Design and Validation of Primer Sets for the Detection and Quantification of Antibiotic Resistance Genes in Environmental Samples by Quantitative PCR.

The high prevalence of antibiotic resistant bacteria (ARB) in several environments is a great concern threatening human health. Particularly, wastewater treatment plants (WWTP) become important contributors to the dissemination of ARB to receiving water bodies, due to the inefficient management or treatment of highly antibiotic-concentrated wastewaters. Hence, it is vital to develop molecular tools that allow proper monitoring of the genes encoding resistances to these important therapeutic compounds (antibiotic resistant genes, ARGs). For an accurate quantification of ARGs, there is a need for sensitive and robust qPCR assays supported by a good design of primers and validated protocols. In this study, eleven relevant ARGs were selected as targets, including aadA and aadB (conferring resistance to aminoglycosides); ampC, blaTEM, blaSHV, and mecA (resistance to beta-lactams); dfrA1 (resistance to trimethoprim); ermB (resistance to macrolides); fosA (resistance to fosfomycin); qnrS (resistance to quinolones); and tetA(A) (resistance to tetracyclines). The in silico design of the new primer sets was performed based on the alignment of all the sequences of the target ARGs (orthology grade > 70%) deposited in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, allowing higher coverages of the ARGs' biodiversity than those of several primers described to date. The adequate design and performance of the new molecular tools were validated in six samples, retrieved from both natural and engineered environments related to wastewater treatment. The hallmarks of the optimized qPCR assays were high amplification efficiency (> 90%), good linearity of the standard curve (R2 > 0.980), repeatability and reproducibility across experiments, and a wide linear dynamic range. The new primer sets and methodology described here are valuable tools to upgrade the monitorization of the abundance and emergence of the targeted ARGs by qPCR in WWTPs and related environments.

Combining High-Resolution Mass Spectrometry and Chemiluminescence Analysis to Characterize the Composition and Fate of Total N-Nitrosamines in Wastewater Treatment Plants.

Monitoring the prevalence and persistence of N-nitrosamines and their precursors in wastewater treatment plants (WWTPs) and effluent-receiving aquatic compartments is a priority for utilities practicing wastewater recycling or exploiting wastewater-impacted source waters. In this work, we developed an analytical framework that combines liquid chromatography-high-resolution mass spectrometry (LC-HRMS) with acidic triiodide-chemiluminescence analysis to characterize the composition and fate of total N-nitrosamines (TONO) and their precursors along the treatment trains of eight WWTPs in New York. Through the parallel application of LC-HRMS and chemiluminescence methods, the TONO scores for 41 N-nitrosamines containing structurally diverse substituents on their amine nitrogen were derived based on their solid-phase extraction recoveries and conversion efficiencies to nitric oxide. Correcting the compositional analysis of TONO using the TONO scores of target N-nitrosamines refined the assessment of the reduction or accumulation of TONO and their precursors across treatment steps in WWTPs. Nontargeted analysis prioritized seven additional N-nitrosamines for confirmation by reference standards, including three previously uncharacterized species: N-nitroso-tert-butylphenylamine, N-nitroso-2-pyrrolidinmethanol, and N-nitrosodesloratadine, although they only served as minor components of TONO. Overall, our study establishes an adaptable methodological framework for advancing the quantitative and qualitative analysis of specific and unknown components of TONO across water treatment and reuse scenarios.

Soluble carbon source recovery using preconditioning coagulants for applicable short-term fermentation of waste activated sludge in WWTPs.

