利用全球数据同化系统 (GDAS) 气象资料和生态环境部环境监测总站的 PM2.5 浓度数据, 使用 MeteoInfo 软件和 TrajStat 插件的聚类方法和聚类统计对 2018 年 12 月-2019 年 1 月到达伊宁市主城区的气流轨迹进行了聚类分析, 运用潜在源贡献 (PSCF) 及浓度权重轨迹 (CWT) 分析了伊宁市主城区 PM2.5 潜在源贡献率 (WPSCF) 和轨迹权重浓度 (WCWT)。 结果显示: a) 轨迹聚类分析表明该区受西南气团影响最大, 主要来自哈萨克斯坦和吉尔吉斯斯坦; b) WPSCF 和 WCWT 分布特征类似, 重度污染源区 WPSCF 最高在 0.7～0.8 以上, WCWT 最高值在 80～110 μg·m-3, 潜在源主要集中在昭苏-特克斯盆地。

Based on the meteorological data of Global Data Assimilation System (GDAS) and PM2.5 concentration data from the China National Environmental Monitoring Station of the Ministry of Ecology and Environment, using MeteoInfo and TrajStat plug-in, a cluster analysis on the airflow trajectory reaching the main urban area of Yining City, China, from December 2018 to January 2019 was carried out, and then the weighted potential source contribution probability (WPSCF) and the weighted concentration weight trajectory (WCWT) of PM2.5 in the main urban area of Yining City was analyzed by using potential source contribution function (PSCF) analysis and concentration weighted trajectory model (CWT) analysis. The results show that: a) Trajectory clustering shows that the region is most affected by the southwest air mass, mainly from Kazakhstan and Kyrgyzstan. b) The WPSCF and WCWT distribution feature are similar, and the highest WPSCF and WCWT in the heavily polluted source area are above 0.7～0.8 and 80～110 μg·m-3 respectively, which are mainly concentrated in Zhaosu-Tekes Basin.