Skip to main content

Advertisement

Environmental Sciences Europe
Environmental Sciences Europe Cover Image

The EU Horizon 2020 project GRACE: integrated oil spill response actions and environmental effects

Environmental Sciences Europe volume 31, Article number: 44 (2019) | Download Citation

Article metrics

Abstract

This article introduces the EU Horizon 2020 research project GRACE (Integrated oil spill response actions and environmental effects), which focuses on a holistic approach towards investigating and understanding the hazardous impact of oil spills and the environmental impacts and benefits of a suite of marine oil spill response technologies in the cold climate and ice-infested areas of the North Atlantic and the Baltic Sea. The response methods considered include mechanical collection in water and below ice, in situ burning, use of chemical dispersants, natural biodegradation, and combinations of these. The impacts of naturally and chemically dispersed oil, residues resulting from in situ burning, and non-collected oil on fish, invertebrates (e.g. mussels, crustaceans) and macro-algae are assessed by using highly sensitive biomarker methods, and specific methods for the rapid detection of the effects of oil pollution on biota are developed. By observing, monitoring and predicting oil movements in the sea through the use of novel online sensors on vessels, fixed platforms including gliders and the so-called SmartBuoys together with real-time data transfer into operational systems that help to improve the information on the location of the oil spill, situational awareness of oil spill response can be improved. Methods and findings of the project are integrated into a strategic net environmental benefit analysis tool (environment and oil spill response, EOS) for oil spill response strategy decision making in cold climates and ice-infested areas.

Background

Accidental oil spills have occurred—and will occur—in different sea areas of the world as long as oil drilling, production and transport activities continue on our planet. The degree of damage of the spills on local ecosystems, and the effectiveness of different response technologies are highly dependent on prevailing environmental conditions and immediately available oil spill response resources. In polar and sub-polar regions, the marine ecosystems are especially vulnerable to oil spills, mainly due to the coldness and slow degradation of the spilled oil compounds. Furthermore, the cold and often ice-infested sea poses serious challenges for oil combating measures. Along with other differences in critical environmental characteristics, it is obvious that each marine region needs risk assessment, monitoring and response methods more or less tailored to fit its specific characteristics.

The Baltic Sea is the second largest brackish water basin in the world and is characterised by strong stratification, high nutrient concentrations, continuous oxygen deficiency in most deep water basins and low salinity [1]. With a coastline shared by nine highly industrialised countries, it supports approximately 15% of the world’s total maritime traffic, including the transport of different types of oil [2, 3]. Since large amounts of oil are used, transported and stored in this region, oil and oil spills are considered a major threat to the Baltic Sea ecosystem [3]. In the Baltic Sea, the rate of oil transportation continuously increases on an annual basis, and therefore possible environmental risks should be taken into consideration [4]. Marine pollution arising from illegal oil discharges from ship tank or bilge pumping is much greater than that from spectacular ship accidents, and is mainly detected along essential navigation routes [4, 5]. With regard to oil spill response activities, the description of the type, location, extent and state of oil at sea is of prime importance for predicting the trajectory of oil slicks and areas of shoreline likely to become polluted [4, 6]. The detection of oil spills and the description of their location and extent is performed using remote sensing imagery (SAR data) [4, 5].

In the Arctic parts of the North Atlantic, the risk of oil spills due to both oil and gas exploration as well as climate change is increasing, the latter opening new shipping routes. Navigation and operations in ice-infested waters are presenting extra challenges to oil spill response [7], and increase the risk rate of ship accidents and related oil spills [8]. Arctic seas, such as the Barents Sea and the East Greenland coast, constitute important areas for fisheries [9, 10], seabirds [11] and marine mammals [12]. Oil pollution in cold subarctic and arctic seas may therefore have serious ecological effects [13] as well as large socioeconomical impacts related to fisheries [14].

The chemical composition of crude oils is a complex mixture of thousands of organic compounds containing alkanes, cycloalkanes, aromatic compounds and asphalthenes. However, it differs significantly among the oils, depending on their origin [15]. Organic compounds containing oxygen, nitrogen, sulphur, as well as organometallic compounds are also found in smaller amounts [3, 16]. Crude oils containing large and heavy hydrocarbon molecules ranging from 5 to 40 carbons in length do not dissolve readily in water [3, 6]. The most toxic components of crude oils are the polycyclic aromatic hydrocarbons (PAHs), many of which possessing mutagenic and/or carcinogenic properties [2, 17]. Moreover, the chemical and physical properties of oil begin to change when it enters the sea and undergoes the so-called weathering. Initially, the oil spreads on the water surface forming a thin film. Some of the oil compounds evaporate, some dissolve in the water, and some form emulsions. Waves contribute to oil becoming mixed into the water column as oil droplets that may aggregate, and oil slicks may also sink and be deposited on the seafloor (sedimentation). The viscosity and behaviour of the oil is greatly affected by the ambient temperature as higher temperatures accelerate the vaporisation, dissolution, and biodegradation of the oil compounds [6]. The longest persistence of an oil spill has been found in soft sediments and on shorelines protected against strong wind and waves. In general, rocky headlands are quickly cleansed by wave and tidal actions. Oil contamination of sediments can be very long lasting, and long-term effects on benthic organisms have been seen in several cases [18].

