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<p>As China strives to achieve the dual goals of air pollution control and carbon neutrality, differences in emission sources and growing regional inequalities pose significant challenges to coordinated environmental governance. This study examines the spatiotemporal evolution and structural drivers of air pollutants and carbon emissions across provinces, focusing on industrial and domestic sources of pollution. A comprehensive analytical framework is constructed based on panel data for 30 provinces from 2011 to 2020, integrating the Logarithmic Mean Divisia Index (LMDI), Dagum’s Gini decomposition, kernel density estimation, and spatial LMDI model. Emissions are decomposed into five key driving factors: carbon intensity, energy intensity, economic output, population, and emission synergy. The contributions of these five factors to intra- and inter-regional disparities are quantitatively assessed. The results show that although overall emissions have declined, the trajectory of emission reductions remains structurally imbalanced. Emissions from industrial sources are affected by significant synergies, and energy efficiency improvements further contribute to emission reductions. In contrast, domestic emissions are mainly driven by economic and demographic pressures, with high spatial heterogeneity and limited synergies. Spatial LMDI analysis reveals uneven regional progress in implementing synergistic emission controls, with inland and resource-dependent provinces showing particularly weak performance. Furthermore, Dagum’s Gini decomposition indicates that only the middle reaches of the Yangtze River and Southwest China maintain relatively balanced emission levels among the eight regions, and that inter-regional disparities and transvariation density are the dominant sources of inequality, particularly for domestic emissions. Therefore, these findings highlight the need for source-specific, regionally differentiated policies and the establishment of cross-regional coordination mechanisms to promote synergistic emission reductions and reduce spatial inequalities in air pollutants and carbon emissions.</p>

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Spatiotemporal and regional differences in air pollution and carbon reduction in china: perspectives from industrial and domestic sources

  • 期刊论文

  • 发表日期：

    2025年12月29日

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  • Weidong Chen,
  • Jingyi Bi

摘要

As China strives to achieve the dual goals of air pollution control and carbon neutrality, differences in emission sources and growing regional inequalities pose significant challenges to coordinated environmental governance. This study examines the spatiotemporal evolution and structural drivers of air pollutants and carbon emissions across provinces, focusing on industrial and domestic sources of pollution. A comprehensive analytical framework is constructed based on panel data for 30 provinces from 2011 to 2020, integrating the Logarithmic Mean Divisia Index (LMDI), Dagum’s Gini decomposition, kernel density estimation, and spatial LMDI model. Emissions are decomposed into five key driving factors: carbon intensity, energy intensity, economic output, population, and emission synergy. The contributions of these five factors to intra- and inter-regional disparities are quantitatively assessed. The results show that although overall emissions have declined, the trajectory of emission reductions remains structurally imbalanced. Emissions from industrial sources are affected by significant synergies, and energy efficiency improvements further contribute to emission reductions. In contrast, domestic emissions are mainly driven by economic and demographic pressures, with high spatial heterogeneity and limited synergies. Spatial LMDI analysis reveals uneven regional progress in implementing synergistic emission controls, with inland and resource-dependent provinces showing particularly weak performance. Furthermore, Dagum’s Gini decomposition indicates that only the middle reaches of the Yangtze River and Southwest China maintain relatively balanced emission levels among the eight regions, and that inter-regional disparities and transvariation density are the dominant sources of inequality, particularly for domestic emissions. Therefore, these findings highlight the need for source-specific, regionally differentiated policies and the establishment of cross-regional coordination mechanisms to promote synergistic emission reductions and reduce spatial inequalities in air pollutants and carbon emissions.