We report the successful use of colorimetric arrays to identify chemical warfare agents (CWAs). Methods were developed to interpret and analyze a 73-indicator array with an entirely automated workflow. Using a cross-validated first-nearest-neighbor algorithm for assessing detection and identification performances on 632 exposures, at 30 min postexposure we report, on average, 78% correct chemical identification, 86% correct class-level identification, and 96% correct red light/green light (agent versus non-agent) detection. Of 174 total independent agent test exposures, 164 were correctly identified from a 30 min exposure in the red light/green light context, yielding a 94% correct identification of CWAs. Of 149 independent non-agent exposures, 139 were correctly identified at 30 min in the red light/green light context, yielding a 7% false alarm rate. We find that this is a promising approach for the development of a miniaturized, field-portable analytical equipment suitable for soldiers and first responders.

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Diffuse reflection data are presented for ethyl methylphosphonate in a fine Utah dirt sample as a model system for organophosphate-contaminated soil. The data revealed a chemometric artifact when the spectra were represented in Kubelka-Munk units that manifests as a linear dependence of spectral peak height on variations in the observed baseline position (i.e., the position of the observed transmission intensity where no absorption features occur in the sample spectrum). We believe that this artifact is the result of the mathematical process by which the raw data are converted into Kubelka-Munk units, and we developed a numerical strategy for compensating for the observed effect and restoring chemometric precision to the diffuse reflection data for quantitative analysis while retaining the benefits of linear calibration afforded by the Kubelka-Munk approach. We validated our Kubelka-Munk correction strategy by repeating the experiment using a simpler system--pure caffeine in potassium bromide. The numerical preprocessing includes conventional multiplicative scatter correction coupled with a baseline offset correction that facilitates the use of quantitative diffuse reflection data in the Kubelka-Munk formalism for the quantitation of contaminants in a complex soil matrix, but is also applicable to more fundamental diffuse reflection quantitative analysis experiments.

Decontamination waste from chemical weapons (CW) agents has been stored in ton containers on Johnston Atoll since 1971. The waste was recently sampled and analyzed to determine its chemical composition in preparation for disposal. Due to the range of products and analytical requirements, multiple chromatographic and spectroscopic methods were necessary, including gas chromatography/ mass spectrometry (GC/MS), gas chromatography/ atomic emission detection (GC/AED), liquid chromatography/ mass spectrometry (LC/MS), capillary electrophoresis (CE), and nuclear magnetic resonance spectroscopy (NMR). The samples were screened for residual agents. No residual sarin (GB) or VX was found to detection limits of 20 ng/mL, but 3% of the samples contained residual sulfur mustard (HD) at <140 ng/mL. Decontamination products of agents were identified. The majority (74%) of the ton containers were documented correctly, in that the observed decontamination products were in agreement with the labeled agent type, but for a number of the containers, the contents were not in agreement with the labels. In addition, arsenic compounds that are decontamination products of the agent lewisite (L) were observed in a few ton containers, suggesting that lewisite was originally present but not documented. This study was a prototype to demonstrate the level of effort required to characterize old bulk CW-related waste.

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