Global Impact of COVID-19 Restrictions on the Surface Concentrations of Nitrogen Dioxide and Ozone

Abstract

Abstract. 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 (NO2) and ozone (O3) at 5756 observation sites in 46 countries from January through June 2020. Reductions in NO2 correlate with 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, NO2 concentrations were 18 % 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 % to the business as usual estimate. NO2 reductions in Europe and the US have been more gradual with a halting recovery starting in late March. We estimate that the global NOx (NO + NO2) emission reduction during the first 6 months of 2020 amounted to 2.9 TgN, equivalent to 5.1 % of the annual anthropogenic total. The response of surface O3 is complicated by competing influences of non-linear atmospheric chemistry. While surface O3 increased by up to 50 % in some locations, we find the overall net impact on daily average O3 between February–June 2020 to be small. However, our analysis indicates a flattening of the O3 diurnal cycle with an increase in night time ozone due to reduced titration and a decrease in daytime ozone, reflecting a reduction in photochemical production. The O3 response is dependent on season, time scale, and environment, with declines in surface O3 forecasted if NOx emission reductions continue.

What can we learn about urban air quality with regard to the first outbreak of the COVID-19 pandemic? A case study from central Europe

“…At the same time, some other important pollutants such as N 100-1000 or SO 2 -which are typically related to larger spatial extent or region and which could, therefore, be influenced by meteorology -did not change significantly. Similar reductions were reported for other urban locations in the world (Keller et al, 2020;Lal et al, 2020;Le et al, 2020;Lee et al, 2020;Tobías et al, 2020). This all can be interpreted that the alterations in NO, NO 2 , CO, N 6-1000 and N 6-100 concentrations were primarily caused by the lower vehicular traffic intensity in the city and that the PBLH could also contribute by approximately 9 % in an absolute sense ( Table 1).…”

“…As a consequence of the implemented measures, road traffic in many cities worldwide was reduced in a substantial manner and for a considerable time interval. In parallel, lower concentrations of several air pollutants were reported from both satellite observations and in situ measurements (Conticini et al, 2020;Frontera et al, 2020;Keller et al, 2020;Lal et al, 2020;Le et al, 2020;Lee et al, 2020;Liu et al, 2020;Mahato et al, 2020;Morawska and Cao, 2020;Nakada and Urban, 2020;Petetin et al, 2020;Tobías et al, 2020;Wang et al, 2020).…”

What can we learn about urban air quality with regard to the first outbreak of the COVID-19 pandemic? A case study from Central Europe

“…At the same time, some other important pollutants such as N100-1000 or SO2which are typically related to larger spatial extent or region and which could, therefore, be influenced strongly by meteorologydid not change significantly. Similar reductions were reported for other urban locations in the world (Keller et al, 2020;Le et al, 2020;Lee et al, 2020;Tobías et al, 2020). This all can be interpreted that the alterations in NO, NO2, CO, N6-1000 and N6-100 concentrations were primarily caused by the lower vehicular https://doi.org/10.5194/acp-2020-997 Preprint.…”

“…As a consequence of the implemented measures, road traffic in many cities worldwide was reduced in a substantial manner and for a considerable time interval. In parallel, lower concentrations of several air pollutants were reported from both satellite observations and in situ measurements (Keller et al, 2020;Le et al, 2020;Lee et al 2020;Mahato et al, 2020;Nakada and Urban, 2020;Petetin et al, 2020;Tobías et al, 2020;Wang et al, 2020).…”

Description of the NASA GEOS Composition Forecast Modeling System GEOS‐CF v1.0

“…Factors that likely contribute to the high NH surface O3 in GEOS-CF are uncertainties in the production of O3 from the oxidation of isoprene (Travis et al, 2016;Bates et al, 2019) and errors in O3 deposition to wet surfaces (Travis et al, 2019). In addition, most OpenAQ observation sites are located near densely populated areas, and the 25x25 km 2 model simulation cannot fully capture the fine-scale features characteristic for these environments (Keller et al, 2020).…”