A METHODOLOGICAL APPROACH TO SUPPORT BUILDING LIFE CYCLE ANALYSIS - Andy McNamara

National University of Ireland, Cork
School of Engineering
Chair of Information Technology in Architecture, Engineering & Construction
Dissertation submitted as part of
MEngSc
Information Technology in Architecture, Engineering & Construction
Academic Year 2015/2016
September 2016
A METHODOLOGICAL APPROACH TO SUPPORT
BUILDING LIFE CYCLE ANALYSIS - AN EXAMPLE TO
USE REVIT-APIS
Andy McNamara
Supervisor: Professor Karsten Menzel
Mentor: Siyu Deng

page i
Declaration
I hereby declare that this thesis is my own work and effort and that it has not been
submitted anywhere for any award. Where other sources of information have been
used, they have been acknowledged.
Signature______________________________________
Print Name: Andy McNamara
Date: _________________________________________

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Acknowledgements
I would like to thank my Supervisors Prof. Karsten Menzel and Siyu Deng for their
support and helpful comments during the course of this thesis.
I would also like to thank my girlfriend Rachel, my family and friends for their
constant support over the past two years.

University College Cork, School of Engineering, IRUSE
College Road, Cork, Ireland
CE6031 DISSERTATION
Andy McNamara
School of Engineering
IT in AEC
Professor Karsten Menzel
Dr. –Ing. habil. Dipl.-Ing.
phone: 00353 21 420 5400
fax: 00353 21 420 5450
eMail: K.Menzel@ucc.ie
Cork, 1 June 2016
Particulars of your Dissertation
The Dissertation provides students with the opportunity to apply their
theoretical knowledge to solve a complex engineering problem in applying
Information Technology to a problem domain in AEC and FM1
requiring
analytical, design, and experimental effort.
Motivation for your topic:
Application Programming Interfaces (API) for BIM will become increasingly
important in the future. API will enable engineers and other BIM-users to
quickly and efficiently exploit the full benefits of holistically developed BIM.
Therefore, it is important that users are provided with knowledge and skills
how to extract or add information to BIM or how to program the behavior of
BIM components. Publicly available programming languages (e.g.
Dynamo) address these requirements.
Your Dissertation Topic is:
A Methodological Approach to Support Building Life Cycle Analysis
- An Example to Use Revit-APIs -
Mentor: Siyu Deng
Internal Examiner: Prof. Karsten Menzel
The Thesis shall emphasise on the following aspects:
(1) A state-of-the-art analysis of publicly and commercially available
API for BIM;
(2) The development of a structured approach how to exchange
relevant data between LCA-tools and Revit through API.
(3) The implementation of an example for BIM-driven LCA
using available models of UCC’s ERI or CEE-building.
1
AEC: Architecture, Engineering, and Construction | FM Facility Management

About your Dissertation
The Dissertation module CE6031 is worth 30 credits and accumulates a total
of approximately 420h to 450h of work over 12 weeks, i.e. a workload of
approximately 35h per week.
The Dissertation should be well-structured and written in Standard English.
Students are expected to demonstrate high ethical and engineering
standards. In milestone meetings students must present intermediate results
and dispute results with their supervisor.
The work on the Dissertation should be structured into three major parts:
(1) An introductory part developing a problem statement and a related
hypothesis on how to solve the problem. It also should include a short,
focused and critical literature review to contextualize the dissertation`s
topic. An initial software architecture and a complementing experimental
plan to verify the hypothesis through software tests, interview results,
etc. needs to be proposed.
(2) The methodological part usually focuses on the development of a
generic solution to the problem. The methodological solution should be
complemented by the design, implementation or set up of a software
system. Experimental set-ups need to be designed allowing to test the
solution by using the developed software. The experimental design
includes the identification of flexible parameters and fixed boundary
conditions which may influence the experimental results.
(3) The experimental part focuses on the execution of particular
experiments aiming to deliver a ‘prove of concept’ (or leading to a
falsification of the hypothesis). The software system set up in phase 2
should be applied to verify the hypothesis and interpret the experimental
results.
Final Submission:
title format number
Digital version Microsoft Word and pdf
1 of each,
on DVD or USB
Figures in additional MS PowerPoint file
Data in additional MS Excel file, also all related files in other
formats (if any)
Models BIM-models shall be submitted with the dissertation in the
native software format (e.g. ViCo, NavisWorks, Revit, etc.)
Source Code Needs to be provided in digital format and as hardcopy as
part of the appendix of the Dissertation
Software Excel, Visual Basic, REVIT, Dynamo
Hardcopies As per guidelines
with this topic-page included
3 pieces

Major Milestones:
In order to assure a smooth and continuous submission process of the
Dissertation the milestones listed in the table below are defined.
Students are requested:
(1) To submit intermediate results to the supervisor. Material must be
submitted in high quality, appropriate layout and in Standard English.
(2) To attend consultation meetings (CM) as listed in table below.
Usually, CM are face-to-face meetings organized in UCC.
(3) To attend progression meetings (P) as listed in table below.
A logbook needs to be tabled and signed-off by the supervisor.
(4) To update and further develop the material submitted and
discussed with the supervisor. The material must be finally
transferred into an integrated part of the overall Dissertation.
No Expected Achievements Subm. Deadline
1 (1.1) Outline of Thesis Structure (draft version of Table of Content)
(1.2) Plan for Introductory Part
(1.3) Initial software architecture for proposed system
03-June-2016
CM 10-June-2016
2 (2.1) Submission of Introductory Part (version 1)
(2.2) Plan for Methodological Part
(2.3) Proposed Software Architecture and Information Flow Diagram
(2.4) Experimental Plan
(2.5) Sign-off log book part 1
16-June-2016
CM+P 22-June-2016
3 (3.1) Submission of Methodological Part (version 1)
(3.2) Submission of source code and executable software
(or models to be processed)
(3.3) Submission of fully developed experimental design
(3.4) Experimental plan
07-July-2016
CM+P 13-July-2016
4 (4.1) Experimental results 05-August-2016
CM: 11-Aug-2016
5 (5.1) Draft Thesis
26-August-2016
CM+P: 01-Sep-2016
6 (6.1) Submission of final version of Thesis to Program Coordinator
(6.2) Sign-off log book (final part)
(6.2) Forward Thesis to Examiners and Exams Office
05-September-2016
CM+P: 05-Sep-2016
08-September-2016
7 (7.1) Submission deadline for reviews to Program Coordinator 22-September-2016
8 (8.1) Required and recommended corrections included in Thesis 06-October-2016
9 (9.1) Corrections approved and final marks sent to exams Office 13-October-2016
Prof. Karsten Menzel, Dr.-Ing. habil. Dipl.-Ing.
Chair Information Technology in Architecture, Engineering and Construction

page iii
Table of Contents
Declaration....................................................................................................................i
Acknowledgements......................................................................................................ii
Table of Contents....................................................................................................... iii
Table of Figures ..........................................................................................................vi
List of Tables............................................................................................................ viii
List of Abbreviations...................................................................................................ix
Abstract ......................................................................................................................11
1 Introduction ...........................................................................................................12
1.1 Life Cycle Analysis (LCA) .........................................................................12
1.2 Building Information Modelling (BIM)......................................................13
1.2.1 LCA Integrated BIM............................................................................13
1.3 Hypothesis...................................................................................................13
1.4 Overview of Chapters..................................................................................14
2 State of the Art Analysis .......................................................................................15
2.1 Building Information Modelling (BIM)......................................................15
2.1.1 OpenBIM .............................................................................................15
2.1.2 ClosedBIM...........................................................................................16
2.1.3 Dynamo................................................................................................17
2.1.4 Flux.io ..................................................................................................17
2.1.5 LCA Integrated BIM............................................................................17
2.2 Climate Change Legislation ........................................................................18
2.2.1 Kyoto Protocol (1997) .........................................................................18
2.3 Principles of LCA........................................................................................21
2.4 ISO 14040:2006 ..........................................................................................22

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2.4.1 LCA System Boundaries......................................................................23
2.5 ISO 14044:2006 ..........................................................................................24
2.5.1 Phases of LCA .....................................................................................24
2.6 LCA Software & Tools ...............................................................................27
2.6.1 Comparison of Commercial LCA Software and Tools........................28
2.6.2 Comparison of Free LCA Software and Tools ....................................31
2.6.3 Comparison of Free LCI Databases .....................................................32
3 Experimental Plan and Data Flow.........................................................................34
3.1 Dynamo BumbleBee Node..........................................................................34
3.2 Building Elements .......................................................................................34
3.2.1 GaBi Database......................................................................................35
3.2.2 Visually Displaying Results.................................................................35
3.3 Dynamo Script.............................................................................................36
4 Methodological Part ..............................................................................................37
4.1 Research Methodology................................................................................37
4.1.1 Requirements........................................................................................37
5 Execution of Experiment.......................................................................................40
5.1 Dynamo Script.............................................................................................40
5.1.1 Dynamo Script 1: Standard Building Elements ...................................41
5.1.2 Dynamo Script 2 - Underfloor Heating................................................43
5.1.3 Dynamo Script 3 - Sensors...................................................................46
5.1.4 Dynamo Script 4 - Transfer Data to Excel...........................................49
5.2 Microsoft Excel Workbook.........................................................................50
5.2.1 Revit Materials Worksheet...................................................................51

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5.2.2 LCI Materials .......................................................................................52
5.2.3 Results..................................................................................................53
5.2.4 Dashboard ............................................................................................55
5.3 Results .........................................................................................................56
6 Conclusion.............................................................................................................57
6.1 Proof of Concept .........................................................................................57
6.2 Limitations...................................................................................................58
6.3 Future Studies / Development .....................................................................58
7 Bibliography............................................................................................................1

