Search Results (947)

The performance of biological wastewater treatment processes directly impacts water resource recycling and ecological safety. This year-long study compared full-scale wastewater treatment plants (WWTPs) using either the anaerobic/anoxic/aerobic (AAO) or modified Bardenpho process. By integrating water quality analysis with 16S rRNA sequencing, we examined how process type, influent quality, and seasonal factors affect microbial communities and treatment performance. Systems with high chemical oxygen demand (COD) and biochemical oxygen demand (BOD)/COD influent exhibited the best pollutant removal performance, with average nitrogen and phosphorus concentrations in the effluent as low as 7.0 mg/L and 0.1 mg/L, respectively. Optimizing a 1:9 influent distribution ratio between the pre-anoxic and first anoxic zones in the modified Bardenpho process increased total nitrogen (TN) removal efficiency by an average of 14 percentage points compared to the AAO process. Additionally, the modified Bardenpho process identified 1100 bacterial genera, indicating a more complex and stable community. Influent water quality had the most significant impact on microbial communities and treatment efficiency, followed by seasonal factors and process type. This study provides theoretical and data support for the optimization of wastewater treatment processes and seasonal regulations. Full article

Chrome tanning of fish skins generates hazardous effluents and carcinogenic Cr(VI) residues; chromium-free routes to valorize collagen-rich by-products from aquaculture and coastal fisheries are therefore needed. We report a 12-stage ecological protocol employing acetic acid/NaCl pickling, Acacia mearnsii tannin, A. podalyriifolia retanning, mashed-papaya enzymatic bating, and cinnamon as antimicrobial/odor adjunct, scaled from bench to pilot using exclusively locally sourced inputs, for Nile tilapia (Oreochromis niloticus) and Patagonian flounder (Paralichthys patagonicus). Three trained operators evaluated macroscopic quality against five predefined criteria adapted from SATRA and ISO 3376 grading conventions, providing a structured feasibility baseline that does not substitute for the standardized instrumental testing designated as priority future work. Both species achieved satisfactory grain stability, complete tannin penetration, pliable handle, and cinnamon-dominant odor without residual amines; dark-brown coloration is a recognized practical limitation for fashion applications. In silico molecular docking (GNINA v1.0) was used to explore the mechanistic plausibility of each ecological substitution, generating testable hypotheses rather than definitive mechanistic conclusions: the multidentate polyphenol proxy (PGG) exhibited consistently superior collagen engagement over the flavanol monomer across both collagen constructs and all three scoring metrics (1CAG: Vina affinity −5.51 ± 0.13 vs. −3.54 ± 0.35 kcal/mol; CNNscore 0.874 ± 0.009 vs. 0.771 ± 0.010; 7CWK: Vina affinity −6.98 ± 1.43 vs. −4.37 ± 0.16 kcal/mol; CNNscore 0.858 ± 0.024 vs. 0.635 ± 0.094). Dipeptide probes were reproducibly accommodated in the papain catalytic cleft, with the closest configuration reaching 3.997 Å from the catalytic nucleophile (OCS25-SG). Trans-cinnamaldehyde occupied the quorum-sensing pocket with reproducible placement (CNNscore 0.718 ± 0.034) but without score-based selectivity over structural decoys, a result interpreted as hypothesis-generating for future microbiological validation. The protocol is reproducible from bench to pilot and generalizable across two species with distinct dermal architectures. Quantitative physical-mechanical testing (shrinkage temperature, tensile strength, elongation, tear load), CIELab colorimetric analysis, and effluent characterization (COD, BOD₅, total phenolics) are designated as priorities for future validation. Full article

