The Effect of Phosphogypsum on Greenhouse Gas Emissions during Cattle Manure Composting
Why this work is in the frame
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Bibliographic record
Abstract
Phosphogypsum (PG), a by-product of the phosphate fertilizer industry, reduces N losses when added to composting livestock manure, but its impact on greenhouse gas emissions is unclear. The objective of this research was to assess the effects of PG addition on greenhouse gas emissions during cattle feedlot manure composting. Sand was used as a filler material for comparison. The seven treatments were PG10, PG20, PG30, S10, S20, and S30, representing the rate of PG or sand addition at 10, 20, or 30% of manure dry weight and a check treatment (no PG or sand) with three replications. The manure treatments were composted in open windrows and turned five times during a 134-d period. Addition of PG significantly increased electrical conductivity (EC) and decreased pH in the final compost. Total carbon (TC), total nitrogen (TN), and mineral nitrogen contents in the final composted product were not affected by the addition of PG or sand. From 40 to 54% of initial TC was lost during composting, mostly as CO(2), with CH(4) accounting for <14%. The addition of PG significantly reduced CH(4) emissions, which decreased exponentially with the compost total sulfur (TS) content. The emission of N(2)O accounted for <0.2% of initial TN in the manure, increasing as compost pH decreased from alkaline to near neutral. Based on the total greenhouse gas budget, PG addition reduced greenhouse gas emissions (CO(2)-C equivalent) during composting of livestock manure by at least 58%, primarily due to reduced CH(4) emission.
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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 | 0.000 |
| 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 it