期刊
PLOS ONE
卷 16, 期 11, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0259745
关键词
-
资金
- National Institute of Environmental Health Sciences [1R21ES024715, 1R33ES024715]
- National Institute of Biomedical Imaging and Bioengineering [U01 EB021923]
Low-cost optical scattering particulate matter (PM) sensors report total or size-specific particle counts and mass concentrations, with estimation by OEM proprietary algorithms. Improved calibration algorithms for the Plantower PMS A003 sensor were developed for enhanced accuracy, taking into account aerosol properties and environmental conditions to reduce errors in mass concentration estimates by the OEM. The calibration models can be used in various monitoring scenarios where field calibration may pose challenges.
Low-cost optical scattering particulate matter (PM) sensors report total or size-specific particle counts and mass concentrations. The PM concentration and size are estimated by the original equipment manufacturer (OEM) proprietary algorithms, which have inherent limitations since particle scattering depends on particles' properties such as size, shape, and complex index of refraction (CRI) as well as environmental parameters such as temperature and relative humidity (RH). As low-cost PM sensors are not able to resolve individual particles, there is a need to characterize and calibrate sensors' performance under a controlled environment. Here, we present improved calibration algorithms for Plantower PMS A003 sensor for mass indices and size-resolved number concentration. An aerosol chamber experimental protocol was used to evaluate sensor-to-sensor data reproducibility. The calibration was performed using four polydisperse test aerosols. The particle size distribution OEM calibration for PMS A003 sensor did not agree with the reference single particle sizer measurements. For the number concentration calibration, the linear model without adjusting for the aerosol properties and environmental conditions yields an absolute error (NMAE) of similar to 4.0% compared to the reference instrument. The calibration models adjusted for particle CRI and density account for non-linearity in the OEM's mass concentrations estimates with NMAE within 5.0%. The calibration algorithms developed in this study can be used in indoor air quality monitoring, occupational/industrial exposure assessments, or near-source monitoring scenarios where field calibration might be challenging.
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