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Record W3004260188 · doi:10.2166/wqrj.2020.011

Ozonation of natural organic matter and aquatic humic substances: the effects of ozone on the structural characteristics and subsequent trihalomethane formation potential

2020· article· en· W3004260188 on OpenAlexaff
Mehrnaz Sadrnourmohammadi, Kenneth Brezinski, Beata Gorczyca

Bibliographic record

VenueWater Quality Research Journal · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTrihalomethaneChemistryOzoneDissolved organic carbonHumic acidEnvironmental chemistryOrganic matterFourier transform infrared spectroscopyWater treatmentNatural organic matterChlorineOrganic chemistryEnvironmental engineeringChemical engineering

Abstract

fetched live from OpenAlex

Abstract The effect of ozonation on the structural and chemical characteristics of natural organic matter (NOM) and its isolated humic fractions, humic acid (HA) and fulvic acid, were studied using Fourier transform infrared coupled to attenuated total reflectance (FTIR-ATR), ultraviolet/visible (UV/Vis) spectroscopy, and synchronous scanning fluorescence (SSF) spectroscopy. The results were linked to the effect of ozonation on trihalomethane formation potential (THMfp) reduction for water standards with high THM precursors. Results showed that ozonation at a dose of 1 mg ozone/mg dissolved organic carbon (DOC) was capable of reducing DOC, UV absorbance at 254 nm (UV254), and THMfp by up to 42%, 95%, and 89% for the HA water standard, respectively. The study of UV/Vis, FTIR-ATR, and SSF revealed trends showing that ozone can alter the composition of DOC in the water standards, causing a significant reduction in aromaticity. The reduction of UV254 for each ozonated sample also affirms that ozone mainly targets aromatic moieties contained in NOM. FTIR-ATR results showed that the reduction of unsaturated functional groups, including aromatic rings and C = C bonds in the water standards tested, were the main components impacted by ozone application. SSF results also revealed that ozonation decreases the fluorescence intensity of the maximum peak – as well as the whole spectra.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.041
GPT teacher head0.281
Teacher spread0.240 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations14
Published2020
Admission routes1
Has abstractyes

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