Evaluation of Low-Cost Sensors for Ambient PM_2.5 Monitoring

Abstract

Low-cost sensors are an opportunity to improve the spatial and temporal resolution of particulate matter data. However, such sensors should be calibrated under conditions close to the final ones before any monitoring actions. The paper presents the results of a collocated comparison of four models of low-cost optical sensors with a TEOM 1400a analyser. SDS011 (Nova Fitness), ZH03A (Winsen), PMS7003 (Plantower), and OPC-N2 (Alphasense) sensors were used in this research. Three copies of each sensor model were placed in a common box to compare the sensor performance under the same measurement conditions. Monitoring of the PM2.5 fraction was conducted for almost half a year from 21 August 2017 to 19 February 2018 in Wrocław (Poland). Reproducibility between sensor units was assessed on the basis of coefficient of variation (CV). CV values were lower than 7% in the case of SDS011 and PMS7003 sensors and equal to 20% for OPC-N2 units. CV was higher than 50% for ZH03A, mainly due to malfunctions. During the measurements, the trends of outputs from sensors were generally similar to TEOM data, but significant overestimation of PM2.5 concentrations was observed for the sensor raw data. A high linear relationship between TEOM and sensors was noticed for 1 min, 15 min, and 1-hour averaged data for PMS7003 sensors (R2≈0.83–0.89), for SDS011 units (R2≈0.79–0.86), and for one unit of ZH03A (R2≈0.74–0.81). R2 values for daily averages were at the level 0.91–0.93 for PMS7003, 0.87–0.90 for SDS011, and 0.89 for ZH03A. OPC-N2 had only a moderate linear relationship with TEOM (R2≈0.53–0.69 for daily data and 0.43–0.61 for shorter time averages). Quite large dispersion of data and high relative errors of PM2.5 estimation were observed for concentration ranges below 20–30 μg/m3. The impact of high relative humidity level was observed for SDS011 and OPC-N2 devices—clear overestimation of outputs was observed above 80% RH.

Strategies of method selection for fine-scale PM<sub>2.5</sub> mapping in an intra-urban area using crowdsourced monitoring

“…the first evaluation period with a weather condition similar to that of the lightly polluted sampling period, RH: 77 %-94 %) (R 2 = 0.2186). This is consistent with the findings of Zheng et al (2018) and Badura et al (2018), who discovered that low-cost sensors tend to overestimate the PM 2.5 concentrations when RH is high (> ∼ 80 %). However, the agreement between laser monitor and the national instrument was rather good (R 2 = 0.89) and the improvement after RH correction was insignificant (0.01); the potential effect of RH on hourly PM 2.5 concentration during veryhigh-RH events could be consistent because of the low intersensor variability (i.e.…”

“…Fine particulate matter (PM 2.5 ) has been associated with an increased risk of morbidity and mortality in both the long term and the short term (Beverland et al, 2012;Di et al, 2017;Lelieveld et al, 2015). The persistent cumulative effects from exposure in daily activities, especially daily travelling, are critical (Kingham et al, 2013;Hankey et al, 2017).…”

Selected Aging Effects in Triaxial MEMS Accelerometers

“…Accelerated testing may be realized as well by harsh electrical loading [20] or by subjecting the tested device to mechanical overloads. In the case of, e.g., PM sensors, accumulation of particles inside the measuring chamber may affect sensor aging, as well as meteorological conditions such as high humidity or extreme temperatures can affect the functioning of electronics of the device [21].…”

Calibration of Portable Particulate Matter–Monitoring Device using Web Query and Machine Learning

“…9(B) and (C), while more pronounced scatter is observed at an elevated temperature and humidity. In general, humidity of the air can affect the performance of optical PM sensors in several ways: failure of the electronic circuits/sensors, overestimated outputs in sensor signals due to hygroscopic growth of some particles, detection of water droplets in fog or mist as particles [24], [25], [26], [27], and deterioration of sensor performance due to absorption of infrared radiation by water [28]. Histogram of PMD PM 2.5 in Fig.…”