Feasibility of organic micropollutant removal from municipal wastewaters by algal treatment vs. activated sludge treatment: Comparison based on non-targeted organic compound analysis.

Sustainability and life-cycle concerns about the conventional activated sludge (CAS) process for wastewater treatment have been driving the development of energy-efficient, greener alternatives. Feasibility of an algal-based wastewater treatment (A-WWT) system has been demonstrated recently as a possible alternative, capable of simultaneous nutrient and energy recovery. This study compared capabilities of the A-WWT and CAS systems in removing organic micropollutants (OMP). Initial assessments based on surrogate organic measures and fluorescence excitation-emission matrix (FEEM) scans revealed that the A-WWT system achieved higher removals of organics than the CAS system. However, effluents of both systems contained residual organic matter, necessitating further OMP assessment for a rigorous comparison. A novel ultrahigh-performance liquid chromatography- Fourier transform mass spectrometry (UPLC-FTMS)-based non-targeted screening approach was adopted here for residual OMP analysis. This approach confirmed that the A-WWT system resulted in better OMP removal, eliminating 329 compounds and partially reducing 472 compounds, compared to 206 eliminations and 410 partial reductions by the CAS system. Mass spectra signal corresponding to some OMPs increased with treatment while some transformation products were observed following treatment. Higher OMP reduction in the A-WWT system with concurrent reductions of biodegradable carbon, nutrients, and pathogens in a single-step while producing energy and nutrient rich algal biomass underscore its potential as a greener alternative for wastewater treatment.

Research Progress on Detection of Pathogens in Medical Wastewater by Electrochemical Biosensors.

The detection of pathogens in medical wastewater is crucial due to the high content of pathogenic microorganisms that pose significant risks to public health and the environment. Medical wastewater, which includes waste from infectious disease and tuberculosis facilities, as well as comprehensive medical institutions, contains a variety of pathogens such as bacteria, viruses, fungi, and parasites. Traditional detection methods like nucleic acid detection and immunological assays, while effective, are often time-consuming, expensive, and not suitable for rapid detection in underdeveloped areas. Electrochemical biosensors offer a promising alternative with advantages including simplicity, rapid response, portability, and low cost. This paper reviews the sources of pathogens in medical wastewater, highlighting specific bacteria (e.g., E. coli, Salmonella, Staphylococcus aureus), viruses (e.g., enterovirus, respiratory viruses, hepatitis virus), parasites, and fungi. It also discusses various electrochemical biosensing techniques such as voltammetry, conductometry, impedance, photoelectrochemical, and electrochemiluminescent biosensors. These technologies facilitate the rapid, sensitive, and specific detection of pathogens, thereby supporting public health and environmental safety. Future research may should pay more attention on enhancing sensor sensitivity and specificity, developing portable and cost-effective devices, and innovating detection methods for diverse pathogens to improve public health protection and environmental monitoring.

Submersible voltammetric sensing probe for rapid and extended remote monitoring of opioids in community water systems.

The intensifying global opioid crisis, majorly attributed to fentanyl (FT) and its analogs, has necessitated the development of rapid and ultrasensitive remote/on-site FT sensing modalities. However, current approaches for tracking FT exposure through wastewater-based epidemiology (WBE) are unadaptable, time-consuming, and require trained professionals. Toward developing an extended in situ wastewater opioid monitoring system, we have developed a screen-printed electrochemical FT sensor and integrated it with a customized submersible remote sensing probe. The sensor composition and design have been optimized to address the challenges for extended in situ FT monitoring. Specifically, ZIF-8 metal-organic framework (MOF)-derived mesoporous carbon (MPC) nanoparticles (NPs) are incorporated in the screen-printed carbon electrode (SPCE) transducer to improve FT accumulation and its electrocatalytic oxidation. A rapid (10 s) and sensitive square wave voltammetric (SWV) FT detection down to 9.9 µgL-1 is thus achieved in aqueous buffer solution. A protective mixed-matrix membrane (MMM) has been optimized as the anti-fouling sensor coating to mitigate electrode passivation by FT oxidation products and enable long-term, intermittent FT monitoring. The unique MMM, comprising an insulating polyvinyl chloride (PVC) matrix and carboxyl-functionalized multi-walled carbon nanotubes (CNT-COOH) as semiconductive fillers, yielded highly stable FT sensor operation (> 95% normalized response) up to 10 h in domestic wastewater, and up to 4 h in untreated river water. This sensing platform enables wireless data acquisition on a smartphone via Bluetooth. Such effective remote operation of submersible opioid sensing probes could enable stricter surveillance of community water systems toward timely alerts, countermeasures, and legal enforcement.

