Quantifying Marine Carbon Dioxide Removal via Alkalinity Enhancement Across Circulation Regimes Using ECCO-Darwin and 1D Models

Ocean Alkalinity Enhancement (OAE) is emerging as a viable method for removing anthropogenic ${CO}_2$ emissions from the atmosphere to mitigate climate change. To achieve substantial carbon reductions, OAE would need to be deployed at scale across the global ocean. Hence, there is a need to quantify how the efficiency of OAE varies globally across a range of space-time scales in preparation for field deployments. Here we develop a marine carbon dioxide removal (mCDR) efficiency evaluation framework based on the data-assimilative ECCO-Darwin ocean biogeochemistry model, which separates and quantifies two key factors over seasonal to multi-annual timescales: (a) mCDR potential, which quantifies the ability of seawater to store additional carbon after an alkalinity perturbation; and (b) dynamical mCDR efficiency, representing the impact of ocean advection, mixing, and air-sea ${CO}_2$ exchange. We apply this framework to virtual OAE deployments in five archetypal ocean circulation regimes with different mCDR potentials and dynamical efficiencies. The simulations highlight the importance of the dynamical factors, especially vertical transport, in driving differences in efficiency. To rapidly isolate and quantify the factors that determine dynamical efficiency, we develop a reduced complexity 1D model, rapid-mCDR. We show that combining the rapid-mCDR model with existing ECCO-Darwin output allows for rapid characterization of OAE efficiency at any location globally. Thus, these tools can be readily employed by research teams and industry to model future field deployments and contribute to essential monitoring, reporting, and verification efforts.