TY - JOUR
T1 - Regional decomposition analysis of electric carbon productivity from the perspective of production and consumption in China
AU - Chen, Guijing
AU - Hou, Fujun
AU - Chang, Keliang
N1 - Publisher Copyright:
© 2017, Springer-Verlag GmbH Germany.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - This study is concerned with the impact factors of electric carbon productivity change in China. Some influencing factors are identified by examining the time series decomposition of electric carbon productivity based on data from 2003 to 2015, where the usual Logarithmic Mean Divisia Index (LMDI) method is used but with the regional dimension taken into consideration. Moreover, this study analyzes the driving factors of electric carbon productivity change from the perspective of production and consumption in China’s power industry, where the influences of power transfers among provinces, imports and exports, and transmission losses are considered. Based on the decomposition analysis of existing data in 30 provinces (including province-level municipalities), from the perspective of production, regional actual electric carbon productivity, and per capita GDP are the main influencing forces for the growth of electric carbon productivity, and the reciprocal of per capita electric carbon emissions, energy intensity, and energy emission intensity play dominate roles in the decline of electric carbon productivity. From the perspective of consumption, the main impact factors to improve electric carbon productivity are power transfers among provinces, imports and exports, the reciprocal of emission intensity of power consumption and regional electric carbon productivity, and the impact of energy consumption on thermal power generation, the proportion of thermal power to total electricity generation, and the effect of transmission losses. Finally, several conclusions are drawn that might be meaningful for the Chinese government to improve China’s electric carbon productivity.
AB - This study is concerned with the impact factors of electric carbon productivity change in China. Some influencing factors are identified by examining the time series decomposition of electric carbon productivity based on data from 2003 to 2015, where the usual Logarithmic Mean Divisia Index (LMDI) method is used but with the regional dimension taken into consideration. Moreover, this study analyzes the driving factors of electric carbon productivity change from the perspective of production and consumption in China’s power industry, where the influences of power transfers among provinces, imports and exports, and transmission losses are considered. Based on the decomposition analysis of existing data in 30 provinces (including province-level municipalities), from the perspective of production, regional actual electric carbon productivity, and per capita GDP are the main influencing forces for the growth of electric carbon productivity, and the reciprocal of per capita electric carbon emissions, energy intensity, and energy emission intensity play dominate roles in the decline of electric carbon productivity. From the perspective of consumption, the main impact factors to improve electric carbon productivity are power transfers among provinces, imports and exports, the reciprocal of emission intensity of power consumption and regional electric carbon productivity, and the impact of energy consumption on thermal power generation, the proportion of thermal power to total electricity generation, and the effect of transmission losses. Finally, several conclusions are drawn that might be meaningful for the Chinese government to improve China’s electric carbon productivity.
KW - China
KW - Driving factors
KW - Electric carbon productivity
KW - LMDI method
KW - Power industry
UR - http://www.scopus.com/inward/record.url?scp=85032966155&partnerID=8YFLogxK
U2 - 10.1007/s11356-017-0590-1
DO - 10.1007/s11356-017-0590-1
M3 - Article
C2 - 29098575
AN - SCOPUS:85032966155
SN - 0944-1344
VL - 25
SP - 1508
EP - 1518
JO - Environmental Science and Pollution Research
JF - Environmental Science and Pollution Research
IS - 2
ER -