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As part of a Comparative Risk Assessment (CRA) developed and reported previously, oil spill modeling of a hypothetical blowout at 1400 m in the northeastern Gulf of Mexico was performed to evaluate changes in oil exposures with alternative response options, i.e., combinations of mechanical recovery, in-situ burning, surface dispersant application and subsea dispersant injection (SSDI). To assess if conclusions from this study could be extended to other spill scenarios, sensitivities of the predicted oil fate and exposure metrics to location, release depth, oil and gas flow rate, gas content, orifice size, oil droplet size distribution, and biodegradation rates were examined. Results show that the fraction of oil surfacing is highly sensitive to oil droplet size distribution and depth of release. Across the simulations performed, SSDI use reduced oil droplet sizes released, thereby mitigating surface and shoreline oiling, volatile hydrocarbon exposures, and potential surface water column exposures.

Performance of a simple backtracking method in searching for a potential spill source for offshore detected oil is investigated through a series of idealized numerical experiments, in which either sea surface source in a 2D case or underwater source in a 3D case is considered. Numerical result shows that, generally, backtracking time is an important input for 2D version of the backtracking method, whereas an accurate ocean dynamic background and an accurate field measurement of oil droplet size are crucial for 3D version. Reducing the uncertainty in oil detection site or accurately measuring the oil droplet size can effectively improve the efficiency of method implementation. External information like satellite images, offshore oil facilities and navigation information is helpful for improving the method efficiency.

Limited experimental and field data are available describing oil droplet formation from subsea releases at high pressure. There are also analytical challenges quantifying oil droplets over a wide size and concentrations range at high pressure. This study quantified oil droplets released from an orifice in seawater at low and high pressure (5 m and 1750 m depth). Oil droplet sizes were quantified using a newly developed sensor (Silhouette camera or SilCam). The droplet sizes measured during experiments at low and high pressure, using the same release conditions, showed no significant difference as a function of pressure. This lack of a pressure effect on oil droplet sizes was observed for both untreated oil and for droplet formation during subsea dispersant injection or SSDI. This strongly indicates that the effectiveness of SSDI is not influenced by water depth or pressure, at least for simulated subsea releases of oil alone (no gas).

Oil-sediment aggregation is an important transport and transformation process of spilled oil, which has been considered as a pathway of spill remediation. This work focused on the individual performance of dispersed oil and sediment during the aggregation process. Dispersion of three oils was first tested and validated in a water tank. An approach of estimating the mass variation of the sediment that has participated in forming the oil-sediment aggregates (OSAs) has been developed by density analysis. Results indicated that the density of the formed OSAs increases during the aggregation. In the context of remediation, it takes longer for sediment to reach equilibrium than for dispersed oil, especially under high mixing energy at a large sediment concentration, which results in the formation of dense OSAs, as well as high aggregation degree and rate. Roncador oil possesses a relatively high capability of capturing sediment to form dense OSAs, especially at an initial sediment concentration of over 150 mg/L. Oil sinking efficiency and the characteristic change rate of aggregated oil mass seem to be proportional to oil dispersion efficiency, and decrease with the mean size of dispersed oil droplets. The process of aggregation can further promote the dispersion of oil into water column. This study also provides fundamental data for the formation kinetics of OSAs.

Small-scale experiments performed at SINTEF, Norway in 2011-12 led to the development of a modified Weber scaling algorithm. The algorithm predicts initial oil droplet sizes (d50) from a subsea oil and gas blowout. It was quickly implemented in a high number of operational oil spill models used to predict fate and effect of subsea oil releases both in academia and in the oil industry. This paper presents experimental data from large-scale experiments generating oil droplet data in a more realistic multi-millimeter size range for a subsea blow-out. This new data shows a very high correlation with predictions from the modified Weber scaling algorithm both for untreated oil and oil treated by dispersant injection. This finding is opposed to earlier studies predicting significantly smaller droplets, using a similar approach for estimating droplet sizes, but with calibration coefficients that we mean are not representative of the turbulence present in such releases.

Increased knowledge about the fate and behaviour of weathered oil in different sea ice conditions is essential for our ability to model oil spill trajectories in ice more precisely and for oil spill response decision making in northern and Arctic areas. As part of the 3-year project: “Fate, Behaviour and Response to Oil Drifting into Scattered Ice and Ice Edge in the Marginal Ice Zone”, a novel wave and current flume was built to simulate these processes in the laboratory. This paper discusses some of the findings from this project, which included Marine Gas Oil and four Norwegian crude oils. All crude oils were weathered prior to testing, simulating having drifted on the sea surface for a period (tentatively 1–3 days) before encountering ice. The build-up of oil drifting against an ice barrier and horizontal and vertical migration of oil droplets under solid ice and in frazil ice was studied.

