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  • This dataset depicts risk of oil spill from overtaking and head-on collisions. The modeled risk is calculated for the scenario year 2020 based on predicted shipping traffic density. The area of the bubbles corresponds to the risk of spill of oil and hazardous substances. The unit of the risk is average tonnes per year. This dataset has been produced by Albrecht Lentz, COWI (http://www.cowi.dk) for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). The dataset is a model result from a software code owned and operated by COWI. BRISK and BRISK-RU provide information on spatial distribution of risks of pollution from ships in the six sub-regions of the Baltic Sea, according to different types of accidents and spill sizes. The assessment takes into account the existing risk control measures as well as the prognosis for future maritime traffic. Groundings and ship-to-ship collisions are by far the most likely types of accidents resulting in pollution. Other kinds of incidents, such as fire, collisions with fixed objects, spills from offshore platforms, as well as illegal discharges have minor contribution to the risks. Further, the oil impact has been modelled. The oil impact can be described as the amount of spilled oil that is expected on the sea surface. The effects of oil drift, weathering and fate, as well as the oil recovery are taken into account. Field descriptions: LON: Longitude (center of ellipse) LAT: Latitude (center of ellipse) SPILLALL: Risk [average tonnes per year], sum of all spills. Used for visualization. SPILL12: Risk [average tonnes per year], small size spills. SPILL34: Risk [average tonnes per year], medium size spills. SPILL123: Risk [average tonnes per year], small & medium size spills. SPILL4: Risk [average tonnes per year], medium size spills. SPILL1234: Risk [average tonnes per year], small & medium size spills. SPILL567: Risk [average tonnes per year] large spills.

  • The data set is showing areas where estuaries occurs in the Baltic Sea area as polygon regions used for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). This dataset has been produced by COWI (http://www.cowi.dk) based on data collected from HELCOM, Finland (Copyright: SYKE), Lithuania, Russia and Sweden. The dataset includes data provided by the BRISK Project Partner organisations from various Baltic Sea countries. The detailed documentation of what partner provided what data is given in the Annex of the document: 70618-3.1.2.2 Data Collection Report. Estuaries have a high biodiversity. They are important breeding and foraging areas for many birds and reproduction areas for many fish species. Stranded oil may degrade slowly and the risk for damage to the habitat is high during clean up actions. The organisms encountered in the habitat are generally very vulnerable to oil.

  • This dataset depicts risk of oil spill from groundings. The modeled risk is calculated for the scenario year 2020 based on predicted traffic density. The area of the bubbles corresponds to the risk of spill of oil and hazardous substances. The unit of the risk is average tonnes per year. This dataset has been produced by Albrecht Lentz, COWI (http://www.cowi.dk) for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). The dataset is a model result from a software code owned and operated by COWI. BRISK and BRISK-RU provide information on spatial distribution of risks of pollution from ships in the six sub-regions of the Baltic Sea, according to different types of accidents and spill sizes. The assessment takes into account the existing risk control measures as well as the prognosis for future maritime traffic. Groundings and ship-to-ship collisions are by far the most likely types of accidents resulting in pollution. Other kinds of incidents, such as fire, collisions with fixed objects, spills from offshore platforms, as well as illegal discharges have minor contribution to the risks. Further, the oil impact has been modelled. The oil impact can be described as the amount of spilled oil that is expected on the sea surface. The effects of oil drift, weathering and fate, as well as the oil recovery are taken into account. Field descriptions: LON: Longitude (center of ellipse) LAT: Latitude (center of ellipse) SPILLALL: Risk [average tonnes per year], sum of all spills. Used for visualization. SPILL12: Risk [average tonnes per year], small size spills. SPILL34: Risk [average tonnes per year], medium size spills. SPILL123: Risk [average tonnes per year], small & medium size spills. SPILL4: Risk [average tonnes per year], medium size spills. SPILL1234: Risk [average tonnes per year], small & medium size spills. SPILL567: Risk [average tonnes per year] large spills.

  • The data set is showing shallow inlets and bays in the Baltic Sea area as polygons used for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). This dataset has been produced by COWI (http://www.cowi.dk) based on data collected from HELCOM, Russia and Estonia. The dataset includes data provided by the BRISK Project Partner organisations. The detailed documentation of what partner provided what data is given in the Annex of the document: 70618-3.1.2.2 Data Collection Report.

