大气与环境光学学报 ›› 2022, Vol. 17 ›› Issue (2): 249-257.

• 环境光学监测技术 • 上一篇    下一篇

成像差分吸收光谱技术的软件研发与数据反演

曹子昊1;2, 曾 议2∗, 鲁晓峰1;2, 廖 捷2;3, 杨东上2;3, 常 振2, 司福祺2, 奚 亮2;3   

  1. 1 合肥学院生物食品与环境学院, 安徽 合肥 230601; 2 中国科学院合肥物质科学研究院安徽光学精密机械研究所, 中国科学院环境光学与技术重点实验室, 安徽 合肥 230031; 3 中国科学技术大学, 安徽 合肥 230026
  • 收稿日期:2020-11-30 修回日期:2022-02-14 出版日期:2022-03-28 发布日期:2022-03-28
  • 通讯作者: E-mail: yzeng@aiofm.ac.cn E-mail:yzeng@aiofm.ac.cn
  • 作者简介:曹子昊 (1996 - ), 江苏南通人, 硕士研究生, 主要从事大气痕量气体反演方面的研究。 E-mail: zihao cao@fpi-inc.com
  • 基金资助:
    Supported by National Key Research and Development Program (国家重点研发计划, 2017YFB0503901)

Software development and data inversion for imaging differential absorption spectroscopy technology

CAO Zihao1;2, ZENG Yi2∗, LU Xiaofeng1;2, LIAO Jie2;3, YANG Dongshang2;3, CHANG Zhen2, SI Fuqi2, XI Liang2;3   

  1. 1 School of Biological Food and Environment, Hefei University, Hefei 230601, China; 2 Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China; 3 University of Science and Technology of China, Hefei 230026, China
  • Received:2020-11-30 Revised:2022-02-14 Published:2022-03-28 Online:2022-03-28

摘要: 成像差分吸收光谱技术 (IDOAS) 能够显示污染物的空间分布, 目前已成功运用于地基扫描、机载与星载等 多个平台, 为环境监测及治理提供了有力支撑, 其中地基 IDOAS 主要运用于对某一污染源的探测。分析了成像系统 基于“推扫”方式的工作原理, 并将此技术应用于城市大气边界层污染物分布的探测。为更高效使用差分吸收光谱技术 (DOAS) 反演各种痕量气体成分, 更精确地分析污染气体的时空分布特征, 对 QDoas 软件进行了源码级分析和优化。 在 Windows 平台上, 使用 C++ 和 QT 对 QDoas 代码进行重组, 通过重新提取、整合、改写与优化代码, 实现了更快速 便捷的反演功能模块。为检验模块的反演效果, 以大气中常见的污染物 NO2 和 SO2 为例, 于 2019 年 11 月 6 日在铜 陵富鑫钢铁厂开展了现场观测实验。使用新编软件对观测数据进行数据反演后成功获得污染气体的二维分布信息图, 证实了该软件在实际大气环境监测中的适用性。

关键词: 差分吸收光谱技术, 数据反演, 二维分布成像, 软件研发

Abstract: Imaging differential absorption spectroscopy technology (IDOAS) can obtain the spatial distribution of pollutants. It has been successfully applied to multiple platforms such as ground-based scanning, airborne and spaceborne, providing strong support for environmental monitoring and management. Among them, the groundbased IDOAS is mainly used in the detection of a certain pollution source. The principle of the imaging system based on the “push-broom” mode is analyzed, and the detection technology is applied to the detection of pollutant distribution in urban atmospheric boundary layer. In order to use the DOAS method to invert various trace gas components more efficiently and analyze the temporal and spatial distribution characteristics of polluted gases more accurately, the source-level analysis and optimization of QDoas software have been carried out. On the Windows platform, C++ and QT are used to reorganize the QDoas code. By re-extracting, integrating, rewriting, and optimizing the code, a faster and more convenient inversion function module is realized. In order to test the inversion performance of the module, taking the common pollutants NO2 and SO2 in the atmosphere as examples, an on-site observation experiment was carried out in Tongling Fuxin Iron and Steel Plant, China, on November 6, 2019. The two-dimensional distribution image of the polluted gas concentration in the target area is successfully obtained after the data inversion with the new compiled software, which confirms the applicability of the developed software in the actual atmospheric environment monitoring.

Key words: differential absorption spectroscopy, data inversion, two-dimensional distribution imaging, software development

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