Physical loss pressure layer combines all human activities that cause physical loss of seabed. The pressure is given as area lost in each cell (km2). For the polygon datasets the area was assumed to be the lost area. For line and point datasets spatial extents were calculated with buffers (below in brackets). If no buffer extent is indicated, the data was reported as polygon. The human activities used for the physical loss pressure: Land claim - Area of polygon or 50 m buffer for points, 30m buffer for lines. Area of polygon - buffered line or point data, equals lost area. Watercourse modification - 50 m buffer. Area of polygon, buffered line or point data, equals lost area. Coastal defence and flood protection - 50 m buffer for lines, area of polygon. Area of polygon, buffered line or point data, equals lost area. Extraction of sand and gravel - Area of polygon. Area of polygon equals lost area. Dredging (capital) - Area of polygon or a 25/50 m buffer for <5000 m3 / >5000m3 sites. Area of polygon, buffered line or point data, equals lost area. Oil platforms - 25 m buffer. Buffered point data, equals lost area. Pipelines - 15 m buffer around cables with operational status. Area of polygon, buffered line or point data, equals lost area. Wind farms - 30 m buffer around each turbine with operational status. Buffered point data, equals lost area. Cables - 1.5 m buffer around cables with operational status. Buffered line data, equals lost area. Harbours - Polygon with 200 m buffer. Area of polygon, buffered line or point data, equals lost area. Marinas and leisure harbour - Point with 200 m buffer. Buffered point data, equals lost area. Bridges - 2 m buffer. Buffered line data, equals lost area. Finfish mariculture - 150 m buffer. Buffered point data, equals lost area. Shellfish mariculture - Area of polygon, 150 m buffer for points. Buffered point data, equals lost area. Activities are combined and potentially overlapping areas are removed. Dataset is clipped with coastline. Combined layer is intersected with 1 km grid to calculate % of area lost within a cell.

This dataset represents the underlying data on core indicator Abundance of coastal fish key functional groups. The core indicator evaluates the abundance of selected functional groups of coastal fish in the Baltic Sea. Quantitative thresholds are used to evaluate if core indicators status is Good, Not good or Not assessed. As a rule, good status is achieved when the abundance of piscivores (i.e. fish that feed on other fish) is above a site-specific threshold value, and the abundance of cyprinids or mesopredators (i.e. mid trophic-level fish) is within an acceptable range for the specific site. The status of functional groups of coastal fish in the Baltic Sea has been evaluated by assessing the status of piscivores and cyprinids/mesopredators during the period 2011-2016. This dataset displays the result of the indicator in HELCOM Assessment Scale 3 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and offshore areas). Attribute information: "COUNTRYID" = Country code "ORGANIZATI" = Data provider "AREANAME" = ICES area name "ASSESSMENT" = Name of scale 3 HELCOM assessment unit "IndicatorI" = Indicator name (abbreviation) "Functional" = Functional group "IndicatorV" = Result value for the indicator "MethodId" = Catch method "GearType_N" = Gear type of catch "Season_NAM" = Season

This dataset represents the underlying water data on core indicator Heavy metals – Lead.The core indicator evaluates the status of the marine environment based on concentrations of heavy metal Lead (Pb) in water, fish liver and sediments. Quantitative thresholds are used to evaluate if core indicators status is Achieve, Fail or Not assessed. Threshold values are based on Environmental quality standards (EQS), defined at EU level for substances included in the priority list under the Water Framework Directive. The Core indicator displays the result of the indicator in HELCOM Assessment Scale 4 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and off-shore areas and division of the coastal areas by WFD water types or water bodies). Attribute information: "region" = MIME subregion "country" = country "station" = Unique text that identifies the station "stationNam" = name for the station "determinan" = determinant parameter (PB = Lead) "detGroup" = the grouping of determinands used to display the results "filtered" = Filtered or unfiltered water sample used in analysis "_shape" = shape used to map assessment results "colour" = colour used to map assessment results "l3area" = HELCOM assessment unit on scale 3 "l4area" = HELCOM assessment unit on scale 4 "nyall" = total number of years of data "nyfit" = number of years of data used in the assessment "nypos" = number of years with at least one measurement above the limit of detection "lastyear" = most recent year of data "prtrend" = the significance of the change over the most recent 20 years; for the assessment conducted in November 2017 and published in June 2018, this is the period 1996-2016 "rtrend" = annual ‘linear’ change over the most recent 20 years "meanLY" = fitted value in last monitoring year "clLY" = upper one-sided 95% confidence limit on fitted value in last monitoring year "EQS" = Threshold value "EQSdiff" = difference between clLY and EQS "EQSbelow" = whether the mean value in the last monitoring year is significantly below EQS

