Addressing uncertainty in mouthing-mediated ingestion of chemicals on indoor surfaces, objects, and dust
Bibliographic record
Abstract
In indoor environments, humans ingest chemicals present as surface residues and bound to settled particles (dust), through mouthing hands (hand-to-mouth transfer) and objects (object-to-mouth transfer). Here, we introduce a novel modeling approach in support of systematic investigation into the mouthing-mediated ingestion of chemicals present in indoor environments. This model explicitly considers the indoor dynamics of dust and chemicals, building on mechanistic links with physicochemical properties of chemicals, features of the indoor environment, and human activity patterns. The evaluation of this model demonstrates that it satisfactorily reproduces chemical hand loadings and exposure data reported in the literature. We then use the evaluated model to investigate the response of mouthing-mediated ingestion to chemical partitioning between the gas phase and solid phases, expressed as the octanol–air partition coefficient (KOA). Assuming a unit emission rate to the indoor environment, we find that low-volatility chemicals (with a KOA greater than 109) are more efficiently enriched in hand skin, resulting in higher mouthing-mediated ingestion than other compounds. For individuals living in a room with a typical level of dustiness, more than half of the chemical mass found in their hands comes from dust transfer, whereas more than half of the chemical mass ingested is the fraction present as residues on hands. We also use the new model to explore how the mouthing-mediated ingestion of chemicals is dependent on factors describing the indoor environment and human behavior. The model predicts that less frequent cleaning leads to higher accumulation of dust on indoor surfaces, thereby transferring more chemicals to hands and mouth in each contact. Introducing more dust into the room, but maintaining the same cleanup frequency, increases the dustiness of indoor surfaces, which promotes the transfer of relatively volatile chemicals (with a KOA lower than 109) to hands and mouth but decreases the transfer of chemicals with low volatility. More frequent hand contact with indoor surfaces increases both the hand loading and mouthing-mediated ingestion of chemicals, but the increases are more remarkable for adults than children because the higher surface contact frequency of children “saturates” hand loadings. An increase in handwashing frequency lowers the hand loading and mouthing-mediated ingestion of chemicals and this mitigating process is more prominent for relatively volatile chemicals. The new evaluated modeling approach can facilitate the prediction of mouthing-mediated ingestion for various age groups and the model predictions can be used to aid future fate and (bio)monitoring studies focusing on indoor contamination.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".