5
Simulant Characteristics and Specifics

As noted in the Introduction, the use of simulants in the testing and evaluation of standoff detectors is necessitated by cost and toxicity considerations that accompany the use of chemical warfare agents (CWAs). An ideal simulant is one that would mimic all the properties of a CWA except for its toxicity. This is never achieved. Thus, only the primary properties important to a particular test can be found in an appropriate simulant. In this context the next sections discuss spectral simulants; that is, chemicals that have the necessary properties to calibrate the infrared spectral detector, and aerosol simulants; that is, chemicals that mimic the physical dispersion characteristics of CWAs as necessary components of the background and delivery concomitants that the detector might “see.”

SPECTRAL SIMULANTS

The type of compounds suitable as spectral simulants are those that give rise to similar spectral characteristics observed for a given CWA in the 10 µm atmospheric window, that is, between 700 and 1,300 cm–1. This criterion does not necessarily mean that the chemical structure of the simulant should be similar to that of the CWA; however, in light of the fact that most functional groups give rise to absorption bands that absorb in a characteristic frequency range, this is quite likely. Ideally, the strongest band in the spectrum of the simulant in the 10 µm atmospheric window should have its maximum absorption within 20 cm–1 of the CWA of interest. If the signal model for the particular CWA places significant weight on one or more other wave number regions, the spectrum of the simulant should also have bands of similar strength within 20 cm–1 of these regions. The spectrum of the simulant should not contain other absorption bands that are stronger than the two strongest bands in the spectrum of the CWA. In terms of their physical properties, spectral simulants should be volatile enough that problems due to aerosol formation do not arise.



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5 Simulant Characteristics and Specifics As noted in the Introduction, the use of simulants in the testing and evaluation of standoff detectors is necessitated by cost and toxicity considerations that accompany the use of chemical warfare agents (CWAs). An ideal simulant is one that would mimic all the properties of a CWA except for its toxicity. This is never achieved. Thus, only the primary properties important to a particular test can be found in an appropriate simulant. In this context the next sections discuss spectral simulants; that is, chemicals that have the necessary properties to calibrate the infrared spectral detector, and aerosol simulants; that is, chemicals that mimic the physical dispersion characteristics of CWAs as necessary components of the background and delivery concomitants that the detector might “see.” SPECTRAL SIMULANTS The type of compounds suitable as spectral simulants are those that give rise to similar spectral characteristics observed for a given CWA in the 10 µm atmospheric window, that is, between 700 and 1,300 cm–1. This criterion does not necessarily mean that the chemical structure of the simulant should be similar to that of the CWA; however, in light of the fact that most functional groups give rise to absorption bands that absorb in a characteristic frequency range, this is quite likely. Ideally, the strongest band in the spectrum of the simulant in the 10 µm atmospheric window should have its maximum absorption within 20 cm–1 of the CWA of interest. If the signal model for the particular CWA places significant weight on one or more other wave number regions, the spectrum of the simulant should also have bands of similar strength within 20 cm–1 of these regions. The spectrum of the simulant should not contain other absorption bands that are stronger than the two strongest bands in the spectrum of the CWA. In terms of their physical properties, spectral simulants should be volatile enough that problems due to aerosol formation do not arise.

