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IJERPH
Volume 17
Issue 9
10.3390/ijerph17093014
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Article

The Effect of Socioeconomic Factors on Spatiotemporal Patterns of PM2.5 Concentration in Beijing–Tianjin–Hebei Region and Surrounding Areas

by
Wenting Wang
1,2,3,†,
Lijun Zhang
2,†,
Jun Zhao
1,2,
Mengge Qi
1,2 and
Fengrui Chen
1,2,*
1
Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education/Collaborative Innovation Center of Yellow River Civilization, Henan University, Kaifeng 475004, China
2
College of Environmental and Planning, Henan University, Kaifeng 475004, China
3
South-to-North Water Diversion Middle Route Information Technology Co., Ltd., Beijing 100038, China
*
Author to whom correspondence should be addressed.
†
Both authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2020, 17(9), 3014; https://doi.org/10.3390/ijerph17093014
Received: 26 March 2020 / Revised: 19 April 2020 / Accepted: 24 April 2020 / Published: 26 April 2020
(This article belongs to the Section Environmental Health)
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Abstract

The study investigated the spatiotemporal evolution of PM2.5 concentration in the Beijing–Tianjin–Hebei region and surrounding areas during 2015–2017, and then analyzed its socioeconomic determinants. First, an estimation model considering spatiotemporal heterogeneous relationships was developed to accurately estimate the spatial distribution of PM2.5 concentration. Additionally, socioeconomic determinants of PM2.5 concentration were analyzed using a spatial panel Dubin model, which aimed to improve the robustness of the model estimation. The results demonstrated that: (1) The proposed model significantly increased the estimation accuracy of PM2.5 concentration. The mean absolute error and root-mean-square error were 9.21 μg/m3 and 13.10 μg/m3, respectively. (2) PM2.5 concentration in the study area exhibited significant spatiotemporal changes. Although the PM2.5 concentration has declined year by year, it still exceeded national environmental air quality standards. (3) The per capita GDP, urbanization rate and number of industrial enterprises above the designated size were the key factors affecting the spatiotemporal distribution of PM2.5 concentration. This study provided scientific references for comprehensive PM2.5 pollution control in the study area. View Full-Text
Keywords: PM2.5; socioeconomic factors; spatiotemporal patterns; spatiotemporal heterogeneous; spatial panel Dubin model PM2.5; socioeconomic factors; spatiotemporal patterns; spatiotemporal heterogeneous; spatial panel Dubin model
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MDPI and ACS Style

Wang, W.; Zhang, L.; Zhao, J.; Qi, M.; Chen, F. The Effect of Socioeconomic Factors on Spatiotemporal Patterns of PM2.5 Concentration in Beijing–Tianjin–Hebei Region and Surrounding Areas. Int. J. Environ. Res. Public Health 2020, 17, 3014. https://doi.org/10.3390/ijerph17093014

AMA Style

Wang W, Zhang L, Zhao J, Qi M, Chen F. The Effect of Socioeconomic Factors on Spatiotemporal Patterns of PM2.5 Concentration in Beijing–Tianjin–Hebei Region and Surrounding Areas. International Journal of Environmental Research and Public Health. 2020; 17(9):3014. https://doi.org/10.3390/ijerph17093014

Chicago/Turabian Style

Wang, Wenting, Lijun Zhang, Jun Zhao, Mengge Qi, and Fengrui Chen. 2020. "The Effect of Socioeconomic Factors on Spatiotemporal Patterns of PM2.5 Concentration in Beijing–Tianjin–Hebei Region and Surrounding Areas" International Journal of Environmental Research and Public Health 17, no. 9: 3014. https://doi.org/10.3390/ijerph17093014

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