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CILECCTA – Life Cycle Cosng and Assessment
Sustainability within the
Construcon Sector
Sustainability within the Construcon Sector
CILECCTA – Life Cycle Cosng and Assessment
Authors: The CILECCTA partners
Editor: SINTEF Building and Infrastructure
ISBN 978-82-536-1343-7 (pdf)
© Copyright SINTEF Academic Press 2013 (Oslo, Norway)
The material in this publicaon is covered by the provisions of
the Norwegian Copyright Act. Without any special agreement
with SINTEF Academic Press any copying and making available
of the material is only allowed to the extent that this is permit-
ted by law or allowed through an agreement with Kopinor, the
Reproducon Rights Organisaon for Norway. Any use contrary
to legislaon or an agreement may lead to liability for damages
and conscaon, and may be punished by nes or imprisonment.
www. cileccta.com
Project Coordinator
Jens Kroepelien (Holte as)
Email: jens.kroepelien@holteconsulng.com
Consorum Manager
Rick Hartwig (Designtech)
Email: Rick.Hartwig@designtech.se
Technical Manager
Frode Eek (Holte as)
Email: frode.eek@holte.no
CILECCTA
«A user-oriented, knowledge-based suite of Construcon Indu-
stry LifE Cycle CosT Analysis soware for pan-European deter-
minaon and cosng of sustainable project opon»
The research leading to the results found in the CILECCTA project
has received funding from the European Union Seventh Frame-
work Programme [FP7/2007-2013] under grant agreement no.
229061.
Any publicity made by the beneciaries in respect of projects
funded by the European Union reects only the author’s views
and the European Union is not liable for any use that may be
made of the informaon contained therein.
Sustainability within the Construcon Sector
CILECCTA – Life Cycle Cosng and Assessment
SINTEF Academic Press
2013
Editor’s Note
Sustainability is a word that is being increasingly used. We use it
in the context of nature, where we want biological systems to re-
main diverse and healthy. Sustainability is used to talk of how we
can live within the means provided by our planets resources. Hu-
manly speaking sustainability is measured in culture, polics, the
ecology and economic terms. An underlying driver to improved
sustainability is change which implies new and innovave think-
ing, which will in turn drive our behaviour.
CILECCTA is about change. Two very dierent disciplines are
brought together into a single process. Life Cycle Costs and Life
Cycle Indicator Results work together to advance into Life Cycle
Cosng and Assessment (LCC+A). World wide nancial and envi-
ronmental data can be integrated and shared via a single plaorm.
And another important thing: we move from determinisc to pro-
balisc thinking.
CILECCTA has been co funded by the European Commission’s FP7
programme. The 15 partners have worked together to develop
something unique. A decision making tool that incorporates prob-
abilisc thinking. Thank you to everyone for your contribuon.
I hope you, the reader, enjoy this book as much as we have en-
joyed wring it.
Change is inevitable in the context of sustainability. CILECCTA will
help you make more informed decisions whether you look ve or
even 50 years ahead.
Rick Hartwig
Exploitaon and Disseminaon Manager
CILECCTA is a large-scale colla bo -
r ave project co-nanced by the
Euro pean Commission under the 7th
Frame work Programme Cooperaon.
The CILECCTA con sor um comprises
15 partners from 7 European coun-
tries. All partners bring their indi-
vidual experse to the project and
each is necessary for its execuon.
In short, the consorum forms com-
plementary enterprises that have
a broad reach across all aspects of
the construcon industry; from ar-
chitects (Cambridge Architectural
Research Limited, APIA XXI) to large
enterprises in the infrastructure
(ACCIONA), from hotels and resorts
(TUI), Research Instutes (Fraun-
hofer-IBP, SINTEF) and an associa-
on represenng their members in
the industry (Norsk Teknologi) to
service providers (Holte as, BSRIA,
PE Internaonal, TechnoBee, ASM,
DesignTech). In addion, the Uni-
versity of Stugart and the Luleå
University of Technology provide a
direct route to higher educaon in
the building sector.
Contents
1 About CILECCTA ............................................................7
2 Life Cycle Costing ......................................................... 11
3 Life Cycle Assessment .................................................. 15
4 Combining LCC and LCA: LCC+A ................................21
5 Advances in LCC+A ...................................................... 25
6 Price Banks and Life Cycle Indicator Results ............... 31
7 CILECCTA Software ..................................................... 35
8 Case Studies ................................................................41
9 Training and e-learning ................................................. 55
10 Seminars,PapersandScienticArticles .......................61
11 Input to Standards ......................................................... 67
12 CILECCTA Business Plan ..................................................... 71
Partners .........................................................................74
Participants ...................................................................75
6
The CILECCTA project has developed a bridge between life cycle think-
ing connected to both economics and the environment, and has created
demonstraon soware based on this.
When a decision is made in the construcon sector, it is oen made on the basis of
an economic evaluaon of various alternaves. Oen these calculaons are based
on investment costs, not considering outlays on future maintenance or waste
treatment, and neglecng the lifeme of the system components. Life Cycle Costs
(LCC) is a calculaon method taking these issues into account. The same can be
done for environmentally damaging emissions using the method of Life Cycle
Assessment (LCA). The CILECCTA soware combines the two methods, thus creat-
ing a new term: Life Cycle Cosng and Assessment (LCC+A).
1 About CILECCTA
Figure 1.1
Combining LCC and LCA
8
The CILECCTA soware is an innovave tool developed to be a deci-
sion making tool which can be used for sustainable planning with-
in all kinds of construcon projects. How to handle uncertainty,
together with the possibility of implemenng exible systems, are
issues which are dealt with in a unique way.
Future uncertainty
Tradional LCC and LCA soware does not take uncertainty into
consideraon in the analysis. Current LCC or LCA tools require pre-
cise data input for all variables throughout the chosen study pe-
riod. With this precise input data the tools generate precise values
for life-cycle cost and environmental impact, known as the deter-
minisc approach to LCC/LCA.
With a typical study period of 20 years plus, many factors are
certain to change, e.g. the price of fuels or energy carriers, build-
ing products, the service life of building products, refurbishment
measures, the usage of buildings and infrastructure etc. Each has
an impact on the cost and environmental eect of an item’s life-
cycle.
It is therefore preferable for the variables in LCC/LCA tools to be
given ranges of values rather than precise values. This is the pro
babilisc approach to LCC /LCA. In this way it is possibe to make
analysis based on dierent scenarios. As a result, the data values
are dened as ranges, typically «three-point esmates» (low-
est conceivable value, most likely value and highest conceivable
value).
Flexibility
A further important feature of CILECCTA is the ability to model
exibility. Flexibility answers fundamental quesons like «how
much does it cost me to invest a lile extra when seng up the
construcon, compared to the cost of wanng to change the con-
strucon at a later point in me». Since they provide the analy-
sis with cost and environmental data, these two scenarios can be
compared. This kind of combined analysis has not been possible
with any other tools.
Integration of LCC and LCA
The integraon of economic-oriented LCC and environmentally-
oriented LCA presents signicant challenges as they are quaned
in dierent units. In addion they originated in very dierent con-
texts – investment eciency for LCC and environmental conserva-
on for LCA – and adopt dierent assumpons. Time preference
(the increased weight given to costs or benets that occur in the near
Life Cycle Thinking
When making a holisc evaluaon of
a systems impact or costs it is oen
dened as life cycle thinking. By con-
suming a product or service, a series
of associated acvies are required
to make it happen. Raw material ex-
tracon, material processing, trans-
portaon, distribuon, consumpon,
maintenance, reuse/recycling, and
disposal are all examples of the phas-
es a product can go through. Looking
at it as one system it is seen as the life
cycle of the product.
9
future compared to those that are further in the future) is formalised
through a discount rate in LCC, but in LCA a discount rate is not used.
In connecon with this issue, together with making it possible to
import data from Price Banks (PBs) and Life Cycle Indicator Results
(LCIRs) across Europe, a mapping tool has been developed using
the Internaonal Framework for Diconaries (IFD). This is a stand-
ard for ontology based on internaonally accepted open stand-
ards. For CILECCTA this means that each potenal data provider
will implement a common interface that accepts a standardized
input and generates a standardized set of return values. The map-
ping approach guarantees that the dierent material categories
are globally unique and therefore the interface to each data pro-
vider will be kept very simple. In this way the user can be sure that
apples and pears are not being compared when data from dier-
ent databases are used.
The CILECCTA e-handbook
The booklet in which you are reading these lines is the «CILEC-
CTA e-handbook». The book aims to give you an introducon to
the methodology behind CILECCTA, together with informaon
about the project and how you can use CILECCTA to your benet.
Chapters 2, 3, 4 and 5 explain the LCC, LCA and LCC+A methods.
Chapters 6 and 7 provide knowledge of how the soware is built
up including informaon regarding Price Banks and Life Cycle In-
dicator Results.
Figure 1.2
Screenshotofthenished CILECCTA software showing a comparison of two different heating systems
10
For an industry dominated by small enterprises (SMEs) it is im-
portant that CILECCTA features are applicable for all enterprises
regardless of their size. All kinds of construcon projects, as well
as project stages can be analysed. In order to make the soware
more tangible and gather experience, the soware has been test-
ed using three demonstraon examples:
ശ decision making on road construcon with regard to layout
and changing mobility.
ശdecision making on using phase change materials for applica-
on in residenal housing.
ശdecision making on what energy system to implement at a re-
sort in Mallorca.
Chapter 8 presents the case studies and experiences gathe red
from these.
