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The detection ability of SO2 cameras has been improved effectively, while the calibration is still the main factor that limits their measurement accuracy. This paper presents a nonlinear calibration theory by considering the effect of light dilution due to the path radiance as well as the dependence of plume aerosol on scattering wavelength. This new spectral calibration method is used to retrieve the SO2 column density and emission rate of the Etna volcano. Results show that, compared with the DOAS calibration approach, the inversion error can be reduced by 13% if the new spectral calibration is adopted. The superiority of the proposed method will become more obvious for long-distance detection of optically thick plumes. [ABSTRACT FROM AUTHOR]

SO2 ultraviolet (UV) camera technology has been successfully applied to the accurate imaging detection of pollutant gas concentration; however, the actual detection ability of this technology has not been intensively studied, especially the detection accuracy and limit under the influence of the light dilution effect. Here, we theoretically and experimentally investigate the UV scattering on SO2 concentration inversion. The radiation transfer model of the light dilution effect is reconstructed, and the concept of the optimized detection limit is discussed. An outfield experiment is conducted on a ship exhaust, and the results are compared with the theoretical calculations, which indicates that the detection limit of the SO2 UV camera is 15 ppm·m at close range and increases to 25 ppm·m when the detection distance is 3.5 km. This study proves that the detection limit of the SO2 UV camera deteriorates with the decreasing atmospheric visibility, the lengthening detection distance, and the increasing aerosol content within the plume. In addition, the hardware indicators of the camera systems also play a key role in the detection limit, and taking reasonable image processing can significantly release the instruments' performance and extend the applicability of the SO2 UV camera. [ABSTRACT FROM AUTHOR]

Observing the O2(a1Δg) dayglow with the limb-viewing DASH instrument enables remote sensing of neutral wind in near space. Many advantages are gained by using this new approach, but the influence factors on measurement accuracy have not been thoroughly investigated. This paper reports the quantitative evaluation of the wind error caused by scattered sunlight. The spectral concept of the O2(a1Δg) band and the measurement technique are briefly described. A comprehensive truth model simulation that is based on atmospheric limb radiance spectra and the instrument concept are used to obtain interferogram images. The algorithm, which uses these images to retrieve the interferogram containing information solely from the target altitude, is described. The self-absorption effect is taken into account in the unraveling of the line-of-sight integration. The influence of scattered sunlight on the limb-viewing weight and signal-to-noise ratio, two definitive factors for wind definitive factors, are also described. Representative wind precision profiles and their variation with surface albedo, aerosol loading, and cloud are presented. This indicates that the random error for Doppler wind is in the range of 2–3 m/s for the tangent height range from 45–80 km, and the wind precision under 45 km suffers significantly from scattered sunlight background. [ABSTRACT FROM AUTHOR]