The RESCUE project explores the Earth system's response to the implementation of Carbon Dioxide Removal (CDR) technologies and develops new climate projection scenarios that incorporate diverse CDR portfolios. It addresses two overarching objectives:
- Quantify Climate and Earth System Responses: Assess the impacts of pathways achieving climate neutrality through CDR deployment, with and without temperature overshoot.
- Evaluate the Role of CDR: Investigate CDR's effectiveness in reducing net greenhouse gas (GHG) emissions, along with its potential environmental risks and co-benefits.
To achieve these goals, RESCUE will advance current understanding of CDR methods and design a suite of global temperature stabilization scenarios targeting various thresholds. Innovative model developments will enable enhanced climate projections that explicitly represent CDR portfolios, supporting detailed analysis of Earth system responses, including changes in mean climate, extremes, sea-level rise, carbon cycling, biodiversity, and ecosystem services. A critical focus will be on the reversibility of changes by comparing overshoot and non-overshoot scenarios.
The project’s second objective will be addressed by examining the factors that determine the effectiveness, impacts, and co-benefits of CDR portfolios. These factors include CDR-specific CO2 uptake, CDR-induced biogeophysical climate feedbacks, CDR-derived non-CO2 radiative forcers, and the interaction between socio-economic and environmental impacts (e.g., biodiversity).
Additionally, RESCUE will establish criteria for monitoring CDR deployment effectiveness and identifying potential side effects. Stakeholder engagement will be integral throughout the project to ensure policy relevance and applicability of results. The findings will be made freely available via established climate service platforms to maximize accessibility and utility.
- Duration
- 08/2023 - 08/2026
- Project management
- Prof. Dr. Julia Pongratz
- Project scientist(s)
- Dr. Shraddha Gupta
- Subject
- Climatology, modelling
- Funded by
- European Union's Horizon Europe research and innovation programme (Grant Agreement no. 101056939)