Light energy is one of the major costs for phototrophic systems. This study evaluated the photoreactor efficiency of purple phototropic bacteria anaerobic membrane bioreactor (PAnMBR) at low irradiance for the treatment of municipal wastewater. Infrared irradiance levels of 3.0 and 1.4 W/m2 produced by an infrared (IR) lamp emitting in the 800–900 nm wavelength range were investigated, with the ultimate goal of optimizing the irradiance energy demand. Experimental and modeling results demonstrated the ability of PPB to grow and treat raw municipal wastewater at the applied low irradiances, with effluent quality below target limits of TCOD˂50 mg/L, TN˂10 mg/L, and TP˂1 mg/L. While Monod kinetic parameters, km and Y, were determined to be lower than previous high-energy studies (1.9 mgCOD/mgVSS-d and 0.38 mgVSS/mgCOD, respectively), the photobioreactor performance were consistently maintained, indicating that energy cost associated with IR illumination can be reduced by up to 97%. To determine whether the treatment process could approach energy neutrality, subsequent anaerobic digestion experiments of the residual PPB biomass proved a potential for biogas recovery of up to 240 NmLCH4/gVSSadded, and a moderate biomass biodegradability of 41%. As a result, the net energy consumption of the process was estimated at 0.5 kWh/m3 of treated municipal wastewater, considering an energy demand for illumination of 0.67 kWh/m3 and an energy recovery attributed to the anaerobic digestion of 0.17 kWh/m3 from the excess PPB biomass wasted from PAnMBR.

Environmental management depends on high-quality monitoring and its meaningful interpretation. The combination of local weather dynamics, regional anthropogenic stresses and global environmental changes make the evaluation of monitoring information in dynamic freshwater systems a challenging task. While the lake ecosystems gather many complex biogeochemical interactions, they remain constrained by the same physical environment of mixing and transport. It is therefore crucial to obtain high-quality physical system insight. Three-dimensional hydrodynamic models are perfectly suited for providing such information. However, these models are complex to implement, and their use is often limited to modellers. Here, we aim to provide model output via a user-friendly platform to a broad audience ranging from scientists to public and governmental stakeholders. We present a unified approach merging the apparently diverse interests through Meteolakes.ch, an online platform openly disseminating lake observations and three-dimensional numerical simulations in near real-time with short-term forecasts and data assimilation. Meteolakes is scalable to a broad range of devices, modular and distributed, hence allowing its expansion to other regions and hardware infrastructures. Since 2016, the platform has continuously provided timely synoptic lake information to more than 250,000 users. This web-based system was built not only to provide guidance to scientists in the design and analysis of field experiments and to foster interdisciplinary lake studies, but also to assist governmental agencies and professionals in the long-term policy and planning of water resources management. Finally, our system aimed at promoting awareness and understanding of the complexity of lakes and providing information to the public through user-friendly interfaces. This article details the design and operation of such a platform and its products. Applications are demonstrated by examples of a recent upwelling and a storm event. Both cases illustrate how Meteolakes help scientists in their quest for process understanding as well as water professionals and civil society in providing specific warnings.

Seawater can be introduced or intrude in sewer systems and can thereby negatively influence biological wastewater treatment processes. Here we studied the impact of artificial seawater on the enhanced biological phosphate removal (EBPR) process performance by aerobic granular sludge (AGS) with synthetic wastewater. Process performance, granule stability and characteristics as well as microbial community of a seawater-adapted AGS system were observed. In seawater conditions strong and stable granules formed with an SVI5 of 20 mL/g and a lower abrasion coefficient than freshwater-adapted granules. Complete anaerobic uptake of acetate, anaerobic phosphate release of 59.5 ± 4.0 mg/L PO43--P (0.35 mg P/mg HAc), and an aerobic P-uptake rate of 3.1 ± 0.2 mg P/g VSS/h were achieved. The dominant phosphate accumulating organisms (PAO) were the same as for freshwater-based aerobic granular sludge systems with a very high enrichment of Ca. Accumulibacter phosphatis clade I, and complete absence of glycogen accumulating organisms. The effect of osmotic downshocks was tested by replacing influent seawater-based medium by demineralized water-based medium. A temporary decrease of the salinity in the reactor led to a decreased phosphate removal activity, while it also induced a rapid release of COD by the sludge, up to 45.5 ± 1.7 mg COD/g VSS. This is most likely attributed to the release of osmolytes by the cells. Recovery of activity was immediately after restoring the seawater feeding. This work shows that functioning of aerobic granular sludge in seawater conditions is as stable as in freshwater conditions, while past research has shown a negative effect on operation of AGS processes with NaCl-based wastewater at the same salinity as seawater.

