Articles | Volume 22, issue 20
https://doi.org/10.5194/bg-22-5723-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-22-5723-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Impulse response functions as a framework for quantifying ocean-based carbon dioxide removal
Elizabeth Yankovsky
CORRESPONDING AUTHOR
[C]Worthy, LLC, Boulder, CO 80302, USA
Yale University, New Haven, CT 06511, USA
Mengyang Zhou
University of Connecticut, Groton, CT 06340, USA
Michael Tyka
Google Inc., Seattle, WA 98103, USA
Scott Bachman
[C]Worthy, LLC, Boulder, CO 80302, USA
NSF National Center for Atmospheric Research, Boulder, CO 80307, USA
David T. Ho
[C]Worthy, LLC, Boulder, CO 80302, USA
University of Hawai`i at Mānoa, Honolulu, HI 96822, USA
Alicia Karspeck
[C]Worthy, LLC, Boulder, CO 80302, USA
Matthew C. Long
[C]Worthy, LLC, Boulder, CO 80302, USA
NSF National Center for Atmospheric Research, Boulder, CO 80307, USA
Related authors
Michael Dominik Tyka, Mengyang Zhou, Elizabeth Yankovsky, and Dustin Carroll
EGUsphere, https://doi.org/10.5194/egusphere-2025-3713, https://doi.org/10.5194/egusphere-2025-3713, 2025
Short summary
Short summary
Quantification of the kinetics of the induced ocean CO2 uptake following application of marine carbon dioxide removal technologies (mCDR) is crucial for such technologies to gain scientific and social acceptance. Here, we compare two circulation models commonly used for this purpose and find substantial differences in their predictions. We analyze which physical aspects of the models contribute the most to the inter-model discrepancies, and thus require future research.
Yuming Jin, Britton B. Stephens, Matthew C. Long, Naveen Chandra, Frédéric Chevallier, Joram J. D. Hooghiem, Ingrid T. Luijkx, Shamil Maksyutov, Eric J. Morgan, Yosuke Niwa, Prabir K. Patra, Christian Rödenbeck, and Jesse Vance
Geosci. Model Dev., 18, 5937–5969, https://doi.org/10.5194/gmd-18-5937-2025, https://doi.org/10.5194/gmd-18-5937-2025, 2025
Short summary
Short summary
We carry out a comprehensive atmospheric transport model (ATM) intercomparison project. This project aims to evaluate errors in ATMs and three air-sea O2 flux products by comparing model simulations with observations collected from surface stations, ships, and aircraft. We also present a model evaluation framework to independently quantify transport-related and flux-related biases that contribute to model-observation discrepancies in atmospheric tracer distributions.
Michael Dominik Tyka, Mengyang Zhou, Elizabeth Yankovsky, and Dustin Carroll
EGUsphere, https://doi.org/10.5194/egusphere-2025-3713, https://doi.org/10.5194/egusphere-2025-3713, 2025
Short summary
Short summary
Quantification of the kinetics of the induced ocean CO2 uptake following application of marine carbon dioxide removal technologies (mCDR) is crucial for such technologies to gain scientific and social acceptance. Here, we compare two circulation models commonly used for this purpose and find substantial differences in their predictions. We analyze which physical aspects of the models contribute the most to the inter-model discrepancies, and thus require future research.
David T. Ho, Laurent Bopp, Jaime B. Palter, Matthew C. Long, Philip W. Boyd, Griet Neukermans, and Lennart T. Bach
State Planet, 2-oae2023, 12, https://doi.org/10.5194/sp-2-oae2023-12-2023, https://doi.org/10.5194/sp-2-oae2023-12-2023, 2023
Short summary
Short summary
Monitoring, reporting, and verification (MRV) refers to the multistep process to quantify the amount of carbon dioxide removed by a carbon dioxide removal (CDR) activity. Here, we make recommendations for MRV for Ocean Alkalinity Enhancement (OAE) research, arguing that it has an obligation for comprehensiveness, reproducibility, and transparency, as it may become the foundation for assessing large-scale deployment. Both observations and numerical simulations will be needed for MRV.
