UV disinfection for reuse applications in North America
Bibliographic record
Abstract
In an effort to conserve and protect limited water resources, the States of Florida and California have actively promoted wastewater reclamation and have implemented comprehensive regulations covering a range of reuse applications. Florida has a semi-tropical climate with heavy summer rains that are lost due to run off and evaporation. Much of California is arid and suffers periodic droughts, low annual rainfall and depleted ground water supplies. The high population density combined with heavy irrigation demands has depleted ground water supplies resulting in salt-water intrusion. During the past decade, Florida reuse sites have increased dramatically from 118 to 444 plants representing a total flow capacity of 826 MGD. California presently has over 250 plants producing 1 BGD with a projected increase of 160 sites over the next 20 years. To prevent the transmission of waterborne diseases, disinfection of reclaimed water is controlled by stringent regulations. Many states regulate wastewater treatment processes, nutrient removal, final effluent quality and disinfection criteria based upon the specific reuse application. As a rule, the resulting effluents have low turbidity and suspended solids. For such effluents, UV technology can economically achieve the most stringent disinfection targets that are required by the States of California and Florida for restricted and unrestricted reuse. This paper compares UV disinfection for wastewater reuse sites in California and Florida and discusses the effect of effluent quality on UV disinfection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".