EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, ocean acidification, contaminants and litter. The chosen parameters are relevant for the Marine Strategy Framework Directive (MSFD), in particular for descriptors 5, 8, 9 and 10. The datasets contain standardized, harmonized and validated data collections from seafloor litter. Datasets concerning seafloor litter data are loaded in a central database after a semi-automated validation phase. Once loaded, a data assessment is performed in order to check data consistency and potential errors are corrected thanks to a feedback loop with data originators. EMODnet seafloor litter data and database are hosted and maintained by ‘Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, Division of Oceanography (OGS/NODC)’ from Italy. For seafloor litter, the harmonized datasets contain all unrestricted EMODnet Chemistry data on seafloor litter data. Data are formatted following Guidelines and forms for gathering marine litter data, which can be found at: https://dx.doi.org/10.6092/15c0d34c-a01a-4091-91ac-7c4f561ab508 The updated vocabularies of admitted values are available at: https://vocab.seadatanet.org/search https://vocab.ices.dk/ The harmonized datasets can be downloaded as EMODnet Sea-floor litter data format version 1.0, which is a csv file, tab separated values.

EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity, contaminants and marine litter. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data profiles on eutrophication and acidity, and covers: the Artic Ocean, the North East Atlantic, the Greater North Sea and Celtic Seas, the Baltic Sea, the Mediterranean Sea and the Black Sea. ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets . This European dataset is the result of the aggregation of the regional datasets concerning eutrophication and acidity present in EMODnet Chemistry. The regional datasets are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.13120/8xm0-5m67 ). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/. This process were regionally performed by: 'Institute of Marine Research - Norwegian Marine Data Centre (NMD)' (Norway), 'IFREMER / IDM / SISMER - Scientific Information Systems for the SEA' (France), 'Aarhus University, Department of Bioscience, Marine Ecology Roskilde' (Denmark), 'Swedish Meteorological and Hydrological Institute (SMHI)' (Sweden), 'Hellenic Centre for Marine Research, Hellenic National Oceanographic Data Centre (HCMR/HNODC)' (Greece) and 'National Institute for Marine Research and Development 'Grigore Antipa' (Romania). When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.025 kg/L. The aggregated dataset can be downloaded as an ODV collection.

This dataset contains the outputs of nutrients concentrations of a global ocean simulation coupling dynamics and biogeochemistry at ¼° over the year 2019. The simulation has been performed using the coupled circulation/ecosystem model NEMO/PISCES (https://www.nemo-ocean.eu/), which is here enhanced to perform an ensemble simulation with explicit simulation of modeling uncertainties in the physics and in the biogeochemistry. This dataset is one of the 40 members of the ensemble simulation. This study was part of the Horizon Europe project SEAMLESS (https://seamlessproject.org/Home.html), with the general objective of improving the analysis and forecast of ecosystem indicators.   See Popov et al. (https://os.copernicus.org/articles/20/155/2024/) for more details on the study.

This visualization product displays the type of litter in percent per net per year from research and monitoring protocols. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Before 2021, there was no coordinated effort at the regional or European scale for micro-litter. Given this situation, EMODnet Chemistry proposed to adopt the data gathering and data management approach as generally applied for marine data, i.e., populating metadata and data in the CDI Data Discovery and Access service using dedicated SeaDataNet data transport formats. EMODnet Chemistry is currently the official EU collector of micro-litter data from Marine Strategy Framework Directive (MSFD) National Monitoring activities (descriptor 10). A series of specific standard vocabularies or standard terms related to micro-litter have been added to SeaDataNet NVS (NERC Vocabulary Server) Common Vocabularies to describe the micro-litter. European micro-litter data are collected by the National Oceanographic Data Centres (NODCs). Micro-litter map products are generated from NODCs data after a test of the aggregated collection including data and data format checks and data harmonization. A filter is applied to represent only micro-litter sampled according to research and monitoring protocols as MSFD monitoring. To calculate percentages for each type, formula applied is: Type (%) = (∑number of particles of each type)*100 / (∑number of particles of all type) When the number of micro-litters was not filled or was equal zero, it was not possible to calculate the percentage. Standard vocabularies for micro-litter types are taken from Seadatanet's H01 library (https://vocab.seadatanet.org/v_bodc_vocab_v2/search.asp?lib=H01 ). Some morphological types of micro-litters may have been sampled but were not defined by the protocole applied during the survey. They are represented as « undefined micro-litter items ». Warnings: - the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the National Oceanographic Data Centre (NODC) for this area. - since 03/07/2023, the preferred label « Undefined micro-litter items » has been integrated into the H01 library whereas the labels « microplastic items », « non-plastic man-made micro-particles (e.g. glass, metal, tar) » and «non-plastic filaments (natural fibres, rubber) » have been deprecated. When defined, the material or polymer type can be checked directly in the source data.

