New PFASs Identified in AFFF Impacted Groundwater by Passive Sampling and Nontarget Analysis.

Monitoring contamination from per- and polyfluoroalkyl substances (PFASs) in water systems impacted by aqueous film-forming foams (AFFFs) typically addresses a few known PFAS groups. Given the diversity of PFASs present in AFFFs, current analytical approaches do not comprehensively address the range of PFASs present in these systems. A suspect-screening and nontarget analysis (NTA) approach was developed and applied to identify novel PFASs in groundwater samples contaminated from historic AFFF use. A total of 88 PFASs were identified in both passive samplers and grab samples, and these were dominated by sulfonate derivatives and sulfonamide-derived precursors. Several ultrashort-chain (USC) PFASs (≤C3) were detected, 11 reported for the first time in Australian groundwater. Several transformation products were identified, including perfluoroalkane sulfonamides (FASAs) and perfluoroalkane sulfinates (PFASis). Two new PFASs were reported (((perfluorohexyl)sulfonyl)sulfamic acid; m/z 477.9068 and (E)-1,1,2,2,3,3,4,5,6,7,8,8,8-tridecafluorooct-6-ene-1-sulfonic acid; m/z 424.9482). This study highlights that several PFASs are overlooked using standard target analysis, and therefore, the potential risk from all PFASs present is likely to be underestimated.

Cumulative Neutral Loss Model for Fragment Deconvolution in Electrospray Ionization High-Resolution Mass Spectrometry Data.

Clean high-resolution mass spectra (HRMS) are essential to a successful structural elucidation of an unknown feature during nontarget analysis (NTA) workflows. This is a crucial step, particularly for the spectra generated during data-independent acquisition or during direct infusion experiments. The most commonly available tools only take advantage of the time domain for spectral cleanup. Here, we present an algorithm that combines the time domain and mass domain information to perform spectral deconvolution. The algorithm employs a probability-based cumulative neutral loss (CNL) model for fragment deconvolution. The optimized model, with a mass tolerance of 0.005 Da and a scoreCNL threshold of 0.00, was able to achieve a true positive rate (TPr) of 95.0%, a false discovery rate (FDr) of 20.6%, and a reduction rate of 35.4%. Additionally, the CNL model was extensively tested on real samples containing predominantly pesticides at different concentration levels and with matrix effects. Overall, the model was able to obtain a TPr above 88.8% with FD rates between 33 and 79% and reduction rates between 9 and 45%. Finally, the CNL model was compared with the retention time difference method and peak shape correlation analysis, showing that a combination of correlation analysis and the CNL model was the most effective for fragment deconvolution, obtaining a TPr of 84.7%, an FDr of 54.4%, and a reduction rate of 51.0%.

Is Nontarget Analysis Ready for Regulatory Application? Influence of Peak-Picking Algorithms on Data Analysis.

The use of peak-picking algorithms is an essential step in all nontarget analysis (NTA) workflows. However, algorithm choice may influence reliability and reproducibility of results. Using a real-world data set, the aim of this study was to investigate how different peak-picking algorithms influence NTA results when exploring temporal and/or spatial trends. For this, drinking water catchment monitoring data, using passive samplers collected twice per year across Southeast Queensland, Australia (n = 18 sites) between 2014 and 2019, was investigated. Data were acquired using liquid chromatography coupled to high-resolution mass spectrometry. Peak picking was performed using five different programs/algorithms (SCIEX OS, MSDial, self-adjusting-feature-detection, two algorithms within MarkerView), keeping parameters identical whenever possible. The resulting feature lists revealed low overlap: 7.2% of features were picked by >3 algorithms, while 74% of features were only picked by a single algorithm. Trend evaluation of the data, using principal component analysis, showed significant variability between the approaches, with only one temporal and no spatial trend being identified by all algorithms. Manual evaluation of features of interest (p-value <0.01, log fold change >2) for one sampling site revealed high rates of incorrectly picked peaks (>70%) for three algorithms. Lower rates (<30%) were observed for the other algorithms, but with the caveat of not successfully picking all internal standards used as quality control. The choice is therefore currently between comprehensive and strict peak picking, either resulting in increased noise or missed peaks, respectively. Reproducibility of NTA results remains challenging when applied for regulatory frameworks.

