GIS-Based Empirical Bayesian Kriging for Spatial Modeling of Electromagnetic Pollution from High-Voltage Power Lines: Erzurum Case Study

Yıl 2026, Cilt: 9 Sayı: 2, 562 - 572, 15.03.2026

Cansu Güller

https://doi.org/10.34248/bsengineering.1849407

https://izlik.org/JA27GN48WS

Öz

In urban areas, extremely low-frequency electromagnetic fields (ELF-EMF) generated by high-voltage power lines (HVPL) have been associated with cancer, neurological disorders, and cognitive development problems in children, emerging as a significant public health threat. Therefore, reliable modeling of ELF-EMF distribution is a critical requirement for urban planning. However, studies on the spatial modeling of ELF-EMF levels in outdoor environments remain limited, and existing methods have been insufficient in capturing heterogeneous spatial patterns. The aim of this study is to develop an Empirical Bayesian Kriging (EBK)-based spatial model to reveal the heterogeneous characteristics of ELF-EMF pollution in urban areas and to integrate built environment variables (building footprints, terrain elevation, and line components) into the spatial estimation process. Measurements conducted along an HVPL corridor in Erzurum demonstrated that an average buffer distance of 140-150 meters from the line axis is required to reach the precautionary threshold value of 0.2 µT referenced from the World Health Organization (WHO). Around transmission towers, the same threshold is attained at distances of approximately 60-70 m. These buffer distances were calculated based on the points at which the measured magnetic field strength fell below 0.2 µT as a function of horizontal distance. The analyses identified not only linear risk corridors but also spatial risk focal zones formed by local maximum values on the EBK interpolation surface. The findings reveal that the current 5-meter building clearance regulation is inadequate and emphasize the necessity of establishing scientifically grounded safety corridors. Overall, ELF-EMF pollution should be considered not only as a measurable environmental parameter but also as a strategic planning concern that directly influences sustainable urban development, public health, and environmental justice.

Anahtar Kelimeler

Empirical Bayesian Kriging , Electromagnetic field , High-voltage power line , Spatial model , Built environment

Etik Beyan

Ethics committee approval was not required for this study because of there was no study on animals or humans.

Yüksek Gerilim Hatlarından Kaynaklanan Elektromanyetik Kirliliğin Mekânsal Modellemesi için CBS Tabanlı Empirical Bayesian Kriging: Erzurum Vaka Çalışması

https://izlik.org/JA27GN48WS

Öz

Kentsel alanlarda yüksek gerilim iletim hatları (High-Voltage Power Lines, HVPL) tarafından üretilen aşırı düşük frekanslı elektromanyetik alanlar (Extremely Low Frequency Electromagnetic Fields, ELF-EMF), kanser, nörolojik bozukluklar ve çocuklarda bilişsel gelişim sorunlarıyla ilişkilendirilmekte ve önemli bir halk sağlığı tehdidi olarak öne çıkmaktadır. Bu nedenle ELF-EMF dağılımının güvenilir biçimde modellenmesi, kent planlama açısından kritik bir gerekliliktir. Buna karşın, dış mekânlarda ELF-EMF düzeylerinin mekânsal modellemesine yönelik çalışmalar sınırlıdır ve mevcut yöntemler heterojen mekânsal örüntüleri yakalamada yetersiz kalmaktadır. Bu çalışmanın amacı, kentsel alanlarda ELF-EMF kirliliğinin heterojen özelliklerini ortaya çıkarmak ve yapılı çevre değişkenlerini (bina ayak izleri, arazi yüksekliği ve hat bileşenleri) tahmin sürecine entegre etmek için Empirical Bayesian Kriging (EBK) tabanlı bir mekânsal model geliştirmektir. Erzurum’da yeni gelişme alanlarından geçen bir HVPL boyunca yapılan ölçümler, çalışmada referans alınan Dünya Sağlık Örgütünün (World Health Organization, WHO) ihtiyatlı eşik değeri olan 0,2 µT’ye ulaşmak için hat ekseninden ortalama 140-150 metrelik bir tampon mesafe gerektiğini; iletim direkleri çevresinde ise aynı eşik değerine 60-70 metre mesafede düşüldüğünü göstermiştir. Bu tampon mesafeler, ölçülen manyetik alan şiddetinin yatay uzaklığa bağlı olarak 0,2 µT’nin altına indiği noktalar esas alınarak hesaplanmıştır. Analizler hem doğrusal risk koridorlarını hem de EBK enterpolasyon yüzeyindeki yerel maksimum değerlerin oluşturduğu alansal risk odaklarını ortaya koymuştur. Sonuçlar, mevcut yönetmelikteki 5 metrelik yapı yaklaşma mesafesinin yetersiz olduğunu ortaya koymakta ve bilimsel temelli güvenlik koridorları oluşturulmasının gerekliliğini vurgulamaktadır. Genel olarak, ELF-EMF kirliliği sadece ölçülebilir bir çevresel parametre olarak değil, aynı zamanda sürdürülebilir kentsel gelişim, halk sağlığı ve çevresel adaleti doğrudan etkileyen stratejik bir planlama konusu olarak değerlendirilmelidir.

