Water Science and Technology最新文献

The increasing use of intermittent aeration controllers in wastewater treatment plants (WWTPs) aims to reduce aeration costs via continuous ammonia and oxygen measurements but faces challenges in detecting sensor and process anomalies. Applying machine learning to this unbalanced, multivariate, multiclass classification challenge requires much data, difficult to obtain from a new plant. This study develops a machine learning algorithm to identify anomalies in intermittent aeration WWTPs, adaptable to new plants with limited data. Utilizing active learning, the method iteratively selects samples from the target domain to fine-tune a gradient-boosting model initially trained on data from 17 plants. Three sampling strategies were tested, with low probability and high entropy sampling proving effective in early adaptation, achieving an F2-score close to the optimal with minimal sample use. The objective is to deploy these models as decision support systems for WWTP management, providing a strategy for efficient model adaptation to new plants, and optimizing labeling efforts.

In this study, three different materials were investigated for their ability to degrade benzene, toluene, and xylene (BTX) using light energy. The materials studied were activated charcoal (AC), zeolitic imidazolate framework (ZIF-8), and zirconium metal-organic framework (Zr-MOF). Initially, AC, ZIF-8, and Zr-MOF were characterized using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) surface area analysis, and spectroscopic analysis techniques. Based on their excellent features, that is, band gap (5.5, 5.45, and 4.75 eV), surface area (711.5, 1,122.1, and 535.4 m²/g), and pore volume (0.291, 0.369, and 0.628 cm³/g), a comparative photodegradation analysis of BTX was performed in acetonitrile. We found that Zr-MOF is the best photocatalyst to degrade BTX, with degradation percentages of 97, 95, and 94% (B > T > X), respectively, followed by ZIF-8 and AC. Our study suggests that these photocatalysts can be used to degrade BTX using light energy, which could reduce the health and environmental impacts of BTX. Our results illustrate that advanced porous materials may be established as photocatalyst materials with the potential to address the long-standing challenges associated with pollutant degradation.

Despite water being a significant output of water and resource recovery facilities (WRRFs), tertiary wastewater treatment processes are often underrepresented in integrated WRRF models. This study critically reviews the approaches used in comprehensive models for ozone (O₃) and biological activated carbon (BAC) operation units for wastewater tertiary treatment systems. The current models are characterised by limitations in the mechanisms that describe O₃ disinfection and disinfection by-product formation, and BAC adsorption in multi-component solutes. Drawing from the insights from the current O₃, BAC, and WRRF modelling approaches, we propose an integrated O₃-BAC model suitable for simulating dissolved organic carbon (DOC) and micropollutants removal in the O₃-BAC systems. We recommend a hybrid modelling approach in which data-driven models can be integrated to compensate for structural limitations in mechanistic models. The model is developed within the activated sludge model (ASM) framework for flexibility in coupling with other WRRF models and hence facilitates developing system-wide WRRF models for wastewater reclamation and reuse systems.

While several studies have investigated the effect of varying carbon-to-nitrogen (C/N) ratios on the ANAMMOX performance, there is still a research gap in illustrating the shift in 16S rRNA gene copy number and functional microbial population during operation. Hence, this study focuses on utilizing a reference gene and target functional genes to demonstrate the synergetic interaction between ANAMMOX, ammonia-oxidizing bacteria (AOB), and nitrite-oxidizing bacteria (NOB), using an up-flow anaerobic sludge blanket (UASB) under different C/N conditions. It was demonstrated that elevating the C/N ratio from 1.0 to 2.0 reduced the COD and NH4⁺-N removal efficiencies from 80.12 to 48.62% and from 88.99 to 72.59%, respectively. Based on the qPCR evaluation, at the C/N ratio of 1.5, the abundance of ANAMMOX, AOB, Nitrobacter, and Nitrospira was 2.52 × 10⁶, 82, 5.39 × 10³, and 12.98 × 10³ copies/μL, respectively. However, with the further increase of C/N ratio to 2.0, their abundance was reduced to 1.09 × 10⁶, 46, 0.98 × 10³, and 3.47 × 10³ copies/μL, respectively. The expression of hzo gene encoding for hydrazine dehydrogenase was 169-folds at C/N = 1 and almost inhibited at C/N = 2. The results of microbial population structure using 16S rRNA reverse transcriptase (RT)-qPCR technique depicted a competition between ANAMMOX and heterotrophic bacteria for the available substrate at higher C/N ratios.

This study extends a previously developed competitive modeling approach for predicting the adsorption of organic micropollutants (OMPs) on powdered activated carbon (PAC) in full-scale advanced wastewater treatment. The approach incorporates adsorption analysis for organic matter fractionation, assumes pseudo-first order kinetics and differentiates between fresh and partially loaded PAC through fraction segregation. Validation through full-scale measurement campaigns reveals successful model predictions of OMP removal, underestimating, however, diclofenac removals by 15-20%. Based on model testing, the impact of excess PAC return to the biological stage enhanced OMP removal, reaching up to 15% improvement for benzotriazole, carbamazepine and metoprolol, but no evident improvement of diclofenac removal. Intermittent PAC dosing revealed rapid process response, where organic matter concentration increased within 2 h after PAC cut-off. The simulation-based study demonstrated that during rain events, the overall OMP removal efficiency in the entire wastewater treatment plant was reduced by approximately 50% due to a shift of OMP concentration and a shortened hydraulic retention time in the biological and adsorption stages. Testing of various PAC dosing strategies revealed potential PAC savings of 10-15% compared to inflow-proportional dosing by using predefined OMP removal grades or maximum allowable effluent OMP concentrations as criteria for PAC dosing.

