Analysis of Spatio-Temporal Heterogeneity and Socioeconomic driving Factors of PM2.5 in Beijing–Tianjin–Hebei and Its Surrounding Areas

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.

Ambient air pollution as a time-varying covariate in the survival probability of childhood cancer patients in the upper Northern Thailand

“…Although the relationship between adult cancer mortality and specific air pollutant exposure, including PM 2.5 [17-19, 21-23, 37-42], PM 10 [19,[21][22][23][43][44][45][46], NO 2 [19,20,22,23,47,48], SO 2 [20,[47][48][49][50], CO [20], and O 3 [20,51], has been extensively investigated, the association between air pollution and the survival rate of children with cancer has not.…”

“…The exposure to air pollution will deteriorate the health and treatment outcome of childhood cancer patients. Several studies in adult patients with cancer found a relationship between cancer mortality and air pollution exposure [18][19][20][21][22][23]. However, the risk of childhood cancer mortality with air pollution was not clearly elucidated.…”

Exploration of Coupling Effects in the Digital Economy and Eco-Economic System Resilience in Urban Areas: Case Study of the Beijing-Tianjin-Hebei Urban Agglomeration

“…Digitization and sustainable development are the main trends of economic and social development [41][42][43]. By harnessing the power of the internet and inclusive finance to bring technological innovation effects and resource allocation effects into play, the digital economy enhances the rational sharing and equitable distribution of the wellbeing outcomes of economic development [44][45][46][47][48].…”

Simulation and Forecasting Study on the Influential Factors of PM2.5 Related to Energy Consumption in the Beijing–Tianjin–Hebei Region

“…Socio-economic factors, like population size, economic development, energy consumption, and industrial construction, also contribute to PM 2.5 emissions. Studies have indicated that the primary socio-economic determinants determining PM 2.5 emissions include population density, economic structure, industrial structure, and energy structure [24,25].…”