2020 Mayıs Ayındaki Kum Fırtınası Sırasında Konya Selçuklu İlçesinde Ölçülen PM Konsantrasyonlarının İstatistiksel Analizi ve Değerlendirilmesi

Öz

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.

Anahtar Kelimeler

• Partikül madde
• toz fırtınaları
• istatistiksel analiz
• korelasyon testi
• Çoklu Doğrusal Regresyon
• PCA

STATISTICAL ANALYSIS AND EVALUATION OF PM CONCENTRATIONS DURING THE DUST STORMS AT MAY 2020 FOR SELÇUKLU DISTRICT OF KONYA CITY, TURKEY

Öz

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.

Anahtar Kelimeler

• Particulate matter
• dust storms
• statistical analysis
• correlation test
• multiple linear regression
• PCA

Kaynakça

1. Abdullah, S., Ismail., M., Ahmed, A.N. (2018) Identification of Air Pollution Potential Sources Through Principal Component Analysis (PCA), International Journal of Civil Engineering and Technology (IJCIET), 9(7), 1435-1442.
2. Anonymous-1, (2020) https://tr.m.wikipedia.org/wiki/Dosya:Konya_in_Turkey.svg, Accessed Date: 25.07.2020.
3. Anonymous-2, (2020) https://gadm.org/maps/TUR/konya/selcuklu.html, Accessed Date: 25.07.2020.
4. Anonymous-3, (2020) https://libguides.library.kent.edu/SPSS/PearsonCorr, Accessed Date: 18.12.2020, Subject: SPSS Tutorials: Pearson Correlation.
5. Anonymous-4 (2020) https://www.statisticshowto.com/varimax-rotation-definition/#:~:text=Varimax%20rotation%20(also%20called%20Kaiser,factor%20loadings%20for%20the%20rest Accessed Date: 08.01.2021, Subject: Varimax Rotation: Definition.
6. Azid, A., Juahir, H., Toriman, M.E., Kamarudin, M.K.A., Saudi, A.S.M., Hasnam, C.N.C., Aziz, N.A.A., Azaman, F., Latif, M.T., Zainuddin, S.F.M., Osman, M.R., Yamin, M. (2014) Prediction of the Level of Air Pollution Using Principal Component Analysis and Artificial Neural Network Techniques: a Case Study in Malaysia, Water Air Soil Pollut, 225,2063. DOI 10.1007/s11270-014-2063-1
7. Boubel, W.R., Fox, D.L., Turner, D.B., Stern, A.C. (1994) Fundamentals of Air Pollution. Third Edition. Elsevier USA, 3-153.
8. Brunekreef, B., Forsberg, B. (2005) Epidemiological evidence of effects of coarse airborne particles on health, Eur Respiratory J, 26,309–18.

