Remediation of inorganic contaminants and polycyclic aromatic hydrocarbons from soils polluted by municipal solid waste incineration residues
Bibliographic record
Abstract
Three soils polluted by municipal solid waste (MSW) incineration residues and containing various concentrations of Cu, Pb, Sb, Sn and Zn were treated using magnetism, gravity separation (jig and shaking table) and flotation/leaching. The process removed between 18% and 39% of the contaminants present in soil 1, between 31% and 53% of the contaminants present in soil 2 and between 42% and 56% of the contaminants present in soil 3. Polycyclic aromatic hydrocarbons were present only in soil 3, and the process removed 64% of its PAHs total content. Magnetism seemed to be the most efficient technique to remove metals from contaminated soils, followed by gravity separation and finally flotation/leaching. The global efficiency of the process was higher when the initial contaminant concentrations were lower (smaller proportions of MSW incineration residues). The estimated costs of the process, including direct and indirect costs, varied from $82 to $88 per ton of treated soil depending on the proportion of MSW incineration residues mixed with the soil.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".