Measurements and quality control of ammonia eddy covariance fluxes: a new strategy for high-frequency attenuation correction
Bibliographic record
Abstract
Abstract. Measurements of the surface–atmosphere exchange of ammonia (NH3) are necessary to study the emission and deposition processes of NH3 from managed and natural ecosystems. The eddy covariance technique, which is the most direct method for trace gas exchange measurements at the ecosystem level, requires trace gas detection at a fast sample frequency and high precision. In the past, the major limitation for measuring NH3 eddy covariance fluxes has been the slow time response of NH3 measurements due to NH3 adsorption on instrument surfaces. While high-frequency attenuation correction methods are used, large uncertainties in these corrections still exist, which are mainly due to the lack of understanding of the processes that govern the time response. We measured NH3 fluxes over a corn crop field using a quantum cascade laser spectrometer (QCL) that enables measurements of NH3 at a 10 Hz measurement frequency. The 5-month measurement period covered a large range of environmental conditions that included both periods of NH3 emission and deposition and allowed us to investigate the time response controlling parameters under field conditions. Without high-frequency loss correction, the median daytime NH3 flux was 8.59 ng m−2 s−1 during emission and −19.87 ng m−2 s−1 during deposition periods, with a median daytime random flux error of 1.61 ng m−2 s−1. The overall median flux detection limit was 2.15 ng m−2 s−1, leading to only 11.6 % of valid flux data below the detection limit. From the flux attenuation analysis, we determined a median flux loss of 17 % using the ogive method. No correlations of the flux loss with environmental or analyser parameters (such as humidity or inlet ageing) were found, which was attributed to the uncertainties in the ogive method. Therefore, we propose a new method that simulates the flux loss by using the analyser time response that is determined frequently over the course of the measurement campaign. A correction that uses as a function of the horizontal wind speed and the time response is formulated which accounts for surface ageing and contamination over the course of the experiment. Using this method, the median flux loss was calculated to be 46 %, which was substantially higher than with the ogive method.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".