Study on the method of reconstructing the vertical plane distribution of SO2 using IDOAS

MingYu Zhong, YuMeng Wei, Liang Xi, Zhen Chang, HaiJin Zhou, FuQi Si, Ke Dou
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Abstract

This paper presents a method that combines Imaging Differential Optical Absorption Spectroscopy (IDOAS) with Computed Tomography (CT) technique to reconstruct the spatial distribution of SO2 in the vertical plane. A cubic quartz glass container with a side length of 450 mm was used, and SO2 gas was injected into the container from a steel cylinder. Two IDOASs were used to collect spectral data on the vertical plane. The Differential Optical Absorption Spectroscopy (DOAS) algorithm was employed to retrieve the slant column densities (SCDs). The gas distribution in the gas container was estimated with the help of linear fitting. It was found that the experimental SCDs were in good agreement with the theoretical analysis. Based on the sparse gradient of the gas distribution in the gas container and the non-negative of the gas concentration, a CT algorithm called ABOCS-TVM with total variational (TV) regularization was introduced. Numerical simulations show that if the gas in the container is uniform, the algorithm works well even under the influence of perturbations, and the artifacts in the reconstructed images are suppressed. The experiment showed that the algorithm is able to accurately locate the SO2 gas and provide an approximate distribution. In particular, the reconstructed peak molecular number density is approximately 11% higher than the theoretical value. Research has demonstrated the feasibility of utilizing IDOAS-based CT reconstruction technology to reconstruct the spatial distribution of SO2 in a vertical plane. This technology allows precise localization of the spatial position of SO2 and quantitative analysis of its distribution.

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利用 IDOAS 重构二氧化硫垂直面分布的方法研究
本文介绍了一种将成像差分光学吸收光谱(IDOAS)与计算机断层扫描(CT)技术相结合的方法,用于重建二氧化硫在垂直面上的空间分布。使用边长为 450 毫米的立方体石英玻璃容器,将二氧化硫气体从钢瓶注入容器。使用两台差分光学吸收光谱仪收集垂直面上的光谱数据。采用差分光学吸收光谱(DOAS)算法检索斜柱密度(SCD)。在线性拟合的帮助下,对气体容器中的气体分布进行了估计。结果发现,实验 SCD 与理论分析十分吻合。基于气体容器中气体分布的稀疏梯度和气体浓度的非负特性,引入了一种名为 ABOCS-TVM 的 CT 算法,并进行了全变分(TV)正则化。数值模拟表明,如果容器中的气体是均匀的,即使在扰动的影响下,该算法也能很好地工作,重建图像中的伪影也会被抑制。实验表明,该算法能够准确定位二氧化硫气体并提供近似分布。特别是重建的峰值分子数密度比理论值高出约 11%。研究证明了利用基于 IDOAS 的 CT 重建技术重建垂直面中二氧化硫空间分布的可行性。这项技术可以精确定位二氧化硫的空间位置,并对其分布进行定量分析。
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