Search Results (893)

This study aims to improve the process of characterizing oil on the sea surface using synthetic aperture radar (SAR) imagery, seeking to increase the accuracy of oil slick classification as natural or anthropogenic. A set of spatial attributes was obtained using semivariograms and phase-space pictures. This novel approach demonstrated potential to add value for monitoring seepage phenomena, which is of great scientific and environmental importance. The results achieved have potential for operational application as an aid in understanding active petroleum systems, reducing exploration risk in the decision-making process. Different targets display semivariograms with distinct geostatistical parameters, thus expressing contrasting models of spatial data correlation. The research results indicate that trajectories developed by the targets “sea”, “seepage slick”, and “oil spill” showed diagnostic behavior in their respective phase-space pictures. Full article

The primary objective of this research is to engineer a high-performance, sustainable material for aquatic remediation by repurposing low-cost biogenic silica into a selective hydrophobic adsorbent. By integrating the natural hierarchical porosity of Diatomaceous Earth (DE) with a tailored silanization strategy, this work aims to provide a scalable and eco-friendly solution for the efficient encapsulation and mechanical recovery of hydrocarbons from contaminated water. To overcome the inherent hydrophilicity of DE, a two-step functionalization process was developed, involving alkaline activation followed by the covalent grafting of hexadecyltrimethoxysilane (C16) in different concentrations. The resulting C16@DE hybrid materials underwent a dramatic surface energy transformation, shifting from hydrophilic behavior to robust hydrophobicity, with static contact angles reaching up to 134.8°. Optical analysis revealed a unique remediation mechanism: while pristine DE disperses homogeneously in the aqueous phase, functionalized C16@DE spontaneously organizes into discrete pellets upon contact with diesel, effectively encapsulating the fuel. Quantitative UV/vis spectrophotometry confirmed that these composites sequester approximately 55–56% of the diesel phase. Together, these results demonstrate that C16@DE materials couple intrinsic biosilica porosity with tailored hydrophobicity to achieve efficient hydrocarbon capture. By combining the natural hierarchical porosity of diatoms with engineered surface selectivity, this research positions functionalized DE as a scalable, low-cost, and eco-friendly promising solution for marine oil spill recovery and industrial wastewater treatment. Full article

Oil spills along the northeast coast of Brazil have the potential to cause catastrophic contamination of coastal environments and their associated biota. Beyond the direct contamination processes occurring on beaches, oil can also be transported inland by tides through estuaries. In addition, wind-driven transport of oil was observed in nearly all sections studied along the coast. Therefore, this study evaluated the potential of wind to transport oil fragments inland using both direct and indirect methods, including field observations and GIS-based mapping tools. The results identified and quantified oil fragmentation processes and wind-driven transport over relatively large distances (hundreds of meters). The presence of exhumed beachrock, combined with the absence or low elevation of foredunes and the high potential for wind transport, plays a crucial role in trapping oil on the beach surface. These factors further facilitate the fragmentation and inland dispersal of oil particles, allowing them to penetrate deeper into the coastal environment. The findings underscore the importance of assessing the contamination risks posed by oil fragments as they become incorporated into aeolian and other interconnected inland systems. Full article

The critically endangered Kemp’s ridley sea turtle (Lepidochelys kempii) population experienced a catastrophic decline from a peak in 1947 to a low in 1985, followed by exponential growth prior to 2010. However, the Deepwater Horizon (DWH) oil spill caused a demographic setback. Monitoring nesting female straight carapace length (SCL) is crucial for assessing population structure and recovery. We analyzed interannual variation in SCL of nesting females at Rancho Nuevo Sanctuary, Tamaulipas, Mexico, during the 2018–2023 nesting seasons. A total of 191 females were measured, and a comprehensive statistical analysis was performed to validate the use of parametric tests. One-way ANOVA revealed significant differences in mean SCL among years (p < 0.001). The lowest seasonal SCL means were in 2020 (59.01 ± 1.79 cm) and 2022 (60.68 ± 1.47 cm), while the highest SCL means occurred in 2018 (62.77 ± 1.81 cm), 2019 (62.01 ± 1.56 cm), 2021 (62.19 ± 1.47 cm), and 2023 (61.75 ± 2.07 cm). There was no significant linear decline in mean SCL from 2018 to 2023 (p = 0.78). These results suggest short-term interannual variability rather than a consistent shift in body size structure, providing updated baseline information for post-DWH population monitoring and future recruitment assessments. Full article

