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. Mapping trace gas emission plumes using in situ measurements from unmanned aerial vehicles (UAVs) is an emerging and attractive possibility to quantify emissions from localized sources. Here, we present the results of an extensive controlled-release experiment in Dübendorf, Switzerland, which was conducted to develop an optimal quantification method and to determine the related uncertainties under various environmental and sampling conditions. Atmospheric methane mole fractions were simultaneously measured using a miniaturized fast-response quantum cascade laser absorption spectrometer (QCLAS) and an active AirCore system mounted on a commercial UAV. Emission fluxes were estimated using a mass-balance method by flying the UAV-based system through a vertical cross-section downwind of the point source perpendicular to the main wind direction at multiple altitudes. A refined kriging framework, called cluster-based kriging, was developed to spatially map individual methane measurement points into the whole measurement plane, while taking into account the different spatial scales between background and enhanced methane values in the plume. We found that the new kriging framework resulted in better quantification compared to ordinary kriging. The average bias of the estimated emissions was −1 %, and the average residual of individual errors was 54 %. A Direct comparison of QCLAS and AirCore measurements shows that AirCore measurements are smoothed by 20 s and had an average time lag of 7 s. AirCore measurements also stretch linearly with time at an average rate of 0.06 s for every second of QCLAS measurement. Applying these corrections to the AirCore measurements and successively calculating an emission estimate shows an enhancement of the accuracy by 3 % as compared to its uncorrected counterpart. Optimal plume sampling, including the downwind measurement distance, depends on wind and turbulence conditions, and it is furthermore limited by numerous parameters such as the maximum flight time and the measurement accuracy. Under favourable measurement conditions, emissions could be quantified with an uncertainty of 30 %. Uncertainties increase when wind speeds are below 2.3 m s−1 and directional variability is above 33∘, and when the downwind distance is above 75 m. In addition, the flux estimates were also compared to estimates from the well-established OTM-33A method involving stationary measurements. A good agreement was found, both approaches being close to the true release and uncertainties of both methods usually capturing the true release.

Controlled-release experiment to investigate uncertainties in UAV-based emission quantification for methane point sources