Search Results (48)

Background: Wastewater treatment plants (WWTPs) are hotspots of antimicrobial resistance (AMR) due to inputs from diverse anthropogenic sources. Aeromonas spp., ubiquitous in aquatic environments, often carry clinically relevant antibiotic resistance genes (ARGs) and can persist beyond fecal contamination indicators, making them promising sentinel organisms for AMR dissemination. The aim of this study was to assess the suitability of Aeromonas spp. in this role by characterizing resistance profiles, associated virulence factor genes (VFGs), genetic mobility, and persistence across wastewater and drinking water treatment processes in the Barcelona metropolitan area, Spain. Methods: Isolates were phenotypically characterized and screened for ARGs, VFGs, integrons, and heavy metal tolerance genes, followed by whole-genome sequencing (WGS). Biofilm formation was assessed in vitro. Conjugation assays with Escherichia coli evaluated horizontal gene transfer (HGT) potential. Results: A total of 428 antibiotic-resistant Aeromonas spp., the most abundant antibiotic-resistant bacteria isolated during the 2023 sampling campaigns from two WWTPs and one drinking water treatment plant (DWTP), were characterized. Trimethoprim/sulfamethoxazole (SXT) non-susceptibility was most frequent (72%), followed by cefoxitin resistance (65.4%). The sul1 (57.5%) and bla_MOX (78.6%) genes predominated among SXT- and β-lactam-resistant isolates. The merA gene was detected in 23.6%; 97.9% harbored at least one VFG (aerA, act, fla, alt, or hlyA), and 70.3% carried intI1. Half formed biofilm. Conjugation confirmed bi-directional HGT, and WGS revealed persistent ST3458 clones across treatment stages. Conclusions: WWTPs and DWTPs act as reservoirs of antibiotic-resistant Aeromonas spp., demonstrating persistence and HGT potential. Findings support their use as sentinel organisms for AMR surveillance in aquatic environments and for assessing treatment efficacy, highlighting variability across treatment types and locations, and reinforcing their relevance for urban water reclamation monitoring. Full article

Optimizing coagulant dosages in Drinking Water Treatment Plants (DWTPs) is critical for reducing operational costs, minimizing chemical waste, mitigating environmental impacts, and ensuring consistent water quality, particularly in resource-constrained settings where conventional jar tests are labor-intensive and poorly suited to real-time demands. This study develops and validates a Random Forest (RF) machine learning model to predict optimal dosages of aluminum sulfate, polyaluminum chloride, and a polymer flocculant at the Miguel de la Cuba Ibarra DWTP in Peru, addressing the need for an efficient, real-time decision support system. Using a historical dataset of 2556 jar tests, a univariate RF model was developed to predict settled water turbidity, tailored to the plant’s typical operational range. The model demonstrated robust predictive performance, achieving a coefficient of determination (R²) of 0.92 during training and 0.76 during validation with unseen data, alongside a Root Mean Square Error (RMSE) of 0.11 NTU and a Mean Absolute Percentage Error (MAPE) of 0.11 in the training phase. Integrated into a digital platform, the model generates real-time NTU ppm dosing curves, providing a practical and responsive tool to enhance operational efficiency for DWTP operators. This work offers a scalable, data-driven solution to improve water treatment processes in resource-limited contexts. Full article

Coagulation is a critical unit process in drinking water treatment plants (DWTPs), where accurate dosing of coagulants such as polyaluminum chloride (PAC) and polyaluminum hydroxide chloride silicate (PACS) directly determines turbidity removal and operational stability. However, nonlinear interactions among water-quality variables complicate dosage prediction, and jar tests or operator heuristics cannot support real-time control. This study presents a scientifically interpretable and operationally transferable framework based on polynomial multiple linear regression (PMLR) with Lasso regularization, which was specifically developed for full-scale DWTP environments. While conventional PMLR rapidly overfits beyond polynomial degrees of 4–5, the Lasso-regularized model maintained stable generalization even at a degree of 10 by automatically pruning redundant terms and suppressing multicollinearity, thereby minimizing the need for manual hyperparameter tuning. Using 8303 hourly operational records from a full-scale DWTP in Korea, the Lasso-PMLR achieved R² = 0.951, RMSE = 0.120, and MAPE = 7.02%, outperforming traditional linear regression (R² = 0.896; MAPE = 8.64%). This proportional stability across increasing polynomial degrees, demonstrated directly using long-term real-world data, is particularly valuable for practical deployment because it ensures robustness without complex model-selection procedures. The transparent coefficient structure enables operators—who typically rely on jar tests—to understand and adjust dosing behavior, offering a field-ready and interpretable alternative to black-box models and supporting more efficient coagulant use, reduced sludge production, and sustainable automation in DWTP operation. Full article

