Life-Cycle Assessment of Apartment Buildings Based on Standard Quantities of Building Materials Using Probabilistic Analysis Technique

Given the increasingly serious nature of environmental problems, many countries have recently declared carbon neutrality policies and expended efforts to implement them. The domestic building industry aims to reduce its environmental impact using life-cycle assessments (LCAs) of buildings according...

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Bibliographic Details
Published in:Materials 2022-06, Vol.15 (12), p.4103
Main Authors: Kim, Hyeonsuk, Jang, Hyeongjae, Tae, Sungho, Kim, Hyunsik, Jo, Kanghee
Format: Article
Language:English
Subjects:
Apartment buildings
Apartments
Building construction
Building materials
Carbon
Clean energy
Climate change
Construction industry
Construction materials
Data analysis
Emissions
Environmental engineering
Environmental impact
Goodness of fit
Green buildings
Greenhouse gases
Housing
Life cycle assessment
Probabilistic analysis
Probability distribution
Residential buildings
Simulation
Statistical analysis
Takeoff
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Summary:Given the increasingly serious nature of environmental problems, many countries have recently declared carbon neutrality policies and expended efforts to implement them. The domestic building industry aims to reduce its environmental impact using life-cycle assessments (LCAs) of buildings according to the Green Standard for Energy and Environmental Design. However, it is difficult to perform efficient LCAs because the required quantity takeoff process is complex, and the quantity takeoff sheet may not exist during the building’s design phase. In this study, 21 building LCAs were used to simplify and improve the efficiency of the proposed method and enable building LCAs even when there was no quantity takeoff sheet. Furthermore, a standard quantity database of building materials was constructed based on the analysis of the input quantities of building materials per unit area, and the apartment buildings LCA method was proposed using this database. The input quantities of building materials were analyzed using the probabilistic analysis technique. The probability distribution was derived using Monte Carlo simulations, and the goodness-of-fit was verified. Finally, the reliability of the proposed building LCA method was verified using a case study.
ISSN:1996-1944
1996-1944
DOI:10.3390/ma15124103