Embodied Carbon Emissions and Regional Transfer Characteristics—Evidence from China

Zhao, Hehua; Chen, Hongwen; Lei, He

doi:10.3390/su14041969

Cited by 6 publications

(4 citation statements)

References 46 publications

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“…In recent years, the Multi-regional input-output model (MRIO) model has gradually become a mainstream analytical instrument to study carbon transfer [60][61][62]. In this paper, this model is used to quantify the amount and transfer of interregional sectoral carbon emissions among 30 provinces in China.…”

Section: Multi-regional Input-output Modelmentioning

confidence: 99%

Temporal and Spatial Divergence of Embodied Carbon Emissions Transfer and the Drivers—Evidence from China’s Domestic Trade

2023

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To understand the embodied carbon transfer in China’s domestic trade from 2007 to 2017 and its driving forces, we quantitatively measured the embodied carbon transfer among 30 provinces by using the Multi-regional input-output (MRIO) model, explored the temporal and spatial evolutionary features of the interprovincial embodied carbon emission transfer by using spatial autocorrelation, and further revealed its drivers using the Geographical Detector Model for the first time. We find that: (1) Based on the producer and consumer accounting principles, the amount of embodied carbon emissions of each province has increased, and there are huge differences. (2) The number of provinces with net embodied carbon emissions transfer is increasing, to 18 in 2017 and the target provinces are mostly energy-rich regions, such as Shanxi, Xinjiang, and Inner Mongolia, which have a severe “carbon leakage” phenomenon with developed coastal provinces. (3) The scale and spatial distribution of net carbon transfer out shows a characteristic of “high in the north and low in the south”, and the tendency of net transfer from the less developed provinces to the developed regions is becoming more and more obvious. (4) The global differences in the promoting factors of the net embodied carbon transfer are not prominent, but the differences at the local scale are significant, with energy intensity and environmental regulation playing an increasingly significant role. Therefore, it is recommended to strengthen low-carbon technology innovation and environmental regulation, increase the percentage of renewable energy consumption, accelerate the mobility of various resource factors, and improve energy utilization efficiency.

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Section: Multi-regional Input-output Modelmentioning

confidence: 99%

Temporal and Spatial Divergence of Embodied Carbon Emissions Transfer and the Drivers—Evidence from China’s Domestic Trade

2023

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“…The input-output (IO) method proposed by Leontief [31] has been used since the 1960s to describe and analyze economic-environmental relationships [13]. Input-output analysis can be further divided into Single-Region Input-Output (SRIO) [32], Bilateral Trade Input-Output (BTIO) [24], and the Multi-Regional Input-Output [33]. The key differences between the three models are mainly related to the technical level setting and the handling of imported intermediate products.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatiotemporal Variation and Driving Factors of Embodied Carbon in China-G7 Trade

2022

Sustainability

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China and G7 countries contribute 70% global GDP and 55% global carbon emissions. The carbon leakage between China and G7 is a crucial issue in achieving the synergetic emission abatement globally. The motivation of this study is to evaluate the embodied carbon transfer between China and G7 in the trade between 2000 and 2014, and investigate the driving factors that impact the embodied carbon trend. A multiregional input–output (MRIO) model based on the WIOD database is constructed, and a structural decomposition analysis (SDA) is employed. The results indicate that China plays the role of net exporter of embodied carbon in trade with G7, which mainly flows to the US (5825.67 Mt), Japan (3170.36 Mt) and Germany (1409.93 Mt). However, China’s embodied carbon exports to the G7 show an inverted U-shaped trend with a turning point after financial crisis, while the G7’s embodied carbon exports to China continue to rise. The conclusion is that to achieve the climate goal of carbon neutrality, it is not enough to rely solely on the low-carbon transition on the production side, the demand side should also be adjusted.

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“…The carbon emission data are from "Emission Inventories for 30 Provinces 2012, 2015 and 2017" downloaded in CEADS [5][6][7]36]. The 45 sectors in the tables are combined into 13, including Agriculture (01), Mining and Dressing (02-07), Food and Tobacco (09-12), Textile and clothing (13)(14)(15), Wood processing (08, 16,17), Papermaking and printing (18)(19)(20), Petrochemical (21)(22)(23)(24)(25)(26), Metal and non-metal (27)(28)(29)(30), Equipment manufacturing (31)(32)(33)(34)(35)(36), Other manufacturing (37)(38), Electric and water supply (39)(40)(41), Construction (42) and Service (43-45) (the numbers with the sector are the serial numbers in the carbon emission tables). All the abbreviations of this paper are shown in Appendix A Table A1.…”

Section: Data Sourcesmentioning

confidence: 99%

“…In contrast, the research on the transfer of carbon emissions driven by interregional trade started relatively late. With the development of the method of compiling multi-regional input-output tables, Isard [28] first proposed the MRIO model, pointing out that compared with the SRIO model, the MRIO model takes into account the technological differences in different regions and the industrial trade between regions, so that different economies and sectors can be linked through intraregional and interregional trade, and the embodied carbon emissions of various sectors between regions through trade can be captured [29]. Relevant achievements mainly include city-centered researches and country-centered researches.…”

Section: Introductionmentioning

confidence: 99%

Virtual Carbon Flow in China’s Capital Economic Circle: A Multi-Regional Input–Output Approach

2022

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The Capital Economic Circle (CEC) is the area with the largest economic aggregate in northern China and has a strong status in driving the economic development of China. However, the industrial structure dominated by high energy consuming industries leads to a large number of carbon dioxide emissions, and the imbalance between economic development and carbon emissions in CEC is serious; therefore, it is necessary to explore how to solve the carbon imbalance problem of the CEC by relying on interregional cooperation. Based on China's multi-regional input–output tables of 2012, 2015 and 2017, this paper proposes the CEC carbon-extended, multi-regional input–output model to measure virtual carbon flow and analyze how the industrial structure leads to the imbalance of carbon flow distribution in CEC. Indicators such as direct carbon emission coefficients, complete carbon emission coefficients and carbon emissions pull coefficients of the industrial sectors in CEC are calculated and the physical carbon emission and virtual carbon flows among the industrial sectors and the regions are evaluated. The results show that there are potential constraints from the uncoordinated configuration of industrial innovation chains among the CEC, and the “carbon imbalance” of CEC is mainly reflected in the backward production technology of Hebei and its inefficient connection with the industrial innovation chain of Beijing and Tianjin. It is suggested that policymakers should promote the low-carbon production system and strengthen green energy development and utilization to enhance green development in CEC. In future research, we should pay attention to the updating method of the input–output table and the development of carbon circular networks. This study has implications for some areas of China and developing countries in Asia, which also have an imbalance between industrial economy development and carbon emissions, and a similarity in space structure and industry layout with CEC.

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Embodied Carbon Emissions and Regional Transfer Characteristics—Evidence from China

Cited by 6 publications

References 46 publications

Temporal and Spatial Divergence of Embodied Carbon Emissions Transfer and the Drivers—Evidence from China’s Domestic Trade

Temporal and Spatial Divergence of Embodied Carbon Emissions Transfer and the Drivers—Evidence from China’s Domestic Trade

Spatiotemporal Variation and Driving Factors of Embodied Carbon in China-G7 Trade

Virtual Carbon Flow in China’s Capital Economic Circle: A Multi-Regional Input–Output Approach

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