Modelling of Atmospheric SO2 Pollution in Seydişehir Town by Artificial Neural Networks

Air pollution has become a major environmental problem since last century because of the effects of fast population growth and industrial developments. Sulphur dioxide is considered as one of the major and most common air pollutant with using fossil fuels causing severe health problems such as disrupting tissues and mucous membranes of the eyes, disturbing nose and throat because of the irritating toxic odour, and affecting badly to upper part of respiratory system and bronchi. Seydişehir town of Konya was selected as working area for this study because heavy industrial activities are very wide in many fields such as mining and manufacturing industry. Also, usage of fossil fuels for heating system in winter period is other important atmospheric pollutants source. Eti Aluminium facility is the biggest industrial unite for SO2 pollution source in Seydişehir town. In this study, SO2 pollution in Seydişehir town was modelled with Artificial Neural Networks (ANN) which uses characteristics of biological neurons and capable of solving highly complex problems constructing parallel computations. Meteorological factors and previous day’s SO2 concentrations were integrated to model as input parameters and next day’s SO2 concentration was tried to be predicted. Two seasons were selected for model development namely winter and summer. Prediction performances of develop models are 67% for winter season and 81% for summer season. These values are compatible compared with previous studies using ANN modelling and can be improved with larger data sets.

Keywords:

SO2, ANN, Air Pollution, Modelling Prediction,

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