Spatial difference, dynamic evolution and influencing factors of carbon emission efficiency in China at the provincial level

Abstract

As the world's largest carbon emitter, China is actively pursuing its goals of carbon peaking and carbon neutrality. This has necessitated the analysis of the spatial and temporal differences in interprovincial carbon emission efficiency (CEE). This study develops a multimethod analytical framework to systematically investigate the static differences, dynamic evolution, and influencing factors of CEE across 30 provincial-level administrative regions in China from 2007 to 2021. Results demonstrate the national average CEE fluctuating between 0.878 and 1.093, with the central region exhibiting the highest mean efficiency at 0.9627 from a static perspective. Considerable disparities are observed between the eastern and western regions. Moreover, high-CEE regions are observed to suppress CEE growth in neighboring low-CEE areas. The Gini coefficient decomposition method reveals inter-regional differences as the main source of the overall inequality, accounting for 67.31% on average. Urbanization and industrial upgrading are observed to be the drivers of CEE, with population density being the strongest suppressor. GDP per capita and technological development are observed to contribute to regional CEE disparities via considerable negative spatial spillover effects. These findings provide a valuable basis for coordinating regional carbon emission reductions in China.

Keywords

Dynamic evolution / Spatial and temporal differences / Influencing factors / Carbon emission efficiency

CRediT authorship contribution statement

Zhinan Hou: Writing – review & editing, Writing – original draft, Visualization, Software, Methodology, Investigation, Data curation, Conceptualization. Zhenglong Cao: Visualization, Methodology, Investigation, Data curation. Chongyang Zhao: Visualization, Methodology, Investigation, Data curation. Yuncheng Zhang: Visualization, Methodology, Investigation, Data curation. Dantong Zhang: Visualization, Methodology, Investigation, Data curation. Shuqi Dai: Visualization, Methodology, Investigation, Data curation. Qiao Ma: Writing – review & editing, Methodology. Qingsong Wang: Writing – review & editing, Methodology. Feifei Liu: Writing – review & editing, Methodology. Jian Zuo: Writing – review & editing, Methodology. Xueliang Yuan: Writing – review & editing, Writing – original draft, Supervision, Funding acquisition, Conceptualization.

Declaration of competing interest

Xueliang Yuan is an executive editor for Green Energy and Resources and was not involved in the editorial review or the decision to publish this article. The authors declare the following financial interests/personal relationships which may be considered as competing interests: Zhenglong Cao, Chongyang Zhao and Yuncheng Zhang are currently employed by Jinan International Airport Construction Co., Ltd. Other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This research is supported by Key R&D Program of Shandong Province (2023SFGC0101), Shandong Provincial Natural Science Foundation (ZR2024QE013), Taishan Scholar Project (tsqn202103010), and Shandong Provincial Housing and Urban-Rural Construction Science and Technology Plan Project (2025RKX-LSDT048).

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