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The COVID-19 pandemic has been a catastrophic event that has affected all aspects of human life worldwide. Due to the high genetic mutations of the virus, there has been a prolonged search for definitive therapeutic discovery, leading to extended periods of home quarantine. As a result, homes have become multipurpose spaces for work, education, sports, and other daily activities. Given the importance of residential buildings as the first line of defense against possible future pandemics, a model has been proposed to assess their readiness to handle pandemics using a sustainable development approach. This study investigates the most crucial criteria for evaluating residential buildings and applies them in a Multi-Criteria Decision Making (MCDM) process. The final evaluation model is presented using the SWARA and COCOSO methods, along with a set of criteria selected and weighted by experts. The study shows that the criteria related to health and safety are more critical than other sectors. Buildings that meet the standards of this group better are likely to have a higher score.
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This research focuses on achieving sustainable development in residential buildings with energy use. Under the influence of the energy crisis and related problems, research on residential buildings for less energy use has great potential. The literature review, according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses, and including VOSviewer analysis, shows the research is increasing and meaningful. Solar Decathlon buildings are used as the main objects in this research. The fifth Solar Decathlon Europe energy use technologies are examined through onsite investigation and online searching. The Analytic Hierarchy Process method for multi-criteria decision analysis is used for sustainability assessment. Moreover, the Ladybug and ClimateStudio plugins simulated respectively the annual solar radiation and the best angle for receiving it. The main findings show that 34 kinds of technologies used in these buildings can be classified into two categories in three directions. Passive technologies should be applied and prioritized, but generating renewable energy is also important. Some infrequently used technologies are not insignificant. The research shows that the combination of technologies decides sustainability performance, but the quantity used does not. Furthermore, energy use also needs to be balanced and coordinated in combination with architectural aesthetics. This research on energy use in residential buildings is beneficial for achieving sustainable development.
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The residential sector's substantial electricity consumption, driven by heating demands during winter, necessitates optimal energy consumption strategies in the era of decarbonization. To address this challenge, this paper introduces a synthetic dataset specifically tailored to simulate energy consumption in residential apartment buildings. Focusing on the interplay of cold weather conditions and the effects of aging factors, the dataset comprehensively encompasses key variables, including indoor temperature, energy consumption, outdoor temperature, outdoor humidity and solar radiation. It underscores the considerable impact of building aging on energy consumption patterns. The dataset's significance extends across various domains, particularly in the realms of energy forecasting and thermal modelling. It serves as a robust foundation for predicting future consumption patterns, optimizing resource allocation, and refining energy efficiency strategies. The inclusion of indoor temperature data facilitates an in-depth thermal modelling approach, shedding light on intricate relationships that influence building performance in cold climates. Beyond traditional, the dataset proves invaluable in nonlinear modelling and machine learning. It emerges as a key tool for algorithm training, enhancing forecast precision, and supporting well-informed decision-making. The introduction of a temporal dimension by accounting for aging factors allows for the exploration of evolving building components over time, a critical consideration for sustainable energy management and building maintenance strategies. The dataset was meticulously generated by creating geometry using SketchUp and conducting energy modelling and simulations via the OpenStudio platform, which integrates the Energy Plus modelling engine to enhance accuracy. In summary, this synthetic dataset generation provides valuable insights into energy consumption in residential buildings exposed to cold weather conditions and the influences of aging. Its multifaceted applications across forecasting, modelling, management, and planning underscore its potential to advance sustainable and efficient energy practices.
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In February 2021, a cluster of Beta variant (B.1.351) coronavirus disease 2019 (COVID-19) cases were identified in an apartment building located in Northern Ontario, Canada. Most cases had no known contact with each other. Objectives of this multi-component outbreak investigation were to better understand the social and environmental factors that facilitated the transmission of COVID-19 through this multi-unit residential building (MURB). A case-control study examined building-specific exposures and resident behaviours that may have increased the odds of being a case. A professional engineer assessed the building's heating, ventilation, and air-conditioning (HVAC) systems. Whole-genome sequencing and an in-depth genomic analysis were performed. Forty-five outbreak-confirmed cases were identified. From the case-control study, being on the upper floors (OR: 10.4; 95% CI: 1.63-66.9) and within three adjacent vertical lines (OR: 28.3; 3.57-225) were both significantly associated with being a case of COVID-19, after adjusting for age. There were no significant differences in reported behaviours, use of shared spaces, or precautions taken between cases and controls. An assessment of the building's ventilation found uncontrolled air leakage between apartment units. A single genomic cluster was identified, where most sequences were identical to one another. Findings from the multiple components of this investigation are suggestive of aerosol transmission between units.
