Articles | Volume 16, issue 4
https://doi.org/10.5194/gmd-16-1427-2023
https://doi.org/10.5194/gmd-16-1427-2023
Model description paper
 | 
02 Mar 2023
Model description paper |  | 02 Mar 2023

Yeti 1.0: a generalized framework for constructing bottom-up emission inventories from traffic sources at road-link resolutions

Edward C. Chan, Joana Leitão, Andreas Kerschbaumer, and Timothy M. Butler

Viewed

Total article views: 1,937 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,479 396 62 1,937 146 45 42
  • HTML: 1,479
  • PDF: 396
  • XML: 62
  • Total: 1,937
  • Supplement: 146
  • BibTeX: 45
  • EndNote: 42
Views and downloads (calculated since 24 Jun 2022)
Cumulative views and downloads (calculated since 24 Jun 2022)

Viewed (geographical distribution)

Total article views: 1,937 (including HTML, PDF, and XML) Thereof 1,839 with geography defined and 98 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 May 2024
Download
Short summary
Yeti is a Handbook Emission Factors for Road Transport-based traffic emission inventory written in the Python 3 scripting language, which adopts a generalized treatment for activity data using traffic information of varying levels of detail introduced in a systematic and consistent manner, with the ability to maximize reusability. Thus, Yeti has been conceived and implemented with a high degree of data and process symmetry, allowing scalable and flexible execution while affording ease of use.