This paper describes the development of a new sampling and measurement method to infer methane flux using proxy measurements of CO2 concentration and wind data recorded by Unmanned Aerial Systems (UAS). The flux method described and trialed here is appropriate to the spatial scale of landfill sites and analogous greenhouse gas emission hotspots, making it an important new method for low-cost and rapid case study quantification of fluxes from currently uncertain (but highly important) greenhouse gas sources. We present a case study using these UAS-based measurements to derive instantaneous methane fluxes from a test landfill site in the north of England using a mass balance model tailored for UAS sampling and co-emitted CO2 concentration as a methane-emission proxy. Methane flux (and flux uncertainty) during two trials on 27 November 2014 and 5 March 2015, were found to be 0.140 kg s-1 (±61% at 1σ), and 0.050 kg s-1 (±54% at 1σ), respectively. Uncertainty contributing to the flux was dominated by ambient variability in the background (inflow) concentration (>40%) and wind speed (>10%); with instrumental error contributing only ∼1-2%. The approach described represents an important advance concerning the challenging problem of greenhouse gas hotspot flux calculation, and offers transferability to a wide range of analogous environments. This new measurement solution could add to a toolkit of approaches to better validate source-specific greenhouse emissions inventories - an important new requirement of the UNFCCC COP21 (Paris) climate change agreement.

The accurate quantification of methane emissions from point sources is required to better quantify emissions for sector-specific reporting and inventory validation. An unmanned aerial vehicle (UAV) serves as a platform to sample plumes near to source. This paper describes a near-field Gaussian plume inversion (NGI) flux technique, adapted for downwind sampling of turbulent plumes, by fitting a plume model to measured flux density in three spatial dimensions. The method was refined and tested using sample data acquired from eight UAV flights, which measured a controlled release of methane gas. Sampling was conducted to a maximum height of 31 m (i.e. above the maximum height of the emission plumes). The method applies a flux inversion to plumes sampled near point sources. To test the method, a series of random walk sampling simulations were used to derive an NGI upper uncertainty bound by quantifying systematic flux bias due to a limited spatial sampling extent typical for short-duration small UAV flights (less than 30 min). The development of the NGI method enables its future use to quantify methane emissions for point sources, facilitating future assessments of emissions from specific source-types and source areas. This allows for atmospheric measurement-based fluxes to be derived using downwind UAV sampling for relatively rapid flux analysis, without the need for access to difficult-to-reach areas.

This study demonstrates novel measurements of in situ ozone (O₃) concentrations and thermodynamics sampled on‐board an instrumented Skywalker Unmanned Aerial Vehicle (UAV). Small spatial and temporal gradients were observed over a localized region, which nearby ground‐based in situ measurements lack the ability to resolve. It was found that the UAV‐measured O₃ concentrations provided a useful additional indicator of O₃ variability at the sub‐urban scale. The ability to sample subtle variability over a localized area highlights the important and novel capabilities of UAVs to rapidly characterize local area micrometeorology and chemistry.