Application of biological early warning systems in wastewater treatment plants: Introducing a promising approach to monitor changing wastewater composition.

Wastewater treatment plants (WWTPs) are a major source of micropollutants to surface waters. Currently, their chemical or biological monitoring is realized by using grab or composite samples, which provides only snapshots of the current wastewater composition. Especially in WWTPs with industrial input, the wastewater composition can be highly variable and a continuous assessment would be advantageous, but very labor and cost intensive. A promising concept are automated real-time biological early warning systems (BEWS), where living organisms are constantly exposed to the water and an alarm is triggered if the organism's responses exceed a harmful threshold of acute toxicity. Currently, BEWS are established for drinking water and surface water but are seldom applied to monitor wastewater. This study demonstrates that a battery of BEWS using algae (Chlorella vulgaris in the Algae Toximeter, bbe Moldaenke), water flea (Daphnia magna in the DaphTox II, bbe Moldaenke) and gammarids (Gammarus pulex in the Sensaguard, REMONDIS Aqua) can be adapted for wastewater surveillance. For continuous low-maintenance operation, a back-washable membrane filtration system is indispensable for adequate preparation of treated wastewater. Only minor deviations in the reaction of the organisms towards treated and filtered wastewater compared to surface waters were detected. After spiking treated wastewater with two concentrations of the model compounds diuron, chlorpyrifos methyl, and sertraline, the organisms in the different BEWS showed clear responses depending on the respective compound, concentration and mode of action. Immediate effects on photosynthetic activity of algae were detected for diuron exposure, and strong behavioral changes in water flea and gammarids after exposure to chlorpyrifos methyl or sertraline were observed, which triggered automated alarms. Different types of data analysis were applied to extract more information out of the specific behavioral traits, than only provided by the vendors algorithms. To investigate, whether behavioral movement changes can be linked to impact other endpoints, the effects on feeding activity of G. pulex were evaluated and results indicated significant differences between the exposures. Overall, these findings provide an important basis indicating that BEWS have the potential to act as alarm systems for pollution events in the wastewater sector.

Predicting microbial water quality in on-site water reuse systems with online sensors.

Widespread implementation of on-site water reuse is hindered by the limited availability of monitoring approaches that ensure microbial quality during operation. In this study, we developed a methodology for monitoring microbial water quality in on-site water reuse systems using inexpensive and commercially available online sensors. An extensive dataset containing sensor and microbial water quality data for six of the most critical types of disruptions in membrane bioreactors with chlorination was collected. We then tested the ability of three typological machine learning algorithms - logistic regression, support-vector machine, and random forest - to predict the microbial water quality as "safe" or "unsafe" for reuse. The main criteria for model optimization was to ensure a low false positive rate (FPR) - the percentage of safe predictions when the actual condition is unsafe - which is essential to protect users health. This resulted in enforcing a fixed FPR ≤ 2%. Maximizing the true positive rate (TPR) - the percentage of safe predictions when the actual condition is safe - was given second priority. Our results show that logistic-regression-based models using only two out of the six sensors (free chlorine and oxidation-reduction potential) achieved the highest TPR. Including sensor slopes as engineered features allowed to reach similar TPRs using only one sensor instead of two. Analysis of the occurrence of false predictions showed that these were mostly early alarms, a characteristic that could be regarded as an asset in alarm management. In conclusion, the simplest algorithm in combination with only one or two sensors performed best at predicting the microbial water quality. This result provides useful insights for water quality modeling or for applications where small datasets are a common challenge and a general advantage might be gained by using simpler models that reduce the risk of overfitting, allow better interpretability, and require less computational power.

Acceptance of on-site wastewater treatment and reuse in Bengaluru, India: The role of perceived costs, risks, and benefits.

