期刊
SUSTAINABILITY
卷 9, 期 4, 页码 -出版社
MDPI
DOI: 10.3390/su9040600
关键词
CO2 emissions; renewable energy consumption; vector auto-regression (VAR) model
资金
- the Fundamental Research Funds for the Central Universities [27R1706019B]
- Recruitment Talent Fund of China University of Petroleum (Huadong) [05Y16060020]
This paper adopts the vector auto-regression model (VAR) to study the dynamic effect of renewable energy consumption on carbon dioxide emissions. Our model is based on a given level of primary energy consumption, economic growth and natural gas consumption in the US, from 1990 to 2015. Our results indicate that a long-running equilibrium relationship exists between carbon emissions and four other variables. According to the variance decomposition of carbon dioxide emissions, the use of primary energy has a positive and notable influence on CO2 emissions, compared to other variables. From the Impulse Response Function (IRF) results, we find that the use of renewable energy would remarkably reduce carbon emissions, despite leading to an increase in emissions in the early stages. Natural gas consumption will have a negative impact on CO2 emissions in the beginning, but will have only a modest impact on carbon emission reductions in the long run. Finally, our study indicates that the use of renewable forms of energy is an effective solution to help reduce carbon dioxide emissions. The findings of our study will help policy makers develop energy-saving and emission-reduction policies.
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