Literature DB >> 29953814

Spatial Distribution of Secondary Organic Aerosol Formation Potential in China Derived from Speciated Anthropogenic Volatile Organic Compound Emissions.

Rongrong Wu1, Shaodong Xie1.   

Abstract

Fine particulate matter (PM2.5), largely composed of secondary organic aerosol (SOA), is currently one of the most intractable environmental problems in China. As crucial precursors for SOA, understanding the formation propensity of various volatile organic compound (VOC) species and sources is useful for pollution control. In this work, we estimated the SOA formation potential (SOAP) of anthropogenic VOC emissions based on an improved speciated VOC emission inventory and investigated its distribution in China. According to our estimates, toluene had the largest SOAP, followed by n-dodecane, m-/p-xylene, styrene, n-decane, and n-undecane, while passenger cars, chemical fiber manufacturing, asphalt paving, and building coating were the top five SOAP-contributing sources nationwide. The spatial distribution of SOAP in China shows a distinct pattern of high values in the southeast and low values in the northwest. Beijing-Tianjin-Hebei and surroundings, the Yangtze River Delta, Pearl River Delta, and Sichuan-Chongqing District were found to have the highest SOAP, particularly in urban areas. The major SOAP-contributing species and sources differed among these regions, which was attributed to local industrial and energy structures. Our results suggest that to mitigate PM2.5 pollution in China, more efficient SOAP-based control measures should be implemented instead of current emissions-based policies, and VOC control strategies should be adapted to local conditions.

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Year:  2018        PMID: 29953814     DOI: 10.1021/acs.est.8b01269

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  1 in total

1.  Implications of Mitigating Ozone and Fine Particulate Matter Pollution in the Guangdong-Hong Kong-Macau Greater Bay Area of China Using a Regional-To-Local Coupling Model.

Authors:  Xuguo Zhang; Jenny Stocker; Kate Johnson; Yik Him Fung; Teng Yao; Christina Hood; David Carruthers; Jimmy C H Fung
Journal:  Geohealth       Date:  2022-03-11
  1 in total

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