Modeling oil weathering and transport in sea ice

Modeling study on oil spill transport in the Great Lakes: The unignorable impact of ice cover

The rise in oil trade and transportation has led to a continuous increase in the risk of oil spills, posing a serious worldwide concern. However, there is a lack of numerical models for predicting oil spill transport in freshwater, especially under icy conditions. To tackle this challenge, we developed a prediction system for oil with ice modeling by coupling the General NOAA Operational Modeling Environment (GNOME) model with the Great Lakes Operational Forecast System (GLOFS) model. Taking Lake Erie as a pilot study, we used observed drifter data to evaluate the performance of the coupled model. Additionally, we developed six hypothetical oil spill cases in Lake Erie, considering both with and without ice conditions during the freezing, stable, and melting seasons spanning from 2018 to 2022, to investigate the impacts of ice cover on oil spill processes. The results showed the effective performance of the coupled model system in capturing the movements of a deployed drifter. Through ensemble simulations, it was observed that the stable season with high-concentration ice had the most significant impact on limiting oil transport compared to the freezing and melting seasons, resulting in an oil-affected open water area of 49 km2 on day 5 with ice cover, while without ice cover it reached 183 km2. The stable season with high-concentration ice showed a notable reduction in the probability of oil presence in the risk map, whereas this reduction effect was less prominent during the freezing and melting seasons. Moreover, negative correlations between initial ice concentration and oil-affected open water area were consistent, especially on day 1 with a linear regression R-squared value of 0.94, potentially enabling rapid prediction. Overall, the coupled model system serves as a useful tool for simulating oil spills in the world's largest freshwater system, particularly under icy conditions, thus enhancing the formulation of effective emergency response strategies.

Quantitative review summarizing the effects of oil pollution on subarctic and arctic marine invertebrates

While meta-analyses are common in the health and some biological sciences, there is a lack of such analyses for petroleum-related marine research. Oil is a highly complex substance consisting of thousands of different compounds. Measurement limitations, different protocols and a lack of standards in recording and reporting various elements of laboratory experiments impede attempts to homogenize and compare data and identify trends. Nevertheless, oil toxicology research would benefit from meta-analyses, through which we could develop meaningful research questions and design robust experiments. Here we report findings from an effort to quantitatively summarize results from oil toxicology studies on arctic and subarctic marine invertebrates. We discovered that the vast majority of studies was conducted on crustaceans, followed by molluscs. Analyzing the sensitivity of response measures across taxa we found that the most sensitive responses tend to rank low in ecological relevance, while less sensitive response measures tend to be more ecologically relevant. We further uncovered that crustaceans appear to be more sensitive to mechanically dispersed than chemically dispersed oil while the opposite seems true for molluscs, albeit not statistically significant. Both crustaceans and molluscs show a higher sensitivity to fresh than to weathered oil. No differences in the sensitivities of crustacean life stages were found. However, due to a lack of data, many questions remain unanswered. Our study revealed that while trends in responses can be elucidated, heterogeneous experimental protocols and reporting regimes prevent a proper meta-analysis.

Recent advances in chemical and biological degradation of spilled oil: A review of dispersants application in the marine environment

Growing concerns over the risk of accidental releases of oil into the marine environment have emphasized our need to improve both oil spill preparedness and response strategies. Among the available spill response options, dispersants offer the advantages of breaking oil slicks into small oil droplets and promoting their dilution, dissolution, and biodegradation within the water column. Thus dispersants can reduce the probability of oil slicks at sea from reaching coastal regions and reduce their direct impact on mammals, sea birds and shoreline ecosystems. To facilitate marine oil spill response operations, especially addressing spill incidents in remote/Arctic offshore regions, an in-depth understanding of the transportation, fate and effects of naturally/chemically dispersed oil is of great importance. This review provides a synthesis of recent research results studies related to the application of dispersants at the surface and in the deep sea, the fate and transportation of naturally and chemically dispersed oil, and dispersant application in the Arctic and ice-covered waters. Future perspectives have been provided to identify the research gaps and help industries and spill response organizations develop science-based guidelines and protocols for the application of dispersants application.

