Data for: Single-blind determination of methane detection limits and quantification accuracy using aircraft-based LiDAR

Methane detection limits, emission rate quantification accuracy, and
potential cross-species interference are assessed for Bridger Photonics’
Gas Mapping LiDAR (GML) system utilizing data collected during laboratory
testing and single-blind controlled release testing. Laboratory testing
identified no significant interference in the path-integrated methane
measurement from the gas species tested (ethylene, ethane, propane,
n-butane, i-butane, and carbon dioxide). The controlled release study,
comprised of 650 individual measurement passes, represents the largest
dataset collected to date to characterize GML with respect to point-source
emissions. Binomial regression is utilized to create detection curves
illustrating the likelihood of detecting an emission of a given size under
different wind conditions and for different flight altitudes.
Wind-normalized methane detection limits (90% detection rate) of 0.25
(kg/h)/(m/s) and 0.41 (kg/h)/(m/s) are observed at a flight 
altitude of 500 feet and 675 feet above ground level, respectively.
Quantification accuracy is also assessed for emissions ranging from 0.15
to 1400 kg/h. When emission rate estimates were generated using wind from
High-Resolution Rapid Refresh (HRRR) model (the primary wind source that
Bridger uses for their commercial operations), linear regression indicates
bias of 8.1% (R2 = 0.89). For 95% of controlled releases above Bridger’s
stated production-sector detection sensitivity (3 kg/h with 90%
probability of detection), accuracy of individual emission rate estimates
produced using HRRR wind ranged from -64.1% to 87.0%. Across all
controlled releases 38.1% of estimates had error within +/- 20%, and 87.3%
of measurements were within a factor of two (-50% to +100% error). At low
wind speed (less than 2 m/s) and low emission rates (less than 3 kg/h)
emission estimates are biased high; however, when removed do not impact
the regression significantly. The aggregate quantification error including
all detected emission events was +8.2% using the HRRR wind source. The
resulting detection curves and quantification accuracy illustrate
important implications which must be considered when using measurements
from GML or other remote emission measurement techniques to inform or
validate inventory models, or to audit reported emission levels from oil
and gas systems.