Embodied Carbon in Buildings: An Australian Perspective

Crawford, Robert H.; Stephan, André; Schmidt, Monique

doi:10.1007/978-3-319-72796-7_18

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…• Construction Phase Indicator: According to the research by Crawford et al [8], carbon emissions during the construction phase account for 20%-40% of the total carbon emissions throughout the building's lifecycle. Therefore, we allocated a weight of 25% for the construction phase indicator and display it in a pie chart • Operational Phase Indicator: The operational phase of a building is the longest and most critical stage in its entire lifecycle, involving aspects such as energy consumption, equipment maintenance, renovations, and updates.…”

Section: Weighting Of the Primary Indicator Systemmentioning

confidence: 99%

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Comprehensive Evaluation of Carbon Emissions from Residential Buildings in Jiangsu Province's Prefectural-level Cities Based on the Entropy Weight-TOPSIS Method

Li,

He,

Zhang

et al. 2024

Atlantis Highlights in Engineering

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This study aims to conduct a comprehensive evaluation of building carbon emissions based on the Entropy Weight-TOPSIS method. The construction industry is one of the primary sources of global greenhouse gas emissions, so evaluating the level of building carbon emissions is crucial for promoting sustainable development. The Entropy Weight-TOPSIS method combines the entropy weight method and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), allowing for a comprehensive assessment of building carbon emission performance considering multiple indicators. This research first identified a series of initial key indicators affecting building carbon emissions, then used the Delphi method to screen and finalize these indicators. Finally, the Entropy Weight-TOPSIS method was applied to rank and evaluate the carbon emission performance of different buildings. The research results can provide decision support for the construction industry to reduce carbon emissions and promote sustainable building development.

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Section: Weighting Of the Primary Indicator Systemmentioning

confidence: 99%

“…Define the minimum value: (6) Define the distance between the evaluation object (where i=1,2,…,n) and the maximum value: (7) Define the distance between the evaluation object (where i=1,2,…,n) and the minimum value: (8) Calculate the unnormalized score for the evaluation object (where i=1,2,…,n):…”

Section: Model Developmentmentioning

confidence: 99%