “Emissions Reductions (ERs)” and these ERs –

once verified -- can be sold for cash on an increasingly open Carbon Market. As opposed to

GEF grants, which are applied at the construction stage, ERs are based on confirmed results

37 http://carbonfinance.org/Router.cfm?Page=ProjPort&ItemID=24702


from an operating scheme and become a revenue stream for a successful project, for a

period of typically 7-14 years.

Table 12: Indicative Carbon Finance Revenue in SWM – Case study of India

MSW treatment & disposal options

Potential Emission Reductions

(tCO2E/tMSW)

Carbon finance for treatment of MSW

Rs/tMSW Assuming Landfill without LFG recovery as baseline Landfill with LFG recovery & flare

0.95-1.20 175-200

Landfill with LFG recovery and energy generation

More than 0.95 More than 175 Rs/ton

Composting More than 1.16 More than 200 Rs//ton

Biomethanation More than 1.16 More than 225 Rs/ton

For existing dumps, closing a dump in a way which prevents further release of methane

could be eligible for Emissions Reductions. Constructing new landfills in a way which

prevents the generation (or at least the release) of methane is another possibility, although

the protocols for Carbon Finance require an innovative approach which achieves additional

reductions beyond “business as usual.” One particularly interesting opportunity is the use of

composting, where careful processing of waste in aerobic conditions avoids the generation

of methane.

For air pollution, this is an avoided 5 percent of emissions.

100 UAPAU

Gasification of Urban and Solid Waste

Biomass is a broad classification of organic and biologically derived materials including

wood, agricultural residue/waste, household waste and animal manure. While wood and

agricultural residues are not easily biodegradable (i.e. broken down into simple molecules

through biological processes such as by action of bacteria and other microorganisms), animal

manure and most household food wastes can be biologically degraded to produce biogas - a

methane rich gas that can be used as fuel. Given the amount of waste generated (500 tons a

day in the winter season – see Figure 32) and the live stock population (see Figure 34), this

might be a viable intervention for small scale household applications in the Ger areas where

the biogas fuel can be used for heating. On a larger scale in Ulaanbaatar, where production

and disposal of large quantities of organic and biodegradable waste, without adequate

treatment, is increasingly becoming a part of the environmental pollution problem biogas

generation might also be a more economic and environmentally beneficial alternative to

aeration at the landfills or burning at disposal sites.

Biogas is produced in anaerobic digesters (operated in the absence of oxygen) and can use

manure as well as food waste as inputs. Besides generating fuel quality gas, the anaerobic

treatment process greatly reduces odor, kills 90 to 99% of pathogens and removes enough

solids so that the byproduct become much easier to handle. As an example, a current

commercial anaerobic Induced Blanket Reactor (IBR) can produce biogas from animal

manure with a methane content of 70 – 80%. Since methane is the major component of

natural gas, biogas can be burned like natural gas in an engine/generator to co-produce

electricity and heat or simply burned in a boiler to produce hot water or steam. Untreated

manure can result in release of significant quantities of methane to the atmosphere - a GHG

that is 21 times more potent than CO2. Trapping and burning methane as biogas greatly

reduces the release of GHGs from animal husbandry. Dr. Conley Hansen (Department of

Nutrition and Food Science, Utah State University; email: [email protected]) is a lead

researcher on the IBR technology in the United States. Another group working on biogas


production issues with considerable knowledge is: Action for Food Production:

http://www.afpro.org

Other biomass types such as wood and agricultural residues, that are more resistant to

biodegradation, can be converted into synthesis gas (a mixture of carbon monoxide and

hydrogen) or producer gas (a mixture of carbon monoxide and nitrogen) – both of which

can yield higher energy yields and clean burning than conventional burning of wood. A

detailed history and variety of gasifiers for production of producer gas in use around the

world is explained in “Scaling Up Biomass Gasifier Use - Applications, Barriers and Interventions” 38.

Current state of the art for synthesis gas production is presented in “Preliminary Screening -

Technical and Economic Assessment of Synthesis Gas to Fuels and Chemicals with Emphasis on the

Potential for Biomass-Derived Syngas”39. The large-scale deployment of such biomass conversion

technologies can help with the heating systems load in Ulaanbaatar.

