苏州市GNSS气象要素与雾霾的相关性分析  

Correlation Analysis between GNSS Meteorological Elements and Haze in Suzhou City

作　　者：张明松 李黎 马乙翔 潘建平 李锴 申文瑜 ZHANG Mingsong;LI Li;MA Yixiang;PAN Jianping;LI KaiSHEN Wenyu(Research Center of Beidou Navigation and Environmental Remote Sensing,Suzhou University of Science and Technology,Suzhou 215009,China)

机构地区：[1]苏州科技大学北斗导航与环境感知研究中心,苏州市215009

出　　处：《大地测量与地球动力学》2024年第11期1142-1147,共6页Journal of Geodesy and Geodynamics

基　　金：江苏省研究生实践创新项目(SJCX23_1718,SJCX24_1901);江苏省科技计划(BK20230660);国家自然科学基金(42204014)。

摘　　要：基于2021~2022年苏州市GNSS站大气可降水量(PWV)、气温、气压和风速等气象要素及其邻近环境监测站的空气质量资料,分析不同季节和降水条件下各GNSS气象要素与PM_(2.5)的相关性及其时序变化特征。结果表明,GNSS气象因素与PM_(2.5)时序变化均呈现季节性特征,PWV、ZTD、气温、风速与PM_(2.5)呈负相关,相关系数分别为-0.389、-0.389、-0.289和-0.318,气压、相对湿度与PM_(2.5)呈正相关,相关系数分别为0.250和0.017,可见PWV、ZTD、气温、气压和风速等是影响PM_(2.5)的主要因素;雾霾发生时,PWV和相对湿度较高,导致PM_(2.5)汇聚,使PWV和相对湿度与PM_(2.5)的正相关系数分别增大29.14%和96.99%;降雨可大幅降低PM_(2.5)浓度,相对湿度与PM_(2.5)的相关系数增大90.39%;小波分解重构后的GNSS气象要素与PM_(2.5)的相关性有显著提高,能更清晰地反映出GNSS气象要素与PM_(2.5)的整体变化趋势。Based on the meteorological elements of precipitable water vapor(PWV),temperature,air pressure,and wind speed at GNSS station,and air quality data at neighboring environmental monitoring station in Suzhou city from 2021 to 2022,we analyze the temporal variation characteristics and their correlations between GNSS meteorological elements and PM_(2.5)under different seasons and precipitation conditions.The results show that GNSS meteorological elements and PM_(2.5)display seasonal variations.The PWV,ZTD,temperature,and wind speed are negatively correlated with PM_(2.5),their correlation coefficients are-0.389,-0.389,-0.289,and-0.318.The air pressure and relative humidity are positively correlated with PM_(2.5),their correlation coefficients are 0.250 and 0.017.This suggests that PWV,ZTD,temperature,air pressure,and wind speed are major factors influencing PM_(2.5)concentration.During haze,the PWV and relative humidity are high,leading to the convergence of PM_(2.5)particles.The correlation coefficients between PWV and relative humidity and PM_(2.5)increase by 29.14%and 96.99%,respectively.Rainfall can significantly reduce PM_(2.5)concentration,and the correlation coefficient between relative humidity and PM_(2.5)increases by 90.39%.The correlation between GNSS meteorological elements and PM_(2.5)is significantly improved after wavelet decomposition reconstruction,which can more clearly reflect the overall trend of GNSS meteorological elements and PM_(2.5)changes.

关 键 词：GNSS 大气可降水量 雾霾 PM_(2.5) 相关性分析 

分 类 号：P228[天文地球—大地测量学与测量工程]