Search Results (759)

Large storage tanks situated in coastal areas are vulnerable to environmental hazards, with earthquakes being one of the most destructive forces threatening their structural safety. Additionally, differential settlement can significantly alter conditions in the tank, including the inclination, thereby changing the direction of external applied excitation forces and affecting the liquid sloshing response. To investigate the coupled effects of structural settlement and external excitation, model tests were conducted in series to analyze liquid sloshing behavior in a tilted tank subjected to harmonic excitation. The results revealed that the liquid response under combined environmental loads displayed distinct characteristics compared with that under single excitation. While the inclination angle had minimal influence during the unstable sloshing stage, it became crucial during the stable stage, particularly for third-order resonant responses, leading to intensified sloshing. More specifically, as the tilt angle of the storage tank from 0° to 8°, the steady-state wave height at third-order resonance increased by approximately 69%. This highlights the amplified risks to the structural stability and safety posed by differential settlement. Furthermore, variations in steady-state wave heights due to differential settlement conditions were investigated. The water level elevation along the tank walls varies as the inclination angles increase, which leads to potential risks to the stability of liquid storage under forced motion, especially under symmetric structural designs, and increases the likelihood of structural instability, oil spills, and other coastal disasters. These results provide valuable insights into the safety risks and sustainable utilization of coastal infrastructure, serving a basis for assessing and mitigating the risks associated with structural settlement and seismic excitations. Full article

The extraction, processing and transport of crude oil in the Niger Delta region of Nigeria has long been associated with collateral environmental damage to the largest mangrove ecosystem in Africa. Oil pollution is impacting not only one of the planet’s most ecologically diverse regions but also the health, livelihoods, and social cohesion of the Delta region inhabitants. Quantifying and directly associating localised oil pollution events to specific petrochemical infrastructure is complicated by the difficulty of monitoring such vast and complex terrain, with documented concerns regarding the thoroughness and impartiality of reported oil pollution events. Earth Observation (EO) offers a means to deliver such a monitoring and assessment capability using Normalised Difference Vegetation Index (NDVI) measurements as a proxy for mangrove biomass health. However, the utility of EO can be impacted by persistent cloud cover in such regions. To overcome such challenges here, we present a workflow that leverages EO-derived high-resolution (10 m) synthetic aperture radar data from the Sentinel-1 satellite constellation combined with machine learning to conduct observations of the spatial land cover changes associated with oil pollution-induced mangrove mortality proximal to pipeline networks in a 9000 km² region of Rivers State located near Port Harcourt. Our analysis identified significant deforestation from 2016–2024, with an estimated mangrove mortality rate of 5644 hectares/year. Using our empirically derived Pipeline Impact Indicator (PII), we mapped the oil pipeline network to 1 km resolution, highlighting specific pipeline locations in need of immediate intervention and restoration, and identified several new pipeline sites showing evidence of significant oil spill damage that have yet to be formally reported. Our findings emphasise the critical need for the continuous and comprehensive monitoring of oil extractive regions using satellite remote sensing to support decision-making and policies to mitigate environmental and societal damage from pipeline oil spills, particularly in ecologically vulnerable regions such as the Niger Delta. Full article

In this study, the ANSYS 2020R1 software simulation is employed to examine the diffusion process of oil leakage and the underground water solute transport law in the Dashagou Yellow River crossing section of the oil pipeline. The simulation results demonstrate that under identical leakage pressure conditions, diesel fuel leakage in powdery, sandy soil is diminished, the emergency window is extended, and the corresponding leakage risk is reduced. In addition, the leakage rate of crude oil is slower than that of diesel oil. After 850 days of downward migration of approximately 190 m, the pollutant reaches quasi-static equilibrium in the big sand ditch. The results of the surface water oil spill analysis demonstrated that the oil film on the river surface migrated for 100 min after the spill, with a thickness that remained between 0.02 and 0.05 mm and a concentration that approached equilibrium. Full article

