NASA reveals how much air pollution dropped during coronavirus lockdowns | Science | News


The coronavirus pandemic led to lockdowns across the globe, with experts immediately noticing a drop in carbon emissions worldwide. Fewer planes were in the sky and fewer cars were on the roads, leading to a welcome break in carbon emissions across the planet. Air pollution has been touted by the Air Quality Life Index (AQLI) to contribute to billions of health problems across the planet, and lead to a shorter life-span for humans.

Particle pollution can trigger asthma attacks, heart attacks and strokes and cause lung cancer.

However, according to computer simulations from NASA, there was a 20 percent drop in the global reduction of nitrogen dioxide emissions – a major pollutant – as a result of lockdowns.

The team created the picture by running a simulation which detailed how 2020 would look without the pandemic.

With many countries vowing to lower their nitrogen dioxide emissions, NASA wanted to see how much of the decline could be attributed to lockdowns.

What the results reveal is that humans are still massively contributing to nitrogen dioxide in the atmosphere.

Project leader and NASA researcher Christoph Keller said: “We all knew the lockdowns were going to have an impact on air quality.

“In some ways I was surprised by how much it dropped.

“Many countries have already done a very good job in lowering their nitrogen dioxide concentrations over the last decades due to clean air regulations, but what our results clearly show is that there is still a significant human behaviour-driven contribution.”

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“People were probably reducing their transit because the talk of the COVID-19 threat was already happening before we were actually told to shut down.”

Once the lockdowns eased, the decreases in nitrogen dioxide lessened, but were still below the “business as usual” model.

Mr Keller said: “We would expect them to be somewhat related because nitrogen dioxide is so closely linked to economic activities, like people who travel and factories running.

“It looks like our data captures this very well.”





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