Linguistic Decoding of Paris Climate Pledges

Parties to the Paris Agreement submit nationally determined contributions (NDCs) outlining their climate mitigation goals and strategies. While prior research has mainly evaluated mitigation targets, much of the broader textual content in NDCs has been underexplored. Using natural language processing to analyse the full text of all NDCs, this study identifies 21 topics grouped into seven themes: development, implementation and planning, mitigation targets, policies and technologies, climate impacts, agriculture and ecosystems, and stakeholders. Next, the analysis assesses how emphasis on these topics varies across countries and over time. This includes clustering parties on the basis of the similarity of topic composition in their NDCs, resulting in nine distinct clusters. A general finding is that high-income countries tend to emphasize mitigation targets while offering limited detail on specific policies. Developing countries, by contrast, often situate mitigation within wider sustainable development narratives, balancing adaptation and development priorities. The study concludes that encouraging a standardized and transparent NDC format could improve comparability and better assess how mitigation goals align with broader sustainability trade-offs and co-benefits.