The rapid spread of COVID-19 resulted in various public lockdowns across the globe. Previous studies showed that resultant travel restrictions improved air quality. The novel results presented here focus on source-specific changes and compare air quality for multiple years controlled for precipitation. This study sought to analyze air pollution changes in Pittsburgh, a city where an industrial past and present has led to elevated levels of particulate matter with representative diameter of ≤ 2.5μm (PM2.5). Data from the Allegheny County Health Department, from monitors located near a variety of site types, were analyzed with generalized linear models that used a gamma distribution with a log link to determine the magnitude and significance of changes in air pollution during the COVID-19 lockdown. The hypothesis was that nitrogen dioxide (NO2), which is primarily linked to vehicular traffic, would decrease significantly while potential decreases in particulate matter (PM2.5 and PM10) would be less apparent. Results of the regression models showed that NO2 was significantly reduced during lockdown at both monitoring sites and that PM10 was also significantly reduced at the majority of monitoring sites. However, decreases in PM2.5 pollution were only observed at half of the monitoring locations, and the location which observed the greatest decreases is located adjacent to an industrial source. Decreases in PM2.5 at this monitoring site were likely a result of reduced industrial processes both dependent and independent of the COVID-19 lockdown. This study suggests that industrial sources are a larger contributor of particulate matter than vehicular transportation in the city of Pittsburgh and that future air pollution reduction efforts should focus attention on emission reduction at these industrial facilities.