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Record W1995763682 · doi:10.1029/2009jd011857

Trapping of trace gases by growing ice surfaces including surface‐saturated adsorption

2009· article· en· W1995763682 on OpenAlexaff
B. Kärcher, Jonathan P. D. Abbatt, R. A. Cox, Peter Popp, Christiane Voigt

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNitric acidAdsorptionCirrusIce cloudDiffusionTrace gasSupersaturationIce crystalsChemical physicsChemistryThermodynamicsAnalytical Chemistry (journal)Atmospheric sciencesEnvironmental chemistryInorganic chemistryMeteorologyPhysical chemistryGeologyRadiative transferPhysicsOrganic chemistryOptics

Abstract

fetched live from OpenAlex

Key steps leading to the uptake of trace gases into atmospheric cloud ice particles include gas phase diffusion of trace gas molecules toward growing ice crystals and the kinetics of molecular interactions at the ice surfaces. In the case of nitric acid, laboratory studies and airborne field observations indicate uptake in growing ice films and cirrus ice particles above the thermodynamic solubility limit. This implies that uptake of nitric acid molecules on growing ice surfaces (trapping) controls the nitric acid content in ice particles residing in supersaturated air. A previous trapping model is updated to include effects of surface‐saturated adsorption. Exact analytical solutions to the problem are derived to enable the calculation of the amount of vapor trapped for a given ice growth rate, assuming Langmuir‐type adsorption isotherms. Those solutions are provided in terms of trapping efficiencies and equivalent uptake coefficients, net vapor fluxes toward ice crystals or ice films, steady state molar ratios of trapped molecules in the ice phase, and gas‐ice partitioning factors. The trapping model includes the underlying adsorption equilibrium model asymptotically for nongrowing ice particles. Comparisons to laboratory and field measurements of nitric acid uptake are carried out. Observed dependences of uptake as a function of nitric acid partial pressure, ice growth rate, and temperature are reproduced fairly well. Nitric acid molar ratios in cirrus ice are neither controlled purely by adsorption nor purely by gas phase diffusion, underscoring the importance of using the trapping concept to interpret these observations. These results also suggest further mechanisms that enhance the nitric acid content in cirrus ice at the tropical tropopause at very low temperatures. A discussion of potential model improvements outlines the physical conditions in which the updated model describes trapping well and leads to further insight into the physical nature of the trapping process.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.044
GPT teacher head0.308
Teacher spread0.264 · 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 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

Citations35
Published2009
Admission routes1
Has abstractyes

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