History of a disaster: A baseline assessment of the Wakashio oil spill on the coast of Mauritius, Indian Ocean

Reusable Solid-form Phase-Selective Organogelators for Rapid and Efficient Remediation of Crude Oil Spill

Phase-selective organogelators (PSOGs) are considered as a prospective tool for their application in oil spill remediation. However, the number of reports on the PSOGs that can be used in powder form for prompt phase-selective gelation of crude oils is still limited. In this study, a series of compounds with l-mandelic acid as the scaffold bearing different amino acid fragments have been prepared. Also, the gelation behaviors and properties of these derivatives toward organic liquids, product oils, and a type of Chinese crude oil were investigated via heating-and-cooling process, stirring, or resting operation. Besides, the micromorphologies of the resulting gels and the driving forces for the gel formation have been studied by scanning electron microscopy, Fourier transform infrared, UV spectroscopy, concentration-dependent 1H NMR, and X-ray diffraction. Particularly, gelator C15-Phe-Mac-Nap was shown to have the capability of congealing the Chinese crude oil selectively from water in powder form with a relatively lower gelator dosage, as compared with the other gelators we reported in the current and previous works. Moreover, gelator C15-Phe-Mac-Nap displayed some advantageous behaviors such as the reusability of gelator, excellent mechanical and chemical stability of the crude oil gels, and nontoxicity of the gelator in the aquatic environment, indicating its great potential application value for marine oil spill remediation.

A quantified risk analysis for oil spill during crude oil loading operation on tanker ship under improved Z-number based Bayesian Network approach

Crude oil cargo operation poses significant oil spill risk although utmost care is exercised by ship and shore crew. This paper focuses on quantitative risk analysis for oil spill incidents in crude oil tanker ships to enhance safety at the operational level and prevent potential pollution. To achieve this purpose, the Bayesian network (BN) is used under the improved Z-numbers theory. While BN provides a powerful tool based on cause and effect network between the variables, the improved Z-numbers are capable of handling uncertainty and improving the reliability of qualitative expert judgments. The findings show that the occurrence probability of oil spill risk in crude oil tanker ships is found 2.90E-02 during the cargo loading operation. The findings of the research are expected to contribute ship crew, safety inspectors, ship owners, HSEQ managers, and terminal managers in risk management decision-making, improving operational safety, taking control actions, and minimizing oil spills.

Aluminum soap nanoparticles-lignin powder form phase-selective gelator as an efficient sorbent for oils/water separation

Rapid and efficient recovery of oil spill is the key link for oil spill remediation, and also a great challenge. Here, the organogelator-polymerized porous matrix composed of adsorbents and organogelators can provide a new strategy for solving this problem. The gelling mechanism of aluminum 12-hydroxystearate (Al HSA) to form spherical nano micelles in solvents was investigated via UV-vis, FT-IR, and XRD. A creative method for aluminum soap-lignin gelator (OTS-AL/Al HSA) syntheses was put forward through the saponification of 12-hydroxystearic acid (HSA) and lignin via epichlorohydrin (ECH) crosslinking. By adjusting the ECH content, the growth of Al HSA nanoparticles (15-40 nm) on lignin can be realized, and the accordingly increased roughness endowed gelator with better hydrophobicity (WCA of 134.6°) before octadecyltrichlorosilane (OTS) modification. Thanks to the porous structures, the gelator powder exhibited a high sorption capacity in the range of 3.5-5.2 g g-1 for oils and organic solvents. Rheological studies demonstrated high mechanical strength of gels (>1.6 × 105 pa) and the gelator still retained 70% sorption capacity after 6 gelation-distillation cycles. The gelation characteristics of OTS-AL/Al HSA were attributed to the rapid sorption of oils by lignin and the self-assembly of Al HSA nano micelles on lignin to form an aggregated network structure trapping oils, thus realizing the synergistic effect of oil sorption-gelation.