A huge production of waste activated sludge (WAS) has been a burden for wastewater treatment plants (WWTPs) with high disposal cost and little benefit back to wastewater purification. The short-chain fatty acids (SCFAs) produced by a short-term acidogenic fermentation of WAS before methane production have been proven to be a high-quality carbon source available for microbial denitrification process. The dual purpose of full recovery of fermentation liquid products and facilitating disposal of residual solid waste necessitate an efficient solid-liquid separation process of short-term fermentation liquid. The transformation and loss of various soluble carbon sources between solid and liquid are very important issues for carbon recovery efficiency when combining short-term fermentation and sludge dewatering in WWTPs. Here we testified the three conventional preconditioning coagulants, Polyferric Sulfate (PFS), Poly Aluminum Chloride (PAC) and Polyacrylamide (PAM), to improve the efficiency of subsequent solid-liquid separation. The results show that conversion yield of SCFAs in the liquid phase of sludge after short-term fermentation was 195 mg COD/g VSS, when using the coagulants PFS, PAC, and PAM for recovery, the recovery ratio was 79.5%, 82.0%, and 85.9%, respectively, while the dewaterability could be improved after preconditioning short-term fermentation sludge. The complexation of Al3+/Fe3+ in metal coagulants with carboxyl groups of SCFA demonstrated by Density Functional Theory calculation led to small part of soluble carbons co-migration to the solid phase, mainly a loss of high molecular weight organic compounds (carbohydrate, proteins, humic acids), while the application of PAM had little impact on carbon recovery. Economic calculations further showed PAM preconditioning short-term fermentation liquid of WAS could achieve higher recovery benefits.

Regulatory of salinity on assembly of activated sludge microbial communities and nitrogen transformation potential in industrial plants of the lower Yangtze River basin.

This study aims to thoroughly investigate the impact mode of salinity carried by industrial wastewater on the anaerobic-anoxic-oxic (A2O) sludge in wastewater treatment plants (WWTPs). Through comprehensive investigation of the A2O stage activated sludge (AS) from 19 industrial WWTPs in the downstream area of the Yangtze River, China, A total of 38 samples of anaerobic sludge and oxic sludge were collected and analyzed. We found that salinity stress significantly inhibits the growth of the AS community, particularly evident in the anaerobic sludge community. Furthermore, the high-saline environment induces changes in the structure and functional patterns of the AS community, leading to intensive interactions and resource exchanges among microorganisms. Halophilic microorganisms may play a crucial role in this process, significantly impacting the overall community structure, especially in the oxic sludge community. Additionally, salinity stress not only suppresses the nitrogen transformation potential of the AS but also leads to the accumulation of nitrite, thereby increasing the emission potential of both NO and N2O, exacerbating the greenhouse effect of the A2O process in industrial WWTPs. The findings of this study provide necessary theoretical support for maintaining the long-term stable operation of the A2O sludge system in industrial WWTPs, reducing carbon footprint, and improving nitrogen removal efficiency.

Tracking SARS-CoV-2 and its variants in wastewater in Tunisia.

Wastewater-based genomic surveillance can improve community prevalence estimates and identify emerging variants of pathogens. Wastewater influents and treated effluents from six wastewater treatment plants (WWTPs) in Tunisia were analyzed between December 2021 and July 2022. Wastewater samples were analyzed with reverse transcription solid digital PCR (RT-sdPCR) and whole-genome sequencing to determine the amount of SARS-CoV-2 RNA and assign SARS-CoV-2 lineages. The virus variants detected in wastewater samples were compared with COVID-19 prevalence data. The quantitative results in wastewater influents revealed that viral RNA concentrations at the treatment plants corroborate with locally reported clinical cases and show an increase before the increment of clinically diagnosed new COVID-19 cases between April and July 2022. Delta and Omicron variants were identified in the Tunisian wastewater. Interestingly, the presence of variant BA.5 was detected in samples prior to its inclusion as a variant of concern (VOC) by the Tunisian National Health Authorities. SARS-CoV-2 was detected in wastewater effluents, indicating that the wastewater treatment techniques used in the majority of Tunisian WWTPs are inefficient in removing the virus traces. This study reports the first identification of SARS-CoV-2 VOCs in Tunisian wastewater samples.

Machine learning reveals the selection pressure exerted by nonantibiotic pharmaceuticals at environmentally relevant concentrations on antibiotic resistance genotypes.

