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Updated: Nov 29, 2025

Mesocosm-Scale Constructed Wetland Design for Wastewater Treatment
Published on: May 2, 2025
Assessing the efficiency of constructed wetlands in removing PPCPs from treated wastewater and mitigating the
Mohamed Bayati1, Thi L Ho2, Danh C Vu3
1Center for Agroforestry, University of Missouri-Columbia, USA; Department of Civil and Environmental Engineering, University of Missouri-Columbia, USA; Department of Environmental Engineering, Tikrit University, Iraq.
Abstract:
The prevalence of pharmaceuticals and personal care products (PPCPs) in municipal wastewater has led to increased concerns about their impact on both human health and ecosystem. The constructed wetlands have been recognized as one of the cost-effective and green mitigation approaches to remove the PPCPs in the municipal wastewater. In this study, the effectiveness of a full scale constructed wetlands treatment system (CCWTs) in removing the 36 PPCPs was investigated. The load mass of PPCPs discharged by the wastewater treatment plant into the CCWTs was calculated. Removal efficiencies of PPCPs were evaluated based on physico-chemical properties such as octanol-water partition coefficient (Log kow), molecular weight (MW, g mol-1) and the acid dissociation constant (pKa). The CCWTs are especially efficient in removing azithromycin, sertraline, tolfenamic acid, and diphenhydramine with removing efficiency >88%. However, the removal efficiencies of PPCPs in CCWTs exhibit a large variability, depending on physical and chemical properties of the molecules, with 4.7-96.7% for antibiotics, 5-86% for antidepressant and antiseizure drugs, 3.5-88% for NSAIDs, 29-77% for β-blockers and statins and 5.5-94% for other types of PPCPs. In addition, the environmental risk assessment showed that majority of the PPCPs (excluding sulfamethoxazole) in the effluent yielded low aquatic risk (risk quotient, RQ ≤ 0.1) due to the efficiency of CCWTs. The toxicity index scores were calculated by integration of the predicted and available toxicological hazard data into the prioritization ranking algorithm through Toxicological Prioritization Index (ToxPi).
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