Critical Assessment of the Chemical Space Covered by LC-HRMS Non-Targeted Analysis.

Non-targeted analysis (NTA) has emerged as a valuable approach for the comprehensive monitoring of chemicals of emerging concern (CECs) in the exposome. The NTA approach can theoretically identify compounds with diverse physicochemical properties and sources. Even though they are generic and have a wide scope, non-targeted analysis methods have been shown to have limitations in terms of their coverage of the chemical space, as the number of identified chemicals in each sample is very low (e.g., ≤5%). Investigating the chemical space that is covered by each NTA assay is crucial for understanding the limitations and challenges associated with the workflow, from the experimental methods to the data acquisition and data processing techniques. In this review, we examined recent NTA studies published between 2017 and 2023 that employed liquid chromatography-high-resolution mass spectrometry. The parameters used in each study were documented, and the reported chemicals at confidence levels 1 and 2 were retrieved. The chosen experimental setups and the quality of the reporting were critically evaluated and discussed. Our findings reveal that only around 2% of the estimated chemical space was covered by the NTA studies investigated for this review. Little to no trend was found between the experimental setup and the observed coverage due to the generic and wide scope of the NTA studies. The limited coverage of the chemical space by the reviewed NTA studies highlights the necessity for a more comprehensive approach in the experimental and data processing setups in order to enable the exploration of a broader range of chemical space, with the ultimate goal of protecting human and environmental health. Recommendations for further exploring a wider range of the chemical space are given.

National Wastewater Reconnaissance of Analgesic Consumption in Australia.

A wastewater-based epidemiology (WBE) method is presented to estimate analgesic consumption and assess the burden of treated pain in Australian communities. Wastewater influent samples from 60 communities, representing ∼52% of Australia's population, were analyzed to quantify the concentration of analgesics used to treat pain and converted to estimates of the amount of drug consumed per day per 1000 inhabitants using pharmacokinetics and WBE data. Consumption was standardized to the defined daily dose per day per 1000 people. The population burden of pain treatment was classified as mild to moderate pain (for non-opioid analgesics) and strong to severe pain (for opioid analgesics). The mean per capita weighted total DDD of non-opioid analgesics was 0.029 DDD/day/person, and that of opioid-based analgesics was 0.037 DDD/day/person across Australia. A greater burden of pain (mild to moderate or strong to severe pain index) was observed at regional and remote sites. The correlation analysis of pain indices with different socioeconomic descriptors revealed that pain affects populations from high to low socioeconomic groups. Australians spent an estimated US $3.5 (AU $5) per day on analgesics. Our findings suggest that WBE could be an effective surveillance tool for estimating the consumption of analgesics at a population scale and assessing the total treated pain burden in communities.

Novel Per- and Polyfluoroalkyl Substances Discovered in Cattle Exposed to AFFF-Impacted Groundwater.

The leaching of per- and polyfluoroalkyl substances (PFASs) from Australian firefighting training grounds has resulted in extensive contamination of groundwater and nearby farmlands. Humans, farm animals, and wildlife in these areas may have been exposed to complex mixtures of PFASs from aqueous film-forming foams (AFFFs). This study aimed to identify PFAS classes in pooled whole blood (n = 4) and serum (n = 4) from cattle exposed to AFFF-impacted groundwater and potentially discover new PFASs in blood. Thirty PFASs were identified at various levels of confidence (levels 1a-5a), including three novel compounds: (i) perfluorohexanesulfonamido 2-hydroxypropanoic acid (FHxSA-HOPrA), (ii) methyl((perfluorohexyl)sulfonyl)sulfuramidous acid, and (iii) methyl((perfluorooctyl)sulfonyl)sulfuramidous acid, belonging to two different classes. Biotransformation intermediate, perfluorohexanesulfonamido propanoic acid (FHxSA-PrA), hitherto unreported in biological samples, was detected in both whole blood and serum. Furthermore, perfluoroalkyl sulfonamides, including perfluoropropane sulfonamide (FPrSA), perfluorobutane sulfonamide (FBSA), and perfluorohexane sulfonamide (FHxSA) were predominantly detected in whole blood, suggesting that these accumulate in the cell fraction of blood. The suspect screening revealed several fluoroalkyl chain-substituted PFAS. The results suggest that targeting only the major PFASs in the plasma or serum of AFFF-exposed mammals likely underestimates the toxicological risks associated with exposure. Future studies of AFFF-exposed populations should include whole-blood analysis with high-resolution mass spectrometry to understand the true extent of PFAS exposure.

