Technical note: How are NH <sub>3</sub> dry deposition estimates affected by combining the LOTOS-EUROS model with IASI-NH <sub>3</sub> satellite observations?
Bibliographic record
Abstract
Abstract. Atmospheric levels of reactive nitrogen have increased substantially during the last century resulting in increased nitrogen deposition to ecosystems, causing harmful effects such as soil acidification, reduction in plant biodiversity and eutrophication in lakes and the ocean. Recent developments in the use of atmospheric remote sensing enabled us to resolve concentration fields of NH3 with larger spatial coverage. These observations may be used to improve the quantification of NH3 deposition. In this paper, we use a relatively simple, data-driven method to derive dry deposition fluxes and surface concentrations of NH3 for Europe and for the Netherlands. The aim of this paper is to determine the applicability and the limitations of this method for NH3. Space-born observations of the Infrared Atmospheric Sounding Interferometer (IASI) and the LOTOS-EUROS atmospheric transport model are used. The original modelled dry NH3 deposition flux from LOTOS-EUROS and the flux inferred from IASI are compared to indicate areas with large discrepancies between the two. In these areas, potential model or emission improvements are needed. The largest differences in derived dry deposition fluxes occur in large parts of central Europe, where the satellite-observed NH3 concentrations are higher than the modelled ones, and in Switzerland, northern Italy (Po Valley) and southern Turkey, where the modelled NH3 concentrations are higher than the satellite-observed ones. A sensitivity analysis of eight model input parameters important for NH3 dry deposition modelling showed that the IASI-derived dry NH3 deposition fluxes may vary from ∼ 20 % up to ∼50 % throughout Europe. Variations in the NH3 dry deposition velocity led to the largest deviations in the IASI-derived dry NH3 deposition flux and should be focused on in the future. A comparison of NH3 surface concentrations with in situ measurements of several established networks – the European Monitoring and Evaluation Programme (EMEP), Meetnet Ammoniak in Natuurgebieden (MAN) and Landelijk Meetnet Luchtkwaliteit (LML) – showed no significant or consistent improvement in the IASI-derived NH3 surface concentrations compared to the originally modelled NH3 surface concentrations from LOTOS-EUROS. It is concluded that the IASI-derived NH3 deposition fluxes do not show strong improvements compared to modelled NH3 deposition fluxes and there is a future need for better, more robust, methods to derive NH3 dry deposition fluxes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".