Comparison of the indoor air quality in an office operating with natural or mechanical ventilation using short-term intensive pollutant monitoring
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Building ventilation systems are used to mitigate occupant exposure to airborne pollutants such as particulate matter (PM), carbon dioxide and total volatile organic compounds. Building rating systems such as Leadership in Energy and Environmental Design promote the use of natural ventilation to reduce building energy consumption while improving occupant satisfaction. A number of investigations have attempted to compare indoor air quality (IAQ) between spaces with natural or mechanical ventilation without reaching a consensus regarding quantitative impacts. This work provides direct quantitative comparison of the IAQ of a single office space designed for operation with either mechanical or natural ventilation. Natural ventilation has been shown to maintain pollutant accumulation below current standards governing IAQ but is subject to significant airflow variability. In contrast, the mechanical ventilation was shown to result in lower levels of indoor pollution and provide tight control of pollutant levels. The correlation between natural ventilation air exchange rate and concentration of total volatile organic compounds was −0.66 compared to no significant correlation for mechanical ventilation. Average indoor to outdoor PM 2.5 ratios were found to be 0.87 and 0.5 for natural and mechanical ventilation, respectively. These results show difficulty in controlling indoor pollutants using prescriptive standard ventilation strategies and that performance-based hybrid ventilation systems provide the most flexibility in meeting IAQ needs.
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.
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 it