Techno-economic analysis of ocean iron fertilization - Ward, C.; Lee Pereira, R. J.; Foteinis, S.; Renforth, P. (Frontiers in Climate, 2025)
This study provides an updated, comprehensive framework for conducting a techno-economic assessment (TEA) of novel carbon dioxide removal approaches. Specifically, the framework is applied to a scenario involving ocean iron fertilization (OIF) in the Southern Ocean. The study investigates whether cost elements, such as administrative and support labor, are accurately included in standard methodologies and proposes solutions for characterizing prospective cost elements and uncertainty in novel CDR TEAs. The first-of-a-kind (FOAK) levelized cost of carbon (LCOC) for OIF deployment is approximately $200 per tonne of CO2. Learning rates are applied, and prospective nth-of-a-kind (NOAK) costs decrease to approximately $180 per tonne of CO2. A local sensitivity analysis indicates that oceanographic parameters, such as the export efficiency of carbon biomass to the deep ocean, have a greater impact on the LCOC compared to engineering parameters like the cost of equipment or materials. Nevertheless, large capital engineering expenditures of approximately $120–160 million also significantly affect the levelized cost. The effect of these high-impact parameters on the LCOC is demonstrated by a cost range from $25 per tonne of CO2 to $53,000 per tonne of CO2 for best- to worst-case scenarios when varying values for monitoring, reporting, and verification (MRV) processes, losses due to nutrient robbing, equivalent carbon (CO2e) losses from N2O production, CO2 ventilation losses to the atmosphere, net increase in primary production, and export efficiency are considered. Additionally, the effect of learning rates on determining prospective costs is shown through a sensitivity analysis to have a less significant impact on the overall costs of deployment and, in turn, future cost reductions when large parameter input uncertainties are present. Based on these results, it is recommended that oceanographic parameters be better characterized through additional research and development to reduce uncertainty in cost estimation. Methods of OIF deployment, including MRV processes, should also be investigated to minimize capital costs. Additionally, the proposed framework, including the bottom-up business cost analysis, should be applied to other CDR approaches to provide consistent and comprehensive comparisons for companies and decision-makers, underpinning informed funding decisions in the CDR space.