School of Social and Behavioral Sciences, Nanjing University, Nanjing, 210023, People's Republic of China.
Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing, China.
Environ Sci Pollut Res Int. 2021 Jun;28(21):26732-26746. doi: 10.1007/s11356-021-12508-6. Epub 2021 Jan 25.
Fine particulate matter (PM2.5) is of widespread concern, as it poses a serious impact on economic development and human health. Although the influence of socioeconomic factors on PM2.5 has been studied, the constitution and the effect analysis of social vulnerability to PM2.5 remain unclear. In this study, a comprehensive theoretical framework with appropriate indicators for social vulnerability to PM2.5 was constructed. Using spatial autocorrelation analysis, a positive global spatial autocorrelation and notable local spatial cluster relationships were identified. Spatial econometric modeling and geographically weighted regression modeling were performed to explore the cause-effect relationship of social vulnerability to PM2.5. The spatial error model indicated that population and education inequality in the sensitivity dimension caused a significant positive impact on PM2.5, and biocapacity and social governance in the capacity dimension strongly contributed to the decrease of PM2.5 globally. The geographically weighted regression model revealed spatial heterogeneity in the effects of the social vulnerability variables on PM2.5 among countries. These empirical results can provide policymakers with a new perspective on social vulnerability as it relates to PM2.5 governance and targeted environmental pollution management.
细颗粒物（PM2.5）受到广泛关注，因为它对经济发展和人类健康造成严重影响。尽管已经研究了社会经济因素对 PM2.5 的影响，但社会对 PM2.5 的脆弱性的构成和影响分析仍不清楚。在这项研究中，构建了一个具有适当 PM2.5 社会脆弱性指标的综合理论框架。利用空间自相关分析，确定了正的全局空间自相关和显著的局部空间聚类关系。进行了空间计量经济学模型和地理加权回归模型分析，以探讨 PM2.5 社会脆弱性的因果关系。空间误差模型表明，敏感性维度的人口和教育不平等对 PM2.5 产生了显著的正向影响，而能力维度的生物承载力和社会治理对全球 PM2.5 的减少有很大贡献。地理加权回归模型揭示了社会脆弱性变量对各国 PM2.5 影响的空间异质性。这些实证结果可以为决策者提供一个新的视角，了解社会脆弱性与 PM2.5 治理和有针对性的环境污染管理之间的关系。
