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

Zawadowicz, Maria A.; Froyd, K. D.; Murphy, D. M.; Cziczo, D. J.

doi:10.5194/acp-17-7193-2017

Cited by 52 publications

(65 citation statements)

References 78 publications

(104 reference statements)

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“…Often, the phosphate markers are combined with organic nitrogen fragments (CNand CNO -). This was found to match laboratory signatures of bioaerosols well Pratt et al 2009a;Schmidt et al 2017;Sultana, Al-Mashat, and Prather 2017;Suski et al 2018;Zawadowicz et al 2017). However, there is also recent evidence that misclassifications with phosphate-rich dust and ash are possible, and a marker ratio-based approach combined with machine learning can improve bioaerosol identification and allow uncertainty analysis (Zawadowicz et al 2017;Zawadowicz et al, 2019).…”

Section: Bioaerosol Detection By Online Masssupporting

confidence: 66%

Real-time sensing of bioaerosols: Review and current perspectives

Huffman

Perring

Savage

et al. 2019

Aerosol Science and Technology

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161

132

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Detection of bioaerosols, or primary biological aerosol particles (PBAPs), has become increasingly important for a wide variety of research communities and scientific questions. In particular, real-time (RT) techniques for autonomous, online detection and characterization of PBAP properties in both outdoor and indoor environments are becoming more commonplace and have opened avenues of research. With advances in technology, however, come challenges to standardize practices so that results are both reliable and comparable across technologies and users. Here, we present a critical review of major RT instrument classes that have been applied to PBAP research, especially with respect to environmental science, allergy monitoring, agriculture, public health, and national security. Eight major classes of RT techniques are covered, including the following: (i) fluorescence spectroscopy, (ii) elastic scattering, microscopy, and holography, (iii) Raman spectroscopy, (iv) mass spectrometry, (v) breakdown spectroscopy, (vi) remote sensing, (vii) microfluidic techniques, and (viii) paired aqueous techniques. For each class of technology we present technical limitations, misconceptions, and pitfalls, and also summarize best practices for operation, analysis, and reporting. The final section of the article presents pressing scientific questions and grand challenges for RT sensing of PBAP as well as recommendations for future work to encourage high-quality results and increased cross-community collaboration.

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Section: Bioaerosol Detection By Online Masssupporting

confidence: 66%

Real-time sensing of bioaerosols: Review and current perspectives

Huffman

Perring

Savage

et al. 2019

Aerosol Science and Technology

Self Cite

161

132

View full text Add to dashboard Cite

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“…The size distributions and MS provide direct evidence that the smaller particles are composed of agar mixed with bacterial fragments, while the larger size particle mode corresponds to intact bacteria cells. The MS of intact bacteria shown in Figures 2 and S1 are similar to previously published single particle mass spectra of laboratory-generated Pseudomonas syringae acquired by two other single particle 10 mass spectrometers (Pratt et al, 2009;Zawadowicz et al, 2017). The negative ion MS are virtually the same, while the positive ion MS presented here exhibit significantly higher intensity in organic peaks, most likely due to the differences in the ablation laser wavelength or power.…”

Section: Resultssupporting

confidence: 74%

Activation of Intact Bacteria and Bacterial Fragments Mixed with Agar as Cloud Droplets and Ice Crystals in Cloud Chamber Experiments

