Time, frequency, and quantile-based impacts of disaggregated electricity generation on carbon neutrality: evidence from leading European Union countries

Abstract

ABSTRACTDue to increasing geopolitical tensions and disruption of gas supplies, European countries have been looking for alternatives for electricity generation (EG). As part of this process, one of the most important goals for long-term sustainability is to ensure carbon neutrality. Therefore, this study analyzes time, frequency, and quantile-based impacts of EG from different electricity generation sources (i.e., renewable, nuclear, and fossil fuels) on carbon neutrality, focusing on four leading European countries. The study applies the wavelet transform coherence (WC), quantile-on-quantile regression (QQ), and Granger causality in quantiles (GQ) to high-frequency daily data between January 2, 2019 and March 10, 2023. Results show that (i) there is a strong time and frequency dependence between EG and CO2 emissions across countries, while results vary by EG sources and countries; (ii) renewable EG dampens CO2 emissions. At higher quantiles, a higher share of renewable EG lowers CO2 emissions in Germany and Spain, while they increase in France; (iii) nuclear EG is beneficial only for the United Kingdom. (iv) Fossil EG increases CO2 emissions in all countries. Excessive fossil EG leads to more CO2 emissions at higher quantiles; (v) the impacts of EG on CO2 emissions have a time-, frequency-, quantile-, country-, and EG source-dependent structure. The outcomes of the study demonstrates that the ideal EG source for countries is mainly renewable EG, while in the case of the United Kingdom, nuclear EG could be an alternative for improving the environment while reducing fossil fuels.KEYWORDS: ElectricityCO2 emissionsEuropean Union countriesDisaggregated Analysisnonlinear methodsJEL CLASSIFICATION: C32N50O13 Highlights The study examines impacts of electricity generation (EG) on carbon neutrality.The study focuses on leading four European countries.The study applies nonlinear approaches by using high-frequency daily data.The ideal EG source is generally renewable and partially nuclear.EG has a time, frequency, quantile, and country-varying impact.The results are consistent and robust based on alternative method.Acronyms BDS=Broock, Scheinkman, Dechert, and LeBaronBRICS=Brazil, Russia, India, China, South AfricaCO2=Carbon DioxideEG=Electricity GenerationEU=European UnionGQ=Granger Causality-in-QuantilesGWh=Gigawatt-HourIEA=International Energy AgencyJB=Jarque BeraOECD=Organization for Economic Co-operation and DevelopmentQQ=Quantile-on-Quantile RegressionQR=Quantile RegressionSDGs=Sustainable Development GoalsTWh=terawatt-hoursUN=United NationsUSD=United States DollarsWC=Wavelet CoherenceDependent Variable=CO2=Total CO2 EmissionsIndependent Variables=REG=Renewable EGNEG=Nuclear EGFEG=Fossil EGAnalysis Scope=DEU=GermanyESP=SpainFRA=FranceGBR=United KingdomDisclosure statementNo potential conflict of interest was reported by the authors.Authors’ contributionsThe authors have contributed equally to this work. All authors read and approved the final manuscript.Availability of data and materialsData will be made available on request.Consent for publicationThe authors are willing to permit the Journal to publish the article.Additional informationFundingThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.