Investigation of variations, causes and component distributions of PM2.5 mass in China using a coupled regional climate-chemistry model

Abstract

China experiences severe particulate matter (PM) pollution. Although a monitoring network for PM2.5 (diameter < 2.5 μm) has been set up in more than 100 major Chinese cities, insufficient spatial coverage of observations limits the study of the temporal and spatial characteristics, influencing factors, and component of PM2.5. In this study, we conducted a one year air quality simulation using a regional climate–chemistry model and evaluated the simulation's performance based on in situ observations concerning meteorological elements and PM2.5 concentrations. The simulated results showed that, higher PM2.5 concentrations appeared in northern China and the Sichuan Basin, and the maximal value occurred in winter. Furthermore, Vertical PM2.5 concentrations presented a gradual decreasing trend from the surface, whereas in southern coastal cities the profiles were unsteady with a secondary peak in the lower layer. Meteorological conditions were conducive to both pollutant diffusion and removal in summer, whereas stagnant conditions appeared in winter, characterized by high sea level pressure (SLP), the lowest planetary boundary layer height (PBLH), and 2-m temperature (T2). In provincial capital cities, PM2.5 was positively correlated with residential emissions but negatively correlated with precipitation, 10-m wind speed, T2, PBLH, and industrial emissions. Finally, we utilized the simulation results to investigate the component variations of PM2.5. Results indicated that primary PM2.5 components had significantly higher concentrations in northern China where residential heating is the major source of PM2.5 emissions, whereas they had lower concentrations in southern China. Secondary components played a crucial role in PM2.5 mass in eastern China. This study provided a clear perspective of seasonal variations, horizontal and vertical distributions of PM2.5 and its components and influence factors, which could be used in subsequent studies to investigate the formation mechanism and emission sources of PM2.5.