Quantitatively Disentangling the Geographical Impacts of Topography on PM2.5 Pollution in China

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Abstract
Fine particulate matter (PM2.5) pollution’s passive effects on public health have attracted a great deal of attention. Extensive studies have tried to uncover the impacts of external drivers on PM2.5 pollution variation; however, the topography’s effects on PM2.5 pollution remain poorly understood. Using annual high-resolution concentration estimates for PM2.5, this paper quantitatively disentangled the geographical impacts of topography on the PM2.5 pollution in China and quantified the mountain blocking effects on the PM2.5 pollution dispersion on a macro scale. The results show that, in China, the plains and surrounding platforms and hills tend to suffer from long-term severe PM2.5 pollution. The most polluted topography type is the plains. In comparison, regions such as high-altitude mountains and plateaus are less affected by PM2.5 pollution. Mountains have significant and evident blocking effects on the cross-regional spread of PM2.5 pollution. Generally, Level I mountains (high elevation, density and coverage mountains) provide better blocking effects than Level II (middle elevation, density and coverage mountains) mountains and Level III mountains (low elevation, density and coverage mountains). The mountains’ blocking effects begin to play an efficient role when their altitudes reach a certain value; however, the exact altitude values vary by different mountains with a value of 163 m for all typical mountains with absolute PM2.5 concentration differences between their two sides greater than 10 μg/m3. In heavily polluted areas, PM2.5 pollution may overflow where the surrounding mountains are not high enough or the mountains’ stretch breaks. This study can provide key theoretical support for air pollution modelling and regional air pollution joint prevention and control.
Funding Information
  • National Science Foundation for Young Scientists of China (42007406, 202102020666, 2022A1515010632)
  • Guangzhou Science and Technology Plan Project (42007406, 202102020666, 2022A1515010632)
  • Guangdong Natural Science Foundation-General Program (42007406, 202102020666, 2022A1515010632)

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