Quantifying emission fluxes of atmospheric pollutants from mobile differential optical absorption spectroscopic (DOAS) observations.

This study demonstrates a mobile passive differential optical absorption spectroscopy (DOAS) based remote sensing method for quantifying the emission fluxes of soot pollutants. First, the mobile DOAS system scans the plume emitted from urban sources. Then, the DOAS method retrieves the total columns of pollutant gases along the measurement path. Combining the longitude, latitude, and mobile speed recorded by vehicle GPS, the net emission fluxes of NO2 and SO2 in the measurement area are calculated by coupling with the wind field data. The NO2 flux in the region is combined with the NO to NO2 concentration ratio in the Copernicus Atmospheric Monitoring Service (CAMS) model to calculate NOx net emission flux in the measurement period. We conducted the mobile DOAS measurements in the coal production area and obtained the distribution of pollutant gases along the measurement path. Meanwhile, the NO2 concentration distribution of the city and surrounding areas were reconstructed by using TROPOMI satellite data. During the mobile measurement, the net NO2 emission flux measured by mobile DOAS are in good agreement with satellite observations (R2 = 0.66). This study verified that the flux calculation method based on mobile DOAS can be used to detect urban soot pollutant gas emissions.

Retrieval of weak non-resonant photoacoustic signal with the chaotic oscillator algorithm.

Photoacoustic (PA) spectroscopic technique has become a popular tool for trace gas detection and is especially suitable for in situ measurement of sulfur hexafluoride (SF6) decomposition components in gas insulated switchgear (GIS). However, the concentrations of SF6 decomposition components are generally very low and the resulting PA signals are too weak to be accurately retrieved with traditional methods. In this study, we proposed a Lyapunov exponent based chaotic oscillator algorithm to retrieve the weak PA signals of SF6 decomposition components. Retrieval of weak PA signals from strong noise background was achieved for both simulation and measurement perspectives. The results were compared with those based on phase-locked amplification technique. Both simulation and measurement results concluded that the proposed chaotic oscillator algorithm is superior to the phase-locked amplification in terms of accuracy, sensitivity and stability. Since most trace gases have weak absorption signatures in the atmosphere (below 1%), this study can provide valuable insights in dealt with such weak signals in remote sensing of atmosphere.