Accurate prediction and optimization of effluent quality are essential for the stable operation of wastewater treatment plants under increasing influent variability and stringent discharge regulations. This study presents an integrated data-driven framework that combines machine learning, deep learning, model interpretability, and optimization to enhance the performance of a full-scale Modified Ludzack–Ettinger (MLE) process. Three years of operational data from a municipal wastewater treatment plant were used to develop and compare random forest (RF), k-nearest neighbors (K-NN), multilayer perceptron (MLP), and deep neural network (DNN) models for the simultaneous prediction of effluent total organic carbon (TOC), biochemical oxygen demand (BOD), and total nitrogen (TN). Model performance was evaluated using the coefficient of determination (R²) and root mean square error (RMSE), and generalization capability was validated using independent field data. The results show that deep learning models, particularly DNN, outperform conventional machine learning approaches by effectively capturing complex nonlinear and multivariate process dynamics. To improve model interpretability, SHapley Additive exPlanations (SHAP) were applied to identify key operational variables affecting effluent quality. In addition, particle swarm optimization (PSO) was integrated with the trained models to determine optimal operating conditions that minimize effluent pollutant concentrations without requiring structural modifications. Overall, the proposed framework provides an interpretable and practical decision-support tool for proactive wastewater treatment plant operation, contributing to improved operational efficiency and environmental sustainability. Full article

This study compares the effects of pulsed and continuous ultrasound at two frequencies (28 and 40 kHz) on hybrid electrocoagulation (EC) systems for the treatment of compost wastewater, combining zeolite addition with different electrode pairs (Al/Al, Fe/Fe, Zn/Zn, and Al/Fe). The experimental investigation addressed four complementary aspects: (i) effluent quality and treatment efficiency evaluation through solution parameters monitoring, (ii) electrode degradation assessment through mass loss measurements and surface analysis, (iii) sedimentation analysis, and (iv) operational costs evaluation in terms of electrode and energy consumption. Process optimization was conducted using a mixed Taguchi L8 design to quantify the combined influence of electrode pairs, ultrasound mode and frequency, zeolite addition, and treatment time on pollutant removal and electrode wear. Operational cost calculation demonstrated that electrode material, ultrasound mode, and frequency, along with applied current and voltage, collectively govern electrode wear and Faraday efficiency, with pulsed ultrasound at 40 kHz and Al electrodes minimizing anodic mass loss and energy consumption. The Taguchi analysis revealed that zeolite addition is the most influential factor negatively affecting COD and turbidity. Meanwhile, the optimal operational parameters for overall performance were identified as an Al/Al electrode pair, a 40 kHz ultrasound frequency, pulsed mode, a 10 min treatment time, and the absence of zeolite. These findings provide practical guidance for designing hybrid pulsed ultrasound EC processes that are both effective and economically sustainable for complex wastewater treatment. Full article

Sulfamethoxazole (SMX) is one of the most frequently detected antibiotics in aquatic environments and is difficult to remove by conventional biological treatment because of its persistence, potential toxicity to microbial communities, and associated risk of antibiotic resistance selection. Aerobic granular sludge membrane bioreactors (AGMBRs), which combine the compact and stratified structure of aerobic granular sludge with membrane-based solid–liquid separation, have emerged as a promising platform for SMX-contaminated wastewater treatment because they provide high biomass retention, decoupled sludge retention time (SRT) and hydraulic retention time (HRT), and stable effluent quality. This review systematically summarizes recent advances in AGMBRs for SMX removal, with emphasis on how operating parameters (e.g., dissolved oxygen, hydraulic retention time, organic loading rate, C/N ratio, and sludge retention time) and membrane-related factors (e.g., membrane flux, aeration-induced shear, membrane type, and pore size) affect treatment performance and process stability. The main SMX attenuation pathways in AGMBRs are discussed from three perspectives: sorption and partitioning within granules and extracellular polymeric substances (EPSs), microbial biodegradation and co-metabolism, and membrane retention that prolongs effective contact time and shapes microbial ecology. Particular attention is given to the dual role of EPS and soluble microbial products (SMPs), which contribute to granule stability and SMX tolerance but also accelerate membrane fouling through cake-layer formation, pore blocking, and transmembrane pressure increase. Current challenges include incomplete understanding of transformation products, ARG- and MGE-related risks, long-term fouling–biodegradation interactions, and the lack of pilot-scale validation. Future research should therefore focus on mechanism clarification, integrated control of removal and fouling, energy-efficient operation, and scale-up of AGMBRs for practical antibiotic wastewater treatment. Full article