Theoretical arguments and numerical investigations were conducted to understand the transport of oil droplets under ice. It was found that the boundary layer (BL) in the water under ice produces a downward velocity that reaches up to 0.2% of horizontal current speed, and is, in general, larger than the rise velocity of 70 μm oil droplets. The eddy diffusivity was found to increase with depth and to decrease gradually afterward. Neglecting the gradient of eddy diffusivity when conducting Lagrangian transport of oil droplets would result in an unphysical spatial distribution. When the downward velocity of water was neglected, oil accumulated at the water-ice interface regardless of the attachment efficiency. The lift force was found to scrape off droplets of the ice, especially for droplets ≤ 70 μm. These findings suggest that previous oil spill simulations may have overestimated the number of small droplets (≤70 μm) at the water-ice interface.

There are significant differences in the aggregation mechanisms and types of aggregates that form by oil-particle interactions in marine and laboratory environments depending on the state of oil (i.e., dissolved, emulsified, floating), size and type of particles involved (i.e., colloidal, granular, organic, inorganic), oil-particle interaction mechanisms, and settling/suspension characteristics. Distinct characteristics of oil-particle aggregates that form by interaction of granular particles with floating oil separate them from the well-known oil-colloidal particle aggregates (OcPA), which are sometimes called Pickering emulsions. Unlike OcPA, which involve emulsified oil (entrained oil droplets suspended in the water column) and colloidal particles, the oil-granular particle aggregates (OgPA) involve the floating oil and granular particles. Here, to clarify the differences and similarities between the two types of aggregates (OcPA and OgPA), we present classification of oil aggregates, drawing attention to important characteristics of OcPA, marine oil snow (MOS), and OgPA.

The fabrication of the materials with special wettability being capable of removing oil layer on water surface and oil droplets in oil-in-water emulsion is an important issue for water pollution. So far, it still remains challenging to explore a simple, facile, environmentally friendly approach for achieving this goal. Herein, inspired by the adhesion of marine mussels, the polydopamine (PDA) coating with hierarchical structure was directly fabricated onto the surface of melamine (MF) sponge by facile self-polymerization in dopamine solution. Then, a superhydrophobic and superoleophilic sponge was successfully obtained after the modification by dodecanethiol (DDT) at ambient temperature. The as-prepared sponge can selectively separate a series of oil droplets in oil-in-water emulsion with high efficiency (transparency: 76.6-93.8%) and absorb various oils or organic solvents up to 45.2-98.6 times of its own weight. Moreover, in conjunction with a vacuum system, great amounts of oils up to 20 times its own weight can be effectively separated from water surface within 1s by the sponge. Due to low cost, simple process, and easy accessibility, the as-prepared sponge has potential applications in oil-in-water emulsion separation and oil spill cleanup.

This paper develops a 3D, transient, mathematical model to estimate the oil release rate and simulate the oil dispersion behavior. The Euler-Euler method is used to estimate the subsea oil release rate, while the Eulerian-Lagrangian method is employed to track the migration trajectory of oil droplets. This model accounts for the quantitative effect of backpressure and hole size on oil release rate, and the influence of oil release rate, oil density, current speed, water depth and leakage position on oil migration is also investigated in this paper. Eventually, the results, e.g. transient release rate of oil, the rise time of oil and dispersion distance are determined by above-mentioned model, and the oil release and dispersion behavior under different scenarios is revealed. Essentially, the assessment results could provide a useful guidance for detection of leakage positon and placement of oil containment boom.

A surface oil entrainment model and droplet size model have been developed to estimate the flux of oil under surface breaking waves. Both equations are expressed in dimensionless Weber number (We) and Ohnesorge number (Oh, which explicitly accounts for the oil viscosity, density, and oil-water interfacial tension). Data from controlled lab studies, large-scale wave tank tests, and field observations have been used to calibrate the constants of the two independent equations. Predictions using the new algorithm compared well with the observed amount of oil removed from the surface and the sizes of the oil droplets entrained in the water column. Simulations with the new algorithm, implemented in a comprehensive spill model, show that entrainment rates increase more rapidly with wind speed than previously predicted based on the existing Delvigne and Sweeney's (1988) model, and a quasi-stable droplet size distribution (d

It is necessary for chemical dispersant to disperse oil effectively and maintain the stability of oil droplets. In this work, Xanthan Gum (XG) was used as an environmentally friendly additive in oil dispersant formulation to enhance the stability and biodegradation of dispersed crude oil droplets. When XG was used together with chemical dispersant 9500A, the dispersion effectiveness of crude oil in artificial sea water (ASW) and the oil droplet stability were both greatly enhanced. In the presence of XG, lower concentration of 9500A was needed to achieve the effective dispersion and stabilization. In addition to the enhancement of dispersion and stabilization, it was found that the biodegradation rate of crude oil by bacteria was dramatically enhanced when a mixture of 9500A and XG was used as a dispersant. Because of the low environmental impact of XG, this would be a potential way to formulate the dispersant with lower toxicity.

An in situ particle imaging system for measurement of high concentrations of suspended particles ranging from 30 μm to several mm in diameter, is presented. The system obtains quasi-silhouettes of particles suspended within an open-path sample volume of up to 5 cm in length. Benchmarking against spherical standards and the LISST-100 show good agreement, providing confidence in measurements from the system when extending beyond the size, concentration and particle classification capabilities of the LISST-100. Particle-specific transmittance is used to classify particle type, independent of size and shape. This is applied to mixtures of oil droplets, gas bubbles and oil-coated gas bubbles, to provide independent measures of oil and gas size distributions, concentrations, and oil-gas ratios during simulated subsea releases. The system is also applied to in situ measurements of high concentrations of large mineral flocs surrounding a submarine mine tailings placement within a Norwegian Fjord.

