Oil Spill Modeling: Comparison
Please note this is a comparison between Version 2 by Vivi Li and Version 1 by GEORGIOS SYLAIOS.
Several oil spill simulation models exist in the literature, which are used worldwide to simulate the evolution of an oil slick created from marine traffic, petroleum production, or other sources. These models may range from simple parametric calculations to advanced, new-generation, operational, three-dimensional numerical models, coupled to meteorological, hydrodynamic, and wave models, forecasting in high-resolution and with high precision the transport and fate of oil. This study presents a review of the transport and oil weathering processes and their parameterization and critically examines eighteen state-of-the-art oil spill models in terms of their capacity (a) to simulate these processes, (b) to consider oil released from surface or submerged sources, (c) to assimilate real-time field data for model initiation and forcing, and (d) to assess uncertainty in the produced predictions. Based on our review, the most common oil weathering processes involved are spreading, advection, diffusion, evaporation, emulsification, and dispersion. The majority of existing oil spill models do not consider significant physical processes, such as oil dissolution, photo-oxidation, biodegradation, and vertical mixing. Moreover, timely response to oil spills is lacking in the new generation of oil spill models. Further improvements in oil spill modeling should emphasize more comprehensive parametrization of oil dissolution, biodegradation, entrainment, and prediction of oil particles size distribution following wave action and well blow outs.
  • oil spill modeling
  • oil weathering processes
  • biodegradation
  • transport and dispersion resurfacing
  • turbulent mixing
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References

  1. ITOPF. Oil Tanker Spill Statistics 2011; The International Tanker Owners Pollution Federation Limited: London, UK, 2011.
  2. ITOPF. Statistics—ITOPF. Available online: https://www.itopf.org/knowledge-resources/data-statistics/statistics/ (accessed on 1 January 2018).
  3. ITOPF. Oil Tanker Spill Statistics 2020. Available online: https://www.itopf.org/knowledge-resources/data-statistics/statistics/ (accessed on 5 February 2021).
  4. Walker, A.H.; Pavia, R.; Bostrom, A.; Leschine, T.M.; Starbird, K. Communication practices for oil spills: Stakeholder engagement during preparedness and response. Hum. Ecol. Risk Assess. Int. J. 2015, 21, 667–690.
  5. Fingas, M.; Fieldhouse, B. Water-in-oil emulsions: Formation and prediction. In Handbook of Oil Spill Science Technology; John Wiley & Sons: Hoboken, NJ, USA, 2014; p. 225.
  6. Azevedo, A.; Oliveira, A.; Fortunato, A.B.; Zhang, J.; Baptista, A.M. A cross-scale numerical modeling system for management support of oil spill accidents. Mar. Pollut. Bull. 2014, 80, 132–147.
  7. Mishra, A.K.; Kumar, G.S. Weathering of oil spill: Modeling and analysis. Aquat. Procedia 2015, 4, 435–442.
  8. Chen, H.; An, W.; You, Y.; Lei, F.; Zhao, Y.; Li, J. Numerical study of underwater fate of oil spilled from deepwater blowout. Ocean Eng. 2015, 110, 227–243.
  9. Lehr, W.; Socolofsky, S.A. The Importance of Understanding Fundamental Physics and Chemistry of Deep Oil Blowouts. In Deep Oil Spills; Springer: Cham, Switzerland, 2020; pp. 14–24.
  10. Murawski, S.A.; Ainsworth, C.H.; Gilbert, S.; Hollander, D.J.; Paris, C.B.; Schlüter, M.; Wetzel, D.L. Scenarios and Responses to Future Deep Oil Spills: Fighting the Next War; Springer: Berlin/Heidelberg, Germany, 2019.
  11. Murray, K.J.; Boehm, P.D.; Prince, R.C. The Importance of Understanding Transport and Degradation of Oil and Gasses from Deep-Sea Blowouts. In Deep Oil Spills; Springer: Cham, Switzerland, 2020; pp. 86–106.
  12. Sim, L.; Graham, J.; Rose, K.; Duran, R.; Nelson, J.; Umhoefer, J.; Vielma, J. Developing a Comprehensive Deepwater Blowout and Spill Model; U.S. Department of Energy, National Energy Technology Laboratory: Albany, NY, USA, 2015; p. 44.
  13. Yapa, P.D.; Wimalaratne, M.R.; Dissanayake, A.L.; DeGraff, J.A., Jr. How does oil and gas behave when released in deepwater? J. Hydro Environ. Res. 2012, 6, 275–285.
  14. Oldenburg, T.B.; Jaeger, P.; Gros, J.; Socolofsky, S.A.; Pesch, S.; Radović, J.R.; Jaggi, A. Physical and Chemical Properties of Oil and Gas Under Reservoir and Deep-Sea Conditions. In Deep Oil Spills; Springer: Cham, Switzerland, 2020; pp. 25–42.