Water quality plays a central role in determining the environmental performance of pond-based tropical aquaculture systems. This study aimed to evaluate the relative environmental performance of different tropical pond-based aquaculture systems by identifying multivariate water quality patterns that allow their discrimination and comparison under commercial production conditions. Four pond-based production systems were evaluated: an aquaponic system (APS), a recirculating aquaculture system (RAS), a conventional earthen pond system (CEP), and an integrated rice–chame system (RCS). Fourteen physicochemical water quality variables were monitored throughout the production cycle under real commercial conditions using a comparative observational design. Multivariate discriminant analysis was applied to identify the variables with the highest discriminatory power and evaluate the ability of water quality patterns to correctly classify observations among production systems. The results revealed a clear multivariate separation between technologically intensive systems (APS and RAS) and less intensive and integrated systems (CEP and RCS), reflecting distinct water quality structures and environmental functioning. Variables associated with mineralization and nutrient dynamics, including electrical conductivity, dissolved solids, turbidity, phosphates, chlorides, dissolved oxygen, nitrites, and temperature, contributed most strongly to system discrimination. The discriminant functions achieved a high overall correct classification rate, demonstrating the robustness of the multivariate approach. These findings support the use of water quality variables as consistent environmental signatures for distinguishing tropical pond-based aquaculture systems, providing an operational framework for assessing their relative environmental performance. Discriminant analysis emerges as a valuable tool for system characterization and comparative evaluation, supporting environmentally informed management and optimization of chame aquaculture under tropical conditions. Although water quality represents a robust integrative indicator, it captures only one dimension of environmental performance, and additional factors such as production efficiency, energy use, and effluent characterization should be incorporated in future studies to achieve a comprehensive sustainability assessment. Full article

The reuse of treated wastewater for agricultural irrigation is increasingly considered a strategic response to water scarcity and climate change, particularly in Mediterranean regions. This study examines the local feasibility and social acceptance of water reuse within the framework of Regulation (EU) 2020/741, focusing on its implementation in Italy. The research combines policy analysis, technical assessment of effluent quality from the GIDA wastewater treatment plant (Prato, Tuscany), GIS-based spatial evaluation, and a mixed-method survey of local agri-food producers. Results show substantial compliance with EU minimum quality requirements, alongside additional constraints arising from national regulatory thresholds. Survey findings reveal cautious but tangible openness among farmers toward reclaimed water use, particularly in response to increasing climate-related pressures. The case of Prato is further analysed within the Prato Circular City and local food policy frameworks, highlighting the role of participatory governance and multi-actor engagement in supporting reuse initiatives. The study contributes empirical evidence on the interaction between EU regulation, national implementation measures, and local socio-institutional conditions shaping peri-urban water reuse systems. Furthermore, it serves as a preliminary framework for future economic feasibility studies and the subsequent regulatory and permitting phases required to operationalize this practice. Full article

