Effect Of Environmental Factors On Photoreactivation Of Microorganisms Under Indoor Conditions
Bibliographic record
Abstract
Ultraviolet (UV) disinfection causes damage to the DNA or RNA of microorganisms, but many microorganisms can repair this damage after exposure to near-UV or visible wavelengths (310–480 nm) by a mechanism called photoreactivation. Photoreactivation is gaining more attention because it can reduce the efficiency of UV disinfection of wastewater several hours after treatment. The focus of many photoreactivation research activities on the single species has caused a considerable lack in knowledge about complex natural communities of microorganisms and their response to UV treatment. In this research, photoreactivation experiments were carried out on the influent of the UV disinfection unit at a municipal wastewater treatment plant (WWTP) in Edmonton, Alberta after exposure to a Medium-Pressure (MP) UV lamp system to evaluate the effect of environmental factors on photoreactivation of microorganisms in the actual municipal wastewater. The effect of reactivation fluence, temperature, and river water on photoreactivation of total coliforms was examined under indoor conditions. The results showed that higher effective reactivation fluence values (up to 20 J/cm<sup>2</sup>) and higher temperatures (up to 25 °C) increased the photoreactivation of total coliforms. However, increasing the percentage of river in the mixtures of the effluent and river water decreased the photoreactivation of the mixtures. The results of this research can help the municipal wastewater treatment industry to examine the environmental effects of discharging their effluents into receiving waters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.009 | 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 teacher head, 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".