Hot and Cold: Photochemical Weathering Mediates Oil Properties and Fate Differently Depending on Seawater Temperature.

Photochemical weathering transforms petroleum oil and changes its bulk physical properties, as well as its partitioning into seawater. This transformation process is likely to occur in a cold water marine oil spill, but little is known about the behavior of photochemically weathered oil in cold water. We quantified the effect of photochemical weathering on oil properties and partitioning across temperatures. Compared to weathering in the dark, photochemical weathering increases oil viscosity and water-soluble content, decreases oil-seawater interfacial tension, and slightly increases density. Many of these photochemical changes are much larger than changes caused by evaporative weathering. Further, the viscosity and water-soluble content of photochemically weathered oil are more temperature-sensitive compared to evaporatively weathered oil, which changes the importance of key fate processes in warm versus cold environments. Compared to at 30 °C, photochemically weathered oil at 5 °C would have a 16× higher viscosity and a 7× lower water-soluble content, resulting in lower entrainment and dissolution. Collectively, the physical properties and thus fate of photochemically weathered oil in a cold water spill may be substantially different from those in a warm water spill. These differences could affect the choice of oil spill response options in cold, high-light environments.

Towards integrated modeling of the long-term impacts of oil spills.

Although great progress has been made to advance the scientific understanding of oil spills, tools for integrated assessment modeling of the long-term impacts on ecosystems, socioeconomics and human health are lacking. The objective of this study was to develop a conceptual framework that could be used to answer stakeholder questions about oil spill impacts and to identify knowledge gaps and future integration priorities. The framework was initially separated into four knowledge domains (ocean environment, biological ecosystems, socioeconomics, and human health) whose interactions were explored by gathering stakeholder questions through public engagement, assimilating expert input about existing models, and consolidating information through a system dynamics approach. This synthesis resulted in a causal loop diagram from which the interconnectivity of the system could be visualized. Results of this analysis indicate that the system naturally separates into two tiers, ocean environment and biological ecosystems versus socioeconomics and human health. As a result, ocean environment and ecosystem models could be used to provide input to explore human health and socioeconomic variables in hypothetical scenarios. At decadal-plus time scales, the analysis emphasized that human domains influence the natural domains through changes in oil-spill related laws and regulations. Although data gaps were identified in all four model domains, the socioeconomics and human health domains are the least established. Considerable future work is needed to address research gaps and to create fully coupled quantitative integrative assessment models that can be used in strategic decision-making that will optimize recoveries from future large oil spills.

Partial Photochemical Oxidation Was a Dominant Fate of Deepwater Horizon Surface Oil.

Following the Deepwater Horizon (DWH) blowout in 2010, oil floated on the Gulf of Mexico for over 100 days. In the aftermath of the blowout, substantial accumulation of partially oxidized surface oil was reported, but the pathways that formed these oxidized residues are poorly constrained. Here we provide five quantitative lines of evidence demonstrating that oxidation by sunlight largely accounts for the partially oxidized surface oil. First, residence time on the sunlit sea surface, where photochemical reactions occur, was the strongest predictor of partial oxidation. Second, two-thirds of the partial oxidation from 2010 to 2016 occurred in less than 10 days on the sunlit sea surface, prior to coastal deposition. Third, multiple diagnostic biodegradation indices, including octadecane to phytane, suggest that partial oxidation of oil on the sunlit sea surface was largely driven by an abiotic process. Fourth, in the laboratory, the dominant photochemical oxidation pathway of DWH oil was partial oxidation to oxygenated residues rather than complete oxidation to CO2. Fifth, estimates of partial photo-oxidation calculated with photochemical rate modeling overlap with observed oxidation. We suggest that photo-oxidation of surface oil has fundamental implications for the response approach, damage assessment, and ecosystem restoration in the aftermath of an oil spill, and that oil fate models for the DWH spill should be modified to accurately reflect the role of sunlight.