The emergence and increasing prevalence of antibiotic resistance pose a global public risk for human health, and nonantimicrobial pharmaceuticals play an important role in this process. Herein, five nonantimicrobial pharmaceuticals, including acetaminophen (ACT), clofibric acid (CA), carbamazepine (CBZ), caffeine (CF) and nicotine (NCT), tetracycline-resistant strains, five ARGs (sul1, sul2, tetG, tetM and tetW) and one integrase gene (intI1), were detected in 101 wastewater samples during two typical sewage treatment processes including anaerobic-oxic (A/O) and biological aerated filter (BAF) in Harbin, China. The impact of nonantibiotic pharmaceuticals at environmentally relevant concentrations on both the resistance genotypes and resistance phenotypes were explored. The results showed that a significant impact of nonantibiotic pharmaceuticals at environmentally relevant concentrations on tetracycline resistance genes encoding ribosomal protection proteins (RPPs) was found, while no changes in antibiotic phenotypes, such as minimal inhibitory concentrations (MICs), were observed. Machine learning was applied to further sort out the contribution of nonantibiotic pharmaceuticals at environmentally relevant concentrations to different ARG subtypes. The highest contribution and correlation were found at concentrations of 1400-1800 ng/L for NCT, 900-1500 ng/L for ACT and 7000-10,000 ng/L for CF for tetracycline resistance genes encoding RPPs, while no significant correlation was found between the target compounds and ARGs when their concentrations were lower than 500 ng/L for NCT, 100 ng/L for ACT and 1000 ng/L for CF, which were higher than the concentrations detected in effluent samples. Therefore, the removal of nonantibiotic pharmaceuticals in WWTPs can reduce their selection pressure for resistance genes in wastewater.

Analytical Methods for the Determination of Pharmaceuticals and Personal Care Products in Solid and Liquid Environmental Matrices: A Review.

Among the various compounds regarded as emerging contaminants (ECs), pharmaceuticals and personal care products (PPCPs) are of particular concern. Their continuous release into the environment has a negative global impact on human life. This review summarizes the sources, occurrence, persistence, consequences of exposure, and toxicity of PPCPs, and evaluates the various analytical methods used in the identification and quantification of PPCPs in a variety of solid and liquid environmental matrices. The current techniques of choice for the analysis of PPCPs are state-of-the-art liquid chromatography coupled to mass spectrometry (LC-MS) or tandem mass spectrometry (LC-MS2). However, the complexity of the environmental matrices and the trace levels of micropollutants necessitate the use of advanced sample treatments before these instrumental analyses. Solid-phase extraction (SPE) with different sorbents is now the predominant method used for the extraction of PPCPs from environmental samples. This review also addresses the ongoing analytical method challenges, including sample clean-up and matrix effects, focusing on the occurrence, sample preparation, and analytical methods presently available for the determination of environmental residues of PPCPs. Continuous development of innovative analytical methods is essential for overcoming existing limitations and ensuring the consistency and diversity of analytical methods used in investigations of environmental multi-class compounds.

Monitoring Pharmaceuticals and Personal Care Products in Healthcare Effluent Wastewater Samples and the Effectiveness of Drug Removal in Wastewater Treatment Plants Using the UHPLC-MS/MS Method.

