Implementing Bayesian networks for ISO 31000:2018-based maritime oil spill risk management: State-of-art, implementation benefits and challenges, and future research directions

JOURNAL OF ENVIRONMENTAL MANAGEMENT

卷:278

Article

Parviainen, Tuuli^1,2,3,4  Goerlandt, Floris^5,6  Helle, Inari^3,7  Haapasaari, Paivi^1,4  Kuikka, Sakari^2,4 

[1] Univ Helsinki, Fac Biol & Environm Sci, Marine Risk Governance Grp, Ecosyst & Environm Res Programme, POB 65,Viikinkaari 1, FI-00014 Helsinki, Finland

[2] Univ Helsinki, Fac Biol & Environm Sci, Fisheries & Environm Management Grp, Ecosyst & Environm Res Programme, POB 65,Viikinkaari 1, FI-00014 Helsinki, Finland

[3] Helsinki Inst Sustainabil Sci HELSUS, Porthania 2nd Floor,Yliopistonkatu 3, FI-00014 Helsinki, Finland

[4] Kotka Maritime Res Ctr, Keskuskatu 7, FI-48100 Kotka, Finland

[5] Aalto Univ, Dept Mech Engn, Marine Technol, POB 15300, FI-00076 Aalto, Finland

[6] Dalhousie Univ, Dept Ind Engn, Halifax, NS B3H 4R2, Canada

[7] Univ Helsinki, Environm & Ecol Stat Grp, Organismal & Evolutionary Biol Res Programme, Fac Biol & Environm Sci, POB 65,Viikinkaari 1, FI-00014 Helsinki, Finland

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

DOI  :  10.1016/j.jenvman.2020.111520

来源: Elsevier

【 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.

【 授权许可】

Free