During an average winter, ca. 40% of the Baltic Sea area is covered by ice. In Arctic marine environments, the spilled oil can be frozen into the ice sheet in various ways, and this preservation is expected to reduce evaporation, dissolution, and degradation. The preservation also implies that the oil will retain much of its potential toxicity upon release from the ice [19]. The estimation of the pathways, release rates, and chemical characteristics of the remaining oil provide the basis for eventual environmental risk and impact assessments [20].

Today, different response methods for removing oil are applied in order to minimise the environmental consequences of oil spills. Oleophilic skimmers are the most used type of mechanical oil spill response equipment. When employed on a large scale, the mechanical recovery method may be very time consuming and expensive due to its low recovery rates [21]. In situ burning, where an oil slick is ignited and burnt in a controlled manner, is considered to be a response method with high potential of oil removal in Arctic conditions [22]. The use of dispersing chemicals is aimed at increasing the natural potential for oil removal from the sea surface by dispersing the oil in the water column [23]. This oil spill response method was the main method used during the Deepwater Horizon blow-out accident aboard an oil-drilling platform in the Gulf of Mexico [24]. However, there is not much experience on the effectivity and hazardous effects of use of dispersants in Arctic areas. Currently dispersants are not used in the Baltic Sea because they are not recommended by the Helsinki Commission (HELCOM).

It is well known that in case of an oil spill, seabirds are among the groups of animals that are most vulnerable (e.g. [25]. Even small amounts of fresh oil can have lethal effects on seabirds by destroying the waterproofing of their plumage, leading to loss of insulation and buoyancy and causing rapid death by hypothermia, starvation or drowning [26]. In the Arctic, these impacts are intensified, as the cold water leads more rapidly to hypothermia. Marine animals can take up PAHs and other crude oil components both passively, i.e. through diffusion over gills (invertebrates and fish) and lungs (birds and mammals), and actively, e.g. through feeding. Biomarkers, indicating changes at the lowest levels of biological complexity (molecular, cellular, tissue-level), provide an “early warning” of ecosystem health deterioration and have been recently suggested by the effect-based tools report of the European Commission to be used for monitoring under the EU Water Framework Directive [27]. In addition, marine monitoring programmes are increasingly including biomarkers in the assessment of biological effects of pollutants. Assessments of the consequences of oil spills is necessary for providing information on the maintenance of biodiversity and the integrity of marine communities and food webs, as well as for protecting critical habitats and safeguarding human health [28, 29].

Aims

The core aim of the GRACE project is to develop, compare and evaluate the effectiveness and environmental effects of different oil spill response methods in cold climate conditions. To date, several approaches have been proposed in the polar region, each catering to specific governmental or environmental requirements that inhibit broad application. GRACE aims to develop such a broadly applicable decision-support tool. Furthermore, a system for the real-time observation of underwater oil spills and a strategic tool for choosing oil spill response methods are developed. Currently, there are no automated systems available that can perform oil spill identification and monitoring in a single united integrated system consisting of remote sensing and in situ sensing. Furthermore, the satellite-detected (e.g. by EMSA’s CleanSeaNet) oil spills are validated by eye [30].

The overall objective of the project is to explore the environmental impacts and benefits of a suite of marine oil spill response technologies in the cold climate and ice-infested areas of the North Atlantic and the Baltic Sea. The response methods considered include mechanical collection in water and below ice, in situ burning, use of chemical dispersants, natural biodegradation, and combinations of these. The impacts of naturally and chemically dispersed oil, residues resulting from in situ burning, and non-collected oil on fish, invertebrates (e.g. mussels, crustaceans) and macro-algae are assessed by means of highly sensitive biomarker methods, and specific methods for the rapid detection of the effects of oil pollution on biota will be developed. By observing, monitoring and predicting oil movements in the sea by using novel online sensors on vessels, fixed platforms including gliders and the so-called SmartBuoys together with real-time data transfer into operational systems that help to improve the information on the location of the oil spill, situational awareness of oil spill response can be improved. Methods and findings of the project are integrated into a strategic net environmental benefit analysis tool for oil spill response strategy decision making in cold climates and ice-infested areas.

Project concept and approach

GRACE aims to achieve the research goals over a period of three and a half years, starting in 2016 and ending in 2019. The project includes a genuine trans-disciplinary consortium comprising experts in the fields of oil monitoring and on-line observations, as well as oil spill response authorities. It makes use of bioanalytics, field and laboratory studies, environmental impact assessment, monitoring and assessing the fate of oil pollutants as well as oil-degradation-related biotechnology, and also contributes to the development of oil spill response technology.

Beyond producing relevant knowledge on technologies that can be used for oil spill response and on their impacts, GRACE develops a tool for strategic net environmental benefit analysis, the environment and oil spill response (EOS) tool for deciding suitable oil spill response strategies in cold climates and ice-infested areas. The EOS results can be used in cross-border and transboundary co-operation and agreements. All gathered knowledge will be fed into the development of a beyond state-of-the-art response system based on high-end detection methods and environmentally friendly yet highly efficient mitigation and remediation techniques.