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COVID-19 , Humanos , Estudios de Casos y Controles , COVID-19/epidemiología , Brotes de Enfermedades , Ontario/epidemiología , Aerosoles y Gotitas Respiratorias , SARS-CoV-2RESUMEN
We investigated a COVID-19 cluster involved seven case-patients lived in a high-rise building in September 2021. We used a simplified tracer-gas experiment and virus sequencing to establish the link between case-patients. Vertical transmission among vertically aligned apartments on different floors in a building was the most likely route of transmission.
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COVID-19 , Humanos , COVID-19/epidemiología , Taiwán/epidemiología , Transmisión Vertical de Enfermedad InfecciosaRESUMEN
Energy-efficient residential building standards require the use of mechanical ventilation systems that replace indoor air with outdoor air. Transient outdoor pollution events can be transported indoors via the mechanical ventilation system and other outdoor air entry pathways and impact indoor air chemistry. In the spring of 2022, we observed elevated levels of NOx (NO + NO2) that originated outdoors, entering the National Institute of Standards and Technology (NIST) Net-Zero Energy Residential Test Facility through the mechanical ventilation system. Using measurements of NOx, ozone (O3), and volatile organic compounds (VOCs), we modeled the effect of the outdoor-to-indoor ventilation of NOx pollution on the production of nitrate radical (NO3), a potentially important indoor oxidant. We evaluated how VOC oxidation chemistry was affected by NO3 during NOx pollution events compared to background conditions. We found that nitric oxide (NO) pollution introduced indoors titrated O3 and inhibited the modeled production of NO3. NO ventilated indoors also likely ceased most gas-phase VOC oxidation chemistry during plume events. Only through the artificial introduction of O3 to the ventilation duct during a NOx pollution event (i.e., when O3 and NO2 concentrations were high relative to typical conditions) were we able to measure NO3-initiated VOC oxidation products, indicating that NO3 was impacting VOC oxidation chemistry.
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Contaminantes Atmosféricos , Contaminación del Aire Interior , Ozono , Compuestos Orgánicos Volátiles , Óxido Nítrico , Compuestos Orgánicos Volátiles/análisis , Contaminantes Atmosféricos/análisis , Contaminación del Aire Interior/análisis , Dióxido de Nitrógeno/análisis , Ozono/análisis , Monitoreo del AmbienteRESUMEN
Residential buildings generate significant greenhouse gas (GHG) emissions and consume energy throughout their life cycle. In recent years, research on GHG emissions and energy consumption of buildings has developed rapidly in response to the growing climate change and energy crisis. Life cycle assessment (LCA) is an important method for evaluating the environmental impacts of the building sector. However, LCA studies of buildings show widely varying outcomes across the world. Besides, environmental impact assessment from a whole life cycle perspective has been undeveloped and slow. Our work presents a systematic review and meta-analysis of LCA studies on GHG emissions and energy consumption in the preuse, use, and demolition stages of residential buildings. We aim to examine the differences among the results of diverse case studies and demonstrate the spectrum of variations under contextual disparities. Results show that residential building emits about 2928 kg GHG emission and consumes about 7430 kWh of energy per m2 of gross building area on average throughout the life cycle. Residential buildings have an average GHG emission of 84.81% in the use phase, followed by the preuse phase and demolition phase; the mean energy consumption in the use stage occupied the largest share of 84.52%, followed by preuse stage and demolition stage. GHG emissions and energy use vary significantly in different regions due to different building types, natural conditions, and lifestyles. Our study stresses the compelling requirement to slash GHG emissions and optimize energy consumption from residential buildings by use of low carbon building materials, energy structure adjustment, consumer behavior transformation, etc.
