Urban and rural differences with regional assessment of household energy consumption in China

This paper explores the crucial factors driving the changes in household energy consumption (HEC) in China during 2005e2017. 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. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

This paper explores the key factors driving changes in household energy consumption in China, using a decomposition framework to analyze the effects of energy intensity, regional structure, per capita consumption, population scale, and energy structure. Results show that energy intensity and regional structure reduced HEC, while population scale, per capita consumption, and energy structure stimulated HEC growth. Rural areas contributed significantly to the increase in HEC, with differences in impact between urban and rural regions.