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Table of Figures
Figure 1 System boundary as defined in ISO 14040:2006 ........................................23
Figure 2 An example of a GaBi Life Cycle “Plan”..................................................28
Figure 3 An example of the GaBi software in use...................................................28
Figure 4 An example of the text/menu based input of SimaPro ...............................29
Figure 5 An example of an output from SimaPro.....................................................30
Figure 6 An example of BumbleBee Graph Generation...........................................35
Figure 8 Dynamo Script to extract the required data for standard building elements
....................................................................................................................................41
Figure 9 UML Activity Diagram describing the dataflow while Script 1 is running
....................................................................................................................................42
Figure 10 RevitLCA_StandardBuildingElements Dynamo package.......................43
Figure 11 Dynamo Script to extract the required data for underfloor heating
elements......................................................................................................................44
....................................................................................................................................45
Figure 13 RevitLCA_UnderfloorHeating Dynamo package ....................................46
Figure 14 Dynamo Script to extract combined environmental impacts of all sensors
....................................................................................................................................47
....................................................................................................................................48
Figure 16 RevitLCA_Sensors Dynamo package ......................................................48

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Figure 17 Dynamo Script to transfer the data to the required cells in Microsoft Excel
....................................................................................................................................49
Figure 18 RevitLCA_TransferDataToExcel Dynamo package.................................50
Figure 19 The Revit Materials worksheet for the ERI Building................................51
Figure 20 A note instructing the user to assign an LCI material to a Revit material.52
Figure 21 LCI Material worksheet............................................................................52
Figure 22 The Results worksheet calculating the environmental impacts of each
element.......................................................................................................................54
Figure 23 Dashboard showing the “Top 10 Materials by Enviromental Impacts”....55

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List of Tables
Table 1 Processes included within an LCA system boundary..................................23

page ix
List of Abbreviations
LCA Life Cycle Analysis
LCI Life Cycle Inventory
BIM Building Information Modelling
GWP Global Warming Potential
EU European Union
UCC University College Cork
ERI Energy Research Institute
bSI buildingSMART International
IFC Industry Foundation Class
API Application Programming Interface
SDK Software Development Kit
UNFCCC United Nations Framework Convention on Climate Change
GHG Green House Gases
UN United Nations
COP Conference of the Parties
ISO International Organisation for Standardisation
LCAI Life Cycle Impact Assessment
ELCD European reference Life Cycle Database
NEEDS New Energy Externalities Developments for Sustainability
US LCI United States Life Cycle Inventory Database
NREL National Renewable Energy Laboratory
LCDN Life Cycle Data Network
AP Acidification Potential
EP Eutrophication Potential
GWP Global Warming Potential

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ODP Ozone Depletion Potential
SFP Smog Potential

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Abstract
The construction industry is ever changing, constantly striving to become more productive,
more cost efficient and more environmentally friendly. Two relatively recent outcomes of this
ever changing industry are the introduction of Building Information Modelling (BIM) and
European legislation to limit the environmental impacts of construction; this usually involves
analysing a buildings lifecycle, or a Life Cycle Analysis (LCA).
BIM Ireland’s “National BIM Survey” has recently found that over 75% of Irish construction
companies have noted the demand for Building Information Modelling within the Irish and
UK construction sectors (CITA, 2015). On the other hand, LCAs are being required on more
jobs to ensure compliance with numerous standards. These figures, paired with the demand
for LCAs, have spurred the Author to seamlessly combine LCA into the BIM workflow.
BIM and LCA, despite being very different, require / contain very similar information. A BIM
contains data pertaining to all building elements including volumes, materials, etc. To carry
out a basic LCA, the user requires the volumes of all materials within a building. Once these
volumes have been combined with a Life Cycle Inventory (LCI), the overall environmental
impacts of a building can be calculated.
By integrating the LCA methodology into the BIM workflow the Author intends to allow
designers to quickly and accurately calculate the environmental impacts of a building, even
during the early design stage. If achieved, this will result in reduced re-design work, fast and
accurate benchmarking of a building’s environmental impacts and increased productivity.
This thesis describes a methodology to integrate LCA into the BIM workflow through the use
of visual programming.

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1 Introduction
Buildings account for approximately 40% of the total energy consumption within the
European Union (EU), establishing the construction sector as one the EU’s leading
causes of environmental damage (European Union, 2010). Subsequently, during the past
decade the construction sector has taken action in a bid to reduce global environmental
damage and the production of greenhouse gasses and constantly searches for innovative
and new methods to achieve sustainable construction, as specified by the European
Union Directive on the energy performance of buildings (Directive 2010/31/EC) (Kylili
et al., 2016).
This introduction chapter will briefly describe LCA (Life Cycle Analysis) and BIM
(Building Information Modelling), outline this paper’s hypothesis, give an overview of
the following chapters and briefly describe what is lacking in the current area.
1.1 LIFE CYCLE ANALYSIS (LCA)
LCA is a methodology for evaluating the environmental loads of processes and products
during their whole life-cycle (Sonnemann, Castells and Schuhmacher, 2004). The
analysis includes the entire life-cycle of a product, process, or system encompassing the
extraction and processing of raw materials; manufacturing, transportation and
distribution; use, reuse, maintenance, recycling and final disposal (Consoli, 1993).
When fully analysed, an LCA examines environmental inputs and outputs related to a
product or service life-cycle from cradle to grave, i.e., from raw material extraction,
through manufacture, usage phase, reprocessing where needed, to final disposal.
(Khasreen, Banfill and Menzies, 2009)
LCA should be utilised as part of the design process as a decision making support tool
to be used by designers in parallel with other aspects like thermal analysis and costings.
By achieving a balance between cost, thermal performance and LCA, the Architect /
designer can achieve the optimal performing building.
LCA and its governing standards and protocols are discussed in detail in Chapter 2.

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1.2 BUILDING INFORMATION MODELLING (BIM)
“A BIM is a shared knowledge resource for information about a facility forming a reliable
basis for decisions during its life-cycle; defined as existing from earliest conception to
demolition.” (Nationalbimstandard.org, n.d.
A BIM is defined as a digital representation of the physical and functional characteristics of a
facility.
1.2.1 LCA Integrated BIM
There has been a significant lack of research relating to the combined use of BIM and LCA
(Kylili et al., 2016), as shown in Chapter 2. This thesis aims to bridge this knowledge gap to
provide a platform for further study.
1.3 HYPOTHESIS
As outlined in the previous section, the benefits of integrating BIM and LCA are numerous.
The author intends to prove this by establishing a “live link” between the BIM authoring
software Autodesk Revit (Revit) and a Microsoft Excel (Excel) based spreadsheet. This “live
link” will be utilised to access and leverage the information contained within a semantically
rich BIM by transferring pertinent data to Excel in order to perform calculations and analyse
all building elements. The proposed solution will result in a seamless link between Revit and
the LCA calculations within Excel that will update in real time, allowing the designer to
constantly have an accurate, up to date LCA.
In this thesis the hypothesis “Life cycle analysis can be further utilised and integrated into the
BIM process through the use of flexible API scripting and graphical programming” will be
investigated and demonstrated through the use of an experimental case study. The
Environmental Research Institute (ERI) Building located on the University College Cork
(UCC) campus will be used in the experimental case study to prove the above hypothesis.

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1.4 OVERVIEW OF CHAPTERS
This thesis is split into seven chapters. These chapters and a brief description are outlined
below.
Chapter 1 - Introduction, briefly introduces the reader to the concepts of LCA and BIM.
Following this, the hypothesis is proposed.
Chapter 2 - State of the Art Analysis is an in-depth analysis investigating the legislation and
standards surrounding LCA, phases of the LCA process and a comparison between LCA
tools, software and databases.
Chapter 3 - Experimental Plan and Data Flow, introduces the reader to the proposed data
flow from the BIM authoring tool to final LCA calculations in Excel.
Chapter 4 - Methodological Part discusses in depth the data required to undergo an LCA. It
also describes workings of each dynamo script in depth.
Chapter 5 - Execution of Experiment describes the case study carried out. This chapter also
includes the results.
Chapter 6 – Conclusion summarises the results as well as discussing the proof of concept,
thesis limitations and future studies and development.
Chapter 7 – Bibliography

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2 State of the Art Analysis
This State of the Art Analysis / literature review focusses on the current developments in LCA
as part of the BIM process currently being adopted through the lifecycle of a building. The
aim is to review the current methods for analysing a building lifecycle and integrating these
methods into the BIM process to allow informed and accurate design decisions while in the
design phase.
2.1 BUILDING INFORMATION MODELLING (BIM)
“A BIM is a shared knowledge resource for information about a facility forming a
reliable basis for decisions during its life-cycle; defined as existing from earliest
conception to demolition.” (Nationalbimstandard.org, n.d.)
In the AEC sector, BIM has emerged as the leading development in IT and collaboration
throughout the past decade (Azhar, 2011). BIM represents both a process and a model, i.e.
Building Information Modelling and Building Information Model. The model is an accurate
virtual representation of a building constructed digitally during the process containing key
information that can be utilized for various purposes throughout a project life cycle including
visualization, drawings, cost estimating, simulation, and facility management (Lee, 2016).
Although there is still room for further improvement, the benefits of BIM are clear and the
potential is grand (Demian & 8 Walters, 2013).
The US National BIM Standard describe a BIM as a digital representation of the physical and
functional characteristics of a facility.
2.1.1 OpenBIM
OpenBIM is an initiative established by the buildingSMART International (bSI) and several
leading software vendors using the open buildingSMART methodology. OpenBIM is a
universal approach to the collaborative design, realisation and operation of buildings based on
open standards and workflows.
By supporting a transparent, open workflow through the use of IFC files, OpenBIM allows all
project members to participate regardless of the software tools they use. It creates a common

