Impacts of COVID-19 lockdown, Spring Festival and meteorology on the NO₂ variations in early 2020 over China based on in-situ observations, satellite retrievals and model simulations

Highlights

• NO₂ in China decreased by 42% and 26% in February and March 2020 due to COVID-19.

• The NO₂ VCDs by satellites were consistent with the surface NO₂ concentrations.

• Spring Festival holiday led to a NO₂ decrease in 30 days with a maximum of 37%.

• COVID-19 led to a NO₂ decrease from 6 days after SF with a maximum of 51%.

• NO₂ concentrations and VCDs decreased by 25% and 40% in 90 days due to meteorology.

Abstract

The lockdown measures due to COVID-19 affected the industry, transportation and other human activities within China in early 2020, and subsequently the emissions of air pollutants. The decrease of atmospheric NO₂ due to the COVID-19 lockdown and other factors were quantitively analyzed based on the surface concentrations by in-situ observations, the tropospheric vertical column densities (VCDs) by different satellite retrievals including OMI and TROPOMI, and the model simulations by GEOS-Chem. The results indicated that due to the COVID-19 lockdown, the surface NO₂ concentrations decreased by 42% ± 8% and 26% ± 9% over China in February and March 2020, respectively. The tropospheric NO₂ VCDs based on both OMI and high quality (quality assurance value (QA) ≥ 0.75) TROPOMI showed similar results as the surface NO₂ concentrations. The daily variations of atmospheric NO₂ during the first quarter (Q1) of 2020 were not only affected by the COVID-19 lockdown, but also by the Spring Festival (SF) holiday (January 24–30, 2020) as well as the meteorology changes due to seasonal transition. The SF holiday effect resulted in a NO₂ reduction from 8 days before SF to 21 days after it (i.e. January 17 - February 15), with a maximum of 37%. From the 6 days after SF (January 31) to the end of March, the COVID-19 lockdown played an important role in the NO₂ reduction, with a maximum of 51%. The meteorology changes due to seasonal transition resulted in a nearly linear decreasing trend of 25% and 40% reduction over the 90 days for the NO₂ concentrations and VCDs, respectively. Comparisons between different datasets indicated that medium quality (QA ≥ 0.5) TROPOMI retrievals might suffer large biases in some periods, and thus attention must be paid when they are used for analyses, data assimilations and emission inversions.