We simulate oil spills of 1500 and 4500 m3/day lasting 14, 45, and 90 days in the spawning grounds of the commercial fish species, Northeast Arctic cod. Modeling the life history of individual fish eggs and larvae, we predict deviations from the historical pattern of recruitment to the adult population due to toxic oil exposures. Reductions in survival for pelagic stages of cod were 0-10%, up to a maximum of 43%. These reductions resulted in a decrease in adult cod biomass of <3% for most scenarios, up to a maximum of 12%. In all simulations, the adult population remained at full reproductive potential with a sufficient number of juveniles surviving to replenish the population. The diverse age distribution helps protect the adult cod population from reductions in a single year's recruitment after a major oil spill. These results provide insights to assist in managing oil spill impacts on fisheries. | publishedVersion

This paper presents a novel method to select the optimal combination of grid resolution and number of Lagrangian elements (LEs) required in numerical modelling of oil concentrations at sea. A sensitivity analysis in terms of grid resolution and the number of LEs, was carried out to understand the uncertainty that these userdependent parameters introduce in the numerical results. A dataset of 211,200 simulations performed under 400 metocean patterns, 6 initial volumes, 11 grid resolutions, and different numbers of LEs (100 to 500,000), was used to analyze the sensitivity of the model along different Thresholds of Concern. Results show the importance of a correct selection of the number of LEs and the grid resolution in Lagrangian modelling of surface oil concentrations. The method proposed will allow selecting the optimal combination of these parameters to find an optimal balance between the accuracy and the computational cost of the simulation. | This work was partly carried out in the framework of the project PID2020-117267RB-I00 (COIL) funded by MCIN/AEI/10.13039/501100011033// and the project PDC2021-120892-I00 (BLOWHAZARD) funded by MCIN/AEI/10.13039/501100011033 and by European Union Next GenerationEU/PRTR.

With the development of marine oil industry, oil spill accidents will inevitably occur, further polluting the intertidal zone and causing biological poisoning. The muddy intertidal zone and Boleophthalmus pectinirostris were selected as the research objects to conduct indoor acute exposure experiments within 48 h of crude oil pollution. Statistical analysis was used to reveal the activity changes of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx) and glutathione S-transferase (GST) in the gills and liver of mudskipper. Then, integrated biomarker response (IBR) indicators were established to comprehensively evaluate the biological toxicity. The results showed that the activities of SOD, CAT and GST in livers were higher than those in gills, and the maximum induction multipliers of SOD, CAT and GPx in livers appeared earlier than those in gills. Both SOD and GPx activities were induced at low pollutant concentrations and inhibited at high pollutant concentrations. For the dose-effect, the change trends of CAT and SOD were roughly inversed. There was substrate competition between GPx and CAT, with opposite trends over time. The activating mechanism of GST was similar to that of GPx, and the activation time was earlier than that of GPx. In terms of dose-effect trends, the IBR showed that the antioxidant enzymes activities in biological tissues were induced by low and inhibited by high pollutant concentrations. Overall, SOD and GPx in gills and CAT and GST in livers of the mudskippers were suitable as representative markers to comprehensively analyze and evaluate the biotoxicity effects of oil pollution in the intertidal zone. The star plots and IBR values obtained after data standardization were consistent with the enzyme activity differences, which can be used as valid supplementary indexes for biotoxicity evaluation. These research findings provide theoretical support for early indicators of biological toxicity after crude oil pollution in intertidal zones.

Rehabilitation is often used to mitigate adverse effects of oil spills on wildlife. With an increase in production of alternatives to conventional crude oil such as diluted bitumen (dilbit), emergency spill responders and wildlife rehabilitators need information regarding the health and survival of free-ranging vertebrates exposed to dilbit under natural conditions. In 2010, one of the largest freshwater oil spills in the United States occurred in the Kalamazoo River in Michigan, when over 3.2 million liters of spilled dilbit impacted 56 km of riverine habitat. During 2010 and 2011 cleanup efforts, thousands of northern map turtles (Graptemys geographica) were captured from oiled stretches of the river, cleaned, rehabilitated, and released. We conducted extensive mark-recapture surveys in 2010, 2011, and 2018–2021, and used this dataset to evaluate the monthly survival probability of turtles 1–14 months post-spill and 8–11 years post-spill based on whether turtles were temporarily rehabilitated and released, overwintered in captivity and then released, or were released without rehabilitation. We found that rehabilitated or overwintered turtles had a higher probability of survival 1–14 months post-spill than non-rehabilitated turtles; however, 8–11 years post-spill the among-group differences in monthly survival probability had become negligible. Additionally, following the oil spill in 2010, nearly 6% of northern map turtles were recovered dead, died during rehabilitation, or suffered injuries that precluded release back into the wild. Our results demonstrate that exposure to dilbit in free ranging turtles causes direct mortality, while effort spent on the capture and rehabilitation of oiled freshwater turtles is important as it increases monthly survival 1–14 months post-spill.

The main objective of this study was to investigate the 2019 and 2022 oil spill events that occurred off the coast of the State of Ceará, Northeastern Brazil. To further assess these mysterious oil spills, we investigated whether the oils stranded on the beaches of Ceará in 2019 and 2022 had the same origin, whether their compositional differences were due to weathering processes, and whether the materials from both were natural or industrially processed. We collected oil samples in October 2019 and January 2022, soon after their appearance on the beaches. We applied a forensic environmental geochemistry approach using both one-dimensional and two-dimensional gas chromatography to assess chemical composition. The collected material had characteristics of crude oil and not refined oils. In addition, the 2022 oil samples collected over 130 km of the east coast of Ceará had a similar chemical profile and were thus considered to originate from the same source. However, these oils had distinct biomarker profiles compared to those of the 2019 oils, including resistant terpanes and triaromatic steranes, thus excluding the hypothesis that the oil that reached the coast of Ceará in January 2022 is related to the tragedy that occurred in 2019. From a geochemical perspective, the oil released in 2019 is more thermally mature than that released in 2022, with both having source rocks with distinct types of organic matter and depositional environments. As the coast of Ceará has vast ecological diversity and Marine Protected Areas, the possibility of occasional oil spills in the area causing severe environmental pollution should be investigated from multiple perspectives, including forensic environmental geochemistry.

