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Spatial Equity of PM 2.5 Pollution Exposures in High-Density Metropolitan Areas Based on Remote Sensing, LBS and GIS Data: A Case Study in Wuhan, China

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  • Zhuoran Shan

    (School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, China
    Hubei Engineering and Technology Research Center of Urbanization, Wuhan 430074, China
    The Key Laboratory of Urban Simulation for Ministry of Natural Resources, Wuhan 430074, China)

  • Hongfei Li

    (Guangzhou Urban Planning Survey and Design Institute, Guangzhou 510060, China)

  • Haolan Pan

    (School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, China
    Hubei Engineering and Technology Research Center of Urbanization, Wuhan 430074, China
    The Key Laboratory of Urban Simulation for Ministry of Natural Resources, Wuhan 430074, China)

  • Man Yuan

    (School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, China
    Hubei Engineering and Technology Research Center of Urbanization, Wuhan 430074, China
    The Key Laboratory of Urban Simulation for Ministry of Natural Resources, Wuhan 430074, China)

  • Shen Xu

    (School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, China
    Hubei Engineering and Technology Research Center of Urbanization, Wuhan 430074, China
    The Key Laboratory of Urban Simulation for Ministry of Natural Resources, Wuhan 430074, China)

Abstract

In-depth studies have been conducted on the risk of exposure to air pollution in urban residents, but most of them are static studies based on the population of residential units. Ignoring the real environmental dynamics during daily activity and mobility of individual residents makes it difficult to accurately estimate the level of air pollution exposure among residents and determine populations at higher risk of exposure. This paper uses the example of the Wuhan metropolitan area, high-precision air pollution, and population spatio-temporal dynamic distribution data, and applies geographically weighted regression models, bivariate LISA analysis, and Gini coefficients. The risk of air pollution exposure in elderly, low-age, and working-age communities in Wuhan was measured and the health equity within vulnerable groups such as the elderly and children was studied. We found that ignoring the spatio-temporal behavioral activities of residents underestimated the actual exposure hazard of PM 2.5 to residents. The risk of air pollution exposure was higher for the elderly than for other age groups. Within the aging group, a few elderly people had a higher risk of pollution exposure. The high exposure risk communities of the elderly were mainly located in the central and sub-center areas of the city, with a continuous distribution characteristic. No significant difference was found in the exposure risk of children compared to the other populations, but a few children were particularly exposed to pollution. Children’s high-exposure communities were mainly located in suburban areas, with a discrete distribution. Compared with the traditional static PM 2.5 exposure assessment, the dynamic assessment method proposed in this paper considers the high mobility of the urban population and air pollution. Thus, it can accurately reveal the actual risk of air pollution and identify areas and populations at high risk of air pollution, which in turn provides a scientific basis for proposing planning policies to reduce urban PM 2.5 and improve urban spatial equity.

Suggested Citation

  • Zhuoran Shan & Hongfei Li & Haolan Pan & Man Yuan & Shen Xu, 2022. "Spatial Equity of PM 2.5 Pollution Exposures in High-Density Metropolitan Areas Based on Remote Sensing, LBS and GIS Data: A Case Study in Wuhan, China," IJERPH, MDPI, vol. 19(19), pages 1-22, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12671-:d:932943
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    References listed on IDEAS

    as
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