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Record W4412045239 · doi:10.1038/s43247-025-02500-0

Semi-empirical estimates of stratospheric circulation and the lifetimes of chlorofluorocarbons and carbon tetrachloride

2025· article· en· W4412045239 on OpenAlexaboutno aff
Stephen Bourguet, Kane A. Stone, Megan Lickley

Bibliographic record

VenueCommunications Earth & Environment · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric AdministrationUniversity of BristolMiljødirektoratetNuclear Safety and Security CommissionMassachusetts Institute of TechnologyNational Aeronautics and Space AdministrationCommonwealth Scientific and Industrial Research OrganisationU.S. Department of EnergyBundesamt für UmweltNational Science Foundation
KeywordsCarbon tetrachlorideCirculation (fluid dynamics)Environmental scienceAtmospheric sciencesCarbon dioxideClimatologyChemistryGeologyEngineeringAerospace engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Chlorofluorocarbons (CFCs) and carbon tetrachloride (CCl 4 ) are ozone-depleting substances with high radiative efficiencies; however, uncertainties in their atmospheric lifetimes hinder top-down emission monitoring efforts. Here, we compute the loss, emission, and lifetime of CFC-11, CFC-12, and CCl 4 using their mass balance in the stratosphere. We first infer the strength of the stratospheric overturning circulation using satellite measurements of nitrous oxide; the mass flux at about 18 km is then used to compute the loss of CFC-11, CFC-12, and CCl 4 . We confirm that anomalous surface measurements of CFC-11 from 2013 to 2018 cannot be attributed to variability in stratospheric transport alone, and we infer near-steady CCl 4 emissions since 2013. Atmospheric lifetimes (50, 86, and 41 yr) independent of previous work are also computed using loss rates. These estimates add confidence to emission inversions and projections of the compounds’ ozone and climate impacts, and may help detect breaches of the Montreal Protocol.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.080
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.232
Teacher spread0.219 · 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 teacher head, 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

Citations2
Published2025
Admission routes1
Has abstractyes

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