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Record W2971631267 · doi:10.5194/amt-13-1129-2020

Validation of MAX-DOAS retrievals of aerosol extinction, SO <sub>2</sub> , and NO <sub>2</sub> through comparison with lidar, sun photometer, active DOAS, and aircraft measurements in the Athabasca oil sands region

2020· article· en· W2971631267 on OpenAlexafffundabout
Zoe Davis, Udo Frieß, K. B. Strawbridge, Monika Aggarwaal, Sabour Baray, Elijah G. Schnitzler, Akshay Lobo, Vitali Fioletov, Ihab Abboud, C. A. McLinden, Jim Whiteway, Megan D. Willis, Alex K. Y. Lee, Jeff Brook, Jason S. Olfert, Jason O’Brien, Ralf M. Staebler, Hans D. Osthoff, Cristian Mihele, R. McLaren

Bibliographic record

VenueAtmospheric measurement techniques · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of CalgaryUniversity of AlbertaUniversity of TorontoEnvironment and Climate Change CanadaYork University
FundersEnvironment CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsDifferential optical absorption spectroscopyAerosolEnvironmental scienceLidarSun photometerAERONETAtmospheric sciencesPhotometerExtinction (optical mineralogy)Planetary boundary layerMeteorologyRemote sensingAbsorption (acoustics)ChemistryMineralogyGeologyMaterials scienceOptics

Abstract

fetched live from OpenAlex

Vertical profiles of aerosols, NO 2 , and SO 2 were retrieved from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements at a field site in northern Alberta, Canada, during August and September 2013. The site is approximately 16 km north of two mining operations that are major sources of industrial pollution in the Athabasca oil sands region. Pollution conditions during the study ranged from atmospheric background conditions to heavily polluted with elevated plumes, according to the meteorology. This study aimed to evaluate the performance of the aerosol and trace gas retrievals through comparison with data from a suite of other instruments. Comparisons of aerosol optical depths (AODs) from MAX-DOAS aerosol retrievals, lidar vertical profiles of aerosol extinction, and the AERONET sun photometer indicate good performance by the MAX-DOAS retrievals. These comparisons and modelling of the lidar S ratio highlight the need for accurate knowledge of the temporal variation in the S ratio when comparing MAX-DOAS and lidar data. Comparisons of MAX-DOAS NO 2 and SO 2 retrievals to Pandora spectral sun photometer vertical column densities (VCDs) and active DOAS mixing ratios indicate good performance of the retrievals, except when vertical profiles of pollutants within the boundary layer varied rapidly, temporally, and spatially. Near-surface retrievals tended to overestimate active DOAS mixing ratios. The MAX-DOAS observed elevated pollution plumes not observed by the active DOAS, highlighting one of the instrument's main advantages. Aircraft measurements of SO 2 were used to validate retrieved vertical profiles of SO 2 . Advantages of the MAX-DOAS instrument include increasing sensitivity towards the surface and the ability to simultaneously retrieve vertical profiles of aerosols and trace gases without requiring additional parameters, such as the S ratio. This complex dataset provided a rare opportunity to evaluate the performance of the MAX-DOAS retrievals under varying atmospheric conditions.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.348
Threshold uncertainty score0.692

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.028
GPT teacher head0.228
Teacher spread0.200 · 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

Citations16
Published2020
Admission routes3
Has abstractyes

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