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.

HOLAS II data set on Nuclear power plants discharge water outlets (name, delta temperature of water discharge, heat load) for 2011-2015. The coverage of the data set is full, except for the Leningrad power plant the data is not available.

Introduction of radionuclides is based on HELCOM MORS Discharge data from 2011 to 2014. The isotopes taken into account were: Cesium-137, Strontium-90, and Cobalt-60. The decay-corrected annual average of the sum of the radionuclide discharges (in Bq) were calculated for the pressure. 10 km buffer with linear decreasing function was used to represent the impact distance from the nuclear power plant outlets.

Input of heat pressure dataset contains delta heat values from warm water discharge of - Discharge of warm water from nuclear power plants - Fossil fuel energy production. Discharge of warm water from nuclear power plants (2016-2021): 1 km buffer with steep decrease around outlet (Type D decline), composed of 4 rings [1]. Average input of heat load (Twh) of discharge of warm water from the nuclear power plant outlets. No data on heat load was available for the Leningrad nuclear power plant; therefore, the average heat load of discharge of warm water from nuclear power plants was given. Fossil fuel energy production (only location available): 1 km buffer with steep decrease around outlet (Type D decline), composed of 6 rings[12]. Heat load 1 (TWh) was given to all production sites, based on the average heat load of an individual production site in Helsinki. Heat load from both layers were summed and the layer was normalized. [1] Extent based on Ilus et al. 1986.

Input of hazardous substances pressure layer is interpolated from CHASE Assessment tool concentration component. The contamination ratio values were calculated with CHASE Assessment tool for hazardous substances monitored in water, sediment and biota. Classified mean contamination ratio was used in the interpolation. Classification is based on the http://stateofthebalticsea.helcom.fi/about-helcom-and-the-assessment/downloads-and-data/. The points were interpolated to cover the entire Baltic Sea with Spline with barriers interpolation method. Please see "lineage" section below for further details on attributes, data source, data processing, etc.

This dataset is built from the following Human activities dataset: • Hunting of seals The number of hunted seals (see separate metadata on hunting of seals) were averaged over 2011-2014 separately for grey seals, ringed seals and harbour seals (e.g. number of hunted grey seals / year). In Sweden the numbers of hunted grey seals in 2011 (74) were reported for the whole Swedish territorial waters), but here the numbers were set only to Swedish Gulf of Bothnia, as corresponding numbers were reported there in 2013 (75) and 2014 (65). The area of the reporting unit was used to calculate the number of hunted seals / km2 and the data was converted to 1km x 1km grid. For the Baltic Sea Impact Index, the values were normalized. Normalized value 0.5 was set to the level of quota for hunting of seal species in the Baltic Sea. The following quotas for hunting were used: Grey seal: 2000, Ringed seal: 350, Harbour seal 230.

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.

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.

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