29032016 disertation final v6 nocv - research collection
Post on 10-May-2022
5 Views
Preview:
TRANSCRIPT
ETH Library
Development of simplified lifecycle assessment methodologyfor construction materials andbuildings outside of the Europeancontext through the use ofgeographic information systems
Doctoral Thesis
Author(s):Zea Escamilla, Edwin
Publication date:2015
Permanent link:https://doi.org/10.3929/ethz-a-010617848
Rights / license:In Copyright - Non-Commercial Use Permitted
This page was generated automatically upon download from the ETH Zurich Research Collection.For more information, please consult the Terms of use.
DISS. ETH NO. 23193
DEVELOPMENT OF SIMPLIFIED LIFE CYCLE ASSESSMENT METHODOLOGY FOR CONSTRUCTION MATERIALS AND BUILDINGS OUTSIDE OF THE EUROPEAN CONTEXT
THROUGH THE USE OF GEOGRAPHIC INFORMATION SYSTEMS
A thesis submitted to attain the degree of
DOCTOR OF SCIENCES of ETH ZURICH
(Dr. Sc. ETH Zurich)
Presented by
EDWIN BYRON BENIGNO ZEA ESCAMILLA
MSc. Wageningen University
Born on 29.05.1978
Citizen of Colombia, Switzerland, Hochdorf (LU) / Ettiswil (LU)
Accepted on the recommendation of
Guillaume Habert Ronald Rovers
Normando Barbosa
2015
In the end he worked out a method which would at least produce a result. He decided not to mind the fact that with the extraordinarily jumble of rules of thumb, wild approximations and arcane guesswork he was using he would be lucky to hit the right galaxy; he just went ahead and got a result.
D. Adams The Ultimate Hitchhiker's Guide to the Galaxy So long, and thanks for all the fish
To my family
Abstract
The global human population had been growing at an unprecedented rate for the last five decades and it is expected to keep this trend for the coming century. United Nations, estimates that the current world population of 7.6 billion will reach 9.5billion by the year 2050 and estimates a global human population of 10.9 billion by the year 2100. Furthermore, this growth had been mainly concentrated on urban areas, which had increased both the acquisition power and the demand for resources on those on those populations. From the environmental perspective, the magnitude of growth of cities have dramatically changed their material flows and the land use around them mainly thought the growth of buildings and infrastructures. The building sector is a multifaceted and decisive actor on this situation, providing benefits on both the global economic and social spheres but at the cost of environmental degradation. The advantages of this situation is that the building sector is financially strong, making it more apt for innovation and development. The challenge for the building sector is to use appropriated construction materials to maximize the economic, environmental and social benefits at a speed that allows it to achieve its main purpose. Consequently, it requires the further development of the existing assessment tools and the generation of data for those assessments for regions where the main urban development is occurring.
The main objective of the present research was to develop an approach for the production of life cycle assessment data for conventional and bamboo-based constructive systems and their associated materials. These data were integrated on a geographic information system in order to allow for the characterization of the data to different countries worldwide. The data and characterization methodologies were tested on several case studies focusing on post-disaster reconstruction and social housing projects. The case studies considered the use of alternative construction materials like bamboo and soil stabilized blocks as well as conventional construction materials like bricks and concrete hollow blocks. These case studies focused on the environmental impacts from the production of buildings using these construction materials on different locations. Additional sustainability aspects were also studied, considering the potential job creation; cost; life span; and carbon crediting potential associated to the used of the construction materials.
The findings from this research indicated that the appropriated selection and application of construction materials is one of the most important factors to consider on the sustainability of buildings. The results showed under different assessment conditions that sustainable buildings can be produced with a diversity of alternative and conventional construction materials. Moreover, the sustainability of a buildings is not directly correlated to its construction material but to the sustainable use of those materials. However, the use of bamboo as a construction material increases significantly the possibilities of producing sustainable buildings on a wide range of contexts. Furthermore, the results showed that the economic, environmental, and social benefits from the production and use of bamboo in construction can not only support the regenerative development of countries producing it but also it can offset the negative environmental impacts from the production and use of other construction materials.
Zusammenfassung
Das starke globale Bevölkerungswachstum der letzten 50 Jahre wird sich auch in Zukunft weiter fortsetzen, so schätzt die UNO die Bevölkerung gegenwärtig auf 7.6 Mrd., sie rechnet im Jahr 2050 mit 9.5 Mrd. und im Jahr 2100 mit 10.9 Mrd. Menschen, wobei sich dieses Wachstum hauptsächlich auf urbane Regionen konzentrieren wird. Durch das grosse Städtewachstum steigt der Ressourcenverbrauch weiter an, Materialflüsse und die stadtnahe Landnutzung verändern sich markant. Dabei ist der Bausektor ein entscheidender und facettenreicher Akteur, der die globale Wirtschaft, die Gesellschaft und die Umwelt erheblich beeinflusst, aber durch seine erhebliche Finanzkraft auch das Potential hat, innovative Entwicklungen voranzutreiben. Die grosse Herausforderung dieser Branche ist gegenwärtig die Wahl geeigneter Baumaterialien, um die Wirtschaftlichkeit, Umweltverträglichkeit und die gesellschaftlichen Aspekte zu verbessern. Um diese Herausforderung angehen zu können, braucht es eine Weiterentwicklung der bestehenden Beurteilungsinstrumente von Baumaterialien in Kombination mit regionalen Daten der schnell wachsenden Gegenden.
Das Ziel der vorliegenden Forschungsarbeit war die Entwicklung einer Lebenszyklusanalyse für herkömmliche und bambus-basierte Bausysteme mit den entsprechenden Materialien. Die Daten der Lebenszyklusanalyse wurden anschliessend in einem Räumlichen Informationssystem integriert und damit den weltweit spezifischen, regionalen Gegebenheiten angepasst. Die angewandte Methode und die erzeugten Daten wurden in verschiedenen Fallstudien mit den Schwerpunkten ‚Wiederaufbau nach Katastrophen‘ und ‚Sozialer Wohnungsbau‘ getestet. In den Fallstudien wurden neben alternativen Baumaterialien wie Bambus und Lehm die herkömmlichen Materialen wie Backsteine und Betonhohlblocksteine berücksichtigt. Im Zentrum der Studien stand die Ermittlung der Umwelteinflüsse beim Gebäudebau unter Verwendung dieser Baumaterialien an verschiedenen Orten der Welt. Ausserdem wurden für die untersuchten Materialien Aspekte der Nachhaltigkeit wie Lebensdauer, Kosten, Arbeitsplatzbeschaffung und das Potential für Kohlenstoffgutschriften analysiert.
Die Forschungsergebnisse zeigen, dass für die Nachhaltigkeit von Gebäuden die richtige Wahl und Anwendung der Baumaterialien entscheidend ist. Nachhaltige Gebäude können aus einer Vielzahl von alternativen und herkömmlichen Baumaterialien erstellt werden, denn die Nachhaltigkeit eines Gebäudes korreliert nicht direkt mit den verwendeten Materialien, sondern mit ihrem angemessenen Einsatz und Gebrauch. Dennoch verbessert die Anwendung von Bambus in vielen Fällen signifikant die Nachhaltigkeit eines Gebäudes. Die Resultate zeigen weiter, dass die Bambusproduktion und -anwendung wirtschaftlichen, umweltrelevanten und gesellschaftlichen Nutzen bringt. Weiter besteht für bambusproduzierende Länder Potential, deren regenerative Entwicklung zu verbessern und die negativen Umwelteinflüsse von den herkömmlichen Baumaterialien auszugleichen.
Table of Contents
1. Introduction ................................................................................................................................... 13
1.1. Global Population growth ............................................................................................................ 13
1.2. The urban growth and environmental degradation................................................................... 15
1.3. The role of the building sector on the environmental crisis ...................................................... 17
1.4. Bamboo .......................................................................................................................................... 18
1.4.1. Bamboo as plant ....................................................................................................................... 18
1.4.2. Bamboo as raw material ........................................................................................................... 21
1.4.3. Bamboo as construction material ............................................................................................. 23
1.4.4. Bamboo in contemporary architecture ..................................................................................... 24
1.5. Life Cycle and its assessment ....................................................................................................... 27
1.5.1. Methodological challenges ....................................................................................................... 29
1.5.2. LCA of buildings ...................................................................................................................... 29
1.5.3. LCA outside of the European context ...................................................................................... 30
1.6. Goal of research project ............................................................................................................... 30
1.7. Dissertation’s outline .................................................................................................................... 30
1.8. References ...................................................................................................................................... 31
2. LCA data for conventional and alternative construction materials ......................................... 37
Summary .............................................................................................................................................. 37
Introduction to the chapter ................................................................................................................ 39
2.1. Environmental impacts from the production of bamboo based construction materials
representing the global production diversity .................................................................................... 41
2.2. Literature review ........................................................................................................................... 41
2.2.1. Bamboo as a construction material ........................................................................................... 41
2.2.2. Life cycle assessment methodological challenges.................................................................... 43
2.2.3. LCA of bamboo-based construction materials ......................................................................... 44
2.3. Data and methods .......................................................................................................................... 44
2.3.1. Functional unit and system boundaries .................................................................................... 44
2.3.2. Inventory data ........................................................................................................................... 45
2.3.3. Impact assessment .................................................................................................................... 51
2.3.4. Uncertainty analysis ................................................................................................................. 51
2.4. Results ............................................................................................................................................ 52
2.4.1. Environmental impacts of the different bamboo products studied ........................................... 52
2.4.2. Process contribution to environmental impact ......................................................................... 52
2.4.3. Uncertainty analysis ................................................................................................................. 54
2
2.4.4. Process contribution to the variability of the results ................................................................ 54
2.5. Discussion ....................................................................................................................................... 56
2.5.1. Choice of impact assessment method ....................................................................................... 56
2.5.2. Process efficiency and energy mix ........................................................................................... 57
2.5.3. Key processes for a simplified bamboo LCA ........................................................................... 57
2.6. Conclusions and recommendations ............................................................................................. 58
2.7. Acknowledgements ........................................................................................................................ 59
2.8. References ...................................................................................................................................... 59
Chapter 2 in a nutshell ........................................................................................................................ 63
3. Methodology and application to characterize LCA data of alternative and conventional
construction materials ......................................................................................................................... 67
Summary .............................................................................................................................................. 67
Introduction to the chapter ................................................................................................................ 71
3.1. Method and application of characterization of life cycle impact data of construction
materials using geographic information systems .............................................................................. 73
3.1.1. Introduction .............................................................................................................................. 73
3.1.2. Methods .................................................................................................................................... 75
3.1.2.1. Developing an LCA geo-database / Characterization of the LCA data ................................. 76
3.1.2.2. Calculation of transport distances per country ...................................................................... 77
3.1.2.3. LCA of the Building .............................................................................................................. 79
3.1.2.4. Identification of seismic and wind risk zones ....................................................................... 79
3.1.2.5. Application ............................................................................................................................ 80
3.1.3. Results ...................................................................................................................................... 81
3.1.4. Discussion ................................................................................................................................ 84
3.1.5. Conclusions .............................................................................................................................. 85
3.1.6. Acknowledgements .................................................................................................................. 85
3.1.7. References ................................................................................................................................ 86
3.2. Case study – Detailed transport distances calculations ............................................................. 89
3.2.1. Abstract .................................................................................................................................... 89
3.2.2. Data and Methods ..................................................................................................................... 89
3.2.3. Results ...................................................................................................................................... 91
3.2.4. Conclusions .............................................................................................................................. 94
3.2.5. Acknowledgements .................................................................................................................. 94
Chapter 3 in a nutshell ........................................................................................................................ 95
4. Additional sustainability aspects from the use of bamboo on buildings .................................. 99
Summary .............................................................................................................................................. 99
3
Chapter’s introduction ...................................................................................................................... 101
4.1. Sustainability of transitional shelters -- Variability on design and transport ....................... 103
4.1.1. Introduction ............................................................................................................................ 103
4.1.2. Methodology .......................................................................................................................... 105
4.1.2.1. Environmental impact ......................................................................................................... 106
4.1.2.2. Cost ...................................................................................................................................... 110
4.1.2.3. Technical performance ........................................................................................................ 111
4.1.3. Results .................................................................................................................................... 113
4.1.3.1. Environmental impact ......................................................................................................... 113
4.1.3.2. Cost assessment ................................................................................................................... 115
4.1.3.3. Technical assessment .......................................................................................................... 116
4.1.3.4. Sustainability assessment .................................................................................................... 117
4.1.4. Discussion .............................................................................................................................. 119
4.1.5. Conclusions ............................................................................................................................ 121
4.1.6. Acknowledgements ................................................................................................................ 121
4.1.7. References .............................................................................................................................. 121
4.2. Sustainability of industrialized bamboo – CO2 Issues ............................................................. 125
4.2.1. Abstract .................................................................................................................................. 125
4.2.2. Results .................................................................................................................................... 125
4.2.2.1. Mass flow model ................................................................................................................. 126
4.2.2.2. Dynamic Model Housing demand ....................................................................................... 126
4.2.2.3. Economic Category ............................................................................................................. 128
4.2.2.4. Social category .................................................................................................................... 129
4.2.2.5. Sustainability assessment .................................................................................................... 129
4.2.3. Discussion .............................................................................................................................. 130
4.2.3.1. Building lifespan ................................................................................................................. 130
4.2.3.2. Electricity mix ..................................................................................................................... 131
4.2.3.3. End-of-life scenarios ........................................................................................................... 132
4.2.3.4. Sustainability Assessment ................................................................................................... 133
4.2.4. Conclusions ............................................................................................................................ 134
4.2.5. Acknowledgments .................................................................................................................. 135
4.3. Environmental Savings Potential from the Use of bamboo in Europe ................................... 137
4.3.2. Abstract .................................................................................................................................. 137
4.3.3. Results .................................................................................................................................... 138
4.3.4. Discussion .............................................................................................................................. 139
4.3.4.1. Uncertainties related to building physics calculations ........................................................ 140
4.3.4.2. Uncertainties related to life span and maintenance needs ................................................... 141
4.3.4.3. Uncertainties related to the selected EMs ........................................................................... 144
4.3.5. Conclusions and recommendations ........................................................................................ 145
4.3.6. Acknowledgments .................................................................................................................. 146
4
Chapter 4 in a nutshell ...................................................................................................................... 147
5. Conclusions .................................................................................................................................. 151
6. Reflections .................................................................................................................................... 155
Acknowledgements ............................................................................................................................ 157
Bibliography ...................................................................................................................................... 159
Annex .................................................................................................................................................. 167
A. Environmental impact of brick production outside Europe ................................................... 169
A.1. Abstract ...................................................................................................................................... 169
A.2. Methods ...................................................................................................................................... 169
A.2.1. Functional unit and systems boundaries ............................................................................... 169
A.2.2. Inventory data ......................................................................................................................... 171
A.2.3. Impact assessment ................................................................................................................... 173
A.2.4. Uncertainty analysis ................................................................................................................ 174
A.3. Results and discussion ............................................................................................................... 174
A.4. Conclusions ................................................................................................................................ 175
B. Bamboo based construction materials ...................................................................................... 177
C. Sustainability assessment of 20 Shelters data in brief ............................................................. 179
C.1. Specifications Table [please fill in right-hand column of the table below] ........................... 179
C.2. Data, Materials and Methods: .................................................................................................. 180
C.2.1. B1 Afghanistan Bamboo ........................................................................................................ 180
C.2.2. B5 Indonesia Bamboo ............................................................................................................. 180
C.2.3. B8 Philippines Bamboo .......................................................................................................... 180
C.2.4. C2 Bangladesh Concrete / Timber ........................................................................................ 181
C.2.5. C6 Pakistan Brick ................................................................................................................... 181
C.2.6. C8 Philippines Concrete ......................................................................................................... 181
C.2.7. C9 Sri Lanka Concrete / Timber ........................................................................................... 182
C.2.8. C11 Nicaragua Ferrocement.................................................................................................. 182
C.2.9. S4 Haiti Steel ........................................................................................................................... 182
C.2.10. S5 Indonesia Steel ................................................................................................................. 182
C.2.11. S10 Vietnam Steel ................................................................................................................. 183
C.2.12. W3 Burkina Faso Timber .................................................................................................... 183
C.2.13. W4(A) Haiti Timber ............................................................................................................. 183
C.2.14. W4(B) Haiti Timber ............................................................................................................. 183
5
C.2.15. W4(C) Haiti Timber ............................................................................................................. 184
C.2.16. W5 Indonesia Timber ........................................................................................................... 184
C.2.17. W6 Pakistan Timber ............................................................................................................ 184
C.2.18. W7(A) Peru Timber ............................................................................................................. 184
C.2.19. W7(B) Peru Timber .............................................................................................................. 185
C.2.10. W8 Philippines Timber ........................................................................................................ 185
C.3. Methods ...................................................................................................................................... 185
C.4. Value of the data ........................................................................................................................ 185
C.5. Acknowledgements .................................................................................................................... 185
C.6. Shelters LCIs .............................................................................................................................. 186
C.7. References .................................................................................................................................. 226
D. Technical performance assessment 20 shelters ........................................................................ 227
6
7
List of Figures
Figure 1.1Global population growth, urban population, life expectancy, and mortality rate at birth[2] ................ 14
Figure 1.2 Material intensity: material extraction per unit of GDP[6] ................................................................... 15
Figure 1.3 Planetary system boundaries[10] .......................................................................................................... 16
Figure 1.4 GDP, CO2 emissions, and construction minerals extraction (Per Capita)[2, 6] .................................... 17
Figure 1.5 Global distribution of bamboo .............................................................................................................. 19
Figure 1.6 Worldwide distribution of bamboo resources [24] ............................................................................... 20
Figure 1.7 Rhizomes structures of bamboo [25] .................................................................................................... 20
Figure 1.8 Structure of the bamboo culm [20] ....................................................................................................... 21
Figure 1.9 Bamboo fibre distribution [28] ............................................................................................................. 22
Figure 1.10 Glue laminated bamboo ...................................................................................................................... 23
Figure 1.11 Bahareque house construction Source: Bambusa Project, Lopez / Trujillo, Colombia ...................... 23
Figure 1.12 Bamboo dome. Source L.F. Lopez ..................................................................................................... 24
Figure 1.13 Bamboo Pavilion. Manizales Colombia [19] ...................................................................................... 25
Figure 1.14 the Kouk Hhlean youth Centre in Phnom Penh, Cambodia Source: [38] ........................................... 26
Figure 1.15 German-Chinese House by Makus Heinsdoff for the World Expo 2010 in Shanghai[39] ................. 26
Figure 1.16 KPMG-CCTH Community centre, PRC [38] ..................................................................................... 27
Figure 1.17 Product's life cycle .............................................................................................................................. 28
Figure 1.18 LCA methodological steps ................................................................................................................. 28
Figure 2.1 Example of a spatial structure. Bamboo Bridge in Bogotá, Colombia. Sce: L.F. Lopez ...................... 42
Figure 2.2 Example of a load-bearing structure. Bamboo house in Ibague, Colombia .......................................... 43
Figure 2.3 Conceptual framework.......................................................................................................................... 46
Figure 2.4 Bamboo-based construction materials .................................................................................................. 48
Figure 2.5 Relative process contribution to environmental impact for the production of BBCM in (%) .............. 53
Figure 2.6 Environmental impacts of the various bamboo-based construction materials. ..................................... 54
Figure 2.7 Relative contribution of the different processes to the impact .............................................................. 55
Figure 2.8 Variation for glue laminated bamboo induced by a change in the electricity mix ................................ 56
Figure 3.1 Conceptual framework of the methodology ......................................................................................... 75
Figure 3.2 LCA of buildings, transport distance, and production efficiency ......................................................... 82
Figure 3.3 Contribution to the environmental impact ............................................................................................ 83
Figure 3.4 LCA and structural performance .......................................................................................................... 84
Figure 3.5 Functional Unit -- General Floor Plan. All measurements in cm. ........................................................ 90
Figure 3.6 (A) Bamboo frame (bahareque); (B) Concrete hollow block; (C) Ferro-cement panel; (D) Soil
stabilized brick. ............................................................................................................................................. 90
Figure 3.7 Environmental impacts at different transport regimes .......................................................................... 92
Figure 3.8 Contribution to environmental impact. ................................................................................................. 93
Figure 3.9 Environmental and structural performance at different locations ......................................................... 94
Figure 4.1 Environmental impact per functional unit .......................................................................................... 114
Figure 4.2 Cost assessment .................................................................................................................................. 116
Figure 4.3 Technical performance. ...................................................................................................................... 117
Figure 4.4 Sustainability assessment .................................................................................................................... 119
Figure 4.5 Variability analysis. ............................................................................................................................ 120
Figure 4.6 Mass flow for one glue laminated bamboo housing unit .................................................................... 126
8
Figure 4.7 CO2 dynamic model ........................................................................................................................... 127
Figure 4.8 Economic category ............................................................................................................................. 128
Figure 4.9 Sustainability assessment .................................................................................................................... 130
Figure 4.10 Sensitivity analysis of electricity mix ............................................................................................... 132
Figure 4.11 Sensitivity analysis of end-of-life scenarios ..................................................................................... 133
Figure 4.12 Sustainability assessment with sensitivity analysis .......................................................................... 134
Figure 4.13 Wall sections ..................................................................................................................................... 138
Figure 4.14 LCA results ....................................................................................................................................... 138
Figure 4.15 Process contribution to environmental impact .................................................................................. 139
Figure 4.16 Effect of XPS thickness on bahareque ESP ...................................................................................... 141
Figure 4.17 ESP range – LCI amounts variations ................................................................................................ 143
Figure 4.18 Results of accumulated EM .............................................................................................................. 145
9
List of Tablets
Table 2-1 Functional units studied ........................................................................................................ 45
Table 2-2 : LCI of bamboo culm ........................................................................................................... 47
Table 2-3 LCI of bamboo pole .............................................................................................................. 49
Table 2-4 LCI of flattened bamboo ....................................................................................................... 49
Table 2-5 LCI of woven bamboo mat ................................................................................................... 50
Table 2-6 LCI of glue laminated bamboo ............................................................................................. 50
Table 2-7 LCI of woven bamboo mat panel .......................................................................................... 51
Table 2-8 Environmental impacts for the production of bamboo-based construction materials ........... 52
Table 2-9 Main parameters that need to evaluate environmental impact and uncertainty .................... 58
Table 3-1 Land area and transport distances from literature ................................................................. 77
Table 3-2 Potential transport distances (sample) .................................................................................. 78
Table 3-3 life cycle inventories of construction materials used in five house designs ......................... 81
Table 3-4 LCIs of the five house designs .............................................................................................. 91
Table 4-1 Shelters' location, structural material and type ................................................................... 105
Table 4-2 LCIs bamboo based shelters ............................................................................................... 108
Table 4-3 LCIs mineral based shelters ................................................................................................ 108
Table 4-4 LCIs steel based shelters ..................................................................................................... 109
Table 4-5 LCIs wood based shelters (part 1) ...................................................................................... 109
Table 4-6 LCIs wood based shelters (part 2) ...................................................................................... 110
Table 4-7 Hazard risk classification .................................................................................................... 111
Table 4-8 Shelter's hazard at location and performance ...................................................................... 112
Table 4-9 Technical performance assessment matrix ......................................................................... 112
Table 4-10 Contribution from components to environmental impact ................................................. 115
Table 4-11 LCI construction 1 m2 insulated bahareque wall .............................................................. 140
Table 4-12 Data input for life span and maintenance calculations – Bahareque wall ......................... 142
Table 4-13 Data input for life span and maintenance calculations – Clay brick wall ......................... 142
Table 4-14 Data input for life span and maintenance calculations – Concrete block wall ................. 142
10
11
Chapter 1: Introduction
12
13
1. Introduction
This chapter presents the context in which the present doctoral dissertation was developed. The first
section describes the current situation in terms of global population growth and the consequent pressure
on resources and the environment. Moreover, it illustrates the concern for the need of housing for the
ever-growing world population and the need for construction materials able to cope with this demand
on a sustainable way. The second section presents bamboo as a plant, its global distribution and its
common uses. Furthermore, this section describe the use of bamboo as construction material and its
application on contemporary architecture. The third section presents an overview of Life Cycle
Assessment (LCA), the methodological challenges its implementation faces and the constrains faced on
its application on buildings, especially those outside the European context. The final section describes
the research project and the contents of this document.
1.1. Global Population growth The global human population had been growing at an unprecedented rate for the last five decades and it
is expected to keep this trend for the coming century[1]. The department of Economic and Social Affairs
from the United Nations, estimates that the current world population of 7.6 billion will reach 9.5billion
by the year 2050 and estimates a global human population of 10.9 billion by the year 2100[1]. This is
not an isolated process, on the contrary, it is the result of several global trends that started in the middle
of the twentieth century. From the population perspective three main trends can be identified. First, over
the last five decades (1960-2015), the mortality rate after birth had been dropping steadily reaching an
all-time low level of 59 death per 1000 births [1, 2] as seen on figure 1.1. Second, the life expectancy
had been increasing over the same period and reaching a global average of 69 years[2]. And third, the
urban populations had been growing at a stunning rate accounting from more than 50% of the total
human population by 2012[3].
All these factors are intertwined and contribute to the burst of human population, but deeper conclusions
can be drawn from them. The fact that the mortality rate has been so dramatically reduced means that
more women and children are able to receive better medical treatment, which is more accessible to urban
populations. Furthermore, this increase on global population is occurring unevenly and it is concentrated
mainly on Africa and Asia. As a consequence the population of ages under 15 accounts for the 28% of
the populations of those regions [1] while accounting for less than 12% in regions like Europe or North
America. Furthermore, the life expectancy is also increasing which can be also associated not only to a
higher accessibility to medical treatments on urban populations but also with the change of employment
type from rural-agricultural to urban-industrial /services that the human global populations is
experiencing[3, 4]. From figure 1.1 it is also possible to see that the rate of growth of urban populations
is much higher than the one of the global human populations. This has two implication, first humans
14
populations are becoming largely urban in some countries up to 90%. Second, the size and density of
those urban areas must be growing at a similar rate.
Figure 1.1Global population growth, urban population, life expectancy, and mortality rate at birth[2]
This situation has both economic and environmental consequences. From the economic perspective, the
past half a century saw the global economic output (GDP) growing more than twenty times. With a 10%
estimated of the GDP being related with the urbanization process [5]. Furthermore, this growth had been
mainly concentrated on urban areas, which had increased both the acquisition power and the demand
for resources on those on those populations [3, 6]. From the environmental perspective, the magnitude
of growth of cities have dramatically changed their material flows and the land use around them. This
has produce a fundamental change the relation between cities and environment and started a massive
process of degradation of the natural environment [7]. Cities had become consumers of vast amounts of
resources not only to maintain their populations but also to develop their infrastructures and
buildings[4]. On this process the natural environment is being pushed to the boundaries of its carrying
capacity to a level that might be irreversible.
15
Figure 1.2 Material intensity: material extraction per unit of GDP[6]
The work of Krausmann et all[6] has shown that the intensity in which resources are extracted had
almost double over the last century as presented on figure 1.2. Furthermore, the type of resources being
extracted is changing from Biomass towards mineral resources, primordially construction minerals[6]
(fig 1.2.). Moreover, the intensity of extraction of construction mineral is growing at a faster rate than
the GDP over the las century. These patterns clearly show the existence of a link between the
urbanization process, the economic growth and the depletion of natural resources experienced on the
last five decades.
1.2. The urban growth and environmental degradation The global urban areas had been growing at pair with the human populations. These areas not only
require vast amount of resources for their operation and development but also produces a significant
amounts of emissions and waste[4, 8]. The extraction of these mineral resources can be considered as
one of the main sources of environmental degradation worldwide [9]. It has been estimated that the
environmental degradation is starting to surpass the carrying capacity of the natural environment[10].
The changes on nine quantifiable planetary systems from the beginning of the century to their current
status are presented on figure 1.3.
16
Figure 1.3 Planetary system boundaries[10]
From figure 1.3 it is possible to see that radical changes on the planetary systems had occurred at the
same time as the urbanization process. Moreover, six out of nine planetary systems had already
surpassed their thresholds and the remaining three are about to surpass theirs. Some of these levels are
irreversible like the case of extinction rate but many others like atmospheric CO2 depend on the human
activities and therefore they can be changed and improved[10]. In the case of climate change related
planetary systems there is consensus that these high values come from human activities [11] and that
the focus should be turned now towards the adaptation and mitigation climate change in order to ensure
a sustainable and resilient built environment[12].
As it has been previously presented, global human populations, urbanization levels, extraction of
construction minerals, atmospheric CO2 and GDP are all growing. A striking similarity can be found in
their growth patterns as presented on figure 1.4.
17
Figure 1.4 GDP, CO2 emissions, and construction minerals extraction (Per Capita)[2, 6]
Figure 1.4. Presents the indexed values per capita of CO2 emissions, construction materials extraction,
and GDP. Due to this relation if the values stay stable it means that they are varying at the same rate as
the population. After the turn of the century the values for all three increased, showing that they were
growing much faster than the population over the same period. GDP and extraction of construction
minerals showing a steeper growth pattern than the one from atmospheric CO2 [8]. These rates of growth
are evidence that the global economies are interconnected with the production of construction materials
and buildings. Once all this information is pieced together, it becomes evident that the building sector
is a decisive player on the future of the global economy and the natural environment[8].
1.3. The role of the building sector on the environmental crisis The building sector is one of the most important sources of economic activity and it is estimated that
contributes to 10% of the global GDP[8, 13]. It providing almost 7% of employment worldwide and it
is considered the largest single employer[8]. Nevertheless, it has been estimated that the building sector
is responsible for the consumption of around half of all the resources extracted from nature[8], and it is
the main consumer of electricity with a global average above 30%[13]. The building sector contributes
more than 7% of all global GHG emission from the production of construction materials and more than
30% from the operation of buildings and infrastructure[8, 13].
18
The building sector also provides infrastructures and housing which are the basis for the economic and
social development of urban areas and their populations. The aforementioned population growth and
urbanization level are creating a rising housing demand worldwide[4, 8]. This demand is more
pronounced in least develop and emerging economies countries but it also occurs in other geographies
[4] . On least develop and emerging economies countries the offer of housing cannot cope with their
rapidly growing populations. This has created a housing gap which size is difficult to assess but it has
been estimated to border the 100.000 units per year[14] and it is expected to continue growing. From
the facts that had been presented on this section it is clear that the provision of urban infrastructures and
housing will be done using non-renewable mineral based construction minerals. Thus, contributing to
further increase the levels of environmental degradation and resource depletion on the global scale. The
building sector is a multifaceted and decisive actor on this crisis, providing benefits on both the global
economic and social spheres but at the cost of environmental degradation. The advantages of this
situation is that the building sector is financially strong, making it more apt for innovation and
development. Moreover, due to its important role in the countries’ economies and societies it counts
with the support from the population and national governments.
A sustainable and resilient built environment requires changes that maximize the economic and social
benefits from the building sector while reducing the associated negative impacts on the natural
environment. On this endeavour it is necessary for the building sector to switch from the mineral based
construction materials towards renewable bio-based solutions, on a purpose specific high performance
basis. The challenge for the building sector is to use appropriated construction materials to maximize
the economic, environmental and social benefits at a speed that allows it to achieve its main purpose.
This is by no means an easy task and few construction materials are able to fulfil all the requirements.
Among them, bamboo had been considered as one with the highest potentials to be sustainably used on
the development of the built environment [15-18].
1.4. Bamboo
1.4.1. Bamboo as plant
Bamboo belongs to the Poeceae – Gramineae family, which mean that it is a giant grass [19, 20]. In fact
bamboos are the only grass adapted to live in a forest. There are about 1250 different bamboo species
and 75 genera worldwide. [21] About 1100 species can be classified as woody bamboo. [22] and they
grow naturally in four continents, Africa, America, Asia and Oceania[19], countries in which bamboo
grows naturally are marked green on figure 1.5.
19
Figure 1.5 Global distribution of bamboo
Bamboo features a wide range of distribution and a great variety of habitats. Bamboo is normally found
in regions where temperature ranges from 8°C to 36 °C with an annual rainfall of 1020 to 6350 mm.
Some bamboo species can develop up to 4000 m above sea level and withstand temperatures as low as
-20 °C [21]. The greatest bamboo diversity can be found in Asia, with about 590 bamboo species and
44 genera. Most of them are endemic to China, where temperate bamboo forests, warm bamboo forests,
hot bamboo forests and plain bamboo forests exhibit the largest number of bamboo species in the
world[21]. The majority of woody bamboo genera and species are endemic to South and Southeast Asia.
This region is gifted with about 150 species with a high economic value [21]. The second richest region
in terms of bamboo diversity is Latin America with a share of 39% of all bamboo species worldwide.
Especially Brazil and Colombia offer a great diversity with more than 100 different species [22].
It is estimated that almost one percent of the world land is covered by bamboo forest [20], 80% of these
bamboo forest are located in Asia and the Pacific regions as it can be seen on figure 1.6. The largest
bamboo resources are found in China, India, Myanmar, Indonesia, Thailand and Vietnam. [21] China
alone has seven million hectares of bamboo forest. More than half of which are managed plantations
and therefore exploited for commercial purposes. The remaining bamboo forests are mainly situated in
mountainous regions and are an important habitats supporting extensive ecosystems[23]. In Latin
America, the bamboo forest area is estimated to be close to eleven million hectares, and a big part of it
belongs to the south-western Amazon basin in Brazil [22].
20
Figure 1.6 Worldwide distribution of bamboo resources [24]
Bamboo plants can be classified based on their rhizome structures: Sympodial, Monopodial and
Amphipodial as shown on figure 1.7. Sympodial rhizomes structures consist only of a culm neck and a
culm base. These rhizomes are quite short and grow vertically into the ground. New shoots emerge on
the culm base and sprout directly into young culms. [25] A monopodial rhizome structure presents long
and thin rhizomes that grow horizontally. Buds develop either into shoots or expand the rhizome
structure. [25] Usually lateral buds become shoots whereas terminal buds form new rhizomes.
Amphipodial rhizomes structures are a case apart as they exhibit features typical for sympodial and
monopodial rhizomes. [25]
Figure 1.7 Rhizomes structures of bamboo [25]
The bamboo culm has a tube shape with walls that consist of different layers. The outer layer of the
bamboo wall is called epidermis and is the oldest part of the plant (fig 1.8). The inner layer is known as
the cortex and has a high content of lignin and silica concentrated in short cells [25]. Under the epidermis
there is the derma section with vascular bundles called parenchyma cells. The innermost part of the
bamboo wall is highly lignified and cells are densely arranged. [25]
21
Figure 1.8 Structure of the bamboo culm [20]
A remarkable process in bamboo is its fast grow stage that takes between six to nine months, depending
on the spices and the environment they grow. During this stage the culm reaches its full height and
diameter. The fast growth is enabled by the simple structure of fibres and the conductive tissue found
on bamboo [20] The parenchyma cells that are arranged axially along the culm allow a rapid flow of
nutrients, thus supporting the grow process. When the bamboo stops growing in height a consolidation
of tissue starts by secondary thickening of the culm’s inner walls [20]. Bamboos are very diverse on
their physiology, the most visible characteristics being the diameters of the canes and their height. The
diameters varies between 0.5cm up to 22cms the height starts from 1m and can reach up to 20m
depending on the species. Roughly classifying, the bamboos can be considered as giant bamboos when
their diameters are beyond 7cms. Another distinctive feature is the way they grow based on the on their
rhizome structures Sympodial and Monopodial structures will produce culms that grow very close to
each other forming clumps while Amphipodial rhizome structures will produce bamboo culms that are
scattered leaving space for new shoots.
1.4.2. Bamboo as raw material Thanks to its geographical distribution bamboo had been available to many cultures around the world
since immemorial times. None surprisingly an incredible wide range of applications had been developed
for it, this combined with its rapid grow and bio mass production made bamboo a prime resource in
Africa, America, and Asia. The shoots of some species of bamboo are edible and had been used in Asian
cuisine for centuries[26]. The foliage had been used as biofuel and as composting materials[26]. The
bamboo canes be burned directly or processed into charcoal for heating and / or cooking. Thanks to its
mechanical characteristic Bamboo canes had been used to make tools, furniture, and hardware. Bamboo
can also be processes into fibres and /or thin veneers which can be used in the production of textiles or
22
mats. Bamboo canes are on itself very good load bearing elements and can be used to produce furniture.
Moreover thanks to its weight to strength ratio bamboo canes can be used to produce light weight
structures and buildings.
Bamboo is mainly composed of cellulose, lignin, pentosan, soluble extracts. The cellulose content is
responsible for the bamboo’s tensile strength parallel to grain. The components hemicellulose and lignin
serve as backbones to cellulose providing bamboo with elasticity and compressive strength. [25] Lignin
occupies the absorptive space of cell walls and thus contributes to the dimensional stability of bamboo
[25]. Bamboo exhibit many physical properties similar to conventional construction materials like wood.
Bamboo is an anisotropic material like wood, which means that the fibres are orientated parallel to each
other. The fibre density is higher at the outer periphery which is one reason for the high flexibility of
bamboo[27, 28] as it can be seen on figure 1.9.
Figure 1.9 Bamboo fibre distribution [28]
The tensile strength along fibres can be as high as 193 N/mm2, the tensile strength across fibres to 8, 1
N/mm2. The compressive strength along fibres reaches values of about 68 N/mm2. For the Young’s
modulus along fibres a value of about 20600 N/mm2 can be assumed[27]. This characteristics make
bamboo a very interesting material that can be used with little processing or can provide fibres for the
production of composite materials. One of the most know of these bamboo composites is glue laminated
bamboo [29-31]. Glue laminated bamboo consists of flattened bamboo culms that are glued together in
stacks figure 1.10. The flattening process is energy-intensive and produce large amounts of by product
(saw dust)[30] [32] as seen in figure 12. The mechanical properties of this composite can be compared
23
to those of glue laminated wood[31, 33] and it had been proposed that it application could transition
from furniture towards a structural material application [18, 30, 34]
Figure 1.10 Glue laminated bamboo
1.4.3. Bamboo as construction material As it was mentioned before, bamboo had been available to many different cultures through the centuries.
As a consequence bamboo has been also used to produce edifications and infrastructures. The
constructive systems based on bamboo are very diverse and its application is strongly related to the
culture and environment of the region. Moreover, the morphology of the bamboo affects as well what
kind of structure were developed. Two main types of constructive systems can be identified: Load
bearing walls and spatial structures. The load bearing walls are created using frames of bamboo or mixes
of bamboo and wood[35]. Then these frames can be cladded with different materials, flattened bamboo,
steel sheets, and / or wood. After the cladding a final coat is applied that can be simple paint or a layer
of mortar-plaster. This provides lightweight walls with high load bearing capacity (fig 1.11). This kind
of structures had been utilized for over two centuries in countries like Colombia, Ecuador and Peru. The
positive experiences and good structural behaviour of these structure have created a lot of interest on
the scientific community. The inclusion of bamboo in the Colombian building code started a process of
ratification of this construction technique in the region. This construction technique had been widely
used over the years but recently it had become an interesting option for social housing solutions[36]
Figure 1.11 Bahareque house construction Source: Bambusa Project, Lopez / Trujillo, Colombia
24
The bamboo based spatial structures are based on struts and columns, this type of structures require
special joints to ensure their structural stability. This constructive system can be applied for edification
with either closed or open envelops (fig 1.12). These kind of constructive system had proved to be very
resilient to external environmental constrains like earthquakes or extreme winds. This lead to extensive
research on the field of structural design with bamboo and to the development of building codes for
bamboo based construction first in Colombia[37], and then in Ecuador, Nicaragua, and Peru. These
constructive systems had evolved from vernacular systems into engineered systems capable to perform
at the same level as modern constructive systems. This system allows to produce impressive buildings
and infrastructure and have open doors for the utilization of bamboo as main construction material in
contemporary architecture.
