Portable, Ambient PM2.5 Sensor for Human and/or Animal Exposure Studies

Tingting Cao, Jonathan E. Thompson

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


A field-portable device for logging PM2.5 mass concentration data has been developed. The device combines the Arduino microprocessor with an SD card, a Sharp DN7C3CA006 optical dust monitor, and 10,000-mAh battery. The dust sensor uses a virtual impactor to size select particles <2.5 microns prior to illuminating the selected fraction with an LED. The LED is triggered by a circuit controlled with the Arduino. Nephelometric detection at 120° referenced to incidence is used. The voltage signal reported by the dust sensor is converted to PM2.5 mass through calibration onboard the Arduino. Data points can be saved to the SD card as rapidly as 0.3 s, although averaging signals over 60 s produced more optimal detection limits. For a 60 s average, the PM2.5 mass limit of detection was 9 µg m−3, indicating that the sensor will be useful for monitoring human exposure to fine particles. Portable exposure monitoring has been demonstrated with the sensing platform as several individuals carried the device with them during daily activities in Lubbock, TX and Atlanta, GA. For this group of test subjects, values of PM2.5 exposure varied from 0 to 1000 µg m−3 during the sampling periods. It was observed that, by far, the highest levels of PM2.5 occur during periods of cooking, or being near cooking operations. Other periods of high PM2.5 occurred during ground transportation, use of personal care products, vacuuming, and visiting restrooms. When hourly personal exposure data were correlated with hourly average PM2.5 for outdoor air for the Atlanta data set, a very weak correlation was found (R2 = 0.026). Only two out of eight sampling periods did the personal monitoring estimate of exposure agree with that predicted by outdoor monitoring to within 15%. Personal exposure was often affected by circumstantial, short-term, high exposure events that are difficult to model or predict effectively. The short-term exposure events generally cause true exposure to be higher than that predicted by using outdoor ambient PM2.5 to generate estimates. This finding complicates interpretation of epidemiological studies that find links between ambient outdoor PM2.5 levels and human health, while it buttresses the case for using personal ambient monitors.

Original languageEnglish
Pages (from-to)712-723
Number of pages12
JournalAnalytical Letters
Issue number4
StatePublished - Mar 4 2017


  • Aerosol
  • PM
  • airborne particles
  • human exposure
  • portable monitoring


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