Pyrolysis-Gas Chromatography-Mass Spectrometry (Py-GC-MS) Quantification of Tire and Road Wear Particles (TRWP) in Environmental Matrices: Assessing the Importance of Microstructure in Instrument Calibration Protocols. (13th April 2022)

• Record Type: Journal Article
• Authors: Miller, Julie V.; Maskrey, Joshua R.; Chan, Kathy; Unice, Kenneth M.
• Is Part Of: Analytical letters. Volume 55:Number 6(2022)
• Page Start: 1004
• Page End: 1016
• Publication Date: 2022-04-13
• Subjects: Microplastic -- microstructure -- pyrolysis-gas chromatography-mass spectrometry (py-GC-MS) -- rubber -- tire and road wear particles; Chemistry, Analytic -- Periodicals; Chemistry, Analytic -- Abstracts; 543
• DOI: 10.1080/00032719.2021.1979994
• Languages: English
• ISSNs: 0003-2719

Abstract

Abstract: Thermogravimetric methods with internal polymer standards have successfully quantified environmental tire and road wear particle (TRWP) concentrations. However, TRWP quantification in environmental matrices via pyrolysis-gas chromatography-mass spectrometry (py-GC-MS) using butadiene rubber (BR) and styrene-butadiene rubber (SBR) marker 4-vinylcyclohexene (4-VCH; 1, 4-butadiene-1, 4-butadiene dimer) may be uncertain because of variable polymer compositions and BR and SBR microstructures. To determine if tire polymer microstructure is contributing to potentially over- or underestimating TRWP in the environment in py-GC-MS analyses, SBR materials ( n = 8) commonly found in tire tread with varying microstructure were quantified via py-GC-MS, using 4-VCH and the deuterated internal standard d-4-VCH to provide a response ratio for each polymer. The response ratios of the dimer response to the total polymer quantity (instrument response slope) varied up to 6.8-fold for SBR, with a reduction to a 3.6-fold range when the polymer quantity was expressed as 1, 4-butadiene mass rather than total polymer mass. Variability was reduced further when considering the polymerization method for emulsion-SBRs ( n = 3; 1.4-fold range), but not solution-SBRs ( n = 5; 2.7-fold range), which reflects the random versus structured heterosequencing of the two rubber types, respectively. Our findings suggest that py-GC-MS response should be interpreted based on empirical analysis of an appropriate number of regionally representative tire tread materials, rather than individual rubbers, because of the lack of methods available for determining unknown average microstructure in environmental samples.