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Greenhouse gas flux studies: an automated online system for gas emission measurements in aquatic environments
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2020 (English)In: Hydrology and Earth System Sciences, Vol. 24, no 7, p. 3417-3430Article in journal (Refereed) Published
Abstract [en]

Aquatic ecosystems are major sources of greenhouse gases (GHGs). Robust measurements of natural GHG emissions are vital for evaluating regional to global carbon budgets and for assessing climate feedbacks of natural emissions to improve climate models. Diffusive and ebullitive (bubble) transport are two major pathways of gas release from surface waters. To capture the high temporal variability of these fluxes in a well-defined footprint, we designed and built an inexpensive device that includes an easily mobile diffusive flux chamber and a bubble counter all in one. In addition to automatically collecting gas samples for subsequent various analyses in the laboratory, this device also utilized a low-cost carbon dioxide (CO2) sensor (SenseAir, Sweden) and methane (CH4) sensor (Figaro, Japan) to measure GHG fluxes. Each of the devices was equipped with an XBee module to enable local radio communication (DigiMesh network) for time synchronization and data readout at a server controller station on the lakeshore. The software of this server controller was operated on a low-cost computer (Raspberry Pi), which has a 3G connection for remote control and monitor functions from anywhere in the world. This study shows the potential of a low-cost automatic sensor network system for studying GHG fluxes on lakes in remote locations.

Place, publisher, year, edition, pages
European Geosciences Union (EGU), 2020. Vol. 24, no 7, p. 3417-3430
National Category
Earth and Related Environmental Sciences
Identifiers
URN: urn:nbn:se:polar:diva-8601DOI: 10.5194/hess-24-3417-2020OAI: oai:DiVA.org:polar-8601DiVA, id: diva2:1519129
Note

Supplement: https://doi.org/10.5194/hess-24-3417-2020-supplement

Data sets: Methane and carbon dioxide fluxes, temperature and relative humidity at Mellersta Harrsjön lake, Stordalen Mire, Abisko, 2015T. D. Nguyen, S. Silverstein, M. Wik, P. Crill, D. Bastviken, and R. K. Varner https://bolin.su.se/data/stordalen-ghg-sensors-2015-iot

Model code and software: Code to build an automated online system for gas emission measurements in aquatic environmentsS. Silverstein and T. D. Nguyen https://doi.org/10.17632/yb4h7p4xp4.2

Available from: 2021-01-18 Created: 2021-01-18 Last updated: 2021-01-18Bibliographically approved

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Publisher's full texthttps://hess.copernicus.org/articles/24/3417/2020/
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