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.

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.

The challenge of water reclamation using membranes in this study was the quite unique wastewater composition resulting from a high share of biotech wastewater. The high content of organic matter and high concentrations of calcium, bicarbonate, and sulphate were considered as challenging for membrane processes. Consequently, an innovative ultra-tight ultrafiltration (u-t UF) membrane was developed and tested on-site at pilot scale. In comparison, a conventional UF and an open nanofiltration (NF) were piloted. The aim was to find the best pre-treatment option for reverse osmosis (RO) to reduce fouling and scaling and produce fit-for-purpose water; for example, cooling. Overall, the quality of the currently used water source was surpassed by the pilot plant. Only a standard post-treatment of the RO permeate was necessary for stabilisation. Results indicated that denser membranes only minimally reduced fouling of RO. An assessment comparing the treatment trains in a life cycle assessment using the data collected from the pilot operation (UF/NF operating settings, RO plant performance, and the design of multi-stage industrial scale RO) revealed lower greenhouse gas emissions compared to seawater desalination. However, if the RO brine treatment becomes mandatory, the greenhouse gas emissions from water reclamation and supply will be higher than those from freshwater supply.