Comparison of 3 methods characterizing H2S exposure in water and wastewater management work.

This study evaluates the effectiveness of self-assessed exposure (SAE) data collection for characterization of hydrogen sulfide (H2S) risks in water and wastewater management, challenging the adequacy of traditional random or campaign sampling strategies. We compared 3 datasets derived from distinct strategies: expert data with activity metadata (A), SAE without metadata (B), and SAE with logbook metadata (C). The findings reveal that standard practices of random sampling (dataset A) fail to capture the sporadic nature of H2S exposure. Instead, SAE methods enhanced by logbook metadata and supported by reliable detection and calibration infrastructure (datasets B and C) are more effective. When assessing risk, particularly peak exposure risks, it is crucial to adopt measures that capture exposure variability, such as the range and standard deviations. This finer assessment is vital where high H2S peaks occur in confined spaces. Risk assessment should incorporate indices that account for peak exposure, utilizing variability measures like range and standard or geometric standard deviation to reflect the actual risk more accurately. For large datasets, a histogram is just as useful as statistical measures. This approach has revealed that not only wastewater workers but also water distribution network workers, can face unexpectedly high H2S levels when accessing confined underground spaces. Our research underscores the need for continuous monitoring with personal electrochemical gas detector alarm systems, particularly in environments with variable and potentially hazardous exposure levels.

Pharmaceutical emissions on the example of the Baltic Sea catchment: comparing measurements with multi-tier predictive models.

Currently, there is uncertainty about emissions of pharmaceuticals into larger closed ecosystems that are at risk such as the Baltic Sea. There is an increasing need for selecting the right strategies on advanced wastewater treatment. This study analysed 35 pharmaceuticals and iodinated X-ray contrast media in effluents from 82 Wastewater Treatment Plants (WWTPs) across Denmark, Estonia, Finland, Germany, Latvia, Lithuania, Poland and Sweden. Measured concentrations from Finland and Denmark were compared to predicted effluent concentrations using different levels of refinement. The concentrations predicted by the Total Residue Approach, as proposed by the European Medicines Agency, correlated with R2 of 0.18 and 0.031 to measured ones for Denmark and Finland, respectively and the predicted data were significantly higher than the measured ones. These correlations improved substantially to R2 of 0.72 and 0.74 after adjusting for estimated human excretion rates and further to R2 = 0.91 and 0.78 with the inclusion of removal rates in WWTPs. Temporal analysis of compound variations in a closely monitored WWTP showed minimal fluctuation over days and weeks for most compounds but revealed weekly shifts in iodinated X-ray contrast media due to emergency-only operations at X-ray clinics during weekends and an abrupt seasonal change for gabapentin. The findings underscore the limitations of current predictive models and findings (...) demonstrate how these methodologies can be refined by incorporating human pharmaceutical excretion/metabolization as well as removal in wastewater treatment plants to more accurately forecast pharmaceutical levels in aquatic environments.

Typical emerging contaminants in sewage treatment plant effluent, and related watersheds in the Pearl River Basin: Ecological risks and source identification.

