Muntaseer Billah, Satoru Chatani and Kengo Sudo

Department of Earth and Environmental Science Graduate School of Environmental Studies

Nagoya University, Nagoya, Japan

Presented at the 8th Annual CMAS Conference, Chapel Hill, NC, October 19-21, 2009

Bangladesh

Location: 20°34´ and 26°38´ N 88°01´ and 92°41´ E

Area: 147, 570 sq kmPopulation: 158.6 millionsPopulation density: 1045/ sq km Population growth: 1.8%Urban population: 27%Major cities: Dhaka (12 millions), Chittagong (7 millions), Khulna (3.5millions)

Rajshahi (3 millions)Climate: Tropical monsoon climate, with a hot and rainy summer and a dry winter

Average Winter temp. (Max. 26°c Min. 11°c)Average Summer temp. (Max. 36°c Min. 21°c)

Bangladesh: at a glance

Source: World Bank

Background Air pollution is the major environmental threat in Bangladesh,

particularly big cities e.g., Dhaka, Chittagong, Khulna, Rajshahi… Air pollution cause annually ~15000 deaths (~5000 in Dhaka) ~million cases of sickness requiring medical treatment ~850 million of minor illness Economic cost of air pollution in four major cities around US$200-

$800 million per year Equivalent to 0.7%-3% of country’s GDP per year

Construction work Vehicle emission

Brick kiln emission

Air Quality Status in Dhaka

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1-hour ozone standard

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PM10 PM2.5

65 µg/m3 24 Hour Standard for PM2.5150 µg/m3 24 Hour Standard for PM10

Monthly average of PM10 and PM2.5

Dhaka experiences winter peak ozone

Real time gas monitors

USEPA certified PM samplers

ObjectiveSurrounded by India which is a

significant air pollutants emitter in Asia

During high pollution episodes, Bangladesh receives most air masses from India.

During low pollution episode, Bangladesh receives air masses from Bay of Bengal

Regional sources of air pollution may be significant for Bangladesh

Both local and regional contribution of air pollution need to be identified

Main ObjectiveTo identify and quantify the local and regional source

contribution of air pollution in Bangladesh

Average wind field generated by MCIP for

January 2004

Modeling Tools Meteorological Model: Weather Research and Forecasting (WRF) version 3.1 Met Data: NCAR/NCEP reanalysis data (1˚× 1˚) Air Quality Model: Community Multiscale Air Quality Model (CMAQ) version 4.7 Emission Data: REAS emission inventory developed by Frontier Research

Center for Global Change.

Physics option

Scheme

Microphysics WRF Single-Moment 3-class scheme

Long wave radiation

RRTM scheme

Short wave radiation

Dudhia scheme

Surface layer MM5 similarity

Land surface Noah Land Surface Model

Planetary Boundary Layer

Yonsei University Scheme

Cumulus Parameterization

Grell 3d ensemble cumulus scheme

Mechanism Option

Chemical mechanism

Statewide Air Pollution Research Center mechanism (SAPRC99)

Aerosol module aero4

WRF CMAQ

Domain Setup

Domain-1 Domain-2

Area 3600 km2 1200 km2

WRF Grids 81 ×81×27 79 ×79×27

CMAQ Grids 69 ×69×27 67 ×67×27

Grid Size 45 km 15 km

Horizontal Co-ordinate

Lambert conformal

Lambert conformal

Geographical Co-ordinate

6°N to 40° N 70°E to 110°E

18°N to 28°N 84°E to 96°E

Dhaka City

Model Configuration

Study Area

January 2004

Episode Selection

Month-long episodes have been chosen for this sensitivity study to represent typical peak pollution episode in Bangladesh

Monthly average PM10 and PM2.5Air pollution in

Bangladesh has distinct seasonal variation

High pollution episode observed during dry winter season

Relatively cleaner atmosphere during wet summer season

Emission Database and Sensitivity Cases

Case Emission sensitivity

Case-1(Base case)

Original REAS emission

Case-2 Shut-off emission in Region-1 (Inside Bangladesh)

Case-3 5-times increase of emission in Region-1 (Inside Bangladesh)

Case-4 Shut-off emission in Region-2 (West Bengal)

Case-5 Shut-off emission in Region-3 (North India)

Case-6 Shut-off emission in Region-2 (West Bengal) and Region-3 (North India)Potential emission source

region

Region-1

Region-2

Region-3

Sensitivity Cases

With Original REAS emissionCASE-1

CMAQ can capture 24-hour average PM2.5 trends but underestimate.CMAQ can not capture hourly variation of gaseous pollutants and largely underestimate.

Possible Reasons:Same emission input was used for both domain.Seasonal variation of emission is not considered in REAS inventory.Biomass burning is not included in REAS inventory.

Comparison of NO2 with satellite NO2 column data

CASE-1Original REAS emission

SCIAMACHYCMAQ

Shut-off emission in Region-1 (Inside Bangladesh)CASE-2

0.2 ppm to 0.5 ppm CO

20 to 40 µg/m3 PM2.5

40 to 45 ppb O3

CMAQ Result – Monthly Average for January 2004

O3

PM2.5

CO

5-times increase of emission in Region-1 (Inside Bangladesh)

CASE-3Domain-1: Monthly Average

Domain-2: Comparison with hourly observation

CO O3 PM2.5

Shut-off emission in Region-2 (West Bengal)CASE-4

Difference between Case1 and Case4

CO O3 PM2.5

Avg: 3 ppb Max: 9 ppb

Avg: 0.04 ppm Max: 0.2

ppm

Avg: 7 µg/m3 Max: 23

µg/m3

CASE-5Shut-off emission in Region-3 (North India)

Difference between Case1 and Case5

CO O3 PM2.5

Avg: 0.04 ppm Max: 0.1

ppm

Avg: 4 ppb Max: 8 ppb

Avg: 7 µg/m3 Max: 13

µg/m3

Contribution of West Bengal (Region-2) and North India (Region-3) in %

CASE-4 vs CASE-5

West Bengal

North India

CO O3 PM2.5

CO O3 PM2.5

Shut-off emission in Region-2 (West Bengal) and Region-3 (North India)

CASE-6

Contribution in %

PM2.5O3CO

Estimated Transboundary Contribution

WRF was able to generate required meteorological inputs for CMAQ model for this region.

CMAQ captured the PM2.5 trends well Concentrations of gaseous pollutant were largely

underestimated by CMAQ. These discrepancies were heavily depended on emission input of CMAQ model.

CMAQ was highly sensitive to emission input which revealed the underestimation of REAS emission in this region by factor of 3~5.

Significant contributions of transboundary transport of pollution were found inside Bangladesh.

Conclusions

Performance evaluation for Kolkata City (24-h average air quality data is available for 2007-2008).

Use of another emission inventory for this region e.g., Streets et al. (2003)

Development and use of own emission inventory.

Future Direction of Study

Thank You