This dataset shows the sub-basins of the Baltic Sea which are used for Baltic Sea Pollution Load Compilation 6.

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.

Eutrophication, caused by excess input of nutrients, is one of the main threats affecting the Baltic Sea marine environment. Nutrients enter the Baltic Sea as waterborne (riverine inputs from the catchment area and direct discharges from point and diffuse sources in coastal areas) and airborne (atmospheric deposition) inputs. In 2007 HELCOM adopted a nutrient reduction scheme which is based on maximum allowable nutrient inputs (MAI) to reach "good environmental status" and country-wise nutrient reduction targets (CART) to share the burden of reducing nutrient pollution to the sea (HELCOM Baltic Sea Action Plan). Monitoring of nutrient inputs to the sea is important for assessing progress of countries towards their CART and to evaluate the effectiveness of measures to reduce pollution. This dataset displays nutrient loading as produced for http://www.helcom.fi/baltic-sea-trends/indicators/inputs-of-nutrients-to-the-subbasins HELCOM Core indicator: Inputs of nutrients to the subbasins based on HELCOM PLC data. Green colour of PLC subbasin indicates that inputs during 2016 were lower than MAI, red colour when they were higher, while yellow indicates that when taking into account the statistical uncertainty of input data it is not possible to determine whether MAI was fulfilled. The dataset contains following attributes: Basin: Name of PLC Subbasin Maximum allowable nutrient input: Maximum allowable nitrogen input for the subbasin (tons/year) N input including statistical uncertainty 2016: the average nitrogen input during 2016 including statistical uncertainty (tons/year) N input 2016 including statistical uncertainty in % of MAI: proportion of normalized nitrogen input during 2016 compared to MAI (%) Classification of achieving MAI: Classification of achieving MAI is given in colours: green=MAI fulfilled, yellow= fulfilment is not determined due to statistical uncertainty, and red=MAI not fulfilled.

The map of herring relative abundance is mainly based on Baltic International acoustic surveys (BIAS), years 2011-2016 (ICES WGBIFS reports), reported as millions of herring / ICES rectangle. Also herring landings data were used to complement the data. For ICES rectangles surveyed by BIAS, values shown are the mean values per ICES rectangle based on BIAS data, average for 2011-2016. For ICES rectangles not surveyed by BIAS, values are calculated as: MAX-value x Weighting factor. The weighting factor is specific to each ICES rectangle, calculated as the ratio between the commercial landings in that rectangle and the commercial landings in the ICES rectangle with highest landings (based on averages for 2011-2016). MAX-value = millions of herring according to BIAS in the ICES rectangle with highest landings. ICES rectangles outside the BIAS survey area with no reported herring landings were given the value 0. The relative abundance values in each ICES rectangle were divided by the area of the rectangle to obtain values per 1km2. If the values in small coastal ICES rectangles (outside BIAS area) became unrealistically large due to high herring landings, the value of the neighboring rectangle was given. The final layer was converted to 1 km x 1km grid cells. Values were first log transformed and 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.

Baltic Sea coastline. The source is OpenStreetMap data downloaded from http://openstreetmapdata.com/data/coastlines and processed at HELCOM. This data contains all the detail available in OSM by 31 Jan 2018.

This dataset is built from following Human activities datasets: • http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/81c917ea-492d-48e2-9f00-e1bb7fe3e4fc • http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/4fcd51dd-b8be-4e83-8cad-37c566782e8f The game hunting of seabirds data (see separate metadata): The total number of hunted seabirds were averaged over 2011-2015 (number of hunted seabirds / year). The area of the reporting unit was used to calculate the number of hunted seabirds / km2 and the data was converted to 1km x 1km grid. The predator control of seabirds data (see separate metadata): The total number of hunted cormorants were averaged over 2011-2015 (number of hunted cormorants / year). The area of the reporting unit was used to calculate the number of hunted cormorants / km2 and the data was converted to 1km x 1km grid. The two datasets were first separately log transformed and then summed, to get the total value for each grid cell. Zero values were given to all grid cells with no reported seabird hunting activity. The layer was normalized.

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.

The dataset contains sand and gravel extraction activity during 2011–2015. The dataset is based on data submission by HELCOM Contacting Parties in response to data request. The dataset is quality assured and contains data from all the Baltic Sea countries. Common extraction sites with information on volume of extraction was included in the dataset. The other extraction sites (building sites, exclusive sites) had only summed data for all the sites, as volumes of extraction in specific sites was classified as confidential information. For these sites the volumes was calculated from reported sum of "other extraction areas". The amount was equally divided between corresponding extraction areas. For some common extraction sites a shared amount was reported.

Baltic International Trawl Survey (BITS) data (2011-2016) from ICES DATRAS database was used as a base to create a map of cod relative abundance (quarter 1 data, CPUE values per ICES subdivision). Cod = 30cm was included. For ICES rectangles surveyed by BITS, values shown are the mean CPUE per ICES subdivision based on BITS data, average for 2011-2016. For ICES rectangles not surveyed by BITS, values are calculated as: MAX-value x Weighting factor. The weighting factor is specific to each ICES rectangle, calculated as the ratio between the commercial landings in that rectangle and the commercial landings in the ICES rectangle with highest landings (based on averages for 2011-2016). MAX-value = CPUE according to BITS in the ICES rectangle with highest landings. ICES rectangles outside the BITS survey area with no reported cod landings were given the value 0. Values were first log transformed and then normalized.