Kocaeli ilinde uydu verileri ve yer istasyonu ölçümlerine bağlı olarak hava kalitesinin değerlendirilmesi

Year 2022, Issue: 81, 53 - 68, 31.12.2022

Mücahit Coşkun Hüseyin Şahiner Sohaib K M Abujayyab Onur Canbulat

https://doi.org/10.17211/tcd.1108123

Abstract

Sanayi faaliyetlerinin ve nüfus miktarının fazla olduğu yerleşim alanlarında hava kalitesinin sürekli kontrolü yaşamsal bir zorunluluktur. Bu öneme bağlı olarak araştırmanın alan kapsamını Kocaeli ili, konu kapsamını ise sahadaki kirleticilerin dağılımı oluşturmaktadır. Araştırmanın amacı çeşitli kaynaklardan atmosfere bırakılan kirleticilerin alansal dağılışını ve atmosferde ulaşacağı yaklaşık yükselti seviyesini ortaya koymaktır. Bu amaç doğrultusunda Sentinel-5P (Troposferic Monitoring Instrument) uydusuna ve Kocaeli ilinde bulunan Marmara Temiz Hava Merkezine ait istasyon verileri kullanılmıştır. Uydu verilerine ait analizler Google Earth Engine ara yüzü ile gerçekleştirilmiş, haritalamalarda ise Arc GIS 10.4 programından faydalanılmıştır. Yapılan analizler sonucunda İzmit ilçesinin körfez kıyısının, Derince ve Körfez ilçeleri sınırını oluşturan sahil şeridinin; Dilovası, Gebze ve Darıca sahil kuşağının hava kirliliğinin en yoğun yaşandığı alanlar olduğu tespit edilmiştir. Ayrıca belirlenen aerosol yüksekliğine paralel olarak araştırma sahasında kirleticiler, 0-500 metre yükselti aralığında yoğunlaşmaktadır. Hem uydu hem de yer istasyon verileri incelendiğinde azot oksitler, karbon monoksit ve kükürt dioksit arasında pozitif korelasyon olduğu tespit edilmiştir. Kış mevsiminde atmosferdeki yoğunluğu artan bu gazlar, yaz aylarında seyrelmektedir. Formaldehit ve aerosol indeksi verileri ise fotokimyasal süreçlerin etkisiyle yaz mevsiminde daha yüksek değerler göstermektedir. Kocaeli gibi hem sanayi hem de nüfus anlamında önlerde yer alan şehirlerde, çok yönlü araştırmaların artırılması öncü bilgiler sağlayarak daha sağlıklı bir hava kalitesini beraberinde getirecektir.

Keywords

Kocaeli, Hava Kirliliği, Google Earth Engine

Evaluation of air quality based on satellite data and ground station measurements in Kocaeli province

Abstract

In areas with heavy industrial activity and population, controlling air pollution is essential for
maintaining a good standard of living. Researchers are drawn to study the behavior of primary
and secondary sources to reduce pollution. Kocaeli is one of the good candidates with high
population and industrial activities. Thus, the scope of the study consists of the distribution
of pollutants in Kocaeli province. The primary objective is to identify the spatial distribution of
pollutants emitted into the atmosphere from various sources as well as the approximate height
at which they will come to a stop. To achieve the goal, data from the Sentinel-5P satellite and
the Marmara Clean Air Center in Kocaeli province were also consulted. Additionally, Arc GIS 10.4
was used for the mapping, and Google Earth Engine was used for processing the satellite data.
The investigation has revealed that the coastal belts of the Dilovas, Gebze, and Darca are those
with the highest levels of air pollution. Pollutant concentrations in the study region have been
concentrated between 0 and 500 meters above the observed aerosol height. It was discovered
that there was a positive correlation between nitrogen oxide derivatives, carbon monoxide, and
sulfur dioxide after both satellite and ground station data were examined. During the winter,
these gases become more dense in the atmosphere, and during the summer, they become less
dense. This state is effectively created by convective motions brought on by conditions of rising
temperature. Data on the aerosol index and formaldehyde reveal greater values throughout the
summer because of photochemical reactions. An improvement in multi-dimensional research
would lead to ground-breaking knowledge and better air quality in cities like Kocaeli, which is
among the first in terms of industry and population.

