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[en] Highlights: • A spatial optimization model is built for tactical oil spill response efforts. • The developed framework is spatially and temporally explicit. • We analyze three oil spill scenarios to test the response model. • The results enhance geospatial intelligence for scenario planning and response. - Abstract: Although anthropogenic oil spills vary in size, duration and severity, their broad impacts on complex social, economic and ecological systems can be significant. Questions pertaining to the operational challenges associated with the tactical allocation of human resources, cleanup equipment and supplies to areas impacted by a large spill are particularly salient when developing mitigation strategies for extreme oiling events. The purpose of this paper is to illustrate the application of advanced oil spill modeling techniques in combination with a developed mathematical model to spatially optimize the allocation of response crews and equipment for cleaning up an offshore oil spill. The results suggest that the detailed simulations and optimization model are a good first step in allowing both communities and emergency responders to proactively plan for extreme oiling events and develop response strategies that minimize the impacts of spills.
[en] Highlights: • Real time oil spill monitoring system integrating heterogeneous data sources. • A Marine Information System based on an Environmental Decision Support System. • Proactive system able to support the monitoring and usage of available resources. • Maritime geo-referenced risk maps based on data gathered from different sources. • Integrated MIS allowing for data correlation and evaluation among different sources. - Abstract: The ability to remotely detect and monitor oil spills is becoming increasingly important due to the high demand of oil-based products. Indeed, shipping routes are becoming very crowded and the likelihood of oil slick occurrence is increasing. In this frame, a fully integrated remote sensing system can be a valuable monitoring tool. We propose an integrated and interoperable system able to monitor ship traffic and marine operators, using sensing capabilities from a variety of electronic sensors, along with geo-positioning tools, and through a communication infrastructure. Our system is capable of transferring heterogeneous data, freely and seamlessly, between different elements of the information system (and their users) in a consistent and usable form. The system also integrates a collection of decision support services providing proactive functionalities. Such services demonstrate the potentiality of the system in facilitating dynamic links among different data, models and actors, as indicated by the performed field tests.
[en] Highlights: • Simple grounding damage assessment model requiring minimal number of input parameters • Closed form equations for grounding resistance and damage opening size • Ice resistance in grounding • Coupled damage assessment and time-dependent oil spill simulation model • Assessment of sensitivity and uncertainties of main input parameters of grounding simulations - Abstract: The risk of oil spills is an ongoing societal concern. Whereas several decision support systems exist for predicting the fate and drift of spilled oil, there is a lack of accurate models for assessing the amount of oil spilled and its temporal evolution. In order to close this gap, this paper presents an online platform for the fast assessment of tanker grounding accidents in terms of structural damage and time-dependent amount of spilled cargo oil. The simulation platform consists of the definition of accidental scenarios; the assessment of the grounding damage and the prediction of the time-dependent oil spill size. The performance of this integrated online simulation environment is exemplified through illustrative case studies representing two plausible accidental grounding scenarios in the Gulf of Finland: one resulting in oil spill of about 50 t, while in the other the inner hull remained intact and no spill occurred.
[en] Highlights: • A bioenergetics model, supported experimentally, simulates oil exposure in birds. • Live oiled cormorants had increased in surface temperatures and food consumption. • Modeled increases in energetic demand were consistent with experimental values. • Mechanistic models can make predictions in a wide range of environmental conditions. • This approach allows rapid quantitative assessments of exposure to oil pollution. - Abstract: To fully understand the impact of oil exposure, it is important to understand sublethal effects like how increased thermoregulatory costs may affect survival and reproduction. However, it is difficult and time-consuming to measure these effects in wild animals. We present a novel use of a bioenergetics model, Niche Mapper™, to estimate thermoregulatory impacts of oiling, using data from captive Double-crested Cormorants (Phalacrocorax auritus) experimentally exposed to oil. Oiled cormorants had significant increases in surface body temperatures following exposure. Niche Mapper accurately predicted surface temperatures and metabolic rates for unoiled and oiled cormorants and predicted 13–18% increased daily energetic demands due to increased thermoregulatory costs of oiling, consistent with increased food consumption observed in experimentally oiled cormorants. We show that Niche Mapper can provide valuable insight into sublethal oiling effects by quantifying the extent to which thermoregulatory costs divert energy resources away from important life processes like maintenance, reproduction and migration.
[en] Highlights: • Existing oil spill recovery capacities for Korea consider only causal factors. • A risk-based approach is presented that includes environmental/economic factors. • Expert analysis is combined with Analytic Hierarchy Process (AHP) weightings. • Excessive regional capacities were redeployed to other regions. • Simulated incident response achieved recovery targets and more balanced deployment. - Abstract: This study presents a regional oil spill risk assessment and capacities for marine oil spill response in Korea. The risk assessment of oil spill is carried out using both causal factors and environmental/economic factors. The weight of each parameter is calculated using the Analytic Hierarchy Process (AHP). Final regional risk degrees of oil spill are estimated by combining the degree and weight of each existing parameter. From these estimated risk levels, oil recovery capacities were determined with reference to the recovery target of 7500 kl specified in existing standards. The estimates were deemed feasible, and provided a more balanced distribution of resources than existing capacities set according to current standards.
