Added: 27th May 2020 by CGG
CGG’s Satellite Mapping team are collaborating with The University of Manchester to explore the potential insights that satellite imagery acquired by the Sentinel-5P satellite can provide with respect to changes in atmospheric trace gases during the unfolding global coronavirus pandemic.
Developed by the European Space Agency, the Sentinel-5P satellite mission focuses on atmospheric monitoring. The satellite hosts the TROPOMI instrument (TROPOspheric Monitoring Instrument), a spectrometer capable of mapping a variety of atmospheric trace gases.
Sentinel-5P is an excellent example of the ability of satellites to map baseline conditions and monitor variations on a global scale; and is ideally positioned to observe the potential impacts of the coronavirus pandemic with respect to reduced anthropogenic activity, a key contributor to atmospheric trace gases.
The team are downloading and processing Sentinel-5P Level 2 data products acquired across the entire globe every day and over the coming weeks intend to publish a series of posts exploring these results on their dedicated blog. Some initial global nitrogen dioxide (NO2) results lifted from that blog are discussed below.
The following graphics visualise Sentinel-5P data across the entire globe, using a seven-day rolling average. The NO2 data is shown using a colour map spanning 0 to 150+ µmol/m2 so does not reveal spatial variation in NO2 levels above 150 µmol/m2.
All images are copyright CGG, backdrop copyright Stamen Design, and contain modified Copernicus Sentinel data (2020).
The global images of the weekly average column of NO2 reveals some striking changes. In January, the world had not yet responded to the coronavirus. Very large column abundances of NO2 are seen across China. This is unsurprising since China hosts many of the world’s largest mega-cities and suffers very substantial NO2 emissions. In January, cold temperatures and low wind speeds lead to conditions that suppress mixing and high concentrations of pollutants result.
High NO2 amounts were also present during January in other megacities such as Tehran (Iran) and Cairo (Egypt), and emissions from biomass burning is widespread across West Africa. In the US, the areas close to New York and Boston and Los Angeles and San Francisco are also very marked. In Europe elevated levels are widespread but pollution thresholds were not exceeded. The exception to this is the Po Valley in northern Italy which is home to Italian industry and during winter traps air between the Alps and the Apennines so is often polluted at this time of year.
By February, Wuhan and other cities in China had shut down and emissions of NO2 had dramatically reduced. The column abundances of NO2 over northern Europe were also much less at the start of February than in January but this was before the shutdown. February in northern Europe was extraordinarily wet and windy and this led to large reductions in the NO2 column due to rapid dilution.
These conditions lasted until mid-March so despite emissions reducing in early April because of shutdowns being initiated across Europe, warmer, high pressure resulted in a modest increase in concentrations. However, by early April the high columns of NO2 seen earlier in the year over the Po Valley and Madrid are absent. Drastic reductions across US cities are also observed by the end of March as the shutdown rolled out.
Caution needs to be applied when looking at these data. For example, Tehran emissions in the image for April cannot be observed due to cloud cover obscuring the region. Conversely, Sentinel-5P cannot sample high latitudes during wintertime and as a result, emissions from Moscow cannot be observed until the end of March, though this is likely to be in time to see the changes induced by the recent shutdown. There is evidence of China’s recovery from the shutdown in April as the NO2 column density has increased significantly.
As the team continue to download, process and analyse the Sentinel-5P data (spanning NO2 and a variety of other atmospheric trace gases) they will begin to take a more local focus (continental, country, major cities), investigate correlations with changing economic activity (downturn and recovery), and explore integration with ground-based observations.