Anahtar Kelimeler

Empirical Bayesian Kriging , Elektromanyetik alan , Yüksek gerilim elektrik hattı , Mekânsal model , Yapılı çevre

Etik Beyan

Bu çalışma için etik kurul onayı gerekli değildir, çünkü hayvanlar veya insanlar üzerinde yapılan bir çalışma yoktur.

Kaynakça

• Abuasbi, F., Lahham, A., & Abdel-Raziq, I. R. (2018). Levels of extremely low-frequency electric and magnetic fields from overhead power lines in the outdoor environment of Ramallah city-Palestine. Radiation Protection Dosimetry, 179(3), 229-232.
• Baysal, U. (2011). Elektromanyetik alanların sağlık etkilerinin değerlendirilmesi. Elektromanyetik Alanlar ve Etkileri Sempozyumu (pp. 258-261). Ezgi Matbaacılık.
• Bernardi, P., Cavagnaro, M., Pisa, S., & Piuzzi, E. (2002). Human exposure to radio base-station antennas in urban environment. IEEE Transactions on Microwave Theory and Techniques, 48(11), 1996-2002.
• Breschi, M., & Cristofolini, A. (2007). Analisi del campo di induzione magnetica disperso da trasformatori: calcolo e misure. Memorie ET2007 (pp. 1-2). Manetti.
• Canales, F. A., Payares-Fontalvo, M., Florez-Guerra, H., & Acuña, G. J. (2022). Geographic information systems (GIS) tools in complementarity research—Estimation and visualization. In Complementarity of Variable Renewable Energy Sources (pp. 81-99). Academic Press.
• Crespi, C. M., Swanson, J., Vergara, X. P., & Kheifets, L. (2019). Childhood leukemia risk in the California Power Line Study: Magnetic fields versus distance from power lines. Environmental Research, 171, 530-535.
• Çerezci, O., Şeker, S., & Pala, K. (2011). İlköğretim ve ana okullarında dış kaynaklı elektromanyetik alan maruziyetinin niteliksel analizi. Elektromanyetik Alanlar ve Etkileri Sempozyumu (EMANET) (pp. 7-8).
• Çevre, Şehircilik ve İklim Değişikliği Bakanlığı. (2015). Erzurum-Erzincan-Bayburt Planlama Bölgesi 1/100.000 Ölçekli Çevre Düzeni Planı. https://mpgm.csb.gov.tr/erzurum-erzincan-bayburt-planlama-bolgesi-1-100.000-olcekli-cevre-duzeni-plani-degisikligi-i-82310 (accessed on 10 July 2025).
• Dehaghi, B. F., Shekarloo, M. V., Golbaghi, A., & Ghavamabadi, L. I. (2024). The impact of electromagnetic field exposure on diabetes: A narrative review. Journal of Environmental Health and Sustainable Development, 9(1), 1-12.
• Draper, G., Vincent, T., Kroll, M. E., & Swanson, J. (2005). Childhood cancer in relation to distance from high voltage power lines in England and Wales: A case-control study. BMJ, 330(7503), 1290.
• ESRI. (2024). ArcGIS Online Help: EBK Regression Prediction. https://pro.arcgis.com/en/pro-app/3.4/tool-reference/geostatistical-analyst/ebk-regression-prediction.htm (accessed on 26 June 2025).
• Gallastegi, M., Jiménez-Zabala, A., Santa-Marina, L., Aurrekoetxea, J. J., Ayerdi, M., Ibarluzea, J., & Huss, A. (2017). Exposure to extremely low and intermediate-frequency magnetic and electric fields among children from the INMA-Gipuzkoa cohort. Environmental Research, 157, 190-197.
• Ghanbari, G., Khodakarim, S., & Eslami, A. (2022). Survey of public exposure to extremely low-frequency magnetic fields in the dwellings. Environmental Health Engineering and Management Journal, 9(1), 1-7.
