Social distancing to combat the COVID-19 pandemic has led to widespread reductions in air pollutant emissions. Quantifying these changes requires a business-as-usual counterfactual that accounts for the synoptic and seasonal variability of air pollutants. We use a machine learning algorithm driven by information from the NASA GEOS-CF model to assess changes in nitrogen dioxide (NO 2 ) and ozone (O 3 ) at 5756 observation sites in 46 countries from January through June 2020. Reductions in NO 2 coincide with the timing and intensity of COVID-19 restrictions, ranging from 60 % in severely affected cities (e.g., Wuhan, Milan) to little change (e.g., Rio de Janeiro, Taipei). On average, NO 2 concentrations were 18 (13–23) % lower than business as usual from February 2020 onward. China experienced the earliest and steepest decline, but concentrations since April have mostly recovered and remained within 5 % of the business-as-usual estimate. NO 2 reductions in Europe and the US have been more gradual, with a halting recovery starting in late March. We estimate that the global NO x (NO + NO 2 ) emission reduction during the first 6 months of 2020 amounted to 3.1 (2.6–3.6) TgN, equivalent to 5.5 (4.7–6.4) % of the annual anthropogenic total. The response of surface O 3 is complicated by competing influences of nonlinear atmospheric chemistry. While surface O 3 increased by up to 50 % in some locations, we find the overall net impact on daily average O 3 between February–June 2020 to be small. However, our analysis indicates a flattening of the O 3 diurnal cycle with an increase in nighttime ozone due to reduced titration and a decrease in daytime ozone, reflecting a reduction in photochemical production. The O 3 response is dependent on season, timescale, and environment, with declines in surface O 3 forecasted if NO x emission reductions continue.
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