A fault tree model to assess probability of contaminant discharge from shipwrecks
Journal article, 2014

Shipwrecks on the sea floor around the world may contain hazardous substances that can cause harm to the marine environment. Today there are no comprehensive methods for environmental risk assessment of shipwrecks, and thus there is poor support for decision-making on prioritization of mitigation measures. The purpose of this study was to develop a tool for quantitative risk estimation of potentially polluting shipwrecks, and in particular an estimation of the annual probability of hazardous substance discharge. The assessment of the probability of discharge is performed using fault tree analysis, facilitating quantification of the probability with respect to a set of identified hazardous events. This approach enables a structured assessment providing transparent uncertainty and sensitivity analyses. The model facilitates quantification of risk, quantification of the uncertainties in the risk calculation and identification of parameters to be investigated further in order to obtain a more reliable risk calculation.

Fault tree analysis

Risk assessment

Shipwreck

Oil

Author

Hanna Landquist

Chalmers, Shipping and Marine Technology, Division of Maritime Operations

Chalmers, Civil and Environmental Engineering, Geology and Geotechnics

Lars Rosen

Chalmers, Civil and Environmental Engineering, Geology and Geotechnics

Andreas Lindhe

Chalmers, Civil and Environmental Engineering, Geology and Geotechnics

Tommy Norberg

Chalmers, Mathematical Sciences, Mathematical Statistics

University of Gothenburg

Ida-Maja Hassellöv

Chalmers, Shipping and Marine Technology, Division of Maritime Operations

Fredrik Lindgren

Chalmers, Shipping and Marine Technology, Division of Maritime Operations

Ingela Dahllöf

University of Gothenburg

Marine Pollution Bulletin

0025-326X (ISSN) 1879-3363 (eISSN)

Vol. 88 1-2 239-248

Subject Categories

Environmental Sciences

DOI

10.1016/j.marpolbul.2014.08.037

More information

Created

10/7/2017