Studies of Stratospheric and Tropospheric Ozone, NO2, and BrO Using UV-Visible Spectroscopy in the Arctic and at Mid-latitudes
Bibliographic record
Abstract
This thesis utilizes UV-visible spectroscopy to develop new datasets, study Arctic and urban atmospheric composition, and validate satellite data products. The primary instruments used here (the Ground-Based Spectrometers, or GBSs) have been taking measurements at the Polar Environment Atmospheric Research Laboratory (PEARL, 80.05°N, 86.42°W) since 1999 and 2006, respectively.The GBS dataset, combined with other measurements at PEARL, was used to validate ozone and NO2 measurements from the Atmospheric Chemistry Experiment (ACE) and Optical Spectrograph and InfraRed Imaging System (OSIRIS) satellite instruments. Ozone from all instruments agrees to within 12.0%, while NO2 measurements agree to within 33.2%. There are no apparent systematic changes in the observed differences between the satellite and the ground-based instruments over time. In the winter/spring of 2020, the unusually strong and cold polar vortex led to unprecedented Arctic ozone depletion. Total column ozone was at an all-time low in the 20-year GBS dataset. Chlorine activation inside the vortex was ongoing until the end of March, resulting in mean chemical ozone loss of 111-127 DU (27-31%) over Eureka, which represents similar absolute loss and greater relative loss compared to that in spring 2011. GBS BrO partial columns were used to investigate Arctic tropospheric ozone depletion during four bromine activation seasons. BrO enhancements show two modes differentiated by air mass history. Contact with the snowpack on sea ice corresponds to increased BrO for one of these modes only, while the other mode is related to storms that almost always bring bromine-enriched air to Eureka. The presence of coarse mode aerosols (likely sea salt aerosol) is a necessary and sufficient condition for observing BrO at Eureka, indicating that sea salt aerosols play an active role in bromine activation. A tropospheric NO2 profile dataset was retrieved from 2018-2020 Pandora spectrometer measurements to investigate NO2 pollution in Toronto. Retrievals using optimal estimation and parametric algorithms show good agreement. Seasonal and diurnal variability is apparent in both the NO2 partial column and surface concentration datasets. During the spring 2020 COVID-19 lockdown in Toronto, daily maximum NO2 values showed substantial reductions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 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".