EC-06. A comparison of ambient measurements of NOx, CO, O3, and PM2.5 during the COVID-19 pandemic with a climatological multiple linear regression model for various U.S. cities

Abstract
Pollutants harmful to human health are measured by air quality monitoring networks throughout the U.S. These data inform the public of the extent and magnitude of pollution and are used to evaluate the effectiveness of emission controls and to constrain air quality models. During the COVID-19 pandemic, most U.S. states and cities implemented procedures to reduce the spread of the disease, which resulted in a reduction in traffic and on-road emissions beginning in Spring 2020. Here, we use measurements of NOx, CO, O3, and PM2.5 and a multiple linear regression model to estimate expected pollution levels, controlled for meteorology, in several U.S. cities during the COVID-19 pandemic. We then compare the model output to observations to determine how emissions and atmospheric chemistry may have changed during the pandemic.