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Environmental risk assessment of antibiotics: comparison of mecillinam, trimethoprim and ciprofloxacin

Halling-Sorensen, B.·2000·Journal of Antimicrobial Chemotherapy

Abstract

The effects of mecillinam, trimethoprim and ciprofloxacin, antibiotics used in the treatment of urinary tract infections, on the aquatic environment were assessed. Mecillinam and ciprofloxacin were both readily biodegradable (primary degradation) in activated sludge, whereas trimethoprim persisted. The toxicity of these antibiotics towards sludge bacteria, a green alga, a cyanobacterium, a crustacean and a fish were investigated; both mecillinam and ciprofloxacin were highly toxic to the cyanobacterium Microcystis aeruginosa (EC50 in the range 5–60 Ìg/L). Risk characterization for the aquatic environment was performed for the three compounds by calculating the predicted environmental concentration (PEC) and the predicted no-effects concentration (PNEC). A PEC/PNEC ratio of <1 indicates that, with the present pattern of use, no environmental risk is expected. PEC/PNEC ratios of <1 for present usage in Europe were found for mecillinam and trimethoprim whereas a PEC/PNEC ratio >1 was found for ciprofloxacin.

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Metadata

Authors
Halling-Sorensen, B.
Venue
Journal of Antimicrobial Chemotherapy
Published
2000-08-01
Volume
46
Issue
90001
Pages
53-58
ISSN
  • 0305-7453 (ISSN-L)
  • 1460-2091
OpenAlex
W4366736487
Cited by
333
References
0
FWCI
3.15
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Environmental risk assessment of antibiotics: comparison of mecillinam, trimethoprim and ciprofloxacin. https://app.cochat.ai/papers/10.1093/jac/46.suppl_1.53
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Halling-Sorensen, B. (2000). Environmental risk assessment of antibiotics: comparison of mecillinam, trimethoprim and ciprofloxacin. Journal of Antimicrobial Chemotherapy. https://doi.org/10.1093/jac/46.suppl_1.53

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.