ArticleEnvironmental science & technology2025
Integrating Monitoring and Biomonitoring Data with Mechanistic Models to Better Estimate and Characterize Aggregate Human Exposures to Semivolatile Organic Chemicals.
Article in Environmental science & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Humans are exposed to many chemicals from multiple sources through various pathways. Many semivolatile organic chemicals (SVOCs) are ubiquitous in indoor environments, but the extent of exposure and relative importance of different pathways (near-field or far-field) are uncertain. Here, 37 SVOCs with measured concentrations in indoor media are used in conjunction with a mass balance indoor fate, exposure, and toxicokinetic model to 1) estimate exposures from indoor environments, 2) incorporate measured dietary (far-field) exposures, 3) evaluate modeled biological concentrations in blood and urine against previously published human biomonitoring (HBM) estimates, 4) calculate the relative importance of different exposure pathways, and 5) demonstrate the value of using models and monitoring data to estimate aggregate exposure for human health assessment. All model calculated blood and urine concentrations are within 2 orders of magnitude of HBM values, and 73% are within 1 order of magnitude. The method explicitly considers uncertainty in measured indoor concentrations and mouthing-mediated ingestion (MMI). When median measured chemical concentrations in dust and MMI are used for modeling, far-field dietary intake is determined to be the dominant contributor to the overall exposure for almost all investigated SVOCs. However, when modeling with higher (third quartile reported) measured chemical concentrations in dust and ∼ 3x higher dust ingestion rates, near-field sources result in exposures for some SVOCs that are comparable to or exceed contributions from far-field exposure pathways. The model also addresses measurement data gaps and, combined with the monitoring data, provides a method to estimate chemical emission rates.
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