Systematically testing alternative cleaning agents and cleaning procedures on a large scale municipal membrane bioreactor, the Erftverband optimized the cleaning strategies and refined the original cleaning procedures for the hollow fiber membranes in use. A time-consuming, intensive ex-situ membrane cleaning twice a year was initially the regular routine. By introducing the effective means of cleaning in place in use today, which employs several acidic and oxidative/alkaline cleaning steps, intensive membrane cleaning could be delayed for years. An overview and an assessment of various cleaning strategies for large scale plants are given.

Endocrine-active substances can adversely impact the aquatic ecosystems. A special emphasis is laid, among others, on the effects of estrogens and estrogen mimicking compounds. Effect-based screening methods like in vitro bioassays are suitable tools to detect and quantify endocrine activities of known and unknown mixtures. This study describes the validation of the Arxula-Yeast Estrogen Screen (A-YES®) assay, an effect-based method for the detection of the estrogenic potential of water and waste water. This reporter gene assay, provided in ready to use format, is based on the activation of the human estrogen receptor alpha. The user-friendly A-YES® enables inexperienced operators to rapidly become competent with the assay. Fourteen laboratories from four countries with different training levels analyzed 17β-estradiol equivalent concentrations (EEQ) in spiked and unspiked waste water effluent and surface water samples, in waste water influent and spiked salt water samples and in a mixture of three bisphenols. The limit of detection (LOD) for untreated samples was 1.8ng/L 17β-estradiol (E2). Relative repeatability and reproducibility standard deviation for samples with EEQ above the LOD (mean EEQ values between 6.3 and 20.4ng/L) ranged from 7.5 to 21.4% and 16.6 to 28.0%, respectively. Precision results are comparable to other frequently used analytical methods for estrogens. The A-YES® has been demonstrated to be an accurate, precise and robust bioassay. The results have been included in the ISO draft standard. The assay was shown to be applicable for testing of typical waste water influent, effluent and saline water. Other studies have shown that the assay can be used with enriched samples, which lower the LOD to the pg/L range. The validation of the A-YES® and the development of a corresponding international standard constitute a step further towards harmonized and reliable bioassays for the effect-based analysis of estrogens and estrogen-like compounds in water samples.

Background: A vast number of chemical substances are released into the aquatic environment, leading to complex chemical mixtures in surface waters. Current water quality assessments, however, are based on the risk assessment of single substances. To consider potential mixture effects in water quality assessments, the North Rhine Westphalian State Agency for Nature, Environment and Consumer Protection (LANUV), Germany started a project assessing mixture toxicity in surface waters. This article summarises the mixture evaluation of chemical data collected by the Erftverband during a water sampling campaign in the Erft River in 2016/2017. Altogether, 153 substances were included in the analysis, of which 98 were detected. Two different approaches based on the concept of concentration addition were used to analyse the data. The results were compared to findings based on datasets from LANUV surveillance monitoring according to the EU Water Framework Directive. Results: Acute and chronic mixture risk calculations indicated risks for 32% and up to 90% of the samples, respectively. The greatest acute toxic pressure was identified for the aquatic flora due to continuous exposure to varying pesticides, whereas the greatest chronic mixture risk was identified for fish as result of a ubiquitous presence of the pharmaceuticals diclofenac and ibuprofen. Overall, only a limited number of substances significantly contributed to the calculated mixture risks. However, these substances varied seasonally and regionally. When mixture risks were calculated based on different datasets, the monitoring design markedly affected the outcome of the mixture risk assessment. Data gaps of both ecotoxicological and exposure data lead to high uncertainties in the mixture risk assessment. Conclusions: Ecotoxicological effects on aquatic organisms caused by chemical mixtures can be expected along the Erft River throughout the year. Both mixture risk assessment approaches can be used for a conservative assessment of mixture risks and characterise the aquatic pollution in the river more realistically than single substance assessments. For the integration of mixture risk evaluations into the assessment and management of the chemical water quality, a two-staged assessment combining both approaches is suggested. To improve future risk assessments, the accessibility and exchange of high-quality ecotoxicological data should be enhanced.