PM2.5 concentration distribution patterns and influencing meteorological factors in the central and eastern China during 1980-2018

Abstract The long-term global record of surface PM2.5 mass concentration is one of the important products from the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). This long-time record began in the 1980s, whereby MERRA-2 has facilitated the study of the interactions between air pollution and climate change in China. In this study, the principal component analysis (PCA) method was applied to classify the PM2.5 concentration distribution representing the primary states. It was also used to investigate relationships between PM2.5 pollution distribution types and atmospheric circulation based on NASA MERRA-2 surface PM2.5 mass concentration and ERA-5 reanalysis data. The distribution of the PM2.5 concentrations in the central and eastern China over the winter was classified into five types. A typical pollution model (Type 2) was linked to the decrease in sea-land temperature differences as a result of increasing in land temperature, weakened air flow, reduced precipitation, stable vertical temperature, and relative humidity formation. For the typical clean models (Types 3 and 4), the meteorological conditions differed greatly from those of Type 2. Type 3 was related to the thermal effects of the Qinghai-Tibet Plateau, causing the diffusion conditions in the bottom layer in eastern China and being detrimental to pollution accumulation. Type 4 was related to good pollution diffusion conditions, caused by cold air and high pressure. Types 1 and 5 represent marginal pollution that are closely related to precipitation, pollution transport, temperature, and the vertical structure of relative humidity. A Gaussian log-likelihood mutation test of PM2.5 concentration time series data in the central and eastern China showed that the mutation point appeared around the year 2000. This is related to the increasing impacts of climate change, such as rising land temperature and falling sea level pressure. This study provides new insights into the relationship between the distribution types of PM2.5 pollution and atmospheric circulation; it elucidates the potential dynamic mechanisms controlling the severity and distribution of heavy air pollution.