Literature DB >> 28871212

Evaluation of consumer monitors to measure particulate matter.

Sinan Sousan1, Kirsten Koehler2, Laura Hallett1, Thomas M Peters1.   

Abstract

Recently, inexpensive (<$300) consumer aerosol monitors (CAMs) targeted for use in homes have become available. We evaluated the accuracy, bias, and precision of three CAMs (Foobot from Airoxlab, Speck from Carnegie Mellon University, and AirBeam from HabitatMap) for measuring mass concentrations in occupational settings. In a laboratory study, PM2.5 measured with the CAMs and a medium-cost aerosol photometer (personal DataRAM 1500, Thermo Scientific) were compared to that from reference instruments for three aerosols (salt, welding fume, and Arizona road dust, ARD) at concentrations up to 8500 μg/m3. Three of each type of CAM were included to estimate precision. Compared to reference instruments, mass concentrations measured with the Foobot (r-value = 0.99) and medium-cost photometer (r-value = 0.99) show strong correlation, whereas those from the Speck (r-value range 0.88 - 0.99) and AirBeam (0.7 - 0.96) were less correlated. The Foobot bias was (-12%) for ARD and measurements were similar to the medium-cost instrument. Foobot bias was (< -46%) for salt and welding fume aerosols. Speck bias was at 18% salt for ARD and -86% for welding fume. AirBeam bias was (-36%) for salt and (-83%) for welding fume. All three photometers had a bias (< -82%) for welding fume. Precision was excellent for the Foobot (coefficient of variation range: 5% to 8%) and AirBeam (2% to 9%), but poorer for the Speck (8% to 25%). These findings suggest that the Foobot, with a linear response to different aerosol types and good precision, can provide reasonable estimates of PM2.5 in the workplace after site-specific calibration to account for particle size and composition.

Entities:  

Keywords:  AirBeam; Foobot; Low-cost monitors; PM2.5; Speck; environmental monitoring; occupational monitoring

Year:  2017        PMID: 28871212      PMCID: PMC5580935          DOI: 10.1016/j.jaerosci.2017.02.013

Source DB:  PubMed          Journal:  J Aerosol Sci        ISSN: 0021-8502            Impact factor:   3.433


  9 in total

Review 1.  Pulmonary responses to welding fumes: role of metal constituents.

Authors:  James M Antonini; Michael D Taylor; Anthony T Zimmer; Jenny R Roberts
Journal:  J Toxicol Environ Health A       Date:  2004-02-13

2.  Comparison of the Grimm 1.108 and 1.109 portable aerosol spectrometer to the TSI 3321 aerodynamic particle sizer for dry particles.

Authors:  Thomas M Peters; Darrin Ott; Patrick T O'Shaughnessy
Journal:  Ann Occup Hyg       Date:  2006-10-14

3.  Comparison of the TSI Model 8520 and Grimm Series 1.108 portable aerosol instruments used to monitor particulate matter in an iron foundry.

Authors:  Yu-Hsiang Cheng
Journal:  J Occup Environ Hyg       Date:  2008-03       Impact factor: 2.155

4.  Evaluation of the Alphasense Optical Particle Counter (OPC-N2) and the Grimm Portable Aerosol Spectrometer (PAS-1.108).

Authors:  Sinan Sousan; Kirsten Koehler; Laura Hallett; Thomas M Peters
Journal:  Aerosol Sci Technol       Date:  2016-09-07       Impact factor: 2.908

Review 5.  Health effects of welding.

Authors:  James M Antonini
Journal:  Crit Rev Toxicol       Date:  2003       Impact factor: 5.635

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.  Risk of lung cancer according to mild steel and stainless steel welding.

