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• W2016147604 abstract "Back-trajectory techniques are extensively used to identify the most probable source locations, starting from the known pollutants concentration data at some receptor sites. In this paper, we review the trajectory statistical methods (TSMs) that are most used in literature for source identification, which are essentially based on the concept of residence time (RT), and we introduce a novel statistical method. To validate this method, artificial receptor data at two receptor sites are derived from numerical simulations with a given aerial source, using the Lagrangian dispersion model (LSM) FLEXPART in forward mode. Then the RTs are computed using again the model FLEXPART, but in backward mode. Then, the new statistical methodology, which is based on the use of peak concentration events, is applied to reconstruct the spatial distribution of emission sources. Our approach requires simulation times shorter than those required in other methods and could overcome the problem of ghost sources." @default.
• W2016147604 created "2016-06-24" @default.
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• W2016147604 date "2014-01-01" @default.
• W2016147604 modified "2023-09-24" @default.
• W2016147604 title "Source identification by a statistical analysis of backward trajectories based on peak pollution events" @default.
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• W2016147604 doi "https://doi.org/10.1504/ijep.2014.065909" @default.
• W2016147604 hasPublicationYear "2014" @default.
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