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Energy poverty (EP) is a problem that affects a large part of the world population, leaving those most vulnerable to suffer from unhealthy indoor conditions in their homes, being cold in winter months, struggling with their monetary situation, and even reducing social activities with relatives. In this context, it is important to assess EP situations and identify those factors that most affect each one. This paper, through the evaluation and adaptation of the Three-dimensional and Territorial Indicator of Energy Poverty (EPITT in Spanish), developed by the Energy Poverty Network in Chile (RedPE Chile), assesses the different EP situations in a social-housing case study located in south-central Chile. The results show different EP situations depending on the dimensions studied, e.g., 35% of households had food and hygiene issues, 27% had issues with lighting and electrical devices, 72% with climate control in the home, and 68% experienced equality in energy expenditure issues. It is possible to say that energy expenditure is the dimension that most influences the EP situation. Furthermore, the values in the different dimensions are below the national average, mainly because of the poor quality of housing, limitations in access to energy, and low income. In conclusion, the adaptation of EPTTI provides a better understanding of EP vulnerability at the local scale. [ABSTRACT FROM AUTHOR]

Today, identifying energy poverty is one of the scientific community's challenges. In this sense, using Geographic Information Systems (GIS) assumes getting to know which areas are the most vulnerable. This study considers the development of a new territory energy poverty evaluation indicator, called Poverty Adaptive Degree Hourly Index (PADHI). The novelty of this indicator is that it combines the number of inhabitants in poverty with the hourly heating and cooling degrees of each climate, determined using adaptive thermal comfort limits based on ASHRAE 55-2017. The area studied focuses on Chile and its 346 municipalities. The application of the adaptive comfort model can exceed 90% in the north of the country and be below 20% in the most meridional areas. The results also outlined that the municipalities defined as PADHI's 10th decile are those which have a higher risk of energy poverty in their population, a higher percentage of income poverty and climatic severity. A cluster analysis was also run for this decile, identifying two risk groups with the aim of identifying the critical areas. This methodology applied to Chile, but international in nature, allows identifying priority areas on which the measures needed to reduce energy poverty can be focused. • Development of the Poverty-Adaptive Degree Hourly Index (PADHI) • Analysis of Chile's municipalities • It is detected that the country's southern municipalities have a lower energy poverty risk. • The most populated areas and those with higher energy demands are the most vulnerable municipalities. [ABSTRACT FROM AUTHOR]

• Fuel Poverty Potential Risk Index (FPPRI) applied to Santiago, Concepción, and Valparaiso (Chile). • A total of 116,640 cases were analysed, considering 9 morphological variables per decile. • Combination of 84 datasets using 2 approaches. • Performance greater than 96% of the individual models for each climate zone. Many studies are focused on the diagnosis of fuel poverty. However, its prediction before occupying households is a developing research area. This research studies the feasibility of implementing the Fuel Poverty Potential Risk Index (FPPRI) in different climate zones of Chile by means of regression models based on artificial neural networks (ANNs). A total of 116,640 representative case studies were carried out in the three cities with the largest population in Chile: Santiago, Concepción, and Valparaiso. Apart from energy price (EP) and income (IN), 9 variables related to the morphology of the building were considered in approach 1. Furthermore, approach 2 was developed by including comfort hours (NCH). A total of 84 datasets were combined considering both approaches and the 5 most unfavourable deciles according to the income level of Chilean families. The results of both approaches showed a better performance in the use of individual models for each climate (MLP C , MLP S , and MLP V), and the dataset with all deciles (Full) could be used. Regarding the influence of the input variables on the models, IN was the most determinant, and NCH becomes important in approach 2. The potential of using this methodology to allocate social housing would guarantee the main objective of the country: the reduction of fuel poverty in the roadmap for 2050. [ABSTRACT FROM AUTHOR]

Energy poverty is a multidimensional and complex phenomenon, and several indicators have been developed to evaluate and quantify it. However, often greater complexity does not mean greater precision. In the case of Chile, the Energy Poverty Network established the Three-dimensional and Territorial Indicator of Energy Poverty (EPTTI in Spanish) to assess the energy poverty situation of Chilean families. The EPTTI is based on a multidimensional approach with 10 indicators. Although, their evaluation involves resources that may hinder a practical application. This study analyzed the consistency between the individual responses of an indicator and the adapted EPTTI evaluation, using a database of 641 families. The results show that the excessive energy expenditure and the type and energy source of heating systems indicators are the variables with the greatest influence on energy poverty assessments. These results served to both propose simplified approaches for energy poverty assessment with the indicator, and establish policies of action that regional governments should address to reduce the situation of energy poverty. [ABSTRACT FROM AUTHOR]

