10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
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Factors Influencing Interpretation of Laser-Induced Fluorescence (LIF) Instruments for Bioaerosol Measurement
J. ALEX HUFFMAN, University of Denver, CO
Abstract Number: 1676 Working Group: Bioaerosols
Abstract Several classes of real-time characterization techniques have been developed and applied recently for the analysis of bioaerosols, with increasing attention in the last decade. Single-particle spectroscopy based on ultraviolet laser-induced fluorescence (UV-LIF) is currently among the most widely used technique for real-time detection and characterization of bioaerosols. The principle of utilizing fluorescence spectroscopy to detect and characterize bioaerosol hinges on the idea that most biological material contains a reasonably small set of characteristic fluorophore classes, e.g. aromatic amino acids or riboflavin, that can be used to differentiate it from non-biological material. Most online UV-LIF techniques for bioaerosols detection thus require components of the aerosol to exhibit intrinsic fluorescence, or autofluorescence. Many instruments have been developed by universities, government labs, and military research organizations. Built on their decades of work and to capitalize on the ability to detect and characterize bioaerosol properties in (semi)-real time, a host of companies have begun offering UV-LIF bioaerosol sensors over the last 10-15 years. Instruments such as the UV-APS (TSI) and WIBS (Droplet Measurement Technologies) have been widely utilized and employed in countless scientific studies, and instruments such as the Bioscout (Environics), Rapid-E (Plair), SIBS (DMT), IMD (BioVigilant), and MBS (Univ. Hertfordshire) are just a few of the many other UV-LIF instruments now available on the commercial marketplace.
High quality interpretation of biological aerosol measurements using fluorescence techniques must also necessarily include an understanding of the limitations of using fluorescence to measure these particles. For example, fluorescence intensity increases strongly as a function of particle size and is especially dependent on surface properties of the particle (e.g. membrane opacity). Detector sensitivity also usually varies as a function of wavelength. As a result, particle detection can be heavily influenced by technical details that influence whether a given particle will be above the noise threshold and thus be categorized as fluorescent or not in a given spectroscopic channel. Different instrument types and different operators may employ very different thresholding strategies, which can dramatically influence the interpretation of results. As a result of these factors, results from different instrument types are often challenging to compare and it is critical that end users properly keep these factors in mind when drawing conclusions from fluorescence-based bioaerosol spectrometers.
Significant work over several decades supported the development of the general technologies, but efforts to systematically characterize the operation of new commercial sensors has also remained somewhat lacking. Specifically, there have been gaps in the understanding of how different classes of biological and non-biological particles can influence the detection ability of LIF instrumentation. A solid understanding of interfering species, which may be very different if e.g. the instrument is operated in a remote field location or inside an occupied building, is critical. Factors related to aerosolization in laboratory studies can also significantly influence fluorescence properties of aerosol. For example, growth conditions of microorganisms may influence their viability state as well as other physical properties, and the choice of growth media can frequently introduce false-positives for fluorescence detection. Lastly, increasingly complex data analysis methods have been applied to commercial UV-LIF sensors, ranging from relatively simple, binary categorization of fluorescent vs non-fluorescent, to more complex applications of clustering or machine-learning algorithms. It is important to understand potential pitfalls of a given analysis style to optimize data interpretation, but this is often not a trivial task and can require significant laboratory study.
For this presentation I will give a brief overview of some of the laboratory, instrumental, and analysis factors involved in optimizing the quality of results for UV-LIF methods for bioaerosol sensing.