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Methane Emissions: Remote Mapping and Source Quantification Using an Open‐Path Laser Dispersion Spectrometer
Author(s) -
Hirst Bill,
Randell David,
Jones Matthew,
Chu Johnny,
Kannath Arun,
Macleod Neil,
Dean Marcella,
Weidmann Damien
Publication year - 2020
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2019gl086725
Subject(s) - environmental science , greenhouse gas , remote sensing , methane , spectrometer , terrain , monte carlo method , atmospheric dispersion modeling , laser , dispersion (optics) , range (aeronautics) , optics , materials science , physics , geology , chemistry , air pollution , ecology , oceanography , statistics , mathematics , organic chemistry , composite material , biology
Reducing man‐made greenhouse gas emissions depends on the effective detection and location of sources. We present a new method that remotely detects, locates, and quantifies gas emission rates by sequentially steering an optical beam between multiple retro‐reflectors. The novel open‐path laser gas sensor uses Laser Dispersion Spectroscopy (LDS), with seven beams up to 98 meters long deployed across open, flat terrain. LDS offers high precision (10–20 ppb), high dynamic range and linearity, enhanced immunity to atmospheric perturbations, with fast response to probe an area in 3 s. Simultaneous wind and concentration data were collected for four calibrated methane gas release schemes with emission rates of ~1.3 kg/hr. The resulting data were processed using a Bayesian, Markov chain Monte‐Carlo inverse solver to locate the sources and quantify their mass emission rates and uncertainty bounds. All the sources were located to within a few meters and mass emission rates established within the associated confidence bounds.