Collimated beam tests: their limitations for assessing wastewater disinfectability by UV, and a proposal for an additional evaluation parameter
Bibliographic record
Abstract
This study examines the effects of the liquid matrix on the disinfectability of waters and wastewaters by ultraviolet (UV) light. Collimated beam (CB) curves, which are routinely used to assess disinfectability, and to provide the average fluence (in microjoules per square centimetre) necessary to reach a target effluent microbial count, eliminate the effect of UV transmission (UVT), using the Morowitz equation. However, this calculation has the consequence of masking the differences between samples of differing UVT, which may indeed require the same average UV fluence to reach the target, but require considerably different energy input and number of lamps in the full-scale system. An additional parameter, called herein an "energy factor'', is proposed in addition to the CB curve to evaluate disinfectability. The energy factor is the applied UV energy per unit volume divided by the average fluence experienced by the microbes in the liquid matrix. Synthetic data and actual CB curves from various types of samples are used to assess the effects of UVT, the depth of sample in the petri dish, the slope of the CB curve, the target microbial count, and, finally, the original microbial count on the energy factor. Key words: ultraviolet disinfection, collimated beam, energy factor.
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 | 0.026 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".