Green Home Research Articles

Contribution of Green Home Appliances in the Green Economy

Environmental deterioration achieved by customers' non-practical usage design is squeezing the climate and is deterring manageable turn of events. To ruin this effect and animate a more feasible economic development, one arrangement is to diminish or move use designs from traditional items to eco-friendly items. The creators directed an audit investigation of green buy conduct research across the 6-year period from 2015 to 2021, distinguishing 108 examinations that met our incorporation rules. The current survey recognizes distinctive unavoidable facilitators, intentions, and snags affecting customers' dynamic cycle towards environmentally friendly items, and it gives likely explanations for logical inconsistencies found in green buy conduct (GPB). The paper uncovers the fundamental determinants of purchaser's GPB, and in light of the survey, 212 factors that influence green buy aim (GPI) were distinguished. In addition, 135 determinants that influence GPB were recorded. Thusly, other than adding to the writing, it will help policymakers in detailing and utilizing techniques to convince eco-friendly buying, and it will offer a chance for advertisers to create appropriate promoting systems for attracting customers and ensuring ideal deals.

Assessing residential sustainable energy autonomous buildings for hot climate applications

This paper introduces an innovative solution for clean energy autonomous building (AB) sustainability, offering a 5Z concept—zero-carbon, zero-energy, zero grid connections, zero energy bills, and zero emission mobility. This paper focuses on fundamental research to design sustainable, energy-ABs striving for self-sufficiency in arid climates, using Kuwait as a case study. The study highlights the importance of stringent engineering AB modeling, renewable technology integration, and clean energy storage. The technical approaches include characterizing non-thermal and thermal demands, achieving net-zero energy generation, and custom sizing renewable energy and energy storage systems (ESS) for electric vehicle (EV) charging points. The research methodology involves local construction with yearly weather and energy profile data to simulate the actual system using ESP-r building model. The study's findings reveal the need for a large-scale energy system, energy demand reduction (EDR) inclusive of heating, cooling, appliances, and EV, with the corresponding changes in local energy production system size, battery capacity, and the number of photovoltaics (PVs). The results show varying EDR levels ranging from base case to 10% and to 50% leading to proportional changes in energy system size, size of battery from 3415 kWh to 1710 kWh and the number of PVs from 362 to 181, which means EDR not only optimizes space but also proves cost-effective. The significant implication of this study, not only bridging the knowledge gap and the lack of how-know, but also making a significant advancement and forward thinking in sustainable green electric home modernization and environmentally friendly transportation. This approach transforms energy management practices for more sustainable cities and societies, reducing emissions in both urban infrastructure and transportation.

The influence of energy-saving information in online reviews on green home appliance purchase behavior based on machine learning

The renewal of green home appliances is a crucial measure for households to save energy and reduce emissions. However, how online reviews, especially those relate to energy-saving, affect green home appliance purchase behavior (GHAPB) lacks exploration. In this paper, we investigate over 1 million online reviews on about 3,116 types of air conditioner from JD. By applying word2vec, we divide energy-saving related information in the following three types: norm information, environmental health information and price information, and construct dictionaries for each. Then, the effect value of energy-saving information is quantified from perspectives of breadth, depth and intensity through sentiment analysis. The influence of energy-saving information in online reviews on GHAPB is finally analyzed by linear regression and machine learning models. The results show that all energy-saving information has positive impact on GHAPB, and environmental health information is the most important one. In addition, the attributes of online reviews impose a greater influence on GHAPB, comparing with those of products. The in-depth exploration of energy-saving information in online reviews provides targeted recommendations for the manufacturer and the retailer to promote the adoption of green home appliances.

Green buildings and their impact on health outcomes and dietary intake: What do we know?

