With the development of economy and improvement in the living standard of people, life energy consumption has been increasing with each passing year. The life energy consumption of residents is expected to become a new growth point for carbon emissions. Using GiNi index, a method for spatial autocorrelation analysis, the characteristics, regional disparity, and spatio-temporal pattern of carbon emissions from life energy consumption were analyzed on regional and provincial levels from 2001 to 2013, in China. We used the STIRPAT model to simulate the impact of factors such as population, affluence level, age structure of population, and the proportion of use of electric energy, on carbon emissions. We observed that for the life of rural residents, the direct and indirect energy carbon emissions increased by 7.65% and 9.16%, respectively. The GiNi index analysis indicated that the difference in carbon emissions was shrinking among the three zones of eastern, central, and western regions. The distribution of rural residents' life energy per capita carbon emissions in provincial China was not completely random. The areas with low levels of direct carbon emissions were mainly distributed in the eastern and western regions, whereas areas with the high levels of direct carbon emissions were relatively stable, and were mainly distributed in Sichuan, Hebei, and Anhui. Population, affluence level, and age structure of population were the main driving factors for the carbon emissions from the life energy consumption of residents, and the change in the rate of carbon emissions from residents' life energy caused by them exceeded that of themselves. Moreover, the rural residents' life energy carbon emissions were higher in the north than that in the south. However, the areas with low levels of indirect carbon emissions were relatively stable with respect to their carbon emissions. Within the range of calculated data, the results of the present analysis support the Environmental Kuznets Curve hypothesis, and the economic development has been the important factor for prompting the turning point of the Environmental Kuznets Curve hypothesis.