Quantifying spatiotemporal greenhouse gas emissions using autonomous surface vehicles

Dunbabin, Matthew and Grinham, Alistair (2016) Quantifying spatiotemporal greenhouse gas emissions using autonomous surface vehicles. Journal of Field Robotics, 34 1: 151-169. doi:10.1002/rob.21665

Author Dunbabin, Matthew
Grinham, Alistair
Title Quantifying spatiotemporal greenhouse gas emissions using autonomous surface vehicles
Journal name Journal of Field Robotics   Check publisher's open access policy
ISSN 1556-4967
Publication date 2016-07-22
Sub-type Article (original research)
DOI 10.1002/rob.21665
Open Access Status Not yet assessed
Volume 34
Issue 1
Start page 151
End page 169
Total pages 19
Place of publication Hoboken, NJ, United States
Publisher John Wiley & Sons
Language eng
Formatted abstract
Accurately quantifying total greenhouse gas emissions (e.g., methane) from natural systems such as lakes, reservoirs, and wetlands requires the spatial and temporal measurement of both diffusive and ebullitive (bubbling) emissions. Ebullitive emissions exhibit high spatial and temporal variability and as such are difficult to measure. Traditional manual measurement techniques provide only limited localized assessment of methane flux, often introducing significant errors when extrapolated to the whole-of-system. This is further exacerbated when whole-of-region estimates are developed for inclusion in global greenhouse gas inventories. In this paper, we directly address these current sampling limitations by comparing two robot boat-based sampling systems with complementary sensing modalities to directly measure in real time the spatiotemporal release of methane to atmosphere across inland waterways. The first system consists of a single Autonomous Surface Vehicle (ASV) fitted with an Optical Methane Detector with algorithms to exploit the robot's mobility and transect repeatability for the accurate detection and quantification of methane bubbles across whole-of-system. The second system consists of multiple networked ASVs capable of persistent operation and scalable to whole-of-region monitoring. Each ASV carries a novel automated chamber-based gas sampling system to allow simultaneous real-time measurement of methane across the waterway. These ASV systems provide a foundation for persistent large-scale spatiotemporal sampling allowing scientists to develop whole-of-region greenhouse gas estimates and greatly improve global inventory budgets. An overview of the single and multi-robot sampling systems is presented, including their automated methane detection and sampling methodologies for the spatiotemporal quantification of greenhouse gas release to atmosphere. Experimental results are shown demonstrating each system's ability to autonomously navigate, detect, and quantify methane release to atmosphere across an entire inland reservoir.
Keyword Greenhouse gas emissions
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Civil Engineering Publications
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Created: Fri, 16 Sep 2016, 19:55:45 EST by Dr Alistair Grinham on behalf of School of Civil Engineering