Browse

Due to limitations in the spatial and temporal coverage of air quality measurements, monitoring data normally are not sufficient as the sole basis for demonstrating the adequacy of emission limits for existing sources. Also, the impacts of new sources that do not yet exist can only be determined through modeling. Dispersion models are used in all the basic applications such as the determination of the effect of a pollutant source on environment, calculation of ground level concentrations and regulatory control of ...

Modelling of air pollution parameters, according to the meteorological data is a necessary for preventing the repetition of same problems. During recent years, neural network-based models have been shown to be powerful tools in the simulation of variations in air quality and provide better alternative to statistical models because of their computational efficiency and generalization ability. In this study, prediction of future daily SO2 concentrations in Konya (Turkey) using MLP (Multilayer Perceptron) artificial ...