  15. Pesch, S.; Schlüter, M.; Aman, Z.M.; Malone, K.; Krause, D.; Paris, C.B. Behavior of Rising Droplets and Bubbles: Impact on the Physics of Deep-Sea Blowouts and Oil Fate. In Deep Oil Spills; Springer: Cham, Switzerland, 2020; pp. 65–82.
  16. Vaz, A.C.; Paris, C.B.; Dissanayake, A.L.; Socolofsky, S.A.; Gros, J.; Boufadel, M.C. Dynamic Coupling of Near-Field and Far-Field Models. In Deep Oil Spills; Springer: Cham, Switzerland, 2020; pp. 139–154.
  17. Masutani, S.M.; Adams, E.E. Experimental Study of Multi-Phase Plumes with Application to Deep Ocean Oil Spills; Hawaii Natural Energy Institute, University of Hawaii: Herndon, VA, USA, 2001.
  18. Boxall, J.A.; Koh, C.A.; Sloan, E.D.; Sum, A.K.; Wu, D.T. Droplet size scaling of water-in-oil emulsions under turbulent flow. Langmuir 2012, 28, 104–110.
  19. Lefebvre, A.H.; McDonell, V.G. Atomization and Sprays; CRC Press: Boca Raton, FL, USA, 2017.
  20. Malone, K.; Aman, Z.M.; Pesch, S.; Schlüter, M.; Krause, D. Jet formation at the spill site and resulting droplet size distributions. In Deep Oil Spills; Springer: Cham, Switzerland, 2020; pp. 43–64.
  21. Li, Z.; Spaulding, M.L.; French-McCay, D. An algorithm for modeling entrainment and naturally and chemically dispersed oil droplet size distribution under surface breaking wave conditions. Mar. Pollut. Bull. 2017, 119, 145–152.
  22. Johansen, Ø.; Brandvik, P.J.; Farooq, U. Droplet breakup in subsea oil releases–Part 2: Predictions of droplet size distributions with and without injection of chemical dispersants. Mar. Pollut. Bull. 2013, 73, 327–335.
  23. Wang, B.; Socolofsky, S.A.; Lai, C.C.; Adams, E.E.; Boufadel, M.C. Behavior and dynamics of bubble breakup in gas pipeline leaks and accidental subsea oil well blowouts. Mar. Pollut. Bull. 2018, 131, 72–86.
  24. Bandara, U.C.; Yapa, P.D. Bubble Sizes, Breakup, and Coalescence in Deepwater Gas/Oil Plumes; 0733-9429; American Society of Civil Engineers: Reston, VA, USA, 2011; pp. 729–738.
  25. Zhao, L.; Boufadel, M.C.; Socolofsky, S.A.; Adams, E.; King, T.; Lee, K. Evolution of droplets in subsea oil and gas blowouts: Development and validation of the numerical model VDROP-J. Mar. Pollut. Bull. 2014, 83, 58–69.
  26. Zhao, L.; Boufadel, M.C.; Adams, E.; Socolofsky, S.A.; King, T.; Lee, K.; Nedwed, T. Simulation of scenarios of oil droplet formation from the Deepwater Horizon blowout. Mar. Pollut. Bull. 2015, 101, 304–319.
  27. Zhao, L.; Boufadel, M.C.; King, T.; Robinson, B.; Gao, F.; Socolofsky, S.A.; Lee, K. Droplet and bubble formation of combined oil and gas releases in subsea blowouts. Mar. Pollut. Bull. 2017, 120, 203–216.
  28. Johansen, Ø.; Rye, H.; Cooper, C. DeepSpill––field study of a simulated oil and gas blowout in deep water. Spill Sci. Technol. Bull. 2003, 8, 433–443.
  29. Yapa, P.D.; Zheng, L.; Chen, F. A model for deepwater oil/gas blowouts. Mar. Pollut. Bull. 2001, 43, 234–241.
  30. Chen, F.; Yapa, P.D. A model for simulating deep water oil and gas blowouts-Part II: Comparison of numerical simulations with “Deepspill” field experiments. J. Hydraul. Res. 2003, 41, 353–365.
  31. Fraga, B.; Stoesser, T.; Lai, C.C.; Socolofsky, S.A. A LES-based Eulerian–Lagrangian approach to predict the dynamics of bubble plumes. Ocean Model. 2016, 97, 27–36.
  32. Zodiatis, G.; Coppini, G.; Perivoliotis, L.; Lardner, R.; Alves, T.; Pinardi, N.; Liubartseva, S.; De Dominicis, M.; Bourma, E.; Neves, A.A.S. Numerical modeling of oil pollution in the Eastern Mediterranean Sea. In Oil Pollution in the Mediterranean Sea: Part I; Springer: Cham, Switzerland, 2017; pp. 215–254.
  33. Carpenter, A.; Kostianoy, A.G. Oil Pollution in the Mediterranean Sea: Part I: The International Context; Springer: Berlin/Heidelberg, Germany, 2019; Volume 83.
  34. De Dominicis, M.; Falchetti, S.; Trotta, F.; Pinardi, N.; Giacomelli, L.; Napolitano, E.; Fazioli, L.; Sorgente, R.; Haley, P.J., Jr.; Lermusiaux, P.F. A relocatable ocean model in support of environmental emergencies. Ocean Dyn. 2014, 64, 667–688.
  35. De Dominicis, M.; Bruciaferri, D.; Gerin, R.; Pinardi, N.; Poulain, P.; Garreau, P.; Zodiatis, G.; Perivoliotis, L.; Fazioli, L.; Sorgente, R. A multi-model assessment of the impact of currents, waves and wind in modelling surface drifters and oil spill. Deep Sea Res. Part II Top. Stud. Oceanogr. 2016, 133, 21–38.
  36. ASTM D6521-19. Standard Practice for Accelerated Aging of Asphalt Binder Using a Pressurized Aging Vessel (PAV); ASTM: West Conshohocken, PA, USA, 2019.
  37. Liubartseva, S.; Coppini, G.; Pinardi, N.; De Dominicis, M.; Lecci, R.; Turrisi, G.; Cretì, S.; Martinelli, S.; Agostini, P.; Marra, P. Decision support system for emergency management of oil spill accidents in the Mediterranean Sea. Nat. Hazards Earth Syst. Sci. 2016, 16, 2009–2020.
  38. Zelenke, B.; O’Connor, C.; Barker, C.H.; Beegle-Krause, C.; Eclipse, L. General NOAA Operational Modeling Environment (GNOME) Technical Documentation; U.S. Department of Commerce: Seattle, WA, USA, 2012.
  39. Beegle-Krause, J. General NOAA oil modeling environment (GNOME): A new spill trajectory model. In Proceedings of the International Oil Spill Conference, Tampa, FL, USA, 26–29 March 2001; pp. 865–871.
  40. Bergin, M.S.; Noblet, G.S.; Petrini, K.; Dhieux, J.R.; Milford, J.B.; Harley, R.A. Formal uncertainty analysis of a Lagrangian photochemical air pollution model. Environ. Sci. Technol. 1999, 33, 1116–1126.
  41. Fingas, M.; Brown, C. Oil spill remote sensing. In Earth System Monitoring; Springer: New York, NY, USA, 2013; pp. 337–388.
  42. Fingas, M.; Brown, C.E. A review of oil spill remote sensing. Sensors 2018, 18, 91.
  43. Zodiatis, G.; Lardner, R.; Alves, T.M.; Krestenitis, Y.; Perivoliotis, L.; Sofianos, S.; Spanoudaki, K. Oil spill forecasting (prediction). J. Mar. Res. 2017, 75, 923–953.
  44. Yapa, P.D.; Zheng, L. Modelling oil and gas releases from deep water: A review. Spill Sci. Technol. Bull. 1997, 4, 189–198.
  45. Zheng, L.; Yapa, P.D.; Chen, F. A model for simulating deepwater oil and gas blowouts-Part I: Theory and model formulation. J. Hydraul. Res. 2003, 41, 339–351.
  46. Reed, M.; Rye, H. A three-dimensional oil and chemical spill model for environmental impact assessment. In Proceedings of the International Oil Spill Conference, Long Beach, CA, USA, 27 February–2 March 1995; pp. 61–66.
  47. Reed, M.; Aamo, O.M.; Daling, P.S. Quantitative analysis of alternate oil spill response strategies using OSCAR. Spill Sci. Technol. Bull. 1995, 2, 67–74.
  48. Aamo, O.; Downing, K.; Reed, M. Calibration, verification, and sensitivity analysis of the IKU oil spill contingency and response (OSCAR) model system. Report 1996, 42, 4048.
  49. Leech, M.; Tyler, A.; Wiltshire, M. OSIS: A PC-based oil spill information system. In Proceedings of the International Oil Spill Conference, Tampa, FL, USA, 29 March–1 April 1993; pp. 863–864.
  50. Spaulding, M.; Kolluru, V.; Anderson, E.; Howlett, E. Application of three-dimensional oil spill model (WOSM/OILMAP) to hindcast the Braer spill. Spill Sci. Technol. Bull. 1994, 1, 23–35.
  51. ASA. OILMAP for Windows (Technical Manual); ASA: Narrangansett, RI, USA, 1997.
  52. Crowley, D.; Mendelsohn, D.; Mulanaphy, N.W.; Li, Z.; Spaulding, M. Modeling subsurface dispersant applications for response planning and preparation. In Proceedings of the International Oil Spill Conference Proceedings, Savannah, GA, USA, 5–8 May 2014; pp. 933–948.
  53. Spaulding, M.; Mendelsohn, D.; Crowley, D.; Li, Z.; Bird, A. Draft Technical Reports for Deepwater Horizon Water Column Injury Assessment: WC_TR. 13: Application of OILMAP DEEP to the Deepwater Horizon Blowout; Prepared for National Oceanic Atmospheric Administration; RPS ASA: South Kingstown, RI, USA, 2015.
  54. Spaulding, M.; Li, Z.; Mendelsohn, D.; Crowley, D.; French-McCay, D.; Bird, A. Application of an integrated blowout model system, OILMAP DEEP, to the Deepwater Horizon (DWH) spill. Mar. Pollut. Bull. 2017, 120, 37–50.
  55. French-McCay, D. Development and application of damage assessment modeling: Example assessment for the North Cape oil spill. Mar. Pollut. Bull. 2003, 47, 341–359.
  56. French-McCay, D.; Rowe, J.J. Evaluation of bird impacts in historical oil spill cases using the SIMAP oil spill model. In Proceedings of the Arctic and Marine Oilspill Program Technical Seminar, Edmonton, AB, Canada, 8–10 June 2004; pp. 421–452.
  57. French McCay, D.; Jayko, K.; Li, Z.; Horn, M.; Kim, Y.; Isaji, T.; Crowley, D.; Spaulding, M.; Decker, L.; Turner, C. Technical Reports for Deepwater Horizon Water Column Injury Assessment–WC_TR14: Modeling Oil Fate and Exposure Concentrations in the Deepwater Plume and Cone of Rising Oil Resulting from the Deepwater Horizon Oil Spill; RPS ASA: South Kingstown, RI, USA, 2015.
  58. Gros, J.; Reddy, C.M.; Nelson, R.K.; Socolofsky, S.A.; Arey, J.S. Simulating gas–liquid–water partitioning and fluid properties of petroleum under pressure: Implications for deep-sea blowouts. Environ. Sci. Technol. 2016, 50, 7397–7408.
  59. Gros, J.; Socolofsky, S.A.; Dissanayake, A.L.; Jun, I.; Zhao, L.; Boufadel, M.C.; Reddy, C.M.; Arey, J.S. Petroleum dynamics in the sea and influence of subsea dispersant injection during Deepwater Horizon. Proc. Natl. Acad. Sci. USA 2017, 114, 10065–10070.
  60. Gros, J.; Arey, J.S.; Socolofsky, S.A.; Dissanayake, A.L. Dynamics of live oil droplets and natural gas bubbles in deep water. Environ. Sci. Technol. 2020, 54, 11865–11875.
  61. Daniel, P. Operational forecasting of oil spill drift at Météo-France. Pract. Appl. Eng. 1996, 3, 53–64.
  62. Daniel, P.; Jan, G.; Cabioc’h, F.; Landau, Y.; Loiseau, E. Drift modeling of cargo containers. Spill Sci. Technol. Bull. 2002, 7, 279–288.
  63. Daniel, P.; Marty, F.; Josse, P.; Skandrani, C.; Benshila, R. Improvement of drift calculation in Mothy operational oil spill prediction system. In Proceedings of the International Oil Spill Conference, Vancouver, BC, Canada, 6–11 April 2003; pp. 1067–1072.
  64. Daniel, P.; Josse, P.; Dandin, P. Further improvement of drift forecast at sea based on operational oceanography systems. WIT Trans. Built Environ. 2005, 78.
  65. Brovchenko, I.; Kuschan, A.; Maderich, V.; Zheleznyak, M. The modelling system for simulation of the oil spills in the Black Sea. In Proceedings of the 3rd EuroGOOS Conference: Building the European Capacity in Operational Oceanography, Athens, Greece, 3–6 December 2002.
  66. Carracedo, P.; Torres-Lopez, S.; Barreiro, M.; Montero, P.; Balseiro, C.F.; Penabad, E.; Leitao, P.C.; Perez-Munuzuri, V. Improvement of pollutant drift forecast system applied to the Prestige oil spills in Galicia Coast (NW of Spain): Development of an operational system. Mar. Pollut. Bull. 2006, 53, 350–360.
  67. Pollani, A.; Triantafyllou, G.; Petihakis, G.; Nittis, K.; Dounas, C.; Koutitas, C. The Poseidon operational tool for the prediction of floating pollutant transport. Mar. Pollut. Bull. 2001, 43, 270–278.
