Citation:

Panagopoulos, D., J. Sobus, E. Ulrich, S. Newton, AND N. Tulve. Using Non-Targeted Analysis and Multimedia Modeling to Identify Tracers to Estimate Children’s Dust Ingestion. 2018 EPA’s Non-Targeted Analysis Collaborative Trial (ENTACT) Workshop, RTP, NC, August 13 - 15, 2018.

Impact/Purpose:

ENTACT was designed to assess the characteristics and performance of cutting-edge non-targeted analysis (NTA) methods using a set of highly controlled synthetic mixtures and reference samples. The workshop will be held on August 13–15, 2018 at EPA's Research Triangle Park campus. This workshop will bring together ENTACT participants, NTA experts, and key stakeholders to discuss findings from ENTACT, as well as next steps for the NTA research community.

Description:

Children are exposed to dust in indoor spaces 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 childrens' 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-butoxyethyl)phosphate (plastic production, 96% DF); caprolactam (plasticizer, 90% DF); laetaceric acid (fungicide, 100% DF), laurocapram (skin absorption enhancer, 91% DF), triamcinolone acetonide (pharmaceutical, 100% DF), fluocinolone acetonide (pharmaceutical, 100% DF) among others. In order to understand the behavior of the potential tracers in the indoor and outdoor environments, and to assess their presence in other relevant environmental media, we developed a mathematical model that describes their environmental fate in the indoor and outdoor environments. According to our modeling calculations, triamcinolone acetonide and fluocinolone acetonide showed promise as potential tracers because they are expected to partition to dust at substantial quantities compared to other compartments such as hard and soft surfaces and they are expected to be undetectable in soil. In future steps, we will expand our tracer list by reviewing all tentatively identified chemicals in the dust samples. We will build a database with information for each chemical. The findings from this study may eventually be used to design a field study.

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