Severe ecological impacts caused by one of the worst orphan oil spills worldwide

Orphan oil spills pose a severe risk to ocean sustainability; however, they are understudied. We provide the first synthetic assessment of short-term ecological impacts of the most extensive oil spill in tropical oceans, which affected 2900 km of Brazil's coastline in 2019. Oil ingestion, changes in sex ratio and size of animals, morphological abnormalities of larvae and eggs, mutagenic, behavioral, and morphological alterations, contamination by polycyclic aromatic hydrocarbons, and mortality were detected. A decrease in species richness and abundance of oil-sensitive animals, an increase in opportunistic and oil-tolerant organisms, and simplification of communities was observed. The impacts were observed in sponges, corals, mollusks, crustaceans, polychaetes, echinoderms, turtles, birds, fish, and mammals. The majority of studies were conducted on bioindicator substrate-associated organisms, with 68.4% of the studies examining the benthos, 21.2% the nekton, and 10.4% the plankton. Moreover, most of the current short-term impacts assessment studies were focused on the species level (66.7%), with fewer studies on the community level (19%), and even fewer on oil-affected ecosystems (14.3%). Oil-related impacts were detected in five sensitive habitats, including blue-carbon ecosystems (e.g., mangroves and seagrass beds) and coastal reefs. These results call for the development of new ocean-basin observation systems for orphan spills. Finally, we discuss how these mysterious oil spills from unknown sources pose a risk to sustainable development goals and ocean-based actions to tackle global climate change.

Ultraviolet-induced fluorescence of oil spill recognition using a semi-supervised algorithm based on thickness and mixing proportion-emission matrices

In recent years, marine oil spill accidents have been occurring frequently during extraction and transportation, and seriously damage the ecological balance. Accurate monitoring of oil spills plays a vital role in estimating oil spill volume, determination of liability, and clean-up. The oil that leaks into natural environments is not a single type of oil, but a mixture of various oil products, and the oil film thickness on the sea surface is uneven under the influence of wind and waves. Increasing the mixed oil film thickness dimension and the mix proportion dimension has been proposed to weaken the effect of the detection environment on the fluorescence measurement results. To preserve the relationships between the data of oil films with different thicknesses and the relationships between the data of oil films with different mixing proportions, the three-dimensional fluorescence spectral data of mixed oil films on a seawater surface were measured in the laboratory, producing a thickness-fluorescence matrix and a proportion-fluorescence matrix. The nonlinear variation of the fluorescence spectra was investigated according to the fluorescence lidar equation. This work pre-processes the data by sum normalization and two-dimensional principal component analysis (2DPCA) and uses the dimensionality reduction results as two feature-point views. Then, semi-supervised classification of collaborative training (co-training) with K-nearest neighbors (KNN) and a decision tree (DT) is used to identify the samples. The results show that the average overall accuracy of this coupling model can reach 100%, which is 20.49% higher than that of the thickness-only view. Using unlabeled data can reduce the cost of data acquisition, improve the classification accuracy and generalization ability, and provide theoretical significance and application prospects for discrimination of spectrally similar oil species in natural marine environments.

Environmental risk assessment of petrogenic hydrocarbon spills in mangrove ecosystems: the Tumaco case study as a baseline, Colombian Pacific

Petrogenic hydrocarbon spills (PHS) are harmful to mangrove ecosystems along tropical coastlines in the short and long term. The aim of this study was to assess the environmental risk of recurrent PHS on mangrove ecosystems in Tumaco municipality, Colombian Pacific. Mangrove characteristics and management aspects led to subdividing the study area into 11 units-of-analysis (UAs) for which threats, vulnerability, potential impacts, and risks were assessed based on environmental factors and the formulation and use of indicators in a rating scale with five categories, which are very low, low, moderate, high, and very high. The results showed that all UAs are highly (64%; 15,525 ha) or moderately (36%; 4,464 ha) threatened by PHS, highly (45%; 13,478 ha) or moderately (55%; 6,511 ha) vulnerable to this kind of pollution, and susceptible to high (73%; 17,075 ha) or moderate (27%; 2,914 ha) potential impacts. The environmental risk was high in 73% (17,075 ha) of the UAs, indicating likely irreversible damage to mangrove ecosystems by PHS, thus pointing to the need of urgent intervention by responsible authorities to ease their recovery and conservation. The methodology and results of this study become technical inputs that serve for environmental control and monitoring, which can be incorporated into contingency and risk management plans.

We need to plan streamlined environmental impact assessment for the future X-Press Pearl disasters

The X-Press Pearl disaster illustrates the urgent needs for streamlined environmental impact assessment to inform decision making. The environmental contamination caused by the disaster is complex, and the biological impact of different environmental stressors, and at different biological scales, needs to be determined. Traditional methods for analyzing complex environmental stressors are often inefficient and do not reflect the biological impact of pollution. The combination of chemical stressors and biological impacts is the key to environmental impact assessment based on integrated monitoring. Whole-cell bioreporters are tools for rapid, efficient and quantitative detection of the bioavailability, stressor effects, and toxicity of pollutants, i.e., spanning a wide range of applications. Here we propose the view that using whole-cell bioreporter technology to streamline short-term environmental impact assessment for maritime disasters such as the X-Press Pearl is more fit-for-purpose/practical than other approaches in use.