Industrial-scale Anaerobic Digestion (AD) is a key technology for the energy recovery of agro-industrial and municipal waste and for the mitigation of greenhouse gas emissions; however, the actual operational performance of industrial biodigesters continues to show significant discrepancies with respect to the theoretical values reported in the scientific literature. In this context, there is still a lack of systematic analysis to identify which operating parameters are consistently monitored in industrial settings and which remain insufficiently explored, particularly those that describe the overall state of the digestion environment. To address this gap, a systematic literature review was conducted in the Scopus database for the period 2000–2026, complemented by a bibliometric analysis using VOSviewer software v1.6.18. 3. After applying inclusion criteria focused exclusively on industrial-scale and pilot systems, 1327 documents corresponding to the category of operating parameters were selected and analyzed using keyword co-occurrence networks and evaluation of occurrence frequencies and total link intensities. The analysis shows a marked concentration of the literature on a small set of classic parameters, highlighting pH (154 occurrences, 3667 link intensities), temperature (147 occurrences, 3255 link intensities), and ammonia (131 occurrences, 2824 link intensities) as the most recurrent variables in the industrial operation of anaerobic digesters. Complementarily, parameters such as chemical oxygen demand, total and volatile solids, and hydrogen sulfide have progressively increased their presence since 2015, mainly associated with effluent quality assessment, nutrient recovery, and overall process sustainability. In contrast, variables that integrate the state of the environment, such as electrical conductivity, oxidation-reduction potential, and the rheological properties of digestate, appear in less than $5\%$ of the studies analyzed, despite their ability to integrate information on stability, buffer capacity, and overall operating conditions. Taken together, these findings highlight an imbalance between the intensive use of traditional parameters and the limited incorporation of integrative indicators in industrial monitoring, suggesting that their systematic inclusion, together with the development of soft sensors and predictive models, could contribute to improving operational control and reducing the gap between the theoretical performance and actual behavior of industrial biodigesters. Full article

Produced-water (PW) management in the Permian Basin faces tightening injection constraints, induced seismicity concerns, and volatile saltwater disposal (SWD) costs. At the same time, chemistry-rich PW contains dissolved constituents (e.g., Li, B, and Sr) that may be valorized if SWD recovery performance and market conditions support favorable techno-economics. Here, we develop an integrated decision-support framework that couples (i) chemistry-informed surrogate models for unit process performance (recovery, effluent quality, and energy/chemical intensity) with (ii) a network-based allocation model that routes PW from sources through pretreatment, optional treatment and mineral-recovery modules (e.g., desalination and direct lithium extraction), and end-use nodes (beneficial reuse, hydraulic fracturing reuse, mineral recovery/valorization, or Class II disposal). This is a screening-level demonstration using publicly available chemistry percentiles and representative pilot-reported performance windows; it is not a site-specific facility design or a bankable TEA for a particular operator. The optimization is posed as a tri-objective problem—to maximize expected net present value, minimize SWD, and minimize an injection-risk indicator R—subject to mass balance, capacity, quality, and regulatory constraints. Uncertainty in commodity prices, recovery fractions, and operating costs is propagated via Monte Carlo scenario sampling, yielding PARETO-efficient portfolios that quantify trade-offs between profitability and risk mitigation. Using the PW chemistry percentiles reported by the Texas Produced Water Consortium for the Delaware and Midland Basins, we derive screening-level break-even lithium concentrations and illustrate how lithium-carbonate-equivalent price and recovery govern the extent to which mineral revenue can offset SWD expenditures. Comparative brine benchmarks (Smackover Formation and Salton Sea geothermal systems) contextualize the Permian’s generally lower-Li PW and highlight transferability of the workflow across brine types. The proposed framework provides a transparent, extensible basis for design matrix planning under evolving injection limits, enabling risk-aware PW management strategies that reduce disposal dependence while improving water resilience. Full article

Effluents from industries, manufacturing companies, textile looms, and floodwater contaminate the surface water reservoirs. This endangers the quality of water for use by humans. Wastewater remediation is one of the ways to recycle the dirty water and make it suitable for use. Photocatalysis is the most common method for wastewater remediation, especially using Titanium dioxide (TiO₂) nanoparticles. However, chemical synthesis and direct addition of nanoparticles may cause toxicity to the flora and fauna present in the water body. To address this limitation, we have green-synthesized TiO₂ nanoparticles using a horticulture waste, Calendula officinalis dried flower extract and entrapped them in a natural polymer, chitosan (CTS-TiO₂-CO nanocomposite). The polymer entrapment ensures biocompatibility as well as reduced aggregation of nanoparticles. The synthesized CTS-TiO₂-CO nanocomposite was characterized using UV-visible spectrophotometry, dynamic light scattering, zeta potential, Fourier Transformed Infrared Spectroscopy (FTIR), X-ray diffractometry (XRD), scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDAX) analysis. The absorption peak was found at 302 nm, and the hydrodynamic diameter at 490 nm. SEM images show flower-like morphology with 326 nm average particle diameter. The non-toxic dose of the nanoparticles was estimated by MTT assay and zebrafish embryo developmental studies. More than 82% fibroblast cells were viable after treatment with 100 μg/mL of CTS-TiO₂-CO nanocomposite. 85% embryos hatched after treatment with 50 μg/mL of CTS-TiO₂-CO nanocomposite. Further, the textile dye remediation assessment was done using the dye crystal violet, exhibiting 69.19% dye degradation after 4 h of sunlight exposure. Altogether, the results demonstrate that the CTS-TiO₂-CO nanocomposite was effective in the remediation of crystal violet without causing any toxicity up to a dose of 100 μg/mL. Full article

