CONICET | Buscador de Institutos y Recursos Humanos

This paper describes in detail PM10 non-traditional modeling for e-government development. In this study, ambient PM10 concentrations are predicted using meteorological variables as inputs. The relevance of the input variables to a generated Artificial Neural Network was analyzed by a leave-one-out method. The work is specially focused on the surroundings of Bahía Blanca city, its petrochemical pole and Ing. White grain port. Its accuracy was tested with time windows ranging from 2004 to 2006. This predictive model will contribute to the local observatory in order to trigger early-alert warnings.