Discerning Emittable from Extractable Chemicals Identified in Consumer Products by Suspect Screening GCxGC-TOFMS

Abstract

Characterization of chemicals in household products is important for understanding this potential source of chemical exposure. Increasingly, suspect screening and nontargeted analysis techniques are used to characterize as many chemical signatures as possible. Solids such as household products are most conveniently prepared using solvent extraction, revealing what chemicals are contained within the product matrix but providing no information about the potential of those chemicals to leave the matrix and cause actual exposure. In this work, the profile and relative abundances of "extractable" chemical signatures found after solvent extraction are compared to those "emittable" to the headspace for 81 household products analyzed by two-dimensional gas chromatography time-of-flight mass spectrometry. This study retrospectively fuses data collected in separate efforts over 3.8 years and 13 analytical batches. Management of the data is made possible by recent developments in processing systems for complex data such as Highlight. Compounds were generically classified as aromatic heteroatom, aromatic hydrocarbon, glycol, hydrocarbon, long chain heteroatom, nonaromatic heteroatom, and unknown/unclassified. Class-based retention time and abundance trends were observed. Liquid extraction resulted in the greatest number of features and the highest relative abundances, while low temperature emission conditions produced the smallest number of features and lowest relative abundances.

Keywords: ExpoCast; clothing; exposomics; highlight; machine learning; rubber; textiles.