10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
Abstract View
Determination of the Size-Resolved Sampling Efficiency for a Commodity (AirBeam) PM2.5 Ambient Aerosol Sensor at a Background U.S. Continental Site
CHARLES STANIER, Nathan Janechek, Nathan Bryngelson, Megan Christiansen, University of Iowa
Abstract Number: 1506 Working Group: Low-Cost and Portable Sensors
Abstract Commodity (also known as low-cost) aerosol sensors are widely accessible, provide real-time localized air pollution information, and can be used as educational tools for classroom and outreach applications. One such example of these sensors is the AirBeam from Habitatmap. The AirBeam is a portable, commodity ($250) sensor that can detect particles in the range ~0.5 – 2.5 µm and concentrations up to 400 µg m-3 at a resolution of 1 second.
While knowledge of site-specific calibration curves, interferences, accuracy, and precision information on commodity aerosol sensors is proliferating, detailed assessment of in-field size-selective sampling efficiency and dynamic response is rare.
Three AirBeam sensors were deployed co-located with SMPS and APS for 25 days during a summer 2017 measurement campaign in Zion, Illinois (north of Chicago along Lake Michigan). AirBeams were housed in tin enclosures with air vents to protect against the weather. Mass concentration, temperature, and humidity were recorded every second by the AirBeams and uploaded to the crowdsourced website. The three AirBeams had good reproducibility with concentrations similar to each other.
Reference instruments measured the aerosol size distribution every 2 minutes, and when used to estimate aerosol mass, PM2.5 concentrations ranged from 1 to 20 µg m-3. The AirBeams, when averaged to the same time basis, were highly correlated, and able to reproduce short-duration peaks in aerosol concentration. The correlation coefficient (r) at 2-min time resolution with the reference instruments was 0.95. However, the AirBeams reported lower concentrations (0.1 – 12 µg m-3) using the manufacturer calibration curve (counts to mass), and the average slope between the commodity and reference instruments for PM2.5 mass was 0.59. Correlation persisted even to very low concentrations in the 1-3 µg m-3, however, the slope varied significantly with concentration.
We will discuss the construction of a size-resolved effective sampling efficiency for the AirBeam, and explore the degree to which it may be generalized to other locations. Our technique will rely on comparison to a reference aerosol size distribution, measured from 1 nm to 2.5 microns every 2 minutes, together with twice-daily organic and inorganic PM2.5 chemical speciation and collocated gravimetic PM mass and meteorological variables. We will investigate if the sampling efficiency varies with relative humidity, temperature, solar radiation, Aeronet aerosol optical properties, black carbon fraction, or other aerosol chemistry factors, and thereby assess the transferability of our efficiency model to other sites.
A stand-alone CPC measuring with 1 second time resolution and known dynamic response for the inlet and instrument, will be used to assess the effective dynamic response for the AirBeams and calculate an effective time-constant for the AirBeam samplers in their housings. This will likely vary with wind speed and that relationship will be evaluated.
The AirBeam uses a Shinyei PPD60PV-T2 sensor which measures light scattering for a single bin which is converted to an estimated mass concentration using a calibration fit developed from outdoor urban aerosols. A corresponding Android device is used to visualize, record, and upload measured data to a crowdsourced website that maps the spatial and temporal resolved data. Previous evaluation of the AirBeam in a laboratory environment at high loadings indicated good reproducibility between sensors and poor correlation compared to traditional instruments.
The AirBeams observed good correlation for ambient outdoor PM2.5 concentrations although concentrations are lower than well-established methods. The AirBeam and AirCasting system provide an easy way to upload and retrieve the sensor data, but frequent Bluetooth connection drops between the Android device and AirBeam occurred.