38 The World Bank Publication No. 30892 39 http://www1.eere.energy.gov/biomass/pdfs/34929.pdf

102 UAPAU

Paved road dust reduction – wet sweeping

Loose materials, such as silt and sand that have accumulated on roadways can be suspended

into the atmosphere by the tires of vehicles. These suspended particulates are referred to as

“road dust” or “fugitive dust”. At some locations near roadways the measured concentration

of dust or fine particulates in the air is significant, resulting in impaired air quality and poor

visibility. In Ulaanbaatar, in the spring and summer months, the silt loading on the roads is

high, due to fugitive dust from the construction sites, unpaved roads, dust storms, coal

burning, tire traction, and vehicular emissions (though small quantities). The movement of

passing vehicles suspends particles and creates a visible dust cloud in the springtime before

roads have been mechanically swept clean or naturally washed by rainfall. In some

municipalities, the sweeping of the roads is part of the solid waste management, where the

sweeping is conducted manually.

In the dry months, in order to mitigate road dust

• Schedule the removal of accumulated dust as early as possible to shorten the

potential period of dust generation.

• Apply dust suppressants during spring clean-up activities. Wetting traction materials

with water or other dust suppressant compounds will help reduce dust generation

during collection.

• Ensure that equipment used for material collection is well maintained and

functioning. Several types of road sweepers are available, including mechanical

broom sweepers (useful for heavier materials but less efficient in removing fine

particles), vacuum sweepers (effective pick-up of material near curbs but inefficient

cleaning along the entire sweeping width), and regenerative air sweepers (more

thorough cleaning of all particle sizes over the road surface).

• The cost of regenerative air sweepers may be 2 to 2.5 times the cost of a traditional

sweeper, however the operation cost and service life are comparable.

Examples: http://www.tymco.com/ (from google search)


Transport Demand Management

Transport projects that promote integration of different transport modes can maximize

overall system efficiency. Similarly, clean technologies, fleet renewal, increased speed, and

decreased travel times promote the modes of transport that meet peak traffic demand,

conform to the zoning regulations of urban areas, and contribute to system efficiency and

reduction of environmental impacts. Traffic demand management, involving parking

controls, area licensing, traffic calming, use restrictions, signal schemes, driver licensing,

congestion charging, and parking management, can have quantitatively measurable impacts.

Finally, intelligent transport systems and traffic rationalization can help leverage resources

from state and local government agencies. So far, urban transport projects co-financed by

the World Bank Group and Global Environmental Facility (GEF) under GEF OP-11 have

focused on aspects of public transport, traffic demand management, and non-motorized

transport. Land use, urban planning, and freight transport issues have received limited

attention. Important opportunities for promoting urban transport objectives exist in these

areas.

Useful links with examples and toolkits.

• Reducing Air Pollution from Urban Transport40

• Promoting Global Environmental Priorities in the Urban Transport Sector - Experience from

World Bank Group-GEF Projects41

• PPIAF – Urban Bus Toolkit42

40 The World Bank publication - http://www.cleanairnet.org/cai/1403/article-56396.html 41 The World Bank publication No. 37469 42 http://www.ppiaf.org/UrbanBusToolkit/assets/home.html

104 UAPAU

Renewables for housing – solar water heaters

Box 3: Example of Solar Water Heaters in Rizhao, China In the Chinese coastal city of Rizhao (population 3 million), a government program enabled 99 percent of households in the central districts to obtain solar water heaters. Most traffic signals and street and park lights are powered by solar cells, limiting the city's carbon emissions and local pollution. "The fact that Rizhao is a small, ordinary Chinese city with per capita incomes even lower than in most other cities in the region makes the story even more remarkable," the Worldwatch report states. "The achievement was the result of an unusual convergence of three key factors: a government policy that encourages solar energy use and financially supports research and development, local solar panel industries that seized the opportunity and improved their products, and the strong political will of the city's leadership to adopt it." http://us.oneworld.net/article/view/149798/1/

In Ulaanbaatar, a large portion of the energy is consumed for heating purposes in homes,

hotels, hospitals, hostels, dairies, industries, institutions, govt. buildings, guest houses etc.

