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Abstract Developing countries face a crisis of deteriorating and unsafe human settlements conditions. Few studies examine the resources and energy required to provide everybody with decent housing. This study presents a generic methodology for the estimation of Life Cycle Energy (LCE) requirements to meet the housing gap and provide basic comfort to everybody in a developing country, based on standards of safety, durability and indoor temperature and humidity limits. The methodology includes the operationalization of this decent housing standard into materials and equipment; development of appropriate building archetypes; calculation of embodied and operating energy using a building simulation model; a parametric analysis to investigate the range of uncertainty in LCE and the attribution to different contextual conditions and energy savings measures. Results for the test case India showed that LCE of decent housing can significantly vary depending on climatic conditions, building typology, construction materials, technical equipment for space cooling-dehumidification and user behaviour. Embodied energy accounts for 27–53% of the LCE, depending on the building type and climate. LCE savings of up to 44% can be achieved with low embodied energy materials, building envelope insulation, ceiling fans and more efficient air-conditioning systems.

Abstract Adaptive comfort plays an important role in defining comfort standards when considering comfort in buildings in free-running mode, including adaptation to external temperatures, opening windows and changing clothing. In this regard, two international standards provide the fundamental basis to model the necessary equations: EN 16798 (formerly 15251) and ASHRAE 55–2017. This research intends on assessing the feasibility of applying these standards to the Chilean context, where a legal framework has begun to be implemented to regulate the occupant's comfort in social housing. Extensive monitoring of inhabitants in existing units under free-running mode has been undertaken in several social housing projects in the city of Concepcion (Chile) and the collected data has been contrasted against the international standards. Results show that users in these houses show more tolerance to cold temperatures, thus, despite being allocated below the standards' lower limits, they are considered to be in thermal comfort. As a result, the outcomes of this research can shed light on the feasibility of applying international standards to social housing and low-income families in Chile. The study presents a proposal for a novel adaptive comfort model for Chile. The new model proposes adapting the thermal comfort threshold's lower limit in order to develop a national standard that better reflects the inhabitants' needs and socio-economic culture. The study demonstrates how the proposed model best fits the thermal comfort conditions in social housing in Chile.

Abstract With growing health risks from rising temperatures in the Global South, the lack of essential indoor cooling is increasingly seen as a dimension of energy poverty and human well-being. Air conditioning (AC) is expected to increase significantly with rising incomes, but it is likely that many who need AC will not have it. We estimate the current location and extent of populations potentially exposed to heat stress in the Global South. We apply a variable degree days (VDD) method on a global grid to estimate the energy demand required to meet these cooling needs, accounting for spatially explicit climate, housing types, access to electricity and AC ownership. Our results show large gaps in access to essential space cooling, especially in India, South-East Asia and sub-Saharan Africa. Between 1.8 to 4.1 billion, depending on the required indoor temperatures and days of exposure, may need AC to avoid heat related stresses under current climate and socio-economic conditions. This number far exceeds the energy poverty gap indicated by the Sustainable Development Goal for electricity access (SDG7). Covering this cooling gap would entail a median energy demand growth of 14% of current global residential electricity consumption, primarily for AC. Solutions beyond improved AC efficiency, such as passive building and city design, innovative cooling technologies, and parsimonious use of AC will be needed to ensure essential cooling for all with minimized environmental damage. Meeting the essential cooling gap, as estimated by this study, can have important interactions with achieving several of the SDGs.

Abstract Cities in China have undergone considerable transformation in recent decades with unprecedented economic growth, rural to urban migration and a rapidly emerging middle class all contributing to increased energy consumption. In this context, we investigate the inability of urban households in the cold climate zone in northern China to access sufficient domestic energy services, and thus their vulnerability to energy poverty, focusing upon heating provision. Results of a questionnaire survey of households in the urban area of Beijing (n = 880) are analysed using Latent Class Analysis, a methodologically novel approach to developing a typology of energy poverty. The analysis highlights vulnerabilities that increase the likelihood of a household being unable to access adequate heating in the home in this context. Despite provision of state-subsidies for heating in cities in northern China, a mechanism that might be anticipated to buffer households from energy poverty, these do not shield from the cold those households that lack access to efficient and flexible networked infrastructures, or a high quality, built environment. Our findings represent the first detailed study of energy poverty in relation to heating in this geographical context and have significant implications for domestic policy-making concerned with energy poverty, residential energy efficiency and energy consumption.

Abstract 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, Concepcion, 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 (MLPC, MLPS, and MLPV), 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 Research on natural cooling of buildings has produced an extensive scientific bibliography since 1980s. Nevertheless, few examples of complete experimental systems are registered, and rigorous procedures for their dimensioning are currently not available. This work analyses the performance of an air-based low energy radiative cooling system in Chile. The system is composed of a series of specialized radiative air collectors, a mechanical ventilation system, and a thermal storage wall, which is part of the indoor environment. The design has been tested in an experimental prototype where external and internal environmental conditions have been monitored during a full week in midsummer conditions. The data obtained is used to validate an analytical model designed to study the behavior of each component and the system’s performance. This work studies the relationship between the radiator surface, the air volume flow rate, and the thermal storage wall volume that serves to neutralize the thermal loads, maintaining comfortable temperature conditions throughout the day. Comparison of the simulations with and without thermal conditioning has been conducted. In term of the system sizing, a thermal wall of 2.55 m3 and a total air flow rate of 48 m3/h is required to reach the optimal operating point of the first floor of the house. A sensibility analysis indicated that increasing the number of collectors slightly reduces the wall’s size. Based on these conditions, the work concludes with the proposal of a simple procedure for the sizing of passive cooling systems installed in social housing developments.

Chile is a South American country experiencing greater social and economic development than the majority of its neighbours and whose economy is transitioning from developing to developed status. It is committed to reduce its greenhouse gas (GHG) emissions by 35–45% by 2030, requiring national energy demand reduction. Chile's housing stock is responsible for 15% of its total final energy consumption and so its Government is regulating the construction of new dwellings, although it is difficult to know if this policy will succeed or lead to unintended consequences affecting energy demand, GHG emissions, and occupant health. Measuring the effects in situ is often time and cost prohibitive and so the simulation of archetypal buildings is a common method of investigation. A range of data sources, such as censuses and building permits, are used to develop archetypal Chilean houses with statistically significant representative values for design parameters related to energy demand and indoor air quality. It finds that 496 archetypes can represent 100% of the Chilean housing stock and only 90 can represent 95% of the stock. The archetypes can be used to predict and evaluate the impacts of policies on indoor air quality and the energy demand of a stock of houses, or to guide future data gathering exercises. The data analysis highlights knowledge gaps in categorical descriptors and occupant behaviours, and poor granularity of physical data. These gaps should be filled by augmenting national surveys and complimented by field work.