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EAPSI: Studying advanced treatment methods for removal of pharmaceuticals from sewage effluent

$5,070FY2014O/DNSF

West Danielle M, Rolla MO

Investigators

Abstract

The abundance of pharmaceuticals found in natural water sources has increased as their applications and production has increased. In the environment, pharmaceuticals have the potential to be toxic, increase microbial resistance, and yield other unforeseen environmental adverse effects. Effluents of municipal sewage treatment plants represent a major pollution source of pharmaceuticals in the environment. Therefore, it is of utmost importance to study different advanced treatment methods to further remove pharmaceuticals in sewage effluent. In collaboration with Dr. Zhimin Qiang, an expert in wastewater research at the Chinese Academy of Sciences, this study will determine the most applicable method to remove typical pharmaceuticals from sewage effluent by advanced treatment processes. The toxicity, microbial resistance, and unforeseen adverse effects in the environment, induced by pharmaceuticals, necessitate a comprehensive study of abatement, degradation pathways, and toxicity changes of each target pollutant during advanced oxidation processes (AOPs). The selected AOPs include three O3-based and UV-based (e.g. O3/H2O2, UV/O3, and UV/H2O2) technologies, which have great potentials to effectively remove pharmaceuticals from sewage effluent. Six frequently detected pharmaceuticals in sewage effluent, including sulfadiazine (SDZ), sulfamethoxazole (SMX), trimethoprim (TMP), metoprolol (MET), roxithromycin (ROX), and caffeine (CAF), will be selected for this study. The abatement of these pharmaceuticals by the AOPs will be studied, along with their degradation byproducts identified by liquid chromatography time-of-flight mass spectrometry (LC/Q-TOF-MS) to propose degradation pathways. In addition, this project will evaluate the pollutant removal efficiency, energy consumption, and operation factors of the different AOPs, to determine the most applicable method. This NSF EAPSI award is funded in collaboration with the Chinese Ministry of Science and Technology.

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