One of the major energy sources missing from the consumption charts is solar. Though the

technology is deemed expensive, it is gaining momentum among the developing country

cities.

Box 4: Renewable energy trends Two main points - If renewables are not yet competitive, they are getting close; and cost comparisons can never be analytically precise, because they depend on assumptions about future fuel prices, interest rates, technology costs, treatment of external costs, and other conditions and thus leave room for analytical arbitrariness and bias. Aside from direct cost differences, many other market barriers have meant that most renewables continue to require policy support. http://www.martinot.info/ (formerly with GEF)

Figure 55 presents some applications from India and Box 4 presents a case study from the

city of Rizhao, China, which transformed itself into a solar city. In the Indian cities presented

below, solar hot water is provided by a rooftop solar collector that heats water and stores it

in a tank for use as domestic hot water. Solar space heating is often part of a “combisystem”

that circulates solar heated water for interior space heating when necessary.


Solar Water Heaters installed in Bangalore

Solar Water Heaters installed in Bangalore

6.6 MW MSW power plant

in Hyderabad

Source: Presentation by Ministry of New and Renewable Energy, Govt. of India, at ICLEI’s “Local Renewables – Model Community Model” program workshop, May, 2007, New Delhi, India

Given Ulaanbaatar experiences more than 250 days of cloud free days and the planned

40,000 new housing complexes in the city of Ulaanbaatar, this could be an intervention,

which will not only reduce the loads on the planned district heating system, but also energy

consumption at the household levels. A typical section of new and upcoming housing

systems in presented in Figure 56, but currently no plans for solar water systems.

Useful links on this topic are:

Solar Cities: Habitats of Tomorrow - http://sc.ises.org/ Solar (and Sustainable) Cities - http://www.martinot.info/solarcities.htm ICLEI: - https://www.iclei.org/fileadmin/user_upload/documents/South_Asia/LR-Newsletter_1_.pdf MNRE, India - http://mnes.nic.in/frame.htm?majorprog.htm

Figure 55: Applications of solar water heating for housing systems in India

106 UAPAU

Figure 56: New buildings in Ulaanbataar

107

7. Future Scenario Analysis

Based on the interventions discussed in Chapter 6, two combinations of scenarios are

ASSUMED and analyzed in the manner similar to the methodology presented in Chapter 4

and Chapter 5. NOTE that the model meteorological inputs are for year 2006 and similar

dispersion patterns are observed here.

Scenario for 2010 and Results

Main assumptions that went this scenario are as follows:

• 50 percent shift to improved stoves in the households

• 50 percent shift from coal to briquettes in the household stoves

• 50 percent abolishment of small heat only boilers operating in the city

• 50 percent improvement in the garbage collection and reduction of in-situ burning

• Use of fly ash from power plant ash ponds, reducing the unknown

Emission inventory for under this scenario is presented in Table 13, resulting in a total

reduction of ~25,600 tons of primary PM10 emissions or 20 percent compared to business

as usual in 2010 (see Table 5 and Figure 36). With the expected growth rates and these

controls are expected to bring the total emissions to 2006 levels for PM. No further controls

are assumed for the power plant sector at this time, making it the dominate pollution source

(see Figure 57). Figure 58 presents modeled total PM10 concentrations (primary and

secondary combined) and percent reductions from the business as usual scenario.

108 UAPAU

Table 13: Estimated emissions inventory for Ulaanbaatar in 2010 with controls (in tons)




Power plants 41,925 16,770 20,000 43,131


Vehicles 3,174 1,587 1,837 13,964



Brick industry 4,164 1,665 320 482



Unknown 10,000 3,500

Total 102,942 42,163 28,413 70,126

HH Stoves10%

HoB14%

Veh3%

UPRD11% Brick

4%

OB3%

HWB0%

UNK10%

Other15%

PP41%

Kiosks2%

PRD2%


Figure 57: Estimated percentage contributions to total PM10 emissions in 2010 with controls