This dataset contains all heavy dioxins in biota monitoring station locations, observed matrix, biota matrix and monitored species as reported to HELCOM secretariat by HELCOM Contracting Parties by 2016.

This dataset contains the in-situ monitoring data used for calculating eutrophication indicator results for following indicators: Chlorophyll-a 2018 Dissolved inorganic nitrogen 2018 Dissolved inorganic phosphorus 2018 Total nitrogen 2018 Total phosphorus 2018 Water clarity 2018 This dataset is extraction for 2011-2016 assessment period from HELCOM COMBINE database, which contains all HELCOM oceanographic monitoring data. Full COMBINE database can be accessed from dedicated web page Attribute information: "Cruise": Platform code of the monitoring cruise, which can be queried from http://vocab.ices.dk/ "Station": Station number "Year": Year of sampling event "Month": Month of sampling event "Day": Day of sampling event "Hour": Hour of sampling event "Minute": Minute of sampling event "Latitude": Latitude coordinate of the sampling location (WGS84 decimal degrees) "Longitude": Longitude coordinate of the sampling location (WGS84 decimal degrees) "BotDepth": Bottom depth (m) of sampling location "Secchi": Secchi depth at sampling location "StationNam": Station name from ICES Station dictionary "Assessment" = HELCOM assessment unit ID "Depth": Sampling depth (m) "Temperature": Temperature (ºC) "Salinity": Salinity "Oxygen": Oxygen (ml/l) "Phosphate": Phosphate (umol/l) "TotalPhos": Total phosphorus (umol/l) "Silicate": Silicate (umol/l) "Nitrate": Nitrate (umol/l) "Nitrite": Nitrite (umol/l) "Ammonium": Ammonium (umol/l) "TotalNitr": Total nitrogen (umol/l) "HydrogenS": Hydrogen sulphide (umol/l) "pH": pH "Alkalinity": Alkalinity (mEq/l) "Chlorophyl": Chlorophyll-a (ug/l)

This dataset contains all HBCD in biota monitoring station locations, observed matrix, biota matrix and monitored species as reported to HELCOM secretariat by HELCOM Contracting Parties by 2016.

This dataset depicts risk of oil spills from collision with fixed objects and spills from offshore platforms, terminals, bunkering and STS operation. The modeled risk is calculated for the scenario year 2020 based on predicted traffic density. The area of the bubbles corresponds to the risk of spill of oil and hazardous substances. The unit of the risk is average tonnes per year. This dataset has been produced by Albrecht Lentz, COWI (http://www.cowi.dk) for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). The dataset is a model result from a software code owned and operated by COWI. BRISK and BRISK-RU provide information on spatial distribution of risks of pollution from ships in the six sub-regions of the Baltic Sea, according to different types of accidents and spill sizes. The assessment takes into account the existing risk control measures as well as the prognosis for future maritime traffic. Groundings and ship-to-ship collisions are by far the most likely types of accidents resulting in pollution. Other kinds of incidents, such as fire, collisions with fixed objects, spills from offshore platforms, as well as illegal discharges have minor contribution to the risks. Further, the oil impact has been modelled. The oil impact can be described as the amount of spilled oil that is expected on the sea surface. The effects of oil drift, weathering and fate, as well as the oil recovery are taken into account. Field descriptions: LON: Longitude (center of ellipse) LAT: Latitude (center of ellipse) SPILLALL: Risk [average tonnes per year], sum of all spills. Used for visualization. SPILL12: Risk [average tonnes per year], small size spills. SPILL34: Risk [average tonnes per year], medium size spills. SPILL123: Risk [average tonnes per year], small & medium size spills. SPILL4: Risk [average tonnes per year], medium size spills. SPILL1234: Risk [average tonnes per year], small & medium size spills. SPILL567: Risk [average tonnes per year] large spills.

