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AbstractBicadinanes (C30H52) are a family of non-hopanoid, pentacyclic triterpane biomarkers whose utility in oil spill fingerprinting has, to our knowledge, not been previously explored. Owing to their derivation from Diptocarpaceae tree (dammar) resin, crude oils containing bicadinanes are geographically and temporally limited to Southeast Asian oils sourced from Oligocene or younger strata. Bicadinane-bearing oils produced from Southeast Asia, however, are shipped worldwide and thereby bicadinanes may be present in oils spilled both within and outside of Southeast Asia. Bicadinanes’ relative or absolute concentrations are readily measured using a standard oil spill identification analytical method (GC/MS-SIM) that routinely targets more conventional biomarkers (triterpanes, steranes, and aromatic steroids). In this study, the absolute concentrations of four bicadinane isomers (W, T, T1 and R) were measured in 42 tarballs collected from shorelines along the southern extent of the Straits of Singapore, an area with very high oil tanker and cargo vessel traffic. The tarballs’ specific origins are unknown but safely presumed to be derived from various unknown oil spills and/or oil seeps in the region. GC/FID was used to classify the tarball oils’ level of biodegradation (Levels 1, 4, and 6). The absolute concentration of total bicadinanes ranged from 7.5 to 208 µg/g and varied widely and independent of the level of biodegradation. The relative concentrations among the four bicadinane isomers (T > W>T1∼R; on average, 56% > 20% > 12% each) also showed no obvious or statistically significant trend with biodegradation for the samples studied. Thus, variations in both total and individual isomer concentrations are attributable to the tarballs’ multiple crude oil sources spilled or seeped in the study area. Diagnostic ratios (DRs) are critical components in oil spill identification protocols. A newly proposed DR of (W + T)/hopane varied widely (0.01 to 0.54) and also independently from the more conventionally used DR of 18α(H)-oleanane/hopane (oleanane/hopane; 0.04 to 0.42). Two newly proposed DRs among the four bicadinane isomers, W/T and T/(T1 + R), also varied among the 42 tarball oils studied (0.27 to 0.45 and 1.4 to 3.2, respectively). The variation in the (W + T)/hopane, oleanane/hopane, W/T and T/(T1 + R) ratios was unrelated to the level of biodegradation for the samples studied and exceeded the statistical criteria used in the CEN (2012) oil spill identification protocol (i.e., 95% repeatability limit) and thereby demonstrates these DRs’ utility in comparing and distinguishing among different crude oils containing bicadinanes – and, of course, between crude oils that do and do not contain bicadinanes. The additional specificity offered by bicadinanes argues they should be included as target analytes in oil spill identification studies throughout Southeast Asia or in other areas where Southeast Asian oils are believed to be present (shipped, handled, or used). [ABSTRACT FROM AUTHOR]

Oil spillages on a sea's or an ocean's surface are a threat to marine and coastal ecosystems. They are mainly caused by ship accidents, illegal discharge of oil from ships during cleaning and oil seepage from natural reservoirs. Synthetic-Aperture Radar (SAR) has proved to be a useful tool for analyzing oil spills, because it operates in all-day, all-weather conditions. An oil spill can typically be seen as a dark stretch in SAR images and can often be detected through visual inspection. The major challenge is to differentiate oil spills from look-alikes, i.e., low-wind areas, algae blooms and grease ice, etc., that have a dark signature similar to that of an oil spill. It has been noted over time that oil spill events in Pakistan's territorial waters often remain undetected until the oil reaches the coastal regions or it is located by concerned authorities during patrolling. A formal remote sensing-based operational framework for oil spills detection in Pakistan's Exclusive Economic Zone (EEZ) in the Arabian Sea is urgently needed. In this paper, we report the use of an encoder–decoder-based convolutional neural network trained on an annotated dataset comprising selected oil spill events verified by the European Maritime Safety Agency (EMSA). The dataset encompasses multiple classes, viz., sea surface, oil spill, look-alikes, ships and land. We processed Sentinel-1 acquisitions over the EEZ from January 2017 to December 2023, and we thereby prepared a repository of SAR images for the aforementioned duration. This repository contained images that had been vetted by SAR experts, to trace and confirm oil spills. We tested the repository using the trained model, and, to our surprise, we detected 92 previously unreported oil spill events within those seven years. In 2020, our model detected 26 oil spills in the EEZ, which corresponds to the highest number of spills detected in a single year; whereas in 2023, our model detected 10 oil spill events. In terms of the total surface area covered by the spills, the worst year was 2021, with a cumulative 395 sq. km covered in oil or an oil-like substance. On the whole, these are alarming figures. [ABSTRACT FROM AUTHOR]

