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Record W2749985726 · doi:10.5194/acp-17-15167-2017

Biogenic, urban, and wildfire influences on the molecular composition of dissolved organic compounds in cloud water

2017· article· en· W2749985726 on OpenAlexaboutno aff
Ryan D. Cook, Ying‐Hsuan Lin, Zhuoyu Peng, Eric Boone, Rosalie Chu, James E. Dukett, Matthew J. Gunsch, Wuliang Zhang, Nikola Tolić, Alexander Laskin, Kerri A. Pratt

Bibliographic record

VenueAtmospheric chemistry and physics · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
FundersNew York State Energy Research and Development Authority
KeywordsChemistryEnvironmental chemistryDissolved organic carbonAqueous solutionTotal organic carbonCarbon fibersOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract. Organic aerosol formation and transformation occurs within aqueous aerosol and cloud droplets, yet little is known about the composition of high molecular weight organic compounds in cloud water. Cloud water samples collected at Whiteface Mountain, New York, during August–September 2014 were analyzed by ultra-high-resolution mass spectrometry to investigate the molecular composition of dissolved organic carbon, with a focus on sulfur- and nitrogen-containing compounds. Organic molecular composition was evaluated in the context of cloud water inorganic ion concentrations, pH, and total organic carbon concentrations to gain insights into the sources and aqueous-phase processes of the observed high molecular weight organic compounds. Cloud water acidity was positively correlated with the average oxygen : carbon ratio of the organic constituents, suggesting the possibility for aqueous acid-catalyzed (prior to cloud droplet activation or during/after cloud droplet evaporation) and/or radical (within cloud droplets) oxidation processes. Many tracer compounds recently identified in laboratory studies of bulk aqueous-phase reactions were identified in the cloud water. Organosulfate compounds, with both biogenic and anthropogenic volatile organic compound precursors, were detected for cloud water samples influenced by air masses that had traveled over forested and populated areas. Oxidation products of long-chain (C10−12) alkane precursors were detected during urban influence. Influence of Canadian wildfires resulted in increased numbers of identified sulfur-containing compounds and oligomeric species, including those formed through aqueous-phase reactions involving methylglyoxal. Light-absorbing aqueous-phase products of syringol and guaiacol oxidation were observed in the wildfire-influenced samples, and dinitroaromatic compounds were observed in all cloud water samples (wildfire, biogenic, and urban-influenced). Overall, the cloud water molecular composition depended on air mass source influence and reflected aqueous-phase reactions involving biogenic, urban, and biomass burning precursors.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.195
Teacher spread0.188 · 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 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

Citations101
Published2017
Admission routes1
Has abstractyes

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