Figure 1.12 Bamboo dome. Source L.F. Lopez
1.4.4. Bamboo in contemporary architecture Bamboo has a place on modern architecture, its application is not widespread but a good number of
examples can be found around the world. One of the most renowned architects for his work with bamboo
based buildings is Simon Velez. Mr. Velez has worked over decades on the use of bamboo as main
structural material for his designs. In 2009 he was the principal laureate of the Prince Claus Fund for
Culture and Development award for his work on the preservation and further development of this
construction technic and material. The work of Mr Velez ranges from private homes, to social housing
projects, institutional and educational buildings. One of the most renown building was the pavilion for
the Zero Emissions Research and Initiative (ZERI) in the world expo in Hannover(GE) in the year 2000
25
(fig 1.13). This was until recently the largest bamboo building in the world and showed to the world the
potential that bamboo based construction withholds.
Figure 1.13 Bamboo Pavilion. Manizales Colombia [19]
One key element on his work is the type of joints used to connect bamboo canes. This kind of joint is
an evolution of the traditional joint type used in Colombia. The work of Mr Velez had been two folded,
on the one hand he had shown that bamboo has a place in contemporary architecture and on the other
he had inspired students and researchers to better understand how this structures work. Consequently,
this lead to a revival of the use of bamboo as main construction materials and to increase the social
acceptance of the material. Furthermore, the work several research institutions lead to the development
of special chapters on the Colombia building code.
This can also be seen in the work of offices like Komitu Architects with their woke on the Kouk Hhlean
youth Centre in Phnom Penh, Cambodia (Fig 1.14) where a mixture of bamboo, bricks and wood was
used to produce interesting aesthetics and mechanical performance.
26
Figure 1.14 the Kouk Hhlean youth Centre in Phnom Penh, Cambodia Source: [38]
Another interesting example is the German-Chinese House by Makus Heinsdoff for the World Expo
2010 in Shanghai. This structure combines bamboo with steel joiners and a clear façade that allows both
illumination and showcases the building materials used (fig 1.15)
Figure 1.15 German-Chinese House by Makus Heinsdoff for the World Expo 2010 in Shanghai[39]
As it was mentioned glue laminated bamboo can also be used in construction of both buildings and
infrastructure. The examples of the use of this material are more limited due to the lack of regulation
and characterization of the materials. The KPMG-CCTH Community centre (fig 1.16) is one excellent
27
example of the application of glue laminated bamboo in construction. As it can be seen from the picture
the main structural elements are made out of glue laminated bamboo.
Figure 1.16 KPMG-CCTH Community centre, PRC [38]
From this examples it becomes clear that bamboo based construction material can play a significant role
in the build environment and become an alternative to conventional construction materials. To better
understand the potentials these materials withhold it is necessary to assess their production process, their
service life and the impact on the environment that their application will produce.
1.5. Life Cycle and its assessment The life cycle of a product can be roughly divided in four phases: (i) extraction, (ii) production, (iii) use
and (iv) disposal[40] as it can be seen on figure 1.17. The extraction phase, as the name indicates,
represents the extraction, recycling and/or re-use of raw materials from the environment [41]. This phase
considered activities like mining, harvesting of crops, and/or up cycle of recycled products. The
production phase considers the transformation of raw materials into processed products. This phase
plays an important role because it describes the efficiency of the transformation and the associated
energy and material demand for the studied product or service[42]. The use phase considers the energy
and material demand of the product during its service. This phase also considers the duration of the
service life, also known as the life span of the product[41]. Finally the disposal phase considers how the
products are disposed into the environment and/or recycled into new products. These four phases are
commonly known as the life cycle of a product.
28
Figure 1.17 Product's life cycle
Life cycle assessment (LCA) is the accepted methodology to evaluate the whole life impacts of products
and services[42]. LCA has been standardize and described in the ISO 14040 [43]norm and it consists of
four steps: definition of goal and scope, development of life cycle inventories (LCI), impact assessment
and interpretation. LCA is an iterative process where the definition of goal and scopes is adjusted based
on the results from the subsequent steps[40] (fig 1.18). The term “environmental impact” is used in LCA
to refer to the effects of the studied system on the environment. These impacts depend directly on the
evaluation method used during the impact assessment step.
Figure 1.18 LCA methodological steps
This methodology allow identify hotspots and to propose improvement potential of the studied
product[42]. In order to achieve this goal LCA requires quality data, which is able to represent the
production practices of the studied product[44]. Moreover, LCA requires an evaluation method, for the
impact assessment, able to characterize the results based on the location and time the product is being
29
produced[45]. The availability of these two elements is one of the main barrier for a widespread
application of LCA[44].
1.5.1. Methodological challenges LCA is a very simple representation of a complex reality[40]. The methodology of LCA is clearly
described on the ISO 14040 norm but its application requires a series of assumptions and
approximations. These assumptions involve for instance how the environmental impacts are allocated
or distributed among products and by products [46, 47], how is going to be the product be disposed or
recycled and under which technical conditions [48, 49], and the extent of the studied systems and why
they are trimmed on that particular location [50]. Furthermore, the quality and availability of data used
along the life cycle phases remains a major challenge[51, 52]. Moreover, the production of LCA data
requires major investments, making it difficult for small companies or alternative solutions to provide
the data related to their products [44]. Besides the financial investment a dedicated LCA practitioner is
needed to produce LCA data following the ISO standards and complying with all the requirements form
databases. In many cases the aim of an LCA is an exploratory work or a support on the decision making
process, thus resources for this kind of investments are usually not viable.
1.5.2. LCA of buildings LCA has been used to assess buildings for over two decades[53]. Its application at early stages can
highlight the improvement potentials on the different building components[54]. These improvements
can be therefore applied on subsequent buildings. The LCA of buildings is inherently complex due to
the number of components and systems that conform a building[54]. Moreover, the efficiency of
production of construction material can widely vary from country to country [55]. To model the life
cycle of a building it is necessary to know where the construction materials were produced not only to
know the production practices and efficiencies used but also to know the total transport distance from
production centres to the buildings construction site[56]. To calculate these transport distances it is
necessary to have a good estimation on possible routes and means of transport and potential sources of
construction materials[57]. Nevertheless, the use of LCA for the assessment of building has paved the
way to a better understanding on the different embodied and operational energy demands[55].
Furthermore, with the advent of energy efficiency regulations and labels major steps had been taken to
reduce the operational energy demand on buildings[58]. As a consequence the focused has shifted
towards the assessment of embodied energy and consequently on the construction materials used[59].
A similar situation can be found in countries without seasons, where there is no heating demand, thus
making the operational energy negligible.
30
1.5.3. LCA outside of the European context The quality of the LCA results depend heavily on the quality of the data used to prepare the LCA
models[44]. Therefore, data that is not representative of a certain production practice in terms of it
process or efficiencies will provide vested results. Moreover, data that has very wide scope, either
regional averages or global averages, is not able to represent the different production practices of specific
locations. These data are usually collected on LCA databases, which are managed by research and
private organizations. The largest databases are EcoInvent[60] and ELCD[61] both based in Europe.
Not surprisingly the main core of data corresponds to the European geography. Even though, regional
and global datasets can be encountered on the latest versions of EcoInvent. To work outside the
European context it is necessary to be able to represent the production conditions outside this geography.
This process is described on the ISO standards[43] but it requires a significant financial and time
investments. These two factors hinder further the development of new datasets outside the European
context. Furthermore, this is also an issue for alternative construction materials that do not have the
support from well financed companies. Consequently, the LCA of buildings carried outside the
European context rely on approximations that produce high levels of uncertainty on their results.
1.6. Goal of research project The main objective of the present research was to develop an approach for the production of life cycle
assessment data for conventional and bamboo-based constructive systems and their associated materials.
These data were integrated on a geographic information system in order to allow for the characterization
of the data to different countries worldwide. The data and characterization methodologies were tested
on several case studies focusing on post-disaster reconstruction and social housing projects. The case
studies considered the use of alternative construction materials like bamboo and soil stabilized blocks
as well as conventional construction materials like bricks and concrete hollow blocks. These case studies
focused on the environmental impacts from the production of buildings using these construction
materials on different locations. Additional sustainability aspects were also studied, considering the
potential job creation; cost; life span; and carbon crediting potential associated to the used of the
construction materials.
1.7. Dissertation’s outline The present document is divided on five chapters which represent the process in which the proposed
research objective was achieved. Chapter 2 presents the main problem of lack of data and the
complexity to generate it outside of the European context. The first part of this section deals with a
methodological approach to generate LCA of bamboo based construction materials with global
representativeness. The methodology was used to produce the first global LCA data sets on the
EcoInvent database. The second part of this section, presents the application of the methodology for the
31
case of conventional and alternative construction materials like concrete, bricks, soil stabilized blocks
and ferro-cement panels. This is very important not only for the production of this kind of data outside
the European context but also because it validates the methodology’s flexibility. The data generated on
this process is used to carry out comparative LCAs. Chapter 3 deals with the development of a
methodological approach to characterize LCA data. This characterization process allows for the cost-
effective production of LCA data worldwide. The proposed methodology represents the wide range of
production practices encountered worldwide for both conventional and alternative construction
materials and the electricity mix used on their production. Moreover, it allows to estimate potential
transport distances based on the land area of the country of study. Furthermore, it also allows for the
identification of hazard risk zones for earthquake and wind on the studied location. On this section, the
implementation of this methodology on one case study is also presented. Chapter 4 presents three case
studies where additional sustainability aspects from the used of bamboo in construction were studied.
In the first case study, the sustainability of 20 transitional shelters and was assessed. Sustainability was
considered as a three component issue, considering environmental impacts, cost and risk/performance
from natural disasters. The results from this section highlight the important role that appropriate
materials selection and design on the sustainability of the built environment. Moreover it present the
pros and cons from the use of local or global construction materials in reconstruction projects with a
worldwide view. The second case study, deals with the sustainability of different construction materials
used in social housing programs. Here a much larger scale and time frame than previous studies is
presented. Housing programs requiring decades to implement and a significant amount of housing units
to cope with the ever growing global housing demand. Here, sustainability was considered in terms of
CO2 emissions; cost in terms of potential CO2 credits generated; and social as potential job positions
created. Moreover, the analysis from this section show that an alternative to the current building
practices is needed and it should be implemented in the very short term to be able to be effective. But
this implementation is limited by The results from this section shows that bio based construction
materials bamboo and timber have a great potential not only to withhold low environmental impacts and
cost but also to reduce the levels of CO2 and produce additional income in form of CO 2 Credits. The
final part of this section shows the potential that bamboo withholds to reduce environmental impacts
from buildings within the European context. Chapter 5 will present the general conclusions of this
research project reflecting on the overall process.
1.8. References 1. DeSA, U., World population prospects: The 2012 revision. Population Division of the
Department of Economic and Social Affairs of the United Nations Secretariat, New York, 2013. 2. IBRD. World bank: Data. 2015 [cited 2015 05.2015]; Available from:
http://data.worldbank.org/. 3. Heilig, G.K., World urbanization prospects: the 2011 revision. United Nations, Department of
Economic and Social Affairs (DESA), Population Division, Population Estimates and Projections Section, New York, 2012.
32
4. UNHabitat, State of the World´s Cities 2010/2011, U. Habitat, Editor. 2011, UN Habitat Nairobi.
5. Maddison, A., The world economy volume 1: A millennial perspective volume 2: Historical statistics. 2007: Academic Foundation.
6. Krausmann, F., et al., Growth in global materials use, GDP and population during the 20th century. Ecological Economics, 2009. 68(10): p. 2696-2705.
7. Costanza, R., L. Graumlich, and W.L. Steffen, Sustainability or collapse?: An integrated history and future of people on Earth. 2007: Mit Press.
8. UNEP, Industry and Environment Vol. 26 Nr.2-3. 2003. 9. Bruckner, M., et al., Materials embodied in international trade–Global material extraction and
consumption between 1995 and 2005. Global Environmental Change, 2012. 22(3): p. 568-576. 10. Rockström, J., et al., A safe operating space for humanity. Nature, 2009. 461(7263): p. 472-475. 11. Edenhofer, O., et al., IPCC, 2014: Climate Change 2014: Mitigation of Climate Change.
Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Transport, 2014.
12. O'Brien, K., et al., Toward a sustainable and resilient future. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC), 2012: p. 437-486.
13. OECD, A., Environmentally Sustainable Buildings, Challenges and Policies. 2003, OECD publications Service, Paris, France.
14. UNESCAP, U., State of the Asian Cities Report 2011. 2011, UN Habitat, UN ESCAP: Bangkok. 15. Asif, M., Sustainability of timber, wood and bamboo in construction. 2009: p. 31-54. 16. Flander, K.D. and R. Rovers, One laminated bamboo-frame house per hectare per year.
Construction and Building Materials, 2009. 23(1): p. 210-218. 17. Murphy, R.J., D. Trujillo, and X. Londoño. Life Cycle Assessment (LCA) of a Guadua House.
in International Symposium of bamboo -- Guadua. 2004. Pereira, Colombia. 18. Van der Lugt, P., A. Van den Dobbelsteen, and J. Janssen, An environmental, economic and
practical assessment of bamboo as a building material for supporting structures. Construction and Building Materials, 2006. 20(9): p. 648-656.
19. Villegas, M., New bamboo architecture and design. First edition ed. 2003, Bogota, Colombia.: Villegas Editores.
20. Archila-Santos, H.F., M.P. Ansell, and P. Walker, Low Carbon Construction Using Guadua Bamboo in Colombia. Key Engineering Materials, 2012. 517: p. 127-134.
21. Tran, V.H., Growth and quality of indigenous bamboo species in the mountaineous regions of Northern Vietnam, in Faculty of Forest Science and Forest Ecology. 2010, Georg-August-Universität Göttingen: Göttingen.
22. Londoño, X., Evaluation of bamboo resources in Latin America. A Summary of the Final Report of Project, 1998(96-8300): p. 01-4.
23. Lu, F., China’s bamboo product trade: performance and prospects [M]. Beijing: INBAR, 2001. 24. Lobovikov, M., et al., World bamboo resources A thematic study prepared in the framework of
the Global Forest Resources Assessment 2005, in Non-wood forest products. 2007, Food & Agriculture Org.: Rome.
25. Yuming, Y. and H. Chaomao, China's bamboo culture/resources/cultivation/utilization, in Technical report I.N.f.B.a.R. (INBAR), Editor. 2010: Bamboo and Rattan Research Institute, China Southwest Forestry University, Kunming, Yunnan, P.R. China, 650224. p. 148 - 206.
26. Yang, Y. and C. Hui, China's Bamboo, culture, resources, cultivation, utilization. 2010, International Network for Bamboo and Rattan.
27. Lakkad, S.C. and J.M. Patel, Mechanical properties of bamboo, a natural composite. Fibre Science and Technology, 1981. 14(4): p. 319-322.
28. Liese, W., The anatomy of bamboo culms. Vol. 18. 1998: Brill. 29. Archila, H.F., C.P. Takeuchi, and D.J. Trujillo, MECHANICAL AND PHYSICAL
CHARACTERIZATION OF COMPOSITE BAMBOO-GUADUA PRODUCTS: PLASTIGUADUA.
30. De Flander, K. and R. Rovers, One laminated bamboo-frame house per hectare per year. Construction and Building Materials, 2009. 23(1): p. 210-218.
33
31. López Muñoz, L.F. and J.F.J. Correal, Exploratory Study Of The Glued Laminated Bamboo Guadua Angustifolia As A Structural Material. Maderas ciencia y tecnología, 2009. 11(3): p. 171-182.
32. Archila, H.A., et al. Evaluation of the mechanical properties of cross laminated bamboo panels by digital image correlation and finite element modelling. in World Conference on Timber Engineering (WCTE) 2014. 2015. University of Bath.
33. Zea Escamilla, E., Design and application of laminated bamboo elements in frame construction and mechanical properties of laminated bamboo, in Chair of Urban Environmental Management. 2008, Wageningen University: Wageningen, NL.
34. Xiao, Y. Development of Prefabricated bamboo Earthquake Relief Shelter. in International conferece of modern bamboo structures. 2009. Bogotá, Colombia: Universidad de los Andes.
35. Lopez Muñoz, L.F. and M. Silva, Seismic behaviour of bahareque structures, in Faculty of Architecture and Civil Engineer. 2000, National University of Colombia, Manizalez: Manizalez, Colombia.
36. Wallbaum, H., et al., Indicator based sustainability assessment tool for affordable housing construction technologies. Ecological Indicators, 2012.
37. AIS, Colombian code for seismic design and construction, NSR-98. 2004, Seismic Engineering Colombian Association: Bogotá, Colombia.
38. van Uffelen, C., Bamboo : architecture & design. 2014, Salenstein, Switzerland: Braun Publishing
39. von Vegesack, A., et al., Design with nature : die Bambusbauten = the bamboo architecture. 2011, Shenyang, China: Liaoning Publishinghouse
40. Bauman, H. and A. Tillman, The Hitch Hiker's Guide to LCA. 2004: Studentlitteratur AB. 41. Bauman, H. and A. Tillman, The hitch hiker's guide to LCA: an orientation in life cycle
assessment methodology and application. 2004, Lund. Sweden: Studentlitteratur. 42. Hellweg, S. and L. Mila i Canals, Emerging approaches, challenges and opportunities in life
cycle assessment. Science, 2014. 344(6188): p. 1109-13. 43. ISO, ISO 14040: environmental management- life cycle assessment- principles and framework,
ed. ISO. 2007, Geneva, Switzerland: International Organization for Standardization. 44. Wang, E. and Z. Shen, A hybrid Data Quality Indicator and statistical method for improving
uncertainty analysis in LCA of complex system – application to the whole-building embodied energy analysis. Journal of Cleaner Production, 2013. 43(0): p. 166-173.
45. Angelakoglou, K. and G. Gaidajis, A review of methods contributing to the assessment of the environmental sustainability of industrial systems. Journal of Cleaner Production, 2015.
46. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part I: goals and scope and inventory analysis. International Journal of Life Cycle Assessment, 2008. 13: p. 290-300.
47. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part II: impact assessment and interpretation. International Journal of Life Cycle Assessment, 2008. 13: p. 374-388.
48. Kim, S., T. Hwang, and K.M. Lee, Allocation for cascade recycling system. International Journal of Life Cycle Assessment, 1997. 2: p. 217-222.
49. Dubreuil, A., et al., Metals recycling maps and allocation procedures in life cycle assessment. International Journal of Life Cycle Assessment, 2010. 15: p. 621-634.
50. Frischknecht, R., LCI modelling approaches applied on recycling of materials in view of environmental sustainability, risk perception and eco-efficiency. International Journal of Life Cycle Assessment, 2010. 15: p. 666-671.
51. Gomes, F., et al., Adaptation of environmental data to national and sectorial context: application for reinforcing steel sold on the French market. International Journal of Life Cycle Assessment, 2013. 18: p. 926-938.
52. Langevin, B., C. Basset-Mens, and L. Lardon, Inclusion of the variability of diffuse pollutions in LCA for agriculture: the case of slurry application techniques. Journal of Cleaner Production, 2010. 18: p. 747-755.
53. Fava, J.A., Will the next 10 years be as productive in advancing life cycle approaches as the last 15 years? International Journal of Life Cycle Assessment, 2006. 11: p. 6-8.
34
54. John, V. and H. Wallbaum. Statistical cluster analysis as a means to complement LCA of buildings. in Life-Cycle and Sustainability of Civil Infrastructure Systems: Proceedings of the Third International Symposium on Life-Cycle Civil Engineering (IALCCE'12), Vienna, Austria, October 3-6, 2012. 2012. CRC Press.
55. John, V. and G. Habert, Where is the embodied CO2 of buildings mainly located? Analysis of different types of construction and various views of the results. 2014.
56. Vogtländer, J.G., N.M. van der Velden, and P. van der Lugt, Carbon sequestration in LCA, a proposal for a new approach based on the global carbon cycle; cases on wood and on bamboo. The International Journal of Life Cycle Assessment, 2013: p. 1-11.
57. Fries, N. and S. Hellweg, LCA of land-based freight transportation: facilitating practical application and including accidents in LCIA. International Journal of Life Cycle Assessment, 2014. 19(3): p. 546-557.
58. Basbagill, J., et al., Application of life-cycle assessment to early stage building design for reduced embodied environmental impacts. Building and Environment, 2013. 60(0): p. 81-92.
59. Heeren, N., et al., Environmental Impact of Buildings・ What Matters? Environmental science & technology, 2015. 49(16): p. 9832-9841.
60. SCLCI. EcoInvent Database. 2011; Available from: http://www.ecoinvent.org. 61. EPLCA. European Life Cycle Database. 2015 [cited 2015; Available from:
http://eplca.jrc.ec.europa.eu/.
35
Chapter 2: LCA data for conventional and alternative
construction materials
36
37
2. LCA data for conventional and alternative construction materials
Summary LCA is confronted with a number of challenges. One of the most important is the availability of data
able to represent production practices outside the European context. Data is the basic requirement to
carry out an LCA and therefore it was considered as priority. When the research project on this field
was started in 2012, the main LCA database EcoInvent 2.7 included only a few datasets outside the
European context but none of them for the case of construction materials. With the advent of EcoInvent
3 and its subsequent releases a new approach was used. In EcoInvent 3, country specific datasets can be
used to generate regional or global datasets. This is a step forward but it heavily relies on the availability
of country specific datasets. This means that if only the datasets for concrete production for Germany
and Switzerland are available the European regional average will be created based on those two sets and
the same will occur with the global average. This average might be quiet different than the production
efficiencies found on other countries. Thus, a need for a cost-effective approach for LCA data generation
still remained. The ISO 14040 standard clearly describes the procedure for LCA data generation, but
experiences on the field had shown that a major economic and human talent investment are required to
produce country specific dataset. Moreover, this kind of development requires engagement from
different companies that not always able to share their data, due to IP issues or the amount of time that
the data collection requires. This problem is incremented when looking at alternative construction
materials due to its inherent variability of production practices and lack financial capacity for this kind
of endeavours.
This research project was faced with a very complex landscape, where a highly variable production
practices of an industry with not enough capital means to produce LCA data with global and local
validity. Furthermore, this problem needed to be approached with simple solutions that would enable
other practitioners or companies to develop their own LCA datasets in a cost-effective way.
The environmental impacts from the use of bamboo as construction material had been the topic of
several research projects. They were all faced with the same challenges and provided different
approaches to solve it. For this research project Bamboo based construction materials presented a prime
example of high variability, but it was clear that this variability had its limits. It was proposed that the
upper and lower limits for the input values could be used to create a triangular distribution. Thus,
providing with results within a range of variability and known uncertainty.
The case of bamboo based construction materials presented a complex challenge. First, each bamboo
specie has a different yearly yield due to their morphology, this can be further affected by environmental
conditions and production practices. All this factors in return also affect the land required for the
production of the bamboo as raw material. Second, the production practices of bamboo based
construction materials differ significantly from one company to the other and are not completely linked
38
to the geography where they are used, contrary to what would be observed in industries like cement or
brick.
The main objective of this research was to develop a cost-effective methodology to generate LCA data
of bamboo based construction materials. This methodology was based on the principle that the
variability on the inputs can represent the worldwide production practices. The contribution from the
inputs to the variability of the results was studied in order to highlight those process with the highest
contributions to the environmental impact and the variability of the results. The results showed that the
level of industrialization can be directly linked to the level of environmental impacts. Furthermore, for
the case of bamboo based construction materials the electricity mix used on their production and the
transport distances play a major role on the variability of the results. On the first stage the LCA data for
bamboo was produced but if a comparative LCA was needed the data for conventional construction
materials was still missing or have different level of detail. A master research project was carried out by
Alex Balzanini and supervised by Prof.Dr. Guillaume Habert and Edwin Zea Escamilla. On this project
LCA data for conventional construction materials like concrete, concrete hollow blocks, bricks, and
alternative construction materials like soil stabilized bricks and ferro-cement panels were generated
applying the same methodology as the one used for bamboo based construction materials. The results
from this project showed that there is less variability on the inputs of these construction materials. In the
case of those materials that contain cement, the main contributor to the variability of the results was the
clinker and the electricity mix and energy source used for its production. Furthermore, they showed that
the transport distances can significantly contribute to the environmental impact.
With these two research projects it was possible to develop a set of LCA data for conventional and
alternative construction materials that were able to represent the global range of production practices.
Moreover, the variability of the results and the main processes contributing to it were identified. These
results were satisfactory but the process of adapting the data sets to specific locations worldwide was
still time consuming and in the case of the transport distances of construction materials there was no
consistent approach to estimate these distances. Moreover, it was considered that the data alone would
solve the main challenge only partially and that a methodology to characterize the data and estimate the
potential transport distances was still needed. Furthermore, it was necessary to understand what were
the limitations to the proposed methodology for data generation and under which conditions the
produced data could be considered as valid.
39
Introduction to the chapter This chapters introduces the topic of generation of Life Cycle Assessment data for conventional and
alternative construction materials with global validity. This chapter is thematically divided on two major
sections, the first describes the methodological approach to generate LCA data outside the European
context and presents an example for its application on bamboo based construction materials. The second
section presents the results from the work of Alex Bazanini whom supervised by Prof.Dr. Guillaume
Habert and Edwin Zea Escamilla applied the methodology to mineral based construction materials both
conventional and alternative.
The first section will introduce the necessity of a cost effective method to generate LCA data with global
validity and the challenges faced on this process. Furthermore, it will describe the potentials that bamboo
withholds as a construction material and describes five bamboo based construction materials. This
section continues with a description of LCA and its application on the assessment of whole life impacts
of buildings. Moreover, it will present a series of practical and methodological challenges faced when
using LCA and specifically those related to the application of LCA on buildings. It will also present an
overview of the different approaches used to assess the life cycle of bamboo based construction
materials.
After this introduction, the proposed method for data generation will be described. First, the functional
units for each bamboo based construction materials and the boundaries to the studied system will be
described. Furthermore, the data used on the methodology is presented showing the variability of input
and the different sources where the data was obtained. This part closes with a description of the
environmental impact evaluation method selected to test the method and a brief description of the set up
for the uncertainty analysis of the application’s results.
The section continues presenting the results from the application of the proposed method on bamboo
based construction materials. These results present a first view of the environmental impact from the
production of bamboo based construction materials and how the different process contribute to this
impact. Furthermore, the contribution from production process to the variability and uncertainty of the
results are presented. This section finishes by discussing the results considering the most sensitive
premises of the method and proposing a series of key parameters for the development of simplified LCA
of bamboo based construction materials.
40
41
Environmental impacts from the production of bamboo based construction materials
representing the global production diversity
Journal of Cleaner Production 69 (2014) 117e127
2.1. Environmental impacts from the production of bamboo based construction materials representing the global production diversity
The construction industry has been recognised as one of the major consumers of resources and energy
and as being responsible for a large proportion of the waste produced worldwide [1, 2]. These three
topics are already of major concern, but if they are considered in light of the staggering urbanisation
process of the last few decades, during which more than 50% of the human population has become urban
[3], it becomes clear that the need for purpose-specific, high-performance construction materials is more
urgent than ever. Moreover, the high levels of CO2 emission coming from the production of
construction materials represents a problem on the global scale [4]. On this respect bio-based
construction materials have an advantage of being not only renewable but also able to sequester CO2
during their growth [5, 6], as well as store it during their use phase. Bamboo can be considered among
the most important bio-based construction materials. However, bio-based materials bring also
challenges for their application. One of the most important is the variability in their growth and yield,
which makes it difficult to accurately estimate their environmental benefits and impacts. This study
focuses on the calculation of the environmental impact associated with the production and use of
bamboo-based construction materials.
Furthermore, it aims to generate data on environmental impact of bamboo based construction materials
representing the global production diversity of these materials. The study provides mean values and
standard deviations for each bamboo-based material and identifies the processes with the greatest
influence on the results, which allows for the identification of those processes requiring additional data
collection.
2.2. Literature review This literature review contains three main components. First, bamboo is introduced, and the potential
for its use as construction material is described. Then, the methodological challenges of Life Cycle
Assessment are presented, emphasizing those challenges related to data quality and uncertainty. Finally,
the state of the art concerning the application of LCA to bamboo-based construction is presented.
2.2.1. Bamboo as a construction material Bamboo is a gigantic grass and is the only tribe in the grass family to successfully adapt to life in the
forest [7]. Bamboo grows naturally in Africa, Asia, America and Oceania, and more than 1200 bamboo
species have been catalogued [8]. A common feature among these species is their rapid growth, which
can reach up to 25 cm per day. Of the 1200 species, approximately 20 are considered suitable for
construction purposes [9]. The most important of these are Moso bamboo (Phyllostachys pubescens),
Guadua (Guadua angustifolia Kunth), and Dendrocalamus asper. These species are considered giants
42
among bamboos. Their culms have a diameter of between 10 and 18 cm, and their height ranges from
12 to 20 m. These features vary from one species to another and with the ecology of their growth site.
Due to their great strength, flexibility, and versatility, the culms of bamboo have been widely used for
housing and other construction purposes. The following five bamboo-based construction materials were
identified (ordered from the least to most industrialised material): bamboo pole, flattened bamboo,
woven bamboo mat, glue-laminated bamboo, and laminated woven bamboo mat panel. In countries such
as Colombia, Ecuador, and Peru, where a tradition of building with bamboo exists [9], these materials
have been integrated into engineered constructive systems thanks to extensive research on the
mechanical behaviour of bamboo-concrete composites[10]; glue laminated bamboo [11] and load
bearing wall systems [9, 12]. Building codes for the bamboo used in construction have been available
in Colombia since 2011 [13] and have been more recently introduced in Peru and Ecuador. The
following two general constructive systems are defined in these codes: spatial structures and load-
bearing walls.
The spatial structure system is mainly used in roofs, pavilions, and bridges. This system is used in the
construction of lightweight structures able to cover large spans, as can be seen in figure 2.1. The load-
bearing wall system consists of frames made out of bamboo poles and is mainly used for houses. The
poles are covered with flattened bamboo and then plastered with soil-cement plaster. Figure 2.2 shows
an example of this type of constructive system, which can be used in a wide range of building styles. A
focus on the five aforementioned bamboo based construction materials enables the calculation of the
environmental impact of most buildings in which bamboo in their structure.
Figure 2.1 Example of a spatial structure. Bamboo Bridge in Bogotá, Colombia. Sce: L.F. Lopez
43
2.2.2. Life cycle assessment methodological challenges To calculate the environmental impact of these five bamboo products, Life Cycle Assessment (LCA)
was used. This assessment method was developed to quantify the material use, energy use, and
environmental impact associated with specific products, services, and technologies. LCA is described
and standardised in ISO1440 [14] and consists of four steps: the definition of goal and scope, the
development of life cycle inventories, impact assessment, and interpretation. LCA is an iterative process
in which the goal and scope are constantly adjusted depending on the data collection limitations and the
insights provided by the impact assessment [15]. The term "environmental impact" is used in LCA to
refer to the effects of the studied system on the environment. These impacts depend directly on the
evaluation method used during the impact assessment step. LCA has been applied in the construction
sector for more than 20 years [16]. Among the difficulties involved in providing accurate environmental
assessments, such as allocation [17, 18], end-of-life scenarios [19, 20], and system boundaries [21], the
quality of the data used all along the supply chain remains a major topic [22, 23]. Indeed, an industrial
material and the data available concerning that material are the result of many different processes. For
instance, the quality of cement data is dependent on the quality of the assessment made for the extraction
and refinement of fuels [24], a process occurring geographically and technologically far removed from
the cement industry.
In LCA, it is common to distinguish foreground data derived directly from the studied process, which
are technical data related to the amount of material and energy used during the specific process, from
background data, which are related to all the upstream processes [25]. The quality of background data
Figure 2.2 Example of a load-bearing structure. Bamboo house in Ibague, Colombia
44
is difficult and expensive to assess because the data are linked to processes far removed from the
evaluated product. The strategy developed for the EcoInvent database, which involves assessing the
quality of the data through a pedigree matrix, enables the definition of a quantified standard deviation
based on different qualitative assessments [26, 27]. In the construction sector, this strategy has been
used recently with a different tool to provide a usable confidence index for the data [28]. The main focus
in the construction sector is to reduce uncertainty only for those materials that make a large contribution
to the overall environmental impact of a building and for which the uncertainty is significant [29]. For
this reason, Heijungs [30] introduced the concepts of uncertainty and contribution as two parameters to
categorise life cycle inventory data. In the case of industrialised materials, the foreground data is derived
from a standardised process that may be similar in different industrial plants. Thus, the low quality of
background data can be ignored. As a result, assessing the environmental impact of one cement plant
enables generalisation, with a high level of confidence, concerning the environmental impact of a cement
bag produced in another plant, as long as the plants operate under the same processes [31, 32], even if
changes in environmental impact due to intrinsic variability in the processes cannot be avoided [24, 33].
For low-industrialised materials, such as bamboo, which are often produced in rural communities with
low quality control, the potential variability of data is significant. Previous studies of low industrialised
products have highlighted this point for brick or concrete block production [34-36]. Moreover, all bio-
based products have an intrinsic product variability [37, 38]. The environmental assessment of bamboo
products combines the challenges of data quality and high data variability. Therefore, the
methodological approaches used for an environmental assessment must deal with these challenges while
also being easy to apply in different contexts.
2.2.3. LCA of bamboo-based construction materials LCAs of non-load-bearing, Bamboo-Based Construction Materials (BBCM), such as flooring [39] and
load-bearing materials in the study of bamboo based houses [40, 41]; supporting structures [42, 43];
concrete-bamboo composite beams [44] and load bearing bamboo walls [45] have been conducted. All
of these studies reported the potential of bamboo for use in the construction sector. However, none of
these studies addressed the problem of results variability and the uncertainty related to the production
of BBCM. This omission can be justified because most of the studies focused on industrial-quality
products, whose variability is, a priori, lower. However, the studies also often focused on only one
bamboo species [43, 46].
2.3. Data and methods In this section, the data collection for the different steps in the life cycle assessment of the materials and
the methodologies for the sensitivity and uncertainty analysis are presented.
2.3.1. Functional unit and system boundaries The goal of this LCA is to evaluate the environmental impacts related to the production of bamboo-
based construction materials considering the need for values with global representativeness and
45
applicability. This LCA was limited to five BBCM: bamboo pole, flattened bamboo, woven bamboo
mat, glue-laminated bamboo, and woven bamboo mat panel. The results can be used to assess all
bamboo-based constructive systems. The functional unit is defined as 1 m3 of material. The decision to
use 1 m3 is based on experience with the development of LCA data for wood products for the EcoInvent
database [47]. Bamboo and wood present similar methodological challenges for their LCA modelling,
as they both experience a loss of mass throughout their processing. This loss is mainly caused by the
drying process of these bio-based materials. The basic properties of the functional units of the studied
materials are described in table 2-1. The detailed calculation of these functional units can be found on
the Annex B.
Table 2-1 Functional units studied
Products Functional
unit Density (kg.m-3)
Resin content (wt%)
Low
in
du
stri
aliz
edp
rodu
cts
Bamboo pole 1m3 100 0
Flattened bamboo 1m3 176.8 0
Woven bamboo mat 1m3 178.2 0
Hig
hly
in
du
stri
aliz
ed
pro
duct
s
Woven bamboo mat panel 1m3 723.9 ~ 6.5
Glue laminated bamboo 1m3 885.4 ~ 5
2.3.2. Inventory data The conceptual framework for the development of life cycle inventories is presented in figure 2.3. Note
that each material interacts with the environment in several ways. First, each has a flow towards the
environment that represents the flow of by-products and emissions. Second, each material has a flow
towards the built environment where it can be used for construction. Finally, a material can also serve
as a resource for a more complex construction material.
46
Figure 2.3 Conceptual framework Showing the relationship between the different bamboo-based construction materials, the environment and the built environment
The Life Cycle Inventory (LCI) data were collected through literature review and interviews with
experts. The focus of data collection was on the material, energy, and transport inputs needed to produce
the functional unit. The infrastructure was also considered, representing the machinery and buildings
that are used for the production of each material [48]. With regard to transport, the common calculation
used in EcoInvent was modified because bamboo is a lightweight material. The usual method of
transport calculation is to divide the truck consumption per km by the weight of material that can be
transported to produce an environmental load per ton and km. Because of the light weight of bamboo,
the truck is full before reaching its maximum load capacity. Therefore, it is needed to divide the truck’s
consumption by a smaller maximum weight, leading to a higher impact per mass transported. In this
study, a 16-t lorry from EcoInvent was considered, which has a useful weight capacity of 9.5 tons. The
maximum volume capacity of the lorry is approximately 25 m3. Consequently, when fully loaded with
bamboo poles, the lorry will carry 2.5 tons because 1m3 of bamboo poles has a density of 100 kg/m3
(see table 2-1). This tonnage is 3.8 times less than the weight capacity modelled in EcoInvent. Therefore,
the input value for transport was calculated by multiplying the mass of bamboo transported by the
distance by the correction factor.
47
In the following section, the LCIs for the production of bamboo-based construction materials are
presented, ranging from the least to the most industrialised material. Each table presents three production
scenarios: the best-case, worst-case, and mean.
Although bamboo culm is not itself considered a construction material, the culm is the main input for
all the materials being assessed; thus, its LCI is presented in table 2-2. Each species of bamboo yields
different numbers of culms per year. This number can be influenced by fertiliser use and natural
events[49]. The culms can be extracted manually or using a chainsaw but lack a direct application as a
construction material because their high water content, approximately 40%, and when untreated their
service life is approximately three years [5, 50]
Table 2-2 : LCI of bamboo culm
Products Unit Mean Lower limit Higher limit Source
Bamboo culm, m3 1
Biomass (branches and leaves) m3 0.5
Occupation, forest m2a 18.5 6 31 [a, b, c, d, e, f]
Transformation, to forest m2 18.5 6 31 [a, b, c, d, e, f]
Bamboo standing at forest m3 1.5 1.33 1.66 [a, b, c, d, e, f]
Transformation, from pasture and meadow m
2 18.5 6 31 [a, b, c, d, e, f]
Urea, as N, at regional storehouse kg 0.7 0 1.4 [g]
Potassium chloride, as K2O, kg 0.23 0 0.47 [g]
Single superphosphate, as P2O5 kg 0.7 0 1.4 [g]
Diesel, low-sulphur, kg 0.1 0.07 0.14 [a, b, c, d, e, f]
Power saw, with catalytic converter min 7.65 5 10 [a, b, c, d, e, f]
aDe Flander and Rovers, 2009; bRiaño et al., 2002; cSalzer, 2011; dYang and Hui, 2010; eZea Escamilla et al., 2013; fZea Escamilla and Wallbaum, 2011; gLiu et al., 2011.
