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Record W2622277870 · doi:10.5194/acp-17-13747-2017

Particulate trimethylamine in the summertime Canadian high Arctic lower troposphere

2017· article· en· W2622277870 on OpenAlexafffundabout
Franziska Köllner, Johannes Schneider, Megan D. Willis, Thomas Klimach, Frank Helleis, Heiko Bozem, Daniel Kunkel, Peter Hoor, Julia Burkart, W. R. Leaitch, Amir A. Aliabadi, Jonathan P. D. Abbatt, Andreas Herber, Stephan Borrmann

Bibliographic record

VenueAtmospheric chemistry and physics · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of GuelphEnvironment and Climate Change CanadaUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNatural Resources CanadaMax-Planck-GesellschaftMax-Planck-Institut für ChemieEnvironment and Climate Change CanadaUniversity of Toronto
KeywordsParticulatesLevoglucosanAerosolArcticParticle (ecology)TroposphereAtmospheric sciencesMethanesulfonic acidTrimethylamineEnvironmental scienceEnvironmental chemistryChemistryBiomass burningOceanographyGeology

Abstract

fetched live from OpenAlex

Abstract. Size-resolved and vertical profile measurements of single particle chemical composition (sampling altitude range 50–3000 m) were conducted in July 2014 in the Canadian high Arctic during an aircraft-based measurement campaign (NETCARE 2014). We deployed the single particle laser ablation aerosol mass spectrometer ALABAMA (vacuum aerodynamic diameter range approximately 200–1000 nm) to identify different particle types and their mixing states. On the basis of the single particle analysis, we found that a significant fraction (23 %) of all analyzed particles (in total: 7412) contained trimethylamine (TMA). Two main pieces of evidence suggest that these TMA-containing particles originated from emissions within the Arctic boundary layer. First, the maximum fraction of particulate TMA occurred in the Arctic boundary layer. Second, compared to particles observed aloft, TMA particles were smaller and less oxidized. Further, air mass history analysis, associated wind data and comparison with measurements of methanesulfonic acid give evidence of a marine-biogenic influence on particulate TMA. Moreover, the external mixture of TMA-containing particles and sodium and chloride (Na ∕ Cl-) containing particles, together with low wind speeds, suggests particulate TMA results from secondary conversion of precursor gases released by the ocean. In contrast to TMA-containing particles originating from inner-Arctic sources, particles with biomass burning markers (such as levoglucosan and potassium) showed a higher fraction at higher altitudes, indicating long-range transport as their source. Our measurements highlight the importance of natural, marine inner-Arctic sources for composition and growth of summertime Arctic aerosol.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.995

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.009
GPT teacher head0.205
Teacher spread0.196 · 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

Citations114
Published2017
Admission routes3
Has abstractyes

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