Dongsheng Chen 1, Tingting Xu1, Yue Li2, Ying Zhou1, Jianlei Lang1, Xiangxue Liu1, Huading Shi3

  • 1 Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing 100124, China
  • 2 Transport Planning and Research Institute, Ministry of Transport, Beijing, China
  • 3 Chinese Research Academy of Environmental Sciences, Beijing, China

Received: October 30, 2014
Revised: December 14, 2014
Accepted: February 13, 2015
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Cite this article:
Chen, D., Xu, T., Li, Y., Zhou, Y., Lang, J., Liu, X. and Shi, H. (2015). A Hybrid Approach to Forecast Air Quality during High-PM Concentration Pollution Period. Aerosol Air Qual. Res. 15: 1325-1337.


  • Hybrid approach applies WRF and statistical analysis to forecast PM10 was developed.
  • This approach was used to forecast daily PM10 in Beijing throughout the year 2013.
  • CMAQ was also used to forecast the daily PM10 in Beijing in the same period.
  • Hybrid approach shows significant improvement during high-PM concentration period.



In this study, a hybrid approach of combining numerical prediction with statistical analysis was proposed to forecast high-PM10 (aerosol particle with aerodynamic diameter less than 10 μm) concentration events in Beijing, China. This approach was used to forecast the daily PM10 in Beijing from January 1 to December 30, 2013. The WRF-CMAQ modeling system was also applied to simulate Beijing’s PM10 in the same period. The performance of the two methods was then assessed according to the mean bias (MB), normalized mean bias (NMB), normalized mean gross error (NME), mean normalized bias (MNB), mean normalized gross error (MNE), and root mean square error (RMSE). The results demonstrate that both methods perform well during low-PM10 concentration periods (PM10 concentration < 250 μg/m3), the MB, NMB, NME, MNB, MNE and RMSE for hybrid approach during low-PM10 concentration periods were 26.15, 24.88%, 41.94%, 43.23%, 56.35% and 61.67, respectively. The MB, NMB, NME, MNB, MNE and RMSE for CMAQ during low-PM10 concentration periods were –6.04, 57.47%, 41.49%, 21.52%, 55.64% and 60.11, respectively. While the MB, NMB, NME, MNB, MNE and RMSE for CMAQ during high-PM10 concentration periods (PM10 concentration ≥ 250 μg/m3) were –162.87, –50.37%, 50.37%, –49.86%, 49.86% and 175.93, respectively. The MB, NMB, NME, MNB, MNE and RMSE for hybrid approach during high-PM10 concentration periods were –30.3, –9.37%, 23.21%, –8.21%, 24.25% and 97.37, respectively. The hybrid approach shows significant improvement in accuracy during high-PM10 concentration periods.

Keywords: Particulate matter; Air pollution; Numerical simulation; Forecast system; Statistical analysis

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