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Dissertation
Advanced oxidation of fluoroquinolone antibiotics in water by heterogeneous photocatalysis
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ISBN: 9789059897021 Year: 2014 Publisher: Ghent : Ghent University,

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Der Boden- und Deckschichtenkörper und seine Schutzfunktion für das oberflächennahe Grundwaser in der niedersächsischen Altmoränenlandschaft : beispielhaft untersucht am Einzugsgebiet des Wasserwerkes Haselünne-Stadtwald (Emsland)
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ISBN: 3936616094 9783936616095 Year: 2003 Publisher: Hannover Universität Hannover. Institut für Landschaftspflege und Naturschutz

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Dissertation
Modeling land-atmosphere interactions in tropical Africa : the climatic impact of deforestation in the Congo Basin
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ISBN: 9789086496709 Year: 2013 Publisher: Leuven Katholieke Universiteit Leuven

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The demand foragricultural land in the Congo basin is expected to yield substantialdeforestation over the coming decades. In addition to thebiogeochemical impact (release of carbon stocks), forest removalaffects the surface energy and moisture balance, and consequently theregional climate. Climate sensitivity to these biogeophysicalprocesses has been modeled during the past few decades usingcoarse-scale global climate models. Although useful as “thoughtexperiments” which yielded insight in the climatic impact ofdeforestation, such studies cannot be considered as realisticprojections for the coming decades, since they are all based on theassumption of total, basin-wide forest removal with furthermore acompletely homogeneous conversion to e.g. bare soil or pasture.Recently, the focus of numerical impact studies has been shiftedsteadily towards more detailed future projections which are oftenregionally investigated. There is, however, still room forimprovement, most notably by implementing observed successionalvegetation in the deforestation scenario. Apart from that, recentdevelopments aiming at more physical realism remain scattered amongdifferent modeling studies and research groups, and are rarelycombined.The overallobjective of this dissertation is to quantify and understand regionalclimatic impact of future deforestation in the Congo Basin, takinginto account several improvements required to achieve more realism.For this purpose, we use the COSMO-CLM regional climate model andprescribe a high-resolution spatially-explicit scenario of futureforest removal for this particular region. Model integrations areperformed with a small-scale grid resolution of 0.22&#176; (~25km). Asopposed to assumptions such as a complete basin-wide conversion offorest to pasture or crops, the total amount of forest loss in thisstudy lies within the range of plausible estimates for deforestationin the next few decades. A state-of-the-art SVAT (soil vegetationatmosphere transfer) scheme is used, including detailed soil andvegetation input datasets and complex process parametrizations.Finally, the removed portion of primary forest is replaced by acombination of successional fallow vegetation types typical of theCongo Basin, based on field observations. It is the first time thatall these improvements are incorporated together. In addition we arethe first to introduce observed successional vegetation in our modelwhich is an important contributor to the overall improvement ofphysical realism.An extensiveevaluation of the model precedes the actual impact assessment andreveals good performance compared to in-situ and satelliteobservations. The model consists of an atmospheric part (COSMO-CLM)which is coupled to a SVAT scheme. First, two SVAT schemes are run instandalone mode (decoupled from the atmospheric model) and forcedwith meteorological in-situ measurements obtained at several tropicalAfrican sites. Model performance is quantified by comparing simulatedsensible and latent heat fluxes with eddy-covariance measurements.The simulations from Community Land Model correspond more closely tothe micrometeorological observations, reflecting the advantages ofthe higher model complexity and physical