Ammonia measurements from space with the Cross-track Infrared Sounder (CrIS): characteristics and applications
Bibliographic record
Abstract
Abstract. Despite its clear importance, the monitoring of atmospheric ammonia, including its sources, sinks and links to the greater nitrogen cycle, remains limited. Satellite data are helping to fill the gap in monitoring from sporadic conventional ground and aircraft-based observations, to better inform policymakers, and assess the impact of any ammonia-related policies. Presented is a description and survey that demonstrate the capabilities of the CrIS ammonia product for monitoring, air quality forecast model evaluation, dry deposition estimates, and emissions estimates from an agricultural hotspot. For model evaluation, while there is a general agreement in the spatial allocation of known major agricultural ammonia hotspots across North America some high-latitude regions during peak forest fire activity often have ammonia concentrations approaching those in agricultural hotspots. The CrIS annual ammonia dry deposition in Canada (excluding Territories) and the U.S. have average and annual variability values of ~0.8 ± 0.08 Tg N year−1 and ~1.23 ± 0.09 Tg N year−1, respectively. These satellite derived dry depositions of reactive nitrogen from NH3 with NO2 show an annual ratio of NH3 compared to their sum (NH3 + NO2) of ~82 % and ~55 % in Canada and U.S., respectively. Furthermore, we show the use of CrIS satellite observations to estimated annual and seasonal emissions near Lethbridge, AB, Canada a region dominated by high emission feedlots also referred to as Concentrated Animal Feeding Operations (CAFOs); the satellite annual emission estimate of 37.1 ± 6.3 kt/yr is at least double the value reported in current bottom-up emission inventories for this region.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".