Cycloalkanes are abundant and toxic compounds in subsurface petroleum reservoirs and their fate is important to ecosystems impacted by natural oil seeps and spills. This study focuses on the microbial metabolism of methylcyclohexane (MCH) and methylcyclopentane (MCP) in the deep Gulf of Mexico. MCH and MCP are often abundant cycloalkanes observed in petroleum and will dissolve into the water column when introduced at the seafloor via a spill or natural seep. We conducted incubations with deep Gulf of Mexico (GOM) seawater amended with MCH and MCP at four stations. Within incubations with active respiration of MCH and MCP, we found that a novel genus of bacteria belonging to the Porticoccaceae family (Candidatus Reddybacter) dominated the microbial community. Using metagenome‐assembled genomes, we reconstructed the central metabolism of Candidatus Reddybacter, identifying a novel clade of the particulate hydrocarbon monooxygenase (pmo) that may play a central role in MCH and MCP metabolism. Through comparative analysis of 174 genomes, we parsed the taxonomy of the Porticoccaceae family and found evidence suggesting the acquisition of pmo and other genes related to the degradation of cyclic and branched hydrophobic compounds were likely key events in the ecology and evolution of this group of organisms. [ABSTRACT FROM AUTHOR]

The Russian-Ukrainian conflict has diverted European nations from purchasing Russian oil and correspondingly increased the demand from Arab Gulf countries, increasing the number of tankers transporting oil via the Gulf of Suez and the Suez Canal. Therefore, the shipping route is vulnerable to oil seepage accidents, affecting Egyptian tourist cities like Hurghada. Thus, the purpose of this study was to determine the most susceptible zones to contamination and calculate affecting processes (evaporation, natural dispersion, and emulsification) that may occur as a result of crude oil spill accidents in the strait of Gubal northern of Hurghada using the General National Oceanic and Atmospheric Administration Operational Oil Modeling Environment (GNOME) and Automated Data Inquiry for Oil Spills (ADIOS2) models. For this purpose, two scenarios were simulated in February and August 2021 of 1000 metric tons of Arabian light crude oil. The trajectory maps highlighted that the northern Red Sea islands (Ashrafie, Small Gubal, Geisum, Tawila, Shadwan, and Gifton), which have enormous economic and strategic significance are the most vulnerable areas to pollution. In addition, the estimated results demonstrated that the movement of the spilled oil is affected by the prevailing wind direction and marine currents. The ADIOS2 model results showed that more than a quarter of the amount of the light crude oil was evaporated. At the same time, the percentage of natural dispersion increased slowly and did not exceed 1.3% in both scenarios. Furthermore, the emulsion's water content increased rapidly to 90% by the end of the simulation, with obvious shrinkage in the surface volume of the spill body including the emulsion with time. Therefore, oil spill responders could use this study as a reference or guide to inform the systematic environmental conservation planning process near Hurghada coasts. [ABSTRACT FROM AUTHOR]

The Gulf of Guinea is a very active area with respect to maritime traffic as well as oil and gas exploitation. Due to the failure of some actors to comply with environmental standards, this region has been subject to a large number of oil pollution episodes. This anthropogenic oil pollution is in addition to natural oil seepage from the ocean floor. This study aims to detect oil slicks in the Gulf of Guinea and to analyse their spatial distribution using synthetic-aperture radar (SAR) images. Previous works have already locally mapped oil slicks in this area; however, to our knowledge, this study is the first to achieve a global statistical analysis based on 10 years of radar images covering 17 exclusive economic zones (EEZs) in the Gulf of Guinea. The present study is based on a database of 3644 SAR images collected between 2002 and 2012 by the Advanced Synthetic Aperture Radar (ASAR) sensor onboard the European Spatial Agency (ESA) Envisat mission, and these images allowed the identification of 18 063 oil slicks. The spatial distribution of these oil slicks is available from Zenodo: 10.5281/zenodo.6470470 (Najoui, 2022b). The oil slicks detected in this work encompass both oil spills of anthropogenic origin and oil seeps of natural origin (natural oil reservoir leaks). A set of 100 georeferenced oil spills is also available from Zenodo: 10.5281/zenodo.6907743 (Najoui, 2022a). [ABSTRACT FROM AUTHOR]

