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

被引:2
|
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
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页数:12
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