The policy implications of an uncertain carbon dioxide removal potential

This article explores the feasibility and uncertainty of carbon dioxide removal (CDR). It conducts an expert survey on the feasible potential for CDR via bioenergy with carbon capture and storage, direct air capture and afforestation. It uses the survey results to represent uncertainty in future CDR availability and assesses the implications in an integrated assessment model (IAM). The modelling demonstrates that uncertainty of future CDR availability provides a strong rationale to increase near-term  decarbonisation efforts.   

In the expert survey, the authors asked respondents to provide their best estimate of the feasible CDR potential in 2030, 2050, and 2100 for three different removal options: bioenergy with carbon capture and storage (BECCS), direct-air carbon capture and storage (DACCS), and afforestation/reforestation (AR). The survey results showed the experts found AR to have the largest potential pre-2050 but lowest long-term potential due to issues such as land availability, institutional challenges, and sink saturation. Experts also found DACCS to have limited pre-2050 potential due to high costs and low technological readiness, but there is also greater long-term potential as costs fall and carbon prices rise, with possible rapid deployment. BECCS is thought to have the lowest feasible potential in both the short and long term. More specifically, the experts estimated DACCS to have the largest cumulative removal potential, with a median estimate of 320 Gt CO2 from 2020 to 2100, compared with BECCS (196 Gt CO2 over the same period).  

However, there is large variation between expert estimates in the survey, with some judging the feasible potential of DACCS to be in excess of 1,000 GtCO2 over the century. Reflecting on this uncertainty, the authors used a detailed-process IAM (TIAM-Grantham) and an uncertainty analysis approach called stochastic optimisation to explore the climate policy implications of this uncertainty related to CDR. Focusing on the 2020s, the model showed that higher levels of uncertainty in CDR leads to faster emission reductions, higher carbon prices, greater renewables deployment, and a faster phaseout of fossil fuels across the energy sector. This is because under a more uncertain CDR future the likely hedging strategy would be to increase action in the near term. The model's results underscore the importance of increasing the pace of decarbonisation in the 2020s, not relying on future CDR deployment to remove emissions later. The authors conclude that scientists, civil society and policymakers should recognise the urgency to push for maximum climate action in the 2020s, rather than betting on highly uncertain CDR resources in the future. 

The research in this paper can be used in arguments for accelerating near-term action to curb fossil fuel production and consumption. It also highlights that arguments in favour of fossil fuel production that rely on CDR can be challenged based on the large uncertainties in the scalability of CDR identified. It is worth noting that many scenarios used in the IPCC assessment reports that project higher levels of oil and gas production also include large amounts of CDR (Achakulwisut et al., 2023).