Volatile organic compound (VOC) adsorption on material: influence of gas phase concentration, relative humidity and VOC type
Bibliographic record
Abstract
UNLABELLED: This paper presents the results of a factorial experiment design analysis to investigate volatile organic compounds (VOC) adsorption on a ceiling tile. The impacts of three factors, VOC gas phase concentration, relative humidity, and VOC type, as single parameters and as a combination, on adsorption have been investigated. Cyclohexane, toluene, ethyl acetate, isopropyl alcohol and methanol were the five VOCs used in this study. A factor significant level was determined through evaluating its F value and comparing it with the critical value of F distribution at 95% confidence level. It was found that: (i) neither the relative humidity and gas phase concentration nor any interaction effect between them had significant impacts on toluene adsorption on the ceiling tile; (ii) the adsorption isotherm appeared to be linear for the non-polar compounds and non-linear for the semi-polar and polar compounds; (iii) no significant impact of relative humidity on adsorption was observed for most VOC compounds except for methanol; and (iv) the ceiling tile had the highest adsorption capacity toward the polar compounds, followed by the aromatic compounds and aliphatic compounds. In addition, the statistical analysis regarding the experimental results of toluene as a single compound or as a part of a mixture showed that toluene adsorption capacity on the ceiling tile as a single compound was higher than as a part of a mixture. PRACTICAL IMPLICATIONS: Building materials and furnishings may act as source and sink of VOCs in the indoor environment. In this study, a factorial experiment design analysis technique was used to show the impact of three factors, VOC gas phase concentration, relative humidity, and VOC type, as single parameters and as a combination, on the adsorption process (sink effect). The aim was to better understand the interaction between these parameters and to verify the common assumptions made in the model development and measurement of indoor air quality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".