To address the feasible issues in water treatment facilities such as low particle removal and overuse of chemical in flocculation–sedimentation treatment of complex sediment-laden particles in snowmelt and high-intensity rainfall water, this research presents a new multi-layered separation tank. Combining a multi-layer structural design and a synergistic enhancement mechanism flocculation–centrifugation, it is possible to engineer the tank to achieve improvement in the coexistence of the sediment and water. This study methodically examines the impact of the agitator speed, agitator height, and the number of blades on the flow field qualities and the effectiveness of the agitator in removing particles in the multi-layer separation tank. Computational fluid dynamics (CFD) simulation validation in comparison with hydro-calculations and laboratory experiments are used in a combined method. The findings show that there is strong agreement between numerical representation and experimental values in determining the optimal conditions of operation and the exact rate of dosage of polyaluminum chloride (PAC) and polyacrylamide (PAM). At these optimized conditions, the system achieves at a 75.25 percent removal rate of particles whose size ranges are 20–50 μm and turbidity of the effluent decreases to 10.6 NTU in 30 min of settling time. The proposed technology is more efficient than conventional coagulation processes in that effluent turbidity is reduced by 22.1% with same dosages of chemical additive indicating a higher performance of the proposed technology. Full article

To assess the treatment efficiency and spatio-temporal variation characteristics of urban wastewater treatment plants, this study analyzed influent and effluent water quality data, including pH, COD, BOD₅, SS, NH₃–N, TN, and TP, as well as treatment volume data from 19 plants in Changsha from 2020 to 2024. The results revealed significant fluctuations in influent water quality across different plants, though effluent quality generally complied with discharge standards. Removal rates of SS, NH₃–N, and BOD₅ all exceeded 80%, while that of TN ranged between 63% and 79%. The COD/BOD₅ ratios in the influent mostly exceeded 0.3, indicating generally good biodegradability of the municipal wastewater. However, 79% of the plants exhibited SS/BOD₅ > 1.5, and 83.2% had BOD₅/TN < 4, suggesting a widespread carbon deficiency for denitrification. Principal component analysis (PCA) demonstrated that both influent and effluent quality indicators were suitable for dimensionality reduction, with pH, COD, NH₃–N, and TN identified as core evaluation factors. Cluster analysis (CA) indicated phased increases in influent concentrations, while effluent quality showed progressive annual improvement from 2020 to 2024. Urban WWTPs’ influent pollution loads were hydrological period-dependent, with high-flow effluent fluctuations and controllable low-flow loads. This study provides data support for operational optimization of wastewater treatment plants in Changsha. Full article

