Comparative performance and environmental evaluation of 222 and 254 nm UV lamps for in-duct air disinfection in building systems
Bibliographic record
Abstract
UV germicidal irradiance has gained significant popularity as a disinfection technology since the COVID-19 pandemic. Challenges remain in accurately characterizing the in-duct irradiance distribution of UVC lamps under varying air parameters, introducing uncertainty in exposure and efficiency estimations. This study experimentally characterizes irradiance of 222 and 254 nm UV lamps in a conduit using a 9-point average method. Irradiance measurements are recorded from five sides at each point, and a correction factor is proposed to account for spectrometer detection angle overlaps. Results indicate that the 254 nm lamp output increases by 18% with an air temperature rise from 25°C to 35°C but decreases by 21% as air velocity rises from 0.5 to 2 m/s. In contrast, the 222 nm lamp shows negligible sensitivity to changes in air temperature or velocity. Relative humidity variations (25%–60%) did not significantly affect either lamp’s output. In addition, the 222 nm lamp generates minimal ozone and total volatile organic compounds (TVOCs) during operation in stagnant air. The particle tracking simulation results revealed higher velocity fluctuations in proximity to the installed 222 nm lamp than the 254 nm lamp due to the larger lamp geometries. Experimental UVGI efficacy tests targeting airborne E . coli inactivation, combined with comprehensive life cycle analysis, demonstrated that the 254 nm lamp offers superior cost-effectiveness and sustainability for continuous in-duct air disinfection. These findings provide practical insights for optimizing UVC systems for air disinfection applications.
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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 | 0.001 | 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) | 0.000 | 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 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".