Predictive double-layer modeling of metal sorption in mine-drainage systems

Abstract

Previous comparison of predictive double-layer modeling and empirically derived metal-partitioning data has validated the use of the double-layer model to predict metal sorption reactions in iron-rich mine-drainage systems. The double-layer model subsequently has been used to model data collected from several mine-drainage sites in Colorado with diverse geochemistry and geology. This work demonstrates that metal partitioning between dissolved and sediment phases can be predictively modeled simply by knowing the water chemistry and the amount of suspended iron-rich particulates present in the system. Sorption on such iron-rich suspended sediments appears to control metal and arsenic partitioning between dissolved and sediment phases, with sorption on bed sediment playing a limited role. At pH > 5, Pb and As are largely sorbed by iron-rich suspended sediments and Cu is partially sorbed; Zn, Cd, and Ni usually remain dissolved throughout the pH range of 3 to 8.