How to optimize the development of carbon trading in China—Enlightenment from evolution rules of the EU carbon price
Guochang Fang,
Lixin Tian,
Menghe Liu,
Min Fu and
Mei Sun
Applied Energy, 2018, vol. 211, issue C, 1039-1049
Abstract:
This paper explores the optimization scheme of carbon trading in China based on a novel energy-saving and emission-reduction (ESER) system with carbon price constraints. With the aid of nonlinear dynamics theory, the dynamics behavior of the novel system is discussed. Genetic algorithm and back propagation neural network is used to identify the quantitative coefficients according to the statistical data of the second period in European Union (EU). Taking the actual situation in EU for instance, the variables which are sensitive to carbon trading are detailedly researched. Enlightened by the EU’s experience, an optimal road of China’s carbon trading is put forward. The results show that carbon emissions could be controlled by carbon trading. The investment to carbon trading hampers economic growth in the near future, and ESER technical progress is negatively correlated with carbon trading in the long run. Demand and supply relationship is closely related to carbon price, both are the important issues in carbon trading system. Excessive government control and extortionate carbon price will deliver the opposite effect and even fatal influence on carbon trading system.
Keywords: Carbon price; Energy-saving and emission-reduction; Energy intensity; Economic growth (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (37)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261917317117
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:211:y:2018:i:c:p:1039-1049
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.2017.12.001
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 ().