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author:

Wang, Yangjun (Wang, Yangjun.) [1] | Li, Li (Li, Li.) [2] | Chen, Changhong (Chen, Changhong.) [3] | Huang, Cheng (Huang, Cheng.) [4] | Huang, Haiying (Huang, Haiying.) [5] | Feng, Jialiang (Feng, Jialiang.) [6] | Wang, Shuxiao (Wang, Shuxiao.) [7] | Wang, Hongli (Wang, Hongli.) [8] | Zhang, Gangfeng (Zhang, Gangfeng.) [9] | Zhou, Min (Zhou, Min.) [10] | Cheng, Ping (Cheng, Ping.) [11] | Wu, Minghong (Wu, Minghong.) [12] (Scholars:吴明红) | Sheng, Guoying (Sheng, Guoying.) [13] | Fu, Jiamo (Fu, Jiamo.) [14] | Hu, Yongtao (Hu, Yongtao.) [15] | Russell, Armistead G. (Russell, Armistead G..) [16] | Wumaer, Akemu (Wumaer, Akemu.) [17]

Indexed by:

SCIE

Abstract:

Understanding the origin of fine particulate matter is essential to proposing proper strategies for heavy haze mitigation in Shanghai, China. In this study we used the Particulate Matter Source Apportionment Technology in Comprehensive Air Quality Model with Extensions to quantify the impacts of emissions on the concentrations of fine particulate matter (PM2.5) and its important components in Shanghai during heavy haze episodes in late autumn (6-22 November 2010). The factors considered here are regions of Shanghai and its surrounding areas, long-range regional transport, and different local emission categories. The results indicate that industrial process is the dominant local contributor to total PM2.5 mass in the whole city except that at the urban center vehicle emission contributes slightly more. In addition, industrial process and vehicle emission are the major local contributors for nitrate in Shanghai, although at urban core the contribution from vehicle emission is remarkably larger. Generally, both local contribution and regional transport contribution could dominate a severe haze event in late autumn. However, the dominant contributor could either be local emission or regional transport, usually depending on the meteorological conditions. Therefore, particular attentions should be paid to the emission control in the upwind adjacent provinces, as well as in local areas, for developing effective strategies to reduce PM2.5 pollution in Shanghai.

Keyword:

5 CAMx PM2 Shanghai Source Apportionment

Community:

  • [ 1 ] [Wang, Yangjun]Shanghai Univ, Sch Environm & Chem Engn, Shanghai, Peoples R China
  • [ 2 ] [Feng, Jialiang]Shanghai Univ, Sch Environm & Chem Engn, Shanghai, Peoples R China
  • [ 3 ] [Cheng, Ping]Shanghai Univ, Sch Environm & Chem Engn, Shanghai, Peoples R China
  • [ 4 ] [Wu, Minghong]Shanghai Univ, Sch Environm & Chem Engn, Shanghai, Peoples R China
  • [ 5 ] [Fu, Jiamo]Shanghai Univ, Sch Environm & Chem Engn, Shanghai, Peoples R China
  • [ 6 ] [Li, Li]Shanghai Acad Environm Sci, Shanghai, Peoples R China
  • [ 7 ] [Chen, Changhong]Shanghai Acad Environm Sci, Shanghai, Peoples R China
  • [ 8 ] [Huang, Cheng]Shanghai Acad Environm Sci, Shanghai, Peoples R China
  • [ 9 ] [Huang, Haiying]Shanghai Acad Environm Sci, Shanghai, Peoples R China
  • [ 10 ] [Wang, Hongli]Shanghai Acad Environm Sci, Shanghai, Peoples R China
  • [ 11 ] [Zhang, Gangfeng]Shanghai Acad Environm Sci, Shanghai, Peoples R China
  • [ 12 ] [Zhou, Min]Shanghai Acad Environm Sci, Shanghai, Peoples R China
  • [ 13 ] [Wang, Shuxiao]Tsinghua Univ, Sch Environm, Beijing 100084, Peoples R China
  • [ 14 ] [Sheng, Guoying]Chinese Acad Sci, Guangzhou Inst Geochem, Guangzhou, Guangdong, Peoples R China
  • [ 15 ] [Hu, Yongtao]Georgia Inst Technol, Sch Civil & Environm Engn, Atlanta, GA 30332 USA
  • [ 16 ] [Russell, Armistead G.]Georgia Inst Technol, Sch Civil & Environm Engn, Atlanta, GA 30332 USA
  • [ 17 ] [Wumaer, Akemu]Urumqi Petrochem Corp, Res Inst, Environm Supervis Stn, Urumqi, Peoples R China

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Source :

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

ISSN: 2169-897X

Year: 2014

Issue: 4

Volume: 119

Page: 1903-1914

3 . 8 0 0

JCR@2023

Cited Count:

WoS CC Cited Count: 149

SCOPUS Cited Count: 137

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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