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Quantifying NH3 and CH4 emissions from a dairy housing using backward Lagrangian stochastic modelling

2020· preprint· en· W3083837533 on OpenAlexaboutno aff
Christoph Häni, Marcel Bühler, Sabine Schrade, Michael Zähner, Simon A. Wyss, Joachim Mohn, Thomas Küpper

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsHomogeneousPhysicsAnimal scienceChemistryThermodynamicsBiology

Abstract

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Inverse dispersion modelling (IDM) using a backward Lagrangian stochastic (bLS) dispersion model has been successfully applied to quantify emissions from confined ground sources e.g. as for ammonia (NH3) loss after manure spreading. The most widely used bLS model for emission measurements of NH3 and methane (CH4) from agricultural sources such as lagoons and livestock buildings is based on Flesch et al. (2004). For such applications, the model assumptions of a diffusive ground source within a homogeneous turbulence field, which implies absence of obstacles as e.g. buildings disturbing the flow, is clearly not fulfilled. It remains unclear to what extend these violations introduce bias into the emission estimates. Further, the model by Flesch et al. does not include deposition removal, which for NH3, can induce an underestimation of the emission from the source (Häni et al., 2018). Häni et al. extended the standard bLS calculation model with an optional dry deposition mechanism. In a field campaign between mid-September and mid-December 2018, CH4 and NH3 emissions from a natural ventilated dairy housing with 40 cows were quantified using the IDM method with the bLS model by Häni et al. (2018). From the three-month period, results for 63 measurement days at 30-minute resolution were evaluated and thereof 71% of the data points were discarded from the emission calculation due to inapplicable turbulence conditions or instrument failure. NH3 and CH4 concentrations were analysed with open-path instruments (NH3: miniDOAS,; CH4: GasFinder, Boreal Laser, Inc., Edmonton, Alberta, Canada) (aligned in parallel) with 50 m path lengths (distance between sensor and reflector). During part of the field campaign (24 days), simultaneous in-house measurements of CH4 and NH3 emissions using the tracer ratio method (iTM) (SF6 and SF5CF3, Mohn et al., 2018) were conducted and results compared with the estimates retrieved by the IDM method. Overall, the results from the IDM method compare well to the results of the in-house measurements, with mean daily emissions of 18.3 kg CH4/d (IDM) and 17.9 kg CH4/d (iTM) and 1.08 kg NH3/d (IDM) and 1.56 kg NH3/d (iTM), respectively. Regarding NH3, the IDM method was run without the inclusion of a dry deposition mechanism. First results from IDM calculations with the inclusion of dry deposition indicate, that dry deposition modelling may explain the difference in NH3 emissions between the IDM method and the iTM. References Flesch, T. K., Wilson, J. D., Harper, L. A., Crenna, B. P., and Sharpe, R. R.: Deducing ground-to-air emissions from observed trace gas concentrations: A field trial, J. Appl. Meteorol., 43, 487–502, 2004. Häni, C., Flechard, C., Neftel, A., Sintermann, J., and Kupper, T.: Accounting for Field-Scale Dry Deposition in Backward Lagrangian Stochastic Dispersion Modelling of NH3 Emissions, Atmosphere, 9, 146, 2018. Mohn, J., Zeyer, K., Keck, M., Keller, M., Zähner, M., Poteko, J., Emmenegger, L., and Schrade, S.: A dual tracer ratio method for comparative emission measurements in an experimental dairy housing, Atmospheric Environment, 179, 12–22, 2018.

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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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.128
GPT teacher head0.301
Teacher spread0.174 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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