Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 26, issue 11
Articles | Volume 26, issue 11
https://doi.org/10.5194/acp-26-7789-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-26-7789-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 11
Research article
 | 
02 Jun 2026
Research article |  | 02 Jun 2026

Quantifying meteorological impacts on local landfill methane emissions by using field measurements and machine learning

Donghee Kim, Sujong Jeong, Dong Yeong Chang, and Jaewon Joo

Viewed

Total article views: 14,624 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
12,885 1,499 240 14,624 23 269 299
  • HTML: 12,885
  • PDF: 1,499
  • XML: 240
  • Total: 14,624
  • Supplement: 23
  • BibTeX: 269
  • EndNote: 299
Views and downloads (calculated since 15 Sep 2025)
Cumulative views and downloads (calculated since 15 Sep 2025)

Viewed (geographical distribution)

Total article views: 14,624 (including HTML, PDF, and XML) Thereof 14,293 with geography defined and 331 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Jul 2026
Download
Short summary
This study uses data and machine learning to better estimate methane emissions from a major landfill in South Korea. By considering local weather conditions like temperature and rain, the research improves how landfill methane is tracked over time. The results help us understand how climate affects emissions and provide tools that can be used worldwide to improve greenhouse gas monitoring and climate action planning.
Read more
Share
Special issue
Greenhouse gas monitoring in the Asia–Pacific region...
Altmetrics
Final-revised paper
Preprint