Mat
eria
ls /
fuel
s
Fert
ilize
rC
uttin
g
Functional unit
By-product
Res
ourc
es
Lan
d us
e
48
Figure 2.4 Bamboo-based construction materials
a) Bamboo poles b) Flattened bamboo. c) Woven bamboo mat. e) Glue laminated bamboo. e) Woven bamboo mat panels. Sce:
Authors
Table 2-3 shows the LCI for bamboo pole, the first BBCM studied (figure 2.4a). The pole is derived
directly from the bamboo culm and is usually trimmed to between 4 and 6 m and treated against fungi
and pests using boric acid before the water content is reduced by drying to approximately 20%. The
poles are then transported from the treatment plant either to a distributor or to an intermediate processing
facility. This transport is generally local, with a range of between 4 and 120 km. For this material, natural
49
gas was considered the fuel used for the drying process. Bamboo poles can be used directly for the
construction of columns, beams, or struts and are also the main input for other BBCM [39, 42].
Table 2-3 LCI of bamboo pole
aMurphy, et al., 2004; bSalzer, 2011; cvan der Lugt, et al., 2009; dVogtländer, et al., 2010; eZea
Escamilla, et al., 2013
The LCI of flattened bamboo (figure 2.4b), a handcrafted construction material, is shown in table 2-4.
To produce flattened bamboo, a bamboo pole is cracked open and its internodes are removed. The
innermost part of the bamboo is then trimmed down. During this process, some fibres are broken,
rendering the material flexible but still able to maintain its shape. The main application of flattened
bamboo is in load-bearing wall systems, where it is used between bamboo poles to support the soil-
cement mortar with which the walls are plastered [40, 45]
Table 2-4 LCI of flattened bamboo
aMurphy, et al., 2004; bSalzer, 2011; c Zea Escamilla, et al., 2013
To produce woven bamboo mats, a bamboo pole is first flattened and then divided into strips with widths
between 2 and 4 cm. These strips are then peeled into 1- to 2-mm-thick veneers, which are then woven
to form a mat. The entire process is manual and is typically performed in small, rural communities. The
woven bamboo mats are usually used as lightweight walls but have also recently been used for
industrially produced panels [51]. As both flattened bamboo and woven bamboo mats are commonly
Products Unit Mean Lower limit Higher limit Source
Bamboo pole m3 1
Biomass (bamboo trims and sawdust) m3 0.18
Bamboo culm m3 1.18 1.12 1.24 [7, 37, 38, 40, 41]
Electricity, production mix CN kWh 30 23 37 [7, 37, 38, 40, 41]
Sawmill parts 6.69 10‐7 5.45E‐07 7.92E‐07 [7, 37, 38, 40, 41]
Boric acid, anhydrous, powder kg 19 11 27 [7, 37, 38, 40, 41]
Air compressor (screw‐type, 300 kW) parts 4.64E‐04 4.64E‐04 4.64E‐04 [7, 37, 38, 40, 41]
Heat, natural gas, at industrial furnace
>100kWMJ 861 795 927 [7, 37, 38, 40, 41]
Wood drying infrastructure parts 6.09E‐05 6.09E‐05 6.09E‐05 [7, 37, 38, 40, 41]
Transport
Lorry >16t, fleet average ton*km 21.55 1.44 43.09 [7, 37, 38, 40, 41]
Functional unit
By‐product
Materials / fuels
Trimming
Treatm
ent
Drying
Products Unit Mean Lower limit Higher limit Source
Flattened bamboo m3 1
Biomass (bamboo trims) m3 0.15
Bamboo pole m3 2.04 2 2.09 [a, b, c]
Functional unit
By‐product
Materials
/ fuels
50
manufactured in facilities extremely close to the point of extraction and/or treatment, no transport is
included in the inventory. The LCI for the production of woven bamboo mats (figure 2.4c) is shown in
table 2-5.
Table 2-5 LCI of woven bamboo mat
aMurphy, et al., 2004; bSalzer, 2011; cZea Escamilla, et al., 2013 Glue-laminated bamboo (figure 2.4d) has been produced for more than 60 years and is mainly used for
flooring and furniture. Recently, this product has also been used in structural applications [11, 52]. Glue-
laminated bamboo is composed of bamboo slats and a bonding agent. Bamboo poles are split, trimmed,
and then planned to produce the slats, which vary in shape and size depending on the production and
application of the material. The slats are glued, placed in a mould, and hot-pressed to form the laminate
(table 2-6) [39, 50].
Table 2-6 LCI of glue laminated bamboo
aDe Flander and Rovers, 2009; bSalzer, 2011; cvan der Lugt, et al., 2009; dVogtländer, et al., 2010
Woven bamboo mat panel (figure 2.4e), is currently used as an alternative to plywood, this product has
also shown promise in structural applications [51]. Woven bamboo mat panels are produced in a fashion
similar to that of glue-laminated bamboo. In this process, woven bamboo mats are layered and glued
together with a bonding agent and then hot-pressed to cure the composite material (table 2-7) [41]. Both
glue-laminated bamboo and woven bamboo mat panels are usually transported from the factory to
retailers or distributors. These transport distances can vary between 0 and 600 km.
Products Unit Mean Lower limit Higher limit Source
Bamboo mats m3 1
Biomass (bamboo trims) m3 0.075
Flattened bamboo m3 1.075 1.05 1.1 [a, b, c]
Materials
/ fuels
Functional unit
By‐product
Products Unit Mean Lower limit Higher limit Source
Glue laminated bamboo m3 1
Glue laminated bamboo panel trims
and sawdustm
3 0.28
Bamboo culm m3 3.4 2.72 4.08 [a, b,c,d]
Electricity, production mix CN kWh 483.5 371 596 [a, b,c,d]
Sawmill parts 4.86E‐04 4.86E‐04 4.86E‐04 [a, b,c,d]
Urea formaldehyde resin kg 19.5 11 28 [a, b,c,d]
Electricity, production mix CN kWh [a, b,c,d]
Heat, natural gas, at boiler modulating
<100kWMJ 34.5 23 46 [a, b,c,d]
Wooden board manufacturing plant parts 3.33E‐08 3.33E‐08 3.33E‐08 [a, b,c,d]
Transport
Lorry >16t, fleet average ton*km 1140 0 2280 [a, b,c,d]
Functional unit
By‐product
Materials / fuels
Trimming
Gluing & pressing
51
Table 2-7 LCI of woven bamboo mat panel
aSalzer, 2011
2.3.3. Impact assessment Three main categories of impact assessment methods can be found in the literature: i) pressure-oriented
methods, such as CML [53] or EDIP [54, 55], which restrict quantitative modelling to relatively early
stages in the cause-effect chain to limit uncertainties; ii) damage-oriented methods, such as Eco-
indicator 99 [56, 57] or IMPACT 2002+ [58], which try to model the cause-effect chain up to the end
point or damage point, sometimes with high uncertainty; and iii) prevention-oriented methods, which
are often monetised and based on the marginal prevention costs of emissions, such as eco-costs [59, 60].
For clarity of the results, the damage-oriented IMPACT 2002+ v 2.1 method was used to reduce the
number of impact categories. In this method, four categories are considered: human health, assessed in
DALY; ecosystems quality, assessed in PDF.m2.yr; climate change, assessed in kg CO2; and resources,
assessed in MJ. The results are normalised with the factors 0.0071 DALY, 13,700 PDF.m2.yr, 9,950 kg
CO2, and 152,000 MJ for the respective impact categories. These factors represent the yearly emissions
of one European citizen. This normalisation allows the results to be expressed in “points”, with one
point equal to the yearly emission of one European citizen in one impact category. As a final step, the
results for the four impact categories were summed, considering an equal contribution for each category,
and presented as a single score value. All the LCA calculations were performed using the software
SIMApro v 7.33 [61] and the database EcoInvent [38].
2.3.4. Uncertainty analysis An environmental assessment necessitates several assumptions whose influence is difficult to fully
constrain. Moreover, background and foreground data have associated uncertainties, which appear
throughout the environmental assessment process [27]. In this study, the focus was on variability in the
main production process and efficiency. The uncertainty analysis was, restricted to the technological
Products Unit Mean Lower limit Higher limit Source
Woven bamboo mat panel m3 1 [a]
Bamboo panel trims and sawdust m3 0.27 [a]
Materials
Bamboo mats m3 0.8 0.7 0.9 [a]
Urea formaldehyde resin kg 21 12 30 [a]
Electricity, production mix CN kWh 258.2 185.4 331 [a]
Heat, natural gas, at boiler modulating
<100kWMJ 34.5 23 46 [a]
Wooden board manufacturing plant parts 3.33E‐08 3.33E‐08 3.33E‐08 [a]
Transport
Transport, lorry >16t, fleet average ton*km 1140 0 2280 [a]
Functional unit
By‐product
Materials / fuels
Gluing & pressing
52
foreground data. In the previous section, three scenarios were proposed: worst-case, best-case, and mean
scenarios. To perform an uncertainty analysis on the data from these scenarios, two approaches were
developed. In the first, the uncertainty of the result due to variability in the inputs between a worst-case
and best-case scenario was calculated, and the relative contribution of these inputs to the uncertainty
was evaluated. A Monte Carlo simulation was used in the first approach and 10,000 runs/iterations were
analysed, with a confidence interval of 99%. In the second approach, the contribution of each input to
the difference between the best-case and worst-case scenarios was calculated. The difference between
these scenarios was then calculated at a process level. These results were normalised to show the total
contribution of each impact to the variability.
2.4. Results The results of the LCAs of the five bamboo-based construction materials are presented. Note that the
research presented here is not a comparative LCA because the functional units are not associated with a
service.
2.4.1. Environmental impacts of the different bamboo products studied The results presented in table 2-8 show that the environmental impact of BBCM increases in relation to
the level of industrialisation required for their production. A significant difference in environmental
impact can be observed between the industrially fabricated and handcrafted materials. The
environmental impact of bamboo pole, is five times smaller than the impact associated with glue-
laminated bamboo. In the case of handcrafted materials, such as flattened bamboo and woven bamboo
mats, the environmental impact increases only because of the material demand associated with their
production. Table 2-8 also shows that for all the bamboo products, the normalised impact for ecosystem
quality is quite small compared with the other three impact categories, among which the remaining
impact is relatively equally shared.
Table 2-8 Environmental impacts for the production of bamboo-based construction materials
2.4.2. Process contribution to environmental impact To better understand the environmental impacts presented here, it is necessary to examine the relative
contribution of the different processes involved in a material’s production. As flattened bamboo and
woven bamboo are handcrafted from the bamboo pole, the processes responsible for their environmental
Human healthEcosystem
qualityClimate change Resources Total
Bamboo pole 1 m3 14.28 1.55 12.37 13.13 41.34
Flattened bamboo 1 m3 28.91 3.15 25.03 26.59 83.67
Bamboo mats 1 m3 31.08 3.38 26.91 28.58 89.95
Woven bamboo mat panel 1 m3 100.09 8.54 69.68 66.32 244.62
Glue laminated bamboo 1 m3 164.55 12.07 113.26 102.21 392.08
Environmental impact [mPt]Functional
UnitProduct
53
impact are the same. Therefore, the results for the low industrialised materials were combined in one
column, whereas the results for the highly industrialised materials were kept separated, as can be seen
in figure 2.5.
Figure 2.5 Relative process contribution to environmental impact for the production of BBCM in (%)
For the low industrialised materials, the contribution of the raw material production, which is the growth
of the bamboo culm, represents less than 10% of the total impact. The drying process is the major
contributor, with 35%, followed by the electricity used for trimming, at 25%, and the treatment for insect
resistance, with a 17% share of the total. The contribution associated with infrastructure and machinery
is much higher for the low- than for the high- industrialised materials, with contributions to the total
impact of 12 and 2%, respectively. Thus, for the low industrialised materials, using machines with long
service lives can more efficiently improve production than using new machinery.
However, the situation is different for the two industrialised materials: woven bamboo mat panel and
glue-laminated bamboo. Here, the contribution of infrastructure can be considered negligible. By
contrast, transport makes a more significant contribution to the environmental impact, amounting to
between 15 and 25%. However, the electricity used for cutting and pressing contributes the most to the
environmental impact of the industrial materials, with a share ranging from 40 to 50%. Finally, the
processes linked to the low industrialised materials that are then further considered as inputs for the
more industrialised materials have a combined contribution below 40%.
54
2.4.3. Uncertainty analysis The production of bamboo-based materials can vary depending on the bamboo species used and the
efficiency of the production processes. These factors induce a large potential variability, which was
identified in a sensitivity analysis. It is clear that the environmental impacts are higher for the
industrialised materials than for the handcrafted ones. This difference can be seen in figure 2.6 and it is
significant no matter the efficiency of production. Moreover, the range of results is greater for the
industrialised materials, which therefore have a higher potential to disperse the impacts. For the glue-
laminated bamboo, the results differ by a factor of 2, whereas the results differ by a factor closer to 1.5
for the low industrialised materials. By using the Monte Carlo simulation, the dispersion is greatly
reduced, and a mean value with a dispersion of ± 10% can be proposed.
Figure 2.6 Environmental impacts of the various bamboo-based construction materials. Impacts are calculated for the best- and worst-case scenarios as well as for a mean scenario with
uncertainty analysis (SD stands for Standard Deviation). The impacts are expressed in mPt
corresponding to the sum with equal contribution of the normalized impact categories of IMPACT
2002+
2.4.4. Process contribution to the variability of the results Note that on bamboo culm the variability derives mainly from the use of fertiliser and hardly from
differences in land use or yield per species (figure 2.7). Thus, a similar result is expected regardless of
the species of bamboo used. Furthermore, the cultivation and extraction practices lose their significance
once the study focuses on the more industrialised bamboo-based construction materials.
55
The other major observation is that the processes with a large contribution to the impact (see figure 2.5)
are not necessarily main contributors to the variability (figure 2.7). For example, the heating process for
bamboo pole contributes 35% of the impact but only 11% of the variability. By contrast, the treatment
process contributes 18% of the impact, but this process is the greatest contributor to the variability
(>30%). For the glue-laminated bamboo, the contribution to the variability of the bamboo pole is greater
than its contribution to the impacts (50% vs. 40%, respectively). Thus, increasing the efficiency of the
pressing process can reduce the environmental impact up to 15%. By contrast, the effect of a change in
the electricity mix can be much more significant.
Figure 2.7 Relative contribution of the different processes to the impact Variation between the best- and worst-case scenarios, for the five bamboo-based construction materials
in (%)
The results in figure 2.8 show the differences in environmental impact among glue-laminated bamboo
materials produced with the same efficiency but in different countries (Brazil, China, and Colombia).
Currently, nearly all bamboo-based construction materials are produced in China, although the industry
is also growing in South America and Southeast Asia. Note that a greater reduction in environmental
impact can be achieved by changing the electricity mix from that of China to that of Brazil than by
improving the efficiency of the production process itself. This result indicates that the choice of
electricity mix is much more important than ensuring a highly efficient production process.
56
Figure 2.8 Variation for glue laminated bamboo induced by a change in the electricity mix
2.5. Discussion In this study, different sources, ranging from reviewed literature to expert interviews, were used to
evaluate the environmental impact associated with the production of bamboo products employed in
construction. The data currently available in the literature is quite specific to each study and therefore
difficult to apply further in other LCA studies. The present research produced reliable LCA data for
materials characterised by a great diversity of biological, geographical, and industrial factors. Moreover,
the uncertainty produced by these factors was assessed and its source was determined. The following
section focuses on several areas that require additional attention.
2.5.1. Choice of impact assessment method IMPACT2002+ with normalised end-point indicators was used to generate a single score value using
equal weighting factors. This choice simplified the handling of the results and enabled an in-depth
evaluation of the process contributions. Clearly, dealing with more than one indicator, either because
we used mid-point indicators or end points without weighting, would have complicated the discussion
of the results and most likely increased the difficulty of drawing conclusions. This complexity is, by
definition, a drawback of LCAs that makes LCA difficult to use as a decision-making tool [62].
However, the approach of working with fewer indicators, while still achieving accurate results, is
gaining acceptance by experts within the LCA community. Switzerland developed a single indicator
that is now used at the federal level to support environmental decision-making [63]. In the construction
sector, LCAs are needed in the early stage of construction, when it is quite difficult to delineate a detailed
scenario, and recently, Lasvaux et al. [64] showed that for building materials, certain indicators are
correlated with one another and therefore provide similar information individually. Other studies [6, 65,
66] drew the same conclusion while identifying energy and land use as two main contributors to
57
environmental impact. For the research presented here, however, land use does not make a significant
contribution to environmental impact. Thus, it is reasonable to argue that a single score indicator offered
the best solution for this study.
2.5.2. Process efficiency and energy mix For the highly industrialised materials assessed, the contribution of electricity to the environmental
impact is significant. The electricity used for trimming and pressing contributes up to 50% of their
environmental impacts. A further 10% can be added from the trimming of the bamboo poles themselves
because the production of the bamboo pole represents 40% of the impact of the highly industrialised
materials, while electricity represents 25% of the impact of the bamboo pole production. Consequently,
60% of the impact of the production of glue-laminated bamboo can be linked with electricity use.
However, the potential reduction in environmental impact that can be achieved by improving the
efficiency of the production process is no greater than 45%; thus, a greater reduction in environmental
impact can be achieved by changing the electricity mix, i.e., by reducing the proportion produced using
coal power, than by improving the production efficiency itself. For example, glue-laminated bamboo
has the same environmental impact whether produced in Colombia using relatively inefficient processes
or in China with the highest efficiency possible (see figures 2.6 and 2.8). Furthermore, local transport
makes limited contribution to the environmental impact of bamboo-based construction materials due to
their light weight and short transportation distances. Moreover, the foreground inputs contribute the
most to the environmental impact of these materials. Therefore, it can be hypothesised that the best
environmental performance might be achieved by growing bamboo in China, where most of the
intensive production is located, and then processing the raw materials in a country with a more
diversified electricity supply or a decentralised renewable electricity source.
2.5.3. Key processes for a simplified bamboo LCA Bonilla et al. [46] identified the use of fertiliser and the burning of diesel fuel as key processes
contributing to the environmental impact of bamboo culms production. These processes were also
identified as key variables in the present research, but their level of contribution was quite different in
the two studies because of the different evaluation methods used, i.e., Emergy analysis in the previous
study and IMPACT 2002+ in the present study. Emergy is focused on energy-related processes and does
not consider the toxicity-related environmental impacts that the IMPACT2002+ method evaluates.
Consequently, the contribution of fossil energy greatly exceeds that of fertiliser in the work of Bonilla
et al. (2010), whereas in the present assessment, the use of fertiliser in the production of bamboo culm
is the main impact. Furthermore, labour represents more than 30% of the impact with Emergy, but labour
is not considered in the IMPACT2002+ method. A similar situation arises in the study by Van der Lugt
et al. [42], in which processing, treatment, and transport were identified as key contributing processes.
58
However, in addition to the different evaluation method used, these authors included the transoceanic
transport of the products to Europe on their models. By contrast, the present study modelled the bamboo-
based construction materials as locally produced and used. Nevertheless, the two studies agree on the
main contributors to the environmental impact. Vögtländer et al. [39] provide another quite similar case,
in which the key processes contributing to the impact are the same as those identified by the present
research. The main difference is again the evaluation method, with the 2010 study focusing on
monetization of the impacts and including transoceanic transport to Europe. The results from the present
research agree with the literature and additionally describe how the identified key processes contribute
to the variability of the results and their uncertainty.
One of the final goals of the present study was to produce accurate data for non-conventional materials,
in a cost-effective way. The results of this study suggest that a practitioner can use the mean values
provided with a deviation of ± 10%. However, this relatively satisfying result conceals the fact that
greater variations, up to factor two, might occur in some cases. Nevertheless, it is necessary to highlight
the inputs that are the main contributors to environmental impact and those critical for reducing the
variability of the results. To increase the accuracy of the results for handcrafted materials, special
attention must be given to the electricity mix and to the type of fuel used in the drying process. However,
to reduce the variability of the results, a practitioner should focus on the amount of boric acid used. For
the more industrialised materials, a practitioner should additionally establish the nature and amount of
electricity used for the production of these materials. Electricity plays a major role in both the accuracy
and the variability of the results, as presented in table 2-9.
Table 2-9 Main parameters that need to evaluate environmental impact and uncertainty
2.6. Conclusions and recommendations The present research focused on five bamboo-based construction materials. The objective was to provide
reliable data for highly variable construction materials that also have highly variable production
processes. The methodological approach proposed for this research consisted of an analysis of the
process contribution to the environmental impact with further variability and uncertainty analysis to
provide accurate data for LCAs of bamboo-based construction materials. With these data, LCA studies
of bamboo-based buildings and infrastructure can be conducted in the future. These studies can either
acknowledge the uncertainty associated with the materials being studied or attempt to reduce the
Low industrialised products high industrialised products
Gas (drying) Electricity (for the last process)
Electricity (trimming) and not the resin
+ amount of Boric acid
Main impact
Main
uncertainty
1st the nature of energy
and 2nd the amount
59
uncertainties by improving the data quality for the process that contributes the greatest environmental
impact, depending on their context.
It can be concluded that inputs related to the harvesting and transport of bamboo and the resin used in
the product have an extremely limited contribution to the environmental impact, whereas the nature and
amount of energy used in the production process are critical parameters. Furthermore, it is recommended
that future research focus on the effects that market demands, such as resource availability, electricity
and heat sources, and transportation, impose on the whole-life environmental impacts of these
construction materials. In conclusion, the proposed approach can be successfully used to assess the
environmental impact of non-conventional materials with a high degree of accuracy. This assessment
can facilitate the process of certification and the labelling of these materials, thus fostering their use in
construction and promoting the industry producing them.
2.7. Acknowledgements The authors of this paper would like to thank Hilti AG for its support of this research and for its
sponsorship.
2.8. References 1. UNEP, Industry and Environment Vol. 26 Nr.2-3. 2003. 2. Dutil, Y., D. Rousse, and G. Quesada, Review: Sustainable Buildings: An Ever Evolving Target.
Sustainability, 2011. 3: p. 443-464. 3. UNHabitat, State of the World´s Cities 2010/2011, U. Habitat, Editor. 2011, UN Habitat
Nairobi. 4. Tsai, W.-H., et al., Incorporating life cycle assessments into building project decision-making:
An energy consumption and CO2 emission perspective. Energy, 2011. 36(5): p. 3022-3029. 5. Riaño, N.M., et al., Plant growth and biomass distribution on Guadua angustifolia Kunth in
relation to ageing in the Valle del Cauca – Colombia. Bamboo Science and Culture, 2002. 16(1): p. 43-51.
6. Vogtländer, J.G., N.M. van der Velden, and P. van der Lugt, Carbon sequestration in LCA, a proposal for a new approach based on the global carbon cycle; cases on wood and on bamboo. The International Journal of Life Cycle Assessment, 2013: p. 1-11.
7. Villegas, M., New bamboo architecture and design. First edition ed. 2003, Bogota, Colombia.: Villegas Editores.
8. Yang, Y. and C. Hui, China's Bamboo, culture, resources, cultivation, utilization. 2010, International Network for Bamboo and Rattan.
9. Lopez Muñoz, L.F. and M. Silva, Seismic behaviour of bahareque structures, in Faculty of Architecture and Civil Engineer. 2000, National University of Colombia, Manizalez: Manizalez, Colombia.
10. Ghavami, K., Bamboo as reinforcement in structural concrete elements. Cement and Concrete Composites, 2005. 27(6): p. 637-649.
11. López Muñoz, L.F. and J.F.J. Correal, Exploratory Study Of The Glued Laminated Bamboo Guadua Angustifolia As A Structural Material. Maderas ciencia y tecnología, 2009. 11(3): p. 171-182.
12. Cardona, O., et al., Assessment manual for rehabilitation and reinforcement of traditional bahareque houses built before the building code 052 of 2002. 2002, Seismic engeniering colombian asociation - AIS: Bogotá, Colombia.
13. AIS, Colombian code for seismic design and construction, NSR-98. 2004, Seismic Engineering Colombian Association: Bogotá, Colombia.
60
14. ISO14040, Environmental Management- Life Cycle Assessment- Principles and Framework, ISO, Editor. 2007, ISO.
15. Bauman, H. and A. Tillman, The Hitch Hiker's Guide to LCA. 2004: Studentlitteratur AB. 16. Fava, J.A., Will the next 10 years be as productive in advancing life cycle approaches as the
last 15 years? International Journal of Life Cycle Assessment, 2006. 11: p. 6-8. 17. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part I: goals and scope
and inventory analysis. International Journal of Life Cycle Assessment, 2008. 13: p. 290-300. 18. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part II: impact
assessment and interpretation. International Journal of Life Cycle Assessment, 2008. 13: p. 374-388.
19. Kim, S., T. Hwang, and K.M. Lee, Allocation for cascade recycling system. International Journal of Life Cycle Assessment, 1997. 2: p. 217-222.
20. Dubreuil, A., et al., Metals recycling maps and allocation procedures in life cycle assessment. International Journal of Life Cycle Assessment, 2010. 15: p. 621-634.
21. Frischknecht, R., LCI modelling approaches applied on recycling of materials in view of environmental sustainability, risk perception and eco-efficiency. International Journal of Life Cycle Assessment, 2010. 15: p. 666-671.
22. Gomes, F., et al., Adaptation of environmental data to national and sectorial context: application for reinforcing steel sold on the French market. International Journal of Life Cycle Assessment, 2013. 18: p. 926-938.
23. Langevin, B., C. Basset-Mens, and L. Lardon, Inclusion of the variability of diffuse pollutions in LCA for agriculture: the case of slurry application techniques. Journal of Cleaner Production, 2010. 18: p. 747-755.
24. Chen, C., et al., Environmental impact of cement production: Detail of the different processes and cement plant variability evaluation. Journal of Cleaner Production, 2010. 18: p. 478-485.
25. Huijbregts, M.A.J., et al., Framework for Modelling Data Uncertainty in Life Cycle Inventories. International Journal of Life Cycle Assessment, 2001. 6: p. 127-132.
26. Huijbregts, M.A.J., LCA Methodology Application of Uncertainty and Variability in LCA. International Journal of Life Cycle Assessment, 1998. 3(5): p. 273 - 280.
27. Weidema, B.P. and M.S. Wesnaes, Data Quality Management for Life Cycle Inventories - An Example of Using Data Quality Indicators. Journal of Cleaner Production, 1996. 4: p. 167-174.
28. Tardivel, Y., G. Habert, and C. Teyssier, DIOGEN database of environmental impacts of materials for civil engineering works, in GC’11: Civil engeniering at service of the sustainable construction. 2011: Cachan, France.
29. Wang, E. and Z. Shen, A hybrid Data Quality Indicator and statistical method for improving uncertainty analysis in LCA of complex system – application to the whole-building embodied energy analysis. Journal of Cleaner Production, 2013. 43(0): p. 166-173.
30. Heijungs, R., Identification of key issues for further investigation in improving the reliability of LCA. Journal of Cleaner Production, 1996. 4(3-4): p. 159-166.
31. Gartner, E., Industrially interesting approaches to “low-CO2” cements. Cement and concrete research, 2004. 34: p. 1489–1498.
32. Bösch, M.E., et al., Applying Cumulative Energy Demand (CExD) Indicators to the ecoinvent Database. International Journal of Life Cycle Assessment, 2007. 12(3): p. 181-190.
33. von Bahr, B., et al., Experiences of environmental performance evaluation in the cement industry. Data quality of environmental performance indicators as a limiting factor for benchmarking and rating. Journal of Cleaner Production, 2003. 11: p. 713-725.
34. Ferraz de Campo, E. and V.M. John, CO2 emissions and residues of Amazon rainforest lumber – preliminary results, in International Symposium on LCA and construction. 2012: Nantes, France. p. 274- 282.
35. Cazaclui, B. and A. Ventura, Technical and environmental effects of concrete production: dry batch versus central mixed plant. Journal of Cleaner Production, 2010. 18: p. 1320-1327.
36. Gough, K.V., Self-help Housing in Urban Colombia; Alternatives for the Production and Distribution of Building Materials. HABITAT International, 1996. 20: p. 635-651.
37. Kellenberger, D., et al., Life Cycle Inventories of Building Products- Data v2.0 (2007). 2007, Swiss Centre for Life Cylce Inventories: Dübendorf.
61
38. SCLCI. EcoInvent Database. 2011; Available from: http://www.ecoinvent.org. 39. Vogtländer, J., P. van der Lugt, and H. Brezet, The sustainability of bamboo products for local
and Western European applications. LCAs and land-use. Journal of Cleaner Production, 2010. 18(13): p. 1260-1269.
40. Murphy, R.J., D. Trujillo, and X. Londoño. Life Cycle Assessment (LCA) of a Guadua House. in International Symposium of bamboo -- Guadua. 2004. Pereira, Colombia.
41. Salzer, C., A life cycle assessment for alternative building technologies. Construction methods for low income inhabitants in the Philipines, in D-BAUG. 2011, Swiss Federal Institute of technology: Zürich.
42. Van der Lugt, P., A. Van den Dobbelsteen, and J. Janssen, An environmental, economic and practical assessment of bamboo as a building material for supporting structures. Construction and Building Materials, 2006. 20(9): p. 648-656.
43. van der Lugt, P., J. Vogtländer, and H. Brezet, Bamboo- a sustainable solution for Western Europe, Design Cases, LCA and Land-Use. 2009, Delft: INBAR International Network For Bamboo and Rattan, Technical University Delft.
44. Zea Escamilla, E. and H. Wallbaum, Environmental savings from the use of vegetable fibres as concrete reinforcement, in 6th International Structural Engineering and Construction Conference. 2011, Research Publishing: Zürich, Switzerland. p. 1315 - 1320.
45. Zea Escamilla, E., G. Habert, and L. Lopez Muñoz, Environmental Savings Potential from the use of Bahareque(mortar cement plastered bamboo) in Switzerland, in International Conference of Non Conventional Materials NOCMAT13. 2013: Joao Pessoa, Brasil.
46. Bonilla, S.H., et al., Sustainability assessment of a giant bamboo plantation in Brazil: exploring the influence of labour, time and space. Journal of Cleaner Production, 2010. 18(1): p. 83-91.
47. Frischknecht, R. and G. Rebitzer, The ecoinvent database system: a comprehensive web-based LCA database. Journal of Cleaner Production, 2005. 13(13–14): p. 1337-1343.
48. Althaus, H.J., et al., Manufacturing and Disposal of Building Materials and Inventorying Infrastructure in ecoinvent. International Journal of Life Cycle Assessment, 2005. 10(1): p. 35 – 42.
49. Liu, J., et al., Seasonal soil CO2 efflux dynamics after land use change from a natural forest to Moso bamboo plantations in subtropical China. Forest Ecology and Management, 2011. 262(6): p. 1131-1137.
50. De Flander, K. and R. Rovers, One laminated bamboo-frame house per hectare per year. Construction and Building Materials, 2009. 23(1): p. 210-218.
51. Xiao, Y. Development of Prefabricated bamboo Earthquake Relief Shelter. in International conferece of modern bamboo structures. 2009. Bogotá, Colombia: Universidad de los Andes.
52. Wang, Z., et al. Application of Bamboo-based Engineered Materials in Construction. in International conference on modern bamboo structures. 2009. Bogotá, Colombia: Universidad de los Andes.
53. Guinée, J.B., et al., Life Cycle Assessment: An Operational Guide to the ISO Standards. . 2002, Kluwer Academic Publishers: Dordrecht.
54. Wenzel, H., M.Z. Hauschild, and L. Alting, Environmental Assessment of Products: Volume 1: Methodology, tools and case studies in product development. Vol. 1. 2000, Norwel, MA, USA: Springer.
55. Hauschild, M.Z. and L. Alting, Environmental assessment of products: Volume 2: Scientific background. Vol. 2. 1997: Springer.
56. Goedkoop, M., et al., ReCiPe 2008 - A life cycle impact assessment method which comprises harmonized category indicators at the midpoint and the endpoint level / Report I: Characterization, in Ministry of Environment. 2009: Den Haag, Netherlands.
57. Goedkoop, M. and R. Spriensma, The Eco-indicator 99, a damage oriented method for Life Cycle Impact Assessment, methodology report. 2001, PRé Consultants BV.
58. Jolliet, O., et al., IMPACT 2002+: A New Life Cycle Impact Assessment Methodology. International Journal of Life Cycle Assessment, 2003. 8(6): p. 324 - 330.
59. Vogtländer, J.G., A. Bijma, and H.C. Brezet, Communicating the eco-efficiency of products and services by means of the eco-costs/value model. Journal of Cleaner Production, 2002. 10(1): p. 57-67.
62
60. Vogtländer, J.G., H.C. Brezet, and C.F. Hendriks, The virtual eco-costs ‘99 A single LCA-based indicator for sustainability and the eco-costs-value ratio (EVR) model for economic allocation. The International Journal of Life Cycle Assessment, 2001. 6(3): p. 157-166.
61. Pre-Conultants. SIMA Pro v7.3.3. 2012; Available from: http://www.pre-sustainability.com/simapro-installation.
62. Krozer, J. and J.C. Vis, How to get LCA in the right direction? Journal of Cleaner Production, 1998. 6(1): p. 53-61.
63. Frischknecht, R., R. Steiner, and N. Jungbluth, The Ecological Scarcity Method Eco-Factors 2006, A method for impact assessment in LCA. 2009, Federal Office for the Environment (BAFU): Zürich, Swtizerland.
64. Lasvaux, S., et al., Towards a reduced set of indicators in buildings LCA applications : a statistical based method, in International symposium on LCA and construction. 2012: Nantes, France. p. 65-72.
65. Huijbregts, M.A.J., et al., Is Cumulative Fossil Energy Demand a Useful Indicator for the Environmental Performance of Products? . Environmental Science and Technology, 2006. 40: p. 641-648.
66. Huijbregts, M.A.J., et al., Ecological footprint accounting in the life cycle assessment of products. Ecological Economics, 2008. 64(4): p. 798-807.
63
Chapter 2 in a nutshell
A cost-effective methodology for the generation of LCA data was developed
The proposed methodology was used to produce LCA data of alternative and conventional
construction materials with global validity
The electricity mix was identified as the process with the highest contribution to the result of
bamboo based construction material, while the amount and type of cement was the highest
contributor for the mineral based construction materials
Transport distance was identifies as a main contributor to the variability and uncertainty of the
results for all construction materials
The LCA data generated with the proposed methodology is able to represent the range of
construction materials’ production practices found around the world.
64
65
Chapter 3: Methodology and application to characterize LCA
data of alternative and conventional construction materials
66
67
3. Methodology and application to characterize LCA data of
alternative and conventional construction materials
Summary This research project was a continuation and expansion of the project presented on chapter 2. When the
data generation project was finished a new question aroused: how to modify the LCA datasets to make
them represent country specific conditions on a cost effective way. This question had two major
component how to integrate the different electricity mixes on the calculations and how to estimate the
potential transport distances of construction materials. It was proposed that an integration of LCA data
and geographic data could provide a suitable solution for this questions. The present research uses the
LCA data generated on the previous project, which shows the range of variation on which the production
process of construction materials might occur. These data can be considered as global and might be used
if the location and / or source of construction materials are unknown. As a result the range of the results
is wide and with high uncertainties. To reduce this range it was proposed that the calculation could
include the country specific electricity mix, which was identified as main contributor to the variability
of the results on the previous projects. This was done by developing a georeferenced database, which
included data on the life cycle impact assessment (LCIA) of conventional and alternative construction
materials; LCIA from electricity production of different countries and regional averages of these values.
Moreover, the database included information on surface area of countries and cities. It was proposed
that the potential transport distances of construction materials could be related to some extent to the size
of the country and the type of material. For instance on a rather small country the transport distances
might be smaller than on a big country. Moreover, big countries like Brazil or Russia develop production
centres that somehow cover the whole country. Furthermore, certain materials like sand or gravel are
transported rather short distances, because they are normally easy to find but materials like cement or
steel required specialized process to produce and major investments to establish their industry. So it was
found that often steel and cement would be transported over much larger distances than other
construction materials. Based on these two premises and the examples found in the literature, a
logarithmic relation between surface are of the country and transport distances of construction materials
was established. A specific relation was develop for each kind of construction material. This approach
allowed to characterize the LCA data to specific locations worldwide but further developments were
needed to carryout comparative LCAs.
Comparative LCAs are used to identify the advantages and drawbacks from different options, like the
use bricks or wood on a buildings. The challenge of comparative LCAs is to establish a functional unit
that provides the same service. This is almost impossible when dealing with construction materials, a
unit of mass of brick can provide a very different services than a unit of mass of wood. In this case the
functional unit needs to be one stage higher and the functional unit needs to be defined at the building
level. For this research project the functional unit was defined as a Core Shelter. This kind of buildings
68
are mainly used in reconstruction projects around the world and are considered as a minimal housing
unit by the International Federation of Red Cross Societies. This provided with a simple functional unit
that could be built with different construction materials to provide the same service: an amount of
covered area over of 18 sqm for a defined period of time of 10 years. Under these condition the
functional units would be comparable in terms of mass units per service but they would still have
different performance under external environmental loads like earthquakes and/or hurricanes. This
problem required a further development of the database and the characterization process. Two world
maps were including on the geodatabase, containing the earthquake and wind risk zones. This
information was used to characterize the functional units, establishing the performance that the shelters
would have under the environmental loads on a given location.
In order to manage all this information and perform the LCA calculations a simple program was created.
The idea behind this program was to reduce the inputs needed from the user. So a user would need to
indicate which country and city would be studied and the type of construction materials that would be
used on the comparative LCA. With this information the programs first identifies the country’s surface
area and electricity mix. Then the amount of materials from the functional units are selected and the
LCIAs are calculated for the production of construction materials using the selected electricity mix. On
the next step, the program calculates the potential transport distances for the different construction
materials and the LCIAs of transport. These values are added with the result from the construction
materials and the environmental impacts for each material option are then calculated. These results are
presented in a range with a low, mean, and high performance limits. The uncertainty of these results is
calculated based on the contribution that each of the inputs has on the total environmental impact.
Furthermore, using the information of the country/city the program identifies the hazard risk zones for
the location and compares it with the potential performance of the shelters. Finally, the results are
presented on a table that shows the range of impacts for each construction material; the contribution to
the impact of each input; the uncertainty of the results; and the performance of the shelters under the
expected risk conditions.
The results of this research project showed that the integration of LCA and GIS opens possibilities not
only for the characterization of data but also to provided more information for a decision making process.
With this results was possible to see that sometimes the options with the best environmental
performances could not withstand the external loads. Thus, a lower environmental performance would
be the best option if it is able to withstand the external loads. On this project bamboo was studied as
main construction materials, it was hypothesized that under extreme conditions of earthquake and wind
risk the extra reinforcement needed would significantly reduce its environmental performance. It was
found out that on those situations a bamboo based building wold have the best environmental
performance but if the transport distances were longer than 500km the performance would be reduced
significantly. This highlighted the important role that the transport distances of construction materials
69
played on a comparative LCA. The program was further develop to be able to calculate with a higher
level of accuracy the transportation distances. This has the drawback of higher data requirements, in
form of the location of production centres of construction materials. Once this information is available
the calculation process is relatively straight forward using the geodatabase. The results of this
development allowed for lower uncertainties and variability on the results. The two approaches to
estimate transport distances provide coherent result, with the second giving a more accurate result at the
cost of higher data requirements.
