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Extensive evaluation and classification of low-cost dust sensors in laboratory using a newly developed test method.

Kang-Ho AhnHandol LeeHae Dong LeeSang Chul Kim
Published in: Indoor air (2019)
An extensive evaluation of low-cost dust sensors was performed using an exponentially decaying particle concentration. A total of 264 sensors including 27 sensors with light-emitting diodes (LEDs) and 237 sensors with laser lighting sources were tested. Those tested sensors were classified into 4 groups based on the deviation from the reference data obtained by a reference instrument. The response linearities of all the tested samples for PM1 , PM2.5 , and PM10 were in excellent agreement with the reference instrument, except a few samples. For the measurements of PM1 and PM2.5 , the lighting source, that is, LED or laser, did not show any significant difference in overall sensor performance. However, LED-based sensors did not perform well for PM10 measurements. The 32, 24, and 16% of all the tested sensors for PM1 , PM2.5 , and PM10 measurement, respectively, are in the category of Class 1 (reference instrument reading ± 20%) requirement. The performance of the low-cost dust sensors for PM10 measurement was relatively less satisfactory.
Keyphrases
  • low cost
  • particulate matter
  • polycyclic aromatic hydrocarbons
  • air pollution
  • heavy metals
  • water soluble
  • health risk
  • machine learning
  • risk assessment
  • deep learning
  • electronic health record
  • mass spectrometry
  • big data