Project consortium

The genuine trans-disciplinary consortium with workgroups and scientists from Europe and Canada conducting the GRACE project consists of 13 partners. Leading research scientist Kirsten Jørgensen from the Finnish Environment Institute SYKE coordinates the project. The project partners are grouped into six work packages (WP), presented below with their contributing members and specific project tasks (Table 1).

Table 1 Composition of the GRACE project consortium
Full size table

Work packages

WP1—Oil spill detection, monitoring, fate and distribution (Lead: Tarmo Kõuts, TUT)

The main objective of this WP is to make in situ operational oil spill detection more accurate and cost-effective. The oil-in-water sensors, the core of in situ oil detection, are commercially available nowadays. However, their performance varies to a large extent, which is why the potential of in situ measurement technologies in respect to their accuracy and representativeness to detect oil spills in surface water of the sea needs to be analysed and tested. The existing oil spill detection and monitoring sensors could also be integrated with new platforms, such as ships of opportunity (SOOP), Smart Buoys, gliders or drifters for in situ oil spill detection. Furthermore, a new local scale model system for oil dispersion, evaporation and fate should be developed (Table 2).

Table 2 The main methods and expected outcome the work of WP1: oil spill detection, monitoring, fate and distribution
Full size table

WP2—Oil biodegradation and bioremediation (Lead: Jaak Truu, UTARTU)

The main objective of this WP is the assessment of natural degradation rates of different oil fractions in seawater, seawater–ice interface, sediments, and shoreline taking into account environmental parameters, dispersants application, cleaning and washing agents, and electro-kinetic treatment. Based on the determination of key bacterial species and metabolic pathways responsible for the degradation of different oil fractions in different sea compartments of the Baltic Sea and the Northern Atlantic, a metagenomic prediction platform for inferring oil biodegradation activity parameters (including biodegradation kinetics) in cold marine environment is being constructed (Table 3).

Table 3 The main methods used and expected outcomes of WP2: oil biodegradation and bioremediation
Full size table

WP3—Oil impacts on biota using biomarkers and ecological risks assessment (Lead: Thomas-Benjamin Seiler, RWTH)

The main objective of WP3 is the achievement of knowledge on (i) biological impacts and adverse outcome links elicited after oil spills, and (ii) the effects oil spill responses in different environmental and biological conditions at a regional scale. Furthermore, it aims at the development, adaptation and optimisation of effect-based methods for oil pollution monitoring, and at the assessment of the efficiency of each response method. In addition, scenario-targeted environmental risk assessments (ERA) are conducted (Table 4).

Table 4 The main methods and expected outcomes of WP3: oil impacts on biota using biomarkers and ecological risks assessment
Full size table

WP4—Combating oil spill in coastal Arctic waters—effectiveness and environmental effects (Lead: Kim Gustavson, AU)

The main objective of this WP is to improve the knowledge base for combating oil spills in ice-infested and cold waters. In addition, a mechanical unit for removal of oil under sea ice is being designed and tested. Environmental fate and effects of stranded oil, shoreline cleaning by in situ burning and shoreline clean-up by chemical agents in Arctic regimes are also assessed. The results of the experiments will provide valuable information for decision makers regarding oil spill response options to be included in the EOS assessment for oil spill response strategy and capacity building in the Arctic and the Baltic Sea (Table 5).

Table 5 Main methods and expected outcome of WP4: combating oil spill in coastal Arctic waters—effectiveness and environmental effects
Full size table

WP5—Strategic net environmental benefit analysis (SNEBA) (Lead: Susse Wegeberg, AU)

The main objective of the WP is to develop and launch a strategic net environmental benefit analysis (SNEBA) tool for decision-making. During the project the title of the tool to be launched was changed to environment and oil spill response (EOS) and it will be used for designing an appropriate and rapid oil spill response strategy combining the right mix of interventions (e.g. mechanical recovery, in situ burning, chemical dispersants, and/or bioremediation) for closed basins with extreme cold temperatures, based on relevant scenarios (Fig. 1).

Fig. 1
figure1

Schematic presentation of input to the environment and oil spill response (EOS) assessment

Full size image

An EOS assessment should not be confused with a net environmental benefit analysis (NEBA)/spill impact mitigating assessment (SIMA) for acute oil spill situations (Table 6).

Table 6 Main methods and expected outcomes of WP5: strategic net environmental benefit analysis (SNEBA)
Full size table

Prospects for the GRACE project

The work obtained in the different work packages is strongly interlinked, and the results will be communicated not only to the scientific community, but also very actively to the relevant stakeholder groups such as cross-border working groups dealing with oil spill response in the Arctic including, e.g. the EPPR (Emergency Prevention, Preparedness and Response) working group of the Arctic Council and the HELCOM RESPONSE working group (Fig. 2).

