Araştırma Makalesi
BibTex RIS Kaynak Göster

Air pollution in Eskişehir: Spatio-temporal variation of PM10, PM2.5, and SO2 concentrations and evaluation of sources

Yıl 2024, Cilt: 13 Sayı: 4, 1 - 1

İlker Balcılar

https://doi.org/10.28948/ngumuh.1459990

Öz

Determining the sources and their contributions to air quality in a region is of great importance for the development of effective control strategies. In this study, PM10, PM2.5, and SO2 data obtained from three different stations in Eskişehir were analyzed for 2023. At all stations, PM10 and PM2.5 concentrations exceeded the limit values recommended by the World Health Organization. Analysis of temporal and spatial variations in pollutants, along with bivariate polar plots, revealed that traffic and residential heating have high contribution on all pollutants at Station 1. At Station 2, the contributions of traffic and residential heating to pollutants differed. At Station 3, anthropogenic sources were more effective for SO2 and PM2.5, while contribution of soil emissions was also observed for PM10. For PM10, the concentration weighted trajectory model identified the Central Anatolia and Aegean regions in Türkiye, as well as regions over Greece, as significant source regions.

Anahtar Kelimeler

Seasonal variation Bivariate polar plot Concentration weighted trajectory

Kaynakça

  • K. Ulusoy, Zonguldak’ta PM2.5 odaklı hava kirliliği-mortalite ilişkisinin incelenmesi. Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 13(1), 301-308, 2023. https://doi.org/10.28948/ngumuh.1372 285.
  • U. A. Bhatti, Z. Zeeshan, M. M. Nizamani, S. Bazai, Z. Yu and L. Yuan, Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19. Chemosphere, 288, Pt 2, 132569, 2022. https://doi.org/10.1016/j.chemosphere.2021.132 569.
  • T. Lauriks, R. Longo, D. Baetens, M. Derudi, A. Parente, A. Bellemans, J. Van Beeck and S. Denys, Application of improved CFD modeling for prediction and mitigation of traffic-related air pollution hotspots in a realistic urban street. Atmospheric Environment, 246, 118127, 2021. https://doi.org/10.1016/j.atmosenv .202 0.118127.
  • WHO, 2022 Ambient (outdoor) air pollution. https://www.who.int/news-room/fact-sheets/detail/am bient-(outdoor)-air-quality-and-health, Erişim Tarihi 01 Mart 2024.
  • B. Caliskan, N. Özengin and S. S. Cindoruk, Air quality level, emission sources and control strategies in Bursa/Turkey. Atmospheric Pollution Research, 11, 12, 2182-2189, 2020. https://doi.org/10.1016/j.apr.2020.0 5.016.
  • M. F. Sari and F. Esen, Atmospheric concentration, spatial variations, and source identification of persistent organic pollutants in urban and semi-urban areas using passive air samplers in Bursa, Turkey. Environmental Science and Pollution Research, 1-11, 2022. https://doi .org/10.1007/s11356-021-17987-1.
  • E. Yücer, A. Erener and G. Sarp, A land use regression model to estimate ambient concentrations of PM10 and SO2 in İzmit, Turkey. Journal of the Indian Society of Remote Sensing, 51, 6, 1329-1341, 2023. https://doi .org/10.1007/s12524-023-01704-1.
  • V. Singh, S. Singh, A. Biswal, A. P. Kesarkar, S. Mor and K. Ravindra, Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India. Environmental Pollution, 266, 115368, 2020. https://doi.org/10.1016/j.envpol.2 020.115368.
  • J. Maffia, E. Dinuccio, B. Amon and P. Balsari, PM emissions from open field crop management: emission factors, assessment methods and mitigation measures – A Review. Atmospheric Environment, 226, 117381, 2020. https://doi.org/10.1016/j.atmosenv.2020.117381
  • B. A. Maher, V. O’Sullivan, J. Feeney, T. Gonet and R. A. Kenny, Indoor particulate air pollution from open fires and the cognitive function of older people. Environmental Research, 192, 110298, 2021. https:// doi.org/10.1016/j.envres.2020.110298.
  • S. K. Kharol, V. Fioletov, C. A. McLinden, M. W. Shephard, C. E. Sioris, C. Li and N. A. Krotkov, Ceramic ındustry at morbi as a large source of SO2 emissions in India. Atmospheric Environment, 223, 117243, 2020. https://doi.org/10.1016/j.atmosenv.201 9.117243.
  • A. L. d. Jesus, M. H. Thompson, L. D. Knibbs, M. Kowalski, J. Cyrys, J. V. Niemi, A. Kousa, H. Timonen, K. Luoma, T. Petäj̈ä, D. C. S. Beddows, R. M. Harrison, P. K. Hopke and L. Morawska, Long-Term trends in PM2.5 mass and particle number concentrations in urban air: The ımpacts of mitigation measures and extreme events due to changing climates. Environmental Pollution, 263, Part A 114500, 2020. https://doi.org/10.1016/j.envpol.2020.114500.
  • S. Sayols-Baixeras, A. Fernández‐Sanlés, A. Prats‐Uribe, I. Subirana, M. Plusquin, N. Künzli, J. Marrugat, X. Basagaña and R. Elosúa, Association between long-term air pollution exposure and DNA methylation: The REGICOR Study. Environmental Research, 176, 108550, 2019. https://doi.org/10.1016/j.envres.2019.1 08550.
  • A. Bari, W. B. Kindzierski and P. Roy, Identification of ambient SO2 sources in ındustrial areas in the Lower Athabasca Oil Sands Region of Alberta, Canada. Atmospheric Environment, 231, 117505, 2020. https:// doi.org/10.1016/j.atmosenv.2020.11750 5.
  • T. F. Mebrahtu, G. Santorelli, T. Yang, J. Wright, J. Tate and R. McEachan, The effects of exposure to NO2, PM2.5 and PM10 on health service attendances with respiratory ıllnesses: A time-series analysis. Environmental Pollution, 333, 122123, 2023. https:// doi.org/10.1016/j.envpol.2023.122123.
