A Yale Center for Natural Carbon Capture (YCNCC) research team led by Scientific Leadership Team (SLT) member and Earth & Planetary Sciences (EPS) Assistant Professor Elizabeth Yankovsky and YCNCC Associate Research Scientist Luke Gloege have won a $1.9 million Phase II Award from the Bezos Earth Fund (BEF) AI for Climate and Nature Grand Challenge. YCNCC SLT member and EPS Professor Noah Planavsky and YCNCC Managing Director Toby Bryce helped to develop the proposal.
Marine carbon dioxide removal (mCDR) is a high-potential natural climate mitigation solution that leverages the ocean’s tremendous scale to remove carbon dioxide from the atmosphere. However, because the world ocean is a massive open system, monitoring, reporting, and verification (MRV) of mCDR solutions’ effectiveness is a significant and unsolved challenge – and an important research focus for the YCNCC.
Most mCDR solutions remove carbon dioxide from the atmosphere via air-sea gas exchange that is governed by small-scale ocean turbulence, which is not factored in current mCDR MRV. Yankovsky, Gloege, and team have proposed a novel method to address this gap, using machine learning to reconcile small-scale, regional, and global modeling in a computationally efficient and high-fidelity forecasting system for mCDR interventions. Once in operation, the system will be made available on an open-source basis to the mCDR research community, mCDR companies and project developers, and carbon credit registries for general use. The system is additionally intended to be used by enhanced weathering project developers to model marine storage of the stable bicarbonate product of weathering.
