Spill Area Research Articles

Oil Spill Mapping from Kompsat-2 High-Resolution Image Using Directional Median Filtering and Artificial Neural Network

Oil spill accidents in marine environments have a massive impact on ecosystems. Various methods have been developed to detect oil spills using high-resolution optical imagery. However, ocean waves caused by heavy winds occurring in the accident area cause sun glint in the image, and this severely impedes the ability to detect the oil spill area. The objective of this study was to detect oil spill areas from high-resolution optic images using the artificial neural network (ANN) through effective suppression of severe sun glint effects. To enable this, a directional median filter (DMF) was adapted, and its use was compared with that of a traditional low-pass filter. A performance test was conducted using a KOMPSAT-2 image acquired during oil spill accidents that occurred in the Gulf of Mexico in 2010. The proposed method involved two main steps: (i) The sun glint effects caused by the ocean waves were corrected using the DMF; and (ii) the ANN approach was used to detect the oil spill area. The results show the following: (i) The designed DMF, which considers the size and angle of ocean waves, was proficient in correcting the sun glint effect in a high-resolution optical image; and (ii) oil spill areas were efficiently detected using the ANN approach with the proposed filtering method. The oil spill area was classified with accuracies of approximately 98.12% and 89.56% using the receiver operating characteristic (ROC) curve and probability of detection (POD) measurements, respectively. These results show that the accuracy of the proposed method is improved by about 9% compared to the traditional detecting algorithm.

An explorative object-oriented Bayesian network model for oil spill response in the Arctic Ocean

This paper proposes an Object-Oriented Bayesian Network model to study oil spill mitigative measures using cost-effectiveness as a decision-making factor. The cost-effectiveness is defined as the ratio of dollar spent to the efficiency of oil removal in the spill area. The proposed model considers the complexity, lack of data, and uncertainties in an oil spill and response modelling scenario for Arctic shipping accident occurrence. The crude oil release, slick formation, weathering and transport, ecological impact, and response scenarios are modelled using Bayesian Network. Application of the model is demonstrated using a hypothetical scenario of an oil spill involving a ship in the Arctic region. The results show that a combination of in-situ burning, mechanical and manual recovery, and use of dispersants would cost the highest, while the use of in-situ burning, and dispersants gives the cheapest option. The study provides a deeper understanding of oil spill dynamics and effectiveness of the response techniques. The proposed model could serve as a useful tool for oil spill response decision-making.

Economic damages from a worst-case oil spill in the Straits of Mackinac

This paper presents research on the economic damages from a hypothetical worst-case oil spill at the Straits of Mackinac between Lakes Huron and Michigan. This spill could occur because the Enbridge Line 5 oil pipeline traverses the Straits between Michigan's Upper and Lower Peninsula. We quantify potential economic damages to outdoor recreation, commercial fishing, shipping, residential properties, and energy and water supplies. Damages are estimated for two spill scenarios occurring at the onset of the summer tourism season with extensive shoreline oiling. Using evidence from past spills, economic damages would last for between one and two years and would affect locations on the periphery of the spill area, depending on the activity. We project the loss from the worst-case scenario would be at least $1.3 billion.

