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Decoupling effect of carbon emissions in the Yangtze River Delta region based on GDIM factor decomposition

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IntroductionQuantifying carbon emissions and identifying their drivers are essential for formulating effective climate policies in key economic zones. This study analyzes the decoupling effects and driving factors of carbon emissions in China’s Yangtze River Delta region from 2008 to 2022.MethodsUsing provincial-level energy balance sheets, carbon emissions were estimated via a top-down approach. The extended Generalized Divisia Index Method (GDIM) decomposed emission drivers, and a novel decoupling index model was developed by integrating GDIM with traditional decoupling analysis to quantify factors’ contributions.ResultsTotal carbon emissions exhibited an initial increase followed by a decline, with an overall reduction exceeding 65%. Economic scale was the primary driver of emission growth, while output carbon intensity was the dominant mitigating factor; energy consumption carbon intensity and energy intensity showed significant emission reduction potential. Most decoupling indices were positive, indicating measurable decoupling progress, with Shanghai achieving strong decoupling (index: 1.5603) during 2014–2016. Decoupling effects transitioned from weak to strong and back to weak across sub-periods, highlighting robust mid-term efforts that weakened later. Output carbon intensity promoted decoupling, whereas energy scale inhibited it.DiscussionPolicy recommendations include developing region-specific carbon reduction strategies, enhancing low-carbon technology R&D and implementation, and continuously optimizing energy structure to sustain decoupling efforts.
Title: Decoupling effect of carbon emissions in the Yangtze River Delta region based on GDIM factor decomposition
Description:
IntroductionQuantifying carbon emissions and identifying their drivers are essential for formulating effective climate policies in key economic zones.
This study analyzes the decoupling effects and driving factors of carbon emissions in China’s Yangtze River Delta region from 2008 to 2022.
MethodsUsing provincial-level energy balance sheets, carbon emissions were estimated via a top-down approach.
The extended Generalized Divisia Index Method (GDIM) decomposed emission drivers, and a novel decoupling index model was developed by integrating GDIM with traditional decoupling analysis to quantify factors’ contributions.
ResultsTotal carbon emissions exhibited an initial increase followed by a decline, with an overall reduction exceeding 65%.
Economic scale was the primary driver of emission growth, while output carbon intensity was the dominant mitigating factor; energy consumption carbon intensity and energy intensity showed significant emission reduction potential.
Most decoupling indices were positive, indicating measurable decoupling progress, with Shanghai achieving strong decoupling (index: 1.
5603) during 2014–2016.
Decoupling effects transitioned from weak to strong and back to weak across sub-periods, highlighting robust mid-term efforts that weakened later.
Output carbon intensity promoted decoupling, whereas energy scale inhibited it.
DiscussionPolicy recommendations include developing region-specific carbon reduction strategies, enhancing low-carbon technology R&D and implementation, and continuously optimizing energy structure to sustain decoupling efforts.

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