  • S. Kong, Q. Yan, H. Zheng, H. Liu, W. Wang, S. Zheng, G. Yang, M. Zheng, J. Wu, S. Qi, G. Shen, L. Tang, Y. Yin, T. Zhao, H. Yu, D. Liu, D. Zhao, Z. Tao, J. Ruan and M. Huang, Substantial reductions in ambient PAHs pollution and lives saved as a co-benefit of effective long-term PM2.5 pollution controls. Environment International, 114, 266-279, 2018. https:// doi.org/10.1016/j.envint.2018.03.002.
  • K. Ulutas, S. K. M. Abujayyab, S. S. Abu Amr, A. F. M. Alkarkhi and S. Duman, The effect of air quality parameters on new COVID-19 cases between two different climatic and geographical regions in Turkey. heoretical and Applied Climatology 152, 1-2, 801-812, 2023. https://doi.org/10.1007/s00704-023-04420-5.
  • K. Ulutaş, Prediction of mortality attributed to NO2 Air pollutant in Sakarya by using Airq+ software for 2018 and 2019. ESTÜDAM Halk Sağlığı Dergisi, 7, 2, 315-325, 2022. https://doi.org/10.35232/estudamhsd.1 060529.
  • K. J. Maji, V. O. Li and J. C. K. Lam, Effects of China’s current air pollution prevention and control action plan on air pollution patterns, health risks and mortalities in Beijing 2014–2018. Chemosphere, 260, 127572, 2020. https://doi.org/10.1016/j.chemosphere.2020.127 572.
  • K. M. Molepo, B. J. Abiodun and R. N. Magoba, The transport of PM10 over Cape Town during high pollution episodes. Atmospheric Environment, 213, 116-132, 2019. https://doi.org/10.1016/j.atmosenv.201 9.05.041.
  • B. Barhoumi, M. Tedetti, J. A. T. Onrubia, A. Dufour, T.-Q. Doan, S. Boutaleb, S. Touil and M. L. Scippo, Chemical Composition and In vitro Aryl Hydrocarbon Receptor-Mediated activity of atmospheric particulate matter at an urban, agricultural and ındustrial site in North Africa (Bizerte, Tunisia). Chemosphere, 258, 127312, 2020. https://doi.org/10.1016/j.chemosphere. 2020.127312.
  • X. Xu, N. Qin, Z. Yang, Y. Liu, S. Cao, B. Zou, L. Jin, Y. Zhang and X. Duan, Potential for Developing ındependent daytime/nighttime LUR Models based on short-term mobile monitoring to ımprove model performance. Environmental Pollution, 268, Part B, 115951, 2021. https://doi.org/10.1016/j.envpol.2020.1 15951.
  • R. Xue, S. Wang, D. Li, Z. Zou, K. L. Chan, P. Valks, A. Saiz‐Lopez and B. Zhou, Spatio-Temporal variations in NO2 and SO2 over Shanghai and Chongming eco-ısland measured by Ozone Monitoring Instrument (OMI) during 2008–2017. Journal of Cleaner Production, 258, 120563, 2020. https://doi.org /10.1016/j.jclepro.2020.120563.
  • A. Jakob, S. Hasibuan and D. Fiantis, Empirical evidence shows that air quality changes during COVID-19 pandemic lockdown in Jakarta, Indonesia Are Due to Seasonal Variation, Not Restricted Movements. Environmental Research, 208, 112391, 2022. https://doi.org/10.1016/j.envres.2021.112391.
  • O. Ozden, T. Dogeroglu and S. Kara, Assessment of ambient air quality in Eskisehir, Turkey. Environment International, 34, 5, 678-87, 2008. https://doi.org/10.10 16/j.envint.2007.12.016.
  • E. O. Gaga and A. Ari, Gas–particle partitioning of polycyclic aromatic hydrocarbons (PAHs) in an urban traffic site in Eskisehir, Turkey. Atmospheric Research, 99, 2, 207-216, 2011. https://doi.org/10.1016/j.atmosre s.2010.10.013.
  • Ö. Özden Üzmez, E. O. Gaga and T. Döğeroğlu, Development and field validation of a new diffusive sampler for determination of atmospheric volatile organic compounds. Atmospheric Environment, 107, 174-186, 2015. https://doi.org/10.1016/j.atmosenv.201 5.02.040.
  • T.C. Kültür ve Turizm Bakanlığı, Eskişehir Coğrafya Yapısı. https://eskisehir.ktb.gov.tr/TR-70841/cografya -yapisi.html, Erişim Tarihi 12 Mart 2024.
  • Türkiye İstatistik Kurumu, Nüfus istasitikleri portalı.https://nip.tuik.gov.tr/?value=CinsiyeteGoreNufus, Erişim Tarihi 12 Mart 2024.
  • Bursa Eskişehir Bilecik Kalkınma Ajansı, Eskişehir Ekonomik Yapı. https://www.investineskisehir.gov.tr/ ekonomik-yapi/, Erişim Tarihi 12 Mart 2024.
  • Eskişehir Organize Sanayi Bölgesi, Tarihçe. https://mobil.eosb.org.tr/vPage/hakkimizda, Erişim Tarihi 12 Mart 2024.
  • T.C. Çevre, Şehircilik ve İklim Değişikliği Bakanlığı, Ulusal Hava Kalitesi İzleme Ağı. https://sim.csb.gov .tr/STN/STN_Report/StationDataDownloadNew, Erişim Tarihi 20 Aralık 2023.
  • E. Koçak, Aksaray kentinin PM10 ve SO2 konsantrasyonlarının zamansal değişimi: koşullu iki değişkenli olasılık fonksiyonu ve K-means kümeleme. Journal of Engineering Sciences and Design, 6, 3, 471-478, 2018. https://doi.org/10.21923/jesd.426741.
  • E. Koçak, Prediction of daily fine particulate matter (PM2.5) concentration in Aksaray, Turkey: Temporal variation, meteorological dependence, and employing artificial neural network. Environmental Progress & Sustainable Energy, 43, 2, e14355, 2024. https://doi.org /10.1002/ep.14355.
  • J. A. Espinoza-Guillen, M. B. Alderete-Malpartida, J. H. Cañari-Cancho, D. L. Pando-Huerta, D. F. Vargas-La Rosa and S. J. Bernabé-Meza, Immission levels and identification of sulfur dioxide sources in La Oroya city, Peruvian Andes. Environment, Development and Sustainability, 25, 11, 12843-12872, 2023. https://doi .org/10.1007/s10668-022-02592-0.
  • Y. Chang, C. Deng, F. Cao, C. Cao, Z. Zou, S. Liu, X. Lee, J. Li, G. Zhang and Y. Zhang, Assessment of carbonaceous aerosols in Shanghai, China–Part 1: long-term evolution, seasonal variations, and meteorological effects. Atmospheric Chemistry and Physics, 17, 16 9945-9964, 2017. https://doi.org/10.51 94/acp-17-9945-2017.
