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Detection of metabolites of trapped humans using ion mobility spectrometry coupled with gas chromatography
journal contributionposted on 09.10.2014, 09:26 by Wolfgang Vautz, Rafael Slodzynski, Chandrasekhara Hariharan, Luzia Seifert, Jurgen Nolte, Rita Fobbe, Stefanie Sielemann, Bolan C. Lao, Ran Huo, Paul Thomas, Lars Hildebrand
For the first time, ion mobility spectrometry coupled with rapid gas chromatography, using multicapillary columns, was applied for the development of a pattern of signs of life for the localization of entrapped victims after disaster events (e.g., earthquake, terroristic attack). During a simulation experiment with entrapped volunteers, 12 human metabolites could be detected in the air of the void with sufficient sensitivity to enable a valid decision on the presence of a living person. Using a basic normalized summation of the measured concentrations, all volunteers involved in the particular experiments could be recognized only few minutes after they entered the simulation void and after less than 3 min of analysis time. An additional independent validation experiment enabled the recognition of a person in a room of ∼25 m3 after ∼30 min with sufficiently high sensitivity to detect even a person briefly leaving the room. Undoubtedly, additional work must be done on analysis time and weight of the equipment, as well as on validation during real disaster events. However, the enormous potential of the method as a significantly helpful tool for search-and-rescue operations, in addition to trained canines, could be demonstrated.
We want to acknowledge the excellent preparation and performance of the “Trapped Human Experiment” by the Centre for Analytical Science, Department of Chemistry at Loughborough University, U.K. Last but not least, we are grateful for the invaluable linguistic support by Jana Vautz. This research was funded by the European Union as part of the project “Second Generator Locator for Urban Search and Rescue” (SGL for USaR). SGL for USaR was a collaborative project (No. 217967) funded under call identifier FP7-SEC- 2007-1, which is part of the Seventh Framework Program. Furthermore, financial support of the Bundesministerium für Bildung and Forschung and the Ministerium für Innovation, Wissenschaft and Forschung des Landes Nordrhein-Westfalen is gratefully acknowledged.