Contributions to the explosive growth of PM2.5 mass due to aerosol–radiation feedback and decrease in turbulent diffusion during a red alert heavy haze in Beijing–Tianjin–Hebei, China
Hong Wang,Yue Peng,Xiaoye Zhang,Hongli Liu,Meng Zhang,Huizheng Che,Yanli Cheng,and Yu Zheng
State Key Laboratory of Severe Weather (LASW),
Chinese Academy of Meteorological Sciences (CAMS), CMA,
Beijing 100081, China
Collaborative Innovation Center on Forecast and
Evaluation of Meteorological Disasters, Nanjing University of
Information Science & Technology, Nanjing 210044, China
Yue Peng
State Key Laboratory of Severe Weather (LASW),
Chinese Academy of Meteorological Sciences (CAMS), CMA,
Beijing 100081, China
Collaborative Innovation Center on Forecast and
Evaluation of Meteorological Disasters, Nanjing University of
Information Science & Technology, Nanjing 210044, China
State Key Laboratory of Severe Weather (LASW),
Chinese Academy of Meteorological Sciences (CAMS), CMA,
Beijing 100081, China
Yanli Cheng
State Key Laboratory of Severe Weather (LASW),
Chinese Academy of Meteorological Sciences (CAMS), CMA,
Beijing 100081, China
Yu Zheng
State Key Laboratory of Severe Weather (LASW),
Chinese Academy of Meteorological Sciences (CAMS), CMA,
Beijing 100081, China
Collaborative Innovation Center on Forecast and
Evaluation of Meteorological Disasters, Nanjing University of
Information Science & Technology, Nanjing 210044, China
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The explosive growth (EG) of PM2.5 resulted in a PM2.5 maximum, which was generally underestimated by atmospheric chemical models due to the deficient description of the local turbulence intermittent. The aerosol–radiation feedback (AF) and decrease in turbulence diffusion (DTD) may reduce the underestimation of PM2.5 EG by 20–25% and 14–20%, respectively. The modeled EG stage PM2.5 error was decreased from −40 to −51% to −11 to 2% by the combined effects of AF and DTD in Jing–Jin–Ji.
The explosive growth (EG) of PM2.5 resulted in a PM2.5 maximum, which was generally...
