As a consequence of growing public concern about UV radiation effects on human health chemical and physical UV filters are increasingly used in personal care and other products. The release of these lipophilic and often persistent compounds into surface waters may pose a risk for aquatic organisms. The aim of the study was to determine effects of four frequently used UV filters on primary aquatic producers and consumers, the green alga Desmodesmus subspicatus and the crustacean Daphnia magna. Exposure to benzophenone 3 (BP3), ethylhexyl methoxycinnamate (EHMC), 3-benzylidene camphor (3-BC) and 3-(4'-methylbenzylidene)-camphor (4-MBC) resulted in growth inhibition of D. subspicatus with 72 h IC(10) values of 0.56 mg/L (BP 3), 0.24 mg/L (EHMC), 0.27 mg/L (3-BC) and 0.21 mg/L (4-MBC). EC(50) concentrations in the acute test with D. magna were 1.67, 0.57, 3.61 and 0.80 mg/L for BP3, EHMC, 3-BC and 4-MBC, respectively. Chronic exposure of D. magna resulted in NOECs of 0.04 mg/L (EHMC) and 0.1 mg/L (3-BC and 4-MBC). BP 3 showed no effects on neonate production or the length of adults. Rapid dissipation of these substances from the water phase was observed indicating the need for more frequent test medium renewal in chronic tests or the use of flow-through test systems.

Endocrine-disrupting chemicals are mainly discharged into the environment by wastewater treatment plants (WWTPs) and are known to induce adverse effects in aquatic life. Advanced treatment with ozone successfully removes such organic micropollutants, but an increase of estrogenic effects after the ozonation of hospital wastewater was observed in previous studies. In order to investigate this effect, estrogenic and androgenic as well as anti-estrogenic and anti-androgenic activities were observed during treatment of hospital wastewater using three different effect-based reporter gene bioassays. Despite different matrix influences, sensitivities, and test-specific properties, all assays used obtained comparable results. Estrogenic and androgenic activities were mainly reduced during the biological treatment and further removed during ozonation and sand filtration, resulting in non-detectable agonistic activities in the final effluent. An increased estrogenic activity after ozonation could not be observed in this study. Antagonistic effects were removed in the biological treatment by up to 50 % without further reduction in the advanced treatment. Due to the presence of antagonistic substances within the wastewater, masking effects were probable. Therefore, this study showed the relevance of antagonistic activities at hospital WWTPs and illustrates the need for a better understanding about antagonistic effects.

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Bio-equivalents (e.g., 17β-estradiol or dioxin equivalents) are commonly employed to quantify the in vitro effects of complex human or environmental samples. However, there is no generally accepted data analysis strategy for estimating and reporting bio-equivalents. Therefore, the aims of the present study are to 1) identify common mathematical models for the derivation of bio-equivalents from the literature, 2) assess the ability of those models to correctly predict bio-equivalents, and 3) propose measures to reduce uncertainty in their calculation and reporting. We compiled a database of 234 publications that report bio-equivalents. From the database, we extracted 3 data analysis strategies commonly used to estimate bio-equivalents. These models are based on linear or nonlinear interpolation, and the comparison of effect concentrations (ECX ). To assess their accuracy, we employed simulated data sets in different scenarios. The results indicate that all models lead to a considerable misestimation of bio-equivalents if certain mathematical assumptions (e.g., goodness of fit, parallelism of dose-response curves) are violated. However, nonlinear interpolation is most suitable to predict bio-equivalents from single-point estimates. Regardless of the model, subsequent linear extrapolation of bio-equivalents generates additional inaccuracy if the prerequisite of parallel dose-response curves is not met. When all these factors are taken into consideration, it becomes clear that data analysis introduces considerable uncertainty in the derived bio-equivalents. To improve accuracy and transparency of bio-equivalents, we propose a novel data analysis strategy and a checklist for reporting Minimum Information about Bio-equivalent ESTimates (MIBEST).

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