利用HYSPLIT4模式和全球资料同化系统(GDAS)气象数据,计算了2010年12月-2011年11月期间抵达上海的气流后向轨迹.结合聚类方法和上海ρ(SO2)、ρ(NO2)、ρ(PM10)数据,分析了各季节不同类型气流轨迹对污染物浓度的影响,利用引入权重因子后的潜在源贡献算法分析了不同季节PM10和NO2潜在WPSCF(源区分布概率)特征.结果表明:上海气流输送季节变化特征明显.冬、春和秋季,上海较易受到来自西北、西南等区域的大陆性气流影响,受沙尘或人为污染排放的影响相对较大,ρ(PM10)、ρ(SO2)和ρ(NO2)平均值相对较高,分别为162、74和53 μg/m3.夏季上海主要受较清洁的海洋性气流影响,ρ(PM10)、ρ(SO2)和ρ(NO2)相对较低,分别为47、19和36 μg/m3.上海PM10和NO2的WPSCF分布特征类似,在冬、春和秋季,WPSCF高值(0.2 ～0.4)主要集中在江苏南部,河南、安徽等地的带状区域也有一定贡献,说明这些区域是上海这2种污染物的潜在源区.夏季WPSCF的分布较为集中,上海以外区域值基本小于0.1,说明外来污染输送的贡献较小.%HYSPLIT4.9 as a trajectory model and Global Data Assimilation System (GDAS) meteorological data were used to compute the backward air flow trajectories from December 2010 to November 2011. This study focused on four seasons. Analysis of the effect of different seasons and trajectories on various pollutants based upon cluster analysis and corresponding pollutants concentration such as SO2, NO2 and PM10 was conducted, In addition, the potential contribution algorithm combined with weight factors ( WPSCF) was utilized to study the spatial probability distribution of PM10 and NO2 area sources for four seasons. The results showed the direction of the air flow in Shanghai was associated with temporal changes, Northwestern and southwestern winds were dominant in autumn, winter and spring. There would be a significant impact on Shanghai, when a trajectory passed through major anthropogenic emission areas. This phenomenon occurred in high ρ(PMl0) , ρ( SO2 ) and ρ(NO2) values, which is 162, 74 and 53 μg/m3. During summer, ρ(PM10), ρ(SO2) and ρ( NO2) were relatively lower due to cleaner air from the ocean, which is 47 , 19 and 36 μg/m3 . In seasons of autumn, winter and spring, Shanghai has a similar probability distribution characteristic as in those PM10 and SO2 sources areas. High WPSCF values (0. 2-0. 4) were concentrated in the south of Jiangsu province. Furthermore, contribution from Inner Mongolia, Henan, and Anhui provinces could not be ignored since the study revealed that these regions are the potential sources of PM10 and NO2 in Shanghai. In summer, WPSCF value outside Shanghai was almost lower than 0. 1, which demonstrates the contribution from area outside of Shanghai is insignificant.
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