  • I. Uria-Tellaetxe and D. C. Carslaw, Conditional bivariate probability function for source identification. Environmental Modelling & Software, 59, 1-9, 2014. https://doi.org/10.1016/j.envsoft.2014.05.002.
  • F. Dominici, A. McDermott, S. L. Zeger and J. M. Samet, On the use of generalized additive models in time-series studies of air pollution and health. American Journal of Epidemiology, 156, 3, 193-203, 2002. https://doi.org/10.1093/aje/kwf062.
  • D. C. Carslaw and K. Ropkins, Openair-an R package for air quality data analysis. Environmental Modelling & Software, 27, 52-61, 2012. https://doi.org/10.1016/j. envsoft.2011.09.008.
  • E. Busa, B. Gugamsetty, R. O. R. Kalluri, R. G. Kotalo, C. R. Tandule, L. R. Thotli, M. Chakala and S. N. R. Palle, Diurnal, seasonal, and vertical distribution of carbon monoxide levels and their potential sources over a semi-arid region, India. Atmósfera, 35, 1, 165-178, 2022. https://doi.org/10.20937/ATM.52808.
  • Y. Wang, An open source software suite for multi-dimensional meteorological data computation and visualisation. Journal of Open Research Software, 7, 1, 21, 2019. http://doi.org/10.5334/jors.267.
  • C. He, S. Hong, H. Mu, P. Tu, L. Yang, B. Ke and J. Huang, Characteristics and meteorological factors of severe haze pollution in China. Advances in Meteorology, 2021, 1-15, 2021. https://doi.org/10.1155 /2021/6680564.
  • X. Tang, X. Chen and Y. Tian, Chemical composition and source apportionment of PM2.5–A case study from one year continuous sampling in the Chang-Zhu-Tan urban agglomeration. Atmospheric Pollution Research, 8, 5, 885-899, 2017. https://doi.org/10.1016/j.apr.2017 .02.004.
  • T.C. Cumhurbaşkanlığı Menzuat Bilgi Sistemi, Hava Kalitesi Değerlendirme ve Yönetimi Yönetmeliği. https://www.mevzuat.gov.tr/File/GeneratePdf?mevzuatNo=12188&mevzuatTur=KurumVeKurulusYonetmeligi&mevzuatTertip=5, Erişim Tarihi 9 Haziran 2024.
  • European Commission, EU air quality standards. https://environment.ec.europa.eu/topics/air/air-quality /eu-air-quality-standards_en, Erişim Tarihi 9 Haziran 2024.
  • K. Ulutaş, S. K. M. Abujayyab and S. Abu Amr, Evaluation of the major air pollutants levels and ıts ınteractions with meteorological parameters in Ankara. Mühendislik Bilimleri ve Tasarım Dergisi, 9, 4, 1284-1295, 2021. https://doi.org/10.21923/jesd.939724.
  • M. Yang, T. Ma and C. Sun, Evaluating the impact of urban traffic investment on SO2 emissions in China cities. Energy Policy, 113, 20-27, 2018. https://doi .org/10.1016/j.enpol.2017.10.039.
  • V. Singh, S. Singh, A. Biswal, A. P. Kesarkar, S. Mor and K. Ravindra, Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India. Environmental Pollution, 266, 3, 2020. https://doi.org/10.1016/j.envpol.2020.11 5368.
  • S. Mor, S. A. Kumar, T. Singh, S. Dogra, V. Pandey and K. Ravindra, Impact of COVID-19 lockdown on air quality in Chandigarh, India: Understanding the emission sources during controlled anthropogenic activities. Chemosphere, 263, 127978, 2021. https:// doi.org/10.1016/j.chemosphere.2020.127978.
  • G. Prabhakar, A. Sorooshian, E. Toffol, A. F. Arellano and E. A. Betterton, Spatiotemporal distribution of airborne particulate metals and metalloids in a populated Arid Region. Atmospheric Environment, 92, 339-347, 2014. https://doi.org/10.1016/j.atmosenv.20 14.04.044.
  • V. Evagelopoulos, P. Begou, P. Kassomenos and S. Zoras, Investigation of the particulate air pollution and the ratio of PM2.5 to PM10 concentrations in the atmosphere over the lignite mining and lignite-fired power plants region of Western Macedonia, Greece. Iop Conference Series Earth and Environmental Science, 1113, 012077, 2022. https://doi.org/10.1088/ 1755-1315/1123/1/012077.
  • S. Dursun, Effects of climate change and drought in Konya: A Reviev. International Journal of Ecosystems and Ecology Science (IJEES), 10, 4, 595-602, 2020. https://doi.org/10.31407/ijees10.403.
  • D. D. Yavaşlı and E. Erlat, Climate model projections of aridity patterns in Türkiye: A comprehensive analysis using CMIP6 models and three aridity indices. International Journal of Climatology, 43, 13, 6207-6224, 2023. https://doi.org/10.1002/joc.8201.
  • E. S. Uzunpinar, I. Imamoglu, A. Rahmani and G. Tuncel, Modification of Saharan dust size distribution during its transport over the Anatolian Plateau. Sci Total Environ, 892, 164646, Sep 20 2023. https://doi. org/10.1016/j.scitotenv.2023.164646.
  • E. Koçak and İ. Balcılar, Spatio-temporal variation of particulate matter with health impact assessment and long-range transport - case study: Ankara, Türkiye. Science of the Total Environment, 938, 173650, 2024. https://doi.org/10.1016/j.scitotenv.2024.173650.
  • Çevre Şehircilik ve İklim Değişikliği Bakanlığı, Eskişehir Temiz Hava Eylem Planı THEP (2014-2019), 2014, Erişim Adresi: https://webdosya.csb.gov.tr/db/ eskisehir/webicerik/webicerik1221.pdf.
  • P. Tarín-Carrasco, U. Im, C. Geels, L. Palacios-Peña and P. Jiménez-Guerrero, Contribution of fine particulate matter to present and future premature mortality over Europe: A non-linear response. Environment International, 153, 106517, 2021. https:// doi.org/10.1016%2Fj.envint.2021.106517.