Improving Wastewater-Based Tobacco Use Estimates Using Anabasine.

In wastewater-based epidemiology (WBE), nicotine metabolites have been used as biomarkers for monitoring tobacco use. Recently, the minor tobacco alkaloids anabasine and anatabine have been suggested as more specific biomarkers for tobacco use since nicotine use can be from both tobacco and non-tobacco sources. This study aimed to provide an in-depth evaluation of the suitability of anabasine and anatabine as WBE biomarkers of tobacco and subsequently estimate their excretion factors for WBE applications. Pooled urine (n = 64) and wastewater samples (n = 277), collected between 2009 and 2019 in Queensland, Australia, were analyzed for nicotine and its metabolites (cotinine and hydroxycotinine), as well as anabasine and anatabine. Anabasine performed as the better biomarker, showing a similar per capita load in pooled urine (2.2 ± 0.3 µg/day/person) and wastewater samples (2.3 ± 0.3 µg/day/person), while the per capita load of anatabine in wastewater was 50% higher than its load in urine. It is estimated that 0.9 µg of anabasine was excreted per cigarette smoked. Triangulation of tobacco sales data and tobacco use estimated from either anabasine or cotinine showed that anabasine-based estimates were 5% higher than sales data, while cotinine-based estimates were between 2 and 28% higher. Our results provided concrete evidence to confirm the suitability of anabasine as a specific biomarker for monitoring tobacco use by WBE.

Increased Nicotine Consumption in Australia During the First Months of the COVID-19 Pandemic.

INTRODUCTION: Mixed findings have been reported about the impact of the COVID-19 pandemic on smoking behavior in different populations. AIMS AND METHODS: In this study, we aimed to quantify changes in smoking prevalence through the proxy of nicotine consumption in the Australian population from 2017 to 2020 inclusive. Estimates of nicotine consumption between 2017 and 2020 were retrieved from a national wastewater monitoring program that covers up to 50% of the Australian population. National sales data for nicotine replacement therapy (NRT) products from 2017 to 2020 were also acquired. Linear regression and pairwise comparison were conducted to identify data trends and to test differences between time periods. RESULTS: The average consumption of nicotine in Australia decreased between 2017 and 2019 but increased in 2020. Estimated consumption in the first half of 2020 was significantly higher (~30%) than the previous period. Sales of NRT products increased gradually from 2017 to 2020 although sales in the first half of the year were consistently lower than in the second half. CONCLUSION: Total nicotine consumption increased in Australia during the early stage of the pandemic in 2020. Increased nicotine consumption may be due to people managing higher stress levels, such as from loneliness due to control measures, and also greater opportunities to smoke/vape while working from home and during lockdowns in the early stage of the pandemic. IMPLICATIONS: Tobacco and nicotine consumption have been decreasing in Australia but the COVID-19 pandemic may have temporarily disrupted this trend. In 2020, the higher impacts of lockdowns and working from home arrangements may have led to a temporary reversal of the previous downward trend in smoking during the early stage of the pandemic.

Identification and Quantification of Micro-Bioplastics in Environmental Samples by Pyrolysis-Gas Chromatography-Mass Spectrometry.

