Reducing carbon emissions with Geoscience solutions: A look at the contributions of nuclear energy, technology, and green finance

Abstract

Standards for Low-Carbon Energy Portfolios (LC-EPS) mandate that a certain percentage of a region's electricity generation originate from zero- or low-emissions sources. From 1995Q1 through 2020Q4, the study used the ARDL-Bounds testing technique to estimate coefficient parameters, Granger causality to draw causal inferences, and variance decomposition analysis to anticipate the factors that will have the greatest impact on carbon emissions in the US economy. Nuclear power significantly impacts carbon emissions, as seen by an inverted U-shaped environmental Kuznets curve, whereas long-term impact of innovation leads to lower emissions. On the other hand, exports of sophisticated technology reduce carbon emissions. Economic growth has a discernible effect on carbon emissions, nuclear power, innovation, and environmentally friendly financing. High-tech exports will likely impact carbon emissions most, followed by a demand for nuclear power, innovation, economic expansion, and sustainable finance for the next ten years. These results give policymakers helpful insight into how the US economy may reduce carbon emissions and fight climate change via renewable energy and green finance.

Keywords

Nuclear energy demand / High technology exports / Innovation / Economic growth / Green finance / USA

CRediT authorship contribution statement

Aifeng Liu: Resources, Visualization, Validation, Data Curation, Writing-Reviewing and Editing. Muhammad Imran: Conceptualization, Methodology, Formal analysis, Software, Writing-Reviewing and Editing. Abdelmohsen A. Nassani: Supervision, Resources, Visualization, Validation, Data Curation, Writing-Reviewing and Editing. Rima H. Binsaeed: Resources, Visualization, Validation, Data Curation, Writing-Reviewing and Editing.  Khalid Zaman: Resources, Visualization, Methodology, Formal analysis, Writing-Reviewing and Editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

Researchers Supporting Project number (RSP2024R87), King Saud University, Riyadh, Saudi Arabia.

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