This pressure dataset is derived from three human activities datasets - Urban land use (on land) - Recreational boating and sports (updated layer for 2018 version, please see separate http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/8c30e828-1340-4162-b7f9-254586ae32b6) - Bathing sites These data are described in more detail in separate fact sheets. Urban land use data was first converted to 1 km grid cells and expanded with 1 km. Thus, coastal urban areas extended also to the sea. These areas were given value 1 and other sea areas, value 0. Bathing sites (points) were converted to 1km grid and given value 1, rest of the sea areas were given value 0. Normalized recreational boating data was converted to 1 km grid cells. These three layers were summed to produce the layer (values from 0 to 3), after that the layer was normalized. Hunting and recreational fishing data were excluded from human disturbance layer, as they are mostly reported per country and would have resulted in overestimation of the actual pressure.

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. The following human activities were combined into the changes to hydrological conditions layer; - Hydropower dams (a 1km2 grid cell in the river estuary was selected) - Water course modification (1 km) - Wind turbines (operational, 0.3 km, linear decline) - Oil platforms (0.5 km, linear decline) 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.

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 (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.

This pressure dataset is derived from three human activities datasets Recreational boating and sports: Total fuel consumption of recreational boats modelled directly to 1 km grid cells[1]. Total fuel consumption of recreational boats presented as presence / absence. Rescaled with depth, log-transformed and normalized. Bathing sites, beaches: Point data converted directly to 1 km grid cells. Location of beaches presented as presence (1) / absence (0). Urban land use: Urban land use data was first converted to 1 km grid cells and expanded with 1 km[2]. Urban land use data was first converted to 1 km grid cells and expanded with 1 km. Thus, coastal urban areas extended also to the sea. These areas were given value 1 and other sea areas, value 0. Hunting and recreational fishing data were excluded from human disturbance layer, as they are mostly reported per country and would have resulted in overestimation of the actual pressure.S pecific pressure layers first modified by spatial extents and depth influence. Each of them is considered as of equal importance (same weight). Calculate the sum of the pressure in a cell. Normalized. [1] SHEBA project [2] Estimate of the human disturbance (underwater sound, visual disturbance).

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.

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.

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.

The Baltic Sea Impact Index is an assessment component that describes the potential cumulative burden on the environment in different parts of the Baltic Sea. The BSII is based on georeferenced datasets of human activities (36 datasets), pressures (18 datasets) and ecosystem components (36 datasets), and on sensitivity estimates of ecosystem components (so-called sensitivity scores) that combine the pressure and ecosystem component layers, created in http://www.helcom.fi/helcom-at-work/projects/holas-ii project. Cumulative impacts are calculated for each assessment unit (1 km2 grid cells) by summing all pressures occurring in the unit for each ecosystem component. Highest impacts are found from the cells where both are abundant, but high impacts can be caused also by a single pressure if there are diverse and sensitive habitats in the grid cell. All data sets and methodologies used in the index calculations are approved by all HELCOM Contracting Parties in review and acceptance processes. This data set covers the time period 2011-2016. Please scroll down to "Lineage" and visit http://stateofthebalticsea.helcom.fi/cumulative-impacts/ for more info.

The dataset represents the radioactive discharges from nuclear facilities in the Baltic Sea area. Data includes isotopes CS137, CO60 and SR90 Aquatic discharges in 2016-2021 with decay corrections. Attribute specification and units SITECODE: Code of the site SITENAME: Name of the site COUNTRY: country in which the site is located CO_2016 - 2020: isotope CO60 discharge during the reporting period SR_2016 - 2020: isotope SR90 discharge during the reporting period CS_2016 - 2020: isotope CS137 discharge during the reporting period CO_avg: average of isotope CO60 for the period CS_avg: average of isotope CS137 for the period SR_avg: average of isotope SR90 for the period