Oil Spill Accidents Research Articles

Investigation of the state of hydrographic objects in the area of oil production according to remote sensing of the Earth

Currently, there are thousands of spills of petroleum products and their components, which have different concentrations of harmful substances, therefore, one of the most important environmental problems is the pollution of hydrographic facilities. The main source of pollution of water areas are accidental oil spills that occur during the extraction and transportation of petroleum products. They are a significant threat to water pollution and the reduction of species of marine life. This problem determines the relevance in the study of the state of hydrographic objects in the area of oil production according to remote sensing of the Earth. Therefore, the purpose of this work is to identify the state of the Usa and Kolva rivers using PlanetScope space images taken at different times. The object of the study is the Usa River and its tributary Kolva, the state of which, as studies show, is very critical.

Log Transformed Coherency Matrix for Differentiating Scattering Behaviour of Oil Spill Emulsions Using SAR Images

Oil spills on the ocean surface are a serious threat to the marine ecosystem. Automation of oil spill detection through full/dual polarimetric Synthetic Aperture Radar (SAR) images is considered a good aid for oil spill disaster management. This paper uses the power of log transformation to discern the scattering behavior more effectively from the coherency matrix (T3). The proposed coherency matrix is tested on patches of the clean sea surface and four different classes of oil spills, viz. heavy sedimented oil, thick oil, oil-water emulsion, fresh oil; by analyzing the entropy (H), anisotropy (A), and mean scattering angle alpha (α), following the H/A/α decomposition. Experimental results show that not only does the proposed T3 matrix differentiate between Bragg scattering of the clean sea surface from a random scattering of thick oil spills but is also able to distinguish between different emulsions of oil spills with water and sediments. Moreover, unlike classical T3, the proposed method distinguishes concrete-like structures and heavy sedimented oil even though both exhibit similar scattering behavior. The proposed algorithm is developed and validated on the data acquired by the UAVSAR full polarimetric L band SAR sensor over the Gulf of Mexico (GOM) region during the Deepwater Horizon (DWH) oil spill accident in June 2010.

Oil Spill Environmental Risk Assessment and Mapping in Coastal China Using Automatic Identification System (AIS) Data

The rapid expansion in shipping traffic, oil tankers, and oil field exploration in coastal and marine areas has, inevitably, resulted in the occurrence of many oil spill accidents. Oil spill accidents, which cause serious socio-economic, health, and environmental risks in coastal and marine areas, are a global concern. An oil spill pollution risk distribution map, combining multiple spill sources, is an effective tool by which to identify high-risk areas, which may help decision-makers in adopting contingency response and integrated coastal management. However, the assessment of oil spill distribution and risk assessment has been restricted, due to their heavy dependence on laboratory experiments and model simulations lacking reliable shipping data, which often derive inaccurate mapping results. This study combines the automatic identification system (AIS) and other data to precisely quantify the spatial extent of accident risk in coastal China. Based on oil quantity, oil spill rate, and accident probability, the ship, oil storage tank, submarine pipeline, and oil platform accidents spill risk index is analyzed. Next, combined with the sensitive degree of a coastal area, considering environmental and social issues, the oil spill environmental risk index is calculated. The oil spill pollution risk level is classified into five categories based on the oil spill pollution risk index, namely the low-risk zone, relatively low-risk zone, moderate-risk zone, relatively high-risk zone, and high-risk zone. The relatively high oil spill environmental risk concentration zone is located in the Bohai Sea, inter-border area between the Yellow Sea and Bohai Sea, the Yangtze River estuary, south of the Taiwan Strait, and the Pearl River estuary. The high-risk zone in the Bohai Sea is 36,018 km2 in area, with an average risk value of 32.23, whereas the high-risk area in the Pearl River estuary is only 14,007 km2. The high-risk area proportions in Tianjin are 23.5%, while those in Fujian, Hainan, Jiangsu, and Guangxi are very low. The low-risk area proportion in Hainan Province is 62%, while the value in Tianjin is only 2.9%. This study will be helpful in assisting decision-makers in mapping the influence area of oil spills and adopting the important strategies and effective management and conservation countermeasures for ship accidents in the coastal areas of China.

