Immiscible Rayleigh-Taylor turbulence: Implications for bacterial degradation in oil spills.

An unstable density stratification between two fluids mixes spontaneously under the effect of gravity, a phenomenon known as Rayleigh-Taylor (RT) turbulence. If the two fluids are immiscible, for example, oil and water, surface tension prevents intermixing at the molecular level. However, turbulence fragments one fluid into the other, generating an emulsion in which the typical droplet size decreases over time as a result of the competition between the rising kinetic energy and the surface energy density. Even though the first phenomenological theory describing this emulsification process was derived many years ago, it has remained elusive to experimental verification, hampering our ability to predict the fate of oil in applications such as deep-water spills. Here, we provide the first experimental and numerical verification of the immiscible RT turbulence theory, unveiling a unique turbulent state that originates at the oil-water interface due to the interaction of multiple capillary waves. We show that a single, non-dimensional, and time-independent parameter controls the range of validity of the theory. Our findings have wide-ranging implications for the understanding of the mixing of immiscible fluids. This includes in particular oil spills, where our work enables the prediction of the oil-water interface dynamics that ultimately determine the rate of oil biodegradation by marine bacteria.

Solvent Geometry Regulated J- and H-Type Aggregates of Photoswitchable Organogelator: Phase-Selective Thixotropic Gelation and Oil Spill Recovery.

We demonstrate supramolecular polymerization and formation of 1D nanofiber of azobenzene based organogelator (AZO-4) in cyclic hydrocarbon solvents (toluene and methylcyclohexane). The AZO-4 exhibits J- and H-type aggregates in toluene: MCH (9 : 1) and MCH: toluene (9 : 1) respectively. The type of aggregate was governed by the geometry of the solvents used in the self-assembly process. The J-type aggregates with high thermal stability in toluene is due to the enhanced interaction of AZO-4 π- surface with the toluene π-surface, whereas H-aggregate with moderate thermal stability in MCH was due to the interruption of the cyclic hydrocarbon in van der Waals interactions of peripheral chains of AZO-4 molecule. The light induced reversible photoisomerization is observed for both J- and H-aggregates. The macroscopic property revealed spontaneous and strong gelation in toluene preferably due to the strong interactions of the AZO-4 nanofibers with the toluene solvent molecules compared to the MCH. The rheological measurements revealed thixotropic nature of the gels by step-strain experiments at room temperature. The thermodynamic parameter (ΔHm) of gel-to-sol transition was determined for all the gels to get more insight into the gelation property. Furthermore, the phase selective gelation property was extended to the oil spill recovery application using diesel/water and petrol/water mixture.

Performance evaluation of rhamnolipid biosurfactant produced by Pseudomonas aeruginosa and its effect on marine oil-spill remediation.

This study aimed to reveal that the effect of biosurfactant on the dispersion and degradation of crude oil. Whole genome analysis showed that Pseudomonas aeruginosa GB-3 contained abundant genes involved in biosurfactant synthesis and metabolic processes and had the potential to degrade oil. The biosurfactant produced by strain GB-3 was screened by various methods. The results showed that the surface tension reduction activity was 28.6 mN·m-1 and emulsification stability was exhibited at different pH, salinity and temperature. The biosurfactant was identified as rhamnolipid by LC-MS and FTIR. The fermentation conditions of strain GB-3 were optimized by response surface methodology, finally the optimal system (carbon source: glucose, nitrogen source: ammonium sulfate, C/N ratio:16:1, pH: 7, temperature: 30-35 °C) was determined. Compared with the initial fermentation, the yield of biosurfactant increased by 4.4 times after optimization. In addition, rhamnolipid biosurfactant as a dispersant could make the dispersion of crude oil reach 38% within seven days, which enhanced the bioavailability of crude oil. As a biostimulant, it could also improve the activity of indigenous microorganism and increase the degradation rate of crude oil by 10-15%. This study suggested that rhamnolipid biosurfactant had application prospect in bioremediation of marine oil-spill.

Genome-wide DNA methylation changes in Oryzias melastigma embryos exposed to the water accommodated fraction of crude oil.

