This dataset represents the integrated assessment of hazardous substances in the Baltic Sea in 2016-2021. This dataset displays the result of the assessment in HELCOM Assessment unit Level 3 (Division of the Baltic Sea into 17 sub-basins and further division into coastal and offshore areas).

This dataset represents the underlying sediment data on core indicator Polyaromatic hydrocarbons (PAH) and their metabolites. The core indicator evaluates the status of the marine environment based on concentrations of Polyaromatic hydrocarbons (PAH) in sediment and biota. Quantitative threshold value is used to evaluate if core indicators status is Achieve, Fail or Not assessed. As There is no commonly agreed threshold value for measuring metabolites available, this report only considers concentrations of contaminants. This dataset 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" = name of subbasin "country" = country "station" = Unique code for the station "stationNam" = name for the station "determinan" = determinant parameter (ANT = anthracene) "detGroup" = the grouping of determinands used to display the results "_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 represents the underlying data on core indicator Population trends and abundance of seals 2018. This dataset contains reported observations for grey seal species. The core indicator evaluates seal distribution to determine whether it reflects good status. Quantitative thresholds are used to evaluate if core indicators status is Good, Not good or Not assessed. Attribute information: "Species" = Species (GS = Grey seal) "Country" = Country (2 digit acronym) "Site" = Name of site "Area" = Area "HELCOM_SUB" = Name of HELCOM Level 2 assessment unit "Latitude" = Latitude (WGS84 decimal degrees) of site "Longitude" = Longitude (WGS84 decimal degrees) of site "N2000_ID" = Natura2000 ID, if the site is located within Natura 2000 site (if available) "Year" = Year of observation "Month" = Month of observation "Day" = Day of observation (if available) "Count" = Number of individuals observed on site "Count_type" = Count type "Age" = Age of individuals (if available) "No_surveys" = Number of surveys "Method" = Method of survey "CV_Estimate" "Estimate_T" = Estimate type: Modelled / minimum (observed) "Source" = Data source

This dataset represents the underlying data on core indicator Seasonal succession of dominating phytoplankton groups 2018. The core indicator evaluates phytoplankton community structure to determine whether it reflects good environmental status. Quantitative thresholds are used to evaluate if core indicators status is Good, Not good or Not assessed. Attribute information: "Code"= ID of HELCOM level 2 assessment unit "Assessment" = Name of HELCOM level 2 assessment unit "Station" = Name of station "Lat" = Latitude of station in WGS 84 decimal degrees "Lon" = Longitude of station in WGS 84 decimal degrees "Data_avail" = Data availability period (years) "Reference" = Reference period (years) "Data_provi" = Data provider organisation "Country" = Data provider country "Station_na" = Station name "Date" = Sampling date and time "Year" = Year of sampling "Month" = Month of sampling "Cyano" = Cyanobacteria "Dino" = Dinoflagellates "Diatoms" = Diatoms "Meso_rub" = Mesodinium rubrum "CyanoIn" = "DinoIn" = "DiatomsIn" = "MesoRubIn" =

This dataset represents the underlying data on core indicator Population trends and abundance of seals 2018. This dataset contains reported observations for harbour seals. The core indicator evaluates seal distribution to determine whether it reflects good status. Quantitative thresholds are used to evaluate if core indicators status is Good, Not good or Not assessed. Attribute information: "Species" = Species (HS = Harbour seal) "Country" = Country (2 digit acronym) "Site" = Name of site "Area" = Area "HELCOM_SUB" = Name of HELCOM Level 2 assessment unit "Latitude" = Latitude (WGS84 decimal degrees) of site "Longitude" = Longitude (WGS84 decimal degrees) of site "N2000_ID" = Natura2000 ID, if the site is located within Natura 2000 site (if available) "Year" = Year of observation "Month" = Month of observation "Day" = Day of observation (if available) "Count" = Number of individuals observed on site "Count_type" = County type "Age" = Age of individuals (if available) "No_surveys" = Number of surveys "Method" = Method of survey "CV_Estimate" "Estimate_T" = Estimate type: Modelled / minimum (observed) "Source" = Data source

This dataset represents the Integrated biodiversity status assessment for harbour seals. Status is shown in five categories based on the integrated assessment scores obtained in the tool. Biological quality ratios (BQR) above 0.6 correspond to good status. The assessment is based on the one-out-all-out approach, i.e. the indicator reflecting the worst status in each assessment unit. The status of the harbour seals was assessed using two core indicators: - Population trends and abundance of seals - Distribution of Baltic seals. This dataset displays the result of the integrated biodiversity status in HELCOM Assessment unit Scale 2 (Division of the Baltic Sea into 17 sub-basins). Attribute information: "HELCOM_ID" = ID of the HELCOM scale 2 assessment unit "level_2 = Name of the HELCOM scale 2 assessment unit "Area_km2" = Area of the HELCOM scale 2 assessment unit "EcosystemC" = Ecosystem component analyzed "BQR" = Biological Quality Ratio "Conf" = Confidence Total_indi" = Number of indicators used "D1CX" = MSFD descriptor 1 criteria X "conf_D1CX" = Confidence of MSFD descriptor criteria X "STATUS" = Status of assessment (0-0.2 = not good (lowest score), 0.2-0.4 = not good (lower score), 0.4-0.6 = not good (low score), 0.6-0.8 = good (high score, 0.8-1.0 = good (highest score))

