Mapping the Transmission of Carbon Emission Responsibility Among Multiple Regions from the Perspective of the Energy Supply Chain: EA-MRIO Method and a Case Study of China
Yuan Yuan,
Yunlong Zhao,
Honghua Yang,
Chin Hao Chong,
Linwei Ma (),
Shiyan Chang and
Zheng Li
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Yuan Yuan: State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China
Yunlong Zhao: China Electric Power Planning & Engineering Institute, Beijing 100120, China
Honghua Yang: China Electric Power Research Institute, State Grid Corporation of China, Beijing 100192, China
Chin Hao Chong: State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China
Linwei Ma: State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China
Shiyan Chang: Tsinghua-Rio Tinto Joint Research Centre for Resources, Energy and Sustainable Development, Laboratory for Low Carbon Energy, Tsinghua University, Beijing 100084, China
Zheng Li: State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China
Sustainability, 2025, vol. 17, issue 18, 1-22
Abstract:
In low-carbon transition policy management, rationally determining the energy-related carbon emission responsibilities (ERCERs) across multiple regions is a fundamental issue. Reasonable allocation must take into account regional heterogeneities, such as energy endowments, economic development levels, industrial structures, and complex interconnections within the multi-regional energy supply chain. Previous studies mostly analyzed it via the multi-regional input–output (MRIO) model on the energy-consumption side, often neglecting the regional distribution of energy production and inter-regional energy transport on the energy-production side. This limitation risks a mismatch between energy policies and economic policies in practical policy governance. To address this gap, this study develops an energy allocation-induced MRIO (EA-MRIO) method integrating energy allocation analysis and an MRIO model to trace ERCER transmissions holistically across the entire energy supply chain. The framework covers seven stages including energy supply, inter-regional energy transport, direct energy consumption of end-use sectors, inter-regional intermediate products input and output, final products supply, inter-regional final products transport, and final demand, applied to a case study of China’s 31 provinces in 2017. Results show that ERCERs mainly transfer from western and northern regions to eastern and southern coastal areas: ERCERs embodied by energy production in western and northern provinces first flow to northern coastal provinces (main intermediate products producers), then to eastern and southern coastal provinces (main final products producers), with 23% ultimately attributed to exports. These findings call for allocating ERCERs based on different subregions’ roles within the national energy–economic system to facilitate more equitable and effective carbon reduction policymaking.
Keywords: energy-related carbon emission responsibility; multi-regional energy supply chain; energy allocation analysis; multi-regional input-output model; spatial transmission; sankey diagram; sustainable development (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:18:p:8166-:d:1746799
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