A multi-residue UHPLC-MS/MS analytical method, previously developed for monitoring 52 pharmaceuticals in drinking water, was used to analyse these pharmaceuticals in wastewater originating from healthcare facilities in the Czech Republic. Furthermore, the methodology was expanded to include the evaluation of the effectiveness of drug removal in Czech wastewater treatment plants (WWTPs). Of the 18 wastewater samples analysed by the validated UHPLC-MS/MS, each sample contained at least one quantifiable analyte. This study reveals the prevalence of several different drugs; mean concentrations of 702 µg L-1 of iomeprol, 48.8 µg L-1 of iopromide, 29.9 µg L-1 of gabapentin, 42.0 µg L-1 of caffeine and 82.5 µg L-1 of paracetamol were present. An analysis of 20 samples from ten WWTPs revealed different removal efficiencies for different analytes. Paracetamol was present in the inflow samples of all ten WWTPs and its removal efficiency was 100%. Analytes such as caffeine, ketoprofen, naproxen or atenolol showed high removal efficiencies exceeding 80%. On the other hand, pharmaceuticals like furosemide, metoprolol, iomeprol, zolpidem and tramadol showed lower removal efficiencies. Four pharmaceuticals exhibited higher concentrations in WWTP effluents than in the influents, resulting in negative removal efficiencies: warfarin at -9.5%, indomethacin at -53%, trimethoprim at -54% and metronidazole at -110%. These comprehensive findings contribute valuable insights to the pharmaceutical landscape of wastewater from healthcare facilities and the varied removal efficiencies of Czech WWTPs, which together with the already published literature, gives a more complete picture of the burden on the aquatic environment.

An assessment and characterization of pharmaceuticals and personal care products (PPCPs) within the Great Lakes Basin: Mussel Watch Program (2013-2018).

Defining the environmental occurrence and distribution of chemicals of emerging concern (CECs), including pharmaceuticals and personal care products (PPCPs) in coastal aquatic systems, is often difficult and complex. In this study, 70 compounds representing several classes of pharmaceuticals, including antibiotics, anti-inflammatories, insect repellant, antibacterial, antidepressants, chemotherapy drugs, and X-ray contrast media compounds, were found in dreissenid mussel (zebra/quagga; Dreissena spp.) tissue samples. Overall concentration and detection frequencies varied significantly among sampling locations, site land-use categories, and sites sampled proximate and downstream of point source discharge. Verapamil, triclocarban, etoposide, citalopram, diphenhydramine, sertraline, amitriptyline, and DEET (N,N-diethyl-meta-toluamide) comprised the most ubiquitous PPCPs (> 50%) detected in dreissenid mussels. Among those compounds quantified in mussel tissue, sertraline, metformin, methylprednisolone, hydrocortisone, 1,7-dimethylxanthine, theophylline, zidovudine, prednisone, clonidine, 2-hydroxy-ibuprofen, iopamidol, and melphalan were detected at concentrations up to 475 ng/g (wet weight). Antihypertensives, antibiotics, and antidepressants accounted for the majority of the compounds quantified in mussel tissue. The results showed that PPCPs quantified in dreissenid mussels are occurring as complex mixtures, with 4 to 28 compounds detected at one or more sampling locations. The magnitude and composition of PPCPs detected were highest for sites not influenced by either WWTP or CSO discharge (i.e., non-WWTPs), strongly supporting non-point sources as important drivers and pathways for PPCPs detected in this study. As these compounds are detected at inshore and offshore locations, the findings of this study indicate that their persistence and potential risks are largely unknown, thus warranting further assessment and prioritization of these emerging contaminants in the Great Lakes Basin.

Deciphering the Role of WWTPs in Cold Environments as Hotspots for the Dissemination of Antibiotic Resistance Genes.

Cold environments are the most widespread extreme habitats in the world. However, the role of wastewater treatment plants (WWTPs) in the cryosphere as hotspots in antibiotic resistance dissemination has not been well established. Hence, a snapshot of the resistomes of WWTPs in cold environments, below 5 °C, was provided to elucidate their role in disseminating antibiotic resistance genes (ARGs) to the receiving waterbodies. The resistomes of two natural environments from the cold biosphere were also determined. Quantitative PCR analysis of the aadA, aadB, ampC, blaSHV, blaTEM, dfrA1, ermB, fosA, mecA, qnrS, and tetA(A) genes indicated strong prevalences of these genetic determinants in the selected environments, except for the mecA gene, which was not found in any of the samples. Notably, high abundances of the aadA, ermB, and tetA(A) genes were found in the influents and activated sludge, highlighting that WWTPs of the cryosphere are critical hotspots for disseminating ARGs, potentially worsening the resistance of bacteria to some of the most commonly prescribed antibiotics. Besides, the samples from non-disturbed cold environments had large quantities of ARGs, although their ARG profiles were highly dissimilar. Hence, the high prevalences of ARGs lend support to the fact that antibiotic resistance is a common issue worldwide, including environmentally fragile cold ecosystems.

