Geo-referenced simulations of E. coli in a sub-catchment of the Vecht River using a probabilistic approach.

The proportion of wild swimmers at non-official bathing sites has increased during the Covid-19 pandemic. Bathing water quality at designated sites is monitored through analysis of the concentration of fecal indicator bacteria such as E. coli. However, non-official sites are generally not monitored. In a previous work, steady state modelling of E. coli was achieved at catchment scale, enabling a comparison of expected concentrations along an entire catchment for longtime average. However, E. coli concentrations can vary over several orders of magnitude at the same monitoring site throughout the year. To capture the temporal variability of E. coli concentrations on the catchment scale, we extended the existing deterministic E. coli sub-module of the GREAT-ER (Geo-referenced Exposure Assessment tool for European Rivers) model for probabilistic Monte-Carlo simulations. Here, selected model parameters are represented by probability distributions instead of fixed values. Wastewater treatment plant (WWTP) emissions and diffuse emissions were parameterized using selected data from a previous monitoring campaign (calibration data set) and in-stream processes were modeled using literature data. Comparison of simulation results with monitoring data (evaluation data set) indicates that predicted E. coli concentrations well-represent median measured concentrations, although the range of predicted concentrations is slightly larger than the observed concentration variability. The parameters with the largest influence on the range of predicted concentrations are flow rate and E. coli removal efficiency in WWTPs. A comparison of predicted 90th percentiles with the threshold for sufficient bathing water quality (according to the EU Bathing Water Directive) indicates that year-round swimming at sites influenced by WWTP effluents is advisable almost nowhere in the study area. A refinement of the model can be achieved if quantitative relationships between the WWTP removal efficiency and both, the treatment technologies as well as the operating parameters are further established.

(Antibiotic-Resistant) E. coli in the Dutch-German Vecht Catchment─Monitoring and Modeling.

Fecally contaminated waters can be a source for human infections. We investigated the occurrence of fecal indicator bacteria (E. coli) and antibiotic-resistant E. coli, namely, extended spectrum beta-lactamase (ESBL)-producing E. coli (ESBL-EC) and carbapenemase-producing E. coli (CP-EC) in the Dutch-German transboundary catchment of the Vecht River. Over the course of one year, bacterial concentrations were monitored in wastewater treatment plant (WWTP) influents and effluents and in surface waters with and without WWTP influence. Subsequently, the GREAT-ER model was adopted for the prediction of (antibiotic-resistant) E. coli concentrations. The model was parametrized and evaluated for two distinct scenarios (average flow scenario, dry summer scenario). Statistical analysis of WWTP monitoring data revealed a significantly higher (factor 2) proportion of ESBL-EC among E. coli in German compared to Dutch WWTPs. CP-EC were present in 43% of influent samples. The modeling approach yielded spatially accurate descriptions of microbial concentrations for the average flow scenario. Predicted E. coli concentrations exceed the threshold value of the Bathing Water Directive for a good bathing water quality at less than 10% of potential swimming sites in both scenarios. During a single swimming event up to 61 CFU of ESBL-EC and less than 1 CFU of CP-EC could be taken up by ingestion.

Ecological Risk Assessment of Pharmaceuticals in the Transboundary Vecht River (Germany and The Netherlands).

Millions of people rely on active pharmaceutical ingredients (APIs) to prevent and cure a wide variety of illnesses in humans and animals, which has led to a steadily increasing consumption of APIs across the globe and concurrent releases of APIs into the environment. In the environment, APIs can have a detrimental impact on wildlife, particularly aquatic wildlife. Therefore, it is essential to assess their potential adverse effects to aquatic ecosystems. The European Water Framework Directive sets out that risk assessment should be performed at the catchment level, crossing borders where needed. The present study defines ecological risk profiles for surface water concentrations of 8 APIs (carbamazepine, ciprofloxacin, cyclophosphamide, diclofenac, erythromycin, 17α-ethinylestradiol, metformin, and metoprolol) in the Vecht River, a transboundary river that crosses several German and Dutch regions. Ultimately, 3 main goals were achieved: 1) the geo-referenced estimation of API concentrations in surface water using the geography-referenced regional exposure assessment tool for European rivers; 2) the derivation of new predicted-no-effect concentrations for 7 of the studied APIs, of which 3 were lower than previously derived values; and 3) the creation of detailed spatially explicit ecological risk profiles of APIs under 2 distinct water flow scenarios. Under average flow conditions, carbamazepine, diclofenac, and 17α-ethinylestradiol were systematically estimated to surpass safe ecological concentration thresholds in at least 68% of the catchment's water volume. This increases to 98% under dry summer conditions. Environ Toxicol Chem 2022;41:648-662. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

An integrated modelling approach to derive the grey water footprint of veterinary antibiotics.

