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Record W3138086797 · doi:10.5194/amt-14-4517-2021

Sizing response of the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) and Laser Aerosol Spectrometer (LAS) to changes in submicron aerosol composition and refractive index

2021· article· en· W3138086797 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.

Bibliographic record

VenueAtmospheric measurement techniques · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Alberta
FundersNuclear Safety and Security CommissionH2020 European Research CouncilNational Aeronautics and Space Administration
KeywordsAerosolSpectrometerParticle sizeAnalytical Chemistry (journal)Refractive indexLaserChemistryParticle (ecology)OpticsMaterials scienceOptoelectronicsChromatography

Abstract

fetched live from OpenAlex

Abstract. We evaluate the sensitivity of the size calibrations of two commercially available, high-resolution optical particle sizers to changes in aerosol composition and complex refractive index (RI). The Droplet Measurement Technologies Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) and the TSI, Inc. Laser Aerosol Spectrometer (LAS) are two commonly used instruments for measuring the portion of the aerosol size distribution with diameters larger than nominally 60–90 nm. Both instruments illuminate particles with a laser and relate the single-particle light scattering intensity and count rate measured over a wide range of angles to the size-dependent particle concentration. While the optical block geometry and flow system are similar for each instrument, a significant difference between the two models is the laser wavelength (1054 nm for the UHSAS and 633 nm for the LAS) and intensity (about 100 times higher for the UHSAS), which may affect the way each instrument sizes non-spherical or absorbing aerosols. Here, we challenge the UHSAS and LAS with laboratory-generated, mobility-size-classified aerosols of known chemical composition to quantify changes in the optical size response relative to that of ammonium sulfate (RI of 1.52+0i at 532 nm) and NIST-traceable polystyrene latex spheres (PSLs with RI of 1.59+0i at 589 nm). Aerosol inorganic salt species are chosen to cover the real refractive index range of 1.32 to 1.78, while chosen light-absorbing carbonaceous aerosols include fullerene soot, nigrosine dye, humic acid, and fulvic acid standards. The instrument response is generally in good agreement with the electrical mobility diameter. However, large undersizing deviations are observed for the low-refractive-index fluoride salts and the strongly absorbing nigrosine dye and fullerene soot particles. Polydisperse size distributions for both fresh and aged wildfire smoke aerosols from the recent Fire Influence on Regional to Global Environments Experiment and Air Quality (FIREX-AQ) and the Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) airborne campaigns show good agreement between both optical sizers and contemporaneous electrical mobility sizing and particle time-of-flight mass spectrometric measurements. We assess the instrument uncertainties by interpolating the laboratory response curves using previously reported RIs and size distributions for multiple aerosol type classifications. These results suggest that, while the optical sizers may underperform for strongly absorbing laboratory compounds and fresh tailpipe emissions measurements, sampling aerosols within the atmospherically relevant range of refractive indices are likely to be sized to better than ±10 %–20 % uncertainty over the submicron aerosol size range when using instruments calibrated with ammonium sulfate.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.212
Teacher spread0.198 · 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