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Title: Impacts of air pollutants from fire and non-fire emissions on the regional air quality in Southeast Asia

Journal Article · · Atmospheric Chemistry and Physics (Online)
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Abstract. Severe haze events in Southeast Asia caused by particulate pollution have become more intense and frequent in recent years. Widespread biomass burning occurrences and particulate pollutants from human activities other than biomass burning play important roles in degrading air quality in Southeast Asia. In this study, numerical simulations have been conducted using the Weather Research and Forecasting (WRF) model coupled with a chemistry component (WRF-Chem) to quantitatively examine the contributions of aerosols emitted from fire (i.e., biomass burning) versus non-fire (including fossil fuel combustion, and road dust, etc.) sources to the degradation of air quality and visibility over Southeast Asia. These simulations cover a time period from 2002 to 2008 and are driven by emissions from (a) fossil fuel burning only, (b) biomass burning only, and (c) both fossil fuel and biomass burning. The model results reveal that 39% of observed low-visibility days (LVDs) can be explained by either fossil fuel burning or biomass burning emissions alone, a further 20% by fossil fuel burning alone, a further 8% by biomass burning alone, and a further 5% by a combination of fossil fuel burning and biomass burning. Analysis of an 24h PM2.5 air quality index (AQI) indicates that the case with coexisting fire and non-fire PM2.5 can substantially increase the chance of AQI being in the moderate or unhealthy pollution level from 23 to 34%. The premature mortality in major Southeast Asian cities due to degradation of air quality by particulate pollutants is estimated to increase from  ∼ 4110 per year in 2002 to  ∼ 6540 per year in 2008. In addition, we demonstrate the importance of certain missing non-fire anthropogenic aerosol sources including anthropogenic fugitive and industrial dusts in causing urban air quality degradation. An experiment of using machine learning algorithms to forecast the occurrence of haze events in Singapore is also explored in this study. All of these results suggest that besides minimizing biomass burning activities, an effective air pollution mitigation policy for Southeast Asia needs to consider controlling emissions from non-fire anthropogenic sources.

Research Organization:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
FG02-94ER61937
OSTI ID:
1459705
Alternate ID(s):
OSTI ID: 1502418
Journal Information:
Atmospheric Chemistry and Physics (Online), Journal Name: Atmospheric Chemistry and Physics (Online) Vol. 18 Journal Issue: 9; ISSN 1680-7324
Publisher:
Copernicus Publications, EGUCopyright Statement
Country of Publication:
Germany
Language:
English
Citation Metrics:
Cited by: 43 works
Citation information provided by
Web of Science

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Figures / Tables (15)

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