Characterization of nano-scale mineral dust aerosols in snow by single particle inductively coupled plasma mass spectrometry

Abstract

Although natural atmospheric nanomaterials are ubiquitous and highly influential in environmental systems, they have only recently begun to be studied. We analyzed sub-micron and nano-scale mineral dust aerosols (MDAs) in wet deposition (snowfall) from two storms in Colorado, USA using single particle inductively coupled plasma mass spectrometry (spICP-MS). We found high particle number concentrations (PNCs) of MDAs (up to 10⁸ particles per mL) and observed an order of magnitude difference in number concentrations related consistent with storm strength and meteorological conditions. We applied novel data processing to particle size distributions (PSDs) obtained with spICP-MS and determined that all PSDs followed the Pareto distribution despite differences in number concentration. We characterized multi-element MDA particle types with single particle ICP-time-of-flight MS (spICP-TOFMS) using particle type-specific detection limits based on crustal abundance ratios, and supplemented this approach with an unsupervised hierarchical clustering algorithm. Both methods confirmed that the median MDA composition largely followed elemental crustal abundance ratios, with a minor class of titanium-rich particles identified. We conclude that the particle size and composition of MDAs can be effectively analyzed in wet deposition by spICP-MS, but quantifying the particle number has greater uncertainty. Characterization of nano-scale MDAs can be used to better understand particle dynamics in the atmosphere, which can affect climate. Analysis of natural particle composition informs studies related to nanogeochemical cycling and can provide background particle data to further advance methods of detecting engineered nanomaterials in the environment.