Testing the near-field Gaussian plume inversion flux quantification technique using unmanned aerial vehicle sampling

Abstract

Abstract. Methane emission fluxes from many facility-scale sources may be poorly quantified, potentially leading to uncertainties in the global methane budget. Accurate atmospheric measurement-based flux quantification is urgently required to address this. This paper describes the first test (using unbiased sampling) of a near-field Gaussian plume inversion (NGI) technique, suitable for facility-scale flux quantification, using a controlled release of methane gas. Two unmanned-aerial-vehicle (UAV) platforms were used to perform 22 flight surveys downwind of a point-source methane gas release from a regulated cylinder with a flowmeter. One UAV was tethered to an instrument on the ground, while the other UAV carried an on-board prototype instrument (both of which used the same near-infrared laser technology). Both instruments were calibrated using certified standards to account for variability in the instrumental gain factor, assuming fixed temperature and pressure. Furthermore, a water vapour correction factor, specifically calculated for the instrument, was applied and is described here in detail. We also provide guidance on potential systematic uncertainties associated with temperature and pressure, which may require further characterisation for improved measurement accuracy. The NGI technique was then used to derive emission fluxes for each UAV flight survey. We found good agreement of most NGI fluxes with the known controlled emission flux, within uncertainty, verifying the flux quantification methodology. The lower and upper NGI flux uncertainty bounds were, on average, 17 %±10(1σ) % and 227 %±98(1σ) % of the controlled emission flux, respectively. This range of conservative uncertainty bounds incorporate factors including the variability in the position of the time-invariant plume and potential for under-sampling. While these average uncertainties are large compared to methods such as tracer dispersion, we suggest that UAV sampling can be highly complementary to a toolkit of flux quantification approaches and may be a valuable alternative in situations where site access for tracer release is problematic. We see tracer release combined with UAV sampling as an effective approach in future flux quantification studies. Successful flux quantification using the UAV sampling methodology described here demonstrates its future utility in identifying and quantifying emissions from methane sources such as oil and gas extraction infrastructure facilities, livestock agriculture, and landfill sites, where site access may be difficult.

Methods for quantifying methane emissions using unmanned aerial vehicles: a review

“…This method requires adequate spatial sampling density in both the y and z directions to resolve a flux [66]. Shah et al [38] tested the NGI method using controlled releases of methane. Two rotary-wing UAVs were used: one tethered to a ground-based off-axis ICOS instrument (Los Gatos Research (now ABB) Micro-portable Greenhouse Gas Analyzer), and the second carrying a miniaturized, lighter prototype of the same instrument.…”

“…The reported lower (17 ± 10%) and upper (227 ± 98%) uncertainty bounds resulted from the variability in the position of instantaneously observed plumes and spatially sparse sampling. While these uncertainties are large, Shah et al [38] concluded that the NGI method is viable in situations where access to an emission source site is prohibited or impractical.…”

Sensitive Drone Mapping of Methane Emissions without the Need for Supplementary Ground-Based Measurements

“…It was noted in both Allen et al 25 and Villa et al 27 that there were no fast high precision CH 4 instruments (defined as better than 100 and 40 ppb/s at 1σ, respectively) available for small UAVs (<7 kg) on the market but that this was a possible future improvement and that simultaneous wind measurements ideally should be made using an instrument on the UAV. Shah et al 28 used two UAVs to measure a controlled CH 4 release: one with an on-board anemometer and a ground-based near-IR CH 4 analyzer connected via tubing and the other UAV with an on-board near-IR CH 4 analyzer (ABB-pMGGA, 3.4 kg and 2.2 ppb precision at 1 Hz). In this paper, we present a small, customized rotary UAV system (6.7 kg total weight; flight time 10 min per battery pair) with the capability to directly map CH 4 hotspots and to measure total area fluxes using on-board instrumentation only, including wind and CH 4 concentrations at high precision and frequency (0.84 ppb and 0.1 m/s at 1 Hz) using a lightweight mid-IR CH 4 sensor (Aeris MIRA Pico, 1.9 kg).…”

On the Viability of Video Imaging in Leak Rate Quantification: A Theoretical Error Analysis

“…In recent years, new measurement systems and technologies have been developed to quantify emissions of methane from equipment and operations with reduced cost and/or improved spatial coverage. Examples include portable methane analyzers [5], open-path laser spectrometers [6], remote sensing of methane from aircraft and satellite [7][8][9], groundbased mobile sensing [10,11] , and airborne mobile sensing approaches using unmanned aerial vehicles (UAVs) [12][13][14][15]. Use of portable methane analyzers is an accurate method for quantifying known emission sources, but localization efforts are often labor intensive with the requirement of investigating entire facilities at a slow pace.…”

“…Ground-based mobile sensing approaches are useful in quantifying emissions from facilities without offering solutions for component leak localization [16,17]. While the use of UAV systems has been promising for leak detection, localization and quantification, large uncertainties arise from the reliance on lightweight sensors and simplistic dispersion models [12,14]. It is worth noting that many non-invasive approaches including transient test-based techniques (TTBTs) have shown success in leak detection and quantification in water systems [18][19][20].…”