Response surface optimised photocatalytic degradation and quantitation of repurposed COVID-19 antibiotic pollutants in wastewaters; towards greenness and whiteness perspectives

Abstract

Environmental context: The consumption of repurposed antibiotics increased due to the management of COVID-19, which in turn led to their increased presence in wastewater and potential environmental effects. This change has created a greater need for their analysis and treatment in different environmental water. This work presents a safe, low-cost method for analysing and treating water samples to ensure their suitability for human and animal use.

Rationale: Certain antibiotics have been repurposed for the management of infected COVID-19 cases, because of their possible effect against the virus, and treatment of co-existing bacterial infection. The consumption of these antibiotics leads to their access to sewage, industrial and hospital effluents, then to environmental waters. This creates a need for the routine analysis and treatment of water resources.

Methodology: Detection and quantitation of three repurposed antibiotics: levofloxacin (LEVO), azithromycin (AZI) and ceftriaxone (CEF) were studied in different water samples using LC-MS/MS methods employing a C18 column and a mobile phase consisting of 80% acetonitrile/20% (0.1% formic acid in water) after solid phase extraction on Oasis HLB Prime cartridges. Real water samples were treated with synthesised graphitic carbon nitride (g-C3N4) to remove the three types of antibiotics from contaminated water under experimental conditions optimised by response surface methodology, using Box–Behnken experimental design.

Results: The analytical method was validated in the concentration range of 10–5000 ng mL–1 for the three drugs. The removal percentages were found to be 92.55, 98.48 and 99.10% for LEVO, AZI and CEF, respectively, using synthesised g-C3N4.

Discussion: The analytical method was used for the estimation of the three cited drugs before and after their removal. The method was assessed using ComplexGAPI as a greenness tool and the RGB 12 algorithm as a whiteness model. The method was applied for the analysis and treatment of real water samples before and after their treatment. It proved to be simple, low-cost and environmentally sustainable.