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Abstract For Solid Oxide Fuel Cells (SOFCs) to become an economically attractive energy conversion technology, suitable materials and structures which enable operation at lower temperatures, while retaining high cell performance, must be developed. Recently, the perovskite-type La 0.6 Ca 0.4 Fe 0.8 Ni 0.2 O 3 oxide has shown potential as an intermediate temperature SOFC cathode. An equivalent circuit describing the cathode polarization resistances was constructed from analyzing impedance spectra recorded at different temperatures in oxygen. A competitive electrode polarization resistance is reported for this oxygen electrode using a Ce 0.8 Gd 0.2 O 1.9 electrolyte, determined by impedance spectroscopy studies of symmetrical cells sintered at 800 °C and 1000 °C. Scanning electron microscopy (SEM) studies of the symmetrical cells revealed the absence of any reaction layer between cathode and electrolyte, and a porous electrode microstructure even when sintered at a temperature of only 800 °C. The performance of this cathode shows favorable oxygen reduction reaction (ORR) properties potentially making it an excellent choice for IT-SOFC application.

The assessment of greenhouse gases (GHGs) and air pollutants emitted to and removed from the atmosphere ranks high on international political and scientific agendas. Growing international concern and cooperation regarding the climate change problem have increased the need to consider the uncertainty in inventories of GHG emissions. The approaches to address uncertainty discussed in this special issue reflect attempts to improve national inventories, not only for their own sake but also from a wider, system analytic perspective. They seek to strengthen the usefulness of national emission inventories under a compliance and/or global monitoring and reporting framework. The papers in this special issue demonstrate the benefits of including inventory uncertainty in policy analyses. The issues raised by the authors and featured in their papers, along with the role that uncertainty analysis plays in many of their arguments, highlight the challenges and the importance of dealing with uncertainty. While the Intergovernmental Panel on Climate Change (IPCC) clearly stresses the value of conducting uncertainty analyses and offers guidance on executing them, the arguments made here in favor of performing these studies go well beyond any suggestions made by the IPCC to date. Improving and conducting uncertainty analyses are needed to develop a clear understanding and informed policy. Uncertainty matters and is key to many issues related to inventorying and reducing emissions. Considering uncertainty helps to avoid situations that can create a false sense of certainty or lead to invalid views of subsystems. Dealing proactively with uncertainty allows for the generation of useful knowledge that the international community should have to hand while strengthening the 2015 Paris Agreement, which had been agreed at the 21st Conference of the Parties to the United Nations Framework Convention on Climate Change (UNFCCC). However, considering uncertainty does not come free. Proper treatment of uncertainty is demanding because it forces us to take the step from “simple to complex” and to grasp a holistic system view. Only, thereafter, can we consider potential simplifications. That is, comprehensive treatment of uncertainty does not necessarily offer quick or easy solutions for policymakers. This special issue brings together 13 papers that resulted from the 2015 (4th) International Workshop on Uncertainty in Atmospheric Emissions, in Cracow, Poland. While they deal with many different aspects of the uncertainty in emission estimates, they are guided by the same principal question: “What GHGs shall be verified at what spatio-temporal scale to support conducive legislation at local and national scales, while ensuring effective governance at the global scale?” This question is at the heart of mitigation and adaptation. It requires an understanding of the entire system of GHG sources and sinks, their spatial characteristics and the temporal scales at which they react and interact, the uncertainty (accuracy and/or precision) with which fluxes can be measured, and last but not least, the consequences that follow from all of the aforementioned aspects, for policy actors to frame compliance and/or global monitoring and reporting agreements. This bigger system context serves as a reference for the papers in the special issue, irrespective of their spatio-temporal focus, and is used as a guide for the reader.

