Abstract
Chemical pollution has profound impacts on marine ecosystem health and services. Most investigations of the distributions of anthropogenic organic chemicals (xenobiotics) have been regionally focused, which limits our understanding of the extent of chemical pollution in the world’s largest biome. To address this gap, we mapped the presence of xenobiotics across marine ecosystems. Here we present a meta-analysis of 21 public non-targeted tandem mass spectrometry datasets, which are not restricted to a predefined set of compounds but rather capture thousands of chemicals. These datasets comprise 2,315 seawater samples, spanning coastal to open ocean environments across three ocean basins. Our analysis revealed that common pollutants such as pesticides and pharmaceuticals were predominantly detected in estuaries and coastal areas but declined with distance from shore, whereas industrial chemicals and additives, including polyalkylene glycols, phthalates and organophosphates, were widely distributed across marine ecosystems. A total of 248 annotated xenobiotic features contributed a median of 2% to the total detected peak area per sample. We observed highest median levels of xenobiotic contribution in coastal datasets (up to 20%) and lowest levels (0.5%) in open ocean datasets, which indicates that anthropogenic organic substances contribute substantially to the dissolved organic matter pool in the surface ocean.
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Data availability
All datasets are publicly available through the MassIVE repository (massive.ucsd.edu) under the following identifiers: Aruba 2019 (UCSD, Q Exactive): MSV000085891; Baltic Sea 2021 (Tuebingen, Q Exactive HF): MSV000089481; California Current 2017 (UCSD, Q Exactive): MSV000082082; California Current 2019 (UCSD, Q Exactive): MSV000085852; California Current 2020 (UCSD, Q Exactive): MSV000086236; California Current 2021 (UCSD, Q Exactive): MSV000090123; Caribbean Netherlands 2022 (NIOZ, Q Exactive): MSV000094015; Curaçao 2018 (UCSD, Q Exactive): MSV000083522; Curaçao 2021/22 (NIOZ, Q Exactive): MSV000094018; Gulf of Maine 2022 (Tuebingen, Q Exactive HF): MSV000090696; Hawaii 2019 (UCSD, Q Exactive): MSV000082085; Moorea 2017 (UCSD, Q Exactive): MSV000082083; Moorea 2022 (UCSD, Q Exactive): MSV000090798; Northern Pacific 2018 (UCSD, Q Exactive): MSV000083365; Northern San Diego Coast 2017/18 (UCSD, Q Exactive): MSV000082312; Northern San Diego Coast 2020 (UCSD, Q Exactive): MSV000085555 and MSV000085779; Pacific OMZ 2018 (UCSD, Q Exactive): MSV000085480; Puerto Rico 2022 (Tuebingen, Q Exactive HF): MSV000092677; South Africa 2018/19 (UCSD, Q Exactive): MSV000085843; Southern San Diego Coast 2019 (UCSD, Q Exactive): MSV000083889; Patagonia 2018 (UCSD, Q Exactive): MSV000083521. All processed data and mzmine batch files used in this study are available via Zenodo at https://doi.org/10.5281/zenodo.16687158 (ref. 51). Source data are provided with this paper.
Code availability
All code, including python scripts, is available via Github at https://github.com/Functional-Metabolomics-Lab/Marine-Xenobiotics and via Zenodo at https://doi.org/10.5281/zenodo.16687158 (ref. 51).
