Author(s)

B. Drozdowicz, S.J. Benz, A.S.M. Santa Cruz & N.J. Scenna

Abstract

A neural network based model for estimating (hourly mean concentrations) carbon monoxide in the urban area of Rosario City, in Santa Fe, Argentine is presented. The data series of carbon monoxide and emission inventory is also a result of this work (up to now no data were reported for Rosario). It is based on a typical neural network architecture, e.g. Lawrence [5]. Several inputs like mean hourly traffic flux -segregating different type of vehicles-, wind speed and dire

Keywords