Articles | Volume 18, issue 23
https://doi.org/10.5194/gmd-18-9967-2025
https://doi.org/10.5194/gmd-18-9967-2025
Model description paper
 | 
11 Dec 2025
Model description paper |  | 11 Dec 2025

DRIVE v1.0: a data-driven framework to estimate road transport emissions and temporal profiles

Daniel Kühbacher, Jia Chen, Patrick Aigner, Mario Ilic, Ingrid Super, and Hugo Denier van der Gon

Viewed

Total article views: 2,771 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,384 328 59 2,771 117 60 81
  • HTML: 2,384
  • PDF: 328
  • XML: 59
  • Total: 2,771
  • Supplement: 117
  • BibTeX: 60
  • EndNote: 81
Views and downloads (calculated since 10 Apr 2025)
Cumulative views and downloads (calculated since 10 Apr 2025)

Viewed (geographical distribution)

Total article views: 2,771 (including HTML, PDF, and XML) Thereof 2,723 with geography defined and 48 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 31 Dec 2025
Download
Short summary
We present DRIVE v1.0, a data-driven framework to estimate road transport emissions, their temporal profiles, and the associated uncertainties. The method was applied to the city of Munich, where we present bottom-up emission estimates for the years 2019 to 2022. The estimates are compared against official municipal reports as well as national and European downscaled inventories.
Share