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Record W2333920832 · doi:10.5194/amtd-6-6147-2013

Application of high resolution Chemical Ionization Mass Spectrometry (CI-ToFMS) to study SOA composition: focus on formation of oxygenated species via aqueous phase processing

2013· preprint· en· W2333920832 on OpenAlexafffund
D. Aljawhary, A. K. Y. Lee, Jonathan P. D. Abbatt

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaOntario Research Foundation
KeywordsChemistryMass spectrometryChemical ionizationAqueous solutionMass spectrumAerosolAnalytical Chemistry (journal)ReagentIonizationTime-of-flight mass spectrometryProtonationIonChemical compositionChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract. This paper demonstrates the capabilities of Chemical Ionization Mass Spectrometry (CIMS) to study secondary organic aerosol (SOA) composition with a high resolution (HR) time-of-flight mass analyzer (aerosol-CI-ToFMS). In particular, by studying aqueous oxidation of Water Soluble Organic Compounds (WSOC) extracted from α-pinene ozonolysis SOA, we assess the capabilities of three common CIMS reagent ions: (a) protonated water clusters (H2O)nH+, (b) acetate CH3C(O)O− and (c) iodide water clusters I(H2O)n− to monitor SOA composition. As well, we report the relative sensitivity of these reagent ions to a wide range of common organic aerosol constituents. We find that (H2O)nH+ is more selective to the detection of less oxidized species, so that the range of O/C and OSC (carbon oxidation state) in the SOA spectra is considerably lower than those measured using CH3C(O)O− and I(H2O)n−. Specifically, (H2O)nH+ ionizes organic compounds with OSC ≤ 1.3, whereas CH3C(O)O− and I(H2O)n− both ionize highly oxygenated organics with OSC up to 4 with I(H2O)n− being more selective towards multi-functional organic compounds. In the bulk O/C and H/C space, i.e. in a Van Krevelen plot, there is a remarkable agreement in both absolute magnitude and oxidation trajectory between CI-ToFMS data and those from a high resolution aerosol mass spectrometer (HR-AMS). This indicates that the CI-ToFMS data captures much of the chemical change occurring in the particle and that gas phase species, which are not detected by the HR-AMS, do not dominate the overall ion signal. Finally, the data illustrate the capability of aerosol-CI-ToFMS to monitor specific chemical change, including the fragmentation and functionalization reactions that occur during organic oxidation, and the oxidative conversion of dimeric SOA species into monomers. Overall, aerosol-CI-ToFMS is a valuable, selective complement to some common SOA characterization methods, such as AMS and spectroscopic techniques. Both laboratory and ambient SOA samples can be analyzed using the techniques illustrated in the paper.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.013
GPT teacher head0.233
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2013
Admission routes2
Has abstractyes

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