This vector dataset represents the benthic broad habitat types in Europe Seas potentially affected by the ship wakes. When navigating, the propellers of ships generate a turbulent mixing of the water that can produce sediment re-suspension in soft bottoms of shallow areas. This can increase the turbidity in those areas, affecting the seafloor organisms (especially those that are directly dependent on light, such as aquatic plants). It may also contribute to an increase of the the eutrophication level of the ecosystem (since the turbid waters may become warmer, which may turn into a reduction of dissolved oxygen in water). Finally, turbidity can produce an increase in the inputs of contaminants and microbial pathogens, since those can become attached to the suspended solids. The dataset has been prepared in the context of the development of the first European Maritime Transport Environmental Report (https://www.eea.europa.eu/publications/maritime-transport).

Blue-Cloud 2026 is a collaborative project that leverages Europe's expertise in aquatic environmental observation and data handling. Building on existing infrastructures like Copernicus and EMODnet, Blue-Cloud aims to create a federated ecosystem for FAIR and open data in marine research. Through a web-based platform, it offers simplified access to multidisciplinary datasets, analytical services, and computing facilities. Over 42 months, Blue-Cloud 2026 will expand its core services, integrate more analytical tools, and enhance data discovery and access. With a focus on supporting the EU Blue Economy and environmental agendas, it strives to contribute to the EU Green Deal and UN Sustainable Development Goals. Coordinated by CNR, Trust-IT Services, and MARIS, the project brings together a dedicated team of 40 partners from 13 EU countries.

This metadata corresponds to the EUNIS Coastal habitat types, distribution based on vegetation plot data dataset. Coastal habitats are those above spring high tide limit (or above mean water level in non-tidal waters) occupying coastal features and characterised by their proximity to the sea, including coastal dunes and wooded coastal dunes, beaches and cliffs. Includes free-draining supralittoral habitats adjacent to marine habitats which are normally only very rarely subject to any type of salt water, in as much as they may be inhabited predominantly by terrestrial species, strandlines characterised by terrestrial invertebrates and moist and wet coastal dune slacks and dune-slack pools. Supralittoral sands and wracks may be found also in marine habitats (M). Excludes supralittoral rock pools and habitats, the splash zone immediately above the the mean water line, as well the spray zone and zone subject to sporadic inundation with salt water in as much as it may be inhabited predominantly by marine species, which are included in marine (M). The verified coastal habitat samples used are derived from the Braun-Blanquet database (http://www.sci.muni.cz/botany/vegsci/braun_blanquet.php?lang=en) which is a centralised database of vegetation plots and comprises copies of national and regional databases using a unified taxonomic reference database. The geographic extent of the distribution data are all European countries except Armenia and Azerbaijan. The dataset is provided both in Geodatabase and Geopackage formats.

This dataset presents the resulting assessment grid (based on the EEA reference grid) with the classification of chemical status of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD). This classification has been performed using the CHASE+ tool, with classifications of the matrices ‘water’, ‘sediment’ and ‘biota’ and indicators of ‘biological effects’, as well as an integrated classification of chemical status, combining results of all matrices. The chemical status is evaluated in five classes, where NPAhigh and NPAgood are recognised as ‘non-problem areas’ and PAmoderate, PApoor and PAbad are recognised as ‘problem areas’. This is the assessment made excluding concentrations of mercury (Hg). The overall area of interest used is based on the marine regions and subregions under the Marine Strategy Framework Directive. Additionally, Norwegian (Barent Sea and Norwegian Sea) and Icelandic waters (’Iceland Sea’) have been added (see Surrounding seas of Europe). Note that within the North East Atlantic region only the subregions within EEZ boundaries (~200 nm) have been included. This dataset underpins the findings and cartographic representations published in the report "Contaminants in Europe's Seas" (EEA, 2019).

'''This product has been archived'''                For operationnal and online products, please visit https://marine.copernicus.eu '''DEFINITION''' The ibi_omi_tempsal_sst_area_averaged_anomalies product for 2021 includes Sea Surface Temperature (SST) anomalies, given as monthly mean time series starting on 1993 and averaged over the Iberia-Biscay-Irish Seas. The IBI SST OMI is built from the CMEMS Reprocessed European North West Shelf Iberai-Biscay-Irish Seas (SST_MED_SST_L4_REP_OBSERVATIONS_010_026, see e.g. the OMI QUID, http://marine.copernicus.eu/documents/QUID/CMEMS-OMI-QUID-ATL-SST.pdf), which provided the SSTs used to compute the evolution of SST anomalies over the European North West Shelf Seas. This reprocessed product consists of daily (nighttime) interpolated 0.05° grid resolution SST maps over the European North West Shelf Iberai-Biscay-Irish Seas built from the ESA Climate Change Initiative (CCI) (Merchant et al., 2019) and Copernicus Climate Change Service (C3S) initiatives. Anomalies are computed against the 1993-2014 reference period. '''CONTEXT''' Sea surface temperature (SST) is a key climate variable since it deeply contributes in regulating climate and its variability (Deser et al., 2010). SST is then essential to monitor and characterise the state of the global climate system (GCOS 2010). Long-term SST variability, from interannual to (multi-)decadal timescales, provides insight into the slow variations/changes in SST, i.e. the temperature trend (e.g., Pezzulli et al., 2005). In addition, on shorter timescales, SST anomalies become an essential indicator for extreme events, as e.g. marine heatwaves (Hobday et al., 2018). '''CMEMS KEY FINDINGS''' The overall trend in the SST anomalies in this region is 0.011 ±0.001 °C/year over the period 1993-2021. '''DOI (product):''' https://doi.org/10.48670/moi-00256

