乌鲁木齐地区PWV对PM2.5的影响趋势分析及预测

Trend analysis and prediction of influence of PWV on PM2.5 in Urumqi

针对当前我国部分地区雾霾频发,而传统雾霾监测手段存在花费高、时空分辨率低等局限性,无法及时准确地掌握雾霾天气的发生时间等问题,提出1种利用全球卫星导航系统(GNSS)技术反演的可降水量(PWV)监测雾霾方法:重点分析乌鲁木齐地区几次雾霾天气前后空气中大气可降水量值及其变化特征;对获得的国际GNSS服务组织(IGS)站数据进行解算得到的大气可降水量与雾霾指数即大气中粒径小于等于2.5微米的颗粒物(可入肺颗粒物(PM2.5))对比分析,发现PWV与PM2.5具有强相关性;并综合考虑其他气象因素,建立多元线性回归分析模型,实现对雾霾的预测。研究结果表明:雾霾形成过程中PM2.5质量浓度与大气可降水量变化密切相关,有显著的正相关性;结合实际天气条件,利用GNSS水汽资料建立的多元线性回归分析模型可实现对雾霾天气的预测。

Aiming at the problems that there is a frequent occurrence of haze in some regions of China,and there exist limitations in traditional haze monitoring methods,such as high cost and low spatial and temporal resolution,and the inability to grasp the occurrence time of haze weather in a timely and accurate manner,the paper proposed a haze monitoring method that uses GNSS technology to invert precipitation(PWV):the analysis of atmospheric precipitation before and after several times of haze weather in Urumqi and its change characteristics was focused;through the comparative analysis of atmospheric precipitation and haze index PM2.5 obtained by calculating the data of several IGS stations,the strong correlation between PWV and PM2.5 was found;and the establishment of multiple linear regression analysis model for haze prediction was achieved by taking other meteorological factors into consideration.Study results showed that:PM2.5 mass concentration would be closely related to the change of atmospheric precipitation during the formation of haze,with a significant positive correlation;combined with the actual weather conditions,the multiple linear regression analysis model established with GNSS water vapor data could be used to predict the haze weather efficiently.