A new technology for the treatment of mercury contaminated water and soils
Bibliographic record
Abstract
A new technology has been developed for the treatment of contaminated water and soils with lignin derivatives. It has been demonstrated that this technology can be used in the process of removal of high levels of mercury from water, and in the immobilization of leachable mercury in contaminated soils. Lignin derivatives contain an abundance of oxygen-containing functional groups such as phenolic, carboxyl, sulfonyl, alcoholic and enolic structures, which will form lignin-metal macromolecular complexes with high stability through ionic and coordinate covalent bonding. This feature is the basis for the application of lignin derivatives in the removal of metal contaminants from water and in the immobilization of leachable metal in soils or sediments. Tests have confirmed that lignin derivatives are capable of combining with a variety of metal ions including chromium, copper, lead, zinc, mercury, nickel and aluminum. In the new water treatment process, lignin derivatives are dissolved in mercury contaminated water to complex mercury in an exceptionally stable form of a lignin-mercury colloid. The lignin-mercury colloid is then coagulated through the addition of a flocculating agent such as ferric chloride. Under optimized conditions, a dean effluent is produced with a residual mercury level of less than 1 microg l(-1), together with a ferric sludge that is not leachable by TCLP, EPA Method 1311. In the new soil stabilization process, a new solid adsorbent of ferric-lignin is blended with mercury contaminated soil. This solid adsorbent can stabilize the soil by complexing with mercury and, thereby, greatly reduce the TCLP mercury of 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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".