Refine
Document Type
- Doctoral Thesis (5)
- Bachelor Thesis (1)
Keywords
- Azeotrope Destillation (1)
- Biodiesel (1)
- Biokraftstoff (1)
- Headspace-Analyse (1)
- Headspace-GCMS (1)
- Kraftstofffilter (1)
- activity coefficient (1)
- azeotrope oil dilution (1)
- diesel particulate filter (1)
Der Klimawandel gehört zu den globalen Herausforderungen des 21. Jahrhunderts. Die Folgen des Klimawandels machen sich u.a. in Form von Hitze, Stürmen oder Starkregen bemerkbar. Dem Klimawandel kann sowohl mithilfe des Klimaschutzes (Mitigation) in Form der Ursachenbekämpfung als auch mithilfe der Klimaanpassung (Adaption), welche sich in Form von Anpassungsmaßnahmen an das sich ändernde Klima darstellt, begegnet werden. Aufgrund ihrer Struktur sind insbesondere urbane Strukturen von Klimafolgen betroffen. Der Raum- und Umweltplanung komme dabei hinsichtlich der sozial-ökologischen Naturverhältnisse eine wichtige Rolle zu, sofern sie die Aufgaben der Krisenbewältigung annehmen und verantwortungsvoll wahrnehmen will.
Auch die Hansestadt Lüneburg steht zukünftig vor einigen Herausforderungen. Durch den allgemeinen Trend der Urbanisierung und als Teil der Metropolregion Hamburg gilt Lüneburg als beliebter Wohnraum. Folglich werden auch zukünftig neue Baugebiete erschlossen, Wohnraum geschaffen und Verdichtung sowie Flächenversiegelung vorgenommen. Im aktuell bearbeiteten Klimagutachten für Lüneburg werden bereits bisherige Risikogebiete bezüglich Hitze und Frischluft aufgezeigt.
In der vorliegenden Arbeit werden zunächst die der Ausarbeitung zugrungegelegten Begriffe sowie die Bedeutung von Starkregenereignissen in der Stadtplanung definiert und näher erläutert. Darauf folgt die Darstellung der zur Beantwortung der Forschungsfrage verwendeten Methoden. Anschließend werden in der empirischen Forschung das bisherige Auftreten von Starkregen analysiert, bestehende Adaptionsstrategien norddeutscher Städte und Regionen aufgezeigt, ein Zukunftsausblick auf Grundlage wissenschaftlicher Prognosen gegeben und konkrete, auf die Hansestadt Lüneburg bezogene, Analysen und Szenarien erstellt, bevor ein Resümee der empirischen Forschung gezogen werden kann. Abschließend wird das methodische Vorgehen reflektiert, die Ergebnisse diskutiert und ein kurzer Ausblick auf zukünftige Herausforderungen gegeben.
Die Arbeit liefert die Grundlagen zur chemischen Entfernung von Biodiesel aus dem Motoröl, um eine Minderung der Einschleppungsproblematiken beim Einsatz von biogenen Kraftstoffen und Dieselpartikelfiltern zu erzielen. Das Prinzip beruht auf einer wechselwirkenden Beimischkomponenten die eine Azeotropbildung mit Biodiesel einleitet. Eine gaschromatographische Headspace-Screening-Methode diente der Messung von Aktivitätskoeffizienten in Anwesenheit von Biodiesel. Die Ergebnisse dieser Analysen lieferten erste Erkenntnisse welche funktionalen Gruppen eine notwendige starke Wechselwirkung mit Biodiesel besitzen. Die gaschromatographischen Analysen wurden zudem mit Simulationsrechnungen mittels COSMOtherm untermauert. Im Laborversuch haben sich polare Säuren wie Ameisensäure oder Essigsäure als gute Beimischkomponenten erwiesen. Aldehyde, Ketone oder Alkohole sind weniger geeignet. Säuren wirken als Hydrogen Bond Donator und besitzen hohe Aktivitätskoeffizienten mit Biodiesel. Durch die Destillation des gebildeten azeotropen Gemischs kann die Entfernung von Biodiesel aus dem Motoröl bei niedrigen Temperaturen von ca. 180 Grad Celsius bis 190 Grad Celsius realisiert werden. Ohne den Einsatz von Beimischkomponenten liegt die Destillationstemperatur von Biodiesel bei ca. 330 Grad Celsius.
