Ocean models are expected to play a central role in the monitoring, reporting, and verification (MRV) of marine carbon dioxide removal (mCDR). Yet model-based MRV studies are often built on bespoke workflows that are difficult to reproduce, limiting transparency, independent verification, and comparison across studies. We present a fully reproducible modeling framework for ocean alkalinity enhancement (OAE) MRV and demonstrate its application to Ebb Carbon's Project Macoma, an electrochemical OAE pilot deployment in the Salish Sea.

The C-Star modeling framework was used to enable reproducible configuration, execution, visualization and standards-compliant analysis of mCDR simulations of this complex coastal environment. The C-Star setup for Project Macoma prescribes observed alkalinity additions as a time-varying source within a nested, coupled physical–biogeochemical model (ROMS-MARBL) to quantify carbon uptake, retention, and uncertainty associated with interannual variability. . The use of a  three-level nested configuration – resolving near-field transport at ~600 m while embedding the deployment within 3 km and 12 km regional domains – with the ability to upscale the OAE signal across domains allows us to f capture the full carbon-removal footprint from the coastal to the basin scale.  This represents a first-of-its-kind multi-scale approach to OAE CDR quantification using a consistent underlying modeling system

We present quantification of the mCDR effort, including total carbon update, efficiency, and analysis of spatio-temportal environmental factors that control mCDR outcomes.  By applying the C-Star framework to an operational OAE deployment, we provide a transparent and transferable template for model-based MRV that improves reproducibility, comparability, and confidence across OAE and other mCDR applications.