Influence of residence time on the particle-gas partitioning of phthalates onto airborne inorganic particle
Bibliographic record
Abstract
In indoor environments, the presence of particulate matter promotes SVOCs volatilization, increasing their overall concentration in the air. This effect arises from the partition of SVOCs between the gas and particulate phases. The particle-gas partition ratio ( K p ) is a critical parameter influencing the fate, transport, and human exposure to indoor SVOCs. Air exchange rate (AER) is a pivotal factor in closed spaces as it regulates the residence time of airborne SVOCs in an indoor environment. It has been reported that AER (or residence time) can affect particle-gas partitioning behavior for organic particles when equilibrium between gas and particle phases is not reached; however, its effect on inorganic particles has not been thoroughly investigated. This study develops an experimental procedure to measure K p of Di-n-butyl phthalate (DnBP) and Diethyl phthalate (DEP) with inorganic sodium chloride (NaCl) particles. Results shows that DnBP had higher K p values than DEP. Positive correlation of K p values and mixing time was observed. These findings are consistent with model predictions. Further experiments were carried out to study the impact of AER on K p , and the results shown that higher air exchange rates (lower residence time) result in lower particle-phase concentrations of SVOCs due to increased dilution and reduced interaction time with particles. These findings have important implications for indoor air quality assessments, highlighting the influence of ventilation strategies on SVOCs behavior in indoor environments.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.001 | 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 teacher head, 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".