Study of Data Processing Based on Differential Optical Absorption Spectroscopy

Differential optical absorption spectroscopy (DOAS) is widely used to measure trace gases in the atmosphere and flue gas from stationary pollution. The technique is based on the recording of differential absorption, the difference between local maxima and minima in the absorption spectrum of the probed gas species. The key procedures in the retrieval algorithms of the recorded DOAS spectra are the separation of the absorption into two parts that represent respectively broad and narrow spectral features and the evaluation of absorption spectra. In this paper three retrieval data processing methods, i.e.,complete integral algorithm, linear least-squares fitting algorithm and Fourier transform filtering algorithm, are studied. The experimental results show that the Fourier transform filtering algorithm has good performance: the maximum deviation is less than 3%. This new method can effectively correct overlapped spectra, reduces the noise and improves the accuracy of the DOAS system. The relative error is smaller than using complete integral algorithm and linear least-squares method.