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Improved algorithms of differential optical absorption spectroscopy for monitoring SO2, NO2 from flue gas

Valuable achievements in differential optical absorption spectroscopy (DOAS) for monitoring atmospheric trace gas have been made in the past decades. However, in flue gas monitoring, it is difficult to monitor the pollutant gases at low optical density. In this paper, two improved inversion algorithms based on the genetic algorithm and Kalman filter, respectively, were developed to accurately calculate the concentrations of SO2 and NO2 from flue gas. Experimental results show that the improved algorithms have the detection limit of 10 ppm and have a zero drift of 1 ppm at a light path length of 0.5 m. Additionally, the improved algorithms of DOAS combined with the traditional DOAS algorithm can broaden the measurement range of pollutant gases by appropriately setting critical values for the maximum value of the differential optical density.