An e-learning program together with educaonal courses has been
constructed to give potenal users the possibility to learn about
life cycle methodology and how the CILECCTA soware works. In
chapters 9 and 10, Training and Elearning and Seminars, Papers
and Scienc Arcles you can learn more about CILECCTA and the
topic of LCC+A.
The demo version of CILECCTA soware is a solid plaorm for fur-
ther add-ons or applicaons to address specic cases according to
specic enterprise’s needs. Chapters 11 and 12 are about the me
aer the CILECCTA project – How to use CILECCTA in standardisa-
on work and how you can use CILECCTA for your benet.
Figure 1.3
CILECCTA provides an innovative
tool to improve decision-making for
construction projects. Photo: Mette
Langeid, SINTEF Academic Press
Life cycle cosng (LCC) is the economic appraisal of a potenal investment
or exisng asset taking into account immediate and longer term costs and
benets. Its purpose is to assist decision-making and it can be applied to
individual products or components, to complete building services systems,
or to enre construcon or refurbishment projects.
The principles of life cycle costing
Life cycle analysis is an iterave process, as can be seen from gure 2.1. The steps
start with need to thoroughly understand the problem that has iniated the anal-
ysis, and also to formulate a range of possible technical soluons to that prob-
lem. Since LCC is essenally a method for evaluaon of costs aspects along the life
2 Life Cycle Costing
Applicaons of LCC
Life cycle cosng has two principal applicaons. Firstly it is used to compare dierent design solu-
ons to a technical problem – in this case it is the relave dierences between the calculated life
cycle costs that are assessed. Secondly it is used to esmate budget expenditure in future years
for the selected design.
Comparave LCCs can also be used to priorise projects compeng for limited funds, by calculat-
ing how much benet each gives per unit of investment.
These two applicaons are quite dierent. For a comparave study any common factors that ap-
ply across all the designs can be ignored, since it is only the relave costs that are appropriate.
This means that underlying inaon and any items of cost that are duplicated across all designs
need not be considered.
12
cycle, it is important that those soluons/designs provide the
same levels of performance or output. For example, comparing
dierent lighng schemes will require that each scheme provides
the same level and quality of workplace or task illuminaon, or
dierent heang systems must deliver the same heat output.
Once a range of alternave designs have been set up, each one is
modelled according to its costs and benets over the same me
period. For some LCC applicaons, the me period is pre-dened,
whereas other applicaons will require a sensible me period to
be chosen. Each model captures the complete prole of costs over
me – inial installaon, maintenance, equipment replacement,
energy use and other operaonal costs, and also any end-of-life
costs such as decommissioning or waste treatment.
The LCC data from the models is calculated turning each costs
and benets prole into a single number, which is the net present
value of the design. This requires the use of a single discount rate
across all models. The choice of this discount rate is a fundamental
part of the LCC process. Within CILECCTA, the discount rate can be
adapted by the user to represent individual preferences.
Figure 2.1
The iterave process of decision making
13
The system boundary
Just like LCA every LCC analysis has a system boundary within
which are contained all the relevant acvies that contribute to
the cost and benet dierences. This may be more widespread
than at rst thought. For example, the life cycle analysis compar-
ing an innovave plasterboard with phase change material against
a standard product will also need to include the eects on the
heang and cooling system in the building. This is because the
principal benet of the innovave plasterboard is to reduce the
peaks and troughs in room temperature and therefore reduce the
energy consumpon of the building because of less need for heat-
ing or cooling.
The system boundary needs to be set in discussion with the client,
to make sure that the assumpons contained in the analysis are
appropriate and reasonable in terms of the level of design detail
when the LCC is carried out, and in terms of the available sources
of input data.
Iteration is a key part of the process
Iteraon in LCC occurs at two disnct levels. Once the inial LCC
models have been created and calculated, the inputs can be
tweaked to assess the impact of uncertaines in any of the data.
This might be something very specic such as the life expectancy
or energy consumpon of a parcular component, or something
much broader such as the likely future movement in energy costs,
or even the mescale for which the LCC is calculated.
The second level of iteraon can occur when the overall results
are interpreted, as this may indicate some assumpons in the
original scenario need to be invesgated or challenged, or some
changes made to the set of designs being modelled (new ideas to
be included or exisng designs to be modied or removed).
Modelling uncertainty in LCC
Uncertainty in data can be modelled using a range of techniques.
Simple variaon in one or two variables can be assessed by alter-
ing the model(s), rerunning the calculaons and then comparing
the results. At its simplest this might be done by selecng high and
low esmates for the variable and seeing if there is any change
to which alternave produces the most favourable life cycle cost.
However, mulple variables or more complicated probability dis-
tribuons need to be analysed using Monte Carlo simulaon. The
models are recalculated many hundreds or thousands of mes us-
ing sets of input data chosen at random according to the prede-
ned probability distribuons. This funconality in the CILECCTA
soware is further described in chapter 4.
Sources of LCC data
LCC data is required in two main
forms. Firstly there are the es-
mates of cost for dierent project
acvies, and secondly there are
the esmates of life expectancy and
maintenance intervals that dictate
when equipment replacement and
maintenance needs to happen.
Cost data can be obtained from
exisng in-house records, supply
chain contacts, from industry price
books or online services. Life ex-
pectancy data for building services
equipment can be obtained from
estate records, from equipment
manufacturers or from published
sources.
You can read more about price
banks in chapter 6.
14
The results from all the calculaons can then be analysed stas-
cally. This gives mean and median values which indicate «aver-
age» values and also standard deviaons to show how the results
vary. The results can also be shown graphically – see fFigure 2.2.
In this case, it can be seen that there is a large area of overlap be-
tween the LCC results from two compeng designs.
Precision of results
One of the natural implicaons of uncertain input data, even if it
is not explicitly modelled, is that there is a limit to how precise the
results of LCC analysis can be. For example, life cycle costs carried
out at the early stages of design should really be interpreted with
a margin of error of ± 15 %, and even those carried out at detailed
design stage should have a margin of error of at least ± 5 %.
For the analyst this means that it is meaningless to quote life
cycle costs to their calculated precision. Only three signicant
gures need be given (£ 103,000 rather than £ 102,731.28), and
somemes only two signicant gures (£ 100,000 in the above
case).
The CILECCTA soware addresses this by generang scaer plots
of cost and environmental impact for the alternaves being mod-
elled, so that the variety of results for the various alternaves can
be easily seen and interpreted. You can read more about this in
chapter 4 and 7.
Figure 2.2
Frequency distribution of results from LCC Monte Carlo simulation
Life cycle assessment (LCA) is a structured method for calculang the en-
vironmental impact of goods and services. It can be applied to any prod-
uct or process and may include manufactured products, processes, assem-
blies, enre HVAC systems, or even whole buildings within construcon
and building services applicaon. This might sound complicated but in fact
the principles are simple.
Different meanings of «life cycle»
The assessment can represent many dierent life cycle stages of the goods or ser-
vices – see gure 3.1. The two main ones are «cradle to grave», where goods are
modelled from raw material extracon through manufacture, delivery, use and dis-
posal, and «cradle to gate», where goods are modelled from raw material extracon
3 Life Cycle Assessment
Applicaons of LCA
Life Cycle Assessment can be used in many dierent ways, by a wide range of stakeholders.
Policy makers at regional, naonal and internaonal level can use LCA to inform policy decisions
in environmental protecon.
Manufacturers of goods and suppliers or services can use LCA to show how new products or tech-
nologies can be less environmentally damaging than exisng products, and thereby support sus-
tainable growth and development.
Purchasers of goods and services can use LCA to compare alternave products and soluons, to
inform their decision-making and to support any goals they have to favour lower-impact designs.
16
through to manufacture and packaging ready to be shipped to a
wholesaler, retailer or end-customer. A third life cycle is «gate to
design» which is used for modelling processes just within a sin-
gle manufacturing organisaon, say taking a set of o-the-shelf
products and assembling them into a new product.
Environmental Impact Categories and
EcoPoints
Environmental impacts are organised into categories that repre-
sent dierent types of impact. At face value these dierent cate-
gories cannot be directly compared or combined. For example, a
material with a high impact in non-renewable resource depleon
but a low global warming potenal cannot be directly compared
with an alternave material that has a low resource depleon
but a high global warming potenal.
LCA soware packages usually present their results according
to each impact category. For example, global impact catego-
ries include ozone depleon as well as the resource depleon
and global warming potenal menoned above. Regional im-
pact cate gories include water use, land use, eutrophicaon and
photo chemical oxidaon.
Figure 3.1
Typical lifecycles within LCA
17
In addion to this detailed and comprehensive list of impacts,
CILECCTA will also oer the possibility of a «Combined Analysis
Chart». This aggregates the environmental impacts to a single
value and then sets it in relaon with the economic aspects of
a soluon. While losing the objecvity of the assessment, this
oers an intuive way to support decision making.
More than just carbon
The impacts covered in LCA are very broad. They go far beyond
carbon dioxide emissions or other greenhouse gases. For ex-
ample, the standard impact categories include non-renewable
resource use, acidicaon of soils leading to forest decline,
eutrophicaon of water bodies leading to sh decline and oth-
ers. Greenhouse gases are more correctly covered under global
warming potenal, where the global warming eects of dier-
ent gases are appropriately factored and combined into a single
gure expressed as Carbon Dioxide equivalent (CO2 e). The same
is done for other impact categories that are expressed in other
reference units.
