Discrimination between individual dust and bioparticles using aerosol time-of-flight mass spectrometry

被引:8
|
作者
Cornwell, G. C. [1 ,6 ]
Sultana, C. M. [1 ]
Petters, M. D. [2 ]
Al-Mashat, H. [1 ]
Rothfuss, N. E. [2 ]
Mohler, O. [3 ]
DeMott, P. J. [4 ]
Martin, A. C. [5 ,7 ]
Prather, K. A. [1 ,4 ]
机构
[1] Univ Calif San Diego, Dept Chem & Biochem, La Jolla, CA 92093 USA
[2] North Carolina State Univ, Dept Marine Earth & Atmospher Sci, Raleigh, NC USA
[3] Karlsruhe Inst Technol, Inst Meteorol & Climate Res, Karlsruhe, Germany
[4] Colorado State Univ, Dept Atmospher Sci, Ft Collins, CO 80523 USA
[5] Univ Calif San Diego, Scripps Inst Oceanog, La Jolla, CA 92093 USA
[6] Pacific Northwest Natl Lab, Richland, WA 99352 USA
[7] Portland State Univ, Dept Geog, Portland, OR 97207 USA
基金
美国国家科学基金会;
关键词
Nicole Riemer; BACILLUS-ATROPHAEUS SPORES; PRIMARY BIOLOGICAL AEROSOL; ICE NUCLEATING PARTICLES; ION FORMATION MECHANISM; MINERAL DUST; MIXED-PHASE; LASER DESORPTION/IONIZATION; SPECTRAL SIGNATURES; MIXING STATE; MU-M;
D O I
10.1080/02786826.2022.2055994
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
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 degrees C. Copyright (c) 2022 American Association for Aerosol Research
引用
收藏
页码:592 / 608
页数:17
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