Oil slicks pose a severe threat to marine ecosystems, making accurate and real-time detection increasingly urgent. Marine X-band radar has become an essential tool for oil slick monitoring due to its high temporal resolution and its ability to sensitively capture the damping of capillary waves on the sea surface caused by oil films. Building upon this, an unsupervised and lightweight SLIC-KMeans-GJO detection framework is proposed. The method first generates superpixels by using Simple Linear Iterative Clustering (SLIC) and then applies K-means clustering to extract region of interest (ROI). An improved Golden Jackal Optimizer (GJO) is adaptively initialized based on the grayscale distribution and information entropy. To enhance optimization performance, Lévy flight and stochastic perturbation mechanisms are incorporated to improve global exploration and local convergence precision. Experimental results demonstrate that the proposed method significantly outperforms conventional thresholding approaches and other intelligent optimization-based segmentation algorithms in terms of noise suppression, target identification accuracy, and discrimination precision for oil slick targets. It effectively mitigates over-segmentation and false detections while preserving fine edge details and the true spatial extent of oil slicks. The proposed framework offers a novel and practical solution for real-time oil slick monitoring, holding strong potential for operational maritime emergency response. Full article

To address critical challenges in marine oil spill remediation, including limited penetration of high-viscosity crude oil and inefficient adsorbent recovery, it is imperative to develop environmentally friendly materials integrating high-efficiency adsorption, in situ viscosity reduction, and controllable recovery. In this study, a delignified corn pith (CPDL) with a three-dimensional porous structure was employed as a green matrix. Through constructing a Fe₃O₄/expansible graphite (EG)/polyvinylidene fluoride (PVDF) composite functional coating combined with silanization modification, a multifunctional biomass-based oil sorbent (Fe₃O₄/EG/PVDF-CPDL) was successfully fabricated. The material maintains the inherent porous architecture while forming a stable micro/nano-rough surface, exhibiting excellent superhydrophobicity with a water contact angle of approximately 155°, and demonstrating exceptional stability in harsh acidic/alkaline/saline environments and multiple cycles. Benefiting from the synergistic photothermal effect of Fe₃O₄ and EG, under one sun illumination (1 kW/m²), the material surface temperature rapidly reaches above 80 °C within 100 s, reducing the viscosity of high-viscosity crude oil by over 95% (from 1.39 × 10⁵ to approximately 6.0 × 10³ mPa·s), thereby enabling rapid penetration and adsorption within 50 s. Moreover, the composite coating significantly enhances mechanical performance, achieving a compressive strength of 320 kPa (approximately eight times higher than that of the pristine substrate), ensuring structural integrity during handling and compression recovery. Meanwhile, the material demonstrates precise directional manipulation and efficient recovery through external magnetic fields due to its superior magnetic responsivity. Experimental results reveal a broad-spectrum adsorption capacity (14.8–30.2 g/g) and separation efficiency exceeding 96% after 20 adsorption–desorption cycles. In summary, this work presents an innovative strategy with significant application potential for efficient and controllable remediation of marine oil spills, particularly high-viscosity crude oil, by integrating synergistic functions of porous adsorption, superhydrophobic corrosion resistance, photothermal viscosity reduction, mechanical reinforcement, and magnetic control. Full article

Mangroves are crucial for biodiversity conservation, coastal protection, and supporting local livelihoods. Mangroves may also protect coasts from storms and rising sea levels and can play a major role in climate mitigation. Threats to their health include activities such as infrastructural development, urban encroachment, aquaculture and crop farming, and oil and gas exploration. We review the threats and opportunities for the restoration of mangrove ecosystems on the coasts of Africa, which are highly impacted by oil spills. The most important challenge for mangrove restoration identified in this review is the restoration of appropriate hydrologic and salinity regimes prior to natural recruitment or the active planting of propagules. Full article

Oil spills represent a severe environmental hazard, threatening marine and coastal ecosystems, biodiversity, and socio-economic stability. Timely and accurate detection of such incidents is critical for mitigating their ecological and economic consequences. Conventional detection techniques, including manual inspection and satellite-based observation, remain limited by high operational costs, temporal delays, and restricted spatial coverage. To overcome these limitations, this study introduces a comprehensive computer vision framework that addresses two core challenges: (i) the construction of a large-scale, high-quality synthetic oil spill dataset through mask extraction and seamless blending of oil spill regions with diverse oceanic backgrounds, and (ii) the development of a fine-tuned YOLOv11m-seg detection model trained on this enriched dataset. To further enhance the realism and spatial distinctiveness of oil spill textures, the Line Integral Convolution (LIC) is applied to estimate and visualize ocean surface flow patterns, generating coherent streamline textures that simulate the natural diffusion and transport of oil in water. The model exhibited strong generalization and precision, achieving a training accuracy exceeding IoU@0.50-0.95 to 85% over 50 epochs. Evaluation metrics confirmed its reliability, with an F1 score of 94%, precision of 94%, and recall (mAP@0.50) of 94%. These results demonstrate that the developed approach not only enhances dataset diversity but also substantially improves the accuracy and representativeness of real-time oil spill detection in marine environments. Full article

