Babakhani, P., Dale, A.W., Woulds, C. et al. (9 more authors) (2026) Global cycling of dissolved organic carbon between seawater and sediments quantified using physics-based artificial intelligence. The Innovation, 7 (9). 101354. ISSN: 2666-6758
Abstract
The origin of dissolved organic carbon (DOC) in the ocean, which represents the largest active reservoir of exchangeable carbon on Earth, remains unknown due to the complexity of determining DOC exchange between marine sediments and seawater. Here, we emulate underlying processes of DOC dynamics using physics-based artificial intelligence (AI) to quantify DOC cycling and preservation in sediments at the global scale. We conclude that up to 11% of all particulate organic carbon deposited on the global seafloor returns to seawater as DOC following hydrolysis within the sediment, which is around half of the riverine DOC flux to the ocean. Around 50% of total solid-phase organic carbon in the upper metre of sediments is formed through sorption of DOC to minerals. Further, we show that the contribution of the abyssal plain to global DOC efflux and preservation, which is typically entirely overlooked in carbon cycle studies, is equivalent to half the contribution of the continental margins. This study also highlights the power of simpler AI algorithms compared to more complex models, and extends the Principle of Parsimony in mathematical modelling to the context of physics-based AI.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | dissolved organic carbon; global carbon cycle; physics-based artificial intelligence; reactive transport model; RTM; marine sediments |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Earth Surface Science Institute (ESSI) (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) |
| Date Deposited: | 30 Jul 2026 11:11 |
| Last Modified: | 30 Jul 2026 11:11 |
| Status: | Published |
| Publisher: | Elsevier |
| Identification Number: | 10.1016/j.xinn.2026.101354 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:242736 |

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