Discrimination between individual dust and bioparticles using aerosol time-of-flight mass spectrometry. Issue 7 (3rd July 2022)

• Record Type: Journal Article
• Authors: Cornwell, G. C.; Sultana, C. M.; Petters, M. D.; Al-Mashat, H.; Rothfuss, N. E.; Möhler, O.; DeMott, P. J.; Martin, A. C.; Prather, K. A.
• Is Part Of: Aerosol science and technology. Volume 56:Issue 7(2022)
• Page Start: 592
• Page End: 608
• Publication Date: 2022-07-03
• Subjects: Nicole Riemer; Aerosols -- Periodicals; Aerosol Propellants -- Periodicals; Aerosols -- Periodicals; 660.294515
• DOI: 10.1080/02786826.2022.2055994
• Languages: English
• ISSNs: 0278-6826

Abstract

Abstract: Ice nucleating particles (INPs) impact cloud properties and precipitation processes through their ability to trigger cloud glaciation. Dust and bioparticles are two important sources of INPs that have markedly different atmospheric loadings and ice nucleating efficiencies. In-situ identification of the sources of INPs in clouds has been accomplished using single particle mass spectrometry (SPMS). However, external mixtures of dust and bioparticles present a unique challenge as they have overlapping mass spectral ion signatures, complicating their unambiguous identification. This study presents a detailed discussion of dust and bioparticle SPMS signatures, uniting data from a broad array of studies. As emphasized, the ion signals from both dust and bioparticles are highly sensitive to ionization conditions. To understand the observed variations, we characterize the mass spectral dependence of distinct dust and bioparticle samples using total positive ion intensity (TPII) as an indicator of the laser pulse energy each particle encountered. Through this analysis, a broad range of characteristic biogenic low intensity ion peaks that may be useful to distinguish bioparticles from dust became apparent and are highlighted. Insights informed by this analysis were utilized to identify bioparticles in ambient SPMS data. Ambient particles exhibiting both dust and characteristic biogenic spectral fingerprints were excluded from the bioparticle classification. Although bioparticles only made up 0.2% of all sampled particles, their abundance was moderately correlated with INP concentrations measured at −15 °C. Copyright © 2022 American Association for Aerosol Research