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An approach for deriving water quality guideline values for antimicrobials that integrates ecotoxicity and antimicrobial resistance endpoints

Integrated Environmental Assessment and Management 2025
Monique T. Binet, Graeme E. Batley, Jennifer L. Stauber, Anupama Kumar, Hsuan-Cheng Lu, Nicholas J. Ashbolt

Summary

Researchers developed an approach for setting water quality guideline values for antimicrobials in Australia and New Zealand that integrates both direct ecotoxicity endpoints and antimicrobial resistance endpoints, addressing a gap in current frameworks that do not account for resistance-promoting environmental concentrations.

Study Type Environmental

Antimicrobials pose ecological risks in aquatic environments, particularly to cyanobacteria, aquatic plants and green algae, and with the potential to disrupt microbiomes upon which all biota rely. Beyond direct toxicity, these chemicals also contribute to the emergence and spread of antimicrobial resistance, posing risks to human, animal (including wildlife) and plant crop health, particularly through wastewater discharges and water reuse. Despite these concerns, Australia and New Zealand currently lack environmental water quality guideline values for antimicrobials. Furthermore, existing guideline value derivation frameworks for this region do not consider environmental endpoints to protect against antimicrobial resistance. This study critically reviews international approaches to estimating antimicrobial hazards to identify possible improvements for use in Australia and New Zealand. Through a co-design process with stakeholders across the water sector, a method for deriving guideline values using species sensitivity distributions was developed that integrates both traditional toxicity and antimicrobial resistance endpoints. Critically, the approach includes microbiome data, essential for capturing the impacts of antimicrobials on complex aquatic microbial communities. A case study with ciprofloxacin demonstrated that combining microbiome and single-species data in species sensitivity distributions provides a scientifically robust and data-efficient approach for developing environmental guideline values for antimicrobials. The framework may also have applicability to other contaminants known to influence antimicrobial resistance, such as other pharmaceuticals, metals, pesticides and microplastics. We also identified critical gaps that remain barriers to implementing antimicrobial resistance-inclusive frameworks for deriving water quality guideline values applicable to Australia and New Zealand.

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