Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Drivers of carbon emissions in the era of artificial intelligence

Case of Japan

Bibliographic Data

ID22430786
AuthorsLidija Kraujalienė (0000-0002-8769-8338, Kazimieras Simonavičius University), Atif Yaseen (0009-0000-0129-300X, Kazimieras Simonavičius University), Saulius Kromalcas (0000-0001-9389-2623, Kazimieras Simonavičius University), Helga Marija Kauzonė (0009-0008-8754-2748, Kazimieras Simonavičius University)
Year2026
Volume0
Issue0
Pages1-31
Publication date2026-06-08
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueTechnological and Economic Development of Economy (JOURNAL)
Journal identifiersISSN: 2029-4913 • E-ISSN: 2029-4921
PublisherVilnius Gediminas Technical University (PUBLISHER • LT)
DOI10.3846/tede.2026.26996
OpenAlexW7163953358
LanguageEN
References cited78

This research is driven by the absence of a unified consensus regarding the relationship between artificial intelligence, energy consumption, and economic growth and their impact on CO2 emissions. Not clear whether AI increases or decreases CO2. The novelty – identification of the two-way causal link between the implementation of AI and carbon emissions, a dynamic not previously confirmed in the literature. The originality – the model tested on a scale of Japan as developed country which still around 90% depending on fossil fuels. Data period: 1995–2024. An ARDL-based econometric approach to analyze the long-term and short-term impacts and several diagnostics to improve the precision and reliability of the study results. Tests used: the Breusch-Godfrey Serial Correlation, Ramsey RESET, Breusch-Pagan-Godfrey, CUSUMSQ and CUSUM. The study outputs reveal that in Japan, AI and energy consumption are associated with an increase in carbon emissions, while exports – with decrease in emission levels. In developed economies governments recommended to lower CO2 emissions by speeding up the shift toward renewable energy sources and investing in environmentally friendly AI technologies. Policymakers should adopt an integrated approach that links AI, energy, environmental, and economic policies, supported by regulatory reforms to promote sustainability and achieve carbon neutrality. First published online 8 June 2026

Energy consumption · Fossil fuel · Greenhouse gas · Novelty · Renewable energy · Sustainability · COVID-19 impact on air quality · Energy, Environment, and Transportation Policies · Energy, Environment, Economic Growth

  • The impact of international trade on CO2 emissions in oil exporting countries

    Open Access•Fakhri Hasanov, Fakhri J Hasanov et al.•Energy Economics•2018

  • An Autoregressive Distributed-Lag Modelling Approach to Cointegration Analysis

    M Hashem Pesaran, Yongcheol Shin et al.•Econometrics and Economic Theory…•2012

  • Consumption-based carbon emissions and International trade in G7 countries

    Open Access•Zeeshan Khan, Shahid Ali et al.•The Science of The Total…•2020

  • Consumption‐based carbon emissions, renewable energy consumption, financial development and economic growth in Chile

    Open Access•Dervis Kirikkaleli, Habibe Güngör et al.•Business Strategy and the…•2022

  • Does artificial intelligence promote energy transition and curb carbon emissions? The role of trade openness

    Open Access•Qiang Wang, Fuyu Zhang et al.•Journal of Cleaner Production•2024

  • Bounds testing approaches to the analysis of level relationships

    Open Access•M Hashem Pesaran, Yongcheol Shin et al.•Journal of Applied Econometrics•2001

  • Distribution of the Estimators for Autoregressive Time Series with a Unit Root

    David A Dickey, Wayne A Fuller•Journal of the American…•1979

  • Ecological footprints, carbon emissions, and energy transitions

    Open Access•Qiang Wang, Yuanfan Li et al.•Humanities and Social Sciences…•2024

  • Energy use and urbanization as determinants of China’s environmental quality

    Irfan Khan, Fujun Hou et al.•Journal of Environmental Planning…•2022

  • Impacts of artificial intelligence on carbon emissions in China

    Open Access•Mingfang Dong, Guo Wang et al.•Sustainable Cities and Society•2024

  • Dominance of Fossil Fuels in Japan’s National Energy Mix and Implications for Environmental Sustainability

    Open Access•Tomiwa Sunday Adebayo, Abraham Ayobamiji Awosusi et al.•International Journal of…•2021

  • Investigating the nexus between CO2 emissions, renewable energy consumption, FDI, exports and economic growth

    Open Access•Amir Iqbal, Xuan Tang et al.•Environment Development and…•2023

  • Examining the relationship between technological innovation, economic growth and carbon dioxide emission

    Open Access•Itbar Khan, Ruoyu Zhong et al.•Environment Development and…•2023

  • Towards smart and sustainable transportation

    Open Access•Walid Chatti, Muhammad Tariq Majeed et al.•Environment Development and…•2024

  • Assessing the interdependence among renewable and non-renewable energies, economic growth, and CO2 emissions in Mexico

    Open Access•Héctor F Salazar-Núñez, Francisco Venegas-Martínez et al.•Environment Development and…•2022

  • Politics of climate change and energy policy in Japan

    Open Access•H Ohta, Brendan Barrett•Earth System Governance•2023

  • The dynamic linkage between remittances, export diversification, education, renewable energy consumption, economic growth, and CO 2 emissions in top remittance‐receiving countries

    Open Access•Muhammad Wasif Zafar, Muhammad Mansoor Saleem et al.•Sustainable Development•2021

  • Artificial intelligence and global embodied carbon flow

    Open Access•Zhipeng Tang, Shujuan Tang et al.•Habitat International•2025

  • Harnessing AI for renewable energy transition

    Open Access•Dong‐ping Song, Yi Hu et al.•Sustainable Futures•2025

  • Thomas Robert Malthus

    D V Gla, D V Glass et al.•Population Studies•1976

Citation velocityhistorical
Highly citedNo
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae