Dissemination of SF6 and tracking its dispersion in the atmosphere is a well-known technique used to predict how pollutant affects the environment. Remote thermal imaging of the atmospheric tracer plume is one of the methods employed to detect and track its dispersion. However, remote detection of SF6 plumes in a stable boundary layer of the atmosphere (SBL) with a multispectral infrared sensor is a challenging task. At SBL conditions the tracer cloud tends to disperse very slowly and therefore its temporal signature is well mixed with the natural temperature variations over the background scene. Furthermore, SBL conditions are frequent during nighttime when the thermal contrast between the air and the background scene is very low. In this article we propose an efficient method to overcome these difficulties. The local temperature variance of the clean background is compared to the variance measured at the same position during the cloud presence in the field of view. The local temperature variance is modified by passage of radiation through the absorbing cloud. The distinctive spectral signature of the atmospheric tracer is expressed in the relative strength of the different spectral band of the IR sensor. The proposed technique is demonstrated with actual data collected during field test in an urban area. Urban background is particularly suitable for applying this method due to its inherent large thermal variance consisted of buildings, streets, parks etc. We demonstrate the usefulness of this detection method for accurate quantitative estimation of the tracer cloud density and its form.