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Record W1510600477 · doi:10.1002/grl.50704

Relative changes in CO emissions over megacities based on observations from space

2013· article· en· W1510600477 on OpenAlexafffund
Matthieu Pommier, C. A. McLinden, M. N. Deeter

Bibliographic record

VenueGeophysical Research Letters · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsEnvironment and Climate Change Canada
FundersNatural Sciences and Engineering Research Council of CanadaNational Aeronautics and Space Administration
KeywordsMegacityEnvironmental scienceTroposphereAtmospheric sciencesAir pollutionMeteorologyEmission inventoryPollutantAir pollutantsPollutionAir quality indexGeographyGeology

Abstract

fetched live from OpenAlex

Urban areas are large sources of several air pollutants, with carbon monoxide (CO) among the largest. Yet measurement from space of their CO emissions remains elusive due to its long lifetime. Here we introduce a new method of estimating relative changes in CO emissions over megacities. A new multichannel Measurements of Pollution in the Troposphere (MOPITT) CO data product, offering improved sensitivity to the boundary layer, is used to estimate this relative change over eight megacities: Moscow, Paris, Mexico, Tehran, Baghdad, Los Angeles, Sao Paulo, and Delhi. By combining MOPITT observations with wind information from a meteorological reanalysis, changes in the CO upwind‐downwind difference are used as a proxy for changes in emissions. Most locations show a clear reduction in CO emission between 2000–2003 and 2004–2008, reaching −43% over Tehran and −47% over Baghdad. There is a contrasted agreement between these results and the MACCity and Emission Database for Global Atmospheric Research v4.2 inventories.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.996

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.057
GPT teacher head0.289
Teacher spread0.232 · 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.

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

Citations118
Published2013
Admission routes2
Has abstractyes

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