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ICP-MS based seasonal and spatiotemporal evaluation of potentially toxic and major elements in surface waters of Akdağ National Park, Türkiye


Abstract

Understanding how potentially toxic and major elements (PTMEs) vary in freshwater systems is essential for evaluating environmental and public health risks. This study explored the seasonal and spatial variations of PTMEs in the surface waters of Akdağ National Park, Türkiye, using inductively coupled plasma-mass spectrometry (ICP-MS).Water samples were collected from nine stations across four seasons and analyzed using inductively coupled plasma-mass spectrometry (ICP-MS). Among the trace elements, Fe, Mn, and Al ranged from 120-460 µg/L, 15-310 µg/L, and 70-380 µg/L, respectively, while Pb and As remained low (1.2-8.4 µg/L and 2.3-6.1 µg/L), all within international safety limits. In contrast, Ca and Mg concentrations (18-72 mg/L and 3.5-12 mg/L) mainly reflected local geological conditions rather than contamination. Spatial interpolation (IDW) within a GIS framework indicated slightly higher PTME levels at certain locations compared with less affected sites. Overall, the results provide the first spatiotemporal baseline of PTMEs for this protected area, emphasizing the need for continuous monitoring to support sustainable water resource management and ecosystem conservation.

References

  1. Zeybek, Z. Akgöl’deki (Karaman-Konya) bazı su kalitesi parametrelerinin araştırılması (Doctoral dissertation). Selçuk Üniversitesi, Fen Bilimleri Enstitüsü (2006).

  2. Gümüş, N. E. & Akköz, C. Eber Gölü (Afyonkarahisar) su kalitesinin araştırılması. J. Limnol. Freshw. Fish. Res. https://doi.org/10.17216/LimnoFish.640775 (2020).

    Google Scholar 

  3. Fidan, A. F. et al. Determination of some heavy metal levels and oxidative status in Carassius carassius L., 1758 from Eber Lake. Environ. Monit. Assess. https://doi.org/10.1007/s10661-007-0091-3 (2008).

    Google Scholar 

  4. Harte, J., Holdren, C., Schneider, R., Shirley, C. Toxics A to Z: A guide to everyday pollution hazards 478 University of California Press https://doi.org/10.2307/jj.8501173 (1991).

  5. Kalay, M. & Canlı, M. Elimination of essential (Cu, Zn) and nonessential (Cd, Pb) metals from tissue of a freshwater fish Tilapia zilli. Turkish J. Zool. 24, 429–436 (2000).

    Google Scholar 

  6. Hudson, P. V. The effect of metal metabolism uptake, disposition and toxicity in fish. Aquat. Toxicol. 11(1–2), 3–18. https://doi.org/10.1016/0166-445x(88)90003-3 (1988).

    Google Scholar 

  7. de Oliveira, F. G., Dos Santos, L. D. & Palmeiro, A. S. Assessment of surface water quality based on physical and chemical parameters in a GIS, for three rivers in southern Brazil. Environ. Pollut. 126, 295. https://doi.org/10.1016/j.envpol.2025.126295 (2025).

    Google Scholar 

  8. de Paiva, M. H. R., Gomes, P. C. S., Dias, L. C. P. & da Fonseca Santiago, A. Simulation of water quality and land use impacts in paired watersheds of the Doce River using warm-GIS tools. Ecohydrol. Hydrobiol. 100, 652. https://doi.org/10.1016/j.ecohyd.2025.100652 (2025).

    Google Scholar 

  9. Hossain, M. N. et al. Application of multi-indexing approach within a GIS framework to investigate the quality and contamination of ground water in Barisal Sadar Bangladesh. Heliyon https://doi.org/10.1016/j.heliyon.2025.e42262 (2025).

    Google Scholar 

  10. Islam, M. T. et al. Regional irrigation water quality index for the Old Brahmaputra River, Bangladesh: A multivariate and GIS-based spatiotemporal assessment. Result. Eng. 24, 103667. https://doi.org/10.1016/j.rineng.2024.103667 (2024).

    Google Scholar 

  11. Halder, J. C. Integrating principal component weighted water quality index (PCWQI) model with GIS for evaluation of groundwater quality in Gangetic West Bengal India. Environ. Pollut. 373, 126167. https://doi.org/10.1016/j.envpol.2025.126167 (2025).

    Google Scholar 

  12. Al-Ruwaih, F., Mohammad, R. & Mohideen, S. Assessment of groundwater quality of Al-Shagaya area (Kuwait) for irrigation and industrial purposes using water quality index and GIS techniques. Kuwait J. Sci. 52(1), 100334. https://doi.org/10.1016/j.kjs.2024.100334 (2025).