Emerging contaminants pose a potential risk to aquatic ecosystems in the Pearl River Basin, China, owing to the high population density and active industry. This study investigated samples from eight sewage treatment plants, and five surface water bodies of related watersheds. To screen the risk of emerging contaminants (ECs), and clarify their sources, this study calculated the risk quotient of detected chemical and performed source identification/apportionment using the positive matrix factorization method. In total, 149 organic pollutants were identified. Pharmaceuticals showed significant concentrations in sewage treatment plant samples (120.87 ng/L), compared with surface water samples (1.13 ng/L). The ecological risk assessment identified three chemicals with a heightened risk to aquatic organisms: fipronil sulfide, caffeine, and roxithromycin. Four principal sources of contaminants were identified: pharmaceutical wastewater, domestic sewage, medical effluent, and agricultural runoff. Pharmaceutical wastewater was the primary contributor (60.4 %), to the cumulative EC concentration and to ECs in sewage treatment plant effluent. Agricultural drainage was the main source of ECs in surface water. This study provides a strategy to obtain comprehensive information on the aquatic risks and potential sources of EC species in areas affected by artificial activities, which is of substantial importance to pollutant management and control.

Non-target liquid chromatography high-resolution mass spectrometry screening to prioritize unregulated micropollutants that persist through domestic wastewater treatment.

Efforts to regulate and monitor emerging contaminants are insufficient because new chemicals are continually brought to market, and many are unregulated and potentially harmful. Domestic wastewater treatment plants are not designed to remove micropollutants and are important sources of emerging contaminants in the aquatic environment. In this study, non-target screening, an unbiased method for analyzing compounds without prior information, was used to identify compounds that may be emitted in wastewater treatment plant effluent and should be monitored. Nine wastewater treatment plants using different treatment methods were studied, and a non-target screening data-processing method was used. The frequencies at which the contaminants were detected and contaminant persistence through the treatment processes were considered, and then the contaminants were prioritized. The predicted no-effect concentration of each prioritized contaminant was used to determine whether further analysis and monitoring of the contaminant was necessary. Quantitative analyses of five compounds (amantadine, atenolol, benzotriazole, diphenhydramine, and sulpiride) were performed using reference standards. Probable molecular formulae and structures were proposed for 17 contaminants, and the risks posed by the contaminants were estimated using predicted no-effect concentrations. The results provide valuable insights into how unregulated micropollutants can be identified and prioritized for monitoring in future studies.

Study of humic-like substances of dissolved organic matter using size exclusion chromatography and chemometrics.

The study of dissolved organic matter (DOM) presents a significant challenge for environmental analyses and the monitoring of wastewater treatment plants (WWTPs). This is particularly true for the tracking of recalcitrant to biodegradation dissolved organic matter (rDOM) compounds, which is generated during the thermal pretreatment of sludge. This study aims to develop analytical and chemometric methods to differentiate melanoidins from humic acids (HAs), two components of rDOM that require monitoring at various stages of wastewater treatment processes due to their distinct biological effects. The developed method implements the separation of macromolecules through ultra-high-performance liquid chromatography size-exclusion chromatography (U-HPLC SEC) followed by online UV and fluorescence detection. UV detection was performed at 210, 254, and 280 nm, and fluorescence detection at six excitation/emission pairs: 230/355 nm, 270/355 nm, 240/440 nm, 270/500 nm, 330/425 nm, and 390/500 nm. Chromatograms obtained for each sample from these nine detection modes were integrated and separated into four molecular fractions: >40 kDa, 20-40 kDa, 10-20 kDa, and <10 kDa. To enhance analytical resolution and normalize the data, ratios were calculated from the areas of chromatographic peaks obtained for each detection mode. The results demonstrate the utility of these ratios in discriminating samples composed of HAs, melanoidins, and their mixtures, through principal component analysis (PCA). Low molecular weight fractions were found to be specific to melanoidins, while high molecular weight fractions were characteristic of HAs. For the detection modes specific to melanoidins, UV absorbance at 210, 254, and 280 nm were predominantly present in the numerators, with tryptophan-like fluorescence emissions in the denominators. Conversely, fluorescence emissions largely represented both numerators and denominators for HAs. This online method also enables the discrimination of pseudo-melanoidins, compounds revealing a nitrogen deficiency in their chemical structures.

Adjusting for dilution in wastewater using biomarkers: A practical approach.

