(57c) Understanding the Performance of Low-Cost Sensors in Characterizing Particulate Matter (PM) in Outdoor and Indoor Environments

With the progressive decrease in the cost of air quality sensors over the past few years, the potential applications of low-cost sensors for wide-spread air quality monitoring have grown. The rise of COVID-19 has particularly emphasised the application of using low-cost sensors to continuously monitor indoor air. However, the increase in low-cost sensor availability has also highlighted the importance of characterizing and quantifying low-cost sensor measurement capabilities. Towards this end, in this study we compared the particulate matter (PM) data reported by two low-cost sensors (Plantower PMS and QuantAQ MODULAIR-PM) in both outdoor and indoor environments on the Georgia Tech Campus. The Plantower sensor consists of a nephelometer and reports PM₁, PM_2.5, and PM₁₀, while the QuantAQ sensor reports size-resolved particle number concentration data from an AlphaSense optical particle counter (OPC) as well as mass concentration data (PM₁, PM_2.5, and PM₁₀) that is determined from a mathematical combination of nephelometer and OPC data. To investigate the effects of aerosol composition and size on the performance of the sensors, sensor data collected outdoors (urban Atlanta) in Winter 2021 were compared to measurements made by two research-grade instruments: Aerosol Chemical Speciation Monitor (ACSM) and Scanning Mobility Particle Sizer (SMPS). To assess sensor performance in indoor environments with PM emitted from various human activities, low-cost sensor data from the same time period were analyzed for three different indoor environments including a classroom, an academic common space, and a cafeteria. To further constrain sensor performance indoors, collocated sensor and SMPS measurements were performed in the classroom in Spring 2022. Results indicated that the data from both sensors generally agreed with research-grade instruments for PM₁ for both indoor and outdoor measurements. However, changes in aerosol mass loading and aerosol size distribution were observed to impact sensor performance and agreement. Specifically, during time periods with higher proportions of particles with diameters greater than 1 mm, the Plantower sensor predicted lower aerosol mass concentrations than the QuantAQ sensor. Results from this study provide data-driven insights into what types of indoor environments each sensor type is best suited for, and under what aerosol conditions they face the most limitations.