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Abstract In this study, the fate of residual oils was investigated during remediation activities for a year after the Wu Yi San oil spill. Microscope observations showed that relatively large amounts of oil-suspended particulate matter aggregate (OSA) were formed. Negatively buoyant OSA was the dominant form (>95%), followed by neutrally (~5%) and positively buoyant (<1%) forms. To elucidate the dominance of negative buoyancy OSA, physicochemical properties of the mineral and residual oils were identified. Chemical analysis showed that the weathering percentage of residual oils was 43.7 ± 2.59%, which was the driving factor for sedimentation of OSA. As the density of oil increased with weathering stages, the density of OSA also increased simultaneously. These results showed that, during mechanical remediation activities, resurfaced residual oils can form negative buoyancy OSA which tends to sink and transfers oil contaminants from intertidal to benthic environments. Highlights • Resuspended residual oils formed oil-suspended particulate matter aggregate (OSA) during remediation activities. • Dominant shape of OSA was oil coated particle with negative buoyancy. • Highly weathered oil was the main cause of negative buoyancy OSA. • Physical remediation activities can transfer residual oil from intertidal to subtidal in the form of OSA. [ABSTRACT FROM AUTHOR]

After the collision of the Singapore-registered oil tanker M/V Wu Yi San into the oil terminal of Yeosu, Korea on January 31, 2014, approximately 900 m of oil and oil mixture were released from the ruptured pipelines. The oil affected more than 10 km of coastline along Gwangyang Bay. Emergency oil spill responses recovered bulk oil at sea and cleaned up the stranded oil on shore. As part of an emergency environmental impact assessment, region-wide monitoring of oil contamination in oyster had been conducted for 2 months. Highly elevated concentrations of polycyclic aromatic hydrocarbons (PAHs) were detected at most of the spill affected sites. Four days after the spill, the levels of PAHs in oysters increased dramatically to 627-81,000 ng/g, the average of which was 20 times higher than those found before the spill (321-4040 ng/g). The level of PAHs in these oysters increased until 10 days after the spill and then decreased. Due to the strong tidal current and easterly winter winds, the eastern part of the Bay-the Namhae region-was heavily contaminated compared with other regions. The accumulation and depuration of spilled oil in oyster corresponded with the duration and intensity of the cleanup activities, which is the first field observation in oil spill cases. Human health risk assessments showed that benzo[a]pyrene equivalent concentrations exceeded levels of concern in the highly contaminated sites, even 60 days after the spill. [ABSTRACT FROM AUTHOR]

Due to the recurrent small spills, oil pollution along coastal regions is still a major environmental issue. Standardized oil fingerprinting techniques are useful for oil spill identifications, but time- and resource-consuming. There have been ongoing needs for simple yet rapid approach for field screening of oil spill. Laser induced fluorescence (LIF) technology can be incorporated into a spectrometer, and with the integration of chemometrics can be consolidated as a potentially useful portable oil type classification device. Using a LIF spectrometer, 775 oil spectra were calibrated into supervised classification models and validated with 162 oil spectra. Reliability of the device to accurately remove background emission from fluorescence spectra was verified. Prediction performance and model robustness were further validated by comparison between commonly used classification models such as partial least square discriminant analysis (PLS-DA) and support vector machine-discriminant analysis (SVM-DA). Robustness in both models were comparable with PLS-DA having a lower number of misclassification (PLS-DA: 5.50%, SVM-DA: 13.8%) while SVM-DA having a lower number of unassigned samples (PLS-DA: 10.9%; SVM-DA: 16 1.39%). This study explicitly demonstrated the development of a new convenient and handy device which can be used as part of the screening process for oil spill fingerprinting. [Display omitted] • Portable oil classification device was developed using LIF coupled with chemometrics. • Tiered approaches were used for development and validation of instrument and model. • 947 spectra of 211 marine fuel oils with 4 different categories were used as a database. • PLS-DA and SVM-DA model allowed highly accurate and robust prediction of oil type. [ABSTRACT FROM AUTHOR]

Oil spills can be environmentally devastating and result in unintended economic and social consequences. An important element of the concerted effort to respond to spills includes the ability to rapidly classify and characterize oil spill samples, preferably on-site. An easy-to-use, handheld sensor is developed and demonstrated in this work, capable of classifying oil spills rapidly on-site. Our device uses the computational power and affordability of a Raspberry Pi microcontroller and a Pi camera, coupled with three ultraviolet light emitting diodes (UV-LEDs), a diffraction grating, and collimation slit, in order to collect a large data set of UV fluorescence fingerprints from various oil samples. Based on a 160-sample (in 5x replicates each with slightly varied dilutions) database this platform is able to classify oil samples into four broad categories: crude oil, heavy fuel oil, light fuel oil, and lubricating oil. The device uses principal component analysis (PCA) to reduce spectral dimensionality (1203 features) and support vector machine (SVM) for classification with 95% accuracy. The device is also able to predict some physiochemical properties, specifically saturate, aromatic, resin, and asphaltene percentages (SARA) based off linear relationships between different principal components (PCs) and the percentages of these residues. Sample preparation for our device is also straightforward and appropriate for field deployment, requiring little more than a Pasteur pipette and not being affected by dilution factors. These properties make our device a valuable field-deployable tool for oil sample analysis. Image 1 • First demonstration of machine learning- and UV fluorescence spectrum-based classification of oil spill samples. • Physicochemical properties (SARA) can also be predicted. • A standalone, Raspberry Pi based handheld device analyzes and classifies oil spill samples. • Classification and analysis are not affected by the dilution factor. [ABSTRACT FROM AUTHOR]

Lubricant (lube) oil discharge from ships has been widely considered as normal "operational consumption", but is now deemed to be oil pollution. Despite the chronic contamination of the marine environment by lube oil, the number of studies related to its environmental impact, characteristics, and toxicity is limited. This study is the first attempt to investigate the environmental fate of lube oil subjected to photooxidation using in situ mesocosms. A tiered approach using thin-layer chromatography–flame ionization detection (TLC–FID), Fourier-transform infrared spectroscopy (FTIR) and gas chromatography–mass spectrometry (GC–MS) demonstrated compositional changes in lube oil and the water-soluble fraction (WSF). Total polycyclic aromatic hydrocarbons (ΣPAHs) in lube oil after 96 h of photooxidation were measured at 79.8 and 41 μg/g in the control (Con) and exposure (Exp) groups, respectively. Meanwhile, the ΣPAHs concentration in WSF after 96 h was very low, at 0.25 and 0.45 μg/L in Con and Exp, respectively. FTIR and GC–MS helped identify bond changes and photoproducts in WSF. A wide range of photoproducts, including carboxylic acids, esters, anhydrides, aldehydes and ketones, were identified in WSF. Toxic effects of WSF in both the Con and Exp groups obtained after 96 h of photooxidation were evaluated on olive flounder (Paralichthys olivaceus) embryos. Morphological defects, especially tail fin fold defects, were found to be significantly elevated in both the Con and Exp groups, with marginally higher frequency in Exp. The results of this study demonstrate the need for further research on lube oil weathering, including monitoring over prolonged periods of time. Image 1 • Environmental significance of lubricant oil inputs to marine water is emphasized. • The first study conducted to assess the environmental fate and toxicity of lubricant. • Photooxidation effects on lubricant oil are characterized. • Toxic effects of lubricant's water-soluble fractions are evaluated using fish embryos. [ABSTRACT FROM AUTHOR]