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Assessing the carbon footprint of artificial intelligence in higher education: a bibliometric and institutional analysis

2026-05-22Artigo científico Acesso aberto
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datacite.subject.fosCiências Naturais::Ciências da Terra e do Ambiente
datacite.subject.sdg13:Ação Climática
datacite.subject.sdg07:Energias Renováveis e Acessíveis
datacite.subject.sdg04:Educação de Qualidade
dc.contributor.authorLeal Filho, Walter
dc.contributor.authorLuetz, Johannes
dc.contributor.authorAlmulhim, Abdulaziz I.
dc.contributor.authorDinis, Maria Alzira Pimenta
dc.date.accessioned2026-07-15T10:51:40Z
dc.date.available2026-07-15T10:51:40Z
dc.date.issued2026-05-22
dc.description.abstractThe rapid integration of artificial intelligence (AI) across higher education has transformed research, teaching, and institutional operations. Yet its environmental implications remain poorly understood at the institutional level. While a growing literature examines the energy consumption and carbon footprint of AI systems, little is known about how these concerns are recognised or addressed within universities. This study addresses this gap by combining a bibliometric analysis of 461 peer-reviewed publications indexed in Scopus (2014–2025) with a multiple-case study analysis of selected research-intensive universities. The bibliometric analysis reveals a rapidly expanding research landscape dominated by themes such as machine learning, energy consumption, optimisation, and sustainability, alongside a comparatively limited focus on higher education as an institutional context. The case studies, based on sustainability reports, climate action plans, and environmental disclosures, focus on a set of research-intensive universities with substantial AI-related infrastructure. They show a consistent pattern: despite the centrality of high-performance computing (HPC) and cloud-based platforms, institutional reporting of energy and carbon emissions remains aggregated, rarely examining AI-specific impacts. This reveals a governance gap between the expanding scientific understanding of AI’s environmental footprint and the maturity of sustainability practices in academia. The novelty of this study lies in the integration of bibliometric analysis with institutional case study evidence to systematically examine how AI-related energy use and carbon emissions are addressed in higher education. By bridging these two analytical dimensions, the study provides new insight into the disconnect between research advances and institutional practice and highlights the need for dedicated frameworks to account for AI-related energy use and emissions. The study also aligns with the United Nations Sustainable Development Goals (SDGs), particularly Affordable and Clean Energy (SDG 7), Climate Action (SDG 13), and Quality Education (SDG 4), contributing to the ongoing debate on responsible and sustainable AI in higher education.eng
dc.identifier.citationLeal Filho, W., Luetz, J. M., Almulhim, A. I., & Dinis, M. A. P. (2026). Assessing the carbon footprint of artificial intelligence in higher education: a bibliometric and institutional analysis [Research]. Environmental Sciences Europe, 38(1), 1–19, Article 132. https://doi.org/10.1186/s12302-026-01414-8
dc.identifier.doi10.1186/s12302-026-01414-8
dc.identifier.issn2190-4715
dc.identifier.urihttp://hdl.handle.net/10284/15523
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Science and Business Media LLC
dc.relation.hasversionhttps://link.springer.com/article/10.1186/s12302-026-01414-8
dc.relation.ispartofEnvironmental Sciences Europe
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectArtificial intelligence
dc.subjectCarbon footprint
dc.subjectHigher education
dc.subjectSustainability
dc.subjectEnergy efficiency
dc.subjectInstitutional governance
dc.titleAssessing the carbon footprint of artificial intelligence in higher education: a bibliometric and institutional analysiseng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage19
oaire.citation.issue1
oaire.citation.startPage1
oaire.citation.titleEnvironmental Sciences Europe
oaire.citation.volume38
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameLeal Filho
person.familyNameLuetz
person.familyNameAlmulhim
person.familyNameDinis
person.givenNameWalter
person.givenNameJohannes
person.givenNameAbdulaziz I.
person.givenNameMaria Alzira Pimenta
person.identifier0000000121351158
person.identifier493603
person.identifier.ciencia-idE01A-32E6-9A1C
person.identifier.ciencia-id4710-147D-FDAF
person.identifier.orcid0000-0002-1241-5225
person.identifier.orcid0000-0002-9017-4471
person.identifier.orcid0000-0002-5384-7219
person.identifier.orcid0000-0002-2198-6740
person.identifier.ridAAH-5131-2019
person.identifier.ridF-3309-2011
person.identifier.scopus-author-id6602389932
person.identifier.scopus-author-id57207844992
person.identifier.scopus-author-id55539804000
relation.isAuthorOfPublication8af3c3c1-d73c-450a-a2a6-9fc392919b70
relation.isAuthorOfPublication40499c39-9554-4a8d-8d0f-3a7ec74d17a1
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relation.isAuthorOfPublication1e85592a-e8e2-4aea-bd8e-1007c94388c0
relation.isAuthorOfPublication.latestForDiscovery1e85592a-e8e2-4aea-bd8e-1007c94388c0

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