No abstract

Today, we are witnesses to the early days of a change in the mobility technology as oil reserves decline and society's environmental awareness increases. Electric technologies are intended to replace those based on hydrocarbons as they have been initially conceived as more environmentally friendly and energy efficient. However, the problem of the future availability of the materials required for this change has arisen. A large demand for this type of mobility could contribute to the depletion of these resources, leading to major problems for the manufacture of vehicles and all other technologies that use these materials if we do not find alternatives that allow us not to deplete these natural resources. These alternatives may involve not only a change in the materials used in electric vehicles but also the use of different modes of transport. To help us estimate which materials related to the transition in the transport sector might be most critical in the future globally, the MEDEAS system dynamics simulation model will be used. Once the simulations on different scenarios have been run, we observe how aluminium, copper, cobalt, lithium, manganese and nickel have such a high demand that would practically cause the exhaustion of their reserves in several scenarios, so we will propose alternative measures to try to avoid their exhaustion due to the use of this type of mobility. Keywords: Transport modes, mineral resources, system dynamics, lithium-ion batteries.

A dispersive device that permits us to analyze two arbitrary spectral profiles simultaneously with the same detector like an optical multichannel analyzer has been designed. The device consists of a holographic grating with two different spatial frequencies, which are not recorded simultaneously, and that are calculated specifically for two spectral lines under study.

The climate change that is currently occurring is due to the increase in the concentration of greenhouse gases (GHG) in the atmosphere as a result of human activity. The large number of factors and variables that directly or indirectly affect GHG emissions, as well as the multiple and complex relationships between them, makes it difficult to make decisions on the best measures to be adopted to slow down or mitigate climate change and to analyze the consequences that each decision entails. This has led to the development of complex simulation models called Integrated Assessment Models (IAMs) or Energy-Economy-Environment Models (E3 models), with a particular focus on climate change. The development and use of these models to guide policy decisions on climate change has grown very significantly in recent years, as evidenced by the reports of the Intergovernmental Panel on Climate Change (IPCC). This paper is a panoramic review of the main existing IAMs and analyzes their main characteristics. The paper focuses especially on the analysis of the limitations of the current IAMs, which should mark the future developments of these tools.