In dealing with water pollution and freshwater scarcity, on-site treatment and reuse of domestic wastewater has shown to be a promising solution. To increase on-site wastewater treatment and reuse, some cities, among them Bengaluru in India, have mandated the installation and use of the necessary technology in certain building types. However, even with a mandate, a successful and sustainable implementation of the technology, including reliable operation, monitoring, and maintenance, depends on the acceptance (i.e. positive valuation) of the technology and its use by the (prospective) users. Literature on technology acceptance indicates perceived costs, risks, and benefits of the respective technology as key predictors of acceptance. Therefore, the present online study assessed this relationship for on-site systems in Bengaluru. The relation was analysed separately for mandated users of on-site systems (N = 103) and current non-users (i.e. potential prospective users, should the mandate be expanded; N = 232), as the perceptions might differ between the two groups, due to the personal experience with the technology among users. The results show that for mandated users and non-users, acceptance of on-site systems is explained by perceived benefits only, namely a positive image of users, environmental benefits, and, only for non-users, also financial benefits for the city. The findings suggest that interventions aimed at promoting on-site systems should include emphasis on the benefits of on-site systems. Whenever possible, interventions should be tailored to the target group's individual cost, risk, and benefit perception.

Gravity-driven membrane filtration with compact second-life modules daily backwashed: An alternative to conventional ultrafiltration for centralized facilities.

Gravity-driven membrane (GDM) filtration is a strategic alternative to conventional ultrafiltration (UF) for the resilient production of drinking water via ultrafiltration when resources become scarce, given the low dependency on energy and chemicals, and longer membrane lifetime. Implementation at large scale requires the use of compact and low-cost membrane modules with high biopolymer removal capacity. We therefore evaluated (1) to what extent stable flux can be obtained with compact membrane modules, i.e., inside-out hollow fiber membranes, and frequent gravity-driven backwash, (2) whether we can reduce membrane expenses by effectively utilizing second-life UF modules, i.e., modules that have been discarded by treatment plant operators because they are no longer under warranty, (3) if biopolymer removal could be maintained when applying a frequent backwash and with second-life modules and (4) which GDM filtration scenarios are economically viable compared to conventional UF, when considering the influence of new or second-life modules, membrane lifetime, stable flux value and energy pricing. Our findings showed that it was possible to maintain stable fluxes around 10 L/m2/h with both new and second-life modules for 142 days, but a daily gravity-driven backwash was necessary and sufficient to compensate the continuous flux drop observed with compact modules. In addition, the backwash did not affect the biopolymer removal. Costs calculations revealed two significant findings: (1) using second-life modules made GDM filtration membrane investment less expensive than conventional UF, despite the higher module requirements for GDM filtration and (2) overall costs of GDM filtration with a gravity-driven backwash were unaffected by energy prices rise, while conventional UF costs rose significantly. The later increased the number of economically viable GDM filtration scenarios, including scenarios with new modules. In summary, we proposed an approach that could make GDM filtration in centralized facilities feasible and increase the range of UF operating conditions to better adapt to increasing environmental and societal constraints.

Sensor setpoints that ensure compliance with microbial water quality targets for membrane bioreactor and chlorination treatment in on-site water reuse systems.

Widespread implementation of on-site water reuse systems is hindered by the limited ability to ensure the level of treatment and protection of human health during operation. In this study, we tested the ability of five commercially available online sensors (free chlorine (FC), oxidation-reduction potential (ORP), pH, turbidity, UV absorbance at 254 nm) to predict the microbial water quality in membrane bioreactors followed by chlorination using logistic regression-based and mechanism-based models. The microbial water quality was assessed in terms of removal of enteric bacteria from the wastewater, removal of enteric viruses, and regrowth of bacteria in the treated water. We found that FC and ORP alone could predict the microbial water quality well, with ORP-based models generally performing better. We further observed that prediction accuracy did not increase when data from multiple sensors were integrated. We propose a methodology to link online sensor measurements to risk-based water quality targets, providing operation setpoints protective of human health for specific combinations of wastewaters and reuse applications. For instance, we recommend a minimum ORP of 705 mV to ensure a virus log-removal of 5, and an ORP of 765 mV for a log-removal of 6. These setpoints were selected to ensure that the percentage of events where the water is predicted to meet the quality target but it does not remains below 5%. Such a systematic approach to set sensor setpoints could be used in the development of water reuse guidelines and regulations that aim to cover a range of reuse applications with differential risks to human health.

