Articles | Volume 18, issue 6
https://doi.org/10.5194/acp-18-4171-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-18-4171-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 Mar 2018
Research article |
| 27 Mar 2018
Evaluation of modeling NO2 concentrations driven by satellite-derived and bottom-up emission inventories using in situ measurements over China
Fei Liu
CORRESPONDING AUTHOR
Royal Netherlands Meteorological Institute (KNMI), Department of
Satellite Observations, De Bilt, the Netherlands
Universities Space Research Association (USRA), GESTAR, Columbia, MD,
USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Ronald J. van der A
Royal Netherlands Meteorological Institute (KNMI), Department of
Satellite Observations, De Bilt, the Netherlands
Henk Eskes
Royal Netherlands Meteorological Institute (KNMI), Department of
Satellite Observations, De Bilt, the Netherlands
Jieying Ding
Royal Netherlands Meteorological Institute (KNMI), Department of
Satellite Observations, De Bilt, the Netherlands
Department of Geoscience and Remote Sensing (GRS), Delft University of
Technology, Delft, the Netherlands
Bas Mijling
Royal Netherlands Meteorological Institute (KNMI), Department of
Satellite Observations, De Bilt, the Netherlands
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Latest update: 17 Apr 2024
Short summary
We used ground measurements from the recently developed air quality monitoring network in China to validate modeling surface NO2 concentrations from the regional chemical transport model (CTM). The CTM simulations driven by satellite-derived and bottom-up inventories show negative and positive differences against the ground measurements, respectively. Our study suggests an improvement of the distribution of emissions between urban and rural areas in the satellite-derived inventory.
We used ground measurements from the recently developed air quality monitoring network in China...
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