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 layer depicts the pressure of hazardous substances in the Baltic Sea, based on the data from the HOLAS 3 integrated hazardous substances assessment. The methodology utilizes the integrated status values available for each HELCOM assessment unit on level 3. The results are based on multiple hazardous substances groups integration, done through the CHASE tool. The integrated assessment assess the hazardous substances status in biota, water and sediment, and final result in based on the worst status. As the SPIA is carried out using a 1x1km grid and the Integrated hazardous substances is assessed on vector-based HELCOM assessment units, the vector data is rasterized. First, the vector data is rasterized to 100x100m resolution, and thereafter it is aggregated to 10x10km grid using a mean value. A 10 km grid is used in order to make the gradients between assessment units slightly smoother and finally values are converted to 1x1 km resolution. Please see "lineage" section below for further details.

This dataset reflects spatial distribution of nutrients load and load of selected hazardous substances on the Baltic Sea from land based sources. The data, obtained through national monitoring programmes in 2014, were reported by Contracting Parties to HELCOM in the frame of HELCOM PLC-6 project and collected in the HELCOM Pollution Load Compilation (PLC-water) database (http://apps.nest.su.se/helcom_plus/). The reporting was organized in accordance with the HELCOM Guidelines for the annual and periodical compilation and reporting of waterborne pollution inputs to the Baltic Sea (PLC-Water, http://www.helcom.fi/Lists/Publications/PLC-Water%20Guidelines.pdf). The dataset has been produced based on guidance by HELCOM PRESSURE and REDCORE Drafting Group. The dataset contains following attributes: Unique code: unique code of the Mercury source Name: Mercury source name Country: country in the BS catchment area PLC sub-basin: Baltic Sea PLC sub-basin Total annual Cd discharge: total annual discharge of Cadmium Total annual Hg discharge: total annual discharge of Mercury Total annual Pb discharge: total annual discharge of Lead

This dataset reflects spatial distribution of nutrients load and load of selected hazardous substances on the Baltic Sea from land based sources. The data, obtained through national monitoring programmes in 2014, were reported by Contracting Parties to HELCOM in the frame of HELCOM PLC-6 project and collected in the HELCOM Pollution Load Compilation (PLC-water) database (http://apps.nest.su.se/helcom_plus/). The reporting was organized in accordance with the HELCOM Guidelines for the annual and periodical compilation and reporting of waterborne pollution inputs to the Baltic Sea (PLC-Water, http://www.helcom.fi/Lists/Publications/PLC-Water%20Guidelines.pdf). The dataset has been produced based on guidance by HELCOM PRESSURE and REDCORE Drafting Group. The dataset contains following attributes: Unique code: unique code of the Lead source Name: Lead source name Country: country in the BS catchment area PLC sub-basin: Baltic Sea PLC sub-basin Total annual Cd discharge: total annual discharge of Cadmium Report_data_Cd: reported data of cadmium Total annual Hg discharge: total annual discharge of Mercury Report_data_Hg: reported data of mercury Total annual Pb discharge: total annual discharge of Lead Report_data_Pb: reported data of lead Source: source of the input

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 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.

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.

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. The Discharge of warm water from nuclear power plants was requested from HELCOM Contracting Parties. Average temperature change of the cooling water (°C) and amount of cooling water (m3) was used to calculate the heat load in TWh. No data on heat load was available for the Leningrad nuclear power plant; therefore the average heat load (TWh) of discharge of warm water from nuclear power plants was given. No heat load information was available for fossil fuel energy production sites. Heat load of 1 (TWh) was given to all production sites, based on average heat load of individual production site in Helsinki from recent years. 1 km buffer was used for both datasets with steep decline around the outlet. Overlapping areas were summed. Heat load from both layers were summed and the layer was normalized.

Concentration of nitrogen pressure layer is interpolated from annual seasonal average of total nitrogen concentrations 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).