Die Erhöhung der Resilienz urbaner Wasserinfrastrukturen wird oft als wichtiges Ziel genannt. Eine Literaturstudie zeigt, dass dafür konkretisiert werden muss, um welche Infrastruktur es sich handelt, gegenüber welcher Störung sie resilient sein soll und an welcher Leistung sich die Resilienz zeigen soll. Hier wird darauf aufbauend ein quantitativer Ansatz der Resilienzmessung vorgeschlagen, der die Schwere des Leistungsausfalls gegenüber einem Grenzwert über die Zeit integriert und dieses Integral über das Zeitintervall und den gewählten Grenzwert normiert. Eine beispielhafte Anwendung für Stadtentwässerungsstrategien bei Starkregenereignissen zeigt, dass der vorgeschlagene Ansatz den Vorteil hat, dass Dauer und Ausmaß eines Leistungsausfalls in einem Resilienzwert berücksichtigt werden können. Zudem erlaubt der Ansatz eine Evaluation unterschiedlicher Störungen, beispielsweise durch Systemausfälle. Durch die Normierung wird ein Vergleich unterschiedlicher Leistungen von Wasserinfrastruktur ermöglicht. Allerdings ist die normierte Resilienz stark von der Wahl des Zeitintervalls und des festgelegten Grenzwertes abhängig und damit nicht ohne weiteres auf andere Systeme übertragbar.

For ensuring microbial safety, the current European bathing water directive (BWD) (76/160/EEC 2006) demands the implementation of reliable early warning systems for bathing waters, which are known to be subject to short-term pollution. However, the BWD does not provide clearly defined threshold levels above which an early warning system should start warning or informing the population. Statistical regression modelling is a commonly used method for predicting concentrations of fecal indicator bacteria. The present study proposes a methodology for implementing early warning systems based on multivariate regression modelling, which takes into account the probabilistic character of European bathing water legislation for both alert levels and model validation criteria. Our study derives the methodology, demonstrates its implementation based on information and data collected at a river bathing site in Berlin, Germany, and evaluates health impacts as well as methodological aspects in comparison to the current way of long-term classification as outlined in the BWD.

In the aftermath of the adoption of the Sustainable Development Goals (SDGs) and the Paris Agreement (COP21) by virtually all United Nations, producing more with less is imperative. In this context, phosphorus processing, despite its high efficiency compared to other steps in the value chain, needs to be revisited by science and industry. During processing, phosphorus is lost to phosphogypsum, disposed of in stacks globally piling up to 3–4 billion tons and growing by about 200 million tons per year, or directly discharged to the sea. Eutrophication, acidification, and long-term pollution are the environmental impacts of both practices. Economic and regulatory framework conditions determine whether the industry continues wasting phosphorus, pursues efficiency improvements or stops operations altogether. While reviewing current industrial practice and potentials for increasing processing efficiency with lower impact, the article addresses potentially conflicting goals of low energy and material use as well as Life Cycle Assessment (LCA) as a tool for evaluating the relative impacts of improvement strategies. Finally, options by which corporations could pro-actively and credibly demonstrate phosphorus stewardship as well as options by which policy makers could enforce improvement without impairing business locations are discussed.

Kanalalterungsmodelle, mit denen sich der Zustand von Abwasserkanälen simulieren lässt, können wertvolle Werkzeuge für die Sanierungsplanung sein. Dennoch werden sie in Deutschland bisher nur von wenigen Kanalnetzbetreibern eingesetzt. Im Rahmen des Forschungsvorhabens SEMA-Berlin wurden verschiedene Modellansätze getestet und hinsichtlich ihrer Prognosequalität bewertet. Für den Modellaufbau wurden die Ergebnisse von mehr als 100 000 TV-Inspektionen sowie Daten zu den individuellen Kanaleigenschaften und Umgebungsfaktoren der Stadt Berlin verwendet. Die Untersuchungen zeigen, dass das statistische Modell GompitZ die Zustandsverteilung des Kanalnetzes mit einer Genauigkeit von 99 % wiedergeben kann. Mit Random Forest, einem Modell des maschinellen Lernens, kann mit einer Trefferquote von 67 % vorhergesagt werden, welcher Kanal sich im schlechten Zustand befindet. Die Ergebnisse können dafür genutzt werden, prioritäre Haltungen für Kanalinspektionen zu identifizieren und Investitionen so zu steuern, dass der Zustand der Kanalisation langfristig erhalten oder sogar verbessert wird.