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language for widely referenced processes, allowing industry and government to procure
projects in transparent commercial engagement, comparable service evaluation and assured
data quality. OpenBIM provides enduring project data for use throughout the asset life-cycle,
avoiding multiple input of the same data and consequential errors while enabling small and
large (platform) software vendors to participate and compete on system independent, ‘best of
breed’ solutions. OpenBIM energises the on-line product supply side with more exact user
demand searches and delivers the product data directly into the BIM. (Think BIM Blog,
2014).
OpenBIM authoring tools include Graphisoft ArchiCAD and Bentley AECOsim Building
Designer. Model checkers that are generally used as part of the OpenBIM workflow includes
Solibri Model Checker and Tekla BIMsight.
2.1.2 ClosedBIM
Unlike OpenBIM, closed BIM systems comprise almost solely of proprietary data and file
formats, internally focussed and exchangeable only within a limited environment using
specific software (Evolve-consultancy.com, 2015). Benefits of a proprietary, ClosedBIM
system include increased interaction between file formats and easier, faster workflows
throughout different software such as BIM authoring, visualisation, model checking.
The Autodesk ecosystem of BIM software is currently the most common BIM package used
throughout the UK (NBS, 2016). The Autodesk package includes Autodesk Revit – BIM
authoring tool, Navisworks – BIM checking tool, Robot – structural analysis, 3DS Max –
visualisation tool and AutoCAD – drafting tool. While it is possible to transfer a model from
one package to another with minimal data loss, transferring a model to tools and software
outside the Autodesk platform, can result in data loss and loss of modelling clarity. This
causes problems when collaborating on large scale projects where numerous stakeholders use
different BIM authoring tools and require the federation of models to undergo analyses such
as clash detection.
The Author has chosen to utilise Autodesk Revit as the BIM authoring tool used throughout
this thesis. This is due to its easily accessible API and the high market share within Ireland
and the UK.

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2.1.3 Dynamo
Dynamo is a free, open source software that allows the user to access the API of
numerous software packages including Revit and Autodesk Navisworks through
graphical programming (Sgambelluri, 2015). It has been “heavily influenced by a
number of visual programming interfaces that have come before”, namely the graphical
programming tool for Rhino; Grasshopper. (Kensek, 2014, p. 3). “At its core, Dynamo
is built to be deployed to any application, and to create new opportunities for cross-
platform and cross-discipline collaboration” (Fralick, n.d.). Primarily, Dynamo
accomplish two tasks: it “creates its own geometry with parametric relationships” and it
“reads and writes to and from external databases” (Sgambelluri, 2015). This transition
into graphically driven parametric design introduces the possibility of bulk manipulation
of components as well as quick modification of model entities allowing combatant users
to increase both accuracy and workflow (Vogt, 2016).
The open source nature of Dynamo means it is not possible to licence or sell individual
scripts. This has caused controversy within the Dynamo community relating to
developers protecting their intellectual property rights to scripts.
2.1.4 Flux.io
Flux.io or Flux, is a cloud based service developed in the Google xLabs in 2012. Flux
combines a Java-based Software Development Kit (SDK) with graphical programming
to allow the user to develop their own applications for software such as Revit, Google
Sketchup, Excel and Grasshopper, similar to Dynamo. However, Flux allows the creator
to protect their intellectual property rights by allowing the user to package and distribute
their scripts without revealing source code. The Author has chosen not to continue this
thesis using Flux due to limitations in his knowledge of the Java programming
language.
2.1.5 LCA Integrated BIM
Kylili et al., (2016) outlines a significant lack of research relating directly to the integration of
BIM with the LCA methodology to investigate the environmental performance of a building
element or of a whole building at an early design stage or throughout the retrofit design stage.

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A basic premise of BIM is collaboration by different stakeholders at different phases of the
life cycle of a facility to insert, extract, update or modify information in the BIM to support
and inform design decisions. A BIMs ability to allow users to update and manipulate
information means its integration with LCA could dramatically increase productivity,
accuracy of LCAs and lead to a greater number of LCA based building performance and
design decisions.
Kulahcioglu, Dang and Candemir (2012) created a prototype software that allows the
interactive analysis of a 3D building model with its environmental impacts. This java-based
software named “3D analyser for BIM-enabled Life Cycle Assessment” has never been
released to the public, however, it is currently still in the research and development phase.
2.2 CLIMATE CHANGE LEGISLATION
A number of LCA and environmental related legislations and protocols are researched and
discussed in this section.
2.2.1 Kyoto Protocol (1997)
The Kyoto Protocol was adopted in Kyoto, Japan in December 1997 and came into force on
16th
February 2005. The Kyoto Protocol became the first international agreement in which
many of the world's industrial nations concluded a verifiable agreement to reduce their
emissions of greenhouse gases in order to prevent global warming. The major feature of the
Kyoto Protocol was the setting out of binding targets for 37 industrialised countries and the
European Community for reducing emissions. These amount to an average of five per cent
against 1990 levels over the five-year period 2008-2012. In total, 184 Parties of the
Convention have ratified its Protocol to date (Epa.ie, n.d.).
The Protocol has strong links to the United Nations Framework Convention on Climate
Change (UNFCCC), however, they differ in the fact that the UNFCCC encourages
industrialised countries to stabilise greenhouse gas emissions, while the Kyoto Protocol is
legally binding, ensuring industrialised countries commit to do so. The Protocol recognises
that developed countries are principally responsible for the current high levels of emissions
and as a result, places a greater burden and increased targets on developed nations under the

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principle of “common but differentiated responsibilities”. (Epa.ie, n.d.).The protocol
signatories are divided into three groups:
1. Industrialised countries that agree to reduce their GHG (Green house gasses)
emissions to targets that are mainly set below their 1990 levels;
2. Developed countries that pay for cost of developing countries;
3. Developing countries that are not expected to de-carbonize their economy unless
developed countries supply financial and technological assistance.
The Protocol’s first commitment period started in 2008 and ended in 2012. The second
commitment period began on 1 January 2013 and will end in 2020.
2.2.1.1 Climate Change in Ireland
Under the Kyoto Protocol, Ireland is required to limit total national greenhouse gas emissions
to 314.2 Mtonnes of CO2eq over the five year period 2008 – 2012 which is equivalent to 62.8
Mtonnes of CO2eq per annum. The Kyoto Protocol limit is calculated as 13% above Ireland’s
1990 baseline value which was established and fixed at 55.61 Mtonnes of CO2
eq following
an in-depth review of Ireland’s 2006 greenhouse gas inventory submission to the UNFCCC
(Ireland’s Greenhouse Gas Emission Projections, 2013).
Prior to the Paris Accord, on March 6th
, 2015, the EU and all its member states agreed to
achieve a reduction of at least 40% compared to 1990 levels in greenhouse gas emissions by
2030. The scope of these greenhouse gasses are:
 Carbon Dioxide (CO2)
 Methane (CH4)
 Nitrous Oxide (N2O)
 Hydrofluorocarbons (HFCs)
 Perfluorocarbons (PFCs)
 Sulphur hexafluoride (SF6)
 Nitrogen trifluoride (NF3)
(Latvian Presidency of the Council of the European Union, 2015)

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2.2.1.2 Copenhagen Accord (2009)
The 15th session of the Conference of the Parties (COP) to the UNFCCC and the fifth session
of the Conference of the Parties serving as the Meeting of the Parties to the Kyoto Protocol
took place in Copenhagen and was hosted by the Government of Denmark in Copenhagen in
December 2009.
The Copenhagen Climate Change Conference raised climate change policy to the highest
political level. Almost 115 world leaders attended the event, making it one of the largest
gatherings of world leaders ever outside UN headquarters in New York. More than 40,000
people representing governments, nongovernmental organisations, intergovernmental
organisations, faith-based organisations, media and UN agencies applied for accreditation.
The Copenhagen Accord contained several key elements on which there was strong
convergence of the views of governments. This included the long-term goal of limiting the
maximum global average temperature increase to no more than 2 degrees Celsius above pre-
industrial levels, subject to a review in 2015. There was, however, no agreement on how to do
this in practical terms. It also included a reference to consider limiting the temperature
increase to below 1.5 degrees - a key demand made by vulnerable developing countries. Other
central outcomes included:
 Developed countries promise to fund actions to reduce greenhouse gas emissions and
to adapt to the inevitable effects of climate change in developing countries. Developed
countries promised to provide US$30 billion for the period 2010-2012, and to
mobilise long-term finance of a further US$100 billion a year by 2020 from a variety
of sources.
 Agreement on the measurement, reporting and verification of developing country
actions, including a reference to "international consultation and analysis", which had
yet to be defined.
 The establishment of four new bodies: a mechanism on REDD-plus, a High-Level
Panel under the Conference of the Parties (COP) to study implementation of financial
provisions, the Copenhagen Green Climate Fund, and a Technology Mechanism.
(UNFCCC.int, 2009)

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2.2.1.3 Paris Accord (2015)
The 21st session of the COP and the 11th session of the Conference of the Parties serving as
the meeting of the Parties to the Kyoto Protocol (CMP) took place from 30th November to
11th December 2015, in Paris, France. Following the Paris Accord, 195 countries adopted the
first-ever universal, legally binding global climate deal. The agreement sets out a global
action plan to put the world on track to avoid dangerous climate change by limiting global
warming to well below 2°C. The agreement is due to enter into force in 2020. The Paris
Agreement acts as “a bridge between today's policies and climate-neutrality before the end of
the century”, (Europa.eu, 2015).
Following the Paris Agreement, Governments agreed:
 To a long-term goal of keeping the increase in global average temperature to well
below 2°C above pre-industrial levels,
 To aim to limit the increase to 1.5°C, since this would significantly reduce risks and
the impacts of climate change,
 On the need for global emissions to peak as soon as possible, recognising that this will
take longer for developing countries,
 To undertake rapid reductions thereafter in accordance with the best available science.
(Europa.eu, 2015)
2.3 PRINCIPLES OF LCA
An LCA is defined as “Compilation and evaluation of the inputs, outputs and the potential
environmental impacts of a product system throughout its life cycle” (ISO 14040, 2006).
An LCA offers guidance for product, process, or constructed element selection and analyses
the entire life cycle environmental burden between stages and processes relative to a
functional unit. “A functional unit is a quantified amount of function obtained from the
product or process”, (ISO 14044, 2006). For example, the functional unit of a light bulb may
be 1,000,000 lumen-hours of light, or the functional unit of a dormitory building might be to
house 200 students for one year. Some consider correct determination of functional unit the
highest priority in LCA, (Klopffer, W. and Grahl, B., 2014). The functional unit must be

