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Diffusion Coefficients and Mixing Times of Organic Molecules in β-Caryophyllene Secondary Organic Aerosol (SOA) and Biomass Burning Organic Aerosol (BBOA)

2021· article· en· W3211622294 on OpenAlexafffund
Erin Evoy, Kristian J. Kiland, Yuanzhou Huang, Elijah G. Schnitzler, Adrian M. Maclean, Saeid Kamal, Jonathan P. D. Abbatt, Allan K. Bertram

Bibliographic record

VenueACS Earth and Space Chemistry · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of TorontoUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAerosolChemistryDiffusionAnalytical Chemistry (journal)Environmental chemistryOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

Information on the diffusion rates of organic molecules within secondary organic aerosol (SOA) and biomass burning organic aerosol (BBOA) is needed to predict the impact of these aerosols on atmospheric chemistry, air quality, and climate. Nevertheless, no studies have measured diffusion rates of organics within SOA generated from β-caryophyllene or within BBOA. Here, we measured diffusion rates of organic molecules in laboratory-generated SOA and BBOA as a function of water activity (aw) using fluorescence recovery after photobleaching. The SOA was generated by the ozonolysis of β-caryophyllene, and the BBOA was generated by the pyrolysis of pine wood. Only the water-soluble component of the BBOA was studied. The measured diffusion coefficients of organic molecules in β-caryophyllene range from 1.1 × 10–16 to 1.3 × 10–14 m2 s–1 for aw values ranging from 0.23 to 0.86. For BBOA, the diffusion coefficients range from 7.3 × 10–17 to 6.6 × 10–16 m2 s–1 for aw values ranging from 0.23 to 0.43. Based on these values, the mixing times of organic molecules within a 200 nm SOA or BBOA are less than 1 min for aw values >0.23. Since aw values are often greater than 0.23 in the planetary boundary layer and temperatures in the planetary boundary are often within 5 K of our experimental temperatures, mixing times are likely often short in that part of the atmosphere for the types of aerosols studied here. For β-caryophyllene SOA, we compared the measured diffusion coefficients with predictions based on the Stokes–Einstein relation and the fractional Stokes–Einstein relation. For both the Stokes–Einstein and the fractional Stokes–Einstein relations, the measured diffusion coefficients agree with the predicted diffusion coefficients. This work illustrates that when the radius of the diffusing molecules is greater than the average radius of the matrix molecules, the Stokes–Einstein equation is able to predict diffusion coefficients in β-caryophyllene SOA with reasonable accuracy.

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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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.086
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.181
Teacher spread0.176 · 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

Citations20
Published2021
Admission routes2
Has abstractyes

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