Following the DWH oil spill event, crude oil reaching the shoreline of Gulf of Mexico produced petroleum oil deposit with a range of distinct geometries, including sphere tar balls and horizontal tar sheets. Numerical models were developed based on the Deep Water Horizon oil spill conditions to evaluate the influence of deposit geometry on long term persistence of residual NAPL oil. Two extreme deposit geometries were modeled in this study: the horizontal tar sheet and the spherical tar ball. Both two-dimensional modeling approach and three-dimensional modeling approach were applied to compare two contrasting geometries. The two-dimensional model results showed that sheet geometry deposits exhibited a greater obstruction to groundwater flow relative to the spherical deposits and induced a larger sulfate reducing zone downgradient of the NAPL source, resulting in significantly greater sulfate-based biodegradation of benzene. Three-dimensional models were constructed to assess the influence of key geometry parameters on oil deposit fate and persistence. Three parameters affecting deposit's geometric structure were recognized, including the upper horizontal area of the sheet deposit, the thickness of the sheet deposit, and the radius of the sphere deposit. The three-dimensional model results suggested that thickness of the sheet deposit and radius of the sphere deposit were important geometry factors impacting the fate and long term persistence of residual NAPL oil in the coastal environment. However, the influence of deposit geometry differed depending on the solubility of the different NAPL components. When high solubility compound and low solubility compound both exist in the oil deposit, the influence of deposit geometry on benzene degradation was significant, while the influence on naphthalene was almost negligible. / Master of Science

The objective of this thesis was to understand the factors that affect the selection of remedial treatments for the complex staining of masonry materials on cultural resources located in environmentally sensitive sites such as Fort Livingston, Louisiana, on the Gulf Coast of the United States and other locations impacted by pollutants including crude oil. After the Deepwater Horizon oil spill in April 2010, the brick-and-tabby Fort was stained by crude oil. The EPA recommends SWA for removal of oil from solid surfaces such as masonry; however, limited research has been conducted into SWA effective for removal of crude oil from masonry, particularly in remote and environmentally sensitive locations. Research was conducted collaboratively at NCPTT and UT-Austin to identify a series of suitable SWA and to develop methods for evaluating SWA effectiveness in the laboratory. Products were selected for laboratory evaluation that do not require long dwell times, are easy to transport to the site, can be applied with portable equipment, produce effluent that can be collected for off-site disposal, and are listed on the EPA-published NCP Product Schedule. Two sets of 36 brick samples each were soiled with crude oil from the Fort. One set of samples was artificially weathered and one set was unweathered prior to being cleaned with selected six SWA. Laboratory evaluation shows that the primary factor affecting cleaner selection for remediation of brick masonry stained by light crude oil is the extent of weathering of oil on the masonry. For light crude oil, such as that spilled in the Gulf, organic solvent-based cleaners may be most effective if cleaning is possible soon after the staining occurs. Aqueous surfactant cleaners are most effective for removing weathered light crude oil from masonry. The following SWA listed in order of performance are recommended for field trials at Fort Livingston: 1. Cytosol; 2. SC-1000; 3. De-Solv-It APC; 4. De-Solv-It Industrial followed by De-Solv-It APC; 5. De-Solv-It Industrial followed by SC-1000. / text

L'application de la Directive Cadre sur l'Eau et l'obligation de surveillance de la qualité d'eau pour la consommation humaine et les activités récréatives ou industrielles, telles que la production d'eau potable, entraînent une forte demande pour des systèmes d'évaluation et de suivi de la qualité de l'eau. Le projet de recherche MIGR'HYCAR (http://www.migrhycar.com) a donc été mis en place pour répondre à un besoin opérationnel et à un défaut d'outils d'aide à la décision adaptés face aux déversements d'hydrocarbures en eaux continentales (rivières, lacs et estuaires) qui représente plus de 50% des déversements accidentels en France. Au cours du projet de recherche MIGR'HYCAR, un modèle mathématique de dérive de nappe d'hydrocarbures, composé d'un modèle lagrangien couplé à un modèle eulérien, a été développé dans la plate-forme hydro-informatique TELEMAC (http://www.opentelemac.org). Le modèle lagrangien décrit le mouvement de la nappe en surface en considérant celle-ci comme un ensemble de particules. Ainsi le modèle développé est capable de modéliser les principaux phénomènes agissant sur une nappe d'hydrocarbures une fois celle-ci déversée : convection, diffusion, échouage, re-largage, étalement, évaporation, dissolution et volatilisation. Bien que le phénomène de dissolution ne concerne qu'un très faible volume d'hydrocarbures, ce processus peut avoir des conséquences importantes du point de vue de la toxicité. Afin de suivre l'évolution du pétrole dissous, un modèle eulérien de suivi de traceurs a été adopté. La quantité de traceur dépend directement de la masse dissoute des particules lagrangiennes. Cette approche permet le suivi des hydrocarbures dissous dans la colonne d'eau. Des cinétiques effectuées en laboratoire ont pour but la calibration du modèle numérique. En complément de cas tests issus de la littérature et de cas réels, des résultats expérimentaux issus d'expérimentations effectuées en canal d'essai doivent permettre de vérifier et valider la qualité des simulations numériques sur des situations où les conditions ne sont que partiellement contrôlées / The application of the European Water Framework Directive on water quality for human consumption and industrial activities creates a need for water quality assessment and monitoring systems. The MIGR'HYCAR research project (http://www.migrhycar.com) was initiated to provide decisional tools for risks connected to oil spills in continental waters (rivers, lakes and estuaries), which represent more than 50% of accidental spills in France. Within the framework of this project, a new numerical oil spill model has been developed, as part of the Telemac hydro-informatics system (see: (http://www.opentelemac.org), by combining Lagrangian and Eulerian methods. The Lagrangian model describes the transport of an oil spill near the free surface. The oil spill model enables to simulate the main processes driving oil plumes: advection, diffusion, oil beaching, oil re-floating, evaporation, dissolution, spreading and volatilization. Though generally considered as a minor process, dissolution is important from the point of view of toxicity. To model dissolved oil in water, an Eulerian advection-diffusion model is used. The fraction of dissolved oil is represented by a passive tracer. This approach is able to follow dissolved hydrocarbons in the water column. Laboratory experiments were conducted to characterise the numerous kinetics of the processes listed above. In addition, meso-scale dynamic experiments in artificial channels and test cases derived from the literature are used to validate the numerical model

Web mashup is a lightweight technology used to integrate data from remote sources without direct access to their databases. As a data consumer, a Web mashup application creates new contents by retrieving data through the Web application programming interface (API) provided by the external sources. As a data provider, the service program publishes its Web API and implements the specified functions. In the project reported by this thesis, we have implemented two Web mashup applications to enhance the Web site oystersentinel.org: the Perkinsus marinus model and the Oil Spill model. Each model overlay geospatial data from a local database on top of a coastal map from Google Maps. In addition, we have designed a Web-based data publishing service. In this experimental system, we illustrated a successful Web mashup interface that allows outside developers to access the data about the local oyster stock assessment.

Abstract The purpose of this study was to explore the impact of the BP Deepwater Horizon oil spill on students of two coastal Louisiana secondary schools. Bronfenbrenner’s (1979) ecological systems theory was used as a framework to understand how exposure, gender, socioeconomic status, and resilience interact to influence the impact of the spill on students. Cross-sectional questionnaires were administered to 155 high school students in May 2012 and 225 middle school students in January 2013 out of 1247 possible for a return rate of about 30%. Results showed that exposure groups differed significantly on students’ Impact of Event Scale (IES; Horowitz, Wilner, & Alvarez, 1979) scores. Students with high exposure to the oil spill had significantly higher IES scores than those with no exposure and low exposure. Logistic regression results indicated that exposure was a significant predictor of higher IES scores and as exposure increased by 1, students were 1.46 times more likely to experience higher impact. Males were found to have significantly higher IES scores than females, with a low effect size. Students did not differ significantly across resilience levels. In the entire sample, lower-SES students did not score significantly different on IES scores than higher-SES students. However, in the high school significant differences were found between SES groups and SES was a significant predictor of higher IES scores. Implications are provided for counselor educators interested in disaster mental health. Conclusions include suggestions for counselors servicing areas affected by the oil spill and how individual and environmental characteristics of students can influence risk factors. Keywords: Disaster mental health, crisis intervention counseling, ecological systems theory, BP Deepwater Horizon oil spill, secondary school students, resilience, risk factors

Derramamentos de petróleo geraram o aumento da atenção de órgãos governamentais e civis quanto a estudos e técnicas para minimizar os danos aos recursos ambientais e socioeconômicos causados por este tipo de acidente. O desenvolvimento de técnicas e os estudos relacionados à prevenção e resposta aos acidentes busca maior eficiência na resposta à contingência e à diminuição dos danos ambientais e socioeconômicos causados na área atingida. A Carta de Sensibilidade Ambiental ao Derramamento de Óleo (Carta SAO) é uma importante ferramenta para a diminuição de danos causados ao ambiente, para o planejamento ambiental na prevenção e na reposta a acidentes em locais de armazenamento e transporte de hidrocarbonetos, tais como dutos, ferrovias, rodovias, etc. Na Carta SAO, para áreas de exposição de sedimentos e rochas sedimentares, procura-se quantificar e qualificar uma determinada área que apresente vulnerabilidade e sensibilidade ao óleo, ou seja, estipular a área e as características intrínsecas do terreno que apresenta alguma probabilidade de ser atingido por óleo, considerando também atividades de resposta. As características dos sedimentos existentes em áreas vulneráveis permitem a determinação de sua sensibilidade, assim buscou-se estudar os parâmetros sedimentares mais influentes na determinação da sensibilidade ambiental do terreno, como a granulometria e seleção, os quais influenciam a porosidade e permeabilidade do terreno, e o cruzamento dessas informações com a declividade do terreno. A fim de testar a eficiência desses parâmetros, o estudo foi aplicado na Bacia do Ribeirão Tamanduá, na região de Cravinhos (SP), por ser interceptada pelo Duto OSBRA e a área de exposição dos arenitos da Formação Botucatu. / Oil spills have resulted in increased awareness among government and private agencies regarding studies and techniques to minimize damages caused by this type of accident to environmental and socio-economic resources. The development of techniques and the studies for prevention and response to accidents is intended to achieve greater effectiveness in dealing with this type of contingency and to decrease the environmental and socio-economic damage to the areas affected by oil spills. The Environmental Sensitivity Index Map for Oil Spills (ESI Map) is an important tool that helps to decrease the damage caused to the environment. It is also useful in planning prevention and responding to accidents in storage areas and in transporting hydrocarbons, in ducts, by rail, road, etc. The purpose of the ESI Map is to quantify and qualify certain areas of exposed sediments and sedimentary rocks that are vulnerable or present sensitivity to oil. In other words, stipulate the area and the intrinsic characteristics of the ground that may receive an oil spill, and considering the response actions. The characteristics of existing sediments in vulnerable areas allow the determination of the area\'s sensitivity. As a result, the study focused on the sedimentary parameters with greatest influence in determining the area\'s environmental sensitivity, such as granulometry and grain selection, which have an influence in the ground\'s porosity and permeability, and cross-referencing this information with the declivity of the ground. In order to test the efficiency of these parameters, the study was implemented in the Bacia do Ribeirão do Tamanduá, in the Cravinhos (SP) region, because it intercepts the OSBRA oil pipeline and an area with exposed sandstone from the Botucatu Formation.

Crude oil causes both lethal and sublethal effects on marine organisms, but the impact upon sensory function remains unexplored. Elasmobranchs rely upon the effective functioning of their sensory systems for use in feeding, mating, and predator avoidance. The objective of this study was to test the effect of crude oil upon the olfactory and electroreceptive sensitivity of the Atlantic stingray, Dasyatis sabina. The magnitudes of the electro-olfactogram (EOG) responses were significantly depressed by 26% (Glutamic Acid) to 157% (Cysteine) for all amino acids when stingrays were exposed to crude oil. The shapes of the EOG responses when exposed to oil were also significantly different, exhibiting a more protracted response compared to un-exposed stingrays. Oil exposed stingrays exhibited a significant decrease in orientation distance to prey-simulating electric fields. This study is the first to quantify the effects of crude oil on olfactory and electrosensory sensitivity of marine predators. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

nÃo hà / O mapeamento da poluiÃÃo de Ãleo no mar utilizando imagens de Radar de Abertura SintÃtica (SAR, do inglÃs Synthetic Aperture Radar) à uma importante Ãrea de interesse na Ãrea da vigilÃncia ambiental. Pode-se utilizar imagens SAR para extrair caracterÃsticas atravÃs de diferentes mÃtodos com o objetivo de predizer atravÃs de Redes Neurais Artificiais (RNAs) se uma regiÃo especÃfica contÃm ou nÃo uma mancha de Ãleo. O principal problema dessa abordagem à a ocorrÃncia de excessivos alarmes falsos decorrentes de erros de classificaÃÃo. Manchas de Ãleo sÃo eventos raros e a pequena disponibilidade de imagens contendo manchas à um fator limitante do desempenho dos classificadores. Este trabalho propÃe a utilizaÃÃo de mÃltiplos conjuntos de caracterÃsticas e mÃtodos de combinaÃÃo de classificadores para minimizar o nÃmero de alarmes falsos a fim de possibilitar a reduÃÃo de custos operacionais de sistemas automÃticos de deteÃÃo de manchas de Ãleo. As imagens SAR utilizadas neste trabalho nÃo estÃo limitadas a um Ãnico sistema de imageamento e diferentes conjuntos de caracterÃsticas baseados na geometria e textura das manchas foram testados. Os desempenhos de generalizaÃÃo de mÃtodos de combinaÃÃo de classificadores, como boosting e bagging, foram comparados com aqueles obtidos com classificadores individuais, como Perceptron Multi-Camadas (MLP, do inglÃs Multi-Layer Perceptron) e MÃquina de Vetor de Suporte (SVM, do inglÃs Support Vector Machine). Os resultados experimentais sugerem que a caracterizaÃÃo das manchas de Ãleo pode ser significativamente melhorada atravÃs do uso do boosting,mesmo quando poucas imagens amostrais estÃo disponÃveis. / Mapping ocean oil pollution by using Synthetic Aperture Radar (SAR) images is an important area of interest for environmental surveillance. One can make use of the SAR images to extract features by using different methods in order to predict if a specific region contains an oil spill or not using Artificial Neural Networks (ANN). A major problem in this approach is the number of false alarms due to misclassification. Oil spills are rare events and the number of available images containing spills is atistically small which is a limitation for the classifier performance. This work proposes the use of multiple feature sets and classifier combining methods to minimize the number of false alarms and thus, reduce the operational costs of automatic oil spill detection systems. The SAR images used in this work are not limited to a specific imaging system and different feature sets based on geometry and texture of the spills were tested. The generalization performances of classifier combination methods as boosting and bagging were compared with those resulting from single classifiers as Multilayer Perceptron (MLP) and Support Vector Machines (SVM). The experimental results suggest that oil spill characterization can be significantly improved using boosting even when few image samples are available and the feature sets have high dimensionality.

Sunken oil is difficult to locate because remote sensing techniques cannot as yet provide views of sunken oil over large areas. Moreover, the oil may re-suspend and sink with changes in salinity, sediment load, and temperature, making deterministic fate models difficult to deploy and calibrate when even the presence of sunken oil is difficult to assess. For these reasons, together with the expense of field data collection, there is a need for a statistical technique integrating limited data collection with stochastic transport modeling. Predictive Bayesian modeling techniques have been developed and demonstrated for exploiting limited information for decision support in many other applications. These techniques brought to a multi-modal Lagrangian modeling framework, representing a near-real time approach to locating and tracking sunken oil driven by intrinsic physical properties of field data collected following a spill after oil has begun collecting on a relatively flat bay bottom. Methods include (1) development of the conceptual predictive Bayesian model and multi-modal Gaussian computational approach based on theory and literature review; (2) development of an object-oriented programming and combinatorial structure capable of managing data, integration and computation over an uncertain and highly dimensional parameter space; (3) creating a new bi-dimensional approach of the method of images to account for curved shoreline boundaries; (4) confirmation of model capability for locating sunken oil patches using available (partial) real field data and capability for temporal projections near curved boundaries using simulated field data; and (5) development of a stand-alone open-source computer application with graphical user interface capable of calibrating instantaneous oil spill scenarios, obtaining sets maps of relative probability profiles at different prediction times and user-selected geographic areas and resolution, and capable of performing post-processing tasks proper of a basic GIS-like software. The result is a predictive Bayesian multi-modal Gaussian model, SOSim (Sunken Oil Simulator) Version 1.0rc1, operational for use with limited, randomly-sampled, available subjective and numeric data on sunken oil concentrations and locations in relatively flat-bottomed bays. The SOSim model represents a new approach, coupling a Lagrangian modeling technique with predictive Bayesian capability for computing unconditional probabilities of mass as a function of space and time. The approach addresses the current need to rapidly deploy modeling capability without readily accessible information on ocean bottom currents. Contributions include (1) the development of the apparently first pollutant transport model for computing unconditional relative probabilities of pollutant location as a function of time based on limited available field data alone; (2) development of a numerical method of computing concentration profiles subject to curved, continuous or discontinuous boundary conditions; (3) development combinatorial algorithms to compute unconditional multimodal Gaussian probabilities not amenable to analytical or Markov-Chain Monte Carlo integration due to high dimensionality; and (4) the development of software modules, including a core module containing the developed Bayesian functions, a wrapping graphical user interface, a processing and operating interface, and the necessary programming components that lead to an open-source, stand-alone, executable computer application (SOSim - Sunken Oil Simulator). Extensions and refinements are recommended, including the addition of capability for accepting available information on bathymetry and maybe bottom currents as Bayesian prior information, the creation of capability of modeling continuous oil releases, and the extension to tracking of suspended oil (3-D).

Purpose: When the Deepwater Horizon oilrig in the Gulf of Mexico faced disaster in late April 2010, news coverage immediately began of the disaster that would unfold. BP took the blame and its financial resources were strained as it struggled with stopping the oil leak, cleanup work as well as its PR image. While the US took many blows of the consequences to ecosystem and tourism, financial consequences swept across the world, mainly Britain, where BP had its headquarters.The event gives an excellent chance at comparing the media coverage from both the US and Britain. By studying The Daily Telegraph and The New York Times, we want to see both similarities and differences in the themes they focused on as well as seeing trends in the themes over time. Theories: The theory chapter is heavily based around the Agenda-setting theory in the media communication field. Methodology: A quantitative content analysis (QCA) of some 500 news articles in The Daily Telegraph and The New York Times from April 22 to July 15. The QCA was made to find the main theme of articles to give us data on how many articles of each theme, as well as their distribution over time. The collected data was ultimately made into diagrams. Conclusion: The two newspapers have a clear difference in that the New York Times have a more than twice the articles published compared to The Daily Telegraph. They do however both share some trends in the themes with some exceptions. Looking at the distribution of these themes within each newspaper, it’s clear that the British newspaper focused more heavily on BP while the American was focusing more heavily on consequences.