Scenario Analysis 109

106.7 106.75 106.8 106.85 106.9 106.95 107 107.0547.8

47.85

47.9

47.95

48

0

30

60

90

120

150

180

210

250

300

106.7 106.75 106.8 106.85 106.9 106.95 107 107.0547.8

47.85

47.9

47.95

48

% change from 2010 business as usual

106.7 106.75 106.8 106.85 106.9 106.95 107 107.0547.8

47.85

47.9

47.95

48

-50

-45

-40

-35

-30

-25

-20

-10

0

106.7 106.75 106.8 106.85 106.9 106.95 107 107.0547.8

47.85

47.9

47.95

48

Figure 58: Modeled 2010 PM10 concentrations (µg/m3) with controls

110 UAPAU

Scenario for 2020 and Results

Main ASSUMPTIONS for this scenario are as follows:

• 100 percent shift to improved stoves in the households

• 100 percent shift from coal to briquettes in the household stoves

• 50 percent abolishment of small heat only boilers operating in the city

• Halving the growth of small and big heat only boilers and promotion of district

heating and solar water heating

• 50 percent improvement in the garbage collection and reduction of in-situ burning

• Introduction of ESPs for all the power plants without (2 & 3) and improving the

efficiency of ESPs with (4 & 5)

• Introduction of FGD systems reducing SO2 and NOx emissions by 75 percent

• Use of fly ash from power plant ash ponds, reducing the unknown

• Mechanical sweeping of the paved roads and reducing the silt loading on roads for

the spring and summer and conversion of a fraction of unpaved to paved roads in

the Ger area.

Emission inventory for under this scenario is presented in Table 14, resulting in a total

reduction of ~89,000 tons of primary PM10 emissions or 50.5 percent compared to business

as usual in 2020 (see Table 7 and Figure 38). No further controls are assumed for the power

plant sector at this time, making it the dominate pollution source (see Figure 59). Figure 60

presents modeled total PM10 concentrations (primary and secondary combined) and percent

reductions from the business as usual scenario.

Scenario Analysis 111

Table 14: Estimated emissions inventory for Ulaanbaatar in 2020 with controls (in tons)


Household stoves in Gers 5,590 3,354 965 7,643


Power plants 17,550 7,020 7,200 15,527


Vehicles 4,931 2,466 2,894 21,450



Brick industry 8,558 3,423 658 991



Unknown 7,000 5,000

Total 87,256 38,349 17,381 54,136

HH Stoves6%

Veh5%

UPRD15%

Brick9%

OB5%

HWB1%

UNK12%

Other28%

HoB20%

PP18%

Kiosks4%

PRD5%


Figure 59: Estimated percentage contributions to total PM10 emissions in 2020 with controls

112 UAPAU

% change from 2020 business as usual

106.7 106.75 106.8 106.85 106.9 106.95 107 107.0547.8

47.85

47.9

47.95

48

-70

-60

-55

-50

-45

-40

-35

-30

-20

106.7 106.75 106.8 106.85 106.9 106.95 107 107.0547.8

47.85

47.9

47.95

48

Figure 60: Modeled 2020 PM10 concentrations (µg/m3) with controls

113

Annex 1: Data Request Sheets

These data sheets were during the visit to Ulaanbaatar in May 2007, to collect available from various departments.

Transport

1. No. of vehicles by year by type For examples, cars, buses, motorcycles, trucks, etc.

2. Trends in vehicular population As disaggregated as possible by diesel, gasoline and alternative fuel vehicles from 1990

3. Information on emission of various vehicles (If available) Emission factors (g/km) for PM, SO2, NOx, CO, CO2, HC Average vehicle kilometers traveled by vehicle type

4. Average age of vehicular fleet Modal split of various vehicular types by their age

5. Motorcycles – 2 stroke or 4 stroke? 6. Fuel consumption levels per year in the transport sector

National and UB City by fuel type – Gasoline, Diesel, LPG Consumption levels by vehicular type (if available) Fuel characteristics for Diesel (e.g., S ppm levels), Gasoline, LPG

7. Fuel efficiency by vehicular type 8. Occupancy rates for buses 9. Projected trends for vehicular growth by vehicular type to year 2020 10. Projected fuel consumption growth by 2020

