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Spatially and temporally coherent reconstruction of tropospheric NO2 over China combining OMI and GOME-2B measurements

Tropospheric NO _2 columns retrieved from ozone monitoring instrument (OMI) are widely used, even though there is a significant loss of spatial coverage due to multiple factors. This work introduces a framework for reconstructing gaps in the OMI NO _2 data over China by using machine learning and an...

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Principais autores: Qin He, Kai Qin, Jason Blake Cohen, Diego Loyola, Ding Li, Jincheng Shi, Yong Xue
Formato: Artigo
Idioma:Inglês
Publicado: IOP Publishing 2020-01-01
Series:Environmental Research Letters
Assuntos:
reconstruction
NO2
gaps
OMI
GOME-2B
machine learning
Acceso en liña:https://doi.org/10.1088/1748-9326/abc7df
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