Water Science and Technology最新文献

Emissions from urban drainage systems can have unwanted consequences for human and environmental health. Unfortunately, traditional water quality monitoring in sewers is expensive and not comprehensive enough to provide detailed data on pollution across an entire catchment. However, with the increasing digitization of society, alternative data sources such as mobile positioning data offer new opportunities to assess wastewater production and dynamics. In this study, we investigate the relation between mobile positioning data and wastewater flows in five catchments in Switzerland with different characteristics and sizes, using data from the largest Swiss telecom provider and simple multiple linear regression models. The initial results of this study are promising although the degree of correlation observed between mobile positioning data and wastewater production is rather low (R² between 0 and 0.73) and varies greatly from catchment to catchment. As expected, we find nonlinear effects in the data that indicate that advanced models - incorporating factors like flow distances and dynamic travel times - are needed for reliable predictions. Also, data privacy issues limit its use in small catchments, highlighting the need for domain-specific preprocessing. This approach holds potential for urban drainage, wastewater treatment, drinking water, epidemiology, and climate adaptation.

The greenhouse gas nitrous oxide, a byproduct of the biological nitrogen removal in wastewater treatment plants (WWTPs), strongly impacts the carbon footprint of the wastewater sector due to its high global warming potential. Although plant design and operational process optimization can reduce N₂O generation and emission, complete avoidance is not possible according to the current knowledge. While physical-chemical end-of-pipe technologies are available for the removal of nitrous oxide in industrial off-gases, a feasible treatment for the exhaust air of WWTPs still needs to be established. This paper critically reviews the currently available treatment technologies, with particular focus on biological systems, as bioscrubbers. The review indicated that implementing N₂O removal technologies is more feasible in sidestream than in the mainstream wastewater treatment. This is primarily due to the smaller area required for exhaust air collection, lower air flowrates, and higher N₂O concentrations observed in the sidestream. Therefore, the proposed concept focuses on sidestream application and is based on the following two main pillars: (i) introducing sidestream deammonification of the sludge dewatering effluent to deplete the N₂O emission factor in the mainstream biological stage and (ii) treating the N₂O-rich exhaust air from the deammonification process using a denitrifying bioscrubber with wastewater as an organic carbon source.

Pakistan's fresh water supply declined significantly from 5,260 to 1,014 m³/person/year between 1950 and 2018. Water-intensive operations of the textile industry further aggravate this fresh water scarcity by contributing significant pollution. This study uses life cycle assessment (LCA) to examine the environmental effects of textile production with emphasis on human health, resources, and ecosystem. Potential sustainable solutions are offered by innovations like energy efficiency techniques and closed-loop water recycling systems. Environmental trade-offs in this study are measured between energy optimization and water recycling. Effects such as resource depletion (RD), global warming potential (GWP), and eutrophication potential (EP) are evaluated. The efficacy of these integrated techniques is demonstrated in results. Energy optimization and integrated solutions reduce GWP by 30.7 and 33.1%, respectively, and water consumption by 43.6 and 43.9%, respectively. However, these approaches also result in trade-offs, including increased freshwater ecotoxicity and depletion of fossil resources. In summary, combining renewable energy with water recycling has significant environmental advantages, but long-term sustainability necessitates rigorous trade-off management and optimization. The textile sector should adopt similar circular economy strategies, supported by robust data collection and monitoring frameworks.

Urban water environment pollution is a pressing global concern, particularly in developing countries where inadequate infrastructure contributes significantly to this challenge. This study builds upon these principles by enhancing drainage pipeline inspection technologies, aiming to streamline processes and reduce resource consumption. This research advances the integration of gyroscopes and accelerometers within a sextuple-axis sensor framework, streamlining a workflow wherein the inspection apparatus is introduced into the conduit and navigates with the fluid motion to aggregate data. The implementation of an attitude determination algorithm rooted in the extended Kalman filter underpins the processing of sensor-acquired data, yielding precise tridimensional attitude measures. Additionally, a refined peak-to-peak anomaly detection technique, based on an adaptive peak algorithm, analyzes the attitude measures to pinpoint deviations in the device's orientation. Empirical evaluations corroborate that the second-generation pipeline inspection device conceived in this study boasts augmented stability and transit efficacy. The integrated approach for attitude calculation and anomaly discernment coalesces data from gyroscopes and accelerometers, guaranteeing meticulous orientation angle computation and enhanced precision in anomaly detection. This accuracy is vital for the accurate replication of the detector's positioning within the pipeline infrastructure and for a comprehensive understanding of the operational state of drainage conduits.

The solid retention time (SRT) is one of the most important parameters for the operation of a wastewater treatment plant (WWTP). Maintaining the SRT at the prescribed set-point is necessary to achieve an appropriate food-to-microorganism (F/M) ratio. This article describes the design and implementation of SRT control at the Ljubljana WWTP. The designed SRT control wastes a defined proportion of the mixed liquor suspended solid (MLSS) mass in the aerobic reactors. The sludge wasted from the secondary settlers is determined based on measurements of the MLSS concentration, waste sludge concentration, and waste sludge flow rate. The SRT control is simple and does not require an SRT estimation or an SRT feedback controller. It includes a constraining controller that keeps the MLSS in the aerobic reactors within the prescribed minimum and maximum values. Validation of the designed SRT control on a mathematical model of the Ljubljana WWTP shows better set-point tracking than the proportional integral (PI) SRT control, as well as reduced SRT variations and lower ammonia nitrogen concentrations compared to the initial MLSS control. The testing of the designed SRT control at the Ljubljana WWTP confirmed the set-point tracking and reduced SRT variations despite large influent variations and operational disturbances.

