Articles | Volume 15, issue 9
https://doi.org/10.5194/essd-15-4023-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-4023-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Barium in seawater: dissolved distribution, relationship to silicon, and barite saturation state determined using machine learning
NIRVANA Laboratories, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
Department of Marine Chemistry and
Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
Department of Earth Sciences, Dartmouth College, Hanover, NH
03755, USA
now at: Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA 02138, USA
Adam V. Subhas
Department of Marine Chemistry and
Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
Heather H. Kim
Department of Marine Chemistry and
Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
Ann G. Dunlea
Department of Marine Chemistry and
Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
Laura M. Whitmore
International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
Alan M. Shiller
School of Ocean Science and Engineering, University of Southern
Mississippi, Stennis Space Center, MS 39529, USA
Melissa Gilbert
School of Ocean Science and Engineering, University of Southern
Mississippi, Stennis Space Center, MS 39529, USA
William D. Leavitt
Department of Earth Sciences, Dartmouth College, Hanover, NH
03755, USA
Department of Chemistry, Dartmouth College, Hanover, NH 03755, USA
Tristan J. Horner
CORRESPONDING AUTHOR
NIRVANA Laboratories, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
Department of Marine Chemistry and
Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
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- Barium cycling in the Gulf of Aqaba K. Mayfield et al. 10.3389/feart.2024.1178487
- The roles of celestine and barite in modulating strontium and barium water column concentrations in the northeast Pacific Ocean Z. Steiner et al. 10.1016/j.gca.2024.10.003
- Multiple Ba Phases in Marine Sediments elucidate environmental processes and conditions for the Holocene Mediterranean A. Filippidi & G. De Lange 10.1016/j.quascirev.2024.108753
- Spatiotemporal changes in riverine input into the Eocene North Sea revealed by strontium isotope and barium analysis of bivalve shells J. Kniest et al. 10.1038/s41598-024-79779-0
- Controls on Dissolved Barium and Radium‐226 Distributions in the Pacific Ocean Along GEOTRACES GP15 E. Le Roy et al. 10.1029/2023GB008005
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8 citations as recorded by crossref.
- Modeling the global ocean distribution of dissolved cadmium based on machine learning—SHAP algorithm Z. Jiang et al. 10.1016/j.scitotenv.2024.177951
- Tracking organic matrix in the seashell by elemental mapping under laser-induced breakdown spectroscopy L. Ren et al. 10.1016/j.talanta.2024.125658
- Barium cycling in the Gulf of Aqaba K. Mayfield et al. 10.3389/feart.2024.1178487
- The roles of celestine and barite in modulating strontium and barium water column concentrations in the northeast Pacific Ocean Z. Steiner et al. 10.1016/j.gca.2024.10.003
- Multiple Ba Phases in Marine Sediments elucidate environmental processes and conditions for the Holocene Mediterranean A. Filippidi & G. De Lange 10.1016/j.quascirev.2024.108753
- Spatiotemporal changes in riverine input into the Eocene North Sea revealed by strontium isotope and barium analysis of bivalve shells J. Kniest et al. 10.1038/s41598-024-79779-0
- Controls on Dissolved Barium and Radium‐226 Distributions in the Pacific Ocean Along GEOTRACES GP15 E. Le Roy et al. 10.1029/2023GB008005
- Reactive carbon capture using saline water: evaluation of prospective sources, processes, and products A. Dickinson-Cove et al. 10.1039/D4CS00701H
Latest update: 20 Jan 2025
Short summary
We present results from a machine learning model that accurately predicts dissolved barium concentrations for the global ocean. Our results reveal that the whole-ocean barium inventory is significantly lower than previously thought and that the deep ocean below 1000 m is at equilibrium with respect to barite. The model output can be used for a number of applications, including intercomparison, interpolation, and identification of regions warranting additional investigation.
We present results from a machine learning model that accurately predicts dissolved barium...
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