TY - JOUR
T1 - Urban and rural differences with regional assessment of household energy consumption in China
AU - Wang, Shubin
AU - Sun, Shaolong
AU - Zhao, Erlong
AU - Wang, Shouyang
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/10/1
Y1 - 2021/10/1
N2 - This paper explores the crucial factors driving the changes in household energy consumption (HEC) in China during 2005–2017. We propose a decomposition framework based on the Kaya identity and the logarithmic mean Divisia index (LMDI) method to decompose the change in HEC into energy structure effect, energy intensity effect, regional structure effect, per capita consumption effect and population scale effect. We use the model to shed light on the differences of these five factors affecting HEC between urban and rural and among regions while retaining their energy-use characteristics respectively. The results suggest that: (1) Energy intensity and regional structure reduced HEC, whereas population scales, per capita consumption, and energy structure stimulated HEC growth. (2) Rural energy structure contributed larger shares of the increment in HEC. Rural per capita consumption increased generally much more energy consumption than urban counterpart in coastal developed economic regions. Rural population scale curbed the growth of HEC, while urban population scale drove the growth of HEC. (3) Although energy intensity decreased energy consumption at regional level, the differences were found between regions. Moreover, the impacts of regional structure differed significantly between regions, but insignificantly at provincial level. Finally, some policy recommendations will be made based on these suggestive conclusions.
AB - This paper explores the crucial factors driving the changes in household energy consumption (HEC) in China during 2005–2017. We propose a decomposition framework based on the Kaya identity and the logarithmic mean Divisia index (LMDI) method to decompose the change in HEC into energy structure effect, energy intensity effect, regional structure effect, per capita consumption effect and population scale effect. We use the model to shed light on the differences of these five factors affecting HEC between urban and rural and among regions while retaining their energy-use characteristics respectively. The results suggest that: (1) Energy intensity and regional structure reduced HEC, whereas population scales, per capita consumption, and energy structure stimulated HEC growth. (2) Rural energy structure contributed larger shares of the increment in HEC. Rural per capita consumption increased generally much more energy consumption than urban counterpart in coastal developed economic regions. Rural population scale curbed the growth of HEC, while urban population scale drove the growth of HEC. (3) Although energy intensity decreased energy consumption at regional level, the differences were found between regions. Moreover, the impacts of regional structure differed significantly between regions, but insignificantly at provincial level. Finally, some policy recommendations will be made based on these suggestive conclusions.
KW - Household energy consumption
KW - Influential factors
KW - LMDI framework
KW - Regional assessment
KW - Urban-rural difference
UR - https://www.scopus.com/pages/publications/85107427522
U2 - 10.1016/j.energy.2021.121091
DO - 10.1016/j.energy.2021.121091
M3 - 文章
AN - SCOPUS:85107427522
SN - 0360-5442
VL - 232
JO - Energy
JF - Energy
M1 - 121091
ER -