Resilience Ruler for Energy Efficiency: An Evaluation of Social Housing Refurbishment

In 2022, a survey showed that around 96% of the houses in one of the residential complexes in the city of Uberlândia (Minas Gerais state, Brazil) underwent some refurbishment within ten years [1]. This research also reported that most residents in the neighborhoods Pequis (63.5%) and Shopping Park (69.23%) observed an increase in their electricity bills over the years. The level of dissatisfaction was high for both residential complexes: 75% for Pequis and 83.34% for Shopping Park. This study assessed the refurbishment of one-story houses in two residential complexes built by the Brazilian social housing program “Minha Casa, Minha Vida” (“My House, My Life” in English) (MCMV) located in the city of Uberlândia, Minas Gerais state, Brazil. The main purpose was to evaluate the refurbishment and interventions performed by the residents to understand their impacts and develop the indicators and methodologies to assess energy efficiency resilience in the built environment. This paper is also a way to achieve the goals Sustainable Cities and Communities and Good Health and Well-being, of the Sustainable Development. The contribution is made by analyzing the MCMV houses and assisting in more sustainable refurbishments.

This research sheds light on the theme of resilience in the environment built in SH in the Brazilian context through investigation “[RESILIENT HOUSE] Design strategies for promoting resilience in social housing from post-occupancy evaluation methods”. The research, developed during the years 2020 to 2023 by the group [MORA] Housing Research at the Faculty of Architecture and Urbanism and Design at the Federal University of Uberlândia, was funded by the CNPq - National Council for Scientific and Technological Development (PQ-CNPQ Nº 311624/2021-9). The ongoing research project aims to identify and provide design strategies for refurbishment and interventions in horizontal single-family social housing, promoting their resilience. The information will be available to architects, contractors, and residents on multiple digital platforms (web and mobile applications). The design strategies were identified by post-occupancy evaluation (POE) applied to the case study. We also aimed to identify the main design attributes and resilience indicators of these refurbishments, including energy efficiency. Figure 1 presents a schematic view of the Resilient House matrix developed by the research group, in which each researcher investigated one attribute, such as environmental comfort, flexibility, etc., to define the indicators. This paper investigates energy efficiency.

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Figure 1. Resilient house assessment matrix (RHAM): Attributes and indicators

We present the results of the proposed methodology for the energy efficiency resilience assessment, named the Resilience Ruler (RR). The RR is a way to assess the resilience, inspired in a tool developed by World Resources Institute (WRI). In this work, the objective was to measure the resilience level in the built environment based on energy efficiency indicators and parameters. The parameters are references to numbers, used to describe the measurement scales for resilience. They are supported by scientific research that has already been consolidated and validated, technical standards, and the national context of Brazil. The indicators on the ruler identify important structural components or social practices that enable homes and their occupants to defend themselves against external forces and thereby increase their resilience [2]. This paper is divided into theoretical basis, methods, case study, results and discussion, and conclusions to validate and develop the RR.

First, we applied Design Science Research [11] to the energy audit procedure for buildings adapted from ASHRAE (American Society of Heating, Refrigerating, and Air-Conditioning Engineers), summarized by Figure 2. In DSR, the project is researched and studied through the design of artifacts, developing solutions for existing systems. Two aspects were developed following these methodologies. The first aspect is a set of POE procedures that include data collection on energy consumption, a questionnaire on energy efficiency, a walkthrough, and the RR (a). The second aspect comprises the registration forms created from the RR results, highlighting the main efficiency problems in social housing (b). These items (a) and (b) are artifacts. This paper focuses on item (a).

POE is crucial in this study since it is a set of methodological procedures that verifies if the built environment meets the subjective and objective needs of the residents over time. Mapping human behavior, observing the standard activities of the residents, and collecting photographs of the built environment can provide good elements to analyze and improve the concepts [10].

