Accurate evaluation of sediment toxicity remains challenging due to complex interactions among sediment geochemistry, contaminant partitioning, and bioavailability. Conventional sediment quality guidelines classify sediments based on bulk contaminant concentrations, often overlooking bioavailability and yielding low predictive accuracy near threshold levels. Likewise, equilibrium partitioning models mainly consider organic carbon and acid volatile sulfides, limiting their applicability under oxidizing conditions where iron oxides dominate metal binding. This study developed a predictive framework for cadmium (Cd) toxicity assessment in freshwater sediments by incorporating multiple sorption phases and bioavailability metrics. A mechanistic model for the sediment–water distribution coefficient (K_d) of Cd was established using pH, total organic carbon (TOC), and amorphous/crystalline iron oxides. Windermere Humic Aqueous Model 7 simulations and adsorption experiments showed that K_d varied over three orders of magnitude across pH ranges, with amorphous iron oxides exhibiting the strongest affinity at alkaline pH (>7.5). Application to 21 field sediments yielded predictions within one order of magnitude of measured K_d values. Predicted K_d values were further used to estimate porewater Cd concentrations and derive Interstitial Water Toxic Units. Comparison with Hyalella azteca bioassays increased classification accuracy from 43 to 76%. This bioavailability-based framework improves sediment toxicity prediction under oxidizing conditions where previous models are inadequate.

Keywords: Sediment toxicity, Sediment effect concentration, Oxidized sediment, Sediment geochemistry, Hyalella azteca bioassay