There is an important reference value for realization of low carbon economy and low carbon life to understand the change of per capita indirect carbon emissions based on different demand levels. Based on the demand-level of residents' consumption, this paper established the corresponding relationship between different demand levels of per capita indirect carbon emissions. We decomposed per capita indirect carbon emissions into three types including survival type, developmental type and luxurious type, and estimated them by the input output method. The temporal and spatial evolution of per capita indirect carbon emissions in different demand levels were studied and the driving mechanisms were identified by the spatial panel method. The corresponding emission reduction measures were also proposed. The results indicate that (1) at the national level, there is an upward trend in per capita indirect carbon emissions in different demand levels. The spatial imbalance is mainly reflected in the difference between the north and the south. The northern region is always the main spatial carrier of them. In most provinces, per capita indirect carbon emissions of the survival type have a strong upward momentum. The high value areas of developmental type and luxurious type have a trend of decreasing first, then increasing, and increasing gradually in the number of provinces separately. (2) The global Moran's I shows that there is a significant spatial autocorrelation of the per capita indirect carbon emissions in different demand levels in 30 provinces of China. There is a strong "Matthew effect". (3) The results of spatial panel regression show that the technological progress is a key factor to achieve indirect carbon emissions' reduction. The negative emission reduction effect of population size of each demand level is much less than that of the positive structure effect. Macroeconomic factors have increasing emission effects, and the influence of consumption factors is different. In addition, some factors have significant spatial spillover effects on each level of demand. Therefore, we should pay attention to the effect of linkage emission reduction between regions, and do a good job of coordination in indirect carbon emission reduction.