Assessing the Mass Concentration of Microplastics and Nanoplastics in Wastewater Treatment Plants by Pyrolysis Gas Chromatography-Mass Spectrometry.

The level of microplastics (MPs) in wastewater treatment plants (WWTPs) has been well evaluated by the particle number, while the mass concentration of MPs and especially nanoplastics (NPs) remains unclear. In this study, pyrolysis gas chromatography-mass spectrometry was used to determine the mass concentrations of MPs and NPs with different size ranges (0.01-1, 1-50, and 50-1000 µm) across the whole treatment schemes in two WWTPs. The mass concentrations of total MPs and NPs decreased from 26.23 and 11.28 µg/L in the influent to 1.75 and 0.71 µg/L in the effluent, with removal rates of 93.3 and 93.7% in plants A and B, respectively. The proportions of NPs (0.01-1 µm) were 12.0-17.9 and 5.6-19.5% in plants A and B, respectively, and the removal efficiency of NPs was lower than that of MPs (>1 µm). Based on annual wastewater effluent discharge, it is estimated that about 0.321 and 0.052 tons of MPs and NPs were released into the river each year. Overall, this study investigated the mass concentration of MPs and NPs with a wide size range of 0.01-1000 µm in wastewater, which provided valuable information regarding the pollution level and distribution characteristics of MPs, especially NPs, in WWTPs.

Effect-Targeted Mapping of Potential Estrogenic Agonists and Antagonists in Wastewater via a Conformation-Specific Reporter-Mediated Biosensor.

Wastewater treatment plants (WWTPs) are regarded as the main sources of estrogens that reach the aquatic environment. Hence, continuous monitoring of potential estrogenic-active compounds by a biosensor is an appealing approach. However, existing biosensors cannot simultaneously distinguish and quantify estrogenic agonists and antagonists. To overcome the challenge, we developed an estrogen receptor-based biosensor that selectively screened estrogenic agonists and antagonists by introducing rationally designed agonist/antagonist conformation-specific reporters. The double functional conformation-specific reporters consist of a Cy5.5-labeled streptavidin moiety and a peptide moiety, serving as signal recognition and signal transduction elements. In addition, the conformation recognition mechanism was further validated at the molecular level through molecular docking. Based on the two-step "turn-off" strategy, the biosensor exhibited remarkable sensitivity, detecting 17ß-estradiol-binding activity equivalent (E2-BAE) at 7 ng/L and 4-hydroxytamoxifen-binding activity equivalent (4-OHT-BAE) at 91 ng/L. To validate its practicality, the biosensor was employed in a case study involving wastewater samples from two full-scale WWTPs across different treatment stages to map their estrogenic agonist and antagonist binding activities. Comparison with the yeast two-hybrid bioassay showed a strong liner relationship (r2 = 0.991, p < 0.0001), indicating the excellent accuracy and reliability of this technology in real applications.

Nontarget Screening and Fate of Emerging Per- and Polyfluoroalkyl Substances in Wastewater Treatment Plants in Tianjin, China.

Wastewater treatment plants (WWTPs) are typical point sources of per- and polyfluoroalkyl substances (PFAS) released into the environment. The suspect and nontarget screening based on gas chromatography or liquid chromatography-high resolution mass spectrometry were performed on atmosphere, wastewater, and sludge samples collected from two WWTPs in Tianjin to discover emerging PFAS and their fate in this study. A total of 40 PFAS (14 neutral and 26 ionic) and 64 PFAS were identified in the atmosphere and wastewater/sludge, respectively, among which 5 short-chain perfluoroalkyl sulfonamide derivatives, 4 ionic PFAS, and 15 aqueous film-forming foam-related cationic or zwitterionic PFAS have rarely or never been reported in WWTPs in China. Active air sampling is more conducive to the enrichment of emerging PFAS, while passive sampling is inclined to leave out some ultrashort-chain PFAS or unstable transformation intermediates. Moreover, most precursors and intermediates could be enriched in the atmosphere at night, while the PFAS associated with aerosols with high water content or particles enter the atmosphere easily during the day. Although most emerging PFAS could not be eliminated efficiently in conventional treatment units, deep bed filtration and advanced oxidation processes could partly remove some emerging precursors.

