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首页> 外文期刊>Journal of Environmental Science and Health. A, Toxic/Hazardous Substances & Environmental Engineering >Reconstruction of Air Contaminant Concentration Distribution in a Two-dimensional Plane by Computed Tomography and Remote Sensing FTIR Spectroscopy
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Reconstruction of Air Contaminant Concentration Distribution in a Two-dimensional Plane by Computed Tomography and Remote Sensing FTIR Spectroscopy

机译：用计算机断层扫描和遥感FTIR光谱重建二维平面中的空气污染物浓度分布

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摘要

This research combined open path FTIR (OP-FTIR) technique and computed tomography (CT) to reconstruct air contaminant concentration distribution in a two-dimensional plane. Remote sensing FTIR instrument was used to scan radial beam geometry and obtain path integrated concentration (PIC) data of acetone gas in the measuring plane. Smooth basis function minimization (SBFM) algorithm was adopted to reconstruct gaseous concentration distribution. For the purpose of finding out the preferable number of Gaussians used in SBFM algorithm, single-Gaussian, double-Gaussian, and three-Gaussian models were used respectively. Experimental results showed that the reconstruction result of acetone concentration distribution by SBFM algorithm with double-Gaussian model agreed with real distribution more qualitatively and quantitatively than single-Gaussian and three-Gaussian. Also, it has been proved that simulated annealing algorithm used in the optimization process of SBFM reconstruction was feasible and effective. Although computed tomography and remote sensing FTIR technique (CT-RS-FTIR) is still at the laboratory study stage, with further improvement of SBFM algorithm and beam geometry, it promises to be used in air pollution monitoring widely.
机译：这项研究结合了开放路径FTIR（OP-FTIR）技术和计算机断层扫描（CT）来重建二维平面中的空气污染物浓度分布。使用遥感FTIR仪器扫描径向束的几何形状并获得测量平面中丙酮气体的路径积分浓度（PIC）数据。采用平滑基函数最小化（SBFM）算法重建气体浓度分布。为了找出在SBFM算法中使用的最佳高斯数，分别使用了单高斯模型，双高斯模型和三高斯模型。实验结果表明，采用双高斯模型的SBFM算法对丙酮浓度分布的重建结果比单高斯和三高斯模型在质量和数量上更符合真实分布。此外，还证明了在SBFM重构优化过程中使用模拟退火算法是可行和有效的。尽管计算机断层扫描和遥感FTIR技术（CT-RS-FTIR）仍处于实验室研究阶段，但随着SBFM算法和射束几何形状的进一步改进，它有望在空气污染监测中得到广泛应用。

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