Probabilistic Risk Assessment and Decision Support Tools for the Evaluation of Oil Transport in the Gulf of Finland, North-Eastern Baltic Sea

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

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

Kuvaus

The maritime traffic in the Gulf of Finland (GoF), North-eastern Baltic
Sea, is predicted to rapidly grow in the near future, which increases the
environmental risks through both direct environmental effects and by increasing the risk of severe oil accident. A multidisciplinary group of researchers has developed a prototype of risk assessment and decision support model, applying Bayesian Networks (BNs), for the evaluation of environmental risks arising from the oil transport. It consists of sub-models on tanker collisions, causation probability (human factor), the resulting leak size, and the efficacy of open sea oil recovery. This meta-model is based on three alternative growth scenarios concerning the maritime traffic of the GoF in 2015 and the probability of a major oil accident given these conditions within four selected areas. The model can be used to compare the effectiveness of some preventive management actions and oil recovery against the accident risk. The multidisciplinary approach developed helps in comparing the risks in different parts of the oil accident cause – effect chain when current knowledge and uncertainty are taken into account. In addition, a user interface for the model has been created and tested for the analysis of spatial ecological risk arising from the oil transport in the GoF. A simplified version of the risk assessment
meta-model is used to calculate probabilistic oil accident scenarios. The resulting probability distributions are used as an input in Geographic Information System (GIS) -environment, where probabilistic oil drifting maps are calculated accordingly. In the end, these drift calculations are evaluated against information on the known occurrences of endangered species on the Finnish coastline and conservation value indexes related to them. This allows us to calculate and compare the total risk for endangered species given the conditions selected in the risk assessment meta-model. This approach provides an interesting, alternative viewpoint concerning the decisions on how and where the available risk management resources should be directed.

Keywords: Oil transport, Bayesian networks, Risk analysis, Decision support
Alkuperäiskielienglanti
OtsikkoManaging Resources of a Limited Planet : Pathways and Visions under Uncertainty
ToimittajatR. Seppelt, A. A. Voinov, S. Lange, D. Bankamp
Sivumäärä9
Julkaisupäivä2012
TilaJulkaistu - 2012
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
Tapahtuma6th International Congress on Environmental Modelling and Software (iEMSs) - Leipzig, Saksa
Kesto: 1 heinäkuuta 20125 heinäkuuta 2012
Konferenssinumero: 6

Lainaa tätä

Lehikoinen, A., Luoma, E., Hänninen, M., Storgård, J., & Kuikka, S. (2012). Probabilistic Risk Assessment and Decision Support Tools for the Evaluation of Oil Transport in the Gulf of Finland, North-Eastern Baltic Sea. teoksessa R. Seppelt, A. A. Voinov, S. Lange, & D. Bankamp (Toimittajat), Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty
Lehikoinen, Annukka ; Luoma, Emilia ; Hänninen, Maria ; Storgård, Jenni ; Kuikka, Sakari. / Probabilistic Risk Assessment and Decision Support Tools for the Evaluation of Oil Transport in the Gulf of Finland, North-Eastern Baltic Sea. Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty . Toimittaja / R. Seppelt ; A. A. Voinov ; S. Lange ; D. Bankamp. 2012.
@inproceedings{a14fb9a276d54cdb943acbc31f38fa56,
title = "Probabilistic Risk Assessment and Decision Support Tools for the Evaluation of Oil Transport in the Gulf of Finland, North-Eastern Baltic Sea",
abstract = "The maritime traffic in the Gulf of Finland (GoF), North-eastern BalticSea, is predicted to rapidly grow in the near future, which increases theenvironmental risks through both direct environmental effects and by increasing the risk of severe oil accident. A multidisciplinary group of researchers has developed a prototype of risk assessment and decision support model, applying Bayesian Networks (BNs), for the evaluation of environmental risks arising from the oil transport. It consists of sub-models on tanker collisions, causation probability (human factor), the resulting leak size, and the efficacy of open sea oil recovery. This meta-model is based on three alternative growth scenarios concerning the maritime traffic of the GoF in 2015 and the probability of a major oil accident given these conditions within four selected areas. The model can be used to compare the effectiveness of some preventive management actions and oil recovery against the accident risk. The multidisciplinary approach developed helps in comparing the risks in different parts of the oil accident cause – effect chain when current knowledge and uncertainty are taken into account. In addition, a user interface for the model has been created and tested for the analysis of spatial ecological risk arising from the oil transport in the GoF. A simplified version of the risk assessmentmeta-model is used to calculate probabilistic oil accident scenarios. The resulting probability distributions are used as an input in Geographic Information System (GIS) -environment, where probabilistic oil drifting maps are calculated accordingly. In the end, these drift calculations are evaluated against information on the known occurrences of endangered species on the Finnish coastline and conservation value indexes related to them. This allows us to calculate and compare the total risk for endangered species given the conditions selected in the risk assessment meta-model. This approach provides an interesting, alternative viewpoint concerning the decisions on how and where the available risk management resources should be directed.Keywords: Oil transport, Bayesian networks, Risk analysis, Decision support",
author = "Annukka Lehikoinen and Emilia Luoma and Maria H{\"a}nninen and Jenni Storg{\aa}rd and Sakari Kuikka",
note = "Volume: Proceeding volume:",
year = "2012",
language = "English",
editor = "R. Seppelt and Voinov, {A. A.} and S. Lange and D. Bankamp",
booktitle = "Managing Resources of a Limited Planet",

}

Lehikoinen, A, Luoma, E, Hänninen, M, Storgård, J & Kuikka, S 2012, Probabilistic Risk Assessment and Decision Support Tools for the Evaluation of Oil Transport in the Gulf of Finland, North-Eastern Baltic Sea. julkaisussa R Seppelt, AA Voinov, S Lange & D Bankamp (toim), Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty . 6th International Congress on Environmental Modelling and Software (iEMSs), Leipzig, Saksa, 01/07/2012.

