Photocatalytic pretreatment of contaminated groundwater for biological nitrification enhancement
Bibliographic record
Abstract
Abstract The sequential photocatalytic/biological treatment of a contaminated groundwater from a local industrial site was studied. The ground water contained approximately 100 mg dm−3 ammonia, as well as mg dm−3 levels of nitrification‐inhibiting organics such as chlorobenzene. An existing treatment system uses carbon adsorption pretreatment to remove the nitrification inhibitors before the water is treated in a biological nitrification system. Photocatalysis, using a corrugated plate photoreactor, was studied as an alternative to the carbon adsorption system for inhibitor removal. Photocatalytic pretreatment was found to significantly enhance the extent of biological nitrification. An optimal pretreatment time appeared to exist, since further pretreatment resulted in accumulation of nitrite. Although further study is required, there appears to be a potential for using photocatalysis to remove inhibitors from biological nitrification systems. © 2002 Society of Chemical Industry
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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".