title: Personal monitoring instrument for the selective measurement of multiple organic vapors.
abstract: Development and laboratory testing of a small instrument capable of recognizing and quantifying multiple organic vapors at low- and sub-ppm concentrations is described. The instrument is slightly larger than a standard personal sampling pump and employs an array of three polymer-coated surface-acoustic-wave microsensors for vapor detection. Vapors are first trapped on a miniature adsorbent preconcentrator housed within the instrument and then thermally desorbed for analysis by the microsensor array. Each measurement cycle requires 5.5 min. The collective responses from the array are stored and then analyzed using pattern recognition methods to yield the identities and concentrations of collected vapors and vapor mixture components. Following initial optimization of instrument operating parameters, calibrations were performed with 16 organic solvent vapors and selected mixtures to establish a response library for each of two identical instruments. Limits of detection < or = 0.1 x threshold limit value were obtained for most vapors. In a series of 90 subsequent exposure tests, vapors were recognized with an error of < 6% (individual vapor challenges) and < 16% (binary mixture challenges) and quantified with an average error of < 10%. Monte Carlo simulations were coupled with pattern recognition analyses to predict the performance for many possible vapor mixtures and sensor combinations. Predicted recognition errors ranged from < 1 to 24%. Performance is shown to depend significantly on the interfacial polymer layers deposited on the sensors in the array and the nature and complexity of the vapor mixtures being analyzed. Results establish the capability of this technology to provide selective multivapor monitoring of personal exposures in workplace environments.
authors.affiliation: Department of Environmental and Health Sciences, University of Michigan, Ann Arbor 48109-2029, USA.
authors.forename: J
authors.initials: J
authors.lastname: Park
authors.forename: G Z
authors.initials: GZ
authors.lastname: Zhang
authors.forename: E T
authors.initials: ET
authors.lastname: Zellers
mesh_terms: D000327:Adsorption; D016902:Air Pollution, Indoor / Q000032:analysis / Q000706:statistics & numerical data; D002138:Calibration; D004784:Environmental Monitoring / Q000295:instrumentation* / Q000706:statistics & numerical data; D004867:Equipment Design; D004864:Equipment and Supplies / Q000706:statistics & numerical data; D009010:Monte Carlo Method; D009930:Organic Chemicals / Q000032:analysis; D012680:Sensitivity and Specificity; D013499:Surface Properties; D014835:Volatilization
chemical_list: D009930:Organic Chemicals