Fig. 2
figure2

Interlinkage of the work packages in GRACE

Full size image

The project has already produced a large number of reports that are available at the GRACE project web site http://www.grace-oil-project.eu. The expected impacts of GRACE are several:

  • Mitigate negative impacts of oil pollution and response activities on the marine environment, coastal economies and communities.

  • Better decision support tools for oil spill response strategy in different conditions.

  • Improve the integration between the scientific community and relevant government agencies charged with dealing with pollution, including cross-border and trans-boundary co-operation.

  • Better business potential for companies producing oil response equipment and monitoring services.

Availability of data and materials

Not applicable.

Abbreviations

EU:

European Union

GRACE:

Integrated oil spill response actions and environmental effects

SAR:

search and rescue

PAHs:

polycyclic aromatic hydrocarbons

EMSA:

European Maritime Safety Agency

SNEBA:

strategic net environmental benefit analysis

EOS:

environment and oil spill response (EOS)

SYKE:

Suomen ympäristökeskus

WP:

work package

TUT:

Tallinn University of Technology

SOOP:

ships of opportunity

UV:

ultra violet

AUV:

autonomous underwater vehicle

UAV:

unmanned aerial vehicle

UTARTU:

University of Tartu

RWTH:

Rheinisch-Westfälische Technische Hochschule

WAF:

water-accommodated fraction

ERA:

Environmental Risk Assessment

AU:

Aarhus University

ROV:

remotely operated vehicle

NEBA:

net environmental benefit analysis

SIMA:

Spill Impact Mitigation Assessment

EPPR:

Emergency Preparedness and Pollution Response

HELCOM:

Helsinki Commission on the protection of the marine environment of the Baltic Sea

IMO:

International Maritime Organization

References

  1. 1.

    Koskinen K, Hultman J, Paulin L, Auvinen P, Kankaanpää H (2010) Spatially differing bacterial communities in water columns of the northern Baltic Sea. FEMS Microbiol Ecol 75:99–110

  2. 2.

    Reunamo A, Riemann L, Leskinen P, Jørgensen KS (2013) Dominant petroleum hydrocarbon-degrading bacteria in the Archipelago Sea in South-West Finland (Baltic Sea) belong to different taxonomic groups than hydrocarbon degraders in the oceans. Mar Pollut Bull 72:174–180

  3. 3.

    Viggor S, Juhanson J, Jõesaar M, Mitt M, Truu J, Vedler E, Heinaru A (2013) Dynamic changes in the structure of microbial communities in Baltic Sea coastal seawater microcosms modified by crude oil, shale oil or diesel fuel. Microbiol Res 168:415–427

  4. 4.

    Uiboupin R, Raudsepp U, Sipelgas L (2008) Detection of oil spills on SAR images, identification of polluters and forecast of the slicks trajectory, US/EU-Baltic international symposium, 2008 IEEE/OES. pp 1–5

  5. 5.

    Anderson S, Raudsepp U, Uiboupin R (2010) Oil Spill statistics from SAR images in the North Eastern Baltic Sea ship route in 2007–2009. In: 2010 IEEE international geoscience and remote sensing symposium (IGARSS). pp 1883–1886

  6. 6.

    Rousi H, Kankaanpää H (2012) The ecological effects of oil spills in the Baltic Sea—the national action plan of Finland. Environmental Administration Guidelines 6en/2012. http://hdl.handle.net/10138/41546

  7. 7.

    Wilkinson J, Beegle-Krause CJ, Evers K-U, Hughes N, Lewis A, Reed M, Wadhams P (2017) Oil spill response capabilities and technologies for ice-covered Arctic marine waters: a review of recent developments and established practices. Ambio 46(Suppl. 3):S423–S441

  8. 8.

    Sormunen O-V, Hänninen M, Kujala P (2016) Marine traffic, accidents, and underreporting in the Baltic Sea. Sci J Maritime 46:163–177

  9. 9.

    Gjøsæter H (2009) Commercial fisheries (fish seafood and marine mammals). In: Sakshaug E, Johnsen G, Kovacs K (eds) Ecosystem Barents Sea. Tapir Academic Press, Trondheim, pp 373–414

  10. 10.

    Haug T, Bogstad B, Chierici M, Gjosaeter H, Hallfredsson EH, Hoines AS, Hakon-Hoel A, Ingvaldsen RB, Jorgensen LL, Knutsen T, Loeng H, Naustvoll LJ, Rottingen I, Sunnana K (2017) Future harvest of living resources in the Arctic Ocean north of the Nordic and Barents Seas: a review of possibilities and constraints. Fisheries Res 188:38–57

  11. 11.

    Gabrielsen GW (2009) Seabirds in the Barents Sea. In: Sakshaug E, Johnsen G, Kovacs K (eds) Ecosystem Barents Sea. Tapir Academic Press, Trondheim, pp 415–453

  12. 12.

    Kovacs KM, Haug T, Lydersen C (2009) Marine Mammals of the Barents Sea. In: Sakshaug E, Johnsen G, Kovacs K (eds) Ecosystem Barents Sea. Tapir Academic Press, Trondheim, pp 453–496

  13. 13.

