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High Throughput Exposure Modeling of Semi-Volatile Chemicals in Articles of Commerce (ACS)
Citation:
Nicolas, Chantel I., Michael R. Goldsmith, Bhavesh K. Ahir, B. Wetmore, Kathie L. Dionisio, K. Mansouri, R. Woodrow Setzer, Richard S. Judson, J. Rabinowitz, AND John F. Wambaugh. High Throughput Exposure Modeling of Semi-Volatile Chemicals in Articles of Commerce (ACS). Presented at American Chemical Society National Meeting, San Fransisco, CA, August 10 - 14, 2014. https://doi.org/10.23645/epacomptox.5082532
Impact/Purpose:
The ExpoCast project is developing a model that estimates indoor exposures to chemical additives in textiles, such as flame retardants, which are found in flooring, upholstery, and articles of clothing. Predictions generated from using high throughput exposure methods were then combined with ToxCast high-throughput bioactivity screening data as a demonstration of high-throughput risk prioritization.
Description:
Risk due to chemical exposure is a function of both chemical hazard and exposure. Near-field exposures to chemicals in consumer products are identified as the main drivers of exposure and yet are not well quantified or understood. The ExpoCast project is developing a model that estimates indoor exposures to chemical additives in textiles, such as flame retardants, which are found in flooring, upholstery, and articles of clothing. Physicochemical properties of chemicals largely dictate how they may accumulate in the indoor environment at higher magnitudes than in the outdoor environment, which along with proximity of the sources, is correlated with high indoor exposure rates. Halogenated flame retardants, such as polybrominated diphenyl ethers (PBDEs), are semi-volatile organic compounds that are potentially harmful to humans. Given that chemical emission calculations principally depend on gas-phase concentration (y˳) and source surface area, we used a model (Little et al. 2012)1 to assess the utility of physicochemical property information in predicting indoor emissions for these additives. Gas-phase concentrations were predicted using a regression model of experimental measurements of 74 chemicals found in 32 flooring materials by Wilke et al. (2004).2 The flooring materials include a range of natural and synthetic floor coverings, installations, and adhesives. A linear regression yielded R2- and p- values of approximately 0.3 and 2.0E-12, respectively, whereby logP and vapor pressure were significant predictors of y˳. These results potentially permit the forecasting of gas-phase concentrations of chemicals for which their analytical data in flooring materials are lacking. Predictions generated from using high throughput exposure methods were then combined with ToxCast high-throughput bioactivity screening data as a demonstration of high-throughput risk prioritization. This abstract does not necessarily reflect EPA policy. 1. Little et al. Environ. Sci. Technol. 2012, 46, 11171-11178 2. Wilke et al. Indoor Air 2004, 14, 98-107
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DOI: High Throughput Exposure Modeling of Semi-Volatile Chemicals in Articles of Commerce (ACS)