Literature DB >> 31863995

Imbalance of carbon embodied in South-South trade: Evidence from China-India trade.

Qiang Wang1, Xue Yang2.   

Abstract

China and India are the countries with the largest increase in carbon emissions and one of the fastest growing economies in the world. A better understanding of the carbon emissions embodied in China-India trade can service to curb carbon emission in both countries. In this work, we investigated temporal change and driving forces of the carbon emissions embodied in China-India trade from 2000 to 2015 using the Multi-Regional Input-Output model and Structural Decomposition Analysis. The results showed China was a net exporter of embodied carbon and a net exporter of trade in China-India trade, which indicated that China increased its environmental costs while gaining economic benefits. And the imbalance in China's embodied carbon trade was far greater than the trade imbalance. The industrial structure of China's export of embodied carbon and India's export of embodied carbon were difference, although electricity and heavy manufacturing industries dominated the embodied carbon exports of China and India. The decomposition results showed the leading contributor to increase in the embodied carbon emissions of China and India was the increase in final demand, in which the effect of per capita demand was the main driving factor affecting the change of embodied carbon emissions. The carbon intensity coefficient effect was the driving factor in suppressing the increase in embodied carbon emissions in China and India. This research could enrich the study of carbon emission embodied in South-South trade.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  China-India trade; Embodied carbon emissions; Multi-regional input–output model; South-South trade; Structural decomposition analysis

Year:  2019        PMID: 31863995     DOI: 10.1016/j.scitotenv.2019.134473

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


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