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Formation Mechanism of a Large-Scale Heavy Pollution Process in North China in Winter Based on Numerical Simulation and Statistical Fitting
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    Abstract:

    Using the WRF/Chem (Weather Research Forecasting/Chemistry) model, a large-scale PM2.5 heavy pollution process in northern China from 25 November to 2 December 2015 was simulated. Comparisons to observations show that the model can realistically capture the magnitude and variation of PM2.5 and meteorological factors, and can be used for the mechanism analysis of this pollution event. This paper further analyzed the mechanism of the strong pollution event from the aspects of dynamics, thermo-meteorological conditions, and chemical transformation. The results show that the dynamic factors mainly affect the pollution event through weakening of the surface wind and vertical wind shear. Thermal factors, such as a boundary layer inversion, promote the enhancement of the atmospheric stability, which is not conducive to pollutant diffusion. Based on the analysis of the PM2.5 composition, the nitrate, sulfate, and organic carbon content increased in this event, indicating that the secondary aerosol formation caused by vehicle exhaust and coal combustion contributes greatly to the PM2.5 pollution. To identify the main factors causing this pollution event, we used multiple linear regression and relative contribution rate accounting methods to quantify the multi-factor analysis. The results show that the thermal factors play a major role in the pollution process, with a variance contribution of 52%, dynamic factor of 34%, and a chemical transformation variance contribution of 14%, indicating that adverse meteorological conditions, especially thermal conditions, are the main causes of the pollution event.

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秦楚菲,孙家仁,张文君,廖志恒,滕宇威,陈朋龙,陈静华.2020.基于数值模拟和统计拟合分析华北冬季一次大范围重污染过程的形成机理[J].气候与环境研究,25(2):185-198. QIN Chufei, SUN Jiaren, ZHANG Wenjun, LIAO Zhiheng, TENG Yuwei, CHEN Penglong, CHEN Jinghua.2020. Formation Mechanism of a Large-Scale Heavy Pollution Process in North China in Winter Based on Numerical Simulation and Statistical Fitting[J]. Climatic and Environmental Research (in Chinese],25(2):185-198.

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History
  • Received:January 11,2019
  • Revised:
  • Adopted:
  • Online: April 02,2020
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