Novel fabrication of hydrophobic/oleophilic human hair fiber for efficient oil/water separation through one-pot dip-coating synthesis route

Frequent oil spill accidents and industrial wastewater discharge has always been one of the most severe worldwide environmental problems. To cope with this problem, many fluorine-containing and high-cost materials with superwettability have been extensively applied for oil–water separation, which hinders its large-scale application. In this work, a novel human hair fiber (HHF)-polymerized octadecylsiloxane (PODS) fiber was fabricated with a facile one-pot dip-coating synthesis approach, inspired by the self-assembly performance and hydrophobicity of OTS modification. The benefits of prominent hydrophobic/lipophilic behavior lie in the low surface energy, and a rough PODS coating was rationally adhered on the surface of HHF. Driven solely by gravity and capillary force, the HHF-PODS showed excellent oil/water separation efficiency (> 99.0%) for a wide range of heavy and light oil/water mixtures. In addition, HHF-PODS demonstrated durability toward different harsh environments like alkaline, acid, and salty solutions.

Solar-assisted self-heating Ti3C2Tx-decorated wood aerogel for adsorption and recovery of highly viscous crude oil

Frequent oil-spill accidents have posed serious threats to ecosystem balance and the efficiency of resources use. Hydrophobic adsorbents that can adsorb and recover oil without causing secondary pollution are ideal candidates for the remediation of oil contamination in water. However, these composites are inefficient for crude oil-spills cleanup because crude oil has low liquidity of at room temperature. Increasing the temperature can effectively enhance the flowability of crude oil. To achieve efficient crude-oil heating and removal in situ, wood aerogels were immersed in Ti3C2Tx suspensions and then coated with polydimethylsiloxane (PDMS) to obtain a solar-heated adsorbent (PT-WA). The prepared PT-WA exhibits super-hydrophobicity (water contact angle: 154° ± 2°), mechanical robustness (withstanding 20 loading-unloading cycles under 50% strain without structural damage), strong solar absorption, and favorable photothermal-conversion capability (rising to ~85 °C within 90 s under 1.5 sun). Owing to these advantages, PT-WA is an effective adsorbent for crude oil cleanup. In addition, a ‘self-heating crude oil collector’ was assembled for the fast adsorption and restoration of crude oil from the water surface. This solar-assisted self-heating sorbent offers a competitive platform for the cleanup and recycling of viscous crude oil spills.

A probabilistic framework for risk management and emergency decision-making of marine oil spill accidents

Offshore oil spills may pose a severe threat to marine ecological environment. In this paper, a new methodology based on Bayesian network (BN) and Influence Diagram (ID) is developed for risk management and emergency decision-making of marine oil spill accidents. The methodology integrates risk management before accident and emergency response after accident, which can balance risk and cost, and render an optimal decision-making. Marine oil spill scenarios including root causations, intermediate and consequent events are identified and modeled using BN considering the dependencies and multi-state of incident process nodes. The probabilities of offshore oil spill incident and the resulting ecological disasters are estimated. The prevention and mitigation measures marine oil spill incidents are identified and added to BN for developing Bayesian ID model, in which the cost and utility of implementing each safety measure are considered. Bayesian ID model can estimate the cost and utility of all safety strategies, and the optimal risk management and emergency strategy are determined by balancing the cost and utility. A case study of marine oil spill accident due to subsea oil pipeline leak is used to illustrate the methodology. It is observed that the methodology can efficiently support the decision-making of oil and gas sector in risk management and emergency response of offshore oil spill accidents.

