Princeton researchers have developed an innovative method to identify and repair greenhouse gas leaks in gas drilling and sewer systems. Published in the journal Remote Sensing of Environment, their laser-based sensing approach can accurately detect and measure leaks of various sizes, including leaks up to 25 times smaller than those typically detected using other methods. The technology enables the localization of emissions sources to within a meter.
By utilizing the remote-sensing capabilities of lasers in combination with drones, this new technique can identify hidden leaks in hard-to-access areas, presenting a significant advancement in atmospheric sensing. Traditional leak detection methods often rely on labor-intensive handheld infrared cameras, which are insensitive to small leaks, or require extensive measurement infrastructure in advance. In contrast, drones equipped with retroreflectors (mirrors reflecting light back to the source) and gas sensing equipment in a base station can quickly identify leak sources and measure their intensity.
According to Gerard Wysocki, associate professor of electrical and computer engineering at Princeton, the flexibility of using drones allows for easy setup of the sensing area, making it a game-changing approach for leak detection. Mark Zondlo, co-author of the study and professor of civil and environmental engineering at Princeton, described this technique as the “holy grail” of leak detection.
Although drone-based atmospheric sensing techniques exist, they typically involve mounting gas sensors directly onto drones. However, this practice faces challenges related to weight limitations and the risk of flying overloaded drones with expensive sensors in hazardous environments. Princeton’s approach overcomes these obstacles by using a retroreflector on the drone and tracking its movement from a base station.
Mark Zondlo, a professor at Princeton University, explains that it is not feasible to fit more than one gas sensor on a drone due to the size and weight limitations. Additionally, it is risky to fly expensive sensors over potentially hazardous areas such as wastewater treatment plants or compressor stations.
To address these challenges, the researchers from Princeton decided to place the expensive gas sensing components on a base station instead of burdening the drone. The base station, which can be mounted on a mobile platform like a van, houses the gas sensing equipment, while the drone carries only a small mirror. This approach allows them to use smaller and more affordable drones with longer flight times to collect highly detailed emissions data over large areas. It potentially enables the monitoring of entire natural gas transmission and distribution facilities in a single drone flight.
This offloading of gas sensing components to the base station represents a paradigm shift in utilizing drones for atmospheric sensing, according to Zondlo. It frees up drones from carrying heavy sensors and maximizes their potential.
Furthermore, the sensing method opens up the possibility of simultaneously measuring multiple gases, which is challenging with other drone-based approaches due to size, weight, and power constraints. By adding lasers of different wavelengths to the base system, the researchers can easily measure gases like carbon dioxide and ammonia alongside methane.
Michael Soskind, the study’s first author and a graduate student at Princeton, explains that incorporating additional gases into the system would be as simple as adding a secondary laser. The rest of the system is already designed to accommodate such expansions.
The researchers believe that their approach is not limited to methane leak detection but can be a platform for future innovation and applications. It provides flexibility for researchers and practitioners to use drones and remote sensing techniques for precise measurements of small leaks and emissions plumes. This technology can facilitate efficient leak detection and repair, helping producers mitigate safety and environmental hazards while saving time and money.
Source: Princeton University