Flammability risk assessment for oil spill response operations

Immediately following a spill at sea, released oil—ranging from diesel to light crude and diluted bitumen, will initially weather through evaporation, resulting in an elevated concentration of light hydrocarbons in the air. As part of oil spill response operations, first responders use hand-held devices to monitor airborne concentrations when approaching a spill. The feasibility of using numerical modelling as an additional tool to assess potential flammability and plan response operations in the spill area was explored in this study. The Lower Explosive Limit (LEL) is defined as the minimum concentration of a gas in air, in this case a mixture of evaporated hydrocarbons, which can produce a flash fire in the presence of an ignition source. This ignition source could be triggered by the vessel itself or by spill response operations. A framework was put into place, utilizing a threedimensional hydrodynamic model (H3D), an oil spill model (SPILLCALC), and an air dispersion model (CALPUFF) to assess the risk of possible ignition of the hydrocarbon vapour in the event of a spill. The study looked at a hypothetical credible worst case tanker spill (16 500 m3) of diluted bitumen (cold lake winter blend) occurring at Arachne Reef in Haro Strait, British Columbia, Canada. SPILLCALC provided one-minute averaged vapour fluxes from the water surface for each of 17 modelled pseudo-components which were used as inputs to CALPUFF. Using the predicted airborne concentrations of each pseudo-component, time-scaled to one-second averages, the flammability potential in the immediate spill area was determined at each grid point using Le Chatelier’s mixing equation. The approach describe here was developed as a proof of concept, and could be established as a real-time system, bringing valuable information in addition to hand-held devices during a spill response, or during a response exercise. This modelling study was conducted as part of Kinder Morgan’s Trans Mountain Pipeline Expansion Project. There are a number of commercially available oil spill models but few if any are equipped with the ability to model air dispersion and forecast hazardous conditions as discussed in this paper.

Measuring and Reducing Chemical Spills by Students: ARandomized Controlled Trial of Providing Feedback.

The ability to handle chemicals safely is a key aspect of the learning development of students studying chemistry; however, there have been no previously reported investigations of the quantity of chemicals spilled by students during lab experiments. Therefore, the first part of this article reports the assessment of the volume of chemicals spilled by year 1 undergraduate chemistry students (n = 64) at a U.K. university during an existing chemical analysis practical designed to develop volumetric handling skills. The experiment was carried out on paper liners, allowing the areas of students’ spills to be visible and quantified using calibrated spill volumes of liquid to determine the resultant spill area. The volume spilled by the student group was ca. 1.2% of that handled; however, the amount spilled by individual students ranged widely, from ca. 0.02% to ca. 10% of the volume handled. A feedback tool has been developed to allow laboratory demonstrators to rapidly quantify chemical spillage by individual students. This tool also provides the demonstrators with a framework to communicate the potential safety significance of the volume of chemical a student has spilled. A randomized controlled trial (RCT) was carried out to examine the effect of providing feedback to students on their chemical spillage during a subsequent experiment. From a cohort of 185 year 1 undergraduate students, 150 consented to be randomized (81%), and data was collected for 144 students (96% of those randomized). A Hodges–Lehmann estimator for the median change in volume spilled during the second experiment due to providing feedback on spillage during first experiment was a 50% decrease in volume spilled (95% confidence range: 0 to 80% decrease, Mann–Whitney U test p = 0.05). The RCT was a waiting list trial, with all student receiving feedback either during or after the RCT, with blinded assessment by the demonstrators assessing volume spilled for the RCT.

Equilibrium models for predicting areas covered by accidentally spilled liquid fuels and an assessment of their efficacy

Majority of the accidents occurring in chemical process industry begin with the accidental spill of one or the other liquid fuel. This makes it important to forecast the areas likely to be covered by the spill of a given fuel on a given surface of a given inclination, and to devise accident prevention strategies on its basis. This work reviews all the reported models for forecasting the area attained by a liquid spill at equilibrium. It then evaluates the efficacy of these models by testing them with available data. It was possible to run four of the six reported models as data was not adequate to operate the remaining two. It is seen that three of the four models thus tested under-predicted the spill area for some liquid―surface combinations and over-predicted it for some others the percentage error covering large ranges. Only one model consistently under-predicted the area and did so in a much narrower error range. After a ‘weight’ or a ‘correction factor’ was attached to that model it was able to forecast spill area with adequate accuracy.