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Gases de Efecto Invernadero , Monitoreo del Ambiente , Materiales de Construcción , Carbono , Cambio Climático , Efecto InvernaderoRESUMEN
Today, an important problem of the building energy performance area is carrying out multi-criteria optimizations of real building designs. To solve this problem, a new method based on a meta-model is proposed in this study. Hence, the EnergyPlus™ is used as the simulation tool for the performance simulation of the building, then a couple of the multi-criteria Modified Coot Optimization Algorithm (MCOA) dynamically combined with the artificial neural network meta-models (ANN-MM) are employed. For the sample generation applied for training and validation of ANN meta-models, an optimum way is presented by this method to minimize the whole building energy simulations needed for their training, and validate precise results of optimization. Moreover, the method is used for the thermal comfort and energy efficiency optimization of a real house to achieve the optimum balance between the heating and cooling behavior of the case building. 12 effective design variables of this case study are selected. Also, the achieved results are put in comparison with the "true" Pareto front found through an optimization method based on simulation performed for more validation. It is assumed that 1280 points are adequate in this case study to obtain precise results on the Pareto set. Thus, 75% of the required simulations' number based on physics has been saved by this size of sample considering the 5120 applied in the method based on simulation. Consequently, the optimum Pareto set of a real multi-criteria building efficiency optimization problem is achieved by the proposed method and accurate results are achieved.
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Accessibility to housing is crucial for people with disabilities as it provides them with equal opportunities and allows them to live independently. A systematic literature review has been conducted to understand the current research on accessibility in housing for people with disabilities in Latin America. The study analysed 56 papers and used co-word analysis to identify common themes and topics within the documents. The results of the analysis showed that Brazil (61%) is the country with the most research on the subject, physical disability, at 36%, is the impairment most analysed, and interventions or analysis for the older people (45%) in their homes is the most researched type of population. The co-word analysis revealed that topics such as policy, regulations, the use of technologies, ergonomics interventions, and architectural criteria or barriers to the daily life of disabled people were frequently discussed in the papers. Although this work shows a substantial and growing increase in research on housing for people with disabilities in Latin America, it also demonstrates the importance of increasing research on other types of impairment, such as visual and cognitive-intellectual disabilities, and including children, caregivers, or even young adults.
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Personas con Discapacidad , Discapacidad Intelectual , Niño , Adulto Joven , Humanos , Anciano , Vivienda , América Latina , PolíticasRESUMEN
Occupancy is used to represent the movements and locations of users among various zones of buildings, and it is the basis of all other daily energy consumption behaviors. This study investigated eight families in cold areas of China based on occupancy measurements obtained in four main rooms, i.e., living room, bedroom, kitchen, and bathroom. In particular, we analyzed the duration of user occupancy and hourly mean occupancy, and characterized their regular and random features. According to the results, we developed an event-based occupancy model using an inhomogeneous Markov chain, where the rooms were modeled and daily events were divided into three categories according to their randomness. We established a new method for conversion between event characteristic parameters and a transition probability matrix, as well as an overlap avoidance method for active events. The model was then validated using real data. The results showed that the model performed well in terms of two evaluation criteria. The model should improve the accuracy of simulations of occupancy.
