Characterisation and potential for reducing optical resonances in FTIR spectrometers of the Network for the Detection of Atmospheric Composition Change (NDACC)

Atmospheric Measurement Techniques Discussions(2020)

引用 0|浏览62
暂无评分
摘要
Abstract. Although optical components in Fourier transform infrared (FTIR) spectrometers are preferably wedged, in practice, infrared spectra typically suffer from the effects of optical resonances (“channeling”) affecting the retrieval of weakly absorbing gases. This study investigates the level of channeling of each FTIR spectrometer within the Network for the Detection of Atmospheric Composition Change (NDACC). Dedicated spectra were recorded by more than twenty NDACC FTIR spectrometers using a laboratory mid-infrared source and two detectors. In the InSb detector domain (1900–5000 cm−1), we find that the amplitude of the most pronounced channeling frequency amounts to 0.1 to 2.0 ‰ of the spectral background level, with a mean of (0.68 ± 0.48) ‰ and a median of 0.60 ‰. In the HgCdTe detector domain (700–1300 cm−1), we find even stronger effects, with the largest amplitude ranging from 0.3 to 21 ‰ with a mean of (2.45 ± 4.50) ‰ and a median of 1.2 ‰. For both detectors, the leading channeling frequencies are 0.9 and 0.11 or 0.23 cm−1 in most spectrometers. These observed spectral frequencies correspond to the optical thickness of the air gap in between the beam splitter and compensator plate (0.9 cm−1) and the beam splitter substrate itself (0.11 and 0.23 cm−1). Since the air gap is a significant source of channeling and the corresponding amplitude differs strongly between spectrometers, we propose new beam splitters with the wedge of the air gap increased to at least 0.8°. We tested the insertion of spacers in a beam splitter’s air gap to demonstrate that increasing the wedge of the air gap decreases the 0.9 cm−1 channeling amplitude significantly. This study shows the potential for reducing channeling in the FTIR spectrometers operated by the NDACC, thereby increasing the quality of recorded spectra across the network.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要