The role of distinct electricity sources on pollution abatement: Evidence from a wide global panel

Abstract

In this study, we examine the contribution of nuclear, fossil (coal, oil, and gas), and renewable (hydro, solar, wind, biofuel) electricity sources to pollution in the globalization era, as measured by total greenhouse gases (GHG) produced by electricity per capita. We conduct an empirical investigation in a global panel of 163 countries which assesses both the concurrent and individual effects of alternative energy sources. Additionally, we implement a second model to assess the roles of various electricity sources on the carbon intensity of electricity generation. Robust GMM estimators show that fossil electricity is a major polluter and a driver of carbon intensity. Furthermore, nuclear and renewable energy reduce pollution on a global scale, with wind emerging as the most efficient energy source in the global fight against pollution and climate change. Moreover, globalization as measured by trade openness tends to reduce the carbon intensity of electricity production (CI), whereas biofuels have an increasing impact on CI. The findings have important policy implications, indicating that shifting to nuclear and renewable energy sources could help countries achieve their sustainable development goals more efficiently.

The Role of Nuclear Energy in Reducing Greenhouse Gas (GHG) Emissions and Energy Security: A Systematic Review

“…However, greenhouse gas emissions from one country may contribute to pollution and global warming and negatively impact economic growth in other nations [107]. The study confirmed that fossil fuel is a major source of greenhouse gas emissions and a driver of carbon intensity [58,78]. Most authors concluded that promoting clean and alternative energy sources as an alternative to fossil fuels reduces carbon emissions [80,85,89].…”

“…Economic growth necessitates a greater need for energy primarily from fossil fuels, which impacts greenhouse gas (GHG) emissions [80]-a recent study claimed that emissions depend on the kind of energy sources used and concluded that using renewable energy reduced emissions while using nonrenewable energy for electricity generation increased emissions. Although past studies on the effects of low-carbon energy on environmental quality have been conflicting, the use of fossil fuel production of electricity has been proven to have a detrimental effect on the environment [78,94,95]. With the tremendous increase in [80].…”

“…Studies over the decades have shown that although all nations have high pollution levels, the more industrialized and densely populated nations produce most of the world's pollutants [106]. Despite the economic downturn in many sectors due to the coronavirus pandemic, global emissions in 2020 exceeded 34 billion tonnes and had recovered to levels that were nearly prepandemic by the end of 2022 [78]. However, greenhouse gas emissions from one country may contribute to pollution and global warming and negatively impact economic growth in other nations [107].…”

“…Most research conducted on the GHG emission reduction practices of the BRICS nations between 1993 and 2017 indicated that despite being effective at reducing emissions, nuclear energy is suboptimal to renewable energy for promoting pollution reductions [112]. Also, some research has proven that nuclear energy has a negligible impact on the world's top five most polluted nations (i.e., the United States, China, India, South Korea, and Japan) despite the efforts to reduce environmental pollution considering the impact of renewable energy development [78,112,113]. Similar results were published by Iwata et al [114] for 11 OECD nations, wherein only Finland, Japan, Korea, and Spain showed that nuclear power had a beneficial effect on carbon dioxide emissions [87].…”

Assessing the Nexus Between Education, Economic Growth, and Innovation: An Empirical Analysis

“…This methodology differs from the cointegration approach proposed by Johansen (1988) and Engle and Granger (1991), as discussed by Nkoro and Uko (2016) or Philips (2018). Furthermore, ARDL models show higher efficiency when describing the short-versus long-run relationships between variables (Horobet et al, 2022).…”