A Bayesian Network Risk Model for Oil Spill Response Effectiveness in the Canadian Arctic (OSRECA)

Throughout the years, there has been an increase in various marine-related activities in the Arctic due to globalization. These include shipping activities, tourism, fisheries, research, mining, and offshore oil drilling. Such actions can lead to potential oil spills, the risk of which has been an i...

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Bibliographic Details
Main Author: Al Sharkawi, Talah
Other Authors: Department of Industrial Engineering, Master of Applied Science, n/a, Dr. John Blake, Dr. Ron Pelot, Dr. Hamid Afshari, Dr. Haibo Niu, Dr. Floris Goerlandt, Received, Not Applicable
Language:English
Published: 2022
Subjects:
Online Access:http://hdl.handle.net/10222/82186
Description
Summary:Throughout the years, there has been an increase in various marine-related activities in the Arctic due to globalization. These include shipping activities, tourism, fisheries, research, mining, and offshore oil drilling. Such actions can lead to potential oil spills, the risk of which has been an increasing concern. When focusing on potential oil spills from shipping activities alone, they can have serious negative consequences to marine ecosystems, lead to important economic costs, and have widespread socio-economic, cultural and health impacts. Therefore, determining the efficiency of oil spill responses will help mitigate some of these negative consequences. To do this, a sub-model needs to be created as an analysis support where different spill types, clean-up technologies, human and environmental conditions are considered. By creating a model, one can tell what a system is doing under certain conditions and the factors and relationships that bring about this behaviour. As such, developing a model for emergency response planning for oil spill incidents has a lot of complexity and uncertainty as there are various variables needed to be considered. Some variables include oil spill location, oil spill incidents, and oil spill size. A Bayesian Network Model is used to aid in understanding the effectiveness of oil spill responses for various scenarios in the Canadian Arctic. While the proposed model can be used as a basis for exploring response effectiveness, adequate attention to the strength of evidence on which the model is built is required. Hence, a strength of evidence, sensitivity analysis, and criticality matrix supplements the risk model, to provide information on the sensitivity of the effectiveness of the sub-models and the evidence on which the model is based. This thesis has aimed to generate a Bayesian Network model to provide insights in oil spill response processes, focused on the effectiveness of different response operations in selected conditions. After the OSRECA model was developed using an ...