Abstract:In the 19th century, the Spanish government, led by a liberal political project, put up for sale the common properties of villages, and deprived local village authorities of their capacities, powers and laws to manage common woodlands, which were passed to the Forestry Service. This paper, based on Ostrom's hypothesis that state intervention can have negative consequences for the conservation of common resources, is a case study of what happened in the province of León. It is shown that, although the conservation of common resources was endangered because those who were more directly concerned with protecting them were deprived of the means to do so, peasant communities staunchly defended the commons by maintaining traditional practices and uses in their commons.

Abstract:In the 19th century, the Spanish government, led by a liberal political project, put up for sale the common properties of villages, and deprived local village authorities of their capacities, powers and laws to manage common woodlands, which were passed to the Forestry Service. This paper, based on Ostrom's hypothesis that state intervention can have negative consequences for the conservation of common resources, is a case study of what happened in the province of León. It is shown that, although the conservation of common resources was endangered because those who were more directly concerned with protecting them were deprived of the means to do so, peasant communities staunchly defended the commons by maintaining traditional practices and uses in their commons.

Increasing the energy efficiency of buildings is a strategic objective in the European Union, and it is the main reason why numerous studies have been carried out to evaluate and reduce energy consumption in the residential sector. The process of evaluation and qualification of the energy efficiency in existing buildings should contain an analysis of the thermal behavior of the building envelope. To determine this thermal behavior and its representative parameters, we usually have to use destructive auscultation techniques in order to determine the composition of the different layers of the envelope. In this work, we present a nondestructive, fast, and cheap technique based on artificial neural network (ANN) models that predict the energy performance of a house, given some of its characteristics. The models were created using a dataset of buildings of different typologies and uses, located in the northern area of Spain. In this dataset, the models are able to predict the U-opaque value of a building with a correlation coefficient of 0.967 with the real U-opaque measured value for the same building.

In recent decades, the scientific community has noted that the pollutants released into atmosphere produced by road traffic is one of the most significant causes in the deterioration of air quality in cities. Therefore, it is important to estimate the emission factors associated with road traffic, which turns out to be the theoretical basis for estimating the emissions of air pollutants in a precise way. The emissions of atmospheric pollutants generated by mobile sources may produce severe impacts on human health because these pollutants are generally produced in areas with a high density of inhabitants and at ground level. The present study aims to estimate the concentration of air pollutants generated by road traffic on the main roads of the city of Cartagena, which were selected while taking into account the critical points of highest traffic congestion. The emission factors for PM2.5, using the inverse modeling technique, were estimated taking into account the average concentrations measured over 24-hour period and the pollutants that represent the greatest threat to public health were determined. This study is a starting point to determine the magnitude of the emissions associated with road traffic in Cartagena, and it also provides technical support to be able to identify in an approximate way the impact of different vehicle sources in the city.