PNNL

Abstract

Abstract Recent discoveries of highly viscous and semi-solid atmospheric organic particles indicated that they can be either directly emitted into the air or formed by various particle-phase ageing processes. Distinguishing highly viscous organic particles within complex mixtures of atmospheric aerosol and accurate descriptions of their composition, size distributions, and mixing states are challenges at the forefront of modern environmental analytical chemistry. Here, we present results obtained from complementary single-particle measurement techniques employed for the in-depth characterization of highly viscous particles. We demonstrate advantages and synergy of this multi-modal particle characterization approach based on the analysis of individual viscous nanoplastic particles formed in the air-discharged waste produced by common technology for sewer pipe repairs. We investigate particle size distributions and morphology of colloidal components of the field-collected aqueous waste condensates using oil immersion flow microscopy and compare results with corresponding measurements of solid nanoplastic particles formed in drying droplets of the discharged waste. The chemical imaging of the nanoplastic particles collected on substrates is then performed using scanning electron microscopy and X-ray spectro-microscopy techniques, which provide assessment of particle viscosity, variability in their sizes and morphology, particle-specific speciation of carbon bonding, its spatial heterogeneity and organic volume fractions within individual particles. The aerosolized suspensions of solid nanoplastic particles were further characterized using high-throughput single particle mass spectrometry. This technique provides real-time measurements of composition, size, and morphological metrics for large numbers of individual particles to identify the mass spectrometric signatures of nanoplastic particles. We highlight applications of these methods for the reported study of nanoplastic particles, discuss existing limitations, and forecast future directions.