realism. The maindeficiencies identified in TERRA-ML consist of (i) a dry-seasonunderestimation of evapotranspiration, caused by erroneous defaultinput data (root depth) deviating largely from the actualregion-specific values (tropical evergreen forest), (ii)overestimations of both latent and sensible heat fluxes, caused byinaccurate leaf area index and albedo (which simply depend onhard-coded model constants), and (iii) an unrealistic fluxpartitioning caused by overestimated superficial water contents(improper parametrization of hydraulic conductivity). Community LandModel is by default more versatile in its global application ondifferent vegetation types and climates.Additionally, theSVAT schemes are tested by coupling them to COSMO-CLM. As expected,some biases of the TERRA-coupled model can be attributed toquestionable default values of input data, for instance root depth ofthe rainforest and albedo of desert sand. The implementation of amore realistic set of input parameters (EcoClimap) causes even worsesimulations in many cases, indicating a wrong model tuning. Theresults of the stand-alone validation already indicated bettersimulations of the Community Land Model compared to TERRA-ML. Thecoupled model validation now confirms the beneficial effects of usingCommunity Land Model, as it indeed also delivers the best coupledmodel results corresponding well with the observations. Hence, basedon its superior performance, the model coupled to Community LandModel is selected to perform the long-term present-day and futureclimate simulations. In one of these future simulations, the default(reference) vegetation map within the model is perturbed by adeforestation scenario. Therefore, an existing spatially-explicitdeforestation scenario is fine-tuned to match currently observeddeforestation rates, and complemented by typical successionalvegetation as observed in the Congo Basin.Successional landcover types are identified and their areal proportions are quantifiedin regions deforested during the past 37 years around the city ofKisangani, D.R.Congo. The fallow vegetation continuum is categorizedin different stages, adapted from existing classifications. Groundtruth points describing the present-day vegetation are obtainedduring a field campaign and used for supervised and validated landcover classification of these categories, using the Landsat image of2012. Areal proportions of successional land cover types are thenderived from the resulting land cover map. To illustrate the use ofthese results, the relative areal proportions are used to re-fine adeforestation scenario and apply it on existing datasets of LAI andcanopy height. Assuming a simple conversion of forest to cropland,the deforestation scenario projected a reduction ofgrid-cell-averaged canopy height from 25.5m to 7.5m (withindeforested cells), whereas the re-fined scenarios that we proposeshow more subtle changes with a reduced canopy height of 13m. Thisillustrates the importance of taking successional land covercorrectly into account in environmental and climatological modelingstudies. In our impactassessment we compared the different model simulations to each other.Differences in average climatology between present-day/future andreference/deforested simulations quantify the long-term impact offuture greenhouse gases and deforestation on the regional climate.Model integrations indicate that the deforestation, expected for themiddle of the 21th century, induces a warming of about 0.7&#176;C. Thisis about half the greenhouse gas-induced surface warming in thisregion, given an intermediate forcing (A1B) with COSMO-CLM driven bythe ECHAM5 global climate model. This shows the necessity of takinginto account deforestation to obtain realistic future climateprojections. The deforestation-induced warming can be attributed toreduced evapotranspiration, but this effect is mitigated by increasedalbedo and increased sensible heat loss to the atmosphere.Precipitation is also affected: As a consequence of surface warmingdue to deforestation, a regional heat low develops above therainforest region. Resulting low-level convergence causes aredistribution of moisture in the boundary layer and a stabilizationof the atmospheric column, thereby reducing convection intensity andhence precipitation by 5 to 10% in the heat low region.


