Profiling Scientific Influences on Climate Policy: A Case Study on IPCC and Country Submissions to UNFCCC

ACL 2024 Workshop ClimateNLP Submission12 Authors

Keywords: natural language processing, topic modelling, climate change, policy

TL;DR: Profiling the intersection between science and policy in the climate change domain

Abstract:

There are abundant information about the science of climate change, and abundant policy documents on measures to mitigate and adapt to climate change. A key question is whether or not, and how much of the former influences the latter.
This work takes a first step towards profiling the scientific influences on climate policy. We present a case study that extracts the mentions and quotes of IPCC, the intergovernmental scientific body, among 1.1M paragraphs of text from 198 countries to the united nations. We use three different methods: counting mentions, modeling topics, and finding quotes. We observe that 80\% of the documents and 2\% paragraphs mention IPCC. Such mentions can be categorized into six broad topical groups, five of which concerns the measurement and sector-specific Green House Gas (GHG) Emissions, and one on Climate Change Scenario and Impact. Upon further examining the phrases that mention IPCC, we found that mentions disproportionally focus on the IPCC GHG guidelines. This is a first step towards profiling the intersection between science and policy, which we hope will generate valuable discussions in the NLP and Climate research community.

Archival Submission: non-arxival

Arxival Submission: arxival

Submission Number: 12