The Mathematical Model of Marine Engine Room Equipment Based on Machine Learning

This study is aimed at reducing the occurrence of oil spill accidents in the engine room of ships and carries out risk prevention for the equipment of the port ships, thereby reducing pollution to the marine ecological environment. Firstly, the concepts and principles of cluster analysis and ship automatic identification system are expounded. Secondly, the data information collected by the ship’s automatic identification system (AIS) is combined with density-based cluster analysis. The accident area and extent at different stages of the ship’s engine room equipment are classified. Finally, cluster analysis is used to evaluate the risk of equipment of the port ship engine room. The results show that there are 43000 ship operation information points in port a, the average operating speed of ships is 9 kilometers, and the fastest operation speed is 16.9 kilometers. In addition, many ship routes in port a need to take risk prevention measures to minimize the impact between ships and reduce the risk of oil leakage in the engine room. The proposed cabin model can easily and quickly analyze the orientation information of the ship and classify all the data into different types according to the surrounding information points. AIS can realize the information transfer between ships and between ship and shore. Information such as the position, speed, and direction of the ship needs to be accurately known to ensure safety at sea. These data need to relate to some terminals and networks to form a maritime monitoring network. The ship AIS based on cluster analysis can cluster the areas where the ship’s speed and direction change significantly in the port area, effectively preventing accidents. Scientific risk prevention measures can effectively reduce the oil leakage risk of ship engine room equipment, improve the working efficiency of marine engines, and provide a strong foundation for the entire marine ecological environment protection.

Robust and durable superhydrophobic and oil-absorbent silica particles with ultrahigh separation efficiency and recyclability

With the continuous occurrence of oil-spill accidents, superhydrophobic materials demonstrate tremendous potential in oil-water separation. In this research work, SiO2 nanospheres with surface mercapto groups were prepared by the condensation reaction of 3-mercaptopropyltriethoxysilane (KH590) and hydroxyl groups on the surface of silica (SiO2) particles. Subsequently, HTPB-coated SiO2 superhydrophobic particles were obtained through the thiol-ene click chemistry reaction between the SiO2 nanospheres and the hydroxyl terminated polybutadiene (HTPB). Depending on the polar attraction between the terminal hydroxyl groups of HTPB and the hydroxyl groups on the surface of SiO2, SiO2 nanospheres could be firmly coated with HTPB. Fortunately, stable and durable superhydrophobic lipophilic SiO2 particles (Si-HTs) was obtained. Because of the existence of micro-nano structures, the resultant Si-HTs could easily float on the oil-water surface, and effectively absorb oil solvents more than 4 times its own weight with an ultrahigh separation efficiency above 99%. Even under strong acid and strong alkali conditions or in the seawater environments, the Si-HTs were afforded with effective oil-absorption capability and high recyclability over 20 times. Consequently, the Si-HTs prepared show great potential as a superhydrophobic nanoparticle for low-cost, high-efficiency and environmentally friendly oil-water separation.

A Bibliometric Review and Science Mapping Research of Oil Spill Response

This study aimed to evaluate the research output of oil spill response and citations from 2000 to 2022 through a bibliometric analysis. The primary findings were as follows: there has been a noticeable increase in the number of publications. The most active journal was Marine Pollution Bulletin. Environmental sciences ranked as the most popular subject area. The United States of America (USA) published the greatest number of single-authored, internationally collaborative, first-authored papers. Oil spill(s) was the most widely queried research term, ranking first in the article title, abstract, and author keyword analysis, respectively. The Deep-Water Horizon disaster, the largest marine oil spill in 2010, was the most frequently analyzed oil spill accident in the research as a sample. This study makes a significant contribution to the field of oil spill response science by being one of the few that applies network visualization and mapping technique. Further research is recommended in light of longer-term data and the diverse Web of Science (WoS) categories found in oil spill science, which may be visualized using a variety of bibliometric visualization applications.

Superhydrophobic, flame-retardant and magnetic polyurethane sponge for oil-water separation

With the increasing environmental pollution by frequent spill accidents and industrial wastewater emissions, superhydrophobic materials for oil-water separation have attracted considerable attention. Herein, we proposed a facile method to prepare superhydrophobic, flame-retardant and magnetic polyurethane sponge (SFRM-PUS) for oil-water separation. Firstly, pristine PUS was immersion-coated with ferric oxide (Fe3O4) nanoparticles, graphene oxide (GO) and phytic acid, and then treated with hydroiodic acid (HI) to reduce GO and modified with perfluorooctyltriethylsilane to provide low surface energy. The SFRM-PUS had a high water contact angle of 156° and a low water sliding angle of 8.9°, and exhibited excellent anti-adhesion property and high oil-water separation efficiency of 98.9%. By means of the magnetic property, the SFRM-PUS was also applied for the removal of oil from water in specified area. In addition, the SFRM-PUS showed superior flame-retardant performance, and the ignited flame extinguished within only 4 s. Our findings conceivably provided a new strategy to prepare functional superhydrophobic materials for the treatment of oil spill accidents and industrial sewage emissions.

