Urban water systems receive and emit antimicrobial chemicals, resistant bacterial strains, and resistance genes (ARGs), thus representing "antimicrobial hotspots". Currently, regional environmental risk assessment (ERA) is carried out using drug consumption data and threshold concentrations derived based on chemical-specific minimum inhibitory concentration values. A legislative proposal by the European Commission released in 2022 addresses the need to include selected ARGs besides the chemical concentration-based ERAs. The questions arise as to (A) how to improve chemical concentration-based risk assessment and (B) how to integrate resistome-related information with chemical-based risk - the main focal areas of this study. A tiered chemical risk prediction method is proposed by considering effluents of sewer networks and water resource recovery facilities (WRRFs). To improve predicted environmental concentrations (PEC in recipient water bodies), the impact of antimicrobial bio- and re-transformation in WRRFs is assessed using reliable global data. To combine chemical and genetic risks, a new parameter, i.e., the gene response efficiency (GRE) is proposed. A regression analysis show four orders of magnitude differences in GRE values amongst the seven antimicrobial classes studied. Higher GRE values in wastewater are obtained for antimicrobials with relatively low consumption rate levels.
Keywords: Antimicrobial chemicals; Antimicrobial resistance; Environmental risk assessment; Modelling.
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