Field performance of a low-cost sensor in the monitoring of particulate matter in Santiago, Chile

Abstract

Integration of low-cost air quality sensors with the internet of things (IoT) has become a feasible approach towards the development of smart cities. Several studies have assessed the performance of low-cost air quality sensors by comparing their measurements with reference instruments. We examined the performance of a low-cost IoT particulate matter (PM 10 and PM 2.5 ) sensor in the urban environment of Santiago, Chile. The prototype was assembled from a PM 10 -PM 2.5 sensor (SDS011), a temperature and relative humidity sensor (BME280) and an IoT board (ESP8266/ Node MCU). Field tests were conducted at three regulatory monitoring stations during the 2018 austral winter and spring seasons. The sensors at each site were operated in parallel with continuous reference air quality monitors (BAM 1020 and TEOM 1400) and a filterbased sampler (Partisol 2000i). Variability between sensor units (n = 7) and the correlation between the sensor and reference instruments were examined. Moderate inter-unit variability was observed between sensors for PM 2.5 (normalized root-mean-square error 9-24%) and PM 10 (10-37%). The correlations between the 1-h average concentrations reported by the sensors and continuous monitors were higher for PM 2.5 (R 2 0.47-0.86) than PM 10 (0.24-0.56). The correlations (R 2 ) between the 24-h PM 2.5 averages from the sensors and reference instruments were 0.63-0.87 for continuous monitoring and 0.69-0.93 for filter-based samplers. Correlation analysis revealed that sensors tended to overestimate PM concentrations in high relative humidity (RH > 75%) and underestimate when RH was below 50%. Overall, the prototype evaluated exhibited adequate performance and may be potentially suitable for monitoring daily PM 2.5 averages after correcting for RH.

Analyzing and Improving the Performance of a Particulate Matter Low Cost Air Quality Monitoring Device

“…Karagulian et al [29] reviewed 110 on-site calibrated and uncalibrated LCAQMDs and concluded that most of them, including the AQY device, underestimate the PM10 hourly concentrations, which is in accordance with our results. Another study [30] evaluated a stand-alone SDS011 sensor (during winter and spring), which is used by the AQY device enhanced with RH corrections, in Santiago, Chile, with similar meteorological conditions as Thessaloniki, and found R 2 in the range (0.24-0.56) for PM10 concentrations against a similar β-attenuation reference instrument. They concluded that the sensor is suitable for monitoring PM2.5 daily levels after RH corrections, but not for PM10 levels.…”

Investigating a Low-Cost Dryer Designed for Low-Cost PM Sensors Measuring Ambient Air Quality

“…The number of particles is then converted to the PM mass concentration. The error occurs because the low-cost PM sensor counts not only the dry particles but also the wet water droplets that can happen at high levels of relative humidity and occur through condensation of the water vapor [ 19 , 20 , 21 ].…”

Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

“…These analyzers have gone through strict field evaluations and demonstrated that they could provide concentration measures equivalent to the filter-based GMM, with the advantage of being usable for continuous PM monitoring (generally with a temporal resolution of 1 h) [5]. Finally, the optical sensors measure particles' size by light scattering, so the concentration of PM can be detected according to the signal [3,6,7]. The optical sensor's accuracy is affected by different factors, such as aerosol characteristics, temperature, humidity, and even seasonal types [3].…”