Ryo Dobashi and David T. Ho
Biogeosciences, 20, 1075–1087, https://doi.org/10.5194/bg-20-1075-2023, https://doi.org/10.5194/bg-20-1075-2023, 2023
Short summary
Short summary
Seagrass meadows are productive ecosystems and bury much carbon. Understanding their role in the global carbon cycle requires knowledge of air–sea CO2 fluxes and hence the knowledge of gas transfer velocity (k). In this study, k was determined from the dual tracer technique in Florida Bay. The observed gas transfer velocity was lower than previous studies in the coastal and open oceans at the same wind speeds, most likely due to wave attenuation by seagrass and limited wind fetch in this area.
Cited articles
Bach, L. T.: The additionality problem of ocean alkalinity enhancement, Biogeosciences, 21, 261–277, https://doi.org/10.5194/bg-21-261-2024, 2024. a, b
Bach, L. T., Gill, S. J., Rickaby, R. E. M., Gore, S., and Renforth, P.: CO2 Removal With Enhanced Weathering and Ocean Alkalinity Enhancement: Potential Risks and Co-benefits for Marine Pelagic Ecosystems, Frontiers in Climate, 1, https://doi.org/10.3389/fclim.2019.00007, 2019. a
Bach, L. T., Ho, D. T., Boyd, P. W., and Tyka, M. D.: Toward a consensus framework to evaluate air–sea CO2 equilibration for marine CO2 removal, Limnology and Oceanography Letters, 8, 685–691, https://doi.org/10.1002/lol2.10330, 2023. a
Berger, M., Kwiatkowski, L., Ho, D. T., and Bopp, L.: Ocean dynamics and biological feedbacks limit the potential of macroalgae carbon dioxide removal, Environmental Research Letters, 18, 024039, https://doi.org/10.1088/1748-9326/acb06e, 2023. a
Berner, R. A., Lasaga, A. C., and Garrels, R. M.: The carbonate-silicate geochemical cycle and its effect on atmospheric carbon dioxide over the past 100 million years, American Journal of Science, 283, 641–683, https://doi.org/10.2475/ajs.283.7.641, 1983. a
Brack, D. and King, R.: Managing Land-based CDR: BECCS, Forests and Carbon Sequestration, Global Policy, 12, 45–56, https://doi.org/10.1111/1758-5899.12827, 2021. a
Computational and Information Systems Lab: HPE SGI ICE XA – Cheyenne, Computational and Information Systems Lab, https://doi.org/10.5065/D6RX99HX, 2025. a
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System Model Version 2 (CESM2), Journal of Advances in Modeling Earth Systems, 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020. a
Doney, S. C., Fabry, V. J., Feely, R. A., and Kleypas, J. A.: Ocean Acidification: The Other CO2 Problem, Annual Review of Marine Science, 1, 169–192, https://doi.org/10.1146/annurev.marine.010908.163834, 2009. a
Ferderer, A., Schulz, K. G., Riebesell, U., Baker, K. G., Chase, Z., and Bach, L. T.: Investigating the effect of silicate- and calcium-based ocean alkalinity enhancement on diatom silicification, Biogeosciences, 21, 2777–2794, https://doi.org/10.5194/bg-21-2777-2024, 2024. a
Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.: Global Carbon Budget 2023, Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, 2023. a
Fuss, S., Canadell, J. G., Peters, G. P., Tavoni, M., Andrew, R. M., Ciais, P., Jackson, R. B., Jones, C. D., Kraxner, F., Nakicenovic, N., Le Quéré, C., Raupach, M. R., Sharifi, A., Smith, P., and Yamagata, Y.: Betting on negative emissions, Nature Climate Change, 4, 850–853, https://doi.org/10.1038/nclimate2392, 2014. a
Gaillardet, J., Dupré, B., Louvat, P., and Allègre, C. J.: Global silicate weathering and CO2 consumption rates deduced from the chemistry of large rivers, Chemical Geology, 159, 3–30, https://doi.org/10.1016/S0009-2541(99)00031-5, 1999. a
