Abstract
Recently, estrogen has attracted widespread concern because it is increasing being detected in wastewater treatment plants. While techniques for estrogen removal have been reported, these have mostly focused on exploring the effect on removal using simple single-factor experiments, rather than applying more complex multifactor mathematical models to wastewater treatment. In this study, reduced graphene oxide-based iron nanoparticles (rGO@Fe NPs) were used for 17α-estradiol (αE2) removal based on adsorption and Fenton oxidation. A response surface methodology, based on a Box-Behnken design, was used to determine the relationships between critical operation factors (pH, temperature, αE2 concentration, rGO@Fe NPs dose and H2O2 concentration) and removal efficiency to establish the optimal conditions for 1 mg L−1 αE2 removal. Under the determined optimal reaction condition of pH 6.0, temperature 40 °C, 0.08 g L−1 rGO@Fe NPs dose and 6 mM H2O2, a maximum removal efficiency of 99.9% was obtained. Subsequently, the presence of co-existing anions (Cl−, SO42− and NO3−) significantly decreased the removal efficiency of αE2. However, αE2 removal from domestic wastewater could be increased by 38.0% when applying RSM results. Moreover, αE2 removal by rGO@Fe NPs remained stable over five reuse cycles indicating that rGO@Fe NPs would be an efficient and practical advanced materials for αE2 removal.
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