We developed a biomarker-based approach to quantify in-sewer dilution by measuring wastewater quality parameters (ammoniacal-N, orthophosphate, crAssphage). This approach can enhance the environmental management of wastewater treatment works (WWTW) by optimising their operation and providing cost-effective information on the health and behaviour of populations and their interactions with the environment through wastewater-based epidemiology (WBE). Our method relies on site specific baselines calculated for each biomarker. These baselines reflect the sewer conditions without the influence of rainfall-derived inflow and infiltration (RDII). Ammoniacal-N was the best candidate to use as proxy for dilution. We demonstrated that the dilution calculated using biomarkers correlates well with the dilution indicated by measured flow. In some instances, the biomarkers showed much higher dilution than measured flows. These differences were attributed to the loss of flow volume at wastewater treatment works due to the activation of combined sewer overflows (CSOs) and/or storm tanks. Using flow measured directly at the WWTW could therefore result in underestimation of target analyte loads.

Preparation of amphiphilic poly(divinylbenzene-co-N-vinylpyrrolidone)-functionalized polydopamine magnetic nanoadsorbents for enrichment of synthetic cannabinoids in wastewater.

Concerns have been raised about synthetic cannabinoids (SCs), which are among the most often trafficked and used illegal substances. An analytical method that holds promise for determining illicit drug use in the general population is wastewater-based epidemiology (WBE). Unfortunately, the concentration of SCs in wastewater is often extremely low on account of their hydrophobic nature, thus presenting a significant obstacle to the accurate detection and quantification of SCs using WBE. In this study, we present novel magnetic nanomaterials as amphiphilic adsorbents for pretreatment of wastewater using magnetic solid phase extraction (MSPE). Polydopamine-modified Fe3O4 nanoparticles were used as the magnetic core and further functionalized with poly(divinylbenzene-N-vinylpyrrolidone). Coupled with UHPLC-MS/MS analysis, an analytical method to simultaneously detect nine SCs at trace-levels in wastewater was developed and validated, enriching 50 mL wastewater to 100 µL with limits of detection (LOD) being 0.005-0.5 ng L-1, limits of quantification (LOQ) being 0.01-1.0 ng L-1, recoveries ranging from 73.99 to 110.72%, and the intra- and inter-day precision's relative standard deviations less than 15%. In comparison to the time-consuming conventional column-based solid phase extraction, the entire MSPE procedure from sample pre-treatment to data acquisition could be finished in one hour, thus largely facilitating the WBE method for drug surveillance and control.

Heavy metal contamination in Sungai Petani, Malaysia: a wastewater-based epidemiology study.

The aim of this study was to investigate the use of wastewater-based epidemiology (WBE) to estimate heavy metal exposure in Sungai Petani, Malaysia. Atomic absorption spectroscopy was used to detect copper (Cu), nickel (Ni), zinc (Zn), iron (Fe), and cadmium (Cd) in wastewater from eight sewage treatment facilities in Sungai Petani in January 2022. The heavy metal concentrations were measured in both influent and effluent, and the mean concentrations in the wastewater were found to be in the following order: Fe > Ni > Zn > Cd > Cu, with a 100% detection frequency. The results of WBE estimation showed that Fe, Ni, and Zn had the highest estimated per population exposure levels, while Cd had the lowest. Compared to a similar study conducted in Penang, Malaysia, all metals except Cu were found to have higher concentrations in Sungai Petani, even though it is a non-industrial district. These findings highlight the importance of addressing heavy metal contamination in Sungai Petani and implementing effective risk management and prevention strategies.

Instrumental and theoretical advancements in pulsed elution-LC × LC: Investigation of pulse parameters and application to wastewater effluent.