Suski¹,

Bell²,

Hiranuma³

et al. 2018

Preprint

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Abstract. Biological particles, including bacteria and bacterial fragments, have been of much interest due to the special ability of some to nucleate ice at modestly low temperatures. This paper presents results from a recent study conducted on two strains of cultivated bacteria which suggest that bacterial fragments mixed with agar, and not whole bacterial cells, serve as cloud condensation nuclei (CCN). Due to the absence of whole bacteria cells in droplets, they are unable to serve as ice nucleating particles (INPs) in the immersion mode under the experimental conditions. Experiments were conducted at the Aerosol 15Interaction and Dynamics in the Atmosphere (AIDA) cloud chamber at the Karlsruhe Institute of Technology (KIT) by injecting bacteria-containing aerosol samples into the cloud chamber and inducing cloud formation by expansion over a temperature range of -5 to -12 °C. Cloud droplets and ice crystals were sampled through a pumped counterflow virtual impactor inlet (PCVI) and their residuals were characterized with a single particle mass spectrometer (miniSPLAT). The size distribution of the overall aerosol was bimodal, with a large particle mode composed of intact bacteria and a mode of smaller particles 20 composed of agar mixed with bacterial fragments that were present in higher concentrations. Results from three expansions with two bacterial strains indicate that the cloud droplet residuals had virtually the same size distribution as the smaller particle size mode and had mass spectra that closely matched those of agar and bacterial fragments. The characterization of ice residuals that were sampled through an ice-selecting PCVI (IS-PCVI) also shows that the same particles that activate to form cloud droplets, bacteria fragments mixed with agar, were the only particle type observed in ice residuals. 25

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“…This method is very promising since it works independently from microbial culturability, even if research is still ongoing on discriminating between different PBA classes and between PBAs and nonbiological fluorescent compounds contaminating the signal (Gabey et al, 2013;Pöhlker et al, 2012;Toprak and Schnaiter, 2013). Single-particle mass spectrometry (SPMS) is also a technique that can be used to detect PBAs by relying on the spectroscopic detection of specific compounds that are assumed as a proxy of bioaerosols (Zawadowicz et al, 2017). Similar to UV-LIF, this method does not rely on PBA culturability and suffers from interference of nonbiological particles with coincident spectral peaks (Zawadowicz et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Single-particle mass spectrometry (SPMS) is also a technique that can be used to detect PBAs by relying on the spectroscopic detection of specific compounds that are assumed as a proxy of bioaerosols (Zawadowicz et al, 2017). Similar to UV-LIF, this method does not rely on PBA culturability and suffers from interference of nonbiological particles with coincident spectral peaks (Zawadowicz et al, 2017). It is important to consider, though, that even if live and dead microorganisms would contribute to cloudrelated processes due to their chemical and physical composition, the latter would not matter from an evolutionary perspective.…”

Section: Discussionmentioning

confidence: 99%

Measurements and modeling of surface–atmosphere exchange of microorganisms in Mediterranean grassland

et al. 2017

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Abstract. Microbial aerosols (mainly composed of bacterial and fungal cells) may constitute up to 74 % of the total aerosol volume. These biological aerosols are not only relevant to the dispersion of pathogens, but they also have geochemical implications. Some bacteria and fungi may, in fact, serve as cloud condensation or ice nuclei, potentially affecting cloud formation and precipitation and are active at higher temperatures compared to their inorganic counterparts. Simulations of the impact of microbial aerosols on climate are still hindered by the lack of information regarding their emissions from ground sources. This present work tackles this knowledge gap by (i) applying a rigorous micrometeorological approach to the estimation of microbial net fluxes above a Mediterranean grassland and (ii) developing a deterministic model (the PLAnET model) to estimate these emissions on the basis of a few meteorological parameters that are easy to obtain. The grassland is characterized by an abundance of positive net microbial fluxes and the model proves to be a promising tool capable of capturing the day-to-day variability in microbial fluxes with a relatively small bias and sufficient accuracy. PLAnET is still in its infancy and will benefit from future campaigns extending the available training dataset as well as the inclusion of ever more complex and critical phenomena triggering the emission of microbial aerosol (such as rainfall). The model itself is also adaptable as an emission module for dispersion and chemical transport models, allowing further exploration of the impact of landcover-driven microbial aerosols on the atmosphere and climate.

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

Cited by 52 publications

References 78 publications

Real-time sensing of bioaerosols: Review and current perspectives

Real-time sensing of bioaerosols: Review and current perspectives

Activation of Intact Bacteria and Bacterial Fragments Mixed with Agar as Cloud Droplets and Ice Crystals in Cloud Chamber Experiments

Measurements and modeling of surface–atmosphere exchange of microorganisms in Mediterranean grassland

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