The reduction of energy consumption and CO 2 emissions in buildings has become an essential field of study in the recent years. Simplified design tools, used in the first design stages, can be of great help in adopting concrete decisions that will, at the end, allow these to be reduced. This paper presents a new predictive model for office buildings in Chile. Starting from the 1,386,000 study cases pursuant the ISO 13790:2008 standard, 18 multivariable regression models have been generated, 9 for energy consumption and 9 for CO 2 emissions., They have been adapted to each climatic zone in Chile. In these case studies, 8 fundamental variables have been considered to cover the design parameters. This research considers number of stories (NS), floor area (FA), form ratio (FR), window-to-wall ratio (WWR), coefficient of performance (COP), Energy efficiency ratio (EER), heating emission factors (HEF) and cooling emission factors (CEF). The models generate an R 2 between 91.81% and 98.05% for energy consumption and between 96.83% and 99.56% for CO 2 emissions, with the results of this research being incorporated into future regulations and into the first stages of design for office buildings in Chile. As an expected outcome, the model will contribute to reduce, or at least contain, energy consumption and CO 2 emissions associated with office buildings in the future. [ABSTRACT FROM AUTHOR]

Numerous studies about climate change have emerged in recent years because of their potential impact on many activities of human life, amongst which, the building sector is no exception. Changes in climate conditions have a direct influence on the external conditions for buildings and, thus, on their energy demand. In this context, computer aided simulation provides handy tools that help in assessing this impact. This paper investigates climate data for future scenarios and the effect on energy demand in office buildings in Chile. This data has been generated in the 9 climatic zones that are representative of the main inhabited areas, for the years 2020, 2050 and 2080. Predictions have been produced for the acknowledged A2 ‘medium-high’ Greenhouse Gases emissions GHG scenario, pursuant the Intergovernmental Panel on Climate Change (IPCC). The effect of climate change on the energy demand for office buildings is optimized by implementing the calculation procedure of ISO-13790:2008, based on iterations of its envelope and form. As a result, this research clarifies how future climate scenarios will affect the energy demand for different types of office buildings in Chile, and how their shape and enclosure can be optimized. [ABSTRACT FROM AUTHOR]

Including recycled waste material in cement mixes, as substitutes for natural aggregates, has resulted in diverse research projects, normally focused on mechanical capacities. In the case of recycled glass as an aggregate, this provides a noticeable improvement in thermal properties, depending on its dosage. This idea raises possible construction solutions that reduce the environmental impact and improves thermal behavior. For this research, an extended building typology that is susceptible to experiencing the risk of energy poverty has been chosen. The typology is typical for social housing, built using mortar blocks with crushed glass. First, the basic thermophysical properties of the mortars were determined by laboratory tests; after that, the dynamic thermal properties of representative constructive solutions using these mortars were simulated in seven representative climate zones in Chile. An analysis methodology based on periodic thermal transmittance, adaptive comfort levels and energy demand was run for the 21 proposed models. In addition, the results show that thermal comfort hours increases significantly in thermal zones 1, 2, 3 and 6; from 23 h up to 199 h during a year. It is in these zones where the distance with respect to the neutral temperature of the m50 solution reduces that of the m25 solution by half; i.e., in zone 1, from −429 °C with the m25 solution to −864 °C with the m50. This research intends to be a starting point to generate an analysis methodology for construction solutions in the built environment, from the point of view of thermal comfort. [ABSTRACT FROM AUTHOR]

Data simulated for occupancy profiles, usually based on standard occupancy schedules, must be validated against real measurements, and many studies have pointed out the gap between them. This problem is more pronounced in homes that are not heated by grid-connected energy sources, such as wood-burning stoves, because the meter cannot provide a real-time estimate. In Central-South Chile, 74% of homes are heated by wood stoves, causing an acute problem of air pollution in several urban areas. The government is trying to solve this problem, but at the moment there is no data on occupancy profiles, hence it is not possible to estimate the energy intensity for heating. This exploratory study aims to clarify to what extent occupancy profiles can be estimated from PM 2.5 pollution levels. To this end, publicly available data on PM 2.5 concentrations in 17 cities in central-south Chile was used as a proxy to build occupancy schedules for homes heated by wood stoves. The results show that there is a clear relationship between pollution levels and occupancy intensity, and that the latter does not follow the schedules outlined in international standards or building codes. The results and methodology can be replicated in cities where air pollution is driven by wood stoves, allowing public authorities to have access to accurate occupancy schedules and providing them with reliable data to address local air pollution problems. [ABSTRACT FROM AUTHOR]