Dissertation
A generic software framework for modelling and virtual experimentation with complex environmental systems
Author:
ISBN: 9789059892231 Year: 2008 Publisher: Gent : Universiteit Gent. Faculteit bio-ingenieurswetenschappen,


Dissertation
Sustainable materialisation of residues from thermal processes into construction materials : construction materials from stainless steel slags
Authors: ---
ISBN: 9789460188602 Year: 2014 Publisher: Leuven Katholieke Universiteit Leuven

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The amount of slag generated is almost athird of the total stainless steel produced. Owing to its mineralogy, a large partof the slag is produced as fines, which has a very low valorisation potentialand has to be landfilled. The present work is aimed at exploring the potentialof these slags to produce construction materials of higher economic value.To address the issue, two valorisationroutes were applied: 1) alkali-activation initiating binding reactions in theslag by the addition of alkali hydroxides and silicates, 2) carbonation initiating hardening reaction in the slag by the formation of alkalicarbonates. Two stainless steel slags, continuous casting (CtCs) slag and Argonoxygen decarburisation (AOD) slag, were targeted for valorisation.Initiation of hardening reactions in theslag was found to occur only under a combined treatment of alkali (Na and K)hydroxides and high temperature (80 &#176;C) which was provided by steam curing. However,only a moderate strength in the mortar specimens was observed under suchconditions along with appearance of efflorescence with NaOH for molaritiesabove 5 M. The problem of low strength and efflorescence in the mortar sampleswas eliminated by the introduction of silicates in the system along with thealkali hydroxides. The compressive strength of the slag mortars was found toincrease with the increase in the amount of silicates in the activatingsolution and with the increase of the curing temperature. The reaction productfrom the activation was found to be C-S-H as confirmed by thermogravimetric,QXRD, FTIR and 29Si NMR analysis.The slag was also found to develop strengthunder acceleration carbonation conditions which was provided under two environments:i) in a carbonation chamber, maintained at atmospheric pressure, 22 &#176;C, 5 vol.%CO2 and 80% RH; and ii) in a carbonation reactor, where the CO2partial pressure (pCO2)and temperature could be further increased. It was found that in thecarbonation chamber the compressive strength of the samples and the CO2sequestration continued to increase up to 3 weeks whereas in the reactor theoptimum for strength and CO2 sequestration was found at 80 &#176;C, 8 barpressure in 2.5 h. The major reaction product was found to be calcite indifferent morphologies.Three types of masonry blocks were preparedform the slag with the two valorisation routes: alkali-activated solid bricks,perforated carbonated bricks and alkali-activated aerated bricks. Thecarbonated bricks were found to have the best resistance to freeze-thaw,whereas the aerated bricks were found to have superior thermal resistivity values.The LCA showed that the environmental impact of the bricks is lower (negativefor carbonated bricks) than the conventional clay fired bricks and the impactof the aerated bricks was found to be similar to the conventional aeratedblocks available in the market. A SWOTanalysis highlighted the advantage of using these bricks in the form of lowerenergy requirement in its production, reduction of stress on the use of prime materialsand ease of metal recovery from the residual slag.The results of the dissertation show that thebinding potential of the stainless steel slags can be exploited as valorisedapplications in the construction industry by novel thermo-alkali activation andcarbonation processes.


Dissertation
Detection and analysis of forest cover dynamics with Landsat satellite imagery : application in the Romanian Carpathian Ecoregion
Authors: ---
ISBN: 9789086496976 Year: 2014 Publisher: Leuven Katholieke Universiteit Leuven