Bioplastics are materials that are biobased and/or biodegradable, but not necessarily both. Concerns about environmental plastic pollution are constantly growing with increasing demand for substituting fossil-based plastics with those made using renewable resource feedstocks. For many conventional bioplastics to completely decompose/degrade, they require specific environmental conditions that are rarely met in natural ecosystems, leading to rapid formation of micro-bioplastics. As global bioplastic production and consumption/use continue to increase, there is growing concern regarding the potential for environmental pollution from micro-bioplastics. However, the actual extent of their environmental occurrence and potential impacts remains unclear, and there is insufficient mass concentration-based quantitative data due to the lack of quantitative analytical methods. This study developed and validated an analytical method coupling pressurized liquid extraction and pyrolysis-gas chromatography-mass spectrometry combined with thermochemolysis to simultaneously identify and quantify five targeted micro-bioplastics (i.e., polylactic acid (PLA), polyhydroxyalkanoate, polybutylene succinate, polycaprolactone, and polybutylene adipate terephthalate (PBAT)) in environmental samples on a polymer-specific mass-based concentration. The recovery of spiked micro-bioplastics in environmental samples (biosolids) ranged from 74 to 116%. The limits of quantification for the target micro-bioplastics were between 0.02 and 0.05 mg/g. PLA and PBAT were commonly detected in wastewater, biosolids, and sediment samples at concentrations between 0.07 and 0.18 mg/g. The presented analytical method enables the accurate identification, quantification, and monitoring of micro-bioplastics in environmental samples. This study quantified five micro-bioplastic types in complex environmental samples for the first time, filling in gaps in our knowledge about bioplastic pollution and providing a useful methodology and important reference data for future research.

From Molecular Descriptors to Intrinsic Fish Toxicity of Chemicals: An Alternative Approach to Chemical Prioritization.

The European and U.S. chemical agencies have listed approximately 800k chemicals about which knowledge of potential risks to human health and the environment is lacking. Filling these data gaps experimentally is impossible, so in silico approaches and prediction are essential. Many existing models are however limited by assumptions (e.g., linearity and continuity) and small training sets. In this study, we present a supervised direct classification model that connects molecular descriptors to toxicity. Categories can be driven by either data (using k-means clustering) or defined by regulation. This was tested via 907 experimentally defined 96 h LC50 values for acute fish toxicity. Our classification model explained ≈90% of the variance in our data for the training set and ≈80% for the test set. This strategy gave a 5-fold decrease in the frequency of incorrect categorization compared to a quantitative structure-activity relationship (QSAR) regression model. Our model was subsequently employed to predict the toxicity categories of ≈32k chemicals. A comparison between the model-based applicability domain (AD) and the training set AD was performed, suggesting that the training set-based AD is a more adequate way to avoid extrapolation when using such models. The better performance of our direct classification model compared to that of QSAR methods makes this approach a viable tool for assessing the hazards and risks of chemicals.

Concentrations of Tire Additive Chemicals and Tire Road Wear Particles in an Australian Urban Tributary.

Tire road wear particles (TRWPs) are one of the largest sources of microplastics to the urban environment with recent concerns as they also provide a pathway for additive chemicals to leach into the environment. Stormwater is a major source of TRWPs and associated additives to urban surface water, with additives including the antioxidant derivative N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine-quinone (6PPD-quinone) demonstrating links to aquatic toxicity at environmentally relevant concentrations. The present study used complementary analysis methods to quantify both TRWPs and a suite of known tire additive chemicals (including 6PPD-quinone) to an urban tributary in Australia during severe storm events. Concentrations of additives increased more than 40 times during storms, with a maximum concentration of 2760 ng/L for ∑15additives, 88 ng/L for 6PPD-quinone, and a similar profile observed in each storm. TRWPs were detected during storm peaks with a maximum concentration between 6.4 and 18 mg/L, and concentrations of TRWPs and all additives were highly correlated. Contaminant mass loads to this catchment were estimated as up to 100 g/storm for ∑15additives, 3 g/storm for 6PPD-quinone, and between 252 and 730 kg of TRWPs/storm. While 6PPD-quinone concentrations in this catchment were lower than previous studies, elevated concentrations post storm suggest prolonged aquatic exposure.

Short Depuration of Oysters Intended for Human Consumption Is Effective at Reducing Exposure to Nanoplastics.

