Ambient and laboratory evaluation of a low-cost particulate matter sensor☆
Graphical abstract
Introduction
Particulate matter (PM) concentration is a key metric for air quality because of its adverse effects on human health, visibility, and climate. From the health standpoint, elevated PM levels are associated with numerous adverse effects including cardiac arrhythmia, lung cancer, heart disease, and mortality (Brook et al., 2010, Lepeule et al., 2012, Peters et al., 2000, Pope et al., 2011). Air pollution accounted for 7 million deaths worldwide in 2012 with fine particulate matter (PM2.5) being the greatest contributor (World Health Organization, 2014). Because of these health and environmental impacts, the US EPA (United States Environmental Protection Agency) regulates ambient concentrations of PM with an aerodynamic diameter of 2.5 μm and smaller (PM2.5) and of PM with an aerodynamic diameter of 10 μm and smaller (PM10). Compliance with these standards is based on a federal reference method (FRM), which involves collecting PM in the appropriate size range on a filter, to determine the 24-h PM concentration and annual average of these PM concentrations. In addition, the EPA has approved federal-equivalent methods (FEMs) for measuring PM concentrations, and this type of monitoring equipment can provide PM concentrations at hourly intervals. Rather than using direct gravimetric measures like FRMs, PM FEMs use alternative methods, such as optical, beta ray attenuation, or tapered element oscillation, to determine PM concentration. Government agencies collect PM concentrations from sparsely distributed monitoring stations equipped with high-quality, expensive FRM/FEMs for their planning, public outreach and forecasting. However, these sparsely distributed stations may not accurately represent the pollutant gradients within a city (Bell et al., 2011, Steinle et al., 2013), particularly for traffic-related air pollutants such as PM2.5 (Health Effects Institute, 2010). Consequently, this poor spatiotemporal resolution of PM levels inhibits estimates of personal PM exposure and epidemiologic studies of PM's health effects, validation of emission inventories and air-quality models, and an understanding of the efficacy of emission-reduction policies (EPA, 2009).
Low-cost sensors offer the potential for gathering large quantities of high-resolution, air-quality data, but the performance of these sensors has not been thoroughly evaluated (Lewis, 2016). A few low-cost PM sensors have been evaluated in some field (Gao et al., 2015, Holstius et al., 2014, SCAQMD, 2016, Wang et al., 2015) and laboratory settings (Austin et al., 2015, Wang et al., 2015). These studies revealed that these PM sensors show promise. Wang et al. (2015) performed controlled laboratory studies of three low-cost sensors (Shinyei PPD42NS, Samyoung DSM501A, and Sharp GP2Y1010AU0F) and found that the PM measurements from these sensors generally correlated linearly (R2 = 0.89) compared to research-grade instruments (TSI SidePak AM510 and a TSI a scanning mobility particle sizer over a particle concentration range of 0–1000 μg/m3. Austin et al. (2015) also performed laboratory tests and found a linear correlation (R2 = 0.66–0.99) for the Shinyei compared to a TSI Corp. aerosol particle sizer (APS) over the concentration range of 1–50 μg/m3 although the slope of the linear relationship varied by more than a factor of 10 depending on the particle diameter. In the field, Gao et al. (2015) compared the response of the Shinyei sensor in a polluted region of China (24-h PM2.5 330–413 μg/m3) and found correlations to co-located research-grade instruments (R2 = 0.86–0.89) and gravimetric measures (R2 = 0.53) in a 4-day study. Holstius et al. (2014) compared the performance of the Shinyei sensor to 24-h FEM (R2 = 0.72, 3.5-month period) and research-grade measurements (R2 = 0.9–0.94, 7-day period) in Oakland, CA with PM2.5 concentrations ranging from 2 to 21 μg/m3. The South Coast Air Quality Management District (SCAQMD) recently released a draft report comparing the PurpleAir (Plantower PMS 1003) sensors to two FEMs (beta attenuation monitor, BAM and GRIMM FEM) over a two-month period in Riverside, CA (24-h PM2.5 2–40 μg/m3) and found good correlations (R2 > 0.9, 24-h average FEM measurements) (SCAQMD, 2016).
As noted in several of the studies, these low-cost sensors have drawbacks. They are not as accurate or precise as FEMs (Isaac, 2014). Some have limited sensitivity and can be affected by humidity and other factors, and sets of the same sensors can perform inconsistently (Gao et al., 2015, Wang et al., 2015). Low-cost, gas-phase sensors can experience significant sensor drift (Piedrahita et al., 2014). Many of these sensors lack independently gathered calibration data under conditions for which they are deployed, quality assurance procedures, or descriptions of when the sensors may provide inaccurate readings. In spite of these potential challenges, organizations have been collecting and posting PM concentrations online and even posting air-quality indices based on these data. (Bischoff, n.d.; PurpleAir, 2016). Presenting information from these PM sensors can cause either unnecessary public concern or complacency about pollution levels and the associated health risks (Isaac, 2014).
