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Browsing by Author "Perez Roa, R"

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    Air-pollution modelling in an urban area: Correlating turbulent diffusion coefficients by means of an artificial neural network approach
    (PERGAMON-ELSEVIER SCIENCE LTD, 2006) Perez Roa, R; Castro, J; Jorquera, H; Perez Correa, JR; Vesovic, V
    The vertical pollutant dispersion is quite sensitive to the eddy diffusivity, K-V. Therefore, good estimations of K-V are essential for improving the predictive performance of Eulerian dispersion models; especially in urban areas where literature based K-V correlations are not always accurate. Here, we present a methodology to obtain a more accurate, but site-specific, Kv correlation. It is based on using artificial neural networks (ANN) to find the best Kv function for a particular urban area by minimizing, in a least-squares sense, the difference between ambient measurements of carbon monoxide and dispersion simulations of this tracer species. The resulting ANN-K-V correlation is a function of three parameters namely, the stability parameter (z/L), the height within the mixing layer (z/h), and the scaled height (zf(C)/u(*))-hence the Monin-Obukhov (L), mixing (h) and Ekman (u(*)/f(C)) lengths are used to predict Kv across the atmospheric boundary layer.

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