In the current context of the climate crisis, it is essential to design buildings that can cope with climate dynamics throughout their life cycle. It will ensure the development of sustainable and resilient building stock. Thus, this study’s primary objective has been to demonstrate that the current climatic zones for buildings in peninsular Spain do not represent the current climatic reality and are not adapted to climate change and the impact on the energy demand of buildings. For this reason, the climatic zones of 7967 peninsular cities have been updated and adapted to the RCP 4.5 and RCP 8.5 scenarios by using the data measured in 77 meteorological reference stations. The results obtained have shown that in more than 80% of the cities, buildings are designed and constructed according to an obsolete climatic classification that does not take into account the current or future climatic reality, which will significantly affect the thermal performance of a building and highlights the need to review the climatic zoning in the country. The results obtained can be extrapolated to other regions. The methodology defined in this work can be used as a reference, thus making an essential scientific contribution in reflecting on current capacities and the possibilities of improving the building stock.

The need for new energy sources and the problems associated with waste in the agroforestry industry are an opportunity for the recovery of this waste. For the use of this agricultural waste as energy, different pretreatments, such as torrefaction, can be carried out. Torrefaction is a thermochemical treatment involving energetic densification of biomass at temperatures ranging from 200 to 300 °C under an inert and anaerobic environment. This study developed a numerical model to evaluate the effect of temperature and residence time of torrefaction on biomass from olive tree waste to determine optimum operative conditions for the process. Four temperatures and four residence times, in the operation range of the process, were tested to determine the weight loss and the higher heating values (HHVs) of the torrefied sample. From these data, a numerical model was developed to infer the complete behavior of the process in the temperature range between 200 and 300 °C and in the residence time range of a few minutes to 2 h. The HHV of the torrefied sample increased at a temperature between 200 and 275 °C. However, from 275 to 300 °C, there was an HHV decrease. The effect of the residence time depended on the torrefaction temperature. At low temperatures, there were no statistically significant differences, although an increase of HHV was detected under 120 min. However, at 250 °C this effect was reversed, and statistically significant differences were not observed between 30 and 120 min. Overall, the increase of temperature in the torrefaction process reduces the residence time needed to achieve the maximum HHV. As a result, the optimum conditions of torrefaction for this biomass were, approximately, 275 °C and 30 min of residence time. This reaction yielded an optimum 5830 cal/g HHV.

The aim of this work is to show how symbolic computation can be used to perform multivariate Lagrange, Hermite and Birkhoff interpolation and help us to build more realistic interpolating functions. After a theoretical introduction in which we analyze the complexity of the method we shall focus our attention on applications.