A risk-based human health exposure assessment (HHEA) model was developed to evaluate the exposure for humans in 4 circular economy (CE) routes investigated in 6 of the 7 case studies in the project PROMISCES. The HHEA is a probabilistic tool evaluating the risk posed to human health. The HHEA was applied to the following routes: 1) semi-closed drinking water cycle; 2) groundwater remediation; 3) water reuse for agricultural irrigation; and 4) nutrient recovery. Each of these exposure routes results in a product – drinking water or lettuce – which can be consumed by humans. For some routes, the exposure is purely theoretical, while for others, the entire process chain is investigated in the PROMISCES case study.

The HHEA is built on Bayesian principles and includes Bayesian updating, which enables assessment of risk under conditions of low data availability and high uncertainty. This is particularly useful for evaluation of substances such as PFAS and other industrial persistent, mobile and potentially toxic (iPMT) substances, the removal of which in treatment processes is not yet well studied in literature. The deliverable explains the different treatments, environmental matrices, and substances which were the focus of the initial assessment. It describes the construction of the HHEA model, with explanations of how different data types – literature data, site specific data, and modelled data – are used to update the prior probability of the removal factor for substances in a process. It also describes how non-technical processes, such as mixing or evaporation, have been included into the treatment trains evaluated. Finally, individual reference quotients for the substances are established, which are used to assess the relative risk of the final concentrations in the products which could be consumed by humans.

Effective decision-making in urban water management requires integrating outputs from specialized models. Berlin’s drinking water supply relies on induced bank filtration and managed aquifer recharge from the Spree and Havel rivers. However, river inflows into Berlin are declining -e.g., in summer 2019, the Spree’s inflow was half that of an average dry summer year- and are expected to decrease further over the next decade due to the ending of coal sump water discharge into the Spree. Long-term impacts from climate change are anticipated to exacerbate this trend. Additionally, an analysis of streamflow data and bank filtrate rate-corrected groundwater extraction has identified regions where maximum monthly extractions from drinking water wells already exceed the lowest monthly river flows in Berlin. This imbalance, combined with increasing water demand driven by population growth, leads to a higher proportion of treated wastewater in Berlin’s streams. As a result, risks to drinking water quality intensify, and the complexity and costs of water and wastewater treatment escalate. Furthermore, higher extraction levels are associated with increased bank filtrate fractions, amplifying system stress and emphasizing the need for sustainable water management practices.

In collaboration with the Belin Waterworks (Berliner Wasserbetriebe), we applied a well-calibrated FEFLOW© model of the Berlin-Friedrichshagen waterworks to simulate bank filtrate rates under various recharge and groundwater extraction scenarios. The model was run under three historical well configurations (2010, 2015, and 2019) and then well pumping rates were adjusted in the same relative configuration under three groundwater recharge scenarios.

A review of prior investigations revealed groups of well galleries exhibiting similar changes in bank filtrate fractions in response to extraction levels; our results complement these former investigations. Bank filtrate behavior across well galleries was found to depend on several factors, including well depth, distance to the riverbanks, the presence of opposing riverbanks, and regional groundwater heads. Relating bank filtrate change groups to site characteristics and bank filtrate fractions in other Berlin develops a city-wide understanding of changes in bank filtrate.

Future FEFLOW© modeling scenarios, including commissioning and decommissioning of well galleries, and implementing managed aquifer recharge will be essential to address remaining uncertainties. Outputs from this modeling effort contribute to regional dynamic water balance modeling for Berlin’s semi-closed water cycle in order to support sustainable water management decision-making amid evolving climatic and regulatory challenges.

This Layman's report is part of Deliverable D6.6 showcasing H2020 PROMISCES project outcomes and results.

This opinion paper reflects on the current challenges facing urban drainage systems (UDS) research, along with solutions for fostering sustainable development. Over the course of a year-long project involving 92 participants aged 24–38, including PhD candidates, post-doctoral researchers, and early-career academics, we identified critical challenges and opportunities for the sustainable development of UDS. Our exploration highlights four key challenges: limited public visibility leading to resource constraints, insufficient collaboration across subfields, issues with data scarcity and data sharing, and geographical specificities. We emphasise the importance of raising public and political awareness regarding UDS's vital role in climate adaptation and urban resilience, advocating for blue-green infrastructure and open data practices. Additionally, we address systemic academic barriers that hinder innovative research. We call for a shift away from metrics that prioritise quantity over quality. We recommend establishing stable career pathways that empower early-career researchers. This paper aims to catalyse a broader community dialogue about the future of UDS research, uniting voices from various career stages. By presenting actionable recommendations, we aim to inspire fundamental changes in research conduct, evaluation, and sustainability, ensuring the field of UDS is prepared to meet pressing urban water management challenges worldwide.