Complex relationship between diverse
in- and outputs
The range of goods and services that contribute to the manu-
facture or use of a single product can be unexpectedly compli-
cated, or even circular. The complexity of life cycle inventories,
where the list of constuents for a given product are stored, can
be demonstrated by the case of the mineral wool that might
be used as an insulaon material for ductwork and pipework.
The inventory for this product contains many dierent inputs of
products, recycled materials and natural resources including ba-
salt, limestone, coke, electricity, water, rail transport, and many
dierent outputs of wastes including waste heat, parculates,
and municipal solid waste, and dierent emissions to air, water
and soil including carbon dioxide. All of these inputs themselves
have inventories and their inputs will also have inventories, and
so on. The ulmate aim is to compile the full list of outputs and
emissions in sucient detail for the analysis.
In fact, loops can oen be found within the life cycle inventory
analysis, where the impacts of all resource, material and process
ows that cross the system boundary are analysed. For example,
a product that has steel as a raw material means that coal is in-
cluded as this is one of the inputs for manufacturing steel. But
coal is mined and processed using equipment that includes steel.
The reliance on inventory data and the complexity of its analysis
means that soware is usually needed to carry out LCA.
Sources of LCA inventory
data
LCA inventory data is crical to cal-
culate environmental impacts. Each
inventory is a detailed list of the in-
puts (e.g. resources, raw materials)
and outputs (e.g. emissions, waste)
arising from the lifecycle of a given
material, product, system or service.
There are some wellknown LCA in-
ventory datasets including the con-
strucon sector (Covering dierent
regions in the EU and worldwide).
These are available for a license fee
or may be included in the price of
LCA soware packages.
GaBi (English/ German)
Ecoinvent (English/Japanese/
German)
DuboCalc (Dutch/English)
IVAM LCA Data (Chinese/ Eng-
lish).
In addion, inventory data has been
compiled by a range of internaonal
trade and material federaons. Most
of these datasets are free.
American Plascs Council
European Aluminium Associa-
on
Internaonal Iron and Steel
Associ aon
Plascs Europe.
Based on those databases, product
systems are modeled and their over-
all environmental impact can be ex-
pressed in an objecve way.
Read more about Life Cycle Invento-
ries in chapter 6.
18
Figure 3.2
Framework for life cycle assessment (based on ISO14040:2006)
The functional unit
The descripon of the mineral wool inventory, above, raises an-
other important issue – that of the funconal unit. As well as its
ability to idenfy environmental hot-spots, LCA is also a compari-
son tool where one technical design can be compared with one
or more alternaves to nd out which is the best. To make the
comparison valid, each soluon has to be analysed on the basis
of its performance. For example, two dierent insulaon materi-
als for pipework would be analysed on the basis of the U-value
they provide, as this expresses their insulaon performance. This
would then need to be analysed to understand how much of the
insulaon would be needed in each case – for example, insulaon
for a 10 m length of 50 mm pipe might require x kg of mineral
wool and y kg of expanded foam. The inventories stored in the da-
tabase would both be compiled on the basis of 1 kg of the insula-
on material and the various inputs and outputs would be scaled
accordingly.
This gives rise to the possibility that 1 kg of a new material produc-
es much higher environmental impacts than 1 kg of a tradional
material, but because the new material is so much more eecve
in its performance, the impacts to deliver a required level of per-
formance actually turn out to be much less.
19
The system boundary and the LCA process
The product being analysed, the hierarchy of inputs and the
level of detail in the life cycle all go to dene the system bound-
ary. The denions of the system boundary and of the funconal
unit are fundamental tasks in seng the goal and scope of a Life
Cycle Assessment. From this the inventory is constructed and then
analysed for the environmental impacts – see gure 3.2. At each
stage, the analysis is interpreted and checked to make sure that
the required levels of model accuracy and levels of compleon
and precision of the inventory are all achieved.
20
The life cycle of buildings or products is becoming more important as
more people learn that investment in the construcon stage can have a
signicant eect over the lifeme. To take account of these concerns in
construcon decision-making, we need tools that look at all the phases a
material or product goes through. With the two dierent focuses as LCC
and LCA have, it can be dicult to see what the best overall soluon is.
According to CILECCTA the answer is to combine these two approaches
into one single method: LCC+A.
While there may be one parameter that is more inuenal in making a decision,
it could help to make a beer overall decision to present the whole picture to the
decision-maker. For example the nancial director would only be concerned with
the cost of the project whereas the environmental manager or person in charge
of the corporate environmental policy would be interested in the environmental
impacts. In the world we live in today, both factors have their place and should be
considered.
Current approaches are based on two separate assessments. An LCC study will be
conducted to assess the discounted cost of dierent scenarios or opons, while an
LCA will be carried out to quanfy environmental impacts. This is typically done
in dierent soware tools. While there are special LCA and LCC tools, there are
no sophiscated tools for an integrated assessment of both environmental and
economic aspects. When creang two separate models in dierent tools, there is
always a danger of neglecng aspects in one study that is not included in the other,
which can result in comparing scenarios that are supposed to be idencal, but
actually have a dierent scope and/or system boundaries. CILECCTA and its under-
lying LCC+A approach allow the modelling of both economic and environmental
aspects in a single model, thereby ensuring idencal scope and system boundaries
4 Combining LCC
and LCA: LCC+A
22
for all scenarios or alternaves to be assessed. Furthermore, the
impacts of uncertainty on both result dimensions can be included
in the assessment.
To show this graphically, a simple XY plot allows the reader to see
how the cost and environmental impact interact. The gures ob-
tained from LCC and LCA calculaons may represent probabilies
rather than absolute gures due to sensivity or unknowns. In
some cases the potenal scaer in the results will overlap.
In the Combined Analysis Chart, cost and environmental results of
analysis are shown. The centre of the ellipses represents the mean
values while the width and height represent standard deviaons.
It is the boom le-hand corner that we are interested in, as this is
the part of the chart indicang least cost and least environmental
impact.
A simplied example is ploed in gure 4.1 showing the possible
cost and equivalent CO2 impacts to build 1m2 of wall out of stand-
ard construcon materials such as brick, concrete block, steel, and
reinforced concrete.
As can be seen, in this case the reinforced concrete has both the
highest cost and environmental impact. The size of the mark-
ers gives an indicaon of the potenal scaer in the values, so
brick could have a higher or lower environmental impact than
block. This is an oversimplied example; if full analysis was un-
dertaken then the insulaon material, mortar, nancial as-
pect of me to build, etc. would have to be considered to give
the full picture of which is the best soluon for both cost and
environmental impact, but it does demonstrate how the cost and
impacts can be easily compared for dierent alternaves.
Figure 4.1
LCC+A results of a wall of 1 m3
23
If the ming of the wall acvity is not known, such as in the case
where an extension to an exisng building will be constructed at
some future date, then probabilies can be applied. This eec-
vely increases the scaer of the various numerical results for
each dierent wall material. So, using the example of a company
needing expansion someme over a 10-year period and needing
to build an extension, with the probability of it happening of 10%
at yearly intervals, then we can use Monte Carlo simulaon (see
fact box) to see the eect. The midpoint is the average and the
range (diuseness) of the spot shows the results of the simula-
on, in this case run 1000 mes. There’s a vercal diuseness
(= sensivity to environmental impacts) and a horizontal diuseness
(= sensivity to costs aspects). Now we can see that steel is more
sensive to costs, than to environmental aspects and that it touch-
es the cost range of both brick and reinforced concrete. This sort
of plong can be produced via the soware development within
the CILECCTA project.
While this way of interpreng the data should not detract from the
individual LCC and LCA reports, it does however show to the less
technically knowledgeable decision-makers in these areas that
somemes a small increase in building costs can have a signicant
eect on their environmental impact, or conversely where there
is very lile dierence in techniques for environmental impact the
cost variaon may be dramac.
As we connue into a future where the environmental impact will
play a more signicant role in policy, the understanding of both
the cost and environment will become a more important part of
decision-making.
Figure 4.2
LCC+A results of a wall of 1 m3 with Monte Carlo simulations
Monte Carlo simulaon
Monte Carlo simulaons rely on re-
peated random sampling to obtain
numerical results. By running simula-
ons many mes over the probability
of an occurrence can be calculated.
This can be compared to actually
playing and recording your results
in a real casino situaon: hence the
name.
24
Any approach to the life cycle evaluaon of buildings and building com-
ponents involves looking into the future. But the future is uncertain. The
CILECCTA soware for LCC+A provides new ways of taking account of
future uncertainty.
Impossibility of prediction
Even though it is impossible to predict the future, many exisng soware systems
for LCC and LCA require precise data inputs for every year of the project study
period, typically 20–60 years. The data inputs are in fact esmates based on
today’s assumpons about the future. Because the assumpons are subject to
uncertainty, the input values also have a margin of uncertainty. For example, the
future CO2 emissions from the electricity used in a building will depend on both the
amount of electricity used and the carbon content of the electricity, but neither of
these factors can be accurately predicted.
When the input data for an LCC or LCA study consists of precise values, or «single-
point» esmates, the output is also a precise number that looks like a predicon
– but it is actually an uncertain esmate.
Instead of ignoring uncertainty, CILECCTA treats it as an integral part of LCC+A.
Uncertainty can be pictured by a «fan» diagram as done in gure 5.1. Time runs
from le to right – the le-hand side represents «now». If we know today’s value
for a system of interest, such as the price of natural gas or the embodied CO2 of
concrete, there is a single point on the «now» line. In situaons where the future
is totally predictable, such as the movement of the sun, there is a single line from
today’s certain value to certain values in the future. In situaons with uncertainty
there is a range of possible values in the future, shown on the right hand side of the
diagram. The greater the uncertainty, the wider the range of values.
