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Record W2747033520 · doi:10.1002/2017gl074388

Considerable contribution of the Montreal Protocol to declining greenhouse gas emissions from the United States

2017· article· en· W2747033520 on OpenAlexaboutno aff
Lei Hu, S. A. Montzka, Scott J. Lehman, David S. Godwin, B. R. Miller, A. E. Andrews, K. W. Thoning, J. B. Miller, Colm Sweeney, Caroline Siso, James W. Elkins, B. D. Hall, D. J. Mondeel, David Nance, Thomas Nehrkorn, Marikate Mountain, M. L. Fischer, Sébastien Biraud, Huilin Chen, Pieter P. Tans

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryClimate Program OfficeBiological and Environmental ResearchNational Oceanic and Atmospheric AdministrationCalifornia Air Resources BoardU.S. Department of Energy
KeywordsMontreal ProtocolGreenhouse gasEnvironmental scienceKyoto ProtocolAtmospheric sciencesAtmosphere (unit)ClimatologyOzoneOzone layerEnvironmental protectionMeteorologyGeography

Abstract

fetched live from OpenAlex

Abstract Ozone depleting substances (ODSs) controlled by the Montreal Protocol are potent greenhouse gases (GHGs), as are their substitutes, the hydrofluorocarbons (HFCs). Here we provide for the first time a comprehensive estimate of U.S. emissions of ODSs and HFCs based on precise measurements in discrete air samples from across North America and in the remote atmosphere. Derived emissions show spatial and seasonal variations qualitatively consistent with known uses and largely confirm U.S. Environmental Protection Agency (EPA) national emissions inventories for most gases. The measurement‐based results further indicate a substantial decline of ODS emissions from 2008 to 2014, equivalent to ~50% of the CO 2 ‐equivalent decline in combined emissions of CO 2 and all other long‐lived GHGs inventoried by the EPA for the same period. Total estimated CO 2 ‐equivalent emissions of HFCs were comparable to the sum of ODS emissions in 2014, but can be expected to decline in the future in response to recent policy measures.

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)0.001
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 score0.347
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.030
GPT teacher head0.319
Teacher spread0.289 · 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

Citations77
Published2017
Admission routes1
Has abstractyes

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