Due to the decoupling of the first (1D) and second (2D) dimension in pulsed elution-LC × LC (PE-LC × LC), method development is more flexible and straightforward compared to fast comprehensive LC × LC where the dependencies of key parameters between the two dimensions limits its flexibility. In this study we present a method for pulse generation, which is based on a switching valve alternating between one pump that delivers the gradient and a second pump that delivers low eluotrophic strength for the pause state. Consequently, the dwell volume of the system was circumvented and 7.5, and 3.75 times shorter pulse widths could be generated at flow rates of 0.2, and 0.4 mL/min with satisfactory accuracies between programmed and observed mobile phase composition (relative deviation of 6.0 %). We investigated how key parameters including pulse width and step height, 2D gradient time and flow rate affected the peak capacity in PE-LC × LC. The conditions yielding the highest peak capacity for the PE-LC × LC- high-resolution mass spectrometry (HRMS) system were applied to a wastewater effluent sample. The results were compared to a one dimensional (1D)-LC-HRMS chromatogram. The peak capacity increased with a factor 34 from 112 for the 1D-LC run to 3770 for PE-LC × LC-HRMS after correction for undersampling. The analysis time for PE-LC × LC-HRMS was 12.1 h compared to 67.5 min for the 1D-LC-HRMS run. The purity of the mass spectra improved for PE-LC × LC-HRMS by a factor 2.6 (p-value 3.3 × 10-6) and 2.0 (p-value 2.5 × 10-3) for the low and high collision energy trace compared to the 1D-LC-HRMS analysis. Furthermore, the signal-to-noise ratio (S/N) was 4.2 times higher (range: 0.06-56.7, p-value 3.8 × 10-2) compared to the 1D-LC-HRMS separation based on 42 identified compounds. The improvements in S/N were explained by the lower peak volume obtained in the PE-LC × LC-HRMS.

High throughput and sensitive quantitation of tobacco-specific alkaloids and nitrosamines in wastewater.

Tobacco-specific alkaloids and nitrosamines are important biomarkers for the estimation of tobacco use and human exposure to tobacco-specific nitrosamines that can be monitored by wastewater analysis. Thus far their analysis has used solid phase extraction, which is costly and time-consuming. In this study, we developed a direct injection liquid chromatography-tandem mass spectrometry method for the quantification of two tobacco-specific alkaloids and five nitrosamines in wastewater. The method achieved excellent linearity (R2 > 0.99) for all analytes, with calibration ranging from 0.10 to 800 ng/L. Method limits of detection and quantification were 0.17 ng/L (N-nitrosonornicotine, NNN) and 1.0 ng/L (N-nitrosoanatabine (NAT) and NNN), with acceptable accuracy (100 % ± 20 %) and precision (± 15 %). Analyte loss during filtration was < 15 %, and the relative matrix effect was < 10 %. The method was applied to 43 pooled wastewater samples collected from three wastewater treatment plants in Australia between 2017 and 2021. Anabasine and anatabine were detected in all samples at concentrations of 5.0 - 33 ng/L and 12 - 41 ng/L, respectively. Three of the five tobacco-specific nitrosamines (NAT, NNN, and (4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol) (NNAL)) were detected, in < 50 % of the wastewater samples, with concentrations nearly ten times lower than the tobacco alkaloids (< 1.0 - 6.2 ng/L). In-sewer stability of the nitrosamines was also assessed in this study, with four (NAT, NNAL, NNN, and N-nitrosoanabasine (NAB)) being stable (i.e. < 20 % transformation over 12 h in both control reactor (CR) and rising main reactor (RM) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) being moderately stable (< 40 % loss over 12 h in RM). This direct injection method provides a high-throughput approach in simultaneous investigation of tobacco use and assessment of public exposure to tobacco-specific nitrosamines.

Development of a "turn off" fluorescent molecularly imprinted nanoparticle-based sensor for selective captopril quantification in synthetic urine and wastewater samples.

The combination of silica nanoparticles with fluorescent molecularly imprinted polymers (Si-FMIPs) prepared by a one-pot sol-gel synthesis method to act as chemical sensors for the selective and sensitive determination of captopril is described. Several analytical parameters were optimized, including reagent ratio, solvent, concentration of Si-FMIP solutions, and contact time. Fourier-transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), and the ninhydrin assay were used for characterization. The selectivity was evaluated against molecules belonging to other drug classes, such as fluoroquinolones, nonacid nonopioids, benzothiadiazine, alpha amino acids, and nitroimidazoles. Under optimized conditions, the Si-FMIP-based sensor exhibited a working range of 1-15 µM, with a limit of detection (LOD) of 0.7 µM, repeatability of 6.4% (n = 10), and suitable recovery values at three concentration levels (98.5% (1.5 µM), 99.9% (3.5 µM), and 99.2% (7.5 µM)) for wastewater samples. The sensor provided a working range of 0.5-15 µM for synthetic urine samples, with an LOD of 0.4 µM and a repeatability of 7.4% (n = 10) and recovery values of 93.7%, 92.9%, and 98.0% for 1.0 µM, 3.5 µM, and 10 µM, respectively. In conclusion, our single-vessel synthesis approach for Si-FMIPs proved to be highly effective for the selective determination of captopril in wastewater and synthetic urine samples.

