A stochastic model for the synthesis and degradation of natural organic matter. Part III: Modeling Cu(II) complexation

Abstract

An agent-based biogeochemical model has been developed which begins with biochemical precursor molecules and simulates the transformation and degradation of natural organic matter (NOM). This manuscript presents an empirical quantitative structure activity relationship (QSAR) which uses the numbers of ligand groups, charge density and heteroatom density of a molecule to estimate Cu-binding affinity ( K Cu ′ ) at pH 7.0 and ionic strength 0.10 for the molecules in this model. Calibration of this QSAR on a set of 41 model compounds gives a root mean square error of 0.88 log units and r 2 = 0.93. Two simulated NOM assemblages, one beginning with small molecules (tannins, terpenoids, flavonoids) and one with biopolymers (protein, lignin), give markedly different distributions of log K Cu ′ . However, calculations based on these log K Cu ′ distributions agree qualitatively with published experimental Cu(II) titration data from river and lake NOM samples.