Background: While numerous research has been conducted on the energy efficiency advantages of green buildings, there remains a limited exploration of their effects on individuals’ health conditions and dietary intake. Green building’s structure and design aim to reduce the impact on the surrounding environments while also helping to improve the quality of health of individuals who live within them.Aim: The objective of this study was to examine the impact of green buildings on health outcomes and dietary intake.Method: Using four databases (Agricola, EBSCO, PubMed, and Web of Science), search of literature was directed with the following keywords: green buildings, green homes, built environment, housing design, health outcomes, dietary patterns, dietary intake, eating behavior, food choices, and others. We reviewed 33 articles, and 19 met our inclusion criteria.Results: The synthesis of literature revealed four overarching themes: the association between green buildings and respiratory diseases, mental health, dietary intake, and physical activity level. Our findings suggest an association between green buildings and the improvement of certain health conditions, including asthma, depression, and obesity.Conclusion: The results emphasize the necessity for additional research to investigate the sustained impact of green buildings on residents’ health and dietary habits over an extended period. The implications of the findings are significant for policymakers, urban planners, and researchers, underscoring the potential of green building initiatives in promoting healthy living environments.

A multiobjective approach for weekly Green Home Health Care routing and scheduling problem with care continuity and synchronized services

Home Health Care (HHC) services are essential for delivering healthcare programs to patients in their homes, with the goal of reducing hospitalization rates and improving patients’ quality of life. However, HHC organizations face significant challenges in scheduling and routing caregivers for home care visits due to complex criteria and constraints. This paper addresses these challenges by considering both caregiver assignments and transportation logistics. The objective is to minimize the total travel distance and CO2 emissions while ensuring a balanced workload for caregivers, meeting patients’ preferences, synchronization, precedence, and availability constraints. To tackle this problem, we propose a multiperiodic Green Home Health Care (GHHC) framework. In the first stage, we utilize multiobjective programming and the NSGA-II algorithm to generate Pareto front solutions that consider travel distance and CO2 emissions. In the second stage, a Mixed-Integer Linear Programming (MILP) model is proposed to balance caregivers’ workload by assigning them to the patient routes generated in the first stage. The results highlight the trade-off between shorter routes and lower emissions. Furthermore, we examine the impact of prioritizing continuity of care and patient satisfaction. This research provides valuable insights into addressing the scheduling and routing challenges in HHC services, contributing to a more efficient and environmentally friendly healthcare delivery.

A Study on Consumer’s Perception on Green Home Appliances

A household is the building block of the society and home appliances are the main power consumers in a household. Hence, they are the best means to save energy at a household level and achieve a reduction in per capita power consumption. If the household units save energy, the nation saves the energy and thereby the ideal place to initiate the green change at the consumer level is through the home appliances sector. Appliances more than 10 years old are clunkers as they use up most of the energy. If consumers replace them with energy efficient appliances, it will not only save billions of kilowatts of energy annually but also billions of tonnes of carbon emissions globally. Most of the home appliances have a longer life. Hence its medium to long term benefits should be weighed while making a purchase decision. “Despite various green initiatives and a vibrant consumer electronics market, consumer adoption of green home appliances is still lagging behind contributing to the high-power consumption and monetary loss to the individual and the country. The study made an attempt to understand consumer understanding, perceptions and acceptance of Green Home Appliances.

Solar power control system on smart green home

The need for fossil fuel electricity usage is increasing every year. If used for a long period of time, it will eventually run out. To reduce the use of fossil fuel energy, other alternatives are needed to maintain the availability of natural resources, one of which is by utilizing renewable energy. Utilization of solar power as an electrical energy source using photovoltaic panels. In its application, a solar power plant requires a controller that can regulate the energy produced. This controller is responsible for regulating the process of selecting the battery to be used. The working principle of this device is that when the battery reaches the minimum voltage threshold, the battery usage will be diverted to another battery with a voltage above the minimum threshold. The results of the research show that the system is capable of performing switching processes well using the smart switching method with a 100% success rate. The system uses an INA219 sensor for reading voltage and current from the battery. This research uses a 10-watt DC lamp, 20-watt DC lamp, and 30-watt DC lamp as loads. The battery can last for 4,8 hours by using a 10-watt DC lamp as a load, 2,4 hours by using 20-watt DC lamps as a load, and 1,6 hours by using 30-watt DC lamp as a load.