    Gabrielsen GW, Sydnes LK (2009) Pollution in the Barents Sea. Gabrielsen GW. 2009. Seabirds in the Barents Sea. In: Sakshaug E, Johnsen G, Kovacs K (eds) Ecosystem Barents Sea. Tapir Academic Press, Trondheim, pp 497–544

  14. 14.

    Hjermann DO, Melsom A, Dingsor GE, Durant JM, Eikeset AM, Roed LP, Ottersen G, Storvik G, Stenseth NC (2007) Fish and oil in the Lofoten–Barents Sea system: synoptic review of the effect of oil spills on fish populations. Mar Ecol Prog Ser 339:283–299

  15. 15.

    Hannisdal A, Hemmingsen PV, Sjoblom J (2005) Group-type analysis of heavy crude oils using vibrational spectroscopy in combination with multivariate analysis. Ind Eng Chem Res 44:1349–1357

  16. 16.

    Redman AD et al (2012) PETROTOX: an aquatic toxicity model for petroleum substances. Environ Toxicol Chem 31:2498–2506. https://doi.org/10.1002/etc.1982

  17. 17.

    Samanta SK, Singh OV, Jain RK (2002) Polycyclic aromatic hydrocarbons: environmental pollution and bioremediation. Trends Biotechnol 20:243–248

  18. 18.

    Shigenaka G (2014) Twenty-five years after the Exxon Valdez oil spill: NOAA’s scientific support, monitoring, and research. NOAA Office of Response and Restoration, Seattle, p 78

  19. 19.

    Sipelgas L, Uiboupin R (2007) Elimination of oil spill like structures from radar image using MODIS data, geoscience and remote sensing symposium, 2007. IGARSS 2007. IEEE International, pp 429–431

  20. 20.

    Faksness LG, Brandvik PJ, Daae RL, Leirvik F, Børseth JF (2011) Large-scale oil-in-ice experiment in the Barents Sea: Monitoring of oil in water and MetOcean interactions. Mar Pollut Bull 62:976–984

  21. 21.

    Broje V, Keller AA (2006) Improved mechanical oil spill recovery using an optimized geometry for the skimmer surface. Environ Sci Technol 40:7914–7918

  22. 22.

    Fritt-Rasmussen J, Ascanius BE, Brandvik PJ, Villumsen A, Stenby EH (2013) Composition of in situ burn residue as a function of weathering conditions. Mar Pollut Bull 67:75–81

  23. 23.

    Nørregaard RD, Gustavson K, Møller EF, Strand J, Tairova Z, Mosbech A (2015) Ecotoxicological investigation of the effect of accumulation of PAH and possible impact of dispersant in resting high arctic copepod Calanus hyperboreus. Aquat Toxicol 167:1–11

  24. 24.

    Lubchenco J, McNutt MK, Dreyfus G, Murawski SA, Kennedy DM, Anastas SC, Hunter T (2012) Science in support of the Deepwater Horizon response. PNAS 109:20212–20221

  25. 25.

    Piatt JF, Lensink CJ, Butler W, Kendziorek M, Nysewander DR (1990) Impact of the ‘Exxon Valdez’ oil spill on marine birds. Auk 107:387–397

  26. 26.

    Leighton FA (1993) The toxicity of petroleum oils to birds. Environ Rev 1:92–103

  27. 27.

    Wernersson A, Carere M, Maggi C, Tusil P, Soldan P, James A, Sanchez W, Dulio V, Broeg K, Reifferscheid G et al (2015) The European technical report on aquatic effect-based monitoring tools under the water framework directive. Environ Sci Eur 27:7

  28. 28.

    Marigómez I, Garmendia L, Soto M, Orbea A, Izagirre U, Cajaraville MP (2013) Marine ecosystem health status assessment through integrative biomarker indices: a comparative study after the Prestige oil spill “Mussel Watch”. Ecotoxicology 22:486–505

  29. 29.

    Marigómez I, Zorita I, Izagirre U, Ortiz-Zarragoitia M, Navarro P, Etxebarria N, Orbea A, Soto M, Cajaraville MP (2013) Combined use of native and caged mussels to assess biological effects of pollution through the integrative biomarker approach. Aquat Toxicol 136:32–48

  30. 30.

    Keramitsoglou I, Cartalis C, Kiranoudis CT (2006) Automatic identification of oil spills on satellite images. Environ Modell Softw 21:640–652

  31. 31.

    Steffens S, Nüßer L, Seiler TB, Ruchter N, Schumann M, Döring R, Cofalla C, Ostfeld A, Salomons E, Schüttrumpf H, Hollert H, Brinkmann M (2017) A versatile and low-cost open source pipetting robot for automation of toxicological and ecotoxicological bioassays. PLoS ONE 12(6):e0179636

  32. 32.

    Nüßer LK, Skulovich O, Hartmann S, Seiler T-B, Cofalla C, Schuettrumpf H, Hollert H, Salomons E, Ostfeld A (2016) A sensitive biomarker for the detection of aquatic contamination based on behavioral assays using zebrafish larvae. Ecotoxicol Environ Safety 133:271–280

  33. 33.