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Forest cover changes have essential implications on a variety of landscape functions and their associated ecosystem services. Globally, contrasting forest trends are present: some countries are greening, while others are still in a deforestation phase. The detection and mapping of forest dynamics is rather challenging since landscapes in the transition phase typically consist of patchy structures and often occur in inaccessible areas such as highlands, which impedes mapping approaches based on fieldwork. Furthermore, forest cover changes in the turnover phase are characterized by subtle up- and downward trends. Remote sensing techniques seem to be adequate tools for the analysis of forest cover changes in mountain areas. Over the past half century, remote sensing imagery has been acquired by a range of multispectral and hyperspectral sensors. Many regional long-term vegetation (change) maps have been derived from medium to low resolution imagery such as the Landsat sensor with a spatial resolution of 30m. Despite recent developments, remote sensing methods for the detection and analysis of forest cover dynamics at regional scale still suffer from methodological challenges: (1) recorded reflectance values are disturbed by atmospheric effects, (2) differences between illuminated and shadowed slopes occur in mountain areas, and (3) regional scale analyses require that multiple images are mosaicked to construct homogeneous image composites. During the last decades, a range of simple empirical and more advanced physically-based preprocessing techniques has been developed to solve these problems. At present, however, it is not clear what the added value of these techniques is for the detection of regional scale forest cover change. The main objective of this PhD research was to evaluate, compare and improve the methods for regional scale detection and analysis of forest cover dynamics. The Romanian Carpathians Mountains, which are characterized by significant forest cover dynamics related to a land decollectivization process were selected as the study area. In order to address the main objective of this thesis, the following specific research questions were formulated: 1. To what extent do available atmospheric and topographic correction techniques improve the land surface reflectance values derived from medium resolution imagery in mountain areas? Do complex physically-based methods perform better than simplified empirical approaches? 2. Does image preprocessing improve land cover classification? 3. Does topographic correction and pixel-based compositing improve large area (change) mapping? 4. What is the pattern and what are the controlling factors of forest cover changes in the Romanian Carpathians? This first research question was addressed by comparing the results of 15 combinations of atmospheric and topographic correction methods. The analyses were performed on a Landsat footprint in the Romanian Carpathian mountains. First, results showed a reduction of the differences between average illuminated and shaded reflectance values after correction. Significant improvements were found for methods with a pixel-based Minnaert (PBM) or a pixel-based C (PBC) topographic correction. Secondly, the analysis of the coefficients of variation showed that the homogeneity for selected forest pixels increased after correction. Finally, the dependency of reflectance values on terrain illumination was reduced after implementation of an atmospheric correction combined with a PBM or PBC correction. Considering overall results, this analysis showed that the most advanced corrections methods produced the most accurate results, but these methods were also the most difficult to automate in a processing chains. Furthermore, the added value of advanced topographic methods was found to be high, while the added value of advanced atmospheric methods was found to be rather limited. In order to address the second research question, all preprocessed imageres (15 combinations) were used as an input for a Maximum Likelihood (ML) land cover classification. The resulting land cover maps, showing e.g. urban area, arable land, grassland, coniferous, broadleaved and mixed forest, were validated by comparison with field observations. Validation results showed that the land cover maps derived from preprocessed images were more accurate than the land cover maps derived from the unpreprocessed images. Furthermore, it was found that class accuracies of especially the coniferous and mixed forest classes were enhanced after correction. Moreover, combined correction methods appeared to be the most efficient on weakly illuminated slopes (cos ß &#8804; 0.65). Considering all results, the best overall classification results were achieved after the application of the combination of an atmospheric correction method based on transmittance functionsand a PBM or PBC topographic correction. Results of this study also indicated that the topographic component had a higher influence on classification accuracy than the atmospheric component. Thethird research question was addressed by the application of a pixel-based compositing algorithm developed by Griffiths et al. (2013b). Composites were developed with 3 degrees of freedom: (1) the classifier (Maximum Likelihood or Support Vector Machine, SVM), (2) number of delineated land cover classes (4 or 8), and (3) the topographic correction (uncorrected or corrected). Land cover maps were produced for the years 1985, 1995 and 2010. The accuracy of the resulting land cover maps was evaluated by comparing the classified land cover with references data collected by field observation or visual inspection of very high resolution imagery. The map validation showed that the SVM classifier resulted in a more accurate land cover classification than the ML classifier. Preprocessing increased the accuracy of the classification even more, but its impact showed to be less important than the selection of the classifier. The overall accuracy of the maps depicting 8 land cover classes was between 66% and 82% for all years. The classification accuracywas further increased by lowering the number of land cover classes. The highest overall accuracies were found for the maps with 4 land cover classed based on preprocessed imagery using a SVM classifier: respectively 85% (1985), 83% (1995) and 91% (2010). By comparing the maps of 1985, 1995 and 2010, land cover change could be detected. Both afforestation and deforestation patterns were detected but it was concluded that overall the Romanian Carpathians were gradually greening between 1985 and 2010 since the first process was dominant. In a final step, an attempt was done to detect the controlling factors of the forest cover dynamics between 1985-1995 and 1995-2010. Therefore, multiple logistic regression models were calibrated in which accessibility, demographic evolution, land use policy and biophysical characteristics were linked with the observed deforestation and afforestation patterns. The results showed that both deforestation and afforestation were more likely to occur at high elevations, but far from nearby secondary roads. No correlation could be found between population change at the level of communes and forest cover dynamics.

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