全国2018~2019年秋冬季气象条件变化对PM2.5影响研究

本文基于WRF-CMAQ模型定量分析了气象条件变化对PM_2.5的影响.全国337个城市2018~2019秋冬季气象条件转差导致PM_2.5平均浓度同比上升约5.55%.24个省市气象条件同比转差,北京气象转差致使PM_2.5同比上升约3.66%.从重点区域来看,京津冀及周边“2+26”城市气象条件转差最显著,汾渭平原次之,长江三角洲（以下称长三角）基本持平,分别导致PM_2.5浓度同比上升约9.4%、8.3%、1.1%.“2+26”城市和汾渭平原气象条件在11月、1月、2月转差,10月、3月气象条件转好.长三角则10月、11月、3月气象条件转差;12月、1月、2月转好.“2+26”城市2018~2019秋冬季PM_2.5浓度同比上升主要为气象条件转差所致;汾渭平原PM_2.5同比变化较小,人为减排有效抵消了气象条件转差带来的不利影响;长三角PM_2.5浓度同比下降,与气象条件变幅小且污染排放较去年同期降低有关.

Impact of meteorological conditions on PM2.5 in autumn and winter of 2018~2019 in key areas

The impact of meteorology variation on PM_2.5 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 PM_2.5 concentration national wide. The meteorological condition of 24 provinces out of 31 got worse from the PM_2.5 pollution point of view. The PM_2.5 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 PM_2.5 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 PM_2.5 concentration in "2+26" cities, while the greater emission reduction and small meteorological condition variation led to drop of PM_2.5 concentration in YRD.