Monterey formation crude oil spilled from an onshore pipeline and entered the surf zone near Refugio State Beach, Santa Barbara County, CA, USA on 19 May 2015. Exposure to nearshore fish was evaluated by measuring biliary polycyclic aromatic hydrocarbon (PAH) metabolite concentrations in surfperch (Embiotocidae), collected near the release point, at a lesser oiled area, Gaviota State Beach, and near the Coal Oil Point oil seep, Campus Point, at both four days and approximately one year after the oil spill. Three to four weeks after the spill, fish, invertebrates, and kelp were collected near the same three sites for PAH analysis of edible tissues to support the fishery closure assessment. Additionally, thirteen days after the spill, vegetation, and invertebrate tissue samples from the seafloor near Refugio State Beach were analyzed for PAHs. In surfperch bile, mean naphthalene, phenanthrene and benzo(a)pyrene metabolite equivalents were significantly higher at Refugio State Beach, compared to Gaviota State Beach or Campus Point in 2015. One year later, there was no significant difference between the three sites. Spatial and depth zone patterns of PAH tissue concentrations from composited invertebrate, vegetation and fish showed highest concentrations were measured in invertebrates collected near Refugio State Beach. Overall, results show elevated PAH levels in nearshore organisms and provide a useful reference for potential PAH exposures in fish and subtidal invertebrates following a large nearshore oil spill. [ABSTRACT FROM AUTHOR]

Gulf of Guinea is a very active area regarding maritime traffic as well as oil and gas exploitation (platforms). As a result of some actors of both sectors that fail to comply with environmental standards, the region is subject to a large number of oil pollutions. This study aims to detect oil slicks spilled in the Gulf of Guinea and analyse their spatial distribution using Synthetic Aperture Radar (SAR) images. If previous works have already locally mapped oil slicks in this area, this study is the first one to achieve a global statistical analysis based on a very high number of radar images covering 17 Exclusive Economic Zones of the Gulf of Guinea. To carry out the present study, a database of 3,644 SAR images, collected between 2002 and 2012 by the Advanced SAR (ASAR) sensor onboard the European Spatial Agency (ESA) Envisat mission has been used. This database allowed the identification of 18,063 oil slicks (Najoui, 2022). These "Oil slicks" herein detected regroup: "oil spills" - of anthropogenic origin- and "oil seeps" - of natural origin (natural oil reservoir leaks). [ABSTRACT FROM AUTHOR]

A newly developed water sampling system enables autonomous detection and sampling of underwater oil plumes. The Midwater Oil Sampler collects multiple 1-L samples of seawater when preset criteria are met. The sampler has a hydrocarbon-free sample path and can be configured with several modules of six glass sample bottles. In August 2019, the sampler was deployed on an autonomous underwater vehicle and captured targeted water samples in natural oil seeps offshore Santa Barbara, CA, USA. [ABSTRACT FROM AUTHOR]

The Persian Gulf, hosting ca. 48% of the world's oil reserves, has been chronically exposed to natural oil seepage. Oil spill studies show a shift in microbial community composition in response to oil pollution; however, the influence of chronic oil exposure on the microbial community remains unknown. We performed genome-resolved comparative analyses of the water and sediment samples along Persian Gulf's pollution continuum (Strait of Hormuz, Asalouyeh, and Khark Island). Continuous exposure to trace amounts of pollution primed the intrinsic and rare marine oil-degrading microbes such as Oceanospirillales, Flavobacteriales, Alteromonadales, and Rhodobacterales to bloom in response to oil pollution in Asalouyeh and Khark samples. Comparative analysis of the Persian Gulf samples with 106 oil-polluted marine samples reveals that the hydrocarbon type, exposure time, and sediment depth are the main determinants of microbial response to pollution. High aliphatic content of the pollution enriched for Oceanospirillales, Alteromonadales, and Pseudomonadales whereas, Alteromonadales, Cellvibrionales, Flavobacteriales, and Rhodobacterales dominate polyaromatic polluted samples. In chronic exposure and oil spill events, the community composition converges towards higher dominance of oil-degrading constituents while promoting the division of labor for successful bioremediation. [ABSTRACT FROM AUTHOR]

