Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 4
Articles | Volume 17, issue 4
https://doi.org/10.5194/gmd-17-1885-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-1885-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 4
Development and technical paper
 | 
01 Mar 2024
Development and technical paper |  | 01 Mar 2024

Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL

Sanam Noreen Vardag and Robert Maiwald

Viewed

Total article views: 973 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
714 214 45 973 38 29
  • HTML: 714
  • PDF: 214
  • XML: 45
  • Total: 973
  • BibTeX: 38
  • EndNote: 29
Views and downloads (calculated since 05 Oct 2023)
Cumulative views and downloads (calculated since 05 Oct 2023)

Viewed (geographical distribution)

Total article views: 973 (including HTML, PDF, and XML) Thereof 908 with geography defined and 65 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 08 May 2024
Download
Short summary
We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Read more