Online soft measurement method for chemical oxygen demand based on CNN-BiLSTM-Attention algorithm.

The measurement of chemical oxygen demand (COD) is very important in the process of sewage treatment. The value of COD reflects the effectiveness and trend of sewage treatment to a certain extent, but obtaining accurate data requires high cost and labor intensity. To1 solve this problem, this paper proposes an online soft measurement method for COD based on Convolutional Neural Network-Bidirectional Long Short-Term Memory Network-Attention Mechanism (CNN-BiLSTM-Attention) algorithm. Firstly, by analyzing the mechanism of the aerobic tank stage in the Anaerobic-Anoxic-Oxic (A2O) wastewater treatment process, the selection range of input variables was preliminarily determined, and the collected sample dataset was subjected to correlation analysis. Finally, pH, dissolved oxygen (DO), electrical conductivity (EC), and water temperature (T) were determined as input variables for soft measurement prediction of COD.Then, based on the feature extraction ability of CNN and the advantage that BiLSTM is able to capture the backward and forward dependencies in time series data, combined with the attention mechanism that can assign higher weights to the key data, a CNN-BiLSTM-Attention algorithm model was established to soft measure COD in the effluent from the aerobic zone of the A2O wastewater treatment process. At the same time, root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of determination (R2) were utilized Three indicators were used to evaluate the model, and the results showed that the model can accurately predict the value of COD and has a high accuracy. At the same time, compared with models such as CNN-LSTM-Attention, CNN-BiLSTM, CNN-LSTM, LSTM, RNN, BP, SVM, XGBoost, and RF etc., the results showed that the CNN-BiLSTM Attention model performed the best, proving the superiority of the algorithm model.The Wilcoxon signed-rank test indicates significant differences between the CNN-BiLSTM-Attention model and other models.

Accumulation and translocation of lead in vegetables through intensive use of organic manure and mineral fertilizers with wastewater.

In many countries with wastewater irrigation and intensive use of fertilizers (minerals and organics), heavy metal deposition by crops is regarded as a major environmental concern. A study was conducted to determine the impact of mineral fertilizers, cow manure, poultry manure, leaf litter, and sugarcane bagasse on soil's trace Pb content and edible parts of vegetables. It also evaluated the risk of lead (Pb) contamination in water, soil, and food crops. Six vegetables (Daucus carota, Brassica oleracea, Pisum sativum, Solanum tuberosum, Raphanus sativus, and Spinacia oleracea) were grown in the field under twelve treatments with different nutrient and water inputs. The lead concentrations in soil, vegetables for all treatments and water samples ranged from 1.038-10.478, 0.09346-9.0639 mg/kg and 0.036-0.26448 mg/L, The concentration of lead in soil treated with wastewater in treatment (T6) and vegetable samples was significantly higher, exceeding the WHO's permitted limit. Mineral and organic fertilizers combined with wastewater treatment reduced lead (Pb) concentrations in vegetables compared to wastewater application without organic fertilizers. Health risk indexes for all treatments except wastewater treatment (T6) were less than one. Pb concentrations in mineral fertilizers, cow manure, poultry manure, leaf litter, and sugarcane bagasse treated were determined to pose no possible risk to consumers.

Development of an orbital shaker-assisted fatty acid-based switchable solvent microextraction procedure for rapid and green extraction of amoxicillin from complex matrices: Central composite design.