An in situ exposure and effects bioassay system was developed for assessing the toxicity of oil spills to aquatic organisms. The assessment tool combines components of 2 previously developed systems, the sediment ecotoxicity assessment ring (SEA Ring) and the drifting particle simulator. The integrated drifting exposure and effects assessment ring (DEEAR) is comprised of a Global Positioning System (GPS) float, a drifter drogue, the SEA Ring, and the Cyclops‐7 fluorescent sensor. Polyethylene passive sampling devices (PED) were mounted for an additional means to characterize water quality conditions and exposures. The DEEAR is optimized for evaluating oil exposure and toxicity in the shallow surface mixing layer of marine waters. A short‐term preliminary test was conducted in San Diego, California, USA, to verify the operation of the GPS tracking, the iridium communications, and the integrated SEA Ring exposure system. Further, a proof‐of‐concept demonstration was conducted offshore in the Santa Barbara Channel, where natural oil seeps produce surface slicks and sheens. Two DEEAR units were deployed for 24 h—one within the oil slick and one in an area outside observable slicks. An aerial drone provided tracking of the surface oil and optimal sites for deployment. The DEEAR proof‐of‐concept demonstrated integrated real‐time tracking and characterization of oil exposures by grab samples, PED, and fluorescent sensors. Oil exposures were directly linked to toxic responses in fish and mysids. This novel integrated system shows promise for use in a variety of aquatic sites to more accurately determine in situ oil exposure and toxicity. Environ Toxicol Chem 2021;40:1452–1462. © 2021 SETAC [ABSTRACT FROM AUTHOR]

The waters adjacent to the Port au Port Peninsula, in Port au Port Bay, Newfoundland and Labrador, are known to be subject to release of hydrocarbons from natural oil seeps and old abandoned oil wells. An investigation was done to determine whether there were sufficient oil compounds present for planned autonomous underwater vehicle (AUV) test missions to develop adaptive sampling algorithms to delineate oil spills. Fluorometers were used in-situ to measure oil concentrations. Oil-and-water samples were taken at selected waypoints for chemical analysis in the laboratory to validate the sensor measurements and to provide a ground truth. Only one of the fluorometers was found to have a minimum detection level that was capable of sensing the hydrocarbons in the water column. The water sample results indicated hydrocarbon levels up to almost 30 ppm in the east side of the bay, just to the west of Shoal Point, but no detectable levels on the west side of the bay. It was concluded that it would be possible to operate an AUV on a planned fixed mission with a pre-programmed search path and record the levels of signal detected from fluorometers or other sensors. However, it would be difficult to implement an adaptive mission in this case because of the low levels of sensor signals resulting from the low concentrations of hydrocarbon present. [ABSTRACT FROM AUTHOR]

Following the Deepwater Horizon oil spill, the spilled Macondo oil was severely weathered during its transport within the deep-sea plume as discrete particles, which were subsequently deposited on the seafloor. The Macondo oil deposited in deep-sea sediments was distinguished from ambient (background) hydrocarbons and naturally-seeped and genetically-similar oils in the Mississippi Canyon region using a forensic method based upon a systematic, multi-year study of 724 deep-sea sediment cores collected in late 2010 and 2011. The method relied upon: (1) chemical fingerprinting of the distinct features of the wax-rich, severely-weathered Macondo oil; (2) hydrocarbon concentrations, considering a core's proximity to the Macondo well or to known or apparent natural oil seeps, and also vertically within a core; and (3) results from proximal cores and flocculent material from core supernatants and slurp gun filters. The results presented herein establish the geographic extent of “fingerprintable” Macondo oil recognized on the seafloor in 2010/2011. [ABSTRACT FROM AUTHOR]

