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Perennial energy crops (PECs) are increasingly used as feedstock to produce energy in an environmental friendly way. Compared to traditional conversion strategies like thermal use, sophisticated technologies such as biomethanation defined different re-quirements of the feedstock. Whereas the first concept relies on dry, woody mate-rial, biomethanation requires a moist feedstock. Thus, over time, the spectrum of species used as PECs has widened. Moreover, harvest dates were adjusted to pro-vide the feedstock at suitable moisture contents. It is well known that perennial, lignocellulose- based energy crops, compared to annual, sugar- and starch- based ones, offer ecological advantages such as, inter alia, improving biodiversity in landscape, protecting soil against erosion, and protecting groundwater from nutrient inputs. However, one of the main arguments for PEC cultivation was their undemanding nature concerning external inputs. With respect to the broader spectrum of PEC spe-cies and changed harvest dates, the question arises whether the concept of PECs being low- input energy crops is still valid. This also implies the question of suitable grow-ing conditions and sustainable management. The aims of this opinion paper were to classify different PECs according to their life- form strategy, compare nutrient exports when harvested in different maturation stages, and to discuss the results in the context of sustainable PEC cultivation on marginal land. This study revealed that nutrient exports with yield biomass of PECs harvested in green state are in the same range than those of annual energy crops and therewith several times higher than those of PECs harvested in brown state or of woody short rotation coppices. Thus, PECs can-not universally be claimed as low- input energy crops. These results also imply the consequences of cultivation of PECs on marginal land. Finally, the question has to be raised whether the term PECs should prospectively be better specified in written and spoken words.
The parameterization of the boundary layer is a challenge for regional climate models of the Arctic. In particular, the stable boundary layer (SBL) over Greenland, being the main driver for substantial katabatic winds over the slopes, is simulated differently by different regional climate models or using different parameterizations of the same model. However, verification data sets with high-resolution profiles of the katabatic wind are rare. In the present paper, detailed aircraft measurements of profiles in the katabatic wind and automatic weather station data during the experiment KABEG (Katabatic wind and boundary-layer front experiment around Greenland) in April and May 1997 are used for the verification of the regional climate model COSMO-CLM (CCLM) nested in ERA-Interim reanalyses. CCLM is used in a forecast mode for the whole Arctic with 15 km resolution and is run in the standard configuration of SBL parameterization and with modified SBL parameterization. In the modified version, turbulent kinetic energy (TKE) production and the transfer coefficients for turbulent fluxes in the SBL are reduced, leading to higher stability of the SBL. This leads to a more realistic representation of the daily temperature cycle and of the SBL structure in terms of temperature and wind profiles for the lowest 200 m.
Roof and wall slates are fine-grained rocks with slaty cleavage, and it is often difficult to determine their mineral composition. A new norm mineral calculation called slatecalculation allows the determination of a virtual mineral composition based on full chemical analysis, including the amounts of carbon dioxide (CO2), carbon (C), and sulfur (S). Derived norm minerals include feldspars, carbonates, micas, hydro-micas, chlorites, ore-minerals, and quartz. The mineral components of the slate are assessed with superior accuracy compared to the petrographic analysis based on the European Standard EN 12326. The inevitable methodical inaccuracies in the calculations are limited and transparent. In the present paper, slates, shales, and phyllites from worldwide occurrences were examined. This also gives an overview of the rocks used for discontinuous roofing and external cladding.
