The detection of residual gasoline for forensic soil investigation in arson

Cheenmatchaya, Arunrat; Kungwankunakorn, Sukjit

doi:10.1080/00450618.2016.1225817

Cited by 5 publications

(5 citation statements)

References 17 publications

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“…The spectrum of gasoline is clearly distinguishable from that of kerosine and diesel. Gasoline detection is important as it is the most common accelerant used in reported arson cases [2]. same as shown above in Figure 3(a).…”

Section: Reference Spectra and Spectral Librarymentioning

confidence: 99%

“…Arsonist typically uses cheap, easily obtainable common ignitable liquids to accelerate combustion. According to statistics most arson cases involve gasoline, diesel, or high-concentration alcohol as an accelerant [2] [3] [4]. Therefore, for the investigator, the identification of accelerants and ignitable liquids are important for determining the nature and cause of the fire.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Rapid Detection of Accelerants in Fire Debris Using a Field Portable Mid-Infrared Quantum Cascade Laser Based Analyzer

Huang,

Zhang,

Dai

et al. 2023

OJAppS

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Arson presents a challenging crime scene for fire investigators worldwide. Key to the investigation of suspected arson cases is the analysis of fire debris for the presence of accelerants or ignitable liquids. This study has investigated the application and method development of vapor phase mid-Infrared (mid-IR) spectroscopy using a field portable quantum cascade laser (QCL) based system for the detection and identification of accelerant residues such as gasoline, diesel, and ethanol in fire debris. A searchable spectral library of various ignitable fluids and fuel components measured in the vapor phase was constructed that allowed for real-time identification of accelerants present in samples using software developed in-house. Measurement of vapors collected from paper material that had been doused with an accelerant followed by controlled burning and then extinguished with water showed that positive identification could be achieved for gasoline, diesel, and ethanol. This vapor phase mid-IR QCL method is rapid, easy to use, and has the sensitivity and discrimination capability that make it well suited for non-destructive crime scene sample analysis. Sampling and measurement can be performed in minutes with this 7.5 kg instrument. This vibrational spectroscopic method required no time-consuming sample pretreatment or complicated solvent extraction procedure. The results of this initial feasibility study demonstrate that this portable fire debris analyzer would greatly benefit arson investigators performing analysis on-site.

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Section: Reference Spectra and Spectral Librarymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Rapid Detection of Accelerants in Fire Debris Using a Field Portable Mid-Infrared Quantum Cascade Laser Based Analyzer

Huang,

Zhang,

Dai

et al. 2023

OJAppS

View full text Add to dashboard Cite

show abstract

“…Cheenmatchaya and Kungwankunakorn investigated gasoline permeation on four types of soils to determine optimum soil sampling depth [ 92 ]. The authors simulated fire scenes by pouring 40 ml of a mixture of gasoline and ethanol on a 1600 cm 2 surface of soil, setting it on fire, and letting it burn for 40 min by adding fire wood.…”

Section: Laboratory Examinationmentioning

confidence: 99%

Interpol review of fire investigation 2016–2019

Stauffer

2020

Forensic Science International: Synergy

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“…Gasoline is one of the ignitable liquids (ILs) that has been widely used to accelerate fires in arson cases . The identification of gasoline may provide investigative lead or linkage to the suspect and assist in investigating the cause of an incendiary fire . Gasoline octane numbers can become essential information that helps the investigators determine the ILs used to set a fire.…”

mentioning

confidence: 99%

“…1 The identification of gasoline may provide investigative lead or linkage to the suspect and assist in investigating the cause of an incendiary fire. 2 Gasoline octane numbers can become essential information that helps the investigators determine the ILs used to set a fire. However, the current standard to test gasoline octane numbers following ASTM D2700-16 is a timeconsuming process 3 and requires analysis by an accredited laboratory.…”

mentioning

confidence: 99%

Development of Crime Scene Intelligence Using a Hand-Held Raman Spectrometer and Transfer Learning

Huang

2021

Anal. Chem.

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The classification of ignitable liquids, such as gasoline, is critical crime scene intelligence to assist arson investigations. Rapid field gasoline classification is challenging because the current forensic testing standard requires gas chromatography–mass spectrometry analysis of evidence in an accredited laboratory. In this work, we reported a new intelligent analytical platform for field identification and classification of gasoline evidence. A hand-held Raman spectrometer was utilized to collect Raman spectra of reference gasoline samples with various octane numbers. The Raman spectrum pattern was converted into image presentations by continuous wavelet transformation (CWT) to facilitate artificial intelligence development using the transfer learning technique. GoogLeNet, a pretrained convolutional neural network (CNN), was adapted to train the classification model. Six different classification models were also developed from the same data set using conventional machine learning algorithms to evaluate the performance of our new approach. The experimental results indicated that the pretrained CNN model developed by our new data workflow outperformed other models in several performance benchmarks, such as accuracy, precision, recall, F1, Cohen’s Kappa, and Matthews correlation coefficient. When the transfer learning model was challenged with the data collected from weathered gasoline samples, the classifier could still offer 73 and 53% accuracy for 50 and 25% weathered gasoline samples, respectively. In conclusion, wavelet transforms combined with transfer learning successfully processed and classified complex Raman spectral data without feature engineering. We envision that this nondestructive, automated, and accurate platform will accelerate crime scene intelligence development based on evidence’s chemical signatures detected by hand-held Raman spectrometers.

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The detection of residual gasoline for forensic soil investigation in arson

Cited by 5 publications

References 17 publications

Rapid Detection of Accelerants in Fire Debris Using a Field Portable Mid-Infrared Quantum Cascade Laser Based Analyzer

Rapid Detection of Accelerants in Fire Debris Using a Field Portable Mid-Infrared Quantum Cascade Laser Based Analyzer

Interpol review of fire investigation 2016–2019

Development of Crime Scene Intelligence Using a Hand-Held Raman Spectrometer and Transfer Learning

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