†Department of Environmental Sciences, Fisheries and Environmental Management Group, Kotka Maritime Research Center, University of Helsinki, Keskuskatu 10, FI-48100 Kotka, Finland.
‡School of Engineering, Department of Applied Mechanics, Kotka Maritime Research Centre, Aalto University, Keskuskatu 10, FI-48100 Kotka, Finland.
Environ Sci Technol. 2015 May 5;49(9):5301-9. doi: 10.1021/es501777g. Epub 2015 Apr 14.
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.
波罗的海东北部的芬兰湾（GoF）的海上石油运输量不断增长，增加了石油事故发生的可能性，从而增加了环境风险。通过整合多学科研究团队的工作和来自多个来源的信息，我们开发了一种概率风险评估应用程序，该程序考虑了该地区未来海上交通和石油运输的可能发展以及由此产生的环境污染风险。该变精度模型用于比较两种预防性管理措施对油轮碰撞概率和由此产生的风险的影响。从四个不同角度评估了由此产生的风险。贝叶斯网络可以集成和利用大量有关因果关系的信息进行概率推理。与 2007-2008 年的基线期相比，到 2015 年，风险水平增加了 4 倍，达到最坏情况。对管理措施进行了评估，发现这些措施可将风险降低 4%至 13%，但它们联合实施带来的效用将低于各自独立实施的效果之和。除了有关不同风险水平的结果外，该应用程序还提供了有关系统不同要素之间关系的有趣信息。
