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Description
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<p>Sediments are known to be a vector for nutrient and contaminant transfer because many substances partition preferentially to fine-grained sediment rather than remaining in solution. Despite the need to obtain reliable information on suspended sediment chemical composition, studies and monitoring programmes are often hampered by the difficulties associated with sampling, and by analytical costs. This, in turn, restricts high frequency sampling campaigns to a limited number of events and reduces the accuracy of the estimated fluxes and yields of sediment-associated chemical constituents.</p><p>Over the past decade, progress in environmental monitoring and analytics has increasingly facilitated the collection of hydro-chemical data at high frequency using <em>in-situ</em> sensors (e.g., minutes). However, sensors to estimate sediment-associated chemical constituents are limited. Here, we propose the use of submerged spectrophotometers, which measure absorbance in the UV-VIS range, to predict sediment mineralogical composition, major and trace elements and colour. Submerged spectrophotometers have already been successfully used to predict mean particle size and sediment carbon content. In this study, we assess the performance of several regression models that relate light absorbance measurements with suspended sediment properties. To this end, spectrophotometers were installed at five different sites across Luxembourg. Preliminary results show that spectrophotometers allow simultaneous assessment of various sediment constituents and/or properties at high frequency, suggesting their deployment can assist in the estimation of reliable fluxes and yields of sediment-associated substances.</p> (2022-03-28)
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Keyword
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Sediment, Environmental science, Absorbance, Environmental chemistry, Sampling (signal processing), Chemistry, Geology, Computer science, Chromatography |
