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Abstract Background Article 12 of the Paris Agreement summons the signing parties to corporate in improving the education of their citizens on climate change and related matters. The article thereby acknowledges the importance of citizens support and understanding of climate change and needed measures to fight climate change. This paper aims to contribute to the goal of informing on the implications of climate change related policy on the power sector in Europe and hence all European citizens by presenting a serious game in which the player can explore how key policy decisions affect capacity mix, investment needs and electricity costs.Results The game is based on more than 1700 scenarios run through an open-source and accessible, yet technologically detailed myopic energy system optimisation model for the electricity supply in the EU27 + 3. The game allows the user to take the role of a decision maker and make decisions in 2020, 2030 and 2040 regarding the usage of CCS, biomass imports, cross-border electricity transmission and the pace of emission reductions. The user is then presented with economic, social, and environmental impacts of these choices. These impacts are for example measured and illustrated in the development of CO2 emissions per capita, levelised cost of electricity, and investment need per citizen.Conclusion The Power Decisions Game provides a first of its kind open-source infrastructure that allows non-modellers to explore the impact of key decisions and preferences on the design of the future European power system. It furthermore, provides insights on the consequences of short-sighted decision making. The game can be used to facilitate policy-science discussions.

Nitrogen oxide (NO) and nitrous oxide (N2O) formation in the circulating fluidized bed (CFB) combustion can be controlled by air staging and fuel staging. An extensive test campaign was carried out with a pilot-scale CFB test rig to observe the possibilities of the methods in the spruce bark and bituminous coal combustion as well as in co-combustion. Fuel staging with liquid petroleum gas (LPG) was done alternately from three locations with three intensities. Air staging was studied alone and during the fuel staging experiment. The experimental trends for NO and N2O emission formation during fuel staging and air staging are presented in this study. It was observed that air staging and fuel staging can have opposing effects on nitrogen oxide emission formation, and thus, when used together, a clear understanding of the fuel behavior and conditions, as well as NO x chemistry in the combustor, is needed. Under the tested conditions, it was observed that if air staging is effective, then fuel staging does not bring further benefits in the NO reduction. Instead, the LPG feed can increase the emission in the lack of oxygen. However, if it is not possible to carry out air staging, then fuel staging can be used in generating oxygen-lean reducing zones for NO. The N2O concentration was also further reduced with LPG in the tests with effective air staging.

In this paper, the results of a research and demonstration project to develop and optimize a transparent insulation (TI) wall heating system are described. First, the overall research and development concept and details of the modelling and optimization of the TI structure with regard to polymer type and cell geometry are described. Second, this paper focusses on the presentation of a novel, polymer film based small-celled TI structure, the optimized TI wall system of the application demonstration building and measurement results gathered during the heating period 2002/03 at the TI wall system. The values for the total energy transmittance and the heat loss coefficient of the novel polymer film based TI structures were found to be superior to the commercially available TI materials. To produce prototypes of the optimized small-celled lamellar structures based on cellulose triacetate films a continuously working prototype production plant was built and the structures were manufactured by a combined winding and joining process. For the application demonstration, a technically and ecologically optimized TI facade system was developed and used to equip a south-oriented wall of a solar house meeting passive house standard in Graz (A). The demonstration building was also equipped with an appropriate data recording system for solar irradiation, temperatures and heat fluxes. The practical experience within the heating period 2002/03 has proven to have an outstanding solar energy efficiency of about 44% of the novel TI wall system.

The growing interest in sustainable development is reflected in both the market’s sensitivity to environmental and social issues and companies’ interest in the opportunities that sustainable development objectives provide. SMEs, which account for most of the world’s pollution, have significant resource constraints for a sustainable development. Sharing their scarce resources can help them to overcome these constraints and to gain agility and organisational resilience against uncertainties, but the distrust inherent in belonging to different companies prevents them from sharing the necessary information for coordination purposes. This paper presents a coordination mechanism proposal with information asymmetry to allow independent companies’ resources to be sustainably shared as a technological driver. The proposed distributed coordination mechanism is compared to both a decentralised–uncoordinated and a centralised situation. The interest of the proposal is evaluated by a computer simulation experiment employing mathematical programming models with independent objectives in the Generic Materials and Operations Planning formulation with a rolling horizon procedure in different demand, uncertainty and product scenarios. Competitive improvement is identified for all members for their excess capacity use and their operations planning.

This paper is to describe an open-source code for optimization of clean energy technologies. The model covers the whole chain of energy systems including mainly 6 areas: renewable energies, clean e ...

The bias and uncertainty of calculated decay heat from spent nuclear fuel (SNF) are essential for code validation. Also, predicting these quantities is crucial for deriving decay heat safety margins, influencing the design and safety of facilities at the back end of the nuclear fuel cycle. This paper aims to analyze the calculated spent nuclear fuel decay heat biases, uncertainties, and correlations. The calculations are based on the Polaris and ORIGEN codes of the SCALE code system. Stochastically propagated uncertainties of inputs and nuclear data into calculated decay heats are compared. Uncertainty propagation using the former code is straightforward. In contrast, the counterpart of ORIGEN necessitated the pre-generation of perturbed nuclear cross-section libraries using TRITON, followed by coincident perturbations in the ORIGEN calculations. The decay heat uncertainties and correlations have shown that the observed validation biases are insignificant for both Polaris and ORIGEN. Also, similarities are noted between the calculated decay heat uncertainties and correlations of both codes. The fuel assembly burnup and cooling time significantly influence uncertainties and correlations, equivalently expressed in both Polaris and ORIGEN models. The analyzed decay heat data are highly correlated, particularly the fuel assemblies having either similar burnup or similar cooling time. The correlations were used in predicting the validation bias using machine learning models (ML). The predictive performance was analyzed for machine learning models weighting highly correlated benchmarks. The application of random forest models has resulted in promising variance reductions and predicted biases significantly similar to the validation ones. The machine learning results were verified using the MOCABA algorithm (a general Monte Carlo-Bayes procedure). The bias predictive performance of the Bayesian approach is examined on the same validation data. The study highlights the potential of neighborhood-based models, using correlations, in predicting the bias of spent nuclear fuel decay heat calculations and identifying influential and highly similar benchmarks.

To foster the implementation of Industrial Symbiosis, several support tools have been developed to facilitate the dissemination of Industrial Symbiosis (IS) and the engagement of stakeholders; the establishment of exchanges between companies, the so-called synergies; and the assessment of impacts and benefits. Despite this, it has been found that stakeholders still do not have a clear envisioning of the required steps to the technical implementation of synergies and there are no facilitating tools, such as methodologies, frameworks, modelling tools, and databases, among others, that aid to technically support decision-making of synergy implementation. Thus, the goal of this paper is to present a dedicated framework that provides a set of guidelines and defines a technical viability analysis to support the implementation of potential synergies, which can be used and replicated by any IS practitioner. It comprehends a methodological approach to assess the compliance of a given synergy opportunity; its characterization concerning the definition of the necessary intermediary steps for the technical implementation; and an assessment of the technical feasibility of the synergy. The implementation of the framework allowed the successful technical validation of the studied synergy opportunities, providing a final technical viability assessment that can support decision-making of technology selection and synergy implementation.