Water pollution by veterinary antibiotics (VAs) resulting from livestock production is associated with severe environmental and human health risks. While upward trends in global animal product consumption signal that these risks might exacerbate toward the future, VA related water pollution is currently insufficiently understood. To increase this understanding, the present research assesses processes influencing VA pollution from VA administration to their discharge into freshwater bodies, using an integrated modelling approach (IMA). For the VAs amoxicillin, doxycycline, oxytetracycline, sulfamethazine, and tetracycline we estimate loads administered to livestock, excretion, degradation during manure storage, fate in soil and transport to surface water. Fate and transport are modelled using the VA transport model (VANTOM), which is fed with estimates from the Pan-European Soil Erosion Risk Assessment (PESERA). The grey water footprint (GWF) is used to indicate the severity of water pollution in volumetric terms by combining VA loads and predicted no effect concentrations. We apply our approach to the German-Dutch Vecht river catchment, which is characterized by high livestock densities. Results show a VA mass load decrease larger than 99% for all substances under investigation, from their administration to surface water emission. Due to metabolization in the body, degradation during manure storage and degradation in soil, VA loads are reduced by 45%, 80% and 90% on average, respectively. While amoxicillin and sulfamethazine dissipate quickly after field application, significant fractions of doxycycline, oxytetracycline and tetracycline accumulate in the soil. The overall Vecht catchment's GWF is estimated at 250,000 m3 yr-1, resulting from doxycycline (81% and 19% contribution from the German and Dutch catchment part respectively). Uncertainty ranges of several orders of magnitude, as well as several remaining limitations to the presented IMA, underscore the importance to further develop and refine the approach.

Geo-referenced simulation of pharmaceuticals in whole watersheds: application of GREAT-ER 4.1 in Germany.

The geo-referenced regional exposure assessment tool for European rivers (GREAT-ER) is designed to support river basin management or the implementation process within the EU Water Framework Directive by predicting spatially resolved exposure concentrations in whole watersheds. The usefulness of the complimentary application of targeted monitoring and GREAT-ER simulations is demonstrated with case studies for three pharmaceuticals in selected German watersheds. Comparison with monitoring data corroborates the capability of the probabilistic model approach to predict the expected range of spatial surface water concentrations. Explicit consideration of local pharmaceutical emissions from hospitals or private doctor's offices (e.g., for X-ray contrast agents) can improve predictions on the local scale without compromising regional exposure assessment. Pharmaceuticals exhibiting low concentrations hardly detectable with established analytical methods (e.g., EE2) can be evaluated with model simulations. Management scenarios allow for a priori assessment of risk reduction measures. In combination with targeted monitoring approaches, the GREAT-ER model can serve as valuable support tool for exposure and risk assessment of pharmaceuticals in whole watersheds.

The grey water footprint of human and veterinary pharmaceuticals.

Water pollution by pharmaceuticals is widespread, causing both environmental and human health risks. We assess pharmaceutical water pollution from human and veterinary pharmaceuticals at three geographical levels: global, national (considering Germany and the Netherlands) and catchment level (with a case study for the Vecht catchment shared by Germany and the Netherlands). The grey water footprint (GWF), a measure of water pollution in volumetric terms, is estimated from pharmaceutical loads entering the aquatic environment, considering different pollutant sources and pathways. We study different substances depending on data availability, which varies across geographical levels. Results show a global per capita GWF of 1900 m3 yr-1 resulting from human consumption of ciprofloxacin. The largest GWFs in both Germany and the Netherlands were found for ethinylestradiol for human and amoxicillin for veterinary use. The estimated per capita GWF from human use of ethinylestradiol is 2300 m3 yr-1 for Germany and 11,300 m3 yr-1 for the Netherlands. The per capita GWFs of German and Dutch consumers of animal products are 12,900 and 10,600 m3 yr-1, respectively. For the Vecht catchment, we estimate the water pollution level per sub-catchment by comparing the GWF to available runoff, which enables us to identify geographic hotspots. In the basin as a whole, GWFs from human and veterinary pharmaceuticals both exceed available runoff. At all levels, pharmaceutical water pollution substantially adds to earlier water footprint studies that excluded this type of pollution, which demonstrates the importance to include pharmaceutics in water footprint studies.