Opportunity and marginal abatement cost savings from China's pilot carbon emissions permit trading system: Simulating evidence from the industrial sectors

2020 ◽  
Vol 271 ◽  
pp. 110975 ◽  
Author(s):  
Yujiao Xian ◽  
Ke Wang ◽  
Yi-Ming Wei ◽  
Zhimin Huang
2019 ◽  
Vol 11 (3) ◽  
pp. 914 ◽  
Author(s):  
Jianguo Zhou ◽  
Yushuo Li ◽  
Xuejing Huo ◽  
Xiaolei Xu

With the official launch of China’s national unified carbon trading system (ETS) in 2017, it has played an increasingly important role in controlling the growth of carbon dioxide emissions. One of the core issues in carbon trading is the allocation of initial carbon emissions permits. Since the industry emits the largest amount of carbon dioxide in China, a study on the allocation of carbon emission permits among China’s industrial sectors is necessary to promote industry carbon abatement efficiency. In this study, industrial carbon emissions permits are allocated to 37 sub-sectors of China to reach the emission reduction target of 2030 considering the carbon marginal abatement cost, carbon abatement responsibility, carbon abatement potential, and carbon abatement capacity. A hybrid approach that integrates data envelop analysis (DEA), the analytic hierarchy process (AHP), and principal component analysis (PCA) is proposed to allocate carbon emission permits. The results of this study are as follows: First, under the constraint of carbon intensity, the carbon emission permits of the total industry in 2030 will be 8792 Mt with an average growth rate of 3.27%, which is 1.57 times higher than that in 2016. Second, the results of the carbon marginal abatement costs show that light industrial sectors and high-tech industrial sectors have a higher abatement cost, while energy-intensive heavy chemical industries have a lower abatement cost. Third, based on the allocation results, there are six industrial sub-sectors that have obtained major carbon emission permits, including the smelting and pressing of ferrous metals (S24), manufacturing of raw chemical materials and chemical products (S18), manufacturing of non-metallic mineral products (S23), smelting and pressing of non-ferrous metals (S25), production and supply of electric power and heat power (S35), and the processing of petroleum, coking, and processing of nuclear fuel (S19), accounting for 69.23% of the total carbon emissions permits. Furthermore, the study also classifies 37 industrial sectors to explore the emission reduction paths, and proposes corresponding policy recommendations for different categories.


2014 ◽  
Vol 1073-1076 ◽  
pp. 2473-2476
Author(s):  
Li Wei Fan ◽  
Xun Zhou

This paper employed a non-radial efficiency analysis technique, namely slacks-based measure, to calculate the marginal abatement cost of carbon emissions. The study was concerning ten manufacturing sectors that have been included in Shanghai’s pilot emission trading scheme. The empirical result shows the overall weighted average marginal abatement cost is 839.3 Yuan/ton. It also indicates that the marginal abatement cost has a negative relationship with carbon emissions. Additionally, the marginal abatement costs vary across the sample sectors. Policy implications are presented based on above results.


2010 ◽  
Vol 7 (sup1) ◽  
pp. 279-288 ◽  
Author(s):  
M. C. Sarofim ◽  
B. J. DeAngelo ◽  
R. H. Beach ◽  
K. A. Weitz ◽  
M. A. Bahner ◽  
...  

2021 ◽  
Vol 13 (24) ◽  
pp. 13693
Author(s):  
Na Liu ◽  
Fu-tie Song

Future emissions scenarios have served as a primary basis for assessing climate change and formulating climate policies. To explore the impact of uncertainty in future emissions scenarios on major outcomes related to climate change, this study examines the marginal abatement cost (MAC) of carbon emissions under the latest Shared Socioeconomic Pathways (SSPs) subject to the economic optimum and the 1.5 °C temperature increase constraint using the Epstein-Zin (EZ) climate model. Taking the ”Regional Rivalry” (SSP3) scenario narrative under the economic optimum as a representative case, the expected MACs per ton CO2 equivalent (CO2e) emissions in the years 2015, 2030, 2060, 2100, and 2200 are: $102.08, $84.42, $61.19, $10.71, and $0.12, respectively. In parallel, the associated expected average mitigation rates (AMRs) are 0%, 63%, 66%, 81%, and 96%, respectively. In summary, in a world developing towards regional rivalry (SSP3) or fossil-fueled development (SSP5) with high mitigation pressure, the MAC values have approximately doubled, compared with the sustainability (SSP1) and inequality (SSP4) storylines with low mitigation pressure levels. The SSP2 (Middle of the Road) shows a moderate MAC decreasing trend with moderate mitigation pressure. The results provide a carbon price benchmark for policy makers with different attitudes towards the unknown future and can be used to formulate carbon mitigation strategy to respond to specific climate goals.


2018 ◽  
Vol 10 (4) ◽  
pp. 558-571 ◽  
Author(s):  
Xianrong Wu ◽  
Junbiao Zhang ◽  
Liangzhi You

PurposeThe purpose of this paper is to estimate shadow prices of agricultural carbon emissions produced by agricultural inputs, rice paddy and burning crop residue, and to explore the impact of cropping pattern on marginal abatement cost (MAC).Design/methodology/approachThe shadow price of agricultural carbon emissions is estimated by applying directional distance function and non-parametric methods.FindingsThe estimated shadow price of agricultural carbon emissions ranges from 6.78 to 557.83 yuan/ton, and the average value is 62.50 yuan/ton (or $10.18/ton). The MAC value varies in different provinces and years. The regional difference of MAC shows a decreasing trend during the investigation period. Cropping pattern shows a significant negative impact on agricultural MAC. A 1 percent decrease of rice proportion leads to a 0.31 percent increase in MAC value. This implies that the higher the proportion of rice is, the lower the economic cost to reduce agricultural carbon emissions would be.Practical implicationsIt is feasible to draw up appropriate mechanisms for the allocation of emission reduction responsibilities according to conditions in various regions, with emphasis on the local cropping patterns. There is a trade-off between reducing carbon emission and increasing crop yields.Originality/valueThis study calculates agricultural MAC by using the shadow price approach, taking agricultural carbon emissions as undesired environmental output. The study also provides a reference emission right price and provides guidance to make use of cropping structure adjustment and optimization for exploring the emission reduction strategy.


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