Examining the impact factors of urban residential energy consumption and CO2 emissions in China - Evidence from city-level data

Rapid urbanization has exerted substantial pressure on China's energy system and contributed to climate change. To find the key drivers of urban residential energy consumption and CO2 emissions, this paper uses an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT), model that employs city-level data to examine the influences of population scale, income level, population compactness and price on house-based residential energy consumption, energy-related CO2 emissions and private vehicle ownership. The empirical results indicate that factors such as population scale, affluence, and population compactness can lead to increases in residential energy consumption and CO2 emissions. In terms of transportation, income and population scale positively drive the growth of private vehicle ownership, while the fuel price negatively influences private vehicle ownership. Moreover, population scale is the most important factor in residential energy consumption and CO2 emissions. Finally, policy recommendations are suggested for China's urban development strategy and urban design and to encourage technology innovations that reduce residential energy consumption and CO2 emissions. (C) 2016 Elsevier Ltd. All rights reserved.