Fisheries and Environmental Management Group, Department of Environmental Sciences, University of Helsinki, Kotka Maritime Research Center, Heikinkatu 7, FI-48100 Kotka, Finland.
Environ Sci Technol. 2013 Feb 19;47(4):1792-9. doi: 10.1021/es303634f. Epub 2013 Feb 7.
Oil transport has greatly increased in the Gulf of Finland over the years, and risks of an oil accident occurring have risen. Thus, an effective oil combating strategy is needed. We developed a Bayesian Network (BN) to examine the recovery efficiency and optimal disposition of the Finnish oil combating vessels in the Gulf of Finland (GoF), Eastern Baltic Sea. Four alternative home harbors, five accident points, and ten oil combating vessels were included in the model to find the optimal disposition policy that would maximize the recovery efficiency. With this composition, the placement of the oil combating vessels seems not to have a significant effect on the recovery efficiency. The process seems to be strongly controlled by certain random factors independent of human action, e.g. wave height and stranding time of the oil. Therefore, the success of oil combating is rather uncertain, so it is also important to develop activities that aim for preventing accidents. We found that the model developed is suitable for this type of multidecision optimization. The methodology, results, and practices are further discussed.
多年来，芬兰湾的石油运输量大幅增加，发生石油事故的风险也有所上升。因此，需要制定一项有效的石油应对策略。我们开发了一个贝叶斯网络（BN）来研究芬兰在波罗的海东部的芬兰湾（GoF）石油应对船只的回收效率和最佳配置。该模型纳入了四个备用母港、五个事故点和十艘石油应对船只，以找到能够最大程度提高回收效率的最佳配置策略。有了这样的组成，石油应对船只的布置似乎对回收效率没有显著影响。该过程似乎受到某些与人类行为无关的随机因素的强烈控制，例如海浪高度和油的搁浅时间。因此，石油应对的成功是相当不确定的，因此开发旨在预防事故的活动也很重要。我们发现，所开发的模型适用于这种多决策优化。进一步讨论了该方法、结果和实践。