    Google Scholar 

  13. Khouni, I., Louhichi, G. & Ghrabi, A. Use of GIS-based inverse distance weighted interpolation to assess surface water quality: Case of Wadi El Bey Tunisia. Environ. Technol. Innov. 24, 101892. https://doi.org/10.1016/j.eti.2021.101892 (2021).

    Google Scholar 

  14. APHA. standard methods for the examination of water and wastewater 23rd edn, American Public Health Association. (2017).

  15. Bajjali, W. ArcGIS for environmental and water issues Springer. https://doi.org/10.1007/978-3-319-61158-7_2 (2017).

    Google Scholar 

  16. Webster, R. & Oliver, M. A. Geostatistics for environmental scientists (Wiley, 2007). https://doi.org/10.1002/9780470517277.

    Google Scholar 

  17. Basciftci, Z. B. et al. Long-term analysis on climate-drought-yield relationship: Eskisehir case study. J. Appl. Biol. Sci. https://doi.org/10.3390/app152211987 (2021).

    Google Scholar 

  18. Isaaks, E. Srivastava, R. An introduction to applied geostatistics. Oxford University Press. https://doi.org/10.1017/s0016756800008189 (1989).

  19. Singh, P. Verma, P. A comparative study of spatial interpolation technique (IDW and Kriging) for determining groundwater quality. In GIS and geostatistical techniques for groundwater science 43-56 Springer. https://doi.org/10.1016/b978-0-12-815413-7.00005-5 (2019).

  20. Hodam, S., Sarkar, S., Marak, A. G., Bandyopadhyay, A. S. & Bhadra, A. Spatial interpolation of reference evapotranspiration in India: Comparison of IDW and Kriging methods. J. Inst. Eng. (India): Ser. A. https://doi.org/10.1007/s40030-017-0241-z (2017).

    Google Scholar 

  21. Taylan, E. D. & Damçayırı, D. Isparta bölgesi yağış değerlerinin IDW ve Kriging enterpolasyon yöntemleri ile tahmini. İMO Teknik Dergi 27, 7551–7559 (2016).

    Google Scholar 

  22. Jumaah, H. J., Ameen, M. H., Kalantar, B., Rizeei, H. R. & Jumaah, S. J. Air quality index prediction using IDW geostatistical technique and OLS-based GIS technique in Kuala Lumpur, Malaysia. Geomat. Nat. Hazard. Risk 10(1), 2185–2199. https://doi.org/10.1080/19475705.2019.1683084 (2019).

    Google Scholar 

  23. Vesković,J. Onjia, A. Two-dimensional Monte Carlo simulation coupled with multilinear regression modeling of source-specific health risks from groundwater. J. Hazard. Mater. Adv. online publication. (2025). https://doi.org/10.1016/j.jhazmat.2025.137309

    Google Scholar 

  24. Vesković, J. Onjia, A. Analytical techniques and source apportionment for heavy metal(loid)s in groundwater: A comprehensive review (Advance online publication, 2025). https://doi.org/10.1016/j.talo.2025.100572.

    Google Scholar 

  25. Karaouzas, I., Kapetanaki, N., Mentzafou, A., Kanellopoulos, T. D. & Skoulikidis, N. Heavy metal contamination status in Greek surface waters: A review with application and evaluation of pollution indices. Chemosphere 263, 128192. https://doi.org/10.1016/j.chemosphere.2020.128192 (2020).

    Google Scholar 

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Acknowledgements

All data and tables supporting the findings of this study are included in this manuscript.

Funding

This research project was supported by the Afyon Kocatepe University Scientific Research Projects Coordination Unit under Project No: 21.VF.02.

The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.

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Contributions

Zeyneb Karakuş: Conceptualization, methodology, supervision, writing original draft. Recep Kara: Laboratory analyses. Mustafa Yalçın: Data interpolation and visualization. Hakan Yılmaz, Hesna Kandır, Fatih Fidan: Data collection and laboratory analyses. All authors reviewed and approved the final version of the manuscript.

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Correspondence to
Zeyneb Karakuş.

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Ethics

This study did not require ethical approval as it did not involve any human or animal subjects. Permission for water sampling within Akdağ National Park was obtained from the General Directorate of Nature Conservation and National Parks of Türkiye. The official permit document is publicly available at the following link: https://acrobat.adobe.com/id/urn:aaid:sc:AP:fcc0ca3a-a61d-4f86-be42-cff0c04b3e2a.

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Karakuş, Z., Kara, R., Yalçın, M. et al. ICP-MS based seasonal and spatiotemporal evaluation of potentially toxic and major elements in surface waters of Akdağ National Park, Türkiye.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-35053-z

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  • DOI: https://doi.org/10.1038/s41598-026-35053-z

Keywords

  • ICP-MS
  • GIS mapping
  • Spatial interpolation
  • Freshwater quality
  • PTMEs
  • Akdağ national park


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