Study on industrial carbon emissions in China based on GDIM decomposition method and two decoupling effects

Abstract

AbstractThe driving factors of China's industrial carbon emissions are decomposed by GDIM, so as to explore the reasons for the change of China's industrial carbon emissions. The decoupling effect of China's industrial carbon emissions and economic growth is studied by speed decoupling and quantity decoupling. The speed decoupling is measured by Tapio decoupling elasticity and emission reduction effort function, and the quantity decoupling is measured by environmental Kuznets curve (EKC). The results show that the positive driving factors are output size effect > industrial energy consumption effect > population size effect, and the negative driving factors are investment carbon emission effect > output carbon intensity effect > per capita output effect > economic efficiency effect > energy intensity effect. The elasticity of emission reduction is basically greater than that of energy conservation, indicating that there is still much room for efforts in emission reduction. The overall decoupling effect of carbon emissions is undecoupling - strong decoupling - undecoupling. The shape of quadratic EKC curve is "U" type, and the shape of cubic EKC curve is "N" type, which satisfies the EKC curve hypothesis.