Sorption of Heavy Metals by Ferralic-Arenosol and Vertic-Luvisol: A Comparative Isothermal Study
Bibliographic record
Abstract
Modeling of sorption data is essential for characterizing retention of heavy metals by the soil matrices as well as to predict the fate of heavy metals in the environment. We carried out a study to evaluate adsorption characteristics of metallic ions (Cr3+, Pb2+ and Cu2+) as sole sorbates as well as in coexistence onto clay extracts of Vertic-Luvisol and Ferralic-Arenosol, the generally under-researched yet wide-spread semi-arid soils. Additionally, sorption kinetics of these heavy metals was evaluated in these soils. Equilibrium sorption data for both non-competitive and competitive metal systems were found to obey the Langmuir isotherm. Overall metal loading capacity was higher in Vertic-Luvisol than Ferralic-Arenosol whereas metal-wise affinity to binding sites favoured sorption of Cr3+ over Pb2+ and Cu2+ in that order. Contrary to the hypothesis of this study, the preferential sorption process was found to be driven by cationic properties as opposed to soil properties. Adsorption of metallic ions onto soils was significantly reduced in competitive systems than non-competitive systems, a phenomenon attributable to the antagonistic effects of coexisting species. Cr3+ suppressed sorption of Pb2+ and Cu2+ on both soils as validated by the competitive adsorption capacity ratios which were < 1 in all instances where Cr3+ coexisted with either one of Pb2+ or Cu2+. The adsorption kinetics of metal ions in both soils followed the pseudo-second-order rate law, suggesting chemical sorption as the rate-limiting step of the adsorption process.
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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 | 0.000 |
| 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 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".