Power Plants

1. Location of the power plants – latitude and longitude 2. Summary sheets for the PPs – generation and consumption stats 3. Coal consumption of the plants by month – 2005/2006 4. Type of coal used, mines that supply, and characteristics of coal 5. Location of the flyash dumpsites

PP-4 has one 3 km away from the plant PP-2 and PP-3 have one close to plants

6. Amount of ash dumped per day or per month 7. Heating water supply efficiency

Pipeline efficiency 8. Pollution control equipment information

Scrubbers at PP-2 and PP-3, their capture efficiencies ESP at PP-4, capture efficiencies

9. Monitoring data for emission rates at boilers, stacks (if available)

114 UAPAU

Industry Processes

1. Construction material mining List of Brick, Cement factories Location and capacity of each plant Coal consumption levels Operational period

2. Sand mining for construction There are 5 locations in UB? Size of these mining areas How many trips are made by the trucks to the city

3. List of various industries in UB City For example –tanning, textile, food processing, furnaces, etc Energy (coal) consumption levels of these plants Location of these plants

Modeling Groups

1. Maps for Mongolia and UB City – geo-referenced in the format that can be imported into Arcview or any other program.

National map with the districts/states listed UB city map with the districts outlined Landuse map/high resolution photos for UB City

2. Shift of Gers to Households Powerpoint presentation for the analysis Excel files for analysis showing trends and expected changes

3. Total energy consumption and Emissions For each of the sectors – Gers, HoBs Tabular data files for HoBs – with their locations – Latitude, Longitude and emissions Tabular data for Ger areas – Number of households/population per Xopoo.

4. Projects for 2020 Expected growth rates for various sectors for fuel consumption.

5. Maps (gifs) for HoB locations (already made), PPs, Gers. 6. Distribution schemes used for this analysis – coal/emissions to grids. 7. List of types of industries that exist in the UB city 8. Result maps from regression analysis – for dispersion 9. Any reports similar to master plan – for other sectors.

Fuel and Energy

1. Total energy consumption levels by fuel type – coal, gasoline, diesel, LPG, wind, alternatives National and UB City

2. Total energy consumption in various sectors Power plants (for each plant), Industries, Domestic (Gers), HoBs, Transport

3. Projected trends in energy consumption by fuel type to year 2020

Data Request Sheets 115

4. List of industries in UB city For example – bricks, cement, tanning, textile, etc

5. Information on emission (if available) Total emission estimates Emission factors (g/km) for PM, SO2, NOx, CO, CO2, HC

6. Coal combustion cycle – loads by season/month Because winter it might be high and summer less

7. Maps of industrial locations With latitude and longitude information

8. Information on new technologies in place or piloting in UB city Coal processing techniques Smokeless coal, briquettes LPG Wind

9. Fuel characteristics For Coal, diesel, gasoline, LPG

10. Costs of fuels Coal, gasoline, diesel, smokeless coal, and briquettes in the market for various sectors

(Gers, industries, PP, Transport) 11. Coal suppliers – Mining locations (maps, if available)

12. For Power Plants Fuel combustion efficiency Control technologies (ESP or scrubbers, etc) and efficiencies for PM, SO2, NOx, CO,

CO2 13. Any reports on energy planning

Environment

1. Material from Parliamentary Committee Meeting for AP reduction planning in February, 2007 Presentations made by the departments Documents summarizing action plans by the Ministries

2. Projections for 2020 Expected growth rates for various sectors – power plants, transport, Gers, construction

material 3. Maps (gifs) of PPs 4. Latitude and longitude locations for monitoring stations 5. GIS maps 6. Presentations on air pollution from various groups

Health and Hospitals – biohazard waste material burning Stoves Miscellaneous fuels used for cooking and heating in Gers

116 UAPAU

Miscellaneous

1. Major sources of pollution besides the obvious – Gers, HoBs, Industries, Transport, and PPs Any reports on these issues that could help with the report

2. Annual split of energy use in the Gers and Industries for heating Which months are Winter Which months are Summer Any percentage splits between the seasons

