Removal of Lead from a Calcareous Soil by Chloride Complexation
Bibliographic record
Abstract
Abstract Remediation of a lead-contaminated calcareous soil using NaCl solutions was examined. The removal of Pb from a coarser fraction of the soil was found to be 83% after three successive extractions at a NaCl concentration of 8 M, whereas an average of 9% of the calcium was removed. Multibatch extractions of Pb from finer soil containing a higher level of Pb were also performed. The removal of Pb from this soil after six successive extractions with 8 M NaCl was found to be 93%. The removal of Pb increased with time in a batch test and approached 80% after 90 h. It was found that the data were adequately described by a first-order rate, and hence it is believed that a single reaction mechanism controlled the release of Pb (i.e., from carbonate bound or exchangeable Pb fractions in the soil). Increasing removal of Pb was found as the volume of water added was increased as the mass of NaCl in solution remained constant. The removal of Pb from the leachate was found to be 90%, 99.7%, and 35% with lime (25.20 g/L), sodium carbonate (4.48 g/L), and calcium carbonate (82.0 g/L) addition, respectively. In the case of sodium carbonate, the removal of Pb was further improved when the pH was adjusted to 8.2. The recycling of free chloride that was generated from leachate resulted in 91% removal of Pb from the soil (particle size < 4.75 mm) after six recycles. Keywords: Soil washingextractionkineticsprecipitationlead removalcalcareous.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".