File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1016/j.strueco.2020.02.007
- Scopus: eid_2-s2.0-85083010054
- WOS: WOS:000537715200021
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Regional and provincial CO2 emission reduction task decomposition of China's 2030 carbon emission peak based on the efficiency, equity and synthesizing principles
Title | Regional and provincial CO<inf>2</inf> emission reduction task decomposition of China's 2030 carbon emission peak based on the efficiency, equity and synthesizing principles |
---|---|
Authors | |
Keywords | CO emission 2 Efficiency principle Equity principle Reduction task decomposition Synthesizing principle |
Issue Date | 2020 |
Citation | Structural Change and Economic Dynamics, 2020, v. 53, p. 237-256 How to Cite? |
Abstract | China has promised to reduce 60–65% of its 2005 carbon emission per GDP unit in 2030. This study aims to decompose China's emission reduction task to regional and provincial levels according to efficiency, equity, and synthesizing principles, respectively, during 1996–2015. Results show the following: (1) Through the cluster analysis of eight indexes including shadow price, China's provinces can be divided into three sub-regions; (2) In regional level, Sub-region 2 should take the largest carbon reduction proportion, accounting for about 60%; Sub-region 3 and Sub-region 1 should take 30% and 10% respectively;(3) On provincial level, the provinces that account for more than 5% of carbon dioxide emission reduction task of China are Shandong (9.33%), Shanxi (8.83%), Hebei (7.56%), Jiangsu (6.90%), Sichuan (6.40%), Guangdong (5.23%), and Inner Mongolia (5.20%);(4) Considering the emission reduction costs, it is best to decompose tasks according to the equity principle in the provincial level. |
Persistent Identifier | http://hdl.handle.net/10722/333430 |
ISSN | 2021 Impact Factor: 5.059 2020 SCImago Journal Rankings: 0.891 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Li, Yan | - |
dc.contributor.author | Wei, Yigang | - |
dc.contributor.author | Zhang, Xiaoling | - |
dc.contributor.author | Tao, Yuan | - |
dc.date.accessioned | 2023-10-06T05:19:19Z | - |
dc.date.available | 2023-10-06T05:19:19Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Structural Change and Economic Dynamics, 2020, v. 53, p. 237-256 | - |
dc.identifier.issn | 0954-349X | - |
dc.identifier.uri | http://hdl.handle.net/10722/333430 | - |
dc.description.abstract | China has promised to reduce 60–65% of its 2005 carbon emission per GDP unit in 2030. This study aims to decompose China's emission reduction task to regional and provincial levels according to efficiency, equity, and synthesizing principles, respectively, during 1996–2015. Results show the following: (1) Through the cluster analysis of eight indexes including shadow price, China's provinces can be divided into three sub-regions; (2) In regional level, Sub-region 2 should take the largest carbon reduction proportion, accounting for about 60%; Sub-region 3 and Sub-region 1 should take 30% and 10% respectively;(3) On provincial level, the provinces that account for more than 5% of carbon dioxide emission reduction task of China are Shandong (9.33%), Shanxi (8.83%), Hebei (7.56%), Jiangsu (6.90%), Sichuan (6.40%), Guangdong (5.23%), and Inner Mongolia (5.20%);(4) Considering the emission reduction costs, it is best to decompose tasks according to the equity principle in the provincial level. | - |
dc.language | eng | - |
dc.relation.ispartof | Structural Change and Economic Dynamics | - |
dc.subject | CO emission 2 | - |
dc.subject | Efficiency principle | - |
dc.subject | Equity principle | - |
dc.subject | Reduction task decomposition | - |
dc.subject | Synthesizing principle | - |
dc.title | Regional and provincial CO<inf>2</inf> emission reduction task decomposition of China's 2030 carbon emission peak based on the efficiency, equity and synthesizing principles | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.strueco.2020.02.007 | - |
dc.identifier.scopus | eid_2-s2.0-85083010054 | - |
dc.identifier.volume | 53 | - |
dc.identifier.spage | 237 | - |
dc.identifier.epage | 256 | - |
dc.identifier.isi | WOS:000537715200021 | - |