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Title: Improved identification of primary biological aerosol particles using single-particle mass spectrometry

Abstract

Measurements of primary biological aerosol particles (PBAP), especially at altitudes relevant to cloud formation, are scarce. Single-particle mass spectrometry (SPMS) has been used to probe aerosol chemical composition from ground and aircraft for over 20 years. Here we develop a method for identifying bioaerosols (PBAP and particles containing fragments of PBAP as part of an internal mixture) using SPMS. We show that identification of bioaerosol using SPMS is complicated because phosphorus-bearing mineral dust and phosphorus-rich combustion by-products such as fly ash produce mass spectra with peaks similar to those typically used as markers for bioaerosol. We have developed a methodology to differentiate and identify bioaerosol using machine learning statistical techniques applied to mass spectra of known particle types. This improved method provides far fewer false positives compared to approaches reported in the literature. The new method was then applied to two sets of ambient data collected at Storm Peak Laboratory and a forested site in Central Valley, California to show that 0.04–2 % of particles in the 200–3000 nm aerodynamic diameter range were identified as bioaerosol. In addition, 36–56 % of particles identified as biological also contained spectral features consistent with mineral dust, suggesting internal dust–biological mixtures.

Authors:
; ; ;
Publication Date:
Research Org.:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1364084
Alternate Identifier(s):
OSTI ID: 1425937
Grant/Contract Number:  
SC0014487; NNX13AO15G; AGS-1461347; AGS-1339264
Resource Type:
Published Article
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online) Journal Volume: 17 Journal Issue: 11; Journal ID: ISSN 1680-7324
Publisher:
European Geosciences Union
Country of Publication:
Germany
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Zawadowicz, Maria A., Froyd, Karl D., Murphy, Daniel M., and Cziczo, Daniel J. Improved identification of primary biological aerosol particles using single-particle mass spectrometry. Germany: N. p., 2017. Web. doi:10.5194/acp-17-7193-2017.
Zawadowicz, Maria A., Froyd, Karl D., Murphy, Daniel M., & Cziczo, Daniel J. Improved identification of primary biological aerosol particles using single-particle mass spectrometry. Germany. doi:10.5194/acp-17-7193-2017.
Zawadowicz, Maria A., Froyd, Karl D., Murphy, Daniel M., and Cziczo, Daniel J. Fri . "Improved identification of primary biological aerosol particles using single-particle mass spectrometry". Germany. doi:10.5194/acp-17-7193-2017.
@article{osti_1364084,
title = {Improved identification of primary biological aerosol particles using single-particle mass spectrometry},
author = {Zawadowicz, Maria A. and Froyd, Karl D. and Murphy, Daniel M. and Cziczo, Daniel J.},
abstractNote = {Measurements of primary biological aerosol particles (PBAP), especially at altitudes relevant to cloud formation, are scarce. Single-particle mass spectrometry (SPMS) has been used to probe aerosol chemical composition from ground and aircraft for over 20 years. Here we develop a method for identifying bioaerosols (PBAP and particles containing fragments of PBAP as part of an internal mixture) using SPMS. We show that identification of bioaerosol using SPMS is complicated because phosphorus-bearing mineral dust and phosphorus-rich combustion by-products such as fly ash produce mass spectra with peaks similar to those typically used as markers for bioaerosol. We have developed a methodology to differentiate and identify bioaerosol using machine learning statistical techniques applied to mass spectra of known particle types. This improved method provides far fewer false positives compared to approaches reported in the literature. The new method was then applied to two sets of ambient data collected at Storm Peak Laboratory and a forested site in Central Valley, California to show that 0.04–2 % of particles in the 200–3000 nm aerodynamic diameter range were identified as bioaerosol. In addition, 36–56 % of particles identified as biological also contained spectral features consistent with mineral dust, suggesting internal dust–biological mixtures.},
doi = {10.5194/acp-17-7193-2017},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 11,
volume = 17,
place = {Germany},
year = {2017},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.5194/acp-17-7193-2017

Citation Metrics:
Cited by: 8 works
Citation information provided by
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