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Record W7033742852

Satellite Limb Observations of Stratospheric NOx

2022· dissertation· en· W7033742852 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
Fundersnot available
KeywordsStratosphereOzone layerTrace gasOzoneNOxSatelliteAerosol
DOInot available

Abstract

fetched live from OpenAlex

The trace gases NO and NO2, collectively called NOx, are critical components of the stratosphere. NOx has become a key contributor to the destruction of the ozone layer since the Montreal Protocol of 1997 successfully reduced emissions of chlorine based ozone depleting substances. It is therefore important to monitor stratospheric NOx concentrations so that we can assess their impact on the ozone layer. The work in this thesis falls into two categories: improvements to the NO2 measurement record from satellite limb profiling instruments, and applications of the NO2 measurements to answer questions about the state of the atmosphere.\n\n An extended time series, spanning from 1984 to 2018, was created by combining observations from the Stratospheric Aerosol and Gas Experiment (SAGE) II with observations from the Optical Spectrograph and InfraRed Imager System (OSIRIS). \n These combined data were used to show that stratospheric NOx has been increasing at a rate of 10%/decade in the tropical lower stratosphere. The construction of the merged data illuminated some biases between the SAGE II and OSIRIS data. This led to the development of a scaling factor for the SAGE retrieval that accounts for changes in chemistry with the position of the sun. This scaling was applied to NO2 retrievals from SAGE III on the International Space Station (ISS). The result was a reduction in the bias between SAGE III/ISS and OSIRIS NO2 by up to 20% at altitudes below 30 km.\n Improvements to the spectral resolution fitting and cloud filtering in the OSIRIS NO2 retrieval were also made, resulting in improved agreement between NO2 observations from OSIRIS, SAGE III/ISS, and the Atmospheric Chemistry Experiment - Fourier Transform Spectrometer (ACE-FTS). These updated data were then used to show that smoke from large wildfires can enter the stratosphere and initiate a series of chemical reactions that can lead to ozone destruction. The NO2 observations were also used to show that the Asian summer monsoon (ASM) results in a NO2 minimum and a NOx maximum in the upper troposphere and lower stratosphere. This provides insight on the chemistry of the ASM that is important for evaluating the performance of chemistry-climate models in that region.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.165
Teacher spread0.155 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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