Long-range transport and potential source regions of PM2.5 during the autumn season in Edirne, Türkiye

Abstract

The variation in daily Particulate Matter 2.5 (PM2.5) concentrations was studied in Edirne city center from September 1, 2019 to November 30, 2019 (autumn season). The values of daily PM2.5 concentrations were between 5.65 and 77.59 μg m-3. The values of PM2.5 concentration had the highest average value on Tuesdays compared to other days. The mean value of daily PM2.5 concentrations on Tuesdays was 23.41 μg m-3. The backward trajectories were computed and clustered by applying the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The backward trajectories clustered in eight major clusters during the autumn. In Cluster 4 (C4), which has more short-range transport according to the other seven clusters, the mean value of PM2.5 concentrations was 19.52 μg m-3. The mean value of PM2.5 concentrations was 28.11 μg m-3 in C8 (3.3%), which has more long-range transport than the other seven clusters. Potential source areas of PM2.5 have been determined by the Potential Source Contribution Function (PSCF) model. The results of PSCF analyses illustrated that the north, northeast, south, and southeast regions of the sampling area as major potential source areas for PM2.5. The results obtained in this study can make important contributions to the evaluation of PM2.5 concentration in the region in terms of health and long-range transport.

Keywords

• Backward trajectory
• HYSPLIT
• particulate matter
• PM2.5
• PSCF

References

1. Begum, B. A., Kim, E., Jeong, C. H., Lee, D. W., & Hopke, P. K. (2005). Evaluation of the potential source contribution function using the 2002 Quebec forest fire episode. Atmospheric Environment, 39(20), 3719-3724.
2. Bie, S., Yang, L., Zhang, Y., Huang, Q., Li, J., Zhao, T., ... & Wang, W. (2021). Source appointment of PM2.5 in Qingdao port, east of China. Science of the Total Environment, 755, 142456.
3. Carslaw, D. C., & Ropkins, K. (2012). Openair-An R package for air quality data analysis. Environmental Modelling & Software, 27-28, 52-61.
4. Carslaw, D. C. (2019). The openair manual - open-source tools for analysing air pollution data. Manual for version 2.6-6, University of York.
5. Cheng, F., Zha, Y., Zhang, J., He, J., & Yan, S. (2017). A study on distance transport of PM2.5 to Xianlin in Nanjing, China and its source areas. Aerosol and Air Quality Research, 17(7), 1672-1683.
6. Ecer, A., Sarikaya, B., Tepe, A. M., & Dogan, G. (2017). Mardin hava kirliliğinin değerlendirilmesi. VII. Ulusal Hava Kirliliği ve Kontrolü Sempozyumu, Antalya, Türkiye. 853-862.
7. ECDR, (2020). Edirne İli 2019 Yılı Çevre Durum Raporu, Türkiye Cumhuriyeti Edirne Valiliği Çevre ve Şehircilik İl Müdürlüğü. https://webdosya.csb.gov.tr/db/edirne/icerikler/2019-yili-ed-rne-il--cevre-durum-raporu-n-ha--20201216122442.pdf, Last accessed on July 30, 2022.
8. Flores, R. M., Mertoglu, E., Ozdemir, H., Akkoyunlu, B. O., Demir, G., Unal, A., & Tayanc, M. (2020). A high-time resolution study of PM2. 5, organic carbon, and elemental carbon at an urban traffic site in Istanbul. Atmospheric Environment, 223, 117241.

