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Record W2398491023 · doi:10.5194/acp-16-14091-2016

Quantifying the loss of processed natural gas within California's South Coast Air Basin using long-term measurements of ethane and methane

2016· article· en· W2398491023 on OpenAlexaff
Debra Wunch, Geoffrey C. Toon, Jacob K. Hedelius, N. Vizenor, Coleen M. Roehl, Katherine M. Saad, Jean-François L. Blavier, D. R. Blake, P. O. Wennberg

Bibliographic record

VenueAtmospheric chemistry and physics · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Toronto
FundersCalifornia Institute of TechnologyJet Propulsion LaboratoryNational Aeronautics and Space Administration
KeywordsMethaneNatural gasMethane emissionsTrace gasAtmospheric methaneEnvironmental scienceAtmospheric sciencesTroposphereOil and natural gasFossil fuelChemistryGeology

Abstract

fetched live from OpenAlex

Abstract. Methane emissions inventories for Southern California's South Coast Air Basin (SoCAB) have underestimated emissions from atmospheric measurements. To provide insight into the sources of the discrepancy, we analyze records of atmospheric trace gas total column abundances in the SoCAB starting in the late 1980s to produce annual estimates of the ethane emissions from 1989 to 2015 and methane emissions from 2007 to 2015. The first decade of measurements shows a rapid decline in ethane emissions coincident with decreasing natural gas and crude oil production in the basin. Between 2010 and 2015, however, ethane emissions have grown gradually from about 13 ± 5 to about 23 ± 3 Gg yr−1, despite the steady production of natural gas and oil over that time period. The methane emissions record begins with 1 year of measurements in 2007 and continuous measurements from 2011 to 2016 and shows little trend over time, with an average emission rate of 413 ± 86 Gg yr−1. Since 2012, ethane to methane ratios in the natural gas withdrawn from a storage facility within the SoCAB have been increasing by 0.62 ± 0.05 % yr−1, consistent with the ratios measured in the delivered gas. Our atmospheric measurements also show an increase in these ratios but with a slope of 0.36 ± 0.08 % yr−1, or 58 ± 13 % of the slope calculated from the withdrawn gas. From this, we infer that more than half of the excess methane in the SoCAB between 2012 and 2015 is attributable to losses from the natural gas infrastructure.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.538

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 head0.020
GPT teacher head0.232
Teacher spread0.212 · 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 designBench or experimental
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

Citations85
Published2016
Admission routes1
Has abstractyes

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