3. Waste Management Location of landfills – location on the maps Average waste generation per household How much waste is taken to the landfill sites Any estimates of waste burning in the city Is there any burning of the waste at the landfills

4. List of various industries in UB City For example – bricks, cement, tanning, textile, etc Any stats on their energy consumption

5. Railways What is the energy consumption at the Railway stations? Any winter-summer split

6. Aircraft Number of flights per day Average fuel consumption per day

7. Hospitals – Burning of biohazard waste Location of the hospitals with these burning facilities (on a map) Amount of waste burnt Pictures of incinerator Any measurements of emission rates

8. Construction material mining Where are these five places of mining Size of these mining areas How many trips are made by the trucks to the city

9. Population statistics Male vs Female Trends in UB city for the last ten years

10. Information on Briquette manufacturers Reports Emission factors (g/km) for PM, SO2, NOx, CO, CO2, HC Proposals

117

Annex 2: Urban Air Pollution Resources

Analytical Studies, Research and Toolkits

World Bank Resources

Environment Mattes 2005 - The Clean Air Initiative: http://siteresources.worldbank.org/INTRANETENVIRONMENT/214578-1128104496469/20669370/13TheCleanAirInitiative.pdf Clean air initiative in Sub-Saharan African Cities - 1998-2002 progress report http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64170222&theSitePK=501889&eid=000012009_20040419142042&siteName=IMAGEBANK Philippines Air Quality Monitor: http://siteresources.worldbank.org/INTEASTASIAPACIFIC/Resources/Philippines2002.pdf Thailand Air Quality Monitor: http://www.worldbank.or.th/WBSITE/EXTERNAL/COUNTRIES/EASTASIAPACIFICEXT/THAILANDEXTN/0,,contentMDK:20206650~pagePK:141137~piPK:217854~theSitePK:333296,00.html Environmental costs of fossil fuels - a rapid assessment method with application to six cities http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000094946_02081904011759&siteName=IMAGEBANK Bangladesh baby taxis: http://www.worldbank.org/html/fpd/esmap/publication/253-02bangladesh.html Improving urban air quality in South Asia by reducing emissions from two-stroke engine vehicles, Volume 1 http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000094946_01032006582921&siteName=IMAGEBANK RAINS-ASIA : an assessment model for acid deposition in Asia http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000009265_3971113151152&siteName=IMAGEBANK Clear water, blue skies : China's environment in the new century http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000009265_3980203115520&siteName=IMAGEBANK Valuing the health effects of air pollution : application to industrial energy efficiency projects in China http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000094946_02031904060584&siteName=IMAGEBANK China : air pollution and acid rain control - the case of Shijiazhuang and the Changsha triangle area http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000012009_20031119145505&siteName=IMAGEBANK

118 UAPAU

Urban air quality management strategy in Asia – guidebook http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000009265_3980312111305&siteName=IMAGEBANK Urban air quality management strategy in Asia : Greater Mumbai report http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000009265_3980217141523&siteName=IMAGEBANK Urban air quality management strategy in Asia : Jakarta report http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000009265_3980313101856&siteName=IMAGEBANK Urban air quality management strategy in Asia : Metro Manila report http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000009265_3980313101901&siteName=IMAGEBANK Urban air quality management strategy in Asia - Kathmandu Valley report http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000009265_3980313102044&siteName=IMAGEBANK Reducing air pollution from urban transport http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64170222&theSitePK=501889&eid=000012009_20041104145056&siteName=IMAGEBANK Vehicular air pollution : experiences from seven Latin American urban centers http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000009265_3971110141450&siteName=IMAGEBANK Transport fuel taxes and urban air quality http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000094946_02050804041027&siteName=IMAGEBANK Health and environment http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000094946_0205040403117&siteName=IMAGEBANK Pollution Management: http://lnweb18.worldbank.org/ESSD/envext.nsf/51ByDocName/PollutionManagement Energy poverty issues and G8 actions http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64170222&theSitePK=501889&eid=000090341_20060517102007&siteName=IMAGEBANK Better environmental decisionmaking : the DSS/IPC http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000094946_00082905303884&siteName=IMAGEBANK Can the environment wait : priorities for East Asia http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000009265_3980312111301&siteName=IMAGEBANK

