A095-0015
Resolving changes in air pollution in the Northeastern US due to COVID-19 across spatial and temporal scales using multi-platform measurements

Thursday, 10 December 2020
Poster
Ellis Robinson1, Zichong Chen1, Christopher D. Heaney2, Kirsten Koehler2, Scot M Miller1 and Peter DeCarlo2, (1)Johns Hopkins University, Department of Environmental Health and Engineering, Baltimore, MD, United States, (2)Johns Hopkins University, Department of Environmental Health and Engineering, Balitmore, MD, United States
Abstract:
The outbreak of COVID-19 prompted swift, global action to curb the spread of the SARS-CoV-2 virus. These actions resulted in the curtailment of many activities responsible for primary emissions, such as driving, restaurant activity, and other modes of transportation. COVID-19 provides a natural experiment to quantify the impacts of these activities on ambient concentrations of various pollutants across locations with different degrees of curtailment. Here we aim to quantify the air quality impacts from COVID-19 shutdowns along the Boston-Washington urban corridor using multi-scale measurements that bridge spatial and temporal scales. Using data from a low-cost sensor network stratified across land-use type (SEARCH network, Baltimore), regulatory monitors (U.S. EPA), and satellite retrievals (TROPOMI, European Space Agency), we assess intracity, intercity, and urban-rural variations in air quality, respectively, across the highly urbanized Northeast corridor of the US. While assessing these spatial variations we account for year-to-year variability, diurnal patterns, and meteorological differences that potentially confound the effect of COVID-19 changes on ambient concentrations. Immediately after stay at home policies were put in place in MD, reductions in PM2.5 were observed across the SEARCH network compared to the pre-COVID period and were more pronounced on weekdays than weekends. EPA regulatory monitoring data show a sharp decrease in CO and subtle decrease in PM2.5 across Northeastern cities corresponding to decreases in vehicle traffic, while TROPOMI retrievals reveal that these changes were starker in urban areas than to rural ones. We plan to combine this multi-scale assessment of air quality changes with concurrent, spatially-resolved mobility and economic data to connect ambient decreases in pollution to changes in specific activities that drive emissions.
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