Jia Jia1, Shuiyuan Cheng 1,2, Lei Liu3, Jianlei Lang1, Gang Wang1, Guolei Chen1, Xiaoyu Liu1

  • 1 Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
  • 2 Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing 100081, China
  • 3 Department of Civil and Resource Engineering, Dalhousie University, Halifax, NS B3H 4RZ, Canada

Received: January 4, 2017
Revised: March 9, 2017
Accepted: March 23, 2017
Download Citation: ||https://doi.org/10.4209/aaqr.2017.01.0009  

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Cite this article:
Jia, J., Cheng, S., Liu, L., Lang, J., Wang, G., Chen, G. and Liu, X. (2017). An Integrated WRF-CAMx Modeling Approach for Impact Analysis of Implementing the Emergency PM2.5 Control Measures during Red Alerts in Beijing in December 2015. Aerosol Air Qual. Res. 17: 2491-2508. https://doi.org/10.4209/aaqr.2017.01.0009


HIGHLIGHTS

  • The Beijing-Tianjin-Hebei region experienced heavy air pollution in December 2015.
  • Local emissions were the most dominant contributors (64.8%–83.5%).
  • Emergency control measures have positive effects on air pollution reduction.
  • Restrictive measures of traffic volume control and were the most effective.

 

ABSTRACT


In December 2015, the Beijing-Tianjin-Hebei (BTH) region experienced several episodes of heavy air pollution. Beijing municipal government therefore issued 2 red alerts on December 7 and 19, respectively, and also implemented emergency control measures to alleviate the negative effects of pollution. It is estimated that the heavy pollutions in 2 red alert periods in Beijing were due mainly to the accumulation of air pollutants from local emission sources and the transboundary transport of pollutants from surrounding areas. The collected meteorological and PM2.5 data indicate that the severity of air pollutions were enlarged by the poor meteorological conditions along with lower mixing layer height. In this study, the WRF-CAMx modeling system was utilized not only for analyzing the contributions of PM2.5 from different sources, but also for quantitatively assessing the effects of implementing various emergency control measures on PM2.5 pollution control during the red alert periods. The modeling results show that local emissions were the most dominant contributors (64.8%–83.5%) among all emission sources, while the main external contributions came from the city of Baoding (3.4%–9.3%). In addition, among 5 different emission source categories, coal and traffic were the two dominant contributors to PM2.5 concentration in urban area of Beijing. Then four pollution control scenarios were designed particularly to investigate the effectiveness of the emergency control measures, and the results show that, generally these emergency control measures have positive effects on air pollution reduction. In particular, restrictive measures of traffic volume control and industrial activity shutdown/suspension have been found as the most effective measures in comparison to other emergency control measures. It is recommended that such effective measures should be considered to implement when next time similar heavy air pollutions occur in the city of Beijing.


Keywords: Beijing; Integrated WRF-CAMx modeling; Red alerts; Emergency control measures


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