金砖五国PM2.5浓度与经济环境因素的关联
Association between PM2.5 Concentrations and Economic/Environmental Factors in BRICS Countries
摘要: 本研究旨在探究金砖国家(巴西、俄罗斯、印度、中国、南非)PM2.5污染的核心驱动因素，以应对其城市化与经济发展中的环境健康挑战，并为差异化治理策略提供依据。基于2010~2019年的面板数据，运用灰色关联模型从人口、人均GDP、平均寿命、能源消耗、城市化水平和森林覆盖率六个维度进行分析。结果表明，各国核心驱动因素存在显著差异：城市化水平(ri = 0.849)、人口(ri = 0.881)和平均寿命(ri = 0.885)是影响中国和印度PM2.5浓度的主导因素；人均GDP (ri = 0.780)与巴西PM2.5污染关联最为密切；森林覆盖率对中国(ri = 0.875)和南非(ri = 0.959)的PM2.5浓度具有显著抑制效应，印证了生态修复工程及自然生态系统在颗粒物去除中的关键作用。本研究揭示了不同发展路径下PM2.5驱动机制的异质性，强调在环境治理中需统筹经济社会因素与生态保护，并提出基于国家具体情况的差异化政策建议。
Abstract: This study aims to investigate the key driving factors of PM2.5 pollution in the BRICS countries (Brazil, Russia, India, China, and South Africa), in response to the environmental health challenges posed by their urbanization and economic development, and to provide a basis for differentiated governance strategies. Using panel data from 2010 to 2019 and applying the grey relational analysis model, six dimensions were examined: population, GDP per capita, average life expectancy, energy consumption, urbanization level, and forest coverage rate. The results indicate significant differences in the core driving factors among the countries: urbanization level (ri = 0.849), population (ri = 0.881), and average life expectancy (ri = 0.885) were the dominant factors affecting PM2.5 concentrations in China and India; GDP per capita (ri = 0.780) showed the strongest association with PM2.5 pollution in Brazil; forest coverage demonstrated a significant inhibitory effect on PM2.5 concentrations in China (ri =0.875) and South Africa (ri = 0.959), underscoring the critical role of ecological restoration projects and natural ecosystems in particulate matter removal. This study reveals the heterogeneity of PM2.5 driving mechanisms under different development paths, emphasizing the need to integrate socioeconomic factors and ecological conservation in environmental governance, and proposes tailored policy recommendations based on country-specific conditions.
文章引用：潘虹宇, 吴冰. 金砖五国PM2.5浓度与经济环境因素的关联[J]. 可持续发展, 2025, 15(10): 11-19. https://doi.org/10.12677/sd.2025.1510280

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