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

Year 2016, Volume: 11 Issue: 1, 1 - 7, 30.03.2016

Z. Cansu Ozturk

Abstract

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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