Shooting distance estimation based on gunshot residues analyzed by XRD and multivariate analysis

Abstract

The most used and validated methods for estimating the shooting distance using the gunshot residues (GSR) in forensic labs are based on chemographic colour tests. In these techniques, the cloth-trapped residues are transferred to a surface to be revealed using chemical reagents. However, because they imply a visual inspection, their interpretation may vary, thus adding possible errors to the forensic results. Therefore, it is important to find an objective analysis technique for deciding during the results interpretation. In this study, X-Ray diffraction (XRD) was used to measure the GSR on cotton-polyester fabrics. The resulting diffractograms were aligned using a correlation optimized warping (COW) function, and then analysed using partial least squares to latent structures (PLS), and orthogonal PLS (OPLS). Both methods gave good prediction models in the 5–300 cm distance range, with determination coefficients of 0.99. Using the gun utilized during the shooting rendered good prediction models with quite small prediction errors (about 3 and 7%). Combining the two guns for the calculations, resulted in a prediction model with a larger prediction error (about 14%) but still good for predicting the shooting distance. This would indicate that it is possible to use a similar gun to perform a shooting distance prediction without having the actual gun used during the investigated shooting.