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<p>As global pressure to combat climate change intensifies, carbon reduction has emerged as a common priority. This study incorporates the Logarithmic Mean Divisia Index (LMDI) method into the Tapio model to enhance the conventional analysis of carbon emissions (CE). Using industrial sector data from Quanzhou, China (2005–2022), it identifies the key driving factors of CE and evaluates their influence on decoupling trends. The LMDI method identified the most significant drivers, which were then used to forecast future emissions. Results indicate that the industrial development (ID) effect is the primary driver of rising CE. During the study period, the industrial sector transitioned from expansion connection to weak decoupling, with energy structure (ES) and energy intensity (EI) effects significantly influencing this shift. The low carbon development scenario (LCDS) represents the most effective pathway for Quanzhou’s industrial sector to achieve sustainability while maintaining economic growth and peaks at 97,191 × 10<sup>4</sup> t in 2030. These findings offer crucial insights for policymakers in Quanzhou, enabling them to develop targeted strategies that harmonize economic growth with energy conservation and carbon reduction. Additionally, they provide valuable insights for promoting low-carbon industrial growth in other urban areas.</p>

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Decoupling and decomposition analysis of industrial carbon emissions, and projection of its future trends: A case study of Quanzhou, China

  • 期刊论文

  • 发表日期：

    2025年11月26日

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  • Yanxi Tang,
  • Jing Xu,
  • Muping Shen,
  • Jiachang Zuo,
  • Fengyi Yu,
  • Yingmao Tang,
  • Tingting Liu,
  • Hongjun Jin,
  • Yongjin Luo,
  • Qingrong Qian,
  • Qinghua Chen

摘要

As global pressure to combat climate change intensifies, carbon reduction has emerged as a common priority. This study incorporates the Logarithmic Mean Divisia Index (LMDI) method into the Tapio model to enhance the conventional analysis of carbon emissions (CE). Using industrial sector data from Quanzhou, China (2005–2022), it identifies the key driving factors of CE and evaluates their influence on decoupling trends. The LMDI method identified the most significant drivers, which were then used to forecast future emissions. Results indicate that the industrial development (ID) effect is the primary driver of rising CE. During the study period, the industrial sector transitioned from expansion connection to weak decoupling, with energy structure (ES) and energy intensity (EI) effects significantly influencing this shift. The low carbon development scenario (LCDS) represents the most effective pathway for Quanzhou’s industrial sector to achieve sustainability while maintaining economic growth and peaks at 97,191 × 104 t in 2030. These findings offer crucial insights for policymakers in Quanzhou, enabling them to develop targeted strategies that harmonize economic growth with energy conservation and carbon reduction. Additionally, they provide valuable insights for promoting low-carbon industrial growth in other urban areas.