Improving forensic casework analysis and interpretation of gunshot residue (GSR) evidence

University of Technology, Sydney. Faculty of Science.There are two main challenges to gunshot residue (GSR) evidence. The first concerns analysis. The lack of screening techniques complicates sampling and analysis of large areas or numbers of exhibits. Also, lead or heavy metal free ammunitions present limitations to the technique for confirmatory detection of residues - scanning electron microscopy/energy dispersive X-ray analysis (SEM/EDX). A screening technique was developed to detect GSR components from all ammunition types. Ion mobility spectrometry (IMS) was proven to allow sensitive and effective screening before proceeding to confirmatory analysis. Lead and heavy metal free ammunitions were examined and a technique developed for detecting components in the organic portion of the residue. Liquid chromatography tandem mass spectrometry (LC-MS/MS) was extremely effective, detecting twenty seven components. The technique is sensitive (to around 1 ppb ), selective, rapid and cost effective. The combination of IMS, SEM/EDX and LC-MS/MS, with visual, physica] and microscopic examination, is proposed as a complete protocol for GSR analysis from all ammunition types. The second challenge involves interpretation. Factors that lead to positive and negative findings must be considered and the weight of evidence assessed. Both background data and application of an interpretive framework have been inadequate. Background levels of GSR in the NSW general population and NSW Police Force were studied and the chances of random presence on a suspect and of contamination during arrest and sampling process determined. Nil GSR was detected on hands of the NSW general population or the sample of general duties police officers. A moderate probability was demonstrated for low levels of GSR on hands of crime scene investigators. GSR was detected on hands of all forensic firearms examiners tested, however their role limits access to suspects and items sampled for GSR, limiting the chance of contamination. Significantly, one high risk area for contamination was identified, the tactical response officers. Background levels of GSR in the Australian Federal Police laboratories were compared before and after implementing contamination controls. The configuration of the original laboratory along with the lack of controls lead to GSR being detected on almost every sample. The newer laboratory was extremely clean, only one GSR particle being detected, demonstrating the importance of effective contamination controls during sample collection and analysis. A statistical interpretive framework was developed. The model utilises Bayesian networks to consider existing data relating to transfer and persistence, and new data from this research, providing more objective assessment and allowing broader application of the Bayesian framework