The ability to calculate the oil droplet size distribution (DSD) and its dynamic behavior in the water column is important in oil spill modeling. Breaking waves disperse oil from a surface slick into the water column as droplets of varying sizes. Oil droplets undergo further breakup and coalescence in the water column due to the turbulence. Available models simulate oil DSD based on empirical/equilibrium equations. However, the oil DSD evolution due to subsequent droplet breakup and coalescence in the water column can be best represented by a dynamic population model. This paper develops a phenomenological model to calculate the oil DSD in wave breaking conditions and ocean turbulence and is based on droplet breakup and coalescence. Its results are compared with data from laboratory experiments that include different oil types, different weathering times, and different breaking wave heights. The model comparisons showed a good agreement with experimental data.

Floating oil and sediments can interact to form oil-particle aggregates (OPAs) in marine environments. Laboratory batch experiments were conducted to investigate the effects of the concentration and size of sediment, temperature, oil types and chemical dispersant on the formation of OPAs. The results showed that the mass of OPAs and oil-particle aggregation rate are mainly related to the sediment concentration. Under the same mass concentration, more oil droplets can be trapped by smaller particles. Nevertheless, larger particles tend to interact more quickly with oil droplets. The effect of temperature on the formation of OPAs is substantially attributed to its influence on oil viscosity, and there is a threshold for oil viscosity which will bring about the maximum OPAs. Spilled oil with a high asphaltene can interact more effectively with the sediments. Appropriate addition of chemical dispersant is favorable for the formation of OPAs while excess addition will inhibit it.

Gelatinous zooplankton are known for their capacity to excrete copious amounts of mucus that can be utilized by other organisms. The release of mucus is exacerbated by stressful conditions. Despite the recognized importance of cnidarian mucus to production and material flux in marine ecosystems, the role of gelatinous zooplankton in influencing the fate of oil spills is unknown. In this study we used laboratory experiments to observe the influence of mucus from the moon jellyfish (Aurelia aurita) on the aggregation and degradation of crude oil. The results show that jellyfish swimming in a dispersed solution of oil droplets produced copious amounts of mucus and the mucus aggregates that were shed by the animals contained 26 times more oil than the surrounding water. Incubation experiments showed that hydrocarbon degrading bacteria cell densities more than doubled in the presence of mucus and after 14 days, resulted in a significant increase in oil degradation. These results suggest that jellyfish can aggregate dispersed oil droplets and embed them within a matrix that favors hydrocarbon degrading bacteria. While this study lends support to the hypothesis that the presence of gelatinous zooplankton can impact oil spills large scale mesocosm studies will be needed to fully quantify the influence on a natural system.

Chemical analysis of sediment cores collected up to 8 km from the Macondo well in 2010/2011 demonstrates the extent of weathering of the Macondo oil deposited in deep-sea sediments following the Deepwater Horizon disaster. On average, dissolution and biodegradation of the oil on the seafloor increased with distance from the well indicating that weathering occurred rapidly and overwhelmingly during the oil's transport as dispersed oil droplets within the deep-sea plume. Beyond about 5 km from the well, the oil deposited on the seafloor had lost most mass below C 25 , was relatively enriched in n -C 25 + n -alkanes and C 3 – and C 4 -alkylated benz[ a ]anthracenes/chrysenes, the latter owing to 95% depletion of total PAHs. Biodegradation of C 28 and C 29 tricyclic terpanes, C 34 and C 35 17α(H),21β(H)-homohopanes, C 27 13β(H),17α(H)-dia and C 27 14β(H),17β(H)-steranes and dissolution of C 26 to C 28 triaromatic steroids occurred. The results provide a means to distinguish Macondo oil in deep-sea sediments from naturally-occurring seep oils and pervasive ambient background hydrocarbons.

The movement of oil droplets due to waves and buoyancy was investigated by assuming an irregular sea state following a JONSWAP spectrum and four buoyancy values. A technique known as Wheeler stretching was used to model the movement of particles under the moving water surface. In each simulation, 500 particles were released and were tracked for a real time of 4.0 h. A Monte Carlo approach was used to obtain ensemble properties. It was found that small eddy diffusivities that decrease rapidly with depth generated the largest horizontal spreading of the plume. It was also found that large eddy diffusivities that decrease slowly with depth generated the smallest horizontal spreading coefficient of the plume. The increase in buoyancy resulted in a decrease in the horizontal spreading coefficient, which suggests that two-dimensional (horizontal) models that predict the transport of surface oil could be overestimating the spreading of oil.

