Key Laboratory for Aerosol-Cloud-Precipitation of China
Meteorological Administration, Collaborative Innovation Center on Forecast
and Evaluation of Meteorological Disasters, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese
Academy of Meteorological Sciences, Beijing 100081, China
Key Laboratory for Aerosol-Cloud-Precipitation of China
Meteorological Administration, Collaborative Innovation Center on Forecast
and Evaluation of Meteorological Disasters, Nanjing University of Information
Science & Technology, Nanjing 210044, China
Institute of Urban Meteorology, China Meteorological
Administration, Beijing 100089, China
Wei Wang
China National Environmental
Monitoring Center, Beijing, 100012, China
Qing Hou
Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese
Academy of Meteorological Sciences, Beijing 100081, China
Zengyuan Guo
Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese
Academy of Meteorological Sciences, Beijing 100081, China
Chao Wang
Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese
Academy of Meteorological Sciences, Beijing 100081, China
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The GRAPES–CUACE aerosol adjoint model was developed and applied in detecting PM2.5 sources for haze events in eastern China (EC). The response time of Beijing PM2.5 pollution peaks to local and surrounding emissions is quantized for regional transport of air pollution over the EC. The adjoint results agreed well with the Models-3/CMAQ assessments. The adjoint method is powerful in simulating the receptor–source relationship and can be utilized in dynamic air quality control scheme design.
The GRAPES–CUACE aerosol adjoint model was developed and applied in detecting PM2.5 sources for...
