AI Article Synopsis
- The increase in shipping heavier hydrocarbons raises the risk of oil sinking after spills, making recovery efforts more challenging.
- Sunken oil can result from various mechanisms, including burn residue or sediment entrainment, with manual recovery being notably effective in sediment scenarios.
- Different oil tracking models, like trajectory and Bayesian models, are compared, with Bayesian models offering advantages by inferring data from existing field conditions rather than needing extensive hydrodynamic inputs.
Article Abstract
A rise in the shipping of heavier hydrocarbon products increases the potential for an oil to sink after a spill. Further, sunken oil is difficult to locate and recover, and appropriate response technologies depend on the sinking mechanism. In this review, principal sinking mechanisms for oil are described and appropriate response technologies are suggested. Then, models appropriate for tracking sunken oil are compared. Oil may sink as burn residue, microscopic oil-particle aggregates (OPAs) or macroscopic oil-sediment mixtures (OSMs), marine oil snow during a MOSSFA event, or due to its high density. The most common mechanism is by sediment entrainment, and in such scenarios manual recovery has been reported as a successful response option. Among oil tracking models, trajectory models and Bayesian oil search models are compared for sunken oil capabilities. Many oil spill models require hydrodynamic inputs, whereas Bayesian models infer parameters based on available field concentration and bathymetric data.
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| http://dx.doi.org/10.1016/j.marpolbul.2020.111626 | DOI Listing |
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