» Articles » PMID: 32704250

Field Test of Several Low-Cost Particulate Matter Sensors in High and Low Concentration Urban Environments

Overview
Date 2020 Jul 25
PMID 32704250
Citations 27
Authors
Affiliations
Soon will be listed here.
Abstract

Detailed quantification of the spatial and temporal variability of ambient fine particulate matter (PM) has, to date, been limited due to the cost and logistics involved with traditional monitoring approaches. New miniaturized particle sensors are a potential strategy to gather more time- and spatially-resolved data, to address data gaps in regions with limited monitoring and to address important air quality research priorities in a more cost-effective manner. This work presents field evaluations and lab testing of three models of low-cost (< $200) PM sensors (SHINYEI: models PPD42NS, PPD20V, PPD60PV) in three locations: urban background (average PM: 8 μg m) and roadside in Atlanta, Georgia, USA (average PM: 21 μg m), and a location with higher ambient concentrations in Hyderabad, India (average PM: 72 μg m). Sensor measurements were compared against reference monitors in the lab using one-minute averages and in field locations using one-hour averages. At the Atlanta sites the sensors were weakly correlated with a tapered element oscillating microbalance (TEOM) at best (R ≤ 0.30). In Hyderabad, the PPD20V sensors had the highest correlation with the environmental beta attenuation monitor (E-BAM) (R > 0.80), however the same sensors had poor agreement if the comparison was restricted to lower concentrations (R = ~0, < 40 μg m). The results of this work indicate the potential usefulness of these sensors, including the PPD20V, for higher concentration applications (< ~250 μg m). These field- testing results provide important insights into the varying performance of low-cost PM sensors under highly contrasting atmospheric conditions. The inconsistent performance results underscore the need for rigorous evaluation of optical particle sensors in the laboratory and in diverse field environments.

Citing Articles

Evaluation of Long-Term Performance of Six PM Sensor Types.

Barkjohn K, Yaga R, Thomas B, Schoppman W, Docherty K, Clements A Sensors (Basel). 2025; 25(4).

PMID: 40006494 PMC: 11861664. DOI: 10.3390/s25041265.


A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors.

Smith S, Trefonides T, Srirenganathan Malarvizhi A, LaGarde S, Liu J, Jia X Sensors (Basel). 2025; 25(4).

PMID: 40006257 PMC: 11859157. DOI: 10.3390/s25041028.


Parsimonious Random-Forest-Based Land-Use Regression Model Using Particulate Matter Sensors in Berlin, Germany.

Venkatraman Jagatha J, Schneider C, Sauter T Sensors (Basel). 2024; 24(13).

PMID: 39000970 PMC: 11244214. DOI: 10.3390/s24134193.


Enhancing the reliability of particulate matter sensing by multivariate Tobit model using weather and air quality data.

Won W, Noh J, Oh R, Lee W, Lee J, Su P Sci Rep. 2023; 13(1):13150.

PMID: 37573439 PMC: 10423292. DOI: 10.1038/s41598-023-40468-z.


Gaps and future directions in research on health effects of air pollution.

Vilcassim R, Thurston G EBioMedicine. 2023; 93:104668.

PMID: 37357089 PMC: 10363432. DOI: 10.1016/j.ebiom.2023.104668.


References
1.
Bart M, Williams D, Ainslie B, McKendry I, Salmond J, Grange S . High density ozone monitoring using gas sensitive semi-conductor sensors in the Lower Fraser Valley, British Columbia. Environ Sci Technol. 2014; 48(7):3970-7. DOI: 10.1021/es404610t. View

2.
Snyder E, Watkins T, Solomon P, Thoma E, Williams R, Hagler G . The changing paradigm of air pollution monitoring. Environ Sci Technol. 2013; 47(20):11369-77. DOI: 10.1021/es4022602. View

3.
Kuula J, Makela T, Hillamo R, Timonen H . Response Characterization of an Inexpensive Aerosol Sensor. Sensors (Basel). 2017; 17(12). PMC: 5751569. DOI: 10.3390/s17122915. View

4.
Austin E, Novosselov I, Seto E, Yost M . Laboratory Evaluation of the Shinyei PPD42NS Low-Cost Particulate Matter Sensor. PLoS One. 2015; 10(9):e0137789. PMC: 4569398. DOI: 10.1371/journal.pone.0137789. View

5.
Jiang R, Acevedo-Bolton V, Cheng K, Klepeis N, Ott W, Hildemann L . Determination of response of real-time SidePak AM510 monitor to secondhand smoke, other common indoor aerosols, and outdoor aerosol. J Environ Monit. 2011; 13(6):1695-702. DOI: 10.1039/c0em00732c. View