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What Drives Air Pollution in China? Evidence from Interpretable Machine Learning and Spatial Analysis of PM2.5

執筆者 ドミンゲス・アルバロ
所 属 アジア成長研究所
発行年月 2026年3月
No. 2025-05
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内容紹介

This paper investigates the determinants of fine particulate matter (PM2.5) across 31 Chinese provinces during 2004–2020, a period of rapid economic transformation accompanied by rising environmental pressures. Using a provincial panel dataset and a flexible empirical framework, we identify the economic, demographic, and energy-related factors most closely associated with regional variation in air quality. Population pressure and the composition of the regional energy mix emerge as the most influential predictors, while higher levels of solar and wind power capacity are associated with lower predicted pollution. The analysis also reveals substantial geographic heterogeneity, indicating that the drivers of air quality differ markedly across regions. These findings underscore the importance of geographically targeted environmental policies that simultaneously expand renewable energy capacity and address urban emission sources, particularly in densely populated provinces.