Preprints
https://doi.org/10.5194/egusphere-2022-598
https://doi.org/10.5194/egusphere-2022-598
26 Jul 2022
 | 26 Jul 2022

Technical Note: Bioaerosol identification by wide particle size range single particle mass spectrometry

Xuan Li, Lei Li, Zeming Zhuo, Guohua Zhang, Xubing Du, Xue Li, Zhengxu Huang, Zhen Zhou, and Zhi Cheng

Abstract. The sources of bioaerosols are complex and diverse, which have a direct impact on the environment, climate, and human health. The effective identification of bioaerosols in the atmosphere is greatly significant for accurately obtaining the atmospheric chemical characteristics of bioaerosols and making biological early warnings and predictions. To improve the identification ability of bioaerosols, this study detected a variety of bioaerosols and abiotic aerosols based on a single particle aerosol mass spectrometry (SPAMS). Furthermore, the bioaerosol particle identification and classification algorithm based on the ratio of phosphate to organic nitrogen was optimized to distinguish bioaerosols from abiotic aerosols. The results show that 15 kinds of pure fungal aerosols were detected by SPAMS based on a wide range sampling system and that fungal aerosols with a particle size up to 10 μm could be detected. Through the mass spectra peak ratio method of PO3- / PO2- and CNO- / CN-, when discriminating abiotic aerosols, such as disruptive biomass combustion particles, automobile exhaust, and dust, from pure bacterial aerosols, the discrimination degree was up to 97.7 %. The optimized ratio detection method of phosphate to organic nitrogen has strong specificity, which can serve as the discriminant basis for identifying bioaerosols in SPAMS source analysis or other analytical processes.

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Xuan Li, Lei Li, Zeming Zhuo, Guohua Zhang, Xubing Du, Xue Li, Zhengxu Huang, Zhen Zhou, and Zhi Cheng

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-598', Anonymous Referee #1, 24 Aug 2022
    • AC1: 'Reply on RC1', Lei Li, 19 Oct 2022
  • RC2: 'Comment on egusphere-2022-598', Anonymous Referee #2, 29 Aug 2022
    • AC2: 'Reply on RC2', Lei Li, 19 Oct 2022
  • RC3: 'Comment on egusphere-2022-598', Anonymous Referee #3, 07 Sep 2022
    • AC3: 'Reply on RC3', Lei Li, 19 Oct 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-598', Anonymous Referee #1, 24 Aug 2022
    • AC1: 'Reply on RC1', Lei Li, 19 Oct 2022
  • RC2: 'Comment on egusphere-2022-598', Anonymous Referee #2, 29 Aug 2022
    • AC2: 'Reply on RC2', Lei Li, 19 Oct 2022
  • RC3: 'Comment on egusphere-2022-598', Anonymous Referee #3, 07 Sep 2022
    • AC3: 'Reply on RC3', Lei Li, 19 Oct 2022
Xuan Li, Lei Li, Zeming Zhuo, Guohua Zhang, Xubing Du, Xue Li, Zhengxu Huang, Zhen Zhou, and Zhi Cheng
Xuan Li, Lei Li, Zeming Zhuo, Guohua Zhang, Xubing Du, Xue Li, Zhengxu Huang, Zhen Zhou, and Zhi Cheng

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Short summary
The particle size and chemical composition of bioaerosol were analyzed based on single particle aerosol mass spectrometer. Fungal aerosol of 10 μm was measured for the first time and the characteristic spectrum of bioaerosol was updated. The ion peak ratio method can distinguish bioaerosols from interferers by 97 %. The factors influencing the differentiation of bioaerosols are also discussed. Single particle mass spectrometry can be a new method for real-time identification of bioaerosols.