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Record W2009521630 · doi:10.5194/amt-8-2449-2015

The micro-orifice uniform deposit impactor–droplet freezing technique (MOUDI-DFT) for measuring concentrations of ice nucleating particles as a function of size: improvements and initial validation

2015· article· en· W2009521630 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAtmospheric measurement techniques · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsEnvironment and Climate Change CanadaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of EnvironmentNational Science Foundation
KeywordsAerosolMaterials scienceParticle (ecology)Substrate (aquarium)NanotechnologyMeteorologyGeologyPhysics

Abstract

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Abstract. The micro-orifice uniform deposit impactor–droplet freezing technique (MOUDI-DFT) combines particle collection by inertial impaction (via the MOUDI) and a microscope-based immersion freezing apparatus (the DFT) to measure atmospheric concentrations of ice nucleating particles (INPs) as a function of size and temperature. In the first part of this study we improved upon this recently introduced technique. Using optical microscopy, we investigated the non-uniformity of MOUDI aerosol deposits at spatial resolutions of 1, 0.25 mm, and for some stages when necessary 0.10 mm. The results from these measurements show that at a spatial resolution of 1 mm and less, the concentration of particles along the MOUDI aerosol deposits can vary by an order of magnitude or more. Since the total area of a MOUDI aerosol deposit ranges from 425 to 605 mm2 and the area analyzed by the DFT is approximately 1.2 mm2, this non-uniformity needs to be taken into account when using the MOUDI-DFT to determine atmospheric concentrations of INPs. Measurements of the non-uniformity of the MOUDI aerosol deposits were used to select positions on the deposits that had relatively small variations in particle concentration and to build substrate holders for the different MOUDI stages. These substrate holders improve reproducibility by holding the substrate in the same location for each measurement and ensure that DFT analysis is only performed on substrate regions with relatively small variations in particle concentration. In addition, the deposit non-uniformity was used to determine correction factors that take the non-uniformity into account when determining atmospheric concentrations of INPs. In the second part of this study, the MOUDI-DFT utilizing the new substrate holders was compared to the continuous flow diffusion chamber (CFDC) technique of Colorado State University. The intercomparison was done using INP concentrations found by the two instruments during ambient measurements of continental aerosols. Results from two sampling periods were compared, and the INP concentrations determined by the two techniques agreed within experimental uncertainty. The agreement observed here is commensurate with the level of agreement found in other studies where CFDC results were compared to INP concentrations measured with other methods.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.081
Threshold uncertainty score0.723

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0000.000

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 head0.032
GPT teacher head0.251
Teacher spread0.219 · 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