Modelling of aerobic granular sludge reactors: the importance of hydrodynamic regimes, selective sludge removal and gradients.

Hydraulic selection is a key feature of aerobic granular sludge (AGS) systems but existing aerobic granular sludge (AGS) models neglect those mechanisms: gradients over reactor height (Hreactor), selective removal of slow settling sludge, etc. This study aimed at evaluating to what extent integration of those additional processes into AGS models is needed, i.e., at demonstrating that model predictions (biomass inventory, microbial activities and effluent quality) are affected by such additional model complexity. We therefore developed a new AGS model that includes key features of full-scale AGS systems: fill-draw operation, selective sludge removal, distinct settling models for flocs/granules. We then compared predictions of our model to those of a fully mixed AGS model. Our results demonstrate that hydraulic selection can be predicted with an assembly of four continuous stirred tank reactors in series together with a correction code for plug-flow. Concentration gradients over the reactor height during settling/plug-flow feeding strongly impact the predictions of aerobic granular sludge models in terms of microbial selection, microbial activities and ultimately effluent quality. Hydraulic selection is a key to predict selection of storing microorganisms (phosphorus-accumulating organisms (PAO) and glycogen-accumulating organisms (GAO)) and in turn effluent quality in terms of total phosphorus, and for predicting effluent solid concentration and dynamic during plug-flow feeding.

Elucidating the role of extracellular polymeric substances (EPS) in dewaterability of fecal sludge from onsite sanitation systems, and changes during anaerobic storage.

As the importance of fecal sludge management (FSM) is increasingly being realized, the need for adequately designed and functioning fecal sludge (FS) treatment plants is also increasing. Research to fill this gap is only emerging and dewatering is a key challenge for developing sustainable treatment solutions. This study evaluated the effect of extracellular polymeric substances (EPS) on dewaterability of FS, and how EPS and dewaterability change during anaerobic storage (as a proxy for time in onsite containment). EPS was extracted from FS and activated sludge using Na2CO3 and sonication and added to sludge samples to determine the effect on dewaterability. The results confirmed that an increase in EPS had a direct impact of decreasing FS dewaterability (as capillary suction time). In this context, we evaluated FS degradation during anaerobic storage, the effect of anaerobic storage time on EPS, EPS fractions and particle size distribution, and the effect of variations in these factors on FS dewaterability. Variations in EPS, EPS fraction and particle size distribution during anaerobic storage were less than expected and average VS reduction of 20% was recorded over 7 weeks. Although anaerobic digestion was verified (biogas production), the results indicate that kinetics of degradation of FS is different from wastewater sludges. Comparatively, EPS fractions in FS were 70 - 75% lower and with higher fractions of humic-like substances than wastewater sludges. Although EPS significantly affects FS dewaterability, anaerobic storage time is not a predictor of dewaterability.

Screening innovative technologies for energy-efficient domestic hot water systems.

Domestic hot water systems are large energy consumers. With the aim of reducing the energy footprint of these systems, we selected and simulated five technologies across a wide range of technology readiness levels: established technologies - pipe insulation and low-flow faucets -, relatively new technologies - shower drain heat exchangers and an innovative pipe system - and a novel experimental technology - a heat exchanger connected to membrane bioreactor for on-site greywater treatment. Using the WaterHub modeling framework, we simulated the technologies alone and in combination and compared the energetic performance of fifteen scenarios with a validated reference domestic hot water system. Low-flow appliances as standalone technologies performed best with 30% less energy required for the boiler tank, but combining low-flow appliances with a membrane bioreactor heat exchanger performed best overall (50% reduction). Deep insights into the temperature dynamics at all locations in the system led to the identification of technological competition patterns to prevent and synergies to exploit. Through our results, we are able to discuss and recommend further investigations regarding critical aspects like hygiene and economic performance.

Tracing N2O formation in full-scale wastewater treatment with natural abundance isotopes indicates control by organic substrate and process settings.

