Articles | Volume 17, issue 1
https://doi.org/10.5194/gmd-17-381-2024
https://doi.org/10.5194/gmd-17-381-2024
Model description paper
 | 
16 Jan 2024
Model description paper |  | 16 Jan 2024

A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3

Sean Raffuse, Susan O'Neill, and Rebecca Schmidt

Viewed

Total article views: 1,623 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,180 389 54 1,623 47 67
  • HTML: 1,180
  • PDF: 389
  • XML: 54
  • Total: 1,623
  • BibTeX: 47
  • EndNote: 67
Views and downloads (calculated since 06 Jul 2023)
Cumulative views and downloads (calculated since 06 Jul 2023)

Viewed (geographical distribution)

Total article views: 1,623 (including HTML, PDF, and XML) Thereof 1,573 with geography defined and 50 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
Short summary
Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.