摘要
为了分析空气质量状况及其与大气水汽的关系,基于四川盆地西部的成都市近年来污染天气频发的现状,利用2015年成都市环境监测中心提供的环境空气质量指数资料和温江国家基准气候站提供的大气水汽探空资料,首先分析了成都空气质量变化特征,进一步结合成都L波段探空水汽数据,初步研究了成都空气质量与大气水汽的关系。结果表明:2015年成都单日空气质量指数(AQI)最高值为309,达到严重污染级别;AQI年分布特征是冬季最高,夏季最低;首要污染物最多的是PM2. 5。春、夏季,大气可降水量(PWV)与臭氧质量浓度在5—8月呈显著负相关;秋、冬季,PWV与PM2. 5及PM10质量浓度在1月、10—11月呈显著正相关,其中水汽对PM2. 5浓度影响较大的时段出现在1月和10月。
Based on the current situation of frequent pollution in Chengdu in the west of Sichuan Basin,the ambient air quality and its relationship with atmospheric water vapor was analyzed.Using the ambient air quality index data provided by the Chengdu City Environmental Monitoring Center in 2015 and the atmospheric vapor sounding data provided by the Wenjiang National Reference Climate Station,this paper analyzed the characteristics of air quality changes in Chengdu,and further integrated with the L-band sounding water vapor data to study the relationship between air quality and atmospheric water vapor in Chengdu.The results showed that:the highest single-day of air quality index(AQI)was 309,which reached the level of severe pollution;the annual distribution characteristics of AQI were the highest in winter and the lowest in summer;the most primary pollutant was PM2.5.In spring and summer,there was a significant negative correlation between precipitable water vapor(PWV)and ozone(8h)concentration in May,June,July and August.In autumn and winter,there was a significant positive correlation between PWV and PM2.5 and PM10 concentrations in January,October and November.January and October were the periods when PM2.5 concentration was significantly affected by water vapor.
作者
文雯
李国平
谢娜
张恬月
WEN Wen;LI Guoping;XIE Na;ZHANG Tianyue(School of Atmospheric Sciences,Chengdu University of Information Technology,Chengdu 610225,China;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing 210044,China;Sichuan Meteorological Service,Chengdu 610072,China;Chengdu Academy of Environmental Sciences,Chengdu 610031,China)
出处
《沙漠与绿洲气象》
2019年第1期21-28,共8页
Desert and Oasis Meteorology
基金
国家重点研发计划项目(2018YFC1507200)
国家自然科学基金(41675057
41765003)资助