Modeling the impacts of changes in nuclear energy, natural gas, and coal in the environment through the novel DARDL approach

There is no doubt that energy consumption and production are the primary sources of greenhouse gases that contribute to climate change and global warming. It will be extremely helpful to develop policies to reduce carbon dioxide emissions by analyzing and estimating the factors responsible for these harmful gases. Against this background, the purpose of this study is to perform an analysis of energy services at a disaggregated level in the environment using a novel methodology called Dynamic Autoregressive Distributed Lag (DARDL) for Pakistan utilizing time series data from 1975 to 2021. Further robustness check is performed by Kernel-based regularized least squares (KRLS). Results show that (i) energy indicators and CO2 emissions are cointegrated; (ii) there is a statistically significant effect of nuclear, hydro, natural gas, oil, and coal energy use on CO2 emissions; (iii) nuclear energy reduces CO2 emissions; (iv) Nuclear energy dwindles CO2 emissions to a great extent when a positive shock is applied to it, even if it is 300%; (v) The use of hydro energy also declines CO2 emissions; (vi) Further, CO2 emissions increases dramatically with positive shocks to coal, even if they are 25 %; and, the robustness of the results is verified through KRLS method. This implies that energy consumption is a significant determinant of CO2 emissions in Pakistan, so efforts to reduce CO2 emissions should be considered in order to ensure a sustainable future.