• Ghazanfarpour, M., Kashani, Z. A., Pakzad, R., Abdi, F., Rahnemaei, F. A., Akbari, P. A., & Roozbeh, N. (2021). Effect of electromagnetic field on abortion: A systematic review and meta-analysis. Open Medicine, 16(1), 1628-1641.
• Gribov, A., & Krivoruchko, K. (2020). Empirical Bayesian kriging implementation and usage. Science of the Total Environment, 722, 137290.
• Guillén-Pina, J., Pérez-Aracil, J., Chocano-del-Cerro, R., Sánchez-Montero, R., López-Espí, P. L., & Salcedo-Sanz, S. (2025). Efficient design of electromagnetic field exposure maps with multi-method evolutionary ensembles. Environmental Research, 278, 121636.
• Harman, B. I., Köseoğlu, H., & Yiğit, C. O. (2016). Performance evaluation of IDW, Kriging and multiquadric interpolation methods in producing noise mapping: A case study at the city of Isparta, Turkey. Applied Acoustics, 112, 147-157.
• Havas, M. (2008). Dirty electricity elevates blood sugar among electrically sensitive diabetics and may explain brittle diabetes. Electromagnetic Biology and Medicine, 27(2), 135-146.
• IEEE. (1994). IEEE Standard Procedures for Measurement of Power Frequency Electric and Magnetic Fields from AC Power Lines (IEEE Std 644).
• Jalilian, H., Najafi, K., Khosravi, Y., & Röösli, M. (2021). Amyotrophic lateral sclerosis, occupational exposure to extremely low frequency magnetic fields and electric shocks: A systematic review and meta-analysis. Reviews on Environmental Health, 36(1), 129-142.
• Jalilian, H., Teshnizi, S. H., Röösli, M., & Neghab, M. (2018). Occupational exposure to extremely low frequency magnetic fields and risk of Alzheimer disease: A systematic review and meta-analysis. Neurotoxicology, 69, 242-252.
• Karadağ, T., Özdemir, A. R., & Abbasov, T. (2014). Long-term electromagnetic field measurements and pollution maps in a university campus. Pamukkale University Journal of Engineering Sciences, 20(8), 314-318.
• Karbalay-Doust, S., Darabyan, M., Sisakht, M., Haddadi, G., Sotoudeh, N., Haghani, M., & Mortazavi, S. M. J. (2023). Extremely low frequency-electromagnetic fields (ELF-EMF) can decrease spermatocyte count and motility and change testicular tissue. Journal of Biomedical Physics & Engineering, 13(2), 135.
• Kelfkens, C., & Pruppers, M. A. T. H. I. E. U. (2006). Magnetic fields zoning in the framework of the Dutch power line policy. Proceedings of the 4th International Workshop on Biological Effects of EMFs (pp. 16-20). Crete, Greece.
• Kiouvrekis, Y., Zikas, S., Katis, I., Tsilikas, I., & Filippopoulos, I. (2024). Development of electromagnetic pollution maps utilizing Gaussian process spatial models. Science of the Total Environment, 955, 176907.
• Krivoruchko, K., & Gribov, A. (2019). Evaluation of empirical Bayesian kriging. Spatial Statistics, 32, 100368.
• Lee, G. M., Neutra, R. R., Hristova, L., Yost, M., & Hiatt, R. A. (2002). A nested case-control study of residential and personal magnetic field measures and miscarriages. Epidemiology, 13(1), 21-31.
• Li, J., & Heap, A. D. (2014). Spatial interpolation methods applied in the environmental sciences: A review. Environmental Modelling & Software, 53, 173-189.
• Loizeau, N., Haas, D., Zahner, M., Stephan, C., Schindler, J., Gugler, M., & Röösli, M. (2024). Extremely low frequency magnetic fields (ELF-MF) in Switzerland: From exposure monitoring to daily exposure scenarios. Environment International, 194, 109181.
