Redox-mediated changes in the release dynamics of lead (Pb) and bacterial community composition in a biochar amended soil contaminated with metal halide perovskite solar panel waste
Bibliographic record
Abstract
This study explored the redox-mediated changes in a lead (Pb) contaminated soil (900 mg/kg) due to the addition of solar cell powder (SC) and investigated the impact of biochar derived from soft wood pellet (SWP) and oil seed rape straw (OSR) (5% w /w) on Pb immobilization using an automated biogeochemical microcosm system. The redox potential (Eh) of the untreated (control; SC) and biochar treated soils (SC + SWP and SC + OSR) ranged from −151 mV to +493 mV. In SC, the dissolved Pb concentrations were higher under oxic (up to 2.29 mg L −1 ) conditions than reducing (0.13 mg L −1 ) conditions. The addition of SWP and OSR to soil immobilized Pb, decreased dissolved concentration, which could be possibly due to the increase of pH, co-precipitation of Pb with Fe Mn (hydro)oxides and pyromorphite, and complexation with biochar surface functional groups. The ability and efficiency of OSR for Pb immobilization were higher than SWP, owing to the higher pH and density of surface functional groups of OSR than SWP. Biochar enhanced the relative abundance of Proteobacteria irrespective of Eh changes, while the relative abundance of Bacteroidota increased under oxidizing conditions. Overall, we found that both OSR and SWP immobilized Pb in solar panel waste contaminated soil under both oxidizing and reducing redox conditions which may mitigate the potential risk of Pb contamination.
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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) | 0.000 | 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 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".