Perceptions of Potential Homebuyers in Purchasing Green Home

Perceptions of Potential Homebuyers in Purchasing Green Home

Do individuals' resist green home investment decisions? An empirical study from status quo bias and inertia perspective

IntroductionThe study explores the influence of Status Quo Bias theory constructs and the mediating role of inertia on individuals' resistance in making sustainable green home investment decisions among Indian homeowners and prospective homebuyers.MethodsA structured questionnaire was administered to 404 participants, and data analysis was performed using Partial Least Squares Structured Equation Modeling (PLS SEM).ResultsThe findings indicate that factors such as loss aversion, transition costs, adherence to social norms, and self-efficacy to change significantly contribute to individuals' resistance to green home investments. Inertia further amplifies the relationship between transition costs, social norms, and self-efficacy to change, but does not mediate the impact of loss aversion.DiscussionThis study is valuable for enhancing our understanding of biases in decision-making processes. To combat this resistance, it is crucial to provide clear information about the benefits of green home upgrades and offer incentives that reduce perceived costs and risks. This research sheds new light on the influence of status quo bias and inertia specifically within the context of green home investment decisions, addressing contemporary concerns for environmental sustainability and the increasing importance of such decisions in today's world.

Renewable Energy and its Moderation on Green Home Selection in Indonesia: Bridging Environment, Product, and Value

This study aims to investigate the moderating role of renewable energy on sustainable environmental factors, environmentally friendly products, and customer value in consumer decision making in choosing a residential house without greenhouse effect in Indonesia. The data source in this study is 270 people who have a residence without a greenhouse effect. The research method is a quantitative descriptive method using Structural Equation Model data analysis using the PLS 3.0 application. The population in this study amounted to 270 people who have a residence without a greenhouse effect, while the number of samples was 270 people who have a residence without a greenhouse effect with a sampling technique using the census method, while the data collection technique was carried out using observation, questionnaires and documentation studies. The results of this study indicate that consumers tend to be more interested in choosing residential houses that use renewable energy and have environmentally friendly features. In addition, customer values perceived by consumers, such as quality, price, comfort, and safety, also have a positive influence on consumer decisions in choosing residential houses without greenhouse effect. Limitations of this study include the use of self-reporting survey data, which may affect the validity and reliability of the results. In addition, this study focused on the context of residential homes in Indonesia, so generalizability of the findings needs to be considered with caution. Recommendations for future research include involving a more representative sample, incorporating objective data to measure environmental variables and environmentally friendly products, and expanding the geographical scope of the study to compare results between different regions in Indonesia.

A multi-city study of indoor air quality in green vs non-green low-income housing

ObjectivesThe condition of the home is a strong predictor of exposure to environmental contaminants, with low-income households being particularly vulnerable. Therefore, improving housing standards is a priority. Housing built to “green” standards, with improved building methods and materials, has been suggested to reduce contaminants. However, evidence is limited as to which contaminants are reduced. The Green Housing Study was conducted to address this issue. The study hypothesis was that housing built using green components has lower concentrations of environmental contaminants compared to conventional housing. MethodsA repeated-measures, 12-month cohort study was performed in three U.S. cities. Data were collected in the home at three time points throughout a year. The level of contaminants were estimated using air samples for particulate matter and black carbon, dust samples for aeroallergens and pesticides, and resident or study staff reporting evidence of mold. To investigate source(s) of PM2.5 and black carbon, multivariable models using stepwise variable selection were developed. ResultsIn adjusted generalized estimating equations (GEE) models, black carbon concentration (μg/m3) (β = −0.22, 95% CI = −0.38 to −0.06, p = 0.01), permethrin (OR = 0.28, 95% CI = 0.15–0.49, p < 0.0001), and reported mold (OR = 0.29, 95% CI = 0.13–0.68, p = 0.003) were significantly lower in green homes. Cockroach antigen was also lower in green homes (OR = 0.59, 95% CI = 0.33–1.08, p = 0.09), although not statistically significant. We found that 68% of PM2.5 was explained by dwelling type and smoking and 42% of black carbon was explained by venting while cooking and use of a gas stove. ConclusionsThis study provides quantitative data suggesting benefits of incorporating green building practices on the level of numerous environmental contaminants known to be associated with health. Occupant behavior, particularly smoking, is an important contributor to indoor air pollution.