Nanoplastics (NPs; <1 µm) have greater availability to marine organisms than microplastics (1-5000 µm). Understanding NP uptake and depuration in marine organisms intended for human consumption is imperative for food safety, but until now it has been limited due to analytical constraints. Oysters (Crassostrea gigas) were exposed to polystyrene NPs doped with palladium (Pd), allowing the measurements of their uptake into tissues by inductively coupled plasma mass spectrometry (ICP-MS) combined with electron microscopy. Oysters were exposed for 6 days (d) to "Smooth" or "Raspberry" NPs, followed by 30 d of depuration with the aim of assessing the NP concentration in C. gigas following exposure, inferring the accumulation and elimination rates, and understanding the clearance of Pd NPs during the depuration period. After 6 d, the most significant accumulation was found in the digestive gland (106.6 and 135.3 µg g-1 dw, for Smooth and Raspberry NPs, respectively) and showed the most evident depuration (elimination rate constant KSmooth = 2 d-1 and KRaspberry = 0.2 d-1). Almost complete depuration of the Raspberry NPs occurred after 30 d. While a post-harvesting depuration period of 24-48 h for oysters could potentially reduce the NP content by 75%, more research to validate these findings, including depuration studies of oysters from the field, is required to inform practices to reduce human exposure through consumption.

Semiquantitative Characterization of Bromo-chloro Paraffins and Olefins in the Australian Environment.

A semiquantitative high-resolution mass spectrometry method was developed and applied to assess the occurrence of bromo-/chloro paraffins (BCPs) and olefins (BCOs) in the environment. More than 400 possible BCPs and BCO congener groups were detected in dust, air, and sewage sludge samples collected from Australia. Median chain analytes with the number of halogen atoms <7 (CnHmClxBry, 14 ≤ n ≤ 17, x + y < 7) prevailed in the dust and sludge samples, while short chain analytes (CnHmClxBry, 10 ≤ n ≤ 13, x + y < 7) predominated the air samples. The estimated concentrations of ∑BCPs and ∑BCOs in dust and sludge were approximately 20% that of the chlorinated paraffins (CPs) present, with the median concentrations of 5.4 µg/g (dust) and 0.18 µg/g (sludge) for ∑BCPs and 22 µg/g (in dust) and 0.50 µg/g (sludge) for BCOs. In the air samples, the concentrations of BCPs (0.020 pg/m3) and BCOs (0.032 pg/m3) were 3-4 orders of magnitudes lower than the concentrations of CPs (790 pg/m3). Significant correlations (P < 0.001) were found between the concentration of CPs, BCPs, and BCOs in all the matrices.

In-Sewer Stability Assessment of Anabolic Steroids and Selective Androgen Receptor Modulators.

Wastewater-based epidemiology is a potential complementary technique for monitoring the use of performance- and image-enhancing drugs (PIEDs), such as anabolic steroids and selective androgen receptor modulators (SARMs), within the general population. Assessing in-sewer transformation and degradation is critical for understanding uncertainties associated with wastewater analysis. An electrospray ionization liquid chromatography mass spectrometry method for the quantification of 59 anabolic agents in wastewater influent was developed. Limits of detection and limits of quantification ranged from 0.004 to 1.56 µg/L and 0.01 to 4.75 µg/L, respectively. Method performance was acceptable for linearity (R2 > 0.995, few exceptions), accuracy (68-119%), and precision (1-21%RSD), and applicability was successfully demonstrated. To assess the stability of the selected biomarkers in wastewater, we used laboratory-scale sewer reactors to subject the anabolic agents to simulated realistic sewer environments for 12 h. Anabolic agents, including parent compounds and metabolites, were spiked into freshly collected wastewater that was then fed into three sewer reactor types: control sewer (no biofilm), gravity sewer (aerobic conditions), and rising main sewer (anaerobic conditions). Our results revealed that while most glucuronide conjugates were completely transformed following 12 h in the sewer reactors, 50% of the investigated biomarkers had half-lives longer than 4 h (mean residence time) under gravity sewer conditions. Most anabolic agents were likely subject to biofilm sorption and desorption. These novel results lay the groundwork for any future wastewater-based epidemiology research involving anabolic steroids and SARMs.

