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The application of nanoscale zero-valent iron (nZVI) for subsurface remediation of groundwater contaminants is a promising new technology, which can be understood as alternative to the permeable reactive barrier technique using granular iron. Dechlorination of organic contaminants by zero-valent iron seems promising. Currently, one limitation to widespread deployment is the fast agglomeration and sedimentation of nZVI in colloidal suspensions, even more so when in soils and sediments, which limits the applicability for the treatment of sources and plumes of contamination. Colloid-supported nZVI shows promising characteristics to overcome these limitations. Mobility of Carbo-Iron Colloids (CIC) - a newly developed composite material based on finely ground activated carbon as a carrier for nZVI - was tested in a field application: In this study, a horizontal dipole flow field was established between two wells separated by 53 m in a confined, natural aquifer. The injection/extraction rate was 500 L/h. Approximately 12 kg of CIC was suspended with the polyanionic stabilizer carboxymethyl cellulose. The suspension was introduced into the aquifer at the injection well. Breakthrough of CIC was observed visually and based on total particle and iron concentrations detected in samples from the extraction well. Filtration of water samples revealed a particle breakthrough of about 12% of the amount introduced. This demonstrates high mobility of CIC particles and we suggest that nZVI carried on CIC can be used for contaminant plume remediation by in-situ formation of reactive barriers. (C) 2015 Elsevier B.V. All rights reserved.
Indonesien zählt zu den weltweit führenden Ländern bei der Nutzung von geothermischer Energie. Die geothermischen Energiequellen sind im Wesentlichen an den aktiven Vulkanismus gebunden, der durch die Prozesse an der indonesischen Subduktionszone verursacht wird. Darüber hinaus sind geotektonische Strukturen wie beispielsweise die Sumatra-Störung als verstärkende Faktoren für das geothermische Potenzial von Bedeutung. Bei der geophysikalischen Erkundung der indonesischen Geothermie-Ressourcen konzentrierte man sich bisher vor allem auf die Magnetotellurik. Passive Seismologie wurde dahingegen ausschließlich für die Überwachung von im Betrieb befindlichen Geothermie-Anlagen verwendet. Jüngste Untersuchungungen z.B. in Island und in den USA haben jedoch gezeigt, dass seismologische Verfahren bereits in der Erkundungsphase wichtige Informationen zu den physikalischen Eigenschaften, zum Spannungsfeld und zu möglichen Fluid- und Wärmetransportwegen liefern können. In der vorgelegten Doktorarbeit werden verschiedene moderne Methoden der passiven Seismologie verwendet, um beispielhaft ein neues, von der indonesischen Regierung für zukünftige geothermische Energiegewinnung ausgewiesenes Gebiet im nördlichen Teil Sumatras (Indonesien) zu erkunden. Die konkreten Ziele der Untersuchungen umfassten (1) die Ableitung von 3D Strukturmodellen der P- und S-Wellen Geschwindigkeiten (Parameter Vp und Vs), (2) die Bestimmung der Absorptionseigenschaften (Parameter Qp), und (3) die Kartierung und Charakterisierung von Störungssystemen auf der Grundlage der Seismizitätsverteilung und der Herdflächenlösungen. Für diese Zwecke habe ich zusammen mit Kollegen ein seismologisches Netzwerk in Tarutung (Sumatra) aufgebaut und über einen Zeitraum von 10 Monaten (Mai 2011 – Februar 2012) betrieben. Insgesamt wurden hierbei 42 Stationen (jeweils ausgestattet mit EDL-Datenlogger, 3-Komponenten, 1 Hz Seismometer) über eine Fläche von etwa 35 x 35 km verteilt. Mit dem Netzwerk wurden im gesamten Zeitraum 2568 lokale Erdbeben registriert. Die integrierte Betrachtung der Ergebnisse aus den verschiedenen Teilstudien (Tomographie, Erdbebenverteilung) erlaubt neue Einblicke in die generelle geologische Stukturierung sowie eine Eingrenzung von Bereichen mit einem erhöhten geothermischen Potenzial. Das tomographische Vp-Modell ermöglicht eine Bestimmung der Geometrie von Sedimentbecken entlang der Sumatra-Störung. Für die Geothermie besonders interessant ist der Bereich nordwestlich des Tarutung-Beckens. Die dort abgebildeten Anomalien (erhöhtes Vp/Vs, geringes Qp) habe ich als mögliche Aufstiegswege von warmen Fluiden interpretiert. Die scheinbar asymetrische Verteilung der Anomalien wird hierbei im Zusammenhang mit der Seismizitätsverteilung, der Geometrie der Beben-Bruchflächen, sowie struktur-geologischen Modellvorstellungen diskutiert. Damit werden wesentliche Informationen für die Planung einer zukünftigen geothermischen Anlage bereitgestellt.