[en] Highlights: • Risk assessment was performed in the Chinese Bohai Sea by using an oil spill model. • Five high-risk zones derived from the risk index of different seasons are proposed. • Detailed suggestions are presented in terms of prevention and readiness for high-risk zones. - Abstract: Oil spill accidents occur with increasing frequency in the Chinese Bohai Sea because of the presence of extensive number of oil platforms and oil pipelines the Chinese Bohai region. An appropriate risk assessment for oil spill prevention and readiness is necessary. Risk assessment for the entire Chinese Bohai Sea based on a quantitative method is proposed. We created a hypothetical simulation of oil spill trajectories based on an oil spill model for 28 oil platforms in the Chinese Bohai region in 2010. Then, we mapped a risk index in the study areas based on a combination of oil spill trajectories and shoreline susceptibility data. Five high-risk areas were identified in the entire Chinese Bohai Sea. Detailed suggestions for prevention and readiness are described here. These results can help in developing a risk assessment of oil spills in the Chinese Bohai Sea and serve as a useful analytic tool for slick-related emergencies.
[en] Highlights: • Oil exploration and production is moving increasingly to deeper waters. • The Faroe-Shetland Channel (FSC) is a complex area in terms of metocean conditions. • Such complexity is a challenge for deepwater oil spill modelling. • We review the state of knowledge relevant to such modelling in the FSC. - Abstract: As oil reserves in established basins become depleted, exploration and production moves towards relatively unexploited areas, such as deep waters off the continental shelf. The Faroe-Shetland Channel (FSC, NE Atlantic) and adjacent areas have been subject to increased focus by the oil industry. In addition to extreme depths, metocean conditions in this region characterise an environment with high waves and strong winds, strong currents, complex circulation patterns, sharp density gradients, and large small- and mesoscale variability. These conditions pose operational challenges to oil spill response and question the suitability of current oil spill modelling frameworks (oil spill models and their forcing data) to adequately simulate the behaviour of a potential oil spill in the area. This article reviews the state of knowledge relevant to deepwater oil spill modelling for the FSC area and identifies knowledge gaps and research priorities. Our analysis should be relevant to other areas of complex oceanography.
[en] Highlights: • We perform simulations of the toxic effects of oil spills on Northeast Arctic cod. • Spill scenarios result in reduced survival for pelagic stages of cod between 0 and 43%. • The reproductive health of the adult population is maintained in all scenarios. • Moderate action by fisheries managers can mitigate impacts on the fisheries. - Abstract: We simulate oil spills of 1500 and 4500 m3/day lasting 14, 45, and 90 days in the spawning grounds of the commercial fish species, Northeast Arctic cod. Modeling the life history of individual fish eggs and larvae, we predict deviations from the historical pattern of recruitment to the adult population due to toxic oil exposures. Reductions in survival for pelagic stages of cod were 0–10%, up to a maximum of 43%. These reductions resulted in a decrease in adult cod biomass of < 3% for most scenarios, up to a maximum of 12%. In all simulations, the adult population remained at full reproductive potential with a sufficient number of juveniles surviving to replenish the population. The diverse age distribution helps protect the adult cod population from reductions in a single year's recruitment after a major oil spill. These results provide insights to assist in managing oil spill impacts on fisheries.
[en] Highlights: • Marine snow increases the adverse effects of oil in benthic ecosystems. • Marine snow inhibits biodegradation of oil in marine sediment. • Severity of adverse effects of marine snow and oil depend on organismal traits. • Ecological effects of marine snow should be considered in oil spill management. - Abstract: After the Deepwater Horizon oil spill, a MOSSFA (Marine Oil Snow Sedimentation and Flocculent Accumulation) event took place, transporting an estimated 14% of total released oil to the sediment, and smothering parts of the benthic ecosystem. This microcosm study describes the effects of oiled artificial marine snow on benthic macroinvertebrates. Corophium volutator survival was reduced by 80% in oil-contaminated snow. Hydrobia ulvae survival was reduced by 40% in oil-contaminated snow, possibly due to consumption of oiled snow. Macoma balthica was sensitive to marine snow, addition of oil slightly decreased survival. This study reveals trait-dependent sensitivity to oil with or without marine snow. The main drivers for organismal response to marine snow and oil are motility, sensitivity to hypoxia and oil toxicity, and feeding habits. Adverse effects of MOSSFA events on benthos will have consequence for the benthic-pelagic habitat and food chain, and should receive more attention in oil spill management.
[en] Highlights: • A formula is presented for evaluating the prediction performance of oil spill models. • Genetic algorithm adoption improves the accuracy of oil spill model simulations. • Optimal parameters and multi-objective optimisation improve prediction accuracy. - Abstract: 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.