Keywords

Kocaeli, Air Pollution, Google Earth Engine

References

• Abdi, H., & Williams, L. J. (2010). Principal component analysis. Wires Computational Statistics, 2(4), 433–459. https://doi. org/10.1002/wics.101
• Aghlmand, M., Kalkan, K., Onur, M. İ., Öztürk, G., & Ulutak, E. (2021). Google Earth Engine ile arazi kullanımı haritalarının üretimi. Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 10(1), 38–47. https://doi.org/10.28948/ngumuh.795977
• Akyürek, Ö., Arslan, O., & Karademir, A. (2013). SO2 ve PM10 hava kirliliği parametrelerinin CBS ile konumsal analizi: Kocaeli örneği. TMMOB coğrafi bilgi sistemleri kongresi, Ankara.
• Archibald, A., Turnock, S., Griffiths, P., Cox, T., Derwent, R., Knote, C., & Shin, M. (2020). On the changes in surface ozone over the twentyfirst century: sensitivity to changes in surface temperature and chemical mechanisms. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 378, 20190329. https://doi.org/10.1098/rsta.2019.0329
• Ashar, N. G. (2016). Chemical and physical properties of sulphur dioxide and sulphur trioxide bt - advances in sulphonation techniques: liquid sulphur dioxide as a solvent of sulphur trioxide (N. G. Ashar (ed.); ss. 9–19). Springer International Publishing. https://doi.org/10.1007/978-3-319-22641-5_2
• Bar, S., Parida, B. R., & Pandey, A. C. (2020). Landsat-8 and Sentinel-2 based Forest fire burn area mapping using machine learning algorithms on GEE cloud platform over Uttarakhand, Western Himalaya. Remote Sensing Applications: Society and Environment, 18, 100324. https://doi.org/10.1016/j.rsase.2020.100324
• Bhaskar, C., & Lakshminarayanachari, K. (2021). Numerical model for primary and secondary air pollutants emitted from an area and point source in an urban area with chemical reaction and removal mechanisms. Materials Today: Proceedings, 37, 2961–2967. https://doi.org/10.1016/j.matpr.2020.08.706
• Çapraz, Ö., & Deniz, A. (2018). Analysing of a Saharan dust event in İstanbul using remote sensing data. Türkiye Ulusal Jeodezi ve Jeofizik Birliği Bilimsel Kongresi.
• Cindoruk, S. S. (2018). Havadaki NO ve NO2 parametrelerinin Marmara Temiz Hava Merkezi ölçümleri kapsamında incelenmesi. Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 7(2), 600–611. https://doi.org/10.28948/ngumuh.443194
• Coşkun, M. (2011). Fundamental pollutants in the European Union (EU) countries and their effects on Turkey. Procedia - Social and Behavioral Sciences, 19, 467–473. https://doi.org/10.1016/j. sbspro.2011.05.156
• Coşkun, M., Coşkun, S., & Gözalan, S. (2020). Temperature Inversion Winter Seasonal in Karabuk-Safranbolu Basin : Possible Effects on Natural and Human Environment ( Turkey ) Turkish Studies 15(1), 71–82. https://doi.org/10.29228/TurkishStudies.40320
• Çevre Şehircilik ve İklim Değişikliği Bakanlığı (2022). Çevre şehircilik ve iklim değişikliği bakanlığı, hava kalitesi izleme istasyonları. http://sim.csb.gov.tr/Servıces/airquality
• Dasgupta, S., Lall, S., & Wheeler, D. (2021). Spatiotemporal analysis of traffic congestion, air pollution, and exposure vulnerability in Tanzania. Science of The Total Environment, 778, 147114. https://doi.org/10.1016/j.scitotenv.2021.147114
• Dey, S., & Chowdhury, S. (2022). Chapter 12 - Air quality management in India using satellite data. In (R.P. Singh (ed.) Asian Atmospheric Pollution (pp. 239–254). Elsevier. https://doi.org/10.1016/ B978-0-12-816693-2.00019-6
• ESA. (2021). The European Space Agency. https://sentinel.esa.int/ web/sentinel/missions/sentinel-5p
• Fayyazbakhsh, A., Bell, M. L., Zhu, X., Mei, X., Koutný, M., Hajinajaf, N., & Zhang, Y. (2022). Engine emissions with air pollutants and greenhouse gases and their control technologies. Journal of Cleaner Production, 376, 134260. https://doi.org/10.1016/j. jclepro.2022.134260