Climate change is affecting the frequency and intensity of rainfall extreme events worldwide. Despite the growing global awareness, developing flood resilient cities has proven to be a major challenge. This paper investigates the application of an event-based scalable Flood Resilience Index (FRI) for assessing climate change adaptation. Flood resilience is represented by three dimensions: physical, social and economic. A household climate adaptation is adopted consisting of a combination of a flood-proof gate with an indoor tank and a submersible pump system implemented in all houses. The climate related impact under a high-emission scenario (RCP8.5) is analysed for Munich with the CRCM5 Large-Ensemble. Results show that for Munich extreme heavy rainfall events are increasing. The FRI can successfully identify households and districts which: a) are mostly affected by heavy rainfall, b) benefit the most from the climate adaptation, and c) are the most resilient. For the most severe future scenario investigated the climate adaptation measure was able to improve 57% of all affected buildings within Maxvorstadt to an FRI equal to 1.0 during the event and recovery phase.

The effects of aeration and stirring systems on the physical properties of sludge were analyzed using a computational fluid dynamics (CFD) model. The aims of this study were to (1) compare the effects of aeration and stirring on sludge properties using the same turbulent mixing intensity, and (2) to reveal the relationship between sludge properties and hydrodynamic indicators to determine how hydrodynamic conditions influence sludge flocculation. Mixing experiments with stirring and aeration were carried out in 2-L beakers with the average velocity gradient (G) set to 90, 190, or 280 s−1. The sludge flocculation performance, zeta potential, and Gibbs free energy (ΔG) were analyzed and the flow rate, turbulence energy, turbulence dissipation rate, and Kolmogorov microscale were calculated as hydrodynamic parameters. The average flow rate and the turbulence dissipation rate were obviously higher in the stirring system than in the aeration system at the same G. However, the turbulence energy and Kolmogorov microscale in the aeration system were much higher than those in the stirring system. Both the zeta potential and ΔG were lower in the aeration system than the stirring system. The zeta potential and ΔG results for the two systems suggest that aeration is more beneficial for sludge flocculation than stirring even though the sludge flocculation performance F/F0 in the stirring and aeration systems showed no obvious differences. Significant relationships between hydrodynamic parameters calculated based on the CFD model and average values of sludge properties in the stable phase showed that the Kolmogorov microscale, average flow rate, and turbulence energy were appropriate hydrodynamic parameters for evaluating the flocculation performance F/F0, zeta potential, and ΔG, respectively.

Lagoon has been used as one of common to treat agricultural wastewater. However, discharging lagoon water without appropriate treatment could because a critical issue that threaten environment and sustainability. It is necessary to monitor the quality of lagoon water before land application. This paper not only proposes an innovative testing method for sewage, but also combines a machine learning methods and spectral processing techniques to analyze the reflectivity of water chemical composition. The nitrogen, phosphorus, bacteria (total coliform), and total solids (TS), are chosen as main indicators for water quality. It was found that the spectral rate of emission or absorption showed a certain correlation with those contaminants. We use machine learning to train three kinds of estimators to prove those correlation, where their core algorithms are normal equation linear regression (LR), stochastic gradient descent (SGD) and ridge regression (R-PLS). At last, the model dataset is evaluated by weight coefficient, function intercept and mean squared error (MSE). The conclusion shows the reflectivity of TS and spectral reflectance of samples close to linear relationship. The MSE of prediction set and decision coefficient are 0.57 and 0.98, respectively. For bacteria, the MSE of prediction set is 0.63, and coefficient R2 is 0.96. The results from this study could provide a versatile method for remote sensing monitoring of agricultural water pollution and a non-destructive spectroscopy technical reference for agricultural wastewater treatment.