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Methods for quantifying methane emissions using unmanned aerial vehicles: a review.

Authors :
Shaw, Jacob T.
Shah, Adil
Yong, Han
Allen, Grant
Source :
Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences. 11/15/2021, Vol. 379 Issue 2210, p1-21. 21p.
Publication Year :
2021

Abstract

Methane is an important greenhouse gas, emissions of which have vital consequences for global climate change. Understanding and quantifying the sources (and sinks) of atmospheric methane is integral for climate change mitigation and emission reduction strategies, such as those outlined in the 2015 UN Paris Agreement on Climate Change. There are ongoing international efforts to constrain the global methane budget, using a wide variety of measurement platforms across a range of spatial and temporal scales. The advancements in unmanned aerial vehicle (UAV) technology over the past decade have opened up a new avenue for methane emission quantification. UAVs can be uniquely equipped to monitor natural and anthropogenic emissions at local scales, displaying clear advantages in versatility and manoeuvrability relative to other platforms. Their use is not without challenge, however: further miniaturization of high-performance methane instrumentation is needed to fully use the benefits UAVs afford. Developments in the models used to simulate atmospheric transport and dispersion across small, local scales are also crucial to improved flux accuracy and precision. This paper aims to provide an overview of currently available UAV-based technologies and sampling methodologies which can be used to quantify methane emission fluxes at local scales. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1364503X
Volume :
379
Issue :
2210
Database :
Academic Search Index
Journal :
Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences
Publication Type :
Academic Journal
Accession number :
153191880
Full Text :
https://doi.org/10.1098/rsta.2020.0450