Search Results (254)

Membrane bioreactors (MBRs) have been utilized for maricultural wastewater treatment, where high-salinity stress results in dramatic membrane fouling in the actual process. A microalgal–bacterial symbiotic system (MBSS) offers advantages for photosynthetic oxygen production, dynamically regulating the structure of extracellular polymeric substances (EPSs) and improving the salinity tolerance of bacteria and algae. This study centered on the mechanisms of membrane fouling mitigation via the microalgal–bacterial interactions in the MBSS, including improving the pollutant removal, optimizing the system parameters, and controlling the gel layer formation. Moreover, the contribution of electrochemistry to decreasing the inhibitory effects of high-salinity stress was investigated in the MBSS. Furthermore, patterns of shifts in microbial communities and the impacts have been explored using metagenomic technology. Finally, this review aims to offer new insights for membrane fouling mitigation in actual maricultural wastewater treatment. Full article

The escalating global demand for fresh water, driven by urbanization and industrial growth, underscores the need for sustainable water management, particularly in the water-intensive construction sector. Although prior studies have primarily concentrated on treated wastewater, the practical viability of utilizing untreated wastewater has not been thoroughly investigated—especially in developing nations where treatment expenses frequently impede actual implementation, even for non-structural uses. While prior research has focused on treated wastewater, the potential of untreated or partially treated wastewater from diverse industrial sources remains underexplored. This study investigates the feasibility of incorporating wastewater from textile, sugar mill, service station, sewage, and fertilizer industries into concrete paver block production. The novelty lies in a dual approach, combining experimental analysis with XGBoost-based machine learning (ML) models to predict the impact of key physicochemical parameters—such as Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Hardness—on mechanical properties like compressive strength (CS), water absorption (WA), ultrasonic pulse velocity (UPV), and dynamic modulus of elasticity (DME). The ML models showed high predictive accuracy for CS (R² = 0.92) and UPV (R² = 0.97 direct, 0.99 indirect), aligning closely with experimental data. Notably, concrete pavers produced with textile (CP-TXW) and sugar mill wastewater (CP-SUW) attained 28-day compressive strengths of 47.95 MPa and exceeding 48 MPa, respectively, conforming to ASTM C936 standards and demonstrating the potential to substitute fresh water for non-structural applications. These findings demonstrate the viability of using untreated wastewater in concrete production with minimal treatment, offering a cost-effective, sustainable solution that reduces fresh water dependency while supporting environmentally responsible construction practices aligned with SDG 6 (Clean Water and Sanitation) and SDG 12 (Responsible Consumption and Production). Additionally, the model serves as a practical screening tool for identifying and prioritizing viable wastewater sources in concrete production, complementing mandatory laboratory testing in industrial applications. Full article

Fenton oxidation can contribute to meeting effluent standards for COD in actual wastewater treatment plant effluents. However, Fenton oxidation is prone to produce iron sludge waste. The application of heterogeneous Fenton-like systems based on Fenton iron mud carbon in wastewater treatment plants is essential for Fenton iron mud reduction and recycling. In this study, a Fenton iron mud carbon catalyst/Ferrate salts/H₂O₂ (FSC/Fe(VI)/H₂O₂) system was developed to remove chemical oxygen demand (COD) from secondary effluents at the pilot scale. The results showed that the FSC/Fe(VI)/H₂O₂ system exhibited excellent COD removal performance with a removal rate of 57% under slightly neutral conditions in laboratory experiments. In addition, the effluent COD was stabilized below 40 mg·L⁻¹ for 65 days at the pilot scale. Fe(IV) and ¹O₂ were confirmed to be the main active species in the degradation process through electron paramagnetic resonance (EPR) and quenching experiments. C=O, O-C=O, N sites and Fe⁰ were responsible for the generation of Fe(IV) and ¹O₂ in the FSC/Fe(VI)/H₂O₂ system. Furthermore, the cost per ton of water treated by the pilot-scale FSC/Fe(VI)/H₂O₂ system was calculated to be only 0.6209 USD/t, further confirming the application potential of the FSC/Fe(VI)/H₂O₂ system. This study promotes the engineering application of heterogeneous Fenton-like systems for water treatment. Full article

