Master Thesis

Untersuchung der Emissionsdynamik von Methan mittels Kammermessungen mit unterschiedlichen Durchlüftungseigenschaften

Marcus Wildner (10/2013-02/2015)

Support: Thomas Foken, Mathias Göckede

In Kooperation mit dem Max-Planck-Institut für Biogeochemie in Jena

The understanding of methane emission from Arctic peatland soils presents a key role for climate development in present and future, since these thawing peatlands store large amounts of carbon in the soil. This thesis investigated therefore CH4-emissions in the permafrost region of north-east Siberia. Complementary to micrometeorological methods non-automatic, non-steady-state ow-through chambers were con gured with di erent setups for a cumulative ux detection of CH4 and CO2. Di erent fan, inlet tube and air path designs inside the chambers have been tested under laboratory and eld conditions, to develop improved ux detection methods for greenhouse gases. Even the bias of changed uxes through large shaped tussock plants as an obstacle thereby could be obviated. Particularly in eld conditions uxes stabilised if fans and integrated inlet tube system were used to create an horizontal air stream inside a closed chamber. However, uxes were in uenced by ooding situation, vegetation, atmospheric conditions such as air pressure and air temperature as well as soil conditions, e.g. soil temperature and active layer depth. In this study the emission pathways of methane were determined, with regard to ebullition. Frequencies of ebullition events occurred in mid of July and beginning August, while the proportion of ebullition on total uxes increased steadily until August and reached on average 2 to 7 % during the summer season. Mainly episodic events were detected with carbon amounts of 2 to 1100 mgC m-2 d-1. Coherences of ebullition was found with increased total CH4-flux as well as with environmental conditions. These results are used for series of studies, which further more deeply focus on passive plant-mediated transport of CH4 and the combination of chamber data with micrometeorological data of wavelet analyses and conditional sampling.

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last modified 2015-09-21