AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
Abstract View
Characteristics of Ambient Ultrafine Particles Using a Combination of Low-Cost Sensors: Size Distributions and Volatility
MOLLY J. HAUGEN, Robert T. Nishida, Tyler T. Johnson, Anna K. Schroeder, Josh Hassim, Marc E.J. Stettler, Simone Hochgreb, Adam M Boies, University of Cambridge
Abstract Number: 249 Working Group: Air Quality Sensors: Low-cost != Low Complexity
Abstract Particle emissions are associated with a variety of health risks. However, the health risks are not currently well correlated to a particular particle metric. Health impacts may be related to the inhaled particle number, surface area, and mass, which may all have distinct health implications. Therefore, using laboratory grade instrumentation to measure these properties simultaneously is beneficial for air quality monitoring and epidemiological studies, albeit prohibitively expensive. Alternatively, low-cost instruments can monitor a range of ambient particle characteristics, and a deliberate combination of instruments provides more value than the sum of each individual instrument. Measurements made in the present study allows the first three moments of a particle size distribution to be determined, using low-cost sensors in a real-world urban environment.
The solid-carbon and volatile components of the ambient aerosol were determined using a catalytic stripper and duplicate low-cost sensors. A Naneos Partector (measuring lung-deposited surface area) measured occasions of purely volatile, nucleation mode aerosols which were not measured by the Alphasense UPM-S1 or micro-aethalometers (measuring active surface area and particle mass concentrations of the carbon component, respectively). The measured volatility and size components allows preliminary determination of the chemical composition and diameter, which can be correlated with particle origin. Video footage enabled correlations between emission spikes and vehicles typically associated with these emissions.
Particle size distributions were estimated using a combination of low-cost instruments over multiple days, including rush hour, midday, and minimal traffic activity. During high traffic periods, an ELPI+ particle classifier determined that particles in the size range 10-50 nm dominated the distribution, whereas during night-time, particle count was significantly reduced and larger particles (>100 nm) showed an increased contribution. The low-cost sensor measurements were consistent with these distributions. The study presented here provides a low-cost particle emission monitoring method that concurrently monitors various particle characteristics.