Comparison of the indoor air quality in an office operating with natural or mechanical ventilation using short-term intensive pollutant monitoring
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.
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 | 0.000 | 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) | 0.001 | 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".