Effects of plant-biochar interaction on the performance of a landfill cover system: field monitoring and numerical modelling
Bibliographic record
Abstract
Biochar has been used as a sustainable amendment to moderate the risks of climate change to plant and soil management. A 3-year field monitoring was conducted at Shenzhen Xiaping landfill to evaluate the performance of a three-layer landfill cover using plant and biochar. Coarse-grained completely decomposed granites (CDG) amended with peanut shell biochar at 0%, 5% and 10% (m 3 /m 3 ) were used for the top layers of three grass plots (10 m×5 m each), respectively. Coarse recycled concrete and fine-grained CDG were used for the middle and bottom layers of all plots. Numerical simulation was conducted to back analyse the monitored results. The results show that the grassed cover with biochar can retain over four times higher negative pore-water pressure than that without biochar. During the monitoring, over 62% of total rainfall was evapotranspirated from biochar amended covers, which was 10% larger than the cover without biochar. With biochar amendments, the infiltration amount was reduced by 13%, but water storage was improved by up to 15%. The measured and computed percolation of the grassed covers with 0%, 5% and 10% biochar meet the recommended criterion by USEPA. It is recommended that 5% biochar content is sufficient to minimise water percolation.
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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 | 0.000 | 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".