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Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices

Yıl 2022, Cilt: 8 Sayı: 2, 383 - 395, 30.07.2022

İsmet YENER Kazım Onur DEMİRARSLAN

https://doi.org/10.21324/dacd.1081167
Cited By: 1

Öz

Air pollution due to anthropogenic activities is currently one of the most important problems faced worldwide. This study aimed to determine the associations between air quality and spatial, meteorological, and anthropogenic factors while evaluating air quality using the air stress index (ASI) and the daily air quality (DAQx) scale. The annual mean levels of CO, NOx, O3, PM 2.5, PM10 and SO2 in the region were 718.6, 39.5, 44.4, 25.5, 51.3, and 9.9 μg/m3, respectively. While anthropogenic variables mostly affected NOx (r=0.56 to 0.64) and O3 (r=-0.34 to 0.64), meteorological (r=-0.38 to 0.45) and spatial factors (r=-0.41 to -0.65) mostly affected particulate matter (PM2.5 and PM10). CO and SO2, on the other hand, were affected by all types of variables at varying directions and rates. The mean ASI and DAQx values of 2.1 and 4.3 indicated that the air quality in the region exhibited distinct air stress and sufficient air quality, respectively. The findings and outcomes could contribute to understanding and evaluating the air quality in the region and could be used as a base for further studies.


Anahtar Kelimeler

Correlation Analysis, Air Stress Index, Daily Air Quality Index, Air Pollution

Kaynakça

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Marmara Bölgesinde Hava Kalitesini Etkileyen Faktörlerin Belirlenmesi ve Hava Kalitesi Endeksleri Kullanılarak Değerlendirilmesi

Yıl 2022, Cilt: 8 Sayı: 2, 383 - 395, 30.07.2022

İsmet YENER Kazım Onur DEMİRARSLAN

https://doi.org/10.21324/dacd.1081167
Cited By: 1

Öz

Antropojenik faaliyetlere bağlı hava kirliliği dünya çapında karşılaşılan en önemli sorunlardan biridir. Bu çalışma, bir yandan hava stres indeksi (ASI) ve günlük hava kalitesi (DAQx) ölçeğini kullanarak hava kalitesini değerlendirirken diğer yandan hava kalitesi ile mekansal, meteorolojik ve antropojenik faktörler arasındaki ilişkileri belirlemeyi amaçlamıştır. Bölgedeki yıllık ortalama CO, NOx, O3, PM2.5, PM10 ve SO2 seviyeleri sırasıyla 718.6, 39.5, 44.4, 25.5, 51.3 ve 9.9 µg/m3'tür. Antropojenik değişkenlerin en çok NOx (r=0,56 ila 0,64) ve O3 (r=-0,34 ila 0,64) kirleticilerini etkilerken, meteorolojik (r=-0,38 ila 0,45) ve mekansal faktörler ise (r=-0,41 ila -0,65) en çok partiküler madde miktarını etkilemiştir. CO ve SO2 ise her türlü değişkenden farklı oranlarda etkilenmiştir. ASI ve DAQx değerleri ortalama 2.1 ve 4.3 olarak bulunmuş ve bölgedeki hava kalitesinin sırasıyla belirgin hava stresi ve yeterli hava kalitesi sergilediğini göstermiştir. Bu çalışmanın bulgu ve sonuçları, bölgedeki hava kalitesinin daha iyi anlaşılıp değerlendirilmesine katkı sağlayabilir ve ileride yapılacak çalışmalar için bir temel oluşturabilir.