This research project showed that the used of Geographic Information Systems offers a wide range of
possibilities for the characterization of LCA data and the calculation of LCA of buildings worldwide. It
also showed that thanks to the integration of LCA data and methods into a GIS if it possible to improve
the quality of comparative LCAs. These results also showed that at the moment of the selection of an
alternative for the construction of building the environmental impact might not be enough and other
parameters, like resilience, cost and performance would be needed to make an inform decision.
70
71
Introduction to the chapter This chapter describes the development of a cost effective methodology to characterize LCA data
worldwide. The first section will introduce the challenges faced when carrying out LCA of buildings,
making special emphasis on data quality and availability. Moreover, the challenge of produce data sets
that can represent the specific production practices connected to different locations. This chapter will
use the LCA data with global representativeness produced on the previous chapter as basis for the
methodology. The first section further introduces the potentials that Geographic Information Systems
(GIS) withhold to connect data with specific geographies.
On the second section, the proposed methodology will be described. First by showing the different types
of data used and how they will interact on the assessment of the building’s life cycle. Furthermore, this
section will describe the development of a Geo-Database that contains both geographic and LCA data.
The geographic data, represent a list 140 countries and their area; around 2500 cities worldwide with
their populations; and detailed wind and earthquake risk zones, The LCA data includes the life cycle
impacts from the production of alternative and conventional construction materials. Furthermore, it
includes the life cycle impacts for production of electricity per country and region. The database includes
life cycle impacts of transport both road and transoceanic. The second section further describes, how the
potential transport distances are calculated based on the land area of a country. This process is based on
findings on the literature and proposes a logarithmic relation between the land area of a country and the
potential transport distances. These distances are differentiated based on the type of construction
material and divided in three potential ranges low, medium, and high performances.
The second section continues with the description of the characterization process of LCA by using both
the geographic and LCA data found on the Geo-database. With this process the LCA data is able to
represent the effect of the different electricity mixes found on more than 140 countries. Furthermore,
this section describes how the LCA of buildings is calculated by using the characterized data and the
potential transport distances previously calculated. Furthermore, the methodology section shows how
the wind and earthquake zones are identified based on the cities selected for the comparative LCA. The
final part of the second section will present the set-up of a comparative LCA study. On this case study
the proposed methodology is used to assess the LCA of a building design on twenty five countries
worldwide. Changes on the type of construction material are included to see the effect of using
alternative or conventional construction materials.
Furthermore, it will present the results of the case study, showing how the electricity mix; type of
material; production efficiencies; and the potential transport distances affect the LCA results.
Furthermore, it will show how the different transport distances ranges affect the results. The
contributions to the environmental impacts from each of the construction materials and their transport
are also presented. Finally, this section show how the buildings might perform on the identified wind
and earthquake zones.
72
Further on, this chapter will present the discussion of the results and the validity of the proposed
methodology. This section will present an overview of the most relevant research on the field and how
the proposed methodology contributes to it. This section makes special emphasis on the discussion on
the generation and characterization processes and how other researchers had approached this problem.
The second part of this chapter presents a case study based in Colombia, South America, and focuses
the effects of a point to point assessment of construction materials’ transport distances. The first section
will introduce the methodology and data used on the case study. Moreover, it will describe the functional
unit; the different structural construction materials; and the locations of both construction materials
production centres and target cities. Furthermore, it will describe the process of calculating the transport
distances from centres of production towards targets cities. The methodology presented here is an
expansion of the method described on chapter 3 and uses the same Geo-Database. On this case, the
geodesic distances between production centres and target cities were calculated using the spatial analysis
features of the GIS software ArcMap.
73
3.1. Method and application of characterization of life cycle impact data of construction materials using geographic information systems
International journal of Life Cycle Assessment (under review)
3.1.1. Introduction Over the past few decades, life cycle assessment (LCA) was developed and established as the main
methodology to quantitatively assess the environmental impacts of goods and processes throughout their
entire lifespan. The models used in an LCA propose a cause-effect relationship between the environment
and human activities to highlight their impacts and consequences [1]. LCA has been used to assess the
environmental performance of buildings and construction materials for more than 20 years [2]; however,
its application has been predominately limited to Europe. The application of LCA faces many
challenges, including impact allocations [3, 4]; end-of-life scenarios [5, 6]; system’s boundaries [7].
More importantly, the availability and quality of the data hinders the application of LCAs [8-10].
LCA can be used to identify the most promising strategies for improving the environmental
performance of products and services throughout their whole life and supply chain; this assessment can
offer a better understanding of the impacts of human activities on the environment [1]. However, human
activities and their impacts on the environment can be geographically separated during the supply chain
and/or during the life of the product. The use of site-dependant life-cycle impact assessment has been
proposed as an approach to reduce the uncertainties associated with the geographical location and
regionalisation of life cycle impacts [11, 12]. Many of these methods are focused on developed
countries, and the lack of a global regionalisation approach of the LCA is evident [13].
To fulfil this need in a cost effective manner, the use of geographic information systems (GIS) has been
proposed [14-16]. GIS was developed to capture, manage, analyse and display all types of
geographically referenced information. The primary use of GIS is to graphically represent and
understand data [15]. GIS has been widely used to conduct assessments on environmental impacts [17,
18] and biodiversity [19]. Furthermore, GIS has been used as a decision-making tool in several fields
[20], such as forestry, greenhouse gas emission, risk assessment, land use, urban development and
sustainability [21-27].
GIS technologies may permit location matching in LCA models when a direct correspondence between
the inventory datasets and evaluation methods is unavailable [10]. This coupling produces finer
resolution results while recognising that production efficiency and its environmental impact have
variability that is intrinsically connected to the geographical context [16, 28]. In the specific case of the
LCAs of buildings, geographically linked factors play a very important role, but they are difficult to
address in an LCA. Factors such as land use, seismic risk zones, and the transport distances of materials
are quite straightforward when using GIS technology [29], but they are quite complex to represent in an
LCA. Transport is of great interest due to the high levels of associated greenhouse gas emissions and
74
the challenge of correctly estimating transport distances, particularly in an LCA [30]. These distances
are related to the suppliers and producers of construction materials, which in many cases are unknown
at the moment of the assessment. This uncertainty is increased when considering the role that global
international trading plays on modern economies. Moreover, it highlights the need to compare
environmental impacts between locations of resource extraction and use through the regionalisation of
LCA data and methods [1].
Furthermore, even if the methods and impacts are regionalised, the data of bio-based products in the
current databases are incomplete due to the large variability in agricultural production levels in various
regions [31, 32]. This is also true for bio-based and alternative construction materials outside Europe,
in which variations in production practices and electricity mixes can dramatically influence the results
of an LCA [33]. To address this problem, the contribution to variance (CTV) has been proposed as a
global sensitivity test for LCAs [31, 32]. The CTV expresses the contribution of each parameter to the
overall variance in the LCA results as a proportional ratio between the variation of inputs and results.
This parameter is important for improving data quality, allowing a practitioner to focus on the main
contributors to the environmental impact [34]. Moreover, this approach can be used as a basis to
calculate the uncertainties related to construction materials in a building [32], thereby improving the
overall consistency of the LCA results. In the case of alternative construction materials(i), electricity
mix(ii); production efficiency(iii); and transport(iv) have been identified as main contributors to the
variation and uncertainty of the results [35, 36].
Using LCA for buildings is unique due to the intrinsic diversity of the data on these types of assessments.
Furthermore, it should be conducted at early design stages when it is still possible to make substantial
changes to the design [1]. This comes at the cost of higher uncertainties regarding the construction
materials to be used; their production efficiency; and transportation. The complexity of this setup is
increased if the LCA is conducted for regions outside the European context where only limited LCA
data is available. This poses a challenge for organizations, working on reconstruction and housing
projects in those regions which try to use LCA as a decision making support tool. Under the current
conditions the development of LCA data of construction materials and buildings requires a major
financial and human talent investment. Nevertheless, these data is necessary to produce insights into the
selection of construction materials. Thus, it is necessary to make compromises between the results’
precision and the resources available in terms of LCA data, time, and budget.
The aim of the present research project was to develop a cost-efficient methodology for the LCA of
buildings using alternative construction materials outside the European context by characterizing the
LCA data of alternative construction materials with the use of a geographic information system.
75
3.1.2. Methods The present methodology proposes that the LCA of buildings can represent the local diversity of
production practices by integrating LCA data and geo-referenced data in a GIS. To achieve this goal,
the proposed methodology considers three levels of geo-referenced data: (i) global, (ii) regional, and
(iii) local, as seen in figure 3.1. The global level represents data that can be considered valid worldwide,
such as the amounts of material per functional unit and the production efficiency of construction
materials. It can be argued that the amount of construction materials needed, to produce a wall for
instance, will not drastically vary from one location to another. Furthermore, the production efficiency
of construction materials will vary within a range of values [35, 36]. The regional level contains data
that can be linked to a specific country’s characteristics, such as electricity mix and transport distances
for construction materials. The local level represents data such as seismic and wind risk zones in which
the buildings can potentially be constructed. The approach to operationalise the methodology comprises
four interconnected steps: characterization of LCA; calculation of transport distances per country; LCA
of the building; and the identification of seismic and wind risk zones.
Figure 3.1 Conceptual framework of the methodology
76
3.1.2.1. Developing an LCA geo-database / Characterization of the LCA data
For the characterization process, a geodatabase was created using the software ArcCatalog10.2 [37].
The database contained two types of information. The first type was the geo-referenced data of
approximately 230 countries and 2000 cities [37], with their respective seismic risks [38] and wind
zones. The second type was the LCIAs for the production of: (i) electricity per country [39]; (ii)
construction materials considering low, mean, and high production efficiency [33, 35]; and (iii) the life
cycle inventories (LCI) of house designs. The LCIAs were calculated using the database EcoInvent 2.7
[40]; the software SIMApro v7.3 [41] and the environmental impact was calculated using the evaluation
method IMPACT2002+ [42]. This method considers four impact categories: (i) human health evaluated
in terms of DALYs; (ii) ecosystem quality assessed by the potentially disappeared fraction (PDF) over
a certain area and during a certain period per kg of emitted substance (PDF.m2.yr); (iii) climate change
assessed with global warming potential [43] in terms of kg CO2 equivalents; and (iv) resources
evaluated by the product’s energy demand in mega joules (MJ). The results were normalized into a
single score value by using the following factors implemented on the software SIMApro v7.3 [44]: (i)
human health: 0.0071 DALY; (ii) ecosystem quality: 13,700 PDF.m2.yr; (iii) climate change: 9,950
kg CO2; and (iv) resources: 152,000 MJ[45].
The LCIA of construction materials was characterized by two main factors: electricity mix and
production efficiency [33, 35]. This kind of approach is very useful for the present case, where the LCA
data is scarce and time and funding are limited. This approach does not produce an exact result but
presents a range in which the result can be found. Furthermore, analysing the contribution to the
variability (CTV) was used to calculate the result’s uncertainty based on the work of by Hocha et al
[32]. To calculate the characterized LCIAs, a script was developed using the programming language
Python 2.7 [46] and the module ArcPy [37]. The script first identified the country and city to be studied,
which were defined by the user. With this information, the database is searched to select: (i) the LCIA
from specified country electricity mix; (ii) the country area in km2; and (iii) the seismic and wind zones
in which the city is located. Simultaneously, the script loads the LCIs that identify the amount of material
needed for each house design. Then the characterized LCIAs are calculated by adding (i) the LCIA from
the electricity mix; (ii) the impact from the production of raw materials; and (iii) processing raw
materials into the construction materials per mass unit (Eqn. 1). These calculations are executed for low,
mean, and high production efficiencies of each construction material.
LCIAmat = EIelec + EIrawmat + EIprocess (Eqn. 1)
LCIAmat = LCIA of materials per kg EIelec = Environmental Impact from electricity production (country specific) EIrawmat = Environmental Impact from production of raw materials EIprocess = Environmental Impact from production of construction materials
77
Then, the LCIA of the materials per functional unit are calculated by first multiplying the characterized
LCIA of each material with the respective amount on the LCIs (Eqn. 2). During this step, the script
calculates three scenarios low, mean, and high performances for each construction material per
functional unit, and established a triangular probabilistic distribution for these data. The standard
deviation of these data is used in combination with CTV to calculate the results’ uncertainty as described
by Hoxha et al [32].
LCIAfu= EImaterial/kg * Amat (Eqn. 2)
LCIAfu = LCIA of materials per functional unit EImaterial/kg = Environmental impact of production 1kg of construction material Amat = Amount of material in kg
3.1.2.2. Calculation of transport distances per country
The calculation of the transport distances of construction materials is highly uncertain and is often
arbitrarily assigned. To rationalise this process, the transport distance was related to the size of the
country and the type of construction material. A relation between country’s area (km2) and transport
distances (km) was estimated based on findings from the literature presented on table 3-1.
Table 3-1 Land area and transport distances from literature
From this data it is possible to see that no direct relation can be established, but in nine out of ten cases,
the transportation distance was below 600 km. Furthermore, for the countries with sizes bellow one
million square kilometres the range of transport was between 45 and 300 km. The longest transport
distances from this sample range between 250 and 300 km. This can be observed in cases of large
countries such as Brazil or Colombia where the construction materials are not transported all over the
country, but centres of production are geographically located to cover most of the country’s needs. It
was also proposed that the relationship between countries’ area and construction materials’ transport
distances will follow a logarithmic pattern (Eqn. 3).
Country Land Area Km2Short distance
transport (local) Km
Long distance transport
(national) KmReferences
Belgium 30,278 N/A 300 (Beuthe et al. 2001)
Netherlands 33,893 100 N/A (Quak 2008)
Switzerland 39,997 N/A 250 (Maggi et al. 2005)
Greece 130,647 32.5 N/A (Koroneos and Dompros 2007)
Italy 294,140 50 N/A (Pulselli et al. 2008)
France 640,427 80 N/A (Nicolas and David 2009)
Turkey 769,632 250 1250 (Ozen and Tuydes-Yaman 2013)
Peru 1’279,996 71 427 (SwissContact 2013)
Indonesia 1’811,569 75 280 (Utama et al. 2012)
Brazil 8’460,415 34 N/A (Bonilla et al. 2010)
78
TD = nmin, mean, max * Ln(A) - mmin, mean, max (Eqn. 3)
TD = Transport distance nmin = 51.37 nmean = 61.05 nmax = 76.27 A = Country’s area in km2 mmin = 448.36 mmean = 500.04 mmax = 621.59
This trend applies for countries with areas larger than 8870 km2. In cases in which the area was equal or
smaller than this value, the minimum transport distance was used for the calculations. Furthermore,
particular construction materials or components have longer transport distances than others. For
example, bricks are usually transported over much shorter distances than reinforced steel or cement. To
acknowledge these differences, three additional transportation ranges were defined (i) minimum, (ii)
mean, and (iii) maximum transport distances (Eqn. 3) a sample of these calculations is presented on
table 3-2:
Table 3-2 Potential transport distances (sample)
The minimum transport distance was used for materials that were considered locally produced, such as
bricks, concrete hollow blocks and sand. The medium transport distance was used for gravel, and the
maximum transport distance was used for bamboo, cement, and steel. However, because the steel market
is an international market, an additional transoceanic transport distance (7,000 km) for all countries was
added to the national transport distance. It is important to note that this solution is not completely
Country ID Country's NameCountry's Area
(km2)
Minimum transport distance
(km)Mean transport distance (km)
Maximum transport distance
(km)
JM Jamaica 10,831 28.89 67.13 90.43
SV El Salvador 20,721 62.22 106.74 140.13
HT Haiti 27,560 76.87 124.15 161.98
DR Dominican Republ 48,320 105.72 158.43 204.99
PA Panama 74,340 127.85 184.73 238
CU Cuba 109,820 147.89 208.55 267.89
NI Nicaragua 119,990 152.44 213.96 274.68
GY Guyana 196,849 177.87 244.18 312.6
EC Ecuador 256,369 191.45 260.31 332.84
VE Venezuela 882,050 254.92 335.75 427.5
CO Colombia 1’038,700 263.32 345.73 440.03
PE Peru 1’279,996 274.05 358.48 456.03
MX Mexico 1’943,945 295.52 383.99 488.04
BR Brazil 8’460,415 371.07 473.78 600.71
US USA 9’158,960 375.15 478.62 606.79
79
accurate, and a compromise between data availability and accuracy is needed in this regard.
Nevertheless, this method provides the first step in rationalising the calculation of transport distances of
construction materials during the early stages of building design. After obtaining these values, the LCIAs
from the transport of construction materials were calculated (Eqn. 4). To obtain this value the amount
of material in tons was multiplied by the transport distance calculated for the specific country; and by
LCIA of transporting 1 tkm of the material:
LCIATD = Amat * TD * EItransport (Eqn. 4)
LCIATD = LCIA from transport of materials Amat = Amount of material in ton TD = Transport distance of construction materials in km EItransport = Environmental impact from transport of 1tkm of construction material
3.1.2.3. LCA of the Building
In order to calculate the LCIA of the studied building the script adds all the characterized LCIAs from
construction materials and their transport. This can be easily done due to the fact that all the LCIAs had
been normalized into single score values as described in section 2.1. This procedure calculates three
levels of performance by combining the results from the high, mean, and low production efficiencies
with the minimum, mean, and maximum transport distances respectively. Then the process contribution
to the environmental impact (PCEI) is calculated in form of a proportional ratio between the total
environmental impact and the impact of each material per functional unit (Eqn. 5). Furthermore, the
CTV is calculated based on the proportional ration between variation of inputs and the consequent
variation of the results (Eqn. 6).
PCEI = (LCIAfu, TD / LCIAbuild) * 100 (Eqn. 5)
PCEI = Process contribution to environmental impact LCIAbuild = LCIA per functional unit LCIAfu = LCIA of materials per functional unit LCIATD = LCIA from transport of materials
CTV = (∆LCIAFU,TD / ∆LCIAbuild) * 100 (Eqn. 6)
CTV = Contribution to variance ∆LCIAFU = Difference between high and low performance levels ∆LCIATD = Difference maximum and minimum transport distances ∆LCIAbuild = Difference between high and low performance levels
3.1.2.4. Identification of seismic and wind risk zones
80
The final step in the calculations is to identify the seismic risk and wind zones in which the studied city
was located. This step has a two folded purpose, on the one hand the identification of risk zones at early
stages of design allow decision makers to understand better the structural requirements on the zone. On
the other hand, it allows to determine whether the studied house design can withstand the external load
(earthquake and wind) at the proposed location. Thereby allowing a better comparison between
constructive systems.
The identification of risk zones was achieved by using spatial analysis tools in the ArcPy [37] module
and the geo-information from the database. Based on this information, an external environmental
constraint factor was defined for each location. This factor indicated what the structural demand would
be on the location. This factor was compared with the structural performance of the studied building, to
calculate the building’s structural performance. If the factor was equal to the performance of the house,
then the structure was considered to perform appropriately for the external constraints (earthquakes and
wind). If the factor was larger than the performance, then the structure would be at risk of collapsing
under the external loads. This condition would require a revision of the structural design or the selection
of an alternative design. Finally, if the factor was smaller than the performance, then the building would
be able to withstand the external loads but would be over-performing.
3.1.2.5. Application
To test the consistency of the proposed methodology a case study was proposed. The case study was a
comparative LCA in which the environmental impact of five different construction materials on a
singular house design was assessed at twenty locations. For this case the selected locations were
concentrated in the American continent and include Jamaica, Puerto Rico, Anguilla, El Salvador, Belize,
Honduras, Costa Rica, Dominican republic, Panama, Cuba, Nicaragua, Guyana, Ecuador, Venezuela,
Colombia, Peru, Mexico, Brazil, USA. This selection covers a wide range of country’s areas and
electricity mixes. Furthermore, all the construction materials are available on the selected countries. The
main aim of the case study was to prove the ability of the proposed methodology to characterize LCIA
data on regions outside of the European context. The functional unit for the LCA was defined as an 18
m2 core shelter unit considering only the structural elements. The LCIs for the five construction material
options were calculated and are presented on table 3-3.
81
Table 3-3 life cycle inventories of construction materials used in five house designs
Each option had distinctive construction material: bamboo, brick, concrete hollow block, ferro-cement
panels, or soil stabilised bricks. These designs are considered “core shelters” that are generally built
during reconstruction projects after disasters [47] or in social housing programs. This type of design was
useful for this research due to its simplicity and its global character. The use phase of the buildings was
not considered due to the fact that the energy demand from this kind of buildings is independent from
the type of construction materials they are built with. Moreover, the selected locations have no seasons,
and therefore no heating demand is required.
3.1.3. Results The results for the case study considering the environmental impact of the construction materials at
different transport distances are shown in figure 3.2, the brick houses had the highest impacts and were
excluded from the results to improve the readability. The three levels of performance were represented
by bands, in which the lower boundary represent the highest performance achievable at the given
average transport distance and upper boundary represents the lowest performance. The separation
between these two boundaries represent the variability of the results and all the possible combinations
of LCIA of construction material and transport might occur within this range. From this figure it is
possible to observe that in cases with short transport distances, the variability of the results is smaller
than those with long transport distances. For countries with the longest transport distances, the variability
of the results was highly influenced by the impact of the transport of materials. From this figure it is
possible to see that that the results from different construction materials overlap. This means for
instance, that at short transport distances one material might have the best performance but it might not
be the best performing at long transport distances.
Materials Block House Bamboo House Brick House Ferro-cement HouseSoilCement House
Bamboo pole (kg) 160
Flattened Bamboo (kg) 397.8
Brick (kg) 5,307.0
Concrete bloc 3,816.0 120
Ferro-cement panel (kg) 3,002.7
Soil stabilized brick (kg) 5,605.1
Reinforcing s 1,604.4 524.9 893.8 798.1 690.2
Concrete (kg) 2,878.3 8,800.0 2,878.3 2,878.3 6,397.7
82
Figure 3.2 LCA of buildings, transport distance, and production efficiency
The results of the bamboo, concrete hollow block and ferro-cement houses were within similar ranges
of variability. Therefore, the level of performance from an average bamboo house can be achieved by a
high performance block or ferro-cement house even at short distances. Thus, the performance of a given
construction technique cannot be directly correlated to the use of specific construction materials but
rather to its appreciated use based on the specific location, the efficiency of production and the
transportation of the construction materials.
To better understand these results, the contributions of the five construction materials to the
environmental impact were calculated and are presented on figure 3.3. This figure shows the average
values for the 25 locations. Thus, representing all the transport distance ranges and electricity mixes.
These results show that the construction materials contributed to approximately 70% of the impact,
while the transport of those construction materials represented between 15 - 30% of the impact,
depending on the construction material. Moreover, in most designs, reinforced steel was the main
contributor to the environmental impact (30 - 40%). This shows that special attention must be paid to
the possible transport ranges that might be associated with a project (transport distances) and to the
external environmental constraints of seismic risk zones and wind loads and thus the need for structural
reinforcement.
83
Figure 3.3 Contribution to the environmental impact Further analysis of the different transport distance ranges showed that at distances less than 450 km, the
bamboo house had the best performance independent of the electricity mix used. If the high performance
level is considered, then this range is reduced to 300 km; if the low performance level is considered,
then the ferro-cement house had the best performance at distances greater than 500 km, beyond this
distance, the block and ferro-cement houses performed better due to the much shorter transportation
distances of the main construction materials. The analysis of the contribution from transport of
construction materials was below 10% at short transport distances. At long transport distances the
contribution from transport increased up to: 30% for the ferro-cement and brick houses; 45% for the
block and soil stabilized houses; and 55% for the bamboo houses. In all these cases, the transport of
concrete components (cement, gravel and sand) contributed the most.
Finally, the effects of the external environmental constraints were analysed. Each location had its own
distinctive requirements for both earthquakes and wind loads as presented on figure 3.4. A colour
gradient from red to green was used to identify the performance. Red indicates that a given house design
would underperform for the seismic/wind demands on the location. Thus, a house might collapse under
the expected external environmental constraints, and the structural design would need to be improved.
Yellow represents an appropriate performance in which the house would withstand the external
environmental constraints. Finally, green represents the over-performance of a house in a given location.
This means that it would be possible to reduce the structural components for a given house design in
84
that location and reduce its environmental impact. From figure 3.4 it can be observed that the “bamboo
house” often had the lowest environmental impact and a better structural performance. However, in
some cases, its impact was much higher than that from the benchmark design, and it still had a better
structural performance. This feature can support the decision-making process when choosing
appropriate construction systems and house designs for specific locations; thus, a decision
maker/designer can prioritise environmental impacts and structural performance depending on the local
conditions.
Figure 3.4 LCA and structural performance
3.1.4. Discussion Nansai et al. [12] and Potting [11] did extensive work on the regionalization of environment impacts on
LCA. These approaches increase the quality of the output results but require low levels of uncertainty
in their data. On the case of LCA of buildings, the uncertainties are the highest at the early stages of
design, when most of the improvements can be achieved. Thus, a site-dependent LCA of buildings could
only bring hindsight’s. In most of the cases buildings are unique interventions, so the usefulness of a
posteriorly site-dependant LCA would be limited. The methodology here presented aims to generate a
range in which the environmental impact can occur by considering the variability on production
practices of construction materials. These kind of results are easier to produce at early stages of design
and can therefore help decision makers and designers to make the optimal choices of construction
materials. Furthermore, the work of [10-12] presented an approach in which both the LCIA and
evaluation methods were regionalised to bridge the data gap. In the present research, the characterization
85
process was conducted by including the country-specific electricity mix in the calculations and the
performance range of technology. These characteristics were combined with the evaluation method
IMPACT2002+ [42], which can be considered global. Nevertheless, it is possible to further refine the
model by including the regionalised evaluation methods and LCIA, as proposed by Mutel et al.
National transport distances were studied in detail in the present research, and several models were
developed to represent four possible transport-distance ranges in relation to the country size. However,
as proposed by [1, 30], more detailed models are needed in which the effects of international transport
can be better represented, to acknowledge the global characteristics of many construction materials used
today. The contribution to variability was used to better understand the effect of the different
construction materials on the LCA results and to test sensitivity, as proposed by [31]. This approach
proved to be very useful for bio-based construction materials, such as bamboo, and for construction
materials whose production process is highly variable and uncertain. The uncertainties in the results
were calculated using part of the methodology developed by [32]; this approach provides an effective
and fast assessment of the uncertainty in the data related to the environmental impacts. With further
developments in the model, it would be possible to include factors such as replacement, maintenance
and end of life.
3.1.5. Conclusions The present research aimed to develop a LCA methodology for buildings that could represent the local
variability of production on a global scale. The use of GIS enabled the development of characterized
LCIA data for construction materials and buildings with a high degree of consistency. Moreover, the
data produced represented the local context by considered country-specific transport distances and
electricity mixes. Furthermore, the proposed approach was able to represent the range of production
practices in use around the world. The results produced with the present methodology provide a range
of values representing the possible variability of results. On the present research the highest level of
uncertainty was used, considering that only the country and construction materials were known. If a
practitioner has more detailed information and data the level of uncertainty and thus the variability of
the results could be reduced. Finally, the proposed methodology can assess building designs in their
early stages, when the uncertainty is highest; thus, it can identify potential improvements to each design
and recognise the structural needs in specific locations.
3.1.6. Acknowledgements The authors of this paper would like to thank HILTI AG for their support and sponsorship of this
research.
86
3.1.7. References 1. Hellweg, S. and L. Mila i Canals, Emerging approaches, challenges and opportunities in life
cycle assessment. Science, 2014. 344(6188): p. 1109-13. 2. Fava, J.A., Will the next 10 years be as productive in advancing life cycle approaches as the
last 15 years? International Journal of Life Cycle Assessment, 2006. 11: p. 6-8. 3. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part I: goals and scope
and inventory analysis. International Journal of Life Cycle Assessment, 2008. 13: p. 290-300. 4. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part II: impact
assessment and interpretation. International Journal of Life Cycle Assessment, 2008. 13: p. 374-388.
5. Kim, S., T. Hwang, and K.M. Lee, Allocation for cascade recycling system. International Journal of Life Cycle Assessment, 1997. 2: p. 217-222.
6. Dubreuil, A., et al., Metals recycling maps and allocation procedures in life cycle assessment. International Journal of Life Cycle Assessment, 2010. 15: p. 621-634.
7. Frischknecht, R., LCI modelling approaches applied on recycling of materials in view of environmental sustainability, risk perception and eco-efficiency. International Journal of Life Cycle Assessment, 2010. 15: p. 666-671.
8. Gomes, F., et al., Adaptation of environmental data to national and sectorial context: application for reinforcing steel sold on the French market. International Journal of Life Cycle Assessment, 2013. 18: p. 926-938.
9. Langevin, B., C. Basset-Mens, and L. Lardon, Inclusion of the variability of diffuse pollutions in LCA for agriculture: the case of slurry application techniques. Journal of Cleaner Production, 2010. 18: p. 747-755.
10. Mutel, C.L. and S. Hellweg, Regionalized life cycle assessment: computational methodology and application to inventory databases. Environmental science & technology, 2009. 43(15): p. 5797-5803.
11. Potting, J., Spatial Differentiation in Life Cycle Impact Assessment A Framework, and Site-Dependent Factors to Assess Acidification and Human Exposure. International Journal of Life Cycle Assessment, 2000. 5(2): p. 77-77.
12. Nansai, K., Y. Moriguchi, and N. Suzuki, Site-dependent life-cycle analysis by the SAME approach: Its concept, usefulness, and application to the calculation of embodied impact intensity by means of an input-output analysis. Environmental science & technology, 2005. 39(18): p. 7318-7328.
13. Mutel, C.L., Framework and tools for regionalization in life cycle assessment. 2012, Diss., Eidgenössische Technische Hochschule ETH Zürich, Nr. 20604, 2012.
14. Gasol, C.M., et al., Environmental assessment:(LCA) and spatial modelling (GIS) of energy crop implementation on local scale. biomass and bioenergy, 2011. 35(7): p. 2975-2985.
15. Liu, K.F.-R., et al., GIS-Based Regionalization of LCA. Journal of Geoscience and Environment Protection, 2014. 2: p. 1-8.
16. Mutel, C.L., S. Pfister, and S. Hellweg, GIS-based regionalized life cycle assessment: how big is small enough? Methodology and case study of electricity generation. Environmental science & technology, 2011. 46(2): p. 1096-1103.
17. Fallahi, G.R., et al., An ontological structure for semantic interoperability of GIS and environmental modeling. International Journal of Applied Earth Observation and Geoinformation, 2008. 10(3): p. 342-357.
18. Jankowski, P., Towards participatory geographic information systems for community-based environmental decision making. Journal of Environmental Management, 2009. 90(6): p. 1966-1971.
19. Gontier, M., B. Balfors, and U. Mörtberg, Biodiversity in environmental assessment—current practice and tools for prediction. Environmental Impact Assessment Review, 2006. 26(3): p. 268-286.
20. Ramsey, K., GIS, modeling, and politics: On the tensions of collaborative decision support. Journal of Environmental Management, 2009. 90(6): p. 1972-1980.
87
21. Höhn, J., et al., A Geographical Information System (GIS) based methodology for determination of potential biomasses and sites for biogas plants in southern Finland. Applied Energy, 2014. 113(0): p. 1-10.
22. Yousefi-Sahzabi, A., et al., GIS modeling of CO2 emission sources and storage possibilities. Energy Procedia, 2011. 4(0): p. 2831-2838.
23. Tang, R., Y. Bai, and T. Wang, Research on GIS Application System of Environmental Risk for Hazardous Chemicals Enterprises. Procedia Environmental Sciences, 2011. 10, Part B(0): p. 1011-1016.
24. Zhang, Y.J., A.J. Li, and T. Fung, Using GIS and Multi-criteria Decision Analysis for Conflict Resolution in Land Use Planning. Procedia Environmental Sciences, 2012. 13(0): p. 2264-2273.
25. Zeilhofer, P. and V.P. Topanotti, GIS and ordination techniques for evaluation of environmental impacts in informal settlements: A case study from Cuiabá, central Brazil. Applied Geography, 2008. 28(1): p. 1-15.
26. Graymore, M.L.M., A.M. Wallis, and A.J. Richards, An Index of Regional Sustainability: A GIS-based multiple criteria analysis decision support system for progressing sustainability. Ecological Complexity, 2009. 6(4): p. 453-462.
27. Javadian, M., H. Shamskooshki, and M. Momeni, Application of Sustainable Urban Development in Environmental Suitability Analysis of Educational Land Use by Using Ahp and Gis in Tehran. Procedia Engineering, 2011. 21(0): p. 72-80.
28. Dresen, B. and M. Jandewerth, Integration of spatial analyses into LCA—calculating GHG emissions with geoinformation systems. International Journal of Life Cycle Assessment, 2012. 17(9): p. 1094-1103.
29. Geyer, R., et al., Coupling GIS and LCA for biodiversity assessments of land use: Part 1: Inventory modeling (LAND USE IN LCA). International journal of life cycle assessment, 2010. 15(5): p. 454-467.
30. Fries, N. and S. Hellweg, LCA of land-based freight transportation: facilitating practical application and including accidents in LCIA. International Journal of Life Cycle Assessment, 2014. 19(3): p. 546-557.
31. Azapagic, A., et al., Approaches for Addressing Life Cycle Assessment Data Gaps for Bio‐based Products. Journal of Industrial Ecology, 2011. 15(5): p. 707-725.
32. Hoxha, E., et al., Method to analyse the contribution of material's sensitivity in buildings' environmental impact. Journal of Cleaner Production, 2014. 66: p. 54-64.
33. Zea Escamilla, E. and G. Habert, Environmental Impacts of Bamboo-based Construction Materials Representing Global Production Diversity. Journal of Cleaner Production, 2014.
34. Mutel, C.L., L. de Baan, and S. Hellweg, Two-Step Sensitivity Testing of Parametrized and Regionalized Life Cycle Assessments: Methodology and Case Study. Environmental science & technology, 2013. 47(11): p. 5660-5667.
35. Balzarini, A., Environmental impact of brick production outside Europe, in Department of Civil, Environmental and Geomatic Engineering. 2013, Swiss Federal Institute of Technology ETH Zürich: Zürich.
36. Zea Escamilla, E. and G. Habert, Environmental impacts from the production of bamboo based cosntruction materials representing the global production diversity. Journal of Cleaner Production, 2013.
37. ESRI. ArcGIS for Desktop. 2014; Available from: http://www.esri.com/software/arcgis/arcgis-for-desktop.
38. Giardini, D., et al., The GSHAP global seismic hazard map. Annals of Geophysics, 1999. 42(6). 39. SCLCI. EcoInvent Database. 2011; Available from: http://www.ecoinvent.org. 40. Frischknecht, R. and G. Rebitzer, The ecoinvent database system: a comprehensive web-based
LCA database. Journal of Cleaner Production, 2005. 13(13–14): p. 1337-1343. 41. Pre-Consultants. SIMA Pro v7.3.3. http://www.pre-sustainability.com/simapro-installation.
2012; Available from: http://www.pre-sustainability.com/simapro-installation. 42. Jolliet, O., et al., IMPACT 2002+: A New Life Cycle Impact Assessment Methodology.
International Journal of Life Cycle Assessment, 2003. 8(6): p. 324 - 330.
88
43. McCarthy, J.J., Climate change 2001: impacts, adaptation, and vulnerability: contribution of Working Group II to the third assessment report of the Intergovernmental Panel on Climate Change. 2001: Cambridge University Press.
44. Frischknecht, R., et al., Implementation of Life Cylce Impact Assessment Methods, Data v2.0 (2007), in EcoInvent Report No. 3. 2007, EcoInvent Swiss Centre for Life Cycle Inventories: Dübendorf.
45. Jolliet, O., et al., IMPACT 2002+: a new life cycle impact assessment methodology. Int J Life Cycle Assess, 2003. 8(6): p. 324 - 330.
46. Python, S.F. Python Language Reference, version 2.7. 2014; Available from: http://www.python.org.
47. IFRC, Post-disaster shelter: Ten designs. 2013, International Federation of Red Cross and Red Crescent Societies: Geneva, Swtizerland.
89
3.2. Case study – Detailed transport distances calculations This section will present the main results from the paper presented at the World Bamboo Congress 2015
in Damyang, South Korea. The full paper can be found on the congress proceedings and on the authors’
researchgate contributions page:
https://www.researchgate.net/profile/Edwin_Zea_Escamilla/contributions
Regionalizing the Environmental Impact of Bamboo-Based Buildings by Integrating Life Cycle Assessment with Geographic Information Systems. A Comparative Case-Study in Colombia.
3.2.1. Abstract The present research aimed to develop a methodology to regionalize the environmental impact
associated with the production of bamboo-based buildings by integrating life cycle assessment
methodologies and geographic information systems for a case study in Colombia. The data were
regionalized at three levels: Global – representing three levels of production efficiency of the materials;
Regional – resenting the type of electricity mix used in the production and national transport distances
at the country level; and Local – representing factors such as seismic and wind risk zones at the city
level. The functional unit for the LCA was defined as an 18 m2 core shelter unit considering only its
structural elements. The life cycle inventories for five designs were calculated, each using a distinctive
construction material: bamboo, brick, concrete hollow block, ferro-cement panels, and soil stabilized
bricks. The results showed that under certain conditions, the environmental impact of a low performance
bamboo house can be achieved by a high performance block house. The effect of the external constraints
(earthquake and wind) were analysed, and their effect on the whole life environmental impact was
assessed. The results show that in most cases, the buildings with high technical performance can achieve
high environmental performance. It is possible to conclude that the use of GIS enables the development
of regionalized LCA data for buildings with a high degree of consistency. Moreover, the proposed
approach was able to accurately represent the range of production practices encountered. Finally, the
use of the proposed methodology can allow the assessment of building design in the early stages where
the uncertainty is the highest, identifying the improvement potential of each design and recognizing the
structural needs for specific locations.
3.2.2. Data and Methods
The proposed case study is a comparative LCA in which five house designs were assessed at twelve
locations in Colombia, South America. This country was selected for several reasons; first the locations
of the production centres for bamboo, cement, and steel are well documented. Second, the size of the
country and its regional administrative units are large enough for the proposed methodology to produce
meaningful results. Finally, the building codes in Colombia include bamboo-based construction and
regulate its application and design.
90
The functional unit for the LCA was defined as an 18 m2 core shelter unit considering only the load
carrying elements in the assessment. This approach is used to reduce the uncertainty produced by
elements such as doors and windows, of which the selection and use is not connected to the type of
construction material used. This core shelter is the minimum housing unit defined by the International
Federation of Red Cross Societies. The functional unit’s main dimensions are presented in figure 3.5.
Figure 3.5 Functional Unit -- General Floor Plan. All measurements in cm.
Figure 3.6 (A) Bamboo frame (bahareque); (B) Concrete hollow block; (C) Ferro-cement panel; (D) Soil stabilized brick. Source: Authors, K. Rhyner, G. Landrou
The life cycle inventories (LCI) for five house designs were calculated based on the functional unit, each
using a distinctive structural construction material: bamboo frame (Bahareque), brick, concrete hollow
block, ferro-cement panels, and soil stabilized bricks, as seen in figure 3.6.
