Evidence map›Paper›PMID 34595707›Full record

ArticleEnvironmental science and pollution research international2022

What drives the export-related carbon intensity changes in China? Empirical analyses from temporal-spatial-industrial perspectives.

Qiaoling Shi, Yuhuan Zhao, Chao Zhong

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Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Qiaoling ShiSchool of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China.
Yuhuan ZhaoSchool of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China. zhaoyuhuan@bit.edu.cn.ORCID http://orcid.org/0000-0003-2188-9702
Chao ZhongBusiness School, Beijing Normal University, Beijing, 100875, China. v_zhongchao@163.com.

Funding

Natural Science Foundation of Beijing Municipality 17JDYJB010
6 · The paper itself

Abstract

This study aims to explore the driving determinants on the export-related carbon intensity (ECI) of China, to better understand the impact of international trade on climate change governance and facilitate China's carbon intensity mitigation goals. First, China's ECI evolution and its gaps with the USA and India are measured during 2002-2014. Then, the main drivers of China's ECIvert study further discusses the influencing factors of ECI in the manufacturing industry using the environmental-extended STIRPAT model and GMM method. The results show that (1) China's overall ECI increases from 1.50 Kg/US$ in 2002 to 1.92 Kg/US$ in 2005 and then decreases to 1.27 Kg/US$ in 2014. The ECI of the manufacturing industry is significantly higher than that of the agriculture and service industry. China's ECI gap with the USA is greater than that with India, and both show a downward trend. (2) Carbon emission coefficient is the domain factor to reduce China's ECI during 2002-2014; the effects of the value-added coefficient, input-output structure, and final demand are limited. The input structure dominantly expands China's ECI gaps both with the USA and India, followed by the value-added coefficient. The carbon emission coefficient enlarges the ECI gap with the USA while reduces that with India. (3) Industrial productivity and value-added rate are negatively correlated with ECI in the manufacturing industry, while per capita capital stock plays the opposite role. The positive correlation between energy intensity and CIE becomes significant after distinguishing technology heterogeneity. In contrast to the non-tech-intensive manufacturing industry, the increase of backward GVCs participation of tech-intensive ones will reduce the ECI. The threshold effect of backward GVCs participation exists in the whole manufacturing industry. Targeted ECI reduction policy implications are suggested.

Indexed as

CarbonCommerceCarbon DioxideChinaInternationalityCarbonCarbon DioxideDriving determinantsExport-related carbon intensity (ECI)Manufacturing industrySTIRPAT modelTemporal and spatial SDA model

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