Spatial patterns of the diurnal variations of PM2.5 and their influencing factors across China

被引:4
|
作者
Liu, Junli [1 ]
Wang, Siyuan [2 ,3 ]
Zhu, Kemin [4 ]
Hu, Jinghao [5 ]
Li, Runkui [5 ,6 ]
Song, Xianfeng [5 ,6 ]
机构
[1] Xidian Univ, Hangzhou Inst Technol, Hangzhou 311200, Peoples R China
[2] Max Planck Inst Biogeochem, Jena, Germany
[3] Tech Univ Dresden, Inst Photogrammetry & Remote Sensing, Dresden, Germany
[4] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China
[5] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
[6] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
基金
中国国家自然科学基金;
关键词
Diurnal variation; Air pollution; Fine particulate matter; Spatial analysis; Meteorological factors; PROVINCIAL CAPITAL CITIES; AIR-QUALITY; PARTICULATE MATTER; REGIONAL TRANSPORT; POLLUTANTS; IMPACT; EMISSIONS; HAZE;
D O I
10.1016/j.atmosenv.2023.120215
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Air pollution, particularly PM2.5, is a significant public health concern in China and worldwide. The diurnal fluctuation feature of PM2.5 is a crucial factor influencing human exposure, but research on its spatiotemporal characteristics across China is limited. This study aims to explore the spatial patterns of diurnal variations in PM2.5 concentrations across China and identify the factors that influence them. We conducted a comprehensive study to investigate the diurnal range of PM2.5 concentration and meteorological factors from 1636 fixed monitoring sites in China from January 2015 to December 2021. We calculated the average diurnal variation of PM2.5 during different seasons at each site and explored the correlation between the diurnal variation of PM2.5 and various types of factors. The main influencing factors was identified by employing eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP). Our spatial analysis revealed significant variations in both the mean concentration and diurnal range of PM2.5 across different regions in China. The main factors affecting the diurnal variation of PM2.5 include topographic factors such as elevation, meteorological factors such as temperature, air pressure, and dew point temperature, and socioeconomic factors such as industry and transportation. This study is beneficial for evidence-based policy decisions aimed at reducing air pollution and protecting public health.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Spatiotemporal variations and the driving factors of PM2.5 in Xi'an, China between 2004 and 2018
    Tuheti, Abula
    Deng, Shunxi
    Li, Jianghao
    Li, Guanghua
    Lu, Pan
    Lu, Zhenzhen
    Liu, Jiayao
    Du, Chenhui
    Wang, Wei
    ECOLOGICAL INDICATORS, 2023, 146
  • [2] Spatiotemporal Variations and Influencing Factors Analysis of PM2.5 Concentrations in Jilin Province, Northeast China
    Wen Xin
    Zhang Pingyu
    Liu Daqian
    CHINESE GEOGRAPHICAL SCIENCE, 2018, 28 (05) : 810 - 822
  • [3] Spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing, China
    Zhang, Licheng
    An, Ji
    Liu, Mengyang
    Li, Zhiwei
    Liu, Yue
    Tao, Lixin
    Liu, Xiangtong
    Zhang, Feng
    Zheng, Deqiang
    Gao, Qi
    Guo, Xiuhua
    Luo, Yanxia
    ENVIRONMENTAL POLLUTION, 2020, 262
  • [4] Diurnal variations of polycyclic aromatic hydrocarbons associated with PM2.5 in Shanghai, China
    Gu, Zeping
    Feng, Jialiang
    Han, Wenliang
    Li, Li
    Wu, Minghong
    Fu, Jiamo
    Sheng, Guoying
    JOURNAL OF ENVIRONMENTAL SCIENCES, 2010, 22 (03) : 389 - 396
  • [5] Spatial-Temporal Pattern and Influencing Factors of PM2.5 Pollution in North China Plain
    Wang, Xiaoyang
    Ma, Mingliang
    Guo, Lin
    Wang, Yuqiang
    Yao, Guobiao
    Meng, Fei
    Yu, Mingyang
    POLISH JOURNAL OF ENVIRONMENTAL STUDIES, 2022, 31 (04): : 3879 - 3891
  • [6] Spatiotemporal variations and connections of single and multiple meteorological factors on PM2.5 concentrations in Xi'an, China
    Zhang, Xiaoxia
    Xu, Haidong
    Liang, Dong
    ATMOSPHERIC ENVIRONMENT, 2022, 275
  • [7] The socioeconomic factors influencing the PM2.5 levels of 160 cities in China
    Li, Wenli
    Yang, Guangfei
    Qian, Xiangyu
    SUSTAINABLE CITIES AND SOCIETY, 2022, 84
  • [8] Diurnal, seasonal, and spatial variation of PM2.5 in Beijing
    Li, Runkui
    Li, Zhipeng
    Gao, Wenju
    Ding, Wenjun
    Xu, Qun
    Song, Xianfeng
    SCIENCE BULLETIN, 2015, 60 (03) : 387 - 395
  • [9] Influencing Factors of PM2.5 Pollution: Disaster Points of Meteorological Factors
    Sun, Ruiling
    Zhou, Yi
    Wu, Jie
    Gong, Zaiwu
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2019, 16 (20)
  • [10] Concentrations, seasonal and diurnal variations of black carbon in PM2.5 in Shanghai, China
    Feng, Jialiang
    Zhong, Mian
    Xu, Binhua
    Du, Yan
    Wu, Minghong
    Wang, Hongli
    Chen, Changhong
    ATMOSPHERIC RESEARCH, 2014, 147 : 1 - 9