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Spatial and temporal visualization of gases and vapours in air using computed tomography. Numerical studies.
Ann Occup Hyg 1997 Jan; 41(1):105-122
An optical remote sensing computed tomography (ORS/CT) system for exposure evaluation and source monitoring was examined. Fifteen two dimensional maps representing the configuration and dispersion of airborne chemicals were generated in a confined room divided into a grid of cells. Open path Fourier transform infrared spectrometers were used to scan the room. The iterative tomographic reconstruction algorithm, the maximum likelihood with expectation maximization (MLEM), was applied to cell correction. The timesteps tested ranged from 15 seconds to 3 minutes. Thus, the entire room was sampled every 10 minutes to 2 hours. The reconstructed maps were then compared with the original maps. The effects of sample time, sample density, and the amount of repetitions in the MLEM on reconstruction quality were assessed qualitatively, by visual assessment, and quantitatively, by nearness, projection data distance, and exposure error and peak location analyses. As the timestep increased, the reconstruction quality deteriorated. Scanning the room in 10 to 20 minutes was sufficient. The underestimation of time weighted average exposures, especially for multiple peaks, increased with increasing timestep. Although peak location error was relatively unaffected by timestep for single and multiple peaks, peak location error increased substantially with increasing timestep for moving peaks. When the method was applied to a simulated gas release, peak height overestimation increased with increasing timestep. However, the shapes and locations of the peaks were generally well defined. Measurement noise resulted in greater error. While the use of 50 iterations produced accurate maps, the use of 150 iterations produced smoother maps, either with or without measurement noise. Reconstruction quality increased with decreasing sampling density. The authors conclude that while the ORS/CT system apparently offers an accurate and efficient approach to exposure evaluation, source monitoring, and leak detection, the practical application of time series concentration maps requires further research.
NIOSH-Publication; NIOSH-Grant; Grants-other; Mathematical-models; Spectrographic-analysis; Simulation-methods; Analytical-instruments; Time-weighted-average-exposure
Environmental Sciences & Engr University of North Carolina CB #7400 Chapel Hill, NC 27599-7400
Issue of Publication
Other Occupational Concerns; Grants-other
Annals of Occupational Hygiene
University of North Carolina Chapel Hill, Chapel Hill, North Carolina
Page last reviewed: April 12, 2019
Content source: National Institute for Occupational Safety and Health Education and Information Division