‘Analytical Chemistry in Near Space: Exploring the Stratosphere, threats to the Ozone Layer, and the Ongoing Challenges to Ozone Recovery’
Bibliographic record
Abstract
Under the international agreement that formed the Montréal Protocol on Substances that Deplete the Ozone Layer, the production and consumption of ozone-depleting substances was phased out, in order to limit their contribution to stratospheric ozone depletion. Ongoing monitoring is necessary in order to ensure compliance with the Montréal Protocol, to identify and respond to new threats to the ozone layer and verify that the atmospheric abundance of ozone-depleting substances continues to fall. Here I utilise a number of different techniques to investigate ozone-depleting substances, this includes model data but primarily focuses on measurements taken using in-situ sample collection from large balloon flights, high-altitude research aircraft flights, and the novel ‘AirCore’ technique which collected samples using smaller balloons. Firstly, this thesis investigates four comparatively longer-lived CFCs (CFC-13, CFC-114, CFC-114a and CFC-115), and derives (sometimes for the first time) observation-based policy relevant metrics for these under-studied compounds. Model data is used to investigate how changes to stratospheric circulation or chemistry could affect these metrics for these compounds, and a sensitivity study of the model is conducted. Next this thesis explores the feasibility of deriving stratospheric concentrations of seven atmospheric trace gases through sampling via the AirCore technique. These compounds are: PFC-116, HFC-125, CFC-113, CFC-115, methyl chloride, HCFC-141b, and HCFC-142b. In addition to testing a range of factors in order to refine a set of ‘best practices’ for the technique, the thesis explores the effect of seasonality and location on key metrics (FRFs and ODPs), the rates at which they dissociate in the stratosphere and their potential for ozone depletion. The thesis investigates previously held assumptions regarding how fractional release (the rate at which a compound dissociates in the stratosphere) is calculated and the impact of seasonality and latitude on these. Having explored a number of compounds that are of interest in ozone depletion chemistry, this thesis investigates ways to monitor their impact on the ozone layer, identifying multiple challenges to accurate monitoring and testing solutions to them. Alongside deriving new estimates of policy relevant metrics which are important tools in accurately assessing and combating threats to the ozone layer, and deriving new emissions estimates for some compounds, this thesis has a few overall conclusions. Firstly, that CFC-13 did not have a previous estimate for stratospheric lifetime, but had a total atmospheric lifetime of 650 years, while CFC-115 had a previous stratospheric lifetime estimate of 664. These lifetime estimates are revised here to 315 years and 369 years respectively, and in order to account for current abundance greater emissions are required (and estimated here). Secondly that the assumptions underlying the calculation of fractional release leave a broad margin for uncertainty, with FRFs varying significantly (e.g. ±12 % for CFC-113 and ±19 % for CFC-115) over different seasons and geographical areas. Finally, that in the absence of reliable in-situ data (methods for which this thesis explores), model simulations and lab-based kinetics experiments cannot tell the whole story, which is something this research seeks to address.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".