AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
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Inferring Aerosol Types and Sources from Low-Cost Air Quality Sensor Measurements: A Case Study in Cambridge, Massachusetts
AMANDA GAO, David Hagan, Jesse Kroll, MIT
Abstract Number: 374 Working Group: Air Quality Sensors: Low-cost != Low Complexity
Abstract Most studies of low cost sensors (LCS) in urban air quality research have focused on gaining accurate concentration measurements from LCS when compared to reference instruments, enabling accurate estimates of pollution levels and human exposures. While these efforts are extremely useful, it is also desirable to use LCS in other applications that can give valuable insight into air quality--without necessitating the sometimes extensive calibrations required for accurate pollutant concentration measurements. Here, we investigate how LCS can be used to better constrain classes and sources of particulate matter and urban pollutants for air quality and regulatory applications. We present a case study where a multipollutant LCS system, outfitted with low-cost CO, NO2, O3, and SO2 electrochemical sensors and an optical particle counter, was used to collect air quality data at a site in Cambridge, Massachusetts (a relatively unpolluted urban environment) over the course of several weeks. Results from factor analyses (including non-negative matrix factorization) of LCS measurements were then compared to data collected from co-located research-grade particle- and gas-phase instruments. This work provides insight into how multipollutant LCS measurements, despite their inherent limitations, can provide useful information on the sources of particulate matter in an urban environment.