What Is Detection Sensitivity and Why Is It Important?
Emission rate detection sensitivity, or often just referred to as “detection sensitivity,” refers to the size of a methane emission rate that can be reliably detected by a technology solution. Having a “better” detection sensitivity (i.e., the ability to detect smaller emissions as well as large ones) that is well-characterized, enables operators to catch more of their emissions and more accurately track their emissions reductions. If a technology’s sensitivity is too “poor”, then a majority of emissions can be missed and it can be impossible to sufficiently reduce emissions or accurately track progress. It’s essential for operators to choose a methane detection solution that has sufficient detection sensitivity to enable them to meet their emissions reduction goals.
We’ve worked with our clients to dial in the right detection sensitivity for our Gas Mapping LiDAR (GML) sensors to identify significant leaks, while avoiding an excessive maintenance burden on the operator with leaks that don’t appreciably impact their overall emissions. We’ve landed on a detection sensitivity that detects >90% of emissions in typical production basins on each scan. See below for our sector-specific detection sensitivities.
Stating a Detection Sensitivity
Characterizing a technology’s detection sensitivity can be harder that one might think. For instance, in addition to stating an emission rate (i.e. size of the leak) that can be detected, the detection sensitivity also needs an accompanying probability of detection (PoD) for an emission of that size. More specifically, the PoD refers to the statistical likelihood that an emission of that size will be detected. For example: a detection sensitivity of 3 kg/hr with a >90% PoD would mean that, statistically, more than nine out of ten emissions of that size will be detected. Similarly, 10 kg/hr with a >50% PoD would mean that, statistically, more than five out of ten times, or half of the time, a leak of 10 kg/hr would be detected.
We discourage the use of minimum detection limit, or “MDL”, when characterizing a detection sensitivity because it doesn’t give a meaningful characterization of detection performance. It simply identifies the lowest detected emission rate event (i.e. smallest leak), which is very often an extremely improbable event. For instance, an MDL may realistically correspond to a PoD of 0.01%. At this MDL emission rate, for every detected emission, 10,000 are missed.
For more information, dig into our past content about detection sensitivity:
Studies That Validate Our Stated Detection Sensitivity
Below are three independent, third-party studies that validate Gas Mapping LiDAR’s 3 kg/hr detection sensitivity. For the distribution sector, the nation’s largest distribution utility has conducted double-blind testing on our technology to determine the detection sensitivity of 0.5 kg/hr with a 90% PoD. Read more about that in a case study.
Robust probabilities of detection and quantification uncertainty for aerial methane detection: Examples for three airborne technologies
Conrad, Bradley M., David R. Tyner, and Matthew R. Johnson. “Robust Probabilities of Detection and Quantification Uncertainty for Aerial Methane Detection: Examples for Three Airborne Technologies.” Remote Sensing of Environment 288 (April 1, 2023): 113499. https://doi.org/10.1016/j.rse.2023.113499.
This study presents a framework for deriving continuous probability of detection functions and quantification uncertainty models for aerial measurement techniques based on controlled release data. The derived results demonstrate the potential of Bridger Photonics Inc.’s GML, Kairos LeakSurveyor, and NASA/JPL AVIRIS-NG technologies in methane detection and mitigation. Based on the study, at typical/target aircraft altitudes and a representative average wind speed of 3 m/s, Bridger’s GML was predicted to identify methane emissions of 2.3 kg/h with 90% probability.
Single-blind determination of methane detection limits and quantification accuracy using aircraft-based LiDAR
Bell, Clay, Jeff Rutherford, Adam Brandt, Evan Sherwin, Timothy Vaughn, and Daniel Zimmerle. “Single-Blind Determination of Methane Detection Limits and Quantification Accuracy Using Aircraft-Based LiDAR.” Elementa: Science of the Anthropocene 10, no. 1 (November 14, 2022): 00080. https://doi.org/10.1525/elementa.2022.00080.
This study reports on the testing of Bridger Photonics' GML system for methane detection and emission rate quantification accuracy. GML showed no significant interference with other gas species in laboratory testing and found that GML has a ≥90% probability of detection of detecting emission sources ≥1 kg/h when flown at 500 ft AGL and ≥2 kg/h when flown at 675 ft AGL, given the prevailing environmental conditions during the experiments (with an average wind speed of 3.9 m/s).
Blinded evaluation of airborne methane source detection using Bridger Photonics LiDAR
Johnson, Matthew R., David R. Tyner, and Alexander J. Szekeres. “Blinded Evaluation of Airborne Methane Source Detection Using Bridger Photonics LiDAR.” Remote Sensing of Environment 259 (June 15, 2021): 112418. https://doi.org/10.1016/J.RSE.2021.112418.
The study evaluated GML for methane detection and quantification accuracy in realistic field conditions and found that it is capable of detecting, locating, and quantifying individual sources at or below regulated venting limits. GML detected all emissions above 2 kg/hr and many below that level, resulting in >90% detection of emissions in typical production basins.
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