Dibyendu Sarkar, Rachana Nagar, Rupali Datta, and Konstantinos Makris. University of Texas at San Antonio, 6900 N. Loop 1604 West, San Antonio, TX 78249
Surface complexation models (SCMs) have been successfully used to describe the adsorption of arsenic by pure phase minerals, such as Fe/Al oxides and hydroxides. However, SCM applicability in complex systems consisting of multi-component sorbents for arsenic has received little attention. Drinking water treatment residuals (WTRs) are one such multi-component system, containing primarily of amorphous Al- and Fe-oxides and hydroxides. The current study attempts to assess the ability of a modified triple layer model (TLM) to predict arsenate adsorption by two types of WTRs, namely the Al-WTRs and the Fe-WTRs as a function of solution properties, primarily the pH and solution ionic strength. Site densities and specific surface areas of the individual sorbents (amorphous Al- and Fe-hydroxides) present in the WTRs that are required by the TLM as input parameters were obtained from relevant literature (e.g., Dzombak and Morel, 1990). The study couples macroscopic data with surface complexation modeling to predict arsenate sorption onto the WTR surfaces, exploring both one-site (monodentate) and two-site (monodentate + bidentate) scenarios. Preliminary results show that pH greatly influences arsenate sorption by the WTRs, and that a single sorbent approach does not accurately predict surface complexation of arsenate by the Al- or Fe-WTRs.