The Chinese government has made ambitious commitments in terms of its carbon intensity reduction targets for 2020 and 2030. Whether China will achieve these targets remains uncertain, especially under the context of increasing consistency in carbon emissions cut globally. This study decomposed total energy consumption into five types and modeled each of them with its influential factors based on the stochastic impacts by regression on population, affluence and technology (STIRPAT) model. Carbon emissions were predicted by combining economic growth forecasting, industrial structure and energy structure projections. The results show that the estimated CO2 emissions in 2020 were 10.05 gigatonnes (Gt), with a 52.8% reduced intensity compared to 2005. And the predicted CO2 emissions in 2030 were 10.39 Gt, with a 70.0% reduced intensity. China's carbon intensity reduction targets in 2020 (40-45%) and 2030 (60-65%) can be met under current policies. However, the total CO2 emissions fail to meet the 450 ppm scenario (8.4 Gt in 2020 and 7.1 Gt in 2030) only by the improvement of industrial structure and energy structure. New policies such as carbon trading market (CTM) and carbon capture, utilization and storage (CCUS) technology need to be developed in depth to further mitigate CO2 emissions. (C) 2017 Elsevier Ltd. All rights reserved.