"Sustainable development: enough for everyone, forever" is the definition of sustainability. Sustainable landscape development is the main goal of decision makers worldwide. Achieving this goal in the long term leads to achieving social, economic and environmental sustainability. Remote sensing has been playing an essential role in monitoring remote areas. This study has employed part of the role of remote sensing in supporting the direction of decision makers towards sustainable landscape development. The study has focused on some of the main elements affecting sustainable environment as stated in Agenda 21. These elements are land uses, specifically agricultural land uses, water quality, forests, and water hazards such as floods.
Three research programs were undertaken to investigate the role of Terrasar-x imagery, as a source of remote sensing data, in monitoring the environment and achieving the previous stated elements. The investigation was intended to investigate the effectiveness of TSX imagery in identifying the cropping pattern of selected study areas by employing a pixel-based supervised maximum likelihood classifier, as published in Paper I, assessment of the efficiency of using TSX imagery in determining land use and the flood risk maps by applying an object-based decision tree classifier as published in Paper II, and determination of the potential of inferential statistics tests such as the two samples Z-test and multivariate analysis, for example Factor Analysis, for identifying the kind of forest canopy, based on the backscattering coefficient of TSX imagery of forest plots, as presented in Paper III. Papers I and II covered two pilot areas in the Lower Saxonian Elbe Valley Biosphere Reserve “das Biosphärenreservat „Niedersächsische Elbtalaue„ around Walmsburger Werder between Elbe-Kilometer 533 - 543 and Wehninger Werder between Elbe-Kilometer 505 - 520. Paper III focused on the Fuhrberger Feld water protection area near Hanover in Germany. The inputs for this research were mainly SAR Imagery and the ground truth data collected from field surveys, in addition to databases, geo-databases and maps.
The study presented in Paper I used two filters to decrease speckle noise namely De-Grandi as multi-temporal speckle filter, and Lee as an adaptive filter. A multi-temporal classification method was used to identify the different crops using a pixel-based maximum likelihood classifier. The classification accuracy was assessed based on the external user accuracy for each crop, the external producer accuracy for each crop, the Kappa index and the external total accuracy for the entire classification. Three cropping pattern maps were produced namely the cropping pattern map of Wehninger Werder in 2011 and the cropping pattern maps of Walmsburger Werder in 2010 and in 2011. The study showed that image filtering was essential for enhancing the accuracy of crop classification. The multi-temporal filter De-Grandi enhanced the producer accuracy by about 10% compared to the Lee filter. Furthermore, gathering and utilizing large ground truth data greatly enhanced the accuracy of the classification. The research verified that using sequence images covering the growing season usually improved the classification results. The results exposed the effect of the polarization, where using VV-polarized data enabled on average 5% higher classification accuracy than the HH-polarized data, however using dual polarized data enhanced the classification accuracy by 3%. The study demonstrated that the majority of the classifications produced according to the crop calendar had higher total producer accuracy than using all acquisitions.
The study demonstrated undertaken in Paper II applied the decision tree object-based classifier in determining the major land uses and the inundation extent areas in 2011 and 2013 using the Lee-filtered imagery. Based on the maps produced for the land uses and inundation areas, the hazard areas due to the floods in 2011 and 2013 were identified. The study illustrated that 95% of the inundated area was classified correctly, that 90% of vegetated lands were accurately determined, and around 80% of the forest and the residential areas were correctly recognized. The study demonstrated that the residential areas did not experience any hazards in both pilot areas, however some cultivated lands were fully or partially submerged in 2011. These fields are in the high flood zone and therefore are expected to be entirely submerged during future high floods. Although, these fields were flooded in January 2011, they were cultivated with maize and potatoes in summer 2011 and in subsequent years and consequently were inundated in June 2013 with high economic losses to the owners of these fields.
The research undertaken in Paper III statistically analyzed the backscattering coefficient of the Lee-filtered TSX in some forest plots by the Factor Analysis and two sample Z-test. The study showed that Factor analysis tools succeeded in differentiating between the coniferous forest and the deciduous forest and mixed forest, but failed to discriminate between the deciduous and the mixed forest. On one hand, only one factor was extracted for each sample plot of the coniferous forest with approximately equal loadings during the whole acquisition period from March 2008 to January 2009. On the other hand, two factors were extracted for each deciduous or mixed forest sample plot, where one factor had high loadings during the leaf-on period from May to October, and the other one had high loadings during the leaf-off period from November to April. Furthermore, the research revealed that the two sample Z-test enabled not only differentiation between the deciduous and the mixed forest against the coniferous forest, but also discrimination between deciduous forest and the mixed forest. Statistically significant differences were observed between the mean backscatter values of the HH-polarized acquisitions for the deciduous forest and the mixed forest during the leaf-off period, but no statistically significant difference was found during the leaf-on period. Moreover, plot samples for the deciduous forest had slightly higher mean backscattering coefficients than those for the mixed forest during the leaf-off period.
Um das noch bestehende Reichweitenproblem von Elektrofahrzeugen zu lösen, sind Fahrzeugkonzepte wie Plug-in Hybridfahrzeuge sehr vielversprechend, sofern mit ihm überwiegend im Batteriebetrieb gefahren wird. Sie kombinieren die Vorteile des Verbrennungsmotors und des Elektromotors, sodass das lokale Emissionsproblem in Ballungszentren gelöst werden kann, ohne dass der Kunde dabei auf die Reichweite verzichten muss. Wenn das Fahrzeug allerdings überwiegend für Kurzstrecken genutzt wird, sind alterungsbedingte Veränderungen des Kraftstoffes möglich, da dieser länger im Tank verbleibt als üblich.
In dieser Arbeit wird ein Konzept zur sensorischen Bestimmung der Qualität des Kraftstoffes vorgestellt. Hierzu wurde ein Prototyp entwickelt, in dem mithilfe des Real- und Imaginärteils der Permittivität alternde Kraftstoffe erkannt werden können. Dabei konnte durch das frequenzabhängige Permittivitätssignal des Sensors spezifisch zwischen nieder- und hochmolekularen Oxidationsprodukten in Kraftstoffen unterschieden werden.
Da das Verbrennungs- und Emissionsverhalten des Motors von der Kraftstoffmischung vorgegeben ist, bietet eine zusätzliche sensorische Erfassung der Kraftstoffzusammensetzung weitere Optimierungspotenziale, um Emissionen zu reduzieren: So ist das Motormanagement im Fahrzeug zumeist auf Referenzkraftstoffe mit gleichbleibender Qualität abgestimmt. Variable Kraftstoffzusammensetzungen, die durch die Erdöllagerstätte und den zusätzlichen Konversionsverfahren zur Herstellung von fortschrittlichen Kraftstoffen vorgegeben sind, werden in dieser Anpassungsstrategie bisher nicht berücksichtigt. Als weitere Aufgabe wird in dieser Arbeit daher ein multisensorischer Ansatz verfolgt, wonach zusätzlich zur Kraftstoffalterung noch die Kraftstoffzusammensetzung erkannt werden kann.
Insgesamt bietet die Sensorik das Potenzial zur kontinuierlichen Kraftstoffüberwachung in Plug-in Hybridfahrzeugen, um so einen Beitrag zum sicheren und nachhaltigen Betrieb solcher Fahrzeuge gewährleisten zu können.
Climate change and atmospheric deposition of nitrogen affect biodiversity patterns and functions of forest ecosystems worldwide. Many studies have quantified tree growth responses to single global change drivers, but less is known about the interaction effects of these drivers at the plant and ecosystem level. In the present study, we conducted a full-factorial greenhouse experiment to analyse single and combined effects of nitrogen fertilization (N treatment) and drought (D treatment) on 16 morphological and chemical response variables (including tissue δ13C signatures) of one-year-old Fagus sylvatica seedlings originating from eight different seed families from the Cantabrian Mountains (NW Spain). Drought exerted the strongest effect on response variables, reflected by decreasing biomass production and increasing tissue δ13C signatures. However, D and N treatments interacted for some of the response variables, indicating that N fertilization has the potential to strengthen the negative effects of drought (with both antagonistic and amplifying interactions). For example, combined effects of N and D treatments caused a sevenfold increase of necrotic leaf biomass. We hypothesize that increasing drought sensitivity was mainly attributable to a significant reduction of the root biomass in combined N and D treatments, limiting the plants’ capability to satisfy their water demands. Significant seed family effects and interactions of seed family with N and D treatments across response variables suggest a high within-population genetic variability. In conclusion, our findings indicated a high drought sensitivity of Cantabrian beech populations, but also interaction effects of N and D on growth responses of beech seedlings.
