中国地理科学 ›› 2018, Vol. 28 ›› Issue (5): 810-822.doi: 10.1007/s11769-018-0992-0

• 论文 • 上一篇    下一篇

Spatiotemporal Variations and Influencing Factors Analysis of PM2.5 Concentrations in Jilin Province, Northeast China

WEN Xin, ZHANG Pingyu, LIU Daqian   

  1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
  • 收稿日期:2018-02-02 修回日期:2018-05-31 出版日期:2018-10-27 发布日期:2018-09-04
  • 通讯作者: ZHANG Pingyu. E-mail:zhangpy@iga.ac.cn E-mail:zhangpy@iga.ac.cn
  • 基金资助:

    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)

Spatiotemporal Variations and Influencing Factors Analysis of PM2.5 Concentrations in Jilin Province, Northeast China

WEN Xin, ZHANG Pingyu, LIU Daqian   

  1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
  • Received:2018-02-02 Revised:2018-05-31 Online:2018-10-27 Published:2018-09-04
  • Contact: ZHANG Pingyu. E-mail:zhangpy@iga.ac.cn E-mail:zhangpy@iga.ac.cn
  • Supported by:

    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)

摘要:

High PM2.5 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 PM2.5 concentrations and identify the decisive influencing factors, a large amount of continuous daily PM2.5 concentration data collected from 33 monitoring stations over 2-year period from 2015 to 2016 were analyzed. Meanwhile, the relationships were investigated between PM2.5 concentrations and the land cover, socioeconomic and meteorological factors from the macroscopic perspective using multiple linear regressions (MLR) approach. PM2.5 concentrations across Jilin Province averaged 49 μg/m3, 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 PM2.5 concentration of each city. Most of the spatial variation in PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 concentration indirectly.

关键词: particulate matter, PM2.5, spatial variation, temporal variation, Jilin Province

Abstract:

High PM2.5 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 PM2.5 concentrations and identify the decisive influencing factors, a large amount of continuous daily PM2.5 concentration data collected from 33 monitoring stations over 2-year period from 2015 to 2016 were analyzed. Meanwhile, the relationships were investigated between PM2.5 concentrations and the land cover, socioeconomic and meteorological factors from the macroscopic perspective using multiple linear regressions (MLR) approach. PM2.5 concentrations across Jilin Province averaged 49 μg/m3, 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 PM2.5 concentration of each city. Most of the spatial variation in PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 concentration indirectly.

Key words: particulate matter, PM2.5, spatial variation, temporal variation, Jilin Province