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Figure 2. Set of mechanisms used for impact identification and energy efficiency resilience assessment

The first step for an energy audit is to analyze the current energy consumption. We analyzed the electricity bills of 18 houses, nine from each residential complex, for one year. The houses were selected after pass for three moments: different solar orientations of the main facade, houses with refurbishments with and without extensions and finally convenience, according with the resident availability. Energy consumption varied due to external factors, such as climatic variation, and internal factors, such as occupancy changes. From this analysis, energy consumption became clear.

In the second step, we analyzed architectural designs, electrical designs, and descriptive memoranda provided by the construction companies. In the third step, we applied a questionnaire together with a technical visit, in which we could check the electrical appliances, building envelope, lighting, and other systems that could interfere with energy consumption.

The energy efficiency resilience assessment is based on the [RESILIENT HOUSE] research mechanism, which was inspired by the Urban Community Resilience Assessment (UCRA), a tool developed by World Resources Institute (WRI). This RR was applied in collaboration with Rio de Janeiro and Porto Alegre municipal governments to evaluate urban community resilience to extreme weather events.

The RR was developed to assess the resilience level in the built environment based on indicators and their parameters. This analysis evaluates the physical features of the houses, considering their capacity to meet the needs of the residents, presenting a behavioral scale. Thus, the RR could be developed based on the energy efficiency criteria for bioclimatic zones, which includes the social housing selected, and the definition of indicators and design strategies. The design strategies evaluate the designs' resilience related to energy efficiency and, based on the results, define the possible strategies that should be developed for the resident and architect.

The RR measures resilience by considering attributes and indicators, the physical features of the built environment (floor and lot area), and residents’ behavior. It measures the adaptive/vulnerability capacity within each attribute. From this built environment assessment, we seek refurbishment design strategies for these vulnerabilities to improve resilience. In addition, this analysis also increases the importance of the methods used in the case study and relates them to the problems identified, which allows the relationship between the parameters and the qualitative and quantitative data.

Figure 3 shows the Resilience Ruler (RR), which is structured as follows: (i) indicators; (ii) sub-indicators and definitions; (iii) score varying from 1 (not resilient) to 5 (very resilient); (iv) parameters based on national and international references and researcher experience; and (v) data collection tools, which included walkthrough and questionnaire.

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Figure 3. Resilience Ruler (RR)

To measure the resilience level in building energy efficiency, we compiled parameters that could evaluate indicators in social housing. These criteria are based on the literature review, current regulations, some Brazilian certifications, such as Selo Casa Azul (Blue House Seal), and procedures for building energy efficiency labeling.

The Resilience Ruler for energy efficiency resilience assessment included five indicators: energy-efficient building envelope, water heating system, energy-efficient lighting, energy-efficient electrical appliances, and integration of green spaces. The indicators were chosen after a detailed literature review: the survey of ownership and use habits of electrical equipment in the residential Class 2019 of Brazil, brought the weight of the consumption of electrical equipment in energy consumption [7]; the ASHRAE (American Society of Heating, Refrigerating, and Air-Conditioning Engineers) emphasizes the building envelope, lighting, hot water and electrical appliances as a scope of energy consumption. From a Brazilian residential perspective, the same items appear [6, 12-14]. Overall, the authors agree that how occupants control heating and ventilation systems is an important factor [14-16]. In addition, the integration of green spaces in the residential context has been studied internationally by some authors, influencing on the time spent outdoors and indoors [15, 17, 18]. Figure 4 summarizes the concepts developed by the group.