Sardine physiological measurments from september to november 2020

EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity, and covers the Greater North Sea and Celtic Seas. Data were aggregated and quality controlled by 'Aarhus University, Department of Bioscience, Marine Ecology Roskilde' in Denmark. ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets . Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.13120/8xm0-5m67 ). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/ . When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.025 kg/L. The aggregated dataset can also be downloaded as an ODV collection and spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV ).

This visualization product displays the spatial distribution of fishing related items density per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during bottom trawl surveys. In cases where the wingspread and/or number of items were/was unknown, it was not possible to use the data because these fields are needed to calculate the density. Data collected before 2011 are concerned by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using the following formula: Distance (km) = Haul duration (h) * Ground speed (km/h); - the trawl coordinates if the ground speed and the haul duration were not filled in. The swept area was calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities were calculated on each trawl and year using the following computation: Density of fishing related items (number of items per km²) = ∑Number of fishing related items / Swept area (km²) Then a grid with 30km x 30km cells was used to calculate the weighted mean of densities in each cell from the formula : Weighted mean (number of items per km²) = ∑ (Distance (km) * Density (number of items per km²)) / ∑ Distance (km) Percentiles 50, 75, 95 & 99 were calculated taking into account data for all years. More information on data processing and calculation are detailed in the attached methodology document. Warning: the absence of data on the map does not necessarily mean that they do not exist, but that no information has been entered in the Marine Litter Database for this area. This work is based on the work presented in the following scientific article: O. Gerigny, M. Brun, M.C. Fabri, C. Tomasino, M. Le Moigne, A. Jadaud, F. Galgani, Seafloor litter from the continental shelf and canyons in French Mediterranean Water: Distribution, typologies and trends, Marine Pollution Bulletin, Volume 146, 2019, Pages 653-666, ISSN 0025-326X, https://doi.org/10.1016/j.marpolbul.2019.07.030.

Rapid changes in ocean circulation and climate have been observed in marine-sediment and ice cores over the last glacial period and deglaciation, highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing. To date, these rapid changes in climate and ocean circulation are still not fully explained. One obstacle hindering progress in our understanding of the interactions between past ocean circulation and climate changes is the difficulty of accurately dating marine cores. Here, we present a set of 92 marine sediment cores from the Atlantic Ocean for which we have established age-depth models that are consistent with the Greenland GICC05 ice core chronology, and computed the associated dating uncertainties, using a new deposition modeling technique. This is the first set of consistently dated marine sediment cores enabling paleoclimate scientists to evaluate leads/lags between circulation and climate changes over vast regions of the Atlantic Ocean. Moreover, this data set is of direct use in paleoclimate modeling studies.

Moving 6-year analysis and visualization of Water body phosphate in the North Sea. Four seasons (December-February, March-May, June-August, September-November). Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis) tool, version 2.7.12. results were subjected to the minfield option in DIVAnd to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. The depth dimension allows visualizing the gridded field at various depths.