Parsing the toxicity paradox: Composition and duration of exposure alter predicted oil spill effects by orders of magnitude.

Oil spilled into an aquatic environment produces oil droplet and dissolved component concentrations and compositions that are highly variable in space and time. Toxic effects on aquatic biota vary with sensitivity of the organism, concentration, composition, environmental conditions, and frequency and duration of exposure to the mixture of oil-derived dissolved compounds. For a range of spill (surface, subsea, blowout) and oil types under different environmental conditions, modeling of oil transport, fate, and organism behavior was used to quantify expected exposures over time for planktonic, motile, and stationary organisms. Different toxicity models were applied to these exposure time histories to characterize the influential roles of composition, concentration, and duration of exposure on aquatic toxicity. Misrepresenting these roles and exposures can affect results by orders of magnitude. Well-characterized laboratory studies for <24-hour exposures are needed to improve toxicity predictions of the typically short-term exposures that characterize spills.

Bridging the lab to field divide: Advancing oil spill biological effects models requires revisiting aquatic toxicity testing.

Oil fate and exposure modeling addresses the complexities of oil composition, weathering, partitioning in the environment, and the distributions and behaviors of aquatic biota to estimate exposure histories, i.e., oil component concentrations and environmental conditions experienced over time. Several approaches with increasing levels of complexity (i.e., aquatic toxicity model tiers, corresponding to varying purposes and applications) have been and continue to be developed to predict adverse effects resulting from these exposures. At Tiers 1 and 2, toxicity-based screening thresholds for assumed representative oil component compositions are used to inform spill response and risk evaluations, requiring limited toxicity data, analytical oil characterizations, and computer resources. Concentration-response relationships are employed in Tier 3 to quantify effects of assumed oil component mixture compositions. Oil spill modeling capabilities presently allow predictions of spatial and temporal compositional changes during exposure, which support mixture-based modeling frameworks. Such approaches rely on summed effects of components using toxic units to enable more realistic analyses (Tier 4). This review provides guidance for toxicological studies to inform the development of, provide input to, and validate Tier 4 aquatic toxicity models for assessing oil spill effects on aquatic biota. Evaluation of organisms' exposure histories using a toxic unit model reflects the current state-of the-science and provides an improved approach for quantifying effects of oil constituents on aquatic organisms. Since the mixture compositions in toxicity tests are not representative of field exposures, modelers rely on studies using single compounds to build toxicity models accounting for the additive effects of dynamic mixture exposures that occur after spills. Single compound toxicity data are needed to quantify the influence of exposure duration and modifying environmental factors (e.g., temperature, light) on observed effects for advancing use of this framework. Well-characterized whole oil bioassay data should be used to validate and refine these models.

Adopting a toxic unit model paradigm in design, analysis and interpretation of oil toxicity testing.

The lack of a conceptual understanding and unifying quantitative framework to guide conduct and interpretation of laboratory oil toxicity tests, has led investigators to divergent conclusions that can confuse stakeholders and impede sound decision-making. While a plethora of oil toxicity studies are available and continue to be published, due to differences in experimental design, results between studies often cannot be compared. Furthermore, much resulting data fails to advance quantitative effect models that are critically needed for oil spill risk and impact assessments. This paper discusses the challenges posed when evaluating oil toxicity test data based on traditional, total concentration-based exposure metrics and offers solutions for improving the state of practice by adopting a unifying toxic unit (TU) model framework. Key advantages of a TU framework is that differences in test oil composition, sensitivity of the test organism/endpoint, and toxicity test design (i.e., type of test) can be taken into quantitative account in predicting aquatic toxicity. This paradigm shift is intended to bridge the utility of laboratory oil toxicity tests with improved assessment of effects in the field. To illustrate these advantages, results from literature studies are reassessed and contrasted with conclusions obtained based on past practice. Using instructive examples, model results are presented to explain how dissolved oil composition and concentrations and resulting TUs vary in WAFs prepared using variable loading or dilution test designs and the important role that unmeasured oil components contribute to predicted oil toxicity. Model results are used to highlight how the TU framework can serve as a valuable aid in designing and interpreting empirical toxicity tests and provide the data required to validate/refine predictive toxicity models. To further promote consistent exposure and hazard assessment of physically and chemically dispersed oil toxicity tests recommendations for advancing the TU framework are presented.

