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 (NOx),
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, NOx 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.
Artificial neural network modelling air pollution PM10 factor
Birincil Dil | İngilizce |
---|---|
Bölüm | Makaleler |
Yazarlar | |
Yayımlanma Tarihi | 30 Eylül 2017 |
Kabul Tarihi | 29 Eylül 2017 |
Yayımlandığı Sayı | Yıl 2017 Cilt: 12 Sayı: 3 |
“Journal of International Environmental Application and Science”