Biogeosciences
Biogeosciences
BG
Articles | Volume 23, issue 4
Articles | Volume 23, issue 4
https://doi.org/10.5194/bg-23-1423-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-23-1423-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 4
Research article
 | 
24 Feb 2026
Research article |  | 24 Feb 2026

Multi-stress interaction effects on BVOC emission fingerprints from Oak and Beech: A cross-investigation using Machine Learning and Positive Matrix Factorization

Biplob Dey, Toke Due Sjøgren, Peeyush Khare, Georgios I. Gkatzelis, Yizhen Wu, Sindhu Vasireddy, Martin Schultz, Alexander Knohl, Riikka Rinnan, Thorsten Hohaus, and Eva Y. Pfannerstill

Viewed

Total article views: 2,477 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,143 285 49 2,477 85 55 51
  • HTML: 2,143
  • PDF: 285
  • XML: 49
  • Total: 2,477
  • Supplement: 85
  • BibTeX: 55
  • EndNote: 51
Views and downloads (calculated since 26 Aug 2025)
Cumulative views and downloads (calculated since 26 Aug 2025)

Viewed (geographical distribution)

Total article views: 2,477 (including HTML, PDF, and XML) Thereof 2,361 with geography defined and 116 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 24 Feb 2026
Download
Short summary
Trees release reactive gases that affect air quality and climate. We studied how these emissions from European beech and English oak change under realistic scenarios of combined and single heat and ozone stress. Heat increased emissions, while ozone reduced most of them. When stressors were combined, the effects were complex and varied by species. Machine learning identified key stress-related compounds. Our findings show that future tree stress may alter air quality and climate interactions.
Read more
Share
Altmetrics
Final-revised paper
Preprint