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Efficiency of energy resource use is a key factor for a sustainable energy future. By matching the exergy levels of supply and demand, Energy Quality Management (EQM) of building energy supply systems may achieve more efficient use of energy resources. Beyond this, environmental impact of energy supply systems is another essential issue. This work addresses the influence of EQM on CO 2 emissions in the operation optimization of a Distributed Energy System (DES). A multi-objective linear programming problem is formulated to reduce energy costs and increase the overall exergy efficiency. Total CO 2 emissions are evaluated for the optimized operation strategies of the DES. The operators of the DES can choose the operation strategy from the Pareto front, based on their priorities and also aware of effects on CO 2 emissions. Results demonstrate more efficient use of energy resources and reduction in CO 2 emissions through EQM, as compared with conventional energy supply systems.

Abstract Sodium-promoted vanadium oxide catalysts supported on MCM-41 and TiO 2 (anatase) were investigated for the partial oxidation of ethanol to acetaldehyde. The catalysts were prepared by incipient wetness impregnation with a vanadium oxide content of 6 wt.%. The experimental characterization was performed by X-ray diffraction (XRD), N 2 adsorption, temperature-programmed reduction (TPR), and diffuse reflectance UV–vis. Temperature-programmed oxidation (TPO) was also used to identify carbon deposits on the spent catalysts. The presence of sodium plays a strong role in the dispersion and reducibility of the vanadium species as detected by TPR analysis and optical absorption spectroscopy. While sodium addition increases the dispersion of the VO x species, its presence also decreases their reducibility. Additionally, TPO of the spent catalysts revealed that an increase in the Na loading decreases the carbon deposition during reaction. In the case of the catalysts supported on MCM-41, these modifications were mirrored by a change in the activity and selectivity to acetaldehyde. Additionally, on the VO x /TiO 2 catalysts the catalytic activity decreased with increasing sodium content in the catalyst . A model in which sodium affects dispersion, reducibility and also acidity of the supported-vanadia species is proposed to explain all these observations.

We report measurement of initial G2-chromatid breaks in normal human fibroblasts exposed to various types of high-LET particles. Exponentially growing AG 1522 cells were exposed to gamma rays or heavy ions. Chromosomes were prematurely condensed by calyculin A. Chromatid-type breaks and isochromatid-type breaks were scored separately. The dose response curves for the induction of total chromatid breaks (chromatid-type + isochromatid-type) and chromatid-type breaks were linear for each type of radiation. However, dose response curves for the induction of isochromatid-type breaks were linear for high-LET radiations and linear-quadratic for gamma rays. Relative biological effectiveness (RBE), calculated from total breaks, showed a LET dependent tendency with a peak at 55 keV/micrometer silicon (2.7) or 80 keV/micrometer carbon (2.7) and then decreased with LET (1.5 at 440 keV/micrometer). RBE for chromatid-type break peaked at 55 keV/micrometer (2.4) then decreased rapidly with LET. The RBE of 440 keV/micrometer iron particles was 0.7. The RBE calculated from induction of isochromatid-type breaks was much higher for high-LET radiations. It is concluded that the increased production of isochromatid-type breaks, induced by the densely ionizing track structure, is a signature of high-LET radiation exposure.

Confluent human fibroblast cells were exposed to 6 Gy gamma-rays or 200 MeV/nucleon Fe ions at 0.7 or 3 Gy. The cells were allowed to repair for 24 hours after exposure and chromosomes were collected using a premature chromosome condensation technique with calyculin-A. Chromosome aberrations were analyzed using the multicolor FISH (mFISH) technique that allows identification of both complex and truly incomplete exchanges. Results showed that both doses of the Fe ions produced higher ratios of complex to simple exchanges and lower ratio of complete to incomplete exchanges than the 6 Gy gamma-exposure. The ratios of aberration yields were similar for the two doses of Fe ions. After 0.7 Gy of Fe ions, most complex aberrations were found to involve three or four chromosomes, indicating this is the maximum number of chromosome domains traversed by a single Fe ion track.

Taking GDP as the standard economic indicator for economic welfare, recent Resources-Economy studies indicate the “dematerialization” of the economy, the so-called decoupling effect. This conclusion seems to alleviate concerns over resource scarcity and limits to growth, and feeds optimism for green growth and sustainability prospects. However, the validity of GDP as the sole and unambiguous measure of the ultimate outcome of the economy has been severely disputed. There is nowadays increasing interest in broader welfare measurements that capture more aspects of economic output and hence constitute better approximations of well-being. The present paper provides an overview of the above discussion and sets out to explore the relevance of three alternative welfare indicators – the Human Development Index (HDI), the Index of Sustainable Economic Welfare (ISEW) and the Genuine Progress Indicator (GPI) – as a basis for evaluating the dependency of welfare and its major engine, the economy, on natural resources. Increasing welfare appears to require a disproportionate use of resources. Strong and increasing dependency on resources at the global level and in giant countries such as China and India may have serious implications for current sustainability policies and the United Nations Sustainable Development Goals.

Sustainable development requires not only the use of sustainable energy resources, but also the efficient use of all energy resources. The latter should be reached by considering the concept of energy as well as exergy - the true magnitude of thermodynamic losses. Exergy describes the quality of an energy flow as the percentage that can be completely transformed into any other form of energy. Reduction of exergy losses represents a more efficient use of energy resources, which is essential in the long run, but it is not captured by standard energy costs, which are crucial in the short run. In this paper, exergy analysis is used in the context of a multi-carrier energy district to match the supply and demand not only in quantity but also in quality. The innovative contribution of this paper is the offering of a trade-off between reducing exergy losses and energy costs, thereby attaining sustainability of the energy district. A mixed-integer programming problem considering several energy devices is formulated to minimize a weighted sum of exergy losses and energy costs while satisfying time-varying user demands. The problem is solved by branch-and-cut. Numerical results demonstrate that the optimized operation of the energy devices makes the energy district sustainable in terms of exergy efficiency and costs.

A risk bidding methodology is proposed to help prosumers formulating optimal quantity-price bids for the day-ahead energy market. A prosumer is the manager of a Low Voltage (LV) Micro-Grid (MG), connected to the main electric grid, where generators are paired with renewable energy sources (RES). To present the optimal bidding in the wholesale electricity market, the prosumers need to resolve a short-term management problem and need to identify all infiuencing variables (i.e. energy exchange, internal production, level of storage, Photovoltaic power plants (PV)). They also have to take into account the uncertainty in RES energy production to evaluate different risks associated with their tolerance preferences.A heterogenous MG which pairs traditional thermal and electrical generators with a PV power production is simulated. An economic model based on genetic algorithms is proposed to formulate the optimal bidding. Although in literature it is possible to find similar decision support models, one of the main original contributions of this work is to estimate the RES input of the proposed model with Analogs Ensemble (AnEn) approach, which is used here to provide day-ahead PV energy forecasting. The results of the model are analyzed evaluating the risk associated with the different prosumer's choices by the expected utility theory. The analyzed case study uses on residential MG and different prosumer risk tolerances (adverse, neutral and incline). Results are shown to demonstrate the effectiveness of the proposed methodology.