Nuclear energy and carbon dioxide emissions dynamics with the Fourier nonlinear ARDL approach: The power of shaping the future

The increasing energy demand and climate change concerns are making the role of low-carbon resources increasingly strategic in energy policies. In this context, this study aims to analyze nuclear energy's short and long-run impacts on carbon emissions using the Fourier Nonlinear ARDL method. The significance of the study stems from the method's ability to account for structural breaks and asymmetric dynamics compared to traditional models, as well as its current and broader perspective, using a dataset encompassing the eight largest nuclear energy producers and the three smallest producers. Nonlinear models suitable for Fourier functions were only valid for South Korea and Slovenia; however, owing to autocorrelation and heteroskedasticity issues in the Slovenian model, only the coefficients of the South Korea model were considered in the analyses. A 1 % increase in nuclear energy reduces carbon dioxide emissions by approximately 0.03 %. According to the error correction model, it takes approximately one year for imbalances that may occur in the short-run to reach balance in the long-run. The analysis results support the claim that nuclear energy is environmentally friendly and clean. This shows that nuclear energy can effectively reduce carbon dioxide emissions and thus play an essential role in the fight against climate change. These findings emphasize the potential of nuclear energy as an energy source that can play an important role in green transformation processes. Energy policies should increase the share of nuclear energy in energy production, considering its stable contribution to nuclear energy, which has strategic value in the face of economic and political shocks.