This data set on deposition sites of dredged material (areas) reported by HELCOM Contracting parties according to http://www.helcom.fi/Recommendations/Rec%2036-2.pdf for the reporting period 2011-2016. The dataset contains data reported by nationally by nominated experts by HELCOM PRESSURE group for Denmark, Germany, Estonia, Finland, Latvia, Lithuania, Poland, Russia and Sweden.

The pressure oil slicks and spills is combination of following datasets: • Illegal oil discharges • Polluting ship accidents Illegal oil discharge data is based on airborne surveillance with remote sensing equipment in the Baltic Sea Area. The area of the detected spills in 2011–2016 was used to represent the pressure. The value of spills under 1km2 were directly given to grid cell, spills over 1km2 were buffered based on estimate spill area. For polluting ship accidents the reported oil spill volumes (m3) in years 2011-2015 were used for the pressure. Some polluting ship accidents spills were missing spilled oil volume, thus a mean of reported volumes was given to accidents with missing oil volume. Datasets were handled separately. Both layers were normalized, summed and normalized again to produce the “oil slicks and spills” pressure layer. Please see below for further details.

This data set on deposition sites of dredged material (points) reported by HELCOM Contracting parties according to http://www.helcom.fi/Recommendations/Rec%2036-2.pdf for the reporting period 2011-2016. The dataset contains data reported by nationally by nominated experts by HELCOM PRESSURE group for Denmark, Germany, Estonia, Finland, Latvia, Lithuania, Poland, Russia and Sweden.

Amount of hunted birds (number of birds/area) per year per area (county) is given separately for each target species: common scooter (Melanitta nigra), velvet scoter (Melanitta fusca), eider (Somateri molissima) and long tailed duck (Clangula hymalis). The data was made available by HELCOM Contracting Parties in response to data request. The data was received from Denmark, Estonia, Finland and Sweden. The activity was declared as not relevant in Germany, Latvia, Lithuania and Poland. For each species, a total number of hunted birds during the time period and a calculated average (hunted birds/year), is given. Data includes a total number (sum) of all hunted birds during the time period per county (total number of hunted birds/ county) and an average for hunted birds annually (hunted individuals/year). Velvet scoter is protected species in Sweden and Finland, and not listed as a game in Estonia. Common scoter is also protected species in Finland, thus hunting data is not available. Attribute specification and units: Country: Country AreaCode: County’s national code Area: County, unit area TOTAL: Total number of hunted birds in 2011-2015 Average: An average of hunted birds in a year (hunted birds/year) 2011_Sco – 2015_Sco: Number of hunted common scoters in 2011-2015 SUM_Sco: Total number of hunted common scoters in 2011-2015 Mean_Sco: An average number of hunted common scoters in a year (hunted individuals/year) 2011_VSco – 2015_VSco: Number of hunted velvet scoters in 2011 - 2015 SUM_Vsco: Total number of hunted velvet scoters in 2011-2015 Mean_Vsco: An average number of hunted velvet scoters in a year (hunted individuals/year) 2011_Eider – 2015_Eider: Number of hunted eiders in 2011 - 2015 SUM_Eider: Total number of hunted eiders in 2011-2015 Mean_Eider: An average number of hunted eiders in a year (hunted individuals/year) 2011_LTDuc – 2015_LTDuc: Number of hunted long tailed ducks in 2011 – 2015 SUM_LTDuck: Total number of hunted long tailed ducks in 2011-2015 Mean_LTDuc: An average number of hunted long tailed ducks in a year (hunted individuals/year) Notes: Notes regarding the data

This dataset is built from following Human activities datasets: • http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/81c917ea-492d-48e2-9f00-e1bb7fe3e4fc • http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/4fcd51dd-b8be-4e83-8cad-37c566782e8f The game hunting of seabirds data (see separate metadata): The total number of hunted seabirds were averaged over 2011-2015 (number of hunted seabirds / year). The area of the reporting unit was used to calculate the number of hunted seabirds / km2 and the data was converted to 1km x 1km grid. The predator control of seabirds data (see separate metadata): The total number of hunted cormorants were averaged over 2011-2015 (number of hunted cormorants / year). The area of the reporting unit was used to calculate the number of hunted cormorants / km2 and the data was converted to 1km x 1km grid. The two datasets were first separately log transformed and then summed, to get the total value for each grid cell. Zero values were given to all grid cells with no reported seabird hunting activity. The layer was normalized.

Data shows the extent of land claim (permanent or temporary establishments of the sea) and the type of the construction. The data was made available by HELCOM Contracting Parties in response to data request. The data was received from Denmark, Finland, Sweden and Poland. The activity was declared as not relevant in Germany, Estonia, Latvia and Lithuanian. From Russia no data was reported. Attribute specification and units: Country: Country Type: Type of construction (land claim) Type_spec: More specified information about the type of land claim Year: Year of construction Estimated: Estimated year of construction from the identification information (environmental permit) given by the country in question Length: Length of the land reclamation (m) Area: Area (km2) of the land claim X_lon: Original Longitude coordinate point (for the data that has been transformed from points into lines) Y_Lat: Original latitude coordinate point (for the data that has been transformed from points into lines)

The extraction of herring data set is based on: 1. http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/a3b67a55-7c1e-469e-b692-58c4e7b79279 for years 2011-2016 reported per ICES statistical rectangles (tonnes / ICES rectangle). Landing values were redistributed within each ICES rectangle by the c-square fishing effort data provided by ICES (all gears, 2011-2013). Tonnes / km² was calculated and the results were converted to 1 km x 1 km grid cells. The layer was log-transformed and normalised to produce the final pressure layer on extraction of herring. Please see "lineage" section below for further details on attributes, data source, data processing, etc.

Input of impulsive anthropogenic sound includes impulsive events from 2011-2016 • Seismic surveys (HELCOM-OSPAR Registry; national data call submissions as lines in the folder of data) • Explosions (HELCOM-OSPAR Registry) • Pile driving (HELCOM-OSPAR Registry) • Airguns (HELCOM-OSPAR Registry) For the different event types, numeric intensity value was used to represent the pressure as categorized in HELCOM-OSPAR Impulsive noise registry. All nationally reported seismic surveys were given intensity values “Very low” (0.25) - Very low (0.25) - Low (0.5) - Medium (0.75) - High (1) The impact distance has not been taken into account due to the different nature of separate datasets used for the pressure layer. We acknowledge that e.g. pile driving and airguns may impact up to 20 km from the source event. The spread of the sound wave depends on the sound frequency, water salinity, temperature and density.

This layer is based on data from the BIAS project representing ambient underwater noise, modelled into a 0.5 km x 0.5 km grid, and representing sound pressure levels at 1/3 octave bands of 125 Hz exceeded at least 5% of the time. Measured and modelled acoustic data is provided as Sound Pressure Level (SPL). The time period for the data is annual values for year 2014. The selected depth interval is 0 m – bottom to represent the ambient underwater noise in the whole water column. The data were normalized setting level 0 at 92 db re 1µPa and level 1 at 127 db re 1µPa.

Concentration of phosphorus pressure layer is interpolated from annual seasonal average of total phosphorus measurements from surface waters (0-10 m) extracted from ICES’s oceanographic database, database of Swedish Meteorological and Hydrological Institute, EEA’s Eionet database and Data from Gulf of Finland year 2014. The points were interpolated to cover the entire Baltic Sea with Spline with barriers interpolation method. Values were log-transformed and normalised (more detailed description below).