Methods for Interpreting the Partitioning and Fate of Petroleum Hydrocarbons in a Sea Ice Environment

Decreases in Arctic Sea ice extent and thickness have led to more open ice conditions, encouraging both shipping traffic and oil exploration within the northern Arctic. As a result, the increased potential for accidental releases of crude oil or fuel into the Arctic environment threatens the pristine marine environment, its ecosystem, and local inhabitants. Thus, there is a need to develop a better understanding of oil behavior in a sea ice environment on a microscopic level. Computational quantum chemistry was used to simulate the effects of evaporation, dissolution, and partitioning within sea ice. Vapor pressures, solubilities, octanol-water partition coefficients, and molecular volumes were calculated using quantum chemistry and thermodynamics for pure liquid solutes (oil constituents) of interest. These calculations incorporated experimentally measured temperatures and salinities taken throughout an oil-in-ice mesocosm experiment conducted at the University of Manitoba in 2017. Their potential for interpreting the relative movements of oil constituents was assessed. Our results suggest that the relative movement of oil constituents is influenced by differences in physical properties. Lighter molecules showed a greater tendency to be controlled by brine advection processes due to their greater solubility. Molecules which are more hydrophobic were found to concentrate in areas of lower salt concentration.

Toxicity to sea urchin embryos of crude and bunker oils weathered under ice alone and mixed with dispersant

A multi-index approach (larval lenghthening and malformations, developmental disruption, and genotoxicity) was applied using sea-urchin embryos as test-organisms. PAH levels measured in the under-ice weathered aqueous fraction (UIWAF) were lower than in the low-energy water accommodated fraction (LEWAF) and similar amongst UIWAFs of different oils. UIWAFs and LEWAFs caused toxic effects, more markedly in UIWAFs, that could not be attributed to measured individual PAHs or to their mixture. Conversely, UIWAF was less genotoxic than LEWAF, most likely because naphthalene concentrations were also lower. In agreement, NAN LEWAF, the most genotoxic, exhibited the highest naphthalene levels. Dispersant addition produced less consistent changes in PAH levels and embryo toxicity in UIWAFs than in LEWAFs, and did not modify LEWAF genotoxicity. Overall, under ice weathering resulted in lowered waterborne PAHs and genotoxicity but augmented embryo toxicity, not modified by dispersant application.

Investigation into the geometry and distribution of oil inclusions in sea ice using non-destructive X-ray microtomography and its implications for remote sensing and mitigation potential

As climate change brings reduced sea ice cover and longer ice-free summers to the Arctic, northern Canada is experiencing an increase in shipping and industrial activity in this sensitive region. Disappearing sea ice, therefore, makes the Arctic region susceptible to accidental releases of different types of oil and fuel pollution resulting in a pressing need for the development of appropriate scientific knowledge necessary to inform regulatory policy formulation. In this study, we examine the microstructure of the surficial layers of sea ice exposed to oil using X-ray microtomography. Through analysis, 3D imaging of the spatial distribution of the ice's components (brine, air, and oil) were made. Additional quantitative information regarding the size, proximity, orientation, and geometry of oil inclusions were computed to ascertain discernable relationships between oil and the other components of the ice. Our results indicate implications for airborne remote sensing and bioremediation of the upper sea ice layers.

Selection of oil spill response method in Arctic offshore waters: A fuzzy decision tree based framework

A fuzzy decision tree (FDT) based framework was developed to facilitate the selection of suitable oil spill response methods in the Arctic. Hypothetical oil spill cases were developed based on six identified attributes, while the suitability of three spill response methods (mechanical containment and recovery, use of chemical dispersants, and in-situ burning) for each spill case was obtained based on expert judgments. Fuzzy sets were used to address the associated uncertainties, and FDTs were then developed through generating: i) one decision tree for all three response methods (FDT-AP1) and ii) one decision tree for each response method and the development of linear regression models at terminal nodes (FDT-LR). The FDT-LR approach exhibited higher prediction accuracy than the FDT-AP1 approach. A maximum of 100% accurate predictions could be achieved for testing cases using it. On average, 75% of suitable oil spill response methods out of 10,000 performed iterations were predicted correctly.

Ecological Risk Assessment of Oil Spills in Ice-Covered Waters: A Surface Slick Model Coupled with a Food-Web Bioaccumulation Model

The limited knowledge on oil-ice interactions and on the ecological outcomes of oil spills in the Arctic represent sources of uncertainties for shipping and oil and gas activities in polar regions. The present work aims at the definition of the ecological risk posed by oil spills in the Arctic by the integration of an improved surface slick model to a fugacity-based food-web bioaccumulation model for icy waters. The model's outcomes are the representation of transport and weathering processes and the concentrations of a toxic component of oil, namely naphthalene, in the environmental media as a function of ice conditions. Given those concentrations, the associated ecological risk is defined in terms of the bioconcentration factor (BCF). Overall, the model predicted low bioaccumulation and biomagnification potential for naphthalene to a hypothetical Arctic food web, regardless of the ice concentration. Integr Environ Assess Manag 2020;16:729-744. © 2020 SETAC.

