Causes of variability in fine particulate matter concentrations (PM2.5) on the American University campus in Washington, D.C.
Particulate matter is a highly important indicator of air quality, and yet its behavior in urban environments is still not well understood. Further complicating attempts to understand causes of variability is the relative scarcity of regulatory-grade air monitors, which makes it difficult to account for local and community-scale variations. This study explores the use of low-cost air quality monitors as a more accessible alternative for air quality measurements, using American University as a test case. Using generalized additive mixed models (GAMMs), the influence of different meteorological and environmental variables on fine particulate matter are explored. The model selected wind speed, relative humidity, temperature, vegetation density, precipitation, atmospheric pressure, and traffic congestion as significant explanatory variables, with an adjusted R-squared of 0.368. Future work is needed to evaluate the generalizability of these results to other locations.