    Petersen W (2014) FerryBox systems: state-of-the-art in Europe and future development. J Mar Syst 140:4–12

  34. 34.

    Lambert P (2003) A literature review of portable fluorescence-based oil-in-water monitors. J Hazard Mater 102:39–55

  35. 35.

    OGP/IPIECA (2014) Capabilities and uses of sensor-equipped ocean vehicles for subsea and surface detection and tracking of oil spills. Oil and Gas Producers Association/International Petroleum Industry Environmental Conservation Association. Oil spill response joint industry project: surveillance, modelling & visualization. Work Package 1: In Water Surveillance

  36. 36.

    URready4OS (2016) Autonomous underwater vehicles in oil spill response. Project White paper

  37. 37.

    Vasilijevic A, Stilinovic N, Nad D, Mandic F, Miskovic N, Vukic Z (2015) AUV based mobile fluorometers: system for underwater oil-spill detection and quantification. Autonomous underwater vehicles ready for oil spill. UReady4OS

  38. 38.

    IPIECA-OGP/IMO/CEDRE (2014) Aerial observation of oil pollution at sea: an operational guide. IPIECA-OGP Good Practice Guide series

  39. 39.

    Fingas M, Brown C (2014) Review of oil spill remote sensing. Mar Pollut Bull 83:9–23

  40. 40.

    Lumpkin R, Özgökmen T, Centurioni L (2017) Advances in the application of surface drifters. Annu Rev Mar Sci 9:59–81

  41. 41.

    American Petroleum Institute (2013) Remote sensing in support of oil spill response: planning guidance. API Technical Report 1144

  42. 42.

    Wolk F (2003) Three-dimensional lagrangian tracer modelling in Wadden Sea Areas (Diploma thesis). Carl von Ossietzky University, Oldenburg

  43. 43.

    Gräwe U, Wolff JO (2010) Suspended particulate matter dynamics in a particle framework. Environ Fluid Mech 10:21–39. https://doi.org/10.1007/s10652-009-9141-8

  44. 44.

    Venosa AD, Holder EL (2007) Biodegradability of dispersed crude oil at two different temperatures. Mar Pollut Bull 54:545–553

  45. 45.

    Brakstad OG, Nonstad I, Faksness L-G, Brandvik PJ (2008) Responses of microbial communities in Arctic Sea ice after contamination by crude petroleum oil. Microb Ecol 55:540–552

  46. 46.

    Garneau MÉ, Michel C, Meisterhans G, Fortin N, King TL, Greer CW, Lee K (2016) Hydrocarbon biodegradation by Arctic sea-ice and sub-ice microbial communities during microcosm experiments, Northwest Passage (Nunavut, Canada). FEMS Microbiol Ecol 92:fiw130

  47. 47.

    Huang S, Chaudhary K, Garmire LX (2017) More is better: recent progress in multi-omics data integration methods. Front Genet 8:84

  48. 48.

    Klemetsen T, Raknes IA, Fu J, Agafonov A, Balasundaram SV, Tartari G, Robertsen E, Willassen NP (2017) The MAR databases: development and implementation of databases specific for marine metagenomics. Nucleic Acids Res 46:D692–D699

  49. 49.

    Masavat N, Oh E, Chai G (2012) A review of electrokinetic treatment technique for improving the engineering characteristics of low permeable problematic soils. Int J Geomate 2:266–272

  50. 50.

    Brack W, Escher BI, Müller E, Schmitt-Jansen M, Schulze T, Slobodnik J, Hollert H (2018) Towards a holistic and solution-oriented monitoring of chemical status of European water bodies: how to support the EU strategy for a non-toxic environment? Environ Sci Eur 30:33

  51. 51.

    Leiniö S, Lehtonen KK (2005) Seasonal variability in biomarkers in the bivalves Mytilus edulis and Macoma balthica from the northern Baltic Sea. Comp Biochem Physiol C 140:408–421

  52. 52.

    Posada-Ureta O, Olivares M, Zatón L, Delgado A, Prieto A, Vallejo A, Paschke A, Etxebarria N (2016) Uptake calibration of polymer-based passive samplers for monitoring priority and emerging organic non-polar pollutants in WWTP effluents. Anal Bioanal Chem 408:3165–3175

  53. 53.

    Villares R, Real C, Fernández JÁ, Aboal J, Carballeira A (2007) Use of an environmental specimen bank for evaluating the impact of the Prestige oil spill on the levels of trace elements in two species of Fucus on the coast of Galicia (NW Spain). Sci Total Environ 374:379–387

  54. 54.

    Garmendia L, Izagirre U, Soto M, Lermen D, Koschorreck J (2015) Combining chemical and biological endpoints, a major challenge for twenty-first century’s environmental specimen banks. Environ Sci Pollut Res 22:1631–1634

  55. 55.

    Counihan KL (2018) The physiological effects of oil, dispersant and dispersed oil on the bay mussel, Mytilus trossulus, in Arctic/Subarctic conditions. Aquat Toxicol 199:220–231

  56. 56.

