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
Bibliographic record
Abstract
Abstract. Vertical profiles of aerosols, NO2, and SO2 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 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 AODs from MAX-DOAS aerosol retrievals, lidar vertical profiles of aerosol extinction, and 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 NO2 and SO2 retrievals to Pandora spectral sun photometer 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 SO2 were used to validate retrieved vertical profiles of SO2. 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".