ESTIMATION OF AIR POLLUTANT CONCENTRATIONS FROM METEOROLOGICAL PARAMETERS USING ARTIFICIAL NEURAL NETWORK
Hamdy K. Elminir - Hala Abdel-Galil
The lack of environmental data is a common feature of many developing countries.
This is fact in Egypt, where air quality is beginning to be systematically
monitored in some places of the country. To overcome these problems, the need
for accurate estimates of air quality levels becomes evermore important. To
achieve such prediction tasks, the use of artificial neural network (ANN) is
regarded as a cost effective technique superior to traditional statistical
methods. In this paper, ANN trained with a back propagation algorithm is used to
estimate the well known pollutants, from readily observable local meteorological
data. The results indicate that the ANN model predicted air pollutant
concentrations with good accuracy of approximately 96 %.
Keywords: air quality, pollutants, artificial neural network