Methodology: Analysing Science in NDCs 3.0

The research methodology developed for the ELEVATE-ProClima project employs a rigorous, interdisciplinary approach to assess the integration of scientific evidence into international climate diplomacy. Specifically, our framework systematically evaluates the presence, function, and legal operationalization of the “best available science” within the third generation of Nationally Determined Contributions (NDCs).

Methodological Pillars

Document Analysis

Keyword & Semantic Tracking

In-Situ Observation

Three Guiding Questions

  • How has the Party articulated references to the IPCC?
  • Has the Party referenced science? (Including broader notions like “best available scientific knowledge” or “latest information”)
  • Has the Party referenced the concept of “best available science”? (As required by the Paris Agreement and strengthened by the GST decision)

Categorising IPCC Engagement

Substantial Engagement

Referencing the IPCC to formulate an ambitious mitigation target that responds to the GST outcomes. This includes using the best available science to align national, economy-wide emission reduction targets with a global 1.5°C trajectory.

Partial Engagement

Referencing IPCC guidelines for greenhouse gas (GHG) accounting, global warming potentials, and inventories, but failing to mention the IPCC in the context of setting an ambitious target or carbon budget.

Minimal Engagement

Referencing the IPCC without explaining how the scientific evidence actually influenced the submission (for example, isolating references only to footnotes).

No Mention

NDCs 3.0 where the IPCC is not referenced at all.

Methodological Limitations

Our focus rests strictly on the articulation of state practice. We assessed linguistic references to understand how Parties interpret their legal obligations; we did not attempt to validate the underlying scientific information provided or assess the actual, real-world progress of policy implementation. Furthermore, as our team analysed data spanning multiple languages, we acknowledge the inherent risk of translational errors due to linguistic nuances.