Express method for investigating natural water quality using a sensor device based on surface plasmon resonance and a conductometer

  • N. V. Kachur Department of sensory systems, Institute of Semiconductor Physics of National Academy of Sciences of Ukraine, 41, Nauki ave., Kyiv, 03028, Ukraine https://orcid.org/0000-0001-6868-8452
  • A. V. Fedorenko Department of sensory systems, Institute of Semiconductor Physics of National Academy of Sciences of Ukraine, 41, Nauki ave., Kyiv, 03028, Ukraine https://orcid.org/0000-0001-6201-6129
  • H. V. Dorozinska Department of Information and Measurement Technologies, National Technical University of Ukraine“Igor Sikorsky Kyiv Polytechnic Institute”, 37, Beresteiskyi ave., Kyiv, 03056, Ukraine https://orcid.org/0000-0002-9352-3761
  • V. M. Ryzhykh Institute of Armament and Military Equipment of the Armed Forces of Ukraine, 28 B, prosp. Povitroflotskyi, Kyiv, 03049, Ukraine https://orcid.org/0000-0003-4008-3560
  • V. P. Maslov Department of sensory systems, Institute of Semiconductor Physics of National Academy of Sciences of Ukraine, 41, Nauki ave., Kyiv, 03028, Ukraine https://orcid.org/0000-0001-7795-6156
Keywords: surface plasmon resonance, electrical conductivity, natural water control, natural water pollution, chemical analysis, optical properties

Abstract

Background: One of the urgent contemporary issues is natural water pollution, which directly affects humanity's life support. This problem is associated with industrial and agricultural intensification and climate change. Water quality standards in Ukraine are defined by state standards, which regulate both organoleptic properties, such as turbidity and odor, and permissible concentrations of harmful substances.

Objective: The objective of this study was to develop a methodology for rapid natural water quality assessment using the SPR method and a conductometer and to simultaneously determine the durability of sensors with protective coatings.

Materials and methods: This study explores the feasibility of combining surface plasmon resonance (SPR) and conductometric methods to monitor the quality of natural water. The first stage involved modeling the concentration dependencies of SPR parameters and conductivity when adding controlled amounts of organic (sugar) and inorganic (table salt and soda) impurities to distilled water. Biological contamination was simulated using live yeast suspensions. Subsequently, samples of coastal water from the Dnipro River in Kyiv, the Stugna River near Vasylkiv, and a pond connected to the Stugna River near Borova village in Fastiv district were analyzed. All SPR studies were conducted using an improved sensor element with an additional protective zinc oxide layer, which reduced measurement errors typically associated with sensor replacement. To validate the reliability of the rapid assessment methods, water samples were additionally analyzed using standard laboratory methods at "Ukrkhimanaliz".

Results: The SPR results indicated that the Stugna River was the most polluted, followed by the pond, with the Dnipro River exhibiting the least pollution.

Conclusions: Summarizing the measurement results, it can be concluded that combining SPR and conductivity measurements enables rapid and objective assessment of natural water pollution levels. This corresponds to the total harmful impurities. Given the small dimensions and autonomy of the devices used in the developed methodology, river water monitoring can be carried out in field conditions by one person.

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References

State Standard of Ukraine. Drinking water. Requirements and control methods of quality. (DSTU 7525:2014). 2014. Available from: http://iccwc.org.ua/docs/dstu_7525_2014.pdf (in Ukrainian)

Water quality. Determination and investigation of color (ISO 7887:2011, IDT). 2011. Available from: https://www.iso.org/standard/46425.html

State Standard of Ukraine. Environmental protection. Quality of natural irrigation water. Agronomical criteria (DSTU 2730:2015). 2015. Available from: https://zakon.isu.net.ua/sites/default/files/normdocs/1-10395-zahyst_dovkillya._yakist_pryrodnoyi_vody_dlya_zroshen.pdf (in Ukrainian)

Jethra R. Turbidity measurement. ISA Transactions. 1993;32(4):397–405. https://doi.org/10.1016/0019-0578(93)90075-8

Aiswarya L, Siddharam, Sandeepika M. Soil moisture distribution pattern under drip irrigation in sandy loam soil using gravimetric method. Asian J Soil Sci Plant Nutr. 2024;10(2):198–204. https://doi.org/10.9734/AJSSPN/2024/v10i2276

Matos T, Martins MS, Henriques R, Goncalves LM. A review of methods and instruments to monitor turbidity and suspended sediment concentration. J Water Process Eng. 2024;64:105624. https://doi.org/10.1016/j.jwpe.2024.105624

Bieroza M, Acharya S, Benisch J, ter Borg RN, Hallberg L, Negri C, et al. Advances in Catchment Science, Hydrochemistry, and aquatic ecology enabled by high-frequency water quality measurements. Environ Sci Technol. 2023;57(12):4701–19. https://doi.org/10.1021/acs.est.2c07798

Cho HH, Jung DH, Heo JH, Lee CY, Jeong SY, Lee JH. Gold nanoparticles as exquisite colorimetric transducers for water pollutant detection. ACS Appl Mater Interfaces. 2023;15(16):19785–806. https://doi.org/10.1021/acsami.3c00627

Singh R, Mehra R, Walia A, Gupta S, Chawla P, Kumar H, et al. Colorimetric sensing approaches based on silver nanoparticles aggregation for determination of toxic metal ions in water sample: a review. Int J Environ Anal Chem. 2023;103(6):1361–76. https://doi.org/10.1080/03067319.2021.1873315

Okoffo ED, Thomas KV. Quantitative analysis of nanoplastics in environmental and potable waters by pyrolysis-gas chromatography–mass spectrometry. J Hazard Mater. 2024;464:133013. https://doi.org/10.1016/j.jhazmat.2023.133013

