Immobilization of Arsenic and Manganese in Contaminated Groundwater by Permeable Reactive Barriers Using Zero Valent Iron and Sheep Manure
Bibliographic record
Abstract
A permeable reactive barriers (PRBs) column test was carried out to remove arsenic (As) and manganese (Mn) from groundwater using zero valent iron (ZVI), sheep manure, compost and woodchips as reactive materials. Arsenic was mainly immobilized through sorption and co-precipitation with iron-bearing minerals, and also possibly precipitation as FeAsO4. The presence of sulfate-reducing bacteria (SRB) in the inoculated column was suggested by decrease of sulfate concentrations and increase of δ34S in the effluent. Arsenic was more effective to immobilize in the inoculated than in the sterilized column due to co-precipitation with sulfides formed by reduction of sulfate in addition sorption and/or co-precipitation with carbonates. The Mn was mainly immobilized through adsorption onto compost and ZVI, and partly by precipitation as carbonates. Manganese was more effectively immobilized in the sterilized than in the inoculated column. Since compost is biodegraded, the capability of compost to immobilize Mn2+ decreased in the inoculated column. The result demonstrates that As is more effective to immobilize using mixture of sheep manure with ZVI than only ZVI as reactive materials in PRBs.
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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) | 0.001 | 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 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".