Bayesian submerged oil tracking with SOSim: Inference from field reconnaissance data and fate-transport model output.

When spilled oil collects at depth, questions as to where and when to dispatch response equipment become daunting, because such oil may be invisible by air, and underwater sensing technology is limited in coverage and by underwater visibility. Further, trajectory modeling based on previously recorded flow field data may show mixed results. In this work, the Bayesian model, SOSim, is modified to locate and forecast the movement of submerged oil, with confidence bound, by inferring model parameters based on any available field concentration data and the output of one or more deterministic trajectory models.

Bayesian sunken oil tracking with SOSim v2: Inference from field and bathymetric data.

Sunken oil is often difficult to detect, and few oil spill models are designed to locate and track such oil. Therefore, the multi-modal Bayesian inferential sunken oil model, SOSim (Subsurface Oil Simulator), was expanded in this work for use during emergency response and damage assessment. Rather than requiring hydrodynamic data as input, SOSim v2 accepts available field concentration data, along with default or custom bathymetric data, for inference of the location and trajectory of sunken oil.

A model for the estimation of the mixing zone behind large sea vessels.

One of the important tasks associated with reducing the concentration of contaminants in the sea surface layer is the determination of their mixing volume, as of the most active systems for mixing the sea surface layer are sea vessels. The wake of a ship is a highly mixed medium. The study of the wake development over time is important when evaluating the mixing of various pollutants in the wake with neutralizing chemicals.

Improving oil spill trajectory modelling in the Arctic.

As petroleum development and other activities move further north, the potential for oil spills in ice-covered waters is of great concern. As a tool for contingency planning and forecasting during response, oil spill models play a key role. With the development of new, high-resolution coupled ice-ocean models, better predictions of sea ice are becoming available.

A critical review of marine snow in the context of oil spills and oil spill dispersant treatment with focus on the Deepwater Horizon oil spill.

Natural marine snow (NMS) is defined as the "shower" of particle aggregates formed by processes that occur in the world's oceans, consisting of macroscopic aggregates of detritus, living organisms and inorganic matter. Recent studies from the Deepwater Horizon oil spill suggest that marine snow is also formed in association with oil spills and was an important factor for the transport of oil to the seabed. This review summarizes the research and literature on MS, mainly from the DWH oil spill, with a focus on the relation between the use of oil spill dispersants and the formation and fate of oil-related marine snow (ORMS).

Oil spill response capabilities and technologies for ice-covered Arctic marine waters: A review of recent developments and established practices.

Renewed political and commercial interest in the resources of the Arctic, the reduction in the extent and thickness of sea ice, and the recent failings that led to the Deepwater Horizon oil spill, have prompted industry and its regulatory agencies, governments, local communities and NGOs to look at all aspects of Arctic oil spill countermeasures with fresh eyes. This paper provides an overview of present oil spill response capabilities and technologies for ice-covered waters, as well as under potential future conditions driven by a changing climate. Though not an exhaustive review, we provide the key research results for oil spill response from knowledge accumulated over many decades, including significant review papers that have been prepared as well as results from recent laboratory tests, field programmes and modelling work.

Impact of climate change and seasonal trends on the fate of Arctic oil spills.

We investigated the effects of a warmer climate, and seasonal trends, on the fate of oil spilled in the Arctic. Three well blowout scenarios, two shipping accidents and a pipeline rupture were considered. We used ensembles of numerical simulations, using the OSCAR oil spill model, with environmental data for the periods 2009-2012 and 2050-2053 (representing a warmer future) as inputs to the model.

The significance of dilution in evaluating possible impacts of wastewater discharges from large cruise ships.

In response to public concerns about discharges from large cruise ships, Alaska's Department of Environmental Conservation (ADEC) sampled numerous effluents in the summer of 2000. The data showed that basic marine sanitation device (MSD) technology for black water (sewage) was not performing as expected. Untreated gray water had high levels of conventional pollutants and surprisingly high levels of bacteria.