Pros and Cons of Biochar to Soil Potentially Toxic Element Mobilization and Phytoavailability: Environmental Implications
Bibliographic record
Abstract
Abstract While the potential of biochar (BC) to immobilize potentially toxic elements (PTEs) in contaminated soils has been studied and reviewed, no review has focused on the potential use of BC for enhancing the phytoremediation efficacy of PTE-contaminated soils. Consequently, the overarching purpose in this study is to critically review the effects of BC on the mobilization, phytoextraction, phytostabilization, and bioremediation of PTEs in contaminated soils. Potential mechanisms of the interactions between BC and PTEs in soils are also reviewed in detail. We discuss the promises and challenges of various approaches, including potential environmental implications, of BC application to PTE-contaminated soils. The properties of BC (e.g., surface functional groups, mineral content, ionic content, and π-electrons) govern its impact on the (im)mobilization of PTEs, which is complex and highly element-specific. This review demonstrates the contrary effects of BC on PTE mobilization and highlights possible opportunities for using BC as a mobilizing agent for enhancing phytoremediation of PTEs-contaminated soils.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".