Detecting aerosols and vapors with Fourier-transform infrared spectrometers

Two experiments are conducted with a Fourier transform infrared (FTIR) spectrometer. (1) to detect and identify Bacillus subtilis subsp. niger (BG) bio-aerosol in an open-air release and (2) to estimate the concentration of a small amount of triethyl phosphate (TEP) vapor in a closed chamber. The algorithms are based on radiative transfer theory and statistical signal processing methods. A subspace orthogonal projection operator is used to statistically subtract the large thermal background contribution to the measurements and a robust maximum likelihood solution is used to deduce the target spectrum and estimate its mass-column concentration. The deduced BG (TEP) extinction spectrum matched the library spectrum very well. The estimation of the TEP vapor time-dependent concentration is excellent. Detection threshold and probabilities of detection and false alarm are computed (expectation-maximization) with a Gaussian-mixture model. The results of this study are encouraging, as they suggest, for the first time to our knowledge, the feasibility of detecting bio-aerosols with passive FTIR sensors