Research Brief
Issue 4, 2015
Streamlined Embodied LCA of Residential Buildings
PROBLEM
APPROACH
400
20
300
15
200
10
100
5
0
Average Embodied GWP
(tonnes CO2 e)
500
Exterior Wall Area (m2)
Traditional life-cycle assessment (LCA) is time,
resource, and data intensive. For complex
systems like residential buildings, the data
demands mean that most LCAs are only
executed in a late design stage when most of
the design decisions have already been made.
Even in the late design stage, there are often
data gaps that exacerbate uncertainty in the
results. This brief demonstrates the use of a
probabilistic underspecification methodology to
streamline comprehensive building embodied
LCA as a means of reducing the expense and
uncertainty in early design stage building LCA.
0
BL2:
BL2: 2
Attribute BL1: All
description: Attributes Medium, stories
1800 ‐
2999 sf
BL2:
BL3:
BL2: BL4: 2600
More 2,400 to Narrow
sf
Windows 2999 sf
Living
Next attribute No
specified: attributes Area
Stories Window‐ Living
Aspect
Living
Specified to‐Wall
Area
Ratio
Area
specified Specified
Ratio
Further Specified Further
Specified Specified
Specified
We have developed a streamlined method that
requires significantly less data and effort for
Fig. 1: Exterior wall area and average global warming
potential (GWP) for progressively specified building geometry
the user than traditional LCA methodologies
attributes
while maintaining a rigorous quantification of
uncertainty and comprehensive scope, and can identify the key parameters that can reduce uncertainty. To test
the method, we have applied it to a building which is progressively specified in terms of early stage building
geometry attributes including living area, number of stories, aspect ratio (side-to-front wall ratio), window-to-wall
area ratio, roof type and roof pitch. Data on US residential building stock was analyzed to quantify the likely value
of these attributes when not completely specified. The building geometry attributes were analyzed at four levels
of specificity: Building Level 1 (BL1) to 4 (BL4), with BL1 being the most generic and BL4 as the most specific. To
demonstrate the method, we analyze a specific insulated concrete form exterior wall. At each level of
specification, the exterior wall area and global warming potential (GWP) were calculated. Uncertainty in the
material environmental impacts is not included to highlight the consequences of specifying building geometry
attributes. These attributes were progressively specified based on the top contributor to the result variance.
FINDINGS
The selected building geometry attributes were resolved at different levels of resolution (BL2 to BL4) of specificity
to see how much improvement in fidelity of the impact estimate can be achieved. All attributes are unspecified in
the first box plot (from left to right) in Figure 1; the next one shows the reduction in uncertainty when specifying
the living area at BL2 level of specification (keeping all the other attributes unspecified) followed by the
specification of the number of stories (third box plot). The last box plot shows the reduction by only specifying
living area (BL4), number of stories (BL2), window-to-wall ratio (BL2) and aspect ratio (BL2). Preliminary results
show that by specifying only four key building geometry attributes greatly improve the fidelity of the estimate
(coefficient of variation decreases from 34 to 4% for this case).
IMPACT
These findings suggest that the specification of very few attributes in the early stages of a building design can
produce robust results in the estimation of building embodied environmental impacts. With this process, the
impact of different conceptual building designs could be compared, enabling important design decisions.
This research was carried out by CSHub@MIT with sponsorship provided by the Portland Cement Association and the Ready
Mixed Concrete Research & Education Foundation. CSHub@MIT is solely responsible for content.
Authors: C. Rodrigues and T. R. Miller, in collaboration with Dr. J. Gregory and Dr. R. Kirchain.