Reservoirs and downstream rivers draining Oregon’s Cascade Range provide critical water supplies for over 1.5 million residents in dozens of communities. These waters also support planktonic and benthic cyanobacteria that produce cyanotoxins that may degrade water quality for drinking, recreation, aquatic life, and other beneficial uses. This 2016–2020 survey examined the sources and transport of four cyanotoxins—microcystins, cylindrospermopsins, anatoxins, and saxitoxins—in six river systems feeding 18 drinking water treatment plants (DWTPs) in northwestern Oregon. Benthic cyanobacteria, plankton net tows, and (or) Solid-Phase Adsorption Toxin Tracking (SPATT) samples were collected from 65 sites, including tributaries, reservoirs, main stems, and sites at or upstream from DWTPs. Concentrated extracts (320 samples) were analyzed with enzyme-linked immuno-sorbent assays (ELISA), resulting in >90% detection. Benthic cyanobacteria (n = 80) mostly Nostoc, Phormidium, Microcoleus, and Oscillatoria, yielded microcystins (76% detection), cylindrospermopsins (41%), anatoxins (45%), and saxitoxins (39%). Plankton net tow samples from tributaries and main stems (n = 94) contained saxitoxins (84%), microcystins (77%), anatoxins (25%), and cylindrospermopsins (22%), revealing their transport in seston. SPATT sampler extracts (n = 146) yielded anatoxins (81%), microcystins (66%), saxitoxins (37%), and cylindrospermopsins (32%), indicating their presence dissolved in the water. Reservoir plankton net tow samples (n = 15), most often containing Dolichospermum, yielded microcystins (87%), cylindrospermopsins (73%), and anatoxins (47%), but no saxitoxins. The high detection frequencies of cyanotoxins at sites upstream from DWTP intakes, and at sites popular for recreation, where salmon and steelhead continue to exist, highlight the need for additional study on these cyanobacteria and the factors that promote production of cyanotoxins to minimize effects on humans, aquatic ecosystems, and economies. Full article

Micro- and nanoplastics (NPs) cannot be completely removed from water/wastewater in conventional wastewater treatment plants (WWTPs) and drinking water treatment plants (DWTPs). According to the literature analysis, membrane processes, one of the advanced treatment technologies, are the most effective and promising technologies for the removal of microplastics (MPs) from water and wastewater. In this article, firstly, the properties of MPs commonly found in water and wastewater treatment and their removal efficiencies are briefly reviewed. In addition, research on the use of microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), reverse osmosis (RO), and membrane bioreactors (MBR) for the remediation of MPs and NPs from water/wastewater is reviewed, and the advantages/disadvantages of each removal method are discussed. Membrane filtration is also compared with other methods used to remove MPs. Furthermore, the problem of membrane fouling by MPs during filtration and the potential for MPs to be released from the polymeric membrane structure are discussed. Finally, based on the literature survey, the current status and gaps in research on MPs removal by membrane technologies are identified, and recommendations for further research are made. Full article

The United States Environmental Protection Agency (US EPA) recently finalized the enforceable maximum contaminant levels for some per- and polyfluoroalkyl substances (PFAS) in drinking water which intends to substantially decrease their level in it. Conventional processes in full-scale drinking water treatment plants (DWTPs) are usually inefficient in PFAS removal from source water (i.e., groundwater and surface water). There is an increasing interest in investigating/evaluating advanced treatment technologies for PFAS removal from PFAS-contaminated water to help generate a number of potential solutions to this water engineering design challenge/problem. While numerous excellent research studies have been carried out and reported in the literature on the efficiency of several treatment processes in removing PFAS from PFAS-contaminated water, mostly at lab- and pilot-scales, full-scale DWTP investigations still need further attention. This study reviews the US EPA’s PFAS water quality guidelines/regulations, remediation technologies for PFAS in water, and PFAS removal studies on full-scale DWTPs. Then, it discusses some configurations of DWTP for PFAS removal from source water (i.e., groundwater and surface water) as well as suggesting future directions. Further research on the effect of environmental factors (e.g., organic matter) on PFAS removal, the effective elimination of short-chain PFAS from real PFAS-contaminated source water using cost-effective and industrially applicable remediation technologies, the efficiency/performance of full-scale treatment trains including innovative advanced technologies in long-term for PFAS removal from source water to produce drinking water and the associated costs, as well as cost reduction/minimization via process optimization is still of interest. Full article

