About the Marine CDR Tools
These Marine CDR tools are a joint project between CarbonPlan and [C]Worthy designed to help people understand how marine CDR works.
Both tools allow users to explore how differences in location and season affect how much carbon removal a marine CDR intervention can achieve over time. The first focuses on ocean alkalinity enhancement (OAE) — an approach that adds alkalinity to the surface ocean, increasing its ability to absorb CO₂ by improving chemical buffering capacity. The second focuses on direct ocean removal (DOR) — an approach that extracts CO₂ from seawater, creating space for the ocean to re-absorb atmospheric CO₂ to return to its original state, and storing or otherwise utilizing the extracted CO₂.
Both map tools are based on the same modeling framework, using a coarse-resolution global ocean circulation model from the Community Earth System Model. Briefly, we divided the surface ocean into 690 regions, and simulated an OAE or DOR intervention occurring in that region for 1 month (e.g., adding alkalinity or removing dissolved inorganic carbon at a rate of 10 mol m–2yr–1). We then ran the model for 15 years to simulate how this intervention led to atmospheric carbon removal.
You can use the tools to explore global patterns in carbon removal efficiency, or drill down to visualize how these interventions move through the ocean and result in carbon removal over time.
Map variables
The two mapping tools share many of the same variables.
| Variable | Units | Tool | |
| Efficiency (DOR comparison) | CO₂ absorbed / potential removal | Both | CO₂ removed from the atmosphere per unit of removal potential created by the DOR or OAE intervention. Higher values indicate more efficient carbon removal. For DOR, the maximum potential removal corresponds directly with the CO₂ deficit created by CO₂ extraction during the intervention period. For OAE, the maximum CO₂ removal is estimated based on the amount of alkalinity added during the intervention period and the seawater chemistry in the injection region. Accessed in OAE under the field “Efficiency (DOR comparison)” and “Efficiency” in the DOR tool. |
| Efficiency | CO₂ absorbed / alkalinity added | OAE only | CO₂ removed per unit of alkalinity added. Higher values indicate more efficient carbon removal. |
| Spread of CO₂ uptake | % | OAE only, DOR forthcoming | Percentage of cumulative CO₂ uptake taking place within a specified distance from the center of the intervention region. |
| DIC anomaly/full field (only at surface) | mol/m³ | Both | Extracting CO₂ creates a dissolved inorganic carbon (DIC) deficit. A larger deficit means more potential for the ocean to absorb CO₂ from the atmosphere. |
| Dissolved inorganic carbon (DIC) | mol/m² | Both | Dissolved inorganic carbon (DIC) is the sum of inorganic carbon in water. Full water column values shown in the tools |
| Partial pressure of CO₂ (pCO₂) | µatm | Both | The partial pressure of carbon dioxide at the ocean surface, a measure of how much CO₂ is dissolved in seawater. Ocean carbon uptake happens when the surface ocean pCO₂ is lower than the partial pressure of CO₂ in the overlying atmosphere. |
| Air-sea CO₂ flux | mol/m²/yr | Both | The movement of carbon dioxide between the atmosphere and the ocean. Negative values indicate ocean CO₂ uptake. |
| pH | N/A | Both | The measurement of acidity, or free hydrogen ions, in surface waters. The lower the pH value, the more acidic the seawater. |
Comparing OAE and DOR
We initially defined OAE efficiency (𝜂) as the amount of CO₂ removed from the atmosphere per unit of alkalinity added. However, to compare across DOR and OAE, we use a different efficiency metric (γ): the amount of CO₂ absorbed from the atmosphere per unit of removal potential generated by the intervention.
For DOR, the maximum potential removal is equivalent to the amount of CO₂ extracted from the surface ocean. For OAE, this comparison requires calculating the maximum removal potential associated with the simulated alkalinity additions. This is done as follows. Our original definition of efficiency, the amount of CO₂ removed from the atmosphere per unit of alkalinity added, can be written as
𝜂(t) = ∆DIC(t) / ∆Alk
where ∆Alk is the amount of alkalinity added to the ocean and ∆DIC(t) is the resulting change in the ocean carbon inventory over time. Under the condition of full re-equilibration, we have
𝜂max = ∆DIC(t=∞) / ∆Alk
where ∆DIC(t=∞) is the amount of potential DIC uptake induced by the chemical effects of the alkalinity addition. Therefore, to compute an efficiency metric for OAE that is directly comparable to DOR, we divide 𝜂(t) by 𝜂max, yielding
γOAE(t) = 𝜂(t) / 𝜂max
To perform this conversion on the OAE dataset, we estimate 𝜂ₘₐₓ from the background ocean state, using the thermodynamic equations defining the seawater carbonate system equilibrium chemistry. Notably, 𝜂ₘₐₓ varies from about 0.7 in the tropical surface ocean to about 0.9 at high latitudes. This approach is not perfect, as we are using time-averaged fields and mixing along the trajectory of the alkalinity plume entrains waters with distinct chemical composition. In practice, however, we find that the errors introduced by these factors are very small (less than ±0.1) relative to the large-scale spatial and seasonal structure in the efficiency fields, so the approach provides a robust basis to compare the efficiency of OAE and DOR.
Version history
| Date | OAE | DOR |
| 10-15-2024 | Initial release | N/A |
| 06-04-2025 | Corrected DIC units; integrated sea surface height into DIC and Efficiency calculations and updated tool data; added new field titled "Efficiency (DOR comparison)" to enable direct comparisons with the DOR data. | Initial release |
Additional resources
| Map tools | OAE | DOR |
| Explainer articles | OAE | DOR |
| Scientific papers | OAE | Forthcoming |
| Research-grade data | OAE | DOR |
| Web tool code | Shared repository |
Acknowledgements
CarbonPlan and [C]Worthy received funding from the Carbon to Sea Initiative (via Windward Fund) and the Environmental Defense Fund for the OAE tool and its explainer. The DOR dataset generation, explainer article, and interactive tool development were supported by grants to [C]Worthy from the Chan Zuckerberg Initiative, the Navigation Fund, and the Grantham Foundation, and funding to CarbonPlan from [C]Worthy.
This material is based on work by [C]Worthy and collaborators that was supported by the National Center for Atmospheric Research (NCAR), a major facility sponsored by the National Science Foundation (NSF) under Cooperative Agreement No. 1852977. Mengyang received support from the Advanced Study Program Graduate Visitor Program at the National Center for Atmospheric Research. The authors acknowledge high performance computing support from the Cheyenne supercomputer provided by NCAR's Computational and Information Systems Laboratory, sponsored by the NSF. This research also used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy Office of Science User Facility using NERSC award ALCC-ERCAP0034226.