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Record W2089845935 · doi:10.1039/c4em00314d

Wastewater micropollutants as tracers of sewage contamination: analysis of combined sewer overflow and stream sediments

2014· article· en· W2089845935 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsPolytechnique MontréalUniversité de MontréalPolymer Source (Canada)Natural Sciences and Engineering Research Council of CanadaHEC Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsWastewaterContaminationEnvironmental scienceSewageCombined sewerWaste managementSewage treatmentEnvironmental engineeringStormwaterEcologyEngineeringSurface runoffBiology

Abstract

fetched live from OpenAlex

A sensitive method was developed to measure the sediment concentration of 10 wastewater micropollutants selected as potential sanitary tracers of sewage contamination and include: nonsteroidal anti-inflammatory drugs (acetaminophen - ACE and diclofenac - DIC), an anti-epileptic drug (carbamazepine - CBZ), a β-blocker (atenolol - ATL), a stimulant (caffeine - CAF), a bronchodilator (theophylline - THEO), steroid hormones (progesterone - PRO and medroxyprogesterone - MedP), an artificial sweetener (aspartame - APM) and personal care products (N,N-diethyl-3-methylbenzamide - DEET). Natural sediments (combined sewer overflow and stream sediments) were extracted by ultrasonic-assisted extraction followed by solid-phase extraction. Analyses were performed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) using atmospheric pressure chemical ionisation in positive mode (APCI+) with a total analysis time of 4.5 min. Method detection limits were in the range of 0.01 to 15 ng g(-1) dry weight (dw) for the compounds of interest, with recoveries ranging from 75% to 156%. Matrix effects were observed for some compounds, never exceeding |±18%|. All results displayed a good degree of reproducibility and repeatability, with relative standard deviations (RSD) of less than 23% for all compounds. The method was applied to an investigation of stream and combined sewer overflow sediment samples that differed in organic carbon contents and particle size distributions. Acetaminophen, caffeine and theophylline (as confounded with paraxanthine) were ubiquitously detected at 0.13-22 ng g(-1) dw in stream bed sediment samples and 98-427 ng g(-1) dw in combined sewer overflow sediment samples. Atenolol (80.5 ng g(-1) dw) and carbamazepine (54 ng g(-1) dw) were quantified only in combined sewer overflow sediment samples. The highest concentrations were recorded for DEET (14 ng g(-1) dw) and progesterone (11.5 ng g(-1) dw) in stream bed and combined sewer overflow sediment samples, respectively. The ratio of concentration to its limit of detection (C : LOD) in sediments for a subset of compounds were compared to their C : LOD in water. In waters with a large capacity for dilution relative to fecal sources, the C : LOD ranges in sediments were greater than in water. Thus monitoring programs for fecal source tracking using wastewater micropollutants should consider sediment sampling, particularly for waters with highly diluted sources of fecal contamination.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.253
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it