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Record W4383600404 · doi:10.5194/amt-16-3421-2023

Controlled-release testing of the static chamber methodology for direct measurements of methane emissions

2023· article· en· W4383600404 on OpenAlexafffund
James P. Williams, Khalil El Hachem, Mary Kang

Bibliographic record

VenueAtmospheric measurement techniques · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsMethaneEnvironmental scienceGreenhouse gasVolumetric flow rateFlow (mathematics)Component (thermodynamics)ChemistryNuclear engineeringMechanicsEngineeringPhysicsThermodynamicsGeology

Abstract

fetched live from OpenAlex

Abstract. Direct measurements of methane emissions at the component level provide the level of detail necessary for the development of actionable mitigation strategies. As such, there is a need to understand the magnitude of component-level methane emission sources and to test methane quantification methods that can capture methane emissions at the component level used in national inventories. The static chamber method is a direct measurement technique that has been applied to measure large and complex methane sources, such as oil and gas infrastructure. In this work, we compile methane emission factors from the Intergovernmental Panel on Climate Change (IPCC) Emission Factor Database in order to understand the magnitude of component-level methane flow rates, review the tested flow rates and measurement techniques from 40 controlled-release experiments, and perform 64 controlled-release tests of the static chamber methodology with mass flow rates of 1.02, 10.2, 102, and 512 g h−1 of methane. We vary the leak properties, chamber shapes, chamber sizes, and use of fans to evaluate how these factors affect the accuracy of the static chamber method. We find that 99 % of the component-level methane emission rates from the IPCC Emission Factor Database are below 100 g h−1 and that 77 % of the previously available controlled-release experiments did not test for methane mass flow rates below 100 g h−1. We also find that the static chamber method quantified methane flow rates with an overall accuracy of +14/-14 % and that optimal chamber configurations (i.e., chamber shape, volume, and use of fans) can improve accuracy to below ±5 %. We note that smaller chambers (≤20 L) performed better than larger-volume chambers (≥20 L), regardless of the chamber shape or use of fans. However, we found that the use of fans can substantially increase the accuracy of larger chambers, especially at higher methane mass flow rates (≥100 g h−1). Overall, our findings can be used to engineer static chamber systems for future direct measurement campaigns targeting a wide range of sources, including landfills, sewerage utility holes, and oil and 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 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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.105
GPT teacher head0.296
Teacher spread0.191 · 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 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

Citations18
Published2023
Admission routes2
Has abstractyes

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