Gernon, T. M., Hincks, T. K., Merdith, A. S., Rohling, E. J., Palmer, M. R., Foster, G. L., Bataille, C. P., and Müller, R. D.: Global chemical weathering dominated by continental arcs since the mid-Palaeozoic, Nature Geoscience, 14, 690–696, https://doi.org/10.1038/s41561-021-00806-0, 2021. a
Goldenberg, S. U., Riebesell, U., Brüggemann, D., Börner, G., Sswat, M., Folkvord, A., Couret, M., Spjelkavik, S., Sánchez, N., Jaspers, C., and Moyano, M.: Early life stages of fish under ocean alkalinity enhancement in coastal plankton communities, Biogeosciences, 21, 4521–4532, https://doi.org/10.5194/bg-21-4521-2024, 2024. a
Hassanzadeh, P. and Kuang, Z.: The Linear Response Function of an Idealized Atmosphere. Part I: Construction Using Green’s Functions and Applications, Journal of the Atmospheric Sciences, 73, 3423–3439, https://doi.org/10.1175/JAS-D-15-0338.1, 2016. a
He, J. and Tyka, M. D.: Limits and CO2 equilibration of near-coast alkalinity enhancement, Biogeosciences, 20, 27–43, https://doi.org/10.5194/bg-20-27-2023, 2023. a, b
Ho, D. T., Law, C. S., Smith, M. J., Schlosser, P., Harvey, M., and Hill, P.: Measurements of air-sea gas exchange at high wind speeds in the Southern Ocean: Implications for global parameterizations, Geophysical Research Letters, 33, https://doi.org/10.1029/2006GL026817, 2006. a, b
Ho, D. T., Bopp, L., Palter, J. B., Long, M. C., Boyd, P. W., Neukermans, G., and Bach, L. T.: Monitoring, reporting, and verification for ocean alkalinity enhancement, in: Guide to Best Practices in Ocean Alkalinity Enhancement Research, edited by: Oschlies, A., Stevenson, A., Bach, L. T., Fennel, K., Rickaby, R. E. M., Satterfield, T., Webb, R., and Gattuso, J.-P., Copernicus Publications, State Planet, 2-oae2023, 12, https://doi.org/10.5194/sp-2-oae2023-12-2023, 2023. a, b
Hutchins, D. A., Fu, F.-X., Yang, S.-C., John, S. G., Romaniello, S. J., Andrews, M. G., and Walworth, N. G.: Responses of globally important phytoplankton species to olivine dissolution products and implications for carbon dioxide removal via ocean alkalinity enhancement, Biogeosciences, 20, 4669–4682, https://doi.org/10.5194/bg-20-4669-2023, 2023. a
IPCC: Summary for Policymakers, in: Climate Change 2021: The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 3–32, ISBN 978-1-00-915788-9, https://doi.org/10.1017/9781009157896.001, 2023. a
Jones, D. C., Ito, T., Takano, Y., and Hsu, W.-C.: Spatial and seasonal variability of the air-sea equilibration timescale of carbon dioxide, Global Biogeochemical Cycles, 28, 1163–1178, https://doi.org/10.1002/2014GB004813, 2014. a
Joos, F., Roth, R., Fuglestvedt, J. S., Peters, G. P., Enting, I. G., von Bloh, W., Brovkin, V., Burke, E. J., Eby, M., Edwards, N. R., Friedrich, T., Frölicher, T. L., Halloran, P. R., Holden, P. B., Jones, C., Kleinen, T., Mackenzie, F. T., Matsumoto, K., Meinshausen, M., Plattner, G.-K., Reisinger, A., Segschneider, J., Shaffer, G., Steinacher, M., Strassmann, K., Tanaka, K., Timmermann, A., and Weaver, A. J.: Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis, Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, 2013. a
Keller, D. P., Feng, E. Y., and Oschlies, A.: Potential climate engineering effectiveness and side effects during a high carbon dioxide-emission scenario, Nature Communications, 5, 3304, https://doi.org/10.1038/ncomms4304, 2014. a
