Personal monitoring instrument for the selective measurement of multiple organic vapors

Development and laboratory testing of a small instrument capable of recogni zing and quantifying multiple organic vapors at low- and sub-ppm concentrat ions is described. The instrument is slightly larger than a standard person al sampling pump and employs an array of three polymer-coated surface-acous tic-wave microsensors for vapor detection. Vapors are first trapped on a mi niature adsorbent preconcentrator housed within the instrument and then the rmally desorbed for analysis by the microsensor array. Each measurement cyc le requires 5.5 min. The collective responses from the array are stored and then analyzed using pattern recognition methods to yield the identities an d concentrations of collected vapors and vapor mixture components. Followin g initial optimization of instrument operating parameters, calibrations wer e performed with 16 organic solvent vapors and selected mixtures to establi sh a response library for each of two identical instruments. Limits of dete ction less than or equal to 0.1 x threshold limit value were obtained for m ost vapors. In a series of 90 subsequent exposure tests, vapors were recogn ized with an error of <6% (individual vapor challenges) and <16% (binary mi xture challenges) and quantified with an average error of <10%. Monte Carte simulations were coupled with pattern recognition analyses to predict the performance for many possible vapor mixtures and sensor combinations. Predi cted recognition errors ranged from <1 to 24%. Performance is shown to depe nd significantly on the interfacial polymer layers deposited on the sensors in the array and the nature and complexity of the vapor mixtures being ana lyzed. Results establish the capability of this technology to provide selec tive multivapor monitoring of personal exposures in workplace environments.