[Spatio-temporal Variation, Meteorological Condition, and Regional Transport Characteristics of PM_2.5 Pollution...

Based on PM_2.5 monitoring data, meteorological observation data, and a CMAQ-ISAM air quality model, the spatio-temporal variation, meteorological conditions, and regional transport characteristics of 108 PM_2.5 pollution events in Beijing from 2018 to 2022 were analyzed. The results showed that the frequency, the mean concentration, and the peak concentration of PM_2.5 pollution events demonstrated a significant decrease and the decrease degree of moderate and heavy pollution events was significantly larger than that of light pollution events. From the seasonal perspective, the PM_2.5 pollution events nearly disappeared in summer, however, were severe in other seasons. According to the diurnal variation curves, PM_2.5 concentration during heavy pollution events decreased significantly from daytime to the first half of night and did not decrease notably in the second half of the night. In the past five years, the mean concentration of PM_2.5 pollution events was higher in the southeast and lower in the northwest, with the highest in the Beijing Economic and Technological Development Area and the lowest in Yanqing District. From the perspective of spatial evolution, the mean concentration in all districts significantly decreased from 2018 to 2022, with a decrease range of 13-31 μg·m^-3 and a decrease percentage of 11%-25%； the frequency in all districts also decreased significantly, with a decrease range of 35-52 days and a decrease percentage of 56%-68%. The mean wind speed, mean relative humidity, and northwest wind frequency were the three most important meteorological factors that had an impact on PM_2.5 concentration in Beijing. For polluted days, the mean wind speed was 1.6 m·s^-1, the mean relative humidity was 62.4%, and the frequency of northwest wind was 3%. Most of the pollution events began from Eastern Beijing and Southern Beijing. Compared to those throughout the whole city, PM_2.5 pollution events usually occurred 12 hours earlier at the southeast border station and 10, 8, and 5 hours earlier at the southern, southwest, and eastern border stations, respectively. During PM_2.5 pollution events in Beijing, the local contribution was 34%, and the transport contribution was 66%. Out of all nearby provinces, Hebei had the biggest contribution of 33%. With regard to cities, Baoding, Langfang, Tianjin, and Tangshan had the most prominent impact on Beijing's PM_2.5 pollution events, accounting for 9%, 6%, 5%, and 5% of the contribution, respectively. When it comes to transport pathways, the southeast pathway contributed 24% and the southwest pathway contributed 23%. The government must establish a regional joint prevention and control mechanism.