Study of atmospheric ozone formation by means of a neural network-based model.
The occurrence of high ozone levels in the atmosphere of urban areas has become a serious pollution problem in a number of large cities in the world. Although mathematical models have been proposed for predicting ozone concentrations as a function of a number of gas components, sometimes there are uncertainties due to lack of the combined effects of meteorological factors and the complex chemical reaction system involved. The application of neural network models, based on measured values of air pollutants and meteorological factors at different locations within the São Paulo Metropolitan Area, combine chemical and meteorological information. This has shown to be a promising tool for predicting ozone concentration. Simulations carried out with the model indicate the sensitivity of ozone in relation to different air pollution and weather conditions. Predictions using this model have shown good agreement with measured values of ozone concentrations.
Guardani
R
R
University of São Paulo, Chemical Engineering Department, Brazil. guardani@usp.br
Nascimento
C A
CA
Guardani
M L
ML
Martins
M H
MH
Romano
J
J
D000465:Algorithms; D001272:Atmosphere / Q000737:chemistry*; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D010126:Ozone / Q000737:chemistry*
D010126:Ozone