The nonhydrostatic regional climate model CCLM was used for a long-term hindcast run (2002–2016) for the Weddell Sea region with resolutions of 15 and 5 km and two different turbulence parametrizations. CCLM was nested in ERA-Interim data and used in forecast mode (suite of consecutive 30 h long simulations with 6 h spin-up). We prescribed the sea ice concentration from satellite data and used a thermodynamic sea ice model. The performance of the model was evaluated in terms of temperature and wind using data from Antarctic stations, automatic weather stations (AWSs), an operational forecast model and reanalyses data, and lidar wind profiles. For the reference run we found a warm bias for the near-surface temperature over the Antarctic Plateau. This bias was removed in the second run by adjusting the turbulence parametrization, which results in a more realistic representation of the surface inversion over the plateau but resulted in a negative bias for some coastal regions. A comparison with measurements over the sea ice of the Weddell Sea by three AWS buoys for 1 year showed small biases for temperature around ±1 K and for wind speed of 1 m s−1. Comparisons of radio soundings showed a model bias around 0 and a RMSE of 1–2 K for temperature and 3–4 m s−1 for wind speed. The comparison of CCLM simulations at resolutions down to 1 km with wind data from Doppler lidar measurements during December 2015 and January 2016 yielded almost no bias in wind speed and a RMSE of ca. 2 m s−1. Overall CCLM shows a good representation of temperature and wind for the Weddell Sea region. Based on these encouraging results, CCLM at high resolution will be used for the investigation of the regional climate in the Antarctic and atmosphere–ice–ocean interactions processes in a forthcoming study.
Der vorliegende Bericht gibt einen Überblick zu den wichtigsten Faktoren, welche durch ihre Interaktionen die Vulnerabilität des Weinbaus an der Mittelmosel vor dem Hintergrund des Klimawandels bestimmen. Hierbei steht die im Projekt Mosel-AdapTiV kooperierende Kommune Traben-Trarbach exemplarisch für eine Vielzahl von Weinbauorten im Untersuchungsgebiet. Neben den direkten klimawandelinduzierten Auswirkungen im Weinbau wird ein besonderer Fokus auf den regionalspezifischen Kontext der Mittelmosel gelegt. Die sich aus dieser Betrachtung ergebenden sozioökonomischen, politisch-administrativen und kulturellen Faktoren der „kontextuellen Vulnerabilität“ werden identifiziert und hinsichtlich ihrer Wirkung auf Problembewusstsein, regionale Anpassungskapazitäten und konkretes Anpassungshandeln bewertet.
Die vorliegende Analyse kontextueller Vulnerabilität des Weinbausektors an der Mittelmosel zeigt, dass trotz eines ausgeprägten Problembewusstseins gegenüber Klimawandelfolgen eine Vielzahl regionalspezifischer Faktoren die Anpassungskapazitäten der Akteur*innen begrenzen. Als konkrete Faktoren sind die traditionellen Betriebsformen vor dem Hintergrund des fortschreitenden Strukturwandels, eine stetige Erweiterung des Aufgabenspektrums der Winzer*innen, die Abhängigkeit von Riesling als regionale Leitsorte sowie die fehlende finanzielle Ausstattung der Kommunen, die Möglichkeiten für eine transformative Anpassungspolitik eingrenzen zu nennen. Aus dem Zusammenspiel dieser unterschiedlichen Faktoren ergeben sich nur gering ausgeprägte kommunale und lokale Anpassungskapazitäten.
Empirisch basiert der Bericht auf einer Auswertung relevanter Literatur, verschiedener Datenquellen sowie mehreren qualitativen Interviews mit Akteur*innen vor Ort. Ebenfalls baut er auf den Ergebnissen eines Lehrforschungsprojekts der Universität Trier aus den Jahren 2016/17 auf (Bruns, 2020).
For grape canopy pixels captured by an unmanned aerial vehicle (UAV) tilt-mounted RedEdge-M multispectral sensor in a sloped vineyard, an in situ Walthall model can be established with purely image-based methods. This was derived from RedEdge-M directional reflectance and a vineyard 3D surface model generated from the same imagery. The model was used to correct the angular effects in the reflectance images to form normalized difference vegetation index (NDVI)orthomosaics of different view angles. The results showed that the effect could be corrected to a certain scope, but not completely. There are three drawbacks that might restrict a successful angular model construction and correction: (1) the observable micro shadow variation on the canopy enabled by the high resolution; (2) the complexity of vine canopies that causes an inconsistency between reflectance and canopy geometry, including effects such as micro shadows and near-infrared (NIR) additive effects; and (3) the resolution limit of a 3D model to represent the accurate real-world optical geometry. The conclusion is that grape canopies might be too inhomogeneous for the tested method to perform the angular correction in high quality.
