Abstract
What factors determine the spatial heterogeneity of household energy consumption (HEC) in China? Can the impacts of these factors be quantified? What are the trends and characteristics of the spatial differences? To date, these issues are still unclear. Based on the STIRPAT model and panel dataset for 30 provinces in China over the period 1997–2013, this paper investigated influences of the income per capita, urbanization level and annual average temperature on HEC, and revealed the spatial effects of these influencing factors. The results show that the income level is the main influencing factor, followed by the annual average temperature. There exists a diminishing marginal contribution with increasing income. The influence of urbanization level varies according to income level. In addition, from the eastern region to western region of China, variances largely depend upon economic level at the provincial level. From the northern region to southern region, change is mainly caused by temperature. The urbanization level has more significant impact on the structure and efficiency of household energy consumption than on its quantity. These results could provide reference for policy making and energy planning.
Highlights
Household energy consumption (HEC) accounts for 35% of total energy end-use worldwide
The spatial difference in residential energy consumption is influenced by income level and urbanization level
The results of the panel unit root tests show that the first-order difference series of all variables, except PP test of LnGDP, are stationary (Appendix A)
Summary
Household energy consumption (HEC) accounts for 35% of total energy end-use worldwide. HEC will further increase by rapid economic growth and urban transformation in China [2,3]. China’s economy is entering the “new normal”, maintaining economic growth above 6.5%. China is one of the most rapidly urbanizing countries in the world with the urbanization rate of 17.9% in 1978 and 54.77% in 2014. The average annual urbanization rate is 1%. It is predicted this rate will reach approximately 70% by the end of 2030 [4]. Excessive consumption of fossil fuels is the major cause of global warming and air pollution, which becomes the greatest challenge to sustainable development [5]. There are many studies on response to the challenge [6], in which few reports are from the view of spatial variances
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