91
The life cycle inventories (LCIs) showing the material demand for the erection of each house design are
presented in table 3-4. The calculation of the life cycle impact assessment (LCIA) data was performed
using the evaluation method IMPACT2002+[1] and the software SIMApro7.3 [2].
Table 3-4 LCIs of the five house designs Materials Block
House
Bamboo
House
Brick House Ferro-cement
House
Soil-cement
House
Bamboo pole 0.0 160.0 0.0 0.0 0.0
Flattened bamboo 0.0 397.8 0.0 0.0 0.0
Brick 0.0 0.0 5307.0 0.0 0.0
Concrete block 3816.0 120.0 0.0 0.0 0.0
Ferro-cement panel 0.0 0.0 0.0 3002.7 0.0
Soil stabilized brick 0.0 0.0 0.0 0.0 5605.1
Reinforcing steel CN 1604.4 524.9 893.8 798.1 690.2
Concrete 2878.3 8800.0 2878.3 2878.3 6397.7
Source: Authors
Three levels of geo-referenced data were developed: global, regional, and local, as seen in Figure 4. The
global level represents data that are valid worldwide, such as the amounts of material per functional unit
and the range of production efficiencies of construction materials. The regional level contains data that
can be linked to the specific country or administrative unit of study, such as the electricity mix and
transport distances for construction materials from their production centre to the target city. The local
level represents data of seismic risk zones and wind risk zones where the buildings can potentially be
built.
3.2.3. Results The LCAs of the five proposed house designs were calculated in 12 locations in Colombia, considering
three levels of production efficiency and three transport distance ranges, and the results are shown in
figure 3.7. The three scenarios of production diversity of construction materials of high, mean and low
performance were represented by a band (fig. 3.7), with the high performance being the lower line and
the low performance the higher line. The X-axis represents the total tons of construction materials times
the total transport distance in kilometres (t*km). From these results, it is possible to see that with short
transport distances, the variation in the results is smaller than with higher transport distances. In the
cases with the largest transport distances, the variation in the results is mainly driven by the impact of
the transport of the materials (fig. 3.7). Not only is the level of impact influenced by the transport
distances but also the difference between these impacts. This means that in some cases, the “bamboo
house” has a higher impact than the “concrete hollow block house”, and the difference between their
impacts also changes depending on the transport distance range.
92
Figure 3.7 Environmental impacts at different transport regimes
The “brick house” has the highest impact and was excluded from the results to improve the readability.
The results of the bamboo, concrete hollow block and ferro-cement houses are in a similar range,
indicating that under certain conditions, the environmental impact of a mean performance bamboo house
can be achieved by a high performance block house. Thus, the environmental performance of a given
construction technique cannot be directly correlated to the use of specific construction materials but to
its appropriated use at the specific location, the efficiency of production and the transportation of
construction materials. This can be seen in Figure 6, where the bands for bamboo and concrete hollow
block overlap between ca 700 t*km and 1300 t*km.
To better understand these results, the contribution to the environmental impact of the five house designs
was calculated (fig. 3.8); this Figure shows the average values for the 12 locations, representing all
transport distance ranges and production efficiencies. These results show that the construction materials
contribute approximately 70% of the impact, whereas the transport of the construction materials
represents between 15% and 30% of the impact, depending on the house design. Moreover, in most
houses, the reinforcing steel is the main contributor to the environmental impact of 30% to 40%. This
result suggests that special attention needs to be paid to the possible transport ranges that might occur
in a project (transport distances) and also to the external environmental constraints of seismic risk zones
and wind loads (structure reinforcement).
93
Figure 3.8 Contribution to environmental impact.
The analysis of the contribution to the impact showed that the impact of transporting the construction
materials increased from approximately 10% at short transport distances to 30% for the ferro-cement
and brick houses, 45% for the block house and 55% for the bamboo house. In all cases, the components
of concrete contribute the most to the impact of transport.
Finally, the effect of the external environmental constraints was analysed. Each location has its
distinctive requirements for both earthquakes and wind loads. A colour range from red to green was
used to identify the performance as seen on figure 3.9. Red indicates that a given house design would
underperform for the seismic/wind demands of the location. Yellow is used to represent an appropriate
performance where the house will withstand the external environmental constraints. Finally, green
represents a house that would over perform at a given location. The “bamboo house” has often both a
lower environmental impact and a better structural performance. However, in some cases, its impact is
much higher than the benchmark design and still has better structural performance. This feature can
support the decision-making process when choosing appropriate constructive systems and house designs
for specific locations, allowing a decision maker/designer to prioritize between environmental impact
and structural performance, depending on the local conditions.
94
Figure 3.9 Environmental and structural performance at different locations
3.2.4. Conclusions The proposed methodology represents the local granularity considering country-specific transport
distances from centres of production to target cities. Furthermore, the proposed approach was able to
accurately represent the range of production practices encountered in the case study. The results showed
that under the high performance scenario, the bamboo house presents the best environmental
performance, independent of the transport distance. Finally, the use of the proposed methodology can
allow for the assessment of building designs in the early stages, where the uncertainty is the highest,
identifying the improvement potential of each design and recognizing the structural needs of specific
locations.
3.2.5. Acknowledgements The authors of this paper would like to thank Hilti AG for their support and sponsorship.
OverperfomHigh performanceApproiatedunderperformSeverely underperform
95
Chapter 3 in a nutshell
A methodology to characterize LCA data was developed, by integrating life cycle impacts of
construction materials with geo-referenced data of countries and cities
The characterization process considers three potential production efficiencies; country specific
electricity mixes and potential transport distances; and local wind and earthquake zones
A case study was carried out considering five different construction materials on twenty five
countries. A second case study focused on detailed transport distances
The results of the case study showed that alternative construction materials, like bamboo, are
more sensitive to the effect of long road transport distances
The proposed integration of LCA and geo-referenced data allowed a cost-efficient assessment
of buildings at early stages of design
Transport of construction materials plays a significant role on the environmental impact and can
contribute up to 30% of the total impact
The assessment of transport induces great variability and uncertainty on the results
96
97
Chapter 4: Additional sustainability aspects from the use of
bamboo on buildings
98
99
4. Additional sustainability aspects from the use of bamboo on
buildings
Summary Up to this point, this research project had been focused on the environmental impacts from the use of
different construction materials. This being one of the fundamental questions on the topic of sustainable
construction and arguably on sustainable development. On this chapter three research projects are
presented, they discuss from different perspective additional aspects that can be assessed in buildings
beyond environmental impacts. The first project was born on the interest of selecting appropriated
constructive systems for affordable housing. Through this process it became clear that additional
information was needed to support the decision process, like cost and social acceptance. This led towards
the study of transitional and core shelters, these can be considered as the minimum housing unit and as
their names indicate, often the centre of a future affordable house. The international federation of Red
Cross association published two reports where their experiences with transitional shelters was presented
in detail. These reports showed the bill of materials; cost, and technical performance of several core and
transitional shelters. These shelters had been used on different locations around the world for very
different situations. Thanks to this information, a sustainability assessment methodology was developed.
Three assessment categories were used (i) environment, (ii) cost, and (iii) technical performance. The
first category was assessed using LCA and was based on the bill of materials from the reports. The
second was assessed considering the total project cost per shelter. The third was assessed based on the
technical performance of a shelter under external environmental loads (wind earthquake and flood) on
specific risk zones. Two main factors were used on the comparison functional units, covered area and
life span. The LCA was calculated using the characterized data presented on chapter 2 and the transport
distances of construction materials were calculated using the methodology presented on chapter 3. The
results from this research showed that it was possible to achieve shelters with high technical performance
at low environmental impacts and cost. It was also found out that the sustainability of a shelter could
not be directly related to the use of a specific construction material but to their proper application and
use. An interesting conclusion from this research was that the use of bamboo is not always the best
solution but it gives the best chances to produce a sustainable building when compared to other
construction materials.
The second project was focussed on the assessment of the sustainability of bio-based construction
materials. This project had approached the problem with similar assessment categories but making
emphasis on the CO2 emissions. Moreover, the project was focused on housing programs considering
large amounts of buildings per year and a time line of more than ninety years. On this project the
environmental assessment was carried out using the characterize data presented on chapter 2 but using
the environmental impact evaluation method IPCC 2007 (100a). This data was used to calculate the CO2
balance of three construction materials: (i) concrete hollow blocks; (ii) glue laminated bamboo; and (iii)
100
glue laminated wood. The basis of these calculations was a dynamic model that showed the flow and
storage of CO2 through the years in which the housing program was running. Furthermore, the economic
aspects we calculated in terms of the CO2 credits that could be potentially obtained by the sequestration
and storage of CO2 on the studied bio-based construction materials. Furthermore, the social category
was assessed in terms of the potential job creation that each of the construction materials withhold. The
results from this project showed that both bio-based construction materials can sequester, store and avoid
CO2 emissions at similar levels but at different rates. The results also showed that a significant amount
of environmental savings and revenue generation was related to avoiding emission by using disposed
bio-based construction materials to produce electricity. This strategy is effective in countries where a
large percentage of the electricity and heating if fossil-fuel based. But in countries with “cleaner”
electricity mixes the avoided emissions are more limited and therefore the savings and revenue are also
reduced. This project also showed that the use industrialized bamboo construction materials can reduce
the levels of CO2 by sequestering, storing and avoiding more CO2 emissions than those related to its
production. Moreover, revenue can be generated from them, which are independent of the commercial
price. Finally, jobs can be created in a direct relation to the amount of bamboo produced. Thus,
industrialized bamboo is able to support the regenerative development of regions where it is applied.
The final project on this section, studies the potential that bamboo withholds on Europe. The market for
bamboo based products is quiet limited on bamboo producing countries. On the contrary the interest on
bamboo based products is growing in Europe. This project studied the environmental savings from the
use of bamboo in Europe, thus separating geographically production, use and disposal of the materials.
This is a common practice with other construction materials and with the globalized markets this practice
is increasing and expanding to other markets. Furthermore, the issue for maintenance regimes and life
span of buildings was also addressed. The results showed that the use of bamboo can bring
environmental savings when compared to conventional construction materials, even when transoceanic
transportation is considered. The savings are reduced when intensive maintenance and replacement
regimes are used. The same happens when short life spans are considered. These situations can be
avoided with proper design and application of the material. This project showed that there are interesting
possibilities to expand not only markets for bamboo based construction materials but also to increase
their social acceptance in bamboo producing countries.
This chapters presents three different approaches to assess the environmental performance and the
sustainability of bamboo based buildings. The three research projects contained on this chapter highlight
the potential that bamboo withholds to produce positive impacts on the economy, and environment of
communities using it. Furthermore, they show that the appropriated selection and use of construction
materials play a significant role on the sustainability of buildings. Moreover, these research had showed
that sustainability can be achieved independently of the use of a specific construction material.
101
Chapter’s introduction This chapter will present three parts discussing additional sustainability benefits from the use of bamboo
in buildings. The first section will introduce the sustainability assessment transitional shelters; the
second of industrialized bamboo solutions for housing; and the third section will discuss the potential
environmental benefits from the use of a bamboo based construction technique in Switzerland.
The first part will present first, the need for transitional shelters and the assessment of their sustainability.
Furthermore, it will describe a methodology to assess the sustainability of buildings on a global context.
The assessment categories of this methodology: (i) Environmental impact; (ii) Cost; and (iii) Technical
Performance will be described. On this section, the functional unit and methodology for each assessment
category will be presented.
Further on this part, the results for the three assessment categories will be presented individually. The
results section will further present the results for the sustainability assessment. This assessment will be
presented in form of a benchmark system that combines the three proposed impact categories. This
benchmark systems integrates the Environmental impact and cost categories in form of quantity data
and the technical performance category as qualitative data. This case study closes with the discussion of
the results for the environmental impact and cost categories.
The second part will introduce the concept of regenerative development and discuss how bamboo can
play a significant role on it. Furthermore, it will present a methodology to assess the sustainability of
social housing solutions considering three impact categories: (i) Environmental impact in terms of CO2
emissions; (ii) cost in form of potential revenue generated from the trade of CO2 credits; and (iii) social
based on the potential job creation of each construction material. This section will analyse three
industrialized construction materials: Concrete, Laminated Bamboo and Laminated wood.
On the methodology section of this part the mass flow and dynamic CO2 models for the three
construction materials are described. The functional unit used on each impact category will be further
described. The results part will presents the results for the tree proposed impact categories and the
sustainability assessment for the studied construction materials. These results will be discussed,
considering the effects of the building’s life span; electricity mix; and endo-of-life scenarios on the
results of each category and on the sustainability assessment.
The third part will present the environmental savings potentials from the use of Bahareque (mortar
cement plastered bamboo). This section will introduce the challenges faced in Europe and specifically
in Switzerland specifically on the field energy efficiency. The methodology part of this section will
describe the set-up of a comparative LCA of walls. The functional units and comparison parameter are
further described on this part.
The results will present the environmental impacts associated to the production of each construction
materials. Using a normalisation process this section will show the potential environmental saving from
102
the use of Bahareque when compared to conventional construction materials. These results will be
discussed on the final part, by considering the effects of uncertainties related to the main system
boundaries: Buildings physics calculations; life span and maintenance; and the selected environmental
impact evaluation method.
103
4.1. Sustainability of transitional shelters -- Variability on design and transport
Global or local construction materials for post-disaster reconstruction? Sustainability assessment
of twenty post-disaster shelter designs
Building and Environment 92 (2015) 692e702 – Best Paper of the year 2015
4.1.1. Introduction
The number and intensity of natural disasters is growing every year, with 394 major events affecting
over 268 million people worldwide in the past decade [1]. After a natural disaster, people whose homes
have been destroyed will go to great lengths to secure shelter again [2]. Post-disaster shelters, also known
as transitional shelters, have been defined by the International Federation of Red Cross and Red Crescent
Societies as rapid post-disaster living quarters constructed from materials that can be upgraded to or re-
used in more permanent structures or relocated from temporary sites to permanent locations[2]. Post-
disaster shelters are designed to facilitate the transition of affected populations to more durable housing
solutions. Transitional shelters respond to the fact that post-disaster shelters are often built by the
affected population themselves and that this resourcefulness and self-management should be supported
[3].
For over a decade, the need for a sustainability assessment of the built environment has driven the
development of methods and tools [4] for assessing different types of residential, commercial and
institutional buildings. These methods and tools emphasize the environmental impacts related to the life
cycle of buildings; however, a building can only be considered sustainable after accounting for its
economic, social and cultural dimensions [5]. Furthermore, these methods assess buildings against a set
of predesigned criteria and are thus not useful for selecting optimal project options [6]. International
efforts to measure sustainability have been conducted, but a multidimensional approach has only been
considered in a few cases. Most cases focus on environmental aspects and overlook other aspects, such
as economic, social, or cultural aspects [7]. The investigation of these aspects is hindered by
methodological limitations and insufficient stakeholder integration [8]. Although the different
dimensions of sustainability are usually considered complementary, it can be argued that connections
and dynamics exist among them. Systems approaches accounting for these interconnections are very
important to assessing sustainability and can be considered as one of the most difficult elements to
implement in an assessment tool or method [9].
The utilization of this approach becomes even more challenging when aiming to assess the sustainability
of buildings due to the intrinsic complexity of life cycle assessment (LCA) [10]. When constructing
buildings, the most fundamental decisions are made during the design phase of the project. During this
phase, little data are available regarding the amounts of materials, material producers, transportation,
104
buildings life span and costs [11, 12]. A significant amount of the lifetime impacts of buildings can be
related to the decisions made during the early design stages. Thus, it is important for builders and
designers to assess the sustainability of their choices even when data are lacking [13]. The selection of
sustainable options for buildings projects depends strongly on a holistic approach that considers the
technical and economic aspects as well as the environmental, cultural and social aspects [14].
Two main approaches are used for sustainability assessments: indicator-based and life-cycle-based
approaches. The indicator-based approach is useful for projects in which data are available and
demonstration buildings have already been constructed [15]. This approach facilitates the selection of
pre-established options but is limited regarding its application to other projects outside of the pre-
established options. On the other hand, LCA is an umbrella method that can be adapted to assess specific
sustainability dimensions. The models used in LCA usually propose cause-effect relationships between
the environment and human activities and highlight their impacts and consequences [16]. However, this
same cause-effect relationship occurs in economic and social dimensions as well. To assess these
dimensions, the life cycle cost [17] and social life cycle [18, 19] can be used. The main advantage of
this approach is that every dimension will be analysed using an overreaching methodology, which makes
the results more consistent and meaningful. Nevertheless, the application of LCA faces many challenges,
such as the allocation of impacts [20, 21], end-of-life scenarios [22, 23], and system boundaries [24].
More importantly, limited data availability and quality hinders the widespread application of LCA [25-
28].
Regarding reconstruction efforts after disasters and/or crisis, sustainability assessment can help ensure
that the necessary quantity and quality of environmental resources upon which the community relies are
maintained [29]. Every post-disaster reconstruction project is faced with the challenge of quickly
responding to the crisis at hand using either global or local materials [30]. In post-disaster scenarios, a
large amount of resources is needed. However, in many cases, no capacity is available for transforming
these resources into housing units. Furthermore, in many cases, the skilled labour force is not large
enough to undertake reconstruction efforts [31]. The question of global vs. local materials goes beyond
the availability of the materials in a crisis situation. Local materials can be characterized by their use on
traditional and vernacular architecture, like bamboo, earth/soil and wood. The constructive practices
related to them are usually geographically and culturally constrained. Global materials are generally
industrialized and engineered construction materials like concrete and steel. This materials are widely
applied not only on infrastructure projects but also housing regardless of the location and/or culture.
Local materials require an emphasis on structural design to produce structures that can withstand natural
hazards, which increases their economic and environmental costs and requires specialized engineers and
construction workers. In contrast, global materials can provide efficient structures that can resist natural
hazards with much higher embedded energy than local materials. For this type of project, the low skill
labour and minimal engineering proficiency often available in the affected regions are sufficient.
105
In this study, twenty transitional shelters were identified in eleven different locations worldwide:
Afghanistan, Bangladesh, Burkina Faso, Haiti, Indonesia, Pakistan, Peru, Philippines, Sri Lanka,
Vietnam and Nicaragua. Six construction materials were assessed: bamboo, bricks, concrete, steel,
stone, and wood. Two types of shelters were identified: transitional and core shelters [2, 3, 32, 33] as it
can be seen on table 4-1.
Table 4-1 Shelters' location, structural material and type
Source: [2, 3, 32, 33] The objective of the study was to identify which strategy for post-disaster reconstruction is most
appropriate: using local or global materials. To compare different transitional shelters, their
environmental, economic, and mechanical/technical performances were compared using a benchmark
system.
4.1.2. Methodology For the sustainability assessment of the shelters, three categories were defined. The environmental
impact category accounted for the effects on the natural environment of the production and transport of
construction materials and the construction of shelters. Cost was associated with the purchase and
transport of construction materials and the erection of shelters. Finally, technical performance was
related to the risk zones in which the communities live as well as the mechanical performance of the
Code Location Structural Material Type
B1 Afghanistan Bamboo TransitionalB5 Indonesia Bamboo TransitionalB8 Philippines Bamboo Core
C2 Bangladesh Concrete CoreC6 Pakistan Brick CoreC8 Philippines Concrete/Timber CoreC9 Sri Lanka Concrete CoreC11 Nicaragua Ferrocement Core
S4 Haiti Steel TransitionalS5 Indonesia Steel TransitionalS10 Vietnam Steel Transitional
W3 Burkina Faso Timber TransitionalW4(A) Haiti Timber TransitionalW4(B) Haiti Timber TransitionalW4(C) Haiti Timber Transitional
W5 Indonesia Timber CoreW6 Pakistan Timber/Stone TransitionalW7(A) Peru Timber TransitionalW7(B) Peru Timber Transitional
W8 Philippines Timber Transitional
106
shelters during the occurrence of a natural hazard event, such as earthquakes, winds, and /or flooding.
The aim of this methodology is to compare the sustainability performance of the shelters. To achieve
this goal, it was necessary to develop a functional unit for each category. These functional units allow
the comparisons across not only shelters but also categories, which increases the consistency of the
results. The two main factors we identified for the development of functional units: life span and area
covered. The life span of the shelters accounts for the fact that some of these structures are temporary,
intended to be relocated or dismantled, and thus might require less material. This is very important
because if the life span is not considered, then the best-performing shelters are those that are the lightest
and least durable, which is not always the best solution for a post-disaster reconstruction project. The
expected shelter’s lifespans used on the calculations were taken from the reports of the International
federation of red cross societies [2, 3]. These reports present estimated lifespans for the studied shelters
based on their application on the field. The second factor (covered area) represents a series of technical
and social issues. It is clear that a larger covered area provides more useful space for future inhabitants
of these shelters, which results in a better sense of privacy, cultural adaptation and health. For the
environmental impact category, the functional unit was defined as the ratio between the shelters’
environmental impact and its covered area and life span. The functional unit for the cost category was
defined as the ratio between the projects’ cost per shelter, its covered area and its life span in months.
For the technical category, the functional unit was defined as the ratio between the risk zone in which
the shelter was located and the shelter’s mechanical performance in the case of a natural event. The
methodologies used to assess each category’s environmental impact, cost and technical performance are
described in the following sections.
4.1.2.1. Environmental impact
Life cycle assessment was used to evaluate the environmental impacts of the twenty proposed
transitional shelter design options. This assessment method was developed to quantify the material use,
energy use, and environmental impact associated with specific products, services, and technologies.
LCA is described and standardized in ISO1440 [34] and consists of four steps: the definitions of goal
and scope, the development of life cycle inventories, an impact assessment, and interpretation [35]. Over
the past few decades since its development, LCA has been established as the main method for
quantitatively assessing the environmental impacts of goods and processes throughout their life spans.
LCA models assume cause-effect relationships between the environment and human activities and
highlight their impacts and consequences [16]. The term "environmental impact" is used in LCA to refer
to the effects of the studied system on the environment. These impacts depend directly on the evaluation
method used during the impact assessment step. For this research project, the IMPACT 2002+ [36]
evaluation method was used for the impact assessment. This method models the cause-effect chain up
to the end point or damage point. This type of evaluation method is known as damage-oriented and is
very useful in assessments that have a global context. In this method, four categories are considered:
107
human health as assessed by the disability-adjusted life year (DALY); ecosystem quality as assessed by
the potentially disappeared fraction (PDF) over a certain area and during a certain period per kg of
emitted substance (PDF.m2.yr); climate change as assessed by the global warming potential as described
by the Intergovernmental Panel on Climate Change [37] (IPCC) in terms of kg CO2 equivalents; and
resources as assessed by the energy demand in mega joules (MJ). The results are normalized for the
respective impact categories using the following factors, which represent the yearly emissions of one
European citizen: 0.0071 DALY, 13,700 PDF.m2.yr, 9,950 kg CO2, and 152,000 MJ[36]. This allows
the results to be expressed in a single unit of points easing the processing of the results but makes them
sensitive to the normalization factor. The values used on the normalization process can be considered
as a good proxy for calculation on a global scale. As a final step, the results for the four impact categories
are summed, considering an equal contribution from each impact category to the total result, and
presented as a single score[36].
To calculate the environmental impacts of buildings, it is necessary to know the amounts of materials
required to erect one building and the distances that the materials need to travel from the production site
to the building’s final location. The amounts and locations of the materials for the shelters were
determined from the following reports: 8 shelter designs [2]; 10 post-disaster shelter designs [3]; the
environmental impact of brick production outside of Europe [32]; and the optimization of bamboo-based
post-disaster housing units for tropical and subtropical regions using LCA methodologies [33]. These
reports include bill of quantities, plans, performance analysis, and lifespan of the studied shelters. To
develop the Life Cycle Inventories (LCI), all the amounts were converted into mass (kg) units and the
transport distance into ton x km. These LCIs represent the production phases of each shelter and the
transportation distances for the construction materials. Two types of distances were included, local
(road) and international (freight ship), which were estimated based on the area of the country of study.
A relationship between a country’s area and construction material transport distances was defined based
on the literature [32, 38-45]. This trend is described by the following formula:
Transport distance= 76.275 * Ln(country area (sq.km))- 621.59 (1)
Note that this trend applies to countries with areas greater than 8870 km2. When the area was equal to
or smaller than this value, the minimum transport distance was used for these calculations. The freight
ship was calculated on a case specific basis. In cases like Haiti where many construction materials were
imported so an extra international freight ship transport was calculated. Furthermore, steel was
considered to be mainly imported product and additional international freight ship transport was
considered. All of the LCA calculations were performed using SIMApro v 7.33 software [46] and the
EcoInvent 2.7 database [47].
The life cycle inventories (LCIs) for the twenty studied shelter designs are presented in tables 4-2
through 4-6.
108
Table 4-2 LCIs bamboo based shelters
B1 AFGHANISTAN
BAMBOO B5 INDONESIA
BAMBOO B8 PHILIPINES
BAMBOO
Materials Amount Unit Amount Unit Amount Unit
bamboo pole, gen 8.44 kg 160.0 kg
bamboo mats 67.7 kg 3370.0 kg
Plywood, outdoor use 38.37 kg
Packaging film, LDPE 128.94 kg
Ceramic tiles 1087.5 kg
Concrete, normal 856.8 kg 4190.0 kg
Reinforcing steel 1.2 kg 350.0 kg
Steel 1.0 kg 10.0 kg
Galvanized steel sheet 130 kg
Transport Amount Unit Amount Unit Amount Unit
Total land transport 11.4 tkm 239 tkm 239.4 tkm
Total transoceanic transport 6.4 tkm 6.7 tkm
Lifespan Amount Unit Amount Unit Amount Unit
Shelter’s lifespan 12 month 60 month 120 month
Source: Authors
Table 4-3 LCIs mineral based shelters
C2 BANGLADESH CONCRETE /
STEEL
C6 PAKISTAN CONCRETE /
BRICK
C8 PHILIPPINES CONCRETE /
TIMBER
C9 SRI LANKA CONCRETE /
TIMBER
C11 NICARAGUA FERROCEMENT
Materials Amount Unit Amount Unit Amount Unit Amount Unit Amount Unit
Concrete, normal 446.3 kg 2815.8 kg 771.1 kg 3449.0 kg 3449.0 kg
Steel 308.0 kg 264.0 kg
Reinforcing steel 354.0 kg 12.0 kg 12.0 kg
Light clay brick 1265.0 kg 20140.0 kg
Sawn timber 148.0 kg 395.0 kg 122.0 kg
Bamboo mats 590.0 kg
Galvanized steel sheet 217.0 kg 135.0 kg 130.0 kg 130.0 kg
Ceramic tiles 714.0 kg
Plywood, outdoor use 109.0 kg
Bitumen sealing V60 14.0 kg
Ferro cement panels 3543.0 kg
Transport Amount Unit Amount Unit Amount Unit Amount Unit Amount Unit
Total land transport 216.3 tkm 3375.69 tkm 459.87 tkm 111.81 tkm 111.39 tkm Total transoceanic transport
6133.0 tkm 2473.68 tkm 0 tkm 982.64 tkm 982.6 tkm
Lifespan Amount Unit Amount Unit Amount Unit Amount Unit Amount Unit
Shelter’s lifespan 60 month 120 month 60 month 120 month 120 month
Source: Authors
109
Table 4-4 LCIs steel based shelters
S4 HAITI STEEL S5 INDONESIA
STEEL S10 VIETNAM
STEEL
Materials Amount Unit Amount Unit Amount Unit
Concrete, normal 3655.7 kg 856.8 kg 7197.1 kg
Steel 4973.8 kg 716.4 kg 7776.9 kg
Reinforcing steel 22.2 kg 102 kg
Sawn timber 272.9 kg 956.8 kg 2.0 kg
Galvanized steel sheet 217.0 kg 159.9 kg 164.3 kg
Plywood, outdoor use 159.7 kg 74.3 kg
Packaging film 8.6 kg
Transport Amount Unit Amount Unit Amount Unit
Total land transport 1909.5 tkm 746.1 tkm 5356.9 tkm
Total transoceanic transport 13571.5 tkm 3061.2 tkm 14638.1 tkm
Lifespan Amount Unit Amount Unit Amount Unit
Shelter’s lifespan 24 month 60 month 60 month
Source: Authors
Table 4-5 LCIs wood based shelters (part 1)
W3 BURKINA
FASO TIMBER W4(A) HAITI
TIMBER W4(B) HAITI
TIMBER W4(C) HAITI
TIMBER W5 INDONESIA
TIMBER
Materials Amount Unit Amount Unit Amount Unit Amount Unit Amount Unit
Concrete, normal 6578.6 kg 6136.12 kg 1399.4 kg 5355 kg 1066.2 kg
Steel 3.9 kg
Palm leaves 124.8 kg
Sawn timber 139.7 kg 629.4 kg 836.8 kg 950.7 kg 324.1 kg
Packaging film, LDPE 99.5 kg 3.4 kg
Galvanized steel sheet 183.1 kg 135.6 kg
Bamboo mats 7.1 kg
Plywood, outdoor use 161.57 kg 576.6 kg 61.78 kg Fibre cement corrugated slab 376.2 kg
Transport Amount Unit Amount Unit Amount Unit Amount Unit Amount Unit
Total land transport 221.4 tkm 71.1 tkm 29.5 tkm 67.4 tkm 565.8 tkm
Total transoceanic transport 0.0 tkm 14404.0 tkm 6898.9 tkm 10965.7 tkm 24.5 tkm
Lifespan Amount Unit Amount Unit Amount Unit Amount Unit Amount Unit
Shelter’s lifespan 24 month 60 month 120 month 60 month 12 month
Source: Authors
110
Table 4-6 LCIs wood based shelters (part 2)
W6 PAKISTAN TIMBER /
STONE W7(A)PERU
TIMBER W7(B)PERU
TIMBER
W8 PHILIPPINES
TIMBER
Materials Amount Unit Amount Unit Amount Unit Amount Unit
Concrete, normal 4284.0 kg 4284.0 kg 1373.6 kg
Steel 190.0 kg 28.1 kg 78.1 kg
Light clay brick 7980.0 kg
Natural stone plate 81.0 kg
Sawn timber 215.6 kg 1643.1 kg 101.0 kg 339.7 kg
Packaging film, LDPE 139.0 kg 50.0 kg
Galvanized steel sheet 124.0 kg
Bamboo mats 29.0 kg 314.0 kg
Flattened bamboo 32.0 kg
Plywood, outdoor use 241.4 kg
Fibre cement corrugated slab 306.0 kg
Reinforcing steel 65.0 kg 51.0 kg
Transport Amount Unit Amount Unit Amount Unit Amount Unit
Total land transport 993.2 tkm 632.6 tkm 557.2 tkm 314.4 tkm
Total transoceanic transport 2648.5 tkm 477.2 tkm 773.4 tkm 364.0 tkm
Lifespan Amount Unit Amount Unit Amount Unit Amount Unit
Shelter’s lifespan 24 month 24 month 12 month 60 month
Source: Authors
4.1.2.2. Cost
Life cycle cost analysis is often used to identify the costs of efficient solutions for building design
options [48]. Although it is more often applied to the design phase than environmental LCA [49], the
challenges are similar, such as data availability and quality. Moreover, the life cycle cost analysis of
buildings is extremely complex because it includes such factors as the life span of the buildings,
maintenance regimes for different building components, and costs of transporting construction materials
from production centres to construction sites [17]. For transitional shelters, this complexity increases
because these factors are associated with natural hazards [50]. Furthermore, post-disaster reconstruction
projects that use transitional shelters encounter unforeseeable challenges, such as shortages of resources
and human talent, recurring natural disasters, corruption and crime. These factors make it extremely
difficult to assess the real costs per unit produced. Using the currently available data, which mainly
consist of the total costs of reconstruction projects, it is very difficult to determine the life cycle costs of
transitional shelter designs. The International Federation of Red Cross Associations estimates that the
cost per unit ranges from 500 Swiss Francs (CHF) to 2500 CHF [3]. Two types of costs are proposed:
the approximate material cost per shelter and the approximate project cost.
To assess the cost categories in this study, an approximate project cost was used. This decision was
based on two factors. First, the project costs were known for most of the studied transitional shelter
design options. Second, this value represents the different challenges and unforeseen situations that may
111
occur in post-disaster reconstruction projects. Moreover, the life span of the shelter designs was
considered to be a determining factor of the cost assessment. The life span was included in these
calculations to compare rapid relief, transitional and core shelters. Finally, the covered area was also
considered because it was included in the environmental impact category. These sets of factors that
consider the functional units in the environmental impact and cost categories allow for comparisons
among shelter design options and across categories. This is the basis for developing a benchmark system
used to compare all twenty shelter design options.
4.1.2.3. Technical performance
This category evaluates the technical performance of the twenty shelter design options by estimating the
hazard risks at each location and the expected shelter performance for a natural disaster. The IFRC
defined on their reports [2, 3] three levels (low, medium, and high) of each of three different types of
hazard risks (earthquake, wind, and flood risks), as described in Table 4-7.
Table 4-7 Hazard risk classification
Hazard risk classification used in Section B for earthquake, wind and flood
Classification used
Earthquake Wind (approximate) Flood
Seismic Design
Category *
Basic Wind Speed **(km/hr)
Saffir/Simpson Hurricane Category
LOW B <113 < 2 Low risk
MEDIUM C 113-160 1 -- 2 Medium risk
HIGH D >160 3 -- 5 High risk * This information is based on ASCE/SEI 7-10, Table 11.6-1 assuming Risk Category I (Table 1.5-1 representing a low risk to human life in the event of failure) and based on the modified PGA. ** The sustained 3-s gust speed at a height of 10 m in flat open terrain for a 50-year return period (as defined in the International Building Code (IBC) 2009, Section 1609). Source: IFRC [3] The shelter’s performance for each hazard were described using three levels in the report 0 post-disaster
shelter designs [3]. Green (Adequate) indicates that the structure meets the safety standards described
by the International Building Code or local standards.[3] Amber (Acceptable) indicates that the
structural system does not fully meet the requirements of the International Building Code but the reduced
design loads will not cause failure of individual members of the structural system[3]. Finally, red
(Inadequate) indicates that the reduced design loads will result in either complete failure of individual
members or overall collapse of the structural system[3]. The hazard risk and performance of the shelters
was described on the reports: 8 shelter designs [2]; 10 post-disaster shelter designs [3]; the
environmental impact of brick production outside of Europe [32]; and the optimization of bamboo-based
post-disaster housing units for tropical and subtropical regions using LCA methodologies [33]. A
112
summary of the hazard risk at location and the technical performance of the twenty shelters is presented
on table 4-8.
Table 4-8 Shelter's hazard at location and performance
Shelter location - Material
Earthquake Wind Flood
Hazard @ Location
Shelter's Performance
Hazard @ Location
Shelter's Performance
Hazard @ Location
Shelter's Performance
B1 Afghanistan Bamboo High Adequate High Acceptable Low Inadequate
B5 Indonesia Bamboo High Inadequate Low Acceptable High Acceptable
B8 Philippines Bamboo High Adequate High Adequate High Acceptable
C2 Bangladesh Steel High Adequate High Inadequate High Adequate
C6 Pakistan Steel Medium Adequate Acceptable Acceptable High Adequate
C8 Philippines Concrete High Acceptable High Inadequate Low Acceptable
C9 Sri Lanka Concrete Medium Adequate Medium Inadequate High Adequate
C11 Nicaragua Ferro cement Medium Adequate Medium Adequate Medium Acceptable
S4 Haiti Steel High Inadequate Very High Inadequate High Adequate
S5 Indonesia Steel High Acceptable Low Inadequate High Adequate
S10 Vietnam Steel Low Acceptable Medium Inadequate High Adequate
W3 Burkina Faso Timber Low Adequate Low Adequate High Inadequate
W4(A) Haiti Timber High Adequate High Acceptable High Adequate
W4(B) Haiti Timber High Adequate High Acceptable High Adequate
W4(C) Haiti Timber High Acceptable High Acceptable High Adequate
W5 Indonesia Timber High Inadequate Low Inadequate High Adequate
W6 Pakistan Timber Medium Adequate Medium Acceptable High Adequate
W7(A) Peru Timber High Inadequate Medium Inadequate Medium Inadequate
W7(B) Peru Timber High Inadequate Medium Inadequate Medium Inadequate
W8 Philippines Timber High Acceptable High Acceptable Low Adequate Source: [2, 3, 32, 33] To assess the technical performance of the shelters, a matrix was developed wherein scores were defined
for each hazard level and structure performance. The best score (6) is obtained when the structure
performs adequately at the “high” hazard level, and the lowest score (2) is awarded when the structure
would collapse (inadequate) at the “low” level of hazard risk, as presented in Table 4-9. The scores
were calculated individually for each hazard risk type: earthquake, wind, and flood. The scores were
then aggregated for the final assessment.
Table 4-9 Technical performance assessment matrix
Hazard/Performance Adequate Acceptable Inadequate
High 6 5 4 Medium 5 4 3
Low 4 3 2 Source: Authors
113
4.1.3. Results This section presents the result for the three proposed impact categories, the environmental impact, cost
and technical performance, and the sustainability assessment. To assess the sustainability of these
shelters and determine which post-disaster reconstruction strategy is the most appropriate, the results
from the impact categories were combined using a benchmark system. To clearly present the results, the
shelters were coded according to the main construction materials: B for bamboo, C for concrete, S for
steel, and W for timber. The locations in Afghanistan, Bangladesh, Burkina Faso, Haiti, Indonesia,
Pakistan, Peru, Philippines, Sri Lanka, Vietnam and Nicaragua were assigned numbers of 1 to 11,
respectively.
4.1.3.1. Environmental impact
The results from this category indicate that the impact per functional unit of the shelters varies widely,
as shown in Figure 4.1. Furthermore, the impact per functional unit is not directly correlated with the
main construction material, in contrast with steel-based shelters. Steel-based shelters present the results
with the highest variation, with the Haiti steel shelter having the highest impact and the Indonesian steel
shelter having the lowest impact. Further analysis of the shelter LCIs (Tables 4-2…4-6) indicates a
significant difference between the amounts of materials used, which resulted in a much higher
environmental impact for steel shelters in Haiti than in Indonesia. The concrete-, brick-, and wood-based
shelters presented a similar range of impacts but with smaller variations between the results than the
steel-based shelters. The bamboo-based shelters have some of the lowest impact levels per functional
unit and the narrowest range of impacts. Thus, these bamboo-based solutions offer the best potential for
reducing the environmental impact of the studied construction materials. It is important to recall that the
availability of construction materials is critical and that transport distances influence their impact. These
results show that appropriate design and material selection play an important role in the performance of
these shelters.
114
Figure 4.1 Environmental impact per functional unit Materials: Bamboo (B), Brick/Concrete (C), Steel (S), Wood (W). Locations: Afghanistan (1), Bangladesh (2), Burkina Faso (3), Haiti (4), Indonesia (5), Pakistan (6), Peru (7), Philippines (8), Sri Lanka (9), Vietnam (10) and Nicaragua (11).
To better understand the environmental impacts of the studied shelter design options, a process
contribution analysis was carried out. The impacts of the construction materials were aggregated around
their main components: foundation, structure walls, and roof. An additional contribution related to the
transport of construction materials was observed, as presented in Table 4-10. This type of analysis can
reveal the hot spots in each shelter design. After studying these 5 components over 20 designs, it was
not possible to establish a general correlation between the construction materials and their environmental
impacts. All components significantly contributed to the environmental impacts on a case-specific basis.
