Corporate responsibility & sustainability report

Descripció feta a partir de: 2014, el 3 setembre 2015

A multi-regional input-output analysis of ozone precursor emissions embodied in Spanish international trade

Higher levels of ozone in the troposphere is a severe threat to both environment and human health. Many countries are concerned about the effects that critical levels of ozone have on them. Countries pollute to satisfy their domestic and external demand (production perspective) and, at the same time, these countries also generate emissions abroad indirectly via their imports and via their domestic production (consumption perspective). Spain is one of the EU countries with the highest pollution records in the emissions of tropospheric ozone precursor gases. A multiregional input-output model (MRIO) allows us to analyze the total emissions embodied in Spanish international trade in 35 sectors within the EU area and the rest of the world. MRIO models, are commonly chosen as they provide an appropriate methodological framework for complete emissions footprint estimates at the national and supranational level The results show that the most polluting sectors involved in Spanish trade are Agriculture, Basic Metals, Coke and Refined Petroleum Production. Some policy recommendations follow these results; for example, a higher number of environmental regulations focused on the Agricultural sector, such as the introduction of codes of good practices in the use of fertilizers and the promotion of cleaner production technologies might lead to less burden to the environment.Ministerio de economía y competitividad (España) ECO 2014-56399-R. Claves para Desacoplar Crecimiento y Emisiones de Co2 en EspañaCátedra de economía de la energía y del medio ambiente (Universidad de Sevilla)Fundación Roger TornéJunta de Andalucía. SEJ 13

Determining and Sharing Risk Data in Distributed Interdependent Systems

While the risks induced by system dependencies have been studied; little is known about modelling complex collections of supposedly independent systems at different geographical locations, which are in reality interdependent due to sharing often-unrecognized common elements. It could be argued that any risk analysis of a large infrastructure that does not take account of such interdependencies is dangerously introspective. We present a top-down, goal-to-dependencies approach to modelling and understanding such Complex Systems, which uses secure, distributed computing protocols to share risk data between the risk models of interdependent systems. We present a Bayesian-sensitivity measure of risk, which is both intuitively satisfying and accords with everyday notions of risk. The core benefit of this approach is to capture dependencies between systems and share risk data such that failure of an entity along the ‘supply chain’ can be rapidly propagated to those who depend on it allowing them to calculate the likely impact and respond accordingly

Sizing and Optimization of Novel General Aviation Vehicles and Propulsion System Architectures

The drive for more efficient flying vehicles in all categories may necessitate a significant departure from the tube-and-wing or rotary-wing norms that have been the mainstay of aviation for many decades. This poses challenges for predicting the aerodynamic characteristics and the weight build-up of such unconventional vehicles in early design phases. Additionally, the design and assessment of advanced/unconventional all-electric or hybrid-electric propulsion system architectures require consideration of degrees-of-freedom and trade-offs that do not arise for conventional purely fuel-powered architectures. Thus, there is a need for a flexible vehicle sizing, trade-off, and optimization capability that is not limited to a single vehicle configuration (e.g., fixed-wing, rotary-wing) or propulsion system architecture. To be suitable for the early design phases, such a framework must evaluate relatively quickly, not require extensive definition of the vehicle, and lend itself to customizable design optimization setups. This paper describes the initial creation of such a capability and demonstrates its application to design trade-offs for a General Aviation vehicle with an advanced propulsion system architecture

Analysis of a local search heuristic for the generalized assignment problem with resource-independent task profits and identical resource capacity

In practice, allocating tasks to resources is often tackled in (near) real-time due to the latency of the task information and sudden task arrivals into a system. Therefore, the problem must be solved within a very short time budget, when tasks are urgent or idle resources are critical to the system's performance. Local search algorithms could be a good solution to this issue. These algorithms usually focus the search on limited solution areas by applying local updates on an incumbent solution. To investigate the feasibility and performance of applying a local search algorithm to resource allocation, a special case of the Generalized Assignment Problem (GAP) is modelled, where task profits are independent of the resources assigned and resources' capacities are identical. Then the performance of a local search algorithm to the target problems is examined empirically, characterizing the features of the GAP that make the problem hard for heuristics

Analysis of a local search heuristic for the generalized assignment problem with resource-independent task profits and identical resource capacity

In practice, allocating tasks to resources is often tackled in (near) real-time due to the latency of the task information and sudden task arrivals into a system. Therefore, the problem must be solved within a very short time budget, when tasks are urgent or idle resources are critical to the system's performance. Local search algorithms could be a good solution to this issue. These algorithms usually focus the search on limited solution areas by applying local updates on an incumbent solution. To investigate the feasibility and performance of applying a local search algorithm to resource allocation, a special case of the Generalized Assignment Problem (GAP) is modelled, where task profits are independent of the resources assigned and resources' capacities are identical. Then the performance of a local search algorithm to the target problems is examined empirically, characterizing the features of the GAP that make the problem hard for heuristics