Suspect and Nontarget Screening Reveal the Underestimated Risks of Antibiotic Transformation Products in Wastewater Treatment Plant Effluents

Environmental Science & Technology, Journal Year: 2023, Volume and Issue: 57(45), P. 17439 - 17451

Published: Nov. 6, 2023

Antibiotics are anthropogenic contaminants with a global presence and of deep concern in aquatic environments, while less is known about the occurrence risks their transformation products (TPs). Herein, we developed comprehensive suspect nontarget screening workflow based on high-resolution mass spectrometry to identify unknown antibiotic TPs wastewater treatment plant effluents. We identified 211 compounds (35 parent antibiotics 176 TPs) at confidence levels ≥3 107 originated from macrolides. were quantified by 17 standards semiquantified predicted response factors accounted for 55.6-95.1% (76.7% average) total concentrations parents TPs. 22.2%, 63.1%, 18.8% estimated be more persistent, mobile, toxic than antibiotics, respectively. Further ecological risk assessment toxicity organisms revealed that cumulative generally higher those parents. Despite newly formed N-oxide TPs, tertiary process (mainly ozonation) could decrease averaged 20.3% 36.2% antibiotic-related compounds. This study highlights necessity include environmental scrutiny different environments.

Language: Английский

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A review of the state-of-the-art wastewater quality characterization and measurement technologies. Is the shift to real-time monitoring nowadays feasible?

Journal of Water Process Engineering, Journal Year: 2024, Volume and Issue: 60, P. 105061 - 105061

Published: March 12, 2024

Efficient characterization of wastewater stream quality is vital to ensure the safe discharge or reuse treated (WW). There are numerous parameters employed characterize water quality, some required by directives (e.g. biological oxygen demand (BOD), total nitrogen (TN), phosphates (TP)), while others used for process controls flow, temperature, pH). Well-accepted methods assess these have traditionally been laboratory-based, taking place either off-line at-line, and presenting a significant delay between sampling result. Alternative can run in-line on-line, generally being more cost-effective. Unfortunately, often not accepted when providing information regulatory bodies. The current review aims describe available laboratory-based approaches compare them with innovative real-time (RT) solutions. Transitioning from RT measurements means obtaining valuable data, avoiding time delays, possibility optimize (WW) treatment management. A variety sensor categories examined illustrate general framework in which applications replace longer conventional processes, an eye toward potential drawbacks. enhancement be achieved through employment advanced soft-sensing techniques Internet Things (IoT), coupled machine learning (ML) artificial intelligence (AI).

Language: Английский

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Revealing specific transformation pattern of sulfonamides during wastewater biological treatment processes by molecular networking nontarget screening

Water Research, Journal Year: 2023, Volume and Issue: 235, P. 119895 - 119895

Published: March 20, 2023

Language: Английский

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Exploring the Complexities of Dissolved Organic Matter Photochemistry from the Molecular Level by Using Machine Learning Approaches

Environmental Science & Technology, Journal Year: 2023, Volume and Issue: 57(46), P. 17889 - 17899

Published: May 29, 2023

Dissolved organic matter (DOM) sustains a substantial part of the transported seaward, where photochemical reactions significantly affect its transformation and fate. The irradiation experiments can provide valuable information on reactivity (photolabile, photoresistant, photoproduct) molecules. However, inconsistency fate irradiated molecules among different curtailed our understanding roles have played, which cannot be properly addressed by traditional approaches. Here, we conducted for samples from two large estuaries in China. Molecules that occurred were characterized Fourier transform ion cyclotron resonance mass spectrometry assigned probabilistic labels to define their reactivity. These with used construct learning database establishing suitable machine (ML) model. We further applied well-trained ML model "un-matched" (i.e., not detected experiments) five worldwide, predict Results showed numerous strong photolability captured solely Moreover, comparing DOM revealed riverine chemistry largely determines subsequent transformation. offer an expandable renewable approach based compatibly integrate existing shed insight into degradation processes.

Language: Английский

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How Wastewater Reflects Human Metabolism─Suspect Screening of Pharmaceutical Metabolites in Wastewater Influent

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: 58(22), P. 9828 - 9839

Published: May 24, 2024

Pharmaceuticals and their human metabolites are contaminants of emerging concern in the aquatic environment. Most monitoring studies focus on a limited set parent compounds even fewer metabolites. However, more than 50% most consumed pharmaceuticals excreted higher amounts as parents, confirmed by literature analysis within this study. Hence, we applied wide-scope suspect screening approach to identify pharmaceutical wastewater influent from three Swiss treatment plants. Based consumption metabolism data, list comprising 268 over 1500 was compiled. Online solid phase extraction combined with liquid chromatography coupled high-resolution tandem mass spectrometry used analyze samples. Data processing, annotation, structure elucidation were achieved various tools, including molecular networking well SIRIUS/CSI:FingerID MetFrag for MS2 spectra rationalization. We 37 reference standards 16 liver S9 incubation experiments. More 25 detected first time wastewater. Semiquantification MS2Quant showed that metabolite concentration ratios generally lower compared expectations, probably due further transformation sewer system or limitations detection. Nonetheless, pose large fraction total contribution wastewater, highlighting need inclusion chemical risk assessment.

