A probabilistic ecological risk model for Arctic marine oil spills

Mawuli Afenyo, Faisal Khan*, Brian Veitch, Ming Yang

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

31 Citations (Scopus)

Abstract

A model that can evaluate the ecological risk posed to the Arctic marine ecosystem is presented in this paper. The proposed model is aimed at evaluating the risk of an accidental oil release. The model incorporates a release and dispersion model, fate and transport model, and ecotoxicological modelling. Uncertainties in the proposed model and data are addressed through a probabilistic framework implemented using a fugacity model to estimate the exposure concentration in the different media that are in contact with oil. This is the focus of this paper. The 95th percentile of Predicted Exposure Concentration (PEC95%) is compared with the 5th percentile of the Predicted No Effect Concentration (PNEC5%) to produce a Risk Quotient (RQ) profile, which indicates the level of risk posed to the Arctic marine ecosystem. The application of the proposed model is illustrated through a case study. The RQ obtained is useful for making decisions on the management of safety for Arctic marine ecosystems, such as setting operational goals to prevent accidents and for designing emergency preparedness plans. The uniqueness of this work in comparison to ealier studies is that, the methodology takes into account all the significant component models needed to address a potential oil spill in a probabilistic way and demonstrated in an Arctic setting. This study also shows that the methodology is useful as a first step to decision making in the absence of data on accidental releases in the Arctic marine waters.

Original languageEnglish
Pages (from-to)1494-1503
Number of pages10
JournalJournal of Environmental Chemical Engineering
Volume5
Issue number2
DOIs
Publication statusPublished - 1 Apr 2017
Externally publishedYes

Keywords

  • Arctic
  • Ecology risk
  • Oil spill
  • Pollution
  • Risk assessment

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