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| Impact of meteorological conditions on PM2.5 in autumn and winter of 2018~2019 in key areas |
| SHI Xu-rong1, LU Shi-ze2, YI Ai-hua3, XUE Wen-bo1,4, LEI Yu1, YAN Gang1, WANG Yan-li1 |
1. Center for Regional Air Quality Simulation and Control, Chinese Academy for Environmental Planning, Beijing 100012, China;
2. School of Environment, Tsinghua University, Beijing 100084, China;
3. The Appraisal Center for Environment and Engineering, Ministry of Ecology and Environment, Beijing 100012, China;
4. State Key Laboratory of Environmental Planning and Policy Simulation, Beijing 100012, China |
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Abstract The impact of meteorology variation on PM2.5 concentration in autumn and winter of 2018~2019 in China was quantified with WRF-CMAQ model. Compared with the previous autumn and winter, the worse meteorological conditions in 2018~2019 led to 5.55% increase of average PM2.5 concentration national wide. The meteorological condition of 24 provinces out of 31 got worse from the PM2.5 pollution point of view. The PM2.5 concentration in Beijing rose by 3.66% due to worse meteorological condition. Among the three key regions, the "2+26" cities was the most unfavorable in terms of the meteorological conditions, which led to the increase of PM2.5 concentration by 9.4% compared with last year, followed by Fenwei plain (8.3%) and Yangtze River Delta(1.1%). The meteorological conditions of "2+26" cities and Fenwei plain were not favorable in November, January and February, and favorable in October and March. For Yangtze River Delta, the unfavorable meteorological condition took place in October, November and March, while the favorable months were December, January and February. Efforts of abating emissions somehow offset the adverse effects from the worse weather condition in Fenwei plain. The worse meteorological condition dominated the change of PM2.5 concentration in "2+26" cities, while the greater emission reduction and small meteorological condition variation led to drop of PM2.5 concentration in YRD.
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Received: 10 December 2019
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