A New Function for Frequency Analysis in the Risk Assessment of Offshore Oil-Related Platforms

_ Risk assessment of offshore oil-related platforms such as the floating production storage and offloading system (FPSO) is extremely important. In earthquakes prone to target sea areas, earthquakes should be considered as one of the important external forces that cause severe damage. In such risk assessments, for estimating the appearance frequency of seismic energy, the complementary cumulative distribution function (CCDF) of seismic energy of a considered area is usually based on the Gutenberg–Richter law. Furthermore, it is important to estimate the CCDF of the leak hole diameter when estimating the damage caused by an oil spill accident in an offshore oil-related platform. Some ship classification societies recommend using a formula based on the power law distribution as used in those processes. However, the power law distribution has a drawback in that, i.e., it is essentially impossible to accurately estimate the CCDF over the entire domain of the random variables. The authors have developed an enhanced power law distribution function that eliminates such defects in the power law distribution function and some practical methods for estimating its parameters. In this study, the developed function is applied to the CCDFs of the seismic energy and leak hole diameter. The results demonstrate that the function fits the existing data with sufficient accuracy. Therefore, the new function introduced here can be well used in the frequency analysis of the risk assessment of offshore oil-related platforms. Introduction In the risk assessment of offshore oil-related platforms like floating production storage and offloading system (FPSO), it is necessary to estimate probabilistic characteristics of external forces against them. Earthquakes are a major external force. Furthermore, it is necessary to estimate the damage when an external force is applied. The frequency of external forces, such as earthquakes, is low, but the damage is extensive. However, damage to offshore oil-related platforms is caused by not only these external forces, but also oil leaks resulting from some factors, such as operation errors and corrosion, that may cause accidents such as fire and explosion. Therefore, it is also essential to estimate the probabilistic characteristics of such damage for the risk assessment of offshore oil-related platforms.

Operational Modeling of North Aegean Oil Spills Forced by Real-Time Met-Ocean Forecasts

Over the latest decades, oil marine pollution has posed a vital threat for global ocean health, since spillages of any scale are related to environmental, social and financial impacts. The worldwide increase in oil and gas demand, and the parallel rise in oil and gas production, exploiting particularly coastal and offshore marine deposits, have significantly increased the risk of accidental oil release to the sea. In the present study, an operational oil spill model was applied to test the oil dispersive properties and to reveal the relative magnitude of weathering processes, after an accidental oil spill release along the main tanker transportation route in the North Aegean Sea. Numerical simulations were implemented using the OpenOil transport and fate numerical model, a subclass of the OpenDrift open-source trajectory framework. This model integrates algorithms with several physical processes, such as oil entrainment, vertical mixing, oil resurfacing and oil emulsification. The oil dispersion model was coupled to real-time met-ocean forecasts received from NOAA-GFS and CMEMS. Present simulation results have focused on the impact of turbulent kinetic energy, induced by the background flow field, on the horizontal spreading of particles, as well as on the evolution of oil mass balance and oil mass properties.

Superhydrophobic starch-based adsorbent with honeycomb coral-like surface fabricated via facile immersion process for removing oil from water

The development of novel superhydrophobic adsorbents is highly demanded for tackling frequent oil spill accidents. Porous starch-based materials have been proven to possess good oil absorption performance, but their superhydrophobicity has not yet been reported, thus limiting their application in oil spill cleanup. Herein, a superhydrophobic starch-based adsorbent (MSC) was fabricated through the facile immersion process of starch cryogel (SC) into toluene solution of methyltrichlorosilane (MTS). Low-surface-energy and honeycomb coral-like micro/nanostructures, which contribute to high water contact angle (>151.0°) and low sliding angle (<15.0°), were provided simultaneously to SC by the hydrolysis-condensation reaction of MTS. MSC exhibited excellent water repellent, self-cleaning, and anti-fouling properties, as well as passable mechanical and chemical durability. The reasonable oil adsorption performance and selective wettability toward oil and water allowed this absorbent to be applied for heavy oil removal underwater and oil slick cleaning from the water surface. It is expected that the facile strategy provided by this work will accelerate the application of superhydrophobic starch-based materials in oil contamination removal and other industrial activities.