After spill, the dispersed oil droplets may collide with suspended particulate matter in the water column to form oil-particle aggregates (OPAs) in turbulent environments. It may be an effective pathway to stabilize the oil by taking advantage of the particulate matter to clean up the contaminated waters. A theoretical model in Payne et al. (2003) is adopted to describe the oil-particle aggregation, and a solution method is proposed and validated against a group of experiments. The effect of the particle size and mass concentration on the aggregation has been examined quantitatively in detail. The particles and the oil droplets are consumed at a fixed ratio. Under the same mass concentration, smaller particles can trap more oil droplets, while larger particles tend to interact more quickly with the oil. The oil-particle aggregation rate and the oil trapping efficiency mainly depend on the particle concentration. The theoretical model is applied to predict the decrease of the dispersed oil in nearshore environments, based on the parameters obtained from the experiments. It is efficient to promote the oil-particle aggregation by increasing the particle concentration in the closed bay. In the open sea, the decrease of the dispersed oil can be effectively enhanced by increasing the particle concentration when it is below 0.50 kg/m3. The information presented in this paper can serve to predict the fate of the dispersed oil in coastal waters and provide technical support for oil spill management strategies.

This paper presents a compilation of data describing interfacial tension between oil and seawater (IFT(oil-water)) as a function of dispersant dosage. The data are from several earlier laboratory studies simulating subsea oil blowouts to evaluate subsea injection of dispersant (SSDI). Three dispersants were tested with four oil types to give a large variation in oil properties (paraffinic, light, waxy and asphaltenic). A general expression for IFT(oil-water) as a function of dispersant dosage is proposed based on the compiled data. IFT(oil-water) versus dosage is needed by algorithms to predict oil droplet sizes from subsea releases. However, such a relationship based on averaged data should be used with care and IFT measurements on the actual oil-dispersant combination should always be preferred.

The degree to which droplet shedding (tip-streaming) can modify the size of rising oil droplets has been a topic of growing interest in relation to subsea dispersant injection. We present an experimental and numerical approach predicting oil droplet shedding, covering a wide range of viscosities and interfacial tensions. Shedding was observed within a specific range of droplet sizes when the oil viscosity is sufficiently high and the IFT is sufficiently low. The affected droplets are observed to reduce in size, as smaller satellite droplets are shed, until the parent droplet reaches a stable size. Shedding of smaller droplets is related to the viscosity-dominated modified capillary number (Ca'), especially for low dispersant dosages recommended for subsea dispersant injection. This, in combination with the IFT-dominated Weber number (We), characterise droplets into three possible states: 1) stable (Ca' 0.21We12); 2) tip-streaming (Ca' 0.21We12); 3) unstable and subject to total breakup (We12).

Both oil droplets and gas bubbles have simultaneously been quantified in laboratory experiments that simulate deep-water subsea releases of both live oil (saturated with gas) and additional natural gas under high pressure. These data have been used to calculate particle size distributions (50–5000 μm) for both oil and gas. The experiments showed no significant difference in oil droplet sizes versus pressure (from 5 m to 1750 m) for experiments with live oil. For combined releases of live oil and natural gas, oil droplet sizes showed a clear reduction as a function of increased gas void fraction (increased release velocity) and a weak reduction with increased depth (increased gas density/momentum). Oil droplets were reduced by a factor of 3 to 4 during simulated subsea dispersant injection (SSDI) and no significant effect of pressure was observed. This indicates that SSDI effectiveness is not dependent on water depth or pressure.

The main objective with this study has been to study injection techniques for subsea dispersant injection (SSDI) to recommend techniques relevant for both laboratory studies and operational response equipment. The most significant factor was the injection point of the dispersant in relation to the release of the oil. The dispersant should be injected immediately before or after the oil is released. Then the dispersant will mix into the oil and reduce IFT before the oil enters the turbulent zone where initial droplet formation occurs. All injection techniques tested gave significant reductions in oil droplet sizes. However, due to the rapid oil droplet formation in turbulent jets and possible formation of surfactant aggregates in the oil, premixing of dispersants should not be used for experimental studies of subsea dispersant injection. This could underestimate dispersant effectiveness and produce results that might not be representative for up-scaled field conditions.

Calculation of oil droplet size distribution is one of the key components of ocean oil spill models. Oil fate and transport calculations of the model are significantly impacted by the droplet size distribution. Accuracy of the model predictions heavily depend on how well the model can calculate or represent oil droplet sizes. However, in early oil spill models, the importance of oil droplet size calculation has been overlooked and they used simple empirical formulas. In recent decades, there have been some significant improvements in understanding of oil droplet size calculations. Both experimental studies as well as numerical studies have been contributed to improve oil droplet size calculations. The traditional equilibrium models have been improved while droplet dynamics models provided a different dimension to the oil DSD calculations. Thus, at this stage it is important to review the existing studies and methods of oil droplet size calculation. The objective of this paper is to review the development of oil droplet size calculation in ocean oil spill models highlighting the recent improvements. Furthermore, this paper discusses the capabilities and limitations of different approaches in calculating oil droplet size distribution in both underwater and surface oil spill models and discuss their applicability to different situations. This study will provide a good guideline for future oil spill model developments to improve the oil droplet size calculations.

