2010
DOI: 10.1007/s10546-010-9501-4
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Modelling the Concentration Distributions of Aerosol Puffs Using Artificial Neural Networks

Abstract: A neural network model was developed to predict the short-term (<150 s) concentration distributions of aerosols released from point sources over very short time periods (approximately 2 s). The model was based on data from field experiments covering a wide range of meteorological conditions. The study focused on relative dispersion about the puff centroid, with puff/cloud meander and large-scale gusts not being considered. The artificial neural network (ANN) model included explicitly a number of meteorological… Show more

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Cited by 6 publications
(11 citation statements)
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“…Cao et al [6] applied ANN in prediction of short-term concentration distributions of aerosols released from point sources. He concluded that the performance of the neural network model was comparable or better than predictions from two Gaussian-based puff models.…”
Section: Contextualization and Problem Descriptionmentioning
confidence: 99%
“…Cao et al [6] applied ANN in prediction of short-term concentration distributions of aerosols released from point sources. He concluded that the performance of the neural network model was comparable or better than predictions from two Gaussian-based puff models.…”
Section: Contextualization and Problem Descriptionmentioning
confidence: 99%
“…The HYSPLIT model, developed by the Air Resources Laboratory, NOAA, 6 is a complete system designed to support a wide range of simulations related to regional or long-range transport and dispersion of airborne particles (Martet et al, 2009). It is possible to compute simple trajectories for complex dispersion and deposition simulations using either puff or particle approaches within a Lagrangian framework (Cao et al, 2010;De Vito et al, 2009). In this work, HYSPLIT will be used to get backward/forward trajectories by tracking air masses backward/forward in time.…”
Section: Hysplit -An Air-modelling Programmementioning
confidence: 99%
“…The data used for ANN and multiple non-linear regression models of dispersion coefficients were the same as those we used for the direct ANN modelling of concentration dispersion (Cao et al 2010). Briefly, data were collected during week-long trials conducted at Valcartier, Quebec, in all four seasons, on a 2 km 2 level plain.…”
Section: Field Experiments and Data Collectionmentioning
confidence: 99%
“…The choice of the release location depended on the wind direction at the time. Details of the meteorological parameters measured, and the instrumentation used, can be found in Cao et al (2010).…”
Section: Field Experiments and Data Collectionmentioning
confidence: 99%
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