## 7 Conclusions  
The constructed simulation model has been compared to experimentally obtained results. The simulated effect of water vapor on a measurement using KT19 underestimates the sensitivity to humidity between 23% and 27% throughout the expected atmospheric humidity range, which is significant. The simulated effect of emissivity uncertainty [0.93; 0.97] closely corresponds to experimental results. The experimentally obtained standard uncertainty contribution due to uncertainty of emissivity was over assessed by 6.7% for the low temperature range and 2.4% for the high temperature range in case 2. The effect of emissivity and reflection temperature was further compared to results from the literature, with the simulation corresponding to reported results within \(\pm\)11%. The uncertainty analysis was performed for multiple envisioned cases of radiation thermometry use. A model of radiation thermometry was constructed and analytical and Monte Carlo simulations were performed, the latter by using a high number (10,000) of input parameter deviation calculations. Uncertainty simulations focused on spectral influence parameters (e.g., spectral sensitivity of the detector) and temperatures, which they are associated with. Five parameters were of key interest in uncertainty simulations: spectral emissivity, radiant temperature of reflection, relative humidity and temperature of the air as well as the atmospheric distance. No other uncertainty contributions have been accounted for in the obtained results, such as calibration uncertainty of the instrument, drift, etc. These uncertainty contributions were omitted in this study and should be added when stating the full measurement uncertainty of the instrument. Specified uncertainty results are expressed as standard uncertainties (\(k=1\)) and can be expanded by the use of multiplication with a coverage factor, e.g., \(k=2\). Case 1 considers using Heitronics KT19.01 as a reference thermometer in calibration by comparison. As no atmospheric correction was used, the uncertainty of atmospheric conditions has been increased to correspond to the change in conditions between the calibration of a reference instrument and subsequent calibrations with that reference instrument. As Heitronics KT19.01 is notorious for its humidity dependence due to the spectral range of measurement, the calculated expanded measurement uncertainty of about 8 \({}^{\circ}\)C is in line with expectations. Compensation of atmospheric influences has been proposed to improve the measurement uncertainty of this instrument. Case 2 is a radiation thermometer calibration by using a flat plate calibrator. Despite manufacturer's common claims of low calibration uncertainties when using flat plate calibration devices, nominal emissivity uncertainties of typical radiators (0.95 \(\pm\) 0.02) contribute significantly to the uncertainty of calibration, in this case reaching the expanded  
Figure 25: Monte Carlo simulated standard measurement uncertainty (\(k=1\)) of a real body temperature measurement using FTIR obtained spectral emissivity measurement and vanadium oxide-based thermal imager. measurement uncertainty near 4 \({}^{\circ}\)C. By choosing radiation thermometers which operate in shorter wavelength ranges, it is possible to obtain lower uncertainty, however the influence of spectral emissivity should be considered as well. Case 3 is a general case of thermal imager use. While atmospheric compensation is present with thermal imagers, emissivity is usually unknown or poorly assessed. Uncertainties, calculated for rather high input uncertainties of emissivity, correspond to the use of radiation thermometers with real objects using general emissivity lookup tables. Obtained uncertainties are high; therefore, such radiation thermometry practice can be expected to yield questionable measurements.