Pressure layer combines all human activities that cause changes to hydrological conditions. The human activities were presented as point data which were given spatial extents (given below). The pressure value was given as the proportion of the grid cell under the pressure. Water course modification: 1 km buffer[10]. Location of water course modifications used for buffer. Overlaps removed and areas of buffer calculated per each grid cell. The final value was the area of the buffer in each individual cell. Wind farms: 300 m buffer around each turbine classified as operational, with linear decline (Type B decline), composed of 3 rings. Location of operational turbines as points were buffered and values given over linear decline. Oil platforms: 500 m buffer around each turbine with linear decline (Type B decline) composed of 5 rings. Location of oil platforms as points were buffered and values given over linear decline. Hydropower dams: A grid cell in the estuary. Locations of hydropower dams were crossed with rivers and the grid cell located in the end of the river was selected as presence (1) – those that are operational and produces energy. Other values in the grid were considered absence. [10] Extent based on wind farms and cables but expanded to 1 km because hydrological parameters are widely spreading. The human activity datasets were first processed separately covering the whole Baltic Sea and then summed together and overlapping areas were dissolved to remove double counting. Attenuation gradients are assigned to each layer as described above. Area effected decreases when distance from avtivity increases. Layer was normalized.

This dataset describes fishing effort (hours/c-square) for midwater trawl in third quarter of 2013 based on VMS/Log book data processed by ICES Working Group on Spatial Fisheries Data (WGSFD). HELCOM requires spatially explicit information on fishing activity affecting the Baltic Sea marine ecosystem for policy purposes. In order to obtain this information a joint ICES/HELCOM/OSPAR data call was issued to relevant authorities of contracting parties to deliver information on fishing activity based on VMS/Log book data. The raw data was submitted to ICES and processed to advice data products by ICES Working Group for Spatial Fisheries (WGSFD) as requested by HELCOM. Processing of the raw data requires specific resources, knowledge and guarantee of anonymity for specific vessels, thus the process was done by ICES WGSFD following Conditions for VMS data use. In 2015 ICES collated Vessel Monitoring System (VMS) and logbook data received; data from Russia were not received. ICES provided to HELCOM advice as fishing abrasion pressure maps as well as fishing effort maps. HELCOM secretariat did the following processing to the data: - Conversion to ETRS89LAEA coordinate system - Added feature and attribute "Reported" to display unreported areas. Dataset attribute information: c-square: Unique reference of the c-square polygon mid_lat: latitude coordinate of the centroid of c-square inWGS84 decimal degrees mid_lon: longitude coordinate of the centroid of c-square inWGS84 decimal degrees Year: Year of fishing activity quarter: Quarter of the year, if applicable geargroup: Fishing gear group (Effort maps) SubsurfSAR: Subsurface swept area ratio (Intensity maps) SurfSAR: Surface swept area ratio (Intensity maps) Fishing_ho: Total fishing effort in hours within c-square (Effort maps) Reported: Yes=Reported data. No= No reported data (area that does not contain effort/intensity value due to lack of reported data.

This core indicator evaluates the state of the marine environment using distribution of the three species of seals that occur in the Baltic Sea. This dataset is for the Harbour seal. Quantitative thresholds are used to evaluate the core indicators status in "Achieve", "Fail" or "Not assessed". The core indicator has three components for each species: distribution of haul-out sites, breeding sites and foraging areas. Good status is achieved when the distribution of seals is close to pristine conditions (e.g. 100 years ago), or where appropriate when currently available haul-out sites are occupied (modern baseline), and when no decrease in area of occupation occurs. The current evaluation covers the assessment period 2011-2016. This dataset displays the result of the indicator in HELCOM Assessment Scale 2 (Division of the Baltic Sea into 17 sub-basins). Attribute information: "HELCOM_ID" = ID of the HELCOM scale 2 assessment unit "Area (km2)" = Area of the HELCOM scale 2 assessment unit "Name" = Name of the HELCOM scale 2 assessment unit "Status" = Status of the indicator (“Achieve”, “Fail” or “Not assessed”) "AULEVEL" = Assessment unit level used for the indicator