摘要
文章利用气象观测数据及大气环境观测数据,分析并与2018年相比了江苏省2019年霾的全省分布特征及主要颗粒物污染物空间分布特征。分析并与2018年相比了2019年主要影响颗粒物污染气象条件的时空分布特征。结合大气化学模式,分析总气象条件对颗粒物污染影响。由分析结果可知,2019年江苏省气象条件相比2018年略有利于颗粒物污染浓度下降,下降了3.4%,实际全省PM2.5浓度下降约6.5%,人为控制因素使颗粒物污染下降3.1%。
By utilizing meteorological observations and atmospheric environmental observations,spatial distribution characteristics of haze and particulate pollution elements of Jiangsu province in 2019 are analyzed and compared with that in 2018.And it analyzes the spatial and temporal characteristics of leading meteorological factors of particulate pollution of Jiangsu province in 2019 and compares it with that in 2018.Combined with atmospheric chemistry model,the influence of total meteorological conditions on particulate pollution is analyzed.From the analysis results,we can see that the meteorological conditions in Jiangsu Province in 2019 are slightly favorable to the decrease of particulate pollution concentration by 3.4%compared with 2018,and the actual PM2.5 concentration in the whole province is reduced by about 6.5%,and the pollution of particulate matter by artificial control factors is reduced by 3.1%.
作者
陈昊
潘晨
曹璐
康志明
Chen Hao;Pan Chen;Cao Lu;Kang Zhiming(Jiangsu Meteorological Observatory,Nanjing 210008,China)
出处
《江苏科技信息》
2020年第15期73-78,共6页
Jiangsu Science and Technology Information
基金
国家自然科学基金,项目名称:基于非均匀通带响应的FY3D MWTS晴空观测算子优化关键技术研究,项目编号:41905099
江苏省自然科学基金,项目名称:云雨条件下FY-3B/MWRI与AMSR2交叉匹配方法研究,项目编号:BK20181101
华东区域气象科技协同创新基金,项目名称:地基微波辐射计产品本地化及强对流天气监测应用,项目编号:QYHZ201802
北极阁开放基金,项目名称:基于卫星遥感资料与深度学习技术的大气湍流诊断方法研究,项目编号:NJCAR2018MS03。
关键词
气象条件
颗粒物污染
霾
大气化学模式
meteorological conditions
particulate pollution
haze
atmospheric chemical model