The water accommodated fraction (WAF) of crude oil exerts considerable impacts on marine fish during embryonic stage. Clarifying changes in epigenetic modifications is helpful for understanding the molecular mechanism underlying the toxicity of embryonic WAF exposure. The aim of this study was to explore genome-wide DNA methylation changes in Oryzias melastigma embryos after exposure to the nominal total petroleum hydrocarbon concentration of 500 µg/L in WAF for 7 days. Whole-genome bisulfite sequencing revealed that 8.47 % and 8.46 % of all the genomic C sites were methylated in the control and WAF-exposed groups, respectively. Among the three sequence contexts, methylated CG site had the largest number in both the two groups. The sequence preferences of nearby methylated cytosines were consistent between the two groups. A total of 4798 differentially methylated regions (DMRs) were identified in the promoter region. Furthermore, Gene Ontology analysis revealed that DMR-related genes were enriched mainly for functions related to development and nervous system. Additionally, the Kyoto Encyclopedia of Genes and Genomes pathways enriched in DMR-related genes were related to nervous system and endocrine system. These novel findings provide comprehensive insights into the genome-wide DNA methylation landscape of O. melastigma following embryonic WAF exposure, shedding light on the epigenetic regulatory mechanisms underlying WAF-induced toxicity.

Salmonid smolt caudal fin and liver transcriptome responses to low sulfur marine diesel and high sulfur fuel oil water accommodated fractions for assessing oil spill effects in marine environments.

The environmental impact of oil spills is a critical concern, particularly pertaining to low sulfur marine diesel (LSMD) and high sulfur fuel oil (HSFO) that are commonly involved in coastal spills. Although transcriptomic biomonitoring of sentinel animals can be a powerful tool for assessing biological effects, conventional methods utilize lethal sampling to examine the liver. As a non-lethal alternative, we have previously shown salmonid caudal fin cyp1a1 is significantly responsive to LSMD-derived toxicants. The present study further investigated the transcriptomic biomonitoring potential of coho salmon smolt caudal fin in comparison to liver tissue in the context of LSMD and HSFO seawater accommodated fraction (seaWAF) exposure in cold-water marine environments. Assessing the toxicity of these seaWAFs involved quantifying polycyclic aromatic hydrocarbon (tPAH50) concentrations and generating gene expression profiles. Initial qPCR analyses revealed significant cyp1a1 response in both liver and caudal fin tissues of both genetic sexes to all seaWAF exposures. RNA-Seq analysis, focusing on the highest LSMD and HSFO seaWAF concentrations (28.4±1.8 and 645.08±146.3 µg/L tPAH50, respectively), revealed distinct tissue-specific and genetic sex-independent transcriptomic responses with an overall enrichment of oxidative stress, cell adhesion, and morphogenesis-related pathways. Remarkably, the caudal fin tissue exhibited transcriptomic response patterns comparable to liver tissue, particularly consistent differential expression of 33 gene transcripts in the liver (independent of sex and oil type) and 44 in the caudal fin. The present work underscores the viability of using the caudal fin as a non-lethal alternative to liver sampling for assessing and tracking oil spill exposure in marine environments.

Offshore Oil Spill Detection Based on CNN, DBSCAN, and Hyperspectral Imaging.

Offshore oil spills have the potential to inflict substantial ecological damage, underscoring the critical importance of timely offshore oil spill detection and remediation. At present, offshore oil spill detection typically combines hyperspectral imaging with deep learning techniques. While these methodologies have made significant advancements, they prove inadequate in scenarios requiring real-time detection due to limited model detection speeds. To address this challenge, a method for detecting oil spill areas is introduced, combining convolutional neural networks (CNNs) with the DBSCAN clustering algorithm. This method aims to enhance the efficiency of oil spill area detection in real-time scenarios, providing a potential solution to the limitations posed by the intricate structures of existing models. The proposed method includes a pre-feature selection process applied to the spectral data, followed by pixel classification using a convolutional neural network (CNN) model. Subsequently, the DBSCAN algorithm is employed to segment oil spill areas from the classification results. To validate our proposed method, we simulate an offshore oil spill environment in the laboratory, utilizing a hyperspectral sensing device to collect data and create a dataset. We then compare our method with three other models-DRSNet, CNN-Visual Transformer, and GCN-conducting a comprehensive analysis to evaluate the advantages and limitations of each model.

OS-BREEZE: Oil Spills Boundary Red Emission Zone Estimation Using Unmanned Surface Vehicles.