Authors:  Anita Rath Sørensen; Ane Marie Thulstrup; Johnni Hansen; Cecilia Høst Ramlau-Hansen; Andrea Meersohn; Axel Skytthe; Jens Peter Bonde
Journal:  Scand J Work Environ Health       Date:  2007-10       Impact factor: 5.024

8.  A Cross-Sectional Study of the Cardiovascular Effects of Welding Fumes.

Authors:  Huiqi Li; Maria Hedmer; Monica Kåredal; Jonas Björk; Leo Stockfelt; Håkan Tinnerberg; Maria Albin; Karin Broberg
Journal:  PLoS One       Date:  2015-07-06       Impact factor: 3.240

9.  Considerations in the use of ozone and PM(2.5) data for exposure assessment.

Authors:  Warren H White
Journal:  Air Qual Atmos Health       Date:  2009-12-09       Impact factor: 3.763

  9 in total
  18 in total

1.  Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul, South Korea.

Authors:  Chris C Lim; Ho Kim; M J Ruzmyn Vilcassim; George D Thurston; Terry Gordon; Lung-Chi Chen; Kiyoung Lee; Michael Heimbinder; Sun-Young Kim
Journal:  Environ Int       Date:  2019-07-27       Impact factor: 9.621

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

Authors:  Misti Levy Zamora; Jessica Rice; Kirsten Koehler
Journal:  Atmos Environ (1994)       Date:  2020-05-31       Impact factor: 4.798

Review 3.  Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone?

Authors:  Lidia Morawska; Phong K Thai; Xiaoting Liu; Akwasi Asumadu-Sakyi; Godwin Ayoko; Alena Bartonova; Andrea Bedini; Fahe Chai; Bryce Christensen; Matthew Dunbabin; Jian Gao; Gayle S W Hagler; Rohan Jayaratne; Prashant Kumar; Alexis K H Lau; Peter K K Louie; Mandana Mazaheri; Zhi Ning; Nunzio Motta; Ben Mullins; Md Mahmudur Rahman; Zoran Ristovski; Mahnaz Shafiei; Dian Tjondronegoro; Dane Westerdahl; Ron Williams
Journal:  Environ Int       Date:  2018-04-26       Impact factor: 9.621

4.  Performance of Four Consumer-grade Air Pollution Measurement Devices in Different Residences.

Authors:  Sydonia Manibusan; Gediminas Mainelis
Journal:  Aerosol Air Qual Res       Date:  2020-02       Impact factor: 3.063

5.  Variation in gravimetric correction factors for nephelometer-derived estimates of personal exposure to PM2.5.

Authors:  Jessica Tryner; Nicholas Good; Ander Wilson; Maggie L Clark; Jennifer L Peel; John Volckens
Journal:  Environ Pollut       Date:  2019-04-05       Impact factor: 8.071

6.  Sources of error and variability in particulate matter sensor network measurements.

Authors:  Christopher Zuidema; Larissa V Stebounova; Sinan Sousan; Geb Thomas; Kirsten Koehler; Thomas M Peters
Journal:  J Occup Environ Hyg       Date:  2019-06-28       Impact factor: 2.155

7.  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

8.  Monitoring secondhand tobacco smoke remotely in real-time: A simple low-cost approach.

Authors:  Ruaraidh Dobson; Laura J Rosen; Sean Semple
Journal:  Tob Induc Dis       Date:  2019-03-05       Impact factor: 2.600

9.  Low-Cost, Distributed Environmental Monitors for Factory Worker Health.

Authors:  Geb W Thomas; Sinan Sousan; Marcus Tatum; Xiaoxing Liu; Christopher Zuidema; Mitchell Fitzpatrick; Kirsten A Koehler; Thomas M Peters
Journal:  Sensors (Basel)       Date:  2018-05-03       Impact factor: 3.576

10.  Validation of Miniaturized Particulate-Matter Real-Time Samplers for Characterizing Personal Polycyclic Aromatic Hydrocarbon Exposure.

Authors:  Beizhan Yan; Masha Pitiranggon; James Ross; Thomas Arthen-Engeland; Andreas Stelter; Steven N Chillrud
Journal:  J Anal Bioanal Tech       Date:  2018-04-11
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