Articles | Volume 10, issue 11
Research article
21 Nov 2017
Research article |  | 21 Nov 2017

Real-time analysis of insoluble particles in glacial ice using single-particle mass spectrometry

Matthew Osman, Maria A. Zawadowicz, Sarah B. Das, and Daniel J. Cziczo

Abstract. Insoluble aerosol particles trapped in glacial ice provide insight into past climates, but analysis requires information on climatically relevant particle properties, such as size, abundance, and internal mixing. We present a new analytical method using a time-of-flight single-particle mass spectrometer (SPMS) to determine the composition and size of insoluble particles in glacial ice over an aerodynamic size range of  ∼  0.2–3.0 µm diameter. Using samples from two Greenland ice cores, we developed a procedure to nebulize insoluble particles suspended in melted ice, evaporate condensed liquid from those particles, and transport them to the SPMS for analysis. We further determined size-dependent extraction and instrument transmission efficiencies to investigate the feasibility of determining particle-class-specific mass concentrations. We find SPMS can be used to provide constraints on the aerodynamic size, composition, and relative abundance of most insoluble particulate classes in ice core samples. We describe the importance of post-aqueous processing to particles, a process which occurs due to nebulization of aerosols from an aqueous suspension of originally soluble and insoluble aerosol components. This study represents an initial attempt to use SPMS as an emerging technique for the study of insoluble particulates in ice cores.

Short summary
This study presents the first-time attempt at using time-of-flight single particle mass spectrometry (SPMS) as an emerging online technique for measuring insoluble particles in glacial snow and ice. Using samples from two Greenlandic ice cores, we show that SPMS can constrain the aerodynamic size, composition, and relative abundance of most particulate types on a per-particle basis, reducing the preparation time and resources required of conventional, filter-based particle retrieval methods.