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Household Indoor Particulate Matter Measurement Using a Network of Low-cost Sensors

Category: Air Pollution and Health Effects

Accepted Manuscripts
DOI: 10.4209/aaqr.2019.01.0046
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Shruti Hegde 1, Kyeong T. Min2, James Moore3, Philip Lundrigan3, Neal Patwari2, Scott Collingwood4, Alfred Balch4, Kerry E. Kelly1

  • 1 University of Utah, Department of Chemical Engineering, Salt Lake City, UT 84112, USA
  • 2 University of Utah, Department of Electrical and Computer Engineering, Salt Lake City, UT 84112, USA
  • 3 School of Computing, University of Utah, Salt Lake City, UT 84112, USA
  • 4 Department of Pediatrics, University of Utah, Salt Lake City, UT 84112, USA


  • Low-cost PM sensors, AirU and UMDS, correlated well with research instruments.
  • Low-cost PM sensor response depends on the PM source’s optical properties.
  • Both the AirU and the UMDS exhibited intra-sensor variability.
  • Elevated outdoor PM levels during a CAP increased indoor PM levels.
  • Cooking/frying and spraying of aerosol caused the greatest increase in indoor PM.


The World Health Organization estimates that 4.3 million deaths globally were attributed to household air pollution in 2012, and particulate matter (PM) with a diameter of 2.5µm or smaller (PM2.5) is a significant contributor to household air pollution. Low-cost PM measurements when integrated in a wireless network offer the promise of providing personalized information on indoor concentrations in real time so that individuals may take action. The objective of this study was to (1) deploy a network of research grade instruments and low-cost sensors in a home environment and evaluate their performance, (2) characterize activities and conditions that increase PM concentrations, and (3) identify how these activities affect PM levels in different rooms in a home. The wireless sensor network included low-cost PM sensors, a gateway, and a database for storing data. The low-cost sensors were based on the commercially available Dylos DC1100 Pro (Utah Modified Dylos Sensor) and Plantower PMS sensor (AirU). These were compared to three research-grade instruments – the GRIMM, DustTrak, and MiniVol in two households in Salt Lake City, during summer and winter. The results suggested that the AirU and Dylos-based sensor correlated well with the DustTrak. In this study, cooking (frying) and spraying of aerosol products caused the greatest increase in PM levels in the room of the activity (specifically in the kitchen and bedroom, respectively) as well as in surrounding rooms. The study also found that elevated outdoor PM levels during a cold air pool caused indoor PM levels to increase. In addition, the different PM sources caused different sensor responses. Consequently, obtaining accurate estimates of mass concentration from an indoor environment, with the wide variety of PM sources, would be challenging. However, low-cost PM sensors could be incorporated into an indoor air-quality measurement network to help individuals manage their personal PM exposure.


Indoor air Particulate matter Sensor network Low-cost particulate matter sensor Cold air pool

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