ABSTRACT
The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.
Subject(s)
Air Pollution , Atmosphere/chemistry , COVID-19/psychology , Greenhouse Gases , Models, Theoretical , COVID-19/epidemiology , Carbon Dioxide , Climate Change , Humans , Methane , Nitrogen Oxides , OzoneABSTRACT
The COVID-19 pandemic and ensuing lockdown of many US States resulted in rapid changes to motor vehicle traffic and their associated emissions. This presents a challenge for air quality modelling and forecasting during this period, in that transportation emission inventories need to be updated in near real-time. Here, we update the previously developed fuel-based inventory of vehicle emissions (FIVE) to account for changes due to COVID-19 lockdowns. We first construct a 2020 business-as-usual (BAU) case inventory and adjust the emissions for a COVID-19 case using monthly fuel sales information. We evaluate cellular phone-based mobility data products (Google COVID-19 Community Mobility, Apple COVID-19 Mobility Trends) in comparison to embedded traffic monitoring sites in four US cities. We find that mobility datasets tend to overestimate traffic reductions in April 2020 (i.e. lockdown period), while fuel sales adjustments are more similar to changes observed by traffic monitors;for example, mobility-based methods for scaling emissions result in an approximately two-times greater estimate of on-road nitrogen oxide (NO x ) reductions in April 2020 than we find using a fuel-based method. Overall, FIVE estimates a 20%–25% reduction in mobile source NO x emissions in April 2020 versus BAU, and a smaller 6%–7% drop by July. Reductions in April showed considerable spatial heterogeneity, ranging from 6% to 39% at the state level. Similar decreases are found for carbon monoxide (CO) and volatile organic compounds. Decreases to mobile source NO x emissions are expected to lower total US anthropogenic emissions by 9%–12% and 3%–4% in April and July, respectively, with larger relative impacts in urban areas. Changes to diurnal and day-of-week patterns of light- and heavy-duty vehicular traffic are evaluated and found to be relatively minor. Beyond the applicability to modelling air quality in 2020, this work also represents a methodology for quickly updating US transportation inventories and for calibrating mobility-based estimates of emissions.