9. Hao, T., Cai, Z., Chen, S., Han, S., Yao, Q., & Fan, W. (2019). Transport pathways and potential source regions of PM2.5 on the west coast of Bohai Bay during 2009-2018. Atmosphere, 10(6), 345.
10. Ho, B. Q. (2012). Urban air pollution. In: Mukesh Khare (ed) Air Pollution-Monitoring, Modelling and Health (pp. 1-38). InTech, Rijeka, Croatia.
11. Jain, S., Sharma, S. K., Choudhary, N., Masiwal, R., Saxena, M., Sharma, A., ... & Sharma, C. (2017). Chemical characteristics and source apportionment of PM2.5 using PCA/APCS, UNMIX, and PMF at an urban site of Delhi, India. Environmental Science and Pollution Research, 24(17), 14637-14656.
12. Kuzu, S. L., & Saral, A. (2017). The effect of meteorological conditions on aerosol size distribution in Istanbul. Air Quality, Atmosphere & Health, 10, 1029-1038.
13. Lagzi, I., Mészáros, R., Gelybó, G., & Leelőssy, Á. (2013). Atmospheric chemistry (pp. 1-201). Eötvös Lorand University.
14. Li, D., Liu, J., Zhang, J., Gui, H., Du, P., Yu, T., ... & Cheng, Y. (2017). Identification of long-range transport pathways and potential sources of PM2.5 and PM10 in Beijing from 2014 to 2015. Journal of Environmental Sciences, 56, 214-229.
15. Li, H., He, Q., & Liu, X. (2020). Identification of long-range transport pathways and potential source regions of PM2.5 and PM10 at Akedala Station, Central Asia. Atmosphere, 11(11), 1183.
16. Lv, M., Hu, A., Chen, J., & Wan, B. (2021). Evolution, transport characteristics, and potential source regions of PM2.5 and O3 pollution in a Coastal City of China during 2015-2020. Atmosphere, 12(10), 1282.
17. MEUCC, (2022). Air Quality Monitoring Station of Republic of Turkey Ministry of Environment, Urbanization and Climate Change, https://sim.csb.gov.tr/STN/STN_Report/StationDataDownloadNew, Last accessed on July 30, 2022.
18. Mukherjee, A., & Agrawal, M. (2018). Assessment of local and distant sources of urban PM2.5 in middle Indo-Gangetic plain of India using statistical modeling. Atmospheric Research, 213, 275-287.
19. Neykova, R., & Hristova, E. (2020). Backward trajectories and cluster analyses for study of PM10 concentration variations in Bulgarian urban areas. Bulgarian Journal of Meteorology and Hydrology, 24(2), 66-83.
20. Oruc, I. (2022). Transport routes and potential source areas of PM10 in Kirklareli, Turkey. Environmental Monitoring and Assessment, 194(2), 104.
21. Ozdemir, H., Aktas, M. A., Yalcin, I. E., Alyuz, U., Okten, H. E., Ozcan, H. K., ... & Alper, U. (2021). Noktasal kaynaklar için ulusal hava kirliliği emisyon faktörleri ve envanterinin belirlenmesi: Metal sektörü için örnek bir çalışma. International Journal of Advances in Engineering and Pure Sciences, 33(3), 337-346.
22. Pekney, N. J., Davidson, C. I., Zhou, L., & Hopke, P. K. (2006). Application of PSCF and CPF to PMF-Modeled sources of PM2.5 in Pittsburgh. Aerosol Science and Technology, 40(10), 952-961.
23. Petroselli, C., Crocchianti, S., Moroni, B., Castellini, S., Selvaggi, R., Nava, S., ... & Cappelletti, D. (2018). Disentangling the major source areas for an intense aerosol advection in the Central Mediterranean on the basis of Potential Source Contribution Function modeling of chemical and size distribution measurements. Atmospheric Research, 204, 67-77.
24. Rolph, G., Stein, A., & Stunder, B. (2017). Real-time environmental applications and display system: READY. Environmental Modelling & Software, 95, 210-228.
25. Stein, A. F., Draxler, R. R., Rolph, G. D., Stunder, B. J. B., Cohen, M. D., & Ngan, F. (2015). NOAA’s HYSPLIT atmospheric transport and dispersion modeling system. Bulletin of the American Meteorological Society, 96(12), 2059-2077.
26. Tepe, A. M., & Dogan, G. (2021). Chemical characterization of PM2.5 and PM2.5-10 samples collected in urban site in Mediterranean coast of Turkey. Atmospheric Pollution Research, 12(1), 46-59.
27. Wallace, J. M., & Hobbs, P. V. (2006). Atmospheric science an introductory survey (2nd ed.). (pp. 1-483). Elsevier Inc., San Diego.
28. Wang, L., Liu, Z., Sun, Y., Ji, D., & Wang, Y. (2015). Long-range transport and regional sources of PM2.5 in Beijing based on long-term observations from 2005 to 2010. Atmospheric Research, 157, 37-48.
29. Wu, X., Ding, Y., Zhou, S., & Tan, Y. (2018). Temporal characteristic and source analysis of PM2.5 in the most polluted city agglomeration of China. Atmospheric Pollution Research, 9(6), 1221-1230.
30. Zeydan, O., & Wang, Y. (2019). Using MODIS derived aerosol optical depth to estimate ground-level PM2.5 concentrations over Turkey. Atmospheric Pollution Research, 10(5), 1565-1576.
31. Zhao, M., Huang, Z., Qiao, T., Zhang, Y., Xiu, G., & Yu, J. (2015). Chemical characterization, the transport pathways and potential sources of PM2.5 in Shanghai: Seasonal variations. Atmospheric Research, 158-159, 66-78.