Separation of Pharmaceutical residues from wastewater

Abstract

Pharmaceutical residues in wastewater threaten both aquatic ecosystems and human health. Approximately 80 % of the wastewater produced worldwide is discharged into the environment without treatment, and 26 % of 258 rivers surveyed in
104 countries have API levels that exceed safe limits, making advanced treatment urgently needed. Herein, three major
separation methods for degrading or removing pharmaceutical pollutants are reviewed: Fenton oxidation, adsorption, and
electrochemical oxidation. Under optimum conditions, reported efficiencies range from 74 % to 100 %; however, their
efficacy usually declines under fluctuating pH and ionic strength and other complex wastewater matrices.

Each of these processes offers trade-offs in scalability, cost, and energy demand; full-scale implementation is further limited
by such issues as sludge formation, adsorbent regeneration, and by-product toxicity. More recently, the integration of machine learning and physics-informed hybrid models has been shown to improve predictive accuracy and operational optimization
over conventional kinetic approaches. The paper concludes by recommending AI-driven frameworks and immersive
visualization for adaptive control of wastewater treatment systems that ensure sustainable, cost-effective, and data-transparent removal of pharmaceutical residues in concert with global water-quality and sustainable development goals.