Abstract
Accurately identifying and quantifying the factors influencing PM2.5 pollution is of great significance for the prevention and control of pollution. However, the redundancy among potential factors of PM2.5 may be overlooked. Meanwhile, the inconsistent spatial distribution of the natural and socioeconomic conditions brings unique implications for the cities within a region, which may lead to an uncertain understanding of the relationship between pollution and environmental factors. This study focused on the Beijing-Tianjin-Hebei (BTH) Region, China, which presents complex and varied background conditions. Potential impact factors on PM2.5 were firstly screened by combining systematic cluster analysis with a random forest recursive feature elimination algorithm. Then, the representative multi-factor responsible for PM2.5 pollution in the region during the key period of 2014–2018 (when the strict national air pollution control policy was implemented). The results showed that the key driving factors of PM2.5 pollution in the BTH cities are different, indicating that the uniqueness of a city will have an impact on the leading causes of pollution. Further discussion shows that air control policy provides an effective way to improve air quality. This study aims to deepen the understanding of the risk drivers of air pollution within the BTH Region. In the future, it is recommended that more attention should be paid to the specific differences between the cities when formulating PM2.5 concentration control measures.
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Acknowledgement
We would also express thanks to Ms. Tong Li for collecting the PM2.5 ground monitoring data.
Funding
Foundation item: Under the auspices of National Natural Science Foundation of China (No. 42171094), Natural Science Foundation of Shandong Province (No. ZR2021MD095, ZR2021QD093), Humanities and Social Science Foundation of Ministry of Education of China (No. 20YJCZH198)
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Wang, Y., Sun, S., Xu, W. et al. Spatial Variability of PM2.5 Pollution in Imbalanced Natural and Socioeconomic Processes: Evidence from the Beijing-Tianjin-Hebei Region of China. Chin. Geogr. Sci. 33, 161–174 (2023). https://doi.org/10.1007/s11769-023-1331-7
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DOI: https://doi.org/10.1007/s11769-023-1331-7