Nitrous oxide (N2O) dominates greenhouse gas emissions in wastewater treatment plants (WWTPs). Formation of N2O occurs during biological nitrogen removal, involves multiple microbial pathways, and is typically very dynamic. Consequently, N2O mitigation strategies require an improved understanding of nitrogen transformation pathways and their modulating controls. Analyses of the nitrogen (N) and oxygen (O) isotopic composition of N2O and its substrates at natural abundance have been shown to provide valuable information on formation and reduction pathways in laboratory settings, but have rarely been applied to full-scale WWTPs. Here we show that N-species isotope ratio measurements at natural abundance level, combined with long-term N2O monitoring, allow identification of the N2O production pathways in a full-scale plug-flow WWTP (Hofen, Switzerland). Heterotrophic denitrification appears as the main N2O production pathway under all tested process conditions (0-2 mgO2/l, high and low loading conditions), while nitrifier denitrification was less important, and more variable. N2O production by hydroxylamine oxidation was not observed. Fractional N2O elimination by reduction to dinitrogen (N2) during anoxic conditions was clearly indicated by a concomitant increase in site preference, δ18O(N2O) and δ15N(N2O). N2O reduction increased with decreasing availability of dissolved inorganic N and organic substrates, which represents the link between diurnal N2O emission dynamics and organic substrate fluctuations. Consequently, dosing ammonium-rich reject water under low-organic-substrate conditions is unfavorable, as it is very likely to cause high net N2O emissions. Our results demonstrate that monitoring of the N2O isotopic composition holds a high potential to disentangle N2O formation mechanisms in engineered systems, such as full-scale WWTP. Our study serves as a starting point for advanced campaigns in the future combining isotopic technologies in WWTP with complementary approaches, such as mathematical modeling of N2O formation or microbial assays to develop efficient N2O mitigation strategies.

Low maintenance gravity-driven membrane filtration using hollow fibers: Effect of reducing space for biofilm growth and control strategies on permeate flux.

The implementation of centralized drinking water treatment systems necessitates lower operational costs and improved biopolymer removal during ultrafiltration (UF), which can be afforded by gravity-driven membrane (GDM) filtration. However, prior to implementing GDM filtration in centralized systems, biofilm growth in compacted membrane configurations, such as inside-out hollow fiber (HF), and its impact on permeate flux need to be investigated. To this end, we operated modules with distinct limits on available space for biofilm growth: (1) outside-in 1.5 mm 7-capillary HF (non-limited), (2) inside-out 1.5 mm 7-capillary HF (limited), and (3) inside-out 0.9 mm 7-capillary HF (very limited). Here, we observed that the lower the space available for biofilm growth, the lower the permeate flux. To improve GDM performance with inside-out HF, we applied daily shear stress to the biofilm surface with forward flush (FF) or combined relaxation and forward flush (R+FF). We showed that applying shear stress to the biofilm surface was insufficient for controlling flux loss due to low available space for biofilm growth. At the experimental endpoint, we backwashed with a stepwise transmembrane pressure (TMP) increase or a single TMP on all inside-out HF modules, which removed the biofilm from its base. Afterwards, higher fluxes were yielded. We also showed that all modules exhibited a gradual increase in biopolymer removal followed by stabilization between 70 and 90%. Additionally, control of biofilm growth with surface shear stress did not affect biopolymer removal. In summary, the implementation of inside-out HF with GDM filtration is challenged by low available space for biofilm growth, but may be remedied with a regular backwash to remove biofilm from its base. We showed that a wider range of GDM applications are available; making GDM potentially compatible with implementation in centralized systems, if space limitation is taken into consideration for operation optimization.

On-site urine treatment combining Ca(OH)2 dissolution and dehydration with ambient air.