Universal Dynamics of Microbial Communities in Full-Scale Textile Wastewater Treatment Plants and System Prediction by Machine Learning.

The performance of full-scale biological wastewater treatment plants (WWTPs) depends on the operational and environmental conditions of treatment systems. However, we do not know how much these conditions affect microbial community structures and dynamics across systems over time and predictability of the treatment performance. For over a year, the microbial communities of four full-scale WWTPs processing textile wastewater were monitored. During temporal succession, the environmental conditions and system treatment performance were the main drivers, which explained up to 51% of community variations within and between all plants based on the multiple regression models. We identified the universality of community dynamics in all systems using the dissimilarity-overlap curve method, with the significant negative slopes suggesting that the communities containing the same taxa from different plants over time exhibited a similar composition dynamic. The Hubbell neutral theory and the covariance neutrality test indicated that all systems had a dominant niche-based assembly mechanism, supporting that the communities had a similar composition dynamic. Phylogenetically diverse biomarkers for the system conditions and treatment performance were identified by machine learning. Most of the biomarkers (83%) were classified as generalist taxa, and the phylogenetically related biomarkers responded similarly to the system conditions. Many biomarkers for treatment performance perform functions that are crucial for wastewater treatment processes (e.g., carbon and nutrient removal). This study clarifies the relationships between community composition and environmental conditions in full-scale WWTPs over time.

Prevalence of Endocrine Disrupting Chemicals in the urban wastewater treatment systems of Dehradun, India: Daunting presence of Estrone.

We quantified the occurrences and seasonal variations of the target endocrine disrupting chemicals (EDCs) at four (two major municipals, and two academic institutions) WWTPs in Dehradun city, Uttarakhand, India. The results showed estrone in higher concentrations at µgL-1 levels in influent among the WWTPs, compared to triclosan (TCS) at ngL-1 levels. An astounding concentration of 123.95 µgL-1 was recorded for the estrone in the influent, which is to date the highest ever recorded, globally. Statistical data treatment was performed to test the distribution of the data (Shapiro-Wilk, Anderson-Darling, Lilliefors, and Jarque-Bera tests), and the significant difference between the mean of the wastewater sample population (ANOVA: F statistics, p values, Mann-Whitney test, Tukey's and Dunn's post hoc analysis). Statistical data treatment indicated EDCs concentration with a bi-modal distribution. The Shapiro-Wilk, Anderson-Darling, Lilliefors, and Jarque-Bera tests elucidate a non-normal distribution for the EDCs sample data. A statistically significant difference (F = 8.46; p < 0.0001) in the seasonal data for the abundance of the target EDCs at the WWTPs have been observed. Highest and significantly different mean EDCs concentrations were recorded during the monsoon, compared to the spring (p = 0.025) and summer (p = 0.0004) seasons in the influent waters. The mean influent concentrations of TCS and estrone in monsoon were 66.45 ngL-1 and 78.02 µgL-1, respectively. Maximum removals were recorded for TCS, while maximum negative removal of ∼293% was observed for estrone in the WWTPs. Particularly, the high levels of estrone in the wastewater pose a significant threat as estrone presence could be led to feminization, dysregulation of reproduction in organisms, and carcinogenesis processes in the environment. This study critically highlights the limitation of the WWTPs in the treatment, degradation, and assimilation of EDCs leading to their hyperaccumulation at WWTP effluents, thereby posing a substantial threat to nearby aquatic ecosystems, human health, and the ecological balance of the region.

