The rapid urbanization and industrialization in developing countries has had a significant negative impact on the ecological environment, especially causing serious air pollution, which has become an important factor in increasing environmental health risks. Beijing is a highly representative megacity where the smog problem has received widespread attention, so it is very important to accurately monitor and analyze the smog. However, smog pollution has characteristics of long-term and complexity, and the current differences in the temporal and spatial distribution of air pollution levels in Beijing and the explanation of influencing factors are not sufficient. Therefore, we select the PM2. 5 concentrations from 13 stations located in Beijing for air quality monitoring to reveal their spatial heterogeneity at different time scales. Then, cluster analysis and multiple regression analysis are used to fit the concentrations of PM2. 5 through a variety of natural and socio-economic conditions to help explain their influencing factors. The results show that there are obvious seasonal differences in the concentrations of PM2. 5, specifically: winter > autumn > spring > summer. The spatial distribution of PM2. 5 concentration is generally stable across seasons, with high PM2. 5 concentration in the southwest and low PM2. 5 concentration in the northeast. The fitted daily average concentration of PM2. 5 is highly consistent with the data from monitoring stations, indicating that meteorology, population, roads, buildings and NDVI all have explanatory power on the variation of PM2. 5 concentration.
