A Bayesian network for assessing the collision induced risk of an oil accident in the Gulf of Finland

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http://hdl.handle.net/10138/224454

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Lehikoinen , A , Hänninen , M , Storgård , J , Luoma , E , Mäntyniemi , S & Kuikka , S 2015 , ' A Bayesian network for assessing the collision induced risk of an oil accident in the Gulf of Finland ' , Environmental Science & Technology , vol. 49 , no. 9 , pp. 5301–5309 . https://doi.org/10.1021/es501777g

Title: A Bayesian network for assessing the collision induced risk of an oil accident in the Gulf of Finland
Author: Lehikoinen, Annukka; Hänninen, Maria; Storgård, Jenni; Luoma, Emilia; Mäntyniemi, Samu; Kuikka, Sakari
Contributor: University of Helsinki, Environmental Sciences
University of Helsinki, Environmental Sciences
University of Helsinki, Environmental Sciences
University of Helsinki, Environmental Sciences
Date: 2015
Language: eng
Belongs to series: Environmental Science & Technology
ISSN: 0013-936X
URI: http://hdl.handle.net/10138/224454
Abstract: The growth of maritime oil transportation in the Gulf of Finland (GoF), North-Eastern Baltic Sea, increases environmental risks by increasing the probability of oil accidents. By integrating the work of a multi-disciplinary research team and information from several sources, we have developed a probabilistic risk assessment application that considers the likely future development of maritime traffic and oil transportation in the area and the resulting risk of environmental pollution. This metamodel is used to compare the effects of two preventative management actions on the tanker collision probabilities and the consequent risk. The resulting risk is evaluated from four different perspectives. Bayesian networks enable large amounts of information about causalities to be integrated and utilized in probabilistic inference. Compared with the baseline period of 2007-2008, the worst-case scenario is that the risk level increases four-fold by the year 2015. The management measures are evaluated and found to decrease the risk by 4–13%, but the utility gained by their joint implementation would be less than the sum of their independent effects. In addition to the results concerning the varying risk levels, the application provides interesting information about the relationships between the different elements of the system.
Subject: 1172 Environmental sciences
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