A fast and sensitive method for the continuous determination of methane (CH4) and its stable carbon isotopic values (delta C-13-CH4) in surface waters was developed by applying a vacuum to a gas/liquid exchange membrane and measuring the extracted gases by a portable cavity ring-down spectroscopy analyser (M-CRDS). The M-CRDS was calibrated and characterized for CH4 concentration and delta C-13-CH4 with synthetic water standards. The detection limit of the M-CRDS for the simultaneous determination of CH4 and delta C-13-CH4 is 3.6 nmol L-1 CH4. A measurement precision of CH4 concentrations and delta C-13-CH4 in the range of 1.1%, respectively, 1.7 parts per thousand (1 sigma) and accuracy (1.3%, respectively, 0.8 parts per thousand [1 sigma]) was achieved for single measurements and averaging times of 10 min. The response time tau of 57 +/- 5 s allow determination of delta C-13-CH4 values more than twice as fast than other methods. The demonstrated M-CRDS method was applied and tested for Lake Stechlin (Germany) and compared with the headspace-gas chromatography and fast membrane CH4 concentration methods. Maximum CH4 concentrations (577 nmol L-1) and lightest delta C-13-CH4 (-35.2 parts per thousand) were found around the thermocline in depth profile measurements. The M-CRDS-method was in good agreement with other methods. Temporal variations in CH4 concentration and delta C-13-CH4 obtained in 24 h measurements indicate either local methane production/oxidation or physical variations in the thermocline. Therefore, these results illustrate the need of fast and sensitive analyses to achieve a better understanding of different mechanisms and pathways of CH4 formation in aquatic environments.
Past climatic change can be reconstructed from sedimentary archives by a number of proxies. However, few methods exist to directly estimate hydrological changes and even fewer result in quantitative data, impeding our understanding of the timing, magnitude and mechanisms of hydrological changes. Here we present a novel approach based on delta H-2 values of sedimentary lipid biomarkers in combination with plant physiological modeling to extract quantitative information on past changes in relative humidity. Our initial application to an annually laminated lacustrine sediment sequence from western Europe deposited during the Younger Dryas cold period revealed relative humidity changes of up to 15% over sub-centennial timescales, leading to major ecosystem changes, in agreement with palynological data from the region. We show that by combining organic geochemical methods and mechanistic plant physiological models on well characterized lacustrine archives it is possible to extract quantitative ecohydrological parameters from sedimentary lipid biomarker delta H-2 data.
The molecular biomarker composition of two sediment cores from Sanabria Lake (NW Iberian Peninsula) and a survey of modern plants in the watershed provide a reconstruction of past vegetation and landscape dynamics since deglaciation. During a proglacial stage in Lake Sanabria (prior to 14.7 cal ka BP), very low biomarker concentration and carbon preference index (CPI) values similar to 1 suggest that the n-alkanes could have derived from eroded ancient sediment sources or older organic matter with high degree of maturity. During the Late glacial (14.7-11.7 cal ka BP) and the Holocene (last 11.7 cal ka BP) intervals with higher biomarker and triterpenoid concentrations (high %nC(29) , nC(31) alkanes), higher CPI and average carbon length (ACL), and lower P-aq (proportion of aquatic plants) are indicative of major contribution of vascular land plants from a more forested watershed (e.g. Mid Holocene period 7.0-4.0 cal ka BP). Lower biomarker concentrations (high %nC(27) alkanes), CPI and ACL values responded to short phases with decreased allochthonous contribution into the lake that correspond to centennial-scale periods of regional forest decline (e.g. 4-3 ka BP, Roman deforestation after 2.0 ka, and some phases of the LIA, seventeenth-nineteenth centuries). Human activities in the watershed were significant during early medieval times (1.3-1.0 cal ka BP) and since 1960 CE, in both cases associated with relatively higher productivity stages in the lake (lower biomarker and triterpenoid concentrations, high %nC(23) and %nC(31) respectively, lower ACL and CPI values and higher P-aq). The lipid composition of Sanabria Lake sediments indicates a major allochthonous (watershed-derived) contribution to the organic matter budget since deglaciation, and a dominant oligotrophic status during the lake history. The study constrains the climate and anthropogenic forcings and watershed versus lake sources in organic matter accumulation processes and helps to design conservation and management policies in mountain, oligotrophic lakes.
Earthquake localization is both a necessity within the field of seismology, and a prerequisite for further analysis such as source studies and hazard assessment. Traditional localization methods often rely on manually picked phases. We present an alternative approach using deep learning that once trained can predict hypocenter locations efficiently. In seismology, neural networks have typically been trained with either single-station records or based on features that have been extracted previously from the waveforms. We use three-component full-waveform records of multiple stations directly. This means no information is lost during preprocessing and preparation of the data does not require expert knowledge. The first convolutional layer of our deep convolutional neural network (CNN) becomes sensitive to features that characterize the waveforms it is trained on. We show that this layer can therefore additionally be used as an event detector. As a test case, we trained our CNN using more than 2000 earthquake swarm events from West Bohemia, recorded by nine local three-component stations. The CNN successfully located 908 validation events with standard deviations of 56.4 m in east-west, 123.8 m in north-south, and 136.3 m in vertical direction compared to a double-difference relocated reference catalog. The detector is sensitive to events with magnitudes down to M-L = -0.8 with 3.5% false positive detections.
