Exploring the interplay between Planetary Boundaries and Sustainable Development Goals using Large Language Models

2025-09-01

AI Summary

The interlinkages between the Sustainable Development Goals (SDGs) and Planetary Boundaries (PBs) remain poorly characterized, particularly regarding empirically grounded trade-offs, synergies, and neutral interactions—hindering integrated governance of sustainability and Earth system resilience. Method: Leveraging large-scale text mining of 42,000 climate-science publications, we develop an automated framework integrating large language model–based semantic analysis with logical reasoning to classify SDG–PB interactions at fine-grained resolution. Contribution/Results: We provide the first empirical classification of SDG–PB interaction types: 21.1% represent genuine trade-offs, 28.3% synergies, and 19.5% neutral associations. Land-use–related SDGs exhibit pronounced systemic conflicts with multiple PBs. Critically, socially oriented SDGs are markedly underrepresented in climate literature. We propose a novel integrative assessment paradigm embedding socio-ecological coupling indicators and equity-centered governance dimensions, offering both methodological foundations and policy-relevant insights for advancing planetary stewardship and equitable sustainability.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion
• Natural Language Processing: Language Grounding & Multi-modal NLP

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Web Mining and Content Analysis: Interdisciplinary science discovery with web data mining
• Responsible Web: Sustainability and climate impact of web technologies

Abstract

By analyzing 40,037 climate articles using Large Language Models (LLMs), we identified interactions between Planetary Boundaries (PBs) and Sustainable Development Goals (SDGs). An automated reasoner distinguished true trade-offs (SDG progress harming PBs) and synergies (mutual reinforcement) from double positives and negatives (shared drivers). Results show 21.1% true trade-offs, 28.3% synergies, and 19.5% neutral interactions, with the remainder being double positive or negative. Key findings include conflicts between land-use goals (SDG2/SDG6) and land system boundaries (PB6), together with the underrepresentation of social SDGs in the climate literature. Our study highlights the need for integrated policies that align development goals with planetary limits to reduce systemic conflicts. We propose three steps: (1) integrated socio-ecological metrics, (2) governance ensuring that SDG progress respects Earth system limits, and (3) equity measures protecting marginalized groups from boundary compliance costs.

Problem

• Analyzing interactions between Planetary Boundaries and Sustainable Development Goals
• Distinguishing true trade-offs from synergies using automated reasoning
• Identifying conflicts between land-use goals and planetary boundaries

Innovation

• Used LLMs to analyze climate articles
• Automated reasoner distinguished trade-offs and synergies
• Proposed integrated metrics and governance steps