Moderate anthropogenic disturbance stimulates versatile microbial taxa contributing to denitrification and aromatic compound degradation.

Wastewater treatment plants (WWTPs) effluent often contains a significant amount of residual organic pollutants and nutrients, causing disturbance to the coastal effluent receiving areas (ERA). Microbial communities in coastal ERA sediments may benefit from the coexistence of organic pollutants and nutrients, promoting the emergence of versatile taxa that are capable of eliminating these substances simultaneously. However, the identification and exploration of versatile taxa in natural environments under anthropogenic disturbances remain largely uncharted territory. In this study, we specifically focused on the versatile taxa coupled by the degradation of aromatic compounds (ACs) and denitrification, using Hangzhou Bay in China as our study area. We explored how WWTPs effluent disturbance would affect the versatile taxa, and particularly examined the role of disturbance intensity in shaping their composition. Intriguingly, we found that versatile taxa were mainly derived from denitrifiers like Pseudomonas, suggesting the fulfilled potential of denitrifiers regarding ACs degradation. We also discovered that moderate disturbance stimulated the diversity of versatile taxa, resulting in strengthened functional redundancy. Through correlation network analysis, we further demonstrated that moderate disturbance enhanced the community-level cooperation. Thus, moderate disturbance serves as a catalyst for versatile taxa to maintain community function, making them more resilient to effluent disturbances. Additionally, we identified COD and NO3--N concentrations as significant environmental factors influencing the versatile taxa. Overall, our findings reveal the role of effluent disturbances in the promotion of versatile taxa, and highlight moderate disturbance can foster more robust versatile taxa that are better equipped to handle effluent disturbances.

A novel deep learning ensemble model based on two-stage feature selection and intelligent optimization for water quality prediction.

Accurate prediction of effluent total nitrogen (E-TN) can assist in feed-forward control of wastewater treatment plants (WWTPs) to ensure effluent compliance with standards while reducing energy consumption. However, multivariate time series prediction of E-TN is a challenge due to the complex nonlinearity of WWTPs. This paper proposes a novel prediction framework that combines a two-stage feature selection model, the Golden Jackal Optimization (GJO) algorithm, and a hybrid deep learning model, CNN-LSTM-TCN (CLT), aiming to effectively capture the nonlinear relationships of multivariate time series in WWTPs. Specifically, convolutional neural network (CNN), long short-term memory (LSTM), and temporal convolutional network (TCN) combined to build a hybrid deep learning model CNN-LSTM-TCN (CLT). A two-stage feature selection method is utilized to determine the optimal feature subset to reduce the complexity and improve the accuracy of the prediction model, and then, the feature subset is input into the CLT. The hyperparameters of the CLT are optimized using GJO to further improve the prediction performance. Experiments indicate that the two-stage feature selection model learns the optimal feature subset to predict best, and the GJO-CLT achieves the best performance for different backtracking windows and prediction steps. These results demonstrate that the prediction system excels in the task of multivariate water quality time series prediction of WWTPs.

Recent advances on microplastics pollution and removal from wastewater systems: A critical review.