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Figure 4. Concepts obtained from the studies performed by the research group

The energy-efficient building envelope sub-indicators were efficient materiality, efficient geometry, and maintainability. The water heating system sub-indicators were efficient heating systems and maintainability. The energy-efficient lighting sub-indicators were natural lighting and LED lighting. The energy-efficient electrical appliance sub-indicators were electrical appliances with the PROCEL (National Program for Energy Conservation) Seal and newer electrical appliances. The conscious behavior sub-indicators were daily habits and consciousness. Green spaces sub-indicators were integrated landscaping and green preservation. Each sub-indicator parameterization was based on normative ruling, methodologies for sustainability assessment, such as seals and certifications, and researcher experience. The parameterization was rated from 1 to 5, in which 4 (resilient) is the minimum level to maintain the quality of the housing units. The RR was applied using walkthrough and questionnaire tools. The scores were processed using a spreadsheet, with the rating for each house after applying the parameters. The general rating of the sub-indicators was the result of a simple general average. In the result section, statistical tests were performed to determine the significance between the two neighborhoods: G Test (likelihooh ratio test) for Table 1 and Mann-Whitney test for Table 2. The design strategies were derived from the 1 to 3 scores. The application of the RR made during the research aimed to provide initial guidance for calibration. The approach was carried out based on the presentation of the researcher, duly identified, with the use of safety equipment (mask, face shields and alcohol gel). Soon after the presentation, there was an invitation to participate in the questionnaire (reinforcing the confidentiality of the data), if a positive response was received, a disposable mask would be offered. The instruments were applied only after the respondent read, understood and accepted the Free and Informed Commitment Term.

5.1 Indicators

We aimed to identify the main elements of energy consumption in the housing units during their use and occupancy based on the literature review and the items listed in the energy audit procedure. Table 1 presents the indicators for energy efficiency resilience in the built environment.

To evaluate the energy-efficient building envelope, we considered the literature review, the Regulation for Energy Efficiency of Residential Buildings (RTQ-R), and the Immetro Normative Instruction for the Classification of Energy Efficiency in Residential Buildings (INI-R). These methodologies allow us to understand the building energy performance, helping to seek and guarantee more efficient buildings [20]. Climate context should be considered to choose the materiality together with the housing design [18].

Lighting plays an important role in reducing energy consumption. Natural and artificial lighting are linked to environmental comfort and space usage [18]. In Brazil, artificial lighting represents, on average, 15% of the electricity consumption [7]. The lighting design should consider the best use of natural light. Thus, the housing units can significantly save energy if the artificial light remains off [6].

Table 1. Energy efficiency indicators to increase resilience in social housing

The characteristics of each Brazilian bioclimatic zone should be considered to define a more efficient water heating system. The Survey of Ownership and Habits of Use of Electrical Appliances in Residential Class, released in 2019, mapped the use of electrical showers in Brazil. Within the income level D-E in the southeast region, 69.11% of Brazilians use electrical energy for heating water, and for those using solar water heating systems (0.64%), only 50% perform periodic cleaning of the solar panels. Solar water heating system is unknown for 43.18%. Most residents would not change the heating system (60.14%) or would not use the solar heating system (47.14%). These data show that promoting alternative sources for heating water is necessary.

The energy consumption of electrical appliances in Brazil tends to increase. In addition, the electrical appliances inside the residences have been growing. For instance, a function earlier performed exclusively by a refrigerator is now also performed by a freezer or an electric water filter [3]. Promoting the use of electrical appliances that save energy can contribute to energy safety and lower environmental impacts.

The resident behavior sets the relationship between building occupancy and energy saving. Several studies have highlighted that building characteristics and resident behavior are important in energy consumption levels. Energy consumption significantly varies in buildings with the same characteristics, mainly due to space usage, domestic work, lifestyle, cognitive variation, and comfort perceptions [18].

The relationship between buildings and vegetation is crucial to mitigate microclimate since green spaces change the air moisture and temperature, filter the sunlight, and absorb the noise and air pollution. Afforestation and vegetation in urban areas, including in the lots, positively influence air moisture and temperature and provide a friendly microclimate, improving the resident’s quality of life [21].

5.2 Questionnaire on energy efficiency

To identify the impacts and problems related to energy efficiency, the questionnaire addressed building envelope, lighting, water heating system, electrical charge, behavior, and green spaces. These items are the indicators, and they are detailed as follows.

