Spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing, China.

Fine particulate matter (PM2.5) pollution has become a worldwide environmental concern because of its adverse impacts on human health. This study aimed to explore the spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing during the 2013-2018 period, and further analyzed the impacts of environmental protection policies implemented in recent years. Notably, this study employed various statistical methods, i.e., ordinary Kriging interpolation, spatial autocorrelation analysis, time-series analysis and the Bonferroni test, to evaluate the regional and seasonal differences of PM2.5 concentrations based on long-term monitoring data. The results illustrated that PM2.5 concentrations decreased on a yearly basis, demonstrating that air pollution control policies have achieved initial success. Furthermore, PM2.5 concentrations were higher in the winter and in the southern regions. Diurnal variation presented a bimodal distribution, which varied slightly with the season. Relative humidity and wind speed were the principal meteorological factors affecting the distribution of PM2.5 concentrations, while precipitation had essentially no effect. A high positive correlation between PM2.5 and gaseous pollutants (SO2, NO2, and CO) indirectly reflected the contribution of automobile exhaust and coal-fired emissions. Generally, PM2.5 concentrations demonstrated strong spatiotemporal variations, and meteorological factors and pollutant emissions played an important role in this.