Abstract
Bioavailability and movement of pollutants through land and underground flows are strongly related to some of the sediment characteristics, such as clay minerals and organic matter. Therefore, the determination of clay and organic matter content in sediment is of great importance for environmental monitoring. Clay and organic matter in sediment were determined using diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy in combination with multivariate analysis methods. Sediment from different depths was used in combination with the soil samples of different texture. Using multivariate methods and DRIFT spectra, sediments from different depths were successfully grouped according to similarity to different texture soils. Also, a quantitative analysis of clay and organic matter content was performed, where a new calibration approach was used in which sediment samples combined with soil samples were used for principal component regression (PCR) calibration. PCR models for the assessment of clay and organic matter were determined for a total of 57 sediment samples and 32 soil samples, and satisfactory determination coefficients were obtained for linear models (0.7136 for clay and 0.7062 for organic matter). The obtained RPD values for both models gave very satisfactory values of 1.9 for clay, i.e., 1.8 for organic matter.
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Funding
This work was supported by the Provincial Secretariat for Science and Technological Development, Autonomous Province of Vojvodina, project no. 142–451-2198/2022–01.
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Branislav Jović and Branko Kordić did the FTIR and statistical analysis and wrote the related parts of the manuscript, as well as prepared figures and tables in the manuscript. Snežana Maletić and Jelena Beljin did the sediment sampling, preparation, clay and organic matter analysis, and wrote the associated aspects of the manuscript. All authors reviewed the manuscript.
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Jović, B., Maletić, S., Kordić, B. et al. DRIFT spectroscopic determination of clay and organic matter in sediment by mixed soil-sediment calibration approach. Environ Monit Assess 195, 437 (2023). https://doi.org/10.1007/s10661-023-11020-3
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DOI: https://doi.org/10.1007/s10661-023-11020-3