Over the last few decades of an increasingly well-connected world, the use of data to assist us in managing the many complex issues that we as a global society are facing has become more and more important.
We have seen this in the IPCC report on climate change, which uses massive amounts of data that has been crunched and analysed to provide facts and figures on what is happening with our planet Earth, under stress because of an increase in temperature which is upsetting ecosystems around the globe.
Satellites are playing an increasingly, more important role in big data projects as the accuracy, quality of imagery and level of detail has improved enormously over the last few decades. It is no wonder that satellites are also used in the battle against COVID-19.
A global team of air quality scientists which includes the Queensland University of Technology (QUT) discovered that real-time satellite data of the air pollutant nitrogen dioxide is a good predictor of when to ease COVID-19 lockdowns.
Nitrogen dioxide is emitted from burning fossil fuels for transport and energy, biomass burning, agricultural practices and aircraft.
Understanding the maths behind how a pandemic works makes it clear how to control and eventually eliminate the COVID-19 virus.
This is what QUT Professor Lidia Morawska, director of the QUT International Laboratory for Air Quality and Health (ILAQH) and a researcher in the Centre for the Environment, has to say about the research of her team:
Observation of atmospheric concentrations of these air pollutants can be used to track changes in industrial, mobile, residential, commercial and agricultural activity — low concentrations indicate reduced economic and social activity. We found that reduced economic and social activity, inferred from the reduction of nitrogen dioxide, is a driver of COVID-19 case deceleration in most of the 211 territories we studied. The effect, however, is not linear but dampens over time and further reductions are only associated with weaker deceleration of cases.
These findings have important applications:
- it could be applied to identify territories where movement restrictions can effectively decelerate the increase in COVID-19 cases. This would enable us to achieve global joint targeted policy action to where it is most needed to strengthen recovery;
- it can evaluate the effects of large-scale activity reduction and microlevel measures such as masking, social distancing and testing, tracing and isolating. It is particularly important in areas where limiting activity is less effective for containing COVID-19 under current circumstances; and
- as real-time NO2 can be achieved at a high resolution from space to match the resolution (50 to 100km) of transport models, it could be combined with atmospheric inversion models to attribute the observed changes in NO2 to specific economic sectors.
The team found almost 1 million daily COVID-19 cases could have been avoided in the last northern winter by optimising the timing and strength of restrictions with satellite observations of the concentration of (NO2) in the air.