Anahtar Kelimeler

Korelasyon Analizi, Hava Stres Indeksi, Günlük Hava Kalitesi Indeksi, Hava Kirliliği

Kaynakça

  • Agac K., (2016), Meteorological Investigation of High PM10 Concentration In Istanbul Kağithane Region, Master Thesis, Istanbul Technical University, Institute of Science and Technology, Istanbul.
  • Aggarwal A., Toshniwal D., (2018), Predicting particulate matter for assessing air quality in Delhi using meteorological features, International Conference on Computational Science and Its Applications, ICCSA 2018: Computational Science and Its Applications – ICCSA 2018, Melbourne, Australia, pp.623-638.
  • Aldrin M., Half I.H., (2005), Generalised additive modelling of air pollution, traffic volume and meteorology, Atmospheric Environment, 39(11), 2145-55.
  • Altincop H., Oktay A.B., (2018), Air Pollution Forecasting with Random Forest Time Series Analysis, 2018 International Conference on Artificial Intelligence and Data Processing (IDAP), Malatya, Turkey, ss.1-5.
  • PISR, (2018), 81 provincial industry situation report. Ankara: industry. Ministry of Science of the Republic of Turkey. https://www.sanayi.gov.tr/plan-program-raporlar-ve-yayinlar/81-il-sanayi-durum-raporlari/mu0603011615, [Accessed 10 January 2022].
  • Arslan O., Akyürek Ö., (2018), Spatial modelling of air pollution from PM10 and SO2 concentrations during winter season in marmara region (2013-2014), International Journal of Environment and Geoinformatics, 5(1), 1-16.
  • Atamaleki A., Saeed M. Z., Yadolah F., Ehsan A. M., Ghasem H., Meysam F., Mahdiyeh D., (2019), Estimation of air pollutants emission (PM10, CO, SO2 and NOx) during development of the industry using AUSTAL 2000 model: A new method for sustainable development, Methods, 10(6), 1581-90.
  • Bai Y., Yong L., Xiaoxue W., Jingjing X., Chuan L., (2016), Air pollutants concentrations forecasting using back propagation neural network based on wavelet decomposition with meteorological conditions, Atmospheric pollution research, 7(3), 557-66.
  • Buchholz R.R., Paton-WalshC., David W.T.G., Kubistin D., Caldow C., Fisher J.A, Deutscher N.M., Kettlewell G., Riggenbach M., Macatangay R., (2016), Source and meteorological influences on air quality (CO, CH4 & CO2) at a Southern Hemisphere urban site, Atmospheric Environment, 126, 274-89.
  • Caf A., Koc A., Sevgi Y., (2017), Effects of Urbanization on Air Quality; Sample of Bingol City, Journal of The Institute of Science and Technology, 7(3), 231-238.
  • Çapraz Ö., Efe B., Deniz A., (2016), Study on the association between air pollution and mortality in İstanbul, 2007–2012, Atmospheric pollution research, 7(1), 147-154.
  • Chen L., Peng S., Liu J., Hou Q, (2012), Dry deposition velocity of total suspended particles and meteorological influence in four locations in Guangzhou, China, Journal of Environmental Sciences, 24(4), 632-639.
  • Chen X., Liu F., Niu Z., Mao S., Tang H., Li N., Chen G., Liu S., Lu Y., Xiang H., (2020), The association between short-term exposure to ambient air pollution and fractional exhaled nitric oxide level: A systematic review and meta-analysis of panel studies, Environmental pollution, 265(2020), 114833, doi: 10.1016/j.envpol.2020.114833.
  • Cheng N., Cheng B., Li S., Ning T. (2019), Effects of meteorology and emission reduction measures on air pollution in Beijing during heating seasons, Atmospheric Pollution Research, 10(3), 971-979.
  • Childs C., (2004), Interpolating surfaces in ArcGIS spatial analyst, ArcUser, July-September 3235(569), 32-35.
  • Çiftci Ç., Dursun S., Levend S., Kunt F., (2013), Effect of Topography, Climatic Conditions and Urbanization on Air Pollution Problem of Konya, Turkey, European Journal of Science and Technology, 1(1), 19-24.
  • Cramer J.C., (1998), Population growth and air quality in California, Demography, 35(1), 45-56.
  • Cuhadaroglu B., Demirci E., (1997), Influence of some meteorological factors on air pollution in Trabzon city, Energy and Buildings, 25(3), 179-184.