We present an experimental approach to study the three-dimensional microstructure of gas diffusion layer (GDL) materials under realistic compression conditions. A dedicated compression device was designed that allows for synchrotron-tomographic investigation of circular samples under well-defined compression conditions. The tomographic data provide the experimental basis for stochastic modeling of nonwoven GDL materials. A plain compression tool is used to study the fiber courses in the material at different compression stages. Transport relevant geometrical parameters, such as porosity, pore size, and tortuosity distributions, are exemplarily evaluated for a GDL sample in the uncompressed state and for a compression of 30 vol.%. To mimic the geometry of the flow-field, we employed a compression punch with an integrated channel-rib-profile. It turned out that the GDL material is homogeneously compressed under the ribs, however, much less compressed underneath the channel. GDL fibers extend far into the channel volume where they might interfere with the convective gas transport and the removal of liquid water from the cell. (C) 2015 AIP Publishing LLC.
In this study we investigate a dayside, midlatitude plasma depletion (DMLPD) encountered on 22 May 2014 by the Swarm and GRACE satellites, as well as ground-based instruments. The DMLPD was observed near Puerto Rico by Swarm near 10 LT under quiet geomagnetic conditions at altitudes of 475-520 km and magnetic latitudes of similar to 25 degrees-30 degrees. The DMLPD was also revealed in total electron content observations by the Saint Croix station and by the GRACE satellites (430 km) near 16 LT and near the same geographic location. The unique Swarm constellation enables the horizontal tilt of the DMLPD to be measured (35 degrees clockwise from the geomagnetic east-west direction). Ground-based airglow images at Arecibo showed no evidence for plasma density depletions during the night prior to this dayside event. The C/NOFS equatorial satellite showed evidence for very modest plasma density depletions that had rotated into the morningside from nightside. However, the equatorial depletions do not appear related to the DMLPD, for which the magnetic apex height is about 2500 km. The origins of the DMLPD are unknown, but may be related to gravity waves.
Compound natural hazards likeEl Ninoevents cause high damage to society, which to manage requires reliable risk assessments. Damage modelling is a prerequisite for quantitative risk estimations, yet many procedures still rely on expert knowledge, and empirical studies investigating damage from compound natural hazards hardly exist. A nationwide building survey in Peru after theEl Ninoevent 2017 - which caused intense rainfall, ponding water, flash floods and landslides - enables us to apply data-mining methods for statistical groundwork, using explanatory features generated from remote sensing products and open data. We separate regions of different dominant characteristics through unsupervised clustering, and investigate feature importance rankings for classifying damage via supervised machine learning. Besides the expected effect of precipitation, the classification algorithms select the topographic wetness index as most important feature, especially in low elevation areas. The slope length and steepness factor ranks high for mountains and canyons. Partial dependence plots further hint at amplified vulnerability in rural areas. An example of an empirical damage probability map, developed with a random forest model, is provided to demonstrate the technical feasibility.
Protection of natural or semi-natural ecosystems is an important part of societal strategies for maintaining biodiversity, ecosystem services, and achieving overall sustainable development. The assessment of multiple emerging land use trade-offs is complicated by the fact that land use changes occur and have consequences at local, regional, and even global scale. Outcomes also depend on the underlying socio-economic trends. We apply a coupled, multi-scale modelling system to assess an increase in nature protection areas as a key policy option in the European Union (EU). The main goal of the analysis is to understand the interactions between policy-induced land use changes across different scales and sectors under two contrasting future socio-economic pathways. We demonstrate how complementary insights into land system change can be gained by coupling land use models for agriculture, forestry, and urban areas for Europe, in connection with other world regions. The simulated policy case of nature protection shows how the allocation of a certain share of total available land to newly protected areas, with specific management restrictions imposed, may have a range of impacts on different land-based sectors until the year 2040. Agricultural land in Europe is slightly reduced, which is partly compensated for by higher management intensity. As a consequence of higher costs, total calorie supply per capita is reduced within the EU. While wood harvest is projected to decrease, carbon sequestration rates increase in European forests. At the same time, imports of industrial roundwood from other world regions are expected to increase. Some of the aggregate effects of nature protection have very different implications at the local to regional scale in different parts of Europe. Due to nature protection measures, agricultural production is shifted from more productive land in Europe to on average less productive land in other parts of the world. This increases, at the global level, the allocation of land resources for agriculture, leading to a decrease in tropical forest areas, reduced carbon stocks, and higher greenhouse gas emissions outside of Europe. The integrated modelling framework provides a method to assess the land use effects of a single policy option while accounting for the trade-offs between locations, and between regional, European, and global scales.