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“clearly defined and measurable”, (ISO 14044, 2006). It is extremely important in
comparative studies to ensure fair comparison.
The LCA framework only intended to address environmental considerations and issues.
Economic, social, and other aspects could be considered using other tools and methodologies.
2.4 ISO 14040:2006
ISO 14040 was first developed by the International Organisation for Standardisation in 1996.
The 2nd (and most current) edition was published in 2006 and outlines the principles of LCA,
its framework and “details the requirement for conducting an LCA” (ISO 14040, 2006) and
Life Cycle Inventory (LCI).
Essentially, ISO 14040 acts as a guiding document for basic LCA procedures. These
procedures are further detailed in:
 ISO14044 – Requirements and guidelines,
 ISO/TR 14047 – Illustrative examples on how to apply ISO 14044 to impact
assessment situations,
 ISO/TS14071 – Critical review process and reviewer competencies: Additional
requirements and guidelines to ISO 14044:2006 ISO,
 TS14048 – Data documentation format.
ISO 14040:2006 contains general information on:
 Goal and scope of LCA,
 Life Cycle Inventory (LCI) phase (discussed in 2.5.1.2),
 Life Cycle Impact Assessment (LCIA) phase (discussed in 2.5.1.3),
 Interpretation phase,
 Reporting and critical review,
 Limitations,
 Relationship between phases,
 Conditions for use of value choices and optional elements.

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2.4.1 LCA System Boundaries
An LCA system boundary is the list of the processes to be included as part of the entire
life cycle system and is defined as a: “Collection of unit processes with elementary and
product flows, performing one or more defined functions, and which models the life
cycle of a product”, (ISO 14040, 2006).
Figure 1 System boundary as defined in ISO 14040:2006
The below table outlines the processes typically included within an LCA system boundary.
Included Excluded
Raw material supply Transport to building site
Transport to manufacturer Packaging
Manufacturing Disposal of packing material
EoL (End of Life) transport Building operational energy use
EoL (End of Life) processing and emissions Building operational water use
Disposal (except packing material) Demolition
Recycling potential (metals)
Construction and maintenance of capital
equipment
Direct emissions during use and installation
phase from products that are wet-applied or
use blowing agents
Maintenance and / or operation of support
equipment
Carbon sequestration during plant growth Human labour and employee commute
(Quartz, 2016)
Table 1 Processes included within an LCA system boundary

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2.5 ISO 14044:2006
The first and only edition of ISO 14044 was published in 2006 by the International
Organisation for Standardisation and sets out the LCA requirements and guidelines. Similar to
ISO 14040, ISO 14044 outlines an introduction to LCA, terminology definitions, phases and
an overview of the process. It differs by describing in more detail the required process for
completing an LCA.
ISO 14044 replaces a host of previous ISO LCA standards including:
 ISO 14041:1998 - Goal and scope definition and inventory analysis
 ISO 14042:2000 - Life cycle impact assessment
 ISO 14043:2000 - Life cycle interpretation
2.5.1 Phases of LCA
ISO 14044 outlines four distinct and linked components of LCA
 Goal and scope of LCA
 Life Cycle Inventory
 Life Cycle Impact Assessment
 Interoperation
These components are described below:
2.5.1.1 Goal and scope
Goal statement is the first component of an LCA and guides much of the subsequent analysis.
A goal must state the intended use of the product / building element, the reasons for study, the
study audience and comment on whether the study will be comparative and disclosed to
public. All scope elements must be developed to be consistent with the stated goal of the
LCA. Scope elements include but are not limited to:
A functional unit defines the functional characteristics of the product system. It can be
defined as a “Quantified performance of a product system for use as a reference unit” (ISO
14044, 2006). For example, a light bulb functional unit might be 1,000,000 lumen-hours of

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light, while the functional unit of a dormitory building might be to house 200 students for one
year.
A system boundary defines the processes that are included in the study. ISO 14040:2006
describes a system boundary as a “Set of criteria specifying which unit processes are part of a
product system”. A system boundary is typically further explained through a process flow
diagram.
An LCAI Methodology outlines which impact categories and category indicators are to be
used in the LCA. It also states which impact characterisation methodology is used.
Inventory data is obtained either from direct measurement of processes or from secondary
sources (or a mix of the two). It generally includes inputs and outputs to air, water, and soil.
Data quality includes addresses, age, geographic coverage, technology coverage, precision,
completeness, representativeness, consistency, reproducibility, sources, minimum length of
time to collect, and uncertainty. For missing data a zero value, non-zero value, or a calculated
value from similar technology should be used and explained.
A Comparison between systems should be undertaken before the LCA begins. All systems
should use the same functional unit, system boundaries, data quality, allocation, and impact
assessment procedures (if not possible, identify differences). Publicly disclosed studies must
include a critical review following the LCIA phase.
All LCAs must state whether or not a critical review will be conducted. It should define how,
and by whom, the critical review will be carried out (Haselbach and Langfitt, 2015).
2.5.1.2 Life Cycle Inventory (LCI)
During the LCI phase each unit process and reference source (time taken, quality, etc.) are
collected and clearly defined to prevent an overlap in the data collection (Haselbach and
Langfitt, 2015).

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The LCA data collection procedure is outlined below:
1. Consider goal and scope
2. Prepare for data collection
3. Collect data
4. Validate data
5. Relate data to unit process and allocations (reuse, etc.)
6. Relate data to functional unit
7. Aggregate data
8. Refine system boundary
9. Revise, repeat as needed
If using an external database such as GaBi or Ecoinvent steps 3, 4 & 5 can be skipped as they
are usually done during the data collection phase of the database.
2.5.1.3 Life Cycle Impact Assessment (LCAI)
During the LCIA phase, data is converted into potential environmental impacts. The LCIA
determines if the quality of data is sufficient to conduct the LCA .It also analyses and
determines the system boundaries and cut-offs (magnitude of input or output flow that is
small enough to be negligible) appropriate to calculate indicator results.
2.5.1.4 Interpretation
The interpretation phase takes the form of conclusions and recommendations. During this
phase it is important to identify significant issues with: inventory data, impact categories and
significant contributions from life cycle stages. Information must be included and related to
assembled findings from LCI and LCIA, methodologies used, value choices, limitations and
roles of interested parties in compilation and review.
A critical review process must be implemented before each LCA is completed. This process is
“intended to ensure consistency between a life cycle assessment and the principles and
requirements of the international Standards on life cycle assessment”(ISO 14040, 2006). The
critical review should be done by an independent party.

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2.6 LCA SOFTWARE & TOOLS
There is a large range of LCA software and tools available to aid the user in handling
the complex data and calculations required to undergo an LCA. These software and
tools can:
 Reduce time needed for assessments
 Prevent errors
 Assisted conversion of data to functional unit basis
 Increase capabilities (e.g. Monte Carlo simulations, sensitivity analyses)
 Organise systems and data
 Automate creation of graphs and tables
 Provide process and flow information through databases only available in the software
package
However, despite their obvious advantages some software packages / databases can be
extremely expensive and may require a steep learning curve to use effectively.
This following chapter; State of the Art Analysis will investigate a number of the most
commonly used free and commercial LCA software tools and databases. These tools include:
 GaBi (Commercial)
 SimaPro (Commercial)
 Quantis Suite (Commercial)
 Umberto (Commercial)
 openLCA (Free)
 Building for Environmental and Economic Sustainability (BEES) (Free)
 Athena IE (Free)

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2.6.1 Comparison of Commercial LCA Software and Tools
2.6.1.1 GaBi
GaBi is short for Ganzheitliche Bilanz, meaning “holistic balance” in German. It is a
commercial software produced by PE International, that has extensive database options
including their own database and integration with external databases, such as ecoinvent, US
LCI, etc. In addition to using the GaBi software to calculate LCA you can commission their
data team to collect data if needed. The below figures depict basic functions of the GaBi
software
Figure 2 An example of a GaBi Life Cycle “Plan”
Figure 3 An example of the GaBi software in use

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Within GaBi, users draw the life cycle “plan” as a flowchart. The software then calculates the
impacts using its inbuilt algorithms. GaBi is sold as a single, non-floating license. The I-report
feature is used to produce high quality reports.
2.6.1.2 SimaPro
SimaPro is produced by PRé Consultants and integrates with a number of databases such as
US LCI, ELCD, ecoinvent, and LCA food databases.
SimaPro differs to GaBi by taking a text / menu based approach to modelling, rather than the
graphical approach found in GaBi. The SimaPro software is server based, meaning it
conveniently allows multiple users in remote locations to work simultaneously. Globally,
SimaPro is more widely used than GaBi allowing for increased collaboration and significantly
more tutorial type information.
The below figures show some of the basic functions available in SimaPro.
Figure 4 An example of the text/menu based input of SimaPro

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Figure 5 An example of an output from SimaPro
2.6.1.3 Quantis Suite
Quantis Suite is a web-based application that integrates with the Ecoinvent 2.2 database. The
simple nature of the software allows modelling by phase, drag and drop inputs and manually
chosen quantities. Quantis Suite has partnered with SimaPro on some tools to expand
distribution reach and resources. Three different pieces of software make up the Quantis
Suite:
 Quantis Suite Product – LCAs according to ISO 14040 and carbon footprint
 Quantis Suite Corporate–Carbon footprint focused, other environmental aspect tools
 Quantis Impulsio–Ecodesign software
2.6.1.4 Umberto
Umberto is produced by IFU Hamburg and features graphically orientated modelling using
Sankey diagrams. The Ecoinvent 3 database is integrated into the Umberto software, however,
the user can also purchase an add-on to integrate the GaBi database. Umberto interfaces with
Microsoft Excel and other Microsoft Office programs. Similarly to Quantis Suite, there are
multiple versions depending on the user’s needs:
 NXT Efficiency: Costs, materials, and energy
 NXT LCA: Life cycle assessment
 NXT CO2: Carbon footprint only
 NXT Universal: Combines environmental with cost and efficiency.

