Monte Carlo uncertainty simulation of surface emissivity at ambient temperature obtained by dual spectral infrared radiometry

•Ambient temperature surface emissivity using dual spectral radiometry is evaluated.•Emissivity uncertainty is evaluated using Monte Carlo simulations.•Uncertainty is minimized for narrow, far apart, and low detector wavelength bands.•Uncertainty is maximized as background temperature approaches surface temperature.

The Monte Carlo statistical method was used to estimate the uncertainty of the emissivity, obtained by dual spectral infrared radiometry, of gray surfaces at ambient temperature. A large number of simulations were carried out, by selecting a wide range of values from parameters that directly affect the resulting emissivity: the emissivity of the target surface, the background temperature of the surrounding surfaces, the maximum error of the detectors, and the width and spectral location of the bands of the detectors.In summary, the level of uncertainty grows very quickly as the background temperature approximates the target surface. In terms of the spectral characteristics of the detectors, it was found that narrow bands, far apart from each other, and short wavelength bands provide the lowest uncertainty from all simulated emissivity values.