Urban areas are prone to climate change impacts. Simultaneously the world’s population increasingly resides in cities. In this light, there is a growing need to equip urban decision makers with evidence-based climate information tailored to their specific context, to adequately adapt to and prepare for future climate change.
To construct climate information high-resolution regional climate models and their projections are pivotal, to provide a better understanding of the unique urban climate and its evolution under climate change. There is a need to move beyond commonly investigated variables, such as temperature and precipitation, to cover a wider breath of possible climate impacts. In this light, the research presented in this thesis is centered around enhancing the understanding about regional-to-local climate change in Berlin and its surroundings, with a focus on humidity. More specifically, following a regional climate modelling and data analysis approach, this research aims to understand the potential of regional climate models, and the possible added value of convection-permitting simulations, to support the development of high-quality climate information for urban regions, to support knowledge-based decision-making.
The first part of the thesis investigates what can already be understood with available regional climate model simulations about future climate change in Berlin and its surroundings, particularly with respect to humidity and related variables. Ten EURO-CORDEX model combinations are analyzed, for the RCP8.5 emission scenario during the time period 1970 ̶ 2100, for the Berlin region. The results are the first to show an urban-rural humidity contrast under a changing climate, simulated by the EURO-CORDEX ensemble, of around 6 % relative humidity, and a robust enlarging urban drying effect, of approximately 2 ̶ 4 % relative humidity, in Berlin compared to its surroundings throughout the 21st century.
The second part explores how crossing spatial scales from 12.5 km to 3 km model grid size affects unprecedented humidity extremes and related variables under future climate conditions for Berlin and its surroundings. Based on the unique HAPPI regional climate model dataset, two unprecedented humidity extremes are identified happening under 1.5 °C and 2 °C global mean warming, respectively SH>0.02 kg/kg and RH<30 %. Employing a double-nesting approach, specifically designed for this study, the two humidity extremes are downscaled to the 12.5 km grid resolution with the regional climate model REMO, and thereafter to the 3 km with the convection-permitting model version of REMO (REMO NH). The findings indicate that the convection-permitting scale mitigates the SH>0.02 kg/kg moist extreme and intensifies the RH<30 % dry extreme. The multi-variate process analysis shows that the more profound urban drying effect on the convection-permitting resolution is mainly due to better resolving the physical processes related to the land surface scheme and land-atmosphere interactions on the 3 km compared to the 12.5 km grid resolution. The results demonstrate the added value of the convection-permitting resolution to simulate future humidity extremes in the urban-rural context.
The third part of the research investigates the added value of convection-permitting models to simulate humidity related meteorological conditions driving specific climate change impacts, for the Berlin region. Three novel humidity related impact cases are defined for this research: influenza spread and survival; ragweed pollen dispersion; and in-door mold growth. Simulations by the regional climate model REMO are analyzed for the near future (2041 ̶ 2050) under emission scenario RCP8.5, on the 12.5 km and 3 km grid resolution. The findings show that the change signal reverses on the convection-permitting resolution for the impact cases pollen, and mold (positive and negative). For influenza, the convection-permitting resolution intensifies the decrease of influenza days under climate change. Longer periods of consecutive influenza and mold days are projected under near-term climate change. The results show the potential of convection-permitting simulations to generate improved information about climate change impacts in urban regions to support decision makers.
Generally, all results show an urban drying effect in Berlin compared to its surroundings for relative and specific humidity under climate change, respectively for the urban-rural contrast throughout the 21st century, for the downscaled future extreme conditions, and for the three humidity related impact cases. Added value for the convection-permitting resolution is found to simulate humidity extremes and the meteorological conditions driving the three impacts cases.
The research makes novel contributions that advance science, through demonstrating the potential of regional climate models, and especially the added value of convection-permitting models, to understand urban rural humidity contrasts under climate change, supporting the development of knowledge-based climate information for urban regions.