Oil spills pose significant threats to marine and coastal ecosystems, biodiversity and local economies, necessitating efficient and accurate detection systems. Traditional detection methods, such as manual inspection and satellite imaging, are often resource-intensive and time consuming. This study addresses these challenges by developing a novel approach to enhance the quality and diversity of oil spill datasets. Several studies have mentioned that the quality and size of a dataset is crucial for training robust vision-based deep learning models. The proposed methodology combines advanced object extraction techniques with traditional data augmentation strategies to generate high quality and realistic oil spill images under various oceanic conditions. A key innovation in this work is the application of image blending techniques, which ensure seamless integration of target oil spill features into diverse environmental ocean contexts. To facilitate accessibility and usability, a Gradio-based web application was developed, featuring a user-friendly interface that allows users to input target and source images, customize augmentation parameters, and execute the augmentation process effectively. By enriching oil spill datasets with realistic and varied scenarios, this research aimed to improve the generalizability and accuracy of deep learning models for oil spill detection. For this, we proposed three key approaches, including oil spill dataset creation from an internet source, labeled oil spill regions extracted for blending with a background image, and the creation of a Gradio web application for simplifying the oil spill dataset generation process. Full article

An effective satellite observation system is developed to retrieve the diatom concentration in freshwater ecosystems that could be utilized for understanding aquatic biogeochemical cycles. Although the singular value decomposition-based retrieval model can reflect the complicated diatom dynamics, the spatial distribution and temporal trend in diatom concentration on a large scale, as well as its driving mechanism, remain prevalently elusive. Based on the Google Earth Engine platform, this study uses Sentinel-2 MultiSpectral Instrument imagery to track the comprehensive diatom dynamics in a large reservoir, i.e., the Three Gorges Reservoir, in China during the years 2019–2023. The results indicate that a synchronous diatom distribution is found between the upstream and downstream artificial lakes along the primary tributary in the Three Gorges Reservoir, and the causal relationships between the declining diatom trend and hydrological/meteorological drivers on the monthly and yearly scales are highlighted. Moreover, the Sentinel-derived diatom concentration can be used to ascertain whether the dominant algae are harmful during bloom periods and aid in distinguishing algal blooms from ship oil spills. This study is a significant step forward in tracking the diatom dynamics in a large-scale freshwater ecosystem involving complex coupling drivers. Full article

Shipping activities continue to experience growth across a multitude of industrial sectors within the Arctic, hence there are risks in terms of severity and likelihood of accidents. The Arctic region is inherently dangerous to transportation and human existence due to its extreme climate and environmental conditions, and hence the complexities associated with emergency situations within the maritime domain are amplified when operating within the Arctic and North-Atlantic (ANA). The definition and characterisation of potential seaborne disasters and catastrophic incidents in the ANA region are significant enablers in providing a set of critical and sustainable tools for Search and Rescue (SAR), Oil Spill Response (OSR), and emergency management practitioners. Therefore, in this paper we aim to identify and characterise high-priority potential seaborne disasters and catastrophic incidents in the ANA region such as cruise ship accidents, oil leaks, radiological leaks, and fishing boat groundings. These were compiled as an outcome of a set of workshops carried out as part of the ARCSAR, EU Horizon 2020 funded project, and from analysis of the literature. We also provide root cause analysis techniques, tools for strategic decision-making, and means of mitigation. We demonstrate how such tools can be used by applying some of them to a selective case study and drawing lessons learned from the application of root cause analysis, which can help emergency response organisations with preparedness work and hence more efficient response. In doing so, we provide a set of tools that can be used for strategic and operational learning. Such approaches can help standardise the definition and characterisation of potential seaborne disasters and catastrophic incidents in the ANA region in both prospective and retrospective analysis. Full article

In this paper, we analyze the serious environmental accident caused by a massive oil spill on 7 February 2024, off the island of Tobago, using two separate algorithms, namely, the established visible near-red index (VNRI) algorithm and the novel IVI visible reflectance ratio index (IVI), both applied to Sentinel-2 satellite images. These algorithms were specifically designed to monitor oil spills in inner waters. In this paper, where the IVI is presented for the first time, its effectiveness in the open sea is also showcased allowing the identification and subsequent monitoring over time of the oily masses that threaten the coral reef of the island. The analysis suggests that with sufficient cloud-free conditions, high temporal revisit multispectral optical satellites could support the timely detection and tracking of oil masses during environmental incidents near natural sanctuaries. Full article

