Nuclear energy transition and CO2 emissions nexus in 28 nuclear electricity-producing countries with different income levels

Author:

Mahmood HaiderORCID

Abstract

Background Nuclear energy carries the least environmental effects compared to fossil fuels and most other renewable energy sources. Therefore, nuclear energy transition (NET) would reduce pollution emissions. The present study investigates the role of the NET on CO2 emissions and tests the environmental Kuznets curve (EKC) in the 28 nuclear electricity-producing countries from 1996–2019. Methods Along with a focus on the whole panel, countries are divided into three income groups using the World Bank classification, i.e., three Lower-Middle-Income (LMI), eight Upper-Middle-Income (UMI), and 17 High-Income (HI) countries. The cross-sectional dependence panel data estimation techniques are applied for the long and short run analyses. Results In the long run, the EKC is corroborated in HI countries’ panel with estimated positive and negative coefficients of economic growth and its square variable. The Netherlands, Sweden, Switzerland, and the USA are found in the 2nd stage of the EKC. However, the remaining HI economies are facing 1st phase of the EKC. Moreover, economic growth has a monotonic positive effect on CO2 emissions in LMI and UMI economies. NET reduces CO2 emissions in UMI and HI economies. On the other hand, NET has an insignificant effect on CO2 emissions in LMI economies. In the short run, the EKC is validated and NET has a negative effect on CO2 emissions in HI countries and the whole panel. However, NET could not affect CO2 emissions in LMI and UMI countries. Based on the long-run results, we recommend enhancing nuclear energy transition in UMI and HI economies to reduce CO2 emissions. In addition, the rest of the world should also build capacity for the nuclear energy transition to save the world from global warming.

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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