Doheon Kim, Dongmin Shin, Jungho Hwang This email address is being protected from spambots. You need JavaScript enabled to view it. 

Department of Mechanical Engineering, Yonsei University, Seoul 03722, Korea

Received: April 28, 2023
Revised: April 28, 2023
Accepted: May 16, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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Kim, D., Shin, D., Hwang, J. (2023). Calibration of Low-cost Sensors for Measurement of Indoor Particulate Matter Concentrations via Laboratory/Field Evaluation. Aerosol Air Qual. Res.


  • This study evaluates the accuracy of LCSs in comparison to a reference PM monitor.
  • LCSs show higher PM concentrations than the reference monitor, with variations.
  • This study conducted regression analysis to identify the causes of varied trends.
  • Identifying causes of varied trends, calibrating models to enhance LCS accuracy.


Recently, low-cost sensors (LCSs) have been widely used in monitoring particulate matter (PM) mass concentrations. Maintaining the accuracy of the sensors is important and requires rigorous calibration and performance evaluation. In this study, two commercial LCSs, Plantower PMS3003 and Plantower PMS7003, were evaluated in the laboratory and in the field using a reference-grade PM monitor (GRIMM 11-D). Laboratory evaluation was conducted with polystyrene latex (PSL) particles in a 1 m3 chamber at 20℃ with a relative humidity of 20%. Each LCS indicated higher mass concentrations than GRIMM 11-D for small-sized PSL particles (0.56 μm); however, the LCSs indicated lower mass concentrations than GRIMM 11-D for PSL particles larger than 0.56 μm. In addition, the difference in mass concentrations between the LCS and GRIMM 11-D became higher with particle sizes greater than 0.56 μm. Nonetheless, a high correlation (R2 > 0.9) between each LCS and GRIMM 11-D was obtained.

Field evaluation was conducted at Yonsei University (Seoul, South Korea) from February 12 to March 31, 2022. The LCSs showed generally higher PM mass concentrations than GRIMM 11-D; however, some data points of the LCSs revealed different trends. We observed that outdoor PM10/PM2.5 and relative humidity had notable impacts on the LCS data; in addition, LCS sensitivity depended on whether the PM concentration was low or high. Based on these observations, regression-based calibration models were constructed using the selected independent variables (outdoor PM10/PM2.5 and relative humidity) after dividing the PM concentration into low and high sections. Consequently, the accuracy of the LCSs was significantly enhanced. Therefore, using LCSs with the calibration models can replace the use of expensive reference PM monitors, resulting in cost savings.

Keywords: Indoor air quality, Particulate matter, Regression analysis, PM2.5, PM10

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