ACS ES&T engineering最新文献

Ensuring the safety and reliability of the water distribution system (WDS) manifests significant importance for residential, commercial, and industrial needs and may benefit from the structure deterioration models for early warning of water pipe breaks. However, challenges exist in model calibration with limited monitoring data, unseen underground conditions, or high computing requirements. Herein, a novel deep learning-based DeeperGCN framework was proposed to predict pipe failure by cooperating with graph convolutional network (GCN) models for graph processing. The DeeperGCN model achieved much deeper architectures and was designed to utilize spatial and temporal data simultaneously. Two graph representation methods and three GCN models were compared, showing the best predictions with the “Pipe_as_Edge” method and the DeeperGEN model. To identify the priority of pipe maintenance directly, the prediction targets were assigned as a binary classification question to determine break or not over 1-, 3-, and 5-year periods, with prediction accuracies of 96.91, 96.73, and 97.23%, respectively. The issue of data imbalance was observed and addressed through varied evaluation metrics, resulting in the weighted F1 scores >0.96. The DeeperGCN framework demonstrated potential applications in visualizing pipe failure prediction with high accuracies of 97.09, 96.31, and 97.81% across three periods in 2015, for example.

Phosphorus (P) is a finite resource used in fertilizers. Urine contains high concentrations of P that can be recovered using urine diversion (UD), but current UD systems become clogged by P precipitation in piping, inhibiting their operations and reducing recoverable P. Dosing systems with acetic acid can prevent precipitation, resulting in more available nutrients for recovery. This study monitored a full-scale multistory UD system and implemented acid dosing to prevent clogging and produce urine suitable for P recovery. Both baseline (i.e., no acid) and acid dosing conditions were tested during normal and below-normal occupancies. In baseline systems, urine collected during below-normal occupancy had higher pH and greater nutrient losses compared to during normal occupancy. However, during both occupancies, baseline systems had clogs that decoupled occupancy patterns from urine collection in the tank and lowered the mass of recoverable P. During both occupancies, acid dosing dissolved pre-existing precipitate, resulting in ∼10× greater recoverable P than in baseline systems, and partially stabilized urine (>10%) and lowered pH (<9) until ∼7 days of operation, suggesting that urine can be immediately treated once the storage tank is full. The results demonstrate that acid dosing can prevent operation challenges in UD, improving UD’s technology readiness.

Taste and odor are crucial factors in evaluating the quality of drinking water for consumers. Geosmin is an example of a pollutant commonly found in potable water responsible for earthy and musty taste, and odor even at low concentrations. We have investigated the use of a hybrid two-step adsorption-mineralization process for low-level volatile organic compounds removal from potable water using dielectric barrier discharge over common metal oxides (MO). The system proposed is a proof of principle with tert-butanol (TBA) used as a model compound for geosmin removal/degradation during wastewater treatment when combined with an appropriate metal oxide adsorbent. Initial assessments of the adsorption properties of titania by density functional theory (DFT) calculations and experimental tests indicated that the adsorption of geosmin and TBA with water present results in only weak interactions between the sorbate and the metal oxide. In contrast, the DFT results show that alumina could be a suitable adsorbent for these tertiary alcohols and were reinforced by experimental studies. We find that while there is a competitive effect between the water and TBA adsorption from gaseous/liquid feed, the VOC can be removed, and the alumina will be regenerated by the reactive oxygen species (ROS) produced by a dielectric barrier discharge (DBD). The use of alumina in conjunction with NTP leads to efficient degradation of the adsorbate and the formation of oxygenated intermediates (formates, carbonates, and carboxylate-type species), which could then be mineralized for the regeneration of the adsorbent. A reaction mechanism has been proposed based on the in-situ infrared measurements and DFT calculations, while the removal of TBA with conventional heating is indicative of a gradual desorption process as a function of temperature rather than the destruction of the adsorbate. Furthermore, steady performance was observed after several adsorption–regeneration cycles, indicating no alteration of the adsorption properties of alumina during the NTP treatment and demonstrating the potential of the approach to be applied in the treatment of high throughput of water, without the challenges faced by the biocatalysts or formation of toxic byproducts.

This study presents the simultaneous conversion of food waste and CO₂ into volatile fatty acids (VFAs) using a 6 L tubular microbial electrosynthesis cell (MES). The MES reactor uses a bioanode to convert food waste into current and CO₂, while on the cathode, H₂ is produced and subsequently consumed by cathode microbes for the conversion of CO₂ to VFAs. The study reveals that system performance is impacted by organic loading, applied voltage, and flow rate, and optimal operational conditions achieve a VFA titer of 1763 mg/L with the Coulombic efficiency (CE) exceeding 90% at the anode, highlighting efficient electron recovery from food waste. Resistance analysis indicates that the cathode contributed most to system resistance, while microbial community analysis shows a synergy between fermentative and electroactive bacteria in the anode and dominant acetogens in the cathode, facilitating efficient electron recovery and VFA synthesis, respectively. The research underscores the tubular MES’s potential for sustainable food waste treatment and CO₂ valorization into valuable VFAs, contributing to waste management and greenhouse gas mitigation strategies.