Validation and demonstration of a drone-based method for quantifying fugitive methane emissions

The development of new measurement methods to assess fugitive methane (CH₄) emissions from industrial sources is needed to improve our understanding of these emissions and promote mitigation practices. Drone-based measurement methods have rapidly emerged in the last few years, however, there are still challenges in finding accurate drone-based measurement approaches and assessing their suitability. This study aims to validate and demonstrate a drone-based method that simultaneously measures atmospheric gas concentrations and wind vectors while flying downwind of the emission source. During the development phase, several tests were performed to ensure that the wind sensor was placed avoiding the majority of downwash and backwash interference. Comparing wind measurements taken at two wind masts and on a mast and a drone produced similar results, thus supporting the reliability of drone-based wind measurements. Moreover, the drone flux method (DFM) was validated by quantifying CH₄ emissions from controlled release tests (2.18 or 3.59 kg h^-1) and the release mimicked (1) a ground-based single source, (2) a ground-based double source and (3) an elevated single source. The DFM results had error rates ranging from +33 to -35%. The DFM was further used to assess emissions from a biogas plant, with simultaneous measurements using the tracer gas dispersion method (TDM). During the same time interval, the DFM quantified the biogas plant emitting CH₄ at a rate of 25.3 ± 6.2 kg h^-1, while the TDM averaged 25.7 ± 4.4 kg h^-1. The method expanded uncertainty (95% confidence interval) assessment was 46% for the controlled release test for single flights quantification. By increasing the number of flights, the uncertainty theoretically decreased to 33% and to 27% for averages of 2 or 3 flights, respectively. Wind sensitivity analysis revealed the importance of assessing wind speed reliably, considering the measured plume height and atmospheric conditions; otherwise, significant errors in the emission determination can occur.