Facile fabrication of natural superhydrophobic eleostearic acid-SiO2@cotton fabric for efficient separation of oil/water mixtures and emulsions

Oily wastewater generated by industrial production and marine oil spill accidents has caused great damage to the environment and human health. The development of superhydrophobic materials prepared from natural resources for oil/water separation is of great significance. In this work, a bio-based modified fabric for oil/water separation was prepared by coating SiO2 and eleostearic acid (EA) on cotton fabric. Due to the rough surface provided by SiO2 and the low-surface-energy EA, the eleostearic acid-SiO2@cotton fabric (EA-SiO2@CF) displayed durable superhydrophobicity even under various harsh environments. The acid-stable SiO2 particles and EA molecules endowed the modified cotton fabric with resistance to high concentrations of strong acid. EA-SiO2@CF also showed pH-responsive behavior, converting between superhydrophobic and superhydrophilic states by ammonia treatment and immersion in EA solution. The superhydrophobic EA-SiO2@CF was used to separate various immiscible oil/water mixtures and surfactant-stabilized (oil-in-water and water-in-oil) emulsions with high separation efficiencies of about 99.5%. This work provides an easy strategy to prepare an environmentally friendly superhydrophobic material which can be applied to the treatment of oily wastewater, anti-corrosion protection, and intelligent response.

Bio-inspired robust superhydrophilic/underwater superoleophobic coating with lubrication, anti-crude oil fouling and anti-corrosion performances

The crude oil spill accidents cause numerous crude oil contaminations and oily wastewater. Underwater superoleophobic coating has excellent ability to resist crude oil contamination and separate oily wastewater. But it’s hard to keep stable performance against the physical or chemical attack. Herein, a robust underwater superoleophobic coating was fabricated by spraying the mixture of polyethyleneimine (PEI) and TiO2 on epoxy resin (E44) surface. Besides the good physical and chemical stability, the coating exhibited better drag reduction, anti-fouling performance and anti-corrosive performance in water compared with the commercially hydrophilic coating. The stainless steel mesh (SSM), coated by the E44/PEI/TiO2 coating, could separate different oil-water emulsions with a high oil rejection greater than 99.7%.

Three-dimensional biomimetic superhydrophobic nickel sponge without chemical modifications for efficient oil/water separation

The frequent oil spill accidents and a large amount of industrial oil wastewater discharges had caused serious economic losses and damage to the marine ecological environment. Hence, oil–water separation technology had received increasing attention from researchers. Herein, three-dimensional (3D) nickel sponge was prepared via a facile hydrothermal reduction route. The nano-spines structure of nickel sponge could exhibit superhydrophobic/superlipophilic properties without further hydrophobic modification by low-surface-energy chemicals. Due to the opened hierarchical porous structures and higher porosity, nickel sponges have excellent adsorption capacity for various oils and organic solvents. Nickel sponge has good resistance to ultraviolet radiation, corrosive aqueous solution ability, can be used for long-term outdoor applications. Moreover, the nickel sponge can also selectively absorb oil from oil/water mixtures under turbulent flow conditions. In addition, nickel sponges can continuously and rapidly collect oil from immiscible oil/water mixtures with the aid of a vacuum. Nickel sponge can also efficient selective filter oil/water mixture with a high separation efficiency over 97%. Due to the combination of metallic properties and the low density, nickel sponges are expected to have potential applications in oil absorption, flexible electrodes and industrial catalysis.

A pH-responsive phosphoprotein surface washing fluid for cleaning oiled shoreline: Performance evaluation, biotoxicity analysis, and molecular dynamic simulation