Maritime transport, responsible for delivering over eighty percent of the world's goods, is the backbone of the global delivery industry. However, it also presents considerable environmental risks, particularly regarding aquatic contamination. Nearly ninety percent of marine oil spills near shores are attributed to human activities, highlighting the urgent need for continuous and effective surveillance. To address this pressing issue, this paper introduces a novel technique named OS-BREEZE. This method employs an Unmanned Surface Vehicle (USV) for assessing the extent of oil pollution on the sea surface. The OS-BREEZE algorithm directs the USV along the spill edge, facilitating rapid and accurate assessment of the contaminated area. The key contribution of this paper is the development of this novel approach for monitoring and managing marine pollution, which significantly reduces the path length required for mapping and estimating the size of the contaminated area. Furthermore, this paper presents a scale model experiment executed at the Coastal and Marine Engineering Research Institute (CAMERI). This experiment demonstrated the method's enhanced speed and efficiency compared to traditional monitoring techniques. The experiment was methodically conducted across four distinct scenarios: the initial and advanced stages of an oil spill at the outer anchoring, as well as scenarios at the inner docking on both the stern and port sides.

Managing deepsea oil spills through a systematic modeling approach.

Offshore oil exploration and production in deepwater are associated with environmental risks to marine ecosystems. This research introduces DWOSM (Deep Water Oil Spill Model), a three-dimensional Lagrangian model, which is developed to simulate the transport and fate of oil spills resulting from subsea blowouts. DWOSM comprises three interconnected modules: DWOSM-DSD, which predicts the oil droplet size distribution from a blowout release; DWOSM-NearField, simulating plume dynamics and tracking oil droplets within the plume region; and DWOSM-FarField, modeling the evolution of dispersed oil beyond the near-field. Compared to other oil spill models, this integrated approach improves the transition between near and far fields using a near-field particle tracking algorithm. It also employs the thermodynamic models to enable the prediction of oil properties under varying deep water pressure and temperature. To gauge the reliability and efficacy of DWOSM, a hypothetical case situated within a North American context is employed for model testing. The DWOSM and its each module are juxtaposed with other established oil spill models. The outcomes indicate that DWOSM yields comparable results to these models by providing reasonable predictions of a deepwater blowout. The model's verification through case scenario testing and comparison underscores its potential as a decision tool for assessing and managing the potential environmental impacts of offshore petroleum activities.

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.

Use of TLM derived models to estimate toxicity of weathered MC252 oil based on conventional chemical data and the potential impact of unresolved polar components.

Target lipid model (TLM) and toxic unit (TU) approaches were applied to ecotoxicity and chemistry data from low-energy WAFs (LE-WAFs) of source and weathered crude oils originating from the Deepwater Horizon oil spill. The weathered oils included artificially weathered oils and naturally weathered samples collected in the Gulf of Mexico after the spill. Oil weathering greatly reduced the concentrations of identified LE-WAF components, however, the mass of uncharacterized polar material (UPC) in the LE-WAFs remained largely unchanged during the weathering process. While the TLM-derived calculations displayed a significant decrease in toxicity (TUs) for the heavily weathered oils, copepod toxicity, expressed as LC10-based TUs, were comparable between LE-WAFs of fresh and weathered oils. The discrepancy between observed and predicted toxicity for the LE-WAFs of artificially weathered oils may be related to limitations by the chemical analyses or increased toxicity due to generation of new unknown compounds during the weathering process.

A review of the prospects, efficacy and sustainability of nanotechnology-based approaches for oil spill remediation.

Numerous marine oil spill incidents and their environmental catastrophe have raised the concern of the research community and environmental agencies on the topic of the offshore crude oil spill. The oil transport through oil tankers and pipelines has further aggravated the risk of the oil spill. This has led to the necessity to develop an effective, environment-friendly, versatile oil spill clean-up strategy. The current review article analyses various nanotechnology-based methods for marine oil spill clean-up, focusing on their recovery rate, reusability and cost. The authors weighed the three primary factors recovery, reusability and cost distinctively for the analysis based on their significance in various contexts. The findings and analysis suggest that magnetic nanomaterials and nano-sorbent have been the most effective nanotechnology-based marine oil spill remediation techniques, with the magnetic paper based on ultralong hydroxyapatite nanowires standing out with a recovery rate of over 99%. The chitosan-silica hybrid nano-sorbent and multi-wall carbon nanotubes are also promising options with high recovery rates of up to 95-98% and the ability to be reused multiple times. Although the photocatalytic biodegradation approach and the nano-dispersion method do not offer benefits for recovery or reusability, they can nevertheless help lessen the negative ecological effects of marine oil spills. Therefore, careful evaluation and selection of the most appropriate method for each marine oil spill situation is crucial. The current review article provides valuable insights into the current state of nanotechnology-based marine oil spill clean-up methods and their potential applications.

