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Artificial intelligence and climate change: the potential roles of foundation models

2025-10-13Journal article Open access
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datacite.subject.fosEngenharia e Tecnologia::Engenharia do Ambiente
datacite.subject.sdg13:Ação Climática
dc.contributor.authorLeal Filho, Walter
dc.contributor.authorKovaleva, Marina
dc.contributor.authorNg, Artie
dc.contributor.authorNagy, Gustavo
dc.contributor.authorLuetz, Johannes
dc.contributor.authorDinis, Maria Alzira Pimenta
dc.date.accessioned2025-10-28T14:50:01Z
dc.date.available2025-10-28T14:50:01Z
dc.date.issued2025-10-13
dc.description.abstractArtificial intelligence (AI) is being developed fast and applied in several areas including education and healthcare with excellent potential for use in fields that require complex analytics, particularly in the case of climate change. Recent developments in AI, such as ChatGPT and OpenAI, machine vision technologies and deep learning, among others, may be deployed in various contexts, including climate change. Of specific interest is the role played by foundation models (FMs), which may help to augment intelligence on climate change and reduce the social risks of adaptation and mitigation initiatives. This article discusses the potential applications of FMs in climate change research and management and illustrates the need for further studies. FMs, built on large unlabelled data sets and enabled by transfer learning, offer versatility in handling complex tasks. Specifically, FMs can aid in climate data analysis, modelling future scenarios, assessing risks, and supporting decision-making processes. Despite their potential, challenges such as data privacy, algorithm bias, and energy consumption require careful consideration. The article emphasizes the importance of interdisciplinary efforts to address these challenges and maximize the positive impact of FMs in mitigation and adaptation. AI, including advanced models like FMs, holds significant promise for addressing climate change challenges.eng
dc.identifier.citationFilho, W. L., Kovaleva, M., Ng, A. W., Nagy, G. J., Lütz, J. M., & Dinis, M. A. P. (2025). Artificial intelligence and climate change: the potential roles of foundation models [Research]. Environmental Sciences Europe, 37(1), 1-9, Article 159. https://doi.org/10.1186/s12302-025-01153-2
dc.identifier.doi10.1186/s12302-025-01153-2
dc.identifier.issn2190-4715
dc.identifier.urihttp://hdl.handle.net/10284/14699
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature
dc.relation.hasversionhttps://link.springer.com/article/10.1186/s12302-025-01153-2
dc.relation.ispartofEnvironmental Sciences Europe
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectArtificial intelligence (AI)
dc.subjectFoundation models (FMs)
dc.subjectClimate change
dc.subjectAdaptation
dc.subjectMitigation
dc.titleArtificial intelligence and climate change: the potential roles of foundation models
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage9
oaire.citation.issue1
oaire.citation.startPage1
oaire.citation.titleEnvironmental Sciences Europe
oaire.citation.volume37
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameLeal Filho
person.familyNameNg
person.familyNameNagy
person.familyNameLuetz
person.familyNameDinis
person.givenNameWalter
person.givenNameArtie
person.givenNameGustavo
person.givenNameJohannes
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.orcid0000-0002-1388-5835
person.identifier.orcid0000-0002-8296-4465
person.identifier.orcid0000-0002-9017-4471
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
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