  68. Lardner, R.; Zodiatis, G.; Hayes, D.; Pinardi, N. Application of the MEDSLIK Oil Spill Model to the Lebanese Spill of July 2006; European Group of Experts on Satellite Monitoring of Sea Based Oil Pollution; European Communities: Brussels, Belgium, 2006; pp. 1018–5593.
  69. Zodiatis, G.; Lardner, R.; Hayes, D.; Georgiou, G.; Pinardi, N.; De Dominicis, M.; Panayidou, X. The Mediterranean oil spill and trajectory prediction model in assisting the EU response agencies. In Proceedings of the Congreso Nacional de Salvamento en la Mar, Cadiz, Spain, 2–4 October 2008; pp. 2–4.
  70. Berry, A.; Dabrowski, T.; Lyons, K. The oil spill model OILTRANS and its application to the Celtic Sea. Mar. Pollut. Bull. 2012, 64, 2489–2501.
  71. Legrand, S.; Duliere, V. OSERIT: An oil spill evaluation and response integrated tool. In Proceedings of the Book of Abstracts of the Fourth International Conference on the Application of Physical Modelling to Port and Coastal Protection, Ghent, Belgium, 17–20 September 2012; pp. 275–276.
  72. De Dominicis, M.; Pinardi, N.; Zodiatis, G.; Lardner, R. MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting—Part 1: Theory. Geosci. Model Dev. 2013, 6, 1851–1869.
  73. De Dominicis, M.; Pinardi, N.; Zodiatis, G.; Archetti, R. MEDSLIK-II, a Lagrangian marine surface oil spill model for short-term forecasting-Part 2: Numerical simulations and validations. Geosci. Model Dev. 2013, 6, 1871–1888.
  74. Röhrs, J.; Dagestad, K.F.; Asbjørnsen, H.; Nordam, T.; Skancke, J.; Jones, C.E.; Brekke, C. The effect of vertical mixing on the horizontal drift of oil spills. Ocean Sci. 2018, 14, 1581–1601.
  75. Dagestad, K.F.; Röhrs, J.; Breivik, Ø.; Ådlandsvik, B. OpenDrift v1.0: A generic framework for trajectory modelling. Geosci. Model Dev. 2018, 11, 1405–1420.
  76. Yapa, P.D.; Li, Z. Simulation of oil spills from underwater accidents I: Model development. J. Hydraul. Res. 1997, 35, 673–688.
  77. Yapa, P.D.; Chen, F. Behavior of oil and gas from deepwater blowouts. J. Hydraul. Eng. 2004, 130, 540–553.
  78. Crowley, D.; French-McCay, D.; Santos, L.; Chowdhury, B.; Markussen, R. Modeling atmospheric volatile organic compound concentrations resulting from a deepwater oil well blowout–Mitigation by subsea dispersant injection. Mar. Pollut. Bull. 2018, 136, 152–163.
  79. Yapa, P.; Zheng, L.; Chen, F. Clarkson Deepwater Oil & Gas∼ CDOG Model; Department of Civil and Environmental Engineering, Clarkson University: Potsdam, NY, USA, 2001.
  80. French-McCay, D.; Crowley, D.; Rowe, J.J.; Bock, M.; Robinson, H.; Wenning, R.; Walker, A.H.; Joeckel, J.; Nedwed, T.J.; Parkerton, T.F. Comparative risk assessment of spill response options for a deepwater oil well blowout: Part 1. Oil spill modeling. Mar. Pollut. Bull. 2018, 133, 1001–1015.
  81. Li, Z.; Spaulding, M.; McCay, D.F.; Crowley, D.; Payne, J.R. Development of a unified oil droplet size distribution model with application to surface breaking waves and subsea blowout releases considering dispersant effects. Mar. Pollut. Bull. 2017, 114, 247–257.
  82. Spaulding, M.; Bishnoi, P.; Anderson, E.; Isaji, T. An integrated model for prediction of oil transport from a deep water blowout. In Proceedings of the Arctic and Marine Oilspill Program Technical Seminar, Vancouver, BC, Canada, 14–16 June 2000; pp. 611–636.
  83. French, D.P.; Schuttenberg, H.Z.; Isaji, T. Probabilities of oil exceeding thresholds of concern: Examples from an evaluation for Florida Power and Light. In Proceedings of the Arctic and Marine Oilspill Program Technical Seminar, Calgary, AB, Canada, 2–4 June 1999; pp. 243–270.
  84. French, D.P.; Rines, H.M. Validation and use of spill impact modeling for impact assessment. In Proceedings of the International Oil Spill Conference, Fort Lauderdale, FL, USA, 6–9 April 1997; pp. 829–834.
