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Record W4224050180 · doi:10.5194/acp-2022-155-rc1

Comment on acp-2022-155

2022· peer-review· en· W4224050180 on OpenAlexaboutno aff
Lu Shen, Ritesh Gautam, Mark Omara, Daniel Zavala‐Araiza, Joannes D. Maasakkers, Tia R. Scarpelli, Alba Lorente, David Lyon, Jian‐Xiong Sheng, Daniel J. Varon, Hannah Nesser, Zhen Qu, Xiao Lu, Melissa P. Sulprizio, Steven P. Hamburg, Daniel Jacob

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
FundersRobertson FoundationNational Aeronautics and Space Administration
KeywordsMethaneMethane emissionsAtmospheric methaneStructural basinEmission inventoryEnvironmental scienceInversion (geology)SatelliteFossil fuelTroposphereAtmospheric sciencesGeologyMeteorologyGeographyGeomorphologyChemistryAir quality index

Abstract

fetched live from OpenAlex

We use satellite methane observations from the Tropospheric Monitoring Instrument (TROPOMI), from May 2018 to February 2020, to quantify methane emissions from individual oil and natural gas (O/G) basins in the US and Canada using a high-resolution (~ 25 km) atmospheric inverse analysis. Our satellite-derived emission estimates show good consistency with in-situ field measurements (R2 = 0.92) in 14 O/G basins distributed across the US and Canada. Aggregating our results to the national scale, we obtain O/G-related methane emission estimates of 12.6 ± 2.1 Tg a-1 for the US and 2.2 ± 0.6 Tg a-1 for Canada, respectively 80 % and 40 % higher than the national inventories reported to the United Nations. About 70 % of the discrepancy in the EPA inventory can be attributed to five O/G basins: the Permian, Haynesville, Anadarko, Eagle Ford and Barnett Basin, which in total account for 40 % of US emissions. We show more generally that our TROPOMI inversion framework can quantify methane emissions exceeding 0.2–0.5 Tg a-1 from individual O/G basins, thus providing an effective tool for monitoring methane emissions from large O/G basins globally.

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)0.003
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.065
Threshold uncertainty score0.219

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0220.014
Insufficient payload (model declined to judge)0.0650.060

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 head0.014
GPT teacher head0.243
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2022
Admission routes1
Has abstractyes

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