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To address climate change effectively, it is essential to quantify CO2 emissions and the driving factors in high-energy-consuming countries. China is the top CO2-emitting country; moreover, there is a lack of comprehensive analytical studies on quantifying the contributions of key drivers to high-energy-consuming countries' CO2 emissions. Therefore, based on data of China's energy consumption from 2005 to 2016, this paper combines the extended Kaya identity with the logarithmic mean Divisia index (LMDI) decomposition method to construct an optimized carbon emission decomposition model. Carbon emission and carbon emission intensity are measured and decomposed. Then, the results of the decomposition are discussed, and the effects of various drivers on carbon emissions from energy consumption in China are analysed. Furthermore, we demonstrate real applications of decomposition analysis in policy-making using examples from China and present some ideas to reduce CO2. The results show that from 2005 to 2016, China's total carbon emissions accounted for nearly one-third of the world's total carbon emissions, and the intensity of carbon emissions in China was generally higher than that of worldwide. The rapid development of economy and acceleration of urbanization are not conducive to reduction of carbon emissions. Reducing the intensity of energy consumption, adjusting the internal structure of the industry and perfecting the economic policy system should be important means used to promote the development of China's low-carbon economy in the future. (c) 2018 Elsevier B.V. All rights reserved.