  • Demirarslan K.O., Akıncı H., (2018), Assessment of Winter Season Air Quality in the Marmara Region Using GIS and Air Quality Data, Journal of Natural Hazards and Environment, 4(1), 11-27.
  • Demircan M., Demir Ö., Atay H., Eskioğlu O., TüvanA., Akçakaya A., (2014), Climate change projections for Turkey with new scenarios, The Climate Change and Climate Dynamics Conference 2014, Istanbul, Turkey, ss.8-10.
  • Dimitriou K., Kassomenos P., (2017), The covariance of air quality conditions in six cities in Southern Germany-The role of meteorology, Science of the Total Environment, 574, 1611-1621.
  • EPA, (2014), A guide to air quality and your health, U.S. Environmental Protection Agency Office of Air Quality Planning and Standards, https://www.airnow.gov/sites/default/files/2018-04/aqi_brochure_02_14_0.pdf, [Accessed 10 May 2022].
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  • ESRI, (2014), ArcMap 10.2. Redlands, USA.
  • Filonchyk M., Yan H., (2018), The characteristics of air pollutants during different seasons in the urban area of Lanzhou, Northwest China. Environmental Earth Sciences, 77(22), 1-17.
  • Ghaedrahmati S., Alian M., (2019), Health risk assessment of relationship between air pollutants' density and population density in Tehran, Iran, Human and Ecological Risk Assessment: An International Journal, 25(7), 1853-1869.
  • Gilliam J.H, Hall E.S., (2016), Reference and Equivalent Methods Used to Measure National Ambient Air Quality Standards (NAAQS), Criteria Air Pollutants-Volume I, US Environmental Protection Agency, EPA/600/R-16/139, Washington, DC.
  • Giorgi F., Meleux F., (2007), Modelling the regional effects of climate change on air quality, Comptes Rendus Geoscience, 339(11-12), 721-33.
  • Gocheva-I., Snezhana G., Stoimenova M.P., (2018), PM10 Prediction and Forecasting Using CART: A Case Study for Pleven, Bulgaria, International Journal of Environmental and Ecological Engineering, 12(9), 572-577.
  • Godish T., Fu J.S., (2003), Air Quality, Fourth Edition, CRC Press, Boca Raton, 480ss.
  • Gu K., Qiao J., Lin W., (2018), Recurrent air quality predictor based on meteorology-and pollution-related factors, IEEE Transactions on Industrial Informatics, 14(9), 3946-3955.
  • Haagenson P.L., (1979), Meteorological and climatological factors affecting Denver air quality, Atmospheric Environment (1967), 13(1), 79-85.
  • Han L., Zhou W., Li W., (2018), Growing urbanization and the impact on fine particulate matter (PM2.5) dynamics, Sustainability, 10(6), 1696.
  • Han S., Bian H., Feng Y., Liu A., Li X., Zeng F., Zhang X., (2011), Analysis of the Relationship between O3, NO and NO2 in Tianjin, China, Aerosol Air Qual. Res, 11(2), 128-39.
  • Han X., Naeher LP., (2006), A review of traffic-related air pollution exposure assessment studies in the developing world, Environment international, 32(1), 106-20.
  • Holzworth G.C., (1974), Climatological Aspects of the Composition and Pollution of the Atmosphere, Secretariat of the World Meteorological Organization.
  • Hu D., Wu J., Tian K., Liao L., Xu M., Du Y., (2017), Urban air quality, meteorology and traffic linkages: Evidence from a sixteen-day particulate matter pollution event in December 2015, Beijing, Journal of Environmental Sciences, 59, 30-38.
  • Huo M., Sun Q., Bai Y., Xie P., Liu Z., Li J., Wang X., Lu S., (2011), Chemical character of precipitation and related particles and trace gases in the North and South of China, Journal of Atmospheric Chemistry, 67(1), 29 doi: 10.1007/s10874-011-9201-6.
  • Jamal A., Nodehi R.N., (2017), Predicting air quality index based on meteorological data: A comparison of regression analysis, artificial neural networks and decision tree, Journal of Air Pollution and Health, 2(1), 27-38.
  • Karroum K., LinY., Chiang Y.Y., Maissa Y.B., El Haziti M., Sokolov A., Delbarre H., (2020), A Review of Air Quality Modeling, MAPAN Journal of Metrology Society of India, 5(2), 287-300.
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Ayrıntılar

