Modeling of Ozone Interactions with Various Air Pollutants and Meteorological Factors Using Jaya and Teaching-Learning Based Optimization (TLBO) Algorithms

Abstract

Ozone (O3), nitrogen oxides (NOx) and carbon monoxide (CO) concentrations and some meteorological parameters measured hourly have been analyzed to examine the interaction patters between O3 and NOx, CO, air temperature, wind speed, relative humidity, and air pressure by taking into account the diurnal variations of them at urban site (Akçaabat ) in Trabzon. Variations of O3 levels have been modeled via Jaya and Teaching-Learning Based Optimization (TLBO) algorithms considering the effects of certain parameters (NOx and CO concentration, air temperature, wind speed, relative humidity, and air pressure) called as the independent variables. The accuracy of Jaya and TLBO methods has been determined and these methods have been carried out with four different functions: quadratic, exponential, linear and power. Some statistical indices have been applied to evaluate the performance of these models. In conclusion, it is shown that Jaya and TLBO algorithms can be used in the optimization of the regression function coefficients in modelling some air pollutants interactions and the best-fit equation for each parameter is obtained from the quadratic function.

Keywords

• Air pollution
• Ozone concentration
• Modeling

Jaya ve Öğretme-Öğrenme Tabanlı Optimizasyon Algoritmalarını Kullanarak Meteorolojik Faktörler ve Çeşitli Hava Kirleticileri ile Ozon Etkileşimlerinin Modellenmesi

Abstract

Ozon (O3), azot oksitler (NOx) ve karbon monoksit (CO) konsantrasyonları ve saatlik olarak ölçülen bazı meteorolojik parametreler, O3 ile NOx, CO, hava sıcaklığı, rüzgar hızı, bağıl nem ve hava basıncı arasındaki etkileşim eğilimini incelemek için, onların Trabzon'daki kentsel alanda (Akçaabat) günlük değişimlerini dikkate alarak analiz edildi. Bağımsız değişkenler olarak adlandırılan belirli parametrelerin (NOx ve CO konsantrasyonu, hava sıcaklığı, rüzgâr hızı, bağıl nem ve hava basıncı) etkilerini dikkate alarak O3 seviyelerinin değişimleri Jaya ve Öğretme-Öğrenme Tabanlı Optimizasyon (TLBO) algoritmaları ile modellenmiştir. Jaya ve TLBO yöntemlerinin doğruluğu belirlenmiş ve bu yöntemler ikinci dereceden, üstel, doğrusal ve güç olmak üzere dört farklı fonksiyona uygulanmıştır. Bu modellerin başarımını test etmek için bazı istatistiksel belirteçler (ortalama karesel hata, ortalama karesel hatanın karekökü, ortalama mutlak hata, ortalama mutlak yüzde hata ve belirleme katsayısı) kullanılmıştır. Sonuç olarak, Jaya ve TLBO algoritmalarının, bazı hava kirletici etkileşimlerinin modellenmesinde regresyon fonksiyonu katsayılarının optimizasyonunda kullanılabileceği ve her parametre için en uygun denklemin ikinci derece fonksiyonundan elde edildiği görülmüştür.

Keywords

• Hava Kirliliği
• Ozon konsantrasyonu
• Modelleme

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