Superhydrophobic magnetic Fe3O4 polyurethane sponges for oil-water separation and oil-spill recovery.

The effective and affordable separation of oil and water, a crucial process in the safe handling of environmental disasters such as crude oil spills and recovery of valuable resources, is a highly sought-after yet challenging task. Herein, superhydrophobic PU sponge was fabricated for the fast and cost-effective adsorptive separation of oil and different organic solvents from water. Octadecyltrichlorosilane (OTS)-functionalized Fe3O4@SiO2 core-shell microspheres were dip-coated on the surface of porous materials via a dip-coating process, thereby endowing them with superhydrophobicity. Owing to the hydrophobic interaction between OTS molecules and oil and increased capillary force in the micropores, the resulting superhydrophobic sponge served as a selective oil-sorbent scaffold for absorbing oil from oil-water mixtures, including oil-water suspensions and emulsions. Remarkably, after the recovery of the adsorbed oil via mechanical extrusion, these superhydrophobic materials could be reused multiple times and maintain their oil-water separation efficacy even after 10 oil-water separation cycles.

Nontraditional Occupational Exposures to Crude Oil Combustion Disasters and Respiratory Disease Risk: A Narrative Review of Literature.

PURPOSE OF REVIEW: Burning of petroleum products has been consistently associated with adverse respiratory health effects. Combustion of crude oil, specifically, produces toxic byproducts, but there have been relatively few studies of health effects. Burning of crude oil is increasingly employed as a means of mitigating environmental disasters despite the potential health risks to workers involved in clean-up efforts. Here, we review epidemiological studies of respiratory effects following unique crude oil burning events to (1) characterize respiratory health effects from this nontraditional occupational exposure and (2) identify approaches used to characterize exposures that could be applied to future disaster-related studies. RECENT FINDINGS: We searched PubMed and EMBASE for references from inception to January 30, 2023. We also manually screened references cited in eligible articles. We identified 14 eligible publications. Our review suggests that exposure to crude oil combustion has adverse respiratory effects, including reduced lung function and increased occurrence of respiratory symptoms and disease. However, the evidence is inconsistent, and quality of data varied across studies. While some studies used quantitative, modeled exposure estimates, most used self-reported proxies of exposure. Although disasters involving crude oil combustion are relatively rare, limited evidence suggests that some worker populations may be at risk for respiratory effects from burning exposures in disaster settings. Future studies that use improved exposure assessment methods (e.g., personal monitors, remote sensing data) may help further quantify the respiratory risk from crude oil burning exposures.

A wave energy driven high-performance self-powered oil spill positioner.

The oil spill positioner is capable of real-time monitoring oil films on the sea surface. However, the lack of high-performance power supply methods greatly restricts the application of oil spill positioner. In this research, we design a high-performance self-powered oil spill positioner based on a soft-contact-triboelectric-nanogenerator (SC-TENG). This device achieves soft-contact by attaching rabbit fur to the rotor, which can effectively reduce frictional resistance, quickly transfer charge to the electrode, and improve the durability of the parts. First, we calculate the highest occupied molecular orbital and the lowest unoccupied molecular orbital of polytetrafluoroethylene (PTFE) and polyvinylidene fluoride (PVDF) molecules through first-principles simulations, and compared the ease of electron excitation between the two materials. The results show that the performance of SC-TENG with PVDF as dielectric material is significantly better than that of PTFE. At the same time, this phenomenon has been confirmed by experiments. On the basis of experimental and simulate research on two types of power management circuits, a bridge rectifier circuit with the function of converting alternating current to direct current is selected to realize the self-power supply of the oil spill positioner. Additionally, by optimizing the structure of the SC-TENG and employing a bridge rectifier circuit, the SC-TENG can achieve a maximum open-circuit voltage of 1400 V and a short-circuit current of 3.49µA, which are enough to light up 200 light-emitting diodes and power the oil spill positioner. Finally, we simulate the open-circuit voltage and short-circuit current of the SC-TENG on a six-degree-of-freedom platform and test its durability under real-world ocean wave conditions, all of which show excellent performance. This work develops an efficient wave energy conversion mechanism and successfully realizes the high-performance self-powering of the oil spill positioner, making oil spill monitoring more flexible and reliable.

