Preprints
https://doi.org/10.5194/amt-2022-292
https://doi.org/10.5194/amt-2022-292
 
02 Dec 2022
02 Dec 2022
Status: this preprint is currently under review for the journal AMT.

Performance evaluation of the Alphasense OPC-N3 and Plantower PMS5003 sensor in measuring dust events in the Salt Lake Valley, Utah

Kamaljeet Kaur and Kerry E. Kelly Kamaljeet Kaur and Kerry E. Kelly
  • Department of Chemical Engineering, University of Utah, SLC, 84102, USA

Abstract. As the changing climate expands the extent of arid and semi-arid lands, the number, severity of, and health effects associated with dust events are likely to increase. However, regulatory measurements capable of capturing dust (PM10, particulate matter smaller than 10 µm in diameter) are sparse, sparser than measurements of PM2.5 (PM smaller than 2.5 µm in diameter). Although low-cost sensors could supplement regulatory monitors, as numerous studies have shown for PM2.5 concentration, most of these sensors are not effective at measuring PM10 despite claims by sensor manufacturers. This study focuses on the Salt Lake Valley, adjacent to the Great Salt Lake, which recently reached historic lows exposing 1865 km2 of dry lakebed. It evaluated the field performance of the Plantower PMS 5003, a common low-cost PM sensor, and the Alphasense OPC-N3, a promising candidate for low-cost measurement of PM10, against a federal equivalent method (FEM, beta attenuation) and research measurements (GRIMM aerosol spectrophotometer) at three different locations. During a month-long field study that included five dust events in the Salt Lake Valley with PM10 concentrations reaching 311 µg/m3, the OPC-N3 exhibited strong correlation with FEM PM10 measurements (R2 = 0.865, RMSE = 12.4 µg/m3) and GRIMM (R2= 0.937, RMSE = 17.7 µg/m3). The PMS sensor exhibited poor to moderate correlations (R2<0.49, RMSE = 33–45 µg/m3) with reference/research monitors and severely underestimated the PM10 concentrations (slope <0.099) for PM10. We also evaluated a PM-ratio-based correction method to improve the estimated PM10 concentration from PMS sensors. After applying this method, PMS PM10 concentrations correlated reasonably well with FEM measurements (R2 > 0.63) and GRIMM measurements (R2 > 0.76), and the RMSE decreased to 15–25 µg/m3. Our results suggest that it may be possible to obtain better resolved spatial estimates of PM10 concentration using a combination of PMS sensors (often publicly available in communities) and measurements of PM2.5 and PM10, such as those provided by FEMs, research-grade instrumentation, or the OPC-N3.

Kamaljeet Kaur and Kerry E. Kelly

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on amt-2022-292', JAMES OUIMETTE, 05 Dec 2022 reply
    • CC2: 'Reply on CC1', Kerry Kelly, 09 Dec 2022 reply
      • RC1: 'Reply on CC2', Shahrul Nadzir, 23 Dec 2022 reply

Kamaljeet Kaur and Kerry E. Kelly

Kamaljeet Kaur and Kerry E. Kelly

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Short summary
We evaluated the Alphasense OPC-N3 and PMS5003 compared to Federal Equivalent Method (FEM) PM10 measurements in the Salt Lake Valley during five dust events. Prior to correction, the OPC-N3 agreed well but the PMS PM10 measurements correlated poorly with the FEM. After correcting the PMS with a PM2.5/PM10 ratio-based factor, the PMS PM10 correlations improved significantly. This suggests the possibility of better resolved spatial estimates of PM10 using PMS measurements and PM2.5/PM10 ratios.