An evaluation model for an optimal decarbonisation process in the built environment

Purpose The goal is to deliver a decision-support framework to both public and private entities engaged in energy retrofit investments in the property market. Design/methodology/approach The evaluation algorithm that is being offered takes an innovative approach to financial and economic analysis. Its foundation is a market-driven/cost-driven method, drawing logic from operational research and goal programming. Findings The algorithm is tested to a real estate portfolio yielding an optimal asset retrofitting schedule. The ranking list is determined by taking into consideration a variety of parameters, including investment costs and total CO 2 emissions from energy retrofit initiatives. The Carbon Risk Real Estate Monitor’s (CRREM) emission targets for 2030 are employed as a reference point in the process of creating a ranking list of the assets that compose the real estate portfolio under examination. Practical implications The evaluation algorithm will allow to determine, in a real estate portfolio, a priority list of assets to be enhanced. This is accomplished by taking into account the client’s financial resources, the overall cost of the intervention programmes for each asset, and the effects that each asset would have on the environment and the energy once the suggested retrofit programme is put into place. Originality/value The study proposes a methodological approach that seeks to balance the optimisation of energy performance, the reduction of environmental effect, the promotion of social well-being and economic sustainability in the context of managing the current property sector.

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Publication Details

Journal
Built Environment Project and Asset Management
Published
2024-10-08
DOI
https://doi.org/10.1108/bepam-05-2024-0126
Citations
5
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
1.33
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article

An evaluation model for an optimal decarbonisation process in the built environment

Francesco Tajani, Francesco Sica, Giuseppe Cerullo
5 citations
Built Environment Project and Asset Management
Building Energy and Comfort Optimization
1.33
article

An evaluation model for an optimal decarbonisation process in the built environment

Francesco Tajani, Francesco Sica, Giuseppe Cerullo
article en
5 citations

Abstract

Purpose The goal is to deliver a decision-support framework to both public and private entities engaged in energy retrofit investments in the property market. Design/methodology/approach The evaluation algorithm that is being offered takes an innovative approach to financial and economic analysis. Its foundation is a market-driven/cost-driven method, drawing logic from operational research and goal programming. Findings The algorithm is tested to a real estate portfolio yielding an optimal asset retrofitting schedule. The ranking list is determined by taking into consideration a variety of parameters, including investment costs and total CO 2 emissions from energy retrofit initiatives. The Carbon Risk Real Estate Monitor’s (CRREM) emission targets for 2030 are employed as a reference point in the process of creating a ranking list of the assets that compose the real estate portfolio under examination. Practical implications The evaluation algorithm will allow to determine, in a real estate portfolio, a priority list of assets to be enhanced. This is accomplished by taking into account the client’s financial resources, the overall cost of the intervention programmes for each asset, and the effects that each asset would have on the environment and the energy once the suggested retrofit programme is put into place. Originality/value The study proposes a methodological approach that seeks to balance the optimisation of energy performance, the reduction of environmental effect, the promotion of social well-being and economic sustainability in the context of managing the current property sector.

Built Environment Project and Asset ManagementVol. 15(1)
Sapienza University of Rome (IT)
Openalex Percentile: Top 21%
Building Energy and Comfort Optimization
1.33
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