This visualization product displays the spatial distribution of seafloor litter 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 fishing bottom trawl surveys. In cases where the wingspread and/or number of items were unknown, data could not be used because these fields are needed to calculate the density. Data collected before 2011 are affected by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using this 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 is calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities have been calculated on each trawl and year using the following computation: Density (number of items per km²) = ∑Number of items / Swept area (km²) Then a grid with 30km x 30km cells is 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 have been calculated taking into account data for all years. More information on data processing and calculation are detailed in the document attached. Warning: the absence of data on the map doesn't necessarily mean that they don't 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.

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). ITS-90 water temperature and Water body salinity variables have been also included (as-is) to complete the Eutrophication and Acidity data. If you use these variables for calculations, please refer to SeaDataNet for having the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets . This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (14 parameters with quality flag indicators), and covers the North Sea with 587584 CDI records. Data were aggregated and quality controlled by 'Aarhus University, Department of Bioscience, Marine Ecology Roskilde' from Denmark. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Quality flags for Water body dissolved inorganic nitrogen (DIN) should be disregarded since that currently they are not based on the original quality flags of nitrite, nitrate and ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/. Detailed documentation is available at: https://dx.doi.org/10.6092/4e85717a-a2c9-454d-ba0d-30b89f742713 Explore and extract data at: https://emodnet-chemistry.webodv.awi.de/eutrophication>NorthSea The aggregated dataset can be downloaded as ODV collection and spreadsheet, which is composed of metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (More information can be found at: http://www.seadatanet.org/Standards-Software/Software/ODV). The original datasets can be searched and downloaded from EMODnet Chemistry Chemistry CDI Data and Discovery Access Service: https://emodnet-chemistry.maris.nl/search

EMODnet Chemistry aims to provide access to marine chemistry data sets and derived data products concerning eutrophication, acidity and contaminants. The chemicals chosen reflect importance to the Marine Strategy Framework Directive (MSFD). ITS-90 water temperature and Water body salinity variables have been also included (as-is) to complete the Eutrophication and Acidity data. This aggregated dataset contains all unrestricted EMODnet Chemistry data on Eutrophication and Acidity (12 parameters with quality flag indicators), and covers the Baltic Sea with 187597 CDI stations. Data were aggregated and quality controlled by "Swedish Meteorological and Hydrological Institute (SMHI)" from Sweden. Regional datasets concerning eutrophication and acidity are automatically harvested and resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all Sea Regions ( https://doi.org/10.6092/9f75ad8a-ca32-4a72-bf69-167119b2cc12). When not present in original data, Water body nitrate plus nitrite was calculated by summing up the Nitrates and Nitrites. Same procedure was applied for Water body dissolved inorganic nitrogen (DIN) which was calculated by summing up the Nitrates, Nitrites and Ammonium. Parameter names are based on P35, EMODnet Chemistry aggregated parameter names vocabulary, which is available at: https://www.bodc.ac.uk/resources/vocabularies/vocabulary_search/P35/ Detailed documentation is available at: https://doi.org/10.6092/ec8207ef-ed81-4ee5-bf48-e26ff16bf02e The aggregated dataset can be downloaded as ODV worksheet, which is composed of metadata header followed by tab separated values. This worksheet can be imported to ODV Software for visualisation (More information can be found at: https://www.seadatanet.org/Software/ODV ) The original datasets can be searched and downloaded from EMODnet Chemistry Download Service: https://emodnet-chemistry.maris.nl/search

Running 6-year analysis of Water body phosphate in the Baltic Sea. Four seasons (March-May, June-August, September-November, December-February). Every year of the time dimension corresponds to a 6-year centred average. Periods span between 1955-2023. Analyses for depths (m) (HELCOM standard depths): 0, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 225, 250, 275, 300. Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis in n dimensions) tool. GEBCO_08 Grid (30 arc-seconds) topography is used for the contouring preparation. Files contain analysed fields, error fields and combined field with the deepest value for each grid point selected. Also pre-masked fields using relative error threshold 0.3 and 0.5 are included. In the analyses the horizontal correlation length is fixed to 80 km and decreasing towards the coastline, the vertical correlation length is varying with depth. Signal to noise ratio is fixed to 1.0. Background fields were created using data for the given time period and season. Log transformation was used in the analyses. No detrending, advection constraints or weighting are applied. Unit is umol/l.

