A bayesian network for assessing the collision induced risk of an oil accident in the gulf of Finland

Annukka Lehikoinen, Maria Hänninen, Jenni Storgård, Emilia Luoma, Samu Mäntyniemi, Sakari Kuikka

Research output: Contribution to journalArticleScientificpeer-review

29 Citations (Scopus)

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 multidisciplinary 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 4-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.

Original languageEnglish
Pages (from-to)5301-5309
Number of pages9
JournalEnvironmental Science and Technology
Volume49
Issue number9
DOIs
Publication statusPublished - 5 May 2015
MoE publication typeA1 Journal article-refereed

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