Eskişehir’de hava kirliliği: PM10, PM2.5 ve SO2 konsantrasyonlarının mekânsal-zamansal değişimi ve kaynaklarının değerlendirilmesi

Yıl 2024, Cilt: 13 Sayı: 4, 1 - 1

İlker Balcılar

https://doi.org/10.28948/ngumuh.1459990

Öz

Bir bölgedeki hava kalitesine etki eden kaynakların ve katkılarının belirlenmesi etkin kontrol stratejilerinin geliştirilmesi için büyük önem taşımaktadır. Bu çalışmada, Eskişehir'deki üç farklı istasyondan elde edilen PM10, PM2.5 ve SO2 verileri 2023 yılı için incelenmiştir. Tüm istasyonlarda, PM10 ve PM2.5 konsantrasyonlarının Dünya Sağlık Örgütü tarafından önerilen sınır değerlerin üzerinde olduğu belirlenmiştir. Kirleticilerin zamansal ve mekânsal değişimleri ile iki değişkenli polar grafikleri incelendiğinde, İstasyon 1'de trafik ve evsel ısınmanın tüm kirleticiler üzerinde yüksek katkısı gözlenmiştir. İstasyon 2'de ise trafik ve ısınmanın kirleticiler üzerindeki katkıları farklılık göstermiştir. İstasyon 3'te ise SO2 ve PM2.5 üzerinde antropojenik kaynaklar daha etkili olurken, PM10'da toprak emisyonlarının etkisi de gözlenmiştir. PM10 için konsantrasyon ağırlıklı yörünge modeli, Türkiye'de İç Anadolu ve Ege bölgeleri ile Yunanistan üzerindeki bölgeleri önemli katkı sağlayan bölgeler olarak belirlemiştir.

Anahtar Kelimeler

Mevsimsel değişim İki değişkenli polar grafik Konsantrasyon ağırlıklı yörünge

Teşekkür

Yazar, bu çalışmada kullanılan kirletici verilerini sağladığı için Çevre, Şehircilik ve İklim Değişikliği Bakanlığı'na teşekkür eder.

