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Record W2317006727 · doi:10.1021/es201955u

Observation of ClNO<sub>2</sub> in a Mid-Continental Urban Environment

2011· article· en· W2317006727 on OpenAlexaffabout
L. H. Mielke, Amanda Furgeson, Hans D. Osthoff

Bibliographic record

VenueEnvironmental Science & Technology · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAerosolChemistryMixing ratioChlorideHYSPLITChlorineTroposphereAtmospheric chemistryEnvironmental chemistryOzoneAtmospheric sciencesOrganic chemistryGeology

Abstract

fetched live from OpenAlex

In the troposphere, nitryl chloride (ClNO₂), produced from uptake of dinitrogen pentoxide (N₂O₅) on chloride containing aerosol, can be an important nocturnal reservoir of NO(x) (= NO + NO₂) and a source of atomic Cl, particularly in polluted coastal environments. Here, we present measurements of ClNO₂ mixing ratios by chemical ionization mass spectrometry (CIMS) in Calgary, Alberta, Canada over a 3-day period. The observed ClNO₂ mixing ratios exhibited a strong diurnal profile, with nocturnal maxima in the range of 80 to 250 parts-per-trillion by volume (pptv) and minima below the detection limit of 5 pptv in the early afternoon. At night, ClNO₂ constituted up to 2% of odd nitrogen, or NO(y). The peak mixing ratios of ClNO₂ observed were considerably below the modeled integrated heterogeneous losses of N₂O₅, indicating that ClNO₂ production was a minor pathway compared to heterogeneous hydrolysis of N₂O₅. Back trajectory analysis using HYSPLIT showed that the study region was not influenced by fresh injections of marine aerosol, implying that aerosol chloride was derived from anthropogenic sources. Molecular chlorine (Cl₂), derived from local anthropogenic sources, was observed at mixing ratios of up to 65 pptv and possibly contributed to formation of aerosol chloride and hence the formation of ClNO₂.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.167
Teacher spread0.157 · 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

Citations222
Published2011
Admission routes2
Has abstractyes

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