Research article Special Issues

Regional disparities and dynamic evolution of carbon emission distribution in China

  • Published: 11 March 2026
  • This study is centered on the measurement of carbon emissions at the provincial level in China and the analysis of their spatial distribution. We address the quantification of regional disparities and the dynamic evolution of emission patterns, which are critical for informing climate governance. Moreover, we aim to systematically measure carbon emissions across Chinese provinces and to investigate the regional disparities and the dynamic evolution in their distribution. Our goal is to provide an empirical basis for formulating differentiated and well-targeted emission reduction policies. The modified carbon emission factor method was employed for accounting. The Theil index and its decomposition were used to quantify regional disparities, while kernel density estimation was applied to characterize the dynamic evolution trends of the emission distribution. The results revealed significant regional imbalances in China's carbon emission distribution, with inter-regional differences identified as the primary source of overall disparity. Kernel density curves further showed distinct heterogeneity in distribution shapes and dynamic evolution across regions, reflecting deep-seated differences in emission structures and development stages. Our findings provide critical data for designing differentiated regional carbon reduction strategies and can directly support policy-making for coordinated emission reduction. They offer practical insights for industrial green transition planning at national and provincial levels, aiding in the alignment of economic development with climate targets.

    Citation: Xiaozhong Huang, Junhui Xie. Regional disparities and dynamic evolution of carbon emission distribution in China[J]. AIMS Environmental Science, 2026, 13(2): 217-240. doi: 10.3934/environsci.2026009

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  • This study is centered on the measurement of carbon emissions at the provincial level in China and the analysis of their spatial distribution. We address the quantification of regional disparities and the dynamic evolution of emission patterns, which are critical for informing climate governance. Moreover, we aim to systematically measure carbon emissions across Chinese provinces and to investigate the regional disparities and the dynamic evolution in their distribution. Our goal is to provide an empirical basis for formulating differentiated and well-targeted emission reduction policies. The modified carbon emission factor method was employed for accounting. The Theil index and its decomposition were used to quantify regional disparities, while kernel density estimation was applied to characterize the dynamic evolution trends of the emission distribution. The results revealed significant regional imbalances in China's carbon emission distribution, with inter-regional differences identified as the primary source of overall disparity. Kernel density curves further showed distinct heterogeneity in distribution shapes and dynamic evolution across regions, reflecting deep-seated differences in emission structures and development stages. Our findings provide critical data for designing differentiated regional carbon reduction strategies and can directly support policy-making for coordinated emission reduction. They offer practical insights for industrial green transition planning at national and provincial levels, aiding in the alignment of economic development with climate targets.



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