Knowledge of the droplet size distribution (DSD) from the Deepwater Horizon (DWH) blowout is an important step in predicting the fate and transport of the released oil. Due to the absence of measurements of the DSD from the DWH incident, we considered herein hypothetical scenarios of releases that explore the realistic parameter space using a thoroughly calibrated DSD model, VDROP-J, and we attempted to provide bounds on the range of droplet sizes from the DWH blowout within 200 m of the wellhead. The scenarios include conditions without and with the presence of dispersants, different dispersant treatment efficiencies, live oil and dead oil properties, and varying oil flow rate, gas flow rate, and orifice diameter. The results, especially for dispersant-treated oil, are very different from recent modeling studies in the literature.

We compare oil spill model predictions for a prototype subsea blowout with and without subsea injection of chemical dispersants in deep and shallow water, for high and low gas–oil ratio, and in weak to strong crossflows. Model results are compared for initial oil droplet size distribution, the nearfield plume, and the farfield Lagrangian particle tracking stage of hydrocarbon transport. For the conditions tested (a blowout with oil flow rate of 20,000 bbl/d, about 1/3 of the Deepwater Horizon), the models predict the volume median droplet diameter at the source to range from 0.3 to 6 mm without dispersant and 0.01 to 0.8 mm with dispersant. This reduced droplet size owing to reduced interfacial tension results in a one to two order of magnitude increase in the downstream displacement of the initial oil surfacing zone and may lead to a significant fraction of the spilled oil not reaching the sea surface.

During the Deepwater Horizon (DWH) accident in 2010 a dispersant (Corexit 9500) was applied at the wellhead to disperse the Macondo oil and reduce the formation of surface slicks. A subsurface plume of small oil droplets was generated near the leaking well at 900–1300 m depth. A novel laboratory system was established to investigate biodegradation of small droplet oil dispersions (10 μm or 30 μm droplet sizes) of the Macondo oil premixed with Corexit 9500, using coastal Norwegian seawater at a temperature similar to the DWH plume (4–5 °C). Biotransformation of volatile and semivolatile hydrocarbons and oil compound groups was generally faster in the 10 μm than in the 30 μm dispersions, showing the importance of oil droplet size for biodegradation. These data therefore indicated that dispersant treatment to reduce the oil droplet size may increase the biodegradation rates of oil compounds in the deepwater oil droplets.

Simulated column was applied to research forming progress of single oil droplet in submerged process, floating progress, and study effects of environment factors and dispersants on the concentration of oil hydrocarbon in water as well as changing rules of oil droplet sizes. As expected, particular formation mechanism of single oil droplet was presented. When necking down length L is 0.5 time of oil droplet diameter (d) after expansion phase, necking down becomes long and thin; when L=2d, necking down begins to break. In floating progress, the shape changes oval and its motion trail becomes an auger-type. Fluctuation occurs at horizontal direction. Dispersants decrease oil droplet size by its dispersion effect, and cut down effect of Van Der Waals force among oil droplets. More broadly, these findings provide rare empirical evidence expounding formation mechanism of single oil droplet to increasing ability of oil spill response.

This study, adsorption behaviors of dispersed oil in seawaters by granular materials were explored in simulation environment. We quantitatively demonstrated the dispersed oil adsorbed by granular materials were both dissolved petroleum hydrocarbons (DPHs) and oil droplets. Furthermore, DPHs were accounted for 42.5%, 63.4%, and 85.2% (35.5% was emulsion adsorption) in the adsorption of dispersed oil by coastal rocks, sediments, and bacterial strain particles respectively. Effects of controlling parameters, such as temperature, particle size and concentration on adsorption of petroleum hydrocarbons were described in detail. Most strikingly, adsorption concentration was followed a decreasing order of bacterial strain (0.5–2 μm) > sediments (0.005–0.625 mm) > coastal rocks (0.2–1 cm). With particle concentration or temperature increased, adsorption concentration increased for coastal rocks particle but decreased for sediments particle. Besides, particle adsorption rate of petroleum hydrocarbons (n-alkanes and PAHs) was different among granular materials during 60 days.

During the Deepwater Horizon blowout, unprecedented volumes of dispersant were applied both on the surface and at depth. Application at depth was intended to disperse the oil into smaller microdroplets that would increase biodegradation and also reduce the volumes buoyantly rising to the surface, thereby reducing surface exposures, recovery efforts, and potential stranding. In forensically examining 5300 offshore water samples for the Natural Resource Damage Assessment (NRDA) effort, profiles of deep-plume oil droplets (from filtered water samples) were compared with those also containing dispersant indicators to reveal a previously hypothesized but undocumented, accelerated dissolution of the polycyclic aromatic hydrocarbons (PAH) in the plume samples. We interpret these data in a fate-and-transport context and conclude that dispersant applications were functionally effective at depth.

Forensic chemistry assessments documented the presence of Macondo (MC252) oil from the Deepwater Horizon (DWH) spill in offshore water samples collected under Natural Resource Damage Assessment (NRDA) protocols. In ocean depths, oiled water was sampled, observed, photographed, and tracked in dissolved oxygen (DO) and fluorometry profiles. Chemical analyses, sensor records, and observations confirmed the shifting, rising oil plume above the wellhead while smaller, less buoyant droplets were entrapped in a layer at ~1000–1400 m and advected up to 412 km southwest. Near-surface oil samples showed substantial dissolution weathering from oil droplets rising through the water column, as well as enhanced evaporative losses of lighter n-alkanes and aromatic hydrocarbons. Dispersant effects from surface applications and injected at the wellhead were seen in oil profiles as enhanced weathering patterns (increased dissolution), thus implying dispersants were a functionally effective mediation treatment. Forensic assessment methods are detailed in the Supplemental information (SI).

