Per- and polyfluoroalkyl substances (PFAS) are highly persistent and potentially toxic chemicals that have been found in many drinking water resources worldwide. Increasingly stringent limits for these substances require advanced treatment concepts to remove these substances during drinking water treatment. Today, the majority of treatment systems for PFAS removal rely on granular activated carbon (AC) or ion exchange resins (IX), whose capacities are often limited by competitive adsorption of dissolved organic matter. In this study, a screening of six AC, five PFAS-specific IX, and seven alternative adsorbents was performed using equilibrium jar tests. The removal of 12 selected PFAS was compared to the removal of 16 other non-PFAS organic micropollutants. Dissolved organic matter competition was investigated using size exclusion chromatography with online organic carbon and UV254 detection. In addition, AC were characterized by determination of the pH at the point of zero charge, cation and anion exchange capacity, and surface oxygen groups. While IX appear to be the best choice for short-chain PFAS removal, AC allows for broader removal of organic micropollutants, and bentonite-based surface modified clays allow for highly selective PFAS removal with very low DOM competition. The data also show that the removal of acesulfame might be used as an indicator for removal of some PFAS, allowing an initial selection of activated carbon or ion exchange resin in the absence of PFAS data. Carbonyl surface oxygen groups determined with thermogravimetric analysis coupled to Fouriertransform infrared spectroscopy served as best predictor for organic micropollutant removal by AC.
The persistence and water mobility of per- and polyfluoroalkyl substances (PFAS) have led authorities worldwide to lower regulatory limits to prevent adverse health effects. Removal via adsorption on activated carbon can be inefficient due to the unspecific surface interaction, while ion exchange resins with positive charges and hydrophobic chains can offer faster kinetics and improved removal. In here, novel cationic resins were synthesized by cross-linking polyethylenimine, followed by methylation. To obtain cross-linked particles and introduce hydrophobic interacting moieties in one single synthetic step, aliphatic, fluorous, and silicone-based oligoethers were used as cross-linkers. These cationic adsorbents were compared with two state-of-the-art strong base gel-type ion exchange resins and granular activated carbon in isotherm and kinetic studies. The newly developed adsorbents showed significantly faster removals of all tested long- and short-chain PFAS. The fluorous cationic adsorbent achieved equilibrium loadings that were comparable to those of the state-of-the-art adsorbents for all PFAS with five or more perfluorinated carbon atoms.
Die Berliner Wasserbetriebe (BWB) haben sich das Ziel gesetzt, bis 2030 klimaneutral zu arbeiten und die Energiewende zu unterstützen. Großes Optimierungspotenzial für die Abwasserreinigung liegt in der biologischen Behandlungsstufe, welche mit ca. 60 % den größten Energieverbrauch hat. Im Kooperationsprojekt „ANNA“ wurde erstmals die Belüftungssteuerung der biologischen Reinigungsstufe unter Anwendung künstlicher neuronaler Netze (KNN) in einer ausgewählten Prozesslinie auf dem Klärwerk Münchehofe untersucht. Ziel des Projektes war es, ein am Markt erhältliches Echtzeitassistenzsystem zur Reduzierung des Energieverbrauchs bei gleichzeitiger Einhaltung der Grenzwerte unter Betriebsbedingungen zu testen. Zur Modellierung des Prozesses kamen KNN zum Einsatz, um die Ablaufkonzentration der Versuchslinie zu prognostizieren. Die KNN wurden mit physikalisch relevanten historischen Daten trainiert. Mit Hilfe der modellbasierten Prognosen ließen sich Vorschläge für Soll-Sauerstoffkonzentration oder Soll-Luftmengen berechnen und umsetzen. Die Implementierung des Assistenzsystems erfolgte schrittweise. Im ersten Schritt wurde die Anwendung des Assistenzsystems manuell getestet. Die vom Betriebspersonal umgesetzten Handlungsempfehlungen führten zu einem reduzierten Luftverbrauch von ca. 10 %. Gleichzeitig wurde eine Erhöhung der Ammoniumkonzentration (NH4-N) im Ablauf der Versuchslinie (2,2 mg/l) im Vergleich zur Vergleichslinie (1,6 mg/l) um 0,6 mg/l festgestellt. Innerhalb der Versuchsphase wurde die Abwasserbeaufschlagung in der Versuchs- und Vergleichslinie teilweise um 10 % erhöht. Hierbei konnte beobachtet werden, dass die Handlungsempfehlungen eine präzise frachtbasierte Belüftungssteuerung ermöglichten. Auch Regenereignisse erkannte das Assistenzsystem frühzeitig, wodurch rechtzeitig, entsprechend des eintretenden Frachtstosses, die Belüftung erhöht und anschließend wieder herabgesetzt wurde. Auf Grundlage der positiven Ergebnisse wurde das Assistenzsystems in den automatischen Betrieb genommen, um seinen Einfluss auf das Optimierungspotenzial und die Ablaufqualität zu untersuchen.
The coordination of construction sites in urban areas is increasingly critical to minimizing their traffic impact. Traditionally, traffic assessments were conducted late in the planning process, limiting opportunities for proactive mitigation. This paper presents a SUMO-based prototype that integrates the Baustellenatlas, a digital construction coordination tool, with SESAM, a cloud-based SUMO simulation service, via a REST API. The system enables automated traffic impact assessments, allowing users to modify road network properties and simulate their effects in real time. Two case studies in Berlin evaluated the prototype: a small-scale demonstrator at Molkenmarkt with randomly generated traffic and a larger, calibrated scenario at Tempelhofer Damm, reflecting real-world demand data. Results highlight the potential of integrating microscopic traffic simulation into early-stage construction planning, making data-driven assessments more accessible. Key challenges include the visualization of rerouting effects, long-term detour modeling, and expanding network modification capabilities. Future work will focus on public transport integration, adaptive signal control, and automatic scenario calibration using real-time traffic data.
We present a versatile flow-through tube passive sampling device (TPS), with a controllable feedwater volumetric flow, that can be calibrated in situ against the feedwater load of organic micropollutants (OMPs). This semipassive approach has the advantage of a determinable water load feeding the sampling device. The design of the TPS allows for new sampling scenarios in closed piping while providing stable and controlled sampling conditions. The calibration referencing an OMP's feedwater load can describe the uptake behavior from wastewater treatment plant effluent with potentially highly fluctuating OMP concentrations. The TPS and its load-dependent calibration under realistic environmental conditions proves possible for a variety of organic trace substances in a challenging matrix. Nine of the 20 monitored representative OMPs could be calibrated load-dependently, leading to a good agreement between the calculated concentration from the TPS and the average concentration of corresponding direct measurements. Due to the simple measuring principle and the membrane-less discs, many influencing factors such as diffusion, turbulence, and lag time phenomena can be neglected. The TPS could support the existing online measurement analytics in a (process-) water treatment plant by delivering integrated water concentrations for discharge monitoring.