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2.6.1.5 Conclusion of Commercial LCA Software
Upon reviewing the above LCA software and tools it is clear they all have similar features.
There are a few differences apart from specific extra features such as the ability to generate
reports within the software, be used remotely, export to other programs, and have add-ons for
specific goals. The main difference between each software is the user interfaces.
Ultimately each piece of software accomplishes the main functionality of simplifying the
process of a life cycle analysis, but differs slightly in specialised capabilities and style of use.
2.6.2 Comparison of Free LCA Software and Tools
In this section a number of freely available LCA software and tools will be explained and
compared.
2.6.2.1 openLCA
openLCA is produced by GreenDelta and runs on an open source platform. It includes
advanced features like parameterisation, Monte Carlo simulation, Sankey diagrams, etc.
openLCA does not come pre-installed with an LCI. This means the user must manually
enter data, access free databases such as ELDC, NEEDS and US LCI, or access
commercial databases such as Ecoinvent and GaBi.
2.6.2.2 Building for Environmental and Economic Sustainability (BEES)
BEES is an online-based tool produced by NIST used for environmental and economic
analysis of building products. BEES comes pre-installed with an LCI containing nearly 200
commonly used products. Most of the data and processes are set, however, the user must
choose weighting scheme, products of interest and transport distance. This means the software
is simple to use but lacks the functionality of modelling parameters, sensitivity analyses, and
manual changing of inputs/outputs that commercial software incorporate.
2.6.2.3 Athena Impact Estimator (IE)
Athena IE for Buildings is a free LCA tool aimed at the North American market. Athena IE
can accurately model 95% of North American building stock. The tool is region specific and

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uses dialog boxes to ask for specific building parameters. Athena IE was developed
specifically for use by Architects, engineers and sustainable design consultants.
2.6.2.4 Conclusion of Free LCA Software and Tools
The above freely available LCA software and tools perform adequately and aid the user
in undertaking an LCA. However, it should be noted that the freely available software
packages do not appear to give the user as much freedom and options as the commercial
software packages, some of which lack the functionality of modelling parameters,
sensitivity analyses and manual changing of inputs/outputs.
2.6.3 Comparison of Free LCI Databases
2.6.3.1 US LCI
The US LCI was produced by the National Renewable Energy Laboratory (NREL)
starting in 2001. The database was intended to provide a free, consistent, US-focused set
of data. The UC LCI was created in conjunction with numerous industrial / government
bodies including Athena Institute, US car manufacturers Ford, General Motors and
DaimlerChrysler, the US Department of Energy, the US Department of Agriculture and
the US Environmental Protection Agency (EPA).
The US LCI can be merged into most common LCA software including SimaPro, GaBi,
OpenLCA, and others. It can also be accessed and used directly from the NREL
website. Most data includes sources, but not embedded information on modelling
procedures. It should be noted that: “Although most of the data in the US LCI database
has undergone some sort of review, the database as a whole has not yet undergone a
formal validation process” (Nexus.openlca.org, 2015).
2.6.3.2 European reference Life Cycle Database (ELCD)
The European reference Life Cycle Database (ELCD) was first released in 2006 and provides
LCI data from front-running EU-level business associations and other sources for key

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materials, energy carriers, transport, and waste management. The aim of the ELCD is to freely
provide background data that is required in a high percentage of LCAs in a European market
context. Coherence and quality are facilitated through compliance with the entry-level
requirements of the Life Cycle Data Network (LCDN), as well as through endorsement by the
organisations that provide the data. Currently, the most up to date dataset is ELCD 3.2.
(European Life Cycle Database - EPLCA, 2014)
2.6.3.3 Conclusion of Free LCA Databases
Upon investigating and using the above LCA databases it became apparent that the freely
available databases lack the detail and size of the commercially available databases such as
GaBi and Ecoinvent. Both the US LCI and ELCD can be imported into the commercially and
freely available software mentioned above.
Ultimately, these freely accessible databases do not contain enough common construction
materials compared to their commercial counterparts.

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3 Experimental Plan and Data Flow
The Author intends to access large amounts of data contained in the Revit model
through the use of the visual programming extension Dynamo. Once the correct data has
been accessed and manipulated, the BumbleBee Dynamo node (explained below) will
be utilised to accurately and seamlessly transfer the data to the appropriate cells in an
Excel workbook. This workbook will contain a multitude of calculations and graphs to
undertake the LCA of building elements and visually display the results.
3.1 DYNAMO BUMBLEBEE NODE
The BumbleBee nodes package was developed by Konrad K. Sobon (Archi-Lab.net).
BumbleBee is an Excel and Dynamo interoperability plugin that vastly improves
Dynamo’s ability to read, write and manipulate Excel files. The Author will take
advantage of this feature to create a seamless link between Revit and Excel. This will
result in a “live link” between the Revit model and the Excel workbook meaning that
any changes to the model will result in instant and automatic updates to the data within
the Excel workbook. The BunmleBee node is explained in chapter 5.1.4.
3.2 BUILDING ELEMENTS
In order to focus the LCA on specific elements from the BIM, the below list has been created
to create boundaries for this Thesis. Only items included in the list will be included in the data
flow to Excel and LCA calculations. Through further research outside the scope of this thesis,
it may be possible to integrate the processes described in this thesis into the OpenBIM
methodology discussed in 2.1.1. To aid this, the Author has combined the below list with their
proposed IFC property sets counterparts.
 Beams (Structural) - IfcBeam
 Ceilings - IfcCovering
 Columns (Architectural) - IfcColumn
 Columns (Structural) - IfcColumn
 Doors - IfcColumn
 Floors (excluding finishes) - IfcSlab

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 Pipes - IfcPipeSegmentType
 Roofs - IfcRoof
 Stairs - IfcStair
 Walls - IfcWall
 Windows - IfcWindow
 Building Sensors - IfcSensorType
 Underfloor Heating System
3.2.1 GaBi Database
The Author has acquired a GaBi Database Educational License. All LCA data (with the
exception of material density) has been taken from the educational database. However,
the GaBi educational database only contains a small number of materials. For this
reason the Author has attempted to match the Revit material to the closest possible GaBi
material. This will result in inaccurate results but will not hinder the proof of concept
during the experimentation phase.
3.2.2 Visually Displaying Results
The Author intends to use BumbleBee’s advanced graphing features to graphically
display the results of the LCA. As the building components or quantities change, these
graphs will change to reflect this in real time.
Figure 6 An example of BumbleBee Graph Generation

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3.3 DYNAMO SCRIPT
The Author has developed a Dynamo script to seamlessly transfer the volumes of each
material within the BIM to Excel for further calculation. By using the “Run Automatically”
feature in Dynamo, the script will run in the background each time the BIM has been
modified. This will allow the volume and material data to update. Assuming there are no null
or error values, the data will be transferred to Excel via the Dynamo BumbleBee node. All
dynamo scripts used are discussed in chapter 5.1.

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4 Methodological Part
4.1 RESEARCH METHODOLOGY
Chapter 2 has demonstrated the vast array of LCA tools, frameworks and guidelines. It is the
author’s intent to simplify this process of LCA while holistically integrating it into current
BIM methodology and workflows. This thesis is primarily focused on the development of a
methodology allowing the automatic LCA of a BIM as it progresses throughout the design
process. The results of this LCA will be displayed both numerically and visually in Microsoft
Excel.
4.1.1 Requirements
In order to develop a complete LCA of a building or building element a number of pieces of
data are required. It is also important to measure each element using the appropriate units.
These are as follows:
 Material Volume: This is the overall volume of each specific material associated with
a building element measured in cubic metres (m³) to four decimal places. To ease the
data transfer, the “ m³” unit will be added in Excel. Example: Floor-
 Concrete: 2.746m³
 Insulation: 1.593m³
 Screed: 0.6632m³
 Timber Floor Finish: 0.1332m³
In some instances such, as windows and doors, it may be beneficial to calculate the building
element by area (squared meters). For this to work, the user would have to either create or
leverage an already existing database containing average LCA values of numerous windows
and doors of different build ups. This database would contain different variations of windows
and doors comprising of different glazing options with different framing options.
 Revit Material: This is the name used in Revit to describe the name of a specific
material. This will consist of a text string. Example: Standard concrete block -
Concrete Masonry Unit _Low Density.