One fundamental challenge with either acute or chronic oil spills is to identify the source, especially in highly polluted areas, near natural oil seeps, when the source contains more than one petroleum product or when extensive weathering has occurred. Here we focus on heavy fuel oil that spilled (~200 000 L) from two suspected fuel tanks that were ruptured on the motor vessel (M/V) Cosco Busan when it struck the San Francisco-Oakland Bay Bridge in November 2007. We highlight the utility of principal component analysis (PCA) of elemental composition data obtained by high resolution FT-ICR mass spectrometry to correctly identify the source of environmental contamination caused by the unintended release of heavy fuel oil (HFO). Using ultrahigh resolution electrospray ionization (ESI) Fourier transform ion cyclotron resonance mass spectrometry, we uniquely assigned thousands of elemental compositions of heteroatom-containing species in neat samples from both tanks and then applied principal component analysis. The components were based on double bond equivalents for constituents of elemental composition, CcHhN1S1. To determine if the fidelity of our source identification was affected by weathering, field samples were collected at various intervals up to two years after the spill. We are able to identify a suite of polar petroleum markers that are environmentally persistent, enabling us to confidently identify that only one tank was the source of the spilled oil: in fact, a single principal component could account for 98% of the variance. Although identification is unaffected by the presence of higher polarity, petrogenic oxidation (weathering) products, future studies may require removal of such species by anion exchange chromatography prior to mass spectral analysis due to their preferential ionization by ESI. [ABSTRACT FROM AUTHOR]

Highlights: [•] Oil spills detection. [•] Image enhancement techniques. [•] Aeromagnetic data processing and interpretation. [Copyright &y& Elsevier]

The aim of this study is to propose and test a multi-level methodology for detection of oil slicks in ENVISAT Advanced Synthetic Aperture Radar (ASAR) imagery, which can be used to support the identification of hydrocarbon seeps. We selected Andrusov Ridge in the Central Black Sea as the test study area where extensive hydrocarbon seepages were known to occur continuously. Hydrocarbon seepage from tectonic or stratigraphic origin at the sea floor causes oily gas plumes to rise up to the sea surface and form thin oil films called oil slicks. Microwave sensors like synthetic aperture radar (SAR) are very suitable for ocean remote sensing as they measure the backscattered radiation from the surface and show the roughness of the terrain. Oil slicks dampen the sea waves creating dark patches in the SAR image. The proposed and applied methodology includes three levels: visual interpretation, image filtering and object-based oil spill detection. Level I, after data preparation with visual interpretation, includes dark spots identification and subsets/scenes creation. After this process, the procedure continues with categorization of subsets/scenes into three cases based on contrast difference of dark spots to the surroundings. In level II, by image and morphological filtering, it includes preparation of subsets/scenes for segmentation. Level III includes segmentation and feature extraction which is followed by object-based classification. The object-based classification is applied with the fuzzy membership functions defined by extracted features of ASAR subsets/scenes, where the parameters of the detection algorithms are tuned specifically for each case group. As a result, oil slicks are discriminated from look-alikes with an overall classification accuracy of 83% for oil slicks and 77% for look-alikes obtained by averaging three different cases. [ABSTRACT FROM AUTHOR]

This paper presents the results of a long-term survey of the Caspian Sea using satellite SAR and multispectral sensors. The primary environmental problem of the Caspian Sea is oil pollution which is determined by its natural properties, mainly by the presence of big oil and gas deposits beneath the seabed. Our research focuses on natural oil slicks (NOS), i.e., oil showings on the sea surface due to natural hydrocarbon emission from seabed seeps. The spatial and temporal variability of NOS in the Caspian Sea and the possibilities of their reliable detection using satellite data are examined. NOS frequency and detectability in satellite images depending on sensor type, season and geographical region are assessed. It is shown that both parameters vary significantly, and largely depend on sensor type and season, with season being most pronounced in visible (VIS) data. The locations of two offshore seep sites at the Iranian and Turkmenian shelves are accurately estimated. Statistics on individual sizes of NOS are drawn. The release rates of crude oil from the seabed to the sea surface are compared. Detailed maps of NOS are put together, and areas exposed to high risk of sea surface oil pollution are determined. [ABSTRACT FROM AUTHOR]