Social, demographic, and economic correlates of food and chemical consumption measured by wastewater-based epidemiology.

Wastewater is a potential treasure trove of chemicals that reflects population behavior and health status. Wastewater-based epidemiology has been employed to determine population-scale consumption of chemicals, particularly illicit drugs, across different communities and over time. However, the sociodemographic or socioeconomic correlates of chemical consumption and exposure are unclear. This study explores the relationships between catchment specific sociodemographic parameters and biomarkers in wastewater generated by the respective catchments. Domestic wastewater influent samples taken during the 2016 Australian census week were analyzed for a range of diet, drug, pharmaceutical, and lifestyle biomarkers. We present both linear and rank-order (i.e., Pearson and Spearman) correlations between loads of 42 biomarkers and census-derived metrics, index of relative socioeconomic advantage and disadvantage (IRSAD), median age, and 40 socioeconomic index for area (SEIFA) descriptors. Biomarkers of caffeine, citrus, and dietary fiber consumption had strong positive correlations with IRSAD, while tramadol, atenolol, and pregabalin had strong negative correlation with IRSAD. As expected, atenolol and hydrochlorothiazide correlated positively with median age. We also found specific SEIFA descriptors such as occupation and educational attainment correlating with each biomarker. Our study demonstrates that wastewater-based epidemiology can be used to study sociodemographic influences and disparities in chemical consumption.

Efficient Removal of Perfluorinated Chemicals from Contaminated Water Sources Using Magnetic Fluorinated Polymer Sorbents.

Efficient removal of per- and polyfluoroalkyl substances (PFAS) from contaminated waters is urgently needed to safeguard public and environmental health. In this work, novel magnetic fluorinated polymer sorbents were designed to allow efficient capture of PFAS and fast magnetic recovery of the sorbed material. The new sorbent has superior PFAS removal efficiency compared with the commercially available activated carbon and ion-exchange resins. The removal of the ammonium salt of hexafluoropropylene oxide dimer acid (GenX) reaches >99 % within 30 s, and the estimated sorption capacity was 219 mg g-1 based on the Langmuir model. Robust and efficient regeneration of the magnetic polymer sorbent was confirmed by the repeated sorption and desorption of GenX over four cycles. The sorption of multiple PFAS in two real contaminated water matrices at an environmentally relevant concentration (1 ppb) shows >95 % removal for the majority of PFAS tested in this study.

From Centroided to Profile Mode: Machine Learning for Prediction of Peak Width in HRMS Data.

Centroiding is one of the major approaches used for size reduction of the data generated by high-resolution mass spectrometry. During centroiding, performed either during acquisition or as a pre-processing step, the mass profiles are represented by a single value (i.e., the centroid). While being effective in reducing the data size, centroiding also reduces the level of information density present in the mass peak profile. Moreover, each step of the centroiding process and their consequences on the final results may not be completely clear. Here, we present Cent2Prof, a package containing two algorithms that enables the conversion of the centroided data to mass peak profile data and vice versa. The centroiding algorithm uses the resolution-based mass peak width parameter as the first guess and self-adjusts to fit the data. In addition to the m/z values, the centroiding algorithm also generates the measured mass peak widths at half-height, which can be used during the feature detection and identification. The mass peak profile prediction algorithm employs a random-forest model for the prediction of mass peak widths, which is consequently used for mass profile reconstruction. The centroiding results were compared to the outputs of the MZmine-implemented centroiding algorithm. Our algorithm resulted in rates of false detection ≤5% while the MZmine algorithm resulted in 30% rate of false positive and 3% rate of false negative. The error in profile prediction was ≤56% independent of the mass, ionization mode, and intensity, which was 6 times more accurate than the resolution-based estimated values.

Multisite Calibration of a Microporous Polyethylene Tube Passive Sampler for Quantifying Drugs in Wastewater.

