Norovirus infections are among the major causes of acute gastroenteritis worldwide. In Germany, norovirus infections are the most frequently reported cause of gastroenteritis, although only laboratory confirmed cases are officially counted. The high infectivity and environmental persistence of norovirus, makes the virus a relevant pathogen for water related infections. In the 2017 guidelines for potable water reuse, the World Health Organization proposes Norovirus as a reference pathogen for viral pathogens for quantitative microbial risk assessment (QMRA). A challenge for QMRA is, that norovirus data are rarely available over long monitoring periods to assess inter-annual variability of the associated health risk, raising the question about the relevance of this source of variability regarding potential risk management alternatives. Moreover, norovirus infections show high prevalence during winter and early spring and lower incidence during summer. Therefore, our objective is to derive risk scenarios for assessing the potential relevance of the within and between year variability of norovirus concentrations in municipal wastewater for the assessment of health risks of fieldworkers, if treated wastewater is used for irrigation in agriculture. To this end, we use the correlation between norovirus influent concentration and reported epidemiological incidence (R²=0.93), found at a large city in Germany. Risk scenarios are subsequently derived from long-term reported epidemiological data, by applying a Bayesian regression approach. For assessing the practical relevance for wastewater reuse we apply the risk scenarios to different irrigation patterns under various treatment options, namely “status-quo” and “irrigation on demand”. While status-quo refers to an almost all-year irrigation, the latter assumes that irrigation only takes place during the vegetation period from May - September. Our results indicate that the log-difference of infection risks between scenarios may vary between 0.8 and 1.7 log given the same level of pre-treatment. They also indicate that under the same exposure scenario the between-year variability of norovirus infection risk may be > 1log, which makes it a relevant factor to consider in future QMRA studies and studies which aim at evaluating safe water reuse applications. The predictive power and wider use of epidemiological data as a suitable predictor variable should be further validated with paired multi-year data.

https://www.sciencedirect.com/science/article/pii/S0043135422010259

https://github.com/KWB-R/r2q

This report delivers a practical manual to support operators with the management of sensors networks in existing water infrastructures. It includes (1) the presentation and assessment of a new easy-to-use sensor for faecal bacteria measurements, (2) methodologies for the validation of online sensors and analysers and (3) best practices for installation, operation, and maintenance.

In DWC, raw data collected from on-line sensors and lab analyses are integrated and analysed to gather conclusive information and early warning to support decisions to deliver safe water reuse and inform about bathing water quality. Three relevant case studies, namely Paris, Berlin and Milan, were investigated in this research. In the case studies of Paris and Berlin, sensors were installed to monitor microbiological contamination in bathing water sites. In the case study of Milan, a real-time sensor network was designed to promote safe water reuse reducing the risk of microbial contamination of soils and crops during irrigation, while assuring compliance of wastewater quality with reuse standard limits.

The technical characteristics of all the installed on-line sensors are reported in section 1, including the innovative ALERT devices manufactured by FLUIDION, which allow the on-line measurements of faecal bacteria indicators. The section also describes in detail measurement characteristics, i.e., static and dynamic characteristics of instrumentation, operational modes, initial measurement accuracy and standards.

The use of real-time data to support health protection and risk management requires primary their validation, in terms of reliability, in order to integrate the standard lab measures with a continuous monitoring system, for control optimization and risk minimization. To date, one of the main lacks on risk management approach is the absence of common procedure on how to treat non-standardized data, such as real-time online data. To answer this question, this report intends to provide practical information about validation, operation and maintenance of on-line sensors for the three representative case studies. Particularly, this report includes

• Return of experience on installation, troubleshooting and maintenance (section 2).

• Data analysis and assessment of the bias, precision and accuracy of the online sensors (section 3).

The conclusions are reported in section 4.

