Articles | Volume 19, issue 3
https://doi.org/10.5194/amt-19-1077-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-1077-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Feb 2026
Research article |
| 16 Feb 2026
| 16 Feb 2026
Correction of PM2.5 underestimation in low-cost sensors under elevated dust loading using only sensor measurements
Kamaljeet Kaur
CORRESPONDING AUTHOR
Department of Chemical Engineering, University of Utah, Salt Lake City, UT, 84112, USA
Tristalee Mangin
Department of Chemical Engineering, University of Utah, Salt Lake City, UT, 84112, USA
Kerry E. Kelly
Department of Chemical Engineering, University of Utah, Salt Lake City, UT, 84112, USA
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Short summary
We improved the accuracy of low-cost particulate matter sensor (PMS5003/6003) measurements under dust-dominated conditions common in arid regions. By applying sensor-specific particle mass ratios and a relative humidity cutoff, dust-influenced measurements were identified and PM2.5 concentrations corrected, reducing bias by ~ 50 % relative to regulatory monitors. This method enables real-time PM2.5 correction where reference data are unavailable.
We improved the accuracy of low-cost particulate matter sensor (PMS5003/6003) measurements under...
