Abstract
The maritime traffic in the Gulf of Finland (GoF) is predicted to rapidly grow in the near future, which increases environmental risks through both direct environmental effects and by increasing the accident risk. Increasing oil transportation has increased the probability of a major oil accident in the GoF.
A multidisciplinary risk assessment and decision support tool, an Object-Oriented Bayesian Influence Diagram (OOBID) applying Bayesian Belief Networks, has been produced in the SAFGOF project. It consists of sub-models on collisions, causation probability including human factor, the resulting leak size, and the efficacy of open sea oil recovery. The OOBID is based on varying growth predictions, i.e. three alternative scenarios concerning maritime traffic of the GoF in 2015 and the probability of a major oil accident. The OOBID can be used to compare the effectiveness of different preventive management actions against the accident risk.
A questionnaire for Finnish maritime experts was formed in the project to study the effectiveness of different maritime safety policy instruments. Vessel Traffic Services and piloting were seen as the most important actions according to Finnish maritime experts. These actions are included in the metamodel as preventive management actions.
In addition, a user interface for the model has been developed for the evaluation of spatial ecological risks. The results of the Bayesian Belief Network can be combined with oil drifting maps and with the information on known endangered species populations on the Finnish coastline. The approach produces unique information on the environmental oil accident risks for certain accident-prone areas in the GoF.
The multidisciplinary approach developed in the SAFGOF project helps to compare the risks in the different parts of the oil accident cause – effect chain when current knowledge and uncertainty are taken into account.
Keywords: Maritime safety, Gulf of Finland, Bayesian belief networks, Decision analysis
A multidisciplinary risk assessment and decision support tool, an Object-Oriented Bayesian Influence Diagram (OOBID) applying Bayesian Belief Networks, has been produced in the SAFGOF project. It consists of sub-models on collisions, causation probability including human factor, the resulting leak size, and the efficacy of open sea oil recovery. The OOBID is based on varying growth predictions, i.e. three alternative scenarios concerning maritime traffic of the GoF in 2015 and the probability of a major oil accident. The OOBID can be used to compare the effectiveness of different preventive management actions against the accident risk.
A questionnaire for Finnish maritime experts was formed in the project to study the effectiveness of different maritime safety policy instruments. Vessel Traffic Services and piloting were seen as the most important actions according to Finnish maritime experts. These actions are included in the metamodel as preventive management actions.
In addition, a user interface for the model has been developed for the evaluation of spatial ecological risks. The results of the Bayesian Belief Network can be combined with oil drifting maps and with the information on known endangered species populations on the Finnish coastline. The approach produces unique information on the environmental oil accident risks for certain accident-prone areas in the GoF.
The multidisciplinary approach developed in the SAFGOF project helps to compare the risks in the different parts of the oil accident cause – effect chain when current knowledge and uncertainty are taken into account.
Keywords: Maritime safety, Gulf of Finland, Bayesian belief networks, Decision analysis
| Original language | English |
|---|---|
| Title of host publication | 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012 (PSAM11 ESREL 2012) : Proceedings of a meeting held 25-29 June 2012, Helsinki, Finland. |
| Number of pages | 8 |
| Publication date | 2012 |
| Pages | 5528-5535 |
| ISBN (Print) | 9781622764365 |
| Publication status | Published - 2012 |
| MoE publication type | A4 Article in conference proceedings |
| Event | 11th International Probabilistic Safety Assessment and Management Conference - Helsinki, Finland Duration: 25 Jun 2012 → 29 Jun 2012 |
Fields of Science
- 1172 Environmental sciences