PNEC

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. Further- more, 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.

Mixture toxicity is a real world problem and as such requires risk assessment solutions that can be applied within different geographic regions, across different spatial scales and in situations where the quantity of data available for the assessment varies. Moreover, the need for site specific procedures for assessing ecotoxicological risk for non-target species in non-target ecosystems also has to be recognised. The work presented in the paper addresses the real world effects of pesticide mixtures on natural communities. Initially, the location of risk hotspots is theoretically estimated through exposure modelling and the use of available toxicity data to predict potential community effects. The concept of Concentration Addition (CA) is applied to describe responses resulting from exposure of multiple pesticides The developed and refined exposure models are georeferenced (GIS-based) and include environmental and physico-chemical parameters, and site specific information on pesticide usage and land use. As a test of the risk assessment framework, the procedures have been applied on a suitable study areas, notably the River Meolo basin (Northern Italy), a catchment characterised by intensive agriculture, as well as comparative area for some assessments. Within the studied areas, the risks for individual chemicals and complex mixtures have been assessed on aquatic and terrestrial aboveground and belowground communities. Results from ecological surveys have been used to validate these risk assessment model predictions. Value and limitation of the approaches are described and the possibilities for larger scale applications in risk assessment are also discussed.