Consequently, there is a need for improved low-cost PM sensors and to validate sensors under real-world as well as laboratory conditions. This paper focuses on evaluating a relatively new PM sensor, the Plantower PMS 1003/3003, in an ambient environment during periodic episodes of high PM levels and in a laboratory wind tunnel. Elevated PM levels are a particularly important issue in northern Utah, which is classified as nonattainment for the 24-hr PM2.5 national ambient air quality standard (NAAQS). During winter, atmospheric stability and the mountainous topography result in cold-air pools (CAPs), which trap pollutants, and during these CAPs maximum daily average PM2.5 concentrations can reach double the national ambient air quality standard of 35 μg/m3. Although PM concentrations in northern Utah have declined over the past 40 years due to the implementation of air-quality regulations, Salt Lake County in northern Utah typically exceeds for 24-hr PM2.5 levels on 18 days per year, and these exceedances almost exclusively occur during winter-time CAPs (Whiteman et al., 2014). During these CAPs in northern Utah, PM2.5 levels tend to increase at a rate of approximately 10 μg/m3 per day until reaching a plateau (typically 60–100 μg/m3, depending on the location). CAPs are associated with temperatures below 0 °C, relative humidity (RH) in excess of 50% and light wind speeds (Whiteman et al., 2014). These episodes of poor air quality create significant health and quality-of-life concerns for the region's citizens, including increased incidence of asthma, juvenile arthritis, pre-term birth and mortality (Beard et al., 2012, Pope et al., 2002, Zeft et al., 2009). As a result of similar topographies and weather patterns, California's San Joaquin Valley, Beijing, Mexico City, and Tehran also experience similar events with accompanied high levels of fine PM (Afsarmanesh, 2013, Molina et al., 2007, Watson and Chow, 2002, Zhang and Cao, 2015).
As a result of public concerns, a local community organization, PurpleAir (PurpleAir, 2016), developed a network of 120 low-cost air-quality measurement devices based on the PMS sensor and is posting values online. However, the performance of these sensors has not been thoroughly evaluated, particularly under the atmospheric conditions for which they are being deployed. Furthermore, the public does not understand the differences between values posted by the low-cost sensors compared to FEMs/FRMs. This study partnered with the local community organization to evaluate PMS sensor performance in a laboratory setting and under realistic ambient conditions during several CAPs, when public interest in PM levels is high, and during several clean-air periods. The ultimate goal is to lead to a better understanding of PMS sensor performance and to develop recommendations for when and how the sensor results may be comparable to FEM/FRMs.
Section snippets
Material and methods
This study evaluated the Plantower PMS 1003/3003 laser particle counter in a wind tunnel and outdoors during several winter CAP events. The PMS 1003/3003 is a relatively inexpensive ($35), commercially available particle sensor (Fig. 1). It employs a fan to draw air through a chamber where it is exposed to a laser-induced light, and 90° scattered light is detected by a photo-diode detector. The laser wavelength was not available from the manufacturer, but it was estimated at 650 ± 10 nm with a
Limit of detection
The PMS 1003 LOD ranges from less than 1–3.22 μg/m3 under laboratory conditions to 10.5 μg/m3 under ambient conditions (details in Tables S-1). This is in the range of published laboratory estimates of LOD for PM low-cost sensors – less than 1–26.9 μg/m3 in laboratory settings (Austin et al., 2015, Wang et al., 2015). During the ambient study period, only 28 hourly FEM readings were less than 1 μg/m3, and additional data may help refine the estimated ambient LOD.
Ambient results
Tables S-2 shows the
Conclusions
This study demonstrated that the PMS 1003/3003 correlates well with FRMs, FEMs, and research-grade instrumentation under ambient conditions during a series of CAPs and in a wind-tunnel environment. Under ambient conditions, this sensor correlates better with a FRM than other low-cost sensors in similar studies. However additional measurements are needed under a variety of ambient conditions to adequately compare the performance of low-cost PM sensors. Although the PMS correlates well to FRMs,
Acknowledgments
Research reported in this publication was supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under Award Number U54EB021973. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Funding for the AirU sensors was provided by the Lawrence T. and Janet T. Dee Foundation and the Michael Foundation. Funding for undergraduate students was
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This paper has been recommended for acceptance by Charles Wong.