scholarly journals Development and Application of Differential Optical Absorption Spectroscopy (DOAS) for Regional Air Pollution Monitoring in China

2014 ◽  
Author(s):  
Pinhua Xie ◽  
Wenqing Liu ◽  
Jianguo Liu ◽  
Ang Li ◽  
Fuqi Si ◽  
...  
Keyword(s):  
Air Pollution ◽  
Optical Absorption ◽  
Absorption Spectroscopy ◽  
Differential Optical Absorption Spectroscopy ◽  
Pollution Monitoring ◽  
Optical Absorption Spectroscopy ◽  
Air Pollution Monitoring ◽  
Regional Air Pollution

scholarly journals Total Ozone Columns from the Environmental Trace Gases Monitoring Instrument (EMI) Using the DOAS Method

2021 ◽  
Vol 13 (11) ◽  
pp. 2098
Author(s):  
Yuanyuan Qian ◽  
Yuhan Luo ◽  
Fuqi Si ◽  
Haijin Zhou ◽  
Taiping Yang ◽  
...  
Keyword(s):  
Optical Absorption ◽  
Absorption Spectroscopy ◽  
Total Ozone ◽  
Scattered Light ◽  
Trace Gases ◽  
Rapid Change ◽  
Differential Optical Absorption Spectroscopy ◽  
Optical Absorption Spectroscopy ◽  
Monitoring Instrument ◽  
Monthly Average

Global measurements of total ozone are necessary to evaluate ozone hole recovery above Antarctica. The Environmental Trace Gases Monitoring Instrument (EMI) onboard GaoFen 5, launched in May 2018, was developed to measure and monitor the global total ozone column (TOC) and distributions of other trace gases. In this study, some of the first global TOC results of the EMI using the differential optical absorption spectroscopy (DOAS) method and validation with ground-based TOC measurements and data derived from Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) observations are presented. Results show that monthly average EMI TOC data had a similar spatial distribution and a high correlation coefficient (R ≥ 0.99) with both OMI and TROPOMI TOC. Comparisons with ground-based measurements from the World Ozone and Ultraviolet Radiation Data Centre also revealed strong correlations (R > 0.9). Continuous zenith sky measurements from zenith scattered light differential optical absorption spectroscopy instruments in Antarctica were also used for validation (R = 0.9). The EMI-derived observations were able to account for the rapid change in TOC associated with the sudden stratospheric warming event in October 2019; monthly average TOC in October 2019 was 45% higher compared to October 2018. These results indicate that EMI TOC derived using the DOAS method is reliable and has the potential to be used for global TOC monitoring.

scholarly journals Satellite monitoring of different vegetation types by differential optical absorption spectroscopy (DOAS) in the red spectral range

2007 ◽  
Vol 7 (1) ◽  
pp. 69-79 ◽  
Author(s):  
T. Wagner ◽  
S. Beirle ◽  
T. Deutschmann ◽  
M. Grzegorski ◽  
U. Platt
Keyword(s):  
Optical Absorption ◽  
Absorption Spectroscopy ◽  
Spectral Range ◽  
Near Infrared ◽  
Vegetation Type ◽  
Differential Optical Absorption Spectroscopy ◽  
Trace Gas ◽  
Satellite Monitoring ◽  
Optical Absorption Spectroscopy ◽  
Vegetation Types

Abstract. A new method for the satellite remote sensing of different types of vegetation and ocean colour is presented. In contrast to existing algorithms relying on the strong change of the reflectivity in the red and near infrared spectral region, our method analyses weak narrow-band (few nm) reflectance structures (i.e. "fingerprint" structures) of vegetation in the red spectral range. It is based on differential optical absorption spectroscopy (DOAS), which is usually applied for the analysis of atmospheric trace gas absorptions. Since the spectra of atmospheric absorption and vegetation reflectance are simultaneously included in the analysis, the effects of atmospheric absorptions are automatically corrected (in contrast to other algorithms). The inclusion of the vegetation spectra also significantly improves the results of the trace gas retrieval. The global maps of the results illustrate the seasonal cycles of different vegetation types. In addition to the vegetation distribution on land, they also show patterns of biological activity in the oceans. Our results indicate that improved sets of vegetation spectra might lead to more accurate and more specific identification of vegetation type in the future.

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