8 resultados para Grünes Gewölbe (Museum : Dresden, Germany)

em Publishing Network for Geoscientific


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CO2 leakage from subsurface storage sites is one of the main concerns connected with the CCS technology. As CO2 leakages into near surface formations appear to be very unlikely within pilot CCS projects, the aim of this work is to emulate a leakage by injecting CO2 into a near surface aquifer. The two main questions pursued by the injection test are (1) to investigate the impact of CO2 on the hydrogeochemistry of the groundwater as a base for groundwater risk assessment and (2) to develop and apply monitoring methods and monitoring concepts for detecting CO2 leakages in shallow aquifers. The presented injection test is planned within the second half of 2010, as a joint project of the University of Kiel (Germany), the Helmholtz-Centre for Environmental Research (Leipzig, Germany) and the Engineering Company GICON (Dresden, Germany). The test site has been investigated in detail using geophysical methods as well as direct-push soundings, groundwater well installation and soil and groundwater analyses. The present paper presents briefly the geological and hydrogeological conditions at the test site as well as the planned injection test design and monitoring concept.

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This data set provides a high-resolution digital elevation model (DEM) of a thermokarst depression (~7 km²) on ice-complex deposits in the Arctic Lena Delta, Siberia. The DEM based on a geodetic field survey and was used for quantitative land surface analyses and detailed description of the thermokarst depression morphology. Detailed morphometrical analyses, volume calculations, and solar radiation modeling were performed and statistically analyzed by Ulrich et al. (2010) to investigate the asymmetrical thermokarst depression development and directed lake migration previously proposed by Morgenstern et al. (2008). Furthermore, the high-resolution DEM in combination with satellite data allowed detailed analyses of spatial and temporal landscape changes due to thermokarst development (Günther, 2009).

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The Lena River Delta, situated in Northern Siberia (72.0 - 73.8° N, 122.0 - 129.5° E), is the largest Arctic delta and covers 29,000 km**2. Since natural deltas are characterised by complex geomorphological patterns and various types of ecosystems, high spatial resolution information on the distribution and extent of the delta environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was conducted and used for the quantification of methane emissions from the delta ecosystems on the regional scale. The applied supervised minimum distance classification was very effective with the few ancillary data that were available for training site selection. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena Delta was calculated with 10.35 mg CH4/m**2/d. Taking our multi-scale approach into account we find that the methane source strength of certain tundra wetland types is lower than calculated previously on coarser scales.

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The data files give the basic field and laboratory data on five ponds in the northeast Siberian Arctic tundra on Samoylov. The files contain water and soil temperature data of the ponds, methane fluxes, measured with closed chambers in the centres without vascular plants and the margins with vascular plants, the contribution of plant mediated fluxes on total methane fluxes, the gas concentrations (methane and dissolved inorganic carbon, oxygen) in the soil and the water column of the ponds, microbial activities (methane production, methane oxidation, aerobic and anaerobic carbon dioxide production), total carbon pools in the different horizons of the bottom soils, soil bulk density, soil substance density, and soil porosity.