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9 October 2019 Preliminary validation of high-detailed GSA/Resurs-P tropospheric NO2 maps with alternative satellite measurements and transport simulations
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Abstract
An experiment for the retrieval of the high-detailed spatial NO2 distribution in the troposphere using measurements of the GSA instrument onboard the Resurs-P satellite was performed in 2016. The authors developed an algorithm to obtain the tropospheric NO2 2D distribution with the horizontal spatial resolution reaching 2,4 km for the first time at the world level and provided on a grid with a step of 120 m. The high spatial resolution of the NO2 space measurements for the first time allowed the identification of local sources of NO2 pollution and their plumes. The paper presents preliminary results of validation of the GSA high-detailed NO2 field obtained on September 29, 2016 for Hebei province, the North China Plain, which is the most NO2 polluted area in the world. To validate the coarse structures in the obtained NO2 field we performed comparisons with OMI NO2 observations having the resolution of 13 km x 24 km. The comparison confirmed the reliability of the GSA NO2 fields in general. For the validation of fine structures detected in the NO2 fields of GSA/Resurs-P, we are developing methods based on comparisons with chemical transport models. The paper presents preliminary comparison of the Resurs-P tropospheric NO2 field with simulation based on HYSPLIT dispersion model. For the solution of the problem, a high-detailed chemical transport model is under the development.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Oleg V. Postylyakov, Alexander N. Borovski, Marina A. Davydova, and Aleksandr A. Makarenkov "Preliminary validation of high-detailed GSA/Resurs-P tropospheric NO2 maps with alternative satellite measurements and transport simulations", Proc. SPIE 11152, Remote Sensing of Clouds and the Atmosphere XXIV, 111520F (9 October 2019); https://doi.org/10.1117/12.2535487
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