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.

Distribution of eelgrass based on data submission by HELCOM contracting parties. Mainly pointwise occurrences of eelgrass were submitted, originally gathered in national mapping and monitoring campaigns, or for scientific research. Polygon data from Puck Bay (Poland) was digitized based on Polish Marine Atlas and Orlowo cliff area was added based on expert knowledge. From Estonian waters, a predictive model was used (200m resolution), that was converted to presence/absence using minimized difference threshold (MDT) criteria. All data (points, polygon and the raster presenting predicted presence of eelgrass in the Estonian waters) were generalized to 5km x 5km grid cells.

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).

Potential cumulative impacts on benthic habitats is based on the same method than http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/9477be37-94a9-4201-824a-f079bc27d097, but is focused on physical pressures and benthic habitats. The dataset was created based on separate analysis for potential cumulative impacts on only the benthic habitats, as these are particularly affected by physical pressures. In this case the evaluation was based on pressure layers representing http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/ea0ef0fa-0517-40a9-866a-ce22b8948c88 and http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/05e325f3-bc30-44a0-8f0b-995464011c82, combined with information on the distribution of eight broad benthic habitat types and five habitat-forming species (http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/363cb353-46da-43f4-9906-7324738fe2c3, http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/f9cc7b2c-4080-4b19-8c38-cac87955cb91, http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/264ed572-403c-43bd-9707-345de8b9503c, http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/822ddece-d96a-4036-9ad8-c4b599776eca and http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/ca327bb1-d3cb-46c2-8316-f5f62f889090). The potential cumulative impacts has been estimated based on currently best available data, but spatial and temporal gaps may occur in underlying datasets. Please scroll down to "Lineage" and visit http://stateofthebalticsea.helcom.fi/cumulative-impacts/ for more info.

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.

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 is the first dedicated SMOS Sea Surface Salinity (SSS) product for the Baltic basin to enhance the science capabilities in the Baltic region and help to fill the gaps and grand challenges identified by the scientific community. These new product has been created under the funded ESA project ITT Baltic+ Salinity dynamics (4000126102/18/I-BG). This basin is one of the most challenging regions for the satellite SSS retrieval. The available EO-based SSS products are quite limited in terms of spatio-temporal coverage and quality. This is mainly due to technical limitations that strongly affect the brightness temperatures (TB), such as the high contamination by interferences and the contamination close to land and ice edges. Moreover, the sensitivity of TB to SSS changes is very low and dielectric models present limitations in this low salinity regime. Baltic+ L4 SSS product comprises 9 years (2011-2019) of daily maps at 0.05 degrees. A detailed explanation of the product algorithms and validation can be found at http://bec.icm.csic.es/doc/BEC_PD_SSS_Baltic_L3_L4.pdf and in the publication: Gonzalez-Gambau et al., “First SMOS Sea Surface Salinity dedicated products over the Baltic Sea“, Earth System Science Data, 2021 We present here the seasonal averaged Baltic+ L4 SSS products for the period 2011-2019. The daily Baltic+ L4 SSS products can be downloaded from the BEC FTP service (sftp://becftp.icm.csic.es) in the directory OCEAN/SSS/SMOS/Baltic/v1.0/L4/daily/

Pressure layer combines all human activities that cause physical disturbance or damage to seabed. For several human activity datasets, spatial extents were given (table below). Buffers with decreasing value rates were applied to represent the impact distance of physical disturbance. The following human activities were combined into the physical disturbance layer; - Cables (under construction, 1 km buffer) - Coastal defence and flood protection (under construction, 500 m buffer) - Deposit of dredged material (500 m buffer for points and areas) - Dredging (maintenance) (500 m buffer for points and areas) - Extraction of sand and gravel (500 m buffer) - Finfish mariculture (1 km buffer) - Fishing intensity 2011-2016 average (subsurface swept area ratio) - Furcellaria harvesting - Pipelines (0,3 km buffer) - Recreational boating and sports - Shellfish mariculture - Shipping density - Wind farms (under construction) (1 km buffer) - Wind farms (operational) (0,1 km buffer) The human activity data sets were first processed separately covering the whole Baltic Sea and then summed together. In this integration, some data layers were down-weighted to arrive at a balanced pressure layer, as described below. High pressure intensity and/or slow recovery (weighting factor 1): Coastal defence and flood protection, Deposit of dredged material, Dredging, Extraction of sand and gravel and Fishing intensity Moderate to high (Weighting factor 0,8): Pipelines and Shipping density Moderate (Weighting factor 0,6): Finfish mariculture, Shellfish mariculture and Wind farms (under construction) Low to moderate (Weighting factor 0,4): Cables Low (Weighting factor 0,2): Maerl and Furcellaria harvesting, Recreational boating and sports and Wind farms (operational) Harbours and marinas were left out from the physical disturbance pressure to avoid double counting due to their representation in the shipping density and recreational boating and sports data sets.

Summary The following 6 categories of annual mean salinity were applied delineating the Kattegat and the Baltic Sea into regions with differences in salinity regime (fig. 15): I. Oligohaline I (< 5psu). II. Oligohaline II (5 - 7.5psu). III. Mesohaline I (7.5 - 11psu). IV. Mesohaline II (11 - 18psu). V. Polyhaline (18 - 30psu). VI. Euhaline (>30psu). Description This dataset was produced by NERI, Denmark, for the BSR INTERREG IIIB project BALANCE. Due to the stratification in the Baltic Sea it was decided to use bottom salinity for the development of the benthic marine landscapes and difference in surface to bottom salinity for the pelagic landscapes. The following 6 categories of annual mean salinity were applied delineating the Kattegat and the Baltic Sea into regions with differences in salinity regime (fig. 15): I. Oligohaline I (< 5psu). II. Oligohaline II (5 - 7.5psu). III. Mesohaline I (7.5 - 11psu). IV. Mesohaline II (11 - 18psu). V. Polyhaline (18 - 30psu). VI. Euhaline (>30psu).

This dataset depicts the landcover in the Baltic Sea catchment area.