Award: OCE-2123768

Human activities have released large amounts of carbon dioxide (CO₂) into the atmosphere, and the global ocean has absorbed roughly one quarter of these emissions, helping to slow global warming. However, the rate and distribution of this oceanic CO₂ uptake remain uncertain, particularly in the deep ocean where long-term carbon storage occurs. This project addressed a key scientific and technical challenge: how to more accurately measure and track anthropogenic (human-derived) CO₂ in the ocean over decadal time scales and across vast regions. In particular, the project aimed to independently measure and cross-check anthropogenic CO₂ accumulation rates in the South and North Atlantic Ocean basins.

To this end, the project developed and applied a new approach for measuring the stable carbon isotope composition of dissolved inorganic carbon in seawater. Carbon isotopes provide a powerful “fingerprint” that allows scientists to distinguish anthropogenic CO₂ from natural carbon and to more sensitively quantify how much human-derived carbon the ocean has absorbed. Traditionally, these measurements required labor-intensive laboratory techniques that limited sample numbers and spatial resolution. This project demonstrated that a newer laser-based method can achieve the same level of precision while dramatically increasing the number of samples that can be analyzed, including directly onboard research vessels.

A major outcome of the project was the successful demonstration that high-quality carbon isotope data can be collected at sea during international oceanographic expeditions. During multiple research cruises, including U.S. East Coast and Atlantic basin surveys, the team analyzed thousands of seawater samples with unprecedented spatial resolution. The measurements achieved accuracy and precision comparable to traditional laboratory methods, while increasing sampling density by up to seven times relative to previous efforts. This capability represents a significant advance in ocean carbon observations and enables future expeditions to routinely collect isotope data alongside standard chemical measurements.

Using these new data, the project improved scientific understanding of how anthropogenic CO₂ is taken up and stored in different regions of the Atlantic Ocean. Results showed clear spatial contrasts in CO₂ accumulation linked to ocean circulation and ventilation, helping explain why some regions absorb human-produced carbon more rapidly than others. The project also revealed that data density strongly influences estimates of long-term CO₂ uptake, highlighting the importance of high-resolution observations for detecting decadal changes. These findings strengthen confidence in ocean carbon budgets and provide critical benchmarks for evaluating climate models. Knowledge gained during this funding period will enable the PI’s team and the broader community to further advance understanding of how the ocean takes up and accumulates anthropogenic CO₂ and how carbon isotope measurements can be used to better quantify the underlying processes. 

Beyond advancing fundamental knowledge, the project produced broader impacts across several areas. It trained multiple early-career scientists, including postdoctoral researchers and graduate students, in advanced analytical techniques, fieldwork, and data analysis. These trainees gained hands-on experience during major international expeditions and are well prepared for careers in oceanography, climate science, and environmental research.

At a societal level, the project contributes to improved understanding of how the ocean moderates Earth’s climate conditions by absorbing anthropogenic CO₂. The data and methods developed through this work are directly relevant to assessing future environmental change, evaluating ocean-based carbon dioxide removal strategies, and informing climate mitigation efforts. By improving our ability to measure and verify ocean carbon uptake, this project helps clarify both the capacity and the limits of the ocean in buffering human carbon emissions.

Last Modified: 01/25/2026
Modified by: Wei-Jun Cai