A predictive model for copper partitioning to suspended particulate matter in river waters

Abstract

A chemical equilibrium-based predictive model expressing Cu partitioning as a function of aqueous and solid phase characteristics was developed. The model takes into account only the most important factors that govern Cu partitioning, and therefore results in a relatively simple formulation. It assumes particulate organic carbon (POC) and dissolved organic carbon (DOC) binding sites play the most important role in solid and aqueous phases. The model formulation assumed one-surface site and two dissolved organic matter (DOM) sites, and included the “solids effect”. Proton effects were considered for both the particle surface sites and the DOM. The model was calibrated with data for samples collected from the Susquehanna River, and validated with White Clay Creek and Delaware River samples. Copper partitioning in natural water systems with different pH, and concentrations of alkalinity, DOC, POC, total suspended solids (TSS), and total copper was predicted reasonably well.