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

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

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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.
Alkuperäiskielienglanti
LehtiEnvironmental Science & Technology
Vuosikerta49
Numero9
Sivut5301–5309
ISSN0013-936X
DOI - pysyväislinkit
TilaJulkaistu - 2015
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä, vertaisarvioitu

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title = "A Bayesian network for assessing the collision induced risk of an oil accident in the Gulf of Finland",
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.",
keywords = "1172 Environmental sciences",
author = "Annukka Lehikoinen and Maria H{\"a}nninen and Jenni Storg{\aa}rd and Emilia Luoma and Samu M{\"a}ntyniemi and Sakari Kuikka",
year = "2015",
doi = "10.1021/es501777g",
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journal = "Environmental Science & Technology",
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publisher = "American Chemical Society",
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A Bayesian network for assessing the collision induced risk of an oil accident in the Gulf of Finland. / Lehikoinen, Annukka; Hänninen, Maria; Storgård, Jenni; Luoma, Emilia; Mäntyniemi, Samu; Kuikka, Sakari.

julkaisussa: Environmental Science & Technology, Vuosikerta 49, Nro 9, 2015, s. 5301–5309.

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinenvertaisarvioitu

TY - JOUR

T1 - A Bayesian network for assessing the collision induced risk of an oil accident in the Gulf of Finland

AU - Lehikoinen, Annukka

AU - Hänninen, Maria

AU - Storgård, Jenni

AU - Luoma, Emilia

AU - Mäntyniemi, Samu

AU - Kuikka, Sakari

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - 1172 Environmental sciences

U2 - 10.1021/es501777g

DO - 10.1021/es501777g

M3 - Article

VL - 49

SP - 5301

EP - 5309

JO - Environmental Science & Technology

JF - Environmental Science & Technology

SN - 0013-936X

IS - 9

ER -