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Improvements were made to a pyrolysis-gas chromatography-ion mobility spectrometry stand-alone biodetector to provide more pyrolyzate compound information to the IMS detector module. Air carrier gas flowing continuously through the pyrolysis tube, the rate of air flow, and pyrolysis rate were found to improve the relative quality and quantity of pyrolyzate compounds detected by the IMS detector compare to earlier work. These improvements allowed a greater degree of confidence in the correlation of biological aerosols obtain in outdoor testing scenarios to a standard GC-IMS biological aerosol dataset. The airflow improvement allowed more biomarker compounds to be observed in the GC-IMS data domain for aerosols of Gram-negative Erwinia herbicola (EH) and ovalbumin protein as compared to previous studies. Minimal differences were observed for Gram-positive spores of Bacillus subtilis var. globigii (BG) from that of earlier work. Prior outdoor aerosol challenges dealt with the detection of one organism, either EH or BG. Biological aerosols were disseminated in a Western Canadian prairie and the Py-GC-IMS was tested for its ability to detect the biological aerosols. The current series of outdoor trials consisted of three different biological aerosol challenges. Forty-two trials were conducted and a simple area calculation of the GC-IMS data domain biomarker peaks correlated with the correct bioaerosol challenge in 30 trials. In another 7 trials, the status of an aerosol was determined to be biological in origin. Two additional trials had no discernible, unambiguous GC-IMS biological response, because they were black water sprays. Reproducible limits of detection were at a concentration of less than 0.5 bacterial analyte-containing particles per liter of air (ACPLA). In order to realize this low concentration, an aerosol concentrator was used to concentrate 2000 liters of air in 2.2 minutes. Previous outdoor aerosol trials have shown the Py-GC-IMS device to be a credible detector with response to determining the presence of a biological aerosol. The current series of outdoor trials has provided a platform to show that the Py-PC-IMS can provide information more specific than a biological or non-biological analysis to an aerosol when the time of dissemination is unknown to the operator. The Py-GC-IMS is shown to be able to discriminate between aerosols of a Gram-positive spore, a Gram-negative bacterium and a protein.
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