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Record W3045052085 · doi:10.5194/amt-13-3993-2020

Recommendations for spectral fitting of SO <sub>2</sub> from miniature multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements

2020· article· en· W3045052085 on OpenAlexafffund
Zoe Davis, R. McLaren

Bibliographic record

VenueAtmospheric measurement techniques · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDifferential optical absorption spectroscopyWavelengthOpticsStray lightAbsorption (acoustics)SpectrometerSpectroscopyRadianceAbsorption spectroscopyChemistryPhysics

Abstract

fetched live from OpenAlex

Fitting sulfur dioxide (SO 2 ) differential slant column densities (dSCDs) from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of scattered sunlight is challenging because actinic light intensity is low in the wavelength regions where the SO 2 absorption features are strongest. SO 2 dSCDs were fit with different wavelength windows ( λ low to λ high ) from ambient measurements with calibration cells of 2.2×10 17 and 2.2×10 16 molec. cm −2 inserted in the light path at different viewing elevation angles using an Ocean Optics USB2000 spectrometer in a miniature MAX-DOAS instrument. SO 2 dSCDs were the least accurate, and fit errors were highest for fitting windows with λ low < 307 or λ low > 312 nm. The SO 2 dSCDs also exhibited an inverse relationship with the depth of the differential features in the SO 2 absorption cross section for fitting windows with λ low < 307 nm. Spectra measured at low viewing elevation angles (i.e., α=2∘) exhibited less accurate SO 2 dSCDs for the same fitting windows compared with higher angles. The use of a 400 nm short-pass filter or a polynomial to account for stray light (the offset function) increased the accuracy of the SO 2 dSCDs for many different fitting windows, decreased fit errors, and decreased the dSCDs' dependence on the depth of the SO 2 differential absorption features. These results suggest that the radiance at shorter wavelengths was increased by stray light. The inaccuracies at lower fitting wavelengths were increased by stray light originating from light with λ > 400 nm. Deviation of the SO 2 dSCD from the true value depended on the SO 2 concentration for some fitting windows rather than exhibiting a consistent bias. Uncertainties in the SO 2 dSCD reported by the fit algorithm were more than 50 % less than the true error for many windows, particularly for the measurements without the filter or offset function. For retrievals with the filter or offset function, increasing λ high > 320 nm tended to decrease the reported fit uncertainty but did not increase the accuracy. Based on the results of this study, a short-pass filter and a fitting window of 307.5 < λ < 319 nm are recommended for the retrieval of SO 2 SCDs from miniature MAX-DOAS measurements. If a filter is not available or conflicts with other species to be determined (e.g., NO 2 or HCHO), the offset function should be enabled, and a fit window 307.5 < λ < 319 nm is still recommended.

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)0.020
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.027
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.052
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0060.004
Science and technology studies0.0020.001
Scholarly communication0.0020.004
Open science0.0060.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0270.038

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 head0.060
GPT teacher head0.258
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

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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations8
Published2020
Admission routes2
Has abstractyes

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