Elucidating biotransformation pathways of ofloxacin in lettuce (Lactuca sativa L)

Emerging contaminants, such as antibiotics, pharmaceuticals, personal care products, hormones, and artificial sweeteners, are recognized as new classes of water contaminants due to their proven or potential adverse effects on aquatic ecosystems and human health. This review provides comprehensive data on the occurrence of 60 emerging contaminants (ECs) in influent, treated effluent, sludge, and biosolids in wastewater treatment plants (WWTPs). In particular, data on the occurrence of ECs in the influents and effluents of WWTPs are systematically summarized and categorized according to geographical regions (Asia, Europe, and North America). The occurrence patterns of ECs in raw influent and treated effluents of WWTPs between geographical regions were compared and evaluated. Concentrations of most ECs in raw influent in Asian region tend to be higher than those in European and North American countries. Many antibiotics were detected in the influents and effluents of WWTPs at concentrations close to or exceeding the predicted no-effect concentrations (PNECs) for resistance selection. The efficacy of EC removal by sorption and biodegradation during wastewater treatment processes are discussed in light of kinetics and parameters, such as sorption coefficients (Kd) and biodegradation constants (kbiol), and physicochemical properties (i.e. log Kowand pKa). Commonly used sampling and monitoring strategies are critically reviewed. Analytical research needs are identified, and novel investigative approaches for future monitoring studies are proposed.

There are concerns that selection pressure from antibiotics in the environment may accelerate the evolution and dissemination of antibiotic-resistant pathogens. Nevertheless, there is currently no regulatory system that takes such risks into account. In part, this is due to limited knowledge of environmental concentrations that might exert selection for resistant bacteria. To experimentally determine minimal selective concentrations in complex microbial ecosystems for all antibiotics would involve considerable effort. In this work, our aim was to estimate upper boundaries for selective concentrations for all common antibiotics, based on the assumption that selective concentrations a priori need to be lower than those completely inhibiting growth. Data on Minimal Inhibitory Concentrations (MICs) were obtained for 111 antibiotics from the public EUCAST database. The 1% lowest observed MICs were identified, and to compensate for limited species coverage, predicted lowest MICs adjusted for the number of tested species were extrapolated through modeling. Predicted No Effect Concentrations (PNECs) for resistance selection were then assessed using an assessment factor of 10 to account for differences between MICs and minimal selective concentrations. The resulting PNECs ranged from 8 ng/L to 64 μg/L. Furthermore, the link between taxonomic similarity between species and lowest MIC was weak. This work provides estimated upper boundaries for selective concentrations (lowest MICs) and PNECs for resistance selection for all common antibiotics. In most cases, PNECs for selection of resistance were below available PNECs for ecotoxicological effects. The generated PNECs can guide implementation of compound-specific emission limits that take into account risks for resistance promotion.