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Record W4409347170 · doi:10.5194/egusphere-2025-1605

Aerodynamic gradient flux measurements of ammonia in intensively grazed grassland: temporal variations, environmental drivers, methodological challenges and uncertainties

2025· preprint· en· W4409347170 on OpenAlexaff
Mubaraq Olarewaju Abdulwahab, Christophe Fléchard, Yannick Fauvel, Christoph Häni, Adrien Jacotot, Anne‐Isabelle Graux, Nadège Edouard, Pauline Buysse, Valérie Viaud, A. Neftel

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsCanadian Anesthesia Research Foundation
Fundersnot available
KeywordsGrasslandEnvironmental scienceFlux (metallurgy)Atmospheric sciencesAerodynamicsPhysicsEcologyChemistryMechanicsBiology

Abstract

fetched live from OpenAlex

Abstract. Understanding the factors controlling surface-atmosphere exchange of ammonia (NH3) in grazed grasslands is crucial for improving atmospheric models and addressing environmental concerns associated with reactive nitrogen. However, in-situ micrometeorological NH3 flux measurements in pastures remain scarce in the literature. This study presents high-resolution NH3 flux data collected during four spring campaigns (2021 – 2024) at an intensively managed grassland site in Northwestern France, using the aerodynamic gradient method (AGM) alongside continuous monitoring of environmental variables and agricultural management. AGM-derived NH3 fluxes exhibited distinctive patterns: (i) high variability during grazing from -113 (deposition) to +3205 (emission) ng NH3 m-2 s-1, influenced by meteorology, grazing livestock density, and vegetation and soil dynamics; (ii) strong diurnal patterns and day-to-day variability; and (iii) transient volatilisation peaks following slurry applications (up to 10235 ng NH3 m-2 s-1). Grazing-induced fluxes often persisted for up to 1–2 weeks following cattle departure. Relative random uncertainties associated with AGM flux measurements ranged from typically 15 % to 70 %, based on errors in vertical concentration gradient slopes and variables related to turbulence and stability. Additional methodological limitations and systematic uncertainties are discussed, in particular errors associated with fundamental AGM assumptions and flux footprint attribution in a rotational grazing setup. Emission factors (EF), calculated for NH3 derived from deposited cattle urine nitrogen, varied considerably between grazing events, from 1 to 23 g NH3-N cow-1 grazing d-1, reflecting the interplay between livestock management and environmental factors. This study highlights the importance of long-term, continuous, high-resolution measurements to document the large variability in grazing-induced NH3 fluxes. The findings also underscore the need for refining bi-directional exchange models that integrate physics (meteorology, turbulence), environmental biogeochemistry (the fate of excreted nitrogen in the soil), biology (dynamic vegetation processes), and pasture management (grazing intensity) in grazed grassland systems.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.062
GPT teacher head0.267
Teacher spread0.206 · 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 designObservational
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

Citations1
Published2025
Admission routes1
Has abstractyes

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