FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2912762343> ?p ?o ?g. }

• W2912762343 endingPage "914" @default.
• W2912762343 startingPage "914" @default.
• W2912762343 abstract "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." @default.
• W2912762343 created "2019-02-21" @default.
• W2912762343 creator A5032180597 @default.
• W2912762343 creator A5032705832 @default.
• W2912762343 creator A5036975155 @default.
• W2912762343 creator A5077242615 @default.
• W2912762343 date "2019-02-11" @default.
• W2912762343 modified "2023-09-27" @default.
• W2912762343 title "How to Allocate Carbon Emission Permits Among China’s Industrial Sectors Under the Constraint of Carbon Intensity?" @default.
• W2912762343 cites W1236934511 @default.
• W2912762343 cites W1543823304 @default.
• W2912762343 cites W1583864722 @default.
• W2912762343 cites W1598223411 @default.
• W2912762343 cites W1709842586 @default.
• W2912762343 cites W1986710973 @default.
• W2912762343 cites W1999928088 @default.
• W2912762343 cites W2017654742 @default.
• W2912762343 cites W2027767186 @default.
• W2912762343 cites W2078635353 @default.
• W2912762343 cites W2084229671 @default.
• W2912762343 cites W209301268 @default.
• W2912762343 cites W2179227251 @default.
• W2912762343 cites W2290571738 @default.
• W2912762343 cites W2345555657 @default.
• W2912762343 cites W2345630031 @default.
• W2912762343 cites W2396115108 @default.
• W2912762343 cites W2489921161 @default.
• W2912762343 cites W2542172843 @default.
• W2912762343 cites W2546541909 @default.
• W2912762343 cites W2582726885 @default.
• W2912762343 cites W2593386173 @default.
• W2912762343 cites W2594669515 @default.
• W2912762343 cites W2598931250 @default.
• W2912762343 cites W2616558605 @default.
• W2912762343 cites W2753021311 @default.
• W2912762343 cites W2770093996 @default.
• W2912762343 cites W2770228027 @default.
• W2912762343 cites W2773742730 @default.
• W2912762343 cites W2776372087 @default.
• W2912762343 cites W2794529627 @default.
• W2912762343 cites W2842780224 @default.
• W2912762343 cites W2884137492 @default.
• W2912762343 cites W4379622027 @default.
• W2912762343 doi "https://doi.org/10.3390/su11030914" @default.
• W2912762343 hasPublicationYear "2019" @default.
• W2912762343 type Work @default.
• W2912762343 sameAs 2912762343 @default.
• W2912762343 citedByCount "8" @default.
• W2912762343 countsByYear W29127623432019 @default.
• W2912762343 countsByYear W29127623432020 @default.
• W2912762343 countsByYear W29127623432021 @default.
• W2912762343 countsByYear W29127623432022 @default.
• W2912762343 crossrefType "journal-article" @default.
• W2912762343 hasAuthorship W2912762343A5032180597 @default.
• W2912762343 hasAuthorship W2912762343A5032705832 @default.
• W2912762343 hasAuthorship W2912762343A5036975155 @default.
• W2912762343 hasAuthorship W2912762343A5077242615 @default.
• W2912762343 hasBestOaLocation W29127623431 @default.
• W2912762343 hasConcept C104779481 @default.
• W2912762343 hasConcept C11413529 @default.
• W2912762343 hasConcept C119599485 @default.
• W2912762343 hasConcept C127413603 @default.
• W2912762343 hasConcept C134560507 @default.
• W2912762343 hasConcept C140205800 @default.
• W2912762343 hasConcept C157247726 @default.
• W2912762343 hasConcept C162324750 @default.
• W2912762343 hasConcept C175605778 @default.
• W2912762343 hasConcept C178790620 @default.
• W2912762343 hasConcept C185592680 @default.
• W2912762343 hasConcept C18903297 @default.
• W2912762343 hasConcept C2776036281 @default.
• W2912762343 hasConcept C2776780212 @default.
• W2912762343 hasConcept C39432304 @default.
• W2912762343 hasConcept C41008148 @default.
• W2912762343 hasConcept C42475967 @default.
• W2912762343 hasConcept C47737302 @default.
• W2912762343 hasConcept C54725983 @default.
• W2912762343 hasConcept C78519656 @default.
• W2912762343 hasConcept C83581075 @default.
• W2912762343 hasConcept C86803240 @default.
• W2912762343 hasConcept C87345402 @default.
• W2912762343 hasConcept C87717796 @default.
• W2912762343 hasConceptScore W2912762343C104779481 @default.
• W2912762343 hasConceptScore W2912762343C11413529 @default.
• W2912762343 hasConceptScore W2912762343C119599485 @default.
• W2912762343 hasConceptScore W2912762343C127413603 @default.
• W2912762343 hasConceptScore W2912762343C134560507 @default.
• W2912762343 hasConceptScore W2912762343C140205800 @default.
• W2912762343 hasConceptScore W2912762343C157247726 @default.
• W2912762343 hasConceptScore W2912762343C162324750 @default.
• W2912762343 hasConceptScore W2912762343C175605778 @default.
• W2912762343 hasConceptScore W2912762343C178790620 @default.
• W2912762343 hasConceptScore W2912762343C185592680 @default.
• W2912762343 hasConceptScore W2912762343C18903297 @default.
• W2912762343 hasConceptScore W2912762343C2776036281 @default.
• W2912762343 hasConceptScore W2912762343C2776780212 @default.
• W2912762343 hasConceptScore W2912762343C39432304 @default.
• W2912762343 hasConceptScore W2912762343C41008148 @default.

• next