Session 1 - Montefiore

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buildings [17,26]. This review reflects the important developments
of LCA studies applied to buildings in the last ten years. However,
a lot of modelling challenges remain. Currently LCA gives benefits
to retroactively design but has limited use during the design stage
[17,18]. Moreover, the building demolition and recycling of materials
are rarely addressed in LCA studies of complete buildings
[21,27]. These references also show that a great deal of buildings
environmental impacts come from their use, primarily water and
energy use. Issues such as orientation, insulation, building operation,
lighting and appliance use, and so forth are therefore very
important. Indeed, the in-use building phase is by far the longest
one of the building life cycle. By comprehensively reviewing the
existing literature from a entire building life cycle perspective, the
phase with the highest environmental impact is the operation
phase, representing approximately 62e98% of the life cycle total
impacts [28], while the construction phase accounts for a total of
1e20% and the dismantling phase represents less than about
0.2e5%. So, trying to reduce fluxes (energy, water and waste)
during the utilisation phase seems to be the first action to achieve.
However, in [28] and [29], it is shown that the chosen service life
time of the building is crucial for the calculation results and
subsequent conclusions drawn from them.
In this study, we will calculate the Embodied carbon and take
the recycling potential of the different materials into account.
Indeed, the recycling potential is important when compared to the
shell embodied materials: it accounts for 29%e40% of the energy
used for manufacturing and transporting the building materials
[16,21].
The quality (precision, completeness, representativeness) of the
data used has a significant impact on the results of an LCA. The
existence of uncertainties in input data and modelling as well as the
boundaries of the system are often mentioned as a crucial drawback
to a clear interpretation of LCA results. To achieve more reliable
results the quality of the input data should be analysed and, if
necessary, improved but such analyses are often outside the scope of
building LCA studies [30]. To understand the reliability of LCAs in the
building sector more clearly, the LCA models should be elaborated
using data uncertainty estimations. They are particularly important
when performing comparative LCA studies [1,29]. Note that Blengini
[21] carried out an extensive sensitivity analysis of his LCA study on
a multi-family residential building. The impacts were re-calculated
by considering different data sources for the two most important
materials included in this building: steel and concrete. The differences
in terms of global energy requirement of the buildings with
two alternative datasets are lower than 8% in comparison with the
first dataset. The differences in terms of greenhouse gas (GHG)
emissions fall within a range of 15% and þ11%. Higher differences
occur when other indicators are considered. The conclusions of
Blengini [21] on this sensitivity analysis are that the uncertainties
relevant to the inventory data of building materials are quite
tolerable as far as energy and greenhouse gas emissions are concerned
but that the other indicators are less reliable. As far as
methods are concerned, three main types of LCA tools can be
identified. The first one is the “process analysis” and is based on
reliable energy consumption figures for particular processes. This
method is often used in research dealing with building structures, as
those presented below. The second one is the “inputeoutput analysis”
that makes use of national statistical information compiled by
governments for the purpose of analysing national economic flows
between sectors. Economic flows are then transformed into energy
flows using average energy tariffs [24]. This method is less accurate
than the first one [31]. To avoid the truncation error due to the
delineation of the assessed system and the omission of contributions
outside this boundary, a number of researcher have suggested
to use a third method, the “hybrid LCA approach”, combining the
B. Rossi et al. / Building and Environment 51 (2012) 395e401
strengths of process analysis with those of inputeoutput analysis to
try to develop a more complete approach [24,31,32].
According to the aim of this study, we have chosen to use
a process analysis type based on comprehensive and reliable
existing databases (BEES database (http://ws680.nist.gov/bees/)
and CRTI (Luxembourg Construction portal, www.crtib.lu))
providing energy consumption and equivalent CO2 emissions for
a quite wide amount of construction materials in Europe. Indeed,
the main objective is to focus on the comparison of different
structural frames under different climates. The results obtained
using the basic tool should thus be lower than those obtained with
a hybrid LCA approach but are more pertinent to draw general
results regarding the aforementioned comparison of the environmental
impacts.
Given the significant consumption of resources in the construction
sector, impact categories related to the depletion of nonrenewable
resources, like land use for example, are also particularly
relevant for building related LCA studies. But the models
used for inventory analysis or to assess environmental impacts
may not be available for all potential impacts or applications, e.g.
models generally accepted by the scientific world for the assessment
of land use do not exist yet in the literature [33]. It is also worth
pointing that some authors take into account the transportation of
buildings occupants, assuming that it is part of the building service
because it is related to the location of the building and that it is
thus contributing to the overall building impacts [22,34]. Nevertheless,
those transport distances will not be considered herein.
Additionally, in [35], the author demonstrates the need for considering
not only the life cycle energy of the building but also the life
cycle energy attributable to activities being undertaken by users of
the buildings (such as holidays, the replacement rate of items such
as washing machine and microwave oven). But because our goal is to
investigate the environmental impacts of different structural frames
in different locations (characterized by different climate data as
well as local energy mixes), the behaviour of the inhabitants is not
considered as a variable in the present study. These indicators
will not be considered herein. A standard profile of occupation
(including internal gains) is defined and assumed to remain
unchanged in the three locations to isolate the impact of parameters
dealing with the building’s structure and the climate. Our tool
focuses on the energy and equivalent CO2 emissions.
The companion paper is complementary to previous research
that compared LCA carried out on buildings with different
construction materials or in different climates. Peuportier [15]
applied LCA to the comparative evaluation of three single family
houses in France: a standard construction made of concrete blocks,
a solar house made of stones and wood and a well-insulated
wooden frame reference house. This study concluded that the
increase of CO2 emissions of the standard concrete blocks house
compared to the well-insulated wooden house represents 18% of
the total emissions for the wooden house, but accounting for endof-life
processes may reduce this value. Bôrjesson and Gustavsson
[30] studied the greenhouse gas balances of a wood versus concrete
multi-storey building from life cycle perspective and concluded
also that the concrete-framed building causes higher emissions
than the wood-framed one. Comparing the environmental impacts
of two dwellings during the entire building life cycle, one in Spain
and one in Colombia, Ortiz-Rodriguez et al. showed that the
difference in their environmental impacts is not only due to
climatic differences but also to the user (energy consumption)
habits in each country [36]. Another recent research [37] studied
a modular building in two different European locations under the
environmental point of view, concluding that the energy mix of the
country strongly influences the environmental impacts of this
specific modular building. In the companion paper, the LCA of two