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.

Ziel des Vorhabens FlexTreat war es, durch die Entwicklung und Demonstration flexibler und an die landwirtschaftlichen Bedürfnisse angepasster technischer und naturnaher Aufbereitungssysteme die sichere Wasserwiederwendung in der Landwirtschaft zu fördern.

Dies umfasste die Entwicklung und Anwendung von wissenschaftlich-technischen Grundlagen für den sicheren Einsatz von aufbereitetem Abwasser für die landwirtschaftliche Bewässerung im In- und Ausland. Außerdem waren die Untersuchung und Optimierung der Reinigungsleistung von innovativen, weitergehenden Abwasserbehandlungsverfahren in Bezug auf ein brei-tes Spektrum von physikalischen, chemischen und mikrobiologischen Wasserqualitätsparametern Ziele des Projektes.

Des Weiteren stand im Fokus die Demonstration der Vorteile von Digital Green Tech (Digitaler Zwilling, online-Simulation, maschinelles Lernen, Nutzung mobiler Endgeräte) für die Prozessüberwachung und Optimierung von Aufbereitungsverfahren. Außerdem die Risikobewertung und das Risikomanagement entlang der Abwasserbehandlung, insb. der weitergehenden Auf-bereitung, unter Berücksichtigung von ausgewählten Aspekten bei Speicherung, Verteilungund Bewässerung bis hin zur Analyse von Risikofaktoren im landwirtschaftlichen Produkt.

Auch wird die Akzeptanz und die Übertragbarkeit der entwickelten Konzepte und Technologienfür die Wasserwiederverwendung in der Landwirtschaft im In- und Ausland betrachtet.

FlexTreat trägt dazu bei, die Umsetzung von Wasserwiederverwendungsprojekten in Deutschland durch eine verbesserte Risikoeinschätzung, Erfahrungswerte aus dem Betrieb relevanter Technologien sowie die Betrachtung weiterer relevanter Faktoren voranzubringen. Ein besonderer Fokus liegt hierbei darauf, Synergieeffekte von konventionellen Technologien, welchefür die Spurenstoffelimination genutzt werden, sowie ergänzenden Behandlungsschritten zur Desinfektion von Abwasser zu identifizieren und zu quantifizieren.

Durch ein verbessertes Verständnis für mögliche Risiken, neue Möglichkeiten zur Prozessüberwachung und der Betrachtung realer Anwendungsfälle sowie außerdeutscher Marktpotentiale liefert FlexTreat wissenschaftlich fundierte Antworten auf offene Fragestellungen im Prozess der Gestaltung der deutschen Gesetzgebung für die Wasserwiederverwendung.

Gleichzeitig wird der Stand der Wissenschaft um zahlreiche spezielle Aspekte erweitert, welche der Wasserwiederverwendung und berührende Themen langfristigen Fortschritt ermöglichen.

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

The PROMISCES project aims to develop innovative, systemic solutions to protect health, environment, and natural resources from persistent, mobile and potentially toxic (PM(T)) substances by addressing regulatory gaps and promoting circular economy principles. This deliverable, in particular seeks to:

· Identify inconsistencies, gaps, and challenges within the existing EU legal and policy framework related to PM(T) substances.

· Promote harmonized regulatory approaches across environmental compartments.

· Provide EU and national policymakers with actionable, evidence-based policy recommendations to improve the management of PMT(s) in the soil-sediment-water system (and beyond).

· Emphasize that updated policy approaches address disparities and technical, financial and social challenges across Member States (MS).

The "Toolbox Fate & Transport Modelling of PMTs in the Environment" is a key deliverable from the H2020 PROMISCES project. This toolbox is a demonstrator that includes a collection of models developed in the PROMISCES project which are designed to assess the fate and transport of persistent, mobile, and toxic substances (PMTs) across various scales (local, regional) and conditions (e.g., urban run-off, bank filtration, unsaturated zone, groundwater).
This toolbox presents the basic information with links to the software and model input files with which the models can be run. This deliverable is intended for qualified modellers. It is complementary with the Guidance document, deliverable D2.4 (Zessner et al., 2025) which describes how to apply modelling tools in a tiered way as part of predictive risk assessment.

The scope of this document, produced as part of the H2020 PROMISCES project, is to provide guidance for applications of models with a specific focus on model trains for the assessment of exposure to PMTs as part of the predictive risk assessment related to surface and groundwater. This document explains the basic concepts of specific models and how best to use them in model
trains in the framework of a tiered approach. The intention is to inform users and interested stakeholders about what needs to be considered when using different methods, what is the best use of specific models, what are the best combinations in model trains and what are their current limitations.

The Horizon 2020 project PROMISCES aims to increase the circularity of resources by overcoming barriers associated with the presence of PM(T)s in the soil-sediment-water system.

This deliverable provides guidance on how to co-create a solution strategy for dealing with PM(T)(s) in a circular economy. For this, we have used the experience and lessons learnt in the co-creation workshops organized within the PROMISCES project.

This model is part of the toolbox built within the framework of the PROMISCES project (Deliverable D2.3).

Emission model to calculate the monthly load of pollutants entering various water bodies and watercourses via stormwater and wastewater via the separate sewer system, combined sewer overflows (CSOs) and wastewater treatment plant (WWTP) effluent.

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.