Research on the evolution and influencing factors of carbon emission efficiency in the Yangtze River Delta urban agglomeration

Enhancing carbon emission efficiency is a critical pathway for advancing global climate governance and achieving the “Dual Carbon” goals. Precisely mapping the spatiotemporal evolution patterns of carbon emission efficiency in urban agglomerations and thoroughly analyzing the underlying driving mechanisms are of paramount importance for optimizing the nation’s overall carbon neutrality pathway. This study examines 26 cities within the Yangtze River Delta urban agglomeration from 2005 to 2023. Employing methods such as the Super-EBM model, exploratory spatiotemporal data analysis, and the Tobit model, it delves into the spatiotemporal evolution of carbon emission efficiency and its influencing factors. Key findings include: (1) Overall carbon emission efficiency remained stable at approximately 0.85 during the study period, with minor fluctuations. (2) Significant spatial disparities in carbon emission efficiency emerged, exhibiting gradually increasing convergence. (3) Local spatial structures of carbon emission efficiency were relatively dynamic yet demonstrated strong spatial dependence, while overall spatial structures remained stable with pronounced spatial cohesion. (4) Urbanization level, economic development level, population density, degree of openness, and technological innovation have a significant impact on improving carbon emission efficiencye, whereas industrial structure and environmental regulation showed no significant promotional impact.

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Publication Details

Journal
Frontiers in Environmental Science
Published
2026-01-22
DOI
https://doi.org/10.3389/fenvs.2026.1750480
Primary Topic
Energy, Environment, Economic Growth
Type
article
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article

Research on the evolution and influencing factors of carbon emission efficiency in the Yangtze River Delta urban agglomeration

Zhe Yang, Chao Hu
Frontiers in Environmental Science
Energy, Environment, Economic Growth
article

Research on the evolution and influencing factors of carbon emission efficiency in the Yangtze River Delta urban agglomeration

Zhe Yang, Chao Hu
article en

Abstract

Enhancing carbon emission efficiency is a critical pathway for advancing global climate governance and achieving the “Dual Carbon” goals. Precisely mapping the spatiotemporal evolution patterns of carbon emission efficiency in urban agglomerations and thoroughly analyzing the underlying driving mechanisms are of paramount importance for optimizing the nation’s overall carbon neutrality pathway. This study examines 26 cities within the Yangtze River Delta urban agglomeration from 2005 to 2023. Employing methods such as the Super-EBM model, exploratory spatiotemporal data analysis, and the Tobit model, it delves into the spatiotemporal evolution of carbon emission efficiency and its influencing factors. Key findings include: (1) Overall carbon emission efficiency remained stable at approximately 0.85 during the study period, with minor fluctuations. (2) Significant spatial disparities in carbon emission efficiency emerged, exhibiting gradually increasing convergence. (3) Local spatial structures of carbon emission efficiency were relatively dynamic yet demonstrated strong spatial dependence, while overall spatial structures remained stable with pronounced spatial cohesion. (4) Urbanization level, economic development level, population density, degree of openness, and technological innovation have a significant impact on improving carbon emission efficiencye, whereas industrial structure and environmental regulation showed no significant promotional impact.

Frontiers in Environmental ScienceVol. 14
Chongqing Normal University (CN), Chongqing Technology and Business University (CN), Chongqing University of Technology (CN)
Openalex Percentile: Top 84%
Energy, Environment, Economic Growth
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Research on the evolution and influencing factors of carbon emission efficiency in the Yangtze River Delta urban agglomeration — Zhe Yang, Chao Hu · Frontiers in Environmental Science (2026) | TGRS Research Map | TGRS