An Econometric Investigation of How the Usage of Non-Renewable Energy Resources Affects the Load Capacity Factor in the United States

Abstract

A substantial body of studies exists regarding the consequences of significant non-renewable energy usage on ecosystem health. Nonetheless, a research deficit exists in examining the nexus within the United States by utilizing the load capacity factor (LCF) as an indicator of environmental sustainability. The current study addresses the identified research gap by employing the autoregressive distributed lag (ARDL) method to examine the influences of non-renewable energy use on the environmental condition of the United States, utilizing data from 1965 to 2022. This analysis delivers a deeper understanding of the long-term impacts of coal, gas, oil, and nuclear utilization on the LCF, considering the United States' significant dependence on energy derived from non-renewable energy resources. The analysis of the ARDL model reveals that a 1% rise in coal, gas, and oil adoption results in a long-term reduction of LCF of 0.14%, 0.12%, and 0.16%, respectively, and a short-term reduction of 0.12%, 0.08%, and 0.10%. However, a 1% increase in nuclear energy usage would enhance LCF by 0.02% in the short term and 0.13% in the long term. This study advocates for the increased adoption of nuclear energy through the gradual diminishment of coal, oil, and gas usage to enhance the sustainability of natural health in the United States while taking into account the social and economic ramifications of transitioning from fossil fuels.