Probabilistic quantitative microbial risk assessment (QMRA) studies define model inputs as random variables and use Monte-Carlo simulation to generate distributions of potential risk outcomes. If local information on important QMRA model inputs is missing, it is widely accepted to justify assumptions about these model inputs by using external literature information. A question, which remains unexplored, is the extent to which previously published external information should influence local estimates in cases of nonexistent, scarce, and moderate local data. This question can be addressed by employing Bayesian hierarchical modeling (BHM). Thus, we study the effects and potential benefits of BHM on risk and performance target calculations at three wastewater treatment plants (WWTP) in comparison to alternative statistical modeling approaches (separate modeling, no-pooling, complete pooling). The treated wastewater from the WWTPs is used for restricted irrigation, potable reuse, or influences recreational waters, respectively. We quantify the extent to which external data affects local risk estimations in each case depending on the statistical modeling approach applied. Modeling approaches are compared by calculating the pointwise expected log-predictive density for each model. As reference pathogens and example data, we use locally collected Norovirus genogroup II data with varying sample sizes (n = 4, n = 7, n = 27), and complement local information with external information from 44 other WWTPs (n = 307). Results indicate that BHM shows the highest predictive accuracy and improves estimates by reducing parameter uncertainty when data are scarce. In such situations, it may affect risk and performance target calculations by orders of magnitude in comparison to using local data alone. Furthermore, it allows making generalizable inferences about new WWTPs, while providing the necessary flexibility to adjust for different levels of information contained in the local data. Applying this flexible technique more widely may contribute to improving methods and the evidence base for decision-making in future QMRA studies.

Im Rahmen des Forschungsvorhabens „Phorwärts“ wurde auf Basis aktuell erhobener Daten die konventionelle Phosphatdüngemittelherstellung (vom Abbau des Phosphaterzes in der Mine bis zur Anwendung auf dem Feld) mit ausgewählten Verfahren der P-Rückgewinnung aus dem Abwasserpfad ökobilanziell verglichen. Die verschiedenen Düngemittel wurden hinsichtlich ihrer Kontaminationen wie den Schwermetallen, den organischen Schadstoffen und den Pharmaka-Rückständen zusätzlich in einer vergleichenden Risikobewertung der Düngemittelanwendung für die Wirkungspfade Bodenorganismen, Grundwasser und im Hinblick auf die menschliche Gesundheit untersucht. Eine Kostenschätzung der verschiedenen Produktionswege komplettiert den Vergleich der konventionellen Phosphatdüngemittelproduktion mit der Produktion von Recyclingdüngern aus der Kläranlage. Die Ergebnisse der Studie zeigen, dass eine technische Phosphatrückgewinnung aus dem Abwasserpfad unter bestimmten Bedingungen ökologisch und wirtschaftlich sinnvoll ist. Neben dem eigentlichen Phosphatrückgewinnungsverfahren sind in hohem Maße die lokalen Randbedingungen bezüglich der Ergebnisse der vergleichenden Bewertung entscheidend. Unter Berücksichtigung der kommenden gesetzlichen Randbedingungen der Dünge- und der Klärschlammverordnung wird in Zukunft voraussichtlich die Monoverbrennung als primäre Option für die Klärschlammentsorgung dienen und die Phosphatrückgewinnung vorwiegend aus der Klärschlammasche erfolgen. Da bei der Rückgewinnung aus der Klärschlammasche hohe Rückgewinnungsraten, die den Vorgaben der Klärschlammverordnung genügen, erzielt werden können, ist ab dem Kalenderjahr 2029 mit etwa 30.000 bis 40.000 Tonnen Phosphor pro Jahr in Form von Phosphatrezyklaten zu rechnen. Inwieweit und zu welchen Preisen diese Rezyklate durch den Markt angenommen werden, kann aus heutiger Sicht noch nicht abgeschätzt werden.

Kompletter Bericht: https://www.umweltbundesamt.de/sites/default/files/medien/1410/publikationen/2019-02-19texte13-2019_phorwaerts.pdf