Removal and biodegradation of the pharmaceutical pollutant cortisone acetate by Scenedesmus obtusus under varying salinity conditions

Pharmaceutical contaminants such as cortisone acetate pose a significant environmental challenge due to their persistence in aquatic systems and the limited effectiveness of conventional wastewater treatment processes. This study evaluated the potential of the microalga Scenedesmus obtusus for the removal and biodegradation of cortisone acetate under varying salinity, pH, and exposure time conditions. An artificial neural network model (ANN) was developed to predict system performance, and a genetic algorithm (GA) was subsequently applied to this model to identify optimal operational parameters, which confirming the influence of environmental factors on treatment efficiency. Under optimized conditions obtained by GA (zero salinity, pH 7, and a 10-day retention period), the model predicted a cortisone acetate removal efficiency of 96.18%, which closely matched the experimentally observed removal efficiency of 97.68%. Additionally, liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis identified several degradation byproducts, consistent with possible biotransformation of cortisone acetate rather than simple retention in algal biomass. Moreover, monitoring of chlorophyll a and b levels indicated increased photosynthetic activity and sustained biomass accumulation throughout the experiment, supporting effective pollutant removal. Scanning electron microscopy further revealed structural changes in the microalgal cells after treatment, including surface roughening and pore formation, consistent with cellular stress responses associated with pollutant exposure. These findings confirm the potential of Scenedesmus obtusus as a sustainable and efficient bioremediation agent for pharmaceutical pollutants in aquatic environments.