5 Advances in LCC+A
26
Describing uncertain data
It is more realisc (and also easier) to specify what will happen
in the future using a range of possible values, rather than a «sin-
gle-point» esmate. A «three-point» esmate is a good way of
doing this. The three points are: a) the lowest conceivable value,
b) the most likely value, and c) the highest conceivable value.
Three-point esmates are widely applicable; for example, to es-
mate the service life of the carpet in a hotel bedroom, the three
points might be: a) 1 year (lowest conceivable value), b) 5 years
(most likely value) and c) 10 years (highest conceivable value). Us-
ers of the CILECCTA soware for LCC+A can enter input data as
three-point esmates.
With the input data specied by data ranges, the CILECCTA so-
ware gives a range of possible LCC+A output values. Using the
method of Monte Carlo simulaon, CILECCTA generates a large
number of trial runs – maybe 1,000, 10,000 or even 100,000 runs.
In each trail run the values for the uncertain inputs are randomly
selected from the data ranges. When the output values from all
the runs are combined they form a probability distribuon – the
probabilisc esmate of LCC+A (gure 5.2).
Figure 5.1
Illustrating uncertainty
27
Using probabilistic results
When CILECCTA presents the results of LCC+A as a range of values,
the user gains addional informaon compared to the single value
given by convenonal methods of LCC and LCA. The average LCC+A
value, at the peak of the probability distribuon, is important, but
the shape of the probability distribuon is also signicant. It in-
dicates how likely it is that that the true value will be higher or
lower than the average. A steeply peaked probability distribuon
suggests that the true value will be close to the average; but with
a aer probability distribuon the true value can vary consider-
ably from the average. This tells the user how much condence to
place on the average value, and how much allowance should be
made for dierent outcomes.
Future decisions and exibility
The most common use of LCC and LCA is to help in today’s deci-
sions between alternaves for a construcon project. However,
during the service life of the project many other decisions are
made, including decisions about the replacement of components
that have a shorter life than the study period.
Figure 5.2
Illustrating the pro babilistic estimate of LCC+A
28
Figure 5.3 b
At the time of replacement there is a new decision and a previously rejected alternative might be chosen
Figure 5.3 c
Some alternatives can be expected to disappear during the service life, and new ones become available
Figure 5.3 a
Illustration of a decision which is repeated like-for-like throughout the study period
29
In convenonal LCC and LCA it is assumed that the rst decision
is repeated like-for-like throughout the study period (gure 5.3 a).
This is unrealisc. At the me of replacement there is a new
decision and a previously rejected alternave might be cho-
sen (gure 5.3 b). Also, some alternaves can be expected to
disappear during the service life, and new ones become available
(gure 5.3 c).
These future decisions allow a construcon project to adapt to
unfolding events that are uncertain at the me of design. For ex-
ample, in a parcular project we may know that a wood-pellet
boiler is a good decision today, but we cannot know whether like-
for-like replacement will also be a good decision in 2030. But the
decision-makers in 2030 will know, and decide accordingly. There-
fore, future decisions improve life-cycle performance.
To maximise the benet from future decisions, construcon pro-
jects should be designed with many opportunies for future de-
cision-making – that is, they should be exible. This is not a new
idea, but the CILECCTA method of LCC+A is the rst that can model
exible designs.
Evaluating exible strategies
CILECCTA describes exibility by specifying the alternaves that
can be selected by future decision-makers. In the Monte Carlo
simulaon runs for a exible strategy the most favourable alterna-
ve is chosen at each replacement cycle, and over many simula-
on runs the LCC+A performance of the exible strategy is estab-
lished. It can be compared to the LCC+A performance of other,
non-exible strategies. Because there is oen an addional cost
for exibility, the benet given by exibility over the life-cycle
must be compared to its inial cost to determine whether the ex-
ible strategy is a good idea. This evaluaon of exibility is a unique
feature of the CILECCTA soware for LCC+A.
30
It is a clear objecve of the CILECCTA development that the soware will
be able to access a number of Pan-European data sources. A task was
therefore established to develop a deep understanding of the two types
of data sources, namely Price Banks (PBs) and Life Cycle Indicator Results
(LCIRs) that would support CILECCTA’s development of an integrated tool.
The CILECCTA team’s objecve were to idenfy PBs and LCIRs, and to:
Analyse the data presented, the architecture and mechanism of access for each
dataset.
Benchmark the exisng PBs and LCIRs against best pracce at a global level.
Build on idened best pracce to design a generic architecture and access
mechanism for both Price Banks and Life Cycle Indicator Results.
Ensure compliance with exisng ISO standards and begin the process of encap-
sulang them in new standards if appropriate.
6 Price Banks and
Life Cycle Indicator
Results
32
Characteristics of identied Price Banks
Both data base types are generally region or country specic and
therefore the CILECCTA team were tasked to idenfy Price Banks
in each of the four European regions (the North, East, South and
West) and if possible, at least one in each EU state. A United States
based PB was included to compare with our ndings. A total of 32
price banks from 13 countries were idened.
Feature Finding
Accessibility The programmatic accessibility is as a major performance characteristic, which could be
achieved with direct access via an API or export capability.
The majority of the databases have no API available. API’s existed where a close relation-
ship the dataset and software.
However there are many PBs in simple electronic formats which can be imported by any
customer–CD’sspreadsheetandpdfles.
Codication TheclassicationcodingisofkeyimportanceforCILECCTAasthereisaneedtomapa
unitsbetweendatabasesandwiththeirrespectivei»ofcodication.Many«internallycodi-
ed»databasesarebasedonnationalstandard.
Weneedtonotethat thecodicationof elementshasagrowing importanceinthe soft-
ware industry due to the tendency to integrate design, measurement and tender or budget
procedures.
However many of the databases are based on several national standards often enriched
withinternalcodication. Our study showed no relationshipwithanyinternationalEuro-
pean wide standard.
Integration In response to the question ‘What relation does the database hold with software pro-
grams?Generallydatasetsexistasseparateentitiesorstand-aloneles.Thesehavetheir
origin in old provided by engineering associations or institutions that are not linked to any
specicsoftwareapplication.
Databasesthatreportedacloserelationwithspecicsoftwaregenerallyusedonlinetools.
Classication A hierarchical structure characteristic, related to the granularity held or used in the data-
bases with more than three levels found.
A Price Bank is a database that in-
cludes product and cost data which is
used to calculate life cycle (nancial)
cost of a structure.
Life Cycle Indicator Results is a data-
base which is used to evaluate and
quanfy the energy and material in-
ows and oulows during the life of
a structure. Data from LCIRs are used
to assess the environmental impact
that a parcular product or process
has throughout its enre life cycle.
33
Characteristics of identied LCIR databases
Life Cycle Indicator Results (LCIR) databases is a new term dened
in CILECCTA. Life Cycle Inventories (LCIs) are the basis for the cal-
culaon of LCIRs.
The Life Cycle Inventory invesgaons revealed two categories of
LCI database, namely «pure LCI databases» and «indicator based
LCI databases» – 23 and 13 databases respecvely. The dierenc-
es can be summarized as follows:
A «pure LCI database» oers datasets which contain pure LCI
informaon on dierent processes, regardless if unit or aggre-
gated processes are displayed. By the help «characterizaon
factors» and using «Life Cycle Impact Assessment» methodo-
logy, input and output ows are transferred into potenal en-
vironmental impacts. If this type of database is used, a tool for
conducng the LCIA is essenal and the outputs are not easily
incorporated into calculaons.
An «indicator-based LCI database» contains already «charac-
terized informaon», also known as environmental Life Cycle
Indicator Results (LCIR), on potenal environmental impacts
for dierent processes. Informaon on mass and energy ows
may be only partly reected.
Few provided datasets exists specically for the use in the con-
strucon sector or the building industry, as most LCIs provide raw
output data (e.g., CO2, SO2) of dierent producon processes.
Nine of the LCIs contain or are indicator based LCIR data. With
regard to a European construcon database on a European level,
the applicaon of an already standardized XML data format and
an electronic data transfer has been established. The ILCD format
technology only requires a web-editor to access data.
We found «pure LCI databases» not appropriate for use, whereas
LCIR databases or results (e.g. of environmental product declara-
ons) provide a beer soluon.
Invesgaon of price banks and LCIs constutes the one of the
rst steps for achieving the broader aim of integrang LCC and
LCA for the assessment of sustainable and economic opons in
the construcon industry.
34
CILECCTA data classication
All Price Bank and Life Cycle Indicator Results databases that have
been idened use some form of classicaon and codicaon
system to idenfy where an item’s nancial and environmental
data belongs. The CILECCTA vision is to have a single tool dealing
with data from PBs and LCIRs from all over Europe there will be
many dierent classicaons to take into consideraon.
There is, however, the need to store all in standardized dened
concepts and their meaning in a central repository that all data
users can access. There are many ways of developing such a tool.
However, there has already been done a lot of work by the build-
ingSmart community to accommodate soluons that use these
ideas in the IFD Library. IFD stands for «Internaonal Framework
for Diconaries» which is simply a standard for terminology librar-
ies or ontologies.
Read more about IFD and data mapping in chapter 7.
Feature Finding
Availability – 40% of the LCIR databases have full online access
– 29% is available in CD/DVD.
