Literature DB >> 33751379

Spatial-temporal characteristics of urban air pollution in 337 Chinese cities and their influencing factors.

Zhulu Lin1, Liming Liu2, Jialing Qi3.   

Abstract

Urban air pollution, especially in the form of haze events, has become a serious threat to socio-economic development and public health in most developing countries. It is of great importance to assess the frequency of urban air pollution occurrence and its influencing factors. The objective of our study is to develop consistent methodologies for constructing an index system and for assessing the influencing factors of the urban air pollution occurrence based on the Driver-Pressure-State-Impact-Response (DPSIR) framework by incorporating spatial analysis, geographical detector, and geographically weighted regression models. The 27 influencing factors were selected for assessing their influences on the urban air pollution occurrence in 337 Chinese cities. The results indicate that the spatial pattern of the urban air pollution in China was mostly consistent with the Chinese population-based Hu Line. Urban air pollution frequently occurred in North China, Central China, Northeast China, and East China, and displayed strong seasonality. The influencing factors of urban air pollution were complex and diverse, varying from season to season. Influencing factor analysis also shows that the explanatory power between any two influencing factors was greater than that of a single influencing factor of the urban air pollution. Furthermore, most influencing factors had both positive and negative effects and local effects on urban air pollution. Finally, we put forward five suggestions on reducing urban air pollution occurrence, which can provide the basis and reference for the government to make policies on urban air pollution control in China.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Keywords:  DPSIR framework; Geographical detector; Geographically weighted regression; Influencing factor; Risk management; Urban air pollution

Year:  2021        PMID: 33751379     DOI: 10.1007/s11356-021-12825-w

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  2 in total

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Authors:  Yuan Wang; Guoyin Cai; Liuzhong Yang; Ning Zhang; Mingyi Du
Journal:  PLoS One       Date:  2022-08-25       Impact factor: 3.752

2.  PM2.5 Concentration Exposure over the Belt and Road Region from 2000 to 2020.

Authors:  Shenxin Li; Sedra Shafi; Bin Zou; Jing Liu; Ying Xiong; Bilal Muhammad
Journal:  Int J Environ Res Public Health       Date:  2022-03-01       Impact factor: 3.390

  2 in total

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