Literature DB >> 21662930

Nonequilbrium quantitation of volatiles in air streams by solid-phase microextraction.

R J Bartelt1, B W Zilkowski.   

Abstract

Solid-phase microextraction (SPME) is a valuable technique for analyzing air-borne organic compounds; one important application is measuring concentrations when these are constant over time. Quantitation normally relies on the SPME fiber being fully equilibrated with the sample medium. Unfortunately, relatively heavy compounds do not equilibrate within a reasonable amount of time, and this has limited the scope of SPME. The ability to quantitate during equilibration was needed and was the focus of this investigation. This entailed having an accurate description of SPME kinetics, and the kinetics of extraction by poly(dimethylsiloxane) fibers was studied for alkanes of 9-22 carbons, primary alcohols of 6-13 carbons, and methyl esters of 6-16-carbon acids. Sampling was from air streams in which analyte concentrations were effectively constant, and sampling times ranged from 30 min to 3 days. Other experimental variables included sampling temperature, fiber coating thickness, air flow rate, and tubing diameter in which the SPME sampling took place. Over 1900 data points were acquired. Previous theoretical kinetic models were not applicable to the present experimental conditions, but a simple kinetic equation was formulated that described the data very well; its key property is an explicit relationship between fiber sensitivity and equilibration time. Using nonlinear regression, the equation parameters were linked to known properties of the analyte (the functional group and GC retention index on a nonpolar column) and to certain sampling conditions (temperature, sampling duration, air flow rate, tubing diameter). The regression equation serves as a practical quantitation formula and allows the absolute concentration of the analyte in the air stream to be calculated directly from the amount extracted by the SPME fiber (which is easily measured by GC), regardless of whether equilibrium has been established or not, as long as the above analyte properties and sampling conditions are known. The residual variability for the model (RSD = 9.4%) was only slightly larger than the variability inherent in SPME alone (∼5%). Considerations for SPME sampling from air are discussed, and new fiber calibration information is presented for the larger hydrocarbons, alcohols, and methyl esters.

Entities:  

Year:  1999        PMID: 21662930     DOI: 10.1021/ac980785f

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  5 in total

1.  Development of synthetic food-related attractant for Carpophilus davidsoni and its effectiveness in the stone fruit orchards in southern Australia.

Authors:  Robert J Bartelt; Mofakhar S Hossain
Journal:  J Chem Ecol       Date:  2006-10       Impact factor: 2.626

2.  Behaviorally active green leaf volatiles for monitoring the leaf beetle, Diorhabda elongata, a biocontrol agent of saltcedar, Tamarix spp.

Authors:  Allard A Cossé; Robert J Bartelt; Bruce W Zilkowski; Daniel W Bean; Earl R Andress
Journal:  J Chem Ecol       Date:  2006-12       Impact factor: 2.626

3.  Determination of total and available fractions of PAHs by SPME in oily wastewaters: overcoming interference from NAPL and NOM.

Authors:  Rui B Gomes; Regina Nogueira; José M Oliveira; João Peixoto; António G Brito
Journal:  Environ Sci Pollut Res Int       Date:  2009-03-17       Impact factor: 4.223

4.  Identification of chemicals emitted by calling males of the Sapote fruit fly, Anastrepha serpentina.

Authors:  David C Robacker; Martin Aluja; Robert J Bartelt; Joseph Patt
Journal:  J Chem Ecol       Date:  2009-05-09       Impact factor: 2.626

5.  Analyzing diurnal and age-related pheromone emission of the olive fruit fly, Bactrocera oleae by sequential SPME-GCMS analysis.

Authors:  Anat Levi-Zada; David Nestel; Daniela Fefer; Esther Nemni-Lavy; Inbal Deloya-Kahane; Maayan David
Journal:  J Chem Ecol       Date:  2012-07-25       Impact factor: 2.626

  5 in total

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