Application of WRF-CMAQ Modeling System to Study of Urban and Regional Air Pollution in Bangladesh

1. Application of WRF-CMAQ Modeling System to Study of Urban and Regional Air Pollution in Bangladesh 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

2. Bangladesh Bangladesh: at a glance • Location: 20°34´ and 26°38´ N • 88°01´ and 92°41´ E • Area: 147, 570 sq km • Population: 158.6 millions • Population 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) Source: World Bank

3. 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 Brick kiln emission Vehicle emission Construction work

4. Air Quality Status in Dhaka Monthly average of PM10 and PM2.5 USEPA certified PM samplers Dhaka experiences winter peak ozone Real time gas monitors

5. Objective • Surrounded 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 Average wind field generated by MCIP for January 2004 • Main Objective • To identify and quantify the local and regional source contribution of air pollution in Bangladesh

6. 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. WRF CMAQ

7. Domain Setup Model Configuration Study Area Dhaka City

8. Episode Selection Monthly average PM10 and PM2.5 • Air pollution in Bangladesh has distinct seasonal variation • High pollution episode observed during dry winter season • Relatively cleaner atmosphere during wet summer season • January 2004 Month-long episodes have been chosen for this sensitivity study to represent typical peak pollution episode in Bangladesh

9. Emission Database and Sensitivity Cases Sensitivity Cases Region-3 Region-1 Region-2 Potential emission source region

10. CASE-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. With Original REAS emission

11. CASE-1 Original REAS emission CMAQ Comparison of NO2 with satellite NO2 column data SCIAMACHY

12. CASE-2 CMAQ Result – Monthly Average for January 2004 CO Shut-off emission in Region-1 (Inside Bangladesh) 20 to 40 µg/m3 PM2.5 0.2 ppm to 0.5 ppm CO PM2.5 O3 40 to 45 ppb O3

13. CASE-3 Domain-1: Monthly Average CO O3 PM2.5 5-times increase of emission in Region-1 (Inside Bangladesh) Domain-2: Comparison with hourly observation

14. CASE-4 Difference between Case1 and Case4 Shut-off emission in Region-2 (West Bengal) CO PM2.5 O3 Avg: 0.04 ppm Max: 0.2 ppm Avg: 3 ppb Max: 9 ppb Avg: 7 µg/m3 Max: 23 µg/m3

15. CASE-5 Shut-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

16. CASE-4 vs CASE-5 O3 PM2.5 CO West Bengal Contribution of West Bengal (Region-2) and North India (Region-3) in % CO O3 PM2.5 North India

17. CASE-6 Contribution in % Shut-off emission in Region-2 (West Bengal) and Region-3 (North India) CO O3 PM2.5

18. Estimated Transboundary Contribution

19. Conclusions • 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.

20. Future Direction of Study • 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.

21. Thank You