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The chemical composition of spilt oils from events that took place on the north-eastern coast of Brazil in 2019 and 2022 was investigated to better understand their sources, and post-spill processes. Oils from both events originated from different sources, based on their fingerprints, hydrocarbons composition and specific biomarkers, such as the C23 tricyclic terpane and oleanane. Despite the differences, the source rocks share similarities in paleoenvironments and depositional conditions and both oils suffered little weathering, mainly due to evaporation and dissolution. Our findings for 2019 spilt oil reinforce that it is a mixed product, enriched both in lighter n-alkanes and 25-norhopanes. Differently, the 2022 samples exhibited characteristics of a non-processed crude oil that originated from a paraffinic deposit in storage tanks. The molecular composition and diagnostic ratios reported for samples from these spill events help to establish baselines for ongoing monitoring of oil spills in marine ecosystems.

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The environmental and economic impact of an oil spill can be significant. Biotechnologies applied during a marine oil spill involve bioaugmentation with immobilised or encapsulated indigenous hydrocarbonoclastic species selected under laboratory conditions to improve degradation rates. The environmental factors that act as stressors and impact the effectiveness of hydrocarbon removal are one of the challenges associated with these applications. Understanding how native microbes react to environmental stresses is necessary for effective bioaugmentation. Herein, Micrococcus luteus and M. yunnanensis isolated from a marine oil spill mooring system showed hydrocarbonoclastic activity on Maya crude oil in a short time by means of total petroleum hydrocarbons (TPH) at 144 h: M. luteus up to 98.79 % and M. yunnanensis 97.77 % removal. The assessment of Micrococcus biofilms at different temperature (30 °C and 50 °C), pH (5, 6, 7, 8, 9), salinity (30, 50, 60, 70, 80 g/L), and crude oil concentration (1, 5, 15, 25, 35 %) showed different response to the stressors depending on the strain. According to response surface analysis, the main effect was temperature > salinity > hydrocarbon concentration. The hydrocarbonoclastic biofilm architecture was characterised using scanning electron microscopy (SEM) and atomic force microscopy (AFM). Subtle but significant differences were observed: pili in M. luteus by SEM and the topographical differences measured by AFM Power Spectral Density (PSD) analysis, roughness was higher in M. luteus than in M. yunnanensis. In all three domains of life, the Universal Stress Protein (Usp) is crucial for stress adaptation. Herein, the uspA gene expression was analysed in Micrococcus biofilm under environmental stressors. The uspA expression increased up to 2.5-fold in M. luteus biofilms at 30 °C, and 1.3-fold at 50 °C. The highest uspA expression was recorded in M. yunnanensis biofilms at 50 °C with 2.5 and 3-fold with salinities of 50, 60, and 80 g/L at hydrocarbon concentrations of 15, 25, and 35 %. M. yunnanensis biofilms showed greater resilience than M. luteus biofilms when exposed to harsh environmental stressors. M. yunnanensis biofilms were thicker than M. luteus biofilms. Both biofilm responses to environmental stressors through uspA gene expression were consistent with the behaviours observed in the response surface analyses. The uspA gene is a suitable biomarker for assessing environmental stressors of potential microorganisms for bioremediation of marine oil spills and for biosensing the ecophysiological status of native microbiota in a marine petroleum environment.

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Marine oil spills pose significant ecological and economic threats worldwide, requiring effective decision-making tools. In this study, the optimal parameters, and configurations for Deep Learning models in oil spill classification and segmentation using Sentinel-1 SAR imagery were identified. First, a new Sentinel-1 image dataset was created. Ninety CNN configurations were explored for classification by varying the number of convolutional layers, filters, hidden layers, and neurons in each layer. For segmentation tasks, MLP and U-Net models were evaluated with variations in convolutional layers, filters, and incorporation of IoU and Focal Loss. The results indicated that a CNN model with six layers, 32 filters, and two hidden layers achieved 99 % classification accuracy. For segmentation, the U-Net model with more layers and filters using Focal Loss achieved 99 % accuracy and 96 % IoU. Therefore, a CNN and U-Net framework was proposed that achieves an overall accuracy of 95 % and an IoU of 90 %.

