Pollution Patterns And Their Meteorological Analysis All Over China

Fine particulate matter (PM2.5) and ozone (O-3) 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 O-3 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 O-3 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 O-3 was accompanied with dry environments and higher temperature. O-3 contaminated areas were accompanied with low pressures, while the correlation with wind speeds were not so significant. Ocean cyclones seriously affected O-3 pollution levels in the south and along the coast. The two maximum centers of correlation coefficients between O-3 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(O-3) 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.