Deterioration models can be successfully deployed only if decision-makers trust the modelling outcomes and are aware of model uncertainties. Our study aims to address this issue by developing a set of clearly understandable metrics to assess the performance of sewer deterioration models from an end-user perspective. The developed metrics are used to benchmark the performance of a statistical model, namely, GompitZ based on survival analysis and Markov-chains, and a machine learning model, namely, Random Forest, an ensemble learning method based on decision trees. The models have been trained with the extensive CCTV dataset of the sewer network of Berlin, Germany (115,258 inspections). At network level, both models give satisfactory outcomes with deviations between predicted and inspected condition distributions below 5%. At pipe level, the statistical model does not perform better than a simple random model, which attributes randomly a condition class to each inspected pipe, whereas the machine learning model provides satisfying performance. 66.7% of the pipes inspected in bad condition have been predicted correctly. The machine learning approach shows a strong potential for supporting operators in the identification of pipes in critical condition for inspection programs whereas the statistical approach is more adapted to support strategic rehabilitation planning.

Combined sewer systems are one of the major sources of microbiological contamination in urban water bodies. However, identification of hotspots for pathogen emissions is not straightforward, especially in large and complex drainage systems. To determine the relevance of different CSO outlets for bathing water quality a simple tracer approach which uses wastewater volume as a proxy for pathogen emissions has been developed and tested for the city of Berlin, Germany. The approach reveals that the average wastewater ratio in CSO varies largely between different river outlets (0 to 15%). Hence, the outlets with the largest CSO volumes are not automatically the greatest wastewater emitters and assumed hotspots for pathogen contamination do not coincide with hydraulic hotspots. This is verified with own measurements that show enormous differences in pathogen concentrations between waste and stormwater of 4 orders of magnitude. As a result, wastewater which represents only 5% of the CSO volume contributes > 99% of the pathogen loadings to the river. The study highlights the relevance of wastewater volumes for the identification of point sources for the hygienic impairment of water bodies.

Das Ziel dieser Arbeit liegt in einer optimierten Betriebsführung der Ozonierung kommunalen Abwassers durch Identifizierung von organischen und mineralischen Ablagerungen auf Sensoroberflächen (Fouling). Als Grundlage dienen die über einen Zeitraum von sieben Monaten aufgenommenen Onlinedaten zweier (unterschiedlicher) photometrischer Sondentypen zur Einzelwellenlängenmessung des SAK254 (s::can – i::scan) und zur spektralen Messung im UV- und UV/VIS-Bereich (TriOS – OPUS, WTW – CarboVis 705 IQ). a über die Dauer des Untersuchungszeitraums sowohl eine Problemanalyse des Praktischen Betriebs als auch eine zusätzliche Versuchsreihe zur Überprüfung der spektralen Foulingauswirkungen durchgeführt. Dabei zeigten sich die für die jeweiligen Sondentypen unterschiedlich stark ausgeprägte Effekte. Die spezifische Beschaffenheit und Funktionsweise von Reinigungsmodul und Trübungskompensation wirkt in hohem Maß auf die Entwicklung und Auswirkung des Foulings ein und beeinflusst die Werte entsprechend stark. Während des Betriebs einer SAK254-Sonde ist die Identifizierung von Fouling durch einen Abgleich des tatsächlichen Ozoneintrags mit der erwarteten SAK254-Reduktion (und umgekehrt) möglich (E-delta SAK-Diagramm). Die Versuche der spektralen Untersuchung zeigten im niedrigeren Wellenlängenbereich um 254 nm ein stärkerer Zuwachs, als bei höheren Wellenlängen um 360 nm nm zu verzeichnen war. Dieser Umstand führt zu einer unzureichenden Trübungskompensation sowie einem Anstieg des gemessenen SAK254. Zur Lösung dieser Problematik wurde ein sondeninterner Abgleich der Spektren durchgeführt, um so die Trübungskompensation mittels Integration eines Korrekturfaktors zu optimieren. Zur Identifizierung von Fouling anhand eines E-delta SAK-Diagramms oder zur Optimierung der Trübungskompensation per Korrekturfaktor, sind jedoch weitere Versuche notwendig.

