Abstract
The Brazilian power generation sector faces a paradigm change driven, on one hand, by a shift from a hydropower dominated mix and, on the other, by international goals for reducing greenhouse gases emissions. The objective of this work was to evaluate five scenarios for the Brazilian power system until 2050 using a multi-criteria decision analysis tool. These scenarios include a baseline trend and low carbon policy scenarios based on carbon taxes and carbon emission limits. To support the applied methodology, a questionnaire was elaborated to integrate the perceptions of experts on the scenario evaluation process. Taking into account the results from multicriteria analysis, scenario preference followed the order of increasing share of renewables in the power system. The preferable option for the future Brazilian power system is a scenario where wind and biomass have a major contribution. The robustness of the multi-criteria tool applied in this study was tested by a sensitivity analysis. This analysis demonstrated that, regardless the respondents' preferences and backgrounds, scenarios with higher shares of fossil fuel sources are the least preferable option, while scenarios with major contributions from wind and biomass are the preferable option to supply electricity in Brazil through 2050.

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The atmospheric dispersion of NOx and PM10 was simulated with a second generation Gaussian model over a medium-size south-European city. Microscopic traffic models calibrated with GPS data were used to derive typical driving cycles for each road link, while instantaneous emissions were estimated applying a combined Vehicle Specific Power/Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (VSP/EMEP) methodology. Site-specific background concentrations were estimated using time series analysis and a low-pass filter applied to local observations. Air quality modelling results are compared against measurements at two locations for a 1 week period. 78% of the results are within a factor of two of the observations for 1-h average concentrations, increasing to 94% for daily averages. Correlation significantly improves when background is added, with an average of 0.89 for the 24 h record. The results highlight the potential of detailed traffic and instantaneous exhaust emissions estimates, together with filtered urban background, to provide accurate input data to Gaussian models applied at the urban scale.

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The corner stone of a language development environment is an editor. For programming languages, several code editors are readily available to be integrated in Web applications. However, only few editors exist for diagrammatic languages. Eshu is an extensible diagram editor, embeddable in Web applications that require diagram interaction, such as modeling tools or e-learning environments. Eshu is a JavaScript library with an API that supports its integration with other components, including importing/exporting diagrams in JSON. Eshu was already integrated in a pedagogical environment with automated diagram assessment, configured for extended entityrelationship diagrams, that served as basis for an usability evaluation. © José Paulo Leal, Helder Correia, and José Carlos Paiva;licensed under Creative Commons License CC-BY.