Moving 6-year analysis of silicate in the Arctic Ocean, for each season in the period 1970-2024. Every year of the time dimension corresponds to the 6-year centered average for each season. Winter: December-February, Spring: March-May, Summer: June-August, Autumn: September-November. Depth range (IODE standard depths): 0, 5, 10, 20, 30, 40, 50, 75, 100, 125, 150, 200, 250, 300, 400, ..., 1500, 1750, 2000, 2500m. Units: umol/l. Description of DIVA analysis: The computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.13, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is 0.125 degrees. Signal-to-noise ratio was fixed to 3.0, horizontal correlation length varying from 45 km near the coast to 150 km, and vertical correlation length varying between 25 and 1000 m. Logarithmic transformation is applied to the data prior to the analysis. Background field: analysis with signal-to-noise ratio = 20, horizontal correlation length 50-200 km, and vertical correlation length 25-1000 m.

Running 6-year analysis of Water body silicate in the Baltic Sea. Four seasons (March-May, June-August, September-November, December-February). Every year of the time dimension corresponds to a 6-year centred average. Periods span between 1965-2021. Analyses for depths (m) (HELCOM standard depths): 0, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 225, 250, 275, 300. Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis in n dimensions) tool. GEBCO_08 Grid (30 arc-seconds) topography is used for the contouring preparation. Files contain analysed fields, error fields and combined field with the deepest value for each grid point selected. Also pre-masked fields using relative error threshold 0.3 and 0.5 are included. In the analyses the horizontal correlation length is fixed to 80 km and decreasing towards the coastline, the vertical correlation length is varying with depth. Signal to noise ratio is fixed to 1.0. Background fields were created using data for the given time period and season. Log transformation was used in the analyses. No detrending, advection constraints or weighting are applied. Unit is umol/l.

Moving 6-year analysis of dissolved oxygen concentration in the Arctic Ocean, for each season in the period 1965-2022. Every year of the time dimension corresponds to the 6-year centered average for each season. Winter: December-February, Spring: March-May, Summer: June-August, Autumn: September-November. Depth range (IODE standard depths): 0, 5, 10, 20, 30, 40, 50, 75, 100, 125, 150, 200, 250, 300, 400, ..., 1500, 1750, 2000, 2500m. Units: umol/l. Description of DIVA analysis: The computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.9, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is 0.1 degrees. Signal-to-noise ratio was fixed to 3.0, horizontal correlation length varying from 45 km near the coast to 150 km, and vertical correlation length varying between 25 and 1000 m. Logarithmic transformation is applied to the data prior to the analysis. Background field: analysis with signal-to-noise ratio = 10, horizontal correlation length 60-200 km, and vertical correlation length 25-1000 m.

Moving 6-year analysis of phosphate in the Arctic Ocean, for each season in the period 1965-2024. Every year of the time dimension corresponds to the 6-year centered average for each season. Winter: December-February, Spring: March-May, Summer: June-August, Autumn: September-November. Depth range (IODE standard depths): 0, 5, 10, 20, 30, 40, 50, 75, 100, 125, 150, 200, 250, 300, 400, ..., 1500, 1750, 2000, 2500m. Units: umol/l. Description of DIVA analysis: The computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.13, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is 0.125 degrees. Signal-to-noise ratio was fixed to 3.0, horizontal correlation length varying from 45 km near the coast to 150 km, and vertical correlation length varying between 25 and 1000 m. Logarithmic transformation is applied to the data prior to the analysis. Background field: analysis with signal-to-noise ratio = 20, horizontal correlation length 50-200 km, and vertical correlation length 25-1000 m.

Units: umol/l. Method: spatial interpolation produced with DIVA (Data-Interpolating Variational Analysis). URL: http://modb.oce.ulg.ac.be/DIVA. Comment: Every year of the time dimension corresponds to a 10-year centred average for each season : - winter season (December-February), - spring (March-May), - summer (June-August), - autumn (September-November). Diva settings: Snr=1.0, CL=0.7

This visualization product displays the single use plastics (SUP) related items abundance of marine macro-litter (> 2.5cm) per beach per year from Marine Strategy Framework Directive (MSFD) monitoring surveys. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter 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 and reference lists used on a European scale. Preliminary processing were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of MSFD surveys only (exclusion of other monitoring, cleaning and research operations); - Exclusion of beaches without coordinates; - Selection of SUP related items only. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines for Macro Litter on Coastlines from JRC (this document is attached to this metadata); - Normalization of survey lengths to 100m & 1 survey / year: in some case, the survey length was not exactly 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of SUP items of the survey (normalized by 100 m) = Number of SUP related items of the survey x (100 / survey length) Then, this normalized number of¨SUP related items is summed to obtain the total normalized number of SUP related items for each survey. Finally, the median abundance of SUP related items for each beach and year is calculated from these normalized abundances of SUP related items per survey. Sometimes the survey length was null or equal to 0. Assuming that the MSFD protocol has been applied, the length has been set at 100m in these cases. Percentiles 50, 75, 95 & 99 have been calculated taking into account SUP related items from MSFD data for all years. More information is available in the attached documents. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area.