The Effects of Crude Oil Spill on Some Soil Properties of Different Sites in Duhok Governorate-Kurdistan Region of Iraq

A study was conducted to investigate the impact of oil spillage on some properties of soils collected from Kashe and Nzarke sites in Duhok governorate, Kurdistan region of Iraq. Soil samples were taken from each site after one weak and then after three months at 0-15 cm and 15-35 cm depths with control samples approximately 500 m from outside oil spill area. The soil samples were analyzed using standardsof routine laboratory methods to determine some soil properties. Based on results of the study the contaminated area has higher % TN (percentage total nitrogen) (0.34 and 0.28 %), % TOC (percentage total carbon) ( 4.84 and 5.81 %), Pb (lead) (1.59 and 2.28 mg L-1) and Fe (Iron) (3.20 and 3.13 mg L-1) for Kashe and Nzarke sites respectively than the control especially for 0-15 cm. Crude oil causes decrease in soil pH below 8.2 and also reduced the concentration of available phosphorus to a values of (18.40 and 15.20 mg L-1) for Kashe and Nzarke soils respectively than the control (20.60 and 16.20 mg L-1) for the two sites respectively. Higher values for EC (electrical conductivity), % TN, available phosphorouswere found in Kashe site while Nzarke had higher % TOC, % OM (organic matter), CEC (cation exchange capacity), THC (total hydrocarbon) and available phosphorus.

Efficacy of existing transient models for spill area forecasting

Efficacy of all the existing transient models for forecasting the area attained by accidentally spilled liquid fuels has been sought to be assessed on the basis of experimental data available in prior art. Of the two models for which required inputs are available in the prior art, the model of Huppert (1982) is able to forecast spill area with much greater precision than the model of Raj and Kalelkar (1974). Both the models give better predictions when the spill volume is higher and the spill duration is lower but neither model yields a correlation between the accuracy of the spill area forecast and the nature of the spilled liquid or the receiving surface.

Oil spill extraction by X-band marine radar using texture analysis and adaptive thresholding

ABSTRACTOil spills cause damage in ocean environment. It is important to identify the oil spills for further treatment. We propose an oil spill detection method based on X-band marine radar image using texture analysis. In this method, first, received radar image was denoised by erasing co-channel interference and small speckles. Then, texture analysis was used to indicate the location of oil spills. In the texture analysis, we proposed a texture index calculated by four texture features of grey level co-occurrence matrix (GLCM). The texture index in oil spill area is higher than it in other place, which can be used for extracting oil spill area roughly. In the end, precise extraction of an oil spill was carried out by an adaptive thresholding algorithm on the area selected by the proposed texture index. According to the X-band marine radar images sampled in the oil spill accident on Xingang Port of Dalian, China, an oil spill detected by the proposed texture analysis method is comparable to visual interpretation.

Spatial Distribution of Oil Spills at the Sea Surface in the Southeastern Baltic Sea According to Satellite Sar Data

Abstract Statistical analysis of the spatial distribution of oil spills detected using Synthetic Aperture Radars (SAR) in 2004-2015 at the sea surface in the Southeastern Baltic Sea was conducted. Number, area, and shape of oil pollution division between Exclusive Economic Zones (EEZ) of Poland, Russia, and Lithuania were estimated for the first time. The most polluted area of the Southeastern Baltic Sea is Russian EEZ, where 55% of the total amount of detected oil spills, and 52% of the total area of oil pollution were located. The average area of an oil spill detected within Territorial Sea (TS) and EEZ was estimated. Tail-shaped spills associated with oil discharge from the moving vessels are prevailed, and their amount and area within TS and EEZ were estimated.

A new approach to oil spill detection that combines deep learning with unmanned aerial vehicles

This study presents a novel approach to automatic oil spill detection, using unmanned aerial vehicle (UAV) images to realize intelligent control in oil production. Despite considerable effort, oil spills still cannot be detected automatically and effectively due to the complexity of the real production environment, which forces oil enterprises to manually inspect facilities and detect oil spills. To solve the problem, we propose an approach consisting of UAVs, deep learning and traditional algorithms—an approach which divides the oil spill detection task into three independent sub-tasks. First, we constructed a model based on the deep convolutional neural network, which can quickly detect the suspected oil spill area in images to ensure there are no omissions. Second, to remove other obstacles in the images, we adjusted the Otsu algorithm to filter the detection results, which improves precision while not affecting the recall rate. Third, the Maximally Stable Extremal Regions algorithm was used to obtain the detail polygon region from the detection box, thus automatically evaluating the severity of the oil spill. Experiments showed that our method could solve problems effectively, reducing the cost of oil spill detection by 57.2% when compared with the traditional manual inspection process.

