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Record W2580091789 · doi:10.1021/acs.est.6b04700

Role of Aerosol Liquid Water in Secondary Organic Aerosol Formation from Volatile Organic Compounds

2017· article· en· W2580091789 on OpenAlexafffund
Jennifer A. Faust, Jenny P. S. Wong, Alex K. Y. Lee, Jonathan P. D. Abbatt

Bibliographic record

VenueEnvironmental Science & Technology · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsAerosolEnvironmental chemistryChemistryEnvironmental scienceOrganic chemistry

Abstract

fetched live from OpenAlex

A key mechanism for atmospheric secondary organic aerosol (SOA) formation occurs when oxidation products of volatile organic compounds condense onto pre-existing particles. Here, we examine effects of aerosol liquid water (ALW) on relative SOA yield and composition from α-pinene ozonolysis and the photooxidation of toluene and acetylene by OH. Reactions were conducted in a room-temperature flow tube under low-NO x conditions in the presence of equivalent loadings of deliquesced (∼20 μg m –3 ALW) or effloresced (∼0.2 μg m –3 ALW) ammonium sulfate seeds at exactly the same relative humidity (RH = 70%) and state of wall conditioning. We found 13% and 19% enhancements in relative SOA yield for the α-pinene and toluene systems, respectively, when seeds were deliquesced rather than effloresced. The relative yield doubled in the acetylene system, and this enhancement was partially reversible upon drying the prepared SOA, which reduced the yield by 40% within a time scale of seconds. We attribute the high relative yield of acetylene SOA on deliquesced seeds to aqueous partitioning and particle-phase reactions of the photooxidation product glyoxal. The observed range of relative yields for α-pinene, toluene, and acetylene SOA on deliquesced and effloresced seeds suggests that ALW plays a complicated, system-dependent role in SOA formation.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.992

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 studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.004
GPT teacher head0.176
Teacher spread0.172 · 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

Citations157
Published2017
Admission routes2
Has abstractyes

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