This study investigates how the loading and composition of atmospheric dust affect IR radiances observed by satellite narrowband and high-resolution sensors. To compute monochromatic radiances accounting for multiple scattering and absorption by aerosols and atmospheric gases, we employed a new radiative transfer code which combines the line-by-line algorithm and discrete ordinate technique. New dust optical models required for such computations were developed for the representative mineral mixtures. We demonstrate that dust decreases the brightness temperature observed by satellite sensors depending mainly on the dust burden and composition, though the sensitivity to the composition differs between the satellite sensors. We found that mineral dust has a unique radiative signature (termed here a “negative slope”) which separates the effect of dust from that of clouds and gases. We conclude that dust must be accounted for in atmospheric correction algorithms if the retrievals of the sea surface temperature and atmospheric gaseous species from the thermal IR radiances are to be of high accuracy.