MétaCan
Menu
Back to cohort
Record W2030289133 · doi:10.1063/1.4803359

Effect of secondary organic aerosol amount and condensational behavior on global aerosol size distributions

2013· article· en· W2030289133 on OpenAlexafffund
S. D. D'Andrea, S. A. K. Häkkinen, D. M. Westervelt, Chongai Kuang, D. V. Spracklen, Ilona Riipinen, Jeffrey R. Pierce

Bibliographic record

VenueAIP conference proceedings · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAerosolAtmospheric sciencesCloud condensation nucleiEnvironmental scienceBoundary layerCondensationCloud baseVolatility (finance)MeteorologyPhysicsThermodynamicsCloud computing

Abstract

fetched live from OpenAlex

Recent research has shown that secondary organic aerosols (SOA) are major contributors to ultrafine particle growth to climatically relevant sizes, increasing global cloud condensation nuclei (CCN) concentrations within the continental boundary layer. Many models treat SOA solely as semivolatile, which leads to condensation of SOA proportional to the aerosol mass distribution; however, recent closure studies with field measurements show that a significant fraction of SOA condenses proportional to the aerosol surface area, which suggests a very low volatility. Additionally, while many global models contain only biogenic sources of SOA (with emissions generally 10-30 Tg yr−1), recent studies have shown a need for an additional source of SOA around 100 Tg yr−1 correlated with anthropogenic carbon monoxide (CO) emissions is required to match measurements. Here, we explore the significance of these two findings using the GEOS-Chem-TOMAS global aerosol microphysics model. The percent change in the number of particles of size Dp > 40 nm (N40) within the continental boundary layer between the surface-area-and massdistribution condensation schemes, both with the base biogenic SOA only, yielded a global increase of 8% but exceeds 100% in biogenically active regions. The percent change in N40 within the continental boundary layer between the base simulation (19 Tg yr−1) and the additional SOA (100 Tg yr−1) both using the surface area condensation scheme (very low volatility) yielded a global increase of 14%, and a global decrease in the number of particles of size Dp > 10 nm (N10) of 32%. These model simulations were compared to measured data from Hyytiälä, Finland and other global locations and confirmed a decrease in the model-measurement bias. Thus, treating SOA as very low volatile as well as including additional SOA correlated with anthropogenic CO emissions causes a significant global increase in the number of climatically relevant sized particles, and therefore we must continue to refine our SOA treatments in aerosol microphysics models.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
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)0.0010.000

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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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 designSimulation or modeling
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

Citations0
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueAIP conference proceedingsSame topicAtmospheric chemistry and aerosolsFrench-language works237,207