  85. Reed, M.; Daling, P.S.; Brakstad, O.G.; Singsaas, I.; Faksness, L.-G.; Hetland, B.; Ekrol, N. OSCAR2000: A multi-component 3-dimensional oil spill contingency and response model. In Proceedings of the Arctic and Marine Oilspill Program Technical Seminar, Vancouver, BC, Canada, 14–16 June 2000; pp. 663–680.
  86. Reed, M.; Turner, C.; Odulo, A. The role of wind and emulsification in modelling oil spill and surface drifter trajectories. Spill Sci. Technol. Bull. 1994, 1, 143–157.
  87. Aamo, O.M.; Reed, M.; Downing, K. Oil spill contingency and response (OSCAR) model system: Sensitivity studies. In Proceedings of the International Oil Spill Conference, Fort Lauderdale, FL, USA, 7–10 April 1997; pp. 429–438.
  88. Aamo, O.M.; Reed, M.; Daling, P. A Laboratory-Based Weathering Model: PC Version for Coupling to Transport Models; Environment Canada: Ottawa, ON, Canada, 1993.
  89. Daling, P.S.; Brandvik, P.J.; Mackay, D.; Johansen, O. Characterization of crude oils for environmental purposes. Oil Chem. Pollut. 1990, 7, 199–224.
  90. Daling, P.S.; Brandvik, P.J. Characterization and Prediction of the Weathering Properties of Oils at Sea-A Manual for the Oils Investigated in the DIWO Project; Institutt for Kontinentalundersoekelser og Petroleumsteknologi A/S: Trondheim, Norway, 1991.
  91. Downing, K.; Reed, M. Object-oriented migration modelling for biological impact assessment. Ecol. Model. 1996, 93, 203–219.
  92. Spaulding, M.; Howlett, E.; Anderson, E.; Jayko, K. OILMAP: A Global Approach to Spill Modeling; Environment Canada: Ottawa, ON, Canada, 1992.
  93. Howlett, E.; Jayko, K.; Isaji, T.; Anid, P.; Gary, M.; Francois, S. Marine forecasting and oil spill modeling in Dubai and the Gulf region. In Proceedings of the CODEPEC VII, Dubai, UAE, 24–28 February 2018.
  94. McGinnis, D.F.; Greinert, J.; Artemov, Y.; Beaubien, S.E.; Wüest, A. Fate of rising methane bubbles in stratified waters: How much methane reaches the atmosphere? J. Geophys. Res. Ocean. 2006, 111.
  95. Socolofsky, S.A.; Bhaumik, T.; Seol, D.-G. Double-plume integral models for near-field mixing in multiphase plumes. J. Hydraul. Eng. 2008, 134, 772–783.
  96. Daniel, P.; Josse, P.; Dandin, P.; Gouriou, V.; Marchand, M.; Tiercelin, C. Forecasting the Erika oil spills. In Proceedings of the International Oil Spill Conference, Tampa, FL, USA, 26–29 March 2001; pp. 649–655.
  97. Daniel, P. Drift Forecasts for the Erika and Prestige Oil Spills. Pract. Appl. Eng. 2010, 4, 301–308.
  98. Cucco, A.; Daniel, P. Numerical modeling of oil pollution in the Western Mediterranean Sea. In Oil Pollution in the Mediterranean Sea: Part I; Springer: Cham, Switzerland, 2016; pp. 255–274.
  99. Zodiatis, G.; De Dominicis, M.; Perivoliotis, L.; Radhakrishnan, H.; Georgoudis, E.; Sotillo, M.; Lardner, R.; Krokos, G.; Bruciaferri, D.; Clementi, E. The Mediterranean decision support system for marine safety dedicated to oil slicks predictions. Deep Sea Res. Part II Top. Stud. Oceanogr. 2016, 133, 4–20.
  100. Daniel, P.; Josse, P.; Dandin, P.; Lefevre, J.-M.; Lery, G.; Cabioch, F.; Gouriou, V. Forecasting the Prestige oil spills. In Proceedings of the Interspill 2004 Conference, Trondheim, Norway, 14–17 June 2004.
  101. Brovchenko, I.; Maderich, V. Numerical Lagrangian method for the modelling of the surface oil slick. Appl. Hydromech. 2002, 4, 23–31.
  102. Saraiva, S.; Fernandes, L.; Leitão, P.C.; Pina, P.; Santos, F.B.; Neves, R. MaBenE Deliverable D4. 5–Part II Integrated modelling tool-MOHID Water Modelling System. 2006.
  103. Perivoliotis, L.; Krokos, G.; Nittis, K.; Korres, G. The Aegean sea marine security decision support system. Ocean Sci. 2011, 7, 671.
  104. Oil Spill Fate and Trajectory Model. Available online: https://poseidon.hcmr.gr/components/forecasting-components/oil-spill-model (accessed on 20 November 2020).
