Proceedings of the 2016 International Seminar on Education Innovation and Economic Management (SEIEM 2016)

Analysis of Primary Energy Structure Based on Carbon Emission Reduction Targets and Countermeasures

Authors
Feng Ren
Corresponding Author
Feng Ren
Available Online December 2016.
DOI
https://doi.org/10.2991/seiem-16.2016.56How to use a DOI?
Keywords
Primary energy, Carbon emission reduction, Markov model, GM(1,1) model
Abstract
In order to study the feasibility of China's preset reduction targets in 2030, this study uses linear regression model, grey model and Markov model to forecast China's primary energy consumption, the structure of primary energy consumption and carbon dioxide emissions. This paper analyze the possibility of the completion of China's emission reduction targets in 2030 one by one, and the results show that the non-fossil energy development target which Chinese authorities proposed cannot be achieved without extra effort, and the carbon peak objective which Chinese authorities set cannot be achieved naturally. Hence, this paper give countermeasures and suggestions to help achieve the emission reduction targets in 2030.The results of this study have a certain reference value for the development of China's energy policy.
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Proceedings
2016 International Seminar on Education Innovation and Economic Management (SEIEM 2016)
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
December 2016
ISBN
978-94-6252-273-2
ISSN
2352-5398
DOI
https://doi.org/10.2991/seiem-16.2016.56How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Feng Ren
PY  - 2016/12
DA  - 2016/12
TI  - Analysis of Primary Energy Structure Based on Carbon Emission Reduction Targets and Countermeasures
BT  - 2016 International Seminar on Education Innovation and Economic Management (SEIEM 2016)
PB  - Atlantis Press
SP  - 221
EP  - 224
SN  - 2352-5398
UR  - https://doi.org/10.2991/seiem-16.2016.56
DO  - https://doi.org/10.2991/seiem-16.2016.56
ID  - Ren2016/12
ER  -