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.

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).

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 source Name: 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

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 source Name: 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

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.

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.

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 aquaculture Producer: name of the producer Country: country in the BS catchment area Sub-basin: Baltic Sea PLC sub-basin Total annual N load: Total annual N load Total annual P load: Total annual P load

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 source Name: 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

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.