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Takahashi, K.: The JRA-55 Reanalysis: General Specifications and Basic Characteristics, Journal of the Meteorological Society of Japan. Ser. II, 93, 5–48, https://doi.org/10.2151/jmsj.2015-001, 2015. a
Kuang, Z.: Linear Response Functions of a Cumulus Ensemble to Temperature and Moisture Perturbations and Implications for the Dynamics of Convectively Coupled Waves, Journal of the Atmospheric Sciences, 67, 941–962, https://doi.org/10.1175/2009JAS3260.1, 2010. a
Lauvset, S. K., Key, R. M., Olsen, A., van Heuven, S., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S., Steinfeldt, R., Jeansson, E., Ishii, M., Perez, F. F., Suzuki, T., and Watelet, S.: A new global interior ocean mapped climatology: the 1° × 1° GLODAP version 2, Earth Syst. Sci. Data, 8, 325–340, https://doi.org/10.5194/essd-8-325-2016, 2016. a, b
Long, M. C., Moore, J. K., Lindsay, K., Levy, M., Doney, S. C., Luo, J. Y., Krumhardt, K. M., Letscher, R. T., Grover, M., and Sylvester, Z. T.: Simulations With the Marine Biogeochemistry Library (MARBL), Journal of Advances in Modeling Earth Systems, 13, e2021MS002647, https://doi.org/10.1029/2021MS002647, 2021. a
Moras, C. A., Bach, L. T., Cyronak, T., Joannes-Boyau, R., and Schulz, K. G.: Ocean alkalinity enhancement – avoiding runaway CaCO3 precipitation during quick and hydrated lime dissolution, Biogeosciences, 19, 3537–3557, https://doi.org/10.5194/bg-19-3537-2022, 2022. a
Nemet, G. F., Callaghan, M. W., Creutzig, F., Fuss, S., Hartmann, J., Hilaire, J., Lamb, W. F., Minx, J. C., Rogers, S., and Smith, P.: Negative emissions – Part 3: Innovation and upscaling, Environmental Research Letters, 13, 063003, https://doi.org/10.1088/1748-9326/aabff4, 2018. a
Olsen, A., Key, R. M., van Heuven, S., Lauvset, S. K., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S., Steinfeldt, R., Jeansson, E., Ishii, M., Pérez, F. F., and Suzuki, T.: The Global Ocean Data Analysis Project version 2 (GLODAPv2) – an internally consistent data product for the world ocean, Earth Syst. Sci. Data, 8, 297–323, https://doi.org/10.5194/essd-8-297-2016, 2016. a, b
Oschlies, A.: Impact of atmospheric and terrestrial CO2 feedbacks on fertilization-induced marine carbon uptake, Biogeosciences, 6, 1603–1613, https://doi.org/10.5194/bg-6-1603-2009, 2009. a
Oschlies, A., Stevenson, A., Bach, L. T., Fennel, K., Rickaby, R. E. M., Satterfield, T., Webb, R., and Gattuso, J.-P. (Eds.): Guide to Best Practices in Ocean Alkalinity Enhancement Research, Copernicus Publications, State Planet, 2-oae2023, https://doi.org/10.5194/sp-2-oae2023, 2023. a
Reinhard, C. T., Planavsky, N. J., and Khan, A.: Aligning incentives for carbon dioxide removal, Environmental Research Letters, 18, 101001, https://doi.org/10.1088/1748-9326/acf591, 2023. a
Renforth, P. and Henderson, G.: Assessing ocean alkalinity for carbon sequestration, Reviews of Geophysics, 55, 636–674, https://doi.org/10.1002/2016RG000533, 2017. a
Rogelj, J., Popp, A., Calvin, K. V., Luderer, G., Emmerling, J., Gernaat, D., Fujimori, S., Strefler, J., Hasegawa, T., Marangoni, G., Krey, V., Kriegler, E., Riahi, K., van Vuuren, D. P., Doelman, J., Drouet, L., Edmonds, J., Fricko, O., Harmsen, M., Havlík, P., Humpenöder, F., Stehfest, E., and Tavoni, M.: Scenarios towards limiting global mean temperature increase below 1.5 °C, Nature Climate Change, 8, 325–332, https://doi.org/10.1038/s41558-018-0091-3, 2018. a
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model, Ocean Modelling, 9, 347–404, https://doi.org/10.1016/j.ocemod.2004.08.002, 2005. a