Due to the numerous geometric parameters and complex hydraulic behaviors of piano key weirs (PKWs), accurately estimating their discharge capacity remains challenging without in-depth experimental studies or computational modeling. This study compares and analyzes recent discharge equations and develops new relationships between key parameters influencing the discharge capacity of PKWs, including the weir height P, weir width W, and effective crest length L. A modified theoretical discharge equation is proposed, derived from dimensional analysis and supported by existing experimental data. The calculated values from the equation agree well with the earlier experimental and the prototype observation results. For the relative water head H/P range from 0.1 to 1.5, the mean absolute percentage error remains below 8%. The proposed modified discharge method offers high accuracy and a simple form, providing a more precise description of the influence of PKW geometric parameters on discharge capacity, making it highly practical for engineering applications.

In urban stormwater source control design, the current method statistically obtains the design target-daily rainfall relationship and uses daily rainfall as the design storm to calculate the size of source control. Since it lacks the rainfall duration needed for sizing calculations under the design storm, it cannot ensure that the design solution achieves the design target. To overcome this problem, this study proposes a statistical method to obtain an hour-level design storm. It includes hour-level event identification, the concept of design storm event set, and a method to obtain the design target-rainfall-duration-maximum 1-h rainfall relationship. Model-based case study results suggested that rainfall volume control was more suitable than rainfall event percentile control as a design target because design solutions achieved the former but not the latter. Across six climate conditions, rainfalls and durations had logarithmic correlations ranging from 0.8454 to 0.9868. The positive near-monotonic relationships supported the source control sizing calculation under the design storm. Besides, a maximum 1-h rainfall could be used to calculate the hydraulic conductivity of planting soil layers, ensuring that the runoff peak penetrates the source control rather than off-site discharge through overflow. The hour-level design storm includes rainfall duration and maximum 1-h rainfall that vary with design target and design rainfall, which is an advantage over a day-level design storm.

Fog water harvesting has emerged as a promising and cost-effective solution to address water scarcity, particularly in remote and arid regions where conventional water supply systems are often unfeasible. This review highlights the potential of fog collectors for providing drinking water, with a focus on successful large fog collector projects worldwide. Despite their potential, sustainability challenges persist due to maintenance issues influenced by environmental conditions and social factors. Recent advancements in fog collection technologies are primarily achieved through the use of nanotechnology and structural improvements, aiming to develop efficient and low-cost fog collectors adaptable to diverse conditions. This paper critically examines the conceptual designs, experimental innovations, and operational performances of fog harvesting systems, specifically for drinking water supply in remote areas. By reviewing global successes and failures, it identifies key challenges and offers insights to enhance future research and practical applications, contributing to sustainable water resource management in regions with limited water access.

The use of moving bed biofilm reactor (MBBR) systems for the treatment of municipal and industrial wastewater has been shown to gain more attention, in contrast to activated sludge systems. However, little is known about the effects of pharmaceuticals on constituent microbial communities. This study investigated the shift in microbial community compositions of biofilms in an MBBR due to exposure to specific antiretroviral (ARV) compounds. Microbial diversity (alpha-diversity) of seeded sludge from a full-scale municipal wastewater treatment plant and biofilm samples from a laboratory-scale MBBR system during pre- and post-introduction of ARV compounds was investigated by Illumina sequencing of the 16S rRNA gene. Microbial diversity results demonstrated that the introduction of ARV drugs affects the bacterial community composition and diversity considerably. For instance, the genus Nitrosomonas, Nitrospira, and Alicycliphilus was found to be higher in post-introduction of ARV compounds biofilm samples than in biofilm samples before the introduction of ARV compounds.

This study provides an uncertainty analysis for a simplified anaerobic digestion model in agricultural biogas production, with implications for model output prioritization during parameter identification. Uncertainty in feed measurements is identified as a primary source of parameter uncertainty, magnifying and cascading into model output uncertainty. Experimental co-digestion of maize silage and cattle slurry is used for model validation. The model results in normalized Nash-Sutcliffe efficiencies of 0.87 for the methane flow rate, 0.8 for the acetic acid concentration, 0.74 for total ammoniacal nitrogen, and 0.7 for effluent volatile solids. Effluent total solids and pH value are modeled at 0.2 and 0.37, respectively. The model gives precise estimates of pH and gas concentrations, with coefficients of variation of 1 and 3-4%, respectively. Reasonably precise output states include effluent total and volatile solids, the methane flow rate and total ammoniacal nitrogen with coefficients of variation of 16, 7, 10, and 18%, respectively. Acetic acid concentration shows the highest coefficients of variation, as high as 81%. These findings provide implications for the development of more reliable and trustworthy forecasts in anaerobic digestion, contributing to more efficient and reliable process control.