Suffered from serious air pollution, Beijing, the capital of China, has implemented multiple measures to reduce the discharge of PM2.5 (particulate matter with aerodynamic diameters of less than 2.5 μm). The average annual PM2.5 concentration of Beijing has shown a continued decline in recent years. However, the improvement was not obvious during the heating season, which had heavier pollution than the non-heating season. Analyzing the spatial distribution of PM2.5 concentrations during heating and non-heating seasons, as well as their spatial differences, is believed to benefit the study of spatial-temporal variation of air pollution and provide scientific reference for the control of air pollution in Beijing. In this study, land use regression (LUR) model was employed to simulate the spatial distribution of PM2.5 concentrations in Beijing during heating and non-heating seasons in 2015. The spatial distribution of the concentration difference between heating and non-heating seasons was analyzed, and the influencing factors were also examined. The results showed that: (1) PM2.5 concentrations during heating and non-heating seasons, as well as their differences, were clearly at a maximum in the south and east of Beijing and at a minimum in the north and west; (2) the area with the biggest concentration difference was situated in a suburban area to the south and east, as well as in outer suburbs to the southeast and northwest; and (3) wind speed, area of transport land and industrial-mining-warehouse land were the main influence factors for the PM2.5 concentration difference in the central, eastern and southern area. Heating activity was not the only cause for the increased PM2.5 concentration during the heating season, vehicle emission, industrial discharge and regional transport of pollutants also played varied roles in PM2.5 pollution in different area.
Keywords: Beijing; Concentration difference; Heating season; Land use regression; PM(2.5).
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