All objects emit infrared energy.  The amount of energy depends mostly on the object's temperature while the spectral qualities of the emitted energy largely depend on the object's composition.  As an example, a plume of steam being exhausted into the open atmosphere will emit quite a bit of infrared energy  If we look at the spectral characteristics of the emitted energy with an infrared spectrometer, we'll find the infrared spectrum of the plume looks a lot like the infrared spectrum of water.  If the plume is from a coal-burning power plant, we may also see the infrared signature of sulfur dioxide (a by-product from the combustion of coal) in the energy emitted by the plume.  Analysis of heated plumes in this way is a typical application of FT-IR remote sensing.

    FT-IR remote sensing offers some obvious advantages over active FT-IR air monitoring, with the most obvious advantage being the ease with which data can be collected from a distance and without access to the site being monitored. Unfortunately, it is often difficult if not impossible to obtain the same quality of information from passive FT-IR monitoring as can be obtained using active FT-IR air monitoring techniques.

    Like active techniques, passive FT-IR techniques detect molecules by identification of their characteristic infrared signatures in the spectra collected.  In active monitoring, though, the signatures always appear as absorption bands thanks to the high-temperature element used as the source of the infrared beam.  In passive spectra, the signatures may appear as emission bands if the temperature of the background scene is cooler than the cloud or plume being monitored (as it usually is if the background scene is the sky).

    Unfortunately, emission bands are a lot tougher to characterize than absorption bands, making the reduction of spectral data to actual information concerning analyte levels much more difficult.  Also, generation of quantitative information from emission bands requires knowledge of the FT-IR instrument's response function.  The instrument's response function is best determined by collecting certain calibration spectra in the field at approximately the same time as the sample spectra are collected and this usually requires some extra field equipment and expertise . Without such calibration spectra, the results of any passive FT-IR monitoring investigation will probably be limited to qualitative or semi-quantitative information only.

    If you have followed the discussion so far, you may be wondering about situations in which passive spectra are collected with background scenes that are warmer than the analyte plume or cloud being monitored.  It turns out that this is not too difficult a situation to arrange on many industrial sites because of the abundance of warm structures like baghouses, boilers, and cooling towers.  It also turns out that the infrared absorption signatures seen in spectra collected against such warm backgrounds can be interpreted in much the same way as the same infrared signatures would be interpreted in active open-path FT-IR spectra.  When such on-site sources of infrared energy have been used by AeroSurvey, detection limits have even approached those associated with traditional active FT-IR air monitoring (i.e., using infrared light we introduce into the sample) and quantitative information has been easily obtained from the spectra collected.

Follow the first link below to see some examples of passive monitoring applications, including photographs and examples of passively-collected spectra.