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Record W2280813206

Development of ammonia emission factors for the land application of poultry manure in the lower fraser valley of British Columbia

2009· article· en· W2280813206 on OpenAlexaffabout
Anthony Lau, S. Bittman And D. E. Hunt

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsManureAmmoniaEnvironmental scienceFertilizerAnimal scienceAgronomyChemistryBiology
DOInot available

Abstract

fetched live from OpenAlex

Lau, A. K., Bittman, S. and Hunt, D. E. 2008. Development of ammonia emission factors for the land application of poultry manure in the Lower Fraser Valley of British Columbia. Canadian Biosystems Engineering/Le genie des biosystemes au Canada 50: 6.47 6.55. The objective of this study was to monitor ammonia emissions and develop updated ammonia emission factors for land application of poultry manure under British Columbia conditions. Field trials, which involved four types of poultry manure as the fertilizer materials, were performed at Agassiz Research Station in 2005 and 2006. After manure application, ammonia emission rates were determined using wind tunnels, capturing the emitted ammonia with acid traps and analyzing with a flow injection analyzer. For all trials, the highest emissions occurred within the first day, and gradually declined over the next 2-3 weeks. Cumulative ammonia emission in all treatments did not exceed the initial amount of ammonianitrogen present in manure. Ammonia emission rates were significantly different among the manure types (pB0.005). The percent total loss of ammonia with time was positively correlated with manure pH. Ammonia emission rates were generally higher in both of the spring trials than the fall trial. The proposed revised ammonia emission factors of 0.12 and 0.16 for the two major types of poultry broiler and layer are in line with current emission factors adopted by Environment Canada. However, current and revised emission factors (0.38 vs. 0.13) were substantially different for turkey manure.

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 score0.400
Threshold uncertainty score0.152

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 studies0.0000.000
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 head0.010
GPT teacher head0.229
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 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

Citations8
Published2009
Admission routes2
Has abstractyes

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