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 LCI Material: Each Revit Material (above) must be assigned an LCI Material. Once
an LCI material has been assigned to a Revit Material, the appropriate environmental
factor values will be mapped to that Revit Material. Environmental factors are
described and explained in section 4.1.1.1.
 Material Density: The material density of each LCI Material defines the materials
density relative to its volume (kg/m³).
 Material Mass: The Material Mass displays the material density multiplied by its
mass, using the unit kg. Example: 1m³ of concrete equates to 2406.5303kg. This
conversion is required as all the environmental factors are measured using the unit kg,
however the Material Volumes are measured in m³.
4.1.1.1 Environmental Factors
All building elements will be analysed using a number of environmental factors. These
environmental factors listed within the LCI are outlined below.
4.1.1.1.1 Acidification Potential (AP) - Unit: kg SO2
A measurement of the emissions that cause acidifying effects to the environment. The
acidification potential is a measure of a molecule’s capacity to increase the hydrogen ion (H+)
concentration in the presence of water, thus decreasing the pH value. Potential effects include
fish mortality, forest decline, and the deterioration of building materials. (Bare, 2012) (EPA,
2012).
4.1.1.1.2 Eutrophication Potential (EP) - Unit: kg N
“Eutrophication” covers all potential impacts of excessively high levels of macronutrients, the
most important of which are nitrogen (N) and phosphorus (P). Nutrient enrichment may cause
an undesirable shift in species composition and elevated biomass production in both aquatic
and terrestrial ecosystems. In aquatic ecosystems, increased biomass production may lead to
depressed oxygen levels because of the additional consumption of oxygen in biomass
decomposition. (Bare, 2012) (EPA, 2012).

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4.1.1.1.3 Global Warming Potential (GWP) - Unit: kg CO2
A measure of greenhouse gas emissions, such as CO2 and methane. These emissions are
causing an increase in the absorption of radiation emitted by the earth, increasing the natural
greenhouse effect. This may in turn have adverse impacts on ecosystem health, human health,
and material welfare. (IPCC, 2013)
4.1.1.1.4 Ozone Depletion Potential (ODP) - Unit: kg CFC-11
A measure of air emissions that contribute to the depletion of the stratospheric ozone layer.
Depletion of the ozone leads to higher levels of UVB ultraviolet rays reaching the earth’s
surface with detrimental effects on humans and plant (Bare, 2012) (EPA, 2012).
4.1.1.1.5 Smog Formation Potential (SFP) - Unit: kg O3
A measure of emissions of precursors that contribute to ground level smog formation (mainly
ozone O3), produced by the reaction of VOC and carbon monoxide in the presence of
nitrogen oxides under the influence of UV light. Ground level ozone may be injurious to
human health and ecosystems, and may also damage crops (Bare, 2012) (EPA, 2012).

40
5 Execution of Experiment
This chapter of the thesis deals with the design and implementation of the Dynamo scripts and
LCA calculation in Excel to quickly and accurately calculate the LCA of the ERI building.
The chapter will build upon the methodology chapter and describe the inner workings of the
dynamo script while also describing the process used to assign LCI Materials to Revit
Materials.
The chapter will also describe how each Dynamo script will be compressed into a “user-
friendly” package that allows the user to run the script without any knowledge of Dynamo or
visual programming.
5.1 DYNAMO SCRIPT
This section will describe the workings behind each Dynamo script. For simplicity and to aid
in explanations, the data acquisition section of the scripts will be separated from the data
transfer to Excel section when explaining the scripts.
There are four different Dynamo scripts used in the data transfer from Revit to Excel. These
scripts are described and explained in chapters 5.1.1 to 5.1.4.
Dynamo Script 1: Standard Building Elements deals with gathering the appropriate data
for the below building elements. This script is further described in 5.1.1.
This script will extract the appropriate data for the following building elements:
 Beams (Structural) - IfcBeam
 Ceilings - IfcCovering
 Columns (Architectural) - IfcColumn
 Columns (Structural) - IfcColumn
 Doors - IfcColumn
 Floors (excluding finishes) – IfcSlab
 Roofs - IfcRoof
 Stairs - IfcStair
 Walls - IfcWall

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 Windows – IfcWindow
Dynamo Script 2: Underfloor Heating extracts the total volume of material found within
the underfloor heating pipe system. This script is further described in 5.1.2.
Dynamo Script 3 – Sensors extracts the total environmental impacts associated with all
building sensors within the building. This script is further described in 5.1.3.
Dynamo Script 4 - Transfer Data to Excel handles the transfer of data from Revit and
Dynamo to the appropriate cells in Excel. This script is further described in 5.1.4.
5.1.1 Dynamo Script 1: Standard Building Elements
The below script allows the user to extract building material data and volumes of almost any
building element. The script is described below using a wall as the chosen building element.
Figure 7 Dynamo Script to extract the required data for standard building elements
1. The user must select a building element (wall, roof, floor, beam, etc.). Dynamo will
automatically select every instance of that element present within the Revit file. By
selecting the Wall category, dynamo creates a list of every wall that has been placed
within the model.
2. The wall list is then fed into the Element.Materials node. The Element.Materials node
is part of the Clockwork Dynamo package. It “Retrieves all materials from a given
element” (GitHub, 2015) and outputs the material data into a number of lists. In this
script we will only require the materials and materialVolumes outputs. Materials
outputs a list of each material name as a text string. MaterialVolumes outputs a list
containing the volume of each material as a decimal digit. Note, the unit of

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measurement of the materialVolumes output depends on the Project Units set in Revit.
If the Revit Project Units are set to meters, the materialVolume will be cubic meters.
3. This section of the script filters out and combines duplicates. For example, if more
than one wall type uses the material “Masonry - Concrete Blocks”, it will appear
multiple times in the Element.Materials outputs. To resolve this, the List.GroupByKey
and Math.Sum nodes are utilised to ensure any duplicate material and its volume are
combined to ensure each material only appears once. This is not necessary, however
by removing duplicated elements it will compact the list and allow for easier
manipulation in Excel.
4. The final section of the script uses the List.Create node to create a list combining the
material names with the material volumes. Running this combined list though the
List.Transpose node changes the list layout to allow for easy import into Excel.
The above Dynamo script is described by the below UML Activity Diagram. The UML
Activity Diagram outlines the processes and data flow within Dynamo while the script is
running
.

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After passing the wall category through this script the wall materials and material volumes are
ready to be passed through the “Script 4: Data transfer to Excel”. This script is outlined in
5.1.4.
This script has been compressed down into an easy to use Dynamo Package called
RevitLCA_StandardBuildingElements. Dynamo packages are compressed dynamo scripts
with minimal user interaction options. By doing this, a user with very little Dynamo
experience will be able to use the above script. The only thing the user needs to do in order to
use this package is to add the Revit category (Walls, roof, floor, ceiling, etc.).
Figure 9 RevitLCA_StandardBuildingElements Dynamo package
5.1.2 Dynamo Script 2 - Underfloor Heating
Within Revit, the simplest and most accurate way of modelling an underfloor heating system
is by creating a Pipe System. However, neither Dynamo nor the Revit API can directly access
the material volume of a particular pipe, or a system of pipes. This has been overcome in the
below script and is explained in point 3 below.
To allow this script to function as intended without any modification, the user must name the
pipe system family type being used to model the underfloor heating to:”Underfloor Heating”.
In addition, no other family title type may be named, or contain “Underfloor Heating”. This is
explained in detail in point 2 below. Once this volume has been transferred to Excel using
script 4, the user can assign the appropriate material such as polyethylene (PEX)

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Figure 10 Dynamo Script to extract the required data for underfloor heating elements
1. Unlike script 1, the Revit category type does not need to be flexible by allowing the
user to select building elements. For this script, Pipes is the only category necessary.
The “All Elements of Category” node creates a list containing every pipe placed
within the Revit model. While this will select all the underfloor heating pipes, it will
also select any other pipe.
2. This section of the script filters the entire list of pipes by searching for the family type
for any that contain the title “Underfloor Heating”. The “String.Contains” node creates
a list containing a series of True or False strings (True if the pipe family type contains
the text “Underfloor Heating” and False if the pipe family does not contain this text).
The “List.FilterByBoolMask” separates the list connected from the “All Elements of
Category” node depending on the True/False list connected from the “String.Contains”
node. The result is two lists. The “In” list, contains all Pipe segments that contain the
family type title containing “Underfloor Heating”, i.e., all underfloor heating pipes.
The “Out” list contains all other pipes.
3. To get the total material volume of a length of pipe the user requires the pile length,
outside diameter and inside diameter. To do this, the list of Underfloor Heating pipes
is fed into the “Element.GetParameterValueByName”. Paired with the correct
parameter name, this gives us a number of lists containing all underfloor pipe lengths
and outside and inside diameters. It should be noted that the parameter names are case
sensitive and must be enclosed within inverted commas.
4. This section of the script manipulates the data linked to the length, inside and outside
diameters. To calculate the material volume the script subtracts the inside diameter
from the inside diameter. This gives the sectional area of a segment of pipe. The
“Math.Sum” node is used to combine the length of all Underfloor Heating pipes. The

45
total pipe length is then multiplied by the sectional area to get the total material
volume of the underfloor heating pipes. The final figure is rounded to four decimal
places using the “Math.Round” node. The final figure can then be fed through script 4
to transfer the data to excel.
running.

46
RevitLCA_UnderfloorHeating. This package allows Dynamo to calculate the total pipe
volume without any user input. This package is displayed below.
Figure 12 RevitLCA_UnderfloorHeating Dynamo package
5.1.3 Dynamo Script 3 - Sensors
Unlike the other building elements included in the LCA calculations, building sensors are the
most difficult to calculate. After a large amount of research the Author has concluded that
there is no feasible way to accurately determine the LCA properties of different building
sensors. This is primarily down to companies protecting their intellectual properties and
designs by not sharing exact plans or material quantities. The author’s solution to this is
mandating all sensor producers to undergo in-depth LCAs of all products. This LCA data can
then be embedded within the Revit families of each product. This would allow the user to
accurately determine the combined LCA results of all sensors within a building. The Author
understands that this is an “ideal world” situation and in reality, sensor producers may not
want to divulge such information. Assuming the manufacturer has included the LCA data
within the Revit family, the below script can be used to extract this data and prepare it for
export to Excel. Note, it is assumed that all sensors will be categorised as Electrical
Equipment within Revit.

