  National security relies on several layers of protection. One of the most
important is the traffic control at borders and ports that exploits Radiation
Portal Monitors (RPMs) to detect and deter potential smuggling attempts. Most
portal monitors rely on plastic scintillators to detect gamma rays. Despite
their poor energy resolution, their cost effectiveness and the possibility of
growing them in large sizes makes them the gamma-ray detector of choice in
RPMs. Unmixing algorithms applied to organic scintillator spectra can be used
to reliably identify the bare and unshielded radionuclides that triggered an
alarm, even with fewer than 1,000 detected counts and in the presence of two or
three nuclides at the same time. In this work, we experimentally studied the
robustness of a state-of-the-art unmixing algorithm to different radiation
background spectra, due to varying atmospheric conditions, in the 16 $^\circ$C
to 28 $^\circ$C temperature range. In the presence of background, the algorithm
is able to identify the nuclides present in unknown radionuclide mixtures of
three nuclides, when at least 1,000 counts from the sources are detected. With
fewer counts available, we found larger differences of approximately 35.9$\%$
between estimated nuclide fractions and actual ones. In these low count rate
regimes, the uncertainty associated by our algorithm with the identified
fractions could be an additional valuable tool to determine whether the
identification is reliable or a longer measurement to increase the
signal-to-noise ratio is needed. Moreover, the algorithm identification
performances are consistent throughout different data sets, with negligible
differences in the presence of background types of different intensity and
spectral shape.
