AAAR 36th Annual Conference October 16 - October 20, 2017 Raleigh Convention Center Raleigh, North Carolina, USA
Abstract View
Spatial and Temporal Variation of PM2.5 and Gaseous Pollutants in Environmental Justice Communities
REBECCA TANZER, Sriniwasa Kumar, Naomi Zimmerman, Albert A. Presto, R. Subramanian, Carnegie Mellon University
Abstract Number: 557 Working Group: Urban Aerosols
Abstract The state-of-the-art in air quality monitoring consists of precise, but expensive and poorly dispersed monitors. Air quality measurements are extrapolated over large domains and therefore may not paint an accurate picture of the spatial and temporal variation of pollutants. There exists a need for reliable low-cost air quality monitors to more accurately assess individuals’ exposure to air pollution. We have developed a low-cost air quality monitor called the Real-time Affordable Multi-Pollutant (RAMP) sensor package. The RAMPs were coupled with off-the-shelf PM2.5 sensors from Met One. The RAMP measures PM2.5 and various gaseous pollutants including SO2, CO, CO2, NO2, and O3. A network of five RAMPs has been deployed within the Monongahela Valley, an environmental justice region, with plans to deploy fifteen more. A coke plant in Clairton and a steel mill in Braddock both contribute to the historic noncompliance of the Monongahela Valley to National Ambient Air Quality Standards. Initial analysis of variations of SO2 and PM2.5 at different RAMP locations indicate that the region is spatially heterogeneous with respect to pollutant dispersion. Preliminary data show a peak exceeding 80 µg/m3 of PM2.5 for over an hour at a RAMP three miles east of the Clairton coke plant. A sensor four miles west of the first RAMP however, did not detect the same PM2.5 spike. The data indicates that pollutant concentrations are highly variable. Further analysis will be conducted on the RAMPs within the Monongahela Valley and the low-cost sensor network will be compared to two state-of-the-art air quality monitors that are situated within the domain. The reliability of the low-cost sensors will be quantified and a high resolution spatial and temporal understanding of the dispersion of air pollutants within the region will be obtained.