The BioSWOT-Med campaign (Doglioli et al., 2023) was conducted aboard R/V L’Atalante from April 20 to May 15, 2023 in the Northwestern Mediterranean Sea, in the region of the North Balearic Front (NBF) to study interactions between fine-scale oceanic circulation and biogeochemical processes.  Three water masses were sampled across the NBF, northern ('A'), southern ('B'), and frontal ('F'). Each Lagrangian station consisted of a 24-hour sampling period following the displacement of a water parcel (Doglioli et al., 2024). Vertical profiles down to 500 m were collected every 6 hours at 06:00 ('T1'), 12:00 ('T2'), 18:00 ('T3'), and 00:00 ('T4') UTC, for a total of 28 Lagrangian stations: first between April~24-28 (A1, F1, B1), and again between May~4-7 (B2, F2, A2), with a final station in southern waters (B3) on May~12-13. B2 and B3 stations were located inside an anticyclonic eddy. Hydrological profiles were obtained using a Sea-Bird CTD, with data averaged to a 1~m vertical resolution, they include potential temperature (°C), practical salinity, fluorescence-derived chlorophyll-a (µg/L) and oxygen (µmol/kg).  Samples for nitrate + nitrite and phosphate (µM) were collected from Niskin bottles and analyzed onboard within 2-12~hours using a segmented flow analyzer (AAIII HR Seal Analytical) following (Aminot et al., 2007). Quantification limits (QL) were 0.05 µM for nitrate and 0.02 µM for phosphate. Phosphate concentrations at a nanomolar level analyses were performed in the laboratory using a high-sensitivity method combining a 1 m Liquid Waveguide Capillary Cell (LWCC) and an auto-analyzer (Zhang et al. 2002), achieving a detection limit of 0.002µM.  A BGC-Argo float (WMO: 1902605 - Provor CTS4 SUNA) equipped with a CTD and SUNA nitrate sensor was deployed near station B2 and sampled the anticyclonic eddy. To better resolve the photic and nutricline layers, the standard sampling cycle was modified to a 6-hour frequency, reaching depths of 300-400~m. The BGC-Argo float nitrate dataset spans May~2-16 and includes 55~profiles, with a 0.5 µM limit of quantification. It passed through a nitrate calibration procedure against 8 ship-made  profiles at B2 and B3. Data export in NetCDF format - Dataset at the 7 Lagrangian stations (28 vertical profiles for each variable, 4 at each station):  ‘BioSWOT-Med_LS_Date_Time.nc’ (with day, time, longitude and latitude);  ‘BioSWOT-Med_LS_Nutrients.nc’ (with nitrate, phosphate and phosphate at nanomolar level concentrations and depths);  'BioSWOT-Med_LS_CTD.nc' (with temperature in situ, practical salinity, chlorophyll-a and oxygen concentrations, photosynthetically active radiations and depth). - Dataset of the BGC-Argo float including 55 vertical profiles recorded between May 2 and 16:  'BioSWOT-Med_BGC-Argo' (with day and time, longitude, latitude; nitrate concentrations with associated depth; temperature in situ and practical salinity associated depth; chlorophyll-a concentrations with associated predepthssure; and oxygen concentrations with associated depth). Contact list  Aude Joël (aude.joel@mio.osupytheas.fr), Sandra Nunige (sandra.nunige@mio.osupytheas.fr, for ship-made nutrient dataset), Riccardo Martellucci (rmartellucci@ogs.it, for the BGC-Argo float dataset) and Andrea Doglioli (andrea.doglioli@mio.osupytheas.fr, for the BioSWOT-Med cruise). References Aminot, A., & Kérouel, R. 2007. Dosage automatique des nutriments dans les eaux marines: méthodes en flux continu. Méthodes d’analyse en milieu marin. Ifremer. Doglioli, A.M., & Gregori, G. 2023. BioSWOT-Med cruise, RV L’Atalante. doi:10.17600/18002392. Doglioli, A., Grégori, G., D’Ovidio, F., Bosse, P. E., A., Carlotti, F., Lescot, M.,. . . Waggonet, E. (2024). Bioswot med. biological applicati.ons of the satellite surface water and ocean topography in the mediterranean. ref. rapport de campagne. université aix-marseille. (doi:10.13155/100060) Zhang, J.Z., & Chi, J. 2002. Automated analysis of nanomolar concentrations of phosphate in natural waters with liquid waveguide. Environ Sci Technol., 1;36(5), 1048–53. doi: 10.1021/es011094v.