Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 24
Articles | Volume 15, issue 24
https://doi.org/10.5194/gmd-15-8957-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-8957-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 24
Model description paper
 | 
14 Dec 2022
Model description paper |  | 14 Dec 2022

GENerator of reduced Organic Aerosol mechanism (GENOA v1.0): an automatic generation tool of semi-explicit mechanisms

Zhizhao Wang, Florian Couvidat, and Karine Sartelet

Viewed

Total article views: 1,589 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,203 347 39 1,589 81 19 22
  • HTML: 1,203
  • PDF: 347
  • XML: 39
  • Total: 1,589
  • Supplement: 81
  • BibTeX: 19
  • EndNote: 22
Views and downloads (calculated since 10 Jun 2022)
Cumulative views and downloads (calculated since 10 Jun 2022)

Viewed (geographical distribution)

Total article views: 1,589 (including HTML, PDF, and XML) Thereof 1,481 with geography defined and 108 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 05 Dec 2023
Download
Short summary
Air quality models need to reliably predict secondary organic aerosols (SOAs) at a reasonable computational cost. Thus, we developed GENOA v1.0, a mechanism reduction algorithm that preserves the accuracy of detailed gas-phase chemical mechanisms for SOA formation, thereby improving the practical use of actual chemistry in SOA models. With GENOA, a near-explicit chemical scheme was reduced to 2 % of its original size and computational time, with an average error of less than 3 %.
Read more