Beta This website is in development — content and design are still changing
IAMC

Publication

From least-cost to SDG-optimal sectoral allocation of Paris Agreement-compatible mitigation efforts

Limiting global warming to well below 2 °C necessitates profound decarbonization, but how to distribute mitigation efforts over sectors remains a widely debated issue. Although integrated assessment models traditionally rely on ‘least-cost’ optimization to answer this question, the resulting sectoral allocations vary widely and ignore impacts on other potential policy objectives.

From least-cost to SDG-optimal sectoral allocation of Paris Agreement-compatible mitigation efforts

Limiting global warming to well below 2 °C necessitates profound decarbonization, but how to distribute mitigation efforts over sectors remains a widely debated issue. Although integrated assessment models traditionally rely on ‘least-cost’ optimization to answer this question, the resulting sectoral allocations vary widely and ignore impacts on other potential policy objectives. Here we connect an integrated assessment models with a portfolio analysis to evaluate how sector-specific mitigation actions impact key indicators from Sustainable Development Goals (SDGs) related to poverty, health, water, economy and land, and to identify Pareto-optimal and Paris-compliant mitigation portfolios that reveal the trade-offs between other sustainable development priorities. Furthermore, we define ‘SDG-balanced’ portfolios that, in most cases, outperform standard least-cost scenarios across all five SDG indicators for an equivalent carbon budget. Our findings demonstrate that the simultaneous evaluation of a broader set of policy priorities is crucial to provide truly policy-relevant guidance for the climate transition.

Van de Ven, DJ., Rodés-Bachs, C., Rouhette, T. et al. From least-cost to SDG-optimal sectoral allocation of Paris Agreement-compatible mitigation efforts. Nat. Clim. Chang. (2026)

https://doi.org/10.1038/s41558-026-02602-3

More publications

A harmonised dataset for Earth system foundation models

Foundation models for Earth systems have so far been trained primarily on physical climate and weather data, with limited representation of the human systems that both drive and respond to environmental change. The lack of a unified global training resource that combines climate, land, ocean, cryosphere, infrastructure, hazards, and socioeconomic