Review of Existing Energy Retrofit Decision Tools for Homeowners

Seddiki, Mohammed; Bennadji, Amar; Laing, Richard; Gray, David; Alabid, Jamal

doi:10.3390/su131810189

Cited by 7 publications

(5 citation statements)

References 33 publications

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“…Even though our results indicate that retrofitting could lead to a decline in rodent population and a reduction in public health cost, implementation is likely to be challenging. The current housing market and deployment of energy retrofit schemes are complex and often exclude home renters (Murto et al 2019, Seddiki et al 2021. Our cost analysis estimates the average cost of retrofitting at $89 104 per home, with additional tiered pricing to account for individual factors like age, model, and previous repairs (Gustavsson and Piccardo 2022).…”

Section: Discussionmentioning

confidence: 99%

Energy efficient homes for rodent control across cityscapes

Gadsden,

Ferraro,

Harris

2024

Environ. Res. Lett.

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Cities spend millions of dollars on rodent mitigation to reduce public health risks. Despite these efforts, infestations often remain high. Rodents thrive in the built environment in part due to reduced natural predators and the exploitation of garbage. Though sanitation and greenspace are important factors in rodent mitigation, more complex governance and action are needed. Urban rodents are dynamic and commensal in nature, so understanding the influence of prolific urban features, like building attributes, warrants scrutiny and additionally intersects mitigation strategies with stakeholders at a localized level. Here, we model how residential structures’ efficiency influences urban rodent populations. To do so, we created an agent-based model using characteristics of urban brown rats and their natural predator, red foxes, based on three distinct neighborhoods in Philadelphia, Pennsylvania. We varied whether retrofitting occurred and its duration as well as the percent of initial energy-efficient homes in each neighborhood. We found that initial housing conditions, retrofitting, and the duration of retrofitting all significantly reduced final rodent populations. However, retrofitting was most effective in reducing rodent populations in neighborhoods with extensive park access and low commercial activity. Additionally, across neighborhoods, single large efficiency initiatives showed greater potential for rodent reduction. Lastly, we show that the costs of large-scale retrofitting schemes are comparable to ten-year public health spending, demonstrating that retrofitting may have the potential to offset near-term costs. Our results showcase how system-view investments in integrated pest management can lead to sustained rodent pest mitigation and advance sustainable development goals, infrastructure innovation (Goal #9), reduced inequalities (Goal #10), and sustainable cities and communities (Goal #11). 

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Section: Discussionmentioning

confidence: 99%

Energy efficient homes for rodent control across cityscapes

Gadsden,

Ferraro,

Harris

2024

Environ. Res. Lett.

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“…Some tools deal with overall building retrofit measures, whether these are the building envelope, building systems, or renewable energy. Some decision-making tool types include economic analysis for energy efficiency measures, such as the life cycle and payback period calculation [26].…”

Section: Existing Global Energy Retrofit Decision-making Tools For Ho...mentioning

confidence: 99%

“…The evaluation of energy savings is conducted by a normative simplified calculation method considering standard conditions of use of the building. Compared to the other existing tools, the main advantage of this tool is to consider technological criteria such as the complexity of implementation works [26].…”

Section: Existing Global Energy Retrofit Decision-making Tools For Ho...mentioning

confidence: 99%

“…This step aimed to calculate the payback period for each energy retrofit scenar payback period is a method used to determine the number of periods (usually year quired to cover the initial investment costs, taking into account interest rates and infla After the end of that period, the return on investment begins [26].…”

Section: Economic Analysis and Payback Period Calculationmentioning

confidence: 99%

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Multi-Objective Decision-Making Tool for Envelope Energy Retrofitting Measures of Gated Community Housing in Egypt

Algohary,

Mahmoud,

Yehya

2023

Designs

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Due to climate change, Egypt has recently suffered from recurring electricity crises. Despite efforts made to increase electricity production in Egypt, recently, in the summer months, the energy demand has increased at unprecedented rates, especially in the housing sector. Therefore, the government and homeowners should work together to improve the energy performance of residential buildings. This paper aimed to develop a decision-making tool that helps homeowners choose optimal energy retrofit measures that suit their priorities. The study began with the data-collection and case study selection. Then, the thermal evaluation of the base case for dwellings in the case study was conducted through simulation runs using the DesignBuilder v7.1 software. Then, the optimal envelope energy retrofitting measures were determined, followed by a retrofitting-measure scenario simulation process. Then, the payback periods were calculated for all scenarios, and the tool database was developed using an Excel spreadsheet. Finally, the user interface for envelope energy retrofitting measures for gated communities (EERMGCs) tool was designed by Visual Basic for Applications. EERMGCs, the tool developed in this paper, is a simple, multi-objective and interactive tool that provides the optimal envelope retrofit measures according to user priorities, either a specific budget, the shortest payback period, the lowest possible costs, or the highest energy saving rate. The outcome of this research is developing a framework that can be considered a basis for developing decision-making tools for gated community housing in Egypt.

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“…TC barriers to implementation also need to be highlighted in terms of the complexity of processing information and finding information about energy retrofits. See also [402] for the characteristics of existing support tools in ten countries. Finally, it should also be noted that for the digital platform to be scaled up, certain initial conditions need to be met.…”

Section: 34mentioning

confidence: 99%

Understanding the decision-making process in homeowner energy retrofits

Ebrahimigharehbaghi

2022

Architecture and the Built Environment

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In 2020, owner-occupied housing accounted for 57% of the housing stock in the Netherlands. Homeowners are fully responsible for the implementation of energy retrofits. Moreover, the processes of energy retrofitting are complex and homeowners face problems such as finding financial support, reliable information and contractors. The complexity of implementing energy retrofits may discourage homeowners from continuing the process and achieving the expected benefits. Behavioural aspects and transaction costs (TC) are among the most important factors influencing consumer decision-making processes. Behavioural factors primarily illustrate a range of personal, contextual, and external factors that influence the decision-making process of homeowners. These include cognitive awareness and biases, attitudes and beliefs, experience and skills, homeowner characteristics, sociodemographic characteristics, property characteristics, and the behaviour of others. TC are any hidden costs that influence decision making but are not included in the direct physical costs of renovation services and products. This dissertation developed an integrated framework of behavioural factors and TC that impede the decisionmaking process for energy retrofits. Key findings include (1) the significant importance of behavioural factors and TC barriers. (2) the behavioural factors are particularly important in the early stages of energy retrofits and the TC barriers after the final decision. (3) the importance of behavioural factors and TC barriers differs according to the type of energy retrofit and non-energy retrofit. (4) Accounting for cognitive biases significantly improves the prediction of households' actual decisions about energy retrofits. This modelling is more accurate than the model that assumes households make rational decisions.

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Review of Existing Energy Retrofit Decision Tools for Homeowners

Cited by 7 publications

References 33 publications

Energy efficient homes for rodent control across cityscapes

Energy efficient homes for rodent control across cityscapes

Multi-Objective Decision-Making Tool for Envelope Energy Retrofitting Measures of Gated Community Housing in Egypt

Understanding the decision-making process in homeowner energy retrofits

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