Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 20, issue 23
Articles | Volume 20, issue 23
https://doi.org/10.5194/acp-20-15487-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-15487-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 23
Research article
 | 
11 Dec 2020
Research article |  | 11 Dec 2020

Quantifying methane emissions from Queensland's coal seam gas producing Surat Basin using inventory data and a regional Bayesian inversion

Ashok K. Luhar, David M. Etheridge, Zoë M. Loh, Julie Noonan, Darren Spencer, Lisa Smith, and Cindy Ong

Viewed

Total article views: 3,274 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,279 933 62 3,274 399 63 66
  • HTML: 2,279
  • PDF: 933
  • XML: 62
  • Total: 3,274
  • Supplement: 399
  • BibTeX: 63
  • EndNote: 66
Views and downloads (calculated since 15 May 2020)
Cumulative views and downloads (calculated since 15 May 2020)

Viewed (geographical distribution)

Total article views: 3,274 (including HTML, PDF, and XML) Thereof 3,359 with geography defined and -85 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
Short summary
With the sharp rise in coal seam gas (CSG) production in Queensland’s Surat Basin, there is much interest in quantifying methane emissions from this area and from unconventional gas production in general. We develop and apply a regional Bayesian inverse model that uses hourly methane concentration data from two sites and modelled backward dispersion to quantify emissions. The model requires a narrow prior and suggests that the emissions from the CSG areas are 33% larger than bottom-up estimates.
Read more
Altmetrics
Final-revised paper
Preprint