Kaynakça

  • K. Ulusoy, Zonguldak’ta PM2.5 odaklı hava kirliliği-mortalite ilişkisinin incelenmesi. Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 13(1), 301-308, 2023. https://doi.org/10.28948/ngumuh.1372 285.
  • U. A. Bhatti, Z. Zeeshan, M. M. Nizamani, S. Bazai, Z. Yu and L. Yuan, Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19. Chemosphere, 288, Pt 2, 132569, 2022. https://doi.org/10.1016/j.chemosphere.2021.132 569.
  • T. Lauriks, R. Longo, D. Baetens, M. Derudi, A. Parente, A. Bellemans, J. Van Beeck and S. Denys, Application of improved CFD modeling for prediction and mitigation of traffic-related air pollution hotspots in a realistic urban street. Atmospheric Environment, 246, 118127, 2021. https://doi.org/10.1016/j.atmosenv .202 0.118127.
  • WHO, 2022 Ambient (outdoor) air pollution. https://www.who.int/news-room/fact-sheets/detail/am bient-(outdoor)-air-quality-and-health, Erişim Tarihi 01 Mart 2024.
  • B. Caliskan, N. Özengin and S. S. Cindoruk, Air quality level, emission sources and control strategies in Bursa/Turkey. Atmospheric Pollution Research, 11, 12, 2182-2189, 2020. https://doi.org/10.1016/j.apr.2020.0 5.016.
  • M. F. Sari and F. Esen, Atmospheric concentration, spatial variations, and source identification of persistent organic pollutants in urban and semi-urban areas using passive air samplers in Bursa, Turkey. Environmental Science and Pollution Research, 1-11, 2022. https://doi .org/10.1007/s11356-021-17987-1.
  • E. Yücer, A. Erener and G. Sarp, A land use regression model to estimate ambient concentrations of PM10 and SO2 in İzmit, Turkey. Journal of the Indian Society of Remote Sensing, 51, 6, 1329-1341, 2023. https://doi .org/10.1007/s12524-023-01704-1.
  • V. Singh, S. Singh, A. Biswal, A. P. Kesarkar, S. Mor and K. Ravindra, Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India. Environmental Pollution, 266, 115368, 2020. https://doi.org/10.1016/j.envpol.2 020.115368.
  • J. Maffia, E. Dinuccio, B. Amon and P. Balsari, PM emissions from open field crop management: emission factors, assessment methods and mitigation measures – A Review. Atmospheric Environment, 226, 117381, 2020. https://doi.org/10.1016/j.atmosenv.2020.117381
  • B. A. Maher, V. O’Sullivan, J. Feeney, T. Gonet and R. A. Kenny, Indoor particulate air pollution from open fires and the cognitive function of older people. Environmental Research, 192, 110298, 2021. https:// doi.org/10.1016/j.envres.2020.110298.
  • S. K. Kharol, V. Fioletov, C. A. McLinden, M. W. Shephard, C. E. Sioris, C. Li and N. A. Krotkov, Ceramic ındustry at morbi as a large source of SO2 emissions in India. Atmospheric Environment, 223, 117243, 2020. https://doi.org/10.1016/j.atmosenv.201 9.117243.
  • A. L. d. Jesus, M. H. Thompson, L. D. Knibbs, M. Kowalski, J. Cyrys, J. V. Niemi, A. Kousa, H. Timonen, K. Luoma, T. Petäj̈ä, D. C. S. Beddows, R. M. Harrison, P. K. Hopke and L. Morawska, Long-Term trends in PM2.5 mass and particle number concentrations in urban air: The ımpacts of mitigation measures and extreme events due to changing climates. Environmental Pollution, 263, Part A 114500, 2020. https://doi.org/10.1016/j.envpol.2020.114500.
  • S. Sayols-Baixeras, A. Fernández‐Sanlés, A. Prats‐Uribe, I. Subirana, M. Plusquin, N. Künzli, J. Marrugat, X. Basagaña and R. Elosúa, Association between long-term air pollution exposure and DNA methylation: The REGICOR Study. Environmental Research, 176, 108550, 2019. https://doi.org/10.1016/j.envres.2019.1 08550.
  • A. Bari, W. B. Kindzierski and P. Roy, Identification of ambient SO2 sources in ındustrial areas in the Lower Athabasca Oil Sands Region of Alberta, Canada. Atmospheric Environment, 231, 117505, 2020. https:// doi.org/10.1016/j.atmosenv.2020.11750 5.
  • T. F. Mebrahtu, G. Santorelli, T. Yang, J. Wright, J. Tate and R. McEachan, The effects of exposure to NO2, PM2.5 and PM10 on health service attendances with respiratory ıllnesses: A time-series analysis. Environmental Pollution, 333, 122123, 2023. https:// doi.org/10.1016/j.envpol.2023.122123.
  • S. Kong, Q. Yan, H. Zheng, H. Liu, W. Wang, S. Zheng, G. Yang, M. Zheng, J. Wu, S. Qi, G. Shen, L. Tang, Y. Yin, T. Zhao, H. Yu, D. Liu, D. Zhao, Z. Tao, J. Ruan and M. Huang, Substantial reductions in ambient PAHs pollution and lives saved as a co-benefit of effective long-term PM2.5 pollution controls. Environment International, 114, 266-279, 2018. https:// doi.org/10.1016/j.envint.2018.03.002.
  • K. Ulutas, S. K. M. Abujayyab, S. S. Abu Amr, A. F. M. Alkarkhi and S. Duman, The effect of air quality parameters on new COVID-19 cases between two different climatic and geographical regions in Turkey. heoretical and Applied Climatology 152, 1-2, 801-812, 2023. https://doi.org/10.1007/s00704-023-04420-5.
  • K. Ulutaş, Prediction of mortality attributed to NO2 Air pollutant in Sakarya by using Airq+ software for 2018 and 2019. ESTÜDAM Halk Sağlığı Dergisi, 7, 2, 315-325, 2022. https://doi.org/10.35232/estudamhsd.1 060529.
