Paper
17 September 2009 Bioaerosols standoff detection simultaneously refereed with particle concentration (ppl) and viability units (ACPLA)
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Abstract
Defence R&D Canada (DRDC) has developed, by the end of the 90s, a standoff bioaerosol sensor prototype based on intensified range-gated spectrometric detection of Laser Induced Fluorescence (LIF) called SINBAHD. This LIDAR system was used to characterize spectrally the LIF of bioaerosol agent simulants and obscurants during 57 cross-wind open-air releases at Suffield, CAN in July 2007. An autoclave and gamma-irradiation killing procedures were performed on Bacillus subtilis var globigii (BG) samples before they were aerosolized, disseminated and spectrally characterized. Slight discrepancies were observed in the spectral characteristics of killed versus live samples but none between the two killing methodologies. Significant signature variabilities were observed from the different batches of Erwinia Herbicolas (EH). The generated cloud was simultaneously characterized in Agent Containing Particle per Liter of Air (ACPLA) by slit sampler units and in particle per litter of air (ppl) by an Aerodynamic Particle Sizer (APS). Correlation assessment between the stand-off sensor SINBAHD and the two referee point sensors was done, allowing an estimation of SINBAHD's sensitivity in ACPLA and in ppl. For a 20-m thick cloud at a range of 990 m, a detection limit of a few tens of ACPLA and a few ACPLA were obtained for BG and EH respectively. The extracted correlation between ACPLA and ppl data for releases performed with an agricultural sprayer showed a high degree of variability: 2 to 29% and 1 to 6% of ACPLA/ppl ratio for BG and EH, respectively.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sylvie Buteau, Jean-Robert Simard, and Susan Rowsell "Bioaerosols standoff detection simultaneously refereed with particle concentration (ppl) and viability units (ACPLA)", Proc. SPIE 7484, Optically Based Biological and Chemical Detection for Defence V, 748408 (17 September 2009); https://doi.org/10.1117/12.830360
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Cited by 3 scholarly publications.
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KEYWORDS
Sensors

Clouds

Laser induced fluorescence

Aerosols

LIDAR

Atmospheric particles

Particles

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