Analysis of solvent vapors in breath and ambient air with a surface acoustic wave sensor array

This article describes the development and evaluation of a small prototype instrument employing an array of four polymer-coated surface acoustic wave (SAW) sensors for rapid analysis of organic solvent vapors in exhaled breat h and ambient air. A thermally desorbed adsorbent preconcentrator within th e instrument is used to increase sensitivity and compensate for background water vapor. Calibrations were performed for breath and dry nitrogen sample s in Tedlar bags spiked with 16 individual solvents and selected binary mix tures. Responses were linear over the 50- to 400-fold concentration ranges examined and mixture responses were additive. The resulting library of vapo r calibration response patterns was used with extended disjoint principal c omponents regression and a probabilistic artificial neural network to devel op vapor-recognition algorithms. In a subsequent analysis of an independent data set all individual vapors and most binary mixture components were cor rectly identified and were quantified to within 25% of their actual concent rations. Limits of detection for a 0.25 l. sample collected over a 2.5-min period were <0.3xTLV for 14 of the 16 vapors based on the criterion that al l four sensors show a detectable response. Results demonstrate the feasibil ity of this technology for workplace analysis of breath and ambient air. (C ) 2001 British Occupational Hygiene Society. Published by Elsevier Science Ltd. All rights reserved