2 resultados para Transport inverse du cholestérol

em Greenwich Academic Literature Archive - UK


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The ATTMA "Aerosol Transport in the Trans-Manche Atmosphere" project investigates the transportation and dispersion of air pollutants across the English Channel, in collaboration with local authorities and other Universities in Southern England and Northern France. The research is concerned with both forward and inverse (receptor based) tracking. Two alternative dispersion simulation methods are used: (a) Lagrangian Particle Dispersion (LPD) models, (b) Eulerian Finite Volume type models. This paper is concerned with part (a), the simulations based on LPD models. Two widely applied LPD models are used and compared. Since in many observed episodes the source of pollution is traced outside the region of interest, long range, trans-continental transport is also investigated.

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The Sahara desert is a significant source of particulate pollution not only to the Mediterranean region, but also to the Atlantic and beyond. In this paper, PM 10 exceedences recorded in the UK and the island of Crete are studied and their source investigated, using Lagrangian Particle Dispersion (LPD) methods. Forward and inverse simulations identify Saharan dust storms as the primary source of these episodes. The methodology used allows comparison between this primary source and other possible candidates, for example large forest fires or volcanic eruptions. Two LPD models are used in the simulations, namely the open source code FLEXPART and the proprietary code HYSPLIT. Driven by the same meteorological fields (the ECMWF MARS archive and the PSU/NCAR Mesoscale model, known as MM5) the codes produce similar, but not identical predictions. This inter-model comparison enables a critical assessment of the physical modelling assumptions employed in each code, plus the influence of boundary conditions and solution grid density. The outputs, in the form of particle concentrations evolving in time, are compared against satellite images and receptor data from multiple ground-based sites. Quantitative comparisons are good, especially in predicting the time of arrival of the dust plume in a particular location.