These impacts varied widely between the components and shelter designs.
115
Table 4-10 Contribution from components to environmental impact
Code Location Structural Material
Foundation Structure Walls Roof Transport
mPt/m2/month mPt/m2/month mPt/m2/month mPt/m2/month mPt/m2/month
B1 Afghanistan Bamboo 0.032 0.006 0.052 0.265 0.002
B5 Indonesia Bamboo 0.011 0.103 1.29E-06 0.215 0.017
B8 Philippines Bamboo 0.008 0.027 0.064 0.015 0.001
C2 Bangladesh Concrete 0.228 0.041 0.089 0.049 0.065
C6 Pakistan Concrete 0.022 0.330 0 0.076 0.157
C8 Philippines Concrete 0.009 0.045 0.053 0.017 0.013
C9 Sri Lanka Concrete 0.568 0.129 0.156 0.216 0.144
C11 Nicaragua Ferrocement 0.116 0.255 0 0.104 0.062
S4 Haiti Steel 0.175 2.543 0.409 0.022 0.620
S5 Indonesia Steel 0.047 0.106 0.116 0.021 0.061
S10 Vietnam Steel 0.070 0.947 0.033 0.018 0.341
W3 Burkina Faso Timber
0.093 0.020 0.056 0.032 0.018
W4(A) Haiti Timber 0.086 0.087 0.093 0.028 0.070
W4(B) Haiti Timber 0.009 0.050 0.145 0.009 0.015
W4(C) Haiti Timber 0.059 0.104 0.028 0.047 0.043
W5 Indonesia Timber 0.090 0.324 0.018 0.176 0.263
W6 Pakistan Timber 0.075 0.542 0.113 0.254 0.195
W7(A) Peru Timber 0.251 0.843 2.85E-05 0.145 0.153
W7(B) Peru Timber 0.353 0.452 0.051 0.257 0.279
W8 Philippines Timber 0.048 0.056 0.151 0.022 0.031
Source: Authors
4.1.3.2. Cost assessment
The results from the cost assessment varied widely, as shown in figure 4.2. Six shelter designs resulted
in values of less than 1 CHF/m2/month, while 15 of the 20 studied shelters achieved values of less than
2 CHF/m2/month. These values indicate no correlation between the material and the proposed functional
unit. An important factor for assessing this category is the life span of the shelters, which can determine
the success of a reconstruction project. From the results shown in Figure 3, it is possible to note that 15
out of the 20 shelters had excellent cost-life span relationships. Further analysis of this category is not
possible due to a lack of disaggregated information regarding of the costs of materials, transport and
construction. It is important to remember that these values are highly case-dependent. Due to a number
of unforeseen events and costs associated with the production of this type of building, the variability
and uncertainty of the results are very high.
116
Figure 4.2 Cost assessment Materials: Bamboo (B), Brick/Concrete (C), Steel (S), Wood (W). Locations: Afghanistan (1), Bangladesh (2), Burkina Faso (3), Haiti (4), Indonesia (5), Pakistan (6), Peru (7), Philippines (8), Sri Lanka (9), Vietnam (10) and Nicaragua
4.1.3.3. Technical assessment
The technical assessment category was sub-divided into three categories to evaluate the performances
of the shelters during flood, wind, or earthquake disasters. Each of these sub-categories was assessed
using the matrix described in the methodology (table 4-9). The assessment scores can range from 2
points to 6 points, and the aggregated values range from 6 to 18 points. The results are presented as
contributions to the performance for the three components individually and summed in figure 4.3. From
this figure, is possible to note that 15 out of the 20 shelters achieved scores equal or above the average
for this whole category. Furthermore, most of the shelters performed well in earthquake and flood
events. However, most of the shelters had relatively low performance in high winds. This result is
significant because wind events such as hurricanes and typhoons occur periodically, while earthquakes
and floods occur randomly. These results show that the technical performance of the shelters is not
perfectly correlated with their construction materials and/or techniques, instead depending on the
structural design used for each risk zone.
117
Figure 4.3 Technical performance. Materials: Bamboo (B), Brick/Concrete (C), Steel (S), Wood (W). Locations: Afghanistan (1), Bangladesh (2), Burkina Faso (3), Haiti (4), Indonesia (5), Pakistan (6), Peru (7), Philippines (8), Sri Lanka (9), Vietnam (10) and Nicaragua (11).
4.1.3.4. Sustainability assessment
To assess the sustainability of the studied shelter designs, a benchmark system was developed. This
benchmark system combined the three proposed assessment categories, environment, cost and technical
performance, as observed in figure 4.4. The results for the environment category are shown on the x-
axis, and the results for the cost category are shown on the y-axis. The results for the technical category
are represented on a numeric/colour scale, in which 10 points (red) is the lowest score and 17 points
(blue) is the highest. In this system, the best performance area is located near the origin and above 12
points (light brown) on the numeric/colour scale.
The studied shelters present very similar performances for the three categories, except for S4 in Haiti.
The results for this shelter were so extreme that it was necessary to remove it before performing further
calculations. These results show that shelters with high technical performance can be achieved
inexpensively and with low environmental impact per functional unit, as shown in Figure 4.
It is important to note that ten out of the twenty shelter designs were located in the figure’s “best
performance” area, with environmental performance values below 0.6 mPt/m2/month and costs below 2
CHF/m2/month. Of these ten designs, nine have scores above the average score of the technical
performance category.
118
Further analysis showed that it could be more cost effective to improve the technical performances of
some shelters, such as B5, W6, and S10, than to reduce the cost or environmental impact of other
shelters, such as S4, S5, W3, and W5. Moreover, special attention should be paid to improving
earthquake and wind resistance, which will increase the shelter’s overall technical performance. An
important factor for which improvements could be cost effective is the life span of the shelter designs.
The results showed that an appropriate balance between the environmental impact of the construction
materials, their costs and the shelter life spans is important for the sustainability of these shelters.
Furthermore, although the material and sustainability performance are correlated, the limits of this
relationship need to be discussed further. From figure 4.4, it is possible to see that the best performance
can be achieved using bamboo, wood, or concrete. However, shelters using these construction materials
also performed worse in the three proposed categories.
These results indicated that reconstruction strategies that used global materials, such as concrete and
steel, and those that used local materials, such as bamboo and wood, can both provide sustainable
reconstruction solutions when the shelter design allows for efficient material use. Moreover, the
sustainability of these strategies must be assessed on a case-specific basis by considering such factors
as the availability of materials and a skilled work force. Local materials, such as bamboo or earth/soil,
can easily achieve high environmental and/or cost performance. However, achieving high technical
performance using these materials requires high levels of knowledge regarding structural design. In
addition, global materials, such as concrete or steel, which are costly and require large amounts of energy
to produce, can be used to produce shelters with high technical performance.
119
Figure 4.4 Sustainability assessment Materials: Bamboo (B), Brick/Concrete (C), Steel (S), Wood (W). Locations: Afghanistan (1), Bangladesh (2), Burkina Faso (3), Haiti (4), Indonesia (5), Pakistan (6), Peru (7), Philippines (8), Sri Lanka (9), Vietnam (10) and Nicaragua (11).
4.1.4. Discussion This research aims to develop a method for assessing transitional shelter options while emphasizing the
selection of construction systems that can produce disaster-resistant buildings with low cost and
environmental impact. To achieve this goal, three impact categories were defined. In the work of Mateus
et al. [5], three dimensions were split into nine categories with twenty-five indicators. However, this
approach is time-consuming, which makes it less suitable for post-disaster reconstruction projects. The
proposed functional unit aims to address these complexities by using a combination of three easily
measured factors for a single category/indicator. This approach is useful for not only assessing the core
and transitional shelter options but also comparing them.
Sensitivity analyses considering the variability of the results from the construction material perspective
were used to validate the outcomes. To better understand how the results vary, the shelters were clustered
around the main construction materials used. Four clusters were defined: bamboo, wood, steel and
concrete/brick. For each construction material cluster, the mean, lowest and highest values were
calculated. This analysis was performed for the three proposed categories of environment, cost and
technical performance. For the technical performance category, these analyses showed that all of the
construction materials were capable of producing disaster-resilient shelters with above-average scores.
120
The concrete-based shelters had the best performance in this category, with the highest mean value (14.2
points) and the narrowest variation of results for the construction materials. The bamboo and wood
clusters had very similar mean values of 13.3 and 13.4 points, respectively, with much wider variations.
The steel cluster had a mean score of 12.7 and a narrow range.
The environmental impact and cost categories were further analysed using a new benchmark with values
from the clusters, as shown in figure 4.5. This figure shows that the bamboo-based shelters have the
lowest impact and cost per functional unit. In addition, figure 5 shows that the best concrete and wood
shelters perform better than the worst bamboo shelters. This result reaffirms our previous statement,
indicating that appropriate design and material selection are key parameters for these types of buildings.
Moreover, these results agree with the results of Wallbaum et al. [15], who identified bamboo, concrete
and wood as the most promising technologies in the field of affordable housing. Similarly, a study
conducted by Cabeza et al. [51] indicated that these construction materials will result in the same ranking
as shown in figure 4.5 in terms of embedded energy per square meter of build area.
Figure 4.5 Variability analysis.
These studies [15, 51] show that the differences in the performances of the studied construction materials
were not significant, supporting the idea that either local or global materials can produce sustainable
solutions. Nonetheless, lower environmental impacts and costs are can be easier be achieved when using
either bamboo, concrete or wood. However, these performances can only be achieved if the materials
121
are available and the workers possess the necessary skill and knowledge. Thus, the sustainability
assessment of these shelter designs can highlight the potentials of either reconstruction strategy.
4.1.5. Conclusions From the studied sample shelters, it was concluded that the proposed functional unit produces
comparable results for diverse construction materials and shelter types. Furthermore, the method
developed here allowed us to identify the most promising material and design combination able to
withstand local natural hazards with the lowest economic and environmental costs. From these results,
it was observed that shelters with high cost and/or environmental impact do not necessarily perform the
best from a technical viewpoint. Furthermore, no direct correlation between the type of construction
material and the shelter sustainability was found. However, it is clear that proper design and material
selection drive the sustainability performance of the studied shelter designs. In addition, both global and
local construction materials can be used to produce sustainable solutions for post-disaster reconstruction
projects, with local materials having higher potential for low environmental impacts and costs and global
materials having higher potential to produce better technical performances. These results show that
shelters with high technical performance can be achieved under low price/low environmental impacts
per functional unit. Although local constructive systems can provide the best compromise between
environmental impacts and cost, their structural design requires more effort.
4.1.6. Acknowledgements The authors would like to thank the students that took part in the BSc and MSc Project in 2013-14 that
contributed to this project. In addition, we thank the International Federation of the Red Cross and Red
Crescent Societies for support and advice. Finally, we thank EcoSur for their invaluable contributions
to this research and HILTI AG for their long-term support in the development of the present research
project.
4.1.7. References 1. Guha-Sapir, D., et al., Annual disaster statistical review 2011: the numbers and trends. 2012,
Brussels: Centre for Research on the Epidemiology of Disasters (CRED). 2. IFRC, Transitional shelters – eight designs. 2011, International Federation of Red Cross and
Red Crescent Societies: Geneva, Swtizerland. 3. IFRC, Post-disaster shelter: ten designs. 2013, International Federation of Red Cross and Red
Crescent Societies: Geneva, Swtizerland. 4. Haapio, A. and P. Viitaniemi, A critical review of building environmental assessment tools.
Enviro Impact Assess Rev, 2008. 28(7): p. 469-482. 5. Mateus, R. and L. Bragança, Sustainability assessment and rating of buildings: developing the
methodology SBTool PT–H. Build Environ, 2011. 46(10): p. 1962-1971. 6. Ding, G.K., Sustainable construction—the role of environmental assessment tools. J Environ
Manage, 2008. 86(3): p. 451-464. 7. Morel, J., et al., Building houses with local materials: means to drastically reduce the
environmental impact of construction. Build Environ, 2001. 36(10): p. 1119-1126. 8. Pan, W. and Y. Ning, Dialectics of sustainable building: evidence from empirical studies 1987-
2013. Build Environ, 2014(0). 9. Singh, R.K., et al., An overview of sustainability assessment methodologies. Ecol Indic, 2012.
15(1): p. 281-299.
122
10. Pajchrowski, G., et al., Materials composition or energy characteristic – what is more important in environmental life cycle of buildings? Build Environ, 2014. 72(0): p. 15-27.
11. Gervásio, H., et al., A macro-component approach for the assessment of building sustainability in early stages of design. Build Environ, 2014. 73(0): p. 256-270.
12. Gerilla, G.P., K. Teknomo, and K. Hokao, An environmental assessment of wood and steel reinforced concrete housing construction. Build Environ, 2007. 42(7): p. 2778-2784.
13. Basbagill, J., et al., Application of life-cycle assessment to early stage building design for reduced embodied environmental impacts. Build Environ, 2013. 60(0): p. 81-92.
14. Wang, N., Y.-C. Chang, and C. Nunn, Lifecycle assessment for sustainable design options of a commercial building in Shanghai. Build Environ, 2010. 45(6): p. 1415-1421.
15. Wallbaum, H., et al., Indicator based sustainability assessment tool for affordable housing construction technologies. Ecol Indic, 2012.
16. Hellweg, S. and L. Mila i Canals, Emerging approaches, challenges and opportunities in life cycle assessment. Science, 2014. 344(6188): p. 1109-13.
17. Manac’h, Y.-G., B. Khaled, and A. Améziane, Life Cycle Cost through Reliability, in New Results in Dependability and Computer Systems. 2013, Springer. p. 523-530.
18. Dreyer, L.C., M.Z. Hauschild, and J. Schierbeck, Characterisation of social impacts in LCA. Int J Life Cycle Assess, 2010. 15(3): p. 247-259.
19. Weidema, B.P., ISO 14044 also applies to social LCA. Int J Life Cycle Assess, 2005. 10(6): p. 381-381.
20. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part I: goals and scope and inventory analysis. Int J Life Cycle Assess, 2008. 13: p. 290-300.
21. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part II: impact assessment and interpretation. Int J Life Cycle Assess, 2008. 13: p. 374-388.
22. Kim, S., T. Hwang, and K.M. Lee, Allocation for cascade recycling system. Int J Life Cycle Assess, 1997. 2: p. 217-222.
23. Dubreuil, A., et al., Metals recycling maps and allocation procedures in life cycle assessment. Int J Life Cycle Assess, 2010. 15: p. 621-634.
24. Frischknecht, R., LCI modelling approaches applied on recycling of materials in view of environmental sustainability, risk perception and eco-efficiency. Int J Life Cycle Assess, 2010. 15: p. 666-671.
25. Gomes, F., et al., Adaptation of environmental data to national and sectorial context: application for reinforcing steel sold on the French market. Int J Life Cycle Assess, 2013. 18: p. 926-938.
26. Langevin, B., C. Basset-Mens, and L. Lardon, Inclusion of the variability of diffuse pollutions in LCA for agriculture: the case of slurry application techniques. J Clean Prod, 2010. 18: p. 747-755.
27. Mutel, C.L. and S. Hellweg, Regionalized life cycle assessment: computational methodology and application to inventory databases. Environ Sci Technol, 2009. 43(15): p. 5797-803.
28. Sesana, M.M. and G. Salvalai, Overview on life cycle methodologies and economic feasibility for nZEBs. Build Environ, 2013. 67(0): p. 211-216.
29. Moldan, B., S. Janoušková, and T. Hák, How to understand and measure environmental sustainability: Indicators and targets. Ecol Indic, 2012. 17(0): p. 4-13.
30. Prinz, G.S. and A. Nussbaumer, On fast transition between shelters and housing after natural disasters in developing regions, in Technologies for sustainable development: a way to reduce poverty, J.C. Bolay, S. Hostettler, and E. Hazboun, Editors. 2014, Springer: Dordrecht, The Netherlands. p. 225-235.
31. Haigh, R. and R. Sutton, Strategies for the effective engagement of multi-national construction enterprises in post-disaster building and infrastructure projects. International Journal of Disaster Resilience in the Built Environment, 2012. 3(3): p. 270-282.
32. Balzarini, A., Environmental impact of brick production outside Europe, in Department of Civil, Environmental and Geomatic Engineering. 2013, Swiss Federal Institute of Technology ETH Zürich: Zürich.
123
33. Zea Escamilla, E., G. Habert, and L. Lopez Muñoz, Optimization of bamboo based post disaster housing units for tropical and subtropical regions through the use of Life Cycle Assessment methodologies. 2014, Swiss Federal Institute of Technology ETH Zürich: Zürich.
34. ISO, ISO 14040: environmental management- life cycle assessment- principles and framework, ed. ISO. 2007, Geneva, Switzerland: International Organization for Standardization.
35. Bauman, H. and A. Tillman, The hitch hiker's guide to LCA: an orientation in life cycle assessment methodology and application. 2004, Lund. Sweden: Studentlitteratur.
36. Jolliet, O., et al., IMPACT 2002+: a new life cycle impact assessment methodology. Int J Life Cycle Assess, 2003. 8(6): p. 324 - 330.
37. McCarthy, J.J., Climate change 2001: impacts, adaptation, and vulnerability: contribution of Working Group II to the third assessment report of the Intergovernmental Panel on Climate Change. 2001: Cambridge University Press.
38. Raza, M. and Y. Aggarwal, Transport geography of India: Commodity flows and the regional structure of the Indian economy. 1986, New Delhi: Concept Publishing Company.
39. Pulselli, R., et al., Specific emergy of cement and concrete: an energy-based appraisal of building materials and their transport. Ecol Indic, 2008. 8(5): p. 647-656.
40. Koroneos, C. and A. Dompros, Environmental assessment of brick production in Greece. Build Environ, 2007. 42(5): p. 2114-2123.
41. Ozen, M. and H. Tuydes-Yaman, Evaluation of emission cost of inefficiency in road freight transportation in Turkey. Energy Policy, 2013. 62: p. 625-636.
42. Nicolas, J.-P. and D. David, Passenger transport and CO2 emissions: what does the French transport survey tell us? Atmos Environ, 2009. 43(5): p. 1015-1020.
43. Quak, H., Sustainability of urban freight transport: Retail distribution and local regulations in cities. 2008: Erasmus Research Institute of Management (ERIM).
44. de Jong, G., H. Gunn, and M. Ben-Akiva, A meta-model for passenger and freight transport in Europe. Trans Policy, 2004. 11(4): p. 329-344.
45. Luo, L., E. Van Der Voet, and G. Huppes, Life cycle assessment and life cycle costing of bioethanol from sugarcane in Brazil. Renew Sust Energy Rev, 2009. 13(6): p. 1613-1619.
46. Pre-Consultants. SIMA Pro v7.3.3. http://www.pre-sustainability.com/simapro-installation. 2012; Available from: http://www.pre-sustainability.com/simapro-installation.
47. SCLCI, EcoInvent database. 2011, Swiss Centre for Life Cycle Inventories Dübendorf, Switzerland.
48. ISO, ISO 15686-5: buildings and constructed assets -- service-life planning -- part 5: life-cycle costing. 2008, Geneva, Switzerland: International Organization for Standardization.
49. Marszal, A.J. and P. Heiselberg, Life cycle cost analysis of a multi-storey residential Net Zero Energy Building in Denmark. Energy, 2011. 36(9): p. 5600-5609.
50. Chang, S.E. and M. Shinozuka, Life-cycle cost analysis with natural hazard risk. J Infrastruct Syst, 1996. 2(3): p. 118-126.
51. Cabeza, L.F., et al., Affordable construction towards sustainable buildings: review on embodied energy in building materials. Curr Opin Environ Sustain, 2013. 5(2): p. 229-236.
124
125
4.2. Sustainability of industrialized bamboo – CO2 Issues This section will present the main results from the paper presented at the First International Conference
on Bio-based Building Materials 2015 in Clermont-Ferrand, France. The full paper can be found on the
congress proceedings and on the author’s researchgate contributions page:
https://www.researchgate.net/profile/Edwin_Zea_Escamilla/contributions
Sustainability Assessment of Industrialized Bamboo Solutions for Housing Programs in The
Philippines
4.2.1. Abstract Rapid population growth and urbanization have created an unprecedented need for housing solutions
worldwide. In the Philippines, it is estimated that more than one hundred thousand additional housing
units are needed every year. The housing demand in the Philippines is further increased by the severity
and number of natural disasters that affect the country every year. Many organizations work in the
country to support the development of reconstruction and social housing projects. The most common
construction systems implemented in such projects use concrete in the form of blocks and/or other
structural elements. These systems are energy intensive and have high levels of greenhouse gas
emissions. It has been proposed that those emissions can be reduced through the use of bamboo-based
construction systems because bamboo is able to sequester high levels of CO2 during its growth and
potentially store it during the building’s lifespan.
The present research aims to assess the sustainability of industrialized bamboo-based construction
solutions, such as glue laminated bamboo, in housing projects. Life Cycle Assessment was used to
characterize the environmental aspects, CO2 crediting was used to examine the economic aspects and
job creation potential measured the social aspects. The results show that the most important variables
are the lifespan of the bamboo-based buildings and their end-of-life scenarios. Moreover, because there
are currently no managed bamboo or wood forests in the Philippines, the results show that the transition
toward a more sustainable built environment will be much faster with the implementation of small- and
medium-sized bamboo production facilities compared with industrial wood production. However, the
potentially shorter service life of bamboo-based buildings will require higher maintenance and a careful
management of the end of life of the product to efficiently store the CO2.
4.2.2. Results In this section, the results for the three proposed assessment categories—environment, economic and
social—are presented, along with the integration of these results into a sustainability assessment
benchmark. The main results represent the calculations for bamboo-based products. For validation, the
same calculations were carried out for glue-laminated wood and concrete hollow blocks as construction
materials.
126
4.2.2.1. Mass flow model
The mass flow for the production of one housing unit is presented in figure 4.6. From this figure, it is
possible to observe that a large amount of the mass coming from the plantation is water contained in the
bamboo poles. Furthermore, due to the planning and trimming process to which the poles are subjected
to produce laminated bamboo, 60% of the mass is converted into a by-product. These results show that
is of great importance to reduce the transport distance between the extraction site and the drying facility.
Moreover, the efficiency of the transformation from bamboo pole into glue laminated bamboo needs to
be improved. The mass flow model shows that the production of one year of one hectare of bamboo
plantation can be processed into enough materials for two housing units.
Figure 4.6 Mass flow for one glue laminated bamboo housing unit
4.2.2.2. Dynamic Model Housing demand
The CO2 flows associated with the execution of industrialized bamboo-based housing solutions are
presented in figure 4.7. This figure presents two types of CO2 temporary storage (captured in the
plantation and stored in buildings) and two types of avoided CO2 emissions (avoided in electricity
generation with material by-products and recycling demolished construction materials). The level of
127
captured CO2 first increases during the bamboo plantation’s establishment period and then has a 25%
reduction once the extraction of poles begins. These values stay stable during plantation operations
because the amount of bamboo that is extracted is equal that the amount that is regenerated. The CO2
stored in plantations reaches 4.5x106 CO2.Eq.Ton after the first 10 years of operation. In the case of
stored CO2, the values grow steadily up to 40 years when the first housing units are demolished and their
materials are used as fuel to produce electricity. At this level, the amount of CO2 stored in buildings
stabilizes at 32x107 CO2.Eq.Ton. This process replaces the use of fossil fuels and therefore emissions
are avoided. This value increases while there is production of materials reaching a maximum of 21x107
CO2.Eq.Ton. The same occurs with the avoided CO2 emissions from the recycling of construction
materials, which peaks (83x107 CO2.Eq.Ton) once the last housing unit has been demolished.
At the end of the model, the temporary CO2 storage disappears because the plantations are no longer
managed and no new housing units are produced. This leaves the total cumulative avoided CO2
emissions of roughly 10x107 CO2Eq Tons over a period of 130 years.
Figure 4.7 CO2 dynamic model
From figure 4.7, it is possible to observe that the model is sensitive to the end of life of the demolished
construction materials. If these avoided emissions are not considered, then the final result is significantly
reduced. Nevertheless, in both cases, a positive impact on the environment can be achieved by using the
128
industrialized bamboo solutions. Furthermore, these positive impacts have a direct connection with the
number of housing units produced and will be limited only by the availability of land to propagate the
bamboo.
4.2.2.3. Economic Category
The results from this category are related directly to the four types of CO2 types, as observed in figure
4.8. It is important to note that the income shown only represents that generated with the potential trade
of CO2 credits while the income generated from the trade of construction materials and housing units is
not considered. For the CO2 crediting calculation, two main categories are considered: temporary storage
and avoided emissions. The first is awarded as long as the CO2 is stored either on plantation or in housing
units, but it only receives a small amount per CO2eqTon on temporary storage and reaches a maximum
of 5x104 CHF. The second is awarded every time an emission of fossil fuel CO2 is avoided and reaches
a maximum of 6x107 CHF. The results show that with a project of the proposed dimensions, an average
of seven million Swiss francs can be potentially generated from the CO2 crediting alone. Almost 92%
of this income is related to avoided emissions, and only 8% is related to temporary storage. Similar to
the environmental category, the results of this category are sensitive to the end of life of the demolished
construction materials. If the avoided emissions from this process are not considered, then the total
income is reduced drastically, but some income can still be obtained from the temporary storage and the
avoided emission during production of construction materials.
Figure 4.8 Economic category
129
4.2.2.4. Social category
This category is directly related to the size of the bamboo plantation and the number of factories and
workshops that are established to produce glue-laminated bamboo. With a proposed size of 55000 ha,
circa 28000 job positions can potentially be created. It can also be considered that such jobs can be
created that are specifically targeted to low-income communities in rural and/or semi-urban areas. It
must also be noted that bamboo production can be decentralized and established with multiple small-
scale operations. The use of unproductive lands also represents a significant improvement of both the
environment and livelihood of communities. In this category, glue-laminated bamboo is found to have
a high potential, with almost 7,000 job positions potentially created, whereas glue-laminated wood is
found to have a middle potential (2,500 jppc) because its production is more centralized and requires
long time spans, larger plantation areas, and specific soils for its implementation. Thus, bamboo exists
as an alternative that not only improves the environment and livelihoods of communities but also does
not compete for land with other activities such as agriculture or forestry. Furthermore, the use of bamboo
can allow the regeneration of areas afflicted by deforestation and its associated problems.
4.2.2.5. Sustainability assessment
The average results over the study period for the sustainability assessment of glue-laminated bamboo,
glue-laminated wood and concrete hollow blocks are presented in figure 4.9. From this figure, it is
possible to observe that under the proposed categories, bamboo provides the most sustainable solution
for housing construction. The main advantage of bamboo comes from its rapid establishment (6 years)
and growth (4 years), which allows for an early start for producing materials, creating jobs, and
stimulating income generation. Moreover, the bamboo plantation is always standing because only 25%
of the canes are harvested per cycle [1]. This provides a stable income from the temporary storage of
CO2 in the plantation. Using wood products is also a solution, but its applicability is more limited
because of its centralized production and the land competition with other human activities. In both cases,
however, housing construction reduces both direct CO2 emissions and indirect emissions from fossil
fuels. Both strategies are thus carbon positive. Moreover, jobs and income can be potentially generated
from the production and commercialization of housing, the CO2 credits associated with temporary
storage in plantations and housing units, and the avoided emission from the use of by products from the
production of materials and demolished construction materials.
130
Figure 4.9 Sustainability assessment
From this figure, it is possible to see that the impacts of glue-laminated bamboo are almost opposite to
those of concrete hollow block. Thus, if a program builds 50% of its housing units using glue-laminated
bamboo and 50% using concrete hollow blocks, the program could be considered as carbon neutral.
However, if the share of industrialized bamboo housing units is increased, the CO2 balance could
become positive.
4.2.3. Discussion This section analyses the sensitivity of the results to the variables, building lifespan, electricity mix, and
end of life of the demolished construction. These variables were found to have the largest contribution
to the variability of the results and are thus studied in detail in this section.
4.2.3.1. Building lifespan
The lifespan of buildings is uncertain and depends not only on the construction materials used but also
on the urban, economic, and social dynamics of its place of construction. For this reason, a sensitivity
analysis was conducted to assess the effect that short (20 years) and long (60 years) building lifespans
will have. Lifespan length is not found to affect the CO2 stored in plantations, crediting for CO2 stored
131
in plantations, and the potential for job creation. However, a reduction in the housing lifespan from 40
to 20 years reduces the amount of CO2 stored in the building over time. As a result, the credits for CO2
stored in buildings are reduced by that amount and are available on an earlier stage. When the housing
unit’s life span is increased, the CO2 stored in buildings also rises. Consequently, the credits for
temporary CO2 storage in buildings also increase, but they are available after 60 years when the first
housing units are demolished and recycled. This analysis further shows that even under short lifespan
conditions, industrialized bamboo solutions provide positive impacts on the environment by avoiding
significant amounts of CO2 emissions. Moreover, under these conditions, the potential income from CO2
crediting is still significant, and its maximum can be achieved in early stages.
4.2.3.2. Electricity mix
The results from this analysis showed that the avoided CO2 emissions from the recycling process
contribute significantly to the results of the environmental impact and economic categories. These
avoided emissions are directly connected to the electricity mix used on the country of study. In the case
of the Philippines, the electricity mix is dominated by fossil fuels, so a significant amount of CO2 credits
can be obtained by avoiding these emissions. This sensitivity analysis considered a variation in the
electricity mix that can occur in the future or the establishment of such a housing program on a different
country. To test the consistency of the results an electricity mix with a share of 70% hydropower, similar
to that found in countries such as Brazil or Colombia, was used. This analysis showed that a variation
in the electricity mix significantly reduces the environmental and economic benefits, as shown in figure
4.10. This is due to the lower amount of CO2 emissions that can be avoided from a “low CO2 emitting”
electricity mix. Nevertheless, even with this different electricity generation mix, positive environmental
and economic benefits are still observed through the use of industrialized bamboo.
132
Figure 4.10 Sensitivity analysis of electricity mix
4.2.3.3. End-of-life scenarios
End-of-life scenarios have significant associated uncertainties because they represent future events that
cannot be completely known. Thus, after the proposed housing unit’s lifespan is reached, it is highly
uncertain what will happen to the demolished materials. For this sensitivity analysis, two scenarios were
considered: first, business as usual, in which the demolished construction materials are not used as fuel
for the production of electricity. Thus, no avoided CO2 emissions were considered in the environmental
impact and economic categories. The second was the best case scenario, where the demolished
construction materials are used as fuel for producing electricity. The results for glue-laminated bamboo
were compared with those of glue-laminated wood and concrete hollow blocks and are presented in
figure 4.11. From this figure, it is possible to see that changes in the end-of-life scenario produce a
variation of 80% in the results for both glue-laminated bamboo and glue-laminated wood. The same
occurs in the economic category, where a significant amount of CO2 credits can be potentially obtained
from the avoided emissions related to the end-of-life scenario. It is important to note that even under
these conditions, both industrialized bamboo and wood perform better than concrete, as observed in
figure 4.11. Furthermore, even if the avoided CO2 emissions from the recycling of demolished
construction materials are not considered, the industrialized bamboo solutions create environmental and
economic benefits.
133
Figure 4.11 Sensitivity analysis of end-of-life scenarios
4.2.3.4. Sustainability Assessment
The results for the three sensitivity analyses were included in the sustainability assessment benchmark,
as observed in figure 4.12. The results from the sensitivity analyses show a significant variation.
Furthermore, it is possible to see that under certain conditions, the results for glue-laminated bamboo
and glue-laminated wood overlap. The three studied construction materials are not affected on the social
category by changes in the proposed variables. In all cases, the glue-laminated bamboo provides positive
impacts across all categories. On the contrary, glue-laminated wood produces emissions when the end
of life is not considered and when the electricity mix is changed.
134
Figure 4.12 Sustainability assessment with sensitivity analysis
Under the proposed conditions and sensitivity analyses, glue-laminated bamboo always provides the
most sustainable solution for housing. Figure 4.12 shows the potential that a bamboo-based housing
program will produce positive impacts on the environment by reducing the levels of CO2 and by
providing extra income from CO2 crediting that can be used in the financing of the housing units
themselves.
4.2.4. Conclusions This research assesses the sustainability of industrialized bamboo solutions for housing programs in the
Philippines. The results and sensitivity analyses show that the use of industrialized bamboo in such
programs can produce environmental, economic and social benefits. Over 28000 potential job positions
can be created by the establishment of 5500 ha of managed bamboo plantations. These positions will be
stable for the duration of the housing program and are only affected by the size of the program and its
associated bamboo plantation. Thus, an increase on the number of planned housing units is associated
with an increase in potential new jobs. Furthermore, the implementation of an industrialized bamboo-
based housing program provides positive impacts on the environment by capturing and avoiding over
108 tons of CO2equivalent of emissions over 130 years. Moreover, circa 490 million CHF can potentially
be created over the same period with the crediting of temporarily stored and avoided CO2 emissions
135
associated with the used of industrialized bamboo solutions. From the sensitivity analyses, housing
lifespan and national electricity generation mix are the most important factors that affect the results.
Finally, it can be concluded that the use of industrialized bamboo solutions offers a sustainable approach
for new housing construction. The associated positive impacts to the environment and the livelihood of
communities engaged in such programs is directly related to the program size. Finally, the use of
industrialized bamboo solutions for housing programs can support the regenerative development of the
regions in which they are applied, leading to long-lasting improvements in their environment and
livelihoods.
4.2.5. Acknowledgments The authors would like to thank HILTI AG for their long term support in the development of the present
research project.
136
137
4.3. Environmental Savings Potential from the Use of bamboo in Europe This section will present the main results from the paper presented at the International Conference Non-
conventional Materials 2013 in Joa-Pesoa, Brazil and further published in the Key engineering materials
Journal in 2014. The full paper can be found on the congress proceedings and on the author’s
researchgate contributions page:
https://www.researchgate.net/profile/Edwin_Zea_Escamilla/contributions
Environmental Savings Potential from the Use of Bahareque (Mortar Cement Plastered Bamboo)
in Switzerland
Key Engineering Materials Vol. 600 (2014) pp 21-33
4.3.2. Abstract The urgency for energy and material efficiency in the building sector increases every day. In the case of
Switzerland, a building’s main energy demand occurs during its use/operation phase and is mainly
related to heating demands during the winter season. As a means of reducing these demands, current
building practice in Switzerland is to insulate with 30cm of foam and to mechanically control indoor
environments. Recent research has shown, however, that alternatives to current practice are readily
available. With these alternative techniques, natural materials with low embodied energy are used to
produce high efficiency building envelopes. The bahareque (fig 4.13)construction method (bamboo
plastered with mortar cement) studied in this paper has been identified as a promising technology both
in terms of producing energy efficient building envelopes and also with regards to reducing the
environmental impact associated with the construction of buildings in Switzerland. The main objective
of the research presented here was to identify the Environmental Savings Potential (ESP) of bahareque
in comparison with state of the art technologies in Switzerland. The calculations were geographically
limited to Switzerland and the main data sets used for the life cycle assessment models corresponded to
this region. Specific datasets were developed for bamboo and bahareque to account for transoceanic
transportation. The results showed that bahareque achieves an ESP of 32% compared with clay brick
construction and 40% when compared with concrete block construction. It was shown that it is feasible
to develop highly efficient building envelopes with low embodied energy that can be used within the
Swiss context.
138
Figure 4.13 Wall sections
4.3.3. Results Figure 4.14 shows the Environmental Saving Potential (ESP) of Bahareque, which can be defined as
the difference in percentage, between the total environmental impact of a benchmark technology and
the total environmental impact of the studied technology. For this research, clay bricks and concrete
block were considered as benchmarks.
Figure 4.14 LCA results
Figure 4.14 shows that bahareque withholds an ESP of 40% when compared with lightweight concrete
wall and an ESP of 33% when compared the clay brick wall.
139
The process contribution analysis showed that the cement mortar was the main contributor to the
environmental impact in the bahareque technique, with a 39%. Followed by bamboo products with 31%,
as seen on figure 4.15. The item bamboo products includes all the process associated to the production
and transportation of flattened bamboo and poles. A detailed analysis of this item showed that the main
process contributing was the transoceanic transportation with 32% while the bamboo products on itself
contribute to less than 1% of the total environmental impact.
For the clay bricks and concrete block techniques, the process contribution showed that the main impacts
are related to the fuels used to produce them. For the case of clay bricks natural gas and heavy oil fuel
for concrete blocks. The extruded polystyrene, used as insulation material, contributes in a significant
manner to the overall environmental impact of these techniques. The XPS contributes to a 27% on the
clay brick wall and 19% to the overall environmental impact on the concrete block wall. The data sets
for the brick and block technology were directly taken from the EcoInvent database and were considered
to have the lowest uncertainty levels.
4.3.4. Discussion In the process of carrying out a LCA certain methodological decisions and assumptions can introduce
unexpected variations on the results. These variations can pass unnoticed and affect in a sensitive way
the final interpretation of the LCA results. On the present paper these variations on the results are
addressed as uncertainties. Three main sources of uncertainties were identified for the present LCA,
uncertainties related to building physics calculations; life span and maintenance; and evaluation
methods. In order to identify the effects of these uncertainties on the final results, new LCA models
were developed for each case.
Figure 4.15 Process contribution to environmental impact
140
4.3.4.1. Uncertainties related to building physics calculations
The calculation set up for the heat transfer coefficient of the studied walls is very simple. Actually, no
heat transfer by convection are considered, which will however, drastically reduce the efficiency of the
7cm layer of air in the bahareque wall. In order to eliminate the uncertainties introduced by this
calculation method, the most secure way of doing a comparison is to choose the worst case for the
bahareque and to consider that the air layer has no effect. In that case, the same insulation material as
for the two benchmark walls is used: an XPS insulation foam. Table 4-11 present the LCI values for
this model and figure 4 shows the section for the XPS insulated bahareque wall.
Table 4-11 LCI construction 1 m2 insulated bahareque wall FU Bahareque wall Original
Inpu
ts
Bamboo Stem (Dry) transported to Europe 165.5 kg Flattened Bamboo 135.7 kg Bolts and nuts 2.756 kg Cement mortar, at plant (Plaster) 66 kg Chicken wire mesh 1 kg Cement mortar, at plant 199 kg Reinforcing steel, at plant 1.8 kg
Polystyrene, extruded (XPS) CO2 blown, at plant 9.6 kg The model of the insulated bahareque wall was compared with the clay brick wall and concrete block
wall. The results show that the inclusion of the insulation foam produces a reduction on the ESP of the
bahareque wall between 17 - 22%. Under these conditions, the bahareque wall still withholds a
significant ESP when compared to the conventional construction techniques.
In order to better understand the effects of the inclusion of a layer of insulation foam another calculation
set up was developed. The new set up considered different thicknesses of the foam layer and their effect
on the ESP. Figure 4.16 show that the insulated bahareque wall will withhold an ESP if its foam layer
is thinner than 32cms when compared to the clay brick wall and 45cms when compared to the concrete
block wall. This also shows that the bahareque can be insulated within practical ranges, 20cms to 30cms,
and still withhold a significant ESP. This are very promising results, but still the practicality of building
a bahareque wall in Switzerland needs to be addressed. Moreover, the effects of the climatic variation
on the ageing behaviour of the bahareque need to be better understood. This effects should also account
for the expected service life and maintenance needs of the bahareque technique.
