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Record W2075592052 · doi:10.2134/jeq2007.0167

Quantifying Ammonia Emissions from a Cattle Feedlot using a Dispersion Model

2007· article· en· W2075592052 on OpenAlexafffundabout
S. M. McGinn, Thomas K. Flesch, B. P. Crenna, K. A. Beauchemin, Trevor Coates

Bibliographic record

VenueJournal of Environmental Quality · 2007
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsUniversity of AlbertaAgriculture and Agri-Food Canada
FundersCanadian Foundation for Climate and Atmospheric Sciences
KeywordsFeedlotManureEnvironmental scienceAtmospheric dispersion modelingFlux (metallurgy)Manure managementAmmoniaDispersion (optics)Wind speedLivestockAir quality indexAtmosphere (unit)Atmospheric sciencesAnimal scienceEnvironmental engineeringHydrology (agriculture)Air pollutionMeteorologyChemistryGeographyAgronomyPhysicsForestryBiology

Abstract

fetched live from OpenAlex

Livestock manure is a significant source of ammonia (NH3) emissions. In the atmosphere, NH3 is a precursor to the formation of fine aerosols that contribute to poor air quality associated with human health. Other environmental issues result when NH3 is deposited to land and water. Our study documented the quantity of NH3 emitted from a feedlot housing growing beef cattle. The study was conducted between June and October 2006 at a feedlot with a one-time capacity of 22,500 cattle located in southern Alberta, Canada. A backward Lagrangian stochastic (bLS) inverse-dispersion technique was used to calculate NH3 emissions, based on measurements of NH3 concentration (open-path laser) and wind (sonic anemometer) taken above the interior of the feedlot. There was an average of 3146 kg NH3 d(-1) lost from the entire feedlot, equivalent to 84 microg NH3 m(-2) s(-1) or 140 g NH3 head(-1) d(-1). The NH3 emissions correlated with sensible heat flux (r2 = 0.84) and to a lesser extent the wind speed (r2 = 0.56). There was also evidence that rain suppressed the NH3 emission. Quantifying NH3 emission and dispersion from farms is essential to show the impact of farm management on reducing NH3-related environmental issues.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.081
GPT teacher head0.333
Teacher spread0.252 · 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 designSimulation or modeling
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

Citations96
Published2007
Admission routes3
Has abstractyes

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