Abstract
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.

Abstract
Urban traffic emissions have been increasing in recent years. To reverse that trend, restrictive traffic measures can be implemented to complement national policies. We have proposed a methodology to assess the impact of three restrictive traffic measures in an urban arterial by using a microsimulation model of traffic and emissions integrated platform. The analysis is extended to some alternative roads and to the overall network area. Traffic restriction measures provided average reductions of 45%, 47%, 35%, and 47% for CO2, CO, NOx, and HC, respectively, due to traffic being diverted to other roads. Nevertheless, increases of 91%, 99%, 55%, and 121% in CO2, CO, NOx, and HC, respectively, can be expected on alternative roads.

Abstract
Eco-routing has been shown as a promising strategy to reduce emissions. However, during peak periods, with limited additional capacity, the eco-friendliness of various routes may change. We have explored this issue empirically by covering about 13,300 km, in three different areas, using GPS-equipped vehicles to record second-by-second vehicle dynamics. This study has confirmed the importance of the eco-routing concept given that the selection of eco-friendly routes can lead to significant emissions savings. Furthermore, these savings are expected to be practically unchanged during the peak period. However, some potential negative externalities may arise from purely dedicated eco-friendly navigation systems.

Abstract
In general, car manufacturers face trade-offs between safety, efficiency and environmental performance when choosing between mass, length, engine power, and fuel efficiency. Moreover, the information available to the consumers makes difficult to assess all these components at once, especially when aiming to compare vehicles across different categories and/or to compare vehicles in the same category but across different model years. The main objective of this research was to develop an integrated tool able to assess vehicle's performance simultaneously for safety and environmental domains, leading to the research output of a Safety, Fuel Efficiency and Green Emissions (SEG) indicator able to evaluate and rank vehicle's performance across those three domains. For this purpose, crash data was gathered in Porto (Portugal) for the period 2006-2010 (N = 1374). The crash database was analyzed and crash severity prediction models were developed using advanced logistic regression models. Following, the methodology for the SEG indicator was established combining the vehicle's safety and the environmental evaluation into an integrated analysis. The obtained results for the SEG indicator do not show any trade-off between vehicle's safety, fuel consumption and emissions. The best performance was achieved for newer gasoline passenger vehicles (<5year) with a smaller engine size (<1400 cm(3)). According to the SEG indicator, a vehicle with these characteristics can be recommended for a safety-conscious profile user, as well as for a user more interested in fuel economy and/or in green performance. On the other hand, for larger engine size vehicles (>2000 cm(3)) the combined score for safety user profile was in average more satisfactory than for vehicles in the smaller engine size group (<1400 cm(3)), which suggests that in general, larger vehicles may offer extra protection. The achieved results demonstrate that the developed SEG integrated methodology can be a helpful tool for consumers to evaluate their vehicle selection through different domains (safety, fuel efficiency and green emissions). Furthermore, SEG indicator allows the comparison of vehicles across different categories and vehicle model years. Hence, this research is intended to support the decision-making process for transportation policy, safety and sustainable mobility, providing insights not only to policy makers, but also for general public guidance.

Abstract
Renewable energy sources (RES) are becoming the main players for the sustainability of the planet and achieving a 100% RES energy system has been attested as a good strategy to go forward in many countries. This target however defies the system to integrate highly variable RES in a system that does not allow for shortage on the energy supply. This work presents a possible 100% RES scenario for an electricity system close to the Portuguese estimating and analysing the economic and technical impacts. The sensitivity of the results to aspects related to RES availability, electricity demand, peak load and interconnection capacity for electricity trading were also analysed. The results highlighted the excess of electricity produced in 100% RES systems and the importance of including interconnection capacity to contribute to overcome this problem.

Abstract
Deterministic models based on most likely forecasts can bring simplicity to the electricity power planning but do not explicitly consider uncertainties and risks which are always present on the electricity systems. Stochastic models can account for uncertain parameters that are critical to obtain a robust solution, requiring however higher modelling and computational effort. The aim of this work was to propose a methodology to identify major uncertainties presented in the electricity system and demonstrate their impact in the long-term electricity production mix, through scenario analysis. The case of an electricity system with high renewable contribution was used to demonstrate how renewables uncertainty can be included in long term planning, combining Monte Carlo Simulation with a deterministic optimization model. This case showed that the problem, of including risk in electricity planning could be explored in short running time even for large real systems. The results indicate that high growth demand rate combined with climate uncertainty represent major sources of risk for the definition of robust optimal technology mixes for the future. This is particularly important for the case of electricity systems with high share of renewables as climate change can have a major role on the expected power output.