Bi-directional exchange of ammonia above a corn crop canopy: from flux measurements to model parameterizations
Bibliographic record
Abstract
Emissions of ammonia (NH3) from agriculture have a significant impact on the environment. Its atmospheric transport and subsequent deposition has been shown to alter nutrient-poor ecosystems thereby reducing biodiversity. As the most abundant base in the atmosphere, NH3 plays a key role in secondary aerosol formation impacting air quality and climate. Due to the lack of long term observations and challenges in performing NH3 flux measurements, large uncertainties exist in both emission quantification from fertilized crop fields and in the bi-directional exchange of NH3 with agroecosystems. We measured NH3 fluxes above a corn field using the eddy covariance technique together with a quantum cascade laser spectroscopy analyzer over two consecutive growing seasons in 2017 and 2018. We found that after initial NH3 emissions following fertilizer application, periods of both NH3 emission and deposition with similar flux magnitudes prevailed throughout the growing seasons (ranging approximately between ±300 ng m-2 s-1), highlighting the importance of the corn crop canopy for regulating the net NH3 exchange. To evaluate the underlying processes of the NH3 bi-directional exchange, a two-layer compensation point model was used. Based on the large range of environmental conditions encountered during the extensive flux measurements periods, the validity of different parameterizations could be assessed. In particular, processes regulating stomatal and non-stomatal flux pathways will be discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".