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  • This dataset contains points of information describing the location and size of illegal oil discharges observed during aerial surveillance flights by HELCOM Contracting Parties during 1998-2017. Further information about illegal discharges of oil in the Baltic Sea area and HELCOM aerial surveillance activities can be found at http://www.helcom.fi/baltic-sea-trends/maritime/illegal-spills/ The dataset contains the following information: Country Year Spill_ID = Spill ID FlightType = The type of flight the detection was made during: National = "N", CEPCO = "C", Super CEPCO = "S" Date = The date of the detection (dd.mm.yyyy) Time_UTC = The time of the detection (hh:mm) Wind_speed = The wind speed at the time of the detection (m/s) Wind_direc = The wind direction at the time of the detection (degrees) Latitude = The latitude of the detection (decimal degrees, WGS84) Longitude = The longitude of the detection (decimal degrees, WGS84) Length__km = The length of the detection (km) Width__km = The width of the detection (km) Area__km2_ = The area of the detection (km2) Spill_cat = The category of the detection: OIL EstimVol_m = Estimated volume of the detection (m3) Polluter = Polluter (rig, ship, other, unknown) Category = Category of the detection: 100m3 = "5" Casefile = The name of the casefile the detection refers to Remarks = Any additional information

  • This dataset depicts risk of oil spills from collision with fixed objects and spills from offshore platforms, terminals, bunkering and STS operation. 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.

  • A vector grid in 2 x 2 km resolution showing model results of environmental impact caused by spill of soluble oil from ships with size greater than 5000 t as as g oil / km^2 weighted.This dataset has been produced by 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/). Fields: COL_NO (Dbl): Column ROW_NO (Dbl): Row WLoad (Dbl): Environmental impact (g oil / km^2 weighted).

  • This dataset depicts risk of oil spill from collisions at intersections. 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.

  • This dataset depicts risk of oil spill from collisions at intersections. 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.

  • 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.

  • 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.

  • A vector grid in 2 x 2 km resolution showing model results of environmental impact caused by spill of soluble oil from ships with size less than 5000 t as as g oil / km^2 weighted.This dataset has been produced by 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/). Fields: COL_NO (Dbl): Column ROW_NO (Dbl): Row WLoad (Dbl): Environmental impact (g oil / km^2 weighted).

  • 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.

  • 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.