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<p>Rapid industrialization in the Pearl River Basin has led to significant urban carbon emissions, posing challenges for sustainable development and climate goals. Understanding the spatiotemporal dynamics and network structure of urban industrial carbon emission efficiency (ICEE) is crucial for effective regional environmental management. This study employs a super-SBM to measure urban ICEE from 2009 to 2019, followed by social network analysis to reveal the spatial interaction patterns of urban ICEEs. The driving factors of the urban ICEE network are identified by quadratic assignment procedure regression. Results show that overall ICEE in the basin exhibits a fluctuating upward trend with significant spatial disparities; core cities like Guangzhou and Shenzhen dominate the network with dense connections, while peripheral cities remain weakly linked. The carbon emission network demonstrates small-world and scale-free properties, indicating high clustering and hub dominance. QAP analysis reveals that geographical proximity, economic development level, and industrial structure similarity significantly promote network formation, whereas differences in environmental regulation hinder linkages. The findings highlight the necessity for differentiated regional policies focusing on enhancing inter-city cooperation, optimizing industrial layouts, and strengthening environmental governance. Coordinated efforts among cities can improve carbon emission efficiency and support sustainable industrial transformation in the Pearl River Basin.</p>

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Study of the spatiotemporal dynamics of urban industrial carbon emission networks in the Pearl River Basin, China

  • 期刊论文

  • 发表日期：

    2025年12月10日

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  • Yi-ni Meng,
  • Jian Yin,
  • Hongtao Jiang,
  • Xiyue Tu

摘要

Rapid industrialization in the Pearl River Basin has led to significant urban carbon emissions, posing challenges for sustainable development and climate goals. Understanding the spatiotemporal dynamics and network structure of urban industrial carbon emission efficiency (ICEE) is crucial for effective regional environmental management. This study employs a super-SBM to measure urban ICEE from 2009 to 2019, followed by social network analysis to reveal the spatial interaction patterns of urban ICEEs. The driving factors of the urban ICEE network are identified by quadratic assignment procedure regression. Results show that overall ICEE in the basin exhibits a fluctuating upward trend with significant spatial disparities; core cities like Guangzhou and Shenzhen dominate the network with dense connections, while peripheral cities remain weakly linked. The carbon emission network demonstrates small-world and scale-free properties, indicating high clustering and hub dominance. QAP analysis reveals that geographical proximity, economic development level, and industrial structure similarity significantly promote network formation, whereas differences in environmental regulation hinder linkages. The findings highlight the necessity for differentiated regional policies focusing on enhancing inter-city cooperation, optimizing industrial layouts, and strengthening environmental governance. Coordinated efforts among cities can improve carbon emission efficiency and support sustainable industrial transformation in the Pearl River Basin.