  • K. J. Maji, V. O. Li and J. C. K. Lam, Effects of China’s current air pollution prevention and control action plan on air pollution patterns, health risks and mortalities in Beijing 2014–2018. Chemosphere, 260, 127572, 2020. https://doi.org/10.1016/j.chemosphere.2020.127 572.
  • K. M. Molepo, B. J. Abiodun and R. N. Magoba, The transport of PM10 over Cape Town during high pollution episodes. Atmospheric Environment, 213, 116-132, 2019. https://doi.org/10.1016/j.atmosenv.201 9.05.041.
  • B. Barhoumi, M. Tedetti, J. A. T. Onrubia, A. Dufour, T.-Q. Doan, S. Boutaleb, S. Touil and M. L. Scippo, Chemical Composition and In vitro Aryl Hydrocarbon Receptor-Mediated activity of atmospheric particulate matter at an urban, agricultural and ındustrial site in North Africa (Bizerte, Tunisia). Chemosphere, 258, 127312, 2020. https://doi.org/10.1016/j.chemosphere. 2020.127312.
  • X. Xu, N. Qin, Z. Yang, Y. Liu, S. Cao, B. Zou, L. Jin, Y. Zhang and X. Duan, Potential for Developing ındependent daytime/nighttime LUR Models based on short-term mobile monitoring to ımprove model performance. Environmental Pollution, 268, Part B, 115951, 2021. https://doi.org/10.1016/j.envpol.2020.1 15951.
  • R. Xue, S. Wang, D. Li, Z. Zou, K. L. Chan, P. Valks, A. Saiz‐Lopez and B. Zhou, Spatio-Temporal variations in NO2 and SO2 over Shanghai and Chongming eco-ısland measured by Ozone Monitoring Instrument (OMI) during 2008–2017. Journal of Cleaner Production, 258, 120563, 2020. https://doi.org /10.1016/j.jclepro.2020.120563.
  • A. Jakob, S. Hasibuan and D. Fiantis, Empirical evidence shows that air quality changes during COVID-19 pandemic lockdown in Jakarta, Indonesia Are Due to Seasonal Variation, Not Restricted Movements. Environmental Research, 208, 112391, 2022. https://doi.org/10.1016/j.envres.2021.112391.
  • O. Ozden, T. Dogeroglu and S. Kara, Assessment of ambient air quality in Eskisehir, Turkey. Environment International, 34, 5, 678-87, 2008. https://doi.org/10.10 16/j.envint.2007.12.016.
  • E. O. Gaga and A. Ari, Gas–particle partitioning of polycyclic aromatic hydrocarbons (PAHs) in an urban traffic site in Eskisehir, Turkey. Atmospheric Research, 99, 2, 207-216, 2011. https://doi.org/10.1016/j.atmosre s.2010.10.013.
  • Ö. Özden Üzmez, E. O. Gaga and T. Döğeroğlu, Development and field validation of a new diffusive sampler for determination of atmospheric volatile organic compounds. Atmospheric Environment, 107, 174-186, 2015. https://doi.org/10.1016/j.atmosenv.201 5.02.040.
  • T.C. Kültür ve Turizm Bakanlığı, Eskişehir Coğrafya Yapısı. https://eskisehir.ktb.gov.tr/TR-70841/cografya -yapisi.html, Erişim Tarihi 12 Mart 2024.
  • Türkiye İstatistik Kurumu, Nüfus istasitikleri portalı.https://nip.tuik.gov.tr/?value=CinsiyeteGoreNufus, Erişim Tarihi 12 Mart 2024.
  • Bursa Eskişehir Bilecik Kalkınma Ajansı, Eskişehir Ekonomik Yapı. https://www.investineskisehir.gov.tr/ ekonomik-yapi/, Erişim Tarihi 12 Mart 2024.
  • Eskişehir Organize Sanayi Bölgesi, Tarihçe. https://mobil.eosb.org.tr/vPage/hakkimizda, Erişim Tarihi 12 Mart 2024.
  • T.C. Çevre, Şehircilik ve İklim Değişikliği Bakanlığı, Ulusal Hava Kalitesi İzleme Ağı. https://sim.csb.gov .tr/STN/STN_Report/StationDataDownloadNew, Erişim Tarihi 20 Aralık 2023.
  • E. Koçak, Aksaray kentinin PM10 ve SO2 konsantrasyonlarının zamansal değişimi: koşullu iki değişkenli olasılık fonksiyonu ve K-means kümeleme. Journal of Engineering Sciences and Design, 6, 3, 471-478, 2018. https://doi.org/10.21923/jesd.426741.
  • E. Koçak, Prediction of daily fine particulate matter (PM2.5) concentration in Aksaray, Turkey: Temporal variation, meteorological dependence, and employing artificial neural network. Environmental Progress & Sustainable Energy, 43, 2, e14355, 2024. https://doi.org /10.1002/ep.14355.
  • J. A. Espinoza-Guillen, M. B. Alderete-Malpartida, J. H. Cañari-Cancho, D. L. Pando-Huerta, D. F. Vargas-La Rosa and S. J. Bernabé-Meza, Immission levels and identification of sulfur dioxide sources in La Oroya city, Peruvian Andes. Environment, Development and Sustainability, 25, 11, 12843-12872, 2023. https://doi .org/10.1007/s10668-022-02592-0.
  • Y. Chang, C. Deng, F. Cao, C. Cao, Z. Zou, S. Liu, X. Lee, J. Li, G. Zhang and Y. Zhang, Assessment of carbonaceous aerosols in Shanghai, China–Part 1: long-term evolution, seasonal variations, and meteorological effects. Atmospheric Chemistry and Physics, 17, 16 9945-9964, 2017. https://doi.org/10.51 94/acp-17-9945-2017.
  • I. Uria-Tellaetxe and D. C. Carslaw, Conditional bivariate probability function for source identification. Environmental Modelling & Software, 59, 1-9, 2014. https://doi.org/10.1016/j.envsoft.2014.05.002.
  • F. Dominici, A. McDermott, S. L. Zeger and J. M. Samet, On the use of generalized additive models in time-series studies of air pollution and health. American Journal of Epidemiology, 156, 3, 193-203, 2002. https://doi.org/10.1093/aje/kwf062.
