Peroxidase-mediated removal of endocrine disrupting compound mixtures from water

Several classes of oxidative enzymes have shown promise for efficient removal of endocrine disrupting compounds (EDCs) that are resistant to conventional wastewater treatments. Although the kinetics of reactions between individual EDCs and selected oxidative enzymes are well documented in the literature, there has been little investigation of reactions with EDC mixtures. This makes it impossible to predict how enzyme-mediated treatment systems will perform since wastewater effluents generally contain multiple EDCs. This paper reports pseudo-first order rate constants for a model oxidative enzyme, horseradish peroxidase (HRP), during single-substrate (k₁) and mixed-substrate (k_1-MIX) reactions. Measured values are compared with literature values of three Michaelis-Menten parameters: half-saturation constant (K_M), enzyme turnover number (k_CAT), and the ratio k_CAT/K_M. Published reports had suggested that each of these could be correlated with HRP reactivity towards EDCs in mixtures, and empirical results from this study show that K_M can be used to predict the sequence of EDC removal reactions within a particular mixture. We also observed that k_1-MIX values were generally greater than k₁ values and that compounds exhibiting greatest estrogenic toxicities reacted most rapidly in a given mixture. Finally, because K_M may be tedious to measure for every EDC of interest, we have constructed a quantitative structure-activity relationship (QSAR) model to predict these values. This model predicts K_M quite accurately (R² = 89%) based on two molecular characteristics: molecular volume and hydration energy. Its accuracy makes this QSAR a useful tool for predicting which EDCs will be removed most efficiently during enzyme treatment of EDC mixtures.     

Fate and transport of atorvastatin and simvastatin drugs during conventional wastewater treatment

This research investigates the environmental behavior of two widely prescribed cholesterol-lowering statin drugs that are expected to be present at significant concentrations in wastewater influents, namely: atorvastatin and simvastatin. Batch biodegradation experiments suggest that both statins are well degraded during secondary treatment, and removal rates exhibit a substrate-enhancement model reflecting elements of both first-order behavior and cometabolism. Resulting biodegradation parameters are used in conjunction with literature sorption parameters to construct a mass-balance model of statin concentrations during conventional treatment. Model results exhibit excellent accuracy compared to measurements from a medium-sized WWTP in the Southeastern USA. Influent concentrations of 1.56 μg L(-1) and 1.23 μg L(-1) were measured for atorvastatin and simvastatin. Results also suggest that 85-90% of each drug is removed during conventional treatment, with sorption accounting for less than 10% of overall removal. Expected effluent concentrations are orders of magnitude less than previously reported ecotoxicity thresholds for both drugs. Overall, results suggest statin active ingredients do not pose a significant environmental threat. It is recommended that future work characterize the fate of statin metabolites and that the same mass-balance modeling approach be used to assess other highly-prescribed pharmaceutical drugs.     

Predicting EDC concentrations in a river mixing zone

The fate and transport of endocrine disrupting chemicals (EDCs) in ambient river waters is a major concern associated with effluents from municipal wastewater treatment plants (WWTPs). This paper presents a methodology for quantifying the spatial distribution of EDCs in a river mixing zone. The core of the technical analysis is based on a two-dimensional steady-state analytical model characterized by ambient turbulence in the receiving water. This model was first calibrated with mass transport data from field measurements for a conservative substance (electrical conductivity) and then used to predict aqueous-phase EDC concentrations throughout a WWTP mixing zone. To demonstrate the usefulness of this methodology for water quality management purposes, the modeling framework presented in this paper was used to determine a lumped in-stream attenuation rate constant (k_d = 3 d⁻¹) for 17β-estradiol under natural conditions. This rate constant likely accounts for the combined contributions of physical sorption, photolysis, microbial and chemical degradation, and the measured value is highly consistent with previously published results from bench-scale removal experiments.