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Detection and quantification of volatile organic chemicals in water using the FTIR-ATR technique

Posted on:2010-07-22Degree:M.SType:Thesis
University:California State University, FullertonCandidate:Lin, WendyFull Text:PDF
GTID:2441390002976040Subject:Chemistry
Abstract/Summary:
The Fourier Transform Infrared-Attenuated Total Reflectance (FTIR-ATR) technique has been used to detect and quantify the following volatile organic chemicals (VOCs) in water: 1,1,1,2-tetrachloroethane, 1,1,2,2-tetrachloroethane, styrene, tetrachloroethylene, benzene, and p-xylene, the first three compounds of which were investigated at ppm levels for the first time using the FTIR-ATR technique. Enhancement of the detection was made by (1) coating the ATR crystal with a hydrophobic polymer membrane, (2) optimizing the flow rate of the sample solution, (3) varying polymer membrane thickness, and (4) increasing the number of reflection bounces within the ATR crystal. Flow rate optimization results suggested that at low turbulent flow, optimal amount of analyte adsorption into the polymers occurs, although this trend is not as clear for some analytes. The optimal membrane thickness was found to be associated with the maximum overlap between the IR evanescent wave penetration depth and the analyte diffusion depth. Consequently, there is no universal optimal flow rate and optimal polymer thickness for detection of all VOCs. Doubling the number of IR beam bounces within the ATR crystal enhanced both detection and sensitivity by about a factor of two. Finally, it was observed from the trend in detection limit concentrations that the polymers have greater physical affinity to the hydrophobic analytes. Results from the present study indicate that the FTIR-ATR technique can be used to monitor water quality and for the kinetics study in aqueous phase chemistry involving VOCs because of its fingerprint-based VOCs identification capability and the linear response to the analyte concentrations.
Keywords/Search Tags:FTIR-ATR, Technique, Detection, Water, Vocs
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