An empirical analysis of the factors driving customers' purchase intention of green smart home products.

With the improvement of consumers' environmental awareness and the popularity of the Internet of Things, green smart home products (GSHPs) are becoming the dominant trend of future home life. This shift not only makes tedious home life easier and more convenient but also helps families save energy and reduce carbon emissions. However, given the impact of the current technological level, the proportion of users who actually purchase GSHPs remains small. Thus, seeking ways to promote the consumption of GSHPs has become an urgent issue. Hence, this study seeks to fill the gap in the existing research on green consumption behavior and obtain a full understanding of the factors influencing the purchase intention of GSHPs. To do so, this work uses task-technology fit theory and considers the actual situation of green smart home consumption to add social-technology fit into the original theoretical basis. In particular, this research focuses on middle- and high-end Chinese consumers who have experience in purchasing GSHPs. Moreover, it aims for an in-depth exploration of the formation mechanism of Chinese consumers' purchase intention for GSHPs through structural equation modeling. Using survey data collected from 331 green smart home product users in China, the study empirically examines the relationships among autonomy, environmental agility, sense of belonging, and self-actualization, and both task-technology fit and social-technology fit, which are expected to shape the purchase intention of GSHP users. The empirical results provide broad support for our hypotheses. The results of this study offer important contributions to the increasing research on GSHPs consumption and shed light on the importance of both technology characteristics and the needs of users in achieving both task-technology fit and social-technology fit and, ultimately enhancing the users' intention to purchase GSHPs.

Research on technological innovation and marketing publicity decision of green intelligent home appliance supply chain considering consumer subsidy and cost-sharing contract

Under the leadership of China’s “dual-carbon” policy, how to reduce energy consumption, reduce carbon emissions, and realize intelligent, low-carbon development has become a key issue faced by the home appliance industry. Studies have shown that green intelligent home appliances can save electricity and reduce carbon emissions. In the context of China’s “dual-carbon” goal, this study examines the technological innovation and marketing publicity decisions of the green intelligent home appliance supply chain considering the consumer subsidy and cost-sharing contract. By constructing a three-level supply chain model that includes home appliance manufacturers, retailers, and consumers, we use the Stackelberg game method to study the decision-making models under four scenarios with and without consumer subsidy and cost-sharing contract and consider the impact of consumers’ green intelligent preference, consumers’ green marketing sensitivity, consumer subsidy and cost-sharing contract on the supply chain optimal decision. Through model solving and further numerical simulation, the results show that 1) the increase of consumers’ green intelligent preference and consumers’ green marketing sensitivity can produce positive spillover effects and promote the improvement of home appliance manufacturers’ technological innovation efforts and retailers’ marketing publicity efforts; 2) consumer subsidy is always beneficial for the green intelligent development of the supply chain, which can effectively increase the total revenue of the supply chain; 3) the reasonable cost-sharing ratio can stimulate the enthusiasm of supply chain enterprises to increase technological innovation and marketing publicity investments and increase the total profit of the supply chain. However, the excessive cost-sharing ratio frustrates the enthusiasm of home appliance retailers to participate in the coordination, which results in a decline in the overall benefit of the supply chain; 4) by considering both consumer subsidy and cost-sharing contract, a reasonable level of consumer subsidy and cost-sharing ratio have a better incentive effect on the supply chain members than in the other three scenarios. This study can provide a broader reference for the green intelligent development of China’s home appliance industry, which plays an important role in the implementation of China’s “dual carbon” goal.

