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Record W2885032588 · doi:10.1098/rsos.180025

Factors affecting <i>N</i> -nitrosodimethylamine formation from poly(diallyldimethyl-ammonium chloride) degradation during chloramination

2018· article· en· W2885032588 on OpenAlexaboutno aff
Siying Tan, Shaojie Jiang, Xiaoyu Li, Qiuhong Yuan

Bibliographic record

VenueRoyal Society Open Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsnot available
Fundersnot available
KeywordsChloraminationChemistryN-NitrosodimethylamineChloramineBromideEnvironmental chemistryChlorideNatural organic matterDegradation (telecommunications)AmmoniaInorganic chemistryNuclear chemistryCarcinogenChlorineAdsorptionOrganic chemistry

Abstract

fetched live from OpenAlex

Poly(diallyldimethylammonium chloride) (polyDADMAC) has been shown to be an important precursor of the probable human carcinogen N -nitrosodimethylamine (NDMA) when in contact with chloramine. In this study, we conducted an orthogonal experiment design to evaluate the effects of pH values, ammonia, bromide, natural organic matter (NOM) and monochloramine dosages on the formation of NDMA from polyDADMAC during chloramination. Meanwhile, single-factor experiments of pH, bromide and NOM prove the results of orthogonal experiment. The results supported that pH was the most critical factor affecting NDMA formation from polyDADMAC during chloramination, and the highest NDMA formation from polyDADMAC occurred at pH near 7 due to released DMA from polyDADMAC degradation and the critical importance of low concentrations of dichloramine in water. In the presence of excess bromide, the NDMA formation was enhanced significantly at all different pH values owing to bromochloramine, which has higher electronegativity of the brominated nitrogen atom than monochloramine or dichloramine. The NDMA formation from polyDADMAC in the presence of NOM was 41.7% lower than NDMA formation in the absence of NOM. The overwhelming majority of NDMA formation from polyDADMAC under simulated conditions was lower than the current advisory levels (i.e. 9 ng l −1 in Ontario, 10 ng l −1 in California).

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.

How this classification was reachedexpand

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
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 score0.081
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 studies0.0020.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.260
Teacher spread0.242 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2018
Admission routes1
Has abstractyes

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