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In 2019, one of Brazil's most significant environmental disasters occurred, involving an oil spill that directly affected Pernambuco state. Contamination along the coast was evaluated by the quantification of polycyclic aromatic hydrocarbons (PAHs) in fifty seawater samples collected in the summer and winter of 2021. Analysis using fluorescence spectroscopy revealed that for all the samples, levels of dissolved/dispersed petroleum hydrocarbons (DDPHs) were higher than the regional baseline for tropical western shores of the Atlantic Ocean. GC-MS analyses quantified 17 PAHs in the samples, with highest total PAHs concentrations of 234 ng L-1 in summer and 33.3 ng L-1 in winter, which were consistent with the highest risks observed in ecotoxicity assays. The use of diagnostic ratios showed that the coast was impacted by a mixture of PAHs from petrogenic and pyrolytic sources. The results indicated the need for continuous monitoring of the regions affected by the 2019 spill.

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Tons of crude oil were found on the Brazilian coast in 2019, and studies assessing its chemical composition are still scarce. This study aimed to develop a new and simple technique of cold vapor generation using infrared irradiation coupled with atomic absorption spectrometry to determine mercury content in sediments contaminated by crude oil. Experimental conditions were evaluated, including formic acid concentration, reactor temperature, and carrier gas flow rate. The accuracy of the method was validated by comparison with mercury contents in a certified reference material (PACS-2). The detection limit was found to be 0.44 µg kg-1. The developed method was applied to determine the total mercury content in marine sediment samples collected from beaches in Ceará State. Mercury concentrations ranged from 0.41 to 0.95 mg kg-1. The proposed method is efficient, simple, low-cost, and adequate for its purpose.

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Mangroves are prone to biotic and abiotic stressors of natural and anthropogenic origin, of which oil pollution is one of the most harmful. Yet the response of mangrove species to acute and chronic oil exposure, as well as to other stressors, remains barely documented. In this study, a non-destructive, non-invasive approach based on field spectroscopy is proposed to unravel these responses. The approach relies on tracking alterations in foliar traits (pigments, sugars, phenols, and specific leaf area) from reflectance data in the 400-2400 nm spectral range. Three mangrove species hit by two of the most notorious oil spills in Brazilian history (1983 and 2019) and various biotic stressors, including grazing, parasitism, and fungal disease, were investigated through field spectroscopy and machine learning. This study reveals strong intra- and interspecific variability of mangrove's spectral and biochemical responses to oil pollution. Trees undergoing acute exposure to oil showed stronger alterations of foliar traits than the chronically exposed ones. Alterations induced by biotic stressors such as parasitism, disease, and grazing were successfully discriminated from those of oil for all species based on Linear Discriminant Analysis (Overall Accuracy ≥76.40% and Kappa ≥0.70). Leaf chlorophyll, phenol, and starch contents were identified as the most relevant traits in stressor discrimination. The study highlights that oil spills affect mangroves uniquely, both acutely and chronically, threatening their global conservation.

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Sea turtle mortality is often related to materials that reach the coast from different anthropic activities worldwide. This study aimed to investigate whether sea turtle mortality was related to older marine problems, such as solid waste, or one of the largest oil spill accidents on the Brazilian coast, that occurred in 2019. We posed three questions: 1) Are there solid residues in the digestive tract samples, and which typology is the most abundant? 2) Can meso­ and macro-waste marine pollutants cause mortality? 3) Is the dark material found really oil? A total of 25 gastrointestinal content (GC) samples were obtained, of which 22 ingested waste of anthropogenic origin and 18 were necropsied. These 22 samples were obtained during or after the 2019 oil spill, of which 17 specimens were affected, making it possible to suggest oil ingestion with the cause of death in the animals that could be necropsied. Macroscopic data showed that the most abundant solid waste was plastic (76.05 %), followed by fabrics (12.18 %) and oil-like materials. However, chemical data confirmed only three specimens with oil levels ranging from remnants to high. It was possible to infer possible causes of death in 16 of the total 18 necropsied cases: Most deaths were due to respiratory arrest (62.5 %), followed by pulmonary edema (12.5 %), cachexia syndrome (12.5 %), circulatory shock (6.25 %), and head trauma (6.25 %), which may have been caused by contact with solid waste, oil, or both. The study showed that not all dark material found in the GCs of turtles killed in oiled areas is truly oil, and in this sense, a chemical analysis step to prove the evidence of oil must be added to international protocols.

