Potential Study onCarbonEmission Reduction and Energy Saving of Guangdong Province based on Sensitivity Analysis

DOI

10.2991/iccahe-16.2016.24How to use a DOI?

Keywords

input output table. sensitivity analysis. energy saving and carbon emission reduction. Guangdong province

Abstract

Based on input-output table and energy consumption balance sheet of Guangdong Province in 2012, this paper formulates non-competitive energy input-output table of Guangdong Province, and calculates energy consumption intensity, carbon intensity and sensitivity coefficient of carbon emission reduction and energy saving of various departments. By applying sensitivity coefficient model to the analysis of carbon emission reduction and energy saving fulfillment under the carbon emission reduction and energy saving measures during the 12th Five-Year Plan in Guangdong Province, conclusions are drawn that the devotion of energy structure optimization, industrial restructuring and higher energy efficiency level to energy saving respectively mount to 13.1%,8.20%and 78.7%, while to carbon emission reduction mount to 15.2%,7.85%, and76.9%. Generally speaking, the reduction of 18.7% in energy consumption intensity and 20.4% in carbon emission intensity can basically meet the requirements of the carbon mission reduction and energy saving goal during the 12th Five-Year Plan.

Copyright

© 2016, 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  - Wei Chen
AU  - Jinfeng Zhou
AU  - Haoxiang Chen
AU  - Yaochu Li
PY  - 2016/10
DA  - 2016/10
TI  - Potential Study onCarbonEmission Reduction and Energy Saving of Guangdong Province based on Sensitivity Analysis
BT  - Proceedings of the 2016 5th International Conference on Civil, Architectural and Hydraulic Engineering (ICCAHE 2016)
PB  - Atlantis Press
SP  - 133
EP  - 144
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccahe-16.2016.24
DO  - 10.2991/iccahe-16.2016.24
ID  - Chen2016/10
ER  -