A hybrid study of multiple contributors to per capita household CO2 emissions (HCEs) in China.

Given the large expenditures by households on goods and services that contribute a large proportion of global CO2 emissions, increasing attention has been paid to household CO2 emissions (HCEs). However, compared with industrial CO2 emissions, efforts devoted to mitigating HCEs are relatively small. A good understanding of the effects of some driving factors (i.e., urbanization rate, per capita GDP, per capita income/disposable income, Engel coefficient, new energy ratio, carbon intensity, and household size) is urgently needed prior to considering policies for reducing HCEs. Given this, in the study, the direct and indirect per capita HCEs were quantified in rural and urban areas of China over the period 2000-2012. Correlation analysis and gray correlation analysis were initially used to identify the prime drivers of per capita HCEs. Our results showed that per capita income/disposable income, per capita GDP, urbanization rate, and household size were the most significantly correlated with per capita HCEs in rural areas. Moreover, the conjoint effects of the potential driving factors on per capita HCEs were determined by performing principal component regression analysis for all cases. Based on the combined analysis strategies, alternative polices were also examined for controlling and mitigating HCEs growth in China.