Passive sampling approaches to monitor licit and illicit drugs of concern in wastewater shows promise as a supplementary sampling technique to grab sampling when conventional composite autosampling may not be possible. Recent studies have assessed the applicability of passive sampling at a single wastewater treatment plant (WWTP). However, it remains unknown whether a single-site calibration can be applied to other WWTPs. This study evaluated the in situ calibration of microporous polyethylene tube passive samplers (MPTs) against simultaneously collected composite samples for 22 different WWTPs. Samples were analyzed for methylamphetamine, amphetamine, hydroxycotinine, cotinine, benzoylecgonine, 3,4-methylenedioxymethamphetamine, and noroxycodone. Estimated rates of chemical uptake (sampling rates) were calculated using the mass accumulated in the samplers, the concentration measured in composite samples, and the duration of deployment. The estimated sampling rates were consistent between WWTPs (>90% within a factor of two) and ranged from 5 mL day-1 (amphetamine) to 9 mL day-1 (noroxycodone). The samplers were effective at estimating analyte concentrations, with 77% of results having a normalized difference to 24 h composite samples of below 30%. Our study suggests that MPT passive samplers provide a tool for the spatiotemporal monitoring of drug use where automated integrative sampling techniques may not be feasible.

Systematic Evaluation of the In-Sample Stability of Selected Pharmaceuticals, Illicit Drugs, and Their Metabolites in Wastewater.

The in-sample stability of selected pharmaceuticals, illicit drugs, and their metabolites in wastewater was assessed under six different conditions-untreated, addition of hydrochloric acid or sodium metabisulfite solution, combined with or without sterile filtration, and at four representative temperatures, at 35 °C for up to 28 days, 22 °C for 56 days, and 4 °C and -20 °C for 196 days, or freeze/thaw cycles for 24 weeks. Paracetamol, 6-monoacetylmorphine, morphine, and cocaine were poorly stable in untreated wastewater-e.g., with 50% transformation within 1.2-8.1 days at 22 °C, and acidification reduced their in-sample transformations. Acesulfame, carbamazepine, cotinine, methamphetamine, 3,4-methylenedioxy-methamphetamine (MDMA), ketamine, norfentanyl, 3,4-methylenedioxy-N-ethylamphetamine (MDEA), and norbuprenorphine were highly or moderately stable over the observed period, even in untreated wastewater. Fitting of pseudo-first-order kinetics and the Arrhenius equation was used to develop a multistage transformation estimation model combined with an interactive tool to evaluate possible transformation scenarios of selected biomarkers for the processes from sampling to preanalysis. However, as the wastewater composition can vary between sites and over time, the variability of in-sample stability requires further exploration.

Intraday variability of indicator and pathogenic viruses in 1-h and 24-h composite wastewater samples: Implications for wastewater-based epidemiology.

We monitored the concentration of indicator viruses crAssphage and pepper mild mottle virus (PMMoV) and human pathogen adenovirus (HAdV) in influent from a wastewater treatment plant in Brisbane, Australia in 1-h and 24-h composite samples. Over three days of sampling, the mean concentration of crAssphage gene copies (GC)/mL in 24-h composite samples did not differ significantly (p = 0.72-0.92), while for PMMoV GC/mL (p value range: 0.0002-0.0321) and HAdV GC/mL (p value range: 0.0028-0.0068) significant differences in concentrations were observed on one day of sampling compared to the other two. For all three viruses, the variation observed in 1-h composite samples was greater than the variation observed in 24-h composite samples. For crAssphage, in 54.1% of 1-h composite samples, the concentration was less than that observed in 24-h composite samples; whereas for PMMoV and HAdV the concentration was less in 79.2 and 70.9% of 1-h composite samples, respectively, compared to the relevant 24-h composite samples. Similarly, the concentration of crAssphage in 1-h compared to 24-h composite samples did not differ (p = 0.1082) while the concentrations of PMMoV (p < 0.0001) and HAdV (p < 0.0001) in 1-h composite samples were significantly different from 24-h composite samples. These results suggest that 24-h composite samples offer increased analytical sensitivity and decreased variability compared to 1-h composite samples when monitoring wastewater, especially for pathogenic viruses with low infection rates within a community. Thus, for wastewater-based epidemiology applications, 24-h composite samples are less likely to produce false negative results and erroneous public health information.