Articles | Volume 22, issue 19
https://doi.org/10.5194/acp-22-12945-2022
https://doi.org/10.5194/acp-22-12945-2022
Research article
 | 
10 Oct 2022
Research article |  | 10 Oct 2022

Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion

Angharad C. Stell, Michael Bertolacci, Andrew Zammit-Mangion, Matthew Rigby, Paul J. Fraser, Christina M. Harth, Paul B. Krummel, Xin Lan, Manfredi Manizza, Jens Mühle, Simon O'Doherty, Ronald G. Prinn, Ray F. Weiss, Dickon Young, and Anita L. Ganesan

Viewed

Total article views: 1,779 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,316 428 35 1,779 114 23 22
  • HTML: 1,316
  • PDF: 428
  • XML: 35
  • Total: 1,779
  • Supplement: 114
  • BibTeX: 23
  • EndNote: 22
Views and downloads (calculated since 04 Jul 2022)
Cumulative views and downloads (calculated since 04 Jul 2022)

Viewed (geographical distribution)

Total article views: 1,779 (including HTML, PDF, and XML) Thereof 1,674 with geography defined and 105 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 28 Mar 2024
Download
Short summary
Nitrous oxide is a potent greenhouse gas and ozone-depleting substance, whose atmospheric abundance has risen throughout the contemporary record. In this work, we carry out the first global hierarchical Bayesian inversion to solve for nitrous oxide emissions. We derive increasing global nitrous oxide emissions over 2011–2020, which are mainly driven by emissions between 0° and 30°N, with the highest emissions recorded in 2020.
Altmetrics
Final-revised paper
Preprint