47
Figure 13 Dynamo Script to extract combined environmental impacts of all sensors
1. Section 1 of this script selects all items categorised as Electrical Equipment that has
been placed within the Revit model and creates a list. This list will contain elements
that are electrical equipment but are not sensors.
2. Each sensor family must contain a parameter called “_LCA Data”. This must be a tick
box (boolean) type parameter. This box will be ticked if the item is a sensor to be
included in the LCA. This section of the script takes the Electrical Equipment list from
above section and filters it using the “_LCA Data” parameter. Similar to script 2, the
“List.FilerByBoolMask” node is used to create two lists. The “In” list contains all
items categorised as Electrical Equipment where the “_LCA Data” tick box has been
ticked. The “Out” list contains all other Electrical Equipment.
3. The “In” list from above is passed through a series of
“Element.GetParameterValueByName” nodes. The parameter name is fed into these
nodes in order to extract the correct data from each family.
4. The LCA extracted from the sensor families must be combined into a list using the
“List.Create” node. This list is then passed though the “List.Transpose” node to
prepare the data for export to Excel using Script 4.
running.

48
RevitLCA_Sensors. This package allows Dynamo to gather the LCA data of each sensor
within the building. Similar to the RevitLCA_UnderfloorHeating package, this package
requires no input from the user to implement.
Figure 15 RevitLCA_Sensors Dynamo package

49
5.1.4 Dynamo Script 4 - Transfer Data to Excel
This script is by far the simplest but arguably the most vital. It allows the user to send data
from Dynamo to Excel seamlessly, and in real time. This means the Excel spread sheet will
always be up to date with the Revit file.
Figure 16 Dynamo Script to transfer the data to the required cells in Microsoft Excel
1. A code block is created to direct the Dynamo data to the appropriate cells and
worksheet within Excel. This information must be within inverted commas and is case
sensitive.
2. The “BB (Bumblebee Data) node” interoperates the Dynamo data while assigning it to
the correct cells on the correct worksheet. The data assigned to this node must only
consist of text strings and/or numbers. The output of this node is fed into the “Write
Excel” node.
3. The “Write Excel” node allows the user to write any data from the “BB Data” node to
Excel. Provided the “Run Automatically” option is enabled in Dynamo, data will be
written / updated anytime a change is made to the model or Dynamo script. By leaving
the “filePath” blank, and providing only one spreadsheet is open, the “Write
Excel”node will target the open worksheet. Alternatively, the user may specify a
specific path for the spreadsheet. The “RunIt” input must be connected to a “Boolean”
node to decide if the transfer to Excel is carried out.

50
RevitLCA_TransferDataToExcel. This package allows Dynamo to write data to the
appropriate cells on the Revit materials worksheet. Similar to the previous packages, this
package does not require any user modification under normal circumstances.
Figure 17 RevitLCA_TransferDataToExcel Dynamo package
5.2 MICROSOFT EXCEL WORKBOOK
The above Dynamo scripts prepare the Revit data for export to Excel, however, without the
accompanying Excel workbook the LCA calculations could not be carried out. This section
describes the Excel workbook used to carry out the quantity and LCA calculations along with
containing the LCI and both numerically and visually displaying the results. The following
four Excel worksheets make up the bulk of this workbook:
1. Revit Materials
2. LCI Materials
3. Results
4. Dashboard
These worksheets will be explained in detail below.
A number of worksheets are used for calculation purposes to allow the dashboard to display
the appropriate data. These calculation worksheets are:
1. Dashboard Data – AP
2. Dashboard Data – EP
3. Dashboard Data – GWP
4. Dashboard Data – ODP
5. Dashboard Data - SP

51
5.2.1 Revit Materials Worksheet
The “Revit Materials” worksheet receives all the material transferred through Dynamo. It
contains three important columns. These columns are listed and described below.
Figure 18 The Revit Materials worksheet for the ERI Building
1. Material Name (From Revit): This column describes the Revit material associated
with each item within the building. This data is taken straight from the Revit material
name, thus accurately assigning materials to Revit and avoiding the Revit default
materials is critical. As described in Chapter 5.1.1, this list of elements will not
contain duplicate materials associated with the same Revit category.
2. Material Volume (m3) (From Revit): This column is similar to the Material Name
(From Revit) as it takes its data straight from the Dynamo script. This column denotes
the volume of each material shown in the Material Name (From Revit) in cubic
meters.
3. LCI Material: The LCI Material column is driven by a list of LCI materials located on
the LCI Materials worksheet. When the user hovers over a cell within the LCI
Material column they are prompted to “Assign LCI Material” (below). The user must
choose a material from the list to associate with the Revit material. Choosing an

52
incorrect material here will result in the wrong LCA data being used for the final
calculations. The user may manually type the name of an LCI material, however, if
they type a material (or misspell), that is not present on the LCI Materials worksheet
they will receive a warning and instruction to assign a correct LCI material.
Figure 19 A note instructing the user to assign an LCI material to a Revit material
5.2.2 LCI Materials
The LCI Materials worksheet contains all the LCI data associated with each LCI material. All
LCA data found on this worksheet has been taken from the GaBi database and is measured
per kg.
Figure 20 LCI Material worksheet
The important columns are listed below:

53
1. Material: This is the name of each LCI material. This list is referenced to the LCI
Material column on the Revit Materials worksheet.
2. Columns B-F: These columns contain the LCA data for each material committed from
the GaBi database. This data includes:
a. Acidification Potential (kg SO3-eq c2g)
b. Eutrophication Potential (kg N-eq c2g)
c. Global Warming Potential (kg CO2-eq c2g)
d. Ozone Depletion Potential (kg CFC11-eq c2g)
e. Smog Potential (kg O3-eq c2g)
3. Density (kg/m3): This column denotes the kilogram per cubic meter of each material.
The GaBi database does not specify a density for most materials, so to overcome this,
density data has taken from different locations online. This is referenced in the Density
Data Reference column. The Author understands that plucking data from numerous
websites is not ideal, however, with the absence of density data on the GaBi database
this was the only other option.
5.2.3 Results
The results worksheet displays the calculation results for each piece of LCA data:
Acidification Potential, Eutrophication Potential, Global Warming Potential, Ozone Depletion
Potential and Smog Potential. This LCA data will vary, depending on what material has been
selected in the LCI Material Selection column. This is done by using a VLOOKUP formula
that links the LCA data to the LCI Material Selection. A number of calculations are carried out
on this worksheet. Each column and its calculations are described below:

54
Figure 21 The Results worksheet calculating the environmental impacts of each element
1. Revit Material: This column is linked directly back to the Material Name (from Revit)
column on the Revit Materials worksheet.
2. LCI Material Selection: Similar to the Revit Material column, this column is directly
linked to the LCI Material column on the Revit Materials worksheet.
3. Volume (m3): This column is linked to the Material Volume (m3) (from Revit)
column on the Revit Materials worksheet.
4. Mass (kg): The Mass (kg) column is calculated using the following formula: Volume x
Density. This gives the total mass of the object in kilograms. This mass can be used to
calculate the LCA data of each element.
5. Density (kg/m3): This column is linked directly to the Density column on the LCI
Materials worksheet.
6. Columns F-J: The data in these columns is linked to columns A-F on the LCI
Materials worksheet. A VLOOKUP formula ensures that the appropriate and correct
data is displayed for each LCI Material. The LCA data is then calculated by
multiplying the LCA data value on the LCI Materials worksheet by the mass. For
example, the Acidification Potential of a Concrete Masonry Unit; 0.00133 (from the

55
LCI Materials worksheet) x Mass (20886.2) = 27.77865kg SO2. The same process is
used to calculate the total values of each of the five Life Cycle Impacts.
7. Row 2, Totals: The Totals row shows the total amount of each Life Cycle Impact. This
is the total throughout the entire building and is the final point in the calculations.
5.2.4 Dashboard
Figure 22 Dashboard showing the “Top 10 Materials by Enviromental Impacts”.
The dashboard will visually display the results of the ten highest materials contributing to
each of the environmental factors outlined in 4.1.1.1. A pie chart will be shown for each Life
Cycle Impact showing how “top ten”erials contribute to total impacts. This will not only give
the designer a quick overview of the impacts but also quickly show what materials have
negative effects compared to those materials that have minimal impacts on the total LCA of
the building.

56
5.3 RESULTS
The achieved results are outlined below:
Environmental Impacts Result
Acidification Potential (kg SO2-eq c2g) 5536.20182
Eutrophication Potential (kg N-eq c2g) 384.728176
Global Warming Potential (kg CO2-eq c2g) 1492901.85
Ozone Depletion Potential (kg CFC11-eq c2g) 8.001749769
Smog Potential (kg O3-eq c2g 31334966.05
Table 2 Results showing the Environmental Impacts of the ERI building
While the results may contain slight inconsistencies due to the lack of materials included
within the GaBi (see chapter 6.2). On a positive note, the data transfer between Dynamo and
Excel went as planed with no errors or inconsistencies. This proves the concepts, methods and
data flows outlined in the above chapters work as intended, however, it also highlights the
importance of a well-structured (Naming conventions, BS1192, BS8541-1, Uniclass
classification, etc) and semantically rich BIM, rather than a “pretty” 3D model.

