Unmanned aerial vehicles (UAVs) are one key platforms for monitoring methane due to their flexible deployment with spatial scales between ground-based sensors and crewed aircraft This review synthesises research on UAV sensing technologies, flight and sampling strategies, quantification methods, and validation practices. It finds that quantitative performance depends on the combined choice of sensor, platform, flight geometry, wind measurement, and estimation method. The key UAV-deployable sensor categories are contrasted based on sensitivity, response, payload restrictions, and field of use, which includes open-path tunable diode laser absorption spectroscopy (TDLAS) and closed-path TDLAS, quantum cascade laser absorption spectroscopy (QCLAS), active AirCore, non-dispersive infrared (NDIR), and thermal imaging sensors. Multirotor UAVs support repeated transects and vertical plume sampling, while fixed-wing platforms are primarily suited to broader-area screening. Mass-balance and Gaussian inversion methods can estimate emission rates, but their results are sensitive to wind uncertainty and incomplete plume coverage. Tracer-based approaches can reduce direct reliance on wind measurements when tracer and methane plumes disperse together. Controlled-release studies also show that small average bias can coexist with substantial errors in individual flights. Across sectors, methods are more developed for oil and gas facilities, landfills, and coal-mine ventilation shafts than for agriculture and wastewater. The literature reviewed identified no dedicated peer-reviewed UAV methane quantification study at an active surface coal mine. Wider use of UAVs for emissions assessment will require survey designs matched to source characteristics, stronger field validation, and more consistent uncertainty reporting.
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Bhandari et al. (2026) studied this question.
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