Modelling of PM10 Pollution in Karatay District of Konya with Artificial Neural Networks

Year 2017, Volume: 12 Issue: 3, 256 - 263, 30.09.2017

Yasin Akın Ayturan , Ali Öztürk Zeynep Cansu Ayturan

Abstract

Air pollution is one of the most significant issues of human being faced
nowadays because it can create adverse effects on both health of human and
other livings. There are several air pollutants which are considered as
dangerous such as sulphur dioxide (SO₂), nitrous oxide (NO_x),
carbon monoxide (CO), volatile organic compounds (VOC) and particulate matter
(PM). Particulate matter is one the most significant air pollutants because it
may create respiratory, cardiological and pulmonary problems by inhalation by
nose on humans. Also, heavy metals and hydrocarbons may be adsorbed on PM
surface, so it is considered as carcinogenic by World Health Organization
(WHO). When all these negative effects of PM are taken into consideration, it
is important that PM future concentration should be determined for taking
precautions. PM is classified according to the diameter of the particles and PM₁₀
is described as particulates which has diameter smaller than 10 micrometres. In
this study, PM₁₀ pollution was predicted with artificial neural
network (ANN) for Karatay district of Konya. ANN includes interconnected
structures that can make parallel computations. Several meteorological factors
and air pollutant concentrations was provided by database of Ministry of
Environment and Urbanisation belonging to autumn period of 2016 such as SO₂
concentration, NO concentration, NO_x concentration, NO₂
concentration, CO concentration, O₃ concentration, wind speed,
temperature, relative humidity, air pressure, wind direction and previous day’s
PM₁₀ concentration. These parameters were used in the model as input
parameters and PM₁₀ concentration for one day later was used as an
output parameter. Prediction performance of the obtained model was very
promising when the similar studies are examined.

Keywords

Artificial neural network, modelling, air pollution, PM10, factor

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