Shepherd, J. G.: Geoengineering the climate: science, governance and uncertainty, Royal Society, ISBN 978-0-85403-773-5, 2009. a
Suessle, P., Taucher, J., Goldenberg, S. U., Baumann, M., Spilling, K., Noche-Ferreira, A., Vanharanta, M., and Riebesell, U.: Particle fluxes by subtropical pelagic communities under ocean alkalinity enhancement, Biogeosciences, 22, 71–86, https://doi.org/10.5194/bg-22-71-2025, 2025. a
Tyka, M. D.: Efficiency metrics for ocean alkalinity enhancements under responsive and prescribed atmospheric pCO2 conditions, Biogeosciences, 22, 341–353, https://doi.org/10.5194/bg-22-341-2025, 2025. a, b
Walker, J. C. G., Hays, P. B., and Kasting, J. F.: A negative feedback mechanism for the long-term stabilization of Earth's surface temperature, Journal of Geophysical Research: Oceans, 86, 9776–9782, https://doi.org/10.1029/JC086iC10p09776, 1981. a
Wang, H., Pilcher, D. J., Kearney, K. A., Cross, J. N., Shugart, O. M., Eisaman, M. D., and Carter, B. R.: Simulated Impact of Ocean Alkalinity Enhancement on Atmospheric CO2 Removal in the Bering Sea, Earth's Future, 11, e2022EF002816, https://doi.org/10.1029/2022EF002816, 2023. a
Wanninkhof, R.: Relationship between wind speed and gas exchange over the ocean revisited, Limnology and Oceanography: Methods, 12, 351–362, https://doi.org/10.4319/lom.2014.12.351, 2014. a, b
Weiss, R. F.: Carbon dioxide in water and seawater: the solubility of a non-ideal gas, Marine Chemistry, 2, 203–215, https://doi.org/10.1016/0304-4203(74)90015-2, 1974. a
Xin, X., Faucher, G., and Riebesell, U.: Phytoplankton response to increased nickel in the context of ocean alkalinity enhancement, Biogeosciences, 21, 761–772, https://doi.org/10.5194/bg-21-761-2024, 2024. a
Yankovsky, E.: Impulse Response Function Notebooks, Zenodo [code], https://doi.org/10.5281/zenodo.13392377, 2024. a
Yeager, S. G., Rosenbloom, N., Glanville, A. A., Wu, X., Simpson, I., Li, H., Molina, M. J., Krumhardt, K., Mogen, S., Lindsay, K., Lombardozzi, D., Wieder, W., Kim, W. M., Richter, J. H., Long, M., Danabasoglu, G., Bailey, D., Holland, M., Lovenduski, N., Strand, W. G., and King, T.: The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2, Geosci. Model Dev., 15, 6451–6493, https://doi.org/10.5194/gmd-15-6451-2022, 2022. a
Zeebe, R. E. and Wolf-Gladrow, D. A.: CO2 in seawater: Equilibrium, kinetics, isotopes, vol. 65, Elsevier Oceanography Series, Elsevier Science, London, UK, ISBN 978-0444509468, 2001. a
Zhou, M., Tyka, M. D., Ho, D. T., Yankovsky, E., Bachman, S., Nicholas, T., Karspeck, A. R., and Long, M. C.: Mapping the global variation in the efficiency of ocean alkalinity enhancement for carbon dioxide removal, Nature Climate Change, 15, 59–65, https://doi.org/10.1038/s41558-024-02179-9, 2025. a, b, c, d, e, f, g, h
Short summary
Ocean alkalinity enhancement (OAE) is a promising strategy for ocean-based carbon dioxide removal, as it attempts to accelerate a natural process operating on Earth and may have climatically significant scalability. However, our best strategy for assessing OAE effects involves running computationally expensive climate models. We develop a powerful statistical technique that is able to encapsulate the climatic response to OAE interventions, thus simplifying the OAE carbon accounting problem.
Ocean alkalinity enhancement (OAE) is a promising strategy for ocean-based carbon dioxide...
Altmetrics
Final-revised paper
Preprint