Fisheries and Environmental Management Group, Department of Environmental Sciences, University of Helsinki, PO Box 65, FI-00014 University of Helsinki, Helsinki, Finland.
J Hazard Mater. 2011 Jan 15;185(1):182-92. doi: 10.1016/j.jhazmat.2010.09.017. Epub 2010 Sep 17.
Maritime traffic poses a major threat to marine ecosystems in the form of oil spills. The Gulf of Finland, the easternmost part of the Baltic Sea, has witnessed a rapid increase in oil transportation during the last 15 years. Should a spill occur, the negative ecological impacts may be reduced by oil combating, the effectiveness of which is, however, strongly dependent on prevailing environmental conditions and available technical resources. This poses increased uncertainty related to ecological consequences of future spills. We developed a probabilistic Bayesian network model that can be used to assess the effectiveness of different oil combating strategies in minimizing the negative effects of oil on six species living in the Gulf of Finland. The model can be used for creating different accident scenarios and assessing the performance of various oil combating actions under uncertainty, which enables its use as a supportive tool in decision-making. While the model is confined to the western Gulf of Finland, the methodology is adaptable to other marine areas facing similar risks and challenges related to oil spills.
海上交通以溢油的形式对海洋生态系统构成了重大威胁。波罗的海最东部的芬兰湾在过去 15 年见证了石油运输的快速增长。如果发生溢油事件，可以通过油污清除来减少对生态的负面影响，但其有效性在很大程度上取决于环境条件和可用的技术资源。这增加了与未来溢油相关的生态后果的不确定性。我们开发了一个概率贝叶斯网络模型，可以用来评估不同的油污清除策略在最大限度地减少对生活在芬兰湾的六种物种的负面影响方面的有效性。该模型可用于创建不同的事故场景，并在不确定性下评估各种油污清除行动的表现，从而使其成为决策支持工具。虽然该模型仅限于芬兰湾西部，但该方法适用于面临类似溢油风险和挑战的其他海洋区域。