Temporary housing units (THUs), which are provided after disasters, are crucial in terms of sustainability pillars (economic, social, and environmental). In general, THUs, which are regular houses with minimum space and facilities, incorporate some negative aspects of the building industry. Additionally, as large numbers of THUs are usually provided in a short time and under emergency situations, some negative impacts of these units escalate. In this context, this study aims at reducing some negative impacts of THUs by applying a novel optimization model that maximises sustainability indexes by simulating the design of interior geometries for THUs. This method is based on the coupling of artificial intelligence and a multi-criteria decision-making model for sustainability assessment. The proposed model generates optimal solutions using a backtracking algorithm together with a binary search. To evaluate the sustainability indexes, an Integrated Value Model for Sustainability Assessment (MIVES) is applied. This novel method enables decision makers to automatically generate the most suitable alternative solutions for the early design stage of THUs. The results confirm that small changes in the interior geometric design can remarkably affect the sustainability indexes of THUs. The authors would like to acknowledge the kind support offered by professors and researchers from Shahid Beheshti University, Islamic Azad University, the Polytechnic University of Catalonia, and experts from the Housing Foundation of Islamic Republic of Iran (HFIR), who supported this paper for collecting and improving data. Additionally, the authors would like to thank UPC's Centre for Development Cooperation (CCD) for funding the authors (NO.: 2017-U006 and 2018-U012), which enabled the authors to follow and analyse the recovery program of Kermanshah earthquake. Peer Reviewed

The climate agenda in France and several other countries is a complex combination of unilateral commitments with regional and international objectives. When analyzing national policies, the findings of worldwide analyses are of limited accuracy and the large aggregates on which they are built level out most local specificities and inertia. Specific. assessments are hence needed. This paper quantifies the dynamic evolution of carbon values for French climate and energy policy. Its time dependency over successive periods and the effects of setting intermediate targets are evaluated using a long-term optimization model. Addressing critical issues for France, we produce consistent energy, emissions and carbon value estimates with a 5-year time step. Our results are situated above the upper range of carbon value estimates of world models with an overlapping zone. We show that the official policy guideline value is only consistent with an optimistic combination of assumptions. The central estimates are 4 times greater than the guideline carbon value for 2050 and up to 14 times greater in 2020 because of short-term inertia that are costly to move. We also find that with intermediate objectives, the carbon value's dynamic is more than a simple upward curve and that its variability is itself time dependent

The article presents analysis results in the reconstruction of the tectonic conditions dynamics for the formation of local plicative deformations and rupturing under conditions of the research both the macrostructure and its local separation using the example of the southwestern area of Kalmius-Toretska kettle-hole in the Donetsk basin. Authors applied the scientific cognition method, representing a sequence of actions to establish structural links between variables and constant elements of the Investigational tectonic system, based on statistical and mathematical methods of analysis. The characteristics of the anticlinal structure formation in the studied area - fields of the “Butivska” mine were obtained. It was revealed that the initial horizontal attitude of rocks of the studied area was changed by a monoclinal attitude with a north-western dip and a north-east strike. Afterwards, under the conditions of tectonic near latitudinal compression and near meridional tension, anticlinal folding was formed. Then, under the influence of shear fields when the deformation mode was enhanced, a compression duplex was formed within which local echelon folding and fracture was formed - Oktiabrskyi fault #1.

Abstract Various assumptions are often made to model turbomachinery bladed assemblies. In particular, the cyclic symmetry of single rotor stages, and dynamically independence of isolated rotor stages are frequently used. The first assumption enables a drastic reduction of the required computational resources by considering only one sector instead of the entire assembly to model and analyze the dynamic behavior of the complete structure. However, small random blade-to-blade structural variations, known as mistuning, exist due to manufacturing tolerances, etc. and significantly affect the dynamic behavior of bladed disks. The second assumption also reduces the needed computational resources and time. However, ignore inter-stage coupling does not always describe accurately the disk or drum flexibility especially at the inter-stage boundaries. In this work, the component mode mistuning method is used for multi-stage assemblies to create a mistuning identification approach. An experimental modal analysis is performed on a two-stage monobloc academic bladed drum. The frequency response function is measured using a base excitation with an electrodynamic shaker and one measurement point per blade of each stage is used. The approach is used to identify mistuning in a multi-stage rotor. Numerical and experimental results are presented. Results show that the proposed approach is effective even for modes which are multi-stage.