Soil contamination from oil spills in the canton of Francisco de Orellana in Ecuador is the biggest contamination problem in the region. It affects the quality of resources and poses health risks to the surrounding communities. To find an economical and efficient alternative for the remediation of soils contaminated with total petroleum hydrocarbons (TPHs), the application of oil palm bagasse was proposed. This is a locally available industrial waste. The methodology of the study was based on the application of six treatments (G-A, G-B, O-A, O-B, M-A, M-B) belonging to the bagasse of Elaeis guineensis and Elaeis oleifera, in two percentages of concentration, 98:2 and 96:4, during a period of 20 days. To determine the efficacy of the treatments, the bagasse of the two palms was characterized. In addition, the initial physicochemical characterization of the soil and the final characterization after the treatments were carried out. Soil characterization included analyses of macronutrients, micronutrients, metals, pH, EC and TPH. The results of the initial characterization revealed that the concentrations of electrical conductivity and TPH were more than 70 and 50 times the values established in the 97-A ministerial agreement, respectively. However, after the final characterization, the effectiveness of the treatments in reducing metal concentrations was observed. Likewise, conductivity levels were reduced by more than 10 times. As for TPH, the G-B treatment stood out by achieving a 56% removal of this pollutant. Full article

Due to the high viscosity and low fluidity of viscous crude oil, how to effectively recover spilled crude oil is still a major global challenge. Although solar thermal absorbers have made significant progress in accelerating oil recovery, its practical application is largely restricted by the variability of solar radiation intensity, which is influenced by external environmental factors. To address this issue, this study created a new composite fiber that not only possesses solar energy conversion and storage capabilities but also facilitates crude oil removal. PF@PAN@PEG was obtained by coaxial electrospinning processing, with PEG within PAN fibers, and a coating layer was applied to the fiber surface to impart oleophilicity and hydrophobicity. PF@PAN@PEG exhibited a high latent heat value (77.12 J/g), high porosity, and excellent photothermal conversion and oil storage capabilities, significantly reducing the viscosity of crude oil. PF@PAN@PEG can adsorb approximately 11.65 g/g of crude oil under sunlight irradiation. Notably, due to the encapsulation of PEG, PF@PAN@PEG can continuously maintain the crude oil at a phase change temperature by releasing latent heat under specific conditions, effectively reducing its viscosity with no PEG leakage at all. When solar light intensity varied, the crude oil collection efficiency increased by 21.99% compared to when no phase change material was added. This research offers a potential approach for the effective use of clean energy and the collection of viscous crude oil spill pollution. Full article

Impact assessments are necessary for supporting fisheries’ disaster applications and management options for states affected by disasters. This paper measures the joint and individual impacts of man-made and natural disasters, global pandemics and recessions, the U.S.-China trade war, and recent increases in fuel prices on commercial dockside values of the Mississippi blue crab fishery. The mean-difference model estimates the direct impacts when the current dockside values fall below the benchmark values. The marine economic recovery model identifies the significant determinants of the variations in the dockside values. Mean-difference model results indicate that the Mississippi blue crab fishery sustained direct losses due to Hurricane Katrina in 2005, the Deepwater Horizon oil spill in 2010, and the opening of the Bonnet Carre Spillway in 2011. The estimated marine economic recovery model explained 93 percent of the variations in real dockside values. Two independent variables are statistically significant, including blue crab landings and time. The disaster variables have the expected signs but are not statistically significant. These methodologies’ usefulness is applicable in assessing the direct impacts on fisheries and other economic sectors affected by disasters such as major hurricanes, oil spills, massive freshwater intrusion, and harmful algal blooms. Full article

This study focused on the investigation of soil samples from the alluvial zone of the Sava River, located near the heating plant in New Belgrade, Serbia. Using gas chromatography with flame ionization detection (GC-FID), a broad range of alkanes, including linear n-alkanes (C₁₀ to C₃₃) and isoprenoids, was analyzed in all samples. The obtained datasets were effectively made simpler by applying multivariate statistical analysis. Various geochemical indices (CPI, ACL, AI, TAR, etc.) and ratios (S/L, Paq, Pwax, etc.) were calculated and used to distinguish between biogenic and anthropogenic contributions. This approach added a higher level of precision to the source identification of hydrocarbons and provided a detailed geochemical characterization of the investigated soil. The results showed that the topsoil had a high content of TPH (average value, 90.65 mg kg⁻¹), potentially related to an accidental oil spill that occurred repeatedly over extended periods. The uncommon n-alkane profiles reported for the investigated soil samples are probably the result of inputs related to anthropogenic sources, emphasizing that petroleum was the main source of the short-chain n-alkanes. The methodology developed in this study was proven to be efficient for the assessment of the environmental quality of the soil in an urban part of New Belgrade, but it can also be a useful tool for soil monitoring and for a pollution assessment in other (sub)urban areas. Full article

