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Functional unit influence on building life cycle assessment
Authors:de Simone Souza  Hugo Henrique  de Abreu Evangelista  Patrícia Pereira  Medeiros  Diego Lima  Albertí  Jaume  Fullana-i-Palmer  Pere  Boncz  Marc Árpád  Kiperstok  Asher  Gonçalves  Jardel Pereira
Affiliation:1.Faculty of Engineering, Architecture and Urbanism, and Geography (FAENG), Environmental Technologies Postgraduate Program (PGTA), Federal University of Mato Grosso do Sul (UFMS), Av. Costa e Silva S/N, CEP, 79070-900, Campo Grande, MS, Brazil
;2.Energy and Environment Postgraduate Program (PGEnAm), Federal University of Bahia (UFBA), Rua Aristides Novis, no 2, Federa??o, CEP 40210-630, Salvador, BA, Brazil
;3.Industrial Engineering Postgraduate Program (PEI), Federal University of Bahia (UFBA), Escola Politécnica, Rua Aristides Novis, no 2, 6o Andar, Federa??o, BA, CEP 40210-630, Salvador, Brazil
;4.UNESCO Chair in Life Cycle and Climate Change ESCI-UPF, Pompeu Fabra University, Passeig Pujades n° 1, 08003, Barcelona, Spain
;
Abstract:Purpose

The building sector is one of the most relevant sectors in terms of environmental impact. Different functional units (FUs) can be used in life cycle assessment (LCA) studies for a variety of purposes. This paper aimed to present different FUs used in the LCA of buildings and evaluate the influence of FU choice and setting in comparative studies.

Methods

As an example, we compared the “cradle to grave” environmental performance of four typical Brazilian residential buildings with different construction typologies, i.e., multi-dwelling and single dwelling, each with high and basic standards. We chose three types of FU for comparison: a dwelling with defined lifetime and occupancy parameters, an area of 1 m2 of dwelling over a year period, and the accommodation of an occupant person of the dwelling over a day.

Results and discussion

The FU choice was found to bias the results considerably. As expected, the largest global warming indicator (GWi) values per dwelling unit and occupant were identified for the high standard dwellings. However, when measured per square meter, lower standard dwellings presented the largest GWi values. This was caused by the greater concentration of people per square meter in smaller area dwellings, resulting in larger water and energy consumption per square meter. The sensitivity analysis of FU variables such as lifetime and occupancy showed the GWi contribution of the infrastructure more relevant compared with the operation in high and basic standard dwellings. The definition of lifetime and occupancy parameters is key to avoid bias and to reduce uncertainty of the results when performing a comparison of dwelling environmental performances.

Conclusions

This paper highlights the need for adequate choice and setting of FU to support intended decision-making in LCA studies of the building sector. The use of at least two FUs presented a broader picture of building performance, helping to guide effective environmental optimization efforts from different approaches and levels of analysis. Information regarding space, time, and service dimensions should be either included in the FU setting or provided in the building LCA study to allow adjustment of the results for subsequent comparison.

Keywords:
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