Bayesian inference-based environmental decision support systems for oil spill response strategy selection.

Contingency plans are essential in guiding the response to marine oil spills. However, they are written before the pollution event occurs so must contain some degree of assumption and prediction and hence may be unsuitable for a real incident when it occurs. The use of Bayesian networks in ecology, environmental management, oil spill contingency planning and post-incident analysis is reviewed and analysed to establish their suitability for use as real-time environmental decision support systems during an oil spill response. It is demonstrated that Bayesian networks are appropriate for facilitating the re-assessment and re-validation of contingency plans following pollutant release, thus helping ensure that the optimum response strategy is adopted. This can minimise the possibility of sub-optimal response strategies causing additional environmental and socioeconomic damage beyond the original pollution event.

[1]  D. Doak,et al.  Long-term impacts of the Exxon Valdez oil spill on sea otters, assessed through age-dependent mortality patterns. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Kim A Anderson,et al.  Impact of the deepwater horizon oil spill on bioavailable polycyclic aromatic hydrocarbons in Gulf of Mexico coastal waters. , 2012, Environmental science & technology.

[3]  Rafael Rumí,et al.  Bayesian networks in environmental modelling , 2011, Environ. Model. Softw..

[4]  Peter A. Vanrolleghem,et al.  Uncertainty in the environmental modelling process - A framework and guidance , 2007, Environ. Model. Softw..

[5]  B. Marcot,et al.  Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement , 2001 .

[6]  Colin M Beale,et al.  Revealing ecological networks using Bayesian network inference algorithms. , 2010, Ecology.

[7]  Emilio Benfenati,et al.  Predicting toxicity through computers: a changing world , 2007, Chemistry Central journal.

[8]  R. Moss,et al.  Ecosystems and human well-being: a framework for assessment , 2003 .

[9]  Robert Aps,et al.  Bayesian Inference For Predicting PotentialOil Spill Related Ecological Risk , 2009 .

[10]  Carlo Giupponi,et al.  Environmental decision support systems: Current issues, methods and tools , 2007, Environ. Model. Softw..

[11]  N Jayasuriya,et al.  A Bayesian network model to assess the public health risk associated with wet weather sewer overflows discharging into waterways. , 2012, Water research.

[12]  Glenn W Suter,et al.  A Framework for Net Environmental Benefit Analysis for Remediation or Restoration of Contaminated Sites , 2004, Environmental management.

[13]  Kathy J. Kuletz,et al.  Population, reproduction and foraging of pigeon guillemots at Naked Island, Alaska, before and after the Exxon Valdez oil spill. Bird study number 9. Exxon Valdez oil spill state/federal natural resource damage assessment final report , 1994 .

[14]  Ralf Denzer,et al.  Generic integration of environmental decision support systems - state-of-the-art , 2005, Environ. Model. Softw..

[15]  Aaron M. Ellison,et al.  Bayesian inference in ecology , 2004 .

[16]  A. Romero,et al.  Integrated assessment for establishing an oil environmental vulnerability map: case study for the Santos Basin region, Brazil. , 2013, Marine pollution bulletin.

[17]  Jenifer M. Baker,et al.  NET ENVIRONMENTAL BENEFIT ANALYSIS FOR OIL SPILL RESPONSE , 1995 .

[18]  Peter Reichert,et al.  On the usefulness of overparameterized ecological models , 1997 .

[19]  J. Meador,et al.  A Perspective on the Toxicity of Petrogenic PAHs to Developing Fish Embryos Related to Environmental Chemistry , 2009 .

[20]  Laura Uusitalo,et al.  Advantages and challenges of Bayesian networks in environmental modelling , 2007 .

[21]  P. Kujala,et al.  A probabilistic model estimating oil spill clean-up costs--a case study for the Gulf of Finland. , 2013, Marine pollution bulletin.

[22]  John F Carriger,et al.  Minimizing risks from spilled oil to ecosystem services using influence diagrams: the Deepwater Horizon spill response. , 2011, Environmental science & technology.

[23]  Robert Aps,et al.  Bayesian Inference For Oil Spill RelatedNet Environmental Benefit Analysis , 2009 .

[24]  Miquel Sànchez-Marrè,et al.  Designing and building real environmental decision support systems , 2004, Environ. Model. Softw..

[25]  Hannes Werthner,et al.  Environmental decision support systems , 1989 .

[26]  Anthony J. Jakeman,et al.  Ten iterative steps in development and evaluation of environmental models , 2006, Environ. Model. Softw..

[27]  Finn Verner Jensen,et al.  Public participation modelling using Bayesian networks in management of groundwater contamination , 2007, Environ. Model. Softw..

[28]  B. Marcot,et al.  Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation , 2006 .

[29]  D. Monson,et al.  Long-term effects of the Exxon Valdez oil spill: sea otter foraging in the intertidal as a pathway of exposure to lingering oil , 2012 .

[30]  Roderick H. Downie,et al.  The International Convention for the Prevention of Pollution from Ships (MARPOL) , 2007 .

[31]  W. Koops,et al.  Net Environmental - Economic Benefit Analysis Model , 2003 .

[32]  M. Fingas.  The Basics of Oil Spill Cleanup, Second Edition , 2000 .

[33]  J. Baker.  Ecological Effectiveness of Oil Spill Countermeasures: How Clean is Clean? , 1999 .

[34]  J. Cain.  Planning improvements in natural resource management. Guidelines for using Bayesian networks to support the planning and management of development programmes in the water sector and beyond , 2001 .

[35]  Anders L. Madsen,et al.  Probabilistic Networks - An Introduction to Bayesian Networks and Influence Diagrams , 2005 .

[36]  Kevin B. Korb,et al.  Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment , 2007, Environ. Model. Softw..

[37]  Barbara Champ Michael A. Ornitz.  Oil spills first principles: prevention and best response , 2002 .

[38]  Fabio Colombo,et al.  Incorporating Ecosystem Service Valuation in the Assessment of Risk and Remedy Implementation , 2012 .

[39]  B. Marcot,et al.  Bayesian belief networks: applications in ecology and natural resource management , 2006 .

[40]  Carlos Alberto Brebbia,et al.  Bayesian inference for predicting ecological water quality under different climate change scenarios. , 2009 .

[41]  G. Claireaux,et al.  Effects of oil exposure and dispersant use upon environmental adaptation performance and fitness in the European sea bass, Dicentrarchus labrax. , 2013, Aquatic toxicology.

[42]  Andrea Emilio Rizzoli,et al.  Delivering environmental decision support systems: Software tools and techniques , 1997 .

[43]  A. Murk,et al.  Weathering and toxicity of marine sediments contaminated with oils and polycyclic aromatic hydrocarbons , 2006, Environmental toxicology and chemistry.

[44]  Konstantinos I. Vatalis,et al.  Assessing the Risk of Soil Pollution around an Industrialized Mining Region Using a Geostatistical Approach , 2014 .

[45]  Serena H. Chen,et al.  Good practice in Bayesian network modelling , 2012, Environ. Model. Softw..

[46]  Hassan A. Karimi,et al.  Coupling methodologies for environmental models , 2000, Environ. Model. Softw..