Liu Na, Yu Ye, Ma Xue-Qian
Qinghai Provincial Key Laboratory of Disaster Prevention and Reduction, Qinghai Weather Modification Office, Xining 810001, China.
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China.
Huan Jing Ke Xue. 2021 Mar 8;42(3):1268-1279. doi: 10.13227/j.hjkx.202007183.
Based on the analysis of seasonal characteristics of PM and PM 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 PM and PM 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 PM and PM 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.
基于对2016年至2018年西宁PM和PM颗粒物质量浓度季节特征的分析,利用混合单粒子拉格朗日积分轨迹(HYSPLIT)模型和全球数据同化系统(GDAS)数据计算了每日72小时后向轨迹。通过对四个季节的聚类分析,确定了PM和PM的主要传输路径并分析了其特征。使用潜在源贡献函数(PSCF)模型和TrajStat软件提供的浓度加权轨迹(CWT)方法确定了潜在源区及其贡献。结果表明,源区大多分布在西宁周边及相邻地区的西北和东北地区且高度较低。西宁市区的传输路径主要受来自西部、西北部、西南部和东部气流的影响。出现概率最高的轨迹特征为距离短、高度低、移动速度慢,春季、夏季和秋季起源于青海,冬季起源于新疆,且以内省传输为主。不同的传输轨迹对PM和PM浓度有不同影响。污染气流主要源于青海内部源、新疆外部源以及新疆西部境外源,所有源区均位于沙漠或戈壁地区。潜在源区的分布和贡献存在明显的季节差异,冬季分布最广、贡献最大,其次是春季和秋季,夏季最小。最重要的潜在源区位于青海北部、中部和东部以及新疆南部、中部和东部,而周边地区是中等贡献的潜在源区。