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Acknowledgements
We thank D. Rasher and D. Yiu for facilitating sample collection in the Gulf of Maine. D.P. was supported by the Simons Foundation International through a Simons Early Career Investigator in Aquatic Microbial Ecology and Evolution Award (SFI-LS-ECIAMEE-00013858) and the German Research Foundation through the Cluster of Excellence Controlling Microbes to Fight Infection (EXC 2124). S.P.-G. and C.C.-I. were supported by the Center for Oceanographic Research (COPAS) Coastal ANID FB210021 (Chile). R.R.T. and Z.A.Q. were supported by the National Science Foundation (NSF) through Graduate Research Fellowship and a Postdoctoral Fellowship (DGE-2038238, OCE-2308400 and award #2019252845). J.M.B. was supported through an NSF CAREER grant (OCE-1555375). We would like to thank the California Current Ecosystem Long Term Ecological Research (CCE-LTER) Program and the Captains and Crew of the RV Atlantis, RV Oceanus, RV Revelle and RV Sally Ride. We would also like to thank the team at University of California Gump Marine Station on Moorea for logistical support. Datasets presented here were supported in part by CCE-LTER funding (NSF OCE-1637632) and Moorea funding (OCE-2023509 to L.I.A. and P.C.D., OCE-2118618 to L.W.K., OCE-2023298 to C.E.N.), and NASA award 80NSSC18K0437 to C.A.C. A.H. was supported by the United States Department of Defense Environmental Security Technology Certification Program (no. CR20-5175). B.R.B.d.C. was supported by São Paulo Research Foundation (FAPESP, grant no. 2023/15215-4) through a Research Internship Abroad Fellowship. J.-C.J.K. was supported by a Rhodes University postdoctoral fellowship and by the South African Medical Research Council as well as the UK Medical Research Council, through the UK Government's Newton Fund (grant no. 96185). We thank the Shallow Marine and Coastal Research Infrastructure platform for research infrastructure support as well as the crew of the RV Ukwabelana and Koos Smith of the African Coelacanth Ecosystem Programme.
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J.-C.J.K., A.K.P.M.S. and D.P. conceptualized the study. L.W.K., C.E.N., C.A.C., J.M.B., R.A.D., D.T., P.C.D., L.I.A. and D.P. supervised the study. S.P.F., R.R.T., L.C., B.M.S., C.U.-T., I.K., Z.A.Q., L.W.K., C.E.N., C.A.C., C.C.-I., S.P.-G., J.M.B., A.A., A.H., X.S.N., R.A.D., D.T., A.F.H., P.C.D., L.I.A. and D.P. performed sampling. S.P.F., P.S., R.R.T., L.C., B.M.S., C.U.-T., I.K., Z.A.Q., L.W.K., C.E.N., S.P.-G., J.M.B., A.H., X.S.N., D.T., A.F.H. and D.P. acquired LC-MS/MS data. J.-C.J.K., B.R.B.d.C., L.G.G., C.E.N., M.W. and D.P. analysed the data. J.-C.J.K., A.K.P.M.S., B.R.B.d.C., S.P.F., L.G.G., T.S., Z.A.Q., C.E.N., M.W. and D.P. wrote the manuscript. All authors edited and approved the final manuscript.
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P.C.D. is an advisor and holds equity in Cybele, BileOmix and Sirenas and is a scientific co-founder, advisor, holds equity in and/or received income from Ometa, Enveda and Arome with prior approval by UC-San Diego. P.C.D. also consulted for DSM animal health in 2023. M.W. is a co-founder of Ometa Labs LLC. The remaining authors declare no competing interests.
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Supplementary information
Supplementary Information (download PDF )
Supplementary Figs. 1–13, Tables 1–3 and description of mass spectrometry datasets and metadata.
Supplementary Table 1 (download CSV )
Metadata of LC-MS/MS datasets.
Supplementary Table 2 (download CSV )
List of detected xenobiotics.
Source data
Source Data Fig. 2 (download XLSX )
PCoA with Bray–Curtis distance, labelled by ecosystem. Xenobiotics grouped.
Source Data Fig. 3 (download XLSX )
Top xenobiotic frequency percentages. Industrial pollutants scaled violin plot. Pesticides scaled violin plots. Xenobiotics scaled violin plots. Drugs scaled violin plots.
Source Data Fig. 4 (download XLSX )
Poly-glycols first neighbours scaled violin plot. Organophosphates first neighbours scaled violin plot. Phthalates first neighbours scaled violin plot.
Source Data Fig. 5 (download XLSX )
Results xenobiotics percentage. Results xenobiotics first neighbours percentage. Distance to coast xenobiotics percentage. Depth bucket xenobiotics percentage.
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Kalinski, JC.J., Pakkir Mohamed Shah, A.K., Ruiz Brandão da Costa, B. et al. Widespread presence of anthropogenic compounds in marine dissolved organic matter. Nat. Geosci. (2026). https://doi.org/10.1038/s41561-026-01928-z
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DOI: https://doi.org/10.1038/s41561-026-01928-z


