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Segmented multi–detection window approach for organic speciation of trace metals – a model and experimental study in estuarine system

Characterization and discrimination of trace metal-organic ligand complexes in natural waters commonly rely on determination of their conditional stability constants (K’MLi) and concentrations of corresponding discrete ligand classes ([Li]T). Electrochemical techniques are the main tool in these studies. Among them competitive ligand exchange–adsorptive cathodic voltammetry (CLE-AdCSV) is most widely used. It is based on the re-distribution of metal between the natural organic ligands present in the sample and added competitive ligand (AL) which forms the electroactive complex with known stability constant. Previous studies have shown that complexation parameters are partially dependent on AL concentration and in order to attain more reliable results it was recommended to conduct multiple individual titrations at different concentrations of AL (MultiDetection Window – MDW) and their modeling (fitting) as a single set of data.[1] Disadvantages of this approach are the longer time needed to perform multiple titrations and requirement for larger sample volume. In order to overcome these shortcomings, we have proposed and tested a revised method called "Segmented MultiDetection Window" (SMDW) which consists in multiple change of AL concentrations (2-4) along only one titration experiment. Support for modeling and processing of these titration curves is incorporated within the already existing ProMCC program.[2] The proposed method was first verified on model titrations encompassing one and two ligand systems, and thereafter experimentally tested on copper (Cu) speciation analysis in the vertical salinity gradient in the pristine Krka River estuary (Croatia). SMDW approach gave complexation parameters comparable to the "classical" approach, indicating that the proposed methodology is very robust and can be used successfully for this type of studies, with less sample consumption and a shorter total time analysis. [1] I. Pižeta, S. G. Sander, R. J. Hudson, D. Omanović et al., Mar. Chem. 173 (2015) 3–24. [2] D. Omanović, C. Garnier, I. Pižeta, Mar. Chem. 173 (2015) 25– 39.

Metal speciation ; marine environment ; Organic ligands ; CLE–AdCSV ; Multi-detection window

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