Assessment of oil spills using Sentinel 1 C-band SAR and Landsat 8 multispectral sensors.

Environmental pollution and disasters have gradually increased with the growth of the population. Surveillance of the effects of these incidents is very important for public health. Satellite missions are a very efficient tool for identifying pollutants such as oil spills. The synthetic aperture radar (SAR) sensor is an active microwave sensing system that can be used for oil spill applications with optical sensors mounted on Landsat 8, Sentinel 2, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite systems taking into account cloud coverage and revisiting time of the satellite at the same location. In this study, the oil spill area caused by a ship running aground at 13:40 local time (LT) on 18 December 2016 was studied on the coast of Ildır Bay (Izmir, Turkey) with Sentinel 1 SAR and Landsat 8 multispectral sensors. Different image-processing techniques were applied to Landsat 8 bands such as minimum noise fraction (MNF), morphology, and convolution filters in order to highlight the oil spill area related to the incident. In the detection stage, oil slicks and look-alikes were successfully distinguished by analyzing the SAR data with Landsat 8 results and the location of the ship. With the visual interpretation of the results, the selected techniques are consistent with each other in terms of showing oil spill areas.

Exposomic Biomarkers from the Residents in the Coastal Area of the Hebei Spirit Oil Spill

Exposomic Biomarkers from the Residents in the Coastal Area of the Hebei Spirit Oil Spill

Performance evaluation of oil spill software systems in early fate and trajectory of oil spill: comparison analysis of OILMAP and PISCES 2 in Mersin bay spill.

The aim of this study is to evaluate the performance level of two advanced oil spill software systems in early transport and fate of oil spill through algorithms accepted in oil spill literature. To do this, the performance level of software systems mostly used in real cases have been compared. OILMAP (the oil spill prediction modeling system) and PISCES 2 (potential incident simulation, control and evaluation system) have been used for spill trajectory in the light of four spill scenarios. The findings reveal that the OILMAP has predicted a relatively larger area of spill. In addition, OILMAP has achieved closer results to the calculations of approaches adopted in the literature for evaporation calculations. Besides, OILMAP software has provided highly reliable results in the evaporation rates of oil compared to the calculations of PISCES 2. On the other hand, as for the determination of the risky area, both software systems have yielded results with high reliability values, which could be used in taking precautions against oil spill in such areas.

Using a genetic algorithm to improve oil spill prediction

The performance of oil spill models is strongly influenced by multiple parameters. In this study, we explored the ability of a genetic algorithm (GA) to determine optimal parameters without the need for time-consuming manual attempts. An evaluation function integrating the percentage of coincidence between the predicted polluted area and the observed spill area was proposed for measuring the performance of a Lagrangian oil particle model. To maximise the objective function, the oil spill was run numerous times with continuously optimised parameters. After many generations, the GA effectively reduced discrepancies between model results and observations of a real oil spill. Subsequent validation indicated that the oil spill model predicted oil slick patterns with reasonable accuracy when equipped with optimal parameters. Furthermore, multiple objective optimisation for observations at different times contributed to better model performance.

The Model of Optimal Allocation of Maritime Oil Spill Combat Ships

The paper describes a two-stage method for optimizing the location of marine oil spill combat forces and assessing the costs related to this action at the sea. An optimization problem relates to positioning the oil pollution combat ships in ports in such a way that they are able combat the anticipated number of oil spills in certain positions in the Polish coast of the Baltic Sea area in the shortest possible time. The problem was classified as NP-hard; therefore, in the first stage, an evolutionary algorithm was applied. The main output of the model based on the evolutionary algorithm is the time of arrival of combat ships from the port to the oil spill area, as well as the costs of such operation; this is defined as the aim function. The first stage of the model does not simulate combat pollution action; therefore, the results obtained were treated as approximate. In the second stage, the several best allocations of oil spill response resources obtained in the first stage were used as input to a detailed simulation model of combat action. For each chosen allocation, a number of oil combat action simulations were carried out. The model can be used to create and verify oil pollution contingency plans, and finally increase the sustainability of sea and coastal areas.

Cancer Incidence Trend in the Hebei Spirit Oil Spill Area, from 1999 to 2014: An Ecological Study.

The Hebei Spirit oil spill (HSOS) occurred in the Republic of Korea on 7 December 2007. We aimed to describe the cancer incidence trend in Taean County before and after the oil spill. Five major cancers and leukemia were analyzed. Cancer incidence data were obtained from the Korean National Cancer Center. We compared the standardized incidence rates in Taean with those observed nationwide and selected three coastal areas. Joinpoint regression analysis was used to examine the trends in the average annual percent change and perform comparisons. The incidence rate of prostate cancer increased from 2007 to 2009 at an annual average of 39.3% (95% confidence interval (CI): −25.9, 161.8), 13.5% (95% CI: 11.7, 15.4), and 15.6% (95% CI: 11.9, 19.5), respectively, in Taean, nationwide, and in the coastal areas. The incidence of leukemia among women increased at an annual average of 9.5% (95% CI: −26.6, 63.4) in Taean and 0.6% (95% CI: 0.2, 0.9) nationwide; the rate decreased by 1.9% (95% CI: −12.8, 10.4) in the coastal areas. The trends between Taean County and the coastal areas differed only for prostate cancer (p = 0.0004). The incidence of prostate cancer among Taean County residents has increased since the HSOS.

Adverse effects and immune dysfunction in response to oral administration of weathered Iranian heavy crude oil in the rockfish Sebastes schlegeli

To demonstrate the effects of weathered crude oil residue on the immune systems of resident fish, we measured the changes in toxic chemical concentrations, apoptosis, phagocytosis, metabolism, immune-related gene expression, and cell cycle arrest in livers or kidneys for up to 96 h after the weathered Iranian heavy crude oil (WIHCO) exposure by oral gavage in juvenile rockfish Sebastes schlegeli. Parent polyaromatic hydrocarbons (PAHs) in livers increased up to 5590 ng/g after 6 h exposure and then declined rapidly within 24 h. Hepato-detoxification and immune-related gene expression were also significantly increased (P < 0.05) after 6 h exposure and then declined rapidly within 24 h. However, biliary PAH metabolites and EROD activity remained elevated throughout the test period. Flow cytometry analysis also indicated sustained apoptosis and cell cycle arrests with reduced phagocytic activity for 96 h. Taken together, these results demonstrate rapid declination of the parent PAHs, whereas PAH metabolites remained much longer in tissues with prolonged suppression of immunity in molecular and cellular level, suggesting that weathered crude oil residue is likely linked to the high incidence of immune dysfunction in residential rockfish in oil spill area.

Tracking an Oil Tanker Collision and Spilled Oils in the East China Sea Using Multisensor Day and Night Satellite Imagery

AbstractSatellite remote sensing is well known to play a critical role in monitoring marine accidents such as oil spills, yet the recent SANCHI oil tanker collision event in January 2018 in the East China Sea indicates that traditional techniques using synthetic aperture radar or daytime optical imagery could not provide timely and adequate coverage. In this study, we show the unprecedented value of Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire product and Day/Night Band data in tracking the oil tanker's drifting pathway and locations when all other means are not as effective for the same purpose. Such pathway and locations can also be reproduced with a numerical model, with root‐mean‐square error of &lt;15 km. While high‐resolution optical imagery after 4 days of the tanker's sinking reveals much larger oil spill area (&gt;350 km2) than previous reports, the impact of the spilled condensate oil on the marine environment requires further research.

Risk of Fuel Spills and the Transient Models of Spill Area Forecasting

Most accidents in chemical process industry, as well as a large number of fires in general, are triggered by accidental spilling of flammable liquids. Such spills either get auto-ignited or are set on fire by one or the other ignition source. If other flammable material happens to catch fire before the initial fire is extinguished, the accident gets escalated. In many situations, the escalation is catastrophic, resulting in very large fires, with or without explosions. This paper assesses the transient models developed so far to predict the areas covered by accidental fuel spills.