• Miletić, S., Beloica, J., & Miljković, P. (2025). Integrating environmental variables into geostatistical interpolation: Enhancing soil mapping for the MEDALUS model in Montenegro. Land, 14(4), 702.
• Mordachev, V. (2024). Radiofrequency electromagnetic pollution of the habitat created by mobile communications. Biology Bulletin, 51(11), 3481-3495.
• National Grid. (2013). Electric and magnetic fields. https://www.nationalgrid.com/document/282716/download (accessed on 1 September 2025).
• Njoku, E. A., Akpan, P. E., Effiong, A. E., & Babatunde, I. O. (2023). The effects of station density in geostatistical prediction of air temperatures in Sweden: A comparison of two interpolation techniques. Resources, Environment and Sustainability, 11, 100092.
• Njoku, E. A., Akpan, P. E., Effiong, A. E., Babatunde, I. O., Owoseni, O. A., & Olanrewaju, J. O. (2022). Evaluation of geostatistical and multiple regression models for assessment of spatial characteristics of carbon monoxide concentration in a data-limited environment. Applied Geography, 149, 102816.
• Núñez-Enríquez, J. C., Correa-Correa, V., Flores-Lujano, J., Pérez-Saldivar, M. L., Jiménez-Hernández, E., Martín-Trejo, J. A., & Mejía-Aranguré, J. M. (2020). Extremely low-frequency magnetic fields and the risk of childhood B-lineage acute lymphoblastic leukemia. Bioelectromagnetics, 41(8), 581-597.
• Panagopoulos, D. J., Yakymenko, I., De Iuliis, G. N., & Chrousos, G. P. (2025). A comprehensive mechanism of biological and health effects of anthropogenic extremely low frequency and wireless communication electromagnetic fields. Frontiers in Public Health, 13, 1585441.
• Paniagua, J. M., Jiménez, A., Rufo, M., Gutiérrez, J. A., Gómez, F. J., & Antolín, A. (2007). Exposure to extremely low frequency magnetic fields in an urban area. Radiation and Environmental Biophysics, 46(1), 69-76.
• Pirani, M., Gulliver, J., Fuller, G. W., & Blangiardo, M. (2014). Bayesian spatiotemporal modelling for the assessment of short-term exposure to particle pollution in urban areas. Journal of Exposure Science & Environmental Epidemiology, 24(3), 319-327.
• Porsius, J. T., Claassen, L., Smid, T., Woudenberg, F., Petrie, K. J., & Timmermans, D. R. (2015). Symptom reporting after the introduction of a new high-voltage power line: A prospective field study. Environmental Research, 138, 112-117.
• Powerlink Queensland. (2023). Electric and magnetic fields. https://www.powerlink.com.au/brochures/electric-and-magnetic-fields (accessed on 1 September 2025).
• Qi, G., Zuo, X., Zhou, L., Aoki, E., Okamula, A., Watanebe, M., & Shimamoto, F. (2015). Effects of extremely low-frequency electromagnetic fields (ELF-EMF) exposure on B6C3F1 mice. Environmental Health and Preventive Medicine, 20(4), 287-293.
• Röösli, M., Jenni, D., Kheifets, L., & Mezei, G. (2011). Extremely low frequency magnetic field measurements in buildings with transformer stations in Switzerland. Science of the Total Environment, 409(18), 3364-3369.
• Sakacı, F. H., & Çerezci, O. (2021). Prediction of magnetic pollution with artificial neural network in living areas. Journal of Electrical Engineering & Technology, 16(5), 2701-2708.
