Kinetics of heavy metal desorption from three soils using citric acid, tartaric acid, and EDTA
Bibliographic record
Abstract
Organic acids are relatively new soil heavy metal leaching agents requiring the development of desorption kinetics before being applied. The objective was to determine the heavy metal desorption rates for three heavily contaminated soils (clay loam, loam, and sandy clay loam), treated under optimum conditions with either citric acid, tartaric acid, or EDTA for comparison. A two-rate reaction (fast and slow) model was defined to describe desorption kinetics, where both first order rates were assumed irreversible and reversible, respectively. Experimental data were collected by initially subjecting the three soils to batch experiments at optimum leaching agent level, for up to 36 h. The results indicated that citric acid was a more consistent leaching agent compared to tartaric acid and EDTA, which were efficient mainly in treating the clay loam and the sandy clay loam, respectively. The two-rate reaction model fitted the data but its empirical coefficients need to be defined for each individual soil to be treated. For Pb common to all three experimental soils, k 1 , representing the fast desorption rate, increased with the ratio of metal equivalence fraction: soil CEC. The coefficients k 2 and α 0 , representing the slower rate of desorption and the proportion of Pb involved in this slow rate, respectively, increased with the mass of Pb held by the oxide and organic matter fractions. The coefficient m 1 , related to the relative rate of the backward reaction from the slow to the fast, varied according to the mass of Pb held by the exchangeable site. Despite the empirical values associated with the kinetics coefficients, their correspondence with individual processes indicate that organic acid remediation can be modeled using the two rate kinetic equation proposed in this project.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".