Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 24, issue 10
Articles | Volume 24, issue 10
https://doi.org/10.5194/acp-24-5803-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-24-5803-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 24, issue 10
Research article
 | 
22 May 2024
Research article |  | 22 May 2024

Bayesian inference-based estimation of hourly primary and secondary organic carbon in suburban Hong Kong: multi-temporal-scale variations and evolution characteristics during PM2.5 episodes

Shan Wang, Kezheng Liao, Zijing Zhang, Yuk Ying Cheng, Qiongqiong Wang, Hanzhe Chen, and Jian Zhen Yu

Viewed

Total article views: 846 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
629 182 35 846 67 22 22
  • HTML: 629
  • PDF: 182
  • XML: 35
  • Total: 846
  • Supplement: 67
  • BibTeX: 22
  • EndNote: 22
Views and downloads (calculated since 23 Oct 2023)
Cumulative views and downloads (calculated since 23 Oct 2023)

Viewed (geographical distribution)

Total article views: 846 (including HTML, PDF, and XML) Thereof 835 with geography defined and 11 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 26 Jun 2024
Download
Short summary
In this work, hourly primary and secondary organic carbon were estimated by a novel Bayesian inference approach in suburban Hong Kong. Their multi-temporal-scale variations and evolution characteristics during PM2.5 episodes were examined. The methodology could serve as a guide for other locations with similar monitoring capabilities. The observation-based results are helpful for understanding the evolving nature of secondary organic aerosols and refining the accuracy of model simulations.
Read more
Altmetrics
Final-revised paper
Preprint