Oil spill accidents can cause negative impacts on the shoreline ecosystem and endanger public health. In the present study, an innovative green surface washing method based on sodium caseinate (NaCas) was proposed for the cleanup of oiled sand that is removed from the shoreline and treated by washing ex-situ. The comprehensive performance evaluation, biotoxicity analysis, and molecular dynamic simulation were conducted to explore the washing process. The addition of NaCas was able to decrease both surface and interfacial tensions, thereby facilitating oil diffusion and leading to a higher oil removal performance. NaCas fluid displayed a comparable washing performance with some surfactants. The factorial analysis demonstrated that three individual factors (temperature, pH, and NaCas concentration) and three interactive effects (temperature/salinity, temperature/pH, and salinity/pH) had a significant impact on the washing performance of NaCas fluid. Notably, the washing effluent displayed good pH responsiveness, generating a super-clean supernatant with low turbidity and oil concentration. Moreover, biotoxicity tests proved that the presence of NaCas could relieve the toxicity caused by oil droplets by enhancing the chlorophyll concentration and decreasing the reactive oxygen species (ROSs) content, respectively. The molecular dynamic simulation further revealed that NaCas could break the oil layer on the sand surface and move the oil droplets away from the sand. NaCas fluid is a promising candidate for oiled shoreline cleanup due to its low cost, good biocompatibility, pH responsiveness, and high oil removal efficiency.

Distribution of heavy metals and benzo(a)pyrene in oil-contaminated soils of the city of Qayyar (Iraq)

The spatial distribution of oil products and benzo(a)pyrene in gray soils as a result of an accidental oil spill in the area of the Kayyara field (Iraq), as well as the gross content and mobile compounds of heavy metals - Pb, Cd, Cu, Zn, Mn, Ni were studied. An increase in the content of oil products and benzo(a)pyrene in the upper soil layer in the zone of influence of the oil spill was revealed. With the accompanying combustion of petroleum gas, the elements under study are deposited on the soil surface. The content of Ni significantly exceeds the background concentrations. Exceeding the standards is also typical for mobile Cd compounds. As a result of the technogenic load, as well as the physicochemical characteristics of the studied soils, the studied HMs are in an easily accessible state. The highest percentage of mobility is characteristic of Cd. The high mobility of elements makes them active in terms of migration to adjacent landscapes. An important feature of the region is the presence of dust storms. Soil material contaminated with oil products and heavy metals can be transported over considerable distances, even in a short period of time. Heavy metals, benzo(a)pyrene and petroleum products can easily move not only into adjacent environments, but also into the human body. Keywords: SEROZEMS, HEAVY METALS, LEAD, CADMIUM, NICKEL, ZINC, COPPER, MANGANESE, PETROLEUM PRODUCTS, BENZO(A)PYRENE

Research on transport and weathering of oil spills in Jiaozhou Bight, China

Jiaozhou Bight is a semi-closed embayment, located on the eastern coast of Jiaodong Peninsula. Qingdao Port located in the bight is one of the largest transportation trade and professional crude oil transportation ports in China. Potential oil spills will cause serious damage to the local ecological environment and lead to huge social and economic losses. In this study, the hydrodynamic model of Jiaozhou Bight was established and its accuracy was verified based on the tidal current data of Qingdao Port and Huangdao Station. The oil spill model of Jiaozhou Bight was constructed by coupling with wind, tidal current and other environmental fields. Taking the “11.22” Huangdao oil spill accident as a case, the accuracy of the developed oil spill model was verified. The key factors affecting oil spill movement in Jiaozhou Bight are found out and the influences of wind regime, tidal current, oil spill source location and oil spill amount on drift and diffusion movement are researched. The effects of wind speed and other factors on weathering of the oil spill are studied. The research results can provide technological supports for making emergency responses to the oil spill in Jiaozhou Bight.

Biodegradation Potential of Bacillus sp. PAH-2 on PAHs for Oil-Contaminated Seawater.

Microbial degradation is a useful tool for inhibiting or preventing polycyclic aromatic hydrocarbons (PAHs) widely distributed in marine environment after oil spill accidents. This study aimed to evaluate the potential and diversity of bacteria Bacillus sp. PAH-2 on Benzo (a) anthracene (BaA), Pyrene (Pyr), and Benzo (a) pyrene (BaP), their composite system, aromatic components system, and crude oil. The seven-day degradation rates against BaA, Pyr, and BaP were 20.6%, 12.83%, and 17.49%, respectively. Further degradation study of aromatic components demonstrated PAH-2 had a high degradation rate of substances with poor stability of molecular structure. In addition, the degradation of PAHs in crude oil suggested PAH-2 not only made good use of PAHs in such a more complex structure of pollutants but the saturated hydrocarbons in the crude oil also showed a good application potential.