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Using Non-Targeted Analysis and Multimedia Modeling to Identify Tracers for Estimating Children’s Dust Ingestion
Citation:
Panagopoulos, D., J. Sobus, E. Ulrich, K. Isaacs, T. Young, AND N. Tulve. Using Non-Targeted Analysis and Multimedia Modeling to Identify Tracers for Estimating Children’s Dust Ingestion. 2018 SETAC NA Annual Meeting, Sacramento, CA, November 04 - 08, 2018.
Impact/Purpose:
Presented at SETAC 2018
Description:
Children are exposed to dust in indoor environments through their regular activities. Dust is known to be a sink for many chemicals from indoor sources such as building materials, furniture, cleaning agents, insecticides and personal care products. Partitioning and accumulation of chemicals in dust contribute to children’s uptake of these chemicals through non-dietary ingestion, inhalation and dermal contact. Dust is routinely collected in observational human exposure studies but its potential to be used as a standard metric for human exposure to chemicals remains unclear due to the large variability in dust composition and human exposure patterns. Previous studies have tried to calculate dust ingestion rates using metals or other earth elements as tracers. These approaches have significant limitations since the proposed tracers are present in matrices besides dust. Our study aims to identify organic chemicals that are unique and ubiquitous in dust, and that can be used as tracers to calculate dust ingestion rates for children. We collected data from three studies that sampled: 1) 50 homes across the U.S., 2) 38 homes in CA and 3) one house in NC with samples collected from each room and at three time-points. Using non-targeted analysis methods, we generated data on thousands of observed dust features, and tentatively identified compounds that were ubiquitous in each sample set (i.e., appearing across homes, rooms, and time points with high detection frequency [DF]). Candidate compounds include tris-(2-chloroisopropyl)phosphate (plastic production, 98% DF); 2-hydroxy-4-methoxybenzophenone (plastic UV stabilizer, 90% DF); fipronil (insecticide, 95% DF) and piperine (black peppercorn, 85% DF), among others. The detected compounds covered a large spectrum of physicochemical properties, from nonpolar and semivolatile to polar and non-volatile compounds. Future work will include applications of statistical and environmental fate modeling to track emission sources and describe the partitioning of the detected chemicals in the indoor environment to better understand their utility as tracers. More details on the candidate compounds and supporting information will be presented.
