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

Qin, Kai and He, Qin and Cohen, Jason and Loyola, Diego and Shi, Jincheng and Xue, Yong (2020) Spatially and temporally coherent reconstruction of tropospheric NO2 over China combining OMI and GOME-2B measurements. Environmental Research Letters, 15 (12), 125011_1-125011_10. Institute of Physics (IOP) Publishing. doi: 10.1088/1748-9326/abc7df. ISSN 1748-9326.

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Official URL: https://iopscience.iop.org/article/10.1088/1748-9326/abc7df/pdf

Abstract

Tropospheric NO2 columns retrieved from 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 NO2 data over China by using machine learning and an adaptive weighted temporal fitting method with NO2 measurements from GOME-2B, and surface measurements. The reconstructed NO2 has four important characteristics. First, there is improved spatial and temporal coherence on a day-to-day basis, allowing new scientific findings to be made. Second, the amount of data doubled, with 40% more data available. Third, the results are reliable overall, with a good agreement with MAX-DOAS measurements (R: 0.75-0.85). Finally, the mean of reconstructed NO2 vertical columns during 2015 and 2018 is consistent with the original data in the spatial distribution, while the standard deviation decreases in most places over mainland China. This novel finding is expected to contribute to both air quality and climate studies.

Item URL in elib:https://elib.dlr.de/137862/
Document Type:Article
Title:Spatially and temporally coherent reconstruction of tropospheric NO2 over China combining OMI and GOME-2B measurements
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Qin, KaiSchool of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, ChinaUNSPECIFIED
He, QinSchool of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, ChinaUNSPECIFIED
Cohen, JasonSchool of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, ChinaUNSPECIFIED
Loyola, DiegoDiego.Loyola (at) dlr.dehttps://orcid.org/0000-0002-8547-9350
Shi, JinchengSchool of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, ChinaUNSPECIFIED
Xue, YongSchool of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, ChinaUNSPECIFIED
Date:5 November 2020
Journal or Publication Title:Environmental Research Letters
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:15
DOI :10.1088/1748-9326/abc7df
Page Range:125011_1-125011_10
Publisher:Institute of Physics (IOP) Publishing
ISSN:1748-9326
Status:Published
Keywords:GOME, TROPOMI, NO2
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Atmospheric and climate research
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Atmospheric Processors
Deposited By: Loyola, Dr.-Ing. Diego
Deposited On:23 Nov 2020 12:55
Last Modified:18 Dec 2020 18:07

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