Inter-provincial embodied carbon emission space and industrial transfer paths in China

• Published in: PloS one Vol. 19; no. 6; p. e0300478
• Main Authors: Zhang, Wenying, Yang, Mengqi, Ge, Jianhua, Wang, Gangzhen
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 27.06.2024; Public Library of Science (PLoS)
• Subjects: Agglomeration; Analysis; Carbon; Carbon - analysis; Carbon emissions; Carbon footprint; China; Clustering; Coastal zone; Decomposition; Earth Sciences; Ecology and Environmental Sciences; Economic development; Economic growth; Emissions; Emissions (Pollution); Energy consumption; Engineering and Technology; Green economy; Industry; International trade; Investigations; People and Places; Physical Sciences; Provinces; Regions; Regulatory agencies; Scale effect; Social Sciences; Thermal power; China; United States > US; Shanxi China
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0300478

To bolster the dual-circulation development model and green economy, this study delves into the spatiotemporal dynamics of implied carbon transfer in China’s inter-provincial and inter-industrial trade, emphasizing its significance for the "dual carbon" objectives. Utilizing multi-regional input-output data from 2012, 2015, and 2017, we employed the multi-region input-output model to gauge embodied carbon transfers across 31 provinces and 28 industries. The Structural Decomposition Analysis (SDA) model further decomposed the growth of trade-related carbon emissions. Key findings include: (1) The electricity and thermal power sectors dominate carbon transfers, with secondary industries seeing rapid growth; (2) Northern provinces significantly outweigh southern ones in carbon transfers and the main direction of it is towards affluent southern coastal regions; (3) Scale effect plays a pivotal role in these transfers. Conclusively, it is crucial for regulatory authorities to rationally formulate region-specific emission policies for inter-regional coordination, and future studies can focus on industrial and spatial clustering effects.