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Free keywords:
carbon dioxide, removals, portfolios, decision-making, uncertainty, planetary boundaries, technological learning
Abstract:
Deep uncertainty about the costs and resource limits of carbon dioxide removal (CDR) options challenges the design of robust portfolios. To address this, we here introduce the CDR sustainable portfolios with endogenous cost model, a mixed-integer linear optimization model for cost-optimal and time-dependent CDR portfolios including endogenous treatment of technology cost dynamics. We explore future uncertainty in three key dimensions: realisable mitigation potentials, cost dynamics, and resource constraints. Our results demonstrate that afforestation and reforestation, and soil carbon sequestration appear as robust options, deployed regardless of the removals required. Direct air carbon capture and storage emerges as the most deployed technology in 2100 at median value (6.7 GtCO2 yr−1), but with the widest range of possible outcomes (interquartile range from 4 to 8.7 GtCO2 yr−1) depending largely on future renewable energy capacity and annual geological storage injection rates. Bioenergy with CCS deployment remains severely constrained by available land, as the median falls from 1.8 to 0.3 GtCO2 yr−1 in land-constrained scenarios, but gains portfolio share when future energy availability is bounded. Our simulations also reveal that ocean alkalinisation could become a dominant solution in high removal scenarios. Evaluating the performance of portfolios beyond economic costs, we also provide a framework to explore trade-offs across different aspects relevant to planetary boundaries.