Transport of Microplastic and Dispersed Oil Co-contaminants in the Marine Environment.

Microplastics (MPs) and oil pollution are major concerns in oceans. Although their coexistence in oceans and the associated MP-oil-dispersant agglomerates (MODAs) have been reported, limited attention is given to the behavior of the co-contaminants. This study investigated MODA transport in a simulated ocean system and explored related mechanisms under various oil types, salinities, and mineral concentrations. We found that more than 90% of the heavy oil-formed MODAs stayed at the seawater surface, while the light oil-formed MODAs were widely distributed throughout the seawater column. The increased salinity promoted MODAs formed by 7 and 90 µm MPs to transport from the seawater surface to the column. This was elucidated by the Derjaguin-Landau-Verwey-Overbeek theory as more MODAs formed under higher salinities and dispersants kept them stable in the seawater column. Minerals facilitated the sinking of large MP-formed MODAs (e.g., 40 µm) as minerals were adsorbed on the MODA surface, but their impact on small MP-formed MODAs (e.g., 7 µm) was negligible. A MODA-mineral system was proposed to explain their interaction. Rubey's equation was recommended to predict the sinking velocity of MODAs. This study is the first attempt to reveal MODA transport. Findings will contribute to the model development to facilitate their environmental risk evaluation in oceans.

Chemical Weathering Patterns of Diluted Bitumen Spilled into Freshwater Limnocorrals.

Due to the sudden nature of oil spills, few controlled studies have documented how oil weathers immediately following accidental release into a natural lake environment. Here, we evaluated the weathering patterns of Cold Lake Winter Blend, a diluted bitumen (dilbit) product, by performing a series of controlled spills into limnocorrals installed in a freshwater lake in Northern Ontario, Canada. Using a regression-based design, we added seven different dilbit volumes, ranging from 1.5 to 180 L, resulting in oil-to-water ratios between 1:71,000 (v/v) and 1:500 (v/v). We monitored changes in the composition of various petroleum hydrocarbons (PHCs), including n-alkanes, polycyclic aromatic hydrocarbons (PAHs), and oil biomarkers in dilbit over time, as it naturally weathered for 70 days. Depletion rate constants (kD) of n-alkanes and PAHs ranged from 0.0009 to 0.41 d-1 and 0.0008 to 0.38 d-1, respectively. There was no significant relationship between kD and spill volume, suggesting that spill size did not influence the depletion of petroleum hydrocarbons from the slick. Diagnostic ratios calculated from concentrations of n-alkanes, isoprenoids, and PAHs indicated that evaporation and photooxidation were major processes contributing to dilbit weathering, whereas dissolution and biodegradation were less important. These results demonstrate the usefulness of large scale field studies carried out under realistic environmental conditions to elucidate the role of different weathering processes following a dilbit spill.

Deep or Shallow? A Comparative Analysis on the Oil Species Identification Based on Excitation-Emission Matrix and Multiple Machine Learning Algorithms.

With the continuous expansion of petroleum extraction, transportation, and storage, the risk of oil spills at sea has also increased, posing a serious threat to marine safety. The excitation-emission matrix (EEM), which is composed of the fluorometric spectra under multiple excitation wavelengths, becomes a feasible approach to identify oil species. Despite the fact that various machine learning models have been applied to analyse EEMs of oil pollutants, it is unclear how much improvements the deep learning models have achieved, especially comparing with the shallow learning models. This paper presents a comparative analysis on the oil species identification using four types of machine learning models: random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), and deep convolutional neural network (DCNN). The fluorescence of some common oils was excited using a tuneable xenon lamp and collected with a high-resolution spectrometer to form the EEMs for model training and testing.The results show that SVM, BPNN, and DCNN achieved high identification accuracies that are more than 93% on all types of oils tested in the study. The two deep learning models didn't have significant improvement over the SVM model. Considering the fact that the deep learning models require much larger number of calculations and longer running time, the SVM tends to be more suitable for oil species identification when considering the balance between the model accuracy and efficiency. This study provides some guidance on the choices of oil species identification model in the cases of oil spills.

Long-term biodegradation of crude oil in high-arctic backshore sediments: The Baffin Island Oil Spill (BIOS) after nearly four decades.

