Dynamic influences of different energy sources, energy efficiency, technological innovation, population, and economic growth toward achieving net zero emissions in the United Kingdom

Abstract

This article analyzed the effect of various energy sources, energy efficiency, technological innovation, population size, and GDP on greenhouse gas (GHG) emissions in the United Kingdom. The annual data spanning from 1990 to 2021 is examined utilizing the Autoregressive Distributed Lag (ARDL) model. Results reveal that a 1 % rise in GDP, population, and fossil fuel consumption led to a 0.11 %, 0.16 %, and 0.60 % increase in GHG emissions in the short-run while 0.28 %, 0.23 %, and 0.74 % in the long-run. Besides, a 1 % improvement in renewable energy, nuclear power, energy efficiency, and technological innovation cut GHG emissions by 0.25 %, 0.13 %, 0.21 %, and 0.29 % in the short-term and 0.39 %, 0.28 %, 38 %, and 48 % in the long-run. The robustness analysis through the Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) demonstrates the consistency of the long-term effects obtained from the ARDL technique. The investigation provides novel insights essential for designing and implementing policies that advance the UK power industry's net-zero goals through cleaner energy, efficiency, and green technology investments.