New technological, societal and legislative developments are necessary to support transitions to low-carbon energy systems. The building sector is responsible for almost 36% of the global final energy and 40% of CO₂ emissions, so this sector has high potential to contribute to the expansion of positive energy districts. With this aim, a new digital Geographic Information System (GIS) platform has been developed to quantify the energy savings obtained through the implementation of refurbishment measures in residential buildings, including solar thermal collectors and geothermal technologies and assuming the postal district as the representative unit for the territory. Solar resources have been estimated from recently updated solar irradiation maps, whereas geothermal resources have been estimated from geological maps. Urbanistic data have been estimated from official cadastre databases. For representative buildings, the annual energy demand and savings are obtained and compared with reference buildings, both for heating and cooling. The GIS platform provides information on average results for each postal district, as well as estimates for buildings with particular parameters. The methodology has been applied to the Asturian region, an area of about 10,600 km² on the Cantabrian coast of Spain, with complex orography and scattered population, qualified as a region in energy transition. High rehabilitation potentials have been achieved for buildings constructed before the implementation of the Spanish Technical Building Code of 2006, being higher for isolated houses than for collective buildings. Some examples of results are introduced in specific localities of different climatic zones.

Air pollution is one of the major environmental problems, especially in industrial and highly populated areas. Remote sensing image is a rich source of information with many uses. This paper is focused on estimation of air pollutants using Landsat-5 TM and Landsat-8 OLI satellite images. Particulate Matter with particle size less than 10 microns (PM10) is estimated for the study area of Principado de Asturias (Spain). When a satellite records the radiance of the surface received at sensor, does not represent the true radiance of the surface. A noise caused by Aerosol and Particulate Matters attenuate that radiance. In many applications of remote sensing, that noise called path radiance is removed during pre-processing. Instead, path radiance was used to estimate the PM10 concentration in the air. A relationship between the path radiance and PM10 measurements from ground stations has been established using Random Forest (RF) algorithm and a PM10 map was generated for the study area. The results show that PM10 estimation through satellite image is an efficient technique and it is suitable for local and regional studies.

In a context where air quality has become a global concern, modelling techniques are becoming very popular for analysing pollutant dispersion conditions. While models based on empirical formulations are most widely used for industrial scenarios, singular cases involving complex terrain or large obstacles in the vicinity of emission sources require a more robust approach to evaluate the dispersion conditions. In this research, a computational fluid dynamics (CFD) model is developed to analyse the dispersion of pollutants from an industrial facility whose location and characteristics suggest the occurrence of complex flow features that affect the dispersion patterns. In addition, the variation of the gas exit temperatures of waste heat recovery systems is proposed as a measure to mitigate the impact of the plume. The simulation results show unexpected deviations in the plume path affecting vulnerable areas in a nearby mountainside, but increasing the gas exit temperature is useful to prevent this event. Therefore, the proposed methodology can be considered a decision support tool to find a compromise between the environmental impact and the fuel consumption of the plant.

Atmospheric pollution is one of the biggest problems and concerns in modern society, especially in industrial and highly populated areas. Poor air quality can have adverse impact on human health and ecosystems. For this reason, air quality forecasting becomes increasingly important, especially for governments and administrations, which use these predictions to enhance the design of mitigation actions in order to reduce air pollution in urban areas. In this framework, process of pollutant dispersion simulation is the best way to predict the most affected areas by industrial and other kinds of emissions. To carry out these simulations, there is a great number of computational tools currently available. However, not all of them have the same functionalities, nor can they be applied to the same case studies, so it is necessary to establish the advantages and disadvantages of each one of them in order to choose the most suitable tool in each case. Therefore, the objective of this paper is to identify the main available simulation tools and to make a comparative review between them in order to define advantages and disadvantages.

The study of meteorological variables and evapotranspiration in open spaces using the three spatial dimensions represents a technical challenge since the high computational resources required only enable the problem to be addressed on a very small scale. This research sets forth a three-dimensional computational fluid dynamics numerical model, characterized by its simplicity, which allows problems to be addressed over large areas (scale of kilometres). Similarly, the corresponding design and software developments carried out allow for a more dynamic introduction of meteorological and evapotranspiration boundary conditions. In the numerical domain created, the Reynolds-Averaged Navier–Stokes equations are solved, supplemented by a multispecies model (to distinguish the movements of dry air, evapotranspiration and air humidity) and one of solar radiation. The numerical model was applied to a semi-arid area in southern Spain, obtaining the three-dimensional special evolution of evapotranspiration, temperature, air humidity and wind velocity, specifically concerning its variation in horizontal and vertical planes of the three-dimensional domain, as well as vertical profiles at discrete points.

Air pollution is one of the consequences of the industrial development, which causes a lot of health and environmental problems. For these reasons, the quality of the air is one of the major concerns of regional, national and European governments. All of them are developing strict normative to reduce the emissions of contaminants. The quality of the air can be analysed by means of numerical simulations. In this paper, a methodology based on Computational Fluid Dynamics (CFD) is described. This technique allows evaluating the dispersion of industrial-type air pollutants in a relatively large area, taking into account the orography, buildings and so on. Also, specific models are studied in order to consider the specific characteristics of the industrial contaminants and particles.