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Feasibility study of multisensor systems for the assessment of water pollution index induced by heavy metal contamination : Microchemical Journal. / Iurgenson, N.; Wang, X.; Kong, L.; Sun, X.; Legin, A.; Wang, P.; Wan, H.; Kirsanov, D.

In: Microchemical Journal, Vol. 197, 109762, 01.02.2024.

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Iurgenson, N. ; Wang, X. ; Kong, L. ; Sun, X. ; Legin, A. ; Wang, P. ; Wan, H. ; Kirsanov, D. / Feasibility study of multisensor systems for the assessment of water pollution index induced by heavy metal contamination : Microchemical Journal. In: Microchemical Journal. 2024 ; Vol. 197.

BibTeX

@article{15206b51115844b18942f9c3af6c93a1,
title = "Feasibility study of multisensor systems for the assessment of water pollution index induced by heavy metal contamination: Microchemical Journal",
abstract = "The development of the analytical instruments for rapid in-field evaluation of integral surface water quality parameters is an urgent analytical task. Using three different sensor devices (optical sensor for cadmium, voltammetric sensor for lead and potentiometric multisensor system), we have explored the possibility of direct quantification of water pollution index (WPI) for contaminations induced by heavy metals. We have applied linear (partial least squares, PLS) and non-linear (kernel regularized least squares, KRLS) multivariate regression tools to construct predictive models evaluating the content of individual metals and WPI in complex aqueous media simulating surface water composition. We have also explored the potential of data fusion at different levels combining the signals from all three sensor devices. The results indicate that all the instruments retain the sensitivity towards target analytes in complex aqueous samples containing humic substances and that the direct quantification of WPI in the range from 1 to 4 is possible using the employed instruments with RMSE values around 0.14. {\textcopyright} 2023 Elsevier B.V.",
keywords = "Chemical sensors, Chemometrics, Heavy metal contamination, Multisensor systems, Water pollution index",
author = "N. Iurgenson and X. Wang and L. Kong and X. Sun and A. Legin and P. Wang and H. Wan and D. Kirsanov",
note = "Цитирования:3 Export Date: 5 October 2024 CODEN: MICJA Адрес для корреспонденции: Wan, H.; Institute of Chemistry, Russian Federation; эл. почта: wh1816@zju.edu.cn Сведения о финансировании: National Natural Science Foundation of China, NSFC, 51861145307 Сведения о финансировании: Russian Foundation for Basic Research, РФФИ, 18-53-80010 Текст о финансировании 1: This work was supported by BRICS Cooperation Project between Russia and China from Russian Basic Research Foundation (Grant No. 18-53-80010 ) and Natural Science Foundation of China (Grant No. 51861145307 ).",
year = "2024",
month = feb,
day = "1",
doi = "10.1016/j.microc.2023.109762",
language = "Английский",
volume = "197",
journal = "Microchemical Journal",
issn = "0026-265X",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Feasibility study of multisensor systems for the assessment of water pollution index induced by heavy metal contamination

T2 - Microchemical Journal

AU - Iurgenson, N.

AU - Wang, X.

AU - Kong, L.

AU - Sun, X.

AU - Legin, A.

AU - Wang, P.

AU - Wan, H.

AU - Kirsanov, D.

N1 - Цитирования:3 Export Date: 5 October 2024 CODEN: MICJA Адрес для корреспонденции: Wan, H.; Institute of Chemistry, Russian Federation; эл. почта: wh1816@zju.edu.cn Сведения о финансировании: National Natural Science Foundation of China, NSFC, 51861145307 Сведения о финансировании: Russian Foundation for Basic Research, РФФИ, 18-53-80010 Текст о финансировании 1: This work was supported by BRICS Cooperation Project between Russia and China from Russian Basic Research Foundation (Grant No. 18-53-80010 ) and Natural Science Foundation of China (Grant No. 51861145307 ).

PY - 2024/2/1

Y1 - 2024/2/1

N2 - The development of the analytical instruments for rapid in-field evaluation of integral surface water quality parameters is an urgent analytical task. Using three different sensor devices (optical sensor for cadmium, voltammetric sensor for lead and potentiometric multisensor system), we have explored the possibility of direct quantification of water pollution index (WPI) for contaminations induced by heavy metals. We have applied linear (partial least squares, PLS) and non-linear (kernel regularized least squares, KRLS) multivariate regression tools to construct predictive models evaluating the content of individual metals and WPI in complex aqueous media simulating surface water composition. We have also explored the potential of data fusion at different levels combining the signals from all three sensor devices. The results indicate that all the instruments retain the sensitivity towards target analytes in complex aqueous samples containing humic substances and that the direct quantification of WPI in the range from 1 to 4 is possible using the employed instruments with RMSE values around 0.14. © 2023 Elsevier B.V.

AB - The development of the analytical instruments for rapid in-field evaluation of integral surface water quality parameters is an urgent analytical task. Using three different sensor devices (optical sensor for cadmium, voltammetric sensor for lead and potentiometric multisensor system), we have explored the possibility of direct quantification of water pollution index (WPI) for contaminations induced by heavy metals. We have applied linear (partial least squares, PLS) and non-linear (kernel regularized least squares, KRLS) multivariate regression tools to construct predictive models evaluating the content of individual metals and WPI in complex aqueous media simulating surface water composition. We have also explored the potential of data fusion at different levels combining the signals from all three sensor devices. The results indicate that all the instruments retain the sensitivity towards target analytes in complex aqueous samples containing humic substances and that the direct quantification of WPI in the range from 1 to 4 is possible using the employed instruments with RMSE values around 0.14. © 2023 Elsevier B.V.

KW - Chemical sensors

KW - Chemometrics

KW - Heavy metal contamination

KW - Multisensor systems

KW - Water pollution index

UR - https://www.mendeley.com/catalogue/9d7fca28-1fc2-329c-bd09-6c82ce08f537/

U2 - 10.1016/j.microc.2023.109762

DO - 10.1016/j.microc.2023.109762

M3 - статья

VL - 197

JO - Microchemical Journal

JF - Microchemical Journal

SN - 0026-265X

M1 - 109762

ER -

ID: 125643837