We present the results of three field tests and three laboratory tests of a new physical-chemical urine treatment system, which can recover all nutrients, while pathogens are inactivated. The system consists of two steps. In the first reactor, biological processes including urea hydrolysis are prevented by mixing fresh urine with calcium hydroxide (Ca(OH)2). Due to the high pH value and the high availability of calcium, phosphate can be recovered by precipitation. The high pH value also fosters the inactivation of microorganisms, including pathogens. In the second reactor, water is evaporated at low energy consumption by blowing unheated ambient air over the stabilized urine. Stabilization in the first reactor was successful in all field and laboratory tests. The pH value remained between 12 and 13, except for short dips due to shortages of Ca(OH)2. Nearly all phosphorus (92-96%) precipitated and could be recovered as calcium phosphate in the first reactor, while nitrogen and potassium overflowed with the urine into the evaporation reactor. The efficiency of the second treatment step was very different for field and laboratory experiments and depended on the duration of the experiment. During a four-day laboratory test, nitrogen recovery was 98%. In contrast, nitrogen recovery was only around 20% in the long-term field experiments. The high nitrogen losses occurred, because biological urea hydrolysis was not inhibited anymore, when the pH value in the second reactor decreased due to the dissolution of high amounts of carbon dioxide from the ambient air. Potassium was not subject to any significant loss, and the measured recovery in the solid evaporation product was 98%. Evaporation rates ranged between 50 g m-2 h-1 (RH = 82±13%, T = 12±6°C) and 130 g m-2 h-1 (RH = 60±19%, T = 24±5°C) in the three field tests. Apart from some disturbances due to low supply of Ca(OH)2, the urine module functioned without any substantial failures and was simple to maintain. The minimum consumption of Ca(OH)2 at full capacity was 6 g·L-1 urine and the electricity demand was 150 Wh kg-1 water evaporated from urine, resulting in operational costs of 0.05 EUR pers-1 d-1.

Release of gold (Au), silver (Ag) and cerium dioxide (CeO2) nanoparticles from sewage sludge incineration ash.

Engineered nanoparticles (NPs) that are released into wastewater are retained by wastewater treatment plants (WWTPs) and accumulate in sewage sludge. Increasing shares of sludge are incinerated and landfilled, especially in industrialized countries. It is debated whether certain types of NPs can outlive the incineration process and subsequently be released from sewage sludge ash (SSA) landfills. To investigate the release of different types of NPs from SSA, we spiked gold (Au), silver (Ag) and cerium dioxide (CeO2) NPs to a pilot WWTP increasing the Au, Ag and Ce concentrations to 30, 43 and 389 mg kg-1 (dry matter basis) in the digested sludge. The spiked sludge was incinerated in a pilot fluidized bed reactor resulting in SSA with Au, Ag and Ce concentrations of 61, 103 and 854 mg kg-1. In addition, two sludge samples from a full-scale WWTP with Au concentrations of 5 and 16 mg kg-1 were incinerated, resulting in SSA with 9 mg kg-1 and 30 mg kg-1 Au. The spiked Au-NPs remain largely unaltered during the wastewater treatment and incineration process, whereas Ag-NPs and CeO2-NPs undergo transformation. During simulated landfill leaching in columns flushed with 400 to 500 pore volumes of artificial rainwater, Ag and Ce were retained in the ash, whereas about 17% of the spiked Au was released, mainly in particulate form. Lower fractions of mostly particulate Au were released from the ashes (3 and 9%) of unspiked SSA. In conclusion, unaltered Au-NPs significantly leach from landfilled SSA, whereas the incorporation of Ag-NPs and CeO2-NPs as transformed species into the SSA matrix limits the leaching of (nano)particulate and dissolved Ag and Ce compounds.

Estimation of countrywide N2O emissions from wastewater treatment in Switzerland using long-term monitoring data.