Porphyrins are highly persistent in the environment and represent a helpful biogeochemical attribute to assess the spatial distribution of the effects of oil spills on ecosystems and their resilience. In areas prone to natural and human-originated oil spills, the measurement of VO– and nickel–porphyrins in marine–sediment samples can identify the effects of oil pollution across spatiotemporal scales. The goal is to explore whether or not these compounds can be useful indicators of the geospatial attributions of oil contamination in the surficial sediments. We hypothesize that the geospatial gradients of porphyrins in marine sediments from petroleum spills and seepage activities—related to traditional indices of oil pollution, such as heavy metals and polycyclic aromatic hydrocarbons—can be identified in small sediment samples and concentrations. The objectives are two-fold: (1) extract and measure VO– and nickel–porphyrins from small marine sediment samples using high-pressure liquid chromatography, and (2) use cluster analysis and the canonical correlation analysis to identify the biogeochemical and geospatial attributions between VO–porphyrins and another index of oil pollution extracted and analyzed from sediments of the Campeche Shelf, in the Gulf of Mexico. High-pressure liquid chromatography with diode array detectors, two inverse phase columns and an isocratic separation method, was used to analyze the marine sediments. We identified 5.1 ng/g to 240.3 ng/g to VO–porphyrins concentrations with gradients toward areas identified as potential sources of oil pollution. Similar patterns were present for nickel–porphyrins, with values two orders of magnitude below those for the VO–porphyrins. The results represent a valuable opportunity to measure the biomarkers associated with oil pollution in small sediment samples. Furthermore, the results can find the potential drawbacks of benthic ecosystem resilience. [ABSTRACT FROM AUTHOR]

Northwestern part is the tectonically impacted region in Tunisia, showing numerous hydrocarbon seeps. The aim of this study is to find a genetic connection between these oil seeps and the potential source rocks in the region. Here we report the organic geochemical data of eighteen oil seeps samples and four source rocks (M'Cherga, Fahdene, Bahloul, and BouDabbous) using aliphatic biomarkers evaluated by GC-MS. Terpanes, hopanes, and steranes biomarkers were identified and statistical analysis was performed to establish oil-oil and oil-source rock correlations. The studied source rocks are derived from a marine environment of deposition, under suboxic conditons, with some traces of continental input for M'Cherga Formation. These source rocks are mature and have entered the oil window, according to C27 18–22,29,30-trisnorneohopane (Ts) and C27 17–22,29,30-trisnorhopane (Tm) biomarkers. About oil seeps, geochemical data suggest that the majority of samples were deposited in an open marine environment, with the exception of four samples that had some continental marks. These latest oil seeps samples have a distinctive lithology (marl) that sets them apart from the rest (carbonate). Statistical study of oil-oil and oil-source rock correlations reveals the existence of two classes of oil seeps. The first included samples that had a positive correlation with BouDabbous black shaleshaving a marine origin and a carbonate lithology. The second is due to M'Cherga source rock and consists of oil seeps with terrestrial traces and a marl trend lithology. The studied oil seeps have no relationship with the Fahdene and Bahloul source rocks. Besides the presence of two generations of hydrocarbon spills in northwestern Tunisia (Lower Cretaceous/Ypresian), there are two types of hydrocarbon spills based on their relationship to tectonic deformations (oil seeps) and outcropping mature source rocks (oil impregnations). • Marine origin of source rocks outcropping in Northern Tunisia. • Presence of oil seeps and hydrocarbon impregnations in Northern Tunisia. • Genetic origin and tectonic associations of oil spills. [ABSTRACT FROM AUTHOR]

The persistence and transformation of water soluble chemical constituents derived from surface oil from the 2015 Refugio Oil Spill and from a nearby natural seep were evaluated under simulated sunlight conditions. Photoirradiation resulted in enhanced oil slick dissolution, which was more pronounced in spill oil compared to seep oil. Nontargeted analysis based on GC × GC/TOF-MS revealed that photoirradiation promoted oil slick dissolution, and more water soluble compounds were released from spill oil (500 compounds) than from seep oil (180 compounds), most of them (488 in spill oil and 150 in seep oil) still persisting in solution after 67 days of photoirradiation. First-order degradation rate coefficients of humic-like water soluble constituents were found to be 0.26 day−1 and 0.29 day−1 for irradiated spill and seep samples, respectively. The decreases in humic-like fluorescence, specific UV absorbance, and aromatic compounds without corresponding decreases in DOC concentration support indirect photochemical transformation in addition to complete photomineralization. [Display omitted] • Oil from a spill and a natural seep were abiotically exposed to simulated sunlight. • Most soluble constituents detected were present after 67 d of sunlight exposure. • Photoirradiation promoted dissolution of surface oil-derived compounds. • Phototransformations occurred in addition to photooxidation. • A new, photolabile fluorescent component was identified in spill oil. [ABSTRACT FROM AUTHOR]