  • The data set is showing wintering areas for sea and shore birds in the Baltic Sea area as polygons used for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). This dataset has been produced by COWI (http://www.cowi.dk) based on data collected from HELCOM, Finland (Copyright: SYKE), Latvia, Lithuania, Poland, Russia and Sweden. The dataset includes data provided by the BRISK Project Partner organisations. The detailed documentation of what partner provided what data is given in the Annex of the document: 70618-3.1.2.2 Data Collection Report.

  • The data set is showing seagrass meadows in the Baltic Sea area as points used for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). This dataset has been produced by COWI (http://www.cowi.dk) based on data from HELCOM.

  • The data set is showing protected areas (Ramsar, UNESCO Biosphere Reserves and Natura2000) in the Baltic Sea area as polygons. This dataset is used for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). The dataset has been produced by COWI (http://www.cowi.dk) based on data collected from HELCOM and Baltic Sea countries (Finland: Copyright SYKE). The dataset includes data provided by the BRISK Project Partner organisations. The detailed documentation of what partner provided what data is given in the Annex of the document: 70618-3.1.2.2 Data Collection Report.

  • This dataset depicts risk of oil spill from illegal spills. The modeled risk is calculated for the scenario year 2020 based on predicted shipping traffic density. The area of the bubbles corresponds to the risk of spill of oil and hazardous substances. The unit of the risk is average tonnes per year. This dataset has been produced by Albrecht Lentz, COWI (http://www.cowi.dk) for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). The dataset is a model result from a software code owned and operated by COWI. BRISK and BRISK-RU provide information on spatial distribution of risks of pollution from ships in the six sub-regions of the Baltic Sea, according to different types of accidents and spill sizes. The assessment takes into account the existing risk control measures as well as the prognosis for future maritime traffic. Groundings and ship-to-ship collisions are by far the most likely types of accidents resulting in pollution. Other kinds of incidents, such as fire, collisions with fixed objects, spills from offshore platforms, as well as illegal discharges have minor contribution to the risks. Further, the oil impact has been modelled. The oil impact can be described as the amount of spilled oil that is expected on the sea surface. The effects of oil drift, weathering and fate, as well as the oil recovery are taken into account. Field descriptions: LON: Longitude (center of ellipse) LAT: Latitude (center of ellipse) SPILLALL: Risk [average tonnes per year], sum of all spills. Used for visualization. SPILL12: Risk [average tonnes per year], small size spills. SPILL34: Risk [average tonnes per year], medium size spills. SPILL123: Risk [average tonnes per year], small & medium size spills. SPILL4: Risk [average tonnes per year], medium size spills. SPILL1234: Risk [average tonnes per year], small & medium size spills. SPILL567: Risk [average tonnes per year] large spills.

  • The data set is showing seagrass meadows in the Baltic Sea area as polygon areas used for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). This dataset has been produced by COWI (http://www.cowi.dk) based on data from Poland and Russia. The dataset includes data provided by the BRISK Project Partner organisations. The detailed documentation of what partner provided what data is given in the Annex of the document: 70618-3.1.2.2 Data Collection Report.

  • This dataset depicts risk of oil spill from overtaking and head-on collisions. The modeled risk is calculated for the years 2008/2009. The area of the bubbles corresponds to the risk of spill of oil and hazardous substances. The unit of the risk is average tonnes per year. This dataset has been produced by Albrecht Lentz, COWI (http://www.cowi.dk) for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). The dataset is a model result from a software code owned and operated by COWI. BRISK and BRISK-RU provide information on spatial distribution of risks of pollution from ships in the six sub-regions of the Baltic Sea, according to different types of accidents and spill sizes. The assessment takes into account the existing risk control measures as well as the prognosis for future maritime traffic. Groundings and ship-to-ship collisions are by far the most likely types of accidents resulting in pollution. Other kinds of incidents, such as fire, collisions with fixed objects, spills from offshore platforms, as well as illegal discharges have minor contribution to the risks. Further, the oil impact has been modelled. The oil impact can be described as the amount of spilled oil that is expected on the sea surface. The effects of oil drift, weathering and fate, as well as the oil recovery are taken into account. Field descriptions: LON: Longitude (center of ellipse) LAT: Latitude (center of ellipse) SPILLALL: Risk [average tonnes per year], sum of all spills. Used for visualization. SPILL12: Risk [average tonnes per year], small size spills. SPILL34: Risk [average tonnes per year], medium size spills. SPILL123: Risk [average tonnes per year], small & medium size spills. SPILL4: Risk [average tonnes per year], medium size spills. SPILL1234: Risk [average tonnes per year], small & medium size spills. SPILL567: Risk [average tonnes per year] large spills.