Oil spills are severe environmental disasters that cause long-lasting damage to marine ecosystems and impose significant economic costs, underscoring the urgent need for efficient detection and monitoring technologies. Conventional field-based observation methods, while valuable, are constrained by limited spatial coverage, high costs, and labor-intensive processes, making them impractical for large-scale or rapid-response applications. To overcome these challenges, satellite remote sensing has been used as an effective alternative for oil spill monitoring. In particular, the advent of Google Earth Engine (GEE), a cloud-based geospatial platform, has transformed oil spill research by enabling scalable management and analysis of large satellite remote sensing datasets. This review synthesizes studies employing GEE for oil spill detection, across marine environments and interconnected aquatic systems, focusing on methodologies based on optical imagery and synthetic aperture radar data and approaches that integrate machine learning techniques. The analysis underscores that GEE enhances oil spill monitoring by facilitating rapid data processing, supporting reproducible workflows, and expanding access to multi-source satellite data. Furthermore, this review highlights the necessity of incorporating very-high-resolution satellite data and achieving tighter integration of external deep learning framework within GEE to improve detection accuracy and the operational applicability in complex marine and coastal contexts. Full article

The development of interface-engineered, multifunctional nanostructured materials with controllable surface and magnetic properties remains a critical challenge in wastewater treatment and environmental remediation. In this work, a novel GO–CoFe₂O₄–Silicone Magnetic Sponge was successfully fabricated through the integration of graphene oxide and CoFe₂O₄ magnetic nanoparticles within a silicone-modified porous sponge matrix. The resulting material combines superhydrophobicity, oleophilicity, high adsorption capacity, and magnetic responsiveness in a single architecture. The prepared sponge exhibited a high water contact angle of 161.5°, confirming its superhydrophobic nature, while maintaining excellent structural integrity during repeated use. Vibrating sample magnetometry revealed clear ferrimagnetic behavior, enabling rapid magnetic manipulation and efficient recovery of the sponge from aqueous media. The GO–CoFe₂O₄–Silicone Magnetic Sponge demonstrated strong adsorption performance toward a wide range of oils and organic solvents, including chloroform, olive oil, toluene, ethanol, acetone, gasoline, and hexane, with adsorption capacities remaining stable over multiple cycles. Furthermore, the sponge showed outstanding separation efficiency exceeding 98.3% for various oil/water and organic solvent/water mixtures, both in batch and continuous vacuum-assisted separation systems. The adsorption capacity and separation efficiency were retained after repeated adsorption–desorption cycles, indicating excellent reusability and durability. Owing to its synergistic combination of surface chemistry, porous structure, and magnetic functionality, the GO–CoFe₂O₄–Silicone Magnetic Sponge represents a promising candidate for practical applications in oil spill cleanup and wastewater treatment. Full article

Bird survival is influenced by both natural and anthropogenic factors, including weather conditions and oil spills. In this study, we examined the impact of a major oil spill (Prestige oil tanker) and climatic conditions (precipitation and wind) on survival and recapture probability in the Kentish plover (Anarhynchus alexandrinus) population in Galicia (NW Spain). To this end, we applied the Cormack–Jolly–Seber (CJS) live recapture model to a sample of 372 adult birds captured between 1994 and 2023. The best-fit model indicated that survival was best explained by the interaction between precipitation and the Prestige oil spill, indicating a decrease in survival post-spill, especially in the periods Post1 (years 2003–2007) and Post2 (2008–2015). Precipitation showed a negative influence on adult survival, but wind had no significant influence. Recapture probability was influenced by the interaction between time, sex, and Prestige, with males showing higher values, probably due to behavioural and detectability differences. Environmental monitoring and preparedness for pollution events are therefore essential to improve the long-term viability of the species. Full article

Used lubricating oils (ULOs) represent one of the largest hazardous liquid waste streams globally and pose significant environmental risks if improperly managed. This study presents a structured review of ULO management pathways, including regeneration, reprocessing, and energy recovery technologies, within a sustainability and circular economy framework. The review systematically categorizes treatment options based on recovery efficiency, waste generation, environmental performance, and technical feasibility. To contextualize environmental risk, a conceptual numerical spill dispersion analysis using the SIMOIL model is included as an illustrative case study under simplified marine conditions. The simulation highlights the rapid dispersion potential of ULOs in coastal environments, reinforcing the need for preventive management strategies. The analysis indicates that refining technologies generally offer higher material circularity potential, while thermochemical processes provide viable alternatives for heavily contaminated oils. The study identifies critical gaps in technoeconomic comparability, regulatory harmonization, and source segregation practices. Strengthening integrated management systems is essential to minimize environmental impact and enhance resource recovery. Full article