This study investigates an innovative hybrid treatment for compost-derived wastewater, combining aluminum-based electrocoagulation (EC), zeolite addition, and magnet assistance. Key experimental variables—presence/absence of magnet, stirring speed (250 and 350 rpm), and contact time (10–30 min)—were systematically varied to analyze process efficiency, electrode dissolution and mass loss, solid–liquid separation dynamics, and quantify energy input and Faraday efficiency (FE). Magnet-assisted processes achieved higher COD reduction at longer treatment times of 30 min and lower mixing speeds of 250 rpm, with up to 89.87%. The highest turbidity reduction of 98.59% is achieved after 20 min at 350 rpm. The magnetic field does not significantly affect the dissolution of Al electrodes, but over time, it helps reduce localized electrode damage, thereby supporting both process efficiency and electrode longevity. Magnetic fields improved sludge settling in shorter treatments by promoting faster aggregation. However, the energy input was generally higher with magnetic assistance. FE in the range of 50.89–65.82% indicates that the actual electrode loss is lower than theoretical. For the experiments conducted according to the L8 Taguchi experimental design, given the significance and contribution of factors to the process, the optimal combination is the absence of a magnet, 350 rpm, and 20 min. Full article

Membrane separation technology has shown significant potential in the treatment of mixed dye wastewater. In this study, a reduced graphene oxide (AH-rGO) membrane was prepared using an amino-hydrothermal method and applied for the first time in mixed dye separation. These membranes can selectively recover high-value dyes while addressing the technical challenges of balancing permeability and selectivity in traditional membrane materials, which are often at odds with each other in the treatment of mixed dye wastewater. We simulated actual dye wastewater using four dyes: methyl orange (MO), methyl blue (MB), rhodamine B (RB), and Victoria Blue B (VBB). The four combinations of mixed dyes were MO/VBB, RB/VBB, MO/MB, and RB/MB, all of which demonstrated high water permeability and separation efficiency. Notably, the MO/VBB combination achieved a maximum water permeability rate of 118.79 L m⁻² h⁻¹ bar⁻¹ and a separation factor of 24.2. The AH-rGO membrane is currently the highest-permeability membrane available, achieving excellent separation results with typical mixed dye wastewater. Additionally, it demonstrates good stability. The experimental results indicate that the overall performance of the AH-rGO membrane is superior to that ofother graphene oxide (GO) membranes, which reveals the significant application potential of this membrane in the field of mixed dye wastewater treatment. Full article

This work investigates, for the first time, the application of a modified natural magnetite material with 35% of lanthanum for phosphorus (P) recovery from synthetic and actual wastewater under both static (batch) and dynamic (continuous stirred tank reactor (CSTR)) conditions. The characterization results showed that the natural feedstock mainly comprises magnetite and kaolinite. Moreover, the lanthanum-modified magnetite (La-MM) exhibited more enhanced textural, structural, and surface chemistry properties than the natural feedstock. In particular, its surface area (82.7 m² g⁻¹) and total pore volume (0.160 cm³ g⁻¹) were higher by 86.6% and 255.5%, respectively. The La-MM efficiently recovered P in batch mode under diverse experimental settings with an adsorption capacity of 50.7 mg g⁻¹, which is significantly greater than that of various engineered materials. It also maintained high efficiency even when used for the treatment of actual wastewater, with an adsorption capacity of 47.3 mg g⁻¹. In CSTR mode, the amount of P recovered from synthetic solutions and real wastewater decreased to 33.8 and 10.2 mg g⁻¹, respectively, due to the limited contact time. The phosphorus recovery process involves mainly electrostatic attraction over a wide pH interval, complexation, and precipitation as lanthanum phosphates. This investigation indicates that lanthanum-modified natural feedstocks from magnetite deposits can be regarded as promising materials for P recovery from aqueous solutions. Full article

