Effect of C:N Ratio on Microbial Activity and N Retention: Bench-scale Study Using Pulp and Paper Biosolids
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Bibliographic record
Abstract
The effect of C:N ratio on the performance of bench-scale composting systems treating pulp and paper biosolids was investigated. The biosolids used were obtained from the Pine Falls Paper Company located in Manitoba. The biosolids, on a wet basis, consisted of 41% primary biosolids, 21% secondary biosolids, and 39% deinking plant sludge. The biosolids were mixed with bark to achieve an initial moisture content of 60%, resulting in a recipe consisting of 1.09 kg of bark per kg of biosolids on a dry basis. Four reactors (treatments) were run with C:N ratios of 107 (control; no N supplement), 55, 29, and 18. Each treatment was replicated three times. Sulfur coated urea was used as the N supplement. Parameters monitored included C:N ratio, N recovery, material compaction, temperature, qualitative odor observations, and volatile solids reduction. The relative microbial activity was observed in-directly using volatile solids removal and the relative heat generation data. The data showed a strong negative linear relationship between C:N ratio and relative heat generation (r2=0.98) and between C:N ratio and volatile solids removal (r2=0.84 for all four treatments; and r2=1.0 for C:N = 29 to 107). The data also showed a strong nonlinear relation between N retention and C:N ratio (% retention = 101(1-0.92C:N); r2 = 0.71; n = 12). Qualitative odor observations and N losses suggested that a C:N ratio of 18 was too low, therefore a performance comparison was made between the C:N-107 and the C:N-29 treatments. It was observed that the mean volatile solids removal was 28.6% higher in the C:N-29 treatments as compared to the C:N-107 control. While this difference is significant from a bench-scale perspective, the authors question the practical significance of the difference and recommend further investigation.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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