New approach to analysis of voltammetric ligand titration data improves understanding of metal speciation in natural waters

In this study, previously published multiple analytical window datasets of competitive ligand exchange-adsorptive cathodic stripping voltammetry titrations for dissolved copper with salicylaldoxime as the competing ligand were reanalyzed. A new numerical method was applied, the Sander-Wells (S-W) method, which is able to simultaneously analyze multiple analytical window titrations as a unified dataset and calculate parameters for one to three ligand classes in the samples. The two datasets used were from separate sampling events at Dumbarton Bridge, San Francisco Bay. The aim of this study was to see if discrete ligand classes can be resolved from these data, and how these compare with results obtained by applying commonly used manual calculations of individual analytical window titrations separately: Scatchard and van den Berg/Ruzic linearizations, and the Gerringa non-linear regression. The united multiple analytical window dataset could only be analyzed simultaneously by the S-W method, and two or three discrete ligand classes were resolved for each sample. Applying the four different data analysis methods independently to each of the five analytical windows resulted in solutions spanning a continuum of conditional stability constants and ligand concentrations. It was shown that the sensitivity S, as well as data structure and iterative optimization, are the major reasons for different results. This study demonstrates the utility of simultaneous analysis of multiple analytical window titration curves to better determine the distribution of trace metal species in aqueous systems and the advantages of adopting such a 'unified data set' approach over fitting individual titration curves.