The Extent of Manure Removal from Storages and Its Impact on Gaseous Emissions
Bibliographic record
Abstract
Manure remaining in storage due to incomplete removal is a source of microbial inoculum that may affect methane (CH 4 ), nitrous oxide (N 2 O), and ammonia (NH 3 ) emissions during subsequent storage. Manure removal was studied by loading fresh manure into outdoor concrete tanks (10.6 m 3 ) that contained previously stored manure (inoculum) at six levels (0, 5, 10, 15, 20, and 25%, with 0% representing an empty tank). Emissions were continuously measured for 6‐mo storage periods (warm and cold seasons) using flow‐through chambers. Fluxes during the warm season (average manure temperature at 80 cm depth, T m = 17°C) were 25 times higher for CH 4 , 20 times higher for N 2 O, and 2.9 times higher for NH 3 compared with the cold season ( T m = 4°C). Cumulative CH 4 emissions increased linearly with the level of added inoculum in the cold season ( r 2 = 0.98). A similar linear increase was observed in the warm season from 0 to 20% inoculum ( r 2 = 0.91), after which a decrease in emissions was observed at 25%. Reducing inoculum from 15 to 5% reduced CH 4 emissions by 26% in the warm season and 45% in the cold season. There was no clear effect of inoculum on N 2 O and NH 3 emissions, suggesting that complete manure storage emptying does not alter their emissions. Core Ideas Manure in storage from incomplete removal is a source of microbial inoculum affecting CH 4 emissions. Cumulative CH 4 emissions increased linearly with the level of added inoculum in the cold season. Cumulative CH 4 emissions increased linearly from 0 to 20% inoculum in the warm season. Reducing inoculum from 15 to 5% reduced CH 4 emissions in warm season by 26% and cold season by 45%.
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 | 0.000 |
| 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".