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Analysis of Methods Used in Spill Response Planning: Trajectory Analysis Planner TAP II
Institution:1. Key Laboratory of Drinking Water Science and Technology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China;2. State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China;3. Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN 37235-1831, United States;4. School of Environment, Tsinghua University, Beijing 100084, PR China;1. Department of Biotechnology, University Institute of Engineering and Technology, Panjab University, Chandigarh 160014, India;2. Wellcome trust/DBT IA Early Career Fellow, Panjab University, Chandigarh 160014, India;1. EPHE, PSL Research University, UMR 7564, LCPME, F-54500 Vandoeuvre-lès-Nancy, France;2. Lorraine University, CNRS, UMR 7564, LCPME, F-54600 Villers-lès-Nancy, France;3. Georgia Institute of Technology, UMI Georgia Tech – CNRS 2958, F-57070 Metz, France;1. School of Aerospace Engineering, Xiamen University, Xiamen 361102, China;2. School of Life and Environmental Sciences, Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology, Guilin, Guangxi, 541004, China;3. State Key Laboratory of Marine Environmental Science, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China;1. Human and Environmental Toxicology, University of Science and Technology, Daejeon 34113, Korea;2. Department of Predictive Toxicology, Korea Institute of Toxicology, Daejeon 34114, Korea;1. Department of Occupational Safety and Health, Faculty of Medical Science, Tarbiat Modares University, Tehran, Iran;2. Faculty of Chemical Engineering, Iran University of Science and Technology, Tehran, Iran
Abstract:Long records of geophysical forcing have been used in numerous studies to estimate a statistical distribution of oil spill scenarios. The resulting set of spill scenarios is then used as a basis for planning a robust response capability that should be able to handle all likely real spills. For model developers to be able to support these expectations there are a number of criteria that must be satisfied: (1) Models must develop and retain the data necessary to answer key response questions; (2) developers must understand the limitations in resolution imposed by the specific algorithms they use; and (3) the cardinality of the long geophysical records (with respect to modeled spill behavior) should be determined and the final collection of spill scenarios must span this set. This paper considers these specific constraints and discusses methods that can be used to quantify some aspects of the uncertainty in the output.
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