Nitrous Oxide Emissions Estimated With the CarbonTracker‐Lagrange North American Regional Inversion Framework
Bibliographic record
Abstract
Abstract North American nitrous oxide (N 2 O) emissions of 1.6 ± 0.3 Tg N/yr over 2008–2014 are estimated using the CarbonTracker‐Lagrange regional inversion framework. The estimated N 2 O emissions are largely consistent with the EDGAR (Emission Database for Global Atmospheric Research) global inventory and with the results of global atmospheric inversions but offer more spatial and temporal detail over North America. Emissions are strongest from the Midwestern Corn/Soybean Belt, which accounts for nearly one third of the total North American N 2 O source. The emissions are maximum in spring/early summer, consistent with a nitrogen fertilizer‐driven source, and also show a late winter spike suggestive of freeze‐thaw effects. Interannual variability in emissions across the primary months of fertilizer application is positively correlated to mean precipitation. The estimated N 2 O flux from the Midwestern Corn/Soybean Belt and the more northerly United States/Canadian wheat belt corresponds to 4.2–4.6% and 2.2–3.0%, respectively, of total synthetic + organic N fertilizer applied to those regions. Consideration of nonagricultural sources and additional N inputs from soybean N 2 fixation could reduce the N 2 O yield from the Midwestern Corn/Soybean Belt to ~2.2–2.4% of total N inputs.
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 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 | 0.000 | 0.003 |
| 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".