9. Çelik, M.B., Kadı, İ. (2007) The Relation Between Meteorological Factors and Pollutants Concentrations in Karabük City, G.U. Journal of Science, 20(4): 87-95.
10. EPA, (2020) Pollution. https://www.epa.gov/pm-pollution, Accessed Date: 10.01.2021, Subject: Particulate Matter (PM).
11. EU, (2020) Air Quality Standards. https://ec.europa.eu/environment/air/quality/standards.htm, Accessed Date: 25.01.2021.
12. Fong, S.Y. Abdullah, Ismail, S.M. (2018) Forecasting of Particulate Matter (PM10) Concentration Based on Gaseous Pollutants and Meteorological Factors for Different Monsoons of Urban Coastal Area in Terengganu, Journal of Sustainability Science and Management, Special Issue Number 5, 3-17.
13. Google Maps, (2020) https://www.google.com/maps/place/Sel%C3%A7uklu%2FKonya/@38.0158124,32.4939558,13.25z/data=!4m5!3m4!1s0x14d0edf71b511581:0x35c05809f6f0a52d!8m2!3d38.0160383!4d32.4920088?hl=tr, Accessed Date: 25 July 2020.
14. Goudarzi, G., Mohammadi, M., Angali, K.A., Mohammadi, B., Soleimani, Z., Babaei, A., Neisi, A., Geravandi, S. (2013) Estimation of number of cardiovascular death, myocardial infarction and chronic obstructive pulmonary disease (COPD) from NO2 exposure using air Q model in Ahvaz City during 2009, Iran J Health Environ, 6, 91–102.
15. Graff, D.W., Cascio, W.E., Rappold, A., Zhou, H., Huang, Y-C.T, Devlin, R.B. (2009) Exposure to concentrated coarse air pollution particles causes mild cardiopulmonary effects in healthy young adults, Environmental Health Perspectives, 117, 1089–1094.
16. Hashim, N.I.M., Noor, N.M., Annas, S. (2018) Influence of meteorological factors on variations of Particulate Matter (PM10) concentration during haze episodes in Malaysia, 4th Electronic and Green Materials International Conference 2018, AIP Conf. Proc., 2045, 020103-1–020103-10; https://doi.org/10.1063/1.5080916.
17. Host, S., Larrieu, S., Pascal, L., Blanchard, M., Declercq, C., Fabre, P., Jusot. J-F., Chardon, B., Le Tertre, A., Wagner, V., Prouvost, H., Lefranc, A. (2008) Short-term associations between fine and coarse particles and hospital admissions for cardiorespiratory diseases in six French cities, Occupational and Environmental Medicine, 5, 544-551.
18. IBM Knowledge Center, (2020) https://www.ibm.com/support/knowledgecenter/SSLVMB_26.0.0/statistics_casestudies_project_ddita/spss/tutoria ls/fac_telco_kmo_01.html, Accessed Date: 05.01.2021, Subject: KMO and Bartlett's Test.
19. Jaafari, J., Naddafi, K., Yunesian, M., Nabizadeh, R., Hassanvand, M.S., Ghozikali, M.G., Nazmara, S., Shamsollahi, H.R., Yaghmaeian, K. (2018) Study of PM10, PM2.5, and PM1 levels in during dust storms and local air pollution events in urban and rural sites in Tehran, Human and Ecological Risk Assessment: An International Journal, 24(2), 482-493. DOI: 10.1080/10807039.2017.1389608
20. Karakaş, B. (2015) Assessment of Particulate Matter (PM10, PM2.5 and PM1) Concentrations in Indoor and Outdoor Environments., Master of Science Thesis, Hacettepe University, Ankara Turkey.
21. Khan, Md.F., Latif, M.T., Juneng, L. Amil, N. Nadzir, M.S.M., Hoque, .M.S. (2015) Physicochemical factors and sources of particulate matter at residential urban environment in Kuala Lumpur, Journal of the Air & Waste Management Association,65:8, 958-969, DOI: 10.1080/10962247.2015.1042094.
22. Linares, C., Tobías, A., Díaz, J. (2010) Is there new scientific evidence to justify reconsideration of the current WHO guidelines for particulate matter during dust intrusions? Sci Total Environ, 408, 2283–4.
23. Malig, B.J., Ostro, B.D. (2009) Coarse particles and mortality: evidence from a multi-city study in California. Occup Environ Med, 66,832–9.
24. Miller, S.D., Kuciauskas, A.P., Liu, M., Ji, Q., Reid, J., Breed, D., Walker, A., Mandoos, A. (2008) Haboob dust storms of the southern Arabian Peninsula, Journal of Geophysical Research-Atmospheres, 113,1-26. 10.1029/2007JD008550.
25. Morand, C.P., Maesano, I.A. (2004) Air pollution: from sources of emissions to health effects. Breathe, 1(2), 109-119.
26. NASA, (2020) https://worldview.earthdata.nasa.gov/, Accessed Date: 15 June 2020.
27. Qiu, H., Yu, I.T-S., Tian, L., Wang, X., Tse, L.A., Tam, W., Wong, T.W. (2012) Effects of coarse particulate matter on emergency hospital admissions for respiratory diseases: a time-series analysis in Hong Kong, Environ Health Perspect., 120, 572–6.
28. Rahman, S.R.A., Ismail, S.N.S., Raml, M.F., Latif, M.T., Abidin, E.Z., Praveena, S.M. (2015) The Assessment of Ambient Air Pollution Trend in Klang Valley, Malaysia, World Environment, 5(1): 1-11, DOI: 10.5923/j.env.20150501.01.
29. Rathner, B. (2009) The correlation coefficient: Its values range between +1/−1, or do they? Journal of Targeting, Measurement and Analysis for Marketing, 17,139–142.
30. Sritong-aon, C., Thomya, J., Kertpromphan, C., Phosri, A. (2021) Estimated effects of meteorological factors and fire hotspots on ambient particulate matter in the northern region of Thailand. Air Qual Atmos Health, https://doi.org/10.1007/s11869-021-01059-x.
31. Song, Z., Wang, J., Wang, S. (2007) Quantitative classification of northeast Asian dust events, J Geophys Res: Atmos, 112, 1–8.
32. Vesilind, P.A., Morgan, S.M., Heine, L.G. (2010) Introduction to Environmental Engineering, Cengage Leraning, Stamford-USA, 415-420.
33. Wang, S., Wang, J., Zhou, Z., Shang, K. (2005) Regional characteristics of three kinds of dust storm events in China, Atmos. Environ., 39, 509–520.
34. WHO, (2018) https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health, Accessed Date: 15 01 2021, Subject: Ambient (outdoor) air pollution.
35. Zu´ska, Z., Kopci ´nska, J., Dacewicz, E., Skowera, B., Wojkowski, J., Ziernicka–Wojtaszek, A. (2019) Application of the Principal Component Analysis (PCA) Method to Assess the Impact of Meteorological Elements on Concentrations of Particulate Matter (PM10): A Case Study of the Mountain Valley (the S ˛acz Basin, Poland), Sustainability, 11, 6740, doi:10.3390/su11236740