Biogeosciences
Biogeosciences
BG
Articles | Volume 21, issue 16
Articles | Volume 21, issue 16
https://doi.org/10.5194/bg-21-3641-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-21-3641-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 21, issue 16
Technical note
 | 
22 Aug 2024
Technical note |  | 22 Aug 2024

Technical note: A Bayesian mixing model to unravel isotopic data and quantify trace gas production and consumption pathways for time series data – Time-resolved FRactionation And Mixing Evaluation (TimeFRAME)

Eliza Harris, Philipp Fischer, Maciej P. Lewicki, Dominika Lewicka-Szczebak, Stephen J. Harris, and Fernando Perez-Cruz

Viewed

Total article views: 627 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
435 150 42 627 21 30 27
  • HTML: 435
  • PDF: 150
  • XML: 42
  • Total: 627
  • Supplement: 21
  • BibTeX: 30
  • EndNote: 27
Views and downloads (calculated since 29 Nov 2023)
Cumulative views and downloads (calculated since 29 Nov 2023)

Viewed (geographical distribution)

Total article views: 627 (including HTML, PDF, and XML) Thereof 661 with geography defined and -34 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 26 Sep 2024
Download
Short summary
Greenhouse gases are produced and consumed via a number of pathways. Quantifying these pathways helps reduce the climate and environmental footprint of anthropogenic activities. The contribution of the pathways can be estimated from the isotopic composition, which acts as a fingerprint for these pathways. We have developed the Time-resolved FRactionation And Mixing Evaluation (TimeFRAME) model to simplify interpretation and estimate the contribution of different pathways and their uncertainty.
Read more
Altmetrics
Final-revised paper
Preprint