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Record W4316810641 · doi:10.5194/amt-16-181-2023

Development and validation of a new in situ technique to measure total gaseous chlorine in air

2023· article· en· W4316810641 on OpenAlexafffund
Teles C. Furlani, RenXi Ye, Jordan Stewart, Leigh R. Crilley, P. M. Edwards, Tara F. Kahan, Cora J. Young

Bibliographic record

VenueAtmospheric measurement techniques · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of SaskatchewanYork University
FundersNatural Environment Research CouncilNatural Sciences and Engineering Research Council of CanadaAlfred P. Sloan FoundationHorizon 2020 Framework ProgrammeH2020 European Research CouncilCanada Research ChairsSight Research UK
KeywordsChemistryChlorineMixing ratioAlkylSpectrometerDecompositionIn situAnalytical Chemistry (journal)DichloromethaneEnvironmental chemistryPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract. Total gaseous chlorine (TClg) measurements can improve our understanding of unknown sources of Cl in the atmosphere. Existing techniques for measuring TClg have been limited to offline analysis of extracted filters and do not provide suitable temporal information on fast atmospheric processes. We describe high-time-resolution in situ measurements of TClg by thermolyzing air over a heated platinum (Pt) substrate coupled to a cavity ring-down spectrometer (CRDS). The method relies on the complete decomposition of TClg to release Cl atoms that react to form HCl, for which detection by CRDS has previously been shown to be fast and reliable. The method was validated using custom organochlorine permeation devices (PDs) that generated gas-phase dichloromethane (DCM), 1-chlorobutane (CB), and 1,3-dichloropropene (DCP). The optimal conversion temperature and residence time through the high-temperature furnace was 825 ∘C and 1.5 s, respectively. Complete conversion was observed for six organochlorine compounds, including alkyl, allyl, and aryl C–Cl bonds, which are amongst the strongest Cl-containing bonds. The quantitative conversion of these strong C–Cl bonds suggests complete conversion of similar or weaker bonds that characterize all other TClg. We applied this technique to both outdoor and indoor environments and found reasonable agreements in ambient background mixing ratios with the sum of expected HCl from known long-lived Cl species. We measured the converted TClg in an indoor environment during cleaning activities and observed varying levels of TClg comparable to previous studies. The method validated here is capable of measuring in situ TClg and has a broad range of potential applications.

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 categoriesnone
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 score0.488
Threshold uncertainty score0.820

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 studies0.0000.000
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 head0.034
GPT teacher head0.231
Teacher spread0.197 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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