Abstract
This paper aims to examine the impacts of fleet composition changes on emission due to the introduction of different road transportation policies in a medium size European country (Portugal) applying an ex-post analysis (e.g. policies based on fuel pricing, car scraping, car taxation). A baseline scenario was compared with a counterfactual scenario in order to understand what would occur in the absence of the introduction of those policies. For each scenario, four approaches were assessed using economic effects and/or human health costs. HC, CO, NOx, PM and CO2 emissions from passenger cars and light duty vehicles were evaluated. The results show high statistical significance (p <= 0.05) between CO emissions and different vehicle features as vehicle age, fuel type and engine classes. The same pattern was observed between the average vehicle age and HC, NOx and PM. After the implementation of road traffic policies, the average emission factors of the fleet decreased 28-62% for HC, CO, NOx, PM and 20-39% for CO2. However, if a counterfactual scenario would be implemented, the reduction would be 20-80% and 26-55% higher, respectively. The results demonstrates that although were recorded some benefits, the fleet characteristics distribution were more environmental friendly in 2001 than in 2011.

Abstract
Ozone (O3) is a secondary pollutant mainly produced in the troposphere by photochemical reactions with high impact on human health. In this work hourly average O3 concentrations from the Portuguese air quality network collected during 24 years (1988–2011) were analysed. The background time series were assessed by environment type (urban, suburban and rural) and considering several criteria: the annual mean O3 concentration, the Directive 2008/50/EC O3 long-term objective and the 2005 WHO Guideline for protection of human health and, finally, the hourly information threshold exceedances. The trend of annual mean O3 concentration data and the maximum daily eight-hour mean ozone concentration data were both annually compared using an one-way ANOVA followed by a Tamhane post-hoc comparison test. In both series, although of an instable trend, a tendency for an increase of the mean O3 concentrations was found. On the other hand, after 2006, for all stations types, the normalized number of exceedances for public O3 information are significantly decreasing (p<0.05). In this paper, the O3 trend will be analyzed and discussed, contributing to improve knowledge of long time series of O3 concentrations in Portugal. © 2014 WIT Press.

Abstract
Renewable technologies are suitable investments to achieve a low carbon electricity production system and to reduce the external energy dependency of Portugal in a long term period. The aim of this work was to develop and evaluate a variety of scenarios to promote these goals until 2030. A long-term electricity expansion planning model is used to design these scenarios and multi-criteria analysis is applied in the evaluation. The results demonstrated that imposing a minimum contribution of renewable energy sources (RES) for the electricity system, can be more costly than imposing CO2 emissions limitations. Taking into account the technical criteria, scenarios with high coal power share are favoured. However, under a pure social approach, the best scenario would be a 100% RES electricity system. When environmental and economic dimensions are more valued, the best options seems to be the ones with higher investments on natural gas and wind power plants.

Abstract
Bonding is an important process used in all fields of industry, where the tight joining of two materials is required. It includes a wide variety of processing technologies that can be placed in a framework of chemistry, physics, and materials science. Although most of these bonding processes have only recently appeared in textbooks, the basic phenomena have been known and used for many centuries. Choosing an appropriate bonding process may result in the improved end-use performance, increased efficiency, and greater design flexibility. Through various bonding techniques, this study aims at investigating the following ones: direct bonding, thermocompression bonding, surface activated bonding, eutectic bonding, adhesive bonding, and glass frit bonding. The characteristic features of these techniques with respect to their many-sided aspects and a review of the current state of the art of each technique are briefly outlined in this chapter.

Abstract
Neural regression provides a rapid solution to modeling complex systems with minimal computation effort. Recurrent structures such as fuzzy cognitive map (FCM) enable for drawing cause effect relationships among system variables assigned to graph nodes. Accordingly, the obtained matrix of edges, known as adjacency model, represents the overall behavior of the system. With this, there are many applications of semantic networks in data mining, computational geometry, physics-based modeling, pattern recognition, and forecast. This article examines a methodology for drawing application-specific adjacency models. The idea is to replace crisp neural weights with functions such as polynomials of desired degree, a property beyond the current scope of neural regression. The notion of natural adjacency matrix is discussed and examined as an alternative to classic neural adjacency matrix. There are examples of stochastic and complex engineering systems mainly in the context of modeling residential electricity demand to examine the proposed methodology.

Abstract
Logistics network design is a major strategic issue due to its impact on the efficiency and responsiveness of the supply chain. This paper focuses on strategic and tactical design of steel supply chain (SSC) networks. Ever-increasing demand for steel products enforces the steel producers to expand their production and storage capacities. The main purpose of the paper includes preparing a countrywide production, inventory, distribution, and capacity expansion plan to design an SSC network. The SSC networks consist of iron ore mines as suppliers, raw steel producer companies as producers, and downstream steel companies as customers. Demand is assumed stochastic with normal distribution and known at the beginning of planning horizon. To achieve the service level of interest, a potential production capacity along with two kinds of safety stocks including emergency and shared safety stocks are suggested by the authors. A mixed integer nonlinear programming (MINLP) model and a mixed integer linear programming (MILP) model are presented to design dynamic multi-commodity SSC networks. To evaluate the performance of the MILP model, a real case of SSC network design is solved. Furthermore, solving two proposed models by using a commercial solver for a set of numerical test cases shows that the MILP model outperforms MINLP in medium- and large-scale problems in terms of computational time. Finally, the complexity of the linear model is investigated by relaxing some major assumptions.