Imaging indoor tracer-gas concentrations with computed tomography: experimental results with a remote sensing FTIR system
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1994/05/01
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Description:Remote sensing Fourier transform infrared spectroscopy (RS FTIR) detection of a tracer gas coupled with computed tomography (CT) was used to quantify airborne pollutant transport in indoor atmospheres. The RS FTIR spectrometer system was mounted on a translating table attached to a rotational platform. Using this arrangement, a set of parallel ray paths were gathered which formed one projection, and then the platform was rotated to a new position at another angle. Under controlled ventilation conditions, a tracer gas was continually released from a point source in a test chamber. The 143 cubic meter test chamber was equipped with a computer controlled sampling system to monitor air concentrations at 14 points, using flame ionization detection. The tracer gas used was acetone vapor. The experiments produced two data sets, one of beam path averaged values, and one of point values from the flame ionization detector array for comparison to the CT data. Good qualitative agreement was found between the two data sets. Limiting factors included sample point location and temporal variability. The authors conclude that the technique is a rapid and minimally intrusive method which can be used to study indoor air mixing and ventilation efficiency. [Description provided by NIOSH]
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ISSN:0002-8894
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Pages in Document:395-402
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Volume:55
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Issue:5
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NIOSHTIC Number:nn:00219812
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Citation:Am Ind Hyg Assoc J 1994 May; 55(5):395-402
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Contact Point Address:Environmental & Indust Health University of Michigan 1420 Washington Heights Ann Arbor, MI 48109-2029
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Federal Fiscal Year:1994
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Performing Organization:University of Michigan at Ann Arbor, Ann Arbor, Michigan
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Peer Reviewed:True
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Start Date:19890901
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Source Full Name:American Industrial Hygiene Association Journal
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End Date:19990929
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Main Document Checksum:urn:sha-512:33c64cc429295cecc8116cfc110004a50afc5a6d2adf45d1342fa6196a470281a5fc23ff089f14511de2328ac2e82f7a5b51017859269cc9fa0693aad167e7de
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