Modeling arsenic (V) removal from water by micellar enhanced ultrafiltration in the presence of competing anions.

With increasing arsenic (As) contamination incidents reported around the world, better processes for As removal from industrial wastewater and other contaminated waters are required to protect drinking water sources. Complexation of As with cetylpyridinium chloride (CPC) cationic surfactant micelles, coupled with ultrafiltration (UF), has the potential to improve As removal, but competition from other anions could be a limiting factor. Using a binary-system ion-exchange model, the selectivity coefficients for binding of the monovalent and divalent forms of arsenate (As (V)) to cationic cetylpyridinium (CP) micelles, relative to Cl, were determined to be 0.55 for HAsO and 0.047 mol L for HAsO, respectively. The affinity sequence for binding of commonly occurring monovalent anions by CP micelles was found to be NO > Cl > HCO > HAsO, and for divalent anions, SO > HAsO. Distribution of As (V) between the micellar and aqueous phases was explored using ion exchange isotherms, with higher pH and lower concentrations of competing anions increasing rejection of As (V) across UF membranes. A model accounting for these effects, based on mass balances across UF membranes and selectivity coefficients for binding of anions to the CP micelles, was used to predict As (V) removal during micellar-enhanced ultrafiltration (MEUF) of mixtures of competing anions. Model predictions agreed well with experiment results for both artificial and spiked natural river water samples. Arsenic (≈0.1 mM) removals of 91% and 84% were achieved from artificial waters and spiked natural river waters, respectively, by adding 20 mM CPC prior to UF.