Recommendations for the advancement of oil-in-water media and source oil characterization in aquatic toxicity test studies.

During toxicity testing, chemical analyses of oil and exposure media samples are needed to allow comparison of results between different tests as well as to assist with identification of the drivers and mechanisms for the toxic effects observed. However, to maximize the ability to compare results between different laboratories and biota, it has long been recognized that guidelines for standard protocols were needed. In 2005, the Chemical Response to Oil Spills: Ecological Effects Research Forum (CROSERF) protocol was developed with existing common analytical methods that described a standard method for reproducible preparation of exposure media as well as recommended specific analytical methods and analyte lists for comparative toxicity testing. At the time, the primary purpose for the data collected was to inform oil spill response and contingency planning. Since then, with improvements in both analytical equipment and methods, the use of toxicity data has expanded to include their integration into fate and effect models that aim to extend the applicability of lab-based study results to make predictions for field system-level impacts. This paper focuses on providing a summary of current chemical analyses for characterization of oil and exposure media used during aquatic toxicity testing and makes recommendations for the minimum analyses needed to allow for interpretation and modeling purposes.

Counter-historical study of alternative dispersant use in the Deepwater Horizon oil spill response.

Recent completion of oil fate modeling and a mass budget of the Deepwater Horizon (DWH) oil spill allows for a counter-historical study using quantitative Comparative Risk Assessment (CRA) methodology. Novel application of subsea dispersant injection (SSDI) during the response reduced surfacing oil, volatile organic carbon emissions, and oil on shorelines. The effectiveness of that application, and potential alternatives had dispersant not been used or been used more aggressively, were evaluated by modifying and comparing the validated oil fate model under different SSDI strategies. A comparison of mass balance results, exposure metrics, and CRA scoring for Valued Ecological Components (VECs) shows the value of SSDI in achieving risk reduction and tradeoffs that were made. Actual SSDI applied during the DWH oil spill reduced exposures to varying degrees for different VECs. Exposures and relative risks across the ecosystem would have been substantially reduced with more effective SSDI.

Validation of oil fate and mass balance for the Deepwater Horizon oil spill: Evaluation of water column partitioning.

Model predictions of oil transport and fate for the 2010 Deepwater Horizon oil spill (Gulf of Mexico) were compared to field observations and absolute and relative concentrations of oil compounds in samples from 900 to 1400 m depth <11 km from the well. Chemical partitioning analyses using quantitative indices support a bimodal droplet size distribution model for oil released during subsea dispersant applications in June with 74% of the mass in >1 mm droplets that surfaced near the spill site within a few hours, and 1-8% as <0.13 mm microdroplets that remained below 900 m. Analyses focused on 900-1400 m depth <11 km from the well indicate there was substantial biodegradation of dissolved components, some biodegradation in microdroplets, recirculation of weathered microdroplets into the wellhead area, and marine oil snow settling from above 900 m carrying more-weathered particulate oil into the deep plume.

Oil fate and mass balance for the Deepwater Horizon oil spill.

Based on oil fate modeling of the Deepwater Horizon spill through August 2010, during June and July 2010, ~89% of the oil surfaced, ~5% entered (by dissolving or as microdroplets) the deep plume (>900 m), and ~6% dissolved and biodegraded between 900 m and 40 m. Subsea dispersant application reduced surfacing oil by ~7% and evaporation of volatiles by ~26%. By July 2011, of the total oil, ~41% evaporated, ~15% was ashore and in nearshore (<10 m) sediments, ~3% was removed by responders, ~38.4% was in the water column (partially degraded; 29% shallower and 9.4% deeper than 40 m), and ~2.6% sedimented in waters >10 m (including 1.5% after August 2010). Volatile and soluble fractions that did not evaporate biodegraded by the end of August 2010, leaving residual oil to disperse and potentially settle. Model estimates were validated by comparison to field observations of floating oil and atmospheric emissions.