Languages Majority available in language of host country
Nature There are many university and consultancy-based LCI databases which character-
ize particular industrial sectors and product groups. They are generally very diverse
and fragmented, with a low level of cross-national harmonisation. Germany, Swe-
den, and Switzerland lead the way in LCI data development.
Data LCI databases provide raw data which may be compared for different options in
LCC+A.
Assume that there are two materials, A and B, which can be used interchangeably
during construction. When comparing the environmental impact of producing those
materials, the material that with the least amount of is selected.
– For material A, a raw LCI database provides an output that 0.3 kg SO3 will be
produced
– For material B, the output is 0.4 CO2. In this case, it is not clear which one should
be selected since the output is expressed in different units.
However, indicator based databases express the output as a number for each
material production, global warming potential would be expressed as GWP g CO2
= 100 000
We concluded that we should use LCIR databases
Classication Classication system indicates how the data is indexed in a database and which
standard is used. Data for building elements, materials, equipment and labour prices
isclassied onnational standardsandabout 20%ofthemarebased onorganiza-
tion-specicinternalstandards.
The main objecve of CILECCTA has been to develop soware that a) goes
beyond state of the art, as far as exisng avai lable tools and methodologies are
concerned, and b) includes and combines cost data and environmental data in
construcon industry decision making. This chapter explains how CILECCTA deals
with issues like building product classicaon, uncertainty, probabilisc cost
modeling and environmental impact categories.
IFD Library – from products to concepts
In the process of mapping cost data and environmental data, in general or for a
specic case, it is of vital importance that data providers nd products and con-
cepts that are similar. In order to allow data providers from all over Europe to map
their domain data against comparable building concepts, CILECCTA have to follow
a common building product classicaon (see fact box). To achieve this, the part-
ners decided to lean on the work currently under development by the building-
Smart community – The IFD Library.
The IFD Library is a building SMART development project and are basing its solu-
ons on the framework provided by ISO 120063:2007 Framework for object ori-
ented informaon.
7 CILECCTA Software
36
Building product
classicaon
The benets of using an interna-
onally developed building-product
classicaon are many:
One gains access to already de-
ned concepts from other mem-
bers
It is possible to compare prod-
ucts with the same properes
across borders
The IFD community has rules
that will make sure concepts are
dened at the same levels
One could contribute to the
community by dening/ adding
concepts to the constantly grow-
ing concepts database.
Figure 7.2
The structure of the IFD Library im-
plemented in the software
Figure 7.1
Screenshotofthemappingtoolusedtocreatemappingles
37
Uncertainty on input values
Current pracce in performing LCC analysis is to discount the fact
that the future is uncertain. The CILECCTA tool oers several tools
to model various types of uncertainty; Three Point Esmate, Bino-
mial Tree and Expression.
Figure 7.3
Screenshot of the possibility of using Three Point Estimate
Using three point estimates on data input will provide the decision-makers
with output results that are more realistic than just discounting uncertain-
ty. This is a commonly used technique when making a probabilistic LCC
analysis.
Figure 7.4
Screenshot of the possibility of using Binominal tree
In the binomial tree approach the uncertainty of the value of the underly-
ing asset is assumed to follow binomial variation. Therefore the binomial
tree is an explicit statement of the underlying uncertainty of the value of
the asset.
Binominal tree
Three Point Esmates
Mathemacal Expressions
Figure 7.5
Screenshot of the possibility of using Mathematical Expressions
Users are also allowed to add their own mathematical expressions to
express how the input values should be represented.
38
Figure 7.6
Screenshot of the presentation of the results with probability included
Probabilistic cost modelling
Included in the soware is the possibility to use Monte Carlo
simulaon. Monte Carlo is a widely used approach for probabi-
lisc cost modeling. The approach is relavely simple in terms of
use, understanding and reporng, and can handle many dierent
formulaons of uncertainty, overcoming some of the limitaons
of other approaches.
When uncertainty is described in terms of a probability distribu-
on, the Monte Carlo approach randomly samples from this prob-
ability distribuon and simulates the response of the system to
this changing, uncertain parameter (e.g. switch to a cheaper en-
ergy source, develop a building, or «wait and see»). This process
is repeated mulple mes, and the results of each sample run are
aggregated to give probability distribuons of the opon value –
which can be used to inform decision-making. Figure 7.6 shows a
screenshot of the presentaon of the results when probability is
included into the analysis.
When modelling probability and uncertainty, the output data will
be shown with standard deviaon. The output is Net Present Val-
ues (discount rates on input values over a given study period) and
not actual costs. The cost output, shown as NPV-values, includes
one-o costs together with ongoing costs during the life me
(gure 7.7).
39
Environmental Impact Factor (EIF)
To be able to compare costs against more than one environmental
impact category (e.g Global Warming Potenal, unit: kg CO2 eq.)
the term Environmental Impact Factor (EIF) has been dened. In
this way the results presented by the soware can be two-dimen-
sional, but sll considering more than one environmental impact
category at once. The Environmental Impact Factor is weighing
the dierent environmental categories against each other result-
ing in one nal factor. The user of the soware can decide what
emphasis she will make on each impact category depending on
what the assessment shall enlighten. See gure 7.8.
Figure 7.8
Weighting factors in the CILECCTA software (screenshot)
Figure 7.7
Screenshot of the presentation of the results with probability included
Figure xx Weighting
factors in the CILEC-
CTA software
40
Figure 7.9
ScreenshotofthenalversionofCILECCTA software
Version 0.1 of the CILECCTA software
The CILECCTA soware v 0.1 has been systemacally tested and
evaluated by the demo projects and the project parcipants
during the project period. The feedback formed the basis of
making new specicaon for improved versions of the soware.
Figure 7.9 shows a screenshot of the nal version as we see it to-
day. The alternaves which are to be compared are presented to
the le and the graphs illustrang the results to the right. Chapter
8 demonstrates the soware through real cases.
In order to test the features of the CILECCTA soware tool, three demon-
straon projects were selected. The demonstraon projects represent a
wide range of scenarios in the construcon sector and have allowed in-
depth tesng of the CILECCTA soware.
The three demonstraon projects are
The MESSIB Demonstraon House
Economic and environmental impacts of thermal storage systems in build-
ings are assessed for the MESSIB demo-house in Greece. Responsible partner:
Acciona.
The Heang System Case
Dierent scenarios for heang systems are assessed for an employee house
related to a resort in Mallorca, Spain. Responsible partner: TUI.
The Road Case
Opmal specicaons for road construcons are idened based on uncertain
development of trac in Spain. Responsible partner: APIA XXI.
Apart from providing actual case studies for the general applicaon of the so-
ware tool, each case study also has a slightly dierent scope. The MESSIB demo
case focuses on the assessment of newly developed construcon materials, such
as phase-change insulaon material. The Heang System Case has a special focus
on the result presentaon and interpretaon. Finally, the road case has been used
to improve the uncertainty analysis part of the CILECCTA tool.
In the following, the demo projects are described in detail, with their tesng scope,
experiences and lessons learned during the tesng and feedback of the tool use.
8 Case Studies
42
The MESSIB demonstration house
MESSIB (Mul-source Energy Storage System Integrated in Build-
ings) was a four-year project nanced by the European Commis-
sion under the 7th Framework Programme from 2009 to 2013.
It has been dedicated to developing, evaluang and demonstrat-
ing the mul-source energy storage systems in buildings, based
on new materials, technologies and advanced intelligent control
systems to manage energy demand in buildings. Energy storage is
the way to conserve energy (thermal or electric) in one form and
release it when needed in the same or another form.
One of the forms of thermal energy storage is realised via special
latent heat storage in Phase Change Materials (PCM) (gure 8.1).
These materials can be integrated in the building structures, such
as: walls, windows, ceilings or oors.
CILECCTA is used to assess the paran-based PCM system in-
stalled in the plasterboards of external and internal walls of the
MESSIB demo house which is a residenal building in Amphilochia,
Greece (gure 8.2).
Plasterboard is a common lining material used in steel-framed
construcons, such as the MESSIB demo-house. Replacing it with
PCM plasterboard provides greater heat capacity, and more en-
Figure 8.1
Gypsum Plaster Board with PCM.
© BASF SE, 2013
43
ergy can be stored in the building´s envelope, which helps to re-
duce energy consumpon for cooling or heang in a passive and
sustainable way.
Two alternaves have been assessed with the CILECCTA tool:
Lower energy consumpon related to the «MESSIB building»
with PCM plasterboards
Higher energy consumpon related to a tradional building
with tradional plasterboards.
Within this demo project, CILECCTA has been used to quanfy the
saving potenal of new materials and the capability of CILECCTA
to assess newly developed materials. Furthermore, the idenca-
on of the inuence of single components such as the PCM on the
enre house has been assessed with CILECCTA.
Figure 8.3 and 8.4 shows results from the tesng. PCM plas-
terboard seem to be more environmentally friendly than the
convenonal material. In the result of sensivity analysis
(gure 8.4), the target price of the PCM plasterboard 30 mm
should be lower than 27€/m² to get lower cost of the MESSIB
building in the inial stage of its life cycle. Figure 8.2
MESSIB demo-house in Amphilo-
chia (Greece)
44 Figure 8.3
Analysis Chart illustrating the results from the testing of MESSIB demonstration case (screenshot)
Figure 8.4
Sensitivity analysis on life cycle costs for the MESSIB demonstration case (screenshot)
45
Tesng experience and lessons learned
«The CILECCTA soware is easy to use and gives exibility in evaluaon of the
economic aspect in the construcon sector. For example probabilisc analy-
sis that helps to calculate the degree of uncertainty of a construcon invest-
ment. At present me it doesn´t have direct competors in the market, which
makes CILECCTA soware unique.
