Size-Resolved Field Performance of Low-Cost Sensors for Particulate Matter Air Pollution

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 mu m). We recommend that crowdsourced air quality monitoring networks stop reporting coarse (PM2.5-10) mode and PM10 mass concentrations from these sensors.

Automated summary

Particulate matter (PM) air pollution is a major health hazard, with health effects closely related to particle size. Low-cost particle sensors have become popular but their accuracy across different particle size fractions is limited. We evaluated three low-cost sensor models in an urban setting and found that they were only accurate for the smallest particle size fraction (PM1), with significant biases and uncertainties for the larger size fractions. We recommend that crowdsourced air quality monitoring networks should not report coarse and PM10 mass concentrations using these sensors.