iAMES: An inexpensive, Automated Methane Ebullition Sensor

4 days ago - Scott G Johnston. Scott G Johnston. Southern ... For field testing, four sensors were deployed for six weeks in a small lake. While ebull...
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iAMES: An inexpensive, Automated, Methane Ebullition Sensor Damien Troy Maher, Michael Drexl, Douglas R. Tait, Scott G Johnston, and Luke C Jeffrey Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 22 May 2019 Downloaded from http://pubs.acs.org on May 22, 2019

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Environmental Science & Technology

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iAMES: An inexpensive, Automated, Methane Ebullition

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Sensor

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Damien T Maher*1,2, Michael Drexl1, Douglas R Tait1, Scott G Johnston1, Luke

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C Jeffrey1

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1Southern

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2School

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2480, Australia

Cross Geoscience, Southern Cross University, Lismore, NSW 2480, Australia

of Environment, Science and Engineering, Southern Cross University, Lismore, NSW

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* Corresponding author [email protected]

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ABSTRACT

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Atmospheric concentrations of methane have increased ~ 2.4 fold since the industrial with

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wetlands and inland waters being the largest source of methane to the atmosphere. Substantial

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uncertainties remain in global methane budgets, due in part to the lack of adequate techniques

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and detailed measurements to assess ebullition in aquatic environments. Here we present

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details of a low cost (~$120 US per unit) ebullition sensor that autonomously logs both

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volumetric ebullition rate and methane concentrations. The sensor combines a traditional

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funnel bubble trap, with an Arduino logger, a pressure sensor, thermal conductivity methane

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sensor, and a solenoid valve. Powered by three AA batteries, the sensor can measure

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autonomously for three months when programed for a sampling frequency of 30 minutes. For

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field testing, four sensors were deployed for six weeks in a small lake. While ebullition was

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spatially and temporally variable, a distinct diurnal trend was observed with the highest rates

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from mid-morning to early afternoon. Ebullition rates were similar for all four sensors when

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integrated over the sampling period. The widespread deployment of low cost automated

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ebullition sensors such as the iAMES described here will help constrain one of the largest

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uncertainties in the global methane cycle.

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INTRODUCTION

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Methane (CH4) is a potent greenhouse gas with a global warming potential 34 times higher

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than carbon dioxide(CO2)1. Concentrations of methane in the atmosphere have increased

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significantly since the industrial revolution from ~ 823 ppb in 1841 to a current concentration

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of ~ 1800 ppb2, 3. Wetlands and inland waterways (lakes, rivers and reservoirs) are major

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sources contributing to the atmospheric burden of methane. Despite the importance of

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wetlands and inland waterways as a source of methane to the atmosphere, significant

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challenges and uncertainties remain in constraining this flux, with current estimates ranging

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between 155 and 235 Tg CH4 yr-1 in 2012 (ref 2).

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Methane can be emitted from wetlands and inland waterways via three dominant pathways;

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diffusive flux (from soils and water), plant-mediated fluxes and via ebbulition4-6. Ebullition is

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often the dominant pathway for methane emissions from wetlands and inland waterways,

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contributing between 50 to over 90% of fluxes from lakes and reserviors2, 7. However, due to

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the high spatiotemporal variability and stochastic nature of ebullition, estimating methane

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emission via ebullition is difficult. As such, most previous studies on wetland and inland

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waterway methane fluxes have neglected the ebullition pathway2. Further, ebullition has

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traditionally been quantified by installing bubble traps that require manual measurement of

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both the volume and methane concentration to estimate fluxes. While this methodology

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provides accurate estimates, the labour intensive nature of the method often prevents long

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term, high spatial and temporal resolution estimates.

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The methodology used to quantify ebullition rates has expanded in recent years. Current

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techniques include automated chambers coupled to laser spectrometer methane detectors8, 9,

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electrical imaging10, hydroacoustic surveys11, bubble traps and time-lapse cameras12 and

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automated bubble traps with pressure sensors13-15. The complexity and cost associated with

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these methods vary, as does the spatial and temporal resolution captured by each approach.

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To the best of our knowledge, all the current systems have either a) high power consumption

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which limits autonomous remote long-term deployments to systems with extensive solar

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arrays and battery backup (e.g. automated chambers and laser spectrometers), b) only capture

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or estimate volumetric fluxes and therefore requiring laboratory analysis of methane

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concentrations (bubble traps, hydoacoustic surveys), or c) are limited to laboratory

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experiments (electrical imaging).

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To refine and improve our understanding of ebullition and to help constrain the importance of

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this process, now and under future climate projections, there is a need for ebullition sensors

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that can autonomously measure both volumetric bubble fluxes and methane concentrations at

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high temporal resolution and over extended periods of time. Any such system should ideally

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be inexpensive to enable widespread use and adequate spatial replication, and also be

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programmable and customisable to suit measurements in a diverse range of inland waterways

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and wetlands. The system should also have low power consumption, to enable remote and

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long-term measurements.

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Here we present the details of the inexpensive Autonomous Methane Ebullition Sensor

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(iAMES). The system integrates a traditional funnel bubble trap with novel electronics

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comprising of a differential pressure sensor, solenoid valve, water temperature sensor,

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thermal conductivity methane sensor, with control and logging undertaken by an Arduino

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pro-mini board. iAMES can autonomously log volumetric fluxes and methane concentrations

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along with ancillary data (water/sediment temperature and atmospheric pressure) for > 3

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months using three AA batteries. The system can be constructed for < $120 USD. To field

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test the new sensor. four iAMES were deployed for a six week period in a shallow (