Differential benefit of coal and natural gas efficiency in Denmark: How clean is the environmental-related innovation?

Abstract

Inspired by Denmark's ambitious renewable energy initiatives and its commitment to achieving a substantial 70 percent reduction in greenhouse gas (GHG) emissions by 2030 and achieving net-zero emissions by 2050, this study delves deeper into examining the roles of energy source efficiency, renewable energy utilization, and environment-related technologies spanning the years from 1990 to 2021. A comprehensive array of wavelet tools, including wavelet coherence, wavelet-based ordinary least squares (WBOLS), Continuous Wavelet Transform (CWT), Granger causality, and wavelet correlation, was employed to dissect these dynamics. The primary findings underscore the potential for enhancing environmental sustainability through these key indicators. For instance, employing the WBOLS method reveals that a percent increase in renewable energy consumption translates into an approximate reduction of ∼0.02%, ∼0.03%, and ∼0.54% in GHG emissions in the short-, medium-, and long-term, respectively. Similarly, improvements in energy efficiency yield remarkable outcomes. A one percent increase in the efficiency of natural gas utilization leads to GHG emission reductions of ∼0.44%, ∼0.19%, and ∼0.83% in the short-, medium-, and long-term, respectively. Moreover, a 1 percent enhancement in coal energy efficiency results in GHG emission reductions of ∼0.23%, ∼0.19%, and ∼0.91% in the short-, medium-, and long-term, respectively. Furthermore, the study indicates that a surge of 1% in innovation through environment-related technologies corresponds to GHG emission reductions of ∼0.56%, ∼0.10%, and ∼0.02% in the short-, medium-, and long-term, respectively. The results are notably substantiated by the CWT Granger causality approach. Considering the somewhat modest impact of innovation on GHG emissions, especially in the long-term, the study recommends a deliberate emphasis on the design and formulation of environmentally-related innovations that prioritize attributes such as reliability, durability, and adaptability.