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https://hdl.handle.net/10217/167284

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Browsing Research Data by Subject "particulate matter"

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    ItemOpen Access
    Dataset associated with "Design and Testing of a Low-Cost Sensor and Sampling Platform for Indoor Air Quality"
    (Colorado State University. Libraries, 2021) Tryner, Jessica; Phillips, Mollie; Quinn, Casey W.; Neymark, Gabe; Wilson, Ander; Jather, Shantanu H.; Carter, Ellison; Volckens, John
    Americans spend most of their time indoors at home, but comprehensive characterization of in-home air pollution is limited by the cost and size of reference-quality monitors. We assembled small "Home Health Boxes" (HHBs) to measure indoor PM2.5, PM10, CO2, CO, NO2, and O3 concentrations using filter samplers and low-cost sensors. Nine HHBs were collocated with reference monitors in the kitchen of an occupied home in Fort Collins, Colorado, USA for 168 h while wildfire smoke impacted local air quality. When HHB data were interpreted using gas sensor manufacturers' calibrations, HHBs and reference monitors (a) categorized the level of each gaseous pollutant similarly (as either low, elevated, or high relative to air quality standards) and (b) both indicated that gas cooking burners were the dominant source of CO and NO2 pollution; however, HHB and reference O3 data were not correlated. When HHB gas sensor data were interpreted using linear mixed calibration models derived via collocation with reference monitors, root-mean-square error decreased for CO2 (from 408 to 58 ppm), CO (645 to 572 ppb), NO2 (22 to 14 ppb), and O3 (21 to 7 ppb); additionally, correlation between HHB and reference O3 data improved (Pearson's r increased from 0.02 to 0.75). Mean 168-h PM2.5 and PM10 concentrations derived from nine filter samples were 19.4 micrograms per cubic meter (6.1% relative standard deviation [RSD]) and 40.1 micrograms per cubic meter (7.6% RSD). The 168-h PM2.5 concentration was overestimated by PMS5003 sensors (median sensor/filter ratio = 1.7) and underestimated slightly by SPS30 sensors (median sensor/filter ratio = 0.91).
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    ItemOpen Access
    Dataset associated with "Laboratory evaluation of low-cost PurpleAir PM monitors and in-field correction using co-located portable filter samplers"
    (Colorado State University. Libraries, 2019) Tryner, Jessica; L'Orange, Christian; Mehaffy, John; Miller-Lionberg, Daniel; Hofstetter, Josephine C.; Wilson, Ander; Volckens, John
    Low-cost aerosol monitors can provide more spatially- and temporally-resolved data on ambient fine particulate matter (PM2.5) concentrations than are typically available from regulatory monitoring networks; however, low-cost monitors—which do not measure PM2.5 mass directly and tend to be sensitive to variations in particle size and refractive index—sometimes produce inaccurate concentration estimates. We investigated laboratory- and field-based approaches for calibrating low-cost PurpleAir monitors against gravimetric filter samples. First, we investigated the linearity of the PurpleAir response to NIST Urban PM and derived a laboratory-based gravimetric correction factor. Then, we co-located PurpleAir monitors with portable filter samplers at 15 outdoor sites spanning a 3×3-km area in Fort Collins, CO, USA. We evaluated whether PM2.5 correction factors derived from periodic co-locations with portable filter samplers improved the accuracy of PurpleAir monitors (relative to reference filter samplers operated at 16.7 L/min). We also compared 72-hour average PM2.5 concentrations measured using portable and reference filter samplers. Both before and after field deployment, the coefficient of determination for a linear model relating NIST Urban PM concentrations measured by a tapered element oscillating microbalance and the PurpleAir monitors (PM2.5 ATM) was 0.99; however, an F-test identified a significant lack of fit between the model and the data. The laboratory-based correction factor did not translate to the field. Correction factors derived in the field from monthly, weekly, semi-weekly, and concurrent co-locations with portable filter samplers increased the fraction of 72-hour average PurpleAir PM2.5 concentrations that were within 20% of the reference concentrations from 15% (for uncorrected measurements) to 45%, 59%, 56%, and 70%, respectively. Furthermore, 72-hour average PM2.5 concentrations measured using portable and reference filter samplers agreed (bias ≤ 20% for 71% of samples). These results demonstrate that periodic co-location with portable filter samplers can improve the accuracy of 72-hour average PM2.5 concentrations reported by PurpleAir monitors.