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Flat glass is a common type of evidence collected from the scenes of crimes such as burglaries, vandalism, and hit-and- run accidents. The usefulness of such evidence lies in the ability to associate the glass from the scene (or a suspect) to the original source. Physical and chemical analysis of the glass can be used for discrimination between the possible sources of glass. If the sample is large enough, physical attributes such as fracture matches, density, color, and thickness can be employed for comparison between a recovered fragment(s) to the suspect source. More commonly, refractive index (RI) comparisons are employed. Due to the improved control over glass manufacturing processes, RI values often cannot differentiate glasses where approximately 6 - 9% of casework samples are not expected to be distinguished by RI alone even if they originated from different sources. Employing methods such as NAA, XRF, ICP-AES, and ICP-MS for the comparison of trace elemental compositions has been shown to be more discriminating than RI comparisons. The multielement capability and the sensitivity of ICP-AES and ICP-MS provide for excellent discrimination power. In this work, the sources of variability in ICP-MS of glass analysis are investigated to determine possible sources of variation. The sources of variation examined include errors due to sample preparation, instrument accuracy and precision, and interlaboratory reproducibility. Other sources of variation include inhomogeneity across a sheet of glass from the same source. Analysis of variance has been applied to our ICP-MS analysis of NIST standards and to the interlaboratory comparisons of float glass samples collected across a sheet in a production facility. The results of these experiments allows for a more accurate interpretation of forensic glass data and a better understanding of the discriminating power (absolute and practical) of ICP-MS.
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