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A large-scale oil spill along the northeastern Brazilian coast in 2019-2020 severely impacted primary manatee habitats in Brazil. This study aimed to assess metal and metalloid contamination in a dead manatee calf found following this oil spill. Several elements were detected, including chromium, iron, nickel, lead, and vanadium, which are crude oil components, and thallium, a component of dispersants used to degrade and dissipate crude oil. The presence of these contaminants in the manatee calf is indicative of maternal exposure, metabolism, and newborn transference via placenta and lactation. This is the first report of mother-calf metal transfer in manatees, highlighting the species' vulnerability and potential long-term population dynamics effects, and the first report for several metals and metalloids in these animals, laying the foundation for future research efforts. These findings highlight the urgent need for continued environmental monitoring, ecotoxicological assessments, and conservation initiatives.

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Remote sensing data and numerical simulation are important tools to rebuild any oil spill accident letting to identify its source and trajectory. Through these tools was identified an oil spill that affected Oaxacan coast in October 2022. The SAR images were processed with a standard method included in SNAP software, and the numerical simulation was made using Lagrangian transport model included in GNOME software. With the combining of these tools was possible to discriminate the look-alikes from true oil slicks; which are the main issue when satellite images are used. Obtained results showed that 4.3m3 of crude oil were released into the ocean from a punctual point of oil pollution. This oil spill was classified such as a small oil spill. The marine currents and weathering processes were the main drivers that controlled the crude oil displacement and its dispersion. It was estimated in GNOME that 1.6 m3 of crude oil was floating on the sea (37.2 %), 2.4 m3 was evaporated into the atmosphere (55.8 %) and 0.3 m3 reached the coast of Oaxaca (7 %). This event affected 82 km of coastline, but the most important touristic areas as well as turtle nesting zones were not affected by this small crude oil spill. Results indicated that the marine-gas-pump number 3 in Salina Cruz, Oaxaca, is a punctual point of oil pollution in the Southern Mexican Pacific Ocean. Further work is needed to assess the economic and ecological damage to Oaxacan coast caused by this small oil spill.

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The oil spill environmental sensitivity index is a key tool for preventing and dealing with environmental disasters caused by oil spills. This study aims to review the available literature on the subject and highlight the importance of methodological advances to improve how the index is applied in continental areas, especially in regions crossed by pipelines. Most current mapping techniques focus on coastal areas and fail to consider the stretches of land that are vulnerable to geodynamic natural disasters. In this context, the need to implement environmental sensitivity indices specific for pipelines has become urgent. This study also presents an overview of the main accidents around the world and a detailed analysis of the history of Brazilian disasters related to oil spills along continental stretches, with a focus on pipelines and natural disasters. In addition, this work highlights the importance of carrying out new research in mountainous areas of Brazil and is aimed at preventing Natechs (natural hazard triggering technological disasters) and improving contingency plans. As a result, several pathways have been identified, which involves the necessity of resolving gaps in terrestrial environmental sensitivity mapping methodologies, particularly as applied to pipelines. Furthermore, solutions must be capable of integrating terrestrial, fluvial, coastal, and maritime environmental sensitivity mapping techniques. Moreover, the need to implement dynamic risk monitoring systems in real time is critical to help manage such a complex problem.

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Recent arrivals of tar balls have been observed in several tropical beaches associated with the oceanic circulation that flows to the Brazilian continental shelf. Between August and September 2022, tar balls were collected in the northeastern coast of Brazil and analyzed. Nearly 90 % of the oils were colonized by barnacles, polychaetes, decapods, and algae. Most rafting organisms were Lepas anserifera with capitulum measuring 0.32 to 22.21 mm. Based on the growth rate of barnacles and the speed of the SEC it was estimated that tar balls were floating since July and August 2022 and traveled a maximum of 1938.82 km. The organisms and tar balls' possible origin is in the international waters, near to the meso-Atlantic ridge, known for oil tanker traffic. The tar balls, in addition to the oil-related impacts, can act as a vector of long-distance species dispersion, and it needs to raise an alert, considering the possible ecological impacts.

