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Environmental Engineering Research 2022;27(5): 200501 DOI: https://doi.org/10.4491/eer.2020.501
A new evaluation method of three different low-cost dust sensors using exponentially decaying particle concentrations
Ki-Tai Kang1, Handol Lee2, Hyeok Chung3, and Kang-Ho Ahn4 
1Department of Mechanical Engineering, Hanyang University, Seoul, 04763, Republic of Korea
2Department of Environmental Engineering, Inha University, Incheon, 22212, Republic of Korea
3ART+, 195-62, Daepyeong-ro, Daewol-myeon, Icheon-si, Gyunggi-do, Republic of Korea
4Department of Mechanical Engineering, Hanyang University, ERICA, Ansan, 15588, Republic of Korea
Corresponding Author: Kang-Ho Ahn ,Tel: +82-31-417-0601, Fax: +82-31-436-8184, Email: khahn@hanyang.ac.kr
Received: September 6, 2020;  Accepted: December 10, 2020.
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Low-cost optical dust sensors are widely used in air purifiers, air conditioners, and air-quality monitoring networks. However, the quality and reliability of these sensors have always been disputed because a standard calibration method has not been established. Low-cost dust sensors used by researchers are calibrated using the researchers’ own methods by applying, for example, a co-location test with reference instruments, a chamber test, or a low-speed duct test. In this study, a test method for the performance evaluation of low-cost sensors was developed using KCl particles with an exponentially decaying particle concentration. With this method, the testing time can be significantly reduced to less than 10 min, and the response characteristics of the sensors to rapidly changing concentrations can be determined. AirAssure from TSI Inc., AirBeam2 from HabitatMap LLC, and DC1100 from Dylos were tested accordingly. The linearities of the measured particulate matter concentrations were significantly good (R2 > 0.95), except for the AirAssure sensors. It was also found that the response characteristics of the sensors depended on the particle concentration decay times.
Keywords: Dust sensor evaluation | Exponentially decaying particle concentration | Low-cost dust sensor | Particulate matter | Response characteristic
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