  • D. C. Carslaw and K. Ropkins, Openair-an R package for air quality data analysis. Environmental Modelling & Software, 27, 52-61, 2012. https://doi.org/10.1016/j. envsoft.2011.09.008.
  • E. Busa, B. Gugamsetty, R. O. R. Kalluri, R. G. Kotalo, C. R. Tandule, L. R. Thotli, M. Chakala and S. N. R. Palle, Diurnal, seasonal, and vertical distribution of carbon monoxide levels and their potential sources over a semi-arid region, India. Atmósfera, 35, 1, 165-178, 2022. https://doi.org/10.20937/ATM.52808.
  • Y. Wang, An open source software suite for multi-dimensional meteorological data computation and visualisation. Journal of Open Research Software, 7, 1, 21, 2019. http://doi.org/10.5334/jors.267.
  • C. He, S. Hong, H. Mu, P. Tu, L. Yang, B. Ke and J. Huang, Characteristics and meteorological factors of severe haze pollution in China. Advances in Meteorology, 2021, 1-15, 2021. https://doi.org/10.1155 /2021/6680564.
  • X. Tang, X. Chen and Y. Tian, Chemical composition and source apportionment of PM2.5–A case study from one year continuous sampling in the Chang-Zhu-Tan urban agglomeration. Atmospheric Pollution Research, 8, 5, 885-899, 2017. https://doi.org/10.1016/j.apr.2017 .02.004.
  • T.C. Cumhurbaşkanlığı Menzuat Bilgi Sistemi, Hava Kalitesi Değerlendirme ve Yönetimi Yönetmeliği. https://www.mevzuat.gov.tr/File/GeneratePdf?mevzuatNo=12188&mevzuatTur=KurumVeKurulusYonetmeligi&mevzuatTertip=5, Erişim Tarihi 9 Haziran 2024.
  • European Commission, EU air quality standards. https://environment.ec.europa.eu/topics/air/air-quality /eu-air-quality-standards_en, Erişim Tarihi 9 Haziran 2024.
  • K. Ulutaş, S. K. M. Abujayyab and S. Abu Amr, Evaluation of the major air pollutants levels and ıts ınteractions with meteorological parameters in Ankara. Mühendislik Bilimleri ve Tasarım Dergisi, 9, 4, 1284-1295, 2021. https://doi.org/10.21923/jesd.939724.
  • M. Yang, T. Ma and C. Sun, Evaluating the impact of urban traffic investment on SO2 emissions in China cities. Energy Policy, 113, 20-27, 2018. https://doi .org/10.1016/j.enpol.2017.10.039.
  • V. Singh, S. Singh, A. Biswal, A. P. Kesarkar, S. Mor and K. Ravindra, Diurnal and temporal changes in air pollution during COVID-19 strict lockdown over different regions of India. Environmental Pollution, 266, 3, 2020. https://doi.org/10.1016/j.envpol.2020.11 5368.
  • S. Mor, S. A. Kumar, T. Singh, S. Dogra, V. Pandey and K. Ravindra, Impact of COVID-19 lockdown on air quality in Chandigarh, India: Understanding the emission sources during controlled anthropogenic activities. Chemosphere, 263, 127978, 2021. https:// doi.org/10.1016/j.chemosphere.2020.127978.
  • G. Prabhakar, A. Sorooshian, E. Toffol, A. F. Arellano and E. A. Betterton, Spatiotemporal distribution of airborne particulate metals and metalloids in a populated Arid Region. Atmospheric Environment, 92, 339-347, 2014. https://doi.org/10.1016/j.atmosenv.20 14.04.044.
  • V. Evagelopoulos, P. Begou, P. Kassomenos and S. Zoras, Investigation of the particulate air pollution and the ratio of PM2.5 to PM10 concentrations in the atmosphere over the lignite mining and lignite-fired power plants region of Western Macedonia, Greece. Iop Conference Series Earth and Environmental Science, 1113, 012077, 2022. https://doi.org/10.1088/ 1755-1315/1123/1/012077.
  • S. Dursun, Effects of climate change and drought in Konya: A Reviev. International Journal of Ecosystems and Ecology Science (IJEES), 10, 4, 595-602, 2020. https://doi.org/10.31407/ijees10.403.
  • D. D. Yavaşlı and E. Erlat, Climate model projections of aridity patterns in Türkiye: A comprehensive analysis using CMIP6 models and three aridity indices. International Journal of Climatology, 43, 13, 6207-6224, 2023. https://doi.org/10.1002/joc.8201.
  • E. S. Uzunpinar, I. Imamoglu, A. Rahmani and G. Tuncel, Modification of Saharan dust size distribution during its transport over the Anatolian Plateau. Sci Total Environ, 892, 164646, Sep 20 2023. https://doi. org/10.1016/j.scitotenv.2023.164646.
  • E. Koçak and İ. Balcılar, Spatio-temporal variation of particulate matter with health impact assessment and long-range transport - case study: Ankara, Türkiye. Science of the Total Environment, 938, 173650, 2024. https://doi.org/10.1016/j.scitotenv.2024.173650.
  • Çevre Şehircilik ve İklim Değişikliği Bakanlığı, Eskişehir Temiz Hava Eylem Planı THEP (2014-2019), 2014, Erişim Adresi: https://webdosya.csb.gov.tr/db/ eskisehir/webicerik/webicerik1221.pdf.
  • P. Tarín-Carrasco, U. Im, C. Geels, L. Palacios-Peña and P. Jiménez-Guerrero, Contribution of fine particulate matter to present and future premature mortality over Europe: A non-linear response. Environment International, 153, 106517, 2021. https:// doi.org/10.1016%2Fj.envint.2021.106517.
Toplam 57 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Hava Kirliliği Modellemesi ve Kontrolü
Bölüm Makaleler
Yazarlar

