A knot in the handkerchief. United States President Joe Biden, joining European Union leaders at the United Nations Climate Summit, pledged to reduce global methane emissions by 30% over the next decade.
This is an epochal change. It will involve various realities active in the sector. In particular, oil and gas infrastructures, which represent 30% of methane emissions in the United States.
The U.S. pipeline landscape
More than 300,000 miles of pipelines transport natural gas across North America causing substantial losses from both an environmental and an economic point of view.
Furthermore, these infrastructures pass through areas of the country that have other sources of methane (livestock, coastal wetlands). For this reason it is essential to identify where the gas comes from and whether its presence is related to a gas pipeline leak.
Research from the University of New Mexico
Researchers at the University of New Mexico are producing an answer to these questions with a project that began in 2020. The research aims to develop low-cost sensors to detect gas leaks. This detection system is based on electrochemical devices with mixed potential.
The sensors thus developed are able to quantify the presence of natural gas and act as an early warning system for gas pipeline leaks.
The methane sensor system, based on the Internet of Things, uses:
– additive manufacturing for rapid prototyping and low-cost manufacturing of devices;
– Machine learning techniques for quantification of methane concentration and identification of the source of these methane leaks;
– portable data acquisition and transmission technologies to facilitate deployment of the sensor systems in remote areas.
Inspiration from car exhaust sensors
These technologies therefore favor real-time monitoring, which translates into early warning of leaks that can therefore be quickly contained.
The devices on which the research is based derive from automobile exhaust sensors, thanks to their ability to withstand harsh environments and exposure to sticky gases, such as ammonia. Furthermore, the need for low maintenance makes them suitable for long-term monitoring in the field.
Sources: news.unm.edu, bizjournals.com