In order to discuss potential sustainability issues of expanding silage maize cultivation in Rhineland-Palatinate, spatially explicit monitoring is necessary. Publicly available statistical records are often not a sufficient basis for extensive research, especially on soil health, where risk factors like erosion and compaction depend on variables that are specific to every site, and hard to generalize for larger administrative aggregates. The focus of this study is to apply established classification algorithms to estimate maize abundance for each independent pixel, while at the same time accounting for their spatial relationship. Therefore, two ways to incorporate spatial autocorrelation of neighboring pixels are combined with three different classification models. The performance of each of these modeling approaches is analyzed and discussed. Finally, one prediction approach is applied to the imagery, and the overall predicted acreage is compared to publicly available data. We were able to show that Support Vector Machine (SVM) classification and Random Forests (RF) were able to distinguish maize pixels reliably, with kappa values well above 0.9 in most cases. The Generalized Linear Model (GLM) performed substantially worse. Furthermore, Regression Kriging (RK) as an approach to integrate spatial autocorrelation into the prediction model is not suitable in use cases with millions of sparsely clustered training pixels. Gaussian Blur is able to improve predictions slightly in these cases, but it is possible that this is only because it smoothes out impurities of the reference data. The overall prediction with RF classification combined with Gaussian Blur performed well, with out of bag error rates of 0.5% in 2009 and 1.3% in 2016. Despite the low error rates, there is a discrepancy between the predicted acreage and the official records, which is 20% in 2009 and 27% in 2016.
Kartenschätze aus Italien
(2018)
Die Entdeckungen der Neuzeit sowie verbesserte Druckverfahren führten ab dem 16. Jahrhundert zu einem enormen Aufschwung der Kartographie. Gerade in Italien entstanden blühende kartographische Zentren mit exzellentem Ruf, die innerhalb kurzer Zeit große Fortschritte hinsichtlich Genauigkeit und Übersichtlichkeit machten. Aus dem der Universitätsbibliothek Trier vermachten Nachlass des Kartensammlers Fritz Hellwig werden drei repräsentative Beispiele vorgestellt.
Diese Untersuchungen beinhalten eine Diskussion von Hintergründen, Konzepten und Herausforderungen der aktuellen Qualitätsdiskussion im tertiären Tourismusbildungs-system des südlichen Afrikas. Dabei werden Fragen wie: "Welche Aspekte haben in diesen Ländern zu einer verstärkten Fokussierung auf Qualität geführt?", "Inwieweit lassen sich Erkenntnisse zu Qualitätsentwicklungen aus westlichen Industrienationen auf afrikanische Länder wie z.B. Namibia übertragen?", als auch "Welche Qualitätskriterien werden in der tertiären namibischen Tourismusbildungsinstitutionen als wichtig erachtet?" diskutiert. In diesen Untersuchungen wird diskursiv aufgezeigt, dass sich in vielen Ländern des südlichen Afrikas aufgrund rechtlicher Rahmenbedingungen in der tertiären Tourismus-bildung unterschiedliche Qualitätsansätze etablieren konnten. Eine fundierte Analyse der stark wachsenden Tourismusdestination Namibia als ausgewählte Fallstudie dient dabei als Basis zur Erarbeitung eines spezifischen Qualitätsinstruments. Neben einer Analyse der bestehende Situation versuchen diese vorliegenden Untersuchungen, einen konstruktiven Beitrag zur Qualtätsentwicklung in der namibischen tertiären Tourismusbildung zu liefern. So steht denn auch als Ziel die Erarbeitung eines namibiaspezifischen Qualitätsinstrumentes im Mittelpunkt des Interesses. Zu dessen Entwicklung wird als zentrale Methode eine angepasste Form des Delphi-Verfahrens angewendet, bei welchem eine breite Anzahl relevanter Stakeholder der namibischen tertiären Tourismusbildung eingebunden ist.