Removal of geosmin and 2-methylisoborneol by biological filtration
Bibliographic record
Abstract
The quality of drinking water is sometimes diminished by the presence of certain compounds that can impart particular tastes or odours. One of the most common and problematic types of taste and odour is the earthy/musty odour produced by geosmin (trans-1, 10-dimethyl-trans-9-decalol) and MIB (2-methylisoborneol). Taste and odour treatment processes including powdered activated carbon, and oxidation using chlorine, chloramines, potassium permanganate, and sometimes even ozone are largely ineffective for reducing these compounds to below their odour threshold concentration levels. Ozonation followed by biological filtration, however, has the potential to provide effective treatment. Ozone provides partial removal of geosmin and MIB but also creates other compounds more amenable to biodegradation and potentially undesirable biological instability. Subsequent biofiltration can remove residual geosmin and MIB in addition to removing these other biodegradable compounds. Bench scale experiments were conducted using two parallel filter columns containing fresh and exhausted granular activated carbon (GAC) media and sand. Source water consisted of dechlorinated tap water to which geosmin and MIB were added, as well as, a cocktail of easily biodegradable organic matter (i.e. typical ozonation by-products) in order to simulate water that had been subjected to ozonation prior to filtration. Using fresh GAC, total removals of geosmin ranged from 76 to 100% and total MIB removals ranged from 47% to 100%. The exhausted GAC initially removed less geosmin and MIB but removals increased over time. Overall the results of these experiments are encouraging for the use of biofiltration following ozonation as a means of geosmin and MIB removal. These results provide important information with respect to the role biofilters play during their startup phase in the reduction of these particular compounds. In addition, the results demonstrate the potential biofilters have in responding to transient geosmin and MIB episodes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".