Detection of marine oil-like features in Sentinel-1 SAR images by supplementary use of deep learning and empirical methods: Performance assessment for the Great Barrier Reef marine park

Continuous monitoring of oil discharges in coastal and open ocean waters using Earth Observation (EO) has undeniably contributed to diminishing their occurrence wherever a detection system was in place, such as in Europe (EMSA's CleanSeaNet) or in the United States (NOAA's OR&R). This study describes the development and testing of a semi-automated oil slick detection system tailored to the Great Barrier Reef (GBR) marine park solely based on EO data as no such service was routinely available in Australia until recently. In this study, a large, curated, historical global dataset of SAR imagery acquired by Sentinel-1 SAR, now publicly available, is used to assess classification techniques, namely an empirical approach and a deep learning model, to discriminate between oil-like features and look-alikes in the scenes acquired over the marine park. An evaluation of this detection system on 10 Sentinel-1 SAR images of the GBR using two performance metrics - the detection accuracy and the false-positive rate (FPR) - shows that the classifiers perform best when combined (accuracy >98 %; FPR 0.01) rather than when used separately. This study demonstrates the benefit of sequentially combining classifiers to improve the detection and monitoring of unreported oil discharge events in SAR imagery. The workflow has also been tested outside the GBR, demonstrating its robustness when applied to other regions such as Australia's Northwest Shelf, Southeast Asia and the Pacific.

Limes to Remediate Marine Oil Spill via Green and Ecofriendly In Situ Salt Formation

An absolute remedy to oil spill is still much solicited owing to empirical issues like (i) viability of the strategy right on the marine surface, (ii) operational ease of the entire process, and (iii) cost of the entire execution, which are difficult to resolve via solo operation. Current work demonstrates a hassle-free, green, and eco-friendly strategy to fix these issues simultaneously. Herein, spontaneous salt formation between carboxylic acids and primary amines, is employed against oil spill. Lime juice, a natural source of citric acid, is used directly with primary amines to congeal petrol/crude oil and spilled-over seawater (at room temperature) without any external stimulus/solvent. The chemistry behind such gelation is probed comprehensively using established physicochemical methods. A realistic model is fabricated by crude oil spilled over marine water and its removal via selective gelation. The recovery of precious oil from accumulated gel is achieved through simple pressure filtration. The feasibility and implications of this strategy is comprehensively analyzed, and an executable blueprint for real-field operation is developed.

Occurrence and distribution of legacy and emerging pollutants including plastic debris in Antarctica: Sources, distribution and impact on marine biodiversity

Since the first explorers reached Antarctica, their activities have quickly impacted both land and sea and thus, together with the long-range transport, hazardous chemicals began to accumulate. It is commonly recognized that anthropogenic pollution in Antarctica can originate from either global or local sources. Heavy metals, organohalogenated compounds, hydrocarbons, and (more recently) plastic, have been found in Antarctic biota, soil sediments, seawater, air, snow and sea-ice. Studies in such remote areas are challenging and expensive, and the complexity of potential interactions occurring in such extreme climate conditions (i.e., low temperature) makes any accurate prediction on potential impacts difficult. The present review aims to summarize the current state of knowledge on occurrence and distribution of legacy and emerging pollutants in Antarctica, such as plastic, from either global or local sources. Future actions to monitor and mitigate any potential impact on Antarctic biodiversity are discussed.

Multi-Risk Source Oil Spill Risk Assessment Based on a Fuzzy Inference System

Oil is one of the most important sources of energy, about 25 percent of which comes from offshore sources. As a result, the transportation of oil tankers, and the construction of offshore oil platforms and subsea pipelines have increased, to facilitate offshore oil exploitation. However, most oil spill risk assessments analyze the impact of one risk source, and rarely consider multiple risk sources in the study area. This paper focuses on three risk sources that may cause oil spills in a certain area, and establishes an oil spill risk assessment model through a fuzzy inference system. Oil spill probabilities for different risk sources are calculated through the model. According to the definition of oil spill risk, the risk probability of multiple risk sources in the study area is obtained, which can provide technical support for regional oil spill emergency capacity and emergency resource allocation.