141
Figure 4.16 Effect of XPS thickness on bahareque ESP
4.3.4.2. Uncertainties related to life span and maintenance needs
The life span of building and its components is one of the most important factors on a LCA study. At
the same time these factors are very sensitive and difficult to properly model. The life span of a building
or a given construction technology depends not only of the durability and ageing behaviour of their
materials, but also are influenced by use, maintenance and even social and urban dynamics. For the
present research we assumed a life span in service, also known as service life, of 60 years. The
maintenance needs were divided in two programs one for the bahareque and one for the brick and block
walls.
The maintenance program for bahareque consisted on the replacement of the outside layer of the wall
including flattened bamboo, plaster, chicken wire mesh and XPS as shown in table 4-12. The program
for bahareque was then develop into three levels high maintenance (every 10 years); mid maintenance
(every 20 years); and low maintenance (every 30 years). For the brick and block technologies the
program considered the replacement of the XPS layer. The levels of maintenance were defined as high
maintenance (every 20 years); mid maintenance (every 30 years) and low maintenance (once at 60years)
these values are presented on tables 4-13 and 4-14.
142
Table 4-12 Data input for life span and maintenance calculations – Bahareque wall Bahareque wall Original 20 years 40 Years 60 Years
Inpu
ts
Bamboo Stem (Dry) transported to Europe
165.5 kg 165.5 kg 165.5 kg 165.5 kg
Flattened Bamboo 135.7 kg 203.58 kg 271.4 kg 339.2 kg Bolts and nuts 2.756 kg 2.756 kg 2.756 kg 2.756 kg Cement mortar, at plant (Plaster) 66 kg 99.0 kg 132.0 kg 165.0 kg Chicken wire mesh 1 kg 1.5 kg 2.0 kg 2.5 kg Cement mortar, at plant 199 kg 199 kg 199 kg 199 kg Reinforcing steel, at plant 1.8 kg 1.8 kg 1.8 kg 1.8 kg Polystyrene, extruded (XPS) CO2 blown, at plant
9.6 kg 19.2 kg 28.8 kg 38.4 kg
Source: Authors
Table 4-13 Data input for life span and maintenance calculations – Clay brick wall Clay brick wall Original 20 years 40 Years 60 Years
Inpu
ts
Light clay brick, at plant 458 kg
458 kg 458 kg 458 kg
Cement mortar, at plant 62.4 kg
62.4
kg 62.4
kg 62.4
kg
Polystyrene, extruded (XPS) CO2 blown, at plant
12.9 kg
25.9
kg 38.8
kg 51.8
kg
Source: Authors
Table 4-14 Data input for life span and maintenance calculations – Concrete block wall Lightweight concrete block brick wall Original 20 years 40 Years 60 Years
Inpu
ts
Lightweight concrete block, expanded clay, at plant
330 kg
330 kg 330 kg
330 kg
Cement mortar, at plant 62.4 kg
62.4 kg 62.4
kg
62.4
kg
Polystyrene, extruded (XPS) CO2 blown, at plant
12.9 kg
25.9 kg 38.8
kg
51.8
kg
Source: Authors
143
Figure 4.17 ESP range – LCI amounts variations Figure 4.17 presents the results for the maintenance program of brick and block technology and the
bahareque wall with and without insulation. On the figure, the thicker lines are used to indicate the
results for the low maintenance program for the brick and block techniques. The stars are used to mark
the instances where a maintenance process was executed. For the case of bahareque without insulation
(Blue and red lines), it can be seen that even under the high maintenance program (red line, every 10
years) the bahareque wall still presents a significant ESP, when compared with the brick and block. The
ESP on the low maintenance program is maintained between 34% and 40% over the studied life span.
On the other hand, the ESP on the high maintenance program presents a variation of 12% during the
same period. It is clear that the higher energy and material demand on the high maintenance program
rebounds on a reduction on the bahareque ESP.
These calculations were also carried out considering the case of an insulated bahareque wall. The same
low, mid, and high maintenance programs were used as with the bahareque without insulation. Under
the low maintenance program (violet line, every 30 years) the insulated bahareque presents significant
ESP over the proposed life span. Under the mid maintenance program (Cyan line, every 20 years), the
insulated bahareque presents ESP under 20 years of life span when compared to the clay brick wall and
under 50 years when compared to the concrete block wall. This shows that the maintenance needs can
play a significant role on the whole life environmental impact of the studied techniques. Under the high
maintenance program (orange line, every 10 years), the insulated bahareque do not present ESP when
144
compared to the clay brick wall and only presents ESP under 15 years of life span when compared to
the concrete block wall.
4.3.4.3. Uncertainties related to the selected EMs
Three additional EMs IMPACT 2002+; IPCC 100; and Cumulative Energy Demand (CED) were used
in order to validate the results provided by Ecological scarcity 2006. IMPACT 2002+ was also
developed in Switzerland, but it assesses a different set of mid and endpoint categories. The results from
IMPACT2002+ are presented in figure 6. It shows that the bahareque wall has an ESP of 27% when
compared with the clay brick wall and 45% in comparison to the concrete block. These results show a
similar trend to the ones from Ecological Scarcity. Similar results were obtained from the assessment
using the other two EMs.
IPCC100, was developed by the International Panel in Climate Change. This EM assesses the amount
in kilos of CO2 equivalents related to the production and/or use of the studied products. Figure 5 shows
that the use of the bahareque technique could rebound on a CO2 reduction of 50% when compared to the
concrete block technique and 33% when compared with the clay bricks. This is a very interesting result,
considering the possibilities not only to reduce the CO2 emissions but also to create CO2 credits that
could be used as financial incentive to the use/development of the bahareque technique in the Swiss
context.
The Cumulative Energy Demand (CeD) EM as its name indicates assesses all the energy needed for the
production and use of the studied products. Figure 6 shows that under this EM the bahareque technique
presents a potential energy demand reduction of 52% when compared to the concrete block technique
and 35% when compared to the clay brick technique. This indicates that this technique has the potential
to produce a reduction in both material and energy demands.
145
Figure 4.18 Results of accumulated EM The aggregated results for the EMs are presented on figure 4.18. The results from each EM were
normalized in order to make possible a comparison between them. Then the normalized results were
benchmarked against the highest score of each EM. The results from this analysis show that the
bahareque wall receives the lowest scores under all the EMs used. This shows that these results are
consistent and withhold low uncertainties. For the cases of concrete block and insulated bahareque the
results are consistent under three out of four EM, this can be considered as a middle uncertainty level.
Finally, the clay brick wall presents the highest variation and the results are only consistent under two
out of four EMs. From these results it is clear that the process included on the clay brick datasets are
very sensitive to the evaluation method used on the assessment.
4.3.5. Conclusions and recommendations
The present research showed that the bahareque technique has the potential to produce building envelops
with low heat transfer coefficient for the Swiss context. The results showed that the process with the
highest contribution to the overall environmental impact of bahareque is the cement used on the plaster
and reinforcements. Moreover, the transoceanic transportation of the bamboo products has a larger
impact than the products itself. This means that the performance of bahareque on bamboo producing
countries can be even higher that the present results.
146
It was also shown that the use of an extra layer of insulation will reduce the ESP of bahareque but under
the studied conditions it will still withhold a significant ESP. Nevertheless, it is necessary to develop
physical testing to establish the thermal transfer coefficient of the bahareque technique. Moreover, it is
necessary to develop models that consider other kinds of insulation materials in order to identify the
most efficient building envelop. The results also showed that even the insulated bahareque will withhold
an ESP after three cycles of maintenance over 60 years of service. Furthermore, the ageing behaviour
of bahareque needs to be established considering not only the exposure to precipitation but also to
temperatures changes similar to those experienced in Switzerland.
The proposed methodological approach had proved to be a valid solution to reduce the level of
uncertainties when dealing with partial datasets. These methodological approaches still need further
development and consolidation into an established methodology. It is also important to mention that
the valid local data sets for the production of bamboo and other alternative construction materials are in
need. It is of great importance to develop and submit these dataset to LCA databases, in order to make
them available to researchers around the world and also to validate them through databases’ peer review
process. It is also of great importance to highlight that the present research focused only on the
environmental impacts associated to the construction and use of a functional unit and to understand the
economic implications of choosing one technique in particular, a life cycle cost assessment is needed.
The present research showed that alternative construction materials have potential to be used in high
energy efficient building envelops. Moreover, it was shown that it is possible to improve on the material
and energy demand for the production of these building envelops.
4.3.6. Acknowledgments
The authors of this paper would like to thank the HILTI AG for its invaluable support on this research
and sponsorship. We would also like to thank Prof. Holger Wallbaum for kindling this line of research
from its very beginning.
147
Chapter 4 in a nutshell
- Sustainability assessment of 20 transitional shelters
The effects of the variability of transport distances and designs on the sustainability of twenty transitional
shelters were studied
It is possible to produce sustainable transitional shelters, with high technical performances at low cost and
environmental impacts
The sustainability of a shelter can be related to the appropriated application of a construction material aiming
to obtain the highest possible performance and not to specific use of a construction materials
- Sustainability assessment of industrialized bamboo housing solutions
Industrialized bamboo-based housing program provides positive impacts on the environment by capturing
and avoiding over 108 tons of CO2equivalent of emissions over 130 years
Circa 490 million CHF can potentially be created over the same period with the crediting of temporarily
stored and avoided CO2 emissions associated with the used of industrialized bamboo solutions
Housing lifespan and national electricity generation mix are the most important factors that affecting the
results
- Environmental savings potential from the use of bamboo in Europe
The environmental savings potential from the use of bamboo based constructive systems in Europe was
estimated in 23% when compared to conventional constructive systems
The main contributors to the environmental impact of bamboo based construction are the steel and concrete
used to reinforce the bamboo
The life span and maintenance regimes of the bamboo based constructive system significantly influence the
environmental impact
148
149
Chapter 5: Conclusions
150
151
5. Conclusions
The main idea behind this research was to develop an approach to produce LCA data of bamboo based
construction materials. In principle it was thought as a straight forward idea but in reality it became more
complex with each step. The problem of LCA data is one of information complexity, the more information
is available the better the result will be. But more information requires a more complex approach to handle
it. Thus, a balance needs to be found where the information and methodology complexities meet to provide
the optimal result. On the present research the information complexity was relatively low at the beginning, a
few examples were known of LCA of bamboo based construction materials. So the first approach to develop
datasets with global validity relied on the identification of the ranges in which the input parameters were
expected to vary. This alone would provide suboptimal results so it was needed to increasing the complexity
of the methodology. To do so, contribution and uncertainty analysis were carried out and as a result the first
datasets of bamboo based construction materials were developed.
At this stage the information complexity increased again and thus the requirement for a better approach. Two
main objectives were set, (i) to be able to compare bamboo based buildings with other alternative and
conventional construction materials; and (ii) to be able to characterize the data to specific countries. The first
was achieved by applying the methodology used on bamboo based construction materials to a selection of
alternative and conventional construction materials. This process help to complete the set of data with global
validity. Moreover, it reinforced the important role that the transport of construction materials played on the
environmental impact. This was a very important factor for the second objective, due to the different potential
transport distances in different countries. For the characterization of LCA data of construction materials two
main variables were identified: electricity mix and transport of construction materials. The electricity used
in a country is a mixture of different sources: coal, hydro, or nuclear power. The environmental impact of
each country mix depends on its composition and the evaluation method used. For this research the electricity
mix of over 50 countries was modelled and their impacts calculated using the evaluation method
IMPACT2002+. These values in combination with those of production of construction materials were used
for the characterization at the material level. But to be able to compare construction materials it is necessary
to carry out the assessment at the building level. It is not possible to find comparable functional units at the
materials level, one unit of mass of a materials provides very different service as the same amount of other
material. At the building level the transport of construction materials becomes very important and its
contribution to the results increases in relation to the distances.
With this challenges a new level of information complexity was reached and a consequent improvement on
the methodology was require. With the information available it was possible to characterize the LCA data of
construction materials but it was a time consuming process and would not cover the potential transport
distances issue. To overcome these problems an integration of LCA and geographic information systems was
used. This approach allowed for the characterization of LCA data and to calculate the potential transport
distances based on the size of the countries. The characterization process was carried out by calculating three
levels of production efficiency of construction materials using the country specific electricity mix.
152
Furthermore, a relationship between the land area of a country and the potential transport distances of
construction materials was estimated. It was also proposed that different construction materials would have
different transport distance regimes. To achieve this goal GIS was used to systematically calculate the
transport three ranges of transport distance based on the land area of a selected country. This information
was combined with the LCA data to calculate the impact of transporting a unit of construction material. At
this point all the information needed to carry and LCA was available and the methodology was further
develop to calculate the LCA of buildings. The calculations included three levels of production efficiency of
construction materials and three potential transport distances regimes for each type of construction materials.
Furthermore, it was possible to calculate the contribution of each process (material and transport) to the
environmental impact and to the variability of the results. Finally, the uncertainty of the results was also
calculated. At this stage it was possible to define a country from a list of 240 and carry out comparative LCA
of buildings with high degree of consistency and automation on the process. But the fine differences between
buildings were difficult to assess. How a building would perform under extreme winds or earthquakes would
certainly influence its life span and user’s acceptance. With the experience of using LCA and GIS information
a new level of complexity was added. Georeferenced data of wind and earthquake risk zones was included
on the existing database. With this information it was possible to identification the risk level of locations
around world. To be able to do this identification georeferenced data of around 2000 cities around the world
was included. The combination of these sets of data and the spatial analysis features on the GIS allowed to
exactly define the risk zones of each city. These were then compared with the performance of the buildings
to define their performance under the expected external loads. This feature allows for a better definition of
functional units and provides more information for a decision making process.
With the level of development achieved at this stage and with the information developed it was possible to
carry out comparative LCA of buildings in different countries but the identification of risk zones was carried
out at the city level. This posed a conjecture on the level of detail of the results and a further objective to be
achieved on the present research: To calculate the transport distances of construction materials at city level.
To achieve this goal, georeferenced data on centres of production of construction materials was included. By
using the spatial analysis feature the geodesic distances between target city and centres of production were
calculated. With this information it was possible to obtain results that had the same level of detail on all the
component impact assessment and risk zones. All the previous calculations were done considering one single
design and the environmental impact from different construction material options to produce it.
At this point the research widened its scope to include a variations on designs and constructive systems.
Furthermore, the assessment went beyond the environmental impact and different approaches to assess
economic and social impacts were developed. The research was focused first on the environmental impact
assessment of 20 transitional shelter designs that had been reported by the International Federation of Red
Cross Associations. These assessment showed that the environmental impact of a building was not connected
to the construction materials used but on how and where they were used. Further assessments approaches
were developed to account for economic issues and structural performance. These assessment were quiet
153
challenging due to the lack of data for the economic assessment and the complexity of the structural
performance assessment. To be able to compare and combine these three categories, (i) environment, (ii)
cost, and (iii) technical performance a benchmark system was developed. The functional units were based on
two main factors: buildings’ area covered and life span. The buildings’ covered area not only helps to
represent the buildings size and the amount of materials used in them but also represents the available space
in which a family can undertake their daily activities. This factor serves a proxy for social issues which are
intrinsically complex and difficult to assess. The life span of a building represents not only the durability of
a constructive system but the purpose of the building itself. In the present research most of the studied
buildings were transitional shelters which have very different expected life services. The proposed
benchmark allowed for the calculation and comparison of the sustainability of very diverse transitional
shelters. These comparison supported the idea of the important role that appropriate use of materials play in
the sustainability of a building.
At this stage, the research project focused on the additional sustainability benefits from the use of bamboo as
construction material. These benefits were assessed on two different research project: the first analysing the
potential sustainability benefits when the bamboo is used locally and the second when bamboo was exported
to Europe. The first project was mainly focus on the CO2 emissions problematic and the opportunities that
lay for bamboo based construction materials. Three impact categories were used environmental impact in
terms of CO2 balance; economic in terms of potential CO2 credits; and social in terms of potential job creation
from the production of bamboo based construction materials. This approach was used to calculate the
potential of three construction materials: (i) concrete hollow block; (ii) glue laminated bamboo; and (iii) glue
laminated wood. These comparisons allowed to show the underlying potentials from the use of bamboo based
construction materials. This project showed that the use of industrialized bamboo construction materials in
social housing projects captures more CO2 than what it is emitted in the production of the materials. This
positive balance can be then turned into CO2 that can be used to generate extra revenue to support and finance
the housing projects. The second project focused on the environmental savings produced from the use of
bamboo in Europe. This project showed that a significant environmental impact saving can be produce when
using bamboo based construction materials even when transoceanic transport of construction materials is
consider. Furthermore, the project highlighted the importance of life span of buildings and their maintenance.
This two factors determine the final environmental savings achieved. The use of bamboo based construction
materials in Europe not only produces lees environmental impacts than conventional construction materials
but also incentives the economies on bamboo producing countries.
The main objective of the present research was to develop LCA data for bamboo based construction
materials. On the process of achieving this objective a methodology to generate and characterize alternative
and conventional construction materials was developed. This methodology can be also used to carry out LCA
of buildings around the world at country or city level. Furthermore, the identification of earthquake and wind
risk zones can be used to support decision making process when choosing constructive systems. Moreover,
methodologies to assess the sustainability of the use of bamboo construction materials in reconstruction and
154
social housing projects were developed and tested. Furthermore, during the course of this research the global
challenges of post-disaster reconstruction and affordable housing were addresses.
The findings from this research indicated that the appropriated selection and application of construction
materials is one of the most important factors to consider on the sustainability of buildings. Moreover, that
the global challenge of housing shortage is not going to be overcome with a single solution but with a mixture
of construction materials and technologies. These should be able to respond to the necessities of the local
context on which they can be applied. The results showed under different assessment conditions that
sustainable buildings can be produced with a diversity of alternative and conventional construction materials.
Moreover, the sustainability of a buildings is not directly correlated to its construction material but to the
sustainable use of those materials. However, the use of bamboo as a construction material increases
significantly the possibilities of producing sustainable buildings on a wide range of contexts. Furthermore,
the results showed that the economic, environmental, and social benefits from the production and use of
bamboo in construction can not only support the regenerative development of countries producing it but also
it can offset the negative environmental impacts from the production and use of other construction materials.
Thanks to these properties the use of bamboo becomes more beneficial when it is scaled up and industrialized.
Bamboo based construction materials and constructive systems offer are interesting enterprises for small and
lager scale companies. Due to its flexibility and sustainability benefits bamboo based construction materials
offers opportunities not only to be used on bamboo producing countries but also to be exported to other
geographies.
155
6. Reflections
LCA is a ground breaking tool and its potential has been extensible proven. The work presented on this
document tackles the first challenge of data generation and their operationalization. Nevertheless, the case of
LCA of construction materials and buildings present a methodological challenge that is still yet needed to be
solved. As it was presented on this document, due to the differences in functional units, construction materials
has to be assess at the building level. This situation makes it complicated the assessment and the selection of
functional units becomes more sensitive than in other LCAs. In general buildings have many different
components and materials making it difficult to assess the real contribution from construction materials.
Moreover, buildings have very long life spans which are driven by factors not directly related to the
construction materials, like economy, society and politics. This long life span makes high levels of
uncertainty in the end of life of the buildings, its components and construction materials. The life span of
buildings can be only estimated based on the socio-economic and politic situation in which the assessment is
carried out. But it is not possible to forecast with a high degree of confidence how that situation will be at
the end of the building’s life span. To overcome this challenges an LCA practitioner needs to oversimplify
the functional units, striping it to its minimum level of material. Furthermore, the end of life scenario have
to be either ignored or build with little knowledge of the conditions in which the building will end it service.
Another methodological challenge that needs to be addressed on LCA is the environmental impact evaluation
methods used. These method can be specific to certain countries and represent their socio-political posture
towards the environment like the case of the Swiss method “Ecological Scarcity”. In many cases these
methods are not able to represent the local environmental impacts produced. Furthermore, the regionalization
process requires significant amounts of data which is usually not available.. These methods have very diverse
implementations on software and their databases making their results dependant on that process.
Furthermore, the calculation and units used are difficult to communicate to communities and decision makers.
This communication problem hinders a widespread use of LCA which general concepts are easy to grasp but
produces results that can only be understood by experts. The development of environmental impact
evaluation methods require significant financial investments and its application is limited. Thus, a new
approach for developing these method and how they are calculated is in need. Fortunately, effort are being
made to produce methods that are open and co-developed by interested organizations like www.maxergy.org.
156
157
Acknowledgements
This is one of the most difficult pages I have ever written and possibly will. On these few pages I would like
to acknowledge all the people and organizations that in one way or the other help me to reach this moment.
First of all I want to thank my family for being my backbone during all this time. To Maya, partner
extraordinaire whose love and support kept me going on the most difficult times. To Emilie and Mauricio
whose smiles always brought me inspiration to keep on writing. To my mother that thought me that anything
worth doing, should be done right….and if you are going to do it your better overdo it. To my sister for
showing me from an early age that “everything can be arranged”. To all my family here and there, aunts,
uncle, cousins, and friends. I specially would like to thank the family Delgado Baron and the Foundation “La
Espiral de Servicio” for being my family away from home and for their support which help me incredibly at
the beginning of this journey.
I would also like to thank Prof.Dr. Holger Wallbaum and Prof.Dr. York Ostermeyer for opening the doors of
the ETHZ to me and for the opportunity of working and learning from them. I would also like to thank my
supervisor Prof.Dr. Guillaume Habert for giving me the opportunity to pursue this dream of mine and whose
clear sight always managed to find the right way. Furthermore, I would like to my co-supervisors Prof.
Ronald Roves and Prof. Normando Barbosa for their support and insights. I would also like to thank to my
co-authors specially Ing. Luis Felipe Lopez, not only for his contributions to my research but also for his
friendship. I would also like to thank to all my colleagues at IBI, and especially to Anne-marie, Annette,
Annika, Dimitra and Viola. I would also like to specially thank all the students from ETHZ that with their
work contributed to the development of my research.
Last but not least I have to acknowledge the support given to me by HILTI AG to develop this research. Whis
was invaluable and allowed me to go beyond my expectations. Specially, I would like to thank Dr. Andreas
Bong for his support and the HILTI foundation for their support and collaboration at the beginning of my
work.
I also want to extend a special acknowledgement to ETH Global and the Sawiris Foundation for Social
Development, whose research for development scholarship was to the key that opened the first door at the
ETHZ for me.
158
159
Bibliography
1. DeSA, U., World population prospects: The 2012 revision. Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat, New York, 2013.
2. IBRD. World bank: Data. 2015 [cited 2015 05.2015]; Available from: http://data.worldbank.org/.
3. Heilig, G.K., World urbanization prospects: the 2011 revision. United Nations, Department of Economic and Social Affairs (DESA), Population Division, Population Estimates and Projections Section, New York, 2012.
4. UNHabitat, State of the World´s Cities 2010/2011, U. Habitat, Editor. 2011, UN Habitat Nairobi.
5. Maddison, A., The world economy volume 1: A millennial perspective volume 2: Historical statistics. 2007: Academic Foundation.
6. Krausmann, F., et al., Growth in global materials use, GDP and population during the 20th century. Ecological Economics, 2009. 68(10): p. 2696-2705.
7. Costanza, R., L. Graumlich, and W.L. Steffen, Sustainability or collapse?: An integrated history and future of people on Earth. 2007: Mit Press.
8. UNEP, Industry and Environment Vol. 26 Nr.2-3. 2003. 9. Bruckner, M., et al., Materials embodied in international trade–Global material extraction and
consumption between 1995 and 2005. Global Environmental Change, 2012. 22(3): p. 568-576. 10. Rockström, J., et al., A safe operating space for humanity. Nature, 2009. 461(7263): p. 472-475. 11. Edenhofer, O., et al., IPCC, 2014: Climate Change 2014: Mitigation of Climate Change.
Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Transport, 2014.
12. O'Brien, K., et al., Toward a sustainable and resilient future. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC), 2012: p. 437-486.
13. OECD, A., Environmentally Sustainable Buildings, Challenges and Policies. 2003, OECD publications Service, Paris, France.
14. UNESCAP, U., State of the Asian Cities Report 2011. 2011, UN Habitat, UN ESCAP: Bangkok. 15. Asif, M., Sustainability of timber, wood and bamboo in construction. 2009: p. 31-54. 16. Flander, K.D. and R. Rovers, One laminated bamboo-frame house per hectare per year.
Construction and Building Materials, 2009. 23(1): p. 210-218. 17. Murphy, R.J., D. Trujillo, and X. Londoño. Life Cycle Assessment (LCA) of a Guadua House.
in International Symposium of bamboo -- Guadua. 2004. Pereira, Colombia. 18. Van der Lugt, P., A. Van den Dobbelsteen, and J. Janssen, An environmental, economic and
practical assessment of bamboo as a building material for supporting structures. Construction and Building Materials, 2006. 20(9): p. 648-656.
19. Villegas, M., New bamboo architecture and design. First edition ed. 2003, Bogota, Colombia.: Villegas Editores.
20. Archila-Santos, H.F., M.P. Ansell, and P. Walker, Low Carbon Construction Using Guadua Bamboo in Colombia. Key Engineering Materials, 2012. 517: p. 127-134.
21. Tran, V.H., Growth and quality of indigenous bamboo species in the mountaineous regions of Northern Vietnam, in Faculty of Forest Science and Forest Ecology. 2010, Georg-August-Universität Göttingen: Göttingen.
22. Londoño, X., Evaluation of bamboo resources in Latin America. A Summary of the Final Report of Project, 1998(96-8300): p. 01-4.
23. Lu, F., China’s bamboo product trade: performance and prospects [M]. Beijing: INBAR, 2001. 24. Lobovikov, M., et al., World bamboo resources A thematic study prepared in the framework of
the Global Forest Resources Assessment 2005, in Non-wood forest products. 2007, Food & Agriculture Org.: Rome.
160
25. Yuming, Y. and H. Chaomao, China's bamboo culture/resources/cultivation/utilization, in Technical report I.N.f.B.a.R. (INBAR), Editor. 2010: Bamboo and Rattan Research Institute, China Southwest Forestry University, Kunming, Yunnan, P.R. China, 650224. p. 148 - 206.
26. Yang, Y. and C. Hui, China's Bamboo, culture, resources, cultivation, utilization. 2010, International Network for Bamboo and Rattan.
27. Lakkad, S.C. and J.M. Patel, Mechanical properties of bamboo, a natural composite. Fibre Science and Technology, 1981. 14(4): p. 319-322.
28. Liese, W., The anatomy of bamboo culms. Vol. 18. 1998: Brill. 29. Archila, H.F., C.P. Takeuchi, and D.J. Trujillo, MECHANICAL AND PHYSICAL
CHARACTERIZATION OF COMPOSITE BAMBOO-GUADUA PRODUCTS: PLASTIGUADUA.
30. De Flander, K. and R. Rovers, One laminated bamboo-frame house per hectare per year. Construction and Building Materials, 2009. 23(1): p. 210-218.
31. López Muñoz, L.F. and J.F.J. Correal, Exploratory Study Of The Glued Laminated Bamboo Guadua Angustifolia As A Structural Material. Maderas ciencia y tecnología, 2009. 11(3): p. 171-182.
32. Archila, H.A., et al. Evaluation of the mechanical properties of cross laminated bamboo panels by digital image correlation and finite element modelling. in World Conference on Timber Engineering (WCTE) 2014. 2015. University of Bath.
33. Zea Escamilla, E., Design and application of laminated bamboo elements in frame construction and mechanical properties of laminated bamboo, in Chair of Urban Environmental Management. 2008, Wageningen University: Wageningen, NL.
34. Xiao, Y. Development of Prefabricated bamboo Earthquake Relief Shelter. in International conferece of modern bamboo structures. 2009. Bogotá, Colombia: Universidad de los Andes.
35. Lopez Muñoz, L.F. and M. Silva, Seismic behaviour of bahareque structures, in Faculty of Architecture and Civil Engineer. 2000, National University of Colombia, Manizalez: Manizalez, Colombia.
36. Wallbaum, H., et al., Indicator based sustainability assessment tool for affordable housing construction technologies. Ecological Indicators, 2012.
37. AIS, Colombian code for seismic design and construction, NSR-98. 2004, Seismic Engineering Colombian Association: Bogotá, Colombia.
38. van Uffelen, C., Bamboo : architecture & design. 2014, Salenstein, Switzerland: Braun Publishing
39. von Vegesack, A., et al., Design with nature : die Bambusbauten = the bamboo architecture. 2011, Shenyang, China: Liaoning Publishinghouse
40. Bauman, H. and A. Tillman, The Hitch Hiker's Guide to LCA. 2004: Studentlitteratur AB. 41. Bauman, H. and A. Tillman, The hitch hiker's guide to LCA: an orientation in life cycle
assessment methodology and application. 2004, Lund. Sweden: Studentlitteratur. 42. Hellweg, S. and L. Mila i Canals, Emerging approaches, challenges and opportunities in life
cycle assessment. Science, 2014. 344(6188): p. 1109-13. 43. ISO, ISO 14040: environmental management- life cycle assessment- principles and framework,
ed. ISO. 2007, Geneva, Switzerland: International Organization for Standardization. 44. Wang, E. and Z. Shen, A hybrid Data Quality Indicator and statistical method for improving
uncertainty analysis in LCA of complex system – application to the whole-building embodied energy analysis. Journal of Cleaner Production, 2013. 43(0): p. 166-173.
45. Angelakoglou, K. and G. Gaidajis, A review of methods contributing to the assessment of the environmental sustainability of industrial systems. Journal of Cleaner Production, 2015.
46. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part I: goals and scope and inventory analysis. International Journal of Life Cycle Assessment, 2008. 13: p. 290-300.
47. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part II: impact assessment and interpretation. International Journal of Life Cycle Assessment, 2008. 13: p. 374-388.
48. Kim, S., T. Hwang, and K.M. Lee, Allocation for cascade recycling system. International Journal of Life Cycle Assessment, 1997. 2: p. 217-222.
161
49. Dubreuil, A., et al., Metals recycling maps and allocation procedures in life cycle assessment. International Journal of Life Cycle Assessment, 2010. 15: p. 621-634.
50. Frischknecht, R., LCI modelling approaches applied on recycling of materials in view of environmental sustainability, risk perception and eco-efficiency. International Journal of Life Cycle Assessment, 2010. 15: p. 666-671.
51. Gomes, F., et al., Adaptation of environmental data to national and sectorial context: application for reinforcing steel sold on the French market. International Journal of Life Cycle Assessment, 2013. 18: p. 926-938.
52. Langevin, B., C. Basset-Mens, and L. Lardon, Inclusion of the variability of diffuse pollutions in LCA for agriculture: the case of slurry application techniques. Journal of Cleaner Production, 2010. 18: p. 747-755.
53. Fava, J.A., Will the next 10 years be as productive in advancing life cycle approaches as the last 15 years? International Journal of Life Cycle Assessment, 2006. 11: p. 6-8.
54. John, V. and H. Wallbaum. Statistical cluster analysis as a means to complement LCA of buildings. in Life-Cycle and Sustainability of Civil Infrastructure Systems: Proceedings of the Third International Symposium on Life-Cycle Civil Engineering (IALCCE'12), Vienna, Austria, October 3-6, 2012. 2012. CRC Press.
55. John, V. and G. Habert, Where is the embodied CO2 of buildings mainly located? Analysis of different types of construction and various views of the results. 2014.
56. Vogtländer, J.G., N.M. van der Velden, and P. van der Lugt, Carbon sequestration in LCA, a proposal for a new approach based on the global carbon cycle; cases on wood and on bamboo. The International Journal of Life Cycle Assessment, 2013: p. 1-11.
57. Fries, N. and S. Hellweg, LCA of land-based freight transportation: facilitating practical application and including accidents in LCIA. International Journal of Life Cycle Assessment, 2014. 19(3): p. 546-557.
58. Basbagill, J., et al., Application of life-cycle assessment to early stage building design for reduced embodied environmental impacts. Building and Environment, 2013. 60(0): p. 81-92.
59. Heeren, N., et al., Environmental Impact of Buildings・ What Matters? Environmental science & technology, 2015. 49(16): p. 9832-9841.
60. SCLCI. EcoInvent Database. 2011; Available from: http://www.ecoinvent.org. 61. EPLCA. European Life Cycle Database. 2015 [cited 2015; Available from:
http://eplca.jrc.ec.europa.eu/. 62. Dutil, Y., D. Rousse, and G. Quesada, Review: Sustainable Buildings: An Ever Evolving Target.
Sustainability, 2011. 3: p. 443-464. 63. Tsai, W.-H., et al., Incorporating life cycle assessments into building project decision-making:
An energy consumption and CO2 emission perspective. Energy, 2011. 36(5): p. 3022-3029. 64. Riaño, N.M., et al., Plant growth and biomass distribution on Guadua angustifolia Kunth in
relation to ageing in the Valle del Cauca – Colombia. Bamboo Science and Culture, 2002. 16(1): p. 43-51.
65. Ghavami, K., Bamboo as reinforcement in structural concrete elements. Cement and Concrete Composites, 2005. 27(6): p. 637-649.
66. Cardona, O., et al., Assessment manual for rehabilitation and reinforcement of traditional bahareque houses built before the building code 052 of 2002. 2002, Seismic engeniering colombian asociation - AIS: Bogotá, Colombia.
67. ISO14040, Environmental Management- Life Cycle Assessment- Principles and Framework, ISO, Editor. 2007, ISO.
68. Chen, C., et al., Environmental impact of cement production: Detail of the different processes and cement plant variability evaluation. Journal of Cleaner Production, 2010. 18: p. 478-485.
69. Huijbregts, M.A.J., et al., Framework for Modelling Data Uncertainty in Life Cycle Inventories. International Journal of Life Cycle Assessment, 2001. 6: p. 127-132.
70. Huijbregts, M.A.J., LCA Methodology Application of Uncertainty and Variability in LCA. International Journal of Life Cycle Assessment, 1998. 3(5): p. 273 - 280.
71. Weidema, B.P. and M.S. Wesnaes, Data Quality Management for Life Cycle Inventories - An Example of Using Data Quality Indicators. Journal of Cleaner Production, 1996. 4: p. 167-174.
162
72. Tardivel, Y., G. Habert, and C. Teyssier, DIOGEN database of environmental impacts of materials for civil engineering works, in GC’11: Civil engeniering at service of the sustainable construction. 2011: Cachan, France.
73. Heijungs, R., Identification of key issues for further investigation in improving the reliability of LCA. Journal of Cleaner Production, 1996. 4(3-4): p. 159-166.
74. Gartner, E., Industrially interesting approaches to “low-CO2” cements. Cement and concrete research, 2004. 34: p. 1489–1498.
75. Bösch, M.E., et al., Applying Cumulative Energy Demand (CExD) Indicators to the ecoinvent Database. International Journal of Life Cycle Assessment, 2007. 12(3): p. 181-190.
76. von Bahr, B., et al., Experiences of environmental performance evaluation in the cement industry. Data quality of environmental performance indicators as a limiting factor for benchmarking and rating. Journal of Cleaner Production, 2003. 11: p. 713-725.
77. Ferraz de Campo, E. and V.M. John, CO2 emissions and residues of Amazon rainforest lumber – preliminary results, in International Symposium on LCA and construction. 2012: Nantes, France. p. 274- 282.
78. Cazaclui, B. and A. Ventura, Technical and environmental effects of concrete production: dry batch versus central mixed plant. Journal of Cleaner Production, 2010. 18: p. 1320-1327.
79. Gough, K.V., Self-help Housing in Urban Colombia; Alternatives for the Production and Distribution of Building Materials. HABITAT International, 1996. 20: p. 635-651.
80. Kellenberger, D., et al., Life Cycle Inventories of Building Products- Data v2.0 (2007). 2007, Swiss Centre for Life Cylce Inventories: Dübendorf.
81. Vogtländer, J., P. van der Lugt, and H. Brezet, The sustainability of bamboo products for local and Western European applications. LCAs and land-use. Journal of Cleaner Production, 2010. 18(13): p. 1260-1269.
82. Salzer, C., A life cycle assessment for alternative building technologies. Construction methods for low income inhabitants in the Philipines, in D-BAUG. 2011, Swiss Federal Institute of technology: Zürich.
83. van der Lugt, P., J. Vogtländer, and H. Brezet, Bamboo- a sustainable solution for Western Europe, Design Cases, LCA and Land-Use. 2009, Delft: INBAR International Network For Bamboo and Rattan, Technical University Delft.
84. Zea Escamilla, E. and H. Wallbaum, Environmental savings from the use of vegetable fibres as concrete reinforcement, in 6th International Structural Engineering and Construction Conference. 2011, Research Publishing: Zürich, Switzerland. p. 1315 - 1320.
85. Zea Escamilla, E., G. Habert, and L. Lopez Muñoz, Environmental Savings Potential from the use of Bahareque(mortar cement plastered bamboo) in Switzerland, in International Conference of Non Conventional Materials NOCMAT13. 2013: Joao Pessoa, Brasil.
86. Bonilla, S.H., et al., Sustainability assessment of a giant bamboo plantation in Brazil: exploring the influence of labour, time and space. Journal of Cleaner Production, 2010. 18(1): p. 83-91.
87. Frischknecht, R. and G. Rebitzer, The ecoinvent database system: a comprehensive web-based LCA database. Journal of Cleaner Production, 2005. 13(13–14): p. 1337-1343.
88. Althaus, H.J., et al., Manufacturing and Disposal of Building Materials and Inventorying Infrastructure in ecoinvent. International Journal of Life Cycle Assessment, 2005. 10(1): p. 35 – 42.
89. Liu, J., et al., Seasonal soil CO2 efflux dynamics after land use change from a natural forest to Moso bamboo plantations in subtropical China. Forest Ecology and Management, 2011. 262(6): p. 1131-1137.
90. Wang, Z., et al. Application of Bamboo-based Engineered Materials in Construction. in International conference on modern bamboo structures. 2009. Bogotá, Colombia: Universidad de los Andes.
91. Guinée, J.B., et al., Life Cycle Assessment: An Operational Guide to the ISO Standards. . 2002, Kluwer Academic Publishers: Dordrecht.
92. Wenzel, H., M.Z. Hauschild, and L. Alting, Environmental Assessment of Products: Volume 1: Methodology, tools and case studies in product development. Vol. 1. 2000, Norwel, MA, USA: Springer.
163
93. Hauschild, M.Z. and L. Alting, Environmental assessment of products: Volume 2: Scientific background. Vol. 2. 1997: Springer.
94. Goedkoop, M., et al., ReCiPe 2008 - A life cycle impact assessment method which comprises harmonized category indicators at the midpoint and the endpoint level / Report I: Characterization, in Ministry of Environment. 2009: Den Haag, Netherlands.
95. Goedkoop, M. and R. Spriensma, The Eco-indicator 99, a damage oriented method for Life Cycle Impact Assessment, methodology report. 2001, PRé Consultants BV.
96. Jolliet, O., et al., IMPACT 2002+: A New Life Cycle Impact Assessment Methodology. International Journal of Life Cycle Assessment, 2003. 8(6): p. 324 - 330.
97. Vogtländer, J.G., A. Bijma, and H.C. Brezet, Communicating the eco-efficiency of products and services by means of the eco-costs/value model. Journal of Cleaner Production, 2002. 10(1): p. 57-67.