Language: Английский

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Machine learning–enhanced molecular network reveals global exposure to hundreds of unknown PFAS

Science Advances, Journal Year: 2024, Volume and Issue: 10(21)

Published: May 23, 2024

Unknown forever chemicals like per- and polyfluoroalkyl substances (PFASs) are difficult to identify. Current platforms designed for metabolites natural products cannot capture the diverse structural characteristics of PFAS. Here, we report an automatic PFAS identification platform (APP-ID) that screens in environmental samples using enhanced molecular network identifies unknown structures machine learning. Our networking algorithm, which enhances characteristic fragment matches, has lower false-positive rate (0.7%) than current algorithms (2.4 46%). support vector model identified test set with 58.3% accuracy, surpassing software. Further, APP-ID detected 733 PFASs real fluorochemical wastewater, 39 previously unreported media. Retrospective screening 126 against public data repository from 20 countries show substitutes prevalent worldwide.

Language: Английский

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Two-layer homolog network approach for PFAS nontarget screening and retrospective data mining

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Jan. 15, 2025

Abstract The rapid increase of novel per- and polyfluoroalkyl substances (PFAS) raises concerns, while their identification remains challenging. Here, we develop a two-layer homolog network approach for PFAS nontarget screening using mass spectrometry. first layer constructs networks between homologs, with evaluation showing that it filters 94% false candidates. second builds classes to expedite the PFAS. We detected 94 in twelve waterproof products two related industrial sludges, including 36 not previously reported any sample. A local dataset is constructed retrospective analysis by re-analyzing our previous samples, revealing fifteen samples collected 2005. retrieval public database MassIVE uncovers from seven countries. reveal historic global presence PFAS, providing guidance management policy-making concerning persistent chemicals.

Language: Английский

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Incorporating Transformation Products for an Integrated Assessment of Antibiotic Pollution and Risks in Surface Water

Environmental Science & Technology, Journal Year: 2025, Volume and Issue: 59(5), P. 2815 - 2826

Published: Jan. 30, 2025

The widespread presence of antibiotics in aquatic ecosystems is a global challenge, yet the occurrence and risks associated with their transformation products (TPs) remain poorly understood. This study investigated potential TPs water along Chaobai River Beijing. We used high-resolution mass spectrometry an integrated target, suspect, nontarget screening approach to identify 21 parent 78 among 90 samples, majority from macrolides sulfonamides. Notably, target quantification machine-learning-assisted semiquantification revealed that cumulative concentrations were higher than compounds, average contributions ranging between 50.7 63.7%. Most downstream samples largely influenced by domestic sewage, as indicated significantly proportions TPs, well greater diversity composition profiles compared upstream reservoir samples. Moreover, 26.9, 67.9, 6.4% exhibited persistence, mobility, or toxicity antibiotics, respectively. Sixteen macrolide presented both ecological organisms resistance selection antibiotics. contributed substantially overall antibiotic-related 31.2 54.1%. highlights antibiotic river water, underscoring need consider comprehensive risk assessments

Language: Английский

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Transformation mechanisms of antidepressants in biological wastewater treatment: Removal kinetic, transformation products and pathways

Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 493, P. 152557 - 152557

Published: May 25, 2024

Language: Английский

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Biotransformation pathways of pharmaceuticals and personal care products (PPCPs) during acidogenesis and methanogenesis of anaerobic digestion

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 478, P. 135444 - 135444

Published: Aug. 6, 2024

Pharmaceuticals and personal care products (PPCPs) exhibit varying biodegradability during the acidogenic methanogenic phases of anaerobic digestion. However, there is limited information regarding end generated these processes. This work investigates biotransformation (BTPs) in a two-phase (TP) acidogenic-methanogenic (Ac-Mt) bioreactor using advanced suspect nontarget strategies. Fourteen BTPs were confidently identified from ten parent PPCPs including carbamazepine (CBZ), naproxen (NPX), diclofenac (DCF), ibuprofen (IBU), acetaminophen (ACT), metoprolol (MTP), sulfamethoxazole (SMX), ciprofloxacin (CIP), methylparaben (MPB) propylparaben (PPB). These linked with oxidation reactions such as hydroxylation, demethylation epoxidation. Their generation was related to organic acid production, since all metabolites detected acidogenesis, some being subsequently consumed methanogenesis, e.g., aminothiophenol kynurenic acid. Another group showed increased concentrations under conditions, hydroxy-diclofenac epoxy-carbamazepine. The most high removal efficiencies (> 90 %) – SMX, CIP, NPX, MTP, ACT, MPB, PPB, while DCF, CBZ IBU demonstrated higher persistence - DCF (42 %); (40 %), (47 %). phase separation digestion provided deeper understanding pathways PPCPs, addition enhancing persistent compounds, i.e., IBU.

Language: Английский

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