  105. NOAA-ORR-ERD. Available online: https://github.com/NOAA-ORR-ERD (accessed on 5 November 2020).
  106. ADIOS Oil Database. Available online: https://adios-stage.orr.noaa.gov (accessed on 10 December 2020).
  107. GNOME Online Oceanographic Data Server. Available online: https://gnome.orr.noaa.gov/goods (accessed on 15 December 2020).
  108. North, E.W.; Adams, E.E.; Schlag, Z.; Sherwood, C.R.; He, R.; Hyun, K.H.; Socolofsky, S.A. Simulating oil droplet dispersal from the Deepwater Horizon spill with a Lagrangian approach. Geophys. Monogr. Ser 2011, 195, 217–226.
  109. Berry, A. Development of OILTRANS Model Code, Drift and Pollutants Behaviour Prediction ARCOPOL: The Atlantic Regions Coastal Pollution Response, Atlantic Area Transnational Programme, version 1.0; European Union: Brussels, Belgium, 2011; p. 24.
  110. Berry, A. OILTRANS: Oil Spill Modelling Software Application User Manual; European Union: Brussels, Belgium, 2012.
  111. Dulière, V.; Legrand, S.; Ovidio, F. Development of an Integrated Software for Forecasting the Impacts of Accidental Oil Pollution (OSERIT); Royal Belgian Institute of Natural Sciences: Brussels, Belgium, 2010.
  112. Fingas, M.F. Oil Spill Science and Technology: Prevention, 1st ed.; Gulf Professional Publishing: Amsterdam, The Netherlands, 2011; p. 1192.
  113. Jokuty, P.; Whiticar, S.; Wang, Z.; Fingas, M.; Fieldhouse, B.; Lambert, P.; Mullin, J.J.E.-O. Properties of Crude Oils and Oil Products; Environment Canada: Ottawa, ON, Canada, 1999.
  114. Sim, L.H. Blowout and Spill Occurrence Model; Oregon State University: Corvallis, OR, USA, 2013.
  115. Duran, R.; Romeo, L.; Whiting, J.; Vielma, J.; Rose, K.; Bunn, A.; Bauer, J. Simulation of the 2003 foss barge-point wells oil spill: A comparison between BLOSOM and GNOME oil spill models. J. Mar. Sci. Eng. 2018, 6, 104.
  116. Socolofsky, S.A.; Adams, E.E.; Boufadel, M.C.; Aman, Z.M.; Johansen, Ø.; Konkel, W.J.; Lindo, D.; Madsen, M.N.; North, E.W.; Paris, C.B. Intercomparison of oil spill prediction models for accidental blowout scenarios with and without subsea chemical dispersant injection. Mar. Pollut. Bull. 2015, 96, 110–126.
  117. Rye, H.; Brandvik, P.; Reed, M. Subsurface oil release field experiment-observations and modelling of subsurface plume behaviour. In Proceedings of the Arctic and Marine Oilspill Program Technical Seminar, Calgary, AB, Canada, 12–14 June 1996; pp. 1417–1436.
  118. Rye, H.; Brandvik, P.J. Verification of subsurface oil spill models. In Proceedings of the International Oil Spill Conference, Fort Lauderdale, FL, USA, 7–10 April 1997; pp. 551–557.
  119. Lehr, W.; Jones, R.; Evans, M.; Simecek-Beatty, D.; Overstreet, R. Revisions of the ADIOS oil spill model. Environ. Model. Softw. 2002, 17, 189–197.
  120. Deltares. D-WAQ PART, User Manual; Deltares: Delft, The Netherlands, 2018.
  121. Bi, H.; Si, H. Dynamic risk assessment of oil spill scenario for Three Gorges Reservoir in China based on numerical simulation. Saf. Sci. 2012, 50, 1112–1118.
  122. Wang, Y.; Zheng, X.; Yu, X.; Liu, X. Temperature and salinity effects in modeling the trajectory of the 2011 Penglai 19-3 oil spill. Mar. Georesour. Geotechnol. 2017, 35, 946–953.
  123. Rubinstein, R.Y.; Kroese, D.P. Simulation and the Monte Carlo Method; John Wiley & Sons: Hoboken, NJ, USA, 2016; Volume 10.
  124. Rubinstein, R. Simulation and the Monte Carlo Method; Wiley: New York, NY, USA, 1981.
  125. Mackay, D.; Paterson, S.; Trudel, K. A Mathematical Model of Oil Spill Behaviour. Report to Research and Development Division, Environment Emergency Branch, Environmental Impact Control Directorate; Environment Canada: Ottawa, ON, Canada, 1980.
