Abstract
Economic development usually leads to increased energy consumption, which in turn will result in an increase in carbon emissions. To break the relationship between economic development and carbon emissions, scholars have turned their attention to the phenomenon of decoupling. In this paper, we studied the decoupling relationship between carbon emissions and economic growth of the equipment manufacturing industry in China from 2000 to 2014. We adapted the LMDI decomposition method, and we used the Tapio decoupling evaluation model to analyze our data. We found that the decoupling relationship between carbon emissions and economic growth of China’s equipment manufacturing industry is weak, which indicates the industry is experiencing faster economic growth than carbon emission growth. We found the economic output is the factor that has the strongest influence on the industry’s carbon emission, and energy consumption intensity has the strongest relationship with the decoupling of economic growth and carbon emission. The indicators of the industry’s decoupling-effort are all less than 1.0, which indicates that the industry is in the state of weak decoupling, and we also observed an annual decreasing trend in the industry’s indicators. Toward the end of this paper, we used the Grey forecasting model to predict the decoupling relationship between carbon emission and economic growth for 2015–2024, and we discussed the implications of our research.
Highlights
As global warming becomes worse, scholars have started to explore ways to achieve low carbon economic growth [1,2]
We found that the decoupling relationship between the carbon emission of the equipment manufacturing industry and economic growth was weakly decoupling, and the state
We found that the decoupling relationship between the carbon emission of the equipment manufacturing industry and economic growth was weakly decoupling, and the state was unstable
Summary
As global warming becomes worse, scholars have started to explore ways to achieve low carbon economic growth [1,2]. Freitas [13] used a region’s data on economic activity and carbon emissions to calculate its decoupling evolution and decoupling status, and Mohamed Amine Boutabba [27] studied the relationship between carbon emissions, economic growth and energy consumption using the Granger causality method. Bithas and Kalimeris [30] recently re-estimated the energy-economic growth decoupling effect of the world by including global data on the physiology and dimensionality of economic goods They found that the results of their research were worse than those in the literature calculated based on the traditional approach that uses energy/GDP ratio. Csereklyei and Stern [17] studied global energy consumption by using the evolution of energy use approach instead of the traditional pollution emission approach In view of these limitations of the literature, we pose the following research question: What are the factors that influence a region’s decoupling standard?
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