Modelling of oil thickness in the presence of an ice edge

Oil slick thickness is a key parameter for the behaviour of oil spilled at sea. It influences evaporation and entrainment, viable response options, and the risk to marine life at the surface. Determining this value is therefore of high relevance in oil spill modelling. In open water, oil can spread as thin films due to gravity alone, and may be further dispersed by horizontal diffusion and differential advection. In the presence of ice, however, a thin oil slick may become concentrated to higher thickness, if compressed against the ice edge. In the present study, we develop a simple model for the thickness of oil forced against a barrier by a current. We compare our theory to flume experiments, and obtain reasonable agreement. We describe an implementation in a Lagrangian oil spill model, and present some examples. We discuss the operational applicability, and suggest further research needs.

Model-based reconstruction of the Ulysse-Virginia oil spill, October-November 2018

In response to the oil spill caused by the collision between the Ro-Ro ship Ulysse and CSL Virginia on 7^th October 2018, the Lagrangian oil spill model MEDSLIK-II was utilized to predict spill transport and fate. Oil drift was forced by the high-resolution sea circulation provided by CMEMS and the ECMWF wind. Successive model runs were restarted 5 times with the distinct overflight- and satellite-derived observations provided by REMPEC and the Copernicus Sentinel-1 mission. The results were verified based on the ability to predict the first oil-beaching event that happened near Saint-Tropez (France) in the early afternoon of 16^th October. Despite the general consistency among the runs, only the last initialization was able to forecast the oil beaching. Stochastic MEDSLIK-II simulations forced by the historical meteo-oceanographic datasets 2014-2018 revealed that the coastlines between Cap Lardier and the Gulf of Saint-Tropez were among the most impacted areas.

Impacts of Oil Spills on Arctic Marine Ecosystems: A Quantitative and Probabilistic Risk Assessment Perspective

Oil spills resulting from maritime accidents pose a poorly understood risk to the Arctic environment. We propose a novel probabilistic method to quantitatively assess these risks. Our method accounts for spatiotemporally varying population distributions, the spreading of oil, and seasonally varying species-specific exposure potential and sensitivity to oil. It quantifies risk with explicit uncertainty estimates, enables one to compare risks over large geographic areas, and produces information on a meaningful scale for decision-making. We demonstrate the method by assessing the short-term risks oil spills pose to polar bears, ringed seals, and walrus in the Kara Sea, the western part of the Northern Sea Route. The risks differ considerably between species, spatial locations, and seasons. Our results support current aspirations to ban heavy fuel oil in the Arctic but show that we should not underestimate the risks of lighter oils either, as these oils can pollute larger areas than heavier ones. Our results also highlight the importance of spatially explicit season-specific oil spill risk assessment in the Arctic and that environmental variability and the lack of data are a major source of uncertainty related to the oil spill impacts.

Performance of a simple backtracking method for marine oil source searching in a 3D ocean

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.

Oil behavior in sea ice: Changes in chemical composition and resultant effect on sea ice dielectrics

There has been increasing urgency to develop methods for detecting oil in sea ice owing to the effects of climate change in the Arctic. A multidisciplinary study of crude oil behavior in a sea ice environment was conducted at the University of Manitoba during the winter of 2016. In the experiment, medium-light crude oil was injected underneath young sea ice in a mesocosm. The physical and thermodynamic properties of the oil-infiltrated sea ice were monitored over a three-week time span, with concomitant analysis of the oil composition using analytical instrumentation. A resonant perturbation technique was used to measure the oil dielectric properties, and the contaminated sea ice dielectric properties were modeled using a mixture model approach. Results showed that the interactions between the oil and sea ice altered their physical and thermodynamic properties. These changes led to an overall decrease in sea ice dielectrics, potentially detectable by remote sensing systems.

An ecological risk assessment model for Arctic oil spills from a subsea pipeline

There is significant risk associated with increased oil and gas exploration activities in the Arctic Ocean. This paper presents a probabilistic methodology for Ecological Risk Assessment (ERA) of accidental oil spills in this region. A fugacity approach is adopted to model the fate and transport of released oil, taking into account the uncertainty of input variables. This assists in predicting the 95th percentile Predicted Exposure Concentration (PEC_95%) of pollutants in different media. The 5th percentile Predicted No Effect Concentration (PNEC_5%) is obtained from toxicity data for 19 species. A model based on Dynamic Bayesian Network (DBN) is developed to assess the ecological risk posed to the aquatic community. The model enables accounting for the occurrence likelihood of input parameters, as well as analyzing the time-variable risk profile caused by seasonal changes. It is observed through the results that previous probabilistic methods developed for ERA can be overestimating the risk level.

Modelling and assessment of accidental oil release from damaged subsea pipelines

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.