Nitrous oxides (N2O) emissions contribute to climate change and stratospheric ozone depletion. Wastewater treatment is an important, yet likely underestimated, source of N2O emissions, as recent, long-term monitoring campaigns have demonstrated. However, the available data are insufficient to representatively estimate countrywide emission due to the brevity of most monitoring campaigns. This study showed that the emission estimates can be significantly improved using an advanced approach based on multiple continuous, long-term monitoring campaigns. In monitoring studies on 14 full-scale wastewater treatment plants (WWTPs), we found a strong variability in the yearly emission factors (EFs) (0.1 to 8% of the incoming nitrogen load) which exhibited a good correlation with effluent nitrite. But countrywide data on nitrite effluent concentrations is very limited and unavailable for emission estimation in many countries. Hence, we propose a countrywide emission factor calculated from the weighted EFs of three WWTP categories (carbon removal, EF: 0.1-8%, nitrification only: 1.8%, and full nitrogen removal: 0.9%). However, EF of carbon removal WWTPs are still highly uncertain given the expected variability in performance. The newly developed approach allows representative, country-specific estimations of the N2O emissions from WWTP. Applied to Switzerland, the estimations result in an average EF of 0.9 to 3.6% and total emissions of 410 to 1690 tN2O-N/year, which corresponds to 0.3-1.4% of the total greenhouse gas emissions in Switzerland. Our results demonstrate that better data availability and an improved understanding of long-term monitoring campaigns is crucial to improve current emission estimations. Finally, our results confirm several measures to mitigate N2O emissions from wastewater treatment; year-round denitrification, limiting nitrite accumulation, and stringent control of sludge age in carbon removal plants.

Biological activated carbon filter for greywater post-treatment: Long-term TOC removal with adsorption and biodegradation.

Biological activated carbon (BAC) filters can be used to remove residual total organic carbon (TOC) from greywater after a membrane bioreactor. The two main TOC removal processes are adsorption to the granular activated carbon (GAC) and biological degradation. Biodegradation leads to the growth of microorganisms in the filter bed, which can lead to increased pressure loss over the filter bed. However, the roles of sorption and biodegradation in long-term TOC removal and how they complement each other are unclear. We monitored TOC removal from greywater in a BAC filter installed following a membrane bioreactor over more than 900 days. Removal performance depended on the operational time of the BAC filter, the influent TOC concentration, and in the upper part of the filter on the empty bed contact time (EBCT). Across the overall filter, the EBCT did not significantly influence TOC removal, showing that the filter was sufficiently large for the range of flow rates observed. Analysis of the long-term data revealed the equal importance of sorption and biodegradation over the whole operation period and the whole filter bed. Most of the TOC was removed in the upper part of the filter, where biodegradation was the dominant mechanism. In the lower part of the filter, sorption capacity remained and allowed high influent TOC concentrations to be buffered. The generous filter design with low average filtration rates ensured long-term TOC removal. The only maintenance needed was backwashing, which was required only after more than 800 days of operation. Backwashing effectively reduced the pressure loss but had no significant influence on the effluent water quality. Our study shows that BAC filters are a suitable post-treatment step for the treatment of greywater with highly variable flow and TOC concentrations.

Stagnation leads to short-term fluctuations in the effluent water quality of biofilters: A problem for greywater reuse?

A key characteristic of decentralized greywater treatment and reuse is high variability in both nutrient concentrations and flow. This variability in flow leads to stagnant water in the system and causes short-term fluctuations in the effluent water quality. Automated monitoring tools provide data to understand the mechanisms underlying the dynamics and to adapt control strategies accordingly. We investigated the fluctuations in a building-scale greywater treatment system comprising a membrane bioreactor followed by a biological activated carbon filter. Short-term dynamics in the effluent of the biological activated carbon filter were monitored with automated flow cytometry and turbidity, and the impact of these fluctuations on various hygiene-relevant parameters in the reuse water was evaluated. Continuous biofilm detachment into the stagnant water in the biological activated carbon filter led to temporarily increased turbidity and cell concentrations in the effluent after periods of stagnation. The fluctuations in cell concentrations were consistent with a model assuming higher detachment rates during flow than during times with stagnant water. For this system, total cell concentration and turbidity were strongly correlated. We also showed that the observed increase in cell concentration was not related to either an increase of organic carbon concentration or the concentration of two opportunistic pathogens, P. aeruginosa and L. pneumophila. Our findings demonstrate that turbidity measurements are sensitive to changes in the effluent water quality and can be used to monitor the fluctuations caused by intermittent flow. Intermittent flow did not lead to an increase in opportunistic pathogens, and this study provides no indications that stagnant water in biological activated carbon filters need be prevented.

The value of human data annotation for machine learning based anomaly detection in environmental systems.

