Abstract

At first glance, an examination of the bulk refractive indices for the 8–12 μm waveband of various bioaerosols suggests differentiation with respect to common background aerosols based upon the spectral characteristics of the absorption. The question of whether there is a spectral signature of bioaerosol clouds when those clouds are immersed in a typical atmosphere, including the boundary layer background aerosols, has been addressed in a simulation using the Weather and Atmospheric Visualization Effects for Simulation (WAVES) suite of codes. Using measured values of the refractive index for common bacterial spores, and their typical size distributions, the single-scattering, ensemble-averaged optical properties such as extinction/absorption coefficients, albedo, and the scattering phase function was computed for bioaerosol clouds at a resolution of 1 cm-1. WAVES was then used to calculate the radiative transfer for a finite sized cloud immersed in background. Results of this simulation indicate that, for a passive remote sensing measurement, it is unlikely that bioaerosol clouds can be identified from the spectral signature alone.

© 2002 Optical Society of America

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References

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Appl. Opt.

Astrophys. Space Sci.

S. Yabushita, and K. Wada, ???The Infrared and Ultraviolet Absorptions of Micro-Organisms and their relation to the Hoyle-Wickamasinghe Hypothesis,??? Astrophys. Space Sci. 110, 405-411 (1985).
[CrossRef]

Atmos. Environ.

R.W. Fenn. E.P Shettle, and W.S. Hering, et.al., ???Atmospheric optical properties and meteorological conditions,??? Atmos. Environ. 15, 1911???1918 (1981)
[CrossRef]

Field. Anal. Chem. Tech.

C.M.Gittins, L.G. Piper, W.T. Rawlins, W.J. Marinelli, J.O. Jensen, A.N. Akinyemi, ???Passive and Active Stando. Infrared Detection of Bio-Aerosols,??? Field. Anal. Chem. Tech. 3, 274???282 (1999).
[CrossRef]

Opt. Eng.

M.L.G. Althouse and C. Chang, ???Chemical vapor detection with a multispectral thermal imager,??? Opt. Eng. 30, 1725???1733 (1991).
[CrossRef]

Proc. SPIE

L. Carr, L. Fletcher, P. Holland, J. Leonelli, D. McPherrin, M. Althouse, ???Characterization of filtered FLIR systems designed for chemical vapor detection and mapping,??? in Infrared Imaging Systems: Design, Analysis, Modeling, and Testing, G.C.Holst, ed., Proc. SPIE Vol. 1309, 90???103 (1990).
[CrossRef]

Other

S.R. Horman, ???Remote Identi.cation of CWAgents by Spectral Techniques: Calculations of Cloud Emission in the Infrared,??? NSWC???TR???3457, (Clearinghouse for Federal Scientific and Technical Information, Cameron Station, VA., 1976).

D.F. Flanigan, ???Hazardous Cloud Imaging: An In-Depth Study, ??? ERDEC-TR-416 (Clearinghouse for Federal Scientific and Technical Information, Cameron Station, VA., 1997).

E.P Shettle, and R.W. Fenn, ???Models for the aerosols of the lower atmosphere and the effects of humidity variations on their optical properties,??? AFGL-TR-79-0214, (Clearinghouse for Federal Scientific and Technical Information, Cameron Station, VA., 1979).

D. Segelstein, ???The complex refractive index of water,??? M.S. Thesis, University of Missouri???Kansas City (1981); P. Ray, ???Broadband complex refractive indices of ice and water,??? Appl. Opt. 11, 1836-1844 (1972).
[CrossRef] [PubMed]

P.S. Gillespie, A.E. Wetmore, D.A. Ligon, ???Weather and Atmospheric Effects for Simulation: WAVES98 Suite Overview,??? ARL-TR-1721-1, (Clearinghouse for Federal Scientific and Technical Information, Cameron Station, VA., 1998).

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Figures (10)

Fig. 1.
Fig. 1.

Bulk refractive indices for the aerosol cloud materials; B. subtilis, M. luteus, and liquid water.

Fig. 2.
Fig. 2.

Ensemble–average extinction, scattering, and absorption coefficients for the aerosol cloud targets; a) Advection fog, b) Radiation fog, c) B. subtilis, and d) M. luteus

Fig. 3.
Fig. 3.

Single–scattering, ensemble–average phase functions for the model aerosol clouds; a) Advection Fog, b) Radiation Fog, c) B. subtilis, and d) M. luteus.

Fig. 4.
Fig. 4.

Geometry of the volume used in the radiative transfer calculation.

Fig. 5.
Fig. 5.

Limiting path radiance for a cloud aerosol loading of γ = 0.5 for the cloud in near field (R/R 0 = 0).

Fig. 6.
Fig. 6.

Limiting path radiance for an cloud aerosol loading of γ = 0.5 for the cloud in far–field (R/R 0 = 24).

Fig. 7.
Fig. 7.

Limiting path radiance for a large cloud aerosol loading of γ = 0.97 for the cloud in near–field (R/R 0 = 0).

Fig. 8.
Fig. 8.

Limiting path radiance for a large cloud aerosol loading of γ = 0.97 for the cloud in far–field (R/R 0 = 24).

Fig. 9.
Fig. 9.

Limiting path radiance for a dominate cloud aerosol loading of γ = 0.99 for the cloud in near–field (R/R 0 = 0).

Fig. 10.
Fig. 10.

Limiting path radiance for a dominate cloud aerosol loading of γ = 0.99 for the cloud in far–field (R/R 0 = 24).

Equations (6)

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c i ( k ) = 0 n ( r ) σ i ( kr ) dr ,
P Ω k = 1 c scat ( k ) 0 n ( r ) ( d σ scat kr Ω d Ω ) dr
n ( r ) = dN dr = A ' ( r r c ) α exp [ α γ ( r r c ) γ ] ,
A ' = N r c γ ( α γ ) α + 1 γ Γ ( α + 1 γ ) .
n ( r ) = dN dr = N 1 2 π σr exp [ ( ln r ln r c ) 2 2 σ 2 ] .
γ = β e , target Γ β e , target + β e , background Γ ,

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