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Record W2048817008 · doi:10.1029/2004jd005113

Reactive uptake of glyoxal by particulate matter

2005· article· en· W2048817008 on OpenAlexaff
John Liggio, Shao‐Meng Li, R. McLaren

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsYork University
Fundersnot available
KeywordsGlyoxalParticulatesRelative humidityAerosolAtmosphere (unit)ChemistryParticle (ecology)RadicalEnvironmental chemistryPhotochemistryMeteorologyOrganic chemistry

Abstract

fetched live from OpenAlex

The uptake of gaseous glyoxal onto particulate matter has been studied in laboratory experiments under conditions relevant to the ambient atmosphere using an aerosol mass spectrometer. The growth rates and reactive uptake coefficients, γ, were derived by fitting a model of particle growth to the experimental data. Organic growth rates varied from 1.05 × 10 −11 to 23.1 × 10 −11 μg particle −1 min −1 in the presence of ∼5 ppb glyoxal. Uptake coefficients (γ) of glyoxal varied from 8.0 × 10 −4 to 7.3 × 10 −3 with a median γ = 2.9 × 10 −3 , observed for (NH 4 ) 2 SO 4 seed aerosols at 55% relative humidity. Increased γ values were related to increased particle acidity, indicating that acid catalysis played a role in the heterogeneous mechanism. Experiments conducted at very low relative humidity, with the potential to be highly acidic, resulted in very low reactive uptake. These uptake coefficients indicated that the heterogeneous loss of glyoxal in the atmosphere is at least as important as gas phase loss mechanisms, including photolysis and reaction with hydroxyl radicals. Glyoxal lifetime due to heterogeneous reactions under typical ambient conditions was estimated to be τ het = 5–287 min. In rural and remote areas the glyoxal uptake can lead to 5–257 ng m −3 of secondary organic aerosols in 8 hours, consistent with recent ambient measurements.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.993

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.024
GPT teacher head0.290
Teacher spread0.266 · 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 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

Citations415
Published2005
Admission routes1
Has abstractyes

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