Output of the 2019 EUSeaMap broad-scale predictive model, produced by EMODnet Seabed Habitats. The extent of the mapped area includes the Mediterranean Sea, Black Sea, Baltic Sea, and areas of the North Eastern Atlantic extending from the Canary Islands in the south to the Barents Sea in the north. The map was produced using a "top-down" modelling approach using classified habitat descriptors to determine a final output habitat. Habitat descriptors differ per region but include: Biological zone Energy class Oxygen regime Salinity regime Seabed substrate Riverine input Habitat descriptors (excepting Substrate) are calculated using underlying physical data and thresholds derived from statistical analyses or expert judgement on known conditions. The model is produced using R and Arc Model Builder (10.1). The model was created using raster input layers with a cell size of 0.00104dd (roughly 100 metres). The model includes the sublittoral zone only; due to the high variability of the littoral zone, a lack of detailed substrate data and the resolution of the model, it is difficult to predict littoral habitats at this scale. This map follows the EUNIS 2007-11 classification system where it is appropriate. It has also been classified according to MSFD Benthic Broad Habitat types. This report details the methods used in the previous version (v2016) - a new report is in progress: Populus J. And Vasquez M. (Eds), 2017. EUSeaMap, a European broad-scale seabed habitat map. Ifremer Available from: http://archimer.ifremer.fr/doc/00388/49975/

This data set presents the resulting assessment grid (based on the EEA reference grid) with the classification of chemical status of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD), providing a mapping of contamination 'problem areas' and ‘non-problem areas’ based on measurements in the matrix "sediments". This classification has been performed using the CHASE+ tool, with classifications of the sediments matrix. The chemical status is evaluated in five classes, where NPAhigh and NPAgood are recognised as ‘non-problem areas’ and PAmoderate, PApoor and PAbad are recognised as ‘problem areas’. Most countries in Europe include marine sediments in long-term monitoring activities. Consequently, the data coverage is good, especially in southern parts of the Baltic Sea, the North Sea, the Celtic Sea, the Bay of Biscay, western parts of the Black Sea and the coastal waters of France, Italy and Portugal.The number of assessment units monitored and classified in the North-East Atlantic Ocean is 511. In the Mediterranean Sea, the number of assessment units is 153. Baltic Sea sediments are monitored on 97 assessment units while only 19 areas are assessed in the Black Sea. This data set underpins the findings and cartographic representations published in the EEA report “Contaminants in Europe’s seas” (No 25/2018). See the mentioned report for further information as well as examples of classification excluding specific groups of substances(e.g. metals, PBDEs).

Prises IPE présentes sur les territoires gérés par la SPL NATHD

The dataset presents the potential combined effects of land-based pressures on marine species and habitats estimated using the method for assessment of cumulative effects, for the entire suite of pressures and a selected set of marine species groups and habitats by an index (Halpern et al. 2008). The spatial assessment of combined effects of multiple pressures informs of the risks of human activities on the marine ecosystem health. The methodology builds on the spatial layers of pressures and ecosystem components and on an estimate of ecosystem sensitivity through an expert questionnaire. The raster dataset consists of a division of the Europe's seas in 10km and 100 km grid cells, which values represents the combined effects index values for pressures caused by land-based human activities. The relative values indicate areas where the pressures potentially affect the marine ecosystem. This dataset underpins the findings and cartographic representations published in the report "Marine Messages" (EEA, 2020).

This product displays the stations where naphthalene has been measured and the values present in EMODnet Chemistry infrastructure are always above the limit of detection or quantification (LOD/LOQ), i.e quality value equal to 1. It is necessary to take into account that LOD/LOQ can change with time. These products aggregate data by station, producing only one final value for each station (above, below or above/below). EMODnet Chemistry has included the gathering of contaminants data since the beginning of the project in 2009. For the maps for EMODnet Chemistry Phase III, it was requested to plot data per matrix (water,sediment, biota), per biological entity and per chemical substance. The series of relevant map products have been developed according to the criteria D8C1 of the MSFD Directive, specifically focusing on the requirements under the new Commission Decision 2017/848 (17th May 2017). The Commission Decision points to relevant threshold values that are specified in the WFD, as well as relating how these contaminants should be expressed (units and matrix etc.) through the related Directives i.e. Priority substances for Water. EU EQS Directive does not fix any threshold values in sediments. On the contrary Regional Sea Conventions provide some of them, and these values have been taken into account for the development of the visualization products. To produce the maps the following process has been followed: 1. Data collection through SeaDataNet standards (CDI+ODV) 2. Harvesting, harmonization, validation and P01 code decomposition of data 3. SQL query on data sets from point 2 4. Production of map with each point representing at least one record that match the criteria The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols. Preliminary processing were necessary to harmonize all the data : • For water: contaminants in the dissolved phase; • For sediment: data on total sediment (regardless of size class) or size class < 2000 μm • For biota: contaminant data will focus on molluscs, on fish (only in the muscle), and on crustaceans • Exclusion of data values equal to 0