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Record W2135705633 · doi:10.5194/acp-11-11335-2011

Cloud condensation nuclei closure study on summer arctic aerosol

2011· article· en· W2135705633 on OpenAlexafffund
M. Martin, Rachel Chang, B. Sierau, S. Sjögren, Erik Swietlicki, Jonathan P. D. Abbatt, Caroline Leck, Ulrike Lohmann

Bibliographic record

VenueAtmospheric chemistry and physics · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Toronto
FundersKnut och Alice Wallenbergs StiftelseDeutsche ForschungsgemeinschaftNatural Sciences and Engineering Research Council of CanadaEuropean CommissionCanadian Foundation for Climate and Atmospheric SciencesPolarforskningssekretariatet
KeywordsAerosolCloud condensation nucleiDifferential mobility analyzerCondensation particle counterAtmospheric sciencesChemistryParticle numberParticle (ecology)Scanning mobility particle sizerEnvironmental scienceParticle sizeParticle-size distributionPhysicsOceanographyNuclear physicsPlasmaGeology

Abstract

fetched live from OpenAlex

Abstract. We present an aerosol – cloud condensation nuclei (CCN) closure study on summer high Arctic aerosol based on measurements that were carried out in 2008 during the Arctic Summer Cloud Ocean Study (ASCOS) on board the Swedish ice breaker Oden. The data presented here were collected during a three-week time period in the pack ice (>85° N) when the icebreaker Oden was moored to an ice floe and drifted passively during the most biological active period into autumn freeze up conditions. CCN number concentrations were obtained using two CCN counters measuring at different supersaturations. The directly measured CCN number concentration was then compared with a CCN number concentration calculated using both bulk aerosol mass composition data from an aerosol mass spectrometer (AMS) and aerosol number size distributions obtained from a differential mobility particle sizer, assuming κ-Köhler theory, surface tension of water and an internally mixed aerosol. The last assumption was supported by measurements made with a hygroscopic tandem differential mobility analyzer (HTDMA) for particles >70 nm. For the two highest measured supersaturations, 0.73 and 0.41%, closure could not be achieved with the investigated settings concerning hygroscopicity and density. The calculated CCN number concentration was always higher than the measured one for those two supersaturations. This might be caused by a relative larger insoluble organic mass fraction of the smaller particles that activate at these supersaturations, which are thus less good CCN than the larger particles. On average, 36% of the mass measured with the AMS was organic mass. At 0.20, 0.15 and 0.10% supersaturation, closure could be achieved with different combinations of hygroscopic parameters and densities within the uncertainty range of the fit. The best agreement of the calculated CCN number concentration with the observed one was achieved when the organic fraction of the aerosol was treated as nearly water insoluble (κorg=0.02), leading to a mean total κ, κtot, of 0.33 ± 0.13. However, several settings led to closure and κorg=0.2 is found to be an upper limit at 0.1% supersaturation. κorg≤0.2 leads to a κtot range of 0.33 ± 013 to 0.50 ± 0.11. Thus, the organic material ranges from being sparingly soluble to effectively insoluble. These results suggest that an increase in organic mass fraction in particles of a certain size would lead to a suppression of the Arctic CCN activity.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
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)0.0070.000

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 head0.025
GPT teacher head0.217
Teacher spread0.192 · 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 designObservational
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

Citations110
Published2011
Admission routes2
Has abstractyes

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