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Methane leak detection and sizing over long distances using dual frequency comb laser spectroscopy and a bootstrap inversion technique



Kuldeep R. Prasad, Caroline Alden


Advances in natural gas extraction technology have led to increased activity in the production and transport sectors in the United States, and as a consequence, an increased need for reliable monitoring of methane leaks to the atmosphere. We present here a new observing system for the detection and attribution of fugitive emissions of methane from distributed potential source location landscapes such as natural gas production sites. We deploy a dual frequency comb spectrometer in the field for the first time, and measure long (>500 m), integrated open path concentrations of atmospheric methane. We combine measurements with an atmospheric transport model to infer leak locations and strengths using a novel statistical method, the non-zero minimum bootstrap (NZMB). A series of synthetic data tests and outdoor field observations using a controlled methane release demonstrate the viability of this approach for the detection and sizing of very small (<2 g m-1) leaks of methane across large distances (4+ km2 in synthetic tests). Field tests demonstrate ability to attribute small atmospheric enhancements of 18 ppb to the emitting source location against a background of combined atmospheric (e.g., background methane variability) and measurement uncertainty of 6 ppb (1-sigma), when measurements are averaged over 2 minutes. We apply a newly developed bootstrapping algorithm to the synthetic and field data sets to find and size leaks. The new statistical method allows us to determine whether the empirical distribution of possible source strengths for a given location excludes zero. Using this information, we identify leaking source locations (i.e., natural gas wells) through rejection of the null hypothesis that the source is not leaking. The method is tested with a series of synthetic data inversions with varying measurement density and varying levels of model-data mismatch.
Atmospheric Measurement Techniques


Methane Leak Detection


Prasad, K. and Alden, C. (2018), Methane leak detection and sizing over long distances using dual frequency comb laser spectroscopy and a bootstrap inversion technique, Atmospheric Measurement Techniques, [online], (Accessed May 28, 2024)


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Created November 1, 2018, Updated June 9, 2020