Journal of Meteorological Research

, Volume 32, Issue 1, pp 49–59 | Cite as

Tracking a Severe Pollution Event in Beijing in December 2016 with the GRAPES–CUACE Adjoint Model

  • Chao Wang
  • Xingqin An
  • Shixian Zhai
  • Zhaobin Sun
Special Collection on the Heavy and Persistent Haze-Fog Episodes in Winter 2016/17 in the Beijing-Tianjin-Hebei Area of China


We traced the adjoint sensitivity of a severe pollution event in December 2016 in Beijing using the adjoint model of the GRAPES–CUACE (Global/Regional Assimilation and Prediction System coupled with the China Meteorological Administration Unified Atmospheric Chemistry Environmental Forecasting System). The key emission sources and periods affecting this severe pollution event are analyzed. For comaprison, we define 2000 Beijing Time 3 December 2016 as the objective time when PM2.5 reached the maximum concentration in Beijing. It is found that the local hourly sensitivity coefficient amounts to a peak of 9.31 μg m–3 just 1 h before the objective time, suggesting that PM2.5 concentration responds rapidly to local emissions. The accumulated sensitivity coefficient in Beijing is large during the 20-h period prior to the objective time, showing that local emissions are the most important in this period. The accumulated contribution rates of emissions from Beijing, Tianjin, Hebei, and Shanxi are 34.2%, 3.0%, 49.4%, and 13.4%, respectively, in the 72-h period before the objective time. The evolution of hourly sensitivity coefficient shows that the main contribution from the Tianjin source occurs 1–26 h before the objective time and its peak hourly contribution is 0.59 μg m–3 at 4 h before the objective time. The main contributions of the Hebei and Shanxi emission sources occur 1–54 and 14–53 h, respectively, before the objective time and their hourly sensitivity coefficients both show periodic fluctuations. The Hebei source shows three sensitivity coefficient peaks of 3.45, 4.27, and 0.71 μg m–3 at 4, 16, and 38 h before the objective time, respectively. The sensitivity coefficient of the Shanxi source peaks twice, with values of 1.41 and 0.64 μg m–3 at 24 and 45 h before the objective time, respectively. Overall, the adjoint model is effective in tracking the crucial sources and key periods of emissions for the severe pollution event.


GRAPES–CUACE adjoint model winter heavy pollution pollution source adjoint tracking sensitivity analysis Beijing 


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Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Chao Wang
    • 1
    • 2
  • Xingqin An
    • 1
    • 2
  • Shixian Zhai
    • 3
  • Zhaobin Sun
    • 4
    • 5
  1. 1.Institute of Atmospheric CompositionChinese Academy of Meteorological SciencesBeijingChina
  2. 2.State Key Laboratory of Severe Weather/Key Laboratory of Atmospheric Chemistry of China Meteorological AdministrationChinese Academy of Meteorological SciencesBeijingChina
  3. 3.Key Laboratory for Aerosol–Cloud–Precipitation of China Meteorological AdministrationNanjing University of Information Science & TechnologyNanjingChina
  4. 4.Institute of Urban MeteorologyChina Meteorological AdministrationBeijingChina
  5. 5.Environmental Meteorology Forecast Center of Beijing–Tianjin–HebeiChina Meteorological AdministrationBeijingChina

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