In recent decades, emerging contaminants (ECs) have surfaced as one of the key environmental problems threatening ecosystems and public health. Most emerging contaminants are present in low concentrations, and therefore often remain undetected and are also referred to as ‘micropollutants’. Despite this, many ECs raise considerable concerns regarding their impacts on human and environmental health. DEMEAU (Demonstration of promising technologies to address emerging contaminants in water and wastewater), a European Seventh Framework Programme (EU-FP7, 2013-2015) project, aimed to tackle ECs in drinking and wastewater by advancing the uptake of knowledge, prototypes, practices and removal technologies. The project followed a solutions-oriented approach using applied research and demonstration sites, and explored four promising technologies for EC removal and/or degradation: Managed Aquifer Recharge (MAR), Hybrid Ceramic Membrane Filtration (HCMF), Automatic Neural Net Control Systems (ANCS) and Advanced Oxidation Techniques (AOT). Furthermore, Bioassays (BA) were investigated as an effect-based monitoring tool. This article shares new findings for each approach and their potential for widespread integration in the drinking- and wastewater sector. Research results from DEMEAU demonstration sites show that opportunities for synergies among these developments offer the most promising and effective methods for tackling ECs in the water sector.

This study analyses reference and innovative POWERSTEP schemes for municipal WWTP in their environmental and economic impacts using life-cycle tools of Life Cycle Assessment and Life Cycle Costing. Based on hypothetical scenarios at defined boundary conditions for WWTP size, influent quality, and effluent discharge limits, multiple process schemes have been modelled in a mass and energy flow model with a benchmarking software for WWTPs. This process data forms the basis to calculate operational efforts, and it is amended by infrastructure data for material demand and related investment costs. In addition, specific data has been added based on results of the POWERSTEP project (e.g. for N2O emissions) or information from literature. The results show that innovative schemes with advanced primary treatment operate with a superior electricity balance compared to current state-of-the-art schemes for municipal wastewater treatment as a reference, increasing electrical self-sufficiency from 27-82% to 80-170%. The POWERSTEP schemes reach this goal without compromising effluent quality targets of the schemes, i.e. reaching the same effluent quality than before. Concentrated influent with high COD levels supports the POWERSTEP approach and enables highly energy efficient schemes. However, nitrogen removal has to be realized with mainstream anammox after enhanced carbon extraction from concentrated influent. This process is still under development, and its performance and stability should be further validated in full-scale references. Sidestream N removal, advanced control of COD extraction and partial bypass of primary treatment are other options to guarantee nitrogen removal after enhanced carbon extraction with conventional denitrification. In the life-cycle perspective, POWERSTEP schemes significantly decrease primary energy demand of WWTP operation by 29-134% compared to the reference. In favourable conditions, their superior electricity balance can fully compensate life-cycle energy demand for chemical production, sludge disposal and infrastructure, resulting in real energy-positive WWTP schemes. Greenhouse gas emissions can also be substantially reduced with POWERSTEP (- 6 to 43%) due to savings in grid electricity production. GHG benefits of POWERSTEP are smaller than energy benefits on a relative scale, because direct emissions such as N2O from biological N removal and mono-incineration also deliver a major contribution to overall GHG emission profiles, and they are not reduced with POWERSTEP. In contrast, POWERSTEP schemes with mainstream anammox will most likely increase N2O emissions, compensating a large part of the electricity-related benefits in GHG emissions. Total annual costs are in a comparable range for both reference and POWERSTEP schemes. While the latter decrease operational costs by 3-16% due to lower purchase of grid electricity, they require higher investment for primary treatment, increasing capital costs by 4-17%. Overall, effects of POWERSTEP on operational and capital costs off-set each other and result in a net increase of total annual costs of 2-7%, which is within the uncertainty range of this cost calculation. Higher electricity prices (> 0.12 €/kWh) will increase the positive impact of POWERSTEP on operating costs, resulting in fully costcompetitive eco-efficient WWTP schemes at power prices of 0.25 €/kWh. Final recommendations are derived on the way to develop eco-efficient WWTP schemes of the future.