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

ABSTRACT

Due 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.

Graphical abstract

KEYWORDS:

• Electricity
• CO₂ emissions
• European Union countries
• Disaggregated Analysis
• nonlinear methods

JEL CLASSIFICATION:

• C32
• N50
• O13

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 LeBaron
BRICS	=	Brazil, Russia, India, China, South Africa
CO2	=	Carbon Dioxide
EG	=	Electricity Generation
EU	=	European Union
GQ	=	Granger Causality-in-Quantiles
GWh	=	Gigawatt-Hour
IEA	=	International Energy Agency
JB	=	Jarque Bera
OECD	=	Organization for Economic Co-operation and Development
QQ	=	Quantile-on-Quantile Regression
QR	=	Quantile Regression
SDGs	=	Sustainable Development Goals
TWh	=	terawatt-hours
UN	=	United Nations
USD	=	United States Dollars
WC	=	Wavelet Coherence
Dependent Variable	=
CO2	=	Total CO2 Emissions
Independent Variables	=
REG	=	Renewable EG
NEG	=	Nuclear EG
FEG	=	Fossil EG
Analysis Scope	=
DEU	=	Germany
ESP	=	Spain
FRA	=	France
GBR	=	United Kingdom

Disclosure statement

No potential conflict of interest was reported by the authors.

Authors’ contributions

The authors have contributed equally to this work. All authors read and approved the final manuscript.

Availability of data and materials

Data will be made available on request.

Consent for publication

The authors are willing to permit the Journal to publish the article.

Additional information

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.