Microplastics (MPs) (plastic particles <5 mm) are globally acknowledged as a serious emerging micropollutant, which passes through various pathways in natural habitats and eventually ends up in our food chain. In this context, the present study critically reviews recent advances in MPs sampling and detection, occurrence, fate, and removal in wastewater treatment plants (WWTPs) by delineating their characteristics that manifest toxicity in the environment via effluent discharge. While there is currently no standard protocol in place, this work examined and compared the latest approaches adopted for improved sampling, sample processing, and characterization of MPs via fluorescence imaging and certified reference materials for method validation. MPs concentration from different sources in the WWTPs varies considerably ranging between 0.28 and 18285 MPs/L (raw wastewater), 0.004-750 MPs/L (effluent), and 0.00023-10380 MPs/kg (sludge). Assessment of MPs removal efficiency across different treatment stages in various in WWTPs has been performed and elucidated their removal mechanisms. The overall MPs removal efficiency in primary, secondary, and tertiary treatment stages in WWTPs reported to be around 57-99%, 78.1-99.4%, and 90-99.2%, respectively. Moreover, the review covers advanced treatment methods for removing MPs, including membrane bioreactors, coagulation/flocculation, ultrafiltration, rapid sand filtration, ozonation, disc filtration, and reverse osmosis, which have been found to be highly effective (>99%). Membrane bioreactors have been proclaimed to be the most reliable secondary treatment technique for MPs removal. Coagulation (92.2-95.7%) followed by ozonation (99.2%) as a tertiary treatment chain has been demonstrated to be the most efficient in removing MPs from secondary-treated wastewater effluent. Further, the review delineates the effect of different treatment stages on the physical and chemical characteristics of MPs, associated toxicity, and potential impact factors that can influence the MPs removal efficiency in WWTPs. Conclusively, the merits and demerits of advanced treatment techniques to mitigate MPs pollution from the wastewater system, research gaps, and future perspectives have been highlighted.

Potential linkage between WWTPs-river-integrated area pollution risk assessment and dissolved organic matter spectral index.

The direct discharge of wastewater can cause severe damage to the water environment of the surface water. However, the influence of dissolved organic matter (DOM) present in wastewater on the allocation of DOM, nitrogen (N), and phosphorus (P) in rivers remains largely unexplored. Addressing the urgent need to monitor areas affected by direct wastewater discharge in a long-term and systematic manner is crucial. In this paper, the DOM of overlying water and sediment in the WWTPs-river-integrated area was characterized by ultraviolet-visible absorption spectroscopy (UV-vis), three-dimensional excitation-emission matrix combined with parallel factor (PARAFAC) method. The effects of WWTPs on receiving waters were investigated, and the potential link between DOM and N, P pollution was explored. The pollution risk was fitted and predicted using a spectral index. The results indicate that the improved water quality index (IWQI) is more suitable for the WWTPs-river integration zone. The DOM fraction in this region is dominated by humic-like matter, which is mainly influenced by WWTPs drainage as well as microbial activities. The DOM fractions in sediment and overlying water were extremely similar, but fluorescence intensity possessed more significant spatial differences. The increase in humic-like matter facilitates the production and preservation of P and also inhibits nitrification, thus affecting the N cycle. There is a significant correlation between DOM fraction, fluorescence index, and N, P. Fluorescence index (FI) fitting of overlying water DOM predicted IWQI and trophic level index, and a(254) fitting of sediment DOM predicted nitrogen and phosphorus pollution risk (FF) with good results. These results contribute to a better understanding of the impact of WWTPs on receiving waters and the potential link between DOM and N and P pollution and provide new ideas for monitoring the water environment in highly polluted areas.

The interaction mechanisms of co-existing polybrominated diphenyl ethers and engineered nanoparticles in environmental waters: A critical review.

This review focuses on the occurrence and interactions of engineered nanoparticles (ENPs) and brominated flame retardants (BFRs) such as polybrominated diphenyl ethers (PBDEs) in water systems and the generation of highly complex compounds in the environment. The release of ENPs and BFRs (e.g. PBDEs) to aquatic environments during their usage and disposal are summarised together with their key interaction mechanisms. The major interaction mechanisms including electrostatic, van der Waals, hydrophobic, molecular bridging and steric, hydrogen and π-bonding, cation bridging and ligand exchange were identified. The presence of ENPs could influence the fate and behaviour of PBDEs through the interactions as well as induced reactions under certain conditions which increases the formation of complex compounds. The interaction leads to alteration of behaviour for PBDEs and their toxic effects to ecological receptors. The intermingled compound (ENPs-BFRs) would show different behaviour from the parental ENPs or BFRs, which are currently lack of investigation. This review provided insights on the interactions of ENPs and BFRs in artificial, environmental water systems and wastewater treatment plants (WWTPs), which are important for a comprehensive risk assessment.