Two algorithms for the complete automation of background estimation in
ICP emission spectroscopy are presented and evaluated. One of these a
lgorithms is based on heuristic spectral interpretation, while the oth
er is based on statistical spectral interpretation. These algorithms b
oth address the weaknesses of the conventionally employed approaches o
f blank subtraction in calibration and background estimation through i
nterpolation from analyst-selected wavelengths adjacent to the analyte
peak. In a rigorous evaluation with synthetic spectra, these algorith
ms are characterized for performance in terms of accuracy, precision,
and robustness. As a demonstration of the algorithms' performance with
experimentally measured spectra, a determination of uranium in the pr
esence of a calcium background interference is performed. These algori
thms require no analyst interaction for their operation, and they esti
mate the background for every spectrum measured.