Substantial boosts in the low-energy nano-oxygenation of incoming process water were achieved at a municipal wastewater treatment plant (WWTP) upstream of activated sludge (AS) aeration lanes on a single-pass basis by means of an electric field nanobubble (NB) generation method (with unit residence times of the order of just 10–15 s). Both ambient air and O₂ cylinders were used as gas sources. In both cases, it was found that the levels of dissolved oxygen (DO) were maintained far higher for much longer than those of conventionally aerated water in the AS lane—and at DO levels in the optimal operational WWTP oxygenation zone of about 2.5–3.5 mg/L. In the AS lanes themselves, there were also excellent conversions to nitrate from nitrite, owing to reactive oxygen species (ROS) and some improvements in BOD and E. coli profiles. Nanobubble-enhanced Dissolved Air Flotation (DAF) was found to be enhanced at shorter times for batch processes: settlement dynamics were slowed slightly initially upon contact with virgin NBs, although the overall time was not particularly affected, owing to faster settlement once the recruitment of micro-particulates took place around the NBs—actually making density-filtering ultimately more facile. The development of machine learning (ML) models predictive of NB populations was carried out in laboratory work with deionised water, in addition to WWTP influent water for a second class of field-oriented ML models based on a more narrow set of more easily and quickly measured data variables in the field, and correlations were found for a more facile prediction of important parameters, such as the NB generation rate and the particular dependent variable that is required to be correlated with the efficient and effective functioning of the nanobubble generator (NBG) for the task at hand—e.g., boosting dissolved oxygen (DO) or shifting Oxidative Reductive Potential (ORP). Full article

Aiming at the defects of the low mass transfer efficiency and large floor space of the traditional ozone process, a cross-tube ozone catalytic oxidation pilot plant was designed and developed. By implementing lateral aeration and a modular series configuration, the gas–liquid mass transfer pathways were optimized, achieving a hydraulic retention time of 25 min and maintaining an ozone dosage of 43 mg/L, which significantly improved the ozone utilization efficiency. During the pilot operation in an industrial park in Suzhou, Anhui Province, the average COD removal efficiency of the device for the actual biochemical tail water (COD 82.5~29.7 mg/L) reached 35.47%, and the effluent concentration was stably lower than 50 mg/L, which meets the stricter discharge standard. The intermediate products in the system were also analyzed by liquid chromatography–mass spectrometry (LC-MS), and the key pollutants were selected for degradation path analysis. Compared to the original tower process in the park, the ozone dosage was reduced by 46%, the reaction residence time was reduced by 60%, and the cost of water treatment was reduced to 0.067 USD, which is both economical and applicable to engineering. This process provides an efficient and low-cost solution for the deep treatment of wastewater in industrial parks, and has a broad engineering application prospect. Full article

Against the backdrop of China’s “dual carbon” strategy, investigating the carbon emission characteristics and low-carbon operational status of wastewater treatment plants (WWTPs) across regions is pivotal for achieving synergistic pollution reduction and carbon mitigation. Leveraging 2024 operational data from 98 WWTPs in eastern China—encompassing treatment volume, energy consumption, sludge production, and chemical dosages—this study refined the Assessment Standard for Carbon Mitigation in Municipal WWTPs and Technical Specification for Low-Carbon Operation of WWTPs. A novel carbon accounting framework and low-carbon performance evaluation system were subsequently developed to analyze the impacts of treatment scale, technological configuration, and load rate on carbon footprints. Key findings revealed an average carbon intensity of 0.399 kg CO₂-eq/m³ for the region, with small-scale facilities (0.582 kg CO₂-eq/m³) exhibiting significantly higher emissions compared to their large-scale counterparts (0.392 kg CO₂-eq/m³). Indirect emissions constituted 62.1% of the total footprint, while chemical dosing contributed 14.2%, primarily driven by carbon sources and phosphorus removal agents. Fossil-derived CO₂ accounted for 4.6% of emissions. Notably, the AAO process demonstrated the lowest carbon intensity (0.370 kg CO₂-eq/m³), whereas SBR systems registered the highest (0.617 kg CO₂-eq/m³). Furthermore, 25% of the assessed facilities were classified as high-emission plants. Strategic recommendations are proposed, including prioritizing AAO process optimization, implementing intelligent chemical dosing control, utilizing food wastewater as an alternative carbon source, and enhancing operational load rates, to advance synergistic environmental and carbon mitigation goals in eastern China’s wastewater sector. Full article