This dataset represents the underlying data on core indicator Abundance of salmon spawners and smolt. The indicator evaluates the status of the abundance of salmon spawners and smolt in the Baltic Sea based on salmon smolt production in rivers flowing into the sea, also making use of additional supporting data on numbers of adult spawners. Determination of whether the threshold value that determines good status is achieved is based on a comparison of estimated smolt production with an estimated potential smolt production capacity. River-specific information provided by ICES WGBAST has been joined with river geometry by HELCOM Secretariat. Attribute information: "River_name" = Name of the river "A_unit" = HELCOM scale 2 Assessment unit "ICES_A_uni" = ICES assessment unit number "Assessment" = HELCOM scale 2 Assessment unit "ICES_Asses" = Number of ICES assessment unit "Estimates_" = Estimates of wild smolt production (*1000) median value "F90_proba" = 90% probability interval "Method_of_" = Method of estimation (1. Bayesian linear regression model, i.e. river model, 2. Sampling of smolts and estimate of total smot run size, 3. Estimate of smolt run from parr production by relation developed in the sae iver, 4. Estimate of smolt run from parr production by relation developed in another river, 5. Inference of smolt production from data derived from similar rivers in the region, 6. Count of spawners, 7. Estimate inferred from stocking of reared fish in the river, 8. Salmon catch in river, exploitation and survival estimate) "Data_sourc" = Data source "Data_origi" = Data originator (natonal instiute) "National_m" = National monitoing (YES/NO) "Use_restri" = Use restrictions (YES/NO)

This dataset represents the underlying data on core indicator Hexabromocyclododecane (HBCDD). The core indicator evaluates the status of the marine environment based on concentrations of Hexabromocyclododecane (HBCDD) in sediment. Quantitative threshold values are used to evaluate if core indicators status is Achieve, Fail or Not assessed. The threshold value is an environmental quality standard (EQS), derived at EU level as a substance included on the priority list under Directive 2008/105/EC. This dataset 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" = name of region "country" = country "station" = Unique code for station "stationNam" = name for the station "determinan" = determinant parameter "detGroup" = the grouping of determinants used to display the results "_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 core indicator evaluates the status of the Baltic Sea based on the number- and the size of illegal oil spills detected in annual aerial surveillance. Quantitative thresholds are used to evaluate if core indicators status is "Achieve", "Fail" or "Not assessed". Good status is achieved when the amount of oil spills are below the threshold value. 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" = Code of the HELCOM scale 2 assessment unit "level_2" = name of he HELCOM scale 2 assessment unit (subbasin) "Area (km2)" = Area of the HELCOM scale 2 assessment unit "AULEVEL" = Assessment unit level used for the indicator "STATUS" = Status of the indicator (“Target achieved”, “Target exceeded” or “Not assessed”)

This dataset contains integrated eutrophication status assessment 2011-2016, visualized for indirect effects (C3_ER). The assessment is done on HELCOM Assessment Unit level 4: HELCOM Subbasins with coastal WFD water type or water bodies. The HEAT 3.0 has been applied for open sea assessment units using HELCOM core indicators and for coastal areas using national WFD indicators. For more information about the methodology, see State of the Baltic Sea report and HELCOM Eutrophication assessment manual. Attribute information: "HELCOM_ID": ID of HELCOM Level 4 Assessment unit "Country": Country / opensea "level_2": Name of HELCOM Level 2 Assessment unit "Name": Name of HELCOM Level 4 Assessment unit "Area_km2" : Area of assessment unit "C1_N": Criteria 1, number of indicators used for calculating Eutrophication Ratio (ER) "C1_ER": Criteria 1, ER "C1_SCORE": Criteria 1, Confidence of ER "C2_N": Criteria 2, number of indicators used for calculating ER "C2_ER": Criteria 2, ER "C2_SCORE": Criteria 2, Confidence of ER "C3_N": Criteria 3, number of indicators used for calculating ER "C3_ER": Criteria 3, ER "C3_SCORE": Criteria 3, Confidence of ER "N": Number of criteria used for calculating overall ER "ER": Overall ER "SCORE": Status confidence "STATUS": Status classification (Good (classes 0-0.5 & 0.5-1.0), Not Good (classes 1.0-1.5, 1.5-2.0 & >2.0), Not assessed) "CONFIDENCE": Final confidence rating (< 50% = low, 50-74 % = Moderate, = 75 % = High) "AULEVEL": Level of assessment units