分钟降水量对能见度及PM_(2.5)浓度影响研究

Impact of Precipitation on Atmospheric Visibility and the PM_(2.5) Concentration Based on the Minute-Scale High-Resolution Observations

为清楚认识降水对能见度及PM_(2.5)浓度的影响,以杭州为例,采用2014—2015年逐分钟气象观测资料,对比分析了不同降水条件下能见度及PM_(2.5)浓度的分布特征,建立了不同强度降水影响能见度及PM_(2.5)浓度的定量关系。研究结果表明降水量大小及持续时间对能见度与PM_(2.5)浓度有明显作用,不仅持续稳定的降水过程能够造成持续的低能见度,突发性强降水更能造成能见度大幅降低;降水与能见度之间关系符合幂函数分布特征,能见度随降水量增加从快速下降过渡到慢速下降,中间存在一个拐点。降水对PM_(2.5)的清除作用受降水量及降水前PM_(2.5)浓度大小共同作用,降水对PM_(2.5)的清除作用在降水较小并持续时,会造成PM_(2.5)浓度的缓慢下降;而强降水过程对PM_(2.5)的清除作用十分明显,降水量、PM_(2.5)浓度、能见度三者之间表现出基本一致的同步变化。基于降水量与降水前PM_(2.5)浓度两个因子,采用非线性拟合方案构建了降水影响PM_(2.5)浓度的定量统计模型,拟合结果与实况较为吻合,说明模型抓住了降水情景下影响PM_(2.5)浓度变化的关键因子。最后针对研究中存在的不足和未来值得进一步发掘的科学问题进行了讨论。

To explicitly investigate the influence of precipitation on visibility and PM2.5 concentration, mi- nute-scale observations of Hangzhou during 2014-2015 are used to comparatively analyze the distribution characteristics of visibility and PM2.5 concentration under different levels of precipitation, and, furthermore, the quantitative impacts of precipitation with different intensities on visibility and PM2.5 concentration are studied. The results indicate that the intensity and duration of precipitation can significantly modulate visibility and PM2.5 concentration. Consistent and stable rainfall are easy to trigger long low-visibility scenario, and the sudden heavy precipitation is an important factor inducing the sharp-decrease of visibility. With the rise of rainfall, the visibility changes from rapid-decline to slow-decline and there exists an inflection point. The removing effect of precipitation on PM2.5 concentration can be mediated by the intensity of rainfall and the PM2. 5 concentration before raining. When there is modest/small rainfall, the removing effect usually occurs several time later. However, heavy precipitation is able to remove PM2. 5 quickly. Basically, synchronous changes among precipitation, PM2.5 concentration and visibility can appear. Based on the two factors of precipitation intensity and PM2.5 concentration before raining, a quantitative statistical model reflecting the technology, and the influence of rainfall on PM2.5 concentration is constructed with the non-linear fitting modeling results agree well with observations. Finally, the existing limitations and some scientific issues which need further exploring in the future are discussed.