University of Hertfordshire

Documents

  • Elizabeth Forde
  • Martin Gallagher
  • Maurice Walker
  • Virginia Foot
  • Alexis Attwood
  • Gary Granger
  • Roland Sarda-Esteve
  • Warren Stanley
  • Paul H. Kaye
  • David Topping
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Original languageEnglish
Article number797
Pages (from-to)1-29
Number of pages29
JournalAtmosphere
Volume10 (2019)
IssueSpecial Issue "Detection and Monitoring of Bioaerosols"
DOIs
Publication statusPublished - 9 Dec 2019

Abstract

Measurements of primary biological aerosol particles (PBAPs) have been conducted worldwide using ultraviolet light-induced fluorescence (UV-LIF) spectrometers. However, how these instruments detect and respond to known biological and non-biological particles, and how they compare, remains uncertain due to limited laboratory intercomparisons. Using the Defence Science and Technology Laboratory, Aerosol Challenge Simulator (ACS), controlled concentrations of biological and non-biological aerosol particles, singly or as mixtures, were produced for testing and intercomparison of multiple versions of the Wideband Integrated Bioaerosol Spectrometer (WIBS) and Multiparameter Bioaerosol Spectrometer (MBS). Although the results suggest some challenges
in discriminating biological particle types across different versions of the same UV-LIF instrument, a difference in fluorescence intensity between the non-biological and biological samples could be identified for most instruments. While lower concentrations of fluorescent particles were detected by the MBS, the MBS demonstrates the potential to discriminate between pollen and other biological
particles. This study presents the first published technical summary and use of the ACS for instrument intercomparisons. Within this work a clear overview of the data pre-processing is also presented, and documentation of instrument version/model numbers is suggested to assess potential instrument variations between different versions of the same instrument. Further laboratory studies sampling different particle types are suggested before use in quantifying impact on ambient classification.

ID: 17828247