AI Article Synopsis
- The study analyzes the factors driving China's industrial carbon emissions using the generalized Divisia index method and explores the relationship between emissions and economic growth through decoupling methods.
- Positive drivers include the size of output, industrial energy consumption, and population size, while negative factors include investment emissions and output carbon intensity.
- The findings indicate that there is significant potential for emission reduction efforts, with the decoupling effect of emissions showing mixed results, including both strong and weak decoupling, as well as support for the environmental Kuznets curve hypothesis.
Article Abstract
The driving factors of China's industrial carbon emissions are decomposed by generalized Divisia index method (GDIM), so as to study the reasons for the change of China's industrial carbon emissions. The decoupling effect of China's industrial carbon emissions and economic growth is examined by speed decoupling and quantity decoupling. The speed decoupling is calculated 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 abundant room for efforts in emission reduction. The overall decoupling effect of carbon emissions is undecoupling-strong decoupling-undecoupling. Quadratic EKC shape is "U" shape, and the inflection point is 11.0987; the shape of cubic EKC is "N," and the inflection points are - 0.0137 and 2.4069, respectively, which satisfies the hypothesis of EKC curve.
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