MétaCan
Menu
Back to cohort

Nitration of Phenols by Reaction with Aqueous Nitrite: A Pathway for the Formation of Atmospheric Brown Carbon

2023· article· en· W4321791771 on OpenAlexafffund
Yutong Wang, Spiro Jorga, Jonathan P. D. Abbatt

Bibliographic record

VenueACS Earth and Space Chemistry · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNitrationChemistryNitriteAqueous solutionCatecholPhenolsPhenolMass spectrometryInorganic chemistryNitrophenolPhotochemistryOrganic chemistryChromatographyNitrateCatalysis

Abstract

fetched live from OpenAlex

Nitrophenols are a major component of light-absorbing atmospheric organic aerosols, commonly referred to as brown carbon (BrC). Most nitrophenol formation pathways involve reactions of phenolic compounds with OH, NO 3, and NO 2 in the gas phase. In this study, an aqueous nitrophenol production pathway is investigated that can proceed in the dark without apparent OH radical formation. Using high-performance liquid chromatography–mass spectrometry, we demonstrate that catechol reacts in acidic solutions with dissolved nitrite to form nitrocatechol. The rate of nitration increases significantly from pH 4.4 to pH 3.4 such that nitrocatechol is susceptible to second-generation reactions under the most acidic conditions producing chromophores that absorb in the visible region (peak at 425 nm). Increases in the N:C ratio of the reaction solution, as detected by aerosol mass spectrometry, and enhanced absorption from 300 to 500 nm of wood and peat smoke aqueous extracts exposed to nitrite suggest that this is a general nitration pathway. The atmospheric conditions under which this BrC formation process may occur are discussed.

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)0.000
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 score0.016
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.181
Teacher spread0.173 · 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 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

Citations17
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueACS Earth and Space ChemistrySame topicAtmospheric chemistry and aerosolsFrench-language works237,207