• Ghasempour, F., Sekertekin, A., & Kutoglu, S. H. (2021). Google Earth Engine based spatio-temporal analysis of air pollutants before and during the first wave Covıd-19 outbreak over Turkey via remote sensing. Journal of Cleaner Production, 319, 128599. https://doi.org/https://doi.org/10.1016/j.jclepro.2021.128599
• Guo, B., Zhang, D., Pei, L., Su, Y., Wang, X., Bian, Y., Zhang, D., Yao, W., Zhou, Z., & Guo, L. (2021). Estimating PM2.5 concentrations via random forest method using satellite, auxiliary, and ground-level station dataset at multiple temporal scales across China in 2017. Science of The Total Environment, 778, 146288. https:// doi.org/https://doi.org/10.1016/j.scitotenv.2021.146288
• Guo, Y., Wang, S., Zhu, J., Zhang, R., Gao, S., Saiz-Lopez, A., & Zhou, B. (2021). Atmospheric formaldehyde, glyoxal and their relations to ozone pollution under low- and high-NOx regimes in summertime Shanghai, China. Atmospheric Research, 258, 105635. https:// doi.org/https://doi.org/10.1016/j.atmosres.2021.105635
• Huo, Y., Wang, Y., Paasonen, P., Liu, Q., Tang, G., Ma, Y., Petaja, T., Kerminen, V. M., & Kulmala, M. (2021). Trends of Planetary Boundary Layer Height Over Urban Cities of China From 1980–2018. Frontiers in Environmental Science, 9(September), 1–12. https:// doi.org/10.3389/fenvs.2021.744255
• İlkılıç, C., & Behçet, R. (2006). Hava kirliliğinin insan sağlığı ve çevre üzerindeki etkisi. Fırat Üniversitesi Doğu Araştırmaları Dergisi, 5(1), 66–72. https://dergipark.org.tr/tr/pub/fudad/issue/ 47092/592365
• İskan, S., & Koç, T. (2021). İnegöl (Bursa) havzasında hava kalitesinin fiziki ortam ile ilişkisi. Türk Coğrafya Dergisi, 77, 7–18. https:// doi.org/10.17211/tcd.871839
• Jamali, A. A., Ghorbani Kalkhajeh, R., Randhir, T. O., & He, S. (2022). Modeling relationship between land surface temperature anomaly and environmental factors using GEE and Giovanni. Journal of Environmental Management, 302, 113970. https:// doi.org/10.1016/j.jenvman.2021.113970
• Keresztes, R., & Rapo, E. (2017). Statistical Analysis of-air pollution with specific regard to factor analysis in the Ciuc basin, Romania. Studia Universitatis Babes-Bolyai. Chemia, 62, 283+. https://link.gale.com/apps/doc/A524380378/ AONE?u=anon~6ff7624f&sid=googleScholar&xid=e1757603
• Kim, M. H., Yeo, H., Park, S., Park, D. H., Omar, A., Nishizawa, T., Shimizu, A., & Kim, S. W. (2021). Assessing Calıop-derived planetary boundary layer height using ground-based lidar. Remote Sensing, 13(8), 1–14. https://doi.org/10.3390/rs13081496
• KOSANO. (2022). Kocaeli ve sanayi. https://kosano.org.tr/kocaeli- ve-sanayi/.
• Li, Y., Li, J., Zhao, Y., Lei, M., Zhao, Y., Jian, B., Zhang, M., & Huang, J. (2021). Long-term variation of boundary layer height and possible contribution factors: A global analysis. Science of the Total Environment, 796(July), 148950. https://doi.org/10.1016/j.scitotenv. 2021.148950
• Liu, S., Kley, D., McFarland, M., Mahlman, J., & Levy, H. (1980). On the origin of tropospheric ozone. Journal of Geophysical Research Atmospheres, 85. https://doi.org/10.1029/JC085iC12p07546
• Luecken, D. J., Napelenok, S. L., Strum, M., Scheffe, R., & Phillips, S. (2018). Sensitivity of Ambient Atmospheric Formaldehyde and Ozone to Precursor Species and Source Types Across the United States. Environmental Science & Technology, 52(8), 4668–4675. https://doi.org/10.1021/acs.est.7b05509
• Ma, J., Zhou, X., Xu, X., Xu, X., Gromov, S., & Lelieveld, J. (2022). Chapter 15 - Ozone and aerosols over the Tibetan Plateau (R. P. B. T.-A. A. P. Singh (ed.); ss. 287–302). Elsevier. https://doi.org/ https://doi.org/10.1016/B978-0-12-816693-2.00008-1
