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Record W4232092565 · doi:10.5194/acpd-10-10839-2010

Options to accelerate ozone recovery:ozone and climate benefits

2010· preprint· en· W4232092565 on OpenAlexaboutno aff
J. S. Daniel, Eric L. Fleming, R. W. Portmann, Guus J. M. Velders, Charles H. Jackman, A. R. Ravishankara

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersNational Aeronautics and Space Administration
KeywordsChlorofluorocarbonOzoneRadiative forcingMontreal ProtocolEnvironmental scienceOzone layerAtmospheric sciencesTonneOzone depletionForcing (mathematics)ClimatologyMeteorologyChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract. Hypothetical reductions in future emissions of ozone-depleting substances (ODSs), including N2O, are evaluated in terms of effects on equivalent effective stratospheric chlorine (EESC), globally-averaged total column ozone, and radiative forcing through 2100. Due to the established success of the Montreal Protocol, these actions can have only a fraction of the impact that regulations already in force have had. If all anthropogenic ODS emissions were halted beginning in 2011, ozone is calculated to be higher by about 1–2{%} during the period 2030–2100 compared to a case of no additional ODS restrictions. Radiative forcing by 2100 would be about 0.23 W/m2 lower due to the elimination of N2O emissions and about 0.005 W/m2 lower due to destruction of the chlorofluorocarbon (CFC) bank. The ability of EESC to be a suitable metric for total ozone is also quantified. Responding to the recent suggestion that N2O should be considered an ODS, we provide an approach to incorporate N2O into the EESC formulation.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.024
GPT teacher head0.237
Teacher spread0.214 · 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 designSimulation or modeling
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

Citations1
Published2010
Admission routes1
Has abstractyes

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