Literature DB >> 32647492

One Year Evaluation of Three Low-Cost PM2.5 Monitors.

Misti Levy Zamora1, Jessica Rice2, Kirsten Koehler1.   

Abstract

The availability of low-cost monitors marketed for use in homes has increased rapidly over the past few years due to the advancement of sensing technologies, increased awareness of urban pollution, and the rise of citizen science. The user-friendly packages can make them appealing for use in research grade indoor exposure assessments, but a rigorous scientific evaluation has not been conducted for many monitors on the open market, which leads to uncertainty about the validity of the data. Furthermore, many previous sensor studies were conducted for a relatively short period of time, which may not capture the changes this type of instrument may exhibit over time (known as sensor aging). We evaluated three monitors (AirVisual Pro, Speck, and AirThinx) in an occupied, non-smoking residence over a 12-month period in order to assess the sensors, the built-in calibrations, and the need for additional data to achieve high accuracy for long deployments. Two units of each type of monitor were evaluated in order to assess the precision between units, and a personal DataRAM (pDR-1200) with a filter was placed in the home for about 20% of the sampling period (e.g., about a week each month) to evaluate the accuracy over time. The average PM2.5 mass concentration from the periods of colocation with the pDR were 5.31 μg/m3 for the gravimetric-corrected pDR (hereafter pDR-corrected), 5.11 and 5.03 μg/m3 for the AirVisual Pro units, 13.58 and 22.68 μg/m3 for the Speck units, and 7.56 and 7.57 μg/m3 for the AirThinx units. The AirVisual Pros exhibited the best accuracy compared to the filter at about 86%, which was slightly better than the nephelometric component of the pDR compared to the filter weight (84%). The accuracies of the Speck (-174 and -405%) and AirThinx (42 and 40%) monitors were much lower. When the 1-minute averaged PM2.5 mass concentrations were categorized by air quality index (AQI), the pDR-corrected matched the AirVisual Pro, Speck, and AirThinx bins about 97, 40, and 87% of the time, respectively. The Pearson correlation coefficients (R2) between the unit pairs and the pDR were 0.90/0.90, 0.50/0.27, and 0.92/0.93 for the AirVisual Pro, Speck, and AirThinx units, respectively. The R2 between units of the same type were 0.99, 0.17, and 1.00 for the AirVisual Pro, Speck, and AirThinx, respectively. All of the monitors could achieve better accuracy by adding filter corrections and post-processing to correct for known biases in addition to the manufacturer's correction routine. Monthly calibrations yielded the highest accuracies, but nearly as high of accuracies could be achieved with only one or two calibrations for the Air Visual Pro and the AirThinx for many applications. In general, this type of new low-cost monitor shows exciting potential for use in scientific research. However, only one of the three monitors exhibited high accuracy (within 20% of the true mass concentration) without any post processing or additional measurements, so an evaluation of each monitor is essential before the data can be used to confidently evaluate residential exposures.

Entities:  

Keywords:  AirThinx; AirVisual Pro; Indoor Air; Indoor Exposures; Low-cost sensors; PM2.5; Pollution; Speck

Year:  2020        PMID: 32647492      PMCID: PMC7347290          DOI: 10.1016/j.atmosenv.2020.117615

Source DB:  PubMed          Journal:  Atmos Environ (1994)        ISSN: 1352-2310            Impact factor:   4.798


  22 in total

1.  Indoor air quality in Portuguese schools: levels and sources of pollutants.

Authors:  J Madureira; I Paciência; C Pereira; J P Teixeira; E de O Fernandes
Journal:  Indoor Air       Date:  2015-08-21       Impact factor: 5.770

2.  Field and Laboratory Evaluations of the Low-Cost Plantower Particulate Matter Sensor.

Authors:  Misti Levy Zamora; Fulizi Xiong; Drew Gentner; Branko Kerkez; Joseph Kohrman-Glaser; Kirsten Koehler
Journal:  Environ Sci Technol       Date:  2019-01-03       Impact factor: 9.028

3.  The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants.

Authors:  N E Klepeis; W C Nelson; W R Ott; J P Robinson; A M Tsang; P Switzer; J V Behar; S C Hern; W H Engelmann
Journal:  J Expo Anal Environ Epidemiol       Date:  2001 May-Jun

4.  Response of consumer and research grade indoor air quality monitors to residential sources of fine particles.

Authors:  B C Singer; W W Delp
Journal:  Indoor Air       Date:  2018-05-14       Impact factor: 5.770

5.  Evaluation of consumer monitors to measure particulate matter.

Authors:  Sinan Sousan; Kirsten Koehler; Laura Hallett; Thomas M Peters
Journal:  J Aerosol Sci       Date:  2017-02-21       Impact factor: 3.433

6.  Inter-comparison of Low-cost Sensors for Measuring the Mass Concentration of Occupational Aerosols.

Authors:  Sinan Sousan; Kirsten Koehler; Geb Thomas; Jae Hong Park; Michael Hillman; Andrew Halterman; Thomas M Peters
Journal:  Aerosol Sci Technol       Date:  2016-03-10       Impact factor: 2.908

7.  Comparison of real-time instruments and gravimetric method when measuring particulate matter in a residential building.

Authors:  Zuocheng Wang; Leonardo Calderón; Allison P Patton; MaryAnn Sorensen Allacci; Jennifer Senick; Richard Wener; Clinton J Andrews; Gediminas Mainelis
Journal:  J Air Waste Manag Assoc       Date:  2016-11       Impact factor: 2.235

8.  Maternal exposure to PM2.5 in south Texas, a pilot study.

Authors:  Misti Levy Zamora; Jairus C Pulczinski; Natalie Johnson; Rosa Garcia-Hernandez; Ana Rule; Genny Carrillo; Josias Zietsman; Brenda Sandragorsian; Suriya Vallamsundar; Mohammad H Askariyeh; Kirsten Koehler
Journal:  Sci Total Environ       Date:  2018-02-20       Impact factor: 7.963

9.  Humidity and gravimetric equivalency adjustments for nephelometer-based particulate matter measurements of emissions from solid biomass fuel use in cookstoves.

Authors:  Sutyajeet Soneja; Chen Chen; James M Tielsch; Joanne Katz; Scott L Zeger; William Checkley; Frank C Curriero; Patrick N Breysse
Journal:  Int J Environ Res Public Health       Date:  2014-06-19       Impact factor: 3.390

Review 10.  Low-Cost Air Quality Monitoring Tools: From Research to Practice (A Workshop Summary).

Authors:  Andrea L Clements; William G Griswold; Abhijit Rs; Jill E Johnston; Megan M Herting; Jacob Thorson; Ashley Collier-Oxandale; Michael Hannigan
Journal:  Sensors (Basel)       Date:  2017-10-28       Impact factor: 3.576

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  2 in total

1.  Evaluating the Performance of Using Low-Cost Sensors to Calibrate for Cross-Sensitivities in a Multipollutant Network.

Authors:  Misti Levy Zamora; Colby Buehler; Hao Lei; Abhirup Datta; Fulizi Xiong; Drew R Gentner; Kirsten Koehler
Journal:  ACS ES T Eng       Date:  2022-04-11

Review 2.  Towards Personalization of Indoor Air Quality: Review of Sensing Requirements and Field Deployments.

Authors:  Qian Xu; Hui Ci Goh; Ehsan Mousavi; Hamed Nabizadeh Rafsanjani; Zubin Varghese; Yogesh Pandit; Ali Ghahramani
Journal:  Sensors (Basel)       Date:  2022-04-30       Impact factor: 3.847

  2 in total

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