Prediction of atmospheric dispersion of pollutants in an airport environment |
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| Affiliation: | 1. Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA;2. School of Mechanical Engineering, Tongji University, Shanghai, PR China;3. Department of Sustainable Biomaterials, Virginia Tech, Blacksburg, VA, USA;1. Département de Géographie, Faculté des Sciences Humaines, Université Saint-Joseph, Liban;2. Institut de Chimie et Procédé pour l''Energie, l''Environnement et la Santé (ICPEES, UMR 7515 CNRS/Unistra), Equipe de Physico-chimie de l''atmosphère, 67087, Strasbourg, France;3. Unité de Recherche Environnement, Génomique et Protéomique (UR-EGP), Faculté des Sciences, Université Saint-Joseph, Liban;1. Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA;2. Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA;3. U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, NC, USA;4. Aerodyne Research, Inc., Billerica, MA, USA;1. Nuclear Science and Technology Development Center, National Tsing Hua University, Hsinchu 30013, Taiwan ROC;2. Radiation Monitoring Center, Atomic Energy Council, Kaohsiung 83347, Taiwan ROC;3. Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital, Taoyuan, Taiwan ROC |
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| Abstract: | In this article we discuss the development of a methodology to predict atmospheric turbulent dispersion of pollutants generated from air traffic in an airport. It is based on the Lagrangian stochastic model (LSM), developed by Das and Durbin [2005. A Lagrangian stochastic model for dispersion in stratified turbulence, Physics of Fluids 17, 025109]. The approach is via the backward trajectory formulation of the model. The sources and receptors in an airport type problem are modeled as spheres and procedures have been derived for concentration calculation by both forward and backward trajectory methods. Some tests are performed to highlight certain features of the method. The turbulence statistics that are required as input are provided in terms of similarity profiles. The airport domain is partitioned to make the required search algorithms efficient. Pollutant concentration profiles are calculated over a range of meteorological data. |
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