Asphaltenes are the most polar and refractory fraction of crude oil, and are typically isolated using petroleum-derived precipitants (e.g., n-hexane, n-heptane) and then dissolved in aromatic solvents such as toluene, which raises safety and sustainability concerns. Here we evaluate D-limonene, a renewable terpene, as a green, room-temperature precipitant for asphaltene fractionation and benchmark it against n-alkanes and the ASTM D-6560 workflow. Multi-technique characterization (ATR-FTIR/NIR, TGA, CHN, EDS, LDI(+) FT-ICR MS, and ¹H/¹³C NMR) shows that D-limonene yields a lower mass of precipitate yet a fraction with reduced thermal refractoriness (lowest TGA residue, broader/attenuated DTG peak). Molecular readouts indicate lower aromatic condensation/cross-linking in the precipitated subpopulation—narrower DBE envelopes by FT-ICR MS and lower aromatic carbon indices (Car_tot, Car-b, Car-j) by ¹³C NMR—consistent with a mechanism in which π–π/dispersion interactions retain highly condensed multi-ring aggregates in solution under cold, static conditions. These results establish D-limonene as a selective green precipitant for asphaltenes, offering immediate analytical benefits (cleaner, safer fractionation for molecular studies) and a sustainable basis for pretreatments of heavy fractions. Full article

Oil spills represent a severe threat to aquatic ecosystems, requiring rapid and reliable detection methods to support environmental response. Hyperspectral imaging (HSI) offers high spectral resolution for distinguishing hydrocarbon types, but its effective use depends on the performance and robustness of deep learning (DL) models, especially under data-limited conditions. This study presents a systematic evaluation of convolutional neural network (CNN) configurations for oil spill classification in visible-near-infrared (VNIR) hyperspectral data, examining the influence of architectural depth and hyperparameters such as the number of convolutional kernels, neuron density, and dropout rate. Two architectures were tested across 54 configurations and two training set sizes (259 and 518 samples). Results show that a compact architecture with an additional max pooling layer achieved near-perfect accuracy (>0.99) with reduced complexity and greater robustness, outperforming its deeper counterpart. Importantly, this study reveals that under small-sample scenarios, optimal performance can still be achieved by carefully balancing model capacity, favouring moderate convolutional depth and high neuron density, while avoiding over-regularisation. These findings provide practical guidance for designing efficient CNNs for UAV-based oil spill monitoring and lay the groundwork for future integration into local real-time processing pipelines and transfer learning applications. Full article

A series of generalized fixed-bed physical model experiments were conducted to investigate the hydrodynamic effects of spur dike configuration and permeability. The study was carried out in a rectangular flume at a geometric scale of 1:40. A traditional impermeable spur dike, a novel impermeable spur dike with a curved geometry, and permeable spur dikes with varying porosities (p = 11.8%, 17.6%, and 23.2%) were systematically examined. Surface velocity and flow direction were measured using a large-scale surface flow field measurement system. Additionally, tracer-based experiments were conducted to characterize oil spill spreading pathways, areas, and rates. The results showed that the novel curved-profile spur dike alleviates upstream backwater effects and weakens downstream plunging flow compared to the conventional straight-profile spur dike, resulting in a more uniform surface flow structure. At low porosity (P = 11.8%), hydrodynamic behavior resembled that of impermeable structures. In contrast, at high porosity (P = 23.2%), upstream–downstream hydraulic connectivity was enhanced, and recirculation intensity was reduced. Regarding oil spill dispersion, spur dike promoted oil retention in the upstream region and lateral spreading around the spur dike head. The extent of the spreading area was strongly influenced by both the cross-sectional geometry and the porosity of the spur dike. Among the permeable cases, the largest spreading area was observed at an intermediate porosity (P = 17.6%). However, permeable spur dike generally exhibited smaller overall spreading areas compared to impermeable spur dike. Finally, an empirical model for predicting the oil spreading area was developed by incorporating flow velocity, water depth, and porosity. These findings provide a scientific basis for optimizing spur dike design and mitigating oil spill risks. Given the severe threat that oil pollution poses to aquatic environments, the retention capacity of spur dikes serves as a critical hydraulic barrier, thereby promoting environmental and ecological sustainability. Full article