    Hansen BH, Altin D, Øverjordet IB, Jager T, Nordtug T (2013) Acute exposure of water soluble fractions of marine diesel on Arctic Calanus glacialis and boreal Calanus finmarchicus: effects on survival and biomarker response. Sci Total Environ 449:276–284

  57. 57.

    Knag AC, Taugbøl A (2013) Acute exposure to offshore produced water has an effect on stress- and secondary stress responses in three-spined stickleback Gasterosteus aculeatus. Comp Biochem Physiol C 158:173–180

  58. 58.

    Van der Oost R, Beyer J, Vermeulen NP (2003) Fish bioaccumulation and biomarkers in environmental risk assessment: a review. Environ Toxicol Pharmacol 13:57–149

  59. 59.

    Turja R, Sanni S, Baršienė J, Stankevičiūtė M, Devier M-H, Budzinski H, Lehtonen KK (2019) Biomarker responses and accumulation of polycyclic aromatic hydrocarbons in Mytilus trossulus and Gammarus oceanicus during exposure to crude oil. Aquat Toxicol (submitted, under revision)

  60. 60.

    Perrichon P, Le Menach K, Akcha F, Cachot J, Budzinski H, Bustamante P (2016) Toxicity assessment of water-accommodated fractions from two different oils using a zebrafish (Danio rerio) embryo-larval bioassay with a multilevel approach. Sci Total Environ 568:952–966

  61. 61.

    de Soysa TY, Ulrich A, Friedrich T, Pite D, Compton SL, Ok D, Bernardos RL, Downes GB, Hsieh S, Stein R, Lagdameo MC, Halvorsen K, Kesich L-R, Barresi MJ (2012) Macondo crude oil from the Deepwater Horizon oil spill disrupts specific developmental processes during zebrafish embryogenesis. BMC Biol 10:40

  62. 62.

    Singer MM, Aurand DV, Coelho GM, Bragin GE, Clark JR, Sowby M, Tjeerdema RS (2001) Making, measuring, and using water-accommodated fractions of petroleum for toxicity testing. Int Oil Spill Conf Proc 2001:1269–1274

  63. 63.

    Turja R, Höher N, Snoeijs P, Barsiene J, Butrimaviciene L, Devier M-H, Budzinski H, Kuznetsova T, Kholodkevich S, Lehtonen KK (2014) A multibiomarker approach for the assessment of pollution impacts in two areas in the Swedish Baltic Sea coast using caged mussels (Mytilus trossulus). Sci Total Environ 473:398–409

  64. 64.

    Buist IA et al (2013) In situ burning in ice-affected waters: state of knowledge report. http://arcticresponse.wpengine.com/reports/. Assessed 25 Jun 2019

  65. 65.

    Fritt-Rasmussen J, Linnebjerg JF, Sørensen MX, Brogaard NL, Rigét FF, Kristensen P, Jomaas G, Boertmann DM, Wegeberg S, Gustavson K (2016) Effects of oil and oil burn residues on seabird feathers. Mar Pollut Bull 109:446–452

  66. 66.

    Fritt-Rasmussen J, Wegeberg S, Gustavson K (2015) Review on burn residues from in situ burning of oil spills in relation to arctic waters. Water Air Soil Pollut 226:329

  67. 67.

    Fukuyama AK, Shigenaka G, Coats DA (2014) Status of intertidal infaunal communities following the Exxon Valdez oil spill in Prince William Sound, Alaska. Mar Pollut Bull 84:56–69

  68. 68.

    Lewis A, Johansen Ø, Singsaas I, Solsberg L (2008) Ice regimes for oil spill response planning. SINTEF report no. 15. https://www.sintef.no/projectweb/jip-oil-in-ice/publications/. Assessed 25 Jun 2019

  69. 69.

    Singsaas I, Resby J, Leirvik F, Johansen B, Solsberg L (2008) Testing and verification of oil skimmers during the field experiment in the Barents Sea, May 2008. SINTEF report no. 9. https://www.sintef.no/projectweb/jip-oil-in-ice/publications/

  70. 70.

    Wegeberg S, Rigét F, Gustavson K, Mosbech A (2016) Store Hellefiskebanke, Grønland. Miljøvurdering af oliespild samt potentialet for oliespildsbekæmpelse. Aarhus University, DCE—Danish Centre for Environment and Energy, 98s. – Scientific report from DCE-DCE—Danish Centre for Environment and Energy no 216. http://dce2.au.dk/pub/SR216.pdf

  71. 71.

    Liungman O, Mattsson J (2011) Scientific Documentation of Seatrack Web; physical processes, algorithms and references. https://stw.smhi.se/. Assessed 25 Jun 2019

  72. 72.

    Bock M, Robinson H, Wenning R, French-McCay D, Rowe J, Walker AH (2018) Comparative risk assessment of oil spill response options for a deepwater oil well blowout: part II. Relative risk methodology. Mar Pollut Bull 133:984–1000

  73. 73.

    Laanemets J, Lilover MJ, Raudsepp U, Autio R, Vahtera E, Lips I, Lips U (2006) A fuzzy logic model to describe the cyanobacteria Nodularia spumigena blooms in the Gulf of Finland, Baltic Sea. Hydrobiol 554:31–45

  74. 74.

