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Quantitative attribution of spatio-temporal pattern of pm2.5 concentration based on geodetector and GWR model: Evidence from China’s three major urban agglomerations

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  • Zeduo Zou
  • Xiuyan Zhao
  • Shuyuan Liu
  • Xiaodie Yuan
  • Chunshan Zhou

Abstract

Clarifying the spatio-temporal evolution of PM2.5 concentration law and its driving mechanism is crucial for the prevention and control of air pollution in urban agglomerations, also helping promote their high-quality development. Based on remote sensing and statistics of urban agglomerations in China’s Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) from 2005 to 2020, the paper analyses the evolution characteristics of the pollution concentration pattern and identifies the influencing factors through spatial analysis method combining the geodetector and geographically weighted regression (GWR) model. As the results show, during the study period: (1) Temporal Trends: annual PM2.5 concentrations exhibited significant declines, with BTH decreasing from 1004.71 μg/m3 (2006) to 528 μg/m3 (2020), YRD from 1434.81 μg/m3 (2008) to 621 μg/m3, and PRD from 405.02 μg/m3 (2007) to 292 μg/m3. The ranking remained YRD > BTH > PRD throughout the study period. (2) Spatial Heterogeneity: Spatial clustering (Moran’s I: 0.286–0.729, p

Suggested Citation

  • Zeduo Zou & Xiuyan Zhao & Shuyuan Liu & Xiaodie Yuan & Chunshan Zhou, 2025. "Quantitative attribution of spatio-temporal pattern of pm2.5 concentration based on geodetector and GWR model: Evidence from China’s three major urban agglomerations," PLOS ONE, Public Library of Science, vol. 20(7), pages 1-25, July.
    • Handle: RePEc:plo:pone00:0326241
    DOI: 10.1371/journal.pone.0326241
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