Adsorption of suspended particles to the interface of surfactant-dispersed oil droplets can alter emulsion phase and sedimentation behavior. This work examines the effects of model mineral aggregates (silica nanoparticle aggregates or SNAs) on the behavior of oil (octane)–water emulsions prepared using sodium bis(2-ethylhexyl) sulfosuccinate (DOSS). Experiments were conducted at different SNA hydrophobicities in deionized and synthetic seawater (SSW), and at 0.5 mM and 2.5 mM DOSS. SNAs were characterized by thermogravimetric analysis (TGA) and dynamic light scattering (DLS), and the emulsions were examined by optical and cryogenic scanning electron microscopy. In deionized water, oil-in-water emulsions were formed with DOSS and the SNAs did not adhere to the droplets or alter emulsion behavior. In SSW, water-in-oil emulsions were formed with DOSS and SNA–DOSS binding through cation bridging led to phase inversion to oil-in-water emulsions. Droplet oil-mineral aggregates (OMAs) were observed for hydrophilic SNAs, while hydrophobic SNAs yielded quickly sedimenting agglomerated OMAs.

The interaction of dispersed oil droplets with large diameter suspended particulate materials (SPM) has been little studied. In the current study, particle size, oil characteristics and chemical dispersant significantly influence the adsorption of oil droplets to SPM in seawater. Sediments with a smaller particulate size (clay) approaching that of the oil droplets (2-20 μm) adsorbed more oil per gram than sediments with large particle size (sand). Heavier, more polar oils with a high asphaltene content adsorbed more efficiently to SPM than lighter, less polar oils. A decrease in the smaller, more water soluble oil components in the sediment adsorbed oil was observed for all oil types. Addition of chemical dispersant decreased the adsorption of oil droplets to suspended carbonate sand in an exponential-like manner. No change in the relative distribution of compounds adsorbed to the sediment was observed, indicating dispersants do not alter the dissolution of compounds from oil droplets.

The process of oil-suspended particulate matter aggregation (OSA) has been recognized by the oil spill remediation community to enhance the natural cleansing of oiled shorelines. A laboratory study was conducted to investigate the kinetics of OSA formation under various mixing intensities using the standard reference material 1941b and Arabian heavy crude oil. The results showed that formation of OSAs increased exponentially with mixing time and reached a maximum within 5h. The maximum oil trapping efficiency increased from 24% to 47%, and the required shaking time decreased from 4.5 to 1.2h as the sediment concentration and mixing energy increased. The maximum oil-to-sediment ratio reached 0.24-0.68 g oil/g sediment within 5h. Most of the formed OSAs were solid OSAs and single droplet OSAs with low mixing energies, and multi-droplet OSAs with high mixing energies. The sizes of the dispersed oil droplets and OSAs were also investigated.

OILMAP DEEP, an integrated system of models (pipeline release, blowout plume, dispersant treatment, oil droplet size distribution, and fountain and intrusion), was applied to the Deepwater Horizon (DWH) oil spill to predict the near field transport and fate of the oil and gas released into the northeastern Gulf of Mexico. The model included multiple, time dependent releases from both the kink and riser, with the observed subsurface dispersant treatment, that characterized the DWH spill and response. The blowout model predictions are in good agreement with the available observations for plume trapping height and the major characteristics of the intrusion layer. Predictions of the droplet size distribution are in good agreement with the limited in situ Holocam observations. Model predictions of the percentage of oil retained in the intrusion layer are consistent with independent estimates based on field observations.

The time taken for spilt oil to appear firstly at the sea surface and its location are two key issues for emergency response. The underwater spread of oil spill in a shear flow was studied experimentally in a re-circulating water channel. The high speed imaging technology was employed to record the whole transport process of oil spilt from a leak of a submarine pipe to the surface. Based on the experimental results, three underwater transport types are identified, which are single droplet pattern (model A), linear chain pattern (model B) and oil plume pattern (model C), respectively. The pressure difference inside and outside of the leak determines the underwater transport pattern. For single droplet pattern, the transport of oil droplet has two successive stage, namely the accumulation stage and the buoyant droplet stage. When it comes to linear chain pattern, the first stage changes to be the initial jet stage. Besides the initial jet stage and the buoyant droplet stage, oil plume pattern has an intermediate transition stage, namely the plume development stage. During the whole floating process, the pressure difference dominates the initial stage, while droplet buoyancy is the driven force in the rest. The required time for oil droplets to reach the surface is increased with the decreasing of the initial momentum and the increasing of the shear flow velocity. In the buoyance dominated stage, the floating rate of oil droplets is basically unchanged and the horizontal migration rate is similar with the shear flow velocity. Both the break-up and coalescence of oil droplets have two forms, which are single droplet splitting and droplet-column separation for break-up form and turbulence merging and pursuit merging for coalescence form, respectively.

