Factor decomposition and decoupling effect of China's industrial carbon emissions

In this paper, a generalized divisia index decomposition method (GDIM) was used to analyze the driving factors of China's industrial carbon emissions from 2000 to 2016. On this basis, a decoupling effort model was innovatively constructed combing with the DPSIR framework to measure the decoupling effect of industrial carbon emissions. The empirical results showed that output scale effect, technological progress effect, energy consumption scale effect and per capita carbon emissions effect were the main factors leading to increased industrial carbon emissions, while output carbon intensity effect and technological progress carbon intensity effect were the key factors which reduce industrial carbon emissions. The decoupling effect of industrial carbon emissions was characterized by negative decoupling~weak decoupling~strong decoupling. The output carbon intensity effect and technological progress carbon intensity effect were the decisive factors to achieve strong decoupling of industrial carbon emissions. At the same time, it was necessary to adjust energy structure, reduce energy intensity and carbon intensity to realize the strong decoupling of industrial carbon emissions. © 2019, Editorial Board of China Environmental Science. All right reserved.