This study aimed to investigate the distribution of commonly used pesticides and their metabolites in drinking water before and after treatment at drinking water treatment plants (DWTPs) in the Yangtze River Delta and to assess the health risks from the perspective of non-carcinogenicity and carcinogenicity. A total of 85 pesticides and their metabolites were analyzed in source, finished, and tap water using online solid-phase extraction coupled with liquid chromatography–tandem mass spectrometry. Across 91 water samples, 31 parent compounds and 9 metabolites were detected, with the median total concentrations of 62.2 (range: 6.20 to 392) ng/L. Atrazine, 2-hydroxyatrazine, and S-metolachlor were detected in all samples. Advanced treatment processes at DWTPs effectively reduced the residues of pesticides and their metabolites (removal rates 51.5~95.2%), with removal rates for metabolites significantly lower than those for parent compounds (p = 0.03). Regarding health risks, the estimated carcinogenic risk for pesticides and metabolites detected in tap water was within acceptable limits and the non-carcinogenic risk was insignificant. However, it is important to note that both of the two compounds with the relatively highest non-carcinogenic risks are pesticide metabolites. Overall, this study showed that despite dozens of pesticides and metabolites being detected in water from the Yangtze River Delta, their health risks were assessed to be insignificant. The lower effectiveness of current advanced treatments in removing pesticide metabolites indicates the necessity of technique improvement in DWTPs. Full article

While microparticles can be removed by a filtration step at a drinking water treatment plant (DWTP), engineered nanoparticles (ENPs), which are widely used in industry, commerce and households, pose a major problem due to their special properties, e.g., size, reactivity and polarity. In addition, many ENPs exhibit toxic potential, which makes their presence in drinking water undesirable. Therefore, this study investigated the removal of ENPs in the laboratory and at a pilot-scale DWTP. Eight ENPs were synthesized and tested for stability in different types of water. Only three of them were stable in natural water: cetyltrimethylammonium bromide-coated gold (CTAB/AuNPs), polyvinylpyrrolidone-stabilized gold and silver nanoparticles (PVP/AuNPs, PVP/AgNPs). Their retention on quartz sand, silica gel and fresh anthracite was low, but CTAB/AuNPs could be retained on fresh river sand and thus should not overcome riverbank filtration, while PVP/AuNPs and PVP/AgNPs showed no retention and may be present in raw water. During ozonation, PVP/AuNPs remained stable while PVP/AgNPs were partially degraded. The advanced oxidation process (AOP) was less effective than ozone. PVP/AgNPs were almost completely retained on the pilot plant anthracite sand filter coated with manganese(IV) oxide and ferrihydrite from raw water treatment. PVP/AuNPs passed the filter with no retention. In contrast to PVP/AuNPs, PVP/AgNPs and CTAB/AuNPs were also retained on activated carbon. The integration of a flocculation step with iron(III) salts can improve ENP removal, with PVP/AuNPs requiring higher flocculant doses than PVP/AgNPs. PVP/AuNPs, in particular, are well-suited for testing the effectiveness of water treatment. Further data on the occurrence of stable ENPs in raw water and their behavior during water treatment are needed to perform a risk assessment and derive the measures. Full article

This study investigated membrane fouling issues associated with the operation of a submerged ultrafiltration membrane in a drinking water treatment plant (DWTP) and optimized the associated chemical cleaning strategies. By analyzing the surface components of the membrane foulant and the compositions of the membrane cleaning solution, the primary causes of membrane fouling were identified. Membrane fouling control strategies suitable for the DWTP were evaluated through chemical cleaning tests conducted for bench-scale, full-scale, and engineering cases. The results show that the membrane foulants were primarily composed of a mixture of inorganics and organics; the inorganics were mainly composed of Al and Si, while the organics were primarily humic acid (HA). Sodium citrate proved to be the most effective cleaning agent for inorganic fouling, which was mainly composed of Al, whereas sodium hypochlorite (NaClO) combined with sodium hydroxide (NaOH) showed the best removal efficiency for organic fouling, which predominantly consisted of HA and Si. However, sodium hypochlorite (NaClO) combined with sodium hydroxide (NaOH) showed the best removal efficiency for organic fouling and Si; organic fouling predominantly consisted of HA. Based on the bench-scale test results, flux recovery was verified in the full-scale system. Under a constant pressure of 30 kPa, the combined acid–alkali cleaning achieved the best flux recovery, restoring the flux from 22.8 L/(m²·h) to 66.75 L/(m²·h). In the engineering tests, combined acid–alkali cleaning yielded results consistent with those of the full-scale tests. In the practical engineering cleaning process, adopting a cleaning strategy of alkaline (NaClO + NaOH) cleaning followed by acidic (sodium citrate) cleaning can effectively solve the membrane fouling problem. Full article

