Effects of EDTA on adsorption of Cd(II) and Pb(II) by low-permeability soil minerals and on their microscopic characteristics
Bibliographic record
Abstract
Abstract Background Ethylenediaminetetraacetic acid (EDTA) can serve as a washing agent in the remediation of low-permeability layers contaminated by heavy metals (HMs). Therefore, batch adsorption experiments, where quartz sands (SM1) and mineral mixtures (SM2) were used as low-permeability soil minerals (SMs), were implemented to explore the effects of different EDTA concentrations, pH and exogenous chemicals on the HM-SM-EDTA adsorption system. Changes in microscopic characterizes of SMs were determined by instrument analysis to investigate the mechanisms.Results As the EDTA concentration increased gradually, it gradually cut down the maximum Cd adsorption capacities of SM1 and SM2 from approximately 135 to 55 mg/kg and 2,660 to 1,453 mg/kg; and the maximum Pb adsorption capacities of SM1 and SM2 were reduced from 660 to 306 mg/kg and 19,677 to 19,262 mg/kg, respectively. When the mole ratio (MR = moles of HM ions / sum of moles of HM ions and EDTA) was closer to 0.5, the effect of EDTA was more effective; and Freundlich isotherm model fitted better to the data. It took 5 to 10 min for EDTA to begin taking its effect. EDTA worked well at pH below 7.0 and 4.0 for Cd and Pb, respectively. Low-molecular-weight organic acids (LMWOAs) affected the system mainly by bridging, complexation, adsorption site competition and reductive dissolution. Cu 2+ , Fe 2+ ions could greatly increase the Cd and Pb adsorption on SM2. There were feature changes in mineral particles including attachment of EDTA and microparticles, agglomeration, connection and smoother surfaces, making the specific surface area decrease from 16.73 to 12.59 m 2 /g.Conclusion All findings indicated that EDTA could effectively and economically reduce the HM adsorption capacity of SMs at the reasonable MR value, contact time and pH. The extent of the effects of LMWOAs and exogenous metal ions on the HM-SM-EDTA system depended on the synthesis of diverse effects and the selectivity of EDTA, respectively. EDTA reduced the HM adsorption capacity of SMs not only by complexation with HM ions, but also decreasing SSA and blocking active sites. Hence, the acquired insight from the presented study can help to promote the remediation of contaminated soil and groundwater.
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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 | 0.001 |
| 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 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".