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New developments in the availability of precision robotics, battery technology, and miniaturised sensors have enabled hitherto impossible techniques in emissions quantification. Airborne drones can now retrieve a dense plane of gas concentration measurements in the cross-section of an advecting plume in a matter of minutes, revealing its structure, density, and variability. When interpolated spatiotemporally, and combined with wind measurements, a simple Eulerian mass balance model can be used to estimate emissions flux relatively quickly, with the potential to repeat measurements many times in a day to constrain uncertainty and characterise source dynamics. The drone mass balance method offers a cost-effective, precise, and flexible approach to measuring complex emitting sources that are otherwise challenging to monitor, at rates as low as 0.1 kg/h. Due to this, the method has received significant attention from industry and regulators in the context of the urgent need to understand and reduce greenhouse gas emissions, particularly methane. Its general applicability reaches wider, most notably to volcanology and other hazardous emission sources. However, as yet there is no consistent method of conducting drone mass balance, and different approaches in analysis of even the same data can lead to significant discrepancies in emissions estimates. This has thus far hindered the method's credibility, comparability, and regulatory uptake. We offer here a proposal for a protocol, based on more than ten years of flux method development, presented in a real-world context with results from campaigns and controlled release tests across Europe. The issues discussed will include best practices in flight planning, signal processing, interpolation, measurement and estimation of wind fields, sensor precision; and the ever-present issue of environmental sciences: how many replicates is sufficient.
McQuilkin et al. (Fri,) studied this question.