This study discusses the concentration characteristics of PM2.5 and PM10, as well as pollution meteorology in large-scale and long-term heavy pollution in the Beijing-Tianjin-Hebei region and its surrounding areas from November 23 to December 4, 2018, where the primary pollutants are comprised of PM2.5 and PM10. The monitoring results obtained from ground-based and vehicle-mounted lidars, as well as the HYSPLIT-4 backward trajectory combined with meteorological factors analysis are discussed. The accuracy and uncertainty of the air quality forecast model of NAQPMS, CMAQ, and CAMx during heavy air pollution were analyzed retrospectively. The results show that PM2.5 and sand dust in most cities in the south-central region contribute to severe pollution levels. The hourly peak concentrations of PM10 in Zhangjiakou, Beijing, Shijiazhuang, Handan, and Zhengzhou were 1589, 864, 794, 738, and 766 μg·m-3, respectively. The respective hourly peak concentrations of PM2.5 were 239, 319, 387, 321, and 380 μg·m-3. Ground static pressure field, high humidity, inversion, and other static and stable conditions, as well as sand dust transmitted from the northwest, were important pollution meteorological and weather factors. The monitoring data of ground-based lidar and vehicle-mounted lidar combined with the HYSPLIT-4 backward trajectory analysis showed that the air pollutant transmitted from the Southwest and Southeast during the heavy pollution period was primarily PM2.5. The air pollutant transmitted from the Northwest during the two sand dust processes. Moreover, the model of NAQPMS, CMAQ, and CAMx performed well in forecasting the heavy pollution process in the Beijing-Tianjin-Hebei region and its surrounding areas. However there are slight deviations for some individual cities, related to uncertainty in the meteorological model prediction, atmospheric chemical reaction mechanism, and pollution source list. Furthermore, the reduction in pollution source emissions caused by pollution emergency measures was also one of the main reasons for the overestimation.
Keywords: Beijing-Tianjin-Hebei region; PM2.5; air pollution meteorology; back trajectory; forecast assessment; lidar; nested air quality prediction modeling system (NAQPMS); sand dust.