Anomaly detection is the process of identifying unexpected data samples in datasets. Automated anomaly detection is either performed using supervised machine learning models, which require a labelled dataset for their calibration, or unsupervised models, which do not require labels. While academic research has produced a vast array of tools and machine learning models for automated anomaly detection, the research community focused on environmental systems still lacks a comparative analysis that is simultaneously comprehensive, objective, and systematic. This knowledge gap is addressed for the first time in this study, where 15 different supervised and unsupervised anomaly detection models are evaluated on 5 different environmental datasets from engineered and natural aquatic systems. To this end, anomaly detection performance, labelling efforts, as well as the impact of model and algorithm tuning are taken into account. As a result, our analysis reveals the relative strengths and weaknesses of the different approaches in an objective manner without bias for any particular paradigm in machine learning. Most importantly, our results show that expert-based data annotation is extremely valuable for anomaly detection based on machine learning.

Robustness of mainstream anammox activity at bench and pilot scale.

New technologies and processes, such as mainstream anammox, aim to reduce energy requirements of wastewater treatment and improve effluent quality. However, in municipal wastewater (MWW) anammox system are often unstable due to process control disturbance, influent variability, or unwanted nitrite oxidizing bacteria (NOB). This study examines the anammox system by focusing on anammox activity and its robustness in a mainstream environment. An 8 m3 pilot-scale sequencing batch reactor (SBR) receiving pretreated MWW (with external nitrite addition) was seeded with pre-colonized carriers. Within six months at 12-20 °C an anammox activity of 200 gN·m-3·d-1 was achieved. After the startup an anammox activity of 260 ± 83 gN·m-3·d-1 was maintained over 450 days. The robustness of the anammox activity was analyzed through three disturbance experiments. Anammox biofilm on carriers were exposed to dissolved oxygen (DO = 1.6 mg·L-1, intermittent aeration), organic loading rate (OLR, C/N increased from 2:1 to 5:1) and temperature disturbances (20 °C to 12 °C) in triplicate 12 L bench scale reactors. The anammox activity and microbial community was monitored during these disturbances. The DO and OLR disturbance experiments were replicated at pilot scale to investigate upscaling effects. Bench and pilot scale anammox activity were unaffected by the DO disturbance. Similarly, an increase in OLR did not deteriorate the bench and pilot scale anammox activity, if nitrate was available. When, at bench scale, the reactor temperature was reduced from 20 °C to 12 °C overnight, anammox activity decreased significantly, this was not the case for the slow seasonal temperature changes (12-25 °C) at pilot scale where no strong temperature dependency was detected in winter. Metagenomic analysis revealed a broad range of Brocadiaceae species with no single dominant anammox species. Anammox thrive under mainstream conditions and can withstand typical process disruptions.

Innovation for improved hand hygiene: Field testing the Autarky handwashing station in collaboration with informal settlement residents in Durban, South Africa.

Safe and accessible water services for hand hygiene are critical to human health and well-being. However, access to handwashing facilities is limited in cities in the Global South, where rapid urbanisation, service backlogs, lack of infrastructure and capacity, and water scarcity impact on the ability of local governments to provide them. Community participation and the co-production of knowledge in the development of innovative technologies, which are aligned with Water, Sanitation and Hygiene (WASH) principles, can lead to more sustainable and socially-acceptable hand hygiene systems. This paper presents the outcomes of the testing of the Autarky handwashing station, a technology that provides onsite treatment and recycling of handwashing water, in an informal settlement in Durban, South Africa. The transdisciplinary research approach adopted enabled the participation of multiple stakeholders with different knowledge systems in the framing, testing and evaluation of the system. The process of co-producing knowledge, as well as the outcomes of the testing, namely high levels of functionality and social acceptability of the technology, supported the WASH principles. The evaluation revealed that the Autarky handwashing station is a niche intervention that improved access to safe and appealing handwashing facilities in an informal settlement. Its novel design, socially desirable features, reliability and ability to save water increased its acceptance in the community. The testing of the system in a real-world context revealed the value of including communities in knowledge production processes for technology innovation. Further work is required to ensure that real-time monitoring of system function is feasible before such systems can be implemented at larger scale.