The effects of socioeconomic factors on particulate matter concentration in China's: New evidence from spatial econometric model

面板数据 社会经济地位 空间分析 微粒 计量经济模型 空间计量经济学 污染物 中国 城市化 地理 空气污染 环境科学 计量经济学 环境卫生 经济 经济增长 人口 生态学 生物 医学 遥感 考古
作者
Uzair Aslam Bhatti,Shah Marjan,Abdul Wahid,M.S. Syam,Mengxing Huang,Hao Tang,Ahmad Hasnain
出处
期刊:Journal of Cleaner Production [Elsevier]
卷期号:417: 137969-137969 被引量:7
标识
DOI:10.1016/j.jclepro.2023.137969
摘要

As a result of rapid industrialization and urbanization, China is now facing a host of environmental problems that have serious health implications. Studies of air pollution's impact on human health are vital in many fields, including epidemiology, environmental science, and the social sciences. To ensure the effective growth of socioeconomic sectors, it is critical to investigate the effect of socioeconomic factors on primary air pollutant particulate matter (PM2.5) and the driving mechanism. We conducted group-wise (i.,e. divide data in 5 different periods, D1 (2002–2006), D2 (2007–2011), D3 (2012–2016), D4 (2017–2021) and D5(2002–2021) spatial autocorrelation and spatial panel regression analyses of PM2.5 emissions using panel data from 34 provincial-level administrative units in China from 2002 to 2021 to understand the factors influencing air pollutant emissions. This study adds to the literature by considering comprehensive features and spatial effects in the panel-data econometric framework of the different areas. The spatial features analysis reveals that pollutant emissions in these regions decreased during the study period, although socioeconomic and natural factors are essential sources of PM2.5. PM2.5 emissions also showed significant positive spatial autocorrelations. Several statistical tests were run to examine the spatial autocorrelation among the regions. The results of a random effect regression model and geometric weighted regression (GWR) revealed that both socioeconomic and natural factors were statistically significant for PM2.5, though to varying degrees depending on region type. Positive and statistically significant results were obtained for China when considering the impacts of urban population, urban green space, economic growth, and economic spending. China has a positive and significant link with the exploitation of energy and natural resources. In light of these findings, we have developed several ideas for addressing air pollution and improving environmental sustainability, such as increasing regional collaboration and reforming the economy.
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