Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 22, issue 23
Articles | Volume 22, issue 23
https://doi.org/10.5194/acp-22-15403-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-15403-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 23
Research article
 | 
05 Dec 2022
Research article |  | 05 Dec 2022

A method for using stationary networks to observe long-term trends of on-road emission factors of primary aerosol from heavy-duty vehicles

Helen L. Fitzmaurice and Ronald C. Cohen

Viewed

Total article views: 2,101 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,608 444 49 2,101 153 40 52
  • HTML: 1,608
  • PDF: 444
  • XML: 49
  • Total: 2,101
  • Supplement: 153
  • BibTeX: 40
  • EndNote: 52
Views and downloads (calculated since 31 Jan 2022)
Cumulative views and downloads (calculated since 31 Jan 2022)

Viewed (geographical distribution)

Total article views: 2,101 (including HTML, PDF, and XML) Thereof 2,133 with geography defined and -32 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 25 Dec 2024
Download
Short summary
We develop a novel method for finding heavy-duty vehicle (HDV) emission factors (g PM kg fuel) using regulatory sensor networks and publicly available traffic data. We find that particulate matter emission factors have decreased by a factor of ~ 9 in the past decade in the San Francisco Bay area. Because of the wide availability of similar data sets across the USA and globally, this method could be applied to other settings to understand long-term trends and regional differences in HDV emissions.
Read more
Altmetrics
Final-revised paper
Preprint