This study determined the environmental condition of the benthos of Milford Haven Waterway, an area that is arguably the most vulnerable in the UK to anthropogenic activities, including the potential effects of a major oil spill in 1996, using historical data on the macrobenthos more than a decade later in 2008, 2010 and 2013. These data show a gradual decline in numerous univariate diversity measures from the outer (marine) to inner (estuarine) stations. Taxonomic distinctness generally falls within the expected range, and most stations have above-average values compared with other monitoring stations around the UK. The W-statistics for Abundance/Biomass Comparison (ABC) plots are usually strongly positive and never negative. There was a sequential change in community composition from the outer to inner stations, which was strongly related to salinity, and, to a lesser extent, sediment granulometry. None of the species regarded as indicators of organic pollution were prominent in the macrobenthic community of Milford Haven Waterway. On this basis, although there are some slight indications of environmental perturbation at particular sites in certain years, it can be concluded that the benthic communities of Milford Haven Waterway are in a healthy state. This study provides a baseline against which the potential effects of any future environmental accidents and/or the increased industrial development can be assessed. Full article

The widespread oil extraction in the Niger Delta and the impacts on different types of vegetation are poorly understood due to lack of ground access. This study aims to determine the impact of oil spills on vegetation in the Niger Delta using a Landsat satellite-derived normalised difference vegetation index (NDVI). The impact of oil spill volume and time after an oil spill on the health of different types of vegetation were evaluated, and the time series of the changes in NDVI were analysed to determine the medium- and long-term responses of vegetation to oil spill exposure, using a combination of linear regression and paired t-tests. With regards to the relationship between spill volume and NDVI, a moderate correlation (R² = 0.5018) was observed for spill volumes in the range of 401–1000 barrels for sparse vegetation, for volumes greater than 1000 barrels for dense vegetation (R² = 0.4356), whilst no correlation was found for mangrove vegetation at any range of spill volume. Similarly, the results of the paired t-test confirmed a significant difference (p-value < 0.05) between the change in NDVI values for spill sites and non-spill sites for all vegetation types, with the sparse vegetation being the most affected of the three types. However, the impact of the oil spill on vegetation over a period is not statistically significant. The outcomes of this study provide insights into how different types of vegetation in the Niger Delta respond to oil spills, which could ultimately help in designing an oil spill clean-up program to reduce the impact on the environment. Full article

To study the fire behavior of UHVDC (ultra-high-voltage direct current) converter transformers and the effectiveness of CAFs (compressed air foams) in suppressing fires, a full-scale model of a 220 kV converter transformer fire was constructed. The model mainly considered the oil pool fires and oil spill fires that form after explosions, causing the casing to completely fall out. The hot oil fire tests were conducted on the physical converter transformer. The fire suppression characteristics of the CAF system for converter transformer fires were studied. The temperature and changes in various locations of the fire model were analyzed under different foam supply strengths. The fire in a converter transformer is characterized by intense heat, high temperatures, and strong radiation. The highest temperature can exceed 1000 °C in cases of complete combustion. The fire in the converter transformer involves a dynamic oil spill and a large pool of oil, making it challenging to extinguish. The fire extinguishing performance and cooling effect of CAFs are outstanding. The recommended foam supply strength for the actual project is more than 8 L/(min·m²). Full article

Oil spills pose significant threats to marine ecosystems, and while existing tools simulate spill dispersion and predict impacts, they often lack full integration of accident specifics, detailed drift simulations, and thorough impact analyses. This paper presents the EcoSensitivity decision support system, a comprehensive platform designed to improve oil spill responses by integrating immediate and cumulative environmental impact assessments. The EcoSensitivity system addresses these gaps by combining the Accidental Damage and Spill Assessment Model (ADSAM), oil drift modeling, and the PlanWise4Blue (PW4B) application, which enables high-resolution cumulative impact assessments. This unified tool provides decision-makers with rapid, data-driven insights, facilitating a more informed and effective response to oil spills. EcoSensitivity represents a substantial advancement in operational modeling, supporting ecosystem resilience and aiding in strategic planning for marine conservation. Full article