USING MULTIPLE REGRESSION ADSORPTION MODELS TO ESTIMATE Zn AND Cu ADSORPTIONS ONTO Fe OXIDES, Mn OXIDES, ORGANIC MATERIALS AND THEIR BLENDS IN SURFICIAL SEDIMENTS

摘要

In this study multiple regression adsorption models (MRAMs) were developed to estimate the degrees of zinc and copper adsorptions onto the components [(Fe oxides ("Fe"), Mn oxides ("Mn"), organic materials (OMs), residuals (Res)] of surficial sediments (SSs) and natural surface coating samples (NSCSs). The MRAMs improve upon previous additional adsorption models (AAMs) with superior goodness-of-fit tests (R~2 - ca. 1.0000), F-tests, and t-tests (p < 0.05); they also revealed the importance of considering interactions, neglected by AAMs, among the SSs and NSCSs components when estimating the adsorptions of Zn and Cu. We verified the results of the MRAMs through adsorption experiments, with relative deviations of less than 15% between the maximum adsorptions of Zn and Cu predicted by the MRAMs and the experimentally obtained values. Our results indicate that the adsorption of Zn is dominated by Mn, Fe/Mn, and Fe, and that of Cu is dominated by Mn, Fe/Mn, and OMs, with lesser roles played by Fe/OMs, Mn/OMs, and Res. The estimated distributions of Zn and Cu among the components of the SSs and NSCSs not only agree well with those predicted previously by AAMs but also highlight the significant contributions made by Fe and Mn oxides in controlling the mobilization of heavy metals in aquatic environments.