With an on-going disproportional warming of the Arctic Ocean and the reduction of the sea ice cover, the risk of an accidental oil spill from ships or future oil exploration is increasing. It is hence important to know how crude oil weathers in this environment and what factors affect oil biodegradation in the Arctic. However, this topic is currently poorly studied. In the 1980s, the Baffin Island Oil Spill (BIOS) project carried out a series of simulated oil spills in the backshore zone of beaches located on Baffin Island in the Canadian High Arctic. In this study two BIOS sites were re-visited, offering the unique opportunity to study the long-term weathering of crude oil under Arctic conditions. Here we show that residual oil remains present at these sites even after almost four decades since the original oiling. Oil at both BIOS sites appears to have attenuated very slowly with estimated loss rates of 1.8-2.7% per year. The presence of residual oil continues to significantly affect sediment microbial communities at the sites as manifested by a significantly decreased diversity, differences in the abundance of microorganisms and an enrichment of putative oil-degrading bacteria in oiled sediments. Reconstructed genomes of putative oil degraders suggest that only a subset is specifically adapted for growth under psychrothermic conditions, further reducing the time for biodegradation during the already short Arctic summers. Altogether, this study shows that crude oil spilled in the Arctic can persist and significantly affect the Arctic ecosystem for a long time, in the order of several decades.

An experimental oil spill at a tidal freshwater wetland along the St. Lawrence River re-visited after 21 years.

In 1999, a tidal wetland located along the St. Lawrence River close to Ste. Croix de Lotbinière (Quebec, Eastern Canada) was the site of an experimental oil spill. Test plots were established and subjected to an experimental crude oil spill to evaluate natural attenuation, nutrient amendment and vegetation cropping as countermeasures. In 2020, this study re-visited the test plots to investigate residual oil and habitat recovery. Only concentrations of mid-chain length n-alkanes (C10-C36), but not of polycyclic aromatic hydrocarbons (PAHs), were significantly above detection limit, and were detected in both test plot and control sediments. Hydrocarbon, total organic carbon, nitrogen and phosphate contents did not differ significantly between test plot and control sediments. Microbial analyses did not detect significant differences in microbial load, microbial diversity or microbial community composition between test plot and control sediments. Key genes for the aerobic and anaerobic degradation of n-alkanes as well as for the aerobic degradation of PAHs were detected in all sediment samples. Associated gene abundances did not differ significantly between test plot and control sediments. This study shows that oil-exposed test plot sediments of the Ste. Croix wetland can be considered completely recovered after 21 years irrespective of the performed countermeasure.

The recalcitrance and potential toxicity of polycyclic aromatic hydrocarbons within crude oil residues in beach sediments at the BIOS site, nearly forty years later.

The Arctic is a unique environment characterized by extreme conditions, including daylight patterns, sea ice cover, and some of the lowest temperatures on Earth. Such characteristics in tandem present challenges when extrapolating information from oil spill research within warmer, more temperate regions. Consequently, oil spill studies must be conducted within the Arctic to yield accurate and reliable results. Sites of the Baffin Island Oil Spill (BIOS) project (Cape Hatt, Baffin Island, Canadian Arctic) were revisited nearly 40 years after the original oil application to provide long-term monitoring data for Arctic oil spill research. Surface and subsurface sediment samples were collected from the intertidal zone of the 1981 nearshore oil spill experiment (Bay 11), from 1980 supratidal control plots (Crude Oil Point) and 1982 supratidal treatment plots (Bay 106). Samples were analyzed for Polycyclic Aromatic Hydrocarbons (PAHs) and alkylated homologues via Gas Chromatography - Mass Spectrometry (GC-MS). Our results suggest that total mean concentrations of all measured PAHs range from 0.049 to 14 mg/kg, whereas total mean concentrations of the 16 US EPA priority PAHs range from 0.02 to 2.1 mg/kg. The relative proportions of individual PAHs were compared between sampling sites and with the original technical mixture. Where available, percent loss of individual PAHs was compared with data from samples collected at the BIOS site, in 2001. All three sites featured samples where concentrations of various priority PAHs exceeded the established Interim Marine Sediment Quality Guidelines. All supratidal samples contained potentially toxic levels of PAHs. Even after nearly four decades of weathering, the recalcitrant crude oil residues remain a potential hazard for the native organisms. Continued monitoring of this unique study site is crucial for establishing a timeline for oil degradation, and to observe a reduction in toxicity over time.