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On August 7th, 2020, a magnitude Mw = 5.0 earthquake shook 5 km north of Mila city center, northeast of Algeria, causing substantial damage directly to structures, and indirectly from induced impacts of landslides and rock falls, ultimately disrupt to everyday civilian life. Given the recent significant seismic occurrences in the region, a detailed and comprehensive examination and assessment of post-earthquake damage is critical to Algeria. This is primarily because masonry, concrete, and colonial-era structures are sensitive to horizontal motions caused by seismic waves, and because masonry and concrete structures constitute a substantial portion of today's Algeria's build environment. We present a post-earthquake investigation of the Mila earthquake, starting from the earthquake source, and a catalogue of buildings type, damage categorization, and failure patterns of residential structures in Mila's historic old town, where colonial-era brick buildings prevail. We find that structures that represent notable architectural achievements were severely damaged as a result of the earthquake. Data acquired during the immediate post-earthquake analysis was also evaluated and discussed. The graphical representations of the damages are detailed and complemented by photos. This seismic event has shown the fragility of Algeria's building stock, which must be addressed properly in future years. This study reports on an overall estimate of residential buildings in Mila's lower city, as well as an evaluation of the seismic vulnerability of three neighborhood towns (El-Kherba, Grareme-Gouga, and Azzeba). A generic database for graphical surveys and geometric research was developed and implemented making it possible to evaluate the shear strength on-site. The broad observations, collated data, and consequences were then loaded into the 3Muri structural verification program. Nonlinear static analysis was conducted to analyze probable failure paths and compare the real damage to the software results.
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@#<b>Objective</b> To investigate the indoor radon concentration and its changing trend in northeastern China. <b>Methods</b> We measured indoor radon levels cumulatively for over three months by solid state nuclear track detection in a total of 261 houses in multi-story or high-rise buildings in Shenyang, Changchun, Harbin, Heihe, and Yichun in northeastern China. The measurement lasted one year in Changchun for seasonal changes. <b>Results</b> The average indoor radon concentration in the five cities was 88 Bq/m<sup>3</sup>, ranging from 12 to 558 Bq/m<sup>3</sup>. The indoor radon concentrations were ≤ 100 Bq/m<sup>3</sup> in 75.1% of the houses, and ≤ 300 Bq/m<sup>3</sup> in 97.7% of the houses. The indoor radon concentration increased with the age of buildings. The indoor radon concentration was highest in winter, and it was higher in summer than in autumn and spring. <b>Conclusion</b> The indoor radon concentration in northeastern China increased compared with the data of 1980s and 1990s. It is highest in the winter heating season, and higher in summer than in spring and autumn. Indoor radon exposure deserves attention.
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In hot and humid climates, a significant part of the energy is used to cool the building. There are several ways to reduce this air conditioning load, but one standout is through the selection and design of the right building envelope and its components. The thermal characteristics of the building envelope, in particular the thermal resistance of the insulation used, have an impact on the thermal and energy performance of building structures. Thermal conductivity, which indicates the ability of heat to move through a material given a temperature difference, is the primary factor affecting the performance of a thermal insulation material. Both temperature and humidity changes can affect a material's thermal conductivity value, which can then change. In fact, due to the fluctuating ambient air temperature and solar radiation, thermal insulation in buildings is susceptible to significant and continuous temperature variations. Thermal insulation used in building walls and roofs helps to reduce the energy demand of the building. It improves thermal comfort and, if used correctly, reduces the operational cost of the building. The present study has focused on the effects of location and insulation material on the energy performance of a residential building by considering five climatic locations in the Kingdom of Saudi Arabia (KSA). Five commonly used insulation materials with different thermal characteristics, namely polyurethane board (PU), expanded polystyrene (EPS), glass wool (GW), urea-formaldehyde foam (UFF), and expanded perlite (EP), were analyzed under various climatic zones as per the Saudi Building Code 601/602. The selected cities were categorized based on cooling degree days (CDD) and outdoor dry bulb temperature (DBT) as hot, very hot, and extremely hot climatic zones. Insulation improves thermal comfort and, if used correctly, reduces running costs. Experiments were conducted to determine the thermal conductivity, and the energy simulation was performed by employing IES-VE software for various insulation options. The findings indicate that the location has a significant impact on the energy performance of the insulating materials. The energy saving potential of polyurethane board (PU) insulation is more attractive in cities with higher DBTs and CDDs than in cities with lower DBTs and CDDs. The benefit of installing insulation ranged from a 2 to 14% decrease in energy demand for the climate zones studied. The sensitivity analysis showed that the energy saving potential of the insulation materials is sensitive to the set-point temperature (ST) band.
