Sensor Selection to Improve Estimates of Particulate Matter Concentration from a Low-Cost Network

Sinan Sousan; Alyson Gray; Christopher Zuidema; Larissa Stebounova; Geb Thomas; Kirsten Koehler; Thomas Peters

doi:10.3390/s18093008

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Sensor Selection to Improve Estimates of Particulate Matter Concentration from a Low-Cost Network

Journal article

Open access

Peer reviewed

Sensor Selection to Improve Estimates of Particulate Matter Concentration from a Low-Cost Network

Sinan Sousan, Alyson Gray, Christopher Zuidema, Larissa Stebounova, Geb Thomas, Kirsten Koehler and Thomas Peters

Sensors (Basel, Switzerland), Vol.18(9), p.3008

09/08/2018

DOI: 10.3390/s18093008

PMCID: PMC6163282

PMID: 30205550

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Abstract

Deployment of low-cost sensors in the field is increasingly popular. However, each sensor requires on-site calibration to increase the accuracy of the measurements. We established a laboratory method, the Average Slope Method, to select sensors with similar response so that a single, on-site calibration for one sensor can be used for all other sensors. The laboratory method was performed with aerosolized salt. Based on linear regression, we calculated slopes for 100 particulate matter (PM) sensors, and 50% of the PM sensors fell within ±14% of the average slope. We then compared our Average Slope Method with an Individual Slope Method and concluded that our first method balanced convenience and precision for our application. Laboratory selection was tested in the field, where we deployed 40 PM sensors inside a heavy-manufacturing site at spatially optimal locations and performed a field calibration to calculate a slope for three PM sensors with a reference instrument at one location. The average slope was applied to all PM sensors for mass concentration calculations. The calculated percent differences in the field were similar to the laboratory results. Therefore, we established a method that reduces the time and cost associated with calibration of low-cost sensors in the field.

sensor selection

occupational monitoring

aerosol exposure

low-cost sensors

low-cost wireless network

sensor calibration

Details

Title: Subtitle: Sensor Selection to Improve Estimates of Particulate Matter Concentration from a Low-Cost Network
Creators: Sinan Sousan - Department of Occupational and Environmental Health, University of Iowa, Iowa City, IA 52242, USA. sousans18@ecu.edu
Alyson Gray - Department of Occupational and Environmental Health, University of Iowa, Iowa City, IA 52242, USA. alyson-gray@uiowa.edu
Christopher Zuidema - Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA. czuidema@jhu.edu
Larissa Stebounova - Department of Occupational and Environmental Health, University of Iowa, Iowa City, IA 52242, USA. larissa-stebounova@uiowa.edu
Geb Thomas - Department of Industrial and Systems Engineering, University of Iowa, Iowa City, IA 52242, USA. geb-thomas@uiowa.edu
Kirsten Koehler - Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA. kkoehle1@jhu.edu
Thomas Peters - Department of Occupational and Environmental Health, University of Iowa, Iowa City, IA 52242, USA. thomas-m-peters@uiowa.edu
Resource Type: Journal article
Publication Details: Sensors (Basel, Switzerland), Vol.18(9), p.3008
DOI: 10.3390/s18093008
PMID: 30205550
PMCID: PMC6163282
NLM abbreviation: Sensors (Basel)
ISSN: 1424-8220
eISSN: 1424-8220
Publisher: Switzerland
Grant note: R01 OH010533 / National Institute for Occupational Safety and Health
Language: English
Date published: 09/08/2018
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Occupational and Environmental Health; Orthopedics and Rehabilitation; Industrial and Systems Engineering
Record Identifier: 9983997468202771

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