Evaluating the performance of a cost effective in situ methane sensor for UAS-based systems and its ability to quantify facility-scale emissions

Abstract

Abstract. Methane (CH4) is the second most important greenhouse gas, and accurate quantification of emissions is critical to improve the efficacy of climate mitigation policies. In this study, we thoroughly evaluated the performance of a commercially available in situ CH4 sensor (LGD-compact A CH4; Axetris AG, Kaegiswil, Switzerland) for quantifying anthropogenic CH4 emissions when deployed on an uncrewed aircraft system (UAS). Sensor stability was assessed through laboratory tests under controlled and varying temperature conditions. Under stable conditions, the sensor achieved a precision of 63 ppb at 2 Hz. Furthermore, the tests revealed the necessity of temperature control, and a water vapour correction was derived and applied to ensure accurate measurements. Additionally, the sensor was used to quantify whole-farm CH4 emissions, by spatially interpolating the measured mole fractions using a Gaussian weighting scheme. This yielded a mean mass emission rate of 4.1 ± 1.6 gCH4 s−1 averaged over four flights, which was comparable to the value of 4.2 ± 1.1 gCH4 s−1 obtained from simultaneous flights with the established AirCore technique. Finally, an uncertainty analysis based on the Ornstein-Uhlenbeck method was used to determine the influence of various sources of uncertainty. This analysis revealed that both wind-related uncertainties and background determination can significantly increase the overall uncertainty when not properly constrained. Furthermore, instrumental errors play a dominant role for smaller mass emission rates, while meteorological uncertainties remain significant even with an increased number of flights per day. Nevertheless, careful flight planning, e.g., ensuring extensive sampling outside of the plume and comprehensive wind monitoring, can reduce these uncertainties. Overall, our results demonstrate that a cost-effective sensor integrated onto a UAS can provide reliable CH4 mass emission rate estimates with uncertainties comparable to those of higher-cost UAS-based systems.