The development and trial of an unmanned aerial system for the measurement of methane flux from landfill and greenhouse gas emission hotspots

Allen, G, Hollingsworth, P, Kabbabe, K, Pitt, JR, Mead, MI, Illingworth, S, Roberts, G, Bourn, M, Shallcross, DE and Percival, CJ (2019) The development and trial of an unmanned aerial system for the measurement of methane flux from landfill and greenhouse gas emission hotspots. Waste Management, 87. pp. 883-892. ISSN 0956-053X

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Abstract

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 1r), and 0.050 kg s 1 (±54% at 1r), 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. Copyright 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).