Abstract

Due to rapid urbanization and socio-economic development, fine particulate matter (PM2.5) pollution has drawn very wide concern, especially in the Beijing–Tianjin–Hebei region, as well as in its surrounding areas. Different socio-economic developments shape the unique characteristics of each city, which may contribute to the spatial heterogeneity of pollution levels. Based on ground fine particulate matter (PM2.5) monitoring data and socioeconomic panel data from 2015 to 2019, the Beijing–Tianjin–Hebei region, and its surrounding provinces, were selected as a case study area to explore the spatio-temporal heterogeneity of PM2.5 pollution, and the driving effect of socioeconomic factors on local air pollution. The spatio-temporal heterogeneity analysis showed that PM2.5 concentration in the study area expressed a downward trend from 2015 to 2019. Specifically, the concentration in Beijing–Tianjin–Hebei and Henan Province had decreased, but in Shanxi Province and Shandong Province, the concentration showed an inverted U-shaped and U-shaped variation trend, respectively. From the perspective of spatial distribution, PM2.5 concentrations in the study area had an obvious spatial positive correlation, with agglomeration characteristics of “high–high” and “low–low”. The high-value area was mainly distributed in the junction area of Henan, Shandong, and Hebei Provinces, which had been gradually moving to the southwest. The low values were mainly concentrated in the northern parts of Shanxi and Hebei Provinces, and the eastern part of Shandong Province. The results of the spatial lag model showed that Total Population (POP), Proportion of Urban Population (UP), Output of Second Industry (SI), and Roads Density (RD) had positive driving effects on PM2.5 concentration, which were opposite of the Gross Domestic Product (GDP). In addition, the spatial spillover effect of the PM2.5 concentrations in surrounding areas has a positive driving effect on local pollution levels. Although the PM2.5 levels in the study area have been decreasing, air pollution is still a serious problem. In the future, studies on the spatial and temporal heterogeneity of PM2.5 caused by unbalanced social development will help to better understand the interaction between urban development and environmental stress. These findings can contribute to the development of effective policies to mitigate and reduce PM2.5 pollutions from a socio-economic perspective.

Highlights

  • With the advancement of industrialization and urbanization, many cities around the world are experiencing severe air pollution, especially particulate matter pollution

  • The results of the spatial lag model showed that Total Population (POP), Proportion of Urban Population (UP), Output of Second Industry (SI), and Roads Density (RD) had positive driving effects on PM2.5 concentration, which were opposite of the Gross Domestic Product (GDP)

  • Cheng et al [14] used a dynamic spatial panel model to analyze the impact of foreign direct investment (FDI) on China’s PM2.5 pollutions, and the results showed that FDI significantly aggravated China’s urban PM2.5 pollutions

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Summary

Introduction

With the advancement of industrialization and urbanization, many cities around the world are experiencing severe air pollution, especially particulate matter pollution. China, India, and South Asia have the most severe particulate matter pollution in the world [1]. In China, since 2011, Beijing–Tianjin–Hebei [2], the Yangtze River Delta [3], and other regions have experienced frequent smog, and air pollution has caused widespread concern. In 2017, the State Ministry of Environmental Protection issued the “Beijing–Tianjin–Hebei and Surrounding Area Air Pollution Prevention and Control Work Plan in 2017”, which first proposed the concept of “2 + 26 cities” and implemented a large number of pollution control measures in these cities to alleviate air pollution in North China. Strengthening scientific understanding of the regulations of regional air particulate pollution will help to formulate urbanization policies and ensure that targeted air pollution control measures are properly implemented

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