Copper Adsorption with Pb and Cd in Sand-Bentonite Liners Under Various pHs. Part I. Effect on Total Adsorption
Bibliographic record
Abstract
Municipal solid wastes could be segregated based on their specific heavy metal content and disposing of them in separate landfill cells. Therefore, the objective of the project was to investigate the interaction between copper (Cu) and either lead (Pb) or cadmium (Cd) using equilibrium batch adsorption experiments. A first test consisted of soaking three types of sand-bentonite liner samples (0, 5, and 10% bentonite) with a respective cation exchange capacities (CEC) of 2, 6.4, and 10.8 cmol(+)/kg in one of nine solutions consisting of a combination of three pH levels (3.7, 5.5, and 7.5) and three heavy metal solutions (Cu alone, Cu with Cd, Cu with Pb) each offering a respective heavy metal equivalence of 1, 2, and 2cmol(+)/kg of liner. A second test set consisted in soaking 5% bentonite liner samples in three solutions at a pH of 3.7, with either Cu alone or with Pb or Cd, at 4.8 cmol(+)/kg of liner. For up to 14 days, duplicate samples were sacrificed to determine the supernatant Cu level and pH. The results indicated that under acidic conditions (pH< 6.5), the liner bentonite content, the solution pH and the presence of Pb or Cd significantly influenced Cu adsorption. Lead, and to a lesser extent Cd, competed with Cu for adsorption sites. Under alkaline conditions (pH> 6.5), carbonate and hydroxyl precipitation governed and masked the Pb and Cd competition. Thus, at low pH, limiting the presence of Pb in landfill leachate can improve Cu adsorption.
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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".