We present a new computed tomography method, the low third derivative (LTD) method, that is particularly suited for reconstructing the spatial distribution of gas concentrations from path-integral data for a small number of optical paths. The method finds a spatial distribution of gas concentrations that (1) has path integrals that agree with measured path integrals, and (2) has a low third spatial derivative in each direction, at every point. The trade-off between (1) and (2) is controlled by an adjustable parameter, which can be set based on analysis of the path-integral data. The method produces a set of linear equations, which can be solved with a single matrix multiplication if the constraint that all concentrations must be positive is ignored; the method is therefore extremely rapid. Analysis of experimental data from thousands of concentration distributions shows that the method works nearly as well as smooth basis function minimization (the best method previously available), yet is about 100 times faster.

10aAir Flow10acomputed tomography10aConcentration mapping10aOptical remote sensing10apollutant dispersion1 aPrice, Phillip, N.1 aFischer, Marc, L.1 aGadgil, Ashok, J.1 aSextro, Richard, G. uhttps://energyanalysis.lbl.gov/publications/algorithm-real-time-tomography-gas02318nas a2200253 4500008004100000245008700041210006900128300001400197490000700211520148700218653001301705653002401718653002701742653002701769100002201796700002301818700002401841700002501865700002301890700002001913700002401933700002201957856008501979 2001 eng d00aRapid Measurement and Mapping of Tracer Gas Concentrations in a Large Indoor Space0 aRapid Measurement and Mapping of Tracer Gas Concentrations in a a2837-28440 v353 aRapid mapping of gas concentrations in air benefits studies of atmospheric phenomena ranging from pollutant dispersion to surface layer meteorology. Here we demonstrate a technique that combines multiple-open-path tunable-diode-laser spectroscopy and computed tomography to map tracer gas concentrations with approximately 0.5 m spatial and 7 s temporal resolution. Releasing CH_{4} as a tracer gas in a large (7 m×9 m×11 m high) ventilated chamber, we measured path-integrated CH_{4} concentrations over a planar array of 28 “long” (2–10 m) optical paths, recording a complete sequence of measurements every 7 s during the course of hour-long experiments. Maps of CH_{4} concentration were reconstructed from the long path data using a computed tomography algorithm that employed simulated annealing to search for a best fit solution. The reconstructed maps were compared with simultaneous measurements from 28 “short” (0.5 m) optical paths located in the same measurement plane. On average, the reconstructed maps capture ∼74% of the variance in the short path measurements. The accuracy of the reconstructed maps is limited, in large part, by the number of optical paths and the time required for the measurement. Straightforward enhancements to the instrumentation will allow rapid mapping of three-dimensional gas concentrations in indoor and outdoor air, with sub-second temporal resolution.

Optical remote sensing and iterative computed tomography (CT) can be applied to measure the spatial distribution of gaseous pollutant concentrations. We conducted chamber experiments to test this combination of techniques using an open path Fourier transform infrared spectrometer (OP-FTIR) and a standard algebraic reconstruction technique (ART). Although ART converged to solutions that showed excellent agreement with the measured ray-integral concentrations, the solutions were inconsistent with simultaneously gathered point-sample concentration measurements. A new CT method was developed that combines (1) the superposition of bivariate Gaussians to represent the concentration distribution and (2) a simulated annealing minimization routine to find the parameters of the Gaussian basis functions that result in the best fit to the ray-integral concentration data. This method, named smooth basis function minimization (SBFM), generated reconstructions that agreed well, both qualitatively and quantitatively, with the concentration profiles generated from point sampling. We present an analysis of two sets of experimental data that compares the performance of ART and SBFM. We conclude that SBFM is a superior CT reconstruction method for practical indoor and outdoor air monitoring applications.

10acomputed tomography10agas monitoring10aRemote sensing10asimulated annealing1 aDrescher, Anushka, C.1 aGadgil, Ashok, J.1 aPrice, Phillip, N.1 aNazaroff, William, W. uhttps://energyanalysis.lbl.gov/publications/novel-approach-tomographic