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After the oil spill disaster occurred in 2019, various events of tar balls reaching the Brazilian coast and archipelagos have been reported. The hypothesis here is that the oil/waste dumped in international waters by ships on-route to Cape of Good Hope is reaching the Brazilian coast. On that account, 30-year probabilistic simulations were used to estimate the probability of dumped oil residue reaching the Brazilian coast. The simulations considered three Zones following the South Atlantic route. The results have shown that up to 28.5 % of large ships could dump oil on-route. Inside the Brazilian Exclusive Economic Zone, the probability of dumped oil/waste reaching the coastline is about 62 % and quickly decreases for Dumping Zones 2 and 3. Equatorial and Northeast shores of Brazil are the most vulnerable to oceanic dumping when compared to other regions.

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This research presents a procedure for determining the origin of marine pollution through the use of a time-direct trajectory modeling, associated with a Kriging metamodel technique and Monte Carlo random sampling. These methods were applied to a real case, specifically the oil spill that affected the Brazilian coast in the second half of 2019 and early 2020. A total of 140 trajectories, defined by the geographical coordinates of the origin and the spill date, were generated through Latin Hypercube Sampling and simulated using the PyGNOME model to construct the Kriging metamodel. The metamodel demonstrated cost-effectiveness by efficiently simulating numerous input data combinations which were compared and optimized based on available real data regarding temporal and spatial pollution distribution.

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In 2019, the largest oil spill ever recorded in tropical oceans in terms of extent occurred in Brazil. The oil from the spill was collected directly from the environment and used in an exposure experiment with the endangered reef-building coral Mussismilia harttii. The treatments of the experiment were control (without oil), 1% oil, 2.5% oil, and direct contact of coral with oil. The most abundant hydrocarbon in the seawater of the experiment was phenatrene, which is toxic to corals. However, overall, the concentration of PAHs was not very high. The analysis of the maximum photosynthetic capacity of Symbiodiniaceae dinoflagellates showed a small impact of oil on corals, mainly on the contact treatment. However, coral microbiomes were affected in all oil treatments, with the contact treatment showing the most pronounced impact. A greater number and abundance of stress-indicating and potentially pathogenic bacteria were found in all oil treatments. Finally, this highly weathered oil that had lain in the ocean for a long time was carrying potentially coral-pathogenic bacteria within the Vibrionaceae family and was able to transmit some of these bacteria to corals. Bacteria within Vibrionaceae are the main causes of disease in different species of corals and other marine organisms.

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Since its introduction comprehensive two-dimensional gas chromatography (GC × GC) has been widely applied to analyze complex samples due to its enhanced peak capacity and selectivity, thereby increasing the number of identifiable peaks and improving coelution issues. Even though it is still undergoing development, GC × GC provides many advantages in the analysis of petroleum-derived samples, whether in reservoir geochemistry applications or in environmental studies associated with spilled oils. In general, it facilitates more thorough fingerprinting and compositional evaluation. In environmental studies, it helps enhance understanding of weathering processes and the environmental behavior of hydrocarbons, as its chromatographic retention indices can robustly estimate liquid vapor pressures, aqueous solubility and other physical chemical properties. This review presents a brief history of GC × GC instrumentation, discussing recent and significant advances in petroleum applications, from data handling techniques to reservoir geochemistry and environmental forensics, as well as some specific advantages achieved and certain limitations that continue to be encountered.

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Multiple studies have focused on the effect of long-term weathering processes on oils after spill events, without considering the chemical compositional changes occurring shortly after the release of oil into the environment. Therefore, the present study provides a broad chemical characterization for understanding of the changes occurring in the chemical compositions of intermediate (°API = 27.0) and heavy (°API = 20.9) oils from the Sergipe-Alagoas basin submitted to two simulated situations, one under marine conditions and the other in a riverine environment. Samples of the oils were collected during the first 72 h of contact with the simulated environments, followed by evaluation of their chemical compositions. SARA fractionation was used to isolate the resins, which were characterized at the molecular level by UHRMS. The evaporation process was highlighted, with the GC-FID chromatographic profiles showing the disappearance of compounds from n-C10 until n-C16, as well as changes in the weathering indexes and pristane + n-C17/phytane + n-C18 ratios for the crude oils submitted to the riverine conditions. Analysis of the resins fraction showed that basic polar compounds underwent little or no alterations during the early stages of weathering. The marine environment was shown to be much less oxidative than the riverine environment. For both environments, a feature highlighted was an increase of acidic oxygenated compounds with the increase of weathering, especially for the crude oil with °API = 27.0.