• Maleika, W. (2020). Inverse distance weighting method optimization in the process of digital terrain model creation based on data collected from a multibeam echosounder. Applied Geomatics, 12(4), 397–407. https://doi.org/10.1007/s12518-020-00307-6
• NOAA. (2022). National Oceanic and Atmospheric Administration, National Centers for Environmental Prediction-Climate Forecast System Reanalysis.
• Ozelkan, E., Karaman, M., Mostamandi, S., Uça Avcı, Z., & Toros, H. (2015). Derivation of PM10 Levels Using OBRA on Landsat 5 TM Images: A Case Study in Izmir, Turkey. Fresenius Environmental Bulletin, 24, 1585–1596.
• Öztürk, S., Gerçek, D., Güven, İ. T., Gaga, E., Özden Üzmez, Ö., & Civan, M. (2021). Kocaelı ̇ İzmiṫ İlçesi’̇nde parti̇kül madde (Pm2.5) konsantrasyon seviẏ eleri,̇ mekânsal ve mevsiṁ sel değerlendiṙ il̇ - mesi.̇ Mühendislik Bilimleri ve Tasarım Dergisi, 9(3), 809–821. https://doi.org/10.21923/jesd.888896
• Pasquill, F. (1961). The estimation of the dispersion of windborne material. Meteorology Magazine, 8(11), 33–40.
• Ren, Y., Wei, J., Wang, G., Wu, Z., Ji, Y., & Li, H. (2022). Evolution of aerosol chemistry in Beijing under strong influence of anthropogenic pollutants: Composition, sources, and secondary formation of fine particulate nitrated aromatic compounds. Environmental Research, 204, 111982. https://doi.org/https://doi. org/10.1016/j.envres.2021.111982
• Stroud, C. A., Zaganescu, C., Chen, J., McLinden, C. A., Zhang, J., & Wang, D. (2016). Toxic volatile organic air pollutants across Canada: multi-year concentration trends, regional air quality modelling and source apportionment. Journal of Atmospheric Chemistry, 73(2), 137–164. https://doi.org/10.1007/s10874- 015-9319-z
• Su, T., Li, Z., Li, C., Li, J., Han, W., Shen, C., Tan, W., Wei, J., & Guo, J. (2020). The significant impact of aerosol vertical structure on lower atmosphere stability and its critical role in aerosol-planetary boundary layer (PBL) interactions. Atmospheric Chemistry and Physics, 20(6), 3713–3724. https://doi.org/10.5194/acp-20- 3713-2020
• Tığlı, N. E., & Cangür, Ş. (2019). Ankara’da farklı hava kalitesi izleme istasyonlarından elde edilen verilerin kantil regresyon analizi ile incelenmesi. Nicel Bilimler Dergisi, 1(2), 62–86. https://dergipark. org.tr/tr/pub/nicel/issue/51142/567926
• Tuna Tuygun, G., & Elbir, T. (2020). Long-term temporal analysis of the columnar and surface aerosol relationship with planetary boundary layer height at a southern coastal site of Turkey. Atmospheric Pollution Research, 11(12), 2259–2269. https:// doi.org/10.1016/j.apr.2020.09.008
• UN. (2021). United Nations Office for Outer Space Affairs Un-Spıder Knowledge Portal. https://un-spider.org/links-and-resources/ gis-rs-software/google-earth-engine-google
• Ünsaldi, E., & Çiftçi, M. K. (2010). Formaldehit, kullanım alanları, risk grubu, zararlı etkileri ve koruyucu önlemler. Yüzüncü Yıl Üniversitesi Veteriner Fakültesi Dergisi, 21(1), 71-77–77.
• Vallero, D. (2019). Characterizing air pollutants (ss. 29–44). https:// doi.org/10.1016/B978-0-12-814934-8.00002-8
• Vries, J., Laan, E., Hoogeveen, R. W. M., Jongma, R., Aben, I., Visser, H., Boslooper, E., Saari, H., Dobber, M., Veefkind, P., Kleipool, Q., & Levelt, P. (2007). Tropomi: Solar backscatter satellite instrument for air quality and climate - art. no. 674409. Proceedings of Spie - The International Society for Optical Engineering. https:// doi.org/10.1117/12.737755
• Yavuz, V., Özen, C., Çapraz, Ö., Özdemir, E., Deniz, A., akbayır, I., & Temur, H. (2022). Analysing of atmospheric conditions and their effects on air quality in Istanbul using Sodar and Ceilometer. Environmental Science and Pollution Research, 29, 1–20. https:// doi.org/10.1007/s11356-021-16958-w