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AEROSOL SIMULANTS Simulants for vapor-phase detection must closely approximate the vapor pressure and spectroscopic absorption bands of the agent being simulated. Aerosols and droplets add considerable complexity to the task of simulation since the distribution of the liquid or solid particles with respect to size depends on material properties, such as viscosity, surface tension, and density, on the method of dispersal, and meteorological conditions. Aerosol particles affect remote sensing observations by contributing to the signal; that is, by infrared emission spectrometry as in passive infrared measurements or absorption in both passive infrared measurements and active measurements such as lidar, and DIAL (differential absorption lidar). Absorption and emission properties of aerosols depend on both composition and particle size relative to the wavelength being probed. For small or weakly absorbing particles the absorption efficiency is proportional to the mass concentration of the absorbing species. On the other hand, large particles will appear to be black, so the emission scales with their projected areas. The size corresponding to the transition between mass and area-dependent absorption/emission depends on the strength of the absorption; that is, on the imaginary part of the refractive index at the particular wavelength being observed. Quantitative analysis of line-of-sight optical absorption or emission measurements thus depends on the size-dependent absorption efficiency and the particle size distribution. The influence of scattering must also be taken into account. For particles that are small compared to the wavelength of light, the scattering scales as d6, where d is the particle diameter, so small particles scatter little light. For particles much larger than the wavelength, the scattering is proportional to the projected area of the particle. For particles with diameters comparable in size to the wavelength (i.e., those in the so-called Mie scattering regime), the scattering efficiency (the ratio of the effective scattering cross section of a particle to its projected area) is a complex function of particle size and material properties and can be substantially larger than unity. The contribution of aerosol particles to the total extinction coefficient of the atmosphere along the line of sight is, thus, an integral over the product of the size-dependent scattering efficiency and the particle size distribution function. Moreover, even nonabsorbing particles scatter radiant energy, so the background aerosol will contribute to and in many cases dominate this mechanism of degradation of the remote sensing signal. A further complication arises at aerosol concentrations that are sufficiently high that multiple scattering must be taken into account. The presence of scattering particles is essential to active remote sensing methods such as lidar, becausethey scatter the probe pulse back to the detector. Return signals are generated by any atmospheric particles. Returns may be enhanced by the cloud produced when a chemical agent is dispersed, but other particles in the air will also contribute, including dust, smoke, fog, or clouds. This preamble highlights the difficulty of developing a generic simulant for agent aerosols and droplets. A rigorous simulation would require matching (1) the optical properties (imaginary and real parts of the refractive index) of the material; (2) the physical properties that determine the way the agent is dispersed, including but not limited to viscosity, surface tension, density, and vapor pressure (and the temperature dependence of those properties); (3) the dispersal method; and (4) the battlefield environment. Chamber experiments can be designed to evaluate the response of the sensor to the particulate agent but require special attention to the properties of suspended particles, particularly their tendency to be lost to chamber walls and to contaminate windows. The sedimentation velocity of a 10 µm droplet with a specific gravity of one is about 3 mm/s, and the sedimentation velocity scales as the d2. Thus, a chamber must be of substantial height to enable extended measurements of the optical effects of suspended particles. Even then, particle losses may be substantial since any air motions in the chamber

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will bring particles close to the surfaces where they can deposit much more quickly than quiescent sedimentation may suggest. Alternatively, a continuous source of aerosolized agent might be employed, although continuous evaporation will complicate quantification of vapor-phase concentrations. Issues in field validation experiments include (1) the ability to detect absorbing species that remain in aerosols or droplets, (2) the influence of particles produced by dispersal methods on the signals obtained from aerosolized agent, (3) the rate of evaporation of aerosols and droplets to produce vapors that may be detected, and (4) the influence of background aerosols on signals from both vapor and particulate agent. While exact duplication of the conditions of any battlefield release is unlikely, method validation is possible by “closure” studies in which the aerosol properties are characterized by in situ measurements of particle concentrations and size distribution, chemical composition, optical properties, etc., thereby enabling a direct comparison of modeled sensor response with field performance. Such closure studies have been successfully employed in many efforts to quantify the effect of aerosols (e.g., optically absorbing smoke, dust, and clouds) on the climate.19,20 19   J.L. Ross, P.V. Hobbs, and B. Holben. 1998. Radiative characteristics of regional hazes dominated by smoke from biomass burning in Brazil: Closure tests and direct radiative forcing, J. Geophys. Res. Atmos. 103:31925-31941. 20   D.R. Collins, H.H. Jonsson, J.H. Seinfeld, R.C. Flagan, S. Gasso, D.A. Hegg, P.B. Russell, B. Schmid, J. M. Livingston, E. Ostrom, K.J. Noone, L.M. Russell, and J.P. Putaud, 2000. In situ aerosol-size distributions and clear-column radiative closure during ACE-2. Tellus Ser. B-Chem. Phys. Meteorol. 52:498-525.