LUAN Qingzu, JIANG Wei, LIU Shuo, GUO Hongxiang. Impact of Urban 3D Morphology on Particulate Matter 2.5 (PM2.5) Concentrations: Case Study of Beijing, China[J]. Chinese Geographical Science, 2020, 30(2): 294-308. doi: 10.1007/s11769-020-1112-5
Citation: LUAN Qingzu, JIANG Wei, LIU Shuo, GUO Hongxiang. Impact of Urban 3D Morphology on Particulate Matter 2.5 (PM2.5) Concentrations: Case Study of Beijing, China[J]. Chinese Geographical Science, 2020, 30(2): 294-308. doi: 10.1007/s11769-020-1112-5

Impact of Urban 3D Morphology on Particulate Matter 2.5 (PM2.5) Concentrations: Case Study of Beijing, China

doi: 10.1007/s11769-020-1112-5
Funds:

Under the auspices of National Key Research and Development Program of China (No. 2016YFB0502504), Beijing Excellent Youth Talent Program (No. 2015400018760G294), National Natural Science Foundation of China (No. 41201443, 41001267)

  • Received Date: 2019-01-14
  • Urban particulate matter 2.5 (PM2.5) pollution and public health are closely related, and concerns regarding PM2.5 are widespread. Of the underlying factors, the urban morphology is the most manageable. Therefore, investigations of the impact of urban three-dimensional (3D) morphology on PM2.5 concentration have important scientific significance. In this paper, 39 PM2.5 monitoring sites of Beijing in China were selected with PM2.5 automatic monitoring data that were collected in 2013. This data set was used to analyze the impacts of the meteorological condition and public transportation on PM2.5 concentrations. Based on the elimination of the meteorological conditions and public transportation factors, the relationships between urban 3D morphology and PM2.5 concentrations are highlighted. Ten urban 3D morphology indices were established to explore the spatial-temporal correlations between the indices and PM2.5 concentrations and analyze the impact of urban 3D morphology on the PM2.5 concentrations. Results demonstrated that road length density (RLD), road area density (RAD), construction area density (CAD), construction height density (CHD), construction volume density (CVD), construction otherness (CO), and vegetation area density (VAD) have positive impacts on the PM2.5 concentrations, whereas water area density (WAD), water fragmentation (WF), and vegetation fragmentation (VF) (except for the 500 m buffer) have negative impacts on the PM2.5 concentrations. Moreover, the correlations between the morphology indices and PM2.5 concentrations varied with the buffer scale. The findings could lay a foundation for the high-precision spatial-temporal modelling of PM2.5 concentrations and the scientific planning of urban 3D spaces by authorities responsible for controlling PM2.5 concentrations.

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Impact of Urban 3D Morphology on Particulate Matter 2.5 (PM2.5) Concentrations: Case Study of Beijing, China

doi: 10.1007/s11769-020-1112-5
Funds:

Under the auspices of National Key Research and Development Program of China (No. 2016YFB0502504), Beijing Excellent Youth Talent Program (No. 2015400018760G294), National Natural Science Foundation of China (No. 41201443, 41001267)

Abstract: 

Urban particulate matter 2.5 (PM2.5) pollution and public health are closely related, and concerns regarding PM2.5 are widespread. Of the underlying factors, the urban morphology is the most manageable. Therefore, investigations of the impact of urban three-dimensional (3D) morphology on PM2.5 concentration have important scientific significance. In this paper, 39 PM2.5 monitoring sites of Beijing in China were selected with PM2.5 automatic monitoring data that were collected in 2013. This data set was used to analyze the impacts of the meteorological condition and public transportation on PM2.5 concentrations. Based on the elimination of the meteorological conditions and public transportation factors, the relationships between urban 3D morphology and PM2.5 concentrations are highlighted. Ten urban 3D morphology indices were established to explore the spatial-temporal correlations between the indices and PM2.5 concentrations and analyze the impact of urban 3D morphology on the PM2.5 concentrations. Results demonstrated that road length density (RLD), road area density (RAD), construction area density (CAD), construction height density (CHD), construction volume density (CVD), construction otherness (CO), and vegetation area density (VAD) have positive impacts on the PM2.5 concentrations, whereas water area density (WAD), water fragmentation (WF), and vegetation fragmentation (VF) (except for the 500 m buffer) have negative impacts on the PM2.5 concentrations. Moreover, the correlations between the morphology indices and PM2.5 concentrations varied with the buffer scale. The findings could lay a foundation for the high-precision spatial-temporal modelling of PM2.5 concentrations and the scientific planning of urban 3D spaces by authorities responsible for controlling PM2.5 concentrations.

LUAN Qingzu, JIANG Wei, LIU Shuo, GUO Hongxiang. Impact of Urban 3D Morphology on Particulate Matter 2.5 (PM2.5) Concentrations: Case Study of Beijing, China[J]. Chinese Geographical Science, 2020, 30(2): 294-308. doi: 10.1007/s11769-020-1112-5
Citation: LUAN Qingzu, JIANG Wei, LIU Shuo, GUO Hongxiang. Impact of Urban 3D Morphology on Particulate Matter 2.5 (PM2.5) Concentrations: Case Study of Beijing, China[J]. Chinese Geographical Science, 2020, 30(2): 294-308. doi: 10.1007/s11769-020-1112-5
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