Contribution of Vehicle Emissions from an Attached Garage to Residential Indoor Air Pollution Levels
Bibliographic record
Abstract
The infiltration of vehicle emissions into a house from the attached garage was studied for 16 homes of differing designs using the same extensively characterized vehicle at each home. Before the in-home measurement program, the cold-start and hot-start tailpipe emissions and hot-soak evaporative emissions from a 1993 Buick Regal were measured using standard vehicle emissions measurement methods. The emissions were chemically characterized for methane, nonmethane hydrocarbons (NMHC), and carbonyl compounds. The in-home measurements occurred over two winter seasons (1997-1998 and 1998-1999) in Ottawa, Ontario, Canada. Samples of indoor air and garage atmosphere were characterized for carbon monoxide, carbon dioxide, methane, NMHC, and carbonyl compounds. During the second year, real-time measurements of carbon, carbon dioxide, and total hydrocarbons were made to determine when and for how long the emissions plume infiltrates the house. Chemical mass balance modeling results using 31 NMHC species suggest that between 9 and 71% of the concentrations measured in the house during the hot-soak test and between 13 and 85% of the concentrations measured in the house during the cold-start test could be attributed to vehicle emissions infiltrating from the garage. In contrast, increases in carbonyl compound concentrations caused by the vehicle were difficult to detect above the already significant levels found in the houses.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".