Spatiotemporal Variations and Influencing Factors Analysis of PM_(2.5) Concentrations in Jilin Province,Northeast China

作     者：WEN Xin ZHANG Pingyu LIU Daqian 

作者机构：Northeast Institute of Geography and AgroecologyChinese Academy of Sciences 

出 版 物：《Chinese Geographical Science》 (中国地理科学（英文版）)

年 卷 期：2018年第28卷第5期

页      面：810-822页

核心收录：

学科分类：07[理学] 08[工学] 070602[理学-大气物理学与大气环境] 081402[工学-结构工程] 081304[工学-建筑技术科学] 0706[理学-大气科学] 0813[工学-建筑学] 0814[工学-土木工程] 

基　　金：Under the auspices of National Natural Science Foundation of China(No.41601607,41771138,41771161) Strategic Planning Project from Institute of Northeast Geography and Agroecology(IGA),Chinese Academy of Sciences(No.Y6H2091001-3) 

主　　题：particulate matter PM2.5 spatial variation temporal variation Jilin Province 

摘      要：High PM_(2.5) concentrations and frequent air pollution episodes during late autumn and winter in Jilin Province have attracted attention in recent years. To describe the spatial and temporal variations of PM_(2.5) concentrations and identify the decisive influencing factors, a large amount of continuous daily PM_(2.5) concentration data collected from 33 monitoring stations over 2-year period from 2015 to 2016 were analyzed. Meanwhile, the relationships were investigated between PM_(2.5) concentrations and the land cover, socioeconomic and meteorological factors from the macroscopic perspective using multiple linear regressions(MLR) approach. PM_(2.5) concentrations across Jilin Province averaged 49 μg/m^3, nearly 1.5 times of the Chinese annual average standard, and exhibited seasonal patterns with generally higher levels during late autumn and over the long winter than the other seasons. Jilin Province could be divided into three kinds of sub-regions according to 2-year average PM_(2.5) concentration of each city. Most of the spatial variation in PM_(2.5) levels could be explained by forest land area, cultivated land area, urban greening rate, coal consumption and soot emissions of cement manufacturing. In addition, daily PM_(2.5) concentrations had negative correlation with daily precipitation and positive correlation with air pressure for each city, and the spread and dilution effect of wind speed on PM_(2.5) was more obvious at mountainous area in Jilin Province. These results indicated that coal consumption, cement manufacturing and straw burning were the most important emission sources for the high PM_(2.5) levels, while afforestation and urban greening could mitigate particulate air pollution. Meanwhile, the individual meteorological factors such as precipitation, air pressure, wind speed and temperature could influence local PM_(2.5) concentration indirectly.