Articles | Volume 20, issue 23
Atmos. Chem. Phys., 20, 15207–15225, 2020
https://doi.org/10.5194/acp-20-15207-2020

Special issue: Dust aerosol measurements, modeling and multidisciplinary...

Atmos. Chem. Phys., 20, 15207–15225, 2020
https://doi.org/10.5194/acp-20-15207-2020

Research article 08 Dec 2020

Research article | 08 Dec 2020

Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China

Jianbing Jin et al.

Viewed

Total article views: 1,197 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
989 197 11 1,197 72 18 16
  • HTML: 989
  • PDF: 197
  • XML: 11
  • Total: 1,197
  • Supplement: 72
  • BibTeX: 18
  • EndNote: 16
Views and downloads (calculated since 22 Jul 2020)
Cumulative views and downloads (calculated since 22 Jul 2020)

Viewed (geographical distribution)

Total article views: 1,332 (including HTML, PDF, and XML) Thereof 1,331 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 18 Sep 2021
Download
Short summary
Data assimilation provides a powerful tool to estimate emission inventories by feeding observations. This emission inversion relies on the correct assumption about the emission uncertainty, which describes the potential spatiotemporal spreads of sources. However, an unrepresentative uncertainty is unavoidable. Especially in the complex dust emission, the uncertainties can hardly all be taken into account. This study reports how adjoint can be used to detect errors in the emission uncertainty.
Altmetrics
Final-revised paper
Preprint