CHASE (Children’s Housing Assessment for a Safe Environment): a protocol for the inspection and modification of injury risks in children’s homes

BackgroundDecades of research and practice experience have led to an extensive body of evidence about effective home safety modifications. However, the benefits of safety modifications have not reached all segments of society. Poor quality housing in low-income neighborhoods, along with limited access to safety products and injury prevention information, can be significant barriers to child safety.MethodsThis is a longitudinal study of 300 low-income families in Baltimore City and Baltimore County with children under 7 years of age who are referred from existing Green & Healthy Homes Initiative (GHHI) home visiting programs. Three home visits will be completed to assess home injury hazards using a previously developed tool, the Children’s Housing Assessment for a Safe Environment (CHASE), and provide a Scope of Work that includes home modifications specific to the identified home injury hazards. An Assessor will also provide do-it-yourself education materials and injury prevention supplies to assist residents in completing the modifications. If the parent or caregiver is unable to complete the home modifications, a professional Housing Intervention Services team will complete the home modifications necessary to prevent injury in the home. This study will involve both quantitative and qualitative data analysis methods. Paired and regression analyses will be conducted to examine the maintenance of modifications and the variables associated with positive outcomes. A thematic analysis of staff and participant interviews will be used to identify perceived barriers and facilitators of successful program implementation.DiscussionBetter data on residential injuries of children and an improvement in the overall surveillance of home injuries are necessitated. This study will set a strong foundation for a larger future study of health and cost effectiveness outcomes and will advance our understanding of the feasibility, costs, and potential benefits of addressing and preventing home injuries to children.

Zero Carbon Ready Metrics for a Single-Family Home in the Sultanate of Oman Based on EDGE Certification System for Green Buildings

A single-family house was designed as a new middle-income green residential building in the Sultanate of Oman, according to criteria defined by the green building certification system EDGE (Excellence in Design for Greater Efficiencies), developed by the International Finance Corporation (IFC), which is a member of the World Bank Group (WBG). The design was accomplished through the free cloud-based tool of EDGE. With respect to a base design for the Sultanate of Oman, the green home design achieved savings of 40.86%, 20.22%, and 26.39% in energy, water, and materials (Embodied Energy), respectively. In addition, a saving of 35.48% in greenhouse gas (GHG) emissions was estimated. Based on the completed green building design, four green building-normalized metrics were used to quantify the efficiency of the base case and the design case in terms of the consumption of resources and polluting emissions. These efficiency metrics are: Carbon Emission Index (CEI), Energy Performance Index (EPI), Water Consumption Index (WCI), and Embodied Energy Index (EEI). Out of these green building performance metrics, the EPI is directly provided by EDGE, while the other three are introduced here as additional useful indicators that allow fair evaluations and comparison with other buildings, due to their less stringent dependence on the floor area or the number of occupants.

The role of social impact on consumer attitudes toward green and healthy home appliances during the COVID-19 pandemic

The role of social impact on consumer attitudes toward green and healthy home appliances during the COVID-19 pandemic

Ontogenetic changes in green turtle (Chelonia mydas) diet and home range in a tropical lagoon

