Study of the green microalga Chlorella sorokiniana for the removal of nutrients and multiple antibiotics in wastewater treatment.

Obtaining clean water is a global priority, as emphasized by the United Nations Sustainable Development Goal 6, which aims to ensure availability and sustainable management of water and sanitation for all. Pharmaceutical pollutants are becoming more prevalent in aquatic environments, triggering public health concerns, negative environmental impacts, and the development of antibiotic resistance. Microalgae hold great potential for bioremediation of antibiotics, although most of the studies to date supporting these observations rely on conditions where artificial wastewater contained one or a few antibiotics. In this study, Chlorella sorokiniana was used to assess the removal of a mixture of 10 antibiotics selected and tested considering environmentally relevant antibiotic concentrations based on data from the National Health Service (United Kingdom). The selected antibiotics had a risk quotient > 1 as calculated by the ratio of predicted environmental concentration (PEC) to predicted no effect concentration. The experimental antibiotic concentration tested for each antibiotic corresponded to their PEC values. After 19 days of incubation, the β-lactam class (amoxicillin, penicillin V, cephalexin) showed the highest percentage of removal (51-85), followed by trimethoprim (24), oxytetracycline (6), metronidazole (6), and sulfamethoxazole (2). Different mechanisms, that is, biodegradation, photodegradation, bioadsorption, and bioaccumulation, were involved at variable range. Increase in algal biomass was observed concomitantly to decrease in the concentration of the tested antibiotics, suggesting their use as a carbon source for cellular growth. In addition, levels of dissolved ammonium, nitrate, phosphate, and chemical oxygen demand, decreased by 88%, 22%, 100%, and 10%, respectively. Our study confirmed the ability of C. sorokiniana to biodegrade antibiotics while also effectively reducing key nutrient loadings.