The wastewater generated during coffee processing contains high levels of acidity and organic matter, posing substantial environmental hazards, particularly in rural areas where traditional treatment methods are financially infeasible. This research assesses the field-scale effectiveness of Chrysopogon zizanioides (vetiver grass) in phytoremediation of coffee wastewater in Huánuco, Peru, with particular attention to how plant maturity affects treatment outcomes. A comparative analysis was performed on untreated and vetiver-filtered effluent from infiltration ponds at four growth stages (6, 8, 19, and 21 months), with measurements of pH, chemical oxygen demand (COD), biochemical oxygen demand (BOD₅), and suspended solids (TSS, SS) conducted according to standardized methods. The findings indicate notable improvements in water quality, as the pH rose from 4.07 ± 0.32 to 5.82 ± 0.40 (p < 0.001) and organic loads decreased by 39–41% (COD: 38,600 ± 12,100 to 23,000 ± 8500 mg L⁻¹ O₂; BOD₅: 27,700 ± 9400 to 16,500 ± 5600 mg L⁻¹ O₂). Total Suspended Solids (TSS) were reduced by 26%, while the settleable suspended solids fraction (SS) decreased by 69%, indicating strong particulate removal through combined filtration and sedimentation mechanisms. Mature vetiver stands (21 months old) showed better results, underscoring the importance of root development for effective phytoremediation. Strong correlations were observed between COD and BOD₅ (r = 0.92), while pH negatively correlated with organic and particulate parameters. The study presents empirical evidence supporting vetiver-based systems as an economical and sustainable approach to decentralized wastewater treatment in coffee-growing areas. Furthermore, it provides actionable insights for improving phytoremediation by focusing on plant maturity, which can be readily adapted for large-scale implementation in resource-constrained settings. The findings underscore the potential of nature-based technologies to address environmental challenges while supporting local economies dependent on coffee production. Full article

The emerging Arthrospira industry in Ordos utilizes alkaline resources, the discharge of aquaculture wastewater from which may potentially influence the surrounding aquatic environment. Water quality and phytoplankton communities were systematically monitored at three representative ponds in both the green (H-1) and yellow ponds (H-2) of Lake Hammatai (three sites per pond) during April, June, August, and October of 2017 and 2018. Our results showed that phytoplankton biomass and abundance in Lake Hammatai were relatively low compared to other saline–alkaline lakes. The phytoplankton community was primarily dominated by Arthrospira spp. and Chlamydomonas spp. A low TN/TP ratio, together with elevated organic nitrogen concentrations, appeared to jointly facilitate the dominance of Arthrospira spp. Both lake water and wastewater were characterized by Na⁺ as the dominant cation, along with high concentrations of HCO₃⁻ and CO₃²⁻. Redundancy analysis (RDA) identified Na⁺, K⁺, Cl⁻, and HCO₃⁻ as the key environmental factors shaping algal community structure. These findings reveal the potential effects of aquaculture effluent on phytoplankton communities and water chemistry in alkaline lakes, offering insights into the response of fragile ecosystems to anthropogenic disturbances and informing targeted management strategies. Full article

Coastal ecosystems are increasingly threatened by anthropogenic activities associated with tourism development and maritime traffic. This study evaluates the environmental quality of a coastal sector using an integrated approach combining sediment characteristics, heavy metal concentrations, and benthic foraminiferal assemblages. Nineteen surface sediments were collected and analyzed for trace metals using ICP-MS, while benthic foraminiferal assemblages were quantified, and ecological indices were calculated. Results reveal elevated concentrations of trace metals at coastal stations, closely associated with high TOM and fine-grained sediments, indicating significant anthropogenic inputs. These stations are characterized by low species richness, reduced Shannon diversity, high dominance, low living foraminiferal percentages, high malformed individuals, and markedly low FoRAM values, reflecting stressed environmental conditions. Opportunistic taxa such as Ammonia tepida dominate impacted sites, whereas sensitive carbonate-producing taxa (Quinqueloculina lamarckiana, Coscinospira hemprichii, Elphidium striatopunctatum, Elphidium crispum) prevail at less disturbed stations. Multivariate analyses clearly separate polluted coastal stations from relatively unimpacted offshore sites. The combined geochemical and biological evidence demonstrates that tourism-related activities and ship effluents exert a strong negative influence on benthic ecosystems. Benthic foraminifera, together with heavy metals, provide an effective and sensitive tool for assessing anthropogenic impacts and coral reef health for sustainable coastal management of Safaga Bay. Full article