• Sánchez-Montero, R., Alén-Cordero, C., López-Espí, P. L., Rigelsford, J. M., Aguilera-Benavente, F., & Alpuente-Hermosilla, J. (2017). Long-term variations measurement of electromagnetic field exposures in Alcalá de Henares (Spain). Science of the Total Environment, 598, 657-668.
• SCENIHR (Scientific Committee on Emerging and Newly Identified Health Risks). (2007). Possible effects of Electromagnetic Fields (EMF) on Human Health. European Commission.
• Seomun, G., Lee, J., & Park, J. (2021). Exposure to extremely low-frequency magnetic fields and childhood cancer: A systematic review and meta-analysis. PLoS One, 16(5), e0251628.
• Shepherd, S., Lima, M. A. P., Oliveira, E. E., Sharkh, S. M., Jackson, C. W., & Newland, P. L. (2018). Extremely low frequency electromagnetic fields impair the cognitive and motor abilities of honey bees. Scientific Reports, 8(1), 1-9.
• TMMOB. (2016). Yerleşim bölgelerinden geçen yüksek gerilim hatlarının etkileri. Bülten. İstanbul.
• Touitou, Y., Selmaoui, B., & Lambrozo, J. (2022). Assessment of cortisol secretory pattern in workers chronically exposed to ELF-EMF generated by high voltage transmission lines and substations. Environment International, 161, 107103.
• Türkkan, A. (2009). Childhood leukemia and electromagnetic fields. The Journal of Current Pediatrics, 8(1), 137-141.
• Vaizoğlu, S. A., Göçgeldi, E., Tekbaş, Ö. F., & Güler, Ç. (2007). Bir büyükşehir belediyesi sınırları içinde yüksek gerilim hatlarına bağlı düşük frekanslı elektromanyetik kirlilik düzeylerinin incelenmesi. XI Ulusal Halk Sağlığı Kongresi (ss. 229). Denizli.
• Vural, E. (2024). Evaluation of electromagnetic field pollution level in Gaziantep City with geographic information systems. International Journal of Environment and Geoinformatics, 11(4), 64-69.
• Wang, L., Liu, R., Liu, J., Qi, Y., Zeng, W., & Cui, B. (2023). A novel regional-scale human health risk assessment model for soil heavy metal (loid) pollution based on empirical Bayesian kriging. Ecotoxicology and Environmental Safety, 258, 114953.
• WHO (World Health Organization). (2007). Environmental Health Criteria 238: Extremely low frequency fields. WHO Press.
• Wickramathilaka, N., & Ujang, U. (2023). 3D Kriging interpolation for traffic noise visualization: designing noise observation points and valuation of spatial interpolation accuracy. IOP Conference Series: Earth and Environmental Science (pp. 012001). IOP Publishing.
• Yavuz, C., Arslanyılmaz, M. M., Vaizoğlu, S. A., Keskin, C., Öngöre, R., & Güler, Ç. (2019). Electromagnetic field levels in houses close to high power line and symptoms. Çukurova Medical Journal, 44, 263-271.
• Zaresefat, M., Derakhshani, R., & Griffioen, J. (2024). Empirical Bayesian Kriging, a robust method for spatial data interpolation of a large groundwater quality dataset from the Western Netherlands. Water, 16(18), 2581.
• Zetu, C., Livadariu, B. P., Neagu, B. C., Gheorghe, G., Tristiu, I., & Simo, A. (2025). Coexistence of Urban Public Areas and High Voltage Overhead Lines–Electromagnetic Field and Risk Analysis. 2025 International Aegean Conference on Electrical Machines and Power Electronics (ACEMP) & 2025 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) (pp. 1-6). IEEE.