Marine carbon dioxide removal (mCDR) will be an essential component of a future negative emissions industry, which, alongside emissions reduction, is necessary to restrict global climate warming to less than 2°C and avoid global, irreversible, and catastrophic changes caused by this temperature rise. Sensing Exports of Anthropogenic Carbon through Ocean Observation (SEA-CO2) seeks to accelerate the development of the mCDR industry through the development of scalable Measurement, Reporting and Validation (MRV) technologies. MRV must be of sufficient quality to quantify carbon drawdown magnitudes, the degree of permanence, and bound the uncertainties associated with these parameters so that carbon markets can ascertain credit quality and financial institutions can make informed decisions regarding investment risk. To achieve these goals, a paradigm shift in chemical oceanographic data collection is required, moving from a single-point collection paradigm towards a goal of persistent sensing of parameters across large areas and/or volumes. In addition, regional-scale modeling of the combined major ocean carbon pathways relevant to mCDR applied to observation simulation experiments with quantifiable uncertainties as outputs are required. These technologies could also enhance our understanding of the secondary environmental effects associated with mCDR.
ARPA-E considers the following advancements ones that would most rapidly enable effective MRV and the robust establishment of financial value for the mCDR industry:
1. Sensing approaches to quantify oceanographic carbon properties, which boast:
- Large spatial scale, volumetric, or area-survey sensing capability with precision and accuracy (equivalent to bias and variance) comparable to today’s single-point state-of-the-art sensing approaches.
- Size, weight, and power requirements that enable utilization on existing ocean data collection platforms.
- Deployment periods exceeding one year without a reliance on physical human interaction.
2. Regionally focused models representing relevant ocean carbon fluxes and cycles at resolutions suitable to distinguish the additionality associated with mCDR events, with root-mean-square errors (RMSE) and anomaly correlation coefficients (ACC) at least comparable to general state-of-the-art ocean models.