Moisture Effects on Nitrogen Availability in Municipal Biosolids from End-of-Life Municipal Lagoons
Bibliographic record
Abstract
Nitrogen (N) availability affects plant biomass yield and, hence, phytoextraction of contaminants during phytoremediation of end-of-life municipal lagoons. End-of-life lagoons are characterized by fluctuating moisture conditions, but the effects on biosolid N dynamics have not been adequately characterized. This 130-d laboratory incubation investigated effects of three moisture levels (30, 60, and 90% water-filled pore space [WFPS]) on N mineralization (N) in biosolids from a primary (PB) and a secondary (SB) municipal lagoon cell. Results showed a net increase in N with time at 60% WFPS and a net decrease at 90% WFPS in PB, while N at 30% WFPS did not change significantly. Moisture level and incubation time had no significant effect on N in SB. Nitrogen mineralization rate in PB followed three-half-order kinetics. Potentially mineralizable N (N) in PB was significantly greater at 60% WFPS (222 mg kg) than at 30% WFPS (30 mg kg), but rate constants did not differ significantly between the moisture levels. Nitrogen mineralization in SB followed first-order kinetics, with N significantly greater at 60% WFPS (68.4 mg kg) and 90% WFPS (94.1 mg kg) than at 30% WFPS (32 mg kg). Low N in SB suggests high-N-demanding plants may eventually have limited effectiveness to remediate biosolids in the secondary cell. While high N in PB would provide sufficient N to support high biomass yield, phytoextraction potential is reduced under dry and near-saturated conditions. These results have important implications on the management of moisture during phytoextraction of contaminants in end-of-life municipal lagoons.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".