The first part of the questionnaire aimed to identify the family configuration of the residents, the number of people, age, the value of the electricity bill, and if they considered the electricity bill expensive. For the building envelope, we analyzed whether there was some refurbishment and whether the original house characteristics were preserved or replaced. For lighting, we evaluated the use of artificial or natural lighting. Considering the water heating system indicator, we analyzed whether the solar system delivered was working or being used and whether there was an electric shower. The questions on electrical appliances observed the number of appliances, time and frequency of use, and whether they received the National Energy Conservation Label (ENCE). For the behavior indicator, we evaluated how long the residents stayed at home, the residents’ professional occupation, and what may interfere with using electrical appliances, such as natural ventilation or natural lighting. The green space indicator assessed whether there was vegetation in the buildings, which mitigates the effect of heat.

We also considered more accessible language to the residents when developing the questionnaire. Before applying the questionnaire, a test was conducted in ten houses randomly selected to calibrate the questions. A walkthrough model was also developed, with items to be observed by the researcher to complete the understanding of the built environment.

We performed a descriptive analysis of the results to identify the scenario experienced by the residents and the impacts observed by them. We also observed the most repeated issues related to the energy efficiency indicators.

Most residents that answered the questionnaire earn between one and two minimum wages and pay between R\$100.00 and R\$200.00 in their electricity bills. Some families fit into the Social Tariff, in which only the minimum rate is charged while the resident is unemployed. The electricity bill is expensive for 80% of the residents in both neighborhoods. The results showed that the number of people living in the house did not affect the value of the electricity bill.

In the Shopping Park neighborhood, all residents answering the questionnaire had already done some refurbishment, in which 57% performed expansions, 23% replaced some frames, and 6% replaced the type of roof tile. In the Pequis neighborhood, 65% of the residents had already done some refurbishment, which corresponded to expansion (50%), frame replacement (23%), roof replacement (3%), and electrical panel replacement (3%). In the Shopping Park neighborhood, 73% had already performed some maintenance, 53% replaced the electrical wiring, 23% painted the house, 15% cleaned the solar heating system, and 3% cleaned the roof. In the Pequis neighborhood, 65% performed maintenance in the houses, corresponding to electrical wiring replacement (34%), house painting (7%), and cleaning the solar heating system (3%). These constant interventions show the low quality of the houses delivered to the families.

Table 2. Main results for the energy-efficient building envelope indicator

The energy supply system is single-phase, and both neighborhoods presented electrical overload. The residents have already recorded fire and power failures due to short circuits induced by the electrical appliances. Some residents decided to replace the electrical panel with a two-phase system and replace all the electrical wires. Regarding lighting, 54% of the residents in Pequis considered natural light to be very good. In Shopping Park, 46% of the residents considered natural light to be good. Excess sunlight was more inconvenient for the residents of Pequis than for Shopping Park. Thus, when there is excess sunlight, artificial lighting is used for internal balance. Both residential complexes were delivered with a solar water heating system. However, most residents still use electrical showers. The solar water heating system presented some operational problems, such as heating problems and leakage. Due to lack of maintenance, we observed that the residents tend not to use the solar water heating system over time. In addition, few residents reported they received the user and maintenance manual.

Regarding electrical appliances, the fridge was the most common in the residences. Most of the fridges, 65% in Shopping Park and 77% in Pequis, were bought more than five years ago. Only 50% of the residents in Pequis stated that their fridge has the ENCE label, against 80% in Shopping Park. Regarding sidewalk trees, most residences in Shopping Park did not have them and had no interest in having them.

