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Spatiotemporal variation and determinants of population’s PM2.5 exposure risk in China, 1998–2017: a case study of the Beijing-Tianjin-Hebei region

Environmental Science and Pollution Research volume 27, pages 31767–31777 (2020)Cite this article

Abstract

PM2.5 pollution has emerged as a global human health risk. The best measure of its impact is a population’s PM2.5 exposure (PPM2.5E), an index that simultaneously considers PM2.5 concentrations and population spatial density. The spatiotemporal variation of PPM2.5E over the Beijing-Tianjin-Hebei (BTH) region, which is the national capital region of China, was investigated using a Bayesian space-time model, and the influence patterns of the anthropic and geographical factors were identified using the GeoDetector model and Pearson correlation analysis. The spatial pattern of PPM2.5E maintained a stable structure over the BTH region’s distinct terrain, which has been described as “high in the northwest, low in the southeast”. The spatial difference of PPM2.5E intensified annually. An overall increase of 6.192 (95% CI 6.186, 6.203) ×103 μg/m3 ∙ persons/km2 per year occurred over the BTH region from 1998 to 2017. The evolution of PPM2.5E in the region can be described as “high value, high increase” and “low value, low increase”, since human activities related to gross domestic product (GDP) and energy consumption (EC) were the main factors in its occurrence. GDP had the strongest explanatory power of 76% (P < 0.01), followed by EC and elevation (EL), which accounted for 61% (P < 0.01) and 40% (P < 0.01), respectively. There were four factors, proportion of secondary industry (PSI), normalized differential vegetation index (NDVI), relief amplitude (RA), and EL, associated negatively with PPM2.5E and four factors, GDP, EC, annual precipitation (AP), and annual average temperature (AAT), associated positively with PPM2.5E. Remarkably, the interaction of GDP and NDVI, which was 90%, had the greatest explanatory power for PPM2.5E ′ s diffusion and impact on the BTH region.

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Acknowledgements

The authors give thanks to Dr. Aaron van Donkelaar of the Atmospheric Physics Institute at Dalhousie University in Canada, who offered the remotely sensed PM2.5 data used in this study. Our deepest gratitude is expressed to our anonymous reviewers and editors for their careful work and constructive suggestions that have helped improve our paper substantially.

Funding

This paper is supported by General Project on Humanities and Social Science Research of the Chinese Ministry of Education (19YJCZH079) and China Postdoctoral Fund (2019M650946).

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Authors and Affiliations

  1. School of Mathematics, South China University of Technology, 381 Wushan Road, Guangzhou, 510000, China

    Ning Jin

  2. School of Statistics, Shanxi University of Finance and Economics, 696 Wucheng Road, Taiyuan, 030006, China

    Junming Li

  3. College of Architecture, Taiyuan University of Technology, 79 Yingze Street, Taiyuan, 030024, China

    Meijun Jin

  4. National Academy of Economic Strategy, Chinese Academy of Social Sciences, 28 Shuguanxili Chaoyang District, Beijing, 100028, China

    Xiaoyan Zhang

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  1. Ning Jin
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  2. Junming Li
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  4. Xiaoyan Zhang
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Correspondence to Junming Li or Meijun Jin.

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Responsible editor: Lotfi Aleya

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Ning Jin and Junming Li are Joint first authors with equal contributions

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Jin, N., Li, J., Jin, M. et al. Spatiotemporal variation and determinants of population’s PM2.5 exposure risk in China, 1998–2017: a case study of the Beijing-Tianjin-Hebei region. Environ Sci Pollut Res 27, 31767–31777 (2020). https://doi.org/10.1007/s11356-020-09484-8

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  • DOI: https://doi.org/10.1007/s11356-020-09484-8

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