Measurement report: The Fifth International Workshop on Ice Nucleation phase 1 (FIN-01): intercomparison of single-particle mass spectrometers
Knowledge of the chemical composition and mixing state of aerosols at a single-particle level is critical for gaining insights into atmospheric processes. One common tool to make these measurements is single-particle mass spectrometry. There remains a need to compare the performance of different sin...
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Published in | Atmospheric chemistry and physics Vol. 24; no. 18; pp. 10869 - 10891 |
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Main Authors | , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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Katlenburg-Lindau
Copernicus GmbH
26.09.2024
Copernicus Publications |
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Abstract | Knowledge of the chemical composition and mixing state of aerosols at a single-particle level is critical for gaining insights into atmospheric processes. One common tool to make these measurements is single-particle mass spectrometry. There remains a need to compare the performance of different single-particle mass spectrometers (SPMSs). An intercomparison of SPMSs was conducted at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) chamber at the Karlsruhe Institute of Technology (KIT) in November 2014, as part of the first phase of the Fifth International Workshop on Ice Nucleation (FIN-01). In this paper we compare size distributions and mass spectra of atmospherically relevant particle types measured by five SPMSs. These include different minerals, desert and soil dusts, soot, bioaerosol (Snomax; protein granule), secondary organic aerosol (SOA), and SOA-coated mineral particles. Most SPMSs reported similar vacuum aerodynamic diameter (dva) within typical instrumental ranges from ∼100–200 nm (lower limit) to ∼2–3 µm (upper limit). In general, all SPMSs exhibited a wide dynamic range (up to ∼103) and high signal-to-noise ratio (up to ∼104) in mass spectra. Common spectral features with small diversities in mass spectra were found with high average Pearson's correlation coefficients, i.e., for average positive spectra ravg-pos=0.74 ± 0.12 and average negative spectra ravg-neg=0.67 ± 0.22. We found that instrument-specific detection efficiency (DE) was more dependent on particle size than particle type, and particle identification favored the use of bipolar, rather than monopolar, instruments. Particle classification from “blind experiments” showed that all instruments differentiated SOA, soot, and soil dust and detected subtle changes in the particle internal mixing but had difficulties differentiating among specific mineral types and dusts. This study helps to further understand the capabilities and limitations of the single-particle mass spectrometry technique in general and the specific performance of the instrument in characterizing atmospheric aerosol particles. |
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AbstractList | Knowledge of the chemical composition and mixing state of aerosols at a single-particle level is critical for gaining insights into atmospheric processes. One common tool to make these measurements is single-particle mass spectrometry. There remains a need to compare the performance of different single-particle mass spectrometers (SPMSs). An intercomparison of SPMSs was conducted at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) chamber at the Karlsruhe Institute of Technology (KIT) in November 2014, as part of the first phase of the Fifth International Workshop on Ice Nucleation (FIN-01). In this paper we compare size distributions and mass spectra of atmospherically relevant particle types measured by five SPMSs. These include different minerals, desert and soil dusts, soot, bioaerosol (Snomax; protein granule), secondary organic aerosol (SOA), and SOA-coated mineral particles. Most SPMSs reported similar vacuum aerodynamic diameter (dva) within typical instrumental ranges from ∼100–200 nm (lower limit) to ∼2–3 µm (upper limit). In general, all SPMSs exhibited a wide dynamic range (up to ∼103) and high signal-to-noise ratio (up to ∼104) in mass spectra. Common spectral features with small diversities in mass spectra were found with high average Pearson's correlation coefficients, i.e., for average positive spectra ravg-pos=0.74 ± 0.12 and average negative spectra ravg-neg=0.67 ± 0.22. We found that instrument-specific detection efficiency (DE) was more dependent on particle size than particle type, and particle identification favored the use of bipolar, rather than monopolar, instruments. Particle classification from “blind experiments” showed that all instruments differentiated SOA, soot, and soil dust and detected subtle changes in the particle internal mixing but had difficulties differentiating among specific mineral types and dusts. This study helps to further understand the capabilities and limitations of the single-particle mass spectrometry technique in general and the specific performance of the instrument in characterizing atmospheric aerosol particles. Knowledge of the chemical composition and mixing state of aerosols at a single-particle level is critical for gaining insights into atmospheric processes. One common tool to make these measurements is single-particle mass spectrometry. There remains a need to compare the performance of different single-particle mass spectrometers (SPMSs). An intercomparison of SPMSs was conducted at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) chamber at the Karlsruhe Institute of Technology (KIT) in November 2014, as part of the first phase of the Fifth International Workshop on Ice Nucleation (FIN-01). In this paper we compare size distributions and mass spectra of atmospherically relevant particle types measured by five SPMSs. These include different minerals, desert and soil dusts, soot, bioaerosol (Snomax; protein granule), secondary organic aerosol (SOA), and SOA-coated mineral particles. Most SPMSs reported similar vacuum aerodynamic diameter (d.sub.va) within typical instrumental ranges from â¼100-200 nm (lower limit) to â¼2-3 µm (upper limit). In general, all SPMSs exhibited a wide dynamic range (up to â¼10.sup.3) and high signal-to-noise ratio (up to â¼10.sup.4) in mass spectra. Common spectral features with small diversities in mass spectra were found with high average Pearson's correlation coefficients, i.e., for average positive spectra r.sub.avg-pos =0.74 ± 0.12 and average negative spectra r.sub.avg-neg =0.67 ± 0.22. We found that instrument-specific detection efficiency (DE) was more dependent on particle size than particle type, and particle identification favored the use of bipolar, rather than monopolar, instruments. Particle classification from "blind experiments" showed that all instruments differentiated SOA, soot, and soil dust and detected subtle changes in the particle internal mixing but had difficulties differentiating among specific mineral types and dusts. This study helps to further understand the capabilities and limitations of the single-particle mass spectrometry technique in general and the specific performance of the instrument in characterizing atmospheric aerosol particles. |
Audience | Academic |
Author | Coe, Hugh Schneider, Johannes Zelenyuk, Alla DeMott, Paul J Wilson, Jacqueline Möhler, Ottmar Saathoff, Harald Hiranuma, Naruki Mohr, Claudia Murphy, Daniel M Bell, David M Mahrt, Fabian Shen, Xiaoli Marsden, Nicholas A Zawadowicz, Maria A Cziczo, Daniel J |
Author_xml | – sequence: 1 fullname: Shen, Xiaoli – sequence: 2 fullname: Bell, David M – sequence: 3 fullname: Coe, Hugh – sequence: 4 fullname: Hiranuma, Naruki – sequence: 5 fullname: Mahrt, Fabian – sequence: 6 fullname: Marsden, Nicholas A – sequence: 7 fullname: Mohr, Claudia – sequence: 8 fullname: Murphy, Daniel M – sequence: 9 fullname: Saathoff, Harald – sequence: 10 fullname: Schneider, Johannes – sequence: 11 fullname: Wilson, Jacqueline – sequence: 12 fullname: Zawadowicz, Maria A – sequence: 13 fullname: Zelenyuk, Alla – sequence: 14 fullname: DeMott, Paul J – sequence: 15 fullname: Möhler, Ottmar – sequence: 16 fullname: Cziczo, Daniel J |
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