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This study simulates the spillage of 1460 metric tons of oil that occurred in January 2022 off La Pampilla Refinery, in central Perú. The oil slick was predominantly displaced northward along the coastline, driven by prevailing currents and winds in the region. The weathering analysis revealed that the removal of oil was mainly due to evaporation (28%) and beaching processes (70%) within 96 h after the initial release. The coastal areas spanning from Ventanilla to Punta Chancay experienced significant impacts from the oil spill, representing 96% of the total affected coastal extent. Specifically, Ventanilla and Santa Rosa Beaches and the National Reserve System of Islands were heavily impacted during the first 24 h, while the surroundings of Ancón Bay, Aucallama and Pasamayo beaches were affected after two days. This modeling case study provides valuable insights into the fate and transport of the Repsol oil spill.

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Since the 2019 oil spill on the northeastern coast of Brazil, oil materials have washed up on the beaches. A characteristic of the recent oil spill that began in late August was that some of the oiled material, such as tarballs, contained the goose barnacle species Lepas anatifera (Cirripedia, Lepadomorpha), which is well-known for its cosmopolitan distribution and wide occurrence in the oceans. The findings of this study provide information on the occurrence and contamination of petroleum hydrocarbons in animals adhered to the surfaces of tarballs sampled from beaches in the Brazilian states of Ceará and Rio Grande do Norte, between September and November 2022. The size of the barnacles varied from 0.122 to 2.20 cm, suggesting that the tarballs had been floating in the ocean for at least a month. All groups of L. anatifera collected from the tarballs had polycyclic aromatic hydrocarbons (PAHs) present (∑21PAHs from 476.33 to 3816.53 ng g-1). In comparison to high-molecular-weight PAHs, which are primarily from pyrolytic sources, low-molecular-weight PAHs, such as naphthalene and phenanthrene, which are mostly related to petrogenic sources, were shown to be more abundant. In addition, dibenzothiophene, which is exclusive of petrogenic origin, was found in all samples (30.74-537.76 ng g-1). The aliphatic hydrocarbons (AHs): n-alkanes, pristane, and phytane were also found and displayed petroleum characteristics. These results highlight the danger of increasing the absorption of petrogenic PAHs and AHs by organisms that use tarballs as substrates. L. anatifera is a crucial component of the food chain because many animals such as crabs, starfish, and gastropods consume it.

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Petroleum activity and the dumping of domestic and industrial sewage are important sources of mercury (Hg) contamination in the aquatic environment. Thus, this article aimed to biomonitor the Hg concentration in fish, mussels, and swimming crabs of commercial importance in southeastern Brazil. The quantifications were carried out over a year to verify the influence of seasonality. Finally, a risk assessment was applied to identify whether the concentrations found could lead to long-term damage to the population. Our results indicate that the contaminations were higher in spring, summer, and winter than in autumn, mainly among fish and swimming crabs. The results of quantification in the animal and estimated monthly intake, despite being below the limit established nationally and internationally, were indicative of risk for these two animals after calculating the Hazard quotient. The highest risk values were attributed to the infant population. Based on the data generated by this work, the consumption of mussels is encouraged throughout the year, to the detriment of the other types of seafood studied, especially during summer, spring, and winter. Our work reinforces the importance of risk assessment for a more reliable understanding of the impact of contaminants in seafood on the population's health.

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After the wide oil spill reached the northeast of Brazil, the resurgence of oil was recorded and to evaluate this oil in detail, two samples collected in the state of Pernambuco in 2019 and 2021 were submitted to multiple analytical techniques. For both, we have found similar saturated biomarkers and triaromatic steroid ratios, implying that they are from the same spilled source. The n-alkanes, isoprenoids, and cycloalkanes were almost completely degraded due to evaporation, photooxidation, and/or biodegradation processes. The preferential loss of less alkylated PAHs than the more alkylated ones suggests that biodegradation was the most active process. This hypothesis is reinforced by the formation of mono and dicarboxylic acids assessed by GC × GC-TOFMS and ESI(-) FT-ICR MS high-resolution techniques. Furthermore, based on the ESI(-) FT-ICR MS results, three new ratios were proposed to evaluate the progress of the biodegradation process over time: Ox>2/O, SOx/SO, and SOx/N.

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