Methodology for estimating emissions from agriculture in the Netherlands : Calculations of CH4, NH3, N2O, NOx, NMVOC, PM10, PM2.5 and CO2 with the National Emission Model for Agriculture (NEMA), Update 2019
Bibliographic record
Abstract
The National Emission Model for Agriculture (NEMA) is used to calculate emissions to air from agricultural activities in the Netherlands on a national scale. Emissions of ammonia (NH3) and other N compounds (NOx and N2O) are calculated for animal housing, manure storage, manure application and grazing using a flow model for total ammoniacal nitrogen (TAN). Emissions from the application of inorganic N fertilizer, compost and sewage sludge, cultivation of organic soils, crop residues, and ripening of crops are calculated as well. The NEMA is also used to estimate emissions of methane (CH4) from enteric fermentation and manure management, nonmethane volatile organic compounds (NMVOC) and particulate matter (PM) from manure management and agricultural soils, as well as for carbon dioxide (CO2) from liming. Emissions are calculated in accordance with the criteria of international guidelines and reported in an annual Informative Inventory Report (IIR; for air pollutants) and National Inventory Report (NIR; for greenhouse gases). This methodology report provides an outline of and describes the background to the calculation of emissions according to the NEMA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".