Disaggregated Impact of Non-Renewable Energy Consumption on the Environmental Sustainability of the United States: A Novel Dynamic ARDL Approach

While there is a vast body of literature on environmental sustainability, the disaggregated impact of major non-renewable energy (NRE) consumption on the environmental sustainability of the United States (U.S.) is understudied, particularly in terms of using a load capacity factor (LCF) perspective. In this study, the above research gap is addressed using a dynamic autoregressive distributed lag (DYNARDL) model to analyze the heterogeneous impact of NRE consumption on the environmental sustainability of the U.S. from 1961 to 2022. Given the U.S.'s heavy reliance on energy consumption from NRE sources, this analysis provides an in-depth examination of the long-term effects of this energy consumption on the environment. Based on the analysis of the DYNARDL model, it is found that an increase of one unit of coal, natural gas, and petroleum energy consumption reduces environmental sustainability by 0.007, 0.006, and 0.008 units in the short-run and 0.006, 0.004, and 0.005 units in the long-run, respectively. However, one unit of nuclear energy consumption increases environmental sustainability by 0.007 units in the long-run. The kernel-based regularized system (KRLS) result reveals that coal and petroleum energy consumption have a significantly negative causal link with environmental sustainability, while nuclear energy consumption demonstrates a significant positive causal relationship. The research suggests the expansion of the use of nuclear energy by gradually reducing the utilization of coal and petroleum-based forms of energy, then natural gas, to improve environmental sustainability in the U.S., while considering the social and economic implications of efforts aimed at shifting away from the use of fossil fuels.