A measurement campaign of wastewater temperatures was carried out in a section of the Berlin wastewater network. These results were used to carry out a temperature simulation using the EPA SWMM-Fork SWMM-HEAT. It was shown that a good agreement between measurements and simulations is possible for predominantly residential areas, even if the network was only moderately thermally calibrated (MAE ≤ 1 °C).

Climate change and industrialization necessitate a reassessment of water management strategies, particularly in agriculture, where reclaimed water supply often fails to meet irrigation needs. Storage can bridge supply gaps but raises concerns about water quality deterioration due to microbial changes and pathogen regrowth. This study examined microbial dynamics and regrowth during reclaimed water storage from a municipal wastewater treatment plant in Germany. The treatment train included ozonation, filtration and UV disinfection, and samples were analyzed using traditional culture methods for indicator organisms (e.g., Escherichia coli,  Clostridium perfringens spores, and somatic coliphages) and 16S rRNA gene amplicon sequencing. Samples were collected throughout the treatment train and stored at 22 °C in the dark for up to 15 days. Results showed effective microbial reduction by treatment, with storage alone achieving similar declines in many cases. While treatment reduced bacterial diversity, storage gradually restored it, forming distinct microbial profiles from the original water quality. Bacterial communities converged during storage, suggesting a succession-like stabilization process. The findings highlight the dynamic nature of reclaimed water microbiomes and the importance of stimulating stable microbial communities to preserve water quality during storage. Advanced treatment should remove contaminants while supporting microbiomes that protect public health and the environment.

Agricultural water reuse is one approach to mitigate water stress. In addition to the minimum requirements, the European water-reuse regulation 2020/741 mandates a risk management approach for agricultural water reuse. In contrast to the microbiological monitoring, the extent of the chemical risk assessment and monitoring is not clearly defined. The resulting complexity of a typical agricultural water-reuse scheme was analyzed. Potentially relevant parameters were identified based on European and German regulatory frameworks, concerning key subjects of protection. An interdisciplinary assessment of efforts and challenges, regarding required analyses, was accomplished, using expertise from recent research investigating agricultural water reuse in Germany. Suggestions were provided for disinfection validation, microbiological monitoring parameters and analytical methods. Additionally, chemical indicator parameters were suggested to address relevant processes during monitoring. Both microbiological and chemical parameters presented analytical challenges, which were described with future needs to support water-reuse implementation. Costs for analyses were estimated using available price information, highlighting the high costs of certain analyses, especially for organic micropollutants. Therefore, analyses need to be further facilitated by the application of process indicators and the implementation of cost-effective, multi-target methods tailored to the requirements of risk management for agricultural water reuse.

In 2020, the European Union published ordinance EU 2020/741, establishing minimum requirements for water reuse in agriculture. The ordinance differentiates between several water quality classes. For the highest water quality class (Class A), the ordinance mandates analytical validation of the treatment performance of new water reuse treatment plants (WRTP) related to the removal of microbial indicators for viral, bacterial, and parasitic pathogens. While the ordinance clearly defines the numeric target values for the required log10-reduction values (LRV), it provides limited to no guidance on the necessary sample sizes and statistical evaluation approaches. The main requirement is that at least 90 % of the validation samples should meet the requirements. However, the interpretation of this 90 % validation target can significantly impact the required sample size, efforts necessary, and the risk of misclassifying WRTPs in practice. The present study compares different statistical evaluation approaches that might be considered applicable for LRV validation monitoring. Special emphasis is placed on the use of tolerance intervals, which combine percentile estimations with sample size-based uncertainty and confidence regions. Tolerance interval-based approaches are compared with alternative methods, including a) a binomial evaluation and b) the calculation of empirical percentiles. The latter are already used in existing European and U.S. regulations for bathing water and irrigation water quality. Our study demonstrates that using tolerance intervals allows for the reliable validation of WRTPs that achieve high LRVs relative to regulatory targets with comparatively smaller sample sizes compared to the other two approaches, while reducing the risk of misclassification. Additionally, we show that simplified approaches, such as a “9 out of 10” approach, pose a substantial risk of misclassification and should not be applied. We illustrate the behavior of these different approaches through simulation experiments and application to real data collected in 2022 and 2023 at a large WRTP in Germany.

Currently, there is uncertainty about emissions of pharmaceuticals into larger closed ecosystems that are at risk such as the Baltic Sea. There is an increasing need for selecting the right strategies on advanced wastewater treatment. This study analysed 35 pharmaceuticals and iodinated X-ray contrast media in effluents from 82 Wastewater Treatment Plants (WWTPs) across Denmark, Estonia, Finland, Germany, Latvia, Lithuania, Poland and Sweden. Measured concentrations from Finland and Denmark were compared to predicted effluent concentrations using different levels of refinement. The concentrations predicted by the Total Residue Approach, as proposed by the European Medicines Agency, correlated with R(2) of 0.18 and 0.031 to measured ones for Denmark and Finland, respectively and the predicted data were significantly higher than the measured ones. These correlations improved substantially to R(2) of 0.72 and 0.74 after adjusting for estimated human excretion rates and further to R(2) = 0.91 and 0.78 with the inclusion of removal rates in WWTPs. Temporal analysis of compound variations in a closely monitored WWTP showed minimal fluctuation over days and weeks for most compounds but revealed weekly shifts in iodinated X-ray contrast media due to emergency-only operations at X-ray clinics during weekends and an abrupt seasonal change for gabapentin. The findings underscore the limitations of current predictive models and findings (...) demonstrate how these methodologies can be refined by incorporating human pharmaceutical excretion/metabolization as well as removal in wastewater treatment plants to more accurately forecast pharmaceutical levels in aquatic environments.