Half of humanity is being affected by the lockdown measures implemented as a result of the Coronavirus pandemic. The strong global decrease of nitrogen dioxide (NO2) concentrations, when compared to the levels detected over the previous year by the European Sentinel-5P satellite is therefore not surprising. Nitrogen oxides are an indicator of air pollution from industrial and transport activities.
However, the comparison is deceptive. This year, polar winds over large parts of Europe and a persistent westerly wind, which prevented the accumulation of pollutants, already provided unusually clean air. Assessing the impact of the Coronavirus on this is therefore complex. Researchers from the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt; DLR) Earth Observation Center (EOC) have obtained scientifically sound evidence of the 'Corona' effect.
Long-term analyses and the influence of the weather
The European satellite MetOp-A has been providing daily measurements of the global distribution of pollutants for many years. Long-term analyses show that there have always been strong, weather-related fluctuations in the density of the air pollutant nitrogen dioxide. The satellite examines the entire atmosphere. At higher altitudes, winds can transport air pollutants, dilute them or distribute them to distant regions. Therefore, these measurements alone are not sufficient. Near ground level, winds and precipitation displace or wash out pollutants. Measurement data from ground stations alone are therefore also not sufficiently conclusive.
The Lombardy region in Italy was impacted by the Coronavirus outbreak at an early stage. Starting on 8 March 2020, the Italian government began adopting quarantine measures, which evolved rapidly. Accordingly, satellite and ground measurements since the lockdown show a deviation from the long-term average. This is a preliminary indication.
But how do DLR scientists take the influence of the weather into account? For this purpose, the pollution levels are simulated using computers.
The scientists start their analyses using emission values of pollutants that are averaged over several years and represent the normal situation. This ensures that the model does not include the Coronavirus-conditioned measures. However, it takes into account the real weather conditions from hour to hour. This is followed by a comparison with this year's measured data. The modelled, normal situation is subtracted from the actual ground measurement values. Then, the lockdown in Lombardy reveals a real reduction of nitrogen dioxide concentration by approximately 20 micrograms per cubic metre. This is a 45 percent decrease.
Only satellites enable the continuous global measurement of pollutants. This investigation shows how well these measurements fit with ground data and models. However, only a combined analysis of satellite measurements, in-situ data and computer modelling can provide scientific proof of the ‘Corona effect’. The atmospheric events are too complex for generalised assessments. This becomes clear in other regions of the world. There, the current measured values are, in part, within the fluctuation range of recent years. Whether this is due to special local weather conditions or to a later start of lockdown measures remains unclear without detailed investigations.
The analysis for Lombardy was carried out using data from the European satellite MetOp-A. Since 2018, the European satellite Sentinel-5P has been providing measurements at a much higher resolution. In the future, these will help to better trace emission sources and pollutant transport mechanisms. Long time series are still not available, so that only comparisons between 2019 and 2020 are possible. In order to at least reduce the impact of the weather, DLR has established global monthly averages. For this purpose, 1.2 trillion individual measurements were processed over two months using DLR algorithms and tested for quality. These data also show – although not weather-independent – a clear reduction in emissions. The data generated at DLR are used, among other things, in the S-VELD project, which is funded by the German Federal Ministry of Transport and Digital Infrastructure, to analyse the impact of traffic emissions on air quality in Germany.