Ontogenetic changes in habitat and diet are widespread among marine species. Most species of sea turtles are characterized by extreme ontogenetic changes in habitat use and diet, with large changes occurring in early developmental stages (e.g., neonates to juveniles). Changes can continue even after recruitment to shallow coastal habitats. In places where substantial transitions in habitat occur across short distances, it is possible that the distances of developmental movements from one habitat to another could be short. We investigated ontogenetic changes in home range size, home range location and diet of Chelonia mydas in a tropical coastal lagoon in north-western Australia by combining acoustic telemetry with stable isotope analysis. There was a substantial (but nonlinear) increase in home-range size (kernel utilization distribution: KUD) with length, and an increase in the average distance of the center of home ranges from shore with length: larger turtles tended to occupy larger areas further from the shore. These patterns were accompanied by complex nonlinear changes in δ13C, δ15N and δ34S of red blood cells and nails; changes were rapid from 36 cm (the length of the smallest individual captured) to 50 cm, before reversing more gradually with increasing size. δ15N and δ34S (but not δ13C) of red blood cells and nails increased monotonically with KUD and distance from shore. Seagrass was likely an important food for all sizes, macroalgae was potentially important for small (&amp;lt; 60 cm CCL) individuals, and the proportion of scyphozoan jellyfish in diet increased monotonically with size. The combination of acoustic telemetry and stable isotope analysis revealed ontogenetic shifts in use of space and diet across short distances in a tropical coastal lagoon.

GREEN RETIREMENT HOMES IN CHINA — BACKGROUND AND CASE STUDY

This paper analyzes China’s age structure until 2100. China is aging severely having tremendous impact on the young generation to care for the elderly people. Against this background, retirement homes with more centralized care for older people will become more and more important. As on the other side, the Chinese population is more and more preferring a low carbon economy and a climate friendly living style in smart cities. Hence, Green retirement homes are expected to be the first choice of accommodation for older people in the future. This paper sheds light on the most important characteristics of Green retirement homes and provides for a concrete example.

FedNILM: Applying Federated Learning to NILM Applications at the Edge

Non-intrusive load monitoring (NILM) helps disaggregate a household&#x2019;s main electricity consumption to energy usages of individual appliances, greatly cutting down the cost of fine-grained load monitoring towards the green home vision. To address the privacy concern in NILM applications, federated learning (FL) could be leveraged for NILM model training and sharing. When applying the FL paradigm in real-world NILM applications, however, we are faced with the challenges of edge resource restriction, edge model personalization, and edge training data scarcity. We present FedNILM, a practical FL paradigm for NILM applications at the edge client. Specifically, FedNILM delivers privacy-preserving and personalized NILM services to large-scale edge clients, by leveraging i) collaborative data aggregation through federated learning, ii) efficient cloud model compression via filter pruning and multi-task learning, and iii) personalized edge model building with unsupervised transfer learning. Our experiments on real-world energy data show that FedNILM can achieve personalized energy disaggregation with the state-of-the-art accuracy, while preserving the user privacy.

Construction Cost Decomposition of Residential Building Energy Retrofit

Buildings are responsible for significant energy consumption and carbon emissions. Green buildings, which incorporate advanced building technologies, offer a solution to reducing energy use. However, high costs associated with green building development present a barrier to widespread adoption. Retrofit projects, involving remodeling, renovation, and redevelopment of existing buildings, offer a viable solution. While prior studies have examined the cost analysis of green and non-green buildings, there is a lack of evidence comparing new and retrofit projects. This study aims to address this gap by providing empirical evidence for the cost decomposition and benefits of new and retrofit projects. Data on energy use, building technology, and costs from 235 certified green homes in the United States were collected, and cost benefits were evaluated. Results show that retrofit projects cost, on average, $1270.5/m2 ($118.0/ft2), which is 30% less than new projects. Land acquisition and development account for 35% of retrofit costs, six times greater than new projects. Excluding land costs, retrofit projects cost, on average, $733.88/m2 ($68.2/ft2), 49% less than new projects. Retrofit projects use similar building technologies as new projects and produce larger energy savings. The cost-benefit values generated by retrofit projects are 86% greater than new projects when considering land costs and 142% greater without considering land costs. These findings contribute to cost management for complex building projects and energy policy for sustainable development. Retrofitting offers great potential to promote the green building movement and suggests effective subsidy programs as a public policy implication.