An oil droplet size model was developed for a variety of turbulent conditions based on non-dimensional analysis of disruptive and restorative forces, which is applicable to oil droplet formation under both surface breaking-wave and subsurface-blowout conditions, with or without dispersant application. This new model was calibrated and successfully validated with droplet size data obtained from controlled laboratory studies of dispersant-treated and non-treated oil in subsea dispersant tank tests and field surveys, including the Deep Spill experimental release and the Deepwater Horizon blowout oil spill. This model is an advancement over prior models, as it explicitly addresses the effects of the dispersed phase viscosity, resulting from dispersant application and constrains the maximum stable droplet size based on Rayleigh-Taylor instability that is invoked for a release from a large aperture.

This study was aimed at testing the applicability of modified Weber number scaling with Alaska North Slope (ANS) crude oil, and developing a Reynolds number scaling approach for oil droplet size prediction for high viscosity oils. Dispersant to oil ratio and empirical coefficients were also quantified. Finally, a two-step Rosin-Rammler scheme was introduced for the determination of droplet size distribution. This new approach appeared more advantageous in avoiding the inconsistency in interfacial tension measurements, and consequently delivered concise droplet size prediction. Calculated and observed data correlated well based on Reynolds number scaling. The relation indicated that chemical dispersant played an important role in reducing the droplet size of ANS under different seasonal conditions. The proposed Reynolds number scaling and two-step Rosin-Rammler approaches provide a concise, reliable way to predict droplet size distribution, supporting decision making in chemical dispersant application during an offshore oil spill.

The formation of oil-suspended particulate matter aggregates (OSAs) results from the heteroaggregation between dispersed oil droplets and suspended particulate matter present in coastal waters. This process has been recognized by the oil spill remediation community to enhance natural cleansing of oiled shorelines and oil dispersion in the water column. While several studies have been conducted on the formation and characteristics of OSAs, few studies have addressed the kinetics of OSA formation. Operationally, this has left decision-makers lacking information on the time scale of this process and its significance to oil dispersion in real spills. A laboratory study was conducted to investigate the kinetics of OSA formation as a function of mixing energy and the sediment-to-oil ratio using the standard reference material 1941b. Results showed that formation of OSAs increased exponentially with the mixing time and reached a maximum within 4 h. When the shaking rate increased from 2.0 to 2.3 Hz, the maximum oil trapping efficiency increased from 20% to 42% and the required shaking time decreased from 3.7 to 0.7 h.

The effectiveness of chemical dispersants (Corexit 9500 and SPC 1000) on heavy fuel oil (IFO180 as test oil) has been evaluated under different wave conditions in a flow-through wave tank. The dispersant effectiveness was determined by measuring oil concentrations and droplet size distributions. An analysis of covariance (ANCOVA) model indicated that wave type and temperature significantly (p0.05) affected the dynamic dispersant effectiveness (DDE). At higher temperatures (16 degrees C), the test IFO180 was effectively dispersed under breaking waves with a DDE of 90% and 50% for Corexit 9500 and SPC 1000, respectively. The dispersion was ineffective under breaking waves at lower temperature (10 degrees C), and under regular wave conditions at all temperatures (10-17 degrees C), with DDE15%. Effective chemical dispersion was associated with formation of smaller droplets (with volumetric mean diameters or VMDor = 200 microm), whereas ineffective dispersion produced large oil droplets (with VMDor = 400 microm).

Testing dispersant effectiveness under conditions similar to that of the open environment is required for improvements in operational procedures and the formulation of regulatory guidelines. To this end, a novel wave tank facility was fabricated to study the dispersion of crude oil under regular non-breaking and irregular breaking wave conditions. This wave tank facility was designed for operation in a flow-through mode to simulate both wave- and current-driven hydrodynamic conditions. We report here an evaluation of the effectiveness of chemical dispersants (Corexit EC9500A and SPC 1000) on two crude oils (Medium South American [MESA] and Alaska North Slope [ANS]) under two different wave conditions (regular non-breaking and plunging breaking waves) in this wave tank. The dispersant effectiveness was assessed by measuring the water column oil concentration and dispersed oil droplet size distribution. In the absence of dispersants, nearly 8-19% of the test crude oils were dispersed and diluted under regular wave and breaking wave conditions. In the presence of dispersants, about 21-36% of the crude oils were dispersed and diluted under regular waves, and 42-62% under breaking waves. Consistently, physical dispersion under regular waves produced large oil droplets (volumetric mean diameter or VMD > or = 300 microm), whereas chemical dispersion under breaking waves created small droplets (VMD < or = 50 microm). The data can provide useful information for developing better operational guidelines for dispersant use and improved predictive models on dispersant effectiveness in the field.