Oil spills occurring either in oceans or inland waterways may cause serious economic losses and ecological damage. Previous studies pertaining to oil spills and their consequences are primarily based on marine environments, whereas few have focused on oil spills occurring in inland waterways characterised by pronounced flow advection transport effects, which differ from the marine environment. A generalised flume experiment is performed to investigate the spread and transport of oil spills, and the relationships between the area and thickness of oil slick over time are analysed parametrically. An oil spill model combined with a depth–integrated two–dimensional non–uniform flow model, which is suitable for modelling inland waterways based on the Lagrangian method, is established; it is calibrated and verified using measured data from the flume experiment. The model is applied to three scenarios on the Luoqi reach of the Yangtze River, and spilled oil drifting trajectory maps are obtained and analysed considering the field wind parameters. The results show that the drift distance of the oil slick in the inland waterway is primarily controlled by the flow velocity with effects of advection transport; however, the oil spill trajectory spreads toward the wind direction when the flow velocity is relatively small compared with the wind speed. The results of this study serve as a reference for predicting the spread and transport of oil spills in inland waterways.

The high density and viscosity of fuel oil leads to its prolonged persistence in the environment and causes widespread contamination. Dispersants with a low environmental impact are necessary for fuel oil spill remediation. This study aimed to formulate bio-based dispersants by mixing anionic biosurfactant (lipopeptides from Bacillus subtilis GY19) with nonionic oleochemical surfactant (Dehydol LS7TH). The synergistic effect of the anionic-nonionic surfactant mixture produced a Winsor Type III microemulsion, which promoted petroleum mobilization. The hydrophilic-lipophilic deviation (HLD) equations for ionic and nonionic surfactant mixtures were compared, and it was found that the ionic equation was applicable for the calculation of lipopeptides and Dehydol LS7TH concentrations. The best formula contained 6.6% w/v lipopeptides and 11.9% w/v Dehydol LS7TH in seawater, and its dispersion effectiveness for bunker fuels A and C was 92% and 78%, respectively. The application of bio-based dispersants in water sources was optimized by Box-Behnken design. The efficiency of the bio-based dispersant was affected by the dispersant-to-oil ratios (DORs) but not by the water salinity. A suitable range of DORs for different oil contamination levels could be identified from the response surface plot. The dispersed fuel oil was further degraded by adding an oil-degrading bacterial consortium to the chemically enhanced water accommodated fractions (CEWAFs). After 7 days of incubation, the concentration of fuel oil was reduced from 3692 mg/L to 356 mg/L (88% removal efficiency). On the other hand, the abiotic control removed less than 40% fuel oil from the CEWAFs. This bio-based dispersant had an efficiency comparable to that of a commercial dispersant. The process of dispersant formulation and optimization could be applied to other surfactant mixtures.

Crude oil pollution is a global environmental concern since it persists in the environment longer than most conventional carbon sources. In December 2014, the hyper-arid Evrona Nature Reserve, Israel, experienced large-scale contamination when crude oil spilled. The overarching goal of the study was to investigate the possible changes, caused by an accidental crude oil spill, in the leaf reflectance and biochemical composition of four natural habitat desert shrubs. The specific objectives were (1) to monitor the biochemical properties of dominant shrub species in the polluted and control areas; (2) to study the long-term consequences of the contamination; (3) to provide information that will assist in planning rehabilitation actions; and (4) to explore the feasibility of vegetation indices (VIs), along with the machine learning (ML) technique, for detecting stressed shrubs based on the full spectral range. Four measurement campaigns were conducted in 2018 and 2019. Along with the various stress indicators, field spectral measurements were performed in the range of 350–2500 nm. A regression analysis to examine the relation of leaf reflectance to biochemical contents was carried out, to reveal the relevant wavelengths in which polluted and control plants differ. Vegetation indices applied in previous studies were found to be less sensitive for indirect detection of long-term oil contamination. A novel spectral index, based on indicative spectral bands, named the “normalized blue-green stress index” (NBGSI), was established. The NBGSI distinguished significantly between shrubs located in the polluted and in the control areas. The NBGSI showed a strong linear correlation with pheophytin a. Machine learning classification algorithms obtained high overall prediction accuracy in distinguishing between shrubs located in the oil-polluted and the control sites, indicating internal component differences. The findings of this study demonstrate the efficacy of indirect and non-destructive spectral tools for detecting and monitoring oil pollution stress in shrubs.

Fossil fuels still prevail over other energy sources in the world’s consumption energy matrix. Thus, oil transportation and operations over maritime routes have been in high demand for a long time. Although oil spill accidents caused by these activities have reduced significantly over the last few decades, they still cause great concern. From this perspective, this paper presents simulation analyses of oil spill case studies using TELEMAC-3D hydrodynamic model coupled with an oil model. Hence a location susceptible to such accidents was selected and three real oil spills were simulated, for each of which there were official technical monitoring reports available. The obtained results contribute to the knowledge of oil pollution susceptibility in environmentally sensitive areas, as well as provide information concerning oil slick behaviour. Additionally, similarities between the modelled results and the technical reports were confirmed. These findings are useful for contingency planning and responding to these probable accidents.