Modeling Complexometric Titrations of Natural Water Samples

Complexometric titrations are the primary source of metal speciation data for aquatic systems, yet their interpretation in waters containing humic and fulvic acids remains problematic. In particular, the accuracy of inferred ambient free metal ion concentrations and parameters quantifying metal complexation by natural ligands has been challenged because of the difficulties inherent in calibrating common analytical methods and in modeling the diverse array of ligands present. This work tests and applies a new method of modeling titration data that combines calibration of analytical sensitivity (S) and estimation of concentrations and stability constants for discrete natural ligand classes ([Li]T and Ki) into a single step using nonlinear regression and a new analytical solution to the one-metal/two-ligand equilibrium problem. When applied to jointly mode