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Record W4414350809 · doi:10.1080/10962247.2025.2553832

The horizontal plane method of fugitive emission rate measurement

2025· article· en· W4414350809 on OpenAlexaboutno aff
Colin L. Y. Wong

Bibliographic record

VenueJournal of the Air & Waste Management Association · 2025
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsnot available
Fundersnot available
KeywordsHorizontal planePlumePerpendicularFugitive emissionsWind directionVolumetric flow ratePlane (geometry)AirflowWind speed

Abstract

fetched live from OpenAlex

The horizontal plane method is a novel method of measuring fugitive emission rates that is based on the mass balance approach. Conventional mass balance approach methods measure concentrations or integrated concentrations of airborne matter across a substantially vertical measurement surface that is substantially perpendicular to the wind flow direction. In contrast, for the horizontal plane method, concentrations or integrated concentrations of airborne matter are measured across a substantially horizontal sampling surface that is substantially parallel to the wind flow direction. This characteristic allows users of the horizontal plane method to sample an entire cross-section of a plume that exceeds the operating ceiling of drones or if there is an operating floor for aircraft. A horizontal plane map may be used to estimate the plan location of individual emission sources. Since sampling is horizontal, there is also the potential to efficiently measure the fugitive emission rate of large areas or the fugitive emission rates of multiple sources over large areas. Optimal conditions to carry out the method include conducting the field work during daytime sunny weather and obtaining the concentration or integrated concentration measurements between an altitude of approximately 110 m and 120 m.A horizontal plane system, which incorporated the horizontal plane method to measure the upper portion of the plume and a conventional mass balance method to measure the lower portion of the plume, was applied at the Vancouver Landfill and a methane emission rate of the landfill of 181 g/s was measured. By comparison, a methane emission rate of 177 g/s was measured using the airborne matter mapping method that had been applied earlier the same afternoon, for a difference of approximately +2.5%. The horizontal plane map that was generated enabled the identification of the estimated location of four areas of the landfill with relatively high emission rates.Implications: Small drones are a low-cost and effective platform for measurement of fugitive emission rates. However, drones are subject to safety regulations that impose an operating ceiling, and this constrains their ability to measure emission rates, especially of large plumes, using available quantification methods. The novel horizontal plane method of fugitive emission rate measurement expands the capabilities of drones by allowing drones to operate within regulatory constraints even if the altitude of a plume exceeds the operating ceiling of drones. The method also provides a map that can be used to estimate the location of individual emission sources.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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
GenreMethods

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

Citations1
Published2025
Admission routes1
Has abstractyes

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