CO2 mitigation through global supply chain restructuring
CO2 mitigation through global supply chain restructuring
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DOI:
10.1016/j.eneco.2021.105768
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发表时间:
2021-12
期刊:
影响因子:
12.8
通讯作者:
Keitaro Maeno;Shohei Tokito;S. Kagawa
中科院分区:
文献类型:
--
作者:
Keitaro Maeno;Shohei Tokito;S. Kagawa
This study develops an integrated analysis framework, called scenario-based extraction method (SEM) using four different input-output methods—unit structure analysis, cluster analysis, extended global extraction analysis and structural decomposition analysis. For the empirical analysis, we used the latest 2014 World Input–Output Database and modeled the global supply chain (GSC) CO2network structure induced by the final demand for one relevant industry in one relevant country (the Japanese automobile industry in this study). The cluster analysis based on the GSC network data revealed CO2emission-intensive clusters existed in this network with overconcentrated CO2emissions outside of Japan. From the SEM analysis, we also found that the restructuring of the Japanese automotive supply chain based on extracting the largest CO2emission cluster (i.e., CO2emission hotspot) reduces its global carbon footprint by 6.5%. Simultaneously, the restructuring increases CO2emissions in all countries other than a hotspot country, particularly in some important locations for the substitute production. We conclude that Japan's current automotive supply chain can significantly reduce CO2emissions through structural reforms. Our framework can help in designing appropriate policies for restructuring green supply chains.