From the early tesng we learned that the process of integraon of PBs
and LCIRs with the CILECCTA soware was tedious and me-consuming. It
required the use of another mapper program to have access to the LCIRs.
Moreover, in the case of the MESSIB demo-house some new construcon ma-
terials had been installed, which do not exist in any available data-base, which
made it challenging to do the analysis properly.
This was all important experiences for further developments of the so-
ware.»
Ewa Alicja Zukowska, Acciona
46
The Heating System Case
Dierent heang systems were considered for the Robinson
Club Cala Serena, a TUI resort in Mallorca. In 2010, a biomass
heater using wood pellets as fuel was integrated in a sta house.
This was taken as a real-life case basis for the dierent scenarios
conducted, as renewable energy sources are being considered for
the enre club.
It was decided to assess the measure ulizing the CILECCTA so-
ware and to compare it with alternave renewable heang sys-
tems. This was done to idenfy both economic and environmen-
tally reasonable systems and combinaons of heang systems in a
life-cycle perspecve. In parcular, there were four systems being
assessed:
S1: a biomass heang system, current status of the building,
which supplies all the heat demand.
S2: a solar thermal heang system, which supplies 60% of the
domesc heated water demand, combined with a natural gas
condensing boiler, which provides the balance of the heated
water.
S3: a biomass heang system, responsible for the domesc
heated water demand, combined with a water-water heat
pump and a suboor heang installaon to heat the building.
Figure 8.5
Robinson Club Cala Serena, Mal-
lorca
47
Figure 8.6
Comparison of heating system
scenarios S1-S5 (screenshot)
S4: a solar thermal heang system, which supplies 60% of the
domesc heated water demand, combined with a water-water
heat pump which provides the rest of the domesc heated
water and a suboor heang installaon to heat the building.
A scenario S5 was also included to compare the scenarios to a
system with a duel fuel boiler using fossil fuels.
Figure 8.6 shows some of the simulaon results were the heang
systems are compared. As can be seen, the biomass system (S1)
is the alternave with the least normalized Environmental Impact
Factor and are here used as reference with Environmental Impact
Factor (EIF) = 1. The solar collector and heat pump system (S4) is a
bit cheaper, but has over 40% larger EIF.
Deterministic versus probabilistic approach
Figure 8.7 shows a simulaon where a determinisc approach
is used to compare the alternaves against kg Sb equivalents.
When comparing this gure with gure 8.8, where uncertain en-
ergy prices are taken into consideraon leading to a probabilisc
approach, it becomes clear why a probabilisc approach can give
beer and more realisc results.
On the other hand, the costs of the future are also uncertain. The
CILECCTA soware gives therefore the percentage probability
of costs for the dierent scenarios. The result can be studied in
gure 8.9.
48
Figure 8.8
Probabilistic approach, taking into account uncertain energy prices (screenshot)
Figur 8.7
Deterministic approach (screenshot)
49
Tesng experiences and lessons learned
«While in general economic and environmental impacts of heang systems
can be calculated separately with other soware tools, an integrated assess-
ment of both dimensions with exisng tools is currently not possible. Fur-
thermore, CILECCTA allows assessment of the implicaons of the uncertain
development of energy prices, among other factors.
The CILECCTA tool is based on an easy-to-understand modular modelling
approach that enables the user very quickly to get rst results, but on the
other hand to model very complex situaons. Especially the possibility of
including probabilisc scenarios enhances the global picture of a project by
far, and helps the aempt to achieve a noon of future trends. It allows you
to systemacally support decision-making processes for all types of construc-
on-related decisions from both an environmental and an economic point of
view.
Apart from regular feedback concerning the use of soware and minor
comments related to improvement, the TUI demo case found the presenta-
on of the results to be a key factor in the wider use of the CILECCTA tool.
CILECCTA processes a large amount of data, both from an environmental and
economic point of view. This data has to be presented in a user-friendly way
and should be easily understandable.»
Dieter Semmelroth, TUI
Figure 8.9
Graph illustrating the probability of costs for the different scenarios (screenshot)
50
The Road Case
A complete road design project includes detailed topograph-
ic studies, geotechnical surveys, analysis and characterizaon
throughout the enre length of the road, and the design of dier-
ent structures (pavement, drainage, bridges, retaining walls, etc.).
The engineering process includes many variables and a long term
project analysis, making it possible to take into account upgrade
situaons depending on trac evoluon or even nancing capa-
bilies. The current road demonstraon case focuses on the de-
sign and selecon of the pavement structure for a generic square
meter of the road, based on the same parameters used on a real
case by the civil engineers.
The design of pavement structures is a science that involves study-
ing the constraints of the road paths, the supporng capacity and
material characteriscs of the available substrates, as well as the
climate, period and above all the trac usage planned for the in-
frastructure. The case study follows the standards used in Spain to
select and size the structural secon of the pavements depending
on two main parameters: the available foundaons for the «sub-
grade», and the «trac category» the road must serve during its
life cycle. As the future development of trac is subject to uncer-
tainty, CILECCTA can contribute to the decision making process by
analyzing the associated real opons and oering the economical
and environmental evaluaon of dierent alternaves, including
Figure 8.10
Road base pavement structure detail
51
Figure 8.11
Economical sensitivity analysis of the road case alternatives when the discount rate varies from 4% to 14%
∈
aspects of the construcon phase, the O&M phase and the po-
tenal upgrades. Therefore, the focus related to the road case has
been the applicaon of the Life Cycle Opon assessment module
of the CILECCTA tool. One example is the evaluaon of the im-
pact the discount rate uncertainty has when deciding if a exible
alternave is more advantageous than a xed non-upgradable
one. Figure 8.10 shows the combined environmental and eco-
nomical evaluaon comparing several road pavement structures,
with dierent surface course, base course and subgrade combina-
ons (E1 212, E2 122 etc.), as well as the possible upgrade paths
(from a 232 to a 132, etc.), while gure 8.11 shows the resulng
economical evaluaon and turning points when the discount rate
is changed. In this use case there was also uncertainty related to
trac growth (evaluated as a three point esmate). Figure 8.12
shows that with low trac growths the exible alternaves oer a
much beer economical result in the long term, while when high-
er trac growths appear high specicaon roads are preferred.
The sensivity analysis proved to be a very powerful tool in or-
der to understand the context dependency of the choices to take.
Since the road case showed a big dependency of two main pa-
rameters, both related to the economy, the discount rate and the
trac growth, it was logical to progress the analysis into a two di-
mensional sensivity analysis. In order to allow a two dimensional
sensivity analysis there must be a selecon done among the al-
ternaves based on a certain criteria; therefore we must dene a
52
Figure 8.12
Economical sensitivity analysis of the road case alternatives when keeping the initial conditions, but varying the
typicaltrafcgrowthfrom0%to4.5%
∈
decider associated to a certain unit within the calculaons. For the
road case the lowest LCC expected value was kept as selecon cri-
teria, while varying the discount rate from 4% to 14% and adding
the uncertainty to the trac intensity growth (from a typical 0% to
a 4.75%), geng the next combined graph (gure 8.13).
The general trend is that for low discount rates and high trac
growth rates, high specicaon soluons perform best, whereas
for high discount rates and low trac growth rates, low specica-
ons with exibility for upgrading perform best.
CILECCTA should not be treated or measured as a future predicon
crystal ball, but instead a present wide range evaluaon tool that
unhides the uncertaines, and is capable of successfully providing
context aware updatable decision roadmaps. The process involves
modelling the basic premises, with the capability to introduce the
associated uncertaines for each variable, and provide environ-
mental and economical life cycle evaluaons of the alternaves
that can help you argument the value of not only the straight
forward soluons, but also the exible real opons alternaves.
CILECCTA allows the construcon sector to eciently analyse and
reason any decision making process by oering a clear picture of
where the alternaves might change, allowing for wiser and more
sustainable decisions.
53
Tesng experiences and lessons learned
«For the tesng process the dierent road design alternaves need to be
clearly dened and modelled, based on the dierent units and parameters of
the materials to use of each layer and work to perform in order to construct
it. As a general experience this task takes a signicant poron of the design
phase, but has the advantage that once the model is in place results will be
possible for a wide range of scenarios. Furthermore one of the greatest add-
ed values of the tool is to be able to take uncertainty parameters, like the
future road trac category, and use it to simulate possible alternave changes
– road pavement upgrades- that can provide some very interesng decision
taking assessments on the most opmal soluon for the current project.»
Ignacio Robles Urquijo, APIA XXI
Figure 8.13
Combined economical sensitivity analysis of the road case alternatives when the discount rate is varies from 4% to
14%andthetrafcgrowthchangesfrom0%toa4.75%
54
Parallel with the CILECCTA soware development, the partners in the con-
sorum have been developing training courses and e-learning modules.
This has been done to explain the topics of sustainability, LCC, LCA, LCC+A,
together with the CILECCTA soware. The courses combine knowledge
from research as well as experience from the demo-projects.
Norwegian Technology has developed in-house training modules and vocaonal
courses, BSRIA has constructed industrial courses, and USTUTT, together with LTU,
has had the responsibility for development of university courses.
