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Shooting Distance Determination: Identifying Variables Affecting Lead Density on a Target

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Description of original award (Fiscal Year 2016, $112,317)

As submitted by the proposer: Empirical methods in forensic science have recently come under fire due to their subjectivity and the inability to perform a statistical analysis of the data and to report error rates on the results. Muzzle-to-target distance determinations is one analysis that depends heavily on colorimetric tests and visual comparison to a set of patterns shot from known distances. The purpose of this research is to determine the variables that affect the density of lead dPb on a target, develop analytic methods to control or account for these variables, and establish the conditions under which lead density is a sufficient factor for determining shooting distance. The new method will complement the existing colorimetric analysis by providing an alternative method that can provide a numerical value that supports the subjective analyses. The steps in the dPb method are similar to the guidelines established by the Scientific Working Group for Firearms and Toolmarks (SWGGUN) for the colorimetric distance determination. A series of test fires are made at known distances. Instead of using chemical tests to produce a visual calibration series, a linear calibration curve is generated by plotting lead density against the firing distance. The mass of lead contaminating the target is determined by extracting it from a specified area around the bullet hole with dilute nitric acid and measuring the concentration via atomic absorption spectroscopy. Preliminary research has shown that the linear relationship between lead density and distance is strong, with correlation coefficients of r2 = 0.94 or better. The goals of the project are to: • To validate the lead extraction method • To collect a large sample of test fires in order to calculate the number of test fires that must be collected in order to use linear regression methods for distance determination • To test the linear regression with test fires from known and unknown distances. Note: This project contains a research and/or development component, as defined in applicable law. Note: This project contains a research and/or development component, as defined in applicable law. ca/ncf
Date Created: September 13, 2016