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.

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.

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).

Concentration of phosphorus pressure layer is interpolated from annual seasonal average of total phosphorus measurements from surface waters (0-10 m) extracted from ICES’s oceanographic database, database of Swedish Meteorological and Hydrological Institute, EEA’s Eionet database and Data from Gulf of Finland year 2014. The points were interpolated to cover the entire Baltic Sea with Spline with barriers interpolation method. Values were log-transformed and normalised (more detailed description below).

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.

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.

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 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.

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.