Tetrasodium iminodisuccinate as a biodegradable complexing agent for remediating metal‐contaminated soil
Bibliographic record
Abstract
Abstract Soil washing is a rapid and cost‐effective method to treat contaminated soils. However, conventional chelating agents exhibit adverse environmental effects. Tetrasodium iminodisuccinate (IDS) is a new type of amino carboxyl chelating agent, which exhibits strong chelating performance, high solubility in aqueous solution, and is environmentally friendly in soil. In this study, batch washing of Cu, Pb, and Cd removal from simulated contaminated soil and real project‐scale soil of a Pb‐polluted field was explored to evaluate the application of IDS in the remediation of potentially toxic metal‐contaminated soil. The effects of the IDS solution pH, concentration, reaction temperature, liquid/soil (L/S) ratio, number of washing cycles, and contact duration were investigated, and the optimal conditions were identified as follows: pH 7, IDS concentration 10 mmol · L−1, L/S ratio 10:1; 25°C; and 24 h. Almost 80.6% of Cu, 71.1% of Pb, and 59.1% of Cd were removed from simulated contaminated soil under optimal conditions. The primary potentially toxic metal removal mechanisms were analyzed by potentially toxic metal state detection before and after IDS washing. Real project‐scale Pb‐polluted field washing was demonstrated under the same conditions in addition to the IDS concentration of 4.5 mmol · L−1. The Pb concentration was reduced from 460 to 86.8 mg · kg−1 (mean value), which is below the threshold identified in the ‘Risk Assessment of Soil Environmental Health in Shanghai’ (Residential Area, 140 mg · kg−1). The results confirm that IDS is a promising soil washing agent that can effectively remove potentially toxic metals from contaminated soil and minimize environmental risks.
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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) | 0.000 | 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".