Scanning infrared remote sensing system for identification, visualization, and quantification of airborne pollutants

Roland Harig; Gerhard Matz; Peter Rusch

doi:10.1117/12.455146

7 February 2002 Scanning infrared remote sensing system for identification, visualization, and quantification of airborne pollutants

Roland Harig, Gerhard Matz, Peter Rusch

Author Affiliations +

Proceedings Volume 4574, Instrumentation for Air Pollution and Global Atmospheric Monitoring; (2002) https://doi.org/10.1117/12.455146
Event: Environmental and Industrial Sensing, 2001, Boston, MA, United States

Abstract

Remote sensing by Fourier-transform infrared (FTIR) spectrometry allows detection, identification, and quantification of airborne pollutants. In the case of leaks in pipelines or leaks in chemical plants, chemical accidents, terrorism, or war, hazardous compounds are often released into the atmosphere. Various Fourier-transform infrared spectrometers have been developed for the remote detection and identification of hazardous clouds. However, for the localization of a leak and a complete assessment of the situation in the case of the release of a hazardous cloud, information about the position and the size of a cloud is essential. Therefore, an imaging passive remote sensing system comprised of an interferometer (Bruker OPAG 22), a data acquisition, processing, and control system with a digital signal processor (FTIR DSP), an azimuth-elevation-scanning mirror, a video system with a DSP, and a personal computer has been developed. The FTIR DSP system controls the scanning mirror, collects the interferograms, and performs the Fourier transformation. The spectra are transferred to a personal computer and analyzed by a real-time identification algorithm that does not require background spectra for the analysis. The results are visualized by a video image, overlaid by false color images. For each target compound of a spectral library, images of the coefficient of correlation, the signal to noise ratio, the brightness temperature of the background, the difference between the temperature of the ambient air and the brightness temperature of the background, and the noise equivalent column density are produced. The column densities of all directions in which a target compound has been identified may be retrieved by a nonlinear least squares fitting algorithm and an additional false color image is displayed. The system has a high selectivity, low noise equivalent spectral radiance, and it allows identification, visualization, and quantification of pollutant clouds.

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Roland Harig, Gerhard Matz, and Peter Rusch "Scanning infrared remote sensing system for identification, visualization, and quantification of airborne pollutants", Proc. SPIE 4574, Instrumentation for Air Pollution and Global Atmospheric Monitoring, (7 February 2002); https://doi.org/10.1117/12.455146

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