Decomposition analysis of electricity generation on carbon dioxide emissions in Ghana

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/142083
Información del item - Informació de l'item - Item information
Title: Decomposition analysis of electricity generation on carbon dioxide emissions in Ghana
Authors: Oteng-Abayie, Eric Fosu | Asaki, Foster Awindolla | Duodu, Emmanuel | Mahawiya, Sulemana | Gyamfi, Bright Akwasi
Center, Department or Service: Universidad de Alicante. Departamento de Fundamentos del Análisis Económico
Keywords: Electricity generation | CO2 emission | ARDL technique | Decomposition analysis | Logarithmic mean divisia index
Issue Date: 15-Apr-2024
Publisher: Elsevier
Citation: Heliyon. 2024, 10(7): e28212. https://doi.org/10.1016/j.heliyon.2024.e28212
Abstract: This study analyses the factors driving CO2 emissions from electricity generation in Ghana from 1990 to 2020. Employing Logarithmic Mean Divisia Index (LMDI) and Autoregressive Distributed Lag (ARDL) techniques, the research decomposes electricity generation into different factors and assesses their impact on CO2 emissions, considering both short and long-run effects. The LMDI analysis reveals that the total CO2 emissions from electricity generation amount to 3.33%, with all factors contributing positively in each subperiod. Notably, fossil fuel intensity, production, and transformation factors exhibit substantial contributions of about 1.16%, 0.49%, and 0.48%, respectively. Contrastingly, the ARDL results highlight that only electricity intensity and production factors significantly increase CO2 emissions by about 0.20% and 0.09% (0.38% and 0.10%) in the short-run (long-run), while other factors contribute to a reduction in electricity generation emissions. Overall, we conclude that electricity intensity and production factors are the primary drivers of CO2 emissions from electricity generation in Ghana. Nevertheless, effective measures to address all decomposition factors is crucial for effective mitigation of electricity generation CO2 emissions.
URI: http://hdl.handle.net/10045/142083
ISSN: 2405-8440
DOI: 10.1016/j.heliyon.2024.e28212
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer Review: si
Publisher version: https://doi.org/10.1016/j.heliyon.2024.e28212
Appears in Collections:Personal Investigador sin Adscripción a Grupo

Files in This Item:
Files in This Item:
File Description SizeFormat 
ThumbnailOteng-Abayie_etal_2024_Heliyon.pdf786,87 kBAdobe PDFOpen Preview


Items in RUA are protected by copyright, with all rights reserved, unless otherwise indicated.