Sensitivity of modeled oil fate and exposure from a subsea blowout to oil droplet sizes, depth, dispersant use, and degradation rates.

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.

Modeling atmospheric volatile organic compound concentrations resulting from a deepwater oil well blowout - Mitigation by subsea dispersant injection.

The atmospheric concentrations of volatile organic compounds (VOCs) generated by surface slicks during an oil spill have not been extensively studied. We modeled oil transport and fate, air emissions, and atmospheric dispersion of VOCs from a hypothetical deepwater well blowout in De Soto Canyon of the Gulf of Mexico assuming no intervention and use of SubSea Dispersant Injection (SSDI) at the source during three week-long periods representing different atmospheric mixing conditions. Spatially varying time histories of atmospheric VOCs within ~2 km from the release site were estimated. As compared to the no-intervention case, SSDI dispersed the discharged oil over a larger water volume at depth and enhanced VOC dissolution and biodegradation, thereby reducing both the total mass of VOCs released to the atmosphere and the concentration of VOCs within 2 km from the release site. Atmospheric conditions also influenced the VOC concentrations, although to a lesser degree than SSDI.

Potential impacts of offshore oil spills on polar bears in the Chukchi Sea.

Sea ice decline is anticipated to increase human access to the Arctic Ocean allowing for offshore oil and gas development in once inaccessible areas. Given the potential negative consequences of an oil spill on marine wildlife populations in the Arctic, it is important to understand the magnitude of impact a large spill could have on wildlife to inform response planning efforts. In this study we simulated oil spills that released 25,000 barrels of oil for 30 days in autumn originating from two sites in the Chukchi Sea (one in Russia and one in the U.S.) and tracked the distribution of oil for 76 days. We then determined the potential impact such a spill might have on polar bears (Ursus maritimus) and their habitat by overlapping spills with maps of polar bear habitat and movement trajectories. Only a small proportion (1-10%) of high-value polar bear sea ice habitat was directly affected by oil sufficient to impact bears. However, 27-38% of polar bears in the region were potentially exposed to oil. Oil consistently had the highest probability of reaching Wrangel and Herald islands, important areas of denning and summer terrestrial habitat. Oil did not reach polar bears until approximately 3 weeks after the spills. Our study found the potential for significant impacts to polar bears under a worst case discharge scenario, but suggests that there is a window of time where effective containment efforts could minimize exposure to bears. Our study provides a framework for wildlife managers and planners to assess the level of response that would be required to treat exposed wildlife and where spill response equipment might be best stationed. While the size of spill we simulated has a low probability of occurring, it provides an upper limit for planners to consider when crafting response plans.

Photochemical oxidation reduced the efficacy of aerial dispersants applied in response to the Deepwater Horizon spill.

Chemical dispersants are one of many tools used to mitigate the overall environmental impact of oil spills. In principle, dispersants break up floating oil into small droplets that disperse into the water column where they are subject to multiple fate and transport processes. The effectiveness of dispersants typically decreases as oil weathers in the environment. This decrease in effectiveness is often attributed to evaporation and emulsification, with the contribution of photochemical weathering assumed to be negligible. Here, we aim to test this assumption using Macondo well oil released during the Deepwater Horizon spill as a case study. Our results indicate that the effects of photochemical weathering on Deepwater Horizon oil properties and dispersant effectiveness can greatly outweigh the effects of evaporative weathering. The decrease in dispersant effectiveness after light exposure was principally driven by the decreased solubility of photo-oxidized crude oil residues in the solvent system that comprises COREXIT EC9500A. Kinetic modeling combined with geospatial analysis demonstrated that a considerable fraction of aerial applications targeting Deepwater Horizon surface oil had low dispersant effectiveness. Collectively, the results of this study challenge the paradigm that photochemical weathering has a negligible impact on the effectiveness of oil spill response and provide critical insights into the "window of opportunity" to apply chemical dispersants in response to oil spills in sunlit waters.