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HVAC systems have a significant impact on the indoor environment, and microbial contamination in HVAC systems has a significant effect on the indoor air quality. In this study, to gain a better understanding of the microbial contamination inside ACs, we used NGS to analyze the 16S rRNA gene of bacteria adhering to AC filters, cooling coils, fans, and air outlet surfaces. The five phyla in terms of the highest relative abundance were Proteobacteria, Firmicutes, Actinobacteria, Cyanobacteria, and Bacteroidetes. The surface of an AC filter provides a history of indoor airborne bacterial contamination, and of the 10 bacterial genera we detected with the highest abundance (in the following order: Pseudomonas > Staphylococcus > Paracoccus > Corynebacterium > Acinetobacter > Streptococcus > Methylobacterium > Enhydrobacter > Sphingomonas > Actinotignum) on the filter surface, the top 6 genera were Gram-negative bacteria. Furthermore, the seventh-most abundant genus adhering to the filter surface (Methylobacterium) was the second-most abundant genus on the cooling coil and fan, and the ninth-most abundant genus on the air filter (Sphingomonas) was the third-most abundant genus on the cooling coil. Various factors impact the bacterial flora inside AC units, including the location of the house, AC unit usage, and occupant activity.
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Particulate matter with an aerodynamic diameter less than 2.5µm (PM2.5) is currently a major air pollutant that has been raising public attention. Studies have found that short/long-term exposure to PM2.5 lead detrimental health effects. Since people in most region of the world spend a large proportion of time in dwellings, personal exposure to PM2.5 in home microenvironment should be carefully investigated. The objective of this review is to investigate and summary studies in terms of personal exposure to indoor PM2.5 pollutants from the literature between 2000 and 2021. Factors from both outdoor and indoor environment that have impact on indoor PM2.5 levels were explicated. Exposure studies were verified relating to individual activity pattern and exposure models. It was found that abundant investigations in terms of personal exposure to indoor PM2.5 is affected by factors including concentration level, exposure duration and personal diversity. Personal exposure models, including microenvironment model, mathematical model, stochastic model and other simulation models of particle deposition in different regions of human airway are reviewed. Further studies joining indoor measurement and simulation of PM2.5 concentration and estimation of deposition in human respiratory tract are necessary for individual health protection.
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The "aging" world implies a rethinking of housing models, to meet the needs of the elderly for physical and mental well-being, independence, social interaction, safety, and accessibility. "Aging in place" is recognized by experts and international literature as a fundamental strategy for maintaining conditions of well-being and reducing public spending on health care. However, often the houses do not have the requirements to easily adapt to the needs that change with aging and possible downsizing of the family unit. For the elderly, maintaining their own home can become unsustainable due to problems of costs, oversizing, physical and perceptual accessibility, and safety. The contribution, taking as a case study the residential building heritage of Turin (Italy), illustrates and critically compares scenarios of adaptive recovery of homes to make them suitable for the needs of the elderly, intending to promote "aging in place" and housing adaptive refurbishment as a sustainable strategy.
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Envejecimiento , Vida Independiente , Anciano , Instituciones de Salud , Vivienda , Humanos , Salud MentalRESUMEN
Many aspects of the daily lives of those living in the United States were substantially impacted by the COVID-19 pandemic in the year 2020. A broad diversity of measures was implemented to curb the spread of the virus, many of which included adjustments to where and how people worked, went to school, and otherwise conducted their daily lives compared to pre-pandemic times. This has impacted how residential buildings are used, how much time people spend in their homes, and as a result, how much energy these buildings consume. The main objective of this study is to analyze, at a national scale, the differences in the occupancy schedules and activities conducted in homes in the U.S., as compared to pre-pandemic. 15 years of American Time Use Survey and Current Population Survey data, from 2006 to 2020, was used in this study to analyze the occupancy schedules for both pandemic (2020) and pre-pandemic (2006-2019) times. These impacts were also analyzed with respect to variables including, weekday/weekend, month of the year, age of the occupants, household income, and household size. The impact of the pandemic on occupant schedules were most substantial in the initial months, whereas as the months progressed, these occupancy profiles slowly changed. Across 2020, people spent, on average, 8 % more time (1.9 h) in their home on weekdays, and 3-6 % (1.2 h) on weekend days. The percentage of time spent for different activities and locations within homes were also studied. For 1-member households, their time spent at home decreased whereas for 2-, 3-, and 4- member households, they spent more time at home. Overall, people spent around 45% more time doing office- and work-related activities at home compared to pre-pandemic, which is likely due to increased remote working and schooling. This research helps to improve the understanding of the occupancy presence and absence profiles in U.S. residential buildings due to the pandemic and provides new insights as to modified profiles for researchers, building designers, and policy makers.