In this study, a cheap, fast and simple orbital shaker-assisted fatty acid-based switchable solvent microextraction (OS-FASS-ME) procedure was developed for the extraction of amoxicillin (AMOX) in dairy products, pharmaceutical samples and wastewater prior to its spectrophotometric analysis. Fatty acid-based switchable solvents were investigated for extracting AMOX. The key factors of the OS-FASS-ME procedure were optimized using a central composite design. The linearity of OS-FASS-ME procedure was in the range 5-600 ng mL-1 with a correlation coefficient of 0.991. In five replicate experiments for 20 ng mL-1 of AMOX solution, the recovery and relative standard deviation were 95.8% and 2.2%, respectively. Limits of detection and quantification were found 1.5 ng mL-1 and 5 ng mL-1, respectively. The accuracy, precision, robustness and selectivity of the OS-FASS-ME procedure were investigated in detail under optimum conditions. The OS-FASS-ME procedure was applied to milk, cheese, wastewater, syrups and tablets. A comparison of the results obtained from the reference method and the OS-FASS-ME method showed that the OS-FASS-ME procedure can be successfully applied to complex matrices.

SARS-CoV-2 wastewater surveillance at two university campuses: lessons learned and insights on intervention strategies for public health guidance.

Wastewater surveillance has been a tool for public health officials throughout the COVID-19 pandemic. Universities established pandemic response committees to facilitate safe learning for students, faculty, and staff. These committees met to analyze both wastewater and clinical data to propose mitigation strategies to limit the spread of COVID-19. This paper reviews the initial efforts of utilizing campus data inclusive of wastewater surveillance for SARS-CoV-2 RNA concentrations, clinical case data from university response teams, and mitigation strategies from Grand Valley State University in West Michigan (population 21,648 students) and Oakland University in East Michigan (population 18,552 students) from November 2020 to April 2022. Wastewater positivity rates for both universities ranged from 32.8 to 46.8%. Peak viral signals for both universities directly corresponded to variant points of entry within the campus populations from 2021 to 2022. It was found that the organization of clinical case data and variability of wastewater testing data were large barriers for both universities to effectively understand disease dynamics within the university population. We review the initial efforts of onboarding wastewater surveillance and provide direction for structuring ongoing surveillance workflows and future epidemic response strategies based on those that led to reduced viral signals in campus wastewater.

Direct injection ultra-performance liquid chromatography-tandem mass spectrometry for the high-throughput determination of etomidate and etomidate acid in wastewater.

Etomidate (ET), a hypnotic agent used for the induction of anesthesia, is rapidly metabolized to etomidate acid (ETA) in the liver. Recently, ET has become one of the most serious alternative drugs of abuse in China. Therefore, an urgent need exists to develop a fast and convenient analysis method for monitoring ET. The current work presents a simple, fast, and sensitive direct injection method for the determination of ET and ETA in wastewater. After the optimization of the ultra-performance liquid chromatography-tandem mass spectrometry and sample filtration conditions, the method exhibited satisfactory limits of detection (1 ng/L) and good filtration loss. The validated method was successfully applied to determine the concentrations of ET and ETA in wastewater samples (n = 245) from several wastewater treatment plants in China. The concentrations of the targets in positive samples ranged from less than the lower limits of quantitation to 47.71 ng/L. The method can meet ET monitoring and high-throughput analysis requirements.

Extraction of Proteins from Municipal Wastewater and Activated Sludge.

Wastewater treatment plants (WWTPs) are the main barrier to cope with the increased pressure of municipal and industrial wastewater on natural water resources in terms of both polluting load and produced volumes. For this reason, WWTP's efficiency should be the highest; thus, their monitoring becomes critical. In conventional WWTPs, biodegradation of pollutants mainly occurs in the biological reactors, and an increasing interest in a deeper characterization of the biomasses involved in these processes (made of biofilms, granules, and suspended activated sludge) rose up in recent years. In this sense, the meta-omics approaches were recently developed to investigate the entire set of biomolecules of a given class in a microbial community with the same general objective: the identification of the biomolecules through the sequence similarity of high degree in the already available databases. Particularly, metaproteomics concerns the identification of all proteins in a microbial community in a given moment or condition. In this chapter, a protocol for the extraction and separation of proteins from activate sludge sampled at WWTPs is proposed.