An international team including researchers from the University of Alicante (UA) and the Universitat Politècnica de València (UPV) has used artificial intelligence to analyse the climate commitments submitted to the United Nations by 158 countries. Their conclusion is stark: profound inequalities persist within global climate planning.
The paper, published in the journal Nature Communications, concludes that high-income nations focus their climate commitments on health, technological transitions and emissions reduction. Conversely, low- and middle-income countries tie climate action to immediate survival challenges – such as access to water, energy, food security and natural resource management.
Researchers analysed Nationally Determined Contributions (NDCs) – the periodic climate action plans submitted under the Paris Agreement – using advanced generative AI models. This technology identified implicit connections between national climate measures and the UN Sustainable Development Goals (SDGs).
Analysing all this information allows us to understand countries' priorities, the risks they consider most important, and where potential inconsistencies or blind spots exist before new decisions are adopted, as explained by Javier García Martínez, one of the authors and a professor at the University of Alicante. The findings are particularly time-sensitive as governments worldwide prepare their next round of climate pledges for 2035.
The study found that over half of the countries analysed do not explicitly mention the SDGs in their pledges. Furthermore, pillars of sustainable transition such as education and gender equality are poorly represented across the board, regardless of a nation's income level.
According to Sergio Hoyas, a professor at the Universitat Politècnica de València (UPV) who participated in the study, "These results highlight critical misalignments between the climate agenda and the sustainable development goals driven by the United Nations".
AI as an ally against cimate change
Beyond diagnosing national priorities, the authors argue that generative AI can serve as a powerful tool to evaluate the quality and coherence of climate policies before they come into effect. The research team suggests this analysis will help governments, international agencies and funding bodies identify genuine priorities, improve resource allocation and prevent future climate strategies from worsening existing global inequities.
"At a time when the international community is debating how to accelerate climate action and finance the energy transition, this study offers an unprecedented map of the concerns, aspirations and contradictions within national climate plans worldwide," concluded UPV professor Alberto Conejero.
The interdisciplinary project brought together Teaching and Research Staff (PDI) from the University of Alicante's Department of Inorganic Chemistry and the UPV's Institute of Pure and Applied Mathematics, alongside experts from the KTH Royal Institute of Technology, the University of Oxford and the University of Michigan.