  126. ASCE. State-of-the-art review of modeling transport and fate of oil spills. J. Hydraul. Eng. 1996, 122, 594–609.
  127. De Dominicis, M.; Leuzzi, G.; Monti, P.; Pinardi, N.; Poulain, P.-M. Eddy diffusivity derived from drifter data for dispersion model applications. Ocean Dyn. 2012, 62, 1381–1398.
  128. Ahlstrom, S. A Mathematical Model for Predicting the Transport of Oil Slicks in Marine Waters; Battelle, Pacific Northwest Laboratories: Richland, WA, USA, 1975.
  129. Hunter, J. The Application of Lagrangian Particle-Tracking Techniques to Modelling of Dispersion in The Sea. North Holl. Math. Stud. 1987, 145, 257–269.
  130. Hasselmann, K. On the spectral dissipation of ocean waves due to white capping. Bound. Layer Meteorol. 1974, 6, 107–127.
  131. Coppini, G.; De Dominicis, M.; Zodiatis, G.; Lardner, R.; Pinardi, N.; Santoleri, R.; Colella, S.; Bignami, F.; Hayes, D.R.; Soloviev, D. Hindcast of oil-spill pollution during the Lebanon crisis in the Eastern Mediterranean, July–August 2006. Mar. Pollut. Bull. 2011, 62, 140–153.
  132. Samaras, A.G.; De Dominicis, M.; Archetti, R.; Lamberti, A.; Pinardi, N. Towards improving the representation of beaching in oil spill models: A case study. Mar. Pollut. Bull. 2014, 88, 91–101.
  133. Rutherford, R.; Moulitsas, I.; Snow, B.J.; Kolios, A.J.; De Dominicis, M. CranSLIK v2. 0: Improving the stochastic prediction of oil spill transport and fate using approximation methods. Geosci. Model Dev. 2015, 8, 3365–3377.
  134. Liubartseva, S.; De Dominicis, M.; Oddo, P.; Coppini, G.; Pinardi, N.; Greggio, N. Oil spill hazard from dispersal of oil along shipping lanes in the Southern Adriatic and Northern Ionian Seas. Mar. Pollut. Bull. 2015, 90, 259–272.
  135. Liubartseva, S.; Smaoui, M.; Coppini, G.; Gonzalez, G.; Lecci, R.; Cretì, S.; Federico, I. Model-based reconstruction of the Ulysse-Virginia oil spill, October–November 2018. Mar. Pollut. Bull. 2020, 154, 111002.
  136. Coppini, G.; Dominicis, M.D.; Lyubartsev, V.; Gonzalez, G. MOON Emergency Response Office: Support to REMPEC for the management of oil spill emergencies at sea by providing monitoring and forecasting system products. In Proceedings of the Quaderno ARPA per il Secondo convegno Nazionale di Oceanografia Operativa, Cesenatico, Italy, 27–28 May 2010.
  137. REMPEC. Regional Marine Pollution Emergency Response Centre for the Mediterranean Sea (REMPEC). Available online: https://www.rempec.org/en (accessed on 5 February 2021).
  138. GitHub. OpenDrift. Available online: https://github.com/OpenDrift/opendrift/ (accessed on 5 February 2021).
  139. Hole, L.R.; Dagestad, K.-F.; Röhrs, J.; Wettre, C.; Kourafalou, V.H.; Androulidakis, I.; Le Hénaff, M.; Kang, H.; Garcia-Pineda, O. Revisiting the DeepWater Horizon spill: High resolution model simulations of effects of oil droplet size distribution and river fronts. Ocean Sci. Discuss. 2018.
  140. Hole, L.R.; Dagestad, K.-F.; Röhrs, J.; Wettre, C.; Kourafalou, V.H.; Androulidakis, Y.; Kang, H.; Le Hénaff, M.; Garcia-Pineda, O. The DeepWater Horizon Oil Slick: High Resolution Model Simulations of River Front Effects, Initialized and Verified by Satellite Observations. J. Mar. Sci. Eng. 2019, 7, 329.
  141. Jones, C.E.; Dagestad, K.F.; Breivik, Ø.; Holt, B.; Röhrs, J.; Christensen, K.H.; Espeseth, M.; Brekke, C.; Skrunes, S. Measurement and modeling of oil slick transport. J. Geophys. Res. Ocean. 2016, 121, 7759–7775.
  142. Li, C.; Miller, J.; Wang, J.; Koley, S.; Katz, J. Size distribution and dispersion of droplets generated by impingement of breaking waves on oil slicks. J. Geophys. Res. Ocean. 2017, 122, 7938–7957.
  143. Visser, A.W. Using random walk models to simulate the vertical distribution of particles in a turbulent water column. Mar. Ecol. Prog. Ser. 1997, 158, 275–281.
  144. Tkalich, P.; Chan, E.S. Vertical mixing of oil droplets by breaking waves. Mar. Pollut. Bull. 2002, 44, 1219–1229.
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