Effects of carbon emission transfer on economic spillover and carbon emission reduction in China

Sun, Luanhong; Wang, Qunwei; Zhou, P.; Cheng, Faxin

doi:10.1016/j.jclepro.2014.12.083

Cited by 68 publications

(35 citation statements)

References 22 publications

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“…There are two types of model that can analyze the embodied carbon emissions from a consumer-based perspective: the single input-output model, SIO, and multi-regional input-output model, MRIO [11]. SIO is mainly focused on the calculation of ECE, while MRIO tends to focus on the ECE flows between different regions [21,35,40]. Therefore, in this paper, we applied the MRIO model to analyze the ECE flows among China's provinces.…”

Section: Methodsmentioning

confidence: 99%

“…This method provides an efficient way to allocate the CER tasks to different cities [20]. Sun et al (2016) studied the effect of economic spillover on regional CER task transfer [21]. The results show that the reduction in task transfer between certain provinces is relatively efficient for the overall reduction target.…”

Section: Previous Carbon Emission Reduction Task Allocation Researchmentioning

confidence: 99%

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Provincial Carbon Emissions Reduction Allocation Plan in China Based on Consumption Perspective

et al. 2018

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China is a country with substantial differences in economic development, energy consumption mix, resources, and technologies, as well as the development path at the provincial level. Therefore, China's provinces have different potential and degrees of difficulty to carry out carbon emission reduction (CER) requirements. In addition, interprovincial trade, with a large amount of embodied carbon emissions, has become the fastest growing driver of China's total carbon emissions. A reasonable CER allocation plan is, therefore, crucial for realizing the commitment that China announced in the Paris Agreement. How to determine a fair way to allocate provincial CER duties has become a significant challenge for both policy-makers and researchers. In this paper, ecological network analysis (ENA), combined with a multi-regional input-output model (MRIO), is adopted to build an ecological network of embodied emissions across 30 provinces. Then, by using flow analysis and utility analysis based on the ENA model, the specific relationships among different provinces were determined, and the amount of responsibility that a certain province should take quantified, with respect to the embodied carbon emission (ECE) flows from interprovincial trade. As a result, we suggest a new CER allocation plan, based on the detailed data of interprovincial relationships and ECE flows.

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Section: Methodsmentioning

confidence: 99%

Section: Previous Carbon Emission Reduction Task Allocation Researchmentioning

confidence: 99%

Provincial Carbon Emissions Reduction Allocation Plan in China Based on Consumption Perspective

et al. 2018

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“…Xu et al [33] reveal that for every 1% increase in industrial transfer, there is a 0.327% increase in industrial carbon transfer before passing the turning point. Sun et al [34] find that the transfer amount of carbon emissions in China's most provinces is relatively large, and on the whole, the carbon emission import is higher than the export.…”

Section: Literature Reviewmentioning

confidence: 99%

The Moderating Effect of R&D Investment on Income and Carbon Emissions in China: Direct and Spatial Spillover Insights

Peng

Tan

2019

Sustainability

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R&D investment plays a great role in achieving China’s low-carbon economy goals, which has a moderating effect on the relationship between income and carbon emissions. Furthermore, such a moderating effect may have spatial differences, given the possible spatial dependence of carbon emissions. Therefore, this paper explores the direct and spatial spillover moderating effects of R&D investment by adopting the panel spatial Durbin model and data of 30 provinces in China during 1998–2015. The empirical results firstly indicate that R&D investment moderates the positive impact of income on local carbon emissions for both the non-spatial and spatial model, and that more R&D investment can make carbon emissions reach the turning point earlier. Secondly, R&D investment in the local province increases the positive influence of local income on neighboring carbon emissions, which mainly results from the transfer effect of carbon emissions rather than the knowledge spillovers effect. The results are indicated to be robust by three types of robustness analyses. Finally, FDI and patents are the main constrained forces of local and neighboring carbon emissions; coal consumption is the main driver of local carbon emissions.

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“…: Y = Y �� + Y �� (4) Assuming that EF �� represents a matrix constituted by the CO � emission intensities of various industry sectors in the horizontal direction, the CO � emission of these industry sectors can be obtained via Formula (2)： C = EF �� (I − A �� ) �� (Y �� + Y �� ) (5) A �� represents the direct consumption matrix of industry sectors in the horizontal direction. Based on the connotation of industrial carbon emission exports (Sun, 2017) [6] , we can obtain the carbon emission exports volume C �� for each industry sector (Su, 2010 [7] ; Sun, 2016 [8] ).…”

Section: Measurement Model For Industrial Carbon Emission Transfermentioning

confidence: 99%

Optimization of Inter-industry Carbon Emission Transfer Structure Based on Decoupling Effects: an empirical analysis from Chinese industry

2018

Self Cite

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This paper utilizes 27 Chinese industry sectors as study objects, and measures the decoupling effects of the industrial carbon emission transfer; furthermore, this paper proposes several optimizing strategies for an inter-industry carbon emission transfer structure toward the realization of dual goals, i.e., industrial economic development and industrial carbon emission reduction. The research result shows that: Different industries show different decoupling effects of carbon emission transfer, and the distribution of the six states of decoupling effects could all be observed. With respect to dynamic variations, the decoupling effects of industrial carbon emission transfer were optimal during the late stage, and the decoupling effects during 2010-2012 were the most optimal. With respect to the optimizing strategies for the inter-industry carbon emission transfer, efforts should be focused on increasing the carbon emission exports, while reducing the carbon emission imports of 11 industries (CMWI and others). Future efforts should be directed at increasing carbon emission imports and reducing carbon emission exports in the three industries of CLII, PPSM, and MPI, while increasing both carbon emission exports and imports in 10 industries (FMTP and others), and reducing both carbon emission imports and exports in the three industries of MMII, OMW, and WRT.

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Effects of carbon emission transfer on economic spillover and carbon emission reduction in China

Cited by 68 publications

References 22 publications

Provincial Carbon Emissions Reduction Allocation Plan in China Based on Consumption Perspective

Provincial Carbon Emissions Reduction Allocation Plan in China Based on Consumption Perspective

The Moderating Effect of R&D Investment on Income and Carbon Emissions in China: Direct and Spatial Spillover Insights

Optimization of Inter-industry Carbon Emission Transfer Structure Based on Decoupling Effects: an empirical analysis from Chinese industry

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