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Reduced Traffic Volumes and Air Quality during the COVID-19 Shutdown
CHEOL H. JEONG, Nathan Hilker, Taylor Edwards, Jon M. Wang, Jerzy Debosz, Yushan Su, Anthony Munoz, Dennis Herod, Greg J. Evans, SOCAAR, University of Toronto
Abstract Number: 178
Working Group: Urban Aerosols
Abstract
The COVID-19 shutdown is providing an unprecedented natural experiment to explore the impact of markedly reduced sources of pollution on air quality. Analysis of traffic volumes during the shutdown allows a greater understanding of improved air quality due to reduced vehicular emissions. In addition to the change in total traffic volume, the fleet composition can also be analyzed to elucidate the influence of the fleet composition of gasoline and diesel vehicles on traffic-relate air pollutants (TRAPs). However, understanding the influences of local and regional sources is challenging due to the temporal and spatial variabilities of TRAP and potential confounding factors in determining the change of air quality. Thus, a comprehensive analysis is necessary to properly assess the impact of the shutdown on urban air quality.
In this study, continuous air pollution data from February to June in 2017-2020 at two near-road sites (NR) located near Highway 401 and downtown in Toronto, Ontario, Canada were used to compare the levels of TRAP pre-, during, and post-shutdown. Urban background (BG) concentrations were obtained from two other sites in Toronto. The TRAPs measured include: nitrogen oxides, carbon monoxide, black carbon, ultrafine particles, and PM2.5. Hourly concentrations of organic and inorganic aerosol and trace elements were also determined using an Aerosol Chemical Speciation Monitor (ACSM, Aerodyne) and Xact metals monitor (Cooper Environ), respectively, at the downtown site. The number, length, and speed of motor vehicles measured at the NR sites were measured to identify the changes to the proportion of gasoline passenger cars and diesel trucks within the fleet.
Urban background concentrations were estimated through baseline subtraction using a spline of minima approach. Regional contributions thereby estimated were compared to data from the BG sites which are representative of regional air quality superimposed with city-wide emissions. Receptor modeling was performed to assess the change of local and regional scale PM2.5 sources using continuous organics, inorganic ions, and trace elements at the downtown NR site. Moreover, the changes observed in 2020 were compared with data from February to June 2017-2019, to estimate an excess change in 2020 due to the shutdown. Finally, the changes in TRAP concentrations were compared to the changes in total traffic volume and fleet composition to resolve how changes to the mix of gasoline and diesel vehicles influence TRAP. This study can help support the development of more specific policies and regulations to reduce local air pollution effectively.