Urban Air Resources 119

South Asia Urban Air Quality Website containing Briefing Notes: http://lnweb18.worldbank.org/SAR/sa.nsf/General/2F391E72031478F685256B17006FF5BB?OpenDocument Non - World Bank Resources Air Pollution and Daily Mortality in a City with Low Levels of Pollution http://ehpnet1.niehs.nih.gov/docs/2003/5276/abstract.pdf Air pollution and climate change - tackling both problems in tandem United Nations Economic Commission for Europe http://www.unece.org/env/emep/pr03_env02e_h.pdf Assessing the Health Benefits of Air Pollution Reduction for Children http://ehp.niehs.nih.gov/members/2003/6299/6299.pdf Integrated Environmental Strategies (IES) http://www.epa.gov/ies/ Health Effects Institute http://www.healtheffects.org Clean Air Initiative Website: http://www.cleanairnet.org Biannual Conference and Exhibit of the Clean Air Initiative for Latin American Cities on Sustainable Transport: Linkages to Mitigate Climate Change and Improve Air Quality - July 24th -27th 2006 -- Sao Paulo, Brazil http://www.cleanairnet.org/saopaulo/1759/channel.html Small Models for Big Problems - New Generation Tools To Assit In Making Informed Air Quality Management Decisions http://www.cleanairnet.org/cai/1403/article-59386.html

Harmonized Emissions Analysis Tool (HEAT) online software to support local greenhouse gas and air pollution emission reduction planning http://heat.iclei.org/ICLEIHEAT/portal/main.jsp Modeling Different Air Pollution Control Solutions: Bogota’s Experience Supplementing Work Carried out in Rio de Janeiro http://www.cleanairnet.org/lac_en/1415/propertyvalue-13841.html Reducing Vehicle Emissions in Asia http://www.adb.org/documents/guidelines/Vehicle_Emissions/reducing_vehicle_emissions.pdf

Appendix - Adverse Health and Environmental Effects from Vehicle Emissions http://www.adb.org/documents/guidelines/Vehicle_Emissions/appendix.pdf An evaluation of public health impact of ambient air pollution under various energy scenarios in Shanghai, China http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6VH3-49V1CVH-B&_user=1916569&_coverDate=01%2F31%2F2004&_alid=466344341&_rdoc=14&_fmt=summary&_orig=

120 UAPAU

search&_cdi=6055&_sort=d&_docanchor=&view=c&_acct=C000055300&_version=1&_urlVersion=0&_userid=1916569&md5=e99284a4e80b4dd1177a878a83cfa559

World Bank Projects with AQM components

Bangkok Air Quality Mgmt project http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64170222&theSitePK=501889&eid=000094946_99072209263727&siteName=IMAGEBANK Thailand - Bangkok Motorcycle Upgrade Project http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64154240&theSitePK=501889&eid=000094946_01021606173129&siteName=IMAGEBANK Hanoi Urban Transport http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64170222&theSitePK=501889&eid=000160016_20060516124451&siteName=IMAGEBANK Chile - Sustainable Transport and Air Quality for Santiago http://www.gefonline.org/projectDetails.cfm?projID=1349 Brazil - Transport and Air Quality Improvement Program for São Paulo http://www.gefonline.org/projectDetails.cfm?projID=2612 Colombia - Sustainable Transport and Air Quality for Bogota and Other Cities http://www.gefonline.org/projectDetails.cfm?projID=2610 Ghana - Ghana Urban Transport http://www.gefonline.org/projectDetails.cfm?projID=2596 Bangladesh - Air Quality Management Project http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64170222&theSitePK=501889&eid=000094946_00090605390782&siteName=IMAGEBANK Argentina - Pollution Management Project http://imagebank.worldbank.org/servlet/WDS_IBank_Servlet?pcont=details&menuPK=64154159&searchMenuPK=64170222&theSitePK=501889&eid=000009265_3980219162630&siteName=IMAGEBANK LAC Regional - Regional Sustainable Transport Project http://www.gefonline.org/projectDetails.cfm?projID=2767

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