İlker Balcılar 0000-0002-0267-7184

Erken Görünüm Tarihi 2 Eylül 2024
Yayımlanma Tarihi
Gönderilme Tarihi 27 Mart 2024
Kabul Tarihi 10 Temmuz 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 13 Sayı: 4

Kaynak Göster

APA Balcılar, İ. (2024). Eskişehir’de hava kirliliği: PM10, PM2.5 ve SO2 konsantrasyonlarının mekânsal-zamansal değişimi ve kaynaklarının değerlendirilmesi. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 13(4), 1-1. https://doi.org/10.28948/ngumuh.1459990
AMA Balcılar İ. Eskişehir’de hava kirliliği: PM10, PM2.5 ve SO2 konsantrasyonlarının mekânsal-zamansal değişimi ve kaynaklarının değerlendirilmesi. NÖHÜ Müh. Bilim. Derg. Eylül 2024;13(4):1-1. doi:10.28948/ngumuh.1459990
Chicago Balcılar, İlker. “Eskişehir’de Hava kirliliği: PM10, PM2.5 Ve SO2 konsantrasyonlarının mekânsal-Zamansal değişimi Ve kaynaklarının değerlendirilmesi”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13, sy. 4 (Eylül 2024): 1-1. https://doi.org/10.28948/ngumuh.1459990.
EndNote Balcılar İ (01 Eylül 2024) Eskişehir’de hava kirliliği: PM10, PM2.5 ve SO2 konsantrasyonlarının mekânsal-zamansal değişimi ve kaynaklarının değerlendirilmesi. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13 4 1–1.
IEEE İ. Balcılar, “Eskişehir’de hava kirliliği: PM10, PM2.5 ve SO2 konsantrasyonlarının mekânsal-zamansal değişimi ve kaynaklarının değerlendirilmesi”, NÖHÜ Müh. Bilim. Derg., c. 13, sy. 4, ss. 1–1, 2024, doi: 10.28948/ngumuh.1459990.
ISNAD Balcılar, İlker. “Eskişehir’de Hava kirliliği: PM10, PM2.5 Ve SO2 konsantrasyonlarının mekânsal-Zamansal değişimi Ve kaynaklarının değerlendirilmesi”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 13/4 (Eylül 2024), 1-1. https://doi.org/10.28948/ngumuh.1459990.
JAMA Balcılar İ. Eskişehir’de hava kirliliği: PM10, PM2.5 ve SO2 konsantrasyonlarının mekânsal-zamansal değişimi ve kaynaklarının değerlendirilmesi. NÖHÜ Müh. Bilim. Derg. 2024;13:1–1.
MLA Balcılar, İlker. “Eskişehir’de Hava kirliliği: PM10, PM2.5 Ve SO2 konsantrasyonlarının mekânsal-Zamansal değişimi Ve kaynaklarının değerlendirilmesi”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, c. 13, sy. 4, 2024, ss. 1-1, doi:10.28948/ngumuh.1459990.
Vancouver Balcılar İ. Eskişehir’de hava kirliliği: PM10, PM2.5 ve SO2 konsantrasyonlarının mekânsal-zamansal değişimi ve kaynaklarının değerlendirilmesi. NÖHÜ Müh. Bilim. Derg. 2024;13(4):1-.

download