Lead Speciation and Bioavailability in Apatite-Amended Sediments
Bibliographic record
Abstract
The in situ sequestration of lead (Pb) in sediment with a phosphate amendment was investigated by Pb speciation and bioavailability. Sediment Pb in preamendment samples was identified as galena (PbS) with trace amounts of absorbed Pb. Sediment exposed to atmospheric conditions underwent conversion to hydrocerussite and anglesite. Sediments mixed with apatite exhibited limited conversion to pyromorphite, the hypothesized end product. Conversion of PbS to pyromorphite is inhibited under reducing conditions, and pyromorphite formation appears limited to reaction with pore water Pb and PbS oxidation products. Porewater Pb values were decreased by 94% or more when sediment was amended with apatite. The acute toxicity of the sediment Pb was evaluated with Hyalella azteca and bioaccumulation of Pb with Lumbriculus variegatus . The growth of H. azteca may be mildly inhibited in contaminated sediment, with apatite-amended sediments exhibiting on average a higher growth weight by approximately 20%. The bioaccumulation of Pb in L. variegatus tissue decreased with increased phosphate loading in contaminated sediment. The study indicates limited effectiveness of apatite in sequestering Pb if present as PbS under reducing conditions, but sequestration of porewater Pb and stabilization of near-surface sediment may be a feasible and alternative approach to decreasing potential toxicity of Pb.
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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 | 0.001 | 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".