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Record W2126222557 · doi:10.4141/cjas10034

Review: Ammonia emissions from dairy farms and beef feedlots

2011· article· en· W2126222557 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Animal Science · 2011
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsAgriculture and Agri-Food Canada
FundersU.S. Department of Agriculture
KeywordsManureAmmonia volatilization from ureaAmmoniaEnvironmental scienceFertilizerManure managementEnvironmental chemistryEutrophicationChemistryAnimal scienceAgronomyNutrient

Abstract

fetched live from OpenAlex

Hristov, A. N., Hanigan, M., Cole, A., Todd, R., McAllister T. A., Ndegwa, P. and Rotz, A. 2011. Review: Ammonia emissions from dairy farms and beef feedlots. Can. J. Anim. Sci. 91: 1–35. Ammonia emitted from animal feeding operations is an environmental and human health hazard, contributing to eutrophication of surface waters and nitrate contamination of ground waters, soil acidity, and fine particulate matter formation. It may also contribute to global warming through nitrous oxide formation. Along with these societal concerns, ammonia emission is a net loss of manure fertilizer value to the producer. A significant portion of cattle manure nitrogen, primarily from urinary urea, is converted to ammonium and eventually lost to the atmosphere as ammonia. Determining ammonia emissions from cattle operations is complicated by the multifaceted nature of the factors regulating ammonia volatilization, such as manure management, ambient temperature, wind speed, and manure composition and pH. Approaches to quantify ammonia emissions include micrometeorological methods, mass balance accounting and enclosures. Each method has its advantages, disadvantages and appropriate application. It is also of interest to determine the ammonia emitting potential of manure (AEP) independent of environmental factors. The ratio of nitrogen to non-volatile minerals (phosphorus, potassium, ash) or nitrogen isotopes ratio in manure has been suggested as a useful indicator of AEP. Existing data on ammonia emission factors and flux rates are extremely variable. For dairy farms, emission factors from 0.82 to 250 g ammonia per cow per day have been reported, with an average of 59 g per cow per day (n=31). Ammonia flux rates for dairy farms averaged 1.03 g m −2 h −1 (n=24). Ammonia losses are significantly greater from beef feedlots, where emission factors average 119 g per animal per day (n=9) with values as high as 280 g per animal per day. Ammonia flux rate for beef feedlots averaged 0.174 g m −2 h −1 (n=12). Using nitrogen mass balance approaches, daily ammonia nitrogen losses of 25 to 50% of the nitrogen excreted in manure have been estimated for dairy cows and feedlot cattle. Practices to mitigate ammonia emissions include reducing excreted N (particularly urinary N), acidifying ammonia sources, or binding ammonium to a substrate. Reducing crude protein concentration in cattle diets and ruminal protein degradability are powerful tools for reducing N excretion, AEP, and whole-farm ammonia emissions. Reducing dietary protein can also benefit the producer by reducing feed cost. These interventions, however, have to be balanced with the risk of lost production. Manure treatment techniques that reduce volatile N species (e.g., urease inhibition, pH reduction, nitrification-denitrification) are also effective for mitigating ammonia emissions. Another option for reducing ammonia emissions is capture and treatment of released ammonia. Examples in the latter category include biofilters, permeable and impermeable covers, and manure incorporation into the soil for crop or pasture production. Process-level simulation of ammonia formation and emission provides a useful tool for estimating emissions over a wide range of production practices and evaluating the potential benefits of mitigation strategies. Reducing ammonia emissions from dairy and beef cattle operations is critical to achieving environmentally sustainable animal production that will benefit producers and society at large.

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.

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)0.001
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 score0.679
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.033
GPT teacher head0.246
Teacher spread0.213 · 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