Polarimetric synthetic aperture radar is an important tool in the effective detection of marine oil spills. In this study, two cases of Radarsat-2 Fine mode quad-polarimetric synthetic aperture radar datasets are exploited to detect a well-known oil seep area that collected over the Gulf of Mexico using the same research area, sensor, and time. A novel oil spill detection scheme based on a multi-polarimetric features model matching method using spectral pan-similarity measure (SPM) is proposed. A multi-polarimetric features curve is generated based on optimal polarimetric features selected using Jeffreys–Matusita distance considering its ability to discriminate between thick and thin oil slicks and seawater. The SPM is used to search for and match homogeneous unlabeled pixels and assign them to a class with the highest similarity to their spectral vector size, spectral curve shape, and spectral information content. The superiority of the SPM for oil spill detection compared to traditional spectral similarity measures is demonstrated for the first time based on accuracy assessments and computational complexity analysis by comparing with four traditional spectral similarity measures, random forest (RF), support vector machine (SVM), and decision tree (DT). Experiment results indicate that the proposed method has better oil spill detection capability, with a higher average accuracy and kappa coefficient (1.5–7.9% and 1–25% higher, respectively) than the four traditional spectral similarity measures under the same computational complexity operations. Furthermore, in most cases, the proposed method produces valuable and acceptable results that are better than the RF, SVM, and DT in terms of accuracy and computational complexity. [ABSTRACT FROM AUTHOR]

A novel empirical approach to categorize oil slicks' sea surface expressions in synthetic aperture radar (SAR) measurements into oil seeps or oil spills is investigated, contributing both to academic remote sensing research and to practical applications for the petroleum industry. We use linear discriminant analysis (LDA) to try accuracy improvements from our previously published methods of discriminating seeps from spills that achieved ~70% of overall accuracy. Analyzing 244 RADARSAT-2 scenes containing 4562 slicks observed in Campeche Bay (Gulf of Mexico), our exploratory data analysis evaluates the impact of 61 combinations of SAR backscatter coefficients (σ°, β°, γ°), SAR calibrated products (received radar beam given in amplitude or decibel, with or without a despeckle filter), and data transformations (none, cube root, log10). The LDA ability to discriminate the oil-slick category is rather independent of backscatter coefficients and calibrated products, but influenced by data transformations. The combination of attributes plays a role in the discrimination; combining oil-slicks' size and SAR information is more effective. We have simplified our analyses using fewer attributes to reach accuracies comparable to those of our earlier studies, and we suggest using other multivariate data analyses—cubist or random forest—to attempt to further improve oil-slick category discrimination. [ABSTRACT FROM AUTHOR]

Our research focuses on refining the ability to discriminate two petrogenic oil-slick categories: the sea surface expression of naturally-occurring oil seeps and man-made oil spills. For that, a long-term RADARSAT-2 dataset (244 scenes imaged between 2008 and 2012) is analyzed to investigate oil slicks (4562) observed in the Gulf of Mexico (Campeche Bay, Mexico). As the scientific literature on the use of satellite-derived measurements to discriminate the oil-slick category is sparse, our research addresses this gap by extending our previous investigations aimed at discriminating seeps from spills. To reveal hidden traits of the available satellite information and to evaluate an existing Oil-Slick Discrimination Algorithm, distinct processing segments methodically inspect the data at several levels: input data repository, data transformation, attribute selection, and multivariate data analysis. Different attribute selection strategies similarly excel at the seep-spill differentiation. The combination of different Oil-Slick Information Descriptors presents comparable discrimination accuracies. Among 8 non-linear transformations, the Logarithm and Cube Root normalizations disclose the most effective discrimination power of almost 70%. Our refined analysis corroborates and consolidates our earlier findings, providing a firmer basis and useful accuracies of the seep-spill discrimination practice using information acquired with space-borne surveillance systems based on Synthetic Aperture Radars. [ABSTRACT FROM AUTHOR]