Seasonal Characteristics of Air Pollutant Sources and Transport Pathways in Xining City

Abstract

Based on the analysis of seasonal characteristics of PM10 and PM2.5 particle mass concentrations in Xining from 2016 to 2018, the daily 72 hour backward trajectories were calculated using the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model and global data assimilation system (GDAS) data. The main transport pathways of PM10 and PM2.5 were identified and their characteristics were analyzed by clustering analysis for four seasons. The potential source regions and their contributions were defined using the potential source contribution function (PSCF) model and the concentration-weighted trajectory (CWT) method provided by TrajStat software. Results indicated that the sources were mostly distributed in the north-west and north-east regions and heights were low in the surrounding and adjacent areas of Xining. The transport pathways were mainly affected by airflows from the west, northwest, southwest, and east in Xining city. The trajectories with the highest probability of occurrence were characterized by short distance, low height, and slow-moving speed, originated from Qinghai in spring, summer and autumn, but from Xinjiang in winter, and was dominated by intra-provincial transportation. Different transport trajectories had different effects on PM10 and PM2.5 concentrations. Polluted airflows mainly originated from internal sources in Qinghai, external sources in Xinjiang, and foreign sources in the west of Xinjiang, with all the source regions located in deserts or Gobi areas. Obviously seasonal differences existed in the distribution and contribution of the potential source areas, with the widest and largest contribution in winter, followed by spring and autumn, and the smallest in summer. The most important potential source regions were located in northern, central, and eastern Qinghai, and southern, central, and eastern Xinjiang, while the surroundings were potential source regions for medium contribution.