Ozone Forecasting In The Urban Area Of Seville
Using Artificial Neural Network Technology
Author(s)
G. Reyes & V.J. Cortes
Abstract
In this paper a short-term ambient ozone model based on artificial neural
networks is presented. The method has been successfully applied in the city of
Seville (Spain) to forecast ozone emission concentration typically one day in
advance. The applied methodology is based on the following steps: l.The
development of an exhaustive measurement campaign in order to evaluate ozone
pollution in the city during 1999 summer, autumn and winter (partially)
providing a consistent data series of ozone and meteorological variables. 2. A
screening of the most relevant variables affecting ozone concentration to obtain
accurate forecasting capabilities based on a reduced number of easy-to-measure
parameters: traffic, meteorology and features of the area (street width, building
height, etc
Keywords
Related Book
Other papers in this volume
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