ORIGINAL RESEARCH
CO2 Emissions from the Power Industry in the China’s Beijing-Tianjin-Hebei Region: Decomposition and Policy Analysis
Caiqing Zhang1, Mi Zhang1, Nan Zhang2
 
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1Department of Economics and Management, North China Electric Power University,
689 Huadian Road, Baoding City, 071003 China
2Department of Power Engineering, North China Electric Power University,
689 Huadian Road, Baoding City, 071003 China
Online publish date: 2017-03-22
Publish date: 2017-03-22
Submission date: 2016-09-07
Final revision date: 2016-10-24
Acceptance date: 2016-11-03
 
Pol. J. Environ. Stud. 2017;26(2):903–916
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ABSTRACT
Based on the energy consumption data of power industry in the Beijing-Tianjin-Hebei region from 1995 to 2014, our paper first estimated CO2 emissions using the IPCC carbon accounting methods. Then, starting from the perspective of the power industry chain – including power generation, transmission, and final consumption – we established the hierarchical LMDI decomposition model; decomposed driving factors of CO2 emissions into effects of fuel mix; the coal consumption rate; power generation structure; the ratio of power generation to consumption, transmission, and distribution losses; production sectors’ electricity intensity; industrial structure; household electricity intensity; economic scale; and population size. Results show that:
1. During 1995-2014, CO2 emissions of power industry in the Beijing-Tianjin-Hebei region developed in fluctuation and showed a rising trend in general, with annual average growth rate of 5.93%.
2. The factors that drive the growth of CO2 emissions from the power industry in the Beijing-Tianjin-Hebei region are, in order, economic scale, population size, transmission and distribution losses, and industrial structure, with a contribution rate of 150.70%, 20.80%, 8.86%, and 8.83%. The factors that drive CO2 emissions reduction are production sectors’ electricity intensity, the coal consumption rate, the ratio of electricity generation and consumption, household electricity intensity, power generation structure, and fuel mix, with a contribution rate of -45.97%, -22.38%, -19.41%, -0.62%, -0.49%, and -0.32%, respectively.
eISSN:2083-5906
ISSN:1230-1485