NASA satellite measures the impact of regulation on air quality

NASA’ s study of worldwide air pollution trends over the last decade has highlighted humanity’s impact on  global air quality.

Using high-resolution satellite maps gathered from the Aura satellite, the NASA team analysed nitrogen dioxide levels around the globe between 2005 and 2014. They found that where governments had stepped in with deliberate policies to curb emissions their influence on nitrogen dioxide levels in the atmosphere could clearly be seen.

“These changes in air quality patterns aren’t random,” said lead researcher, Bryan Duncan. “When governments step in and say we’re going to build something here or we’re going to regulate this pollutant, you see the impact in the data.”

Image courtesy of NASA

Image courtesy of NASA

NASA identified the United States and Europe as the largest emitters of nitrogen dioxide, but both regions also showed the most dramatic reductions between 2005 and 2014, with both territories reducing emissions by as much as 50%.

On the other hand, China, the world’s growing manufacturing hub, saw an increase of 20 to 50% in nitrogen dioxide emissions. However, demand for cleaner air from Beijing’s middle-class residents has caused a reduction in emissions in the city.

In Syria, nitrogen dioxide levels decreased since 2011, most likely because of the civil war, which has interrupted economic activity and displaced millions of people, but levels have increased in neighbouring countries as Syrians seek refuge.

“By monitoring levels of nitrogen dioxide from space we can see and quantify the effects of things like energy usage, environmental policy and even civil unrest on air quality across the globe,” said Duncan.

Image courtesy of NASA

Image courtesy of NASA

The space-based mapping allowed scientists to gather information on pollution for cities and countries that have limited ground-based air monitoring stations.

South Africa, for instance, was shown to have the highest nitrogen dioxide levels in the Southern Hemisphere, but has achieved decreases in Johannesburg and Pretoria after new cars were required to have better emissions controls. The heavily industrialized area just east of the cities, however, shows both decreases and increases. The decreases may be associated with fewer emissions from eight large power plants east of the cities since the decrease occurs over their locations.

“We had seen seemingly contradictory trends over this area of industrial South Africa in previous studies,” said co-author, Anne Thompson. “Until we had this new space view, it was a mystery.”

Shazam for earthquakes will transform how seismologists detect tremors

An earthquake-detecting algorithm based on song-matching app Shazam is helping Stanford scientists pinpoint the location of microquakes.

The idea for Fingerprint and Similarity Thresholding (FAST) occurred to Greg Beroza, professor of geophysics at Stanford School of Earth, Energy & Environmental Sciences, several years ago.

Like thousands of users before him, Beroza used Shazam to identify a song he didn’t know. Unlike thousands of other users however, Beroza realised from that initial usage that Shazam wasn’t simply comparing the digital file of the song against other files in a database. It was doing something more sophisticated, namely capturing the audio waveform of a short section of the song and comparing that snippet to other waveforms housed on an online server, while at the same time filtering out irrelevant noise from the environment such as people’s conversations.

“I thought, ‘That’s cool,’ and then a moment later, ‘That’s what I want to do with seismology,'” said Beroza.

Earthquake2

So far the device has been able to identify several dozen weak earthquakes, but its creators’ hope that by gaining an understanding of how often different magnitudes of earthquakes happen seismologists might be able to predict how frequently large, natural quakes will occur.

In the new study, the Stanford scientists used FAST to analyse a week’s worth of data collected in 2011 by a seismic station on the Calaveras Fault in California’s Bay Area. This same fault recently ruptured and set off a sequence of hundreds of small quakes.

Not only did FAST detect the known earthquakes, it also discovered several dozen weak quakes that had previously been overlooked.

“A lot of the newer earthquakes that we found were magnitude 1 or below, so that tells us our technique is really sensitive,” said study co-author Clara Yoon. “FAST was able to spot the missed quakes because it looks for similar wave patterns across the seismic data, regardless of their energy level.”

Image courtesy of Ilissa Ocko

Image courtesy of Ilissa Ocko

The FAST technique could replace traditional methods of detecting microquakes, such as template matching which functions by comparing an earthquake’s seismic wave pattern against previously recorded wave signatures in a database.

Unlike template matching, FAST doesn’t require seismologists to have a clear idea of the signal they are looking for ahead of time. It works, like Shazam, by searching for similarities in pre-recorded data from a seismic shift.

“Instead of comparing a signal to every other signal in the database, most of which are noise and not associated with any earthquakes at all, FAST compares like with like,” said Beroza. “Tests we have done on a 6-month data set show that FAST finds matches about 3,000 times faster than conventional techniques. Larger data sets should show an even greater advantage.”