Evaluation of a new low-cost particle sensor as an internet-of-things device for outdoor air quality monitoring

Figures & data

Table 1. Summary of selected low-cost PM sensor validation studies. Values are for ambient air measurements unless otherwise stated. The R² and mean absolute error (MAE) values for PM_2.5 and PM₁₀ are from the comparison of the low-cost sensor to a reference sensor. MAE values are included when reported.

Low-cost sensor	R^2 Value for PM2.5/MAE	R^2 Value for PM10 /MAE	Reference
AirBeam	R^2 = 0.66^a	-	Mukherjee et al. (2017)
Alphasense OPC-N2	R^2 = 0.41^a	R^2 = 0.82^a	Mukherjee et al. (2017)
	R^2 = 0.48^a/MAE = 5.23^a	-	Feenstra et al. (2019)
Honeywell HPMA115S0	R^2 = 0.64^f (1-h) (when RH<90%)	-	Báthory et al. (2019)Báthory et al. (2019)
	R^2 = 0.20^f (1-h) (when RH>90%)	-
Innociple PSM305	R^2 = 0.74^e	-	Jayaratne et al. (2020)
Nova SDS011	R^2 = 0.900 (24-h)/MAE = 4.827	R^2 = 0.840 (24-h)/MAE = 5.103	Cavaliere et al. (2018)Jayaratne et al. (2020)
	R^2 = 0.8095^c,d	R^2 = 0.7221^c,d
	-	-
Nova SDL607	R^2 = 0.82^e	-	Jayaratne et al. (2020)
Plantower PMS A003	R^2 = 0.91 (1-h)	-	Zamora et al. (2018)
Plantower PMS1003	R^2 = 0.75^a,c (1-h)	-	Liu et al. (2020)
	R^2 = 0.80^a,b,c (1-h)	-	Jayaratne et al. (2020)
	-	-
	R^2 = 0.88^a (24-h)	-	Kelly et al. (2017)
Plantower PMS 3003	R^2 = 0.93 (24-h)^a; R^2 = 0.84 (12-h)^a; R^2 = 0.80 (6-h)^a; R^2 = 0.41 (1-h)^a	-	Zheng et al. (2018)
SDS011	R^2 = 0.5^a	R^2 = 0.35^a	Lehmann et al. 2019)
Sensirion SPS30	R^2 = 0.75/MAE = 1.83 (24-h) (Trimmed)^a,c,e,f	-	This study
	R^2 = 0.57/MAE = 2.34 (1-h) (Trimmed)^a,c,e,f	-	This study
	R^2 = 0.34/MAE = 2.23 (1-h) (Strict)^a,c,e,f	-	This study
	R^2 = 0.53 ^a,f/MAE = 5.59 ^a	-	Motlaugh et al. (2021)
	R^2 = 0.64–0.84 ^a,d,f	-	Demanega et al. (2021)
	R^2 = 0.83^a,d,f	R^2 = 0.12 ^a,d,f	Kuula et al. 2020)
Sharp GP2Y1010AU0F	R^2 = 0.08^e	-	Jayaratne et al. (2020)
Shinyei PPD42NS	R^2 = 0.06^e	-	Jayaratne et al. (2020)
Shinyei PM Evaluation Kit	R^2 = 0.74^a/MAE = 4.4^a	-	Feenstra et al. (2019)
12 Sensors	R^2 = 0.48–0.95^a/MAE = 4.26–15.96^a	-	Feenstra et al. (2019)
Yi Shan A4 Plantower PMS7003Plantower PMS7003 (different exterior shell)	4.24^g 1.59^g 8.13^g	1.51^g 2.12^g 1.07^g	Cho et al. (2019)Cho et al. (2019)Cho et al. (2019)

^aAveraged values from multiple sensors of the same model.

^bCorrected for environmental factors (temperature, humidity).

^cOutlier values excluded.

^dLaboratory calibration.

^eAmbient conditions with PM_2.5 concentration was known to be less than 20 µg/m³.

^f,gR² value calculated from given R value.

