On the integrated analysis and forensic interpretation of gunshot residues

Author: Callum Bonnar

Bonnar, Callum, 2023 On the integrated analysis and forensic interpretation of gunshot residues, Flinders University, College of Science and Engineering

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Abstract

Gunshot residue (GSR) is a type of trace material that can be very important to the investigative, coronial, or criminal justice outcomes of incidents involving firearms. If scientists can identify and interpret these traces, they can contribute valuable information to the forensic process. The intent of this body of work was to improve the capabilities available to forensic practitioners, regarding this particular category of trace evidence.

Specifically, it was identified that contemporary GSR analyses largely target the inorganic portion of gunshot residues (IGSR). Forensic scientists already recognize that firearms also produce organic residues (OGSR). Research into the exploitation of OGSR traces as evidence has been well documented in academic literature, but as yet no single technique has been adopted into routine laboratory use. It is even rarer for an integrated (IGSR/OGSR) methodology, using data on both components of the trace, to be used forensically for either detection or evaluation of traces. The original contribution to knowledge made by this PhD project was the exploration of options for this unified approach.

New data on the subject were generated using combinations of laboratory experimentation, firing range fieldwork, and collection of survey samples. Authentic GSR samples were collected both from shooting experiments performed under controlled conditions and also following “natural” shooting activities undertaken by recreational shooters. It was found that liquid chromatography-mass spectrometry instrumentation, already available to forensic chemistry laboratories, could detect known OGSR compounds from recovered traces. A process for preparing subsamples for this organic analysis, while still retaining the possibility of inorganic analysis by scanning electron microscopy (SEM-EDS), was developed. Further samples were collected alongside written surveys asking about recent firearm use. Analysis of the pool of “non-shooter” background samples gave confidence that the combination of analytical methods was specific for the detection of GSR, with few to no false positives. This tandem approach offers potential improvement over current methodologies, as it increases the mass of material that can be targeted for detection. It also allows greater confidence when discriminating between GSR and inorganic, environmental GSR-like interferences by providing more chemical data to the analyst from each trace. These data are applicable to sub-source and activity-level evaluations used by experts in some jurisdictions when presenting their findings.

Next, different strategies for combining the outputs of each test into a single reportable result were investigated. Initially, the inorganic and organic laboratory tests were judged to indicate whether samples were either “positive” or “negative” for GSR using separate, predetermined categorical requirements. A Bayesian updating approach was then used to show that a statistical improvement in diagnostic accuracy was achieved when using two categorical tests in tandem. More advanced statistical methods including both univariate and multivariate models were also used to generate likelihood ratios representing the potential strength of evidence that could be provided to an investigator or courtroom. Of several techniques evaluated, artificial neural networks were chosen as the preferred method for synthesising multivariate data into a cohesive output without needing to discard any underlying information. Some perceived advantages and disadvantages of choosing categorical or likelihood ratio-based reporting are discussed. Data were also used as examples to perform certain sub-source and activity-level evaluations.

Finally, two separate spectrometers featuring ambient-ionisation capability were assessed for possible use as rapid and selective detectors for analysing GSR. Both “Direct Sample Analysis” (DSATM) and “Direct Analysis in Real-Time” (DART®) ion-sources were found to be capable of desorbing and ionising relevant OGSR compounds. Either instrument was suitable for analysing, and potentially discriminating between, smokeless powders collected in their unburned state. However, the outcomes for GSR samples collected using adhesive stubs were poor due to a significant background signal arising from the adhesive in the stubs themselves. Therefore it is suggested that any future efforts to incorporate AIMS into a GSR detection procedure should focus on sample collection or isolation procedures.

In summary, the integrated analysis of GSR traces was found by the author to both be technically feasible and to offer greater value to forensic scientists than the sum of its parts.

Keywords: gunshot residue, organic gunshot residue, smokeless powder, firearms, ambient mass spectrometry, forensic science, forensic chemistry, trace evidence, forensic statistics, integrated analysis, tandem analysis, bayesian statistics, likelihood ratios

Subject: Forensic & Analytical Chemistry thesis

Thesis type: Doctor of Philosophy
Completed: 2023
School: College of Science and Engineering
Supervisor: Prof. K Paul Kirkbride