Der Einfluss des Biofilms, der Inkrustation, der Fließgeschwindigkeit und der Wasserqualität auf die Freisetzung von PAK wurde in Batch-, Drehkolbenreaktorversuchen und an einem Rohrleitungssystem untersucht. Chlorung von tauchgeteerten Edelstahlcoupons mit Biofilm führten zu einer fast vollständigen Ablösung des Biofilms und einer Zunahme der Freisetzung von Fluoren, Phenanthren und Fluoranthen. Die PAK-Freisetzung von tauchgeteerten Edelstahlcou-pons in einer Lösung von Trinkwasser mit 0,1% Natriumazid als Hemmstoff der Atmungskette, der den Biofilm nicht ablöst, führten zu einer Zunahme aller untersuchten PAK in der gleichen Größenordnung wie ohne Bio-film. In chloriertem Teerleachat wurden unter der teilweisen Anwendung einer einfachen Methode der kontinu-ierlichen Extraktion folgende PAK-Derivate analysiert: Chloracenaphthen, 1-Chlorpyren, 9-Fluorenon, Anthron. Da Reaktionsprodukte von Phenanthren und Fluoranthen nicht gefunden werden konnten, wird eine Weiterreaktion zu 9-Fluorenon vorgeschlagen, die durch die Pechoberfläche katalysiert wird. Instationäre Korrosion und nicht vorhandener aerober Abbau sind die Gründe für eine PAK-Zunahme während Stagnationphasen. / The influence of biofilm, encrustation, flow velocity and water quality on the release of PAHs was investigated in batch, continuously flown reactor experiments and in a pipe rig system. Chlorination of coal-tar coated stainless steel slides with biofilm resulted in an almost complete removal of the biofilm and an increase of the release of fluorene, phenanthrene and fluoranthene. PAH release of coal-tar coated stainless steel slides exposed to a solution of drinking water with 0,1% sodium azide as an inhibitor of the respiratory chain which did not remove the biofilm led to an increase of all observed PAHs up to the same magnitude as without biofilm. In chlorinated coal-tar leachate the following derivatives were detected while partly utilizing an easy method for a continuously extrac-tion: chloroacenaphthene, 1-chloropyrene, 9-fluorenone, anthrone. While reaction products of phenanthrene and fluoranthene could not be found a further reaction to 9-fluorenone catalysed by the coal-tar surface is proposed. Instationary corrosion and no aerobic degradation are the reasons for PAH increase during stagnation periods.

Current global agricultural practices are recognized as unsustainable. The increase in overall human population as well as the global trend of rural to urban migration, partially as a result of historically and continual unsustainable agricultural practices, exacerbates the vicious cycle of poverty and hunger in developing countries. Furthermore, cities and regions in developed countries practice unsustainable food production, distribution and consumption patterns, and as a result, exceed their global ecological footprint (Rees 2009). Consequently, the world is facing a global food (FAO 2009) and water crisis (UN Sick Water 2010). Cities and Regions must learn to feed themselves to address local food insecurity as well as protect from the climate effects of increased urbanization, including the Urban Heat Island effect (UHIe) by optimizing and fully integrating the local ecosystem services of food, water and forest within a tightly woven compact urban form through the implementation of strategic urban and regional food system planning. Cities can mitigate climate change and reduce the UHIe, by implementing sustainable intensive urban agriculture approaches through policy and zoning interventions that include concepts such as intensively productive urban agriculture that includes green roofs, vertical farming and greenways as continuously productive and edible urban landscapes, referred to in this paper as continuously productive urban agriculture and forestation (CPUAF) in the private and public realm. A highly participative, adaptive systems approach is explored as the key to sustainability within an economic world order that included corporate social responsibility and social enterprise as the foundation for the integration of multiple synergies. An increasing body of evidence often links urban forestation with urban greenery initiatives, as a carbon sink to reduce UHI effects, to reduce GHG emissions and as a tool for urban beautification and place making (ISDR: 2009,109). Urban agriculture, through the production of local food is increasingly recognized as a means to reduce fossil fuel emissions by reducing transportation and production outputs, to provide a secure local food source, enhance biodiversity and educate the public regarding food source while fostering a sense of community, environmental awareness and stewardship. This thesis explores the links between intensive urban agriculture and forestation, and the relationship between climate change, and the UHI’s as an adaptation and mitigation process in global cities, implemented as a interconnected, integrated, holistic urban management approach that has a further benefit of providing food security and a sustainable and local urban food source. / Dissertation (MTRP)--University of Pretoria, 2012. / Town and Regional Planning / unrestricted

Visual place recognition is the task of finding same places in a set of database images for a given set of query images. This becomes particularly challenging for long-term applications when the environmental condition changes between or within the database and query set, e.g., from day to night. Visual place recognition in changing environments can be used if global position data like GPS is not available or very inaccurate, or for redundancy. It is required for tasks like loop closure detection in SLAM, candidate selection for global localization, or multi-robot/multi-session mapping and map merging. In contrast to pure image retrieval, visual place recognition can often build upon additional information and data for improvements in performance, runtime, or memory usage. This includes additional data-inherent knowledge about information that is contained in the image sets themselves because of the way they were recorded. Using data-inherent knowledge avoids the dependency on other sensors, which increases the generality of methods for an integration into many existing place recognition pipelines. This thesis focuses on the usage of additional data-inherent knowledge. After the discussion of basics about visual place recognition, the thesis gives a systematic overview of existing data-inherent knowledge and corresponding methods. Subsequently, the thesis concentrates on a deeper consideration and exploitation of four different types of additional data-inherent knowledge. This includes 1) sequences, i.e., the database and query set are recorded as spatio-temporal sequences so that consecutive images are also adjacent in the world, 2) knowledge of whether the environmental conditions within the database and query set are constant or continuously changing, 3) intra-database similarities between the database images, and 4) intra-query similarities between the query images. Except for sequences, all types have received only little attention in the literature so far. For the exploitation of knowledge about constant conditions within the database and query set (e.g., database: summer, query: winter), the thesis evaluates different descriptor standardization techniques. For the alternative scenario of continuous condition changes (e.g., database: sunny to rainy, query: sunny to cloudy), the thesis first investigates the qualitative and quantitative impact on the performance of image descriptors. It then proposes and evaluates four unsupervised learning methods, including our novel clustering-based descriptor standardization method K-STD and three PCA-based methods from the literature. To address the high computational effort of descriptor comparisons during place recognition, our novel method EPR for efficient place recognition is proposed. Given a query descriptor, EPR uses sequence information and intra-database similarities to identify nearly all matching descriptors in the database. For a structured combination of several sources of additional knowledge in a single graph, the thesis presents our novel graphical framework for place recognition. After the minimization of the graph's error with our proposed ICM-based optimization, the place recognition performance can be significantly improved. For an extensive experimental evaluation of all methods in this thesis and beyond, a benchmark for visual place recognition in changing environments is presented, which is composed of six datasets with thirty sequence combinations.