Size-Resolved Field Performance of Low-Cost Sensors for Particulate Matter Air Pollution
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2023/03/14
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Description:Particulate matter (PM) air pollution is a major health hazard. The health effects of PM are closely linked to particle size, which governs its deposition in (and penetration through) the respiratory tract. In recent years, low-cost sensors that report particle concentrations for multiple-sized fractions (PM1.0, PM2.5, PM10) have proliferated in everyday use and scientific research. However, knowledge of how well these sensors perform across the full range of reported particle size fractions is limited. Unfortunately, erroneous particle size data can lead to spurious conclusions about exposure, misguided interventions, and ineffectual policy decisions. We assessed the linearity, bias, and precision of three low-cost sensor models, as a function of PM size fraction, in an urban setting. Contrary to manufacturers' claims, sensors are only accurate for the smallest size fraction (PM1). The PM1.0-2.5 and PM2.5-10 size fractions had large bias, noise, and uncertainty. These results demonstrate that low-cost aerosol sensors (1) cannot discriminate particle size accurately and (2) only report linear and precise measures of aerosol concentration in the accumulation mode size range (i.e., between 0.1 and 1 µm). We recommend that crowdsourced air quality monitoring networks stop reporting coarse (PM2.5-10) mode and PM10 mass concentrations from these sensors. [Description provided by NIOSH]
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ISSN:2328-8930
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Pages in Document:247-253
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Volume:10
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Issue:3
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NIOSHTIC Number:nn:20067739
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Citation:Environ Sci Technol Lett 2023 Mar; 10(3):247-253
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Contact Point Address:John Volckens, Department of Mechanical Engineering, Colorado State University, Fort Collins, Colorado 80523, United States
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Email:john.volckens@colostate.edu
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Federal Fiscal Year:2023
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Performing Organization:Colorado State University
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Peer Reviewed:True
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Start Date:20190901
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Source Full Name:Environmental Science and Technology Letters
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End Date:20230831
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Main Document Checksum:urn:sha-512:c0d13f8ed2737c5485949eb6a43e60b27fe7a4e52d85a82d16dca716f8baad21a147248838f2521c0b107c4846fc57b9f34fe6d6e445182faf9e8b2d010654c5
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