Articles | Volume 16, issue 4
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


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-147', Sergio Ibarra, 18 Jul 2022
  • RC2: 'Comment on gmd-2022-147', Stefan Hausberger, 25 Oct 2022
  • RC3: 'Comment on gmd-2022-147', Christina Quaassdorff, 21 Nov 2022
  • EC1: 'Comment on gmd-2022-147', Christoph Knote, 22 Nov 2022
  • AC1: 'Comment on gmd-2022-147', Edward C. Chan, 16 Jan 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Edward C. Chan on behalf of the Authors (16 Jan 2023)  Author's response
ED: Publish as is (30 Jan 2023) by Christoph Knote
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.