To analyze the behavior indicator, we compiled the main results that show the behavioral profile of the residents. In the social housing context, passive building strategies play an important role and are partially controlled by the resident. The housing units were delivered with window shutters in all bedrooms, but some were replaced in the refurbishment. In Shopping Park, 11.45% of the housing units no longer have window shutters, while 3.85% in Pequis ignore the use of window shutters. Most residents use window shutters for lighting control (darken the room) and natural ventilation (refresh the room). We also observed that most residents in both neighborhoods close the glass window at some point, 61.54% in Shopping Park and 80.77% in Pequis, either to stop the ventilation (> 34%) or for security measures (> 26%). Analyzing the green space, we considered the presence of vegetation inside the lots and on the sidewalk, as shown in Figure 7. Plants and tree cultivation can help filter the air and provides shade. We observed plants in the houses, and the residents understood their importance to the environmental quality of the house. Most houses had permeable spaces with grass, shrubs, trees, or potted plants (more than 79%).

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Figure 7. Vegetation inside the lots

5.3 Resilience Ruler (RR)

The RR was initially applied for calibration. We selected ten housing units, five from each neighborhood, to participate in the initial survey, questionnaire, and walkthrough. The first applications of the RR showed that the parameters needed some adjustments. The RR should be applied according to the Brazilian bioclimatic zone where the housing units are located since each local has climatic characteristics affecting the building energy efficiency. The RR application was descriptive, considering the particularities of each neighborhood. A weight was assigned for each letter, being A=5, B=4, C=3, D=2, and E=1, as indicated in Figure 8.

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Figure 8. Resilience assessment framework

Table 3 presents the main results of applying the RR. In general, the two neighborhoods were moderately resilient. Even presenting different architectural and constructive characteristics, the RR was similar to almost all indicators. Energy-efficient building envelopes reported the worst RR in both neighborhoods. Efficient materiality and maintainability were not resilient and little resilient, respectively. Efficient geometry achieved a satisfactory result, being resilient in both neighborhoods.

For the water heating system, the two neighborhoods were little resilient. Since the housing units in the Shopping Park neighborhood were delivered earlier than in the Pequis neighborhood, we observed a higher tendency to use an electrical shower than the solar water heating system. Maintenance in both neighborhoods was very low and characterized as not resilient.

Energy-efficient lighting reported the most divergent results between the two neighborhoods. The Pequis neighborhood was characterized as very resilient, while Shopping Park was moderately resilient. This difference is due to the number of expansions the Shopping Park housing complex underwent in ten years. In the expansions, some rooms may not receive natural light since the openings are blocked or removed.

Energy-efficiency electrical appliance results were similar and characterized both neighborhoods as moderately resilient. In Shopping Park, the residents showed better knowledge about ENCE labels and the importance of purchasing more energy-efficient appliances. Regarding conscious behavior, both neighborhoods were moderately resilient. However, residents in Shopping Park were more conscious than those in Pequis. The houses’ energy bill in Shopping Park is more expensive than Pequis, leading the residents to save energy more often.

The results for integration of green spaces were different for both neighborhoods. Green preservation was little resilient in Pequis and moderately resilient in Shopping Park. Landscaping was moderately resilient in Pequis and very resilient in Shopping Park. The residents received the housing units without green space infrastructure. The residents built walls around the housing units to contain the dust from the permeable surface. Few residents have gardening habits or seek to preserve the trees in the lots. This standard behavior was more evident in Pequis than in Shopping Park.

The p-value near or less than 0.05 shows the differences between the two neighborhoods that are statistically significant. In this way, we can highlight: the type of roof; electric shower use; time of electric shower use; activities outside the house; avoid the standby mode. For future applications in Brazilian bioclimatic zones, the RR parameters should be adjusted according to the relevant characteristics of the region. The RR application highlighted the main problems in energy efficiency resilience in the built environment. From this analysis, we can propose design strategies for refurbishments and interventions that are more energy efficient. Such as helping choose the best painting color for the external walls or calculating the windows’ protection from the direct sunlight that can improve the energy consumption.

The authors thank the National Council for Scientific and Technological Development (PQ-CNPQ Nº 311624/2021-9), Research Support Foundation of the State of Minas Gerais) and to the Improvement of Higher Education Personnel – CAPES, PPGAU/UFU for supporting this study.