In-house training
To allow training of the in-house parcipants in the project, a series of e-learning
courses has been developed and divided into three modules:
Module 1 Basic training contains general theory about LCC and LCA, and users are
presented with the concepts of exible design. The purpose of this training course
is to give the project parcipants basic knowledge and understanding of the princi-
ples the CILECCTA soware is based on. These modules will form the basis for vo-
caonal training. You can take Module 1 e-learning course by clicking on gure 9.1.
9 Training and
e-learning
56
Module 2 is the in-house training course for the CILECCTA so-
ware v0.1. The purpose of this training course is go give project
parcipants’ basic training in trying out the soware to provide
feedback to the developers of the soware. This module is avail-
able to project parcipants on the CILECCTA website and requires
login.
Module 3 is more advanced training in the use of the CILECCTA
soware. The purpose of this training course is to show what the
soware is capable of, and will focus on how changes in input data
will aect the results of the calculaon. Parts of this module will
also be included in vocaonal training.
Figure 9.1
Module 1 Basic training. Click on
theguretotakethecourse
Figure 9.2
e-learning Module 3. Three anima-
tion videos are made illustrating
each demonstration case: The
MESSIB Demonstration House, The
Heating System Case and The Road
Case (picture)
57
CILECCTA education possibilities
You are able to do courses within the environmental and econom-
ic topics that CILECCTA is built on. Educaon within CILECCTA is
divided into three levels; vocaonal, industrial and higher educa-
on.
Vocational training
Vocaonal training will be an e-learning course using Module 1
Basic training as basis. In addion it will show an example from the
CILECCTA soware and focus on the results from the calculaon
and how to understand them. This training course will be avail-
able on the CILECCTAwebsite. It is planned to oer this course for
example in summer school.
Industrial training
Industrial training aims at potenal applicants of the CILECCTA
soware from industry. Therefore, the course will focus more
strongly on everyday aspects of LCC, LCA and LCC+A. Special focus
will be on model generaon, modelling guidelines and interpreta-
on of results, while scienc background is not at the core of
training. The course will be oered to industrial applicants through
members of the CILECCTA consorum.
Figure 9.3
CILECCTA training
Photo: Taran Gjoeystdal
58
Industrial training has been divided into three courses. Two of
these courses are in a classroom style that is aimed at industrial
personnel who wish to learn how to understand or carry out life
cycle cosng or life cycle analysis. The third course will be delivered
via webinar and covers LCC+ A. This course is aimed at decision-
makers within industry so that they can understand how to use
both LCC and LCA in the decision-making process.
Course 1
Advanced Life Cycle Cosng – a oneday course
(This is an addon to a 2day course on Life Cycle Cosng).
Life Cycle Cosng enables project sponsors and delivery teams to
evaluate the combined capital and operang costs of construc-
on work. This is important to make sure that the client is geng
long term value for money from the project. This training course
presents some advanced topics such as probabilisc analysis, «the
opons-based approach», the principles of deferring decisions,
the Binomial Tree method of calculang costs or benets of de-
ferring decisions, and the impacts of these approaches. Pricing a
deferred decision enables a client to take a realisc view of the
nancial benets of incorporang exibility into a design. Exam-
ples might include deliberately designing a new building so that it
can be converted from commercial to domesc use and vice versa
as cheaply and easily as possible, or deliberately designing a heat-
ing system that can use mulple fuels so that the primary fuel can
be switched as prices change.
Course 2
Life Cycle Assessment – a two day training course
Life Cycle Assessment is becoming a key tool in understanding the
environmental impact of a product or process. LCA enables pro-
ject teams to make informed design decisions as to which opons
have the lowest impact on the environment across their whole
lifeme. A full LCA covers the cradle-to-grave scenario, analysing
the impacts of the raw materials used, manufacturing processes,
use of the product and nally disposal processes. Outputs can be
various, not just the carbon emissions, thus providing a full pic-
ture of the predicted impact on the environment. The course will
cover the key processes in LCA as outlined in ISO 14040:2006 –
Environmental Management – Life Cycle Assessment – Principles
and Framework, and ISO 14044:2006 – Environmental
Management – Life Cycle Assessment – Requirements and Guide-
lines.
Course 3
Combining life cycle cosng and life cycle assessment – Webinar
Life cycle cosng is becoming more widely used to help project
teams understand the long-term cost implicaons of the design
implicaons they make, for example whether a higher equipment
specicaon is worthwhile in terms of savings from increased en-
59
ergy eciency or equipment life expectancy. Life cycle assessment
is also being used to highlight the environmental impacts of de-
sign decisions such as choice of construcon materials, or passive
vs. acve heang and cooling.
These two analyses are usually reported separately to cost consul-
tants and to sustainability consultants respecvely. But to make
the best overall decision it is necessary to combine the economic
and environmental performance into a single set of results. This
webinar will explain how the results of lifecycle cosng and life
cycle assessment can be brought together in a praccal way, to
help clients, designers, contractors and specialist suppliers make
beer decisions. The webinar will also explain some of the pialls
that clients and project teams should avoid.
If you are interested, please contact Ian Wallis at BSRIA (ian.wal-
lis@bsria.co.uk). More informaon about the courses can also be
found at www.bsria.co.uk.
Figure 9.4
CILECCTA education
Photo: Taran Gjoeystdal
60
Higher education
The probabilisc approach of the soware allows benets com-
pared with determinisc approaches, as it is possible to evaluate
the future outcome connected to uncertainty. With these possibil-
ies there is a need of knowledge among students. The university
courses have been constructed as general decision making cours-
es and are suitable for both economics and engineering students.
The entry requirements are general; no other university course
is necessary before taking the rst course. In total, there are four
courses: a Sustainability course, an LCC course, an LCA course and
an LCC+A course.
The sustainability course focuses on what sustainability actually is
and why it is relevant to industry and society today. It also intro-
duces the students to the concept of life cycle thinking (LCT).
Among the topics in the LCC course are the advantages and dis-
advantages of dierent economic methods for cost analysis and
dierent life-cycle cost models.
Life Cycle Assessment or LCA describes a method of quanfying
the environmental impacts of products, processes or services
along their enre life cycle. Within this segment of the course, the
background methodology of LCA, as well as its applicaons, is de-
scribed.
The LCC+A course focuses on the analysis and evaluaon of in-
put and output for the soware. The students will learn and use
dierent concepts such as real opon alternaves and muldi-
mensional decision criteria.
LCC+A Course
The LCC+A course at university level is
available free of charge for students
and university employees, as well as
for members of non-prot research
bodies. This course is based on the
outcomes of the CILECCTA project
with major contribuons by BSRIA,
the University of Luleå and the Uni-
versity of Stugart.
If you are interested in this course,
please contact Hannes Krieg at the
University of Stugart (hannes.
krieg@lbp.uni-stugart.de)
Results and ndings from the CILECCTA project have been made available
to the public through seminars, papers and arcles in scienc journals.
From January to May 2013, CILECCTA seminars were held in eastern, western,
northern and southern Europe. The seminars were aiming to give an introducon
to the methodology behind CILECCTA, together with informaon about the so-
ware and how it can give benets to the construcon sector.
In January a seminar was held in Poznań, Poland. The seminar took place at the
BUDMA Construcon Fair, which is considered the most important trade meeng
in Poland. In April two training events connected to the CILECCTA demonstraon
cases were organised, focusing on assessment capabilies for the soware. One
was held in Madrid, Spain, and another one in Hannover, Germany.
In May CILECCTA was represented by a stand at the Elfack trade fair in Gothenburg,
Sweden. Here the tool was presented by an animaon video and a quiz was held to
challenge the audience to see how much they know about life cycle assessments
and CILECCTA.
A full-day seminar took place in London in February. In total 47 feedback forms
were received at the end of the event. 65% of all delegates completed a form. This
is a very high return, given that the feedback forms where not submied by some
of the CILECCTA partners present and actual speakers who felt that their views
might be biased.
Figure 10.1 shows that building owners, consulng engineers and FM and mainte-
nance providers comprised three quarters of all those aending.
10 Seminars, Papers
and Scientic
Articles
62
Figure 10.3
Question: Where your objectives met?
Figure 10.1
Attending delegates
Delegates were asked for their objecves for aending the semi-
nar. From the 45 responses answering this queson, life cycle in
general was a key objecve, accounng for 56% of responses. As
for the overall dierence between LCA (environmental) and LCC
(nancial) implicaons, there was no overall dierence with 20%
each (gure 10.2).
As can be seen in gure 10.3, an very high percentage (93%) of
respondents stated their objecves had been met.
Figure 10.2
Question: What were your objectives
for attending this event?
63
Figure 10.4
The presentations from the semi-
narwerecapturedonlm
The presentaons from the seminar in London were captured on
lm. Just click on gure 10.4 and you will be guided to these ve
presentaons:
Life Cycle Cosng: David Churcher, BSRIA
Life Cycle Assessment: Hannes Krieg, University of Stugart
Evaluang Life Cycle Opons: William Fawce, Cambridge
Architectural Research
Road Construcon – Ulizing Trac: Ignacio Robles, APIAXXI
Low Carbon Heang Systems: Hannes Krieg, University of
Stugart
Figure 10.5
Seminar in London, England
64
Figure 10.8
Elfack trade fair in Gothenburg, Sweden
Figure 10.9
CILECCTA event in Madrid, Spain
Figure 10.7
CILECCTA event in Hannover, Germany
Figure 10.6
Seminar in Poznan , Poland
65
Papers and scientic articles
Many papers and scienc arcles have been produced during the four years of
CILECCTA. Selected examples are listed below.
