Tire wear particles (TWPs) are one of the environment's most important emission sources of microplastics. In this work, chemical identification of these particles was carried out in highway stormwater runoff through cross-validation techniques for the first time. Optimization of a pre-treatment method (i.e., extraction and purification) was provided to extract TWPs, avoiding their degradation and denaturation, to prevent getting low recognizable identification and consequently underestimates in the quantification. Specific markers were used for TWPs identification comparing real stormwater samples and reference materials via FTIR-ATR, Micro-FTIR, and Pyrolysis-gas-chromatography-mass spectrometry (Pyr-GC/MS). Quantification of TWPs was carried out via Micro-FTIR (microscopic counting); the abundance ranged from 220,371 ± 651 TWPs/L to 358,915 ± 831 TWPs/L, while the higher mass was 39,6 ± 9 mg TWPs/L and the lowest 31,0 ± 8 mg TWPs/L. Most of the TWPs analyzed were less than 100 ?m in size. The sizes were also confirmed using a scanning electron microscope (SEM), including the presence of potential nano TWPs in the samples. Elemental analysis via SEM supported that a complex mixture of heterogeneous composition characterizes these particles by agglomerating organic and inorganic particles that could derive from brake and road wear, road pavement, road dust, asphalts, and construction road work. Due to the analytical lack of knowledge about TWPs chemical identification and quantification in scientific literature, this study significantly contributes to providing a novel pre-treatment and analytical methodology for these emerging contaminants in highway stormwater runoff. The results of this study highlight the uttermost necessity to employ cross-validation techniques, i.e., FTIR-ATR, Micro-FTIR, Pyr-GC/MS, and SEM for the TWPs identification and quantification in the real environmental samples.
Identification and quantification of tire wear particles by employing different cross-validation techniques: FTIR-ATR Micro-FTIR, Pyr-GC/MS, and SEM
Gregoris E;Barbante C;Gambaro A;Corami F
2023
Abstract
Tire wear particles (TWPs) are one of the environment's most important emission sources of microplastics. In this work, chemical identification of these particles was carried out in highway stormwater runoff through cross-validation techniques for the first time. Optimization of a pre-treatment method (i.e., extraction and purification) was provided to extract TWPs, avoiding their degradation and denaturation, to prevent getting low recognizable identification and consequently underestimates in the quantification. Specific markers were used for TWPs identification comparing real stormwater samples and reference materials via FTIR-ATR, Micro-FTIR, and Pyrolysis-gas-chromatography-mass spectrometry (Pyr-GC/MS). Quantification of TWPs was carried out via Micro-FTIR (microscopic counting); the abundance ranged from 220,371 ± 651 TWPs/L to 358,915 ± 831 TWPs/L, while the higher mass was 39,6 ± 9 mg TWPs/L and the lowest 31,0 ± 8 mg TWPs/L. Most of the TWPs analyzed were less than 100 ?m in size. The sizes were also confirmed using a scanning electron microscope (SEM), including the presence of potential nano TWPs in the samples. Elemental analysis via SEM supported that a complex mixture of heterogeneous composition characterizes these particles by agglomerating organic and inorganic particles that could derive from brake and road wear, road pavement, road dust, asphalts, and construction road work. Due to the analytical lack of knowledge about TWPs chemical identification and quantification in scientific literature, this study significantly contributes to providing a novel pre-treatment and analytical methodology for these emerging contaminants in highway stormwater runoff. The results of this study highlight the uttermost necessity to employ cross-validation techniques, i.e., FTIR-ATR, Micro-FTIR, Pyr-GC/MS, and SEM for the TWPs identification and quantification in the real environmental samples.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