Table 2. Table of the sensors and data available for comparison. All sensors are located at the Parklane site in Columbia, SC.

Sensor	Particle Size (PM)	Instrument Precision	Timeframe	Resolution
Low-Cost Sensor (LCS) A, B, and C	1, 2.5, 4, 10	±10 for 0–100 µg/m^3	7/29/2019 – 12/12/2019	5 Minute
Thermo Scientific 1405-F FDMS w/SCC – FDMSi (FEM)	2.5	±10% for 100–1000 µg/m^3	2019	1 Hour
R & P Model 2025 PM-2.5 Sequential Air Sampler w/VSCC – Gravimetric (FRM)	2.5, 10	±0.75% µg/m^3	2019	24 hr Every 3rd Day

Table 3. Mean (SD = standard deviation) of the relative error of strict hourly measurements from LCS compared to the FEM for each time period. The LCS values in this table have not yet been bias adjusted, as can be seen in the high relative error for LCS A from Aug. 22–Oct. 5 (−0.75) and LCS C from Sep. 13–Dec. 12 (−0.36).

	Sensor B	Sensor A		Sensor B	Sensor C
Time	Mean (SD)	Mean (SD)	Time	Mean (SD)	Mean (SD)
Jul. 29–Aug. 21	0.04 (0.45)	−0.03 (0.41)	Jul. 29–Sep. 13	0.03 (0.45)	−0.02 (0.41)
Aug. 22–Oct. 5	−0.06 (0.12)	−0.75 (0.05)	Sep. 13–Dec. 12	−0.13 (0.29)	−0.36 (0.21)
Oct. 9–Dec. 12	−0.14 (0.30)	−0.11 (0.31)

Figure 1. Panel a is the raw PM_2.5 and Panel b is the raw PM₁₀ concentration (µg/m3) data from the sensors at the Parklane site in Columbia, SC from August to December 2019. Sensors include FRM, FEM, LCS A, LCS B, and LCS C. 68 negative values from the FEM, on the PM_2.5 plot were not included.

Figure 2. A pairwise comparison plot of the strict hourly PM_2.5 concentration measurements from the LCSs. Panel a shows the comparison of LCS A and B with three distinct trendlines indicting different date ranges; the yellow asterisks represent Jul.29 to Aug. 21, the orange squares indicate Aug. 22 – Oct. 5, and the blue circles indicate the time period from Oct. 9 – Dec. 12. Panel b shows a pairwise comparison of LCS B and C; the blue circles indicate the time frame from Jul. 29 to Sep. 13 and the red crosses indicate Sep. 16 – Dec. 12.

Figure 3. Plot of the relative error of trimmed daily measurements of the low-cost sensors versus the FEM at the Parklane site in Columbia, SC. Includes 93 values for each sensor.

Table 4. Linear regression summary for trimmed daily bias adjusted sensor measurements versus FEM.

X-Axis	Sensor	R^2	Linear Regression
FEM daily PM2.5	LCS A daily PM2.5	0.73	y = 0.98x − 1.3
FEM daily PM2.5	LCS B daily PM2.5	0.75	y = 0.98x − 1.5
FEM daily PM2.5	LCS C daily PM2.5	0.77	y = 1.0x − 1.6

Figure 4. A four-panel plot of the FEM versus the daily measurements for the FRM and LCSs. Panel a is a plot of 45 measurements between the FEM vs the FRM. Panels b, c, and d are of the FEM versus LCS A, B, and C respectively, and plots 93 trimmed bias adjusted daily measurements. Horizontal error bars represent the accuracy of the FEM +/- 0.75% while the vertical error bars represent the standard deviation of the average hourly measurements for the LCSs. The linear fit line is solid black and the 1:1 line is dashed.

Figure 5. The ratio of hourly trimmed measurements of LCS B to the FEM plotted versus Relative Humidity (%) and Temperature (°C). This figure includes 2764 measurements, more than the 2300 measurements evaluated otherwise as these are only the measurements that are from LCS B compared to the FEM.

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Data availability statement

The data that support the findings of this study are available from the corresponding author, ARM, upon reasonable request.