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。

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 ground-based 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.