What determines provincial carbon emission reduction performance in China? A study on co-movement effect based on QCA

Provincial carbon emission reduction performance (CERP) evaluation is crucial for China's climate change mitigation efforts. However, existing research lacks an in-depth exploration of the conditions and mechanisms enhancing provincial CERP. This study evaluates provincial CERP during the 13th Five-Year Plan (FYP) period in China using a comprehensive evaluation method and identifies four antecedent conditions influencing CERP based on provincial policy practices: industrial structure adjustment, energy efficiency improvement, energy structure optimization, and supporting mechanisms enhancement. Using the qualitative comparative analysis (QCA) method, this study reveals the complex causal mechanisms driving provincial CERP: 1) single conditions are insufficient to determine high/low CERP, as it results from the co-movement of multiple conditions; 2) there are multiple pathways to achieve high CERP, each requiring the interaction of multiple conditions; 3) different types of provinces have different pathways to high CERP. Specifically, resource-abundant provinces have two pathways to high CERP, where substantial optimization of energy structure is necessary. Resource-lacking provinces have three pathways to high CERP, where substantial improvement in energy efficiency is necessary; and 4) multiple pathways leading to low CERP, all asymmetrically related to those for high CERP. These findings highlight varied pathways to high CERP, offering tailored emission reduction strategies for different provinces.

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Publication Details

Journal
Advances in Climate Change Research
Published
2025-04-25
DOI
https://doi.org/10.1016/j.accre.2025.04.011
Citations
5
Primary Topic
Qualitative Comparative Analysis Research
Type
article
Field-Weighted Citation Impact
21.01

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article

What determines provincial carbon emission reduction performance in China? A study on co-movement effect based on QCA

Xian‐chun Tan, Hongshuo Yan, Yonglong Cheng
5 citations
Advances in Climate Change Research
Qualitative Comparative Analysis Research
21.01
article

What determines provincial carbon emission reduction performance in China? A study on co-movement effect based on QCA

Xian‐chun Tan, Hongshuo Yan, Yonglong Cheng
article en
5 citations

Abstract

Provincial carbon emission reduction performance (CERP) evaluation is crucial for China's climate change mitigation efforts. However, existing research lacks an in-depth exploration of the conditions and mechanisms enhancing provincial CERP. This study evaluates provincial CERP during the 13th Five-Year Plan (FYP) period in China using a comprehensive evaluation method and identifies four antecedent conditions influencing CERP based on provincial policy practices: industrial structure adjustment, energy efficiency improvement, energy structure optimization, and supporting mechanisms enhancement. Using the qualitative comparative analysis (QCA) method, this study reveals the complex causal mechanisms driving provincial CERP: 1) single conditions are insufficient to determine high/low CERP, as it results from the co-movement of multiple conditions; 2) there are multiple pathways to achieve high CERP, each requiring the interaction of multiple conditions; 3) different types of provinces have different pathways to high CERP. Specifically, resource-abundant provinces have two pathways to high CERP, where substantial optimization of energy structure is necessary. Resource-lacking provinces have three pathways to high CERP, where substantial improvement in energy efficiency is necessary; and 4) multiple pathways leading to low CERP, all asymmetrically related to those for high CERP. These findings highlight varied pathways to high CERP, offering tailored emission reduction strategies for different provinces.

Advances in Climate Change ResearchVol. 16(4)
Chinese Academy of Sciences (CN), Institutes of Science and Development (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 1%
Qualitative Comparative Analysis Research
21.01
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