The removal of mercury(II) from aquatic environments using polyurea-crosslinked calcium alginate (X-alginate) aerogels was investigated through batch-type experiments, focusing on low mercury concentrations (50–180 μg·L⁻¹), similar to those found in actual contaminated environments. Within this concentration range, the metal retention was very high, ranging from 85% to quantitative (adsorbent dosage: 0.6 g L⁻¹). The adsorption process followed the Langmuir isotherm model with a sorption capacity of 4.4 mmol kg⁻¹ (883 mg kg⁻¹) at pH 3.3. Post-adsorption analysis with EDS confirmed the presence of mercury in the adsorbent and the replacement of calcium in the aerogel matrix. Additionally, coordination/interaction with other functional groups on the adsorbent surface may occur. The adsorption kinetics were best described by the pseudo-first-order model, indicating a diffusion-controlled mechanism and relatively weak interactions. The adsorbent was regenerated via washing with a Na₂EDTA solution and reused at least three times without substantial loss of sorption capacity. Furthermore, X-alginate aerogels were tested for mercury removal from an industrial wastewater sample (pH 7.75) containing 61 μg·L⁻¹ mercury (and competing ions), achieving 71% metal retention. These findings, along with the stability of X-alginate aerogels in natural waters and wastewaters, highlight their potential for sustainable mercury removal applications. Full article

Micropollutants (MPs), which include both natural and manmade substances, are becoming more prevalent in aquatic habitats as a result of the insufficient removal of these compounds in wastewater treatment plants (WWTPs). Advanced remediation techniques are required due to their persistence and potential ecotoxicological hazards. Although adsorption and photo(electro)catalysis exhibit potential in laboratory-scale investigations, the effects of their use in actual WWTP systems are still poorly understood. However, before large-scale application can be implemented, a number of issues need to be resolved, including material limitations, reactor design and optimization, and actual wastewater complexities. This study critically evaluates the application of adsorption and photo(electro)catalysis to actual wastewater, as well as recent advancements in adsorption and photo(electro)catalytic systems for the removal of micropollutants. We also explore the particular difficulties and strategies involved in the large-scale use of adsorption and photo(electro)catalysis in the treatment of wastewater. Emerging trends such as nanocomposites, metal–organic frameworks (MOFs), heterojunctions, and single-atom catalysts (SACs) are highlighted by the bibliometric analysis. We also evaluate MPs’ ecological effects in aquatic environments and the incorporation of artificial intelligence (AI) for process optimization. A strategy for transferring nanotechnologies from laboratory-scale research to wastewater treatment implementation is presented in this paper. In this strategy, implementation is proposed based on actual wastewater conditions, focusing on the development of adsorbents and catalysts, reactor design and optimization, synergy between adsorption and catalysis, life cycle analysis, and cost–benefit studies. Full article

Heavy metal contamination in livestock and poultry farm wastewater poses significant risks to both the environment and human health, so it is critical to accurately and rapidly quantify heavy metal ion concentrations in water. This research develops a bioelectric active hydrogel sensor for detecting heavy metal ions in livestock wastewater. The sensor integrates microbial surface display technology with graphene hydrogel, displaying glucose oxidase (GOx) on the surface of yeast cells, and covalently incorporating it into the graphene hydrogel through the bio-reduction activity of metal-reducing bacteria, enhancing its electrochemical performance. The sensor demonstrates excellent sensitivity and stability in detecting Cu²⁺, with a detection limit for Cu²⁺ of 17.0 µM. This sensor is also applicable for detecting Zn²⁺ in wastewater. When various heavy metal ions coexist in the solution, they exert a more pronounced inhibitory effect on enzyme activity. Consequently, the sensor can be employed to assess the overall heavy metal content in water samples. In the detection of Cu²⁺ in real livestock and poultry wastewater, the recovery rate of the graphene hydrogel electrode ranged from 88% to 106.5%, indicating that the sensor holds significant potential for application in actual sample analysis. Full article

