These data along with assumptions of particle shape and density can be converted to estimate mass concentrations that compare favorably to reference instruments ( T. OPCs use the light scattered from individual particles to estimate number concentration for different particle size ranges. Some of these instruments depend on light scattering, such as optical particle counters (OPCs) or photometers. Equivalent methods (e.g.,personal dust monitor PDM 3700, Thermo Scientific, TSI Inc., Shoreview, MN, USA) often provide high temporal resolution, but are expensive (>$15,000 per monitor), resulting in little spatial information ( White, 2009).ĭirect-reading instruments are available to measure PM at high temporal resolution and in situ ( Cheng, 2008 Yanosky, Williams, & MacIntosh, 2002). Although accurate and precise, filter-based measurements are expensive, time-consuming, and provide little temporal information.
These measurements are based on gravimetric, filter-based methods (the “gold standard”), or methods deemed equivalent to filter-based methods ( NIOSH, 1975). To avoid the development of adverse health effects from inhaling particles, the Occupational Safety and Health Administration (OSHA) requires employers to maintain workplace, 8-h time-weighted average, respirable PM below 5 mg/m 3 for particles not otherwise regulated (PNOR) ( OSHA, 2006). In occupational studies, exposure to respirable particulate matter (PM), the fraction of particles that can penetrate to the alveolar regions of the lungs ( Antonini, 2003), is associated with respiratory diseases ( Antonini, 2003, Taylor, Zimmer, & Roberts, 2004), lung cancer ( Sørensen et al., 2007), and cardiovascular diseases ( Li et al., 2015). These findings suggest that the Foobot, with a linear response to different aerosol types and good precision, can provide reasonable estimates of PM 2.5 in the workplace after site-specific calibration to account for particle size and composition. 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%). All three photometers had a bias (< −82%) for welding fume. AirBeam bias was (−36%) for salt and (−83%) for welding fume. Speck bias was at 18% salt for ARD and −86% for welding fume. Foobot bias was (< −46%) for salt and welding fume aerosols. The Foobot bias was (−12%) for ARD and measurements were similar to the medium-cost instrument. 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. Three of each type of CAM were included to estimate precision. In a laboratory study, PM 2.5 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/m 3.
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. Recently, inexpensive (<$300) consumer aerosol monitors (CAMs) targeted for use in homes have become available.
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