Probabilistic Risk Assessment and Decision Support Tools for the Evaluation of Oil Transport in the Gulf of Finland, North-Eastern Baltic Sea. / Lehikoinen, Annukka; Luoma, Emilia; Hänninen, Maria; Storgård, Jenni; Kuikka, Sakari.

Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty . toim. / R. Seppelt; A. A. Voinov; S. Lange; D. Bankamp. 2012.

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

TY - GEN

T1 - Probabilistic Risk Assessment and Decision Support Tools for the Evaluation of Oil Transport in the Gulf of Finland, North-Eastern Baltic Sea

AU - Lehikoinen, Annukka

AU - Luoma, Emilia

AU - Hänninen, Maria

AU - Storgård, Jenni

AU - Kuikka, Sakari

N1 - Volume: Proceeding volume:

PY - 2012

Y1 - 2012

N2 - The maritime traffic in the Gulf of Finland (GoF), North-eastern BalticSea, is predicted to rapidly grow in the near future, which increases theenvironmental risks through both direct environmental effects and by increasing the risk of severe oil accident. A multidisciplinary group of researchers has developed a prototype of risk assessment and decision support model, applying Bayesian Networks (BNs), for the evaluation of environmental risks arising from the oil transport. It consists of sub-models on tanker collisions, causation probability (human factor), the resulting leak size, and the efficacy of open sea oil recovery. This meta-model is based on three alternative growth scenarios concerning the maritime traffic of the GoF in 2015 and the probability of a major oil accident given these conditions within four selected areas. The model can be used to compare the effectiveness of some preventive management actions and oil recovery against the accident risk. The multidisciplinary approach developed helps in comparing the risks in different parts of the oil accident cause – effect chain when current knowledge and uncertainty are taken into account. In addition, a user interface for the model has been created and tested for the analysis of spatial ecological risk arising from the oil transport in the GoF. A simplified version of the risk assessmentmeta-model is used to calculate probabilistic oil accident scenarios. The resulting probability distributions are used as an input in Geographic Information System (GIS) -environment, where probabilistic oil drifting maps are calculated accordingly. In the end, these drift calculations are evaluated against information on the known occurrences of endangered species on the Finnish coastline and conservation value indexes related to them. This allows us to calculate and compare the total risk for endangered species given the conditions selected in the risk assessment meta-model. This approach provides an interesting, alternative viewpoint concerning the decisions on how and where the available risk management resources should be directed.Keywords: Oil transport, Bayesian networks, Risk analysis, Decision support

AB - The maritime traffic in the Gulf of Finland (GoF), North-eastern BalticSea, is predicted to rapidly grow in the near future, which increases theenvironmental risks through both direct environmental effects and by increasing the risk of severe oil accident. A multidisciplinary group of researchers has developed a prototype of risk assessment and decision support model, applying Bayesian Networks (BNs), for the evaluation of environmental risks arising from the oil transport. It consists of sub-models on tanker collisions, causation probability (human factor), the resulting leak size, and the efficacy of open sea oil recovery. This meta-model is based on three alternative growth scenarios concerning the maritime traffic of the GoF in 2015 and the probability of a major oil accident given these conditions within four selected areas. The model can be used to compare the effectiveness of some preventive management actions and oil recovery against the accident risk. The multidisciplinary approach developed helps in comparing the risks in different parts of the oil accident cause – effect chain when current knowledge and uncertainty are taken into account. In addition, a user interface for the model has been created and tested for the analysis of spatial ecological risk arising from the oil transport in the GoF. A simplified version of the risk assessmentmeta-model is used to calculate probabilistic oil accident scenarios. The resulting probability distributions are used as an input in Geographic Information System (GIS) -environment, where probabilistic oil drifting maps are calculated accordingly. In the end, these drift calculations are evaluated against information on the known occurrences of endangered species on the Finnish coastline and conservation value indexes related to them. This allows us to calculate and compare the total risk for endangered species given the conditions selected in the risk assessment meta-model. This approach provides an interesting, alternative viewpoint concerning the decisions on how and where the available risk management resources should be directed.Keywords: Oil transport, Bayesian networks, Risk analysis, Decision support

M3 - Conference contribution

BT - Managing Resources of a Limited Planet

A2 - Seppelt, R.

A2 - Voinov, A. A.

A2 - Lange, S.

A2 - Bankamp, D.

ER -

Lehikoinen A, Luoma E, Hänninen M, Storgård J, Kuikka S. Probabilistic Risk Assessment and Decision Support Tools for the Evaluation of Oil Transport in the Gulf of Finland, North-Eastern Baltic Sea. julkaisussa Seppelt R, Voinov AA, Lange S, Bankamp D, toimittajat, Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty . 2012