Cutting CO2 intensity targets of interprovincial emissions trading in China
Kai Chang and
Hao Chang
Applied Energy, 2016, vol. 163, issue C, 221 pages
Abstract:
This paper proposes the allocation of CO2 emissions increment quotas and carbon intensity reduction burdens based on information entropy method. Allocating emissions increment quotas and cutting emissions intensity target should consider each province’s objective weights of some valuable factors, such as carbon emissions reduction capacity, responsibility, potential and energy efficiency under interprovincial emissions trading system in China. Those provinces with better economic level, heavier cumulative CO2 emissions, stronger industrial carbon intensity and greater energy consumers may undertake greater shares of carbon intensity reduction targets during 2014–2020. All provinces in China may achieve a surprising reduction of CO2 emissions increment quotas during 2014–2020 with an increase of national emissions intensity reduction targets, and then have to increase greater burdens of emissions intensity reduction compared with the 2013 level.
Keywords: Carbon emissions trading; Carbon intensity; Emission-reduction target allocation; Information entropy method (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (32)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261915013884
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:163:y:2016:i:c:p:211-221
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2015.10.146
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().