Indoor Concentrations and Sources of Semi-Volatile Organic Compounds in the Context of Vulnerable Populations
Bibliographic record
Abstract
People are widely exposed to semi-volatile organic compounds (SVOCs) in indoor environments, where concentrations are typically higher than outdoors. Some SVOCs, such as pesticides, ortho-phthalate (PAEs) plasticizers, organophosphate esters (OPEs) used as flame retardants and plasticizers, as well as benzophenones (BPs), salicylates (SALs), and phenolic benzotriazoles (PBs) used as UV filters, are known or suspected to have health impacts with various indoor sources, including building materials and consumer products. Indoor exposure to SVOCs is a significant concern, particularly in North America, where individuals spend over 90% of their time indoors. This thesis aims to enhance our understanding of residential exposure to selected SVOCs from indoor sources in context of vulnerable populations, notably residents of low-income social housing and young children in sleeping microenvironments (SME).Particle-bound concentrations of legacy and current use pesticides quantitatively estimated in low-income social housing in Toronto, Canada, using portable air cleaners equipped with quantitative filter forensics (QFF). Elevated levels of legacy and current use pesticides were measured at levels higher than previously reported, despite long after restrictions. Apart from intentional use of pesticides to control pests, through pest eradication programs or/and by residents themselves, smoking tobacco among residents were identified as sources of indoor herbicide presence. This thesis also confirmed mattress as a source for children early-life exposures to PAEs, OPEs, and UV-filters in SMEs. The emissions of SVOCs were found to increase as a function of children's body temperature and weight, leading to elevated exposure during sleeping. Numbers of newly purchased children’s mattresses, through product testing, were found to either not comply with Canadian regulations for children's mattresses or to be near non-compliance. Factors such as bedroom characteristics, SME contents, and the use of personal care products were also correlated with the levels of some SVOCs in children's SMEs. This thesis found exposures of residents of low-income households and young children to selected SVOCs of concern, reinforcing the importance of better understanding the available sources indoors, as well as the factors contributing to SVOC levels, including building characteristics, use of consumer products, and individual habits, with the aim of reducing exposures in an equitable manner.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".