Integrating Monitoring and Biomonitoring Data with Mechanistic Models to Better Estimate and Characterize Aggregate Human Exposures to Semivolatile Organic Chemicals

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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Publication Details

Journal
Environmental Science & Technology
Published
2025-12-02
DOI
https://doi.org/10.1021/acs.est.5c08964
Primary Topic
Indoor Air Quality and Microbial Exposure
Type
article
Field-Weighted Citation Impact
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article

Integrating Monitoring and Biomonitoring Data with Mechanistic Models to Better Estimate and Characterize Aggregate Human Exposures to Semivolatile Organic Chemicals

Lauren Hughes, Lieve Geerts, Katleen De Brouwere, Jon A. Arnot et al.
Environmental Science & Technology
Indoor Air Quality and Microbial Exposure
article

Integrating Monitoring and Biomonitoring Data with Mechanistic Models to Better Estimate and Characterize Aggregate Human Exposures to Semivolatile Organic Chemicals

Lauren Hughes, Lieve Geerts, Katleen De Brouwere, Jon A. Arnot, Alessandro Sangion, Jirka Cops, Li Li
article en

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.

Environmental Science & TechnologyVol. 59(49)
University of Nevada, Reno (US), University of Toronto (CA), Canada Research Chairs (CA), ARC Resources (Canada) (CA), Flemish Institute for Technological Research (BE)
Openalex Percentile: Top 53%
Indoor Air Quality and Microbial Exposure
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