Henry’s Law Constants and Indoor Partitioning of Microbial Volatile Organic Compounds
Bibliographic record
Abstract
Microbial volatile organic compounds (MVOCs) play an essential role in many environmental fields, such as indoor air quality. Long-term exposure to odorous and toxic MVOCs can negatively affect the health of occupants. Recently, the involvement of surface reservoirs in indoor chemistry has been realized, which signifies the importance of the phase partitioning of volatile organic pollutants. However, reliable partition coefficients of many MVOCs are currently lacking. Equilibrium partition coefficients, such as Henry’s law constant, H, are crucial for understanding the environmental behavior of chemicals. This study aims to experimentally determine the H values and their temperature dependence for key MVOCs under temperature relevant to the indoor environment. The H values were determined with the inert gas-stripping (IGS) method and variable phase ratio headspace (VPR-HS) technique. A two-dimensional partitioning model was applied to predict the indoor phase distribution of MVOCs and potential exposure pathways to the residences. The findings show that the MVOCs are likely distributed between the gas and weakly polar (e.g., organic-rich) reservoirs indoors. Temperature and the volume of reservoirs can sensitively affect indoor partitioning. Our results give a more comprehensive view of indoor chemical partitioning and exposure.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".