Development of a Biochar-Based Substrate Added with Nitrogen from a Mining Effluent for the Production of Picea mariana Seedlings
Bibliographic record
Abstract
Ammoniacal nitrogen (N-NH3) is one of the pollutants that has adverse effects on the environment and is present in most effluents generated by mining operations. Therefore, mining companies must manage it to keep it below the regulated discharge criteria to avoid environmental contamination. In this context, the present study aims to valorize N-NH3 in the form of ammonium sulphate ((NH4)2SO4) for the manufacture of biochar pellets used as growth substrates for the production of forest seedlings. The biochar was first produced by fast pyrolysis, at 320 °C, and different recipes of pellets were then prepared to evaluate their hardness, binder type and content, humidity and durability. The optimal granule chosen was composed of biochar, corn starch and canola oil. Six combinations of different compositions were then prepared as substrates for black spruce growth: (1) Peat (P); (2) Peat and bulk biochar (PB); (3) Peat and bulk biochar impregnated with ammonium sulfate (PBAS); (4) Peat and biochar pellets impregnated with water (PBPeW); (5) Peat and biochar pellets impregnated with an ammonium sulfate solution (PBPeAS); (6) Peat, biochar pellets impregnated with ammonium sulfate and perlite (PBPeASPer). The effects of these substrates on the growth of black spruce seedlings, as well as fertilizer leaching, were measured. The results show that seedling biomass is equivalent to the control for the granular treatment, but higher biomass was obtained with bulk biochar (PB). This shows that a quarter of peat could be replaced by biochar to obtain similar or even better results of biomass yield and, consequently, solve part of the supply issue. As to plant nutrition, no tendency was observed for the experiments apart from the higher proportion of Ca in spruce needles. The prepared biochar-based pellet substrate appears to not only be advantageous for spruce production but also for other uses such as golf courses, forestry producers and horticultural nurseries using conventional fertilizers and peat as growing media. In addition, these approaches could help the Abitibi-Témiscamingue region in Québec, Canada to build a local circular economy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".