    Wenning RJ, Robinson H, Bock M, Rempel-Hesterc MA, Gardinerd W (2018) Current practices and knowledge supporting oil spill risk assessment in the Arctic. Mar Environ Res 141:289–304

  75. 75.

    Jensen PE, Fritt-Rasmussen J (2016) Influence of introduction of e-based distance learning on student experience and performance. In: Proceedings of the international RILEM conference: materials, systems and structures in civil engineering 2016 segment on innovation of teaching in materials and structures. Proceedings PRO 108, pp 37–46

Download references

Acknowledgements

The authors are grateful to Veronica Witick for technical help with the manuscript.

Funding

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 679266.

Author information

Affiliations

  1. Marine Research Center, Finnish Environment Institute (SYKE), Agnes Sjöbergin Katu 2, 00790, Helsinki, Finland

    • Kirsten S. Jørgensen
    • , Kari K. Lehtonen
    • , Harri Kankaanpää
    •  & Jorma Rytkönen

  2. Aarhus Universitet (AU), Biosciences, Frederiksborgvej 399, 4000, Roskilde, Denmark

    • Susse Wegeberg
    • , Kim Gustavson
    •  & Janne Fritt-Rasmussen

  3. Institute of Molecular and Cell Biology, University of Tartu (UTARTU), Riia 23, 51010, Tartu, Estonia

    • Jaak Truu

  4. Tallinn University of Technology (TUT) Marine Systems Institute, Akadeemia Tee 15a, 12618, Tallinn, Estonia

    • Tarmo Kõuts
    •  & Madis-Jaak Lilover

  5. RWTH Aachen University, Worringer Weg 1, 52074, Aachen, Germany

    • Anne Kreutzer
    • , Thomas-Benjamin Seiler
    • , Henner Hollert
    •  & Sarah Johann

  6. Marine Station Plentzia (PiE), University of the Basque Country (UPV/EHU), Areatza, z/g, 48620, Plentzia, Spain

    • Ionan Marigómez
    • , Manu Soto
    •  & Xabier Lekube

  7. Norges Teknisk-naturvitenskapelige Universitet (NTNU) NO10, Høgskoleringen 1, 7491, Trondheim, Norway

    • Bjørn M. Jenssen
    •  & Tomasz M. Ciesielski

  8. Greenland Oil Spill Response A/S (GOSR) AS, Aqqusinersuaq 48A, 3900, Nuuk, Greenland

    • Lonnie B. Wilms

  9. Lamor Corporation Ab (Lamor) OY, Rihkamatori 2, 06100, Porvoo, Finland

    • Rune Högström
    •  & Mika Pirneskoski

  10. Meritaito Oy (MTOY) OY, Porkkalankatu 5, 00180, Helsinki, Finland

    • Seppo Virtanen

  11. SSPA Sweden AB (SSPA) AB, Chalmers Tvärgata 10, 40022, Göteborg, Sweden

    • Björn Forsman

  12. Northern Research Institute Narvik AS (NORUT Narvik) AS, Rombaksveien (E6) 47, 8504, Narvik, Norway

    • Chris Petrich
    •  & Nga Phuong-Dang

  13. Center for Earth Observation Science, and Dept. of Environment and Geography, University of Manitoba (MICB), Manitoba, R3T 2N2, Canada

    • Feiyue Wang

  14. HAW, Ulmenliet 30, 21033, Hamburg, Germany

    • Anne Kreutzer

Authors

  1. Search for Kirsten S. Jørgensen in:

  2. Search for Anne Kreutzer in:

  3. Search for Kari K. Lehtonen in:

  4. Search for Harri Kankaanpää in:

  5. Search for Jorma Rytkönen in:

  6. Search for Susse Wegeberg in:

  7. Search for Kim Gustavson in:

  8. Search for Janne Fritt-Rasmussen in:

  9. Search for Jaak Truu in:

  10. Search for Tarmo Kõuts in:

  11. Search for Madis-Jaak Lilover in:

  12. Search for Thomas-Benjamin Seiler in:

  13. Search for Henner Hollert in:

  14. Search for Sarah Johann in:

  15. Search for Ionan Marigómez in:

  16. Search for Manu Soto in:

  17. Search for Xabier Lekube in:

  18. Search for Bjørn M. Jenssen in:

  19. Search for Tomasz M. Ciesielski in:

  20. Search for Lonnie B. Wilms in:

  21. Search for Rune Högström in:

  22. Search for Mika Pirneskoski in:

  23. Search for Seppo Virtanen in:

  24. Search for Björn Forsman in:

  25. Search for Chris Petrich in:

  26. Search for Nga Phuong-Dang in:

  27. Search for Feiyue Wang in:

Contributions

KSJ (SYKE) and TBS and AK (RWTH Aachen University) compiled the manuscript and wrote the introductory part of the manuscript. Other authors contributed to the work package descriptions. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Kirsten S. Jørgensen.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests. Henner Hollert is Editor-in-Chief of Environmental Sciences Europe.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark