Oil Spill Emergency Response Research Articles

Graphene aerogel with double pore structure for marine oil spill emergency response

Due to its high porosity, large specific surface area, and strong photothermal conversion performance, graphene aerogel has unique advantages in the field of pollution treatment, especially in the field of recovering highly viscous oils. However, for the treatment of highly viscous oils, the high adsorption capacity and high adsorption rate of graphene aerogel often cannot be combined, which is one of the important reasons limiting its development in this field. A double-step templating strategy for graphene aerogels preparation was used in this work, i.e., Pickering emulsion soft templating and unidirectional freeze casting. Specifically, the dense Pickering emulsion droplets can be stabilized in a short period of time, so that they can be cured quickly. After that, graphene aerogels (DGA-0.8-25) with dual pore structure were prepared by unidirectional freeze casting technology to further form aligned pores based on the pores formed by the Pickering emulsion droplet soft template. The dense presence of Pickering emulsion droplets gives DGA-0.8-25 an ultra-high porosity (96.8 %), which can adsorb 184.53 times its own mass of crude oil. Due to the unidirectional pore structure, the adsorption rate of DGA-0.8-25 on crude oil is as high as 8.39 g·g−1·min−1, which realizes dual improvement of the adsorption capacity and rate of graphene aerogel on crude oil and shows a good application prospect in the treatment of high viscosity crude oil. In addition, DGA-0.8-25 has unique advantages in the field of oil–water separation, with a separation efficiency of 99.04 % for water-in-oil emulsions and 97.63 % for oil-in-water emulsions. When repeated used in photothermal adsorption of highly viscous oil, DGA-0.8-25 can still maintain more than 90.61 % of its initial adsorption capacity after ten cycles of use-regeneration. Because of its unique advantages such as high efficiency and low cost, DGA shows promising in its future large-scale use.

Session 17. Oral Presentation for: Satellite based oil spill emergency response and recovery support

Session 17. Oral Presentation for: Satellite based oil spill emergency response and recovery support

Satellite based oil spill emergency response and recovery support

Oil spills at sea pose a complex and challenging problem. Detecting, reporting, and potentially acting on the spill are difficult tasks, especially if the information is only obtained from the perspective of a vessel. Near-real time and relevant information is crucial for effective management of an oil spill event. This paper demonstrates how satellite-based images, combined with methods for thickness extraction and oil drift trajectory, can provide end-users with actionable and timely information for emergency response and recovery support. The results show the high value of quick delivery and the importance of using multiple sensors and data sources during an emergency, which enhance situational awareness and decision making. We highlight the value of satellite imagery for oil detection and show how it can be used to document the polluter, identify relative oil thickness, model oil drift, and compare different sensors.

A multi-criteria simulation-optimization coupling approach for effective emergency response in marine oil spill accidents

Effective marine oil spill responses are vital to reduce environmental, societal, and economic damage. This study developed a Multi-Criteria Emergency Response System (MC-ERS) to comprehensively evaluate response efficiency, operational costs, and environmental losses. The proposed system integrates dynamic multiphase simulation of oil weathering and oil cleanup processes and further provides effective planning for multi-stage resource allocation through system optimization. The developed weight-sum model improved the performance of response operations by reducing the complexity of multi-criteria decision-making. Particle Swarm Optimization (PSO) was chosen as the foundational optimization algorithm due to its efficiency in rapid convergence and suitability for complex problems. From extensive comparisons of PSO variants across benchmark functions and inertia strategies, the C-PSO algorithm was developed, demonstrating enhanced optimization performance for MC-ERS. The developed modelling system performance was demonstrated and evaluated through a representative case study. The optimization plan coordinated resource allocation from onshore warehouses to harbors and spill sites, balancing oil recovery efficiency, costs, and ecological losses. Optimized results indicate an oil recovery of up to 76.50% in five days. Additionally, the system cuts costs by 3.45% and environmental losses by 15.75%. The findings enhance the efficiency of marine oil spill emergency response and provide support for such incidents.

Optimizing oil spill emergency logistics: a time-varying multi-resource collaborative scheduling model.

Emergency resource scheduling is at the heart of the response to an oil spill, as it lays the foundation for all other emergency operations. Extant studies address the dynamicity inherent to these operations primarily by modeling a dynamic network flow with static data, which is not applicable to continuously changing conditions resulting from oil film movement. To enhance the responsiveness and cost-efficiency of the response to oil spills, this paper takes a novel approach and formulates a multi-objective location-routing model for multi-resource collaborative scheduling, namely, harnessing time-varying parameters rather than static data to model real-time changes in the demand for emergency resources and the transportation network. Additionally, the model considers various operational factors, including the transportation of multiple resources in the order of operating procedures; the coordination of split delivery with the consumption of emergency resources; and the matching of multiple resources with suitable vehicles. To solve the proposed model, a hybrid heuristic algorithm of PSO-PGSA is developed, which utilizes particle swarm optimization (PSO) to search widely for non-dominated solutions. The algorithm then makes use of the plant growth simulation algorithm (PGSA) to find the more effective vehicle routes based on the obtained solutions. Finally, a numerical analysis is used to illustrate the practical capabilities of the developed model and solution strategies. Most significantly, our work not only validates the methodology proposed here but also underlines the importance of incorporating the features of an oil spill emergency response into emergency logistics in general.

Utilizing Numerical Models and GIS to Enhance Information Management for Oil Spill Emergency Response and Resource Allocation in the Taiwan Waters

This study aims to establish a comprehensive workflow for developing emergency response plans for both actual and scenario oil spill incidents in the Taiwan waters while addressing the resource allocation for oil spill containment as well. This workflow comprises two vital components. The first component involves the integration of numerical tools and observational data, which includes the incorporation of wind data from sources such as the National Centers for Environmental Prediction (NCEP) or meteorological stations. Additionally, it incorporates ocean current data simulated by the semi-implicit cross-scale hydroscience integrated system model (SCHISM) into the general NOAA operational modeling environment (GNOME) model, which is a new approach for this purpose. In order to assess the efficacy of this component, two distinct case studies were conducted. The first case study focused on an incident in a northern coastal area of Taiwan under open sea conditions, whereas the second case study examined an incident within a major commercial harbor in central Taiwan. The second component of this workflow involves creating oil risk maps by integrating the results from the first component with specific geographical factors into Google Earth. These oil risk maps serve multiple purposes. They offer real-time information to emergency response commanders regarding oil spill hazard prediction, and they also enable the effective development of emergency response strategies and disposal plans for potential oil spill incidents. This is achieved by generating risk maps for various scenarios using the approach outlined in the first component. Additionally, these maps assist in the assessment and planning of resource allocation for oil containment.

Combined effects of chemical dispersant and suspended minerals on the dispersion process of spilled oil

The dispersion process of spilled oil is an important concern for the effective disposal of oil spills. The dispersed oil concentration and oil droplets size distribution were studied through a wave tank test under the application of chemical dispersant and suspended minerals. The results indicated that dispersant and minerals increased the dispersed oil concentration and the effect of dispersant was more significant, and they had a synergistic effect on oil dispersion. When dispersant and minerals were applied together, the volume mean diameter of oil droplets decreased in the first 30 min, then increased and reached a maximum value at 90–120 min, and decreased again. Moreover, suspended minerals could inhibit the coalescence of oil droplets. This study can afford data support for oil spill emergency response that occurs in inshore or estuaries.

Analysis of Factors Affecting the Effectiveness of Oil Spill Clean-Up: A Bayesian Network Approach

Ship-related marine oil spills pose a significant threat to the environment, and while it may not be possible to prevent such incidents entirely, effective clean-up efforts can minimize their impact on the environment. The success of these clean-up efforts is influenced by various factors, including accident-related factors such as the type of accident, location, and environmental weather conditions, as well as emergency response-related factors such as available resources and response actions. To improve targeted and effective responses to oil spills resulting from ship accidents and enhance oil spill emergency response methods, it is essential to understand the factors that affect their effectiveness. In this study, a data-driven Bayesian network (TAN) analysis approach was used with data from the U.S. Coast Guard (USCG) to identify the key accident-related factors that impact oil spill clean-up performance. The analysis found that the amount of discharge, severity, and the location of the accident are the most critical factors affecting the clean-up ratio. These findings are significant for emergency management and planning oil spill clean-up efforts.

A Multilevel Spatial and Spectral Feature Extraction Network for Marine Oil Spill Monitoring Using Airborne Hyperspectral Image

Marine oil spills can cause serious damage to marine ecosystems and biological species, and the pollution is difficult to repair in the short term. Accurate oil type identification and oil thickness quantification are of great significance for marine oil spill emergency response and damage assessment. In recent years, hyperspectral remote sensing technology has become an effective means to monitor marine oil spills. The spectral and spatial features of oil spill images at different levels are different. To accurately identify oil spill types and quantify oil film thickness, and perform better extraction of spectral and spatial features, a multilevel spatial and spectral feature extraction network is proposed in this study. First, the graph convolutional neural network and graph attentional neural network models were used to extract spectral and spatial features in non-Euclidean space, respectively, and then the designed modules based on 2D expansion convolution, depth convolution, and point convolution were applied to extract feature information in Euclidean space; after that, a multilevel feature fusion method was developed to fuse the obtained spatial and spectral features in Euclidean space in a complementary way to obtain multilevel features. Finally, the multilevel features were fused at the feature level to obtain the oil spill information. The experimental results show that compared with CGCNN, SSRN, and A2S2KResNet algorithms, the accuracy of oil type identification and oil film thickness classification of the proposed method in this paper is improved by 12.82%, 0.06%, and 0.08% and 2.23%, 0.69%, and 0.47%, respectively, which proves that the method in this paper can effectively extract oil spill information and identify different oil spill types and different oil film thicknesses.

Oil spill identification in X-band marine radar image using K-means and texture feature.

Marine oil pollution poses a serious threat to the marine ecological balance. It is of great significance to develop rapid and efficient oil spill detection methods for the mitigation of marine oil spill pollution and the restoration of the marine ecological environment. X-band marine radar is one of the important monitoring devices, in this article, we perform the digital X-band radar image by "Sperry Marine" radar system for an oil film extraction experiment. First, the de-noised image was obtained by preprocessing the original image in the Cartesian coordinate system. Second, it was cut into slices. Third, the texture features of the slices were calculated based on the gray-level co-occurrence matrix (GLCM) and K-means method to extract the rough oil spill regions. Finally, the oil spill regions were segmented using the Sauvola threshold algorithm. The experimental results indicate that this study provides a scientific method for the research of oil film extraction. Compared with other methods of oil spill extraction in X-band single-polarization marine radar images, the proposed technology is more intelligent, and it can provide technical support for marine oil spill emergency response in the future.

SPATIAL ANALYSIS OF ENVIRONMENTAL SENSITIVITY FOR MITIGATION OF OIL SPILL DISASTERS IN THE SERIBU ISLANDS NATIONAL PARK

The Seribu Islands National Park (Taman Nasional Kepulauan Seribu - TNKpS) which has a marine ecosystem area that has the potential to be affected by oil spills originating from oil discharges from ships passing through the Sunda Strait and ship accidents in and out of Tanjung Priuk Port. In addition, in the TNKpS area there are also oil and gas mining companies as well as oil distribution through pipelines which have the potential to cause oil pollution due to leakage of oil distribution pipelines. The availability of maps of Environmental Sensitivity Index and comprehensive environmental data is important for the government to understand the condition of sensitive areas around oil and gas mining areas to mitigate environmental pollution due to oil spills, and can then take priority actions. to protect areas deemed sensitive. The compilation of thematic maps related to environmental sensitivity to oil spills in TNKpS shows that the beach type is not sensitive to oil spills, where the dominant beach type is gently sloping sand which is a substrate that is easy to clean when an oil spill occurs. While the component of biodiversity has the highest sensitivity. The most sensitive socioeconomic components affected by the oil spill are fish farming and marine tourism (snorkeling and diving), both of which are the main livelihoods for the people in TNKpS, especially from the tourism sector. Mitigation of oil spills in TNKpS should focus on dealing with oil spills before reaching sensitive areas where oil collection with skimmers and spraying of dispersants can be carried out before entering the coral reef area. The next step is the protection of sensitive areas from oil spills where this protection can be done by dispelling using an oil boom and directing the oil spill to a less sensitive area. The final step is cleaning the beach area in accordance with oil spill emergency response procedures. Spill simulations carried out with a duration of 3 hours, 5 hours and 24 hours showed that the oil spill had not yet reached the sensitive area when it was 3 hours, so that the ideal anticipatory oil response is to have an oil control exercise with a duration of 3 hours to protect sensitive areas.

Marine Oil Spill Detection with X-Band Shipborne Radar Using GLCM, SVM and FCM

Marine oil spills have a significant adverse impact on the economy, ecology, and human health. Rapid and effective oil spill monitoring action is extraordinarily important for controlling marine pollution. A marine oil spill detection scheme based on X-band shipborne radar image with machine learning is proposed here. First, the original shipborne radar image collected on Dalian 7.16 oil spill accident was transformed into a Cartesian coordinate system and noise suppressed. Then, texture features and SVM were used to indicate the effective monitoring location of ocean waves. Third, FCM was applied to classify the oil films and ocean waves. Finally, the oil spill detection result was transformed back to a polar coordinate system. Compared with an improved active contour model and another oil spill detection method with SVM, our method performed more intelligently. It can provide data support for marine oil spill emergency response.

Study on the Key Technology of Deepwater Oil Spill Simulation in the South China Sea

With the development of oil and gas fields in deepwater areas, the risk of deepwater oil spill accidents is increasing. In order to improve the capacity of deepwater oil spill contingency response and management in the South China Sea, an user-friendly and robust 3D (three-dimensional) underwater oil spill simulation system is developed by using the MFC (Microsoft Foundation Classes) interface library and the 3D OSG (Open Scene Graph) rendering engine. Many key technologies including submarine topography drawing, sea surface emulation, three-dimensional current display and oil particle simulation are developed and integrated, and the functions including 3D simulations of marine environment and deepwater oil spill prediction are also implemented in the simulation software system. The 3D oil spill simulation system has been applied in the preparation of oil spill response plans (OSRP) for Liwan 3-1 Block, Liwan 43-11 Block, Chevron’s Block 42-05 and Baiyun Block in the South China Sea. Preliminary application shows that the system can provide convenient and intuitive visual interactive services for the exploitation of oil and gas resources in the deepwater area of the South China Sea. Meanwhile, the system also specifies underwater trajectories of oil spill in deep waters, the concentration distribution of oil spilled in water, and the time and place the spilled oil reaches the surface, thus providing technical support for on-scene oil spill emergency response and marine environmental impact assessment.

Jet mixing unit for introducing a light bulk substance into a liquid stream

For the oil spill emergency response, a ship system for supplying an active substance to the contaminated zone has been proposed. Various chemical compounds and substances, microorganisms can be used as active substances. To collect most of the oil spill, it was proposed to use a thermally split graphite sorbent. Its supply to the contaminated zone should be carried out in the form of a pulp. One of the key elements of the system is a mixer for introducing the sorbent into the water flow. This article presents the results of three stages of the study of the influence of the geometric parameters of the jet mixer on the average volumetric content of the sorbent in the pulp, the shape of the nozzle and flow of the working fluid. The necessity of mandatory use of a arch destruction device in a bunker with a light sorbent is noted.

Governance of global vessel-source marine oil spills: Characteristics and refreshed strategies

With the rapid development of the international shipping industry, global shipping is getting increasingly frequent and vessel-source oil pollution has become one of the significant contributors to marine environmental pollution. As a special method of oil transportation, oil tankers will do more harm if they have oil spills. The marine pollution caused by ship oil spills around the world has become an increasingly prominent concern of the international community. This paper approaches the subject from beforehand prevention, in-process response, ex-post handling, and comprehensive governance aspects. After analyzing the evolution and the characteristics of the vessel-source oil pollution governance policies worldwide, this paper identifies four crucial issues which include defects in oil tankers' fire and explosion prevention technologies, emergency response systems in oil spills, compensation mechanisms for oil pollution damage, and human factors and ship registry system governance. It then proposes strategy to improve the governance of vessel-source oil pollution, in particular refining the fire and explosion prevention technology for oil tankers, enhancing the oil spill emergency response, perfecting the oil pollution compensation system, paying more attention to the human factor, and advancing the management of flags of convenience. In the final section, this paper points out the future directions of research. The aim of this article is providing a systematic and scientific reference for government departments and concerned organizations, and so that they could take actions to tackle global vessel-source oil pollution.

Next-Generation Smart Response Web (NG-SRW): An Operational Spatial Decision Support System for Maritime Oil Spill Emergency Response in the Gulf of Finland (Baltic Sea)

The Baltic Sea is a unique and sensitive brackish-water ecosystem vulnerable to damage from shipping activities. Despite high levels of maritime safety in the area, there is a continued risk of oil spills and associated harmful environmental impacts. Achieving common situational awareness between oil spill response decision makers and other actors, such as merchant vessel and Vessel Traffic Service center operators, is an important step to minimizing detrimental effects. This paper presents the Next-Generation Smart Response Web (NG-SRW), a web-based application to aid decision making concerning oil spill response. This tool aims to provide, dynamically and interactively, relevant information on oil spills. By integrating the analysis and visualization of dynamic spill features with the sensitivity of environmental elements and value of human uses, the benefits of potential response actions can be compared, helping to develop an appropriate response strategy. The oil spill process simulation enables the response authorities to judge better the complexity and dynamic behavior of the systems and processes behind the potential environmental impact assessment and thereby better control the oil combat action.

Kenya's National Framework to Enhance the Response Capability to Oil Spills

ABSTRACT Investment in the oil and gas sector in the East Africa region should commingle with the incorporation of best practices in oil spill emergency response. Upstream, Midstream, and Downstream operations must focus on prevention of emergencies but always be prepared to implement response actions if all engineering and safety defenses fail. Elements of environmental stewardship, applied scientific research, and technology are among key considerations needed in contingency planning to mitigate the socioeconomic and ecological consequences of hydrocarbon releases. Kenya is in the process of realizing its oil and gas potential. The country has started injection and production testing of its oil reserves in Turkana and has initiated oil export through the Port of Mombasa. These activities, coupled with increased rate of sea borne trade and planned relocation of Kipevu Oil Terminal to an offshore platform, places the country at risk of oil spills and therefore the need to have a robust system of spill prevention, preparedness and response. The World Bank's International Development Assistance (IDA) recognized the relevance of enhancing preparedness and response capability and, through the Kenya Ministry of Petroleum and Mining, initiated the development of the national framework for onshore and offshore oil prevention, preparedness, and response capacity in Kenya. The project is divided into four phases (Identification, Development, Implementation, and Kenya's Regional (East Africa) Response Capacity Enhancement) and four primary deliverables: National Oil Spill Contingency Plan for Marine and Navigable WatersOnshore National Oil Spill Contingency PlanNational Shoreline Cleanup Assessment Technique (SCAT) Guidance ManualNational Oiled Wildlife Response and Preparedness Guidance Manual This paper provides an overview of the four phases, describes the approach used to meet the project objectives, and provides an overview of the national oil spill contingency plans and national guidance manuals.

Emergency treatment technology and case study of sudden environmental pollution caused by oil spill in river basin

Based on the characteristics of sudden oil spill environmental pollution in a river basin, this paper presented a method for emergency treatment of sudden oil spill environmental pollution in a river basin by analyzing and summarizing a large number of oil spill emergency treatment cases. Stratigies such as pollution source blocking, sluice dam controlling and pollutant interception were applied to control and eliminate the pollution situation. Besides, typical oil spill emergency response cases were picked and analyzed to provide a reference and guidance for the emergency treatment of oil spill incidents in China.

High-throughput screening of oil fingerprint using FT-IR coupled with chemometrics

An important element of the oil spill emergency response is the ability to rapidly identify the properties of oil spilled. Chemometrics provides large numbers of multivariate analysis tools that allow for more extensive use of data. Fourier transformed infrared spectroscopy coupled with classification and prediction models such as partial least square (PLS) and PLS-DA (discriminant analysis) allows the rapid identification of oil type and characteristics. By searching for the maximum covariance with the variables of interest, PLS allows the visualization of relations between samples and variables. The framework of this study is based on two main steps: The first is classification of oil and the second is prediction of physicochemical properties. Separated into four main categories: crude, light fuel, heavy fuel, and lubricant, spectrums of 92 oils were calibrated to predict the oil type and physicochemical properties of 26 oils. The predictability and robustness of the model was further validated using weathered oil. The classification and prediction models have accuracy of >95%. Most of the PLS models have root mean square error of calibration and prediction ranging from 0.10–3.07 and 0.3–2.8, respectively. External cross validations using weathered oils showed high prediction accuracy (relative standard deviations <5%). By increasing the number of oil type and samples, this approach is a promising method and can be included as part of the oil spill fingerprinting protocols.

Application of the SOSim v2 Model to Spills of Sunken Oil in Rivers

Sunken oil transport processes in rivers differ from those in oceans, and currently available models may not be generally applicable to sunken oil in river settings. The open-source Subsurface Oil Simulator (SOSim) model has been expanded to handle spills of sunken oil in navigable rivers, utilizing Bayesian inference to integrate field concentration data with bathymetric data to predict the location and movement of sunken oil. A novel prior likelihood function incorporates bathymetric input, with sampling grid and default parameters adapted appropriately for rivers. SOSim v2 was demonstrated versus field observations taken following the M/T (Motor Tanker) Athos I oil spill. The model was also modified to operate in 1-D, to assess the longitudinal distribution of sunken oil in a non-navigable river using available poling data collected following the Enbridge Kalamazoo River oil spill in 2010. Results of both case studies were consistent with observed data and local bathymetry in 2-D and 1-D, and the model is suggested as a complement to deterministic models for oil spill emergency response in rivers.