Pollution patterns and their meteorological analysis all over China. (1st February 2021) - Zhou, Lihua; Zhang, Jing; Lu, Tianwei; Bao, Mengying; Deng, Xiaoqing; Hu, Xiaomin
Abstract: Fine particulate matter (PM2.5 ) and ozone (O3 ) are the two important pollutants because of their harmfulness. In addition to pollution emission level and location, meteorological factors affect the distribution of extreme pollution, so analysing the weather fields under extreme pollution is of great significance to predict extreme pollution. In this study, based on PM2.5 and O3 atmospheric composition monitoring data from China National Environmental Monitoring Center (CNEMC) Network and daily meteorological data from Version 2 of Climate Forecast System of National Centers for Environmental Protection (NCEP) Climate Forecast System, the distribution types of wintertime PM2.5 and summertime O3 pollution in China from 2015 to 2019 were classified with Empirical orthogonal function (EOF) method, and the types of weather characteristics were analyzed, respectively. The results showed that the distribution of extreme pollution and the distribution of meteorological fields had a good correspondence. High PM2.5 was accompanied with high relative humidity (RH), higher temperature (T), low pressures (P) and low wind speeds (W). The two maximum centers of correlation coefficients between PM2.5 and the atmospheric circulation field were located on Siberia and the east of Japan. High O3 was accompanied with dry environments and higher temperature. O3 contaminated areas were accompanied with low pressures, while the correlation with wind speeds were not so significant. Ocean cyclones seriously affected O3 pollution levels in the south and along the coast. The two maximum centers of correlation coefficients between O3 mass concentration and 500 hPa geopotential height were located on the east of Lake Baikal and southern China. The relevant indexes established in the key areas had all passed the significance test and had an indicative significance for forecasting the pollution level. We believe that the apparent correlations between PM2.5 (O3 ) and RH, T, as well as W related to the external factors associated with the life cycle of midlatitude mesoscale weather system, rather than the underlying direct internal cause. Highlights: Different pollution patterns of PM2.5 and O3 are obtained by EOF. RH, T, P and W fields corresponding to different pollution distributions are presented. Meteorological conditions are external factors that affect the area and frequency of pollution. The key area of 500 hPa affecting PM2.5 is on Siberia and the east of Japan. The key area of 500 hPa affecting O3 is on the east of Lake Baikal and southern China.