Study of Potential Embodied Carbon Transfer Flows Based on Link Prediction Model

Ruijin Du, Yue Liu, Xiaorui Guo, Gaogao Dong (), Lixin Tian, Xinghua Fan and Muhammad Ahsan
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Ruijin Du: Institute of Carbon Neutrality Development, Jiangsu University, Zhenjiang 212013, China
Yue Liu: School of Mathematical Sciences, Jiangsu University, Zhenjiang 212013, China
Xiaorui Guo: School of Mathematical Sciences, Jiangsu University, Zhenjiang 212013, China
Gaogao Dong: School of Mathematical Sciences, Jiangsu University, Zhenjiang 212013, China
Lixin Tian: Institute of Carbon Neutrality Development, Jiangsu University, Zhenjiang 212013, China
Xinghua Fan: School of Mathematical Sciences, Jiangsu University, Zhenjiang 212013, China
Muhammad Ahsan: School of Mathematical Sciences, Jiangsu University, Zhenjiang 212013, China

Energies, 2025, vol. 18, issue 8, 1-23

Abstract: In the increasingly severe situation of global climate change, reducing CO 2 emissions has become the consensus of governments. Grounded in the principle of consumer responsibility, policymakers are increasingly focusing on the cross-regional transfer of carbon emissions to delineate responsibilities more clearly. Evaluating embodied carbon emissions ( E C s ) in goods and services and forecasting transfer pathways is essential for driving the energy transition and devising effective carbon-reduction strategies. This study summarizes the evolutionary characteristics of the global E C -transfer network from 2013 to 2022 and analyzes the underlying causes. Further, a link prediction model incorporating both endogenous and exogenous factors is developed to investigate potential E C -transfer pathways. The findings reveal the following: (1) Since 2013, China, Russia, and India have dominated net E C out-strength, accounting for over 70% of total E C -transfer strength, primarily directed towards the European Union (EU) and the United States (USA). (2) The analysis of net E C out-intensity and in-intensity indicates that countries like Russia and South Africa have more carbon-emitting export-oriented industries in their economic structure and should transfer the corresponding carbon-emission responsibility to downstream consuming countries. Countries like Mexico and Switzerland, due to their reliance on importing E C -intensive products, should assume the corresponding carbon-emission responsibility. (3) Economies such as Germany, China, the USA, and France, characterized by high E C -transfer efficiency, serve as key drivers for the implementation of global emission-reduction strategies. (4) The link prediction based on the proposed hybrid similarity indicator has the highest accuracy. The results reveal a higher probability of forming stable links between net E C importers, and between net E C importers and exporters. This study enhances policymakers’ understanding of international trade and E C management, and facilitates the development of long-term strategies for cross-national collaborative emission reduction.

Keywords: embodied carbon emissions transfer; link prediction; complex network; structural evolution (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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