98. Vogtländer, J.G., H.C. Brezet, and C.F. Hendriks, The virtual eco-costs ‘99 A single LCA-based indicator for sustainability and the eco-costs-value ratio (EVR) model for economic allocation. The International Journal of Life Cycle Assessment, 2001. 6(3): p. 157-166.
99. Pre-Conultants. SIMA Pro v7.3.3. 2012; Available from: http://www.pre-sustainability.com/simapro-installation.
100. Krozer, J. and J.C. Vis, How to get LCA in the right direction? Journal of Cleaner Production, 1998. 6(1): p. 53-61.
101. Frischknecht, R., R. Steiner, and N. Jungbluth, The Ecological Scarcity Method Eco-Factors 2006, A method for impact assessment in LCA. 2009, Federal Office for the Environment (BAFU): Zürich, Swtizerland.
102. Lasvaux, S., et al., Towards a reduced set of indicators in buildings LCA applications : a statistical based method, in International symposium on LCA and construction. 2012: Nantes, France. p. 65-72.
103. Huijbregts, M.A.J., et al., Is Cumulative Fossil Energy Demand a Useful Indicator for the Environmental Performance of Products? . Environmental Science and Technology, 2006. 40: p. 641-648.
104. Huijbregts, M.A.J., et al., Ecological footprint accounting in the life cycle assessment of products. Ecological Economics, 2008. 64(4): p. 798-807.
105. Kim, S., T. Hwang, and K.M. Lee, Allocation for cascade recycling system. International Journal of Life Cycle Assessment, 1997. 2: p. 217-222.
106. Mutel, C.L. and S. Hellweg, Regionalized life cycle assessment: computational methodology and application to inventory databases. Environmental science & technology, 2009. 43(15): p. 5797-5803.
107. Potting, J., Spatial Differentiation in Life Cycle Impact Assessment A Framework, and Site-Dependent Factors to Assess Acidification and Human Exposure. International Journal of Life Cycle Assessment, 2000. 5(2): p. 77-77.
108. Nansai, K., Y. Moriguchi, and N. Suzuki, Site-dependent life-cycle analysis by the SAME approach: Its concept, usefulness, and application to the calculation of embodied impact intensity by means of an input-output analysis. Environmental science & technology, 2005. 39(18): p. 7318-7328.
109. Mutel, C.L., Framework and tools for regionalization in life cycle assessment. 2012, Diss., Eidgenössische Technische Hochschule ETH Zürich, Nr. 20604, 2012.
110. Gasol, C.M., et al., Environmental assessment:(LCA) and spatial modelling (GIS) of energy crop implementation on local scale. biomass and bioenergy, 2011. 35(7): p. 2975-2985.
111. Liu, K.F.-R., et al., GIS-Based Regionalization of LCA. Journal of Geoscience and Environment Protection, 2014. 2: p. 1-8.
112. Mutel, C.L., S. Pfister, and S. Hellweg, GIS-based regionalized life cycle assessment: how big is small enough? Methodology and case study of electricity generation. Environmental science & technology, 2011. 46(2): p. 1096-1103.
113. Fallahi, G.R., et al., An ontological structure for semantic interoperability of GIS and environmental modeling. International Journal of Applied Earth Observation and Geoinformation, 2008. 10(3): p. 342-357.
164
114. Jankowski, P., Towards participatory geographic information systems for community-based environmental decision making. Journal of Environmental Management, 2009. 90(6): p. 1966-1971.
115. Gontier, M., B. Balfors, and U. Mörtberg, Biodiversity in environmental assessment—current practice and tools for prediction. Environmental Impact Assessment Review, 2006. 26(3): p. 268-286.
116. Ramsey, K., GIS, modeling, and politics: On the tensions of collaborative decision support. Journal of Environmental Management, 2009. 90(6): p. 1972-1980.
117. Höhn, J., et al., A Geographical Information System (GIS) based methodology for determination of potential biomasses and sites for biogas plants in southern Finland. Applied Energy, 2014. 113(0): p. 1-10.
118. Yousefi-Sahzabi, A., et al., GIS modeling of CO2 emission sources and storage possibilities. Energy Procedia, 2011. 4(0): p. 2831-2838.
119. Tang, R., Y. Bai, and T. Wang, Research on GIS Application System of Environmental Risk for Hazardous Chemicals Enterprises. Procedia Environmental Sciences, 2011. 10, Part B(0): p. 1011-1016.
120. Zhang, Y.J., A.J. Li, and T. Fung, Using GIS and Multi-criteria Decision Analysis for Conflict Resolution in Land Use Planning. Procedia Environmental Sciences, 2012. 13(0): p. 2264-2273.
121. Zeilhofer, P. and V.P. Topanotti, GIS and ordination techniques for evaluation of environmental impacts in informal settlements: A case study from Cuiabá, central Brazil. Applied Geography, 2008. 28(1): p. 1-15.
122. Graymore, M.L.M., A.M. Wallis, and A.J. Richards, An Index of Regional Sustainability: A GIS-based multiple criteria analysis decision support system for progressing sustainability. Ecological Complexity, 2009. 6(4): p. 453-462.
123. Javadian, M., H. Shamskooshki, and M. Momeni, Application of Sustainable Urban Development in Environmental Suitability Analysis of Educational Land Use by Using Ahp and Gis in Tehran. Procedia Engineering, 2011. 21(0): p. 72-80.
124. Dresen, B. and M. Jandewerth, Integration of spatial analyses into LCA—calculating GHG emissions with geoinformation systems. International Journal of Life Cycle Assessment, 2012. 17(9): p. 1094-1103.
125. Geyer, R., et al., Coupling GIS and LCA for biodiversity assessments of land use: Part 1: Inventory modeling (LAND USE IN LCA). International journal of life cycle assessment, 2010. 15(5): p. 454-467.
126. Azapagic, A., et al., Approaches for Addressing Life Cycle Assessment Data Gaps for Bio‐based Products. Journal of Industrial Ecology, 2011. 15(5): p. 707-725.
127. Hoxha, E., et al., Method to analyse the contribution of material's sensitivity in buildings' environmental impact. Journal of Cleaner Production, 2014. 66: p. 54-64.
128. Zea Escamilla, E. and G. Habert, Environmental Impacts of Bamboo-based Construction Materials Representing Global Production Diversity. Journal of Cleaner Production, 2014.
129. Mutel, C.L., L. de Baan, and S. Hellweg, Two-Step Sensitivity Testing of Parametrized and Regionalized Life Cycle Assessments: Methodology and Case Study. Environmental science & technology, 2013. 47(11): p. 5660-5667.
130. Balzarini, A., Environmental impact of brick production outside Europe, in Department of Civil, Environmental and Geomatic Engineering. 2013, Swiss Federal Institute of Technology ETH Zürich: Zürich.
131. Zea Escamilla, E. and G. Habert, Environmental impacts from the production of bamboo based cosntruction materials representing the global production diversity. Journal of Cleaner Production, 2013.
132. ESRI. ArcGIS for Desktop. 2014; Available from: http://www.esri.com/software/arcgis/arcgis-for-desktop.
133. Giardini, D., et al., The GSHAP global seismic hazard map. Annals of Geophysics, 1999. 42(6). 134. Pre-Consultants. SIMA Pro v7.3.3. http://www.pre-sustainability.com/simapro-installation.
2012; Available from: http://www.pre-sustainability.com/simapro-installation.
165
135. McCarthy, J.J., Climate change 2001: impacts, adaptation, and vulnerability: contribution of Working Group II to the third assessment report of the Intergovernmental Panel on Climate Change. 2001: Cambridge University Press.
136. Frischknecht, R., et al., Implementation of Life Cylce Impact Assessment Methods, Data v2.0 (2007), in EcoInvent Report No. 3. 2007, EcoInvent Swiss Centre for Life Cycle Inventories: Dübendorf.
137. Jolliet, O., et al., IMPACT 2002+: a new life cycle impact assessment methodology. Int J Life Cycle Assess, 2003. 8(6): p. 324 - 330.
138. Python, S.F. Python Language Reference, version 2.7. 2014; Available from: http://www.python.org.
139. IFRC, Post-disaster shelter: Ten designs. 2013, International Federation of Red Cross and Red Crescent Societies: Geneva, Swtizerland.
140. Pre-Consultants. SIMA Pro v7.3.3. 2012; Available from: http://www.pre-sustainability.com/simapro-installation.
141. Guha-Sapir, D., et al., Annual disaster statistical review 2011: the numbers and trends. 2012, Brussels: Centre for Research on the Epidemiology of Disasters (CRED).
142. IFRC, Transitional shelters – eight designs. 2011, International Federation of Red Cross and Red Crescent Societies: Geneva, Swtizerland.
143. Haapio, A. and P. Viitaniemi, A critical review of building environmental assessment tools. Enviro Impact Assess Rev, 2008. 28(7): p. 469-482.
144. Mateus, R. and L. Bragança, Sustainability assessment and rating of buildings: developing the methodology SBTool PT–H. Build Environ, 2011. 46(10): p. 1962-1971.
145. Ding, G.K., Sustainable construction—the role of environmental assessment tools. J Environ Manage, 2008. 86(3): p. 451-464.
146. Morel, J., et al., Building houses with local materials: means to drastically reduce the environmental impact of construction. Build Environ, 2001. 36(10): p. 1119-1126.
147. Pan, W. and Y. Ning, Dialectics of sustainable building: evidence from empirical studies 1987-2013. Build Environ, 2014(0).
148. Singh, R.K., et al., An overview of sustainability assessment methodologies. Ecol Indic, 2012. 15(1): p. 281-299.
149. Pajchrowski, G., et al., Materials composition or energy characteristic – what is more important in environmental life cycle of buildings? Build Environ, 2014. 72(0): p. 15-27.
150. Gervásio, H., et al., A macro-component approach for the assessment of building sustainability in early stages of design. Build Environ, 2014. 73(0): p. 256-270.
151. Gerilla, G.P., K. Teknomo, and K. Hokao, An environmental assessment of wood and steel reinforced concrete housing construction. Build Environ, 2007. 42(7): p. 2778-2784.
152. Basbagill, J., et al., Application of life-cycle assessment to early stage building design for reduced embodied environmental impacts. Build Environ, 2013. 60(0): p. 81-92.
153. Wang, N., Y.-C. Chang, and C. Nunn, Lifecycle assessment for sustainable design options of a commercial building in Shanghai. Build Environ, 2010. 45(6): p. 1415-1421.
154. Wallbaum, H., et al., Indicator based sustainability assessment tool for affordable housing construction technologies. Ecol Indic, 2012.
155. Manac’h, Y.-G., B. Khaled, and A. Améziane, Life Cycle Cost through Reliability, in New Results in Dependability and Computer Systems. 2013, Springer. p. 523-530.
156. Dreyer, L.C., M.Z. Hauschild, and J. Schierbeck, Characterisation of social impacts in LCA. Int J Life Cycle Assess, 2010. 15(3): p. 247-259.
157. Weidema, B.P., ISO 14044 also applies to social LCA. Int J Life Cycle Assess, 2005. 10(6): p. 381-381.
158. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part I: goals and scope and inventory analysis. Int J Life Cycle Assess, 2008. 13: p. 290-300.
159. Reap, J., et al., A survey of unresolved problems in life cycle assessment. Part II: impact assessment and interpretation. Int J Life Cycle Assess, 2008. 13: p. 374-388.
160. Kim, S., T. Hwang, and K.M. Lee, Allocation for cascade recycling system. Int J Life Cycle Assess, 1997. 2: p. 217-222.
166
161. Dubreuil, A., et al., Metals recycling maps and allocation procedures in life cycle assessment. Int J Life Cycle Assess, 2010. 15: p. 621-634.
162. Frischknecht, R., LCI modelling approaches applied on recycling of materials in view of environmental sustainability, risk perception and eco-efficiency. Int J Life Cycle Assess, 2010. 15: p. 666-671.
163. Gomes, F., et al., Adaptation of environmental data to national and sectorial context: application for reinforcing steel sold on the French market. Int J Life Cycle Assess, 2013. 18: p. 926-938.
164. Langevin, B., C. Basset-Mens, and L. Lardon, Inclusion of the variability of diffuse pollutions in LCA for agriculture: the case of slurry application techniques. J Clean Prod, 2010. 18: p. 747-755.
165. Mutel, C.L. and S. Hellweg, Regionalized life cycle assessment: computational methodology and application to inventory databases. Environ Sci Technol, 2009. 43(15): p. 5797-803.
166. Sesana, M.M. and G. Salvalai, Overview on life cycle methodologies and economic feasibility for nZEBs. Build Environ, 2013. 67(0): p. 211-216.
167. Moldan, B., S. Janoušková, and T. Hák, How to understand and measure environmental sustainability: Indicators and targets. Ecol Indic, 2012. 17(0): p. 4-13.
168. Prinz, G.S. and A. Nussbaumer, On fast transition between shelters and housing after natural disasters in developing regions, in Technologies for sustainable development: a way to reduce poverty, J.C. Bolay, S. Hostettler, and E. Hazboun, Editors. 2014, Springer: Dordrecht, The Netherlands. p. 225-235.
169. Haigh, R. and R. Sutton, Strategies for the effective engagement of multi-national construction enterprises in post-disaster building and infrastructure projects. International Journal of Disaster Resilience in the Built Environment, 2012. 3(3): p. 270-282.
170. Zea Escamilla, E., G. Habert, and L. Lopez Muñoz, Optimization of bamboo based post disaster housing units for tropical and subtropical regions through the use of Life Cycle Assessment methodologies. 2014, Swiss Federal Institute of Technology ETH Zürich: Zürich.
171. Raza, M. and Y. Aggarwal, Transport geography of India: Commodity flows and the regional structure of the Indian economy. 1986, New Delhi: Concept Publishing Company.
172. Pulselli, R., et al., Specific emergy of cement and concrete: an energy-based appraisal of building materials and their transport. Ecol Indic, 2008. 8(5): p. 647-656.
173. Koroneos, C. and A. Dompros, Environmental assessment of brick production in Greece. Build Environ, 2007. 42(5): p. 2114-2123.
174. Ozen, M. and H. Tuydes-Yaman, Evaluation of emission cost of inefficiency in road freight transportation in Turkey. Energy Policy, 2013. 62: p. 625-636.
175. Nicolas, J.-P. and D. David, Passenger transport and CO2 emissions: what does the French transport survey tell us? Atmos Environ, 2009. 43(5): p. 1015-1020.
176. Quak, H., Sustainability of urban freight transport: Retail distribution and local regulations in cities. 2008: Erasmus Research Institute of Management (ERIM).
177. de Jong, G., H. Gunn, and M. Ben-Akiva, A meta-model for passenger and freight transport in Europe. Trans Policy, 2004. 11(4): p. 329-344.
178. Luo, L., E. Van Der Voet, and G. Huppes, Life cycle assessment and life cycle costing of bioethanol from sugarcane in Brazil. Renew Sust Energy Rev, 2009. 13(6): p. 1613-1619.
179. SCLCI, EcoInvent database. 2011, Swiss Centre for Life Cycle Inventories Dübendorf, Switzerland.
180. ISO, ISO 15686-5: buildings and constructed assets -- service-life planning -- part 5: life-cycle costing. 2008, Geneva, Switzerland: International Organization for Standardization.
181. Marszal, A.J. and P. Heiselberg, Life cycle cost analysis of a multi-storey residential Net Zero Energy Building in Denmark. Energy, 2011. 36(9): p. 5600-5609.
182. Chang, S.E. and M. Shinozuka, Life-cycle cost analysis with natural hazard risk. J Infrastruct Syst, 1996. 2(3): p. 118-126.
183. Cabeza, L.F., et al., Affordable construction towards sustainable buildings: review on embodied energy in building materials. Curr Opin Environ Sustain, 2013. 5(2): p. 229-236.
167
Annex
168
169
A. Environmental impact of brick production outside Europe
This section will present briefly the work and results from the Master Project from Mr. Alex Balzarini,
which was developed under the supervision of Prof.Dr. Guillaume Habert and Edwin Zea
Escamilla. Mr. Balzarani, used the methods presented on the paper Zea Escamilla, E. and G.
Habert, Environmental impacts of bamboo-based construction materials representing global production
diversity. Journal of Cleaner Production, 2014.
A.1. Abstract A 90% of the net increase in world population of 4 billion people by 2050 is projected to reside in urban
areas of developing countries. Most of these people will earn low to moderate incomes and construct
their homes as cheap as possible (Ferguson and Smets, 2009). Bricks are an easy and cheap building
material. Therefore they are and will remain the major building material in developing countries (Wang,
2010). The worldwide annual production of bricks is currently about 1391 billion units and the demand
for bricks is expected to be continuously rising. Quarrying operations for obtaining the clay are energy
intensive, adversely affect the landscape, and generate high level of waste. The high temperature kiln
firing not only consumes significant amount of energy, but releases large quantities of greenhouse gases
(Zhang, 2013). This study focuses on the calculation of the environmental impact associated with the
production of bricks in developing countries. Additionally, it searches for alternatives to bricks as a
building material which are also cheap and easy to produce. The study provides mean values and
standard deviations for the different materials and identifies the processes with the greatest influence on
the results, which allows the processes that can be optimized to be identified (Escamilla and Habert,
2014). Another goal is to obtain results which are valid on a global scale, not just for a single country.
Furthermore it aims to assess the impact of bricks and the alternative building materials for some realistic
scenarios. The study uses an easy structure to compare the total impact of the different materials from
the cradle to the finished housing.
A.2. Methods The calculation of the environmental impact for the different materials was done with the software
SIMApro 7.3.3. The values for the total impact were determined using the EcoInvent database for the
life cycle inventory (LCI) and the IMPACT 2002+ method for the calculations. The LCI data were
collected through literature review. An uncertainty analysis was also made. Three products as alternative
were examined
A.2.1. Functional unit and systems boundaries The goal of the LCA presented here is to evaluate the environmental impacts related to the production
of construction materials for developing countries, considering the need for values with global
representativeness and applicability (Zea Escamilla and Habert, 2014). This LCA was limited to four
construction materials: bricks (burned with wood or gas), concrete hollow blocks, stabilized soil bricks
and ferrocement panels. The functional unit is defined as 1 m2 of wall. There are two different ways to
170
compare 1 m2 of wall: with and without structure. In this study both comparisons are used. The
engineering information for the structural wall is from Franklin Martinez who has been project director
and on-site engineer in housing projects and was able to refer to some of his notes. Thus the figures are
as close as possible, taking as base real life in Nicaragua.
The weights of building materials per m2 of wall are given in Table 1 (SWISSCONTACT) for non-
structural walls and in Table A1 -A4 (Martinez and Rhyner, 2013) for structural walls.
Building Material kg per m2 of wall
Brick 147.00
Stabilized soil brick 147.00
Concrete hollow block 117.00
Ferrocement panel 78.75
Tabel A 1Masses of building materials necessary to build 1m2 of non-structural wall
Bricks and stabilized soil
bricks
units per m2 of wall
Average cement 40.13 kg
Sand 226.83kg
Rebar (9mm and 6mm) 7.13kg
Bricks 147.00 kg
Tabel A 2 Masses of building materials necessary to build 1m2 of structural wall with bricks and stabilized soil bricks
Concrete hollow blocks units per m2 of wall
Average cement 33.66 kg
Sand 196.34kg
Rebar (9mm and 6mm) 7.13kg
Concrete hollow blocks 117.00 kg
Tabel A 3 Masses of building materials necessary to build 1m2 of structural wall with concrete hollow blocks
171
Ferrocement panels units per m2 of wall
Average cement 15.43 kg
Sand 91.06kg
Rebar (9mm and 6mm) 3.55kg
Ferrocement panels 78.75 kg
Tabel A 4 Masses of building materials necessary to build 1m2 of structural wall with ferrocement panels
A.2.2. Inventory data The Life Cycle Inventory (LCI) data were collected through literature review. The focus of data
collection was on the material, energy, and transport inputs needed to produce the functional unit
(Zea Escamilla and Habert, 2014). The infrastructure was also considered, representing the machinery
that is used for the production of each material (Salzer, 2011).
For the transport of the raw materials to the production site two different ranges of distances are used:
The one for cement is assumed to vary from 50km (Pulselli et al, 2008) to 500km (UN-HABITAT,
1989). For all other materials the transport distances are assumed to vary from 24km (Koroneos
and Dompros, 2007) to 75km (Salzer, 2011). For the case study in Haiti, the transport distance for
the building materials to the construction site is 20km. For the transport of brand-name cement, high
quality concrete hollow blocks and stabilized soil bricks the distance is assumed to be 250km. To
determine the influence of transport distances, an extreme scenario has been chosen for a case study:
In November of 2013 the typhoon Haiyan devastated parts of the Philippines, the province of
Leyete was one of the most affected (The Guardian, 2013). Assuming that the cement plants
and building materials factories nearby are destroyed, brand name cement and high quality
products for reconstruction have to be delivered from far away. In this case it was assumed that they
are transported from the area of Manila, which means that transport distance is 950km by road in
addition to 30km by freight. Three different types of cement are used for this study, they are
represented in Table A 5 (EcoInvent, 2011): a brand-name cement, a generic cement for which the
input was increased by 50% compared to the brand-name one and an average of these two products.
172
Cement unit generic cement average cement brand/name cement
mat
eria
ls
Clinker kg 1,3545 1,1288 0,9030
Ethylene glycol kg 0,0003 0,0002 0,0002
infr
astr
uctu
re
Cement plant
p
8,04E/11
6,70E/11
5,36E/11
Steel, low/alloyed
kg
7,50E/05
6,25E/05
5,00E/05
fuel
s an
d en
ergy
Heat waste
MJ
0,1575
0,1313
0,1050
Electricity
kwh
0,0438
0,0365
0,0292
Tabel A 5 Materials, infrastructure, fuels and energy for the production of 1kg of cement
For the stabilized soil brick, the input is almost the same as for bricks. Instead of using wood or gas to
burn the brick, the stability is provided by adding cement. The additional inputs for the stabilized soil
brick and the ones changed are given in Table A6 (Salzer, 2011; EcoInvent, 2011).
Stabilized soil brick unit low performance average high performance
mat
eria
ls
Cement
kg
0,2332
0,1555
0,0777
infr
astr
uctu
re
Industrial machine, heavy, automized
kg
0,01
0,00
0,00
Concrete mixing plant
p
2,47ED10
1,23ED10
0,00E+00
fuel
s an
d en
ergy
Diesel
MJ
0,0120
0,0060
0,0000
Electricity
kwh
0,0040
0,0020
0,0000
Tabel A 6 Additional or changing inputs for 1kg of stabilized soil brick. The other inputs are the same as for 1kg of brick not using natural gas, sawdust, eucalyptus branches and woodAnother alternative for bricks are concrete hollow blocks shown in Table A7 (Salzer, 2011; SWISSCONTACT; EcoInvent, 2011).
CONCRETE HOLLOW unit low performance average high performance
mat
eria
ls Cement kg 0,1350 0,1053 0,0756
Clay kg 0,9000 0,4500 0,0000 Tap water kg 0,4440 0,2639 0,0837
Sand kg 0,8330 0,4165 0,0000 Gravel kg 0,8050 0,5831 0,3611
infr
astr
uctu
re
Mine
p
1,00EG10
Industrial machine, heavy, automized
kg
0,0061
0,0030
0,0000
fuel
s an
d en
ergy
Diesel
MJ
0,0160
0,0130
0,0100
Electricity
kwh
0,0065
0,0053
0,0040
Tabel A 7 Materials, infrastructure, fuels and energy for the production of 1kg of concrete hollow block
173
Ferrocement panels represent a completely different but also cheap alternative to bricks as building
material. For this dataset, there were only mean values without deviations available, they are given in
Table A8 (Martinez and Rhyner, 2013). For the transport distance of the raw materials 50km were
assumed.
Ferrocement panel unit average
mat
eria
ls Sand kg 1,0333
Steel rebars kg 0,0444 Chromium steel kg 0,0100 Lubrificating oil kg 0,0025
Cement kg 0,2800
infr
astr
uctu
re
Industrial machine, heavy, automized
kg
0,0030
fuel
s an
d en
ergy
Diesel
MJ
0,0754
Electricity
kwh
0,0040
Tabel A 8 Materials, infrastructure, fuels and energy for the production of 1kg of ferrocement panel
A.2.3. Impact assessment As proposed by (Zea Escamilla and Habert, 2014), the following method is used to assess the total
impact: Three main categories of impact assessment methods can be found in the literature: i)
pressure-oriented methods, such as CML (Guinée et al., 2002) or EDIP (Hauschild and Alting, 1997;
Wenzel et al., 2000), which restrict quantitative modeling to relatively early stages in the cause-
effect chain to limit uncertainties; ii) damage-oriented methods, such as Eco-indicator 99 (Goedkoop
et al., 2009; Goedkoop and Spriensma, 2001) or IMPACT 2002+ (Jolliet et al., 2003), which try to
model the cause-effect chain up to the end point or damage point, sometimes with high uncertainty;
and iii) prevention-oriented methods, which are often monetized and based on the marginal prevention
costs of emissions, such as eco-costs (Vogtländer et al., 2002; Vogtländer et al., 2001).
For clarity of the results, the damage-oriented IMPACT 2002+ v 2.1 method was used to reduce
the number of impact categories. In this method, four categories are considered: human health,
assessed in DALY; ecosystems quality, assessed in PDF.m2.yr; climate change, assessed in kg CO2;
and resources, assessed in MJ. The results are normalized with the factors 0.0071 DALY, 13,700
PDF.m2.yr, 9,950 kg CO2, and 152,000 MJ for the respective impact categories. These factors
represent the yearly emissions of one European citizen. This normalization allows the results to be
expressed in “points”, with one point equal to the yearly emission of one European citizen in one
impact category. As a final step, the results for the four impact categories were summed, considering
an equal contribution for each category, and presented as a single score value. All the LCA
174
calculations were performed using the software SimaPro v 7.33 (Pre-Conultants, 2012) and the database
EcoInvent (2011).
A.2.4. Uncertainty analysis The uncertainty analysis was conducted as described by (Zea Escamilla and Habert, 2014) in a similar
way: An environmental assessment necessitates several assumptions whose influence is difficult to fully
constrain. Moreover, background and foreground data have associated uncertainties, which appear
throughout the environmental assessment process (Weidema and Wesnaes, 1996). In the study
presented here, the focus was primarily on variability in the main production process and in process
efficiency. The uncertainty analysis was, therefore, restricted to the technological foreground data. In
the previous section, three scenarios were proposed: high, low and average performance. To perform
an uncertainty analysis on the data from these scenarios, two approaches were developed. In the first
approach, the uncertainty of the result due to variability in the inputs between a worst-case and best-
case scenario was calculated, and the relative contribution of these inputs to the uncertainty was
evaluated. A Monte Carlo simulation was used in the first approach. Because of the scarcity and the
high variability of data, a triangular probabilistic distribution was used. This type of distribution is
commonly used for cases in which the relationship between variables is known but data are scarce,
making it impossible to exactly define an input value. In the Monte Carlo simulation, 1000
runs/iterations were analyzed, with a confidence interval of 95%. In the second approach, the
contribution of each input to the difference between the best-case and worst- case scenarios was
calculated. The environmental impact of each material was calculated for its best-case and worst-case
scenarios. The difference between these scenarios was then calculated at a process level. These
results were normalized to show the total contribution of each impact to the variation between the
scenarios.
A.3. Results and discussion The processes providing the stability in the building materials (the heat for burning the bricks and the
cement for the other materials) are the main contributors to the total impact. Figure 1 shows the
mentioned processes contribute more than 50% for all building materials.
A significant difference in the total impact can be observed between the bricks (burned with wood or
gas) and the alternative building materials with cement, as shown in Figure 2.9. The mean impact of
bricks burned with wood, for example, is more than seven times higher than the one of concrete hollow
blocks. The impacts of the cement products do not show these big differences, the best performing
(concrete hollow blocks) has about a two times smaller impact than the worst performing (ferrocement
panels). Additionally, brick show a much higher uncertainty for the total impact than the other materials.
Figure 2.9 shows the total impact of stabilized soil bricks and concrete hollow blocks as a function of
transport distance for a case study in Haiti by comparing 1m2 of structural wall. The transport has little
influence: Local, inefficient production instead of remote, high quality production gets only more
175
attractive for transport distances bigger than 443.6km for stabilized soil bricks and 169.7km for concrete
hollow blocks.
Figure A.1 Total impact for 1m2 of non-structural wall of each building material in the study
A.4. Conclusions The results of this LCA study support the following conclusions:
Brick production in developing countries has high environmental impacts, the obtained results
show a high variability
Alternative building materials with cement have much lower environmental impacts and less
variation in the results
Efficiency in brick production has to be increased drastically to lower the total impacts:
Reuse of heat waste
Use of renewable electricity sources for production
Cradle and production in the same place to eliminate transport of raw materials
For cement products, it is very important not to exceed the needed amount to keep impacts low
Generally, using brand-name cement has positive effects for the environment
Transport for production and construction has little influence on the total impacts (only for
extreme cases with very high distances local production becomes attractive)
The results suggest to search for alternatives to bricks as building materials and to increase the efficiency
in brick production in developing countries. In this study, social and monetary influences were neglected
which might cause changes, if considered. To make the alternative building materials mentioned in this
176
study competitive with bricks, it is crucial that they can be produced easily and that they have
approximately the same price as bricks. The obtained results are applicable on a global scale and can be
used for all developing countries. Further investigations can be made considering the whole life cycle
of a building, from cradle to grave, providing better bases for decision-making.
177
B. Bamboo based construction materials The environmental impacts associated to these bamboo based construction materials can be found in section
2.4.
Table B 1 bamboo based construction materials FU dimensions
Length (m)
Ext diam (m)
# Culms Weight
per culm
Density kg/m3
1 m3 culm 18 0.11 5 25 125
Length (m)
Ext diam (m)
# Poles Weight per pole
(kg)
Density kg/ m3
1m3 pole 6 0.11 15 6.67 100
Length (m)
Width (m)
Height (m)
Flattened thickness
(m)
# flattened per m3
Density kg/ m3
1m3 flattened Bamboo 6 0.35 0.48 0.025 19 176.8
Length (m)
Width (m)
Height (m)
Mat thickness
(m)
# mats per m3
Density kg/ m3
1m3 Woven bamboo mat 2.4 1.2 0.35 0.003 116 178.2
Length (m)
Width (m)
Height (m)
Panel thickness
(m)
# panels per m3
Weight per panel
(kg)
Density kg/ m3
1m3 Woven mat panel
2.4 1.2 0.35 0.012 29 25.02 724
Length (m)
Width (m)
Height (m)
Panel thickness
(m)
# panels per m3
Weight per panel
(kg)
Density kg/ m3
1m3 Glue Laminated Bamboo
2.4 1.2 0.35 0.02 17 51 885
178
179
C. Sustainability assessment of 20 Shelters data in brief
Data in Brief 4 (2015) 308–314
Abstract
This data article presents the life cycle inventories of 20 transitional shelter solutions. The data was gathered
from the reports 8 shelter designs [1]; 10 post-disaster shelter designs [2]; the environmental impact of brick
production outside of Europe [3]; and the optimization of bamboo-based post-disaster housing units for
tropical and subtropical regions using LCA methodologies [4]. These reports include bill of quantities, plans,
performance analysis, and lifespan of the studied shelters. The data from these reports was used to develop
the Life Cycle Inventories (LCI). All the amounts were converted from their original units (length, volume
and amount) into mass (kg) units and the transport distance into ton x km. These LCIs represent the
production phases of each shelter and the transportation distances for the construction materials. Two types
of distances were included, local (road) and international (freight ship), which were estimated based on the
area of the country of study. Furthermore, the digital visualization of the shelters is presented for each of the
20 designs. Moreover, this data article presents a summary of the results for the categories Environment,
Cost and Risk and the contribution to the environmental impact from the different building components of
each shelter. These results are related to the article “Global or local construction materials for post-disaster
reconstruction? Sustainability assessment of twenty post-disaster shelter designs”[5]
C.1. Specifications Table [please fill in right-hand column of the table below] Subject area Sustainability
More specific subject area Life cycle assessment, sustainable construction
Type of data Tables
How data was acquired Literature review
Data format analysed
Experimental factors None
Experimental features None
Data source location Worldwide
Data accessibility The data is available at http://www.ifrc.org/PageFiles/95186/900300-Transitional%20Shelters-Eight%20designs-EN-LR.pdf
180
C.2. Data, Materials and Methods:
Three types of data are presented on this data article. First the lifecycle inventories for each shelter, this data
represents the amount of construction material need to construct each shelter. Moreover this data present the
transport distance that each amount of material was transported form its production site to the construction
site. Second, Assessment results: this data presents the performance of each shelter on the proposed
assessment categories Environment, Cost, and Risk and are associated to the article “Global or local
construction materials for post-disaster reconstruction? Sustainability assessment of twenty post-disaster
shelter designs“ [5]. Finally, the contribution to environmental impacts. This data represent the contribution
that each building component, foundation, structure, walls, roof and transport of construction material
produces on the overall environmental impact and it is related to the article article “Global or local
construction materials for post-disaster reconstruction? Sustainability assessment of twenty post-disaster
shelter designs“ [5]. Finally, a digital representation of the shelters is provided.
C.2.1. B1 Afghanistan Bamboo This shelter was built to act as a shell to protect occupants living in tents. Each shelter contains one tent,
erected inside the structure. It is rectangular in plan and has 1.8m tall side walls and a gable roof. The covered
floor area is approximately 9m x 4.3m. The frames are constructed from bamboo poles. The frames are
connected using plywood gusset plates and bolts. The walls and roof are plastic sheeting, and are supported
on the bamboo frame and purlins. The floor is compacted soil. The shelter frames were shop fabricated in
the camp and transported to the construction site. The frames are embedded into the ground for support.[2]
C.2.2. B5 Indonesia Bamboo The rectangular bamboo frame structure measures 6m x 4m on plan and has a hipped roof of terracotta tiles
laid on bamboo matting and laths. The frame has woven bamboo matting walls, a door at the front and two
windows on each side. The back section has a raised floor which forms a sleeping area constructed from
bamboo joists and panelling. The floor void has been filled with rubble confined by a low masonry wall all
round. The structure is braced with bamboo members on all sides which provides stability with an additional
roof truss in the centre. The shelter is supported by five bucket foundations with a length of bamboo cast in
to connect to the four main columns. The frame connections are pinned using bamboo pegs and then secured
with rope. The roofing and flooring are fixed with nails.[1]
C.2.3. B8 Philippines Bamboo This shelter is a rectangular structure with 2 or 4 slopes on the roof depending on the configuration. The inner
areas is approximately 3m x 6m. The roof extends 1m on each direction to provide protection from the rain.
The exterior is composed of bamboo based frames using bamboos with diameters between 8 and 10cms. The
frames are cladded with flattened bamboo and chicken mesh. The cladding can be applied outside and inside
181
or only outside depending on the external hazards. The cladding layer is covered with a mortar cement plaster
with thickness from 1cm to 2cms. The frames are supported by a line of concrete hollow blocks. The roof
consists of a bamboo poles structure and galvanized steel sheets. The joints between bamboo elements are
reinforced with steel elements and slurry concrete. The design can be customized with several options for
doors and windows depending on the desired configuration.[4, 6, 7]
C.2.4. C2 Bangladesh Concrete / Timber This shelter is has reinforced concrete columns, a steel framed hip roof with metal roofing and bamboo mat
walls. The total covered area is approximately 4.5m x 3.2m, and there is one door and three windows. The
floor is raised above existing grade, and a short brick wall is provided around the perimeter to resist flood
waters and windblown rain. The 8 concrete columns are embedded approximately 1.5m into the ground. The
roof truss is constructed with steel angles and is anchored to the concrete columns. The foundation consists
of the 8 embedded columns, and a perimeter concrete grade beam. There are wooden beams between the
columns approximately 2.1m above the first floor, which allow the addition of a mezzanine level to the
shelter. The shelter is designed to be easily moved by unbolting the columns and roof frame with hand tools
and the materials can be re-used as a part of permanent housing reconstruction. Additionally it is designed
so that a mezzanine level can be built to provide storage space in case of floods.[2]
C.2.5. C6 Pakistan Brick This shelter is a rectangular structure with a flat roof with approximate dimensions of 4.8m x 3.9m. Walls
are built with 230mm thick unreinforced fire burned brick walls supporting the roof. The roof is constructed
with ceramic tiles supported on steel beams, and a cement plaster coating is placed on top of the tiles. The
foundation consists of unreinforced brick footings and foundation walls. The mud plastered floor is raised a
minimum of 610mm above the surrounding ground surface. As designed, the shelter has one door and one
window, along with air vents near the top of the walls.[2]
C.2.6. C8 Philippines Concrete This shelter is a rectangular structure with a single pitch roof and a covered floor area of approximately 4.8m
x 3.7m. The shelter is supported on concrete piers and footings such that the first floor is raised approximately
750mm above grade. The floor and roof are framed with coconut wood beams and joists. The floor is plywood
and the roof is corrugated metal roofing. The exterior walls consist of amakan (woven panels of bamboo or
palm leaves) fastened to the coconut wood frame. The light weight wood frame can be lifted off the concrete
piers and moved to a different location by a small number of people. As designed, the shelter has one door
and two windows.[2]
182
C.2.7. C9 Sri Lanka Concrete / Timber This shelter is a rectangular structure with a gable roof and an enclosed floor area of approximately 3.5m x
2.8m with an additional covered veranda of approximately 3.5m x 2.8m. The exterior walls are built with
unreinforced bricks with six reinforced masonry piers. All masonry blocks are fabricated by the shelter
occupants prior to construction. The roof consists of coconut wood rafters and purlins supporting corrugated
iron sheet roofing. The compacted earth and concrete floor is raised above the surrounding ground surface.
The perimeter walls extend into the ground, and are supported on brick footings. The modular construction
for the shelter allows for expansion in both horizontal directions with only minor modifications to the core
shelter. As designed, the shelter has one door and one window.[2]
C.2.8. C11 Nicaragua Ferrocement This shelter is a rectangular structure with a gable roof and a covered area of approximately 3m x 6m with
additional division walls. The exterior is built with ferrocement panels of 0.5m x 2.5m. All the panels are
prefeabricated either at small facory or locally depending on the availiability. The reinforcement consit on a
lower and upper concrete ring. The roof consist of a galvanized steel sheets. The floor is a slat of poor
concrete. The constructive system used on this shelter allows for its expansion both vertically and
horizontally. The shelter can be customized with several options for doors and windows depending on the
desired configuration.[3]
C.2.9. S4 Haiti Steel The shelter consists of a galvanised rectangular steel frame with an 8.5 degree mono-pitch roof and a
suspended floor. The height to the eaves is 2.55m and 3m to the ridge and there is no bracing. The shelter is
3 x 6 m on plan and has 6 columns spaced on a 3m grid, fixed to 800x800x400mm rectangular reinforced
concrete foundations using a 300x300x6mm base plate and four ordinary bolts per base. The raised floor is
also supported by 13 additional stub columns on 100x100x6mm base plates bearing directly on to the soil.
The main structure is three primary frames with rectangular hollow section columns. The roof cladding is
corrugated steel sheeting nailed to steel secondary roof members spaced at 0.75m intervals spanning between
the three primary frames. Timber studs are screwed to the steel members and the plastic wall sheeting is
attached to this. