Reducing methane emissions has taken center stage in slowing
global warming, but their systematic detection has remained elusive
so far. After years of research, a team of scientists that spun out
of the Los Alamos National Laboratory has managed to build the
first global and automated high resolution methane emissions
detection system, published this week in Nature Communications.
LOS
ALAMOS, N.M. , May 15, 2024
/PRNewswire-PRWeb/ -- Responsible for about a third of global
warming to date, methane is much more effective than CO2 at
trapping heat in the atmosphere. Curbing methane emissions is
therefore widely considered to be among the fastest ways to slow
down global warming – explaining a surge in corporate commitments
and new regulations, including the recent introduction of fines on
methane emissions by the US Environmental Protection Agency.
"This technology is the first able to
automatically detect emissions with good spatial resolution,
anywhere on Earth, every few days."
However, no solution exists today to detect methane at scale.
Energy companies and government agencies rely on imperfect
information to introduce remedial actions. Detections from local
sensors or sensors mounted on cars, planes or drones have limited
coverage. Current detections from satellites are not entirely
automated and come with a trade-off between poor detection
capabilities or poor coverage.
In a study that just came out in Nature Communications, the
research team of Geolabe, out of Los
Alamos, New Mexico, has developed the first method to
automatically detect methane emissions at high spatial and temporal
resolution and global scale. The team trained an AI algorithm able
to parse through large amounts of data produced by the powerful
Sentinel-2 satellite constellation, and autonomously identify
methane signatures. As shown in the peer reviewed study, the
approach can detect more than 85% of methane emitted from oil and
gas basins such as the Permian Basin and is precise enough to
identify the particular source of individual leaks and
emissions.
"This technology is the first able to automatically detect
emissions with good spatial resolution, anywhere on Earth, every
few days", says Bertrand Rouet-Leduc, the main author of the
research. "Automation is paramount when analyzing large areas, and
we also were able to dramatically improve detection
thresholds".
The AI algorithm can precisely identify emission sources that
before could only be detected by airplane or by pointing a
dedicated satellite. "This hasn't really been done before,
especially at that level of detection thresholds and accuracy",
says Claudia Hulbert, also author on
the study.
"Our technology and platform will hopefully provide a reliable
and inexpensive way to get at the fine spatial distribution of
methane emissions and their historical trends."
The paper "Automatic Detection of Methane Emissions in
Multi-Spectral Satellite Imagery Using a Vision Transformer" is
appearing on May 14th, 2024 in Nature
Communications:
https://www.nature.com/articles/s41467-024-47754-y
Geolabe, LLC was founded in 2020 by scientists from the Los
Alamos National Laboratory. The team, who has won a NASA award for
their research, is developing AIs to extract actionable insights
from complex satellite data. www.geolabe.com
Media Contact
Claudia Hulbert, Geolabe LLC, 1
505 570 9614, claudiah@geolabe.com, www.geolabe.com
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SOURCE Geolabe LLC