In the context of global warming, low-carbon economy with low energy consumption, low pollution and low emissions as the main characteristics has become the focus of attention. The paper takes 30 provincial-level units in China as the basic research object, uses DEA model to measure China‘s carbon emission performance in 2005, 2010, 2015 and 2019, and uses spatial visualization and trend surface analysis method to analyze its spatial-temporal rule. On this basis, geographical detector is used to analyze the influencing factors and the results show that: (1) China‘s carbon emission performance is at a relatively low level, except for that of provinces such as Beijing, Shanghai, Hainan and Qinghai while other provinces still need more efforts to perform better. In addition, the carbon emission performance fluctuates during the research period. Specifically, the change trend of east-west direction is greater than that of north-south direction. (2) The spatial difference of the performance is significant. In general, areas of high performance are mainly distributed in the eastern and southern regions while areas at low performance level mainly in the western and northern parts. There is an evident spatial trend of mixed distribution, initially forming the development trend of „overall mixed distribution and partial aggregation“. (3) Government intervention has the greatest influence on carbon emission performance, followed by ownership structure, foreign investment, energy structure, technological progress, industrial structure, and degree of opening to the outside world. In addition, interaction factors have a greater impact on performance than single factors, and show nonlinear enhancement characteristics.