The current global water crisis has prompted research into technologies that can reuse different water resources to mitigate water scarcity. The use of treated greywater can be proposed to provide additional water resources. By reusing this water in different applications, this water crisis can be mitigated at the local scale. This study presents a bibliometric analysis to assess the state of the art of greywater treatment and its reuse technologies. This analysis is based on the scientific literature published until 2023 in Scopus regarding greywater treatment and 1,024 documents were found. The results showed a clear exponential increase in the accumulated number of publications in this topic, which was spurred during the mid-1990s. The most prolific country was the United States, while China, the other typical scientific superpower in most fields, occupied the sixth position in the ranking. Environmental Sciences was the knowledge subject with more documents, followed by Engineering and Chemical Engineering. The bibliometric study was complemented using SciMAT to create bibliometric networks that represent the dynamic evolution of the themes. The most important themes were identified, among which three key points stand out: greywater characterization, technologies for greywater treatment, and water management, including the reuse of treated greywater.

Reducing blue and total water footprint outputs in irrigated agriculture with greywater footprint input from irrigation with recycled wastewater is an issue that needs to be investigated in protecting freshwater resources by increasing water availability. Therefore, the effect of three different irrigation levels of recycled wastewater and freshwater in the subsurface drip irrigation (SSDI), surface drip irrigation (SDI), and furrow irrigation (FI) methods on the blue, green, grey, and total water footprints per unit yield of silage maize, which is widely produced worldwide and has high water consumption, was investigated with a 2-year field study. The blue and total water footprints per unit fresh and dry biomass yields in the SSDI were 1.20-1.23-fold lower than that in the SDI and 1.69-1.76-fold lower than that in the FI. Full wastewater irrigation provided the lowest blue, green, and total water footprints per unit yield across all methods. Full wastewater irrigation under SSDI provided the lowest total water footprint per unit fresh biomass yield, similar to the 33% deficit irrigation practice with wastewater. It was concluded that full irrigation with recycled wastewater as a greywater resource under SSDI may be the most suitable application for the sustainable management of scarce blue water resources.

Rotating algae biofilm reactors (RABRs) can reduce energy requirements for wastewater reclamation but require further optimization for implementation at water resource recovery facilities (WRRF). Optimizing RABR operation is challenging because conditions at WRRF change frequently, and disregarding interaction terms related to these changes can produce incorrect conclusions about RABR behavior. This study evaluated the two-way interaction and main effects of four factors on the biomass productivity and phosphorus removal efficiency of a microalgae-bacteria biofilm grown in municipal anaerobic digester centrate, with factor levels and operating conditions selected to mimic a pilot RABR at a WRRF in Utah. Two-way interactions harvesting period*light intensity (LI), harvesting period*temperature, and LI*hydraulic retention time (HRT) had significant effects on biomass productivity: at high temperature and low LI, highest biomass productivity was achieved with a 14-day harvesting period, but at medium temperature and high LI, highest biomass productivity was achieved with a 7-day harvesting period. At high HRT, highest biomass productivity occurred at low LI, but at low HRT, highest biomass productivity occurred at high LI. Phosphorus removal was strongly influenced by LI and occurred most rapidly during the first 2 days HRT, which suggests precipitation contributed significantly to phosphorus removal. These observations provide insight for further RABR optimization.

Moving bed biofilm reactors can purify urban domestic sewage through microbial biodegradation. High-throughput sequencing was used to study the response mechanism of the biofilm microbial community to temperature. The effluent quality of the reactor declined with the decrease in temperature. Proteobacteria, Bacteroidota, and Nitrospirota were the dominant bacteria, accounting for 59.2, 11.9, and 9.4%, respectively. Gammaproteobacteria (38.3%), Alphaproteobacteria (23.2%), and Bacteroidia (12.4%) were the dominant bacteria at the class level. Low temperature had an obvious directional domestication effect on microbial flora, and the composition of the bacterial community was more similar. Pseudomonas was one of the dominant bacterial groups at 5 °C. Nitrospira (p < 0.001) and Trichococcus (p < 0.05) were significantly negatively correlated with effluent ammonia nitrogen and significantly positively correlated with NO₃^- (p < 0.05) at low temperature. Functional bacteria related to chemoheterotrophy (25.88%) and aerobic_chemoheterotrophy (21.56%) accounted for a relatively high proportion. The bacteria related to nitrate reduction only accounted for 2.62%. Studies have shown that low temperatures can inhibit the growth of nitrogen-cycling bacteria, and few domesticated and selected nitrogen-cycling bacteria play a major role in the removal and transformation of ammonia nitrogen. The degradation of chemical oxygen demand can still be achieved through the adsorption and degradation of dominant functional bacteria.

The use of activated sludge models (ASMs) is a common way in the field of wastewater engineering in terms of plant design, development, optimization, and testing of stand-alone treatment plants. The focus of this study was the development of a joint control system (JCS) for a municipal wastewater treatment plant (mWWTP) and an upstream industrial wastewater treatment plant (iWWTP) to create synergies for saving aeration energy. Therefore, an ASM3 + BioP model of the mWWTP was developed to test different scenarios and to find the best set-points for the novel JCS. A predictive equation for the total nitrogen load (TN) coming from the iWWTP was developed based on real-time data. The predictive TN equation together with an optimized aeration strategy, based on the modelling results, was implemented as JCS. First results of the implementation of the JCS in the real environment showed an increase in energy efficiency for TN removal.