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研究报告

摘要：分析2012-2016年上海徐家汇站的雨量和颗粒物（PM₁、PM_2.5、PM₁₀）观测数据发现，降雨对PM_2.5的湿清除作用明显，降雨日的PM_2.5质量浓度较非降雨日平均降低约30%，在污染季节降低更加显著约50%.降雨时PM₁在PM_2.5中的占比明显下降，PM₁质量浓度下降幅度占PM_2.5下降幅度的84%，表明降雨对PM₁的有效清除是PM_2.5质量浓度下降的主要原因.降雨过程结束后PM_2.5质量浓度是否下降和降雨前PM_2.5的初始质量浓度关系密切，当初始浓度在冬季大于70 μg·m^-3、在其他季节大于45 μg·m^-3时，80%以上的降雨过程结束后PM_2.5质量浓度较降雨前下降，因此可作为研判降雨过程对PM_2.5湿清除影响的预报因子.

Abstract：The effect of wet scavenge of PM_2.5 by rainfall in Shanghai, China is analyzed. The analysis includes the in-situ measurements of precipitation and particulate matter (PM₁, PM_2.5 and PM₁₀) from 2012-2016 at Xujiahui in downtown Shanghai. The results show that precipitation plays an important role in reducing PM_2.5 mass concentration. For example, the mean PM_2.5 mass concentration on rainy days decreases about 30% compared with non-rainy days, with a maximum reduction of 50% in winter. The ratio of mass concentration between PM₁ and PM_2.5 also significantly decreases on rainy days. The reduced PM₁ mass concentration contributes 84% to the PM_2.5 reduction, suggesting that wet scavenge is more effective for smaller particles than large particles. Therefore, the decrease in PM_2.5 concentrations on rainy days is mostly attributed to the effective wet scavenge of PM₁. The PM_2.5 tendency related to rainfall is closely associated with the initial PM_2.5 level prior to precipitation. There are about 80% of the rainfall processes leading to PM_2.5 decreasing under the condition that the initial PM_2.5 mass concentration is above 70 μg·m^-3 in winter and 45 μg·m^-3 in other seasons, which could be considered as a predictor for forecasting the PM_2.5 tendency due to precipitations.