Raindrops falling on the sea surface produce turbulence. The present study examined the influence of rain-induced turbulence on oil droplet size and dispersion of oil spills in Douglas Channel in British Columbia, Canada using hourly atmospheric data in 2011–2013. We examined three types of oils: a light oil (Cold Lake Diluent - CLD), and two heavy oils (Cold Lake Blend - CLB and Access Western Blend - AWB). We found that the turbulent energy dissipation rate produced by rainfalls is comparable to what is produced by wind-induced wave breaking in our study area. With the use of chemical dispersants, our results indicate that a heavy rainfall (rain rate > 20 mm h − 1 ) can produce the maximum droplet size of 300 μm for light oil and 1000 μm for heavy oils, and it can disperse the light oil with fraction of 22–45% and the heavy oils of 8–13%, respectively. Heavy rainfalls could be a factor for the fate of oil spills in Douglas Channel, especially for a spill of light oil and the use of chemical dispersants.

Controlled laboratory studies of the formation of oil-mineral aggregates (OMA) in seawater demonstrate that sediment concentration and sediment size are key variables for determining the quantity of oil droplets stabilised by OMA formation. Experiments with a single sediment size and a range of sediment concentrations show that as sediment concentration increases, the quantity of oil trapped in OMA increases abruptly. In experiments with a single sediment concentration and a range of sediment sizes, the quantity of oil trapped in OMA decreases as sediment size increases. These results provide direct support to the hypothesis that there is a critical sediment concentration for OMA formation. Below this concentration, stabilisation of oil droplets by OMA decreases rapidly, while above this concentration, stabilisation is extensive. The results also support simple geometric models of OMA formation that predict that the critical sediment mass concentration increases linearly with sediment particle diameter. These results will help to place quantitative constraint on predictions of where and when OMA formation will be a factor in the natural dispersal of oil accidentally spilled into the ocean.

Modeling of deep-water releases of gas and oil involves conventional plume theory in combination with thermodynamics and mass transfer calculations. The discharges can be understood in terms of multiphase plumes, where gas bubbles and oil droplets may separate from the water phase of the plume and rise to the surface independently. The gas may dissolve in the ambient water and/or form gas hydrates--a solid state of water resembling ice. All these processes will tend to deprive the plume as such of buoyancy, and in stratified water the plume rise will soon terminate. Slick formation will be governed by the surfacing of individual oil droplets in a depth and time variable current. This situation differs from the conditions observed during oil-and-gas blowouts in shallow and moderate water depths. In such cases, the bubble plume has been observed to rise to the surface and form a strong radial flow that contributes to a rapid spreading of the surfacing oil. The theories and behaviors involved in deepwater blowout cases are reviewed and compared to those for the shallow water blowout cases.

The droplet size distribution of dispersed phase (oil and/or gas) in submerged buoyant jets was addressed in this work using a numerical model, VDROP-J. A brief literature review on jets and plumes allows the development of average equations for the change of jet velocity, dilution, and mixing energy as function of distance from the orifice. The model VDROP-J was then calibrated to jets emanating from orifices ranging in diameter, D, from 0.5 mm to 0.12 m, and in cross-section average jet velocity at the orifice ranging from 1.5 m/s to 27 m/s. The d50/D obtained from the model (where d50 is the volume median diameter of droplets) correlated very well with data, with an R2 = 0.99. Finally, the VDROP-J model was used to predict the droplet size distribution from Deepwater Horizon blowouts. The droplet size distribution from the blowout is of great importance to the fate and transport of the spilled oil in marine environment.

Size distribution of oil droplets formed in deep water oil and gas blowouts have strong impact on the fate of the oil in the environment. However, very limited data on droplet distributions from subsurface releases exist. The objective of this study has been to establish a laboratory facility to study droplet size versus release conditions (rates and nozzle diameters), oil properties and injection of dispersants (injection techniques and dispersant types). This paper presents this facility (6 m high, 3 m wide, containing 40 m(3) of sea water) and introductory data. Injection of dispersant lowers the interfacial tension between oil and water and cause a significant reduction in droplet size. Most of this data show a good fit to existing Weber scaling equations. Some interesting deviations due to dispersant treatment are further analyzed and used to develop modified algorithms for predicting droplet sizes in a second paper (Johansen et al., 2013).

A new method for prediction of droplet size distributions from subsea oil and gas releases is presented in this paper. The method is based on experimental data obtained from oil droplet breakup experiments conducted in a new test facility at SINTEF. The facility is described in a companion paper, while this paper deals with the theoretical basis for the model and the empirical correlations used to derive the model parameters from the available data from the test facility. A major issue dealt with in this paper is the basis for extrapolation of the data to full scale (blowout) conditions. Possible contribution from factors such as buoyancy flux and gas void fraction are discussed and evaluated based on results from the DeepSpill field experiment.

The aim of the work was to establish methodology for realistic laboratory-based test exposures of organisms to oil dispersions, specifically designed to generate parameterized toxicity data. Such data are needed to improve the value of numerical models used to predict fate and effects of oil spills and different oil spill responses. A method for continuous and predictable in-line production of oil dispersions with defined size distribution of different oil qualities was successfully established. The system enables simultaneous comparison between the effects of different concentrations of dispersion and their corresponding equilibrium water soluble fractions. Thus, net effects of the oil droplet fraction may be estimated. The method provides data for comparing the toxicity of oil dispersions generated both mechanically and with the use of chemical dispersions, incorporating the toxicity of both dissolved oil and droplets of oil.