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首页> 外文期刊>Journal of Environmental Management >Implementing Bayesian networks for ISO 31000:2018-based maritime oil spill risk management: State-of-art, implementation benefits and challenges, and future research directions
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Implementing Bayesian networks for ISO 31000:2018-based maritime oil spill risk management: State-of-art, implementation benefits and challenges, and future research directions

机译：实施贝叶斯网络ISO 31000：2018年的海上漏油风险管理：最先进的，实施福利和挑战，以及未来的研究方向

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摘要

The risk of a large-scale oil spill remains significant in marine environments as international maritime transport continues to grow. The environmental as well as the socio-economic impacts of a large-scale oil spill could be substantial. Oil spill models and modeling tools for Pollution Preparedness and Response (PPR) can support effective risk management. However, there is a lack of integrated approaches that consider oil spill risks comprehensively, learn from all information sources, and treat the system uncertainties in an explicit manner. Recently, the use of the international ISO 31000:2018 risk management framework has been suggested as a suitable basis for supporting oil spill PPR risk management. Bayesian networks (BNs) are graphical models that express uncertainty in a probabilistic form and can thus support decision-making processes when risks are complex and data are scarce. While BNs have increasingly been used for oil spill risk assessment (OSRA) for PPR, no link between the BNs literature and the ISO 31000:2018 framework has previously been made. This study explores how Bayesian risk models can be aligned with the ISO 31000:2018 framework by offering a flexible approach to integrate various sources of probabilistic knowledge. In order to gain insight in the current utilization of BNs for oil spill risk assessment and management (OSRA-BNs) for maritime oil spill preparedness and response, a literature review was performed. The review focused on articles presenting BN models that analyze the occurrence of oil spills, consequence mitigation in terms of offshore and shoreline oil spill response, and impacts of spills on the variables of interest. Based on the results, the study discusses the benefits of applying BNs to the ISO 31000:2018 framework as well as the challenges and further research needs.
机译：随着国际海运的持续发展，海洋环境中，大规模漏油的风险仍然很大。环境以及大规模漏油泄漏的社会经济影响可能很大。污水泄漏模型和用于污染准备和反应的建模工具（PPR）可以支持有效的风险管理。然而，缺乏综合方法，可以全面地考虑石油泄漏风险，从所有信息来源学习，并以明确的方式对系统不确定性进行治疗。最近，使用国际ISO 31000：2018年风险管理框架被建议为支持石油泄漏PPR风险管理的合适依据。贝叶斯网络（BNS）是表达概率形式的不确定性的图形模型，因此可以在风险复杂并且数据稀缺时支持决策过程。虽然BDS越来越多地用于PPR的石油泄漏风险评估（OSRA），但先前没有BNS文献与ISO 31000：2018框架之间的联系。本研究探讨了贝叶斯风险模型如何与ISO 31000：2018框架对齐，通过提供灵活的方法来整合各种概率知识来源。为了进入目前利用BNS的漏洞风险评估和管理（OSRA-BNS）进行海上溢油的准备和反应，进行了文献综述。该审查侧重于呈现BN模型的文章，分析了溢油的发生，在海上和海岸线油溢出的反应方面的发生，以及溢出对兴趣变量的影响。根据结果​​，该研究讨论了将BNS应用于ISO 31000：2018框架以及挑战和进一步研究需求的好处。

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  • 来源
    《Journal of Environmental Management》 |2021年第1期|111520.1-111520.13|共13页
  • 作者

    Tuuli Parviainen; Floris Goerlandt; Inari Helle; Paeivi Haapasaari; Sakari Kuikka;

  • 作者单位

    University of Helsinki Marine Risk Governance Group Ecosystems and Environment Research Programme Faculty of Biological and Environmental Sciences P.O Box 65 Viikinkaari 1 FI-00014 University of Helsinki Finland University of Helsinki Fisheries and Environmental Management Group Ecosystems and Environment Research Programme Faculty of Biological and Environmental Sciences P.O Box 65 Viikinkaari 1 FI-00014 University of Helsinki Finland Helsinki Institute of Sustainability Science (HELSUS) Porthania (2nd Floor) Yliopistonkatu 3 FI-00014 University of Helsinki Finland Kotka Maritime Research Centre Keskuskatu 7 FI-48100 Kotka Finland;

    Aalto University Department of Mechanical Engineering Marine Technology P.O. Box 15300 FI-00076 Aalto Finland Dalhousie University Department of Industrial Engineering Halifax Nova Scotia B3H 4R2 Canada;

    Helsinki Institute of Sustainability Science (HELSUS) Porthania (2nd Floor) Yliopistonkatu 3 FI-00014 University of Helsinki Finland University of Helsinki Environmental and Ecological Statistics Group Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences P.O Box 65 Viikinkaari 1 FI-00014 University of Helsinki Finland;

    University of Helsinki Marine Risk Governance Group Ecosystems and Environment Research Programme Faculty of Biological and Environmental Sciences P.O Box 65 Viikinkaari 1 FI-00014 University of Helsinki Finland Kotka Maritime Research Centre Keskuskatu 7 FI-48100 Kotka Finland;

    University of Helsinki Fisheries and Environmental Management Group Ecosystems and Environment Research Programme Faculty of Biological and Environmental Sciences P.O Box 65 Viikinkaari 1 FI-00014 University of Helsinki Finland Kotka Maritime Research Centre Keskuskatu 7 FI-48100 Kotka Finland;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Oil spills; Pollution preparedness and response; Bayesian networks; Uncertainty; Risk management; ISO 31000:2018;

    机译：漏油;污染准备和反应;贝叶斯网络;不确定;风险管理;ISO 31000：2018;

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