Detection and Quantification of Tire Particles in Sediments Using a Combination of Simultaneous Thermal Analysis, Fourier Transform Infra-Red, and Parallel Factor Analysis

Detection and quantification of tread wear particles in the environment have been a challenge owing to lack of a robust method. This study investigated the applicability of a combination of Simultaneous Thermal Analysis (STA), Fourier Transform Infra-Red (FTIR), and Parallel Factor Analysis (PARAFAC) in the detection and quantification of tire particles from formulated sediments. FTIR spectral data were obtained by heating 20 samples in STA. Among the 20 samples, 12 were tire granules in formulated sediments (TGIS) containing 1%, 2%, 5%, and 10% by mass of tire granules, while the remaining eight contained 0.5, 1, 2.5, and 5 mg of tire granules only (TGO). The PARAFAC models decomposed the trilinear data into three components. Tire rubber materials in tire granules (RM) and a combination of water and carbon dioxide were the components identified in all samples. The linear regression analysis of score values from the PARAFAC models showed that the RM quantity predicted were comparable to measured values in both TGIS and TGO. Decomposing the overlying components in the spectral data into different components, and predicting unknown quantity in both sample types, the method proves robust in identifying and quantifying tire particles from sediments.