The scope of the present study is the estimation of key operational parameters of a drinking water treatment plant (DWTP), particularly the dosages of treatment chemicals, using artificial neural networks (ANNs) based on measurable in situ data. The case study consists of the Aposelemis DWTP, where the plant operator had an estimation of the ANN output parameters for the required dosages of water treatment chemicals based on observed water quality and other operational parameters at the time. The estimated DWTP main operational parameters included residual ozone (O₃) and dosages of the chemicals used: anionic polyelectrolyte (ANPE), poly-aluminum chloride hydroxide sulfate (PACl), and chlorine gas (Cl_2(g)). Daily measurable results of water sample analysis and recordings from the DWTP Supervisory Control and Data Acquisition System (SCADA), covering a period of 38 months, were used as input parameters for the artificial neural network (1188 values for each of the 14 measurable parameters). These input parameters included: raw water supply (Q), raw water turbidity (T₁), treated water turbidity (T₂), treated water residual free chlorine (Cl₂), treated water concentration of residual aluminum (Al), filtration bed inlet water turbidity (T₃), daily difference in water height in reservoir (∆H), raw water pH (pH₁), treated water pH (pH₂), and daily consumption of DWTP electricity (El). Output/target parameters were: residual O₃ after ozonation (O₃), anionic polyelectrolyte (ANPE), poly-aluminum chloride hydroxide sulfate (PACl), and chlorine gas supply (Cl_2(g)). A total of 304 different ANN models were tested, based on the best test performance (tperf) indicator. The one with the optimum performance indicator was selected. The scenario finally chosen was the one with 100 neural networks, 100 nodes, 42 hidden nodes, 10 inputs, and 4 outputs. This ANN model achieved excellent simulation results based on the best testing performance indicator, which suggests that ANNs are potentially useful tools for the prediction of a DWTP’s main operational parameters. Further research could explore the prediction of water chemicals used in a DWTP by using ANNs with a smaller number of operational parameters to ensure greater flexibility, without prohibitively reducing the reliability of the prediction model. This could prove useful in cases with a much higher sample size, given the data-demanding nature of ANNs. Full article

The management of drinking water treatment plant (DWTP) sludge is challenging for water treatment facilities. Previous studies reported mainly on handling sludge through landfilling, release into water bodies, discharge into wastewater treatment plants, onsite disposal, and incineration methods for the treatment of sludge. The limitations of these sludge-handling methods are well documented. This article focuses on the hierarchical approach as an alternative and comprehensive method for handling DWTP sludge. The core of hierarchical management streamlines the minimization of the generated DWTP sludge; treatment of DWTP sludge to reduce toxicity; changing of the physicochemical form of DWTP sludge; and finally, the reuse, recycling, and recovery of DWTP sludge. The premise is to achieve zero landfilling of DWTP sludge, establish a circular economy, generate job opportunities, and preserve the environment. Thus, this study also proposes two main technologies, which are gravity-based sludge separators for fractionating the sludge and photocatalytic membrane reactors (PMRs) as a technology for the treating and/or recovery of nutrients and minerals from DWTP sludge. Until the chemical deductive or minus approach becomes a reality in water treatment, the use of PMRs and gravity-based sludge separators will enhance the management of DWTP sludge when incorporated into the hierarchical approach. Full article

Microplastics (MPs), which are defined as plastics with a size of less than 5 mm, cannot be treated completely in wastewater treatment plants (WWTPs) and discharged to a water body because they are too small in size. It has been reported that MPs can have adverse effects on human beings and water ecosystems. There is a need to combine existing drinking water treatment plants (DWTPs) and WWTPs with the traditional treatment process and technology with high removal efficiency of MPs or to develop a new technology to separate MPs from water and wastewater. In this study, the effects of MPs (polyethylene (PE), 125 μm) and organic matter (humic acid) were researched in a hybrid treatment process of ceramic microfiltration (MF) and photocatalyst (TiO₂)-mounted polyether sulfone (PES) spheres with air backwashing. The roles of the MF, photooxidation, and adsorption of PES spheres were confirmed in a single MF process (MF), an MF process with UV irradiation (MF+UV), MF and PES sphere adsorption without UV irradiation (MF+PES), and a hybrid process incorporating MF and PES spheres with UV irradiation (MF+PES+UV). The impact of the air backwashing cycle (filtration time, FT) on filtration characteristics and treatment efficiencies in the hybrid process was studied. In the MF process, membrane fouling increased with increasing organic matter (HA, humic acid). The treatment efficiency of MPs increased; however, that of dissolved organic matter (DOM) decreased with increasing HA. As MPs increased, the membrane fouling decreased; however, total filtration volume (V_T) remained almost constant. The treatment efficiency of MPs increased a little, and that of DOM showed a dropping trend. In the hybrid process, the membrane fouling was controlled via the adsorption and UV photooxidation of the PES spheres, and the DOM treatment efficiency increased by combining processes from MF to MF+PES+UV. The optimal FT was 10 min at BT 10 s in this hybrid process. The results could be applied to separate MPs effectively in DWTPs/WWTPs. Full article

