Articles | Volume 15, issue 21
https://doi.org/10.5194/amt-15-6309-2022
https://doi.org/10.5194/amt-15-6309-2022
Research article
 | 
02 Nov 2022
Research article |  | 02 Nov 2022

Calibrating networks of low-cost air quality sensors

Priyanka deSouza, Ralph Kahn, Tehya Stockman, William Obermann, Ben Crawford, An Wang, James Crooks, Jing Li, and Patrick Kinney

Viewed

Total article views: 7,293 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
4,889 2,281 123 7,293 460 162 170
  • HTML: 4,889
  • PDF: 2,281
  • XML: 123
  • Total: 7,293
  • Supplement: 460
  • BibTeX: 162
  • EndNote: 170
Views and downloads (calculated since 08 Mar 2022)
Cumulative views and downloads (calculated since 08 Mar 2022)

Viewed (geographical distribution)

Total article views: 7,293 (including HTML, PDF, and XML) Thereof 7,215 with geography defined and 78 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 04 May 2026
Download
Short summary
How sensitive are the spatial and temporal trends of PM2.5 derived from a network of low-cost sensors to the calibration adjustment used? How transferable are calibration equations developed at a few co-location sites to an entire network of low-cost sensors? This paper attempts to answer this question and offers a series of suggestions on how to develop the most robust calibration function for different end uses. It uses measurements from the Love My Air network in Denver as a test case.
Share