Performance evaluation of the Alphasense OPC-N3 and Plantower PMS5003 sensor in measuring dust events in the Salt Lake Valley, Utah
- Department of Chemical Engineering, University of Utah, SLC, 84102, USA
- 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.
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Kamaljeet Kaur and Kerry E. Kelly
Status: open (extended)
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CC1: 'Comment on amt-2022-292', JAMES OUIMETTE, 05 Dec 2022
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This evaluation of the OPC-N3 for PM10 during wind blown dust episodes is both timely and valuable. FYI, the Great Basin APCD headquartered in Bishop, California, is starting to evaluate the OPC-N3 sensor within the Alphasense monitor for wind blown dust PM10 at Keeler, next to the Owens dry lake, and at Mono Lake. I have contacts if you're interested.
A minor correction to your preprint - - on lines 61-63 it states that some low cost sensors are ineffective at measuring PM10 and dust, primarily due to the sensor’s inability to aspirate these larger particles into the device, and cites our paper by Ouimette (2022). In our paper we did not state that poor aspiration efficiency was the primary reason for the coarse particle inefficiency. Based on the Plantower PMS5003 particular geometry our physical-optical model predicted an 80-90% reduction in the 2-um particle scattering coefficient compared to a perfect nephelometer, due to truncation of the forward scattering signal. However, the lab data showed more like a 95% reduction in 2-um light scattering. Based on Willeke and others' work we hypothesized that poor aspiration efficiency could be a reason for this additional 5-15% loss. But we neither modeled nor measured it for that paper. It's extremely difficult to measure aspiration losses for the PMS5003 because any measurement slows or stops its flow rate due to Δp across the little fan.
I hope this helps. Best wishes on your paper review.
Regards,
Jim Ouimette
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CC2: 'Reply on CC1', Kerry Kelly, 09 Dec 2022
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Thank you very much for the kind words and this correction. We will ensure that this text modified in the final version. We also appreciate the connection to the group working on Owens Lake dust and will drop you a separate note about that.
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RC1: 'Reply on CC2', Shahrul Nadzir, 23 Dec 2022
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Dear Kelly et al
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Thank you for your answer to the comment by the public. I have read through the entire manuscript and it has been well-revised.Â
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RC1: 'Reply on CC2', Shahrul Nadzir, 23 Dec 2022
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CC2: 'Reply on CC1', Kerry Kelly, 09 Dec 2022
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Kamaljeet Kaur and Kerry E. Kelly
Kamaljeet Kaur and Kerry E. Kelly
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