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Coupling electrochemical and spectroscopic methods for river water dissolved organic matter characterization

Environmental Monitoring and Assessment 2025 Score: 38 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Stefan Platikanov, Abel Palomas, Michelle Cedeño Mata, Romá Tauler, Jorge L. Villar, R. Bragós, Sandra Bermejo, Joaquim Jaumot, Sı́lvia Lacorte

Summary

Researchers combined electrochemical impedance spectroscopy with traditional light-based methods to better characterize dissolved organic matter in river water — organic compounds that interact with pollutants including microplastics. The integrated approach revealed patterns in organic matter composition that optical methods alone would miss, offering a more complete picture of water quality.

Monitoring dissolved organic matter (DOM) in surface waters is essential for assessing ecosystem health and detecting pollution. However, conventional spectroscopic techniques often provide limited information about the electrochemical behavior of DOM. This study integrates electrochemical impedance spectroscopy (EIS) with classical methods such as UV-Vis absorption and fluorescence spectroscopies to improve DOM characterization in river water samples. In particular, this coupling provides additional insights into the electrochemical properties of DOM, which are not captured by conventional spectroscopic techniques. This study combined multiple data sources, including physicochemical parameters (e.g., water temperature, pH, conductivity), EIS spectral scores, fluorescence indices, and DOM fractions resolved by multivariate curve resolution-alternating least squares (MCR-ALS) applied to excitation-emission matrix (EEM) fluorescence data. The results from these different methods were then merged into a single dataset for a global principal component analysis (PCA), which allowed us to identify shared patterns and correlations across methods. The results revealed that low-altitude rivers showed the highest DOM content, followed by mid-altitude rivers, while high-altitude rivers presented the lowest. The PCA model indicated that low-frequency regions in the EIS spectra correlated with higher DOM content, whereas mid- to high-frequency regions were associated with lower DOM levels. These frequency-dependent patterns reflected differences in charge transfer and dielectric behavior of DOM in the river samples, which are not accessible through optical techniques. This highlights the potential of EIS as a complementary tool that provides electrochemical information on DOM composition for better water quality assessment.

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