Oil Transport Following the Deepwater Horizon Blowout

The Deepwater Horizon oil spill in the Gulf of Mexico in 2010 was the largest in US history, covering more than 1,000 km of shorelines and causing losses that exceeded $50 billion. While oil transformation processes are understood at the laboratory scale, the extent of the Deepwater Horizon spill made it challenging to integrate these processes in the field. This review tracks the Deepwater Horizon oil during its journey from the Mississippi Canyon block 252 (MC252) wellhead, first discussing the formation of the oil and gas plume and the ensuing oil droplet size distribution, then focusing on the behavior of the oil on the water surface with and without waves. It then reports on massive drifter experiments in the Gulf of Mexico and the impact of the Mississippi River on the oil transport. Finally, it concludes by addressing the formation of oil-particle aggregates. Although physical processes lend themselves to numerical modeling, we attempted to elucidate them without using advanced modeling, as our goal is to enhance communication among scientists, engineers, and other entities interested in oil spills.

Modeling turbulent transport of aerosols inside rooms using eddy diffusivity

One major approach to modeling dispersion of pollutants inside confined spaces describes the turbulent transport of material as the product of an eddy diffusivity and the local concentration gradient. This paper examines the applicability of this eddy diffusivity/gradient model by (1) describing the conditions under which this approach is an appropriate representation of turbulent transport, and (2) re-analysis of data provided in studies that have successfully applied gradient transport to describe tracer concentrations. We find that the solutions of the mass conservation equation based on gradient transport provide adequate descriptions of concentration measurements from two studies representative of two types of sources: instantaneous and continuous release of aerosols. We then provide the rationale for the empirical success of the gradient transport model. The solutions of the gradient transport model allow us to examine the relationship between the ventilation rate and the spatial and temporal behavior of the dose of material associated with aerosol releases in a room. We conclude with the associated implications on mitigation of exposure to aerosols such as airborne virus or bacteria.

Turbulent eddy diffusion models in exposure assessment - Determination of the eddy diffusion coefficient

The use of the turbulent eddy diffusion model and its variants in exposure assessment is limited due to the lack of knowledge regarding the isotropic eddy diffusion coefficient, D_T. But some studies have suggested a possible relationship between D_T and the air changes per hour (ACH) through a room. The main goal of this study was to accurately estimate D_T for a range of ACH values by minimizing the difference between the concentrations measured and predicted by eddy diffusion model. We constructed an experimental chamber with a spatial concentration gradient away from the contaminant source, and conducted 27 3-hr long experiments using toluene and acetone under different air flow conditions (0.43-2.89 ACHs). An eddy diffusion model accounting for chamber boundary, general ventilation, and advection was developed. A mathematical expression for the slope based on the geometrical parameters of the ventilation system was also derived. There is a strong linear relationship between D_T and ACH, providing a surrogate parameter for estimating D_T in real-life settings. For the first time, a mathematical expression for the relationship between D_T and ACH has been derived that also corrects for non-ideal conditions, and the calculated value of the slope between these two parameters is very close to the experimentally determined value. The values of D_T obtained from the experiments are generally consistent with values reported in the literature. They are also independent of averaging time of measurements, allowing for comparison of values obtained from different measurement settings. These findings make the use of turbulent eddy diffusion models for exposure assessment in workplace/indoor environments more practical.