Comparative risk assessment of spill response options for a deepwater oil well blowout: Part III. Stakeholder engagement.

This paper describes oil spill stakeholder engagement in a recent comparative risk assessment (CRA) project that examined the tradeoffs associated with a hypothetical offshore well blowout in the Gulf of Mexico, with a specific focus on subsea dispersant injection (SSDI) at the wellhead. SSDI is a new technology deployed during the Deepwater Horizon (DWH) oil spill response. Oil spill stakeholders include decision makers, who will consider whether to integrate SSDI into future tradeoff decisions. This CRA considered the tradeoffs associated with three sets of response strategies: (1) no intervention; (2) mechanical recovery, in-situ burning, and surface dispersants; and, (3) SSDI in addition to responses in (2). For context, the paper begins with a historical review of U.S. policy and engagement with oil spill stakeholders regarding dispersants. Stakeholder activities throughout the project involved decision-maker representatives and their advisors to inform the approach and consider CRA utility in future oil spill preparedness.

Comparative risk assessment of oil spill response options for a deepwater oil well blowout: Part II. Relative risk methodology.

Subsea dispersant injection (SSDI) was a new oil spill response (OSR) technology deployed during the Deepwater Horizon accident. To integrate SSDI into future OSR decisions, a hypothetical deepwater oil spill to the Gulf of Mexico was simulated and a comparative risk assessment (CRA) tool applied to contrast three response strategies: (1) no intervention; (2) mechanical recovery, in-situ burning, and surface dispersants; and, (3) SSDI in addition to responses in (2). A comparative ecological risk assessment (CRA) was applied to multiple valued ecosystem components (VECs) inhabiting different environmental compartments (ECs) using EC-specific exposure and relative VEC population density and recovery time indices. Results demonstrated the added benefit of SSDI since relative risks to shoreline, surface wildlife and most aquatic life VECs were reduced. Sensitivity of results to different assumptions was also tested to illustrate flexibility of the CRA tool in addressing different stakeholder priorities for mitigating the impacts of a deepwater blowout.

Comparative Risk Assessment of spill response options for a deepwater oil well blowout: Part 1. Oil spill modeling.

Oil spill model simulations of a deepwater blowout in the Gulf of Mexico De Soto Canyon, assuming no intervention and various response options (i.e., subsea dispersant injection SSDI, in addition to mechanical recovery, in-situ burning, and surface dispersant application) were compared. Predicted oil fate, amount and area of surfaced oil, and exposure concentrations in the water column above potential effects thresholds were used as inputs to a Comparative Risk Assessment to identify response strategies that minimize long-term impacts. SSDI reduced human and wildlife exposure to volatile organic compounds; dispersed oil into a large water volume at depth; enhanced biodegradation; and reduced surface water, nearshore and shoreline exposure to floating oil and entrained/dissolved oil in the upper water column. Tradeoffs included increased oil exposures at depth. However, since organisms are less abundant below 200 m, results indicate that overall exposure of valued ecosystem components was minimized by use of SSDI.

An algorithm for modeling entrainment and naturally and chemically dispersed oil droplet size distribution under surface breaking wave conditions.

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<~50µm) is developed in the near surface water.

Application of an Integrated Blowout Model System, OILMAP DEEP, to the Deepwater Horizon (DWH) Spill.

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.

Development of a unified oil droplet size distribution model with application to surface breaking waves and subsea blowout releases considering dispersant effects.

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.