Study on The Influential Factors of Carbon Emissions from Thermal Power Industrial in China Using Partial Least Square Regressive Model

DOI

10.2991/icmmct-17.2017.112How to use a DOI?

Keywords

carbon emissions, thermal power, the Partial Least Square Regressive model, influential factors.

Abstract

This paper firstly analyzed the current thermal power situation in China, and then determined several influential factors by referring to the Kaya identity. Finally, the Partial Least Square Regressive model is applied on this issue. To validate the model, this paper calculated the actual Carbon emissions from thermal power industrial by means of the formula formulating by the Intergovernmental Panel on Climate Change's 2006 guide from 1991-2014 across China. Under the model, we find that the amount of population, consumption of the coal and the ritio of the thermal power are the main factors influencing the carbon emissions from thermal power industrial.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Mei Liu
AU  - Jing-Yan Li
PY  - 2017/04
DA  - 2017/04
TI  - Study on The Influential Factors of Carbon Emissions from Thermal Power Industrial in China Using Partial Least Square Regressive Model
BT  - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
PB  - Atlantis Press
SP  - 523
EP  - 528
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-17.2017.112
DO  - 10.2991/icmmct-17.2017.112
ID  - Liu2017/04
ER  -