The building drainage system (BDS) is a critical building component and must be designed to protect public health by maintaining safe and hygienic conditions within the indoor environment. The recent COVID-19 pandemic and the emergence of other wastewater-related issues, such as the spread of anti-microbial resistance (AMR), place the BDS at the centre of the public health agenda. To understand the complex characteristics of the BDS and its performance, the numerical simulation model AIRNET was used to model whole system responses to discharging events. In this study, the model’s effectiveness and accuracy were evaluated through its application in a case study system representative of a real-world tall building. Data reflecting actual conditions were collected using the drainage test rig at the National Lift Tower (NLT) in Northampton. The data show a strong correlation between the measured and modelled air pressures in the system over time and along the drainage stack height. More importantly, a sample dataset representing various ventilation configurations, flow rates, and water usage combinations shows a strong linear relationship between the simulated and measured pressure values. These results confirm the accuracy and reliability of the AIRNET model in modelling the BDS, even when applied to high-rise buildings. This is crucial for addressing drainage challenges in high-rise building design. Full article

The abuse of chemical agents in wastewater treatment is very universal. However, accurate predictive models capable of addressing this issue rely on precise and abundant data. Limitations in sampling frequency and equipment often lead to insufficient data, resulting in model overfitting. To address this, the IA Mix-up data augmentation algorithm, based on correlation coefficient-weighted mixing, has been proposed. By ranking the temporal correlation of water quality data and incorporating error weight mixing into original labels, the algorithm adjusts mixed label weights according to the temporal characteristics of the original signal, preserving time-series correlation. Experimental results demonstrate an average 8.75% improvement in prediction accuracy across four neural network models, with R²-e reduced to 1–5%. Among the four prediction models, the LSTM model has the highest prediction accuracy of 89%. Compared with existing time-series data augmentation methods, IA Mix-up enhances the r value by 9.5%, improves prediction accuracy by 7%, and reduces the training-validation prediction error by 3.67%. These results indicate that the proposed algorithm effectively mitigates overfitting and enhances model performance. In actual use, the total phosphorus in the effluent meets the Class I effluent standards while saving 33% of polyaluminum chloride. Full article

This study achieved the preparation of budget-friendly stratified Ca-Al adsorbents using a simplified precipitation synthesis route with subsequent pyroprocessing, showing superior defluoridation capabilities in aqueous environments. The structural properties and defluoridation performance of the adsorbents were systematically investigated by optimizing critical synthesis parameters, including calcium-to-aluminum molar ratios, the solution pH during co-precipitation, and calcination temperature. Characterization results revealed that the optimal sample (prepared at a Ca/Al ratio of 2:3, initial pH of 10, and calcination temperature of 600 °C) exhibited a high specific surface area, ordered mesoporous structure, and abundant surface hydroxyl groups, facilitating efficient fluoride adsorption. Batch adsorption experiments demonstrated significant effects of adsorbent mass, solution pH, and initial fluoride concentration on removal efficiency. The isothermal adsorption characteristics conformed to the Langmuir model, complemented by pseudo-second-order kinetic compliance, which jointly confirmed chemisorption-dominated monolayer coverage. Notably, the maximum adsorption capacity reached 263.33 mg g⁻¹, surpassing most comparable adsorbents reported in the literature. The material maintained a superior fluoride removal performance across a wide pH range (4~12) and exhibited superior recyclability. Rapid adsorption kinetics were observed, with equilibrium achieved within 60 min. The material showed a good removal effect in actual fluoride-containing smelting wastewater, which further proved its application potential. In addition, the analysis of the adsorption mechanism showed that the removal of fluoride was mainly achieved through the coordination between fluoride and metal ions and the ion-exchange reaction with surface hydroxyl groups. These findings suggest that the adsorbent has significant prospects for practical water quality fluoride removal applications. Full article