Kaur G, Braveen M, Krishnapriya S, Wawale SG, Castillo-Picon J, Malhotra D, et al. Machine learning integrated multivariate water quality control framework for prawn harvesting from fresh water ponds. J Food Qual. 2023;2023:1–9. https://doi.org/10.1155/2023/3841882

Pérez-Beltrán CH, Robles AD, Rodriguez NA, Ortega-Gavilán F, Jiménez-Carvelo AM. Artificial intelligence and water quality: From drinking water to wastewater. TrAC Trends Anal Chem. 2024;172:117597. https://doi.org/10.1016/j.trac.2024.117597

Murphy K, Heery B, Sullivan T, Zhang D, Paludetti L, Lau KT, et al. A low-cost autonomous optical sensor for water quality monitoring. Talanta. 2015;132:520–7. https://doi.org/10.1016/j.talanta.2014.09.045

Yaroshenko I, Kirsanov D, Marjanovic M, Lieberzeit PA, Korostynska O, Mason A, et al. Real-time water quality monitoring with chemical sensors. Sensors. 2020;20(12):3432. https://doi.org/10.3390/s20123432

Wang Y-X, Fu S-F, Xu M-X, Tang P, Liang J-G, Jiang Y-F, et al. Integrated passive sensing chip for highly sensitive and reusable detection of differential-charged nanoplastics concentration. Sensors. 2023;8(10):3862–72. https://doi.org/10.1021/acssensors.3c01406

Zhu M, Wang J, Yang X, Zhang Y, Zhang L, Ren H, et al. A review of the application of machine learning in water quality evaluation. Eco-Environ. Health. 2022;1(2):107–16. https://doi.org/10.1016/j.eehl.2022.06.001

Li Y, Wang X, Zhao Z, Han S, Liu Z. Lagoon water quality monitoring based on digital image analysis and machine learning estimators. Water Res. 2020;172:115471. https://doi.org/10.1016/j.watres.2020.115471

Nasir N, Kansal A, Alshaltone O, Barneih F, Sameer M, Shanableh A, et al. Water quality classification using machine learning algorithms. J Water Process Eng. 2022;48:102920. https://doi.org/10.1016/j.jwpe.2022.102920

Mohseni-Dargah M, Falahati Z, Dabirmanesh B, Nasrollahi P, Khajeh K. Machine learning in surface plasmon resonance for environmental monitoring. In: Mohsen Asadnia, Amir Razmjou and Amin Beheshti, editors. Artificial Intelligence and Data Science in Environmental Sensing. Academic Press; 2022. p. 269–98. https://doi.org/10.1016/B978-0-323-90508-4.00012-5

Zhang P, Chen Y-P, Wang W, Shen Y, Guo J-S. Surface plasmon resonance for water pollutant detection and water process analysis. Trends Anal Chem. 2016;85:153–65. https://doi.org/10.1016/j.trac.2016.09.003

Sayed FA, Elsayed HA, Al-Dossari M, Eissa MF, Mehaney A, Aly AH. Angular surface plasmon resonance-based sensor with a silver nanocomposite layer for effective water pollution detection. Sci Rep. 2023;13(1):21793. https://doi.org/10.1038/s41598-023-48837-4

Radov DH, Maslov VP, Ushenin YV, Dorozinsky G, Kushnir H, Konchenko A, Kachur N, inventors; Radov DH, Maslov VP, Ushenin YV, Dorozinsky G, Kushnir H, Konchenko A, Kachur N, assignee. Method for controlling water purification degree. Ukraine patent; U 115844, 2017 Apr 25. 5 p. Available from: https://sis.nipo.gov.ua/uk/search/detail/804176/ (in Ukrainian)

Radov DH, Bezruk ZD, Maslov VP, Dorozinsky G, Dorozinska HV, Konchenko A. Study of water purification patterns from tap water using freezing method. Bull Natl Tech Univ “KhPI”, Ser Mech Technol Syst Complexes. 2016;50:137–41. Available from: http://mtsc.khpi.edu.ua/article/view/99937 (in Ukrainian)

Dorozinsky G, Maslov V, Klestova Z, Ushenin Yu, Dorozinska H, Blotska O, Yuschenko A. Development high sensitivity sensor based on surface plasmon resonance phenomenon. 2019 IEEE 39th International Conference on Electronics and Nanotechnology (ELNANO). Kyiv, Ukraine, 2019, p. 249–252. http://doi.org/10.1109/ELNANO.2019.8783945

Fedorenko A, Kachur N, Sulima OV, Maslov V. Protective properties of ZnO nanofilm against wear and mechanical damage of sensitive SPR sensor element. Funct Mater. 2024;31(2):199-204. http://doi.org/10.15407/fm31.02.199

Berendsen HJC. A Student’s Guide to Data and Error Analysis. Berendsen H, editor. Cambridge: Cambridge University Press; 2011. 225 p.

Maslov V, Kachur N, Fedorenko A, inventors; Lashkariov institute of semiconductor physics of National Academy of Sciences of Ukraine, assignee. Sensitive element of a device for studying liquid and gaseous substances based on the phenomenon of surface plasmon resonance. Ukraine patent; U 154656, 2023 Nov 29. Available from: https://sis.nipo.gov.ua/uk/search/detail/1773421/ (in Ukrainian)

Published
2025-12-19
Cited
How to Cite
Kachur, N. V., Fedorenko, A. V., Dorozinska, H. V., Ryzhykh, V. M., & Maslov, V. P. (2025). Express method for investigating natural water quality using a sensor device based on surface plasmon resonance and a conductometer. Biophysical Bulletin, (54), 36-48. https://doi.org/10.26565/2075-3810-2025-54-03
Section
Methods of biophysical investigations