In recent years, the ubiquitous occurrence of plastic debris has become a significant environmental concern, posing considerable harm to our ecosystems. Microplastics (MPs) (1 μm–5 mm) and nanoplastics (NPs) (<1 μm) are noticeable in diverse forms, spreading throughout the environment. Notably, wastewater treatment plants (WWTPs) emerge as major contributors to the generation of MP and NP. Within these treatment plants, water influx from domestic and commercial sources carries a considerable load of MPs derived from items like fiber clothing, personal care products, and toothpaste. Lacking dedicated removal mechanisms, these MPs persist through the wastewater treatment process, ultimately entering natural water bodies and the soil environment. The novelty of this review lies in its detailed examination of contemporary methodologies for sampling, detecting, and eliminating MPs specifically from WWTPs. By critically assessing the efficacy of current removal techniques at various treatment stages, the review offers targeted insights into practical aspects of MP management in these facilities. As the study of micro/nano plastics is still in its early stages, this article aims to contribute by offering a comprehensive review of the methods utilized for plastic debris removal in both WWTPs and drinking water treatment plants (DWTPs). Furthermore, the article provides a comprehensive overview of the existing rules, regulations, and policies concerning MPs in the United States. This inclusion not only broadens the scope of the review but also establishes it as a valuable reference for understanding the regulatory framework related to MPs. This review uniquely combines a focused evaluation of WWTPs/DWTPs, an exploration of removal methods, and an examination of regulatory framework, making a different contribution to the review article. Through this review, we aim to enhance understanding and awareness of the multi-layered challenges posed by MPs, offering insights that can inform future research directions and policy initiatives. Full article

As an emerging contaminant, the presence of microplastics is widespread in the environment. However, current research regarding the removal of microplastics by drinking water treatment plants (DWTPs) remains insufficient. This study aims to investigate microplastics in water and sludge in four DWTPs in Zhengzhou; these DWTPs have different water sources. The results revealed that the abundance of microplastics in raw water ranged from 12.80 ± 0.80 to 25.07 ± 1.67 n/L. Overall, fibers and fragments ranging from 10 to 100 μm constituted the primary components. The proportion of white and transparent microplastics was the highest. Among the ten polymer types detected, polyvinyl chloride, polyphenylene oxide, and polyethylene terephthalate were the predominant ones in raw water; polyethylene terephthalate emerged as the prevalent polymer type in treated drinking water, with both polyethylene terephthalate and polyvinyl chloride being primarily present in sludge. The removal rate of microplastics ranged from 45.8% to 74.5%. Furthermore, the removal rates at the sedimentation tank outlet accounted for more than 50.0% of the total removal rate. The abundance of microplastics in sludge was significantly higher than that in water, indicating a concentrated environment for the persistence of microplastics. The proper disposal of sludge has emerged as one of the challenges requiring our attention. Full article

This paper evaluates the washing interval of the rapid sand filter at the central drinking water treatment plant Nová Ves—Frýdlant nad Ostravicí in the Czech Republic (DWTP Nová Ves). The aim was to conduct automated flow cytometry measurements (FCM) and find the link between FCM and turbidity. The monitor parameters were the length of the wash cycle in hours, the flow rate of the filter and the production, the pumping of the recirculating wash water, and the physico-chemical and microbial analysis of the water samples. The focus of this paper is the detailed characteristics of the filtration mode evaluated during the summer and winter periods. During the measurements, it was confirmed that turbidity replicated the FCM data measured by the FC BactoSense instrument. Turbidity can be identified as one of the key features that can be related to the measurements made. Turbidity and the cell count itself are influenced, among other things, by the pumping of the return water, whereby an increase in the cell count can be observed after the pumping has stopped but gradually stabilizes at the values measured before pumping. Full article