The pressure layer represents biological pressure caused by introduction of non-indigenous species. The data is obtained from core indicator Trend in the arrival of new non-indigenous species (BSEP 129b: http://www.helcom.fi/Lists/Publications/BSEP129B.pdf). For the Baltic Sea Impact Index, the layer was normalized.

This dataset represents the underlying data on core indicator Abundance of waterbirds in the breeding season 2018. The data is resulting from a data call carried out by HELCOM for State of the Baltic Sea report. Attribute information: "YEAR" = Year of the observation "SPECIES" = Species accepted scientific name "ABUNDANCE" = Abundance count "Country" = Country of observation "SITECODE" = Unique site code

Broad-scale habitat maps for the Baltic Sea have been produced in the EUSeaMap project in 2016. For German and Estonian marine areas, national (more accurate) datasets were used. German data included both substrate and light information (division into infralittoral/circalittoral). Estonian data included only substrate and the division into light regimes was obtained from the EuSeaMap data. Here, the habitat class “infralittoral mud” includes classes “Fine mud”, “Mud to sandy mud” and “Sandy mud” of the original data, in the infralittoral zone. The original polygon maps have been converted to 1 km x 1km grid. The scale of the substrate data used in broad-scale habitat maps varies from 1:250 000 to 1:1M (data from EMODnet Geology). Coarser resolution data has been used in areas, where 1: 250 000 substrate data has not been available. Due to different scales used, the habitat classes may show different sized patterns in different areas.

The map of sprat relative abundance is mainly based on Baltic International acoustic surveys (BIAS), years 2011-2016, (ICES WGBIFS reports), reported as millions of sprat per ICES rectangle. The BIAS surveys cover almost the whole area where sprat is commonly encountered. Outside BIAS area, sprat landings data was used to complement the data. For ICES rectangles surveyed by BIAS, values shown are the mean values per ICES rectangle based on BIAS data, average for 2011-2016. For ICES rectangles not surveyed by BIAS, values are calculated as: MAX-value x Weighting factor. The weighting factor is specific to each ICES rectangle, calculated as the ratio between the commercial landings in that rectangle and the commercial landings in the ICES rectangle with highest landings (based on averages for 2011-2015). MAX-value = millions of sprat according to BIAS in the ICES rectangle with highest landings. ICES rectangles outside the BIAS survey area with no reported sprat landings were given the value 0. The abundance values / ICES rectangle were divided by the area of the rectangle to obtain values per 1km2, and then converted to 1 km x 1km grid cells. Values were first log transformed and then normalised.

This dataset was collected by HELCOM Secretariat during the HELCOM MORE project and represents monitoring stations in the Baltic Sea. This dataset contains all nutrient stations in the Baltic Sea as reported to the HELCOM MORE project.

Introduction of radionuclides is based on HELCOM MORS discharge data (2016-2020) . Annual averages of CO60, CS137 and SR90 from the period 2016-2020 per nuclear power plant. Gradual buffer around outlet to 10km distance (Type B decline). 10 km buffer with linear decline composed of 5 rings from discharges of radioactive substances (Type B decline)12.

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.

The data set is showing sandy beaches along the Baltic Sea coast as polyline used for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). This dataset has been produced by COWI (http://www.cowi.dk) based on data collected from Russia and COWI from figure 2.7 Major coast types in the Baltic (Bird & Schwartz 1985) and HELCOM (1993) Tacis rapport and additions in Germany (CRJ).

This indicator evaluates the eutrophication status of the Baltic Sea area based on dissolved inorganic phosphorus (DIP) concentration. The measured average DIP is based on in-situ PO4 measurements from oceanographic monitoring data for winter period (December-February) 2011-2016 (umol/l), surface water (0-10 m). More detailed description on methodology can be found at http://www.helcom.fi/baltic-sea-trends/indicators/Dissolved-inorganic-phosphorus-(DIP) and http://www.helcom.fi/Documents/Eutrophication%20assessment%20manual.pdf This dataset displays the result of the indicator in HELCOM Assessment Scale 4 (Division of the Baltic Sea into 17 open sea sub-basins and division of coastal areas to WFD water types or water bodies). The open sea areas have been assessed based on HELCOM Monitoring data and results for coastal areas are based on national WFD results. Attribute information: "HELCOM_ID" = Code of the HELCOM scale 4 assessment unit "Country" = country "level_2" = name of subbasin "name" = Name of the HELCOM scale 4 assessment unit "Area (km2)" = Area of the HELCOM scale 2 assessment unit "Indicator" = Name of indicator “Season” = Season of the indicator (Winter = December-February) “Period” = Assessment unit period (20112016 = 2011 – 2016) Indicator value (ES) = Indicator value calculated for the assessment unit "Standard deviation (STD)" = Standard deviation of data used for calculating ES "Number of samples " = Number of samples in assessment unit "Thershold value (ET)" = Commonly agreed thershold value "Ratio between ES and ET (ER)" = Ratio between ES and ET (in case of indicator with positive response to eutrophication) "ES_SCORE” = Confidence based on the data used for calculating ES "ET_SCORE” = Confidence of target-setting procedure "I_SCORE” = Confidence (%) = average of ES-Score and ET-Score "Indicator Weight" = Indicator Weight in integrated eutrophication assessment “Status” = Status of the indicator (“Achieve”, “Fail”, “Not assessed” or "Not applicable") “Confidence” = Confidence of result based on I-SCORE (“High”, “Moderate”, “Low” or "Not assessed") "AULEVEL" = Assessment unit level used for the indicator

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.