Toz fırtınaları, rüzgârın yönü ve hızı ile ilgili olarak dünyanın birçok ülkesine yayılan ve yılda birkaç kez meydana gelen yaygın olaylardır. Özellikle partikül madde (PM), bu fırtınalarla yayılan ana kirletici maddedir. Toz fırtınaları nedeniyle, toz fırtınası geçişleri yolunda bulunan alanlarda PM konsantrasyonları hızla artmaktadır. Bu çalışmada, istatistiksel değerlendirme Konya'nın Selçuklu ilçesinde ölçülen PM verileri ile yakınlarda bulunan Çevre ve Şehircilik Bakanlığına bağlı hava kalitesi izleme istasyonundan sağlanan meteorolojik ve kirlilik verilerine göre yapılmıştır. Her iki veri setine de Pearson korelasyon testi uygulanmış veriler arasında önemli bir ilişki tespit edilmiştir. Ayrıca, PM2.5 ve PM10 verilerine ayrı ayrı çoklu doğrusal regresyon uygulanmıştır. Regresyon analizinin düzeltilmiş R2'si PM2.5 ve PM10 için sırasıyla 0.573 ve 0.559 olarak bulunmuştur ve bu da PM ile meteorolojik değişkenler arasındaki ilişkinin neredeyse yarısını açıklamaktadır. Hava sıcaklığının, PM kirliliği üzerinde en yüksek pozitif etkiye sahip olduğu bulunmuştur. Son olarak, temel bileşen analizi (PCA) hem ölçülen hem de sağlanan verilere uygulanmış ve 4 farklı ana bileşen tespit edilmiştir. Ölçülen PM2.5 ve PM10, hava sıcaklığı ve bağıl nem aynı bileşen grubunda kümelenmiştir.
Partikül madde toz fırtınaları istatistiksel analiz korelasyon testi Çoklu Doğrusal Regresyon PCA
Dust storms are widespread events that occur several times a year and spread over many countries of the world relating the wind direction and speed. Especially particulate matter (PM) is the main pollutant spread over by these storms. Because of the dust storms, PM concentrations increase rapidly in the areas found on the way of dust storm passes In this study, statistical evaluation was made accordingly the PM data measured with personal measurement device in Selçuklu District of Konya and the meteorological and the air pollution data provided from air quality monitoring station, which is affiliated by the Ministry of Environment and Urbanization, located nearby. Pearson correlation test has been applied to both data sets and a significant relationship has been detected between the measured and provided data. Moreover, multiple linear regression was applied to the data for PM2.5 and PM10 separately. Adjusted R2 of the analysis has been found as 0.573 and 0.559 respectively for PM2.5 and PM10 which explains almost half of the relationship between PM and meteorological variables. The highest positive effect on PM pollution was determined as air temperature. Finally, principal component analysis (PCA) was applied to both data and 4 different principal components were detected. Measured PM2.5 and PM10, air temperature, and relative humidity were clustered at the same component group.
Particulate matter dust storms statistical analysis correlation test multiple linear regression PCA
Primary Language | English |
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Subjects | Environmental Engineering |
Journal Section | Research Articles |
Authors | |
Publication Date | August 31, 2021 |
Submission Date | May 22, 2021 |
Acceptance Date | August 5, 2021 |
Published in Issue | Year 2021 Volume: 26 Issue: 2 |
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