57
6 Conclusion
This thesis set out to identify and verify the hypothesis “Life cycle analysis can be further
utilised and integrated into the BIM process through the use of flexible API scripting and
graphical programming” through the use of a case study, while using available data. The
UCC ERI building was chosen for this case study.
Using the graphical programming tool, Dynamo, combined with the commercial BIM
software, Autodesk Revit and Microsoft Excel the Author has successfully demonstrated the
implementation of LCA into the BIM design workflow. By allowing the quick and accurate
LCA throughout the early design phase the designer can easily study alternative design
options, implement changes and improve performance and sustainability.
6.1 PROOF OF CONCEPT
The Authors original intention was to carry out an LCA on a BIM of the ERI building
supplied by UCC. However, the provided model contained inconsistent data and lacked much
of the material information required to undergo the analysis. To combat this, the Author added
data to prove the concept of the data flow. For this reason, the LCA results of the ERI
Building may not be accurate, however if the correct information was modelled within the
BIM the LCA would have been accurate. Despite these small inaccuracies within the final
LCA results, the data flows required to undergo the LCA have been achieved and the proof of
concept proven to be true. By proving this proof of concept and integrating LCA into the BIM
process through the use of graphical programming the author has proven this papers
hypothesis to be true.

58
6.2 LIMITATIONS
A number of limitations were found during the undertaking of this thesis. These limitations
are described below.
Software: The described workflow has only been tested on the following software packages:
 Autodesk Revit 2016
 Dynamo 1.0.0
 Microsoft Excel 2010
In theory, this workflow should run on any up-to-date versions of the above software,
however, this has not been tested.
Integrity of the BIM: Without a semantically rich, well modelled and detailed BIM this
process will lead to inaccurate results. The results can only ever be as accurate as the data
inputted in the BIM.
GaBi Educational Database: The GaBi Educational Database contains only a small dataset
spread-out over a large range of industries. Due to this it was difficult to get the LCI data for
some building elements. To combat this, the author has used the data of the nearest material
possible. While this will cause some slight inaccuracies, it will not hinder the proof of concept
that this thesis has set out to prove.
6.3 FUTURE STUDIES / DEVELOPMENT
This Thesis has potential to act as a foundation for further studies in the future through the
further development of the BIM to LCA methodology outlined in the chapters above. The
same workflow could be replicated through the use of Revit API scripting to create native
Revit plugins. This would alleviate the need for Dynamo and would drastically increase the
potential to monetise the idea.
Flux.io (outlined in 2.1.4) would also serve as a platform to replicate the workflow outlined in
this thesis. By utilising Flux and its Java based SDK, the ability to calculate large numbers of
algorithms increases exponentially, while the ability to create a visual “project dashboard” is
added. Through further development, these factors could lead to BIM to LCA calculations and

59
visualisations without the use of Dynamo or Excel. Ideally, this would result in the user
editing a Revit model, once changes have been made the data presented on the Flux based
dashboard updates seamlessly and automatically. Similar to the Revit API approach, this
would allow the developer to monetise the final product.

7 Bibliography
Bare, J. (2012). Tool for the Reduction and Assessment of Chemical and other
Environmental Impacts (TRACI) - Software Name and Version Number: TRACI
version 2.1 - User’s Manual.. Washington.
CITA, (2015). BIM Ireland - National BIM Survey. Construction IT Alliance.
Consoli, F. (1993). Guide Lines for Life-Cycle Assessment: A ‘Code of Practice’.
Pensacola, FL: Society of Environmental Toxicology and Chemistry, (SETAC).
Epa.ie. (n.d.). The Kyoto Protocol :: Environmental Protection Agency, Ireland.
[online] Available at: http://www.epa.ie/climate/thekyotoprotocol/ [Accessed 23
Jun. 2016].
Europa.eu. (2015). Paris Agreement - European Commission. [online] Available at:
http://ec.europa.eu/clima/policies/international/negotiations/paris/index_en.htm
[Accessed 1 Jul. 2016].
European Life Cycle Database - EPLCA. (2014). ELCD 3.2. [online] Available at:
http://eplca.jrc.ec.europa.eu/?page_id=126 [Accessed 22 Aug. 2016].
European Union, (2010). DIRECTIVE 2010/31/EU OF THE EUROPEAN
PARLIAMENT AND OF THE COUNCIL of 19 May 2010 on the energy
performance of buildings. Official Journal of the European Union.
Evolve-consultancy.com. (2015). UK BIM - HOW FAR HAVE WE COME?
(UPDATED) | Evolve-Consultancy. [online] Available at: http://www.evolve-
consultancy.com/resource/bim-brief/uk-bim-how-far-have-we-come [Accessed 9
Sep. 2016].
Fralick, F. (n.d.). Presentations: Computation | BIMForum. [online] Bimforum.org.
Available at: https://bimforum.org/presentations-computation/ [Accessed 22
Jun. 2016].
GitHub. (2015). ClockworkForDynamo. [online] Available at:
https://github.com/andydandy74/ClockworkForDynamo/blob/master/nodes/0.7.
x/Element.Materials.dyf [Accessed 1 Aug. 2016].
Haselbach, L. and Langfitt, Q. (2015). Welcome to the Life Cycle Assessment (LCA)
Learning Module Series.

Ireland’s Greenhouse Gas Emission Projections. (2013). 1st ed. [ebook] Dublin:
Environmental Protection Agency, pp.2-3. Available at:
https://www.epa.ie/pubs/reports/air/airemissions/EPA_GHG_Emission_Proj_p
ub_2013_FINAL.pdf [Accessed 23 Jun. 2016].
ISO 14040:2006. (2006). Geneva, Switzerland: International Organization for
Standardization.
ISO, (2006). ISO 14040:2006. Geneva, Switzerland: International Organization for
Standardization.
Jrade, A. and Abdulla, R. (2012). Integrating Building Information Modelling and
Life Cycle Assessment tools to design sustainable buildings. In: CIB W78 2012:
29th International Conference. [online] Beirut: CIB W78, pp.1-10. Available at:
http://itc.scix.net/data/works/att/w78-2012-Paper-24.pdf [Accessed 13 Jun.
2016].
Kensek, K. (2014). Integration of Environmental Sensors with BIM: case studies
using Arduino, Dynamo, and the Revit API. Informes de la Construcción,
66(536), p.e044.
Khasreen, M., Banfill, P. and Menzies, G. (2009). Life-Cycle Assessment and the
Environmental Impact of Buildings: A Review. Sustainability, 1(3), pp.674-701.
Kulahcioglu, T., Dang, J. and Candemir, T. (2012). A 3D analyzer for BIM-enabled
Life Cycle Assessment of the whole process of construction. HVAC&R
Research, 18(1-2), p.283.
Kwon, O. and Cho, J. (2015). BIM Clash Quality Control by Expert
System. Transactions of the Society of CAD/CAM Engineers, 20(1), pp.22-35.
Kylili, A., Fokaides, P., Vaiciunas, J. and Seduikyte, L. (2016). Integration of
Building Information Modelling (BIM) and Life Cycle Assessment (LCA) for
sustainable constructions. Journal of Sustainable Architecture and Civil
Engineering, 13(4).
Latvian Presidency of the Council of the European Union, (2015). SUBMISSION BY
LATVIA AND THE EUROPEAN COMMISSION ON BEHALF OF THE
EUROPEAN UNION AND ITS MEMBER STATES. [online] Riga: Latvian
Presidency of the Council of the European Union. Available at:
http://www4.unfccc.int/Submissions/INDC/Published%20Documents/Latvia/1/L
V-03-06-EU%20INDC.pdf [Accessed 6 Jul. 2016].

Lee, B. (2016). APPLYING SYSTEMS MODELING AND CASE STUDY
METHODOLOGIES TO DEVELOP BUILDING INFORMATION MODELING
FOR MASONRY CONSTRUCTION. MEngSc. Georgia Institute of Technology.
Murphy, F., Sosa, A., McDonnell, K. and Devlin, G. (2016). Life cycle assessment of
biomass-to-energy systems in Ireland modelled with biomass supply chain
optimisation based on greenhouse gas emission reduction. Energy, 109,
pp.1040-1055.
Nationalbimstandard.org. (n.d.). Frequently Asked Questions About the National
BIM Standard-United States™ | National BIM Standard - United States.
[online] Available at: https://www.nationalbimstandard.org/faqs#faq1
[Accessed 14 Jun. 2016].
NBS, (2016). National BIM Report 2106. [online] LOndon: NBS. Available at:
https://www.thenbs.com/~/media/files/pdf/bim-report-2016.pdf?la=en
[Accessed 9 Sep. 2016].
Nexus.openlca.org. (2015). openLCA Nexus: The source for LCA data sets. [online]
Available at: https://nexus.openlca.org [Accessed 4 Sep. 2016].
Quartz. (2016). LCA Methodology. [online] Available at:
http://quartzproject.org/methodology [Accessed 28 Jun. 2016].
Sgambelluri, M. (2015). Simply Complex: WHAT IS DYNAMO?. [online]
Therevitcomplex.blogspot.co.uk. Available at:
http://therevitcomplex.blogspot.co.uk/2015/01/what-is-dynamo.html [Accessed
21 Jun. 2016].
Sonnemann, G., Castells, F. and Schuhmacher, M. (2004). Integrated life-cycle and
risk assessment for industrial processes. Boca Raton, FL: Lewis Publishers.
Think BIM Blog. (2014). [online] Available at:
http://ckegroup.org/thinkbimblog/wp-content/uploads/2012/04/BIM-vs-
OPENBIM.pdf [Accessed 26 Aug. 2016].
Tollefson, J. (2009). Copenhagen accord emerges. Nature.
Tubielewicz-Michalczuk, M. (2015). ArchiCAD use the architectural design
construction. Mechanik, (7), pp.569/913-569/920.
UNFCCC.int. (2009). Copenhagen Climate Change Conference - December 2009.
[online] Available at:

http://unfccc.int/meetings/copenhagen_dec_2009/meeting/6295.php [Accessed 2
Jul. 2016].
Vogt, T. (2016). Current application of graphical programming in the design phase
of a BIM project: Development opportunities and future scenarios with
'Dynamo'. MSc. UNIVERSITY OF NORTHUMBRIA AT NEWCASTLE.

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