Birincil Dil İngilizce
Konular Çevre Mühendisliği
Bölüm Araştırma Makalesi
Yazarlar

İsmet YENER
ARTVİN ÇORUH ÜNİVERSİTESİ, ORMAN FAKÜLTESİ, ORMAN MÜHENDİSLİĞİ BÖLÜMÜ
0000-0001-6998-9791
Türkiye

Kazım Onur DEMİRARSLAN
ARTVİN ÇORUH ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, ÇEVRE MÜHENDİSLİĞİ BÖLÜMÜ
0000-0002-1023-7584
Türkiye

Yayımlanma Tarihi 30 Temmuz 2022
Yayınlandığı Sayı Yıl 2022Cilt: 8 Sayı: 2

Kaynak Göster

Bibtex @araştırma makalesi { dacd1081167, journal = {Doğal Afetler ve Çevre Dergisi}, eissn = {2528-9640}, address = {}, publisher = {Artvin Çoruh Üniversitesi}, year = {2022}, volume = {8}, number = {2}, pages = {383 - 395}, doi = {10.21324/dacd.1081167}, title = {Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices}, key = {cite}, author = {Yener, İsmet and Demirarslan, Kazım Onur} }
APA Yener, İ. & Demirarslan, K. O. (2022). Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices . Doğal Afetler ve Çevre Dergisi , 8 (2) , 383-395 . DOI: 10.21324/dacd.1081167
MLA Yener, İ. , Demirarslan, K. O. "Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices" . Doğal Afetler ve Çevre Dergisi 8 (2022 ): 383-395 <http://dacd.artvin.edu.tr/tr/pub/issue/71418/1081167>
Chicago Yener, İ. , Demirarslan, K. O. "Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices". Doğal Afetler ve Çevre Dergisi 8 (2022 ): 383-395
RIS TY - JOUR T1 - Marmara Bölgesinde Hava Kalitesini Etkileyen Faktörlerin Belirlenmesi ve Hava Kalitesi Endeksleri Kullanılarak Değerlendirilmesi AU - İsmetYener, Kazım OnurDemirarslan Y1 - 2022 PY - 2022 N1 - doi: 10.21324/dacd.1081167 DO - 10.21324/dacd.1081167 T2 - Doğal Afetler ve Çevre Dergisi JF - Journal JO - JOR SP - 383 EP - 395 VL - 8 IS - 2 SN - -2528-9640 M3 - doi: 10.21324/dacd.1081167 UR - https://doi.org/10.21324/dacd.1081167 Y2 - 2022 ER -
EndNote %0 Doğal Afetler ve Çevre Dergisi Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices %A İsmet Yener , Kazım Onur Demirarslan %T Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices %D 2022 %J Doğal Afetler ve Çevre Dergisi %P -2528-9640 %V 8 %N 2 %R doi: 10.21324/dacd.1081167 %U 10.21324/dacd.1081167
ISNAD Yener, İsmet , Demirarslan, Kazım Onur . "Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices". Doğal Afetler ve Çevre Dergisi 8 / 2 (Temmuz 2022): 383-395 . https://doi.org/10.21324/dacd.1081167
AMA Yener İ. , Demirarslan K. O. Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices. Doğ Afet Çev Derg. 2022; 8(2): 383-395.
Vancouver Yener İ. , Demirarslan K. O. Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices. Doğal Afetler ve Çevre Dergisi. 2022; 8(2): 383-395.
IEEE İ. Yener ve K. O. Demirarslan , "Determining the Factors Affecting Air Quality in Marmara, Turkey, and Assessing it Using Air Quality Indices", Doğal Afetler ve Çevre Dergisi, c. 8, sayı. 2, ss. 383-395, Tem. 2022, doi:10.21324/dacd.1081167

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