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Record W1925941191 · doi:10.1039/c5em00338e

The degradation behaviour of nine diverse contaminants in urban surface water and wastewater prior to water treatment

2015· article· en· W1925941191 on OpenAlex
Guillaume Cormier, Benoît Barbeau, Hans Peter H. Arp, Sébastien Sauvé

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 · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsPolytechnique MontréalNatural Sciences and Engineering Research Council of CanadaUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaNorges ForskningsrådUniversité Laval
KeywordsWastewaterEnvironmental chemistryEnvironmental scienceSurface waterAtrazineContaminationSewage treatmentDegradation (telecommunications)PollutantWater qualityWater treatmentChemistryEnvironmental engineeringPesticideBiologyEcology

Abstract

fetched live from OpenAlex

An increasing diversity of emerging contaminants are entering urban surface water and wastewater, posing unknown risks for the environment. One of the main contemporary challenges in ensuring water quality is to design efficient strategies for minimizing such risks. As a first step in such strategies, it is important to establish the fate and degradation behavior of contaminants prior to any engineered secondary water treatment. Such information is relevant for assessing treatment solutions by simple storage, or to assess the impacts of contaminant spreading in the absence of water treatment, such as during times of flooding or in areas of poor infrastructure. Therefore in this study we examined the degradation behavior of a broad array of water contaminants in actual urban surface water and wastewater, in the presence and absence of naturally occurring bacteria and at two temperatures. The chemicals included caffeine, sulfamethoxazole, carbamazepine, atrazine, 17β-estradiol, ethinylestradiol, diclofenac, desethylatrazine and norethindrone. Little information on the degradation behavior of these pollutants in actual influent wastewater exist, nor in general in water for desethylatrazine (a transformation product of atrazine) and the synthetic hormone norethindrone. Investigations were done in aerobic conditions, in the absence of sunlight. The results suggest that all chemicals except estradiol are stable in urban surface water, and in waste water neither abiotic nor biological degradation in the absence of sunlight contribute significantly to the disappearance of desethylatrazine, atrazine, carbamazepine and diclofenac. Biological degradation in wastewater was effective at transforming norethindrone, 17β-estradiol, ethinylestradiol, caffeine and sulfamethoxazole, with measured degradation rate constants k and half-lives ranging respectively from 0.0082-0.52 d(-1) and 1.3-85 days. The obtained degradation data generally followed a pseudo-first-order-kinetic model. This information can be used to model degradation prior to water treatment.

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 categoriesnone
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 score0.144
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

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

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 head0.026
GPT teacher head0.274
Teacher spread0.249 · 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