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The rapid spread of COVID-19 caused a significant impact on many sectors, including the energy demand in building due to the quarantine. This paper overviews the impact of the restriction's measures caused by the spread of COVID 19 on energy consumption in a residential building for three building constructions under six climatic conditions referring to the representative zones of the recent Moroccan climatic zoning. The three-building constructions are Reference House without any passive energy efficiency, Insulation House equipped with thermal insulation in external wall and roof and PCM House equipped with PCM (Phase Change Materials). The three houses are simulated by means of dynamic simulation using TRNSYS software. The quarantine in which the occupants have to stay all-time at home is compared to an ordinary occupancy scenario in terms of energy demand to reach the desired thermal comfort. The major finding of this work is that quarantine can significantly impact the cooling loads than the heating demand depending on building constructions and climatic conditions. The rising-rate in annual energy needs is the range of 10 %-35 %. The impact of the number of occupants is also investigated in respect to the two occupancy scenarios, the three-building constructions and under the six climatic conditions. The results show that when increasing the number of the inhabitants from 2 to 4, under the quarantine period, the energy demand of the PCM house is increased to 50 % depending on the climatic zones.
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The consequences of climate change are profound for the residential building industry and, unless appropriate adaptation strategies are implemented, will increase exponentially. The consequences of climate change, such as increased repair costs, can be reduced if buildings are designed and built to be adaptive to climate change risks. This research investigates the preparedness of the Australian residential building sector to adapt to such risks, with a view to informing the next review of the National Construction Code (2022), which at present does not include provisions for climate change adaptation. Twelve semi-structured interviews were conducted with construction managers from residential building companies in Brisbane, Queensland to understand their level of preparedness to adapt with climate change risks. Three aspects of preparedness were investigated: participant's awareness of climate change risks, their company's capacity to include climate change information in planning, and actions taken to address climate change risks. Participants were also asked about climate change adaptation policies and what they thought the path towards increased preparedness in the residential construction industry to climate change risks might involve. Qualitative analysis of interview data was undertaken using NVivo software, and illustrative examples and direct quotes from this data are included in the results. The results indicate a low level of preparedness of the residential building industry to adapt with climate risks. Levels of awareness of managing the consequences of climate change risks, analytical capacity, and the actions taken to address climate change were all found to be low. Legislating climate adaptation practices and increasing the adaptation awareness of the residential constructors are some of the recommendations to enhance the preparedness of the residential construction industry in Australia to adapt with climate change risks.
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The real-time hourly electricity consumption data of a middle-income household in the Gauteng Province of South Africa was tracked for 30 months (i.e. 2019 to 2021) over three different residential properties. Layout diagram and physical characteristics of each of the residential properties are provided. An energy audit of all appliances at the residence was conducted at the beginning of the study and acquisition of new appliances was also captured. The aggregated electricity consumption throughout the study of all appliances at the family residence was captured from a single-phase electricity distribution sub-panel. The granularity of the captured data was at the hourly resolution level and presented as kilowatt-hour. A total of 20,852 hours of data points were captured. The data has not been processed further. In addition to the energy consumption data, 16 months of hourly data for wind speed, temperature, and humidity of the closest weather station to two of the residential properties has been provided. The energy consumption data will be useful for teaching and research in energy consumption prediction studies, and energy management strategy development. Considering the timing of the study that encompasses pre-COVID-19 and three peaks of COVID-19 in South Africa, the data can be useful in analysing the impact of COVID-19 on household electricity consumption.