Exposure to indoor air contaminants in school buildings with and without reported indoor air quality problems
Bibliographic record
Abstract
Reported indoor air quality (IAQ) complaints are common even in relatively new or renovated school buildings in Finland. However, detecting the causes for complaints with commonly used indoor air measurements is difficult. This study presents data on perceived and measured IAQ in six comprehensive school buildings in Finland. The aim of this study was to discover the possible differences of perceived and measured IAQ between schools with reported IAQ complaints and schools without reported IAQ complaints. The initial categorisation of schools with ('problematic schools') and without ('comparison schools') complaints was ensured via a validated indoor climate survey and a recently developed online questionnaire, which were completed by 186 teachers and 1268 students from the six schools. IAQ measurements of physical parameters, gaseous pollutants, particulate matter and bioaerosols were conducted in four problematic school buildings (26 classrooms) and two comparison school buildings (12 classrooms). Using air sampling as well as exhaust air filters and classroom settled dust to detect the presence of elevated concentrations of airborne cultivable microbes and pathogenic, toxigenic and mycoparasitic Trichoderma strains were the most indicative methods in distinguishing problematic schools from comparison schools. Other IAQ-related measurements did not detect clear differences between problematic and comparison schools, as the concentration levels were very low. The results indicate that the complaints reported by occupants could have been related to excess moisture or mould problems that had not been found or repaired. Ventilation pressure condition investigations and simultaneous exhaust and supply air filter dust culture should be addressed precisely in future studies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".