2013
Title Integrated environmental and economic assessment in the construc-
on sector
Authors Hannes Krieg, Stefan Albrecht, J. Gantner, William
Fawce
Where SIM conference, June 26-29, Lisbon
Title Time Preference and Risk Aversion Among Development and Construc-
on Professionals and Managers
Authors Ian Ellingham, William Fawce, and Peter Wallström
Where The Internaonal Associaon of People-Environment Studies (IAPS),
25-28 June, A Coruna, Spain
Title
Whole-life carbon analysis: integrang the analysis with design
Author
William Fawce
Where
Ecobuild 2013, London, 7 March
2012
Title Flexible strategies for long-term sustainability under uncertainty
Authors William Fawce, Marn Hughes, Hannes Krieg, Stefan Albrecht &
Anders Vennström
Where Building Research & Informaon, Volume 40, Issue 5, Routledge
Title Quanfying the benets of open building
Authors William Fawce and Marn Hughes
Where Internaonal Conference on Open Building 18th, 19–21 Nov, Beijing
Title
Embodied carbon: an overview of measurement techniques and cur-
rent material labelling
Author
William Fawce
Where
Ecobuild 2012, London, 21 March 2012
2011
Title Invesng in exibility: The Lifecycle opons synthesis
Authors William Fawce
Where Projecon, Volume 10, MIT
Link hp://web.mit.edu/dusp/projecons/projecons10web/Projec-
ons10_fawce.pdf
66
Title Sustainiable construcon projects: case study of
exible strategies for long-term sustainability under uncertainty
Authors William Fawce, Hannes Krieg, Marn Hughes, Stefan Albrecht &
Anders Vennström
Where SB11 conference, November, Helsinki
Title Using Life Cycle thinking approaches for energy price sensivity analy-
sis along the value chain
Authors Stefan Albrecht, Hannes Krieg, Thilo Kupfer, Jan Paul Lindner
Where SIM2011 – Sustainable Intelligent Manufacturing
ISBN : 978-989-8481-03-0
2010
Title Determinaon and cosng of sustainiable construcon projects: opon
based decision support
Authors Anders Vennström, Thomas Olofsson, William Fawce, Ala Dikbas
Where CIB W78 – Applicaons of IT in the AEC Industry&
Accelerang BIM Research, 27th Internaonal Conference 16-19 No-
vember, Cario
Title CILECCTA Herramientas de análisis de ciclo de vida, costes y opciones
Authors Juan José González Méndez, Ingacio Robles Urquijo
Where SB10mad Sustainable construcon. Revitalizaon and rehabilitaon of
neighborhoods, 28th of April, Madrid
Link hp://www.sb10mad.com/ponencias/archivos/c/C059.pdf
The CILECCTA project was iniated to try to combine methodologies relat-
ed to Life Cycle Cosng and Life Cycle Assessment. The aim was to develop
soware which will make it possible to take both costs and environmental
impact into consideraon before making important decisions. In pracce,
this means going beyond «state of the art» and established pracces.
The results developed by CILECCTA are innovave. Most standards in the building
industry are not based on innovave thinking. They are the result of exisng prac-
ces over me. Output from CILECCTA would naturally constute input to guid-
ance documents, training-courses or specicaons that could make the industry
adopt the new approaches and perhaps work dierently than they do today.
Over the last 10–15 years a lot of specicaons and standards have been draed
and developed in order to increase and improve the ow of building informaon
in building projects. Organizaons like buildingSMART Internaonal have made it
possible to organize projects providing standardizaon bodies with new innovave
specicaons and standards. Results from CILECCTA may also constute input to
buildingSMART or relevant standardizaon commiees.
11 Input to Standards
68
Recommendations for existing and new
standards
The CILECCTA project has provided relevant standardizaon
commiees with technical report containing recommendaons
to exisng and new standards. Experiences concerning data-
mapping and development of mapping tools are topics discussed,
together with recommendaons related to the following topics:
New terms and methods
─ LCC+A: describing both cost and environmental aspects of
a project
─ Flexible alternaves: alternaves modelled with real opon
techniques
─ Probabilisc instead of determinisc thinking
Case-use examples
The 3 demo projects in CILECCTA could all constute informa-
ve annexes to standards showing how it is possible to use
probabilisc techniques when analyzing costs and environ-
mental impacts on projects. This is not something exisng
standards promote today.
Uncertainty
Exisng standards are what one could call a result of how the
building industry thinks Life Cycle Cosng should be dealt with.
Most analyses are done based on historical data and probabil-
isc analyses are seldom used. Exisng standards barely men-
on this as a possibility.
A real improvement to exisng standards would be to imple-
ment, as an alternave to tradional determinisc analyses,
simple workows and techniques describing how to perform
various probabilisc analyses. Examples in the informave sec-
on of the standard could show the benets of carrying out
analyses in this way.
69
Figure 11.1
Construction work at Bjørvika in Oslo, Norway. Photo: Mette Langeid, SINTEF Academic Press
70
The purpose of CILECCTA is to oer decision support when modeling vari-
ous construcon related scenarios – start up through operaon, mainte-
nance, change of use and demolion phases of a construcon project.
The core of the CILECCTA soware is the calculaon engine that can be accessed
through a web enabled interface. The soware will connect to external data bas-
es of nancial and environmental data. Alternavely a user has the opon of up-
loading proprietary data.
The CILECCTA team is oering customers the opon of developing unique tem-
plate for the running of the soware. Theses applicaon templates will be devel-
oped at a price to be agreed with a user. They will have the opon of making these
applicaons available through a library, for at a fee which will generate an income
stream for the applicaon owner.
It is also possible to consider customizaon if a customer would like to directly con-
nect the CILECCTA core engine or applicaons with their exisng system.
12 CILECCTA Business
Plan
72 Regional exploitation strategies
In addion to this main overall strategy the CILECCTA partners
have explored other possibilies on a more regional or local level.
Several of the partners have monitored other ongoing projects,
possible future projects or business opportunies throughout the
CILECCTA project.
The new CILECCTA webpage
The consorum will be launching a new commercial page. Please
go to www.cileccta.com for more informaon on the CILECCTA
soware.
This is the most important contact point for aracng new part-
ners who might be interested in CILECCTA as «Soware as a Ser-
vice», or addional services like applicaons development servic-
es, customizaon services, training and support.
You can also nd us on
Facebook: hps://www.facebook.com/cileccta
Twier: hps://twier.com/cileccta
Google + :
hps://plus.google.com/110518289328581828009
Pinterest: hp://pinterest.com/cileccta/
Slideshare: hp://www.slideshare.net/cileccta
The possibilies are numerous to use CILECCTA knowledge as a
basis for further developments in the years to come.
Figur 12.1
Illustration of the CILECCTA busi-
ness model
73
Partners
CAMBRIDGE
ARCHITECTURAL
RESEARCH
LIMITED
ASM-CENTRUM BADAŃ I ANA-
LIZ RYNKU Sp. z o.o. (Poland)
www.asm-poland.com.pl
Holte as (Norway)
www.holte.no
Cambridge Architectural
Research Ltd (UK)
www.carltd.com
BSRIA (UK)
www.bsria.co.uk
Luleå University of Technology
(Sweden)
www.ltu.se
Fraunhofer Instute for Build-
ing Physics (IBP) (Germany)
www.ibp.fraunhofer.de
University of Stugart
(Germany)
www.lbp.uni-stugart.de
TechnoBee (Turkey)
www.technobee.com.tr
Designtech (Sweden)
www.designtech.se
PE INTERNATIONAL AG
(Germany)
www.pe-internaonal.com
Norsk Teknologi (Norway)
www.norskteknologi.no
SINTEF Building and
Infrastructure (Norway)
www.sintef.no
TUI AG (Germany)
www.tui-group.com
ACCIONA Infraestructuras S.A.
(Spain)
www.acciona.com
APIA XXI S.A. (Spain)
www.apiaxxi.es
ACCIONA Edith Guedella Bustamante ES
ACCIONA Ewa Alicja Zukowska ES
APIA XXI Ignacio Robles ES
APIA XXI Israel Pinto ES
ASM Agnieszka Kowalska PL
ASM Katarzyna Stachurska PL
ASM Michał Jabłoński PL
BSRIA David Churcher UK
BSRIA Ian Wallis UK
BSRIA Peter Tse UK
CARLTD William Fawce UK
CARLTD Ian Ellingham UK
CARLTD Marn Hughes UK
CARLTD Anthony Waterman UK
Designtech Johan Falk SE
Designtech Patrik Svanerudh SE
Designtech Rick Hartwig SE
Fraunhofer IBP Katrin Lenz DE
Fraunhofer IBP Mahias Fischer DE
Holte as Aleksander Bjaaland NO
Holte as Frode Eek NO
Holte as Jørgen Wang Svendsen NO
Holte as Lars Mikalsen NO
Holte as Per Kveim NO
LTU Peter Wallström SE
LTU Thomas Olofsson SE
Norsk Teknologi Svein Harald Larsen NO
Norsk Teknologi Åge Lauritzen NO
PEI Alexander Forell DE
PEI Johannes Kreissig DE
PEI Siegrun Kielberger DE
PEI Viviana Carrillo DE
SINTEF Kari Sørnes NO
SINTEF Kari Thunshelle NO
TBEE Ala Dikbas TR
TUI Dieter Semmelroth DE
TUI Ingo Woltmann DE
USTUTT Hannes Krieg DE
USTUTT Johannes Gantner DE
USTUTT Stefan Albrecht DE
Participants
www.cileccta.com
