Field Evaluation of Low-Cost Particulate Matter Sensors in Beijing

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 16; p. 4381
• Main Authors: Mei, Han, Han, Pengfei, Wang, Yinan, Zeng, Ning, Liu, Di, Cai, Qixiang, Deng, Zhaoze, Wang, Yinghong, Pan, Yuepeng, Tang, Xiao
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 05.08.2020; MDPI
• Subjects: Accuracy; Aerosols; Bias; Calibration; Climate change; Correlation analysis; Dust storms; Efficiency; Evaluation; Experiments; field evaluation; Field study; high PM concentration; Humidity; impact of air humidity; Laboratories; Low cost; low-cost particulate matter sensors; Monitoring; Monitors; Particle size; Particulate emissions; Relative humidity; Sensors; Universal Serial Bus; Beijing China; China
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s20164381

Numerous particulate matter (PM) sensors with great development potential have emerged. However, whether the current sensors can be used for reliable long-term field monitoring is unclear. This study describes the research and application prospects of low-cost miniaturized sensors in PM2.5 monitoring. We evaluated five Plantower PMSA003 sensors deployed in Beijing, China, over 7 months (October 2019 to June 2020). The sensors tracked PM2.5 concentrations, which were compared to the measurements at the national control monitoring station of the Ministry of Ecology and Environment (MEE) at the same location. The correlations of the data from the PMSA003 sensors and MEE reference monitors (R2 = 0.83~0.90) and among the five sensors (R2 = 0.91~0.98) indicated a high accuracy and intersensor correlation. However, the sensors tended to underestimate high PM2.5 concentrations. The relative bias reached −24.82% when the PM2.5 concentration was >250 µg/m3. Conversely, overestimation and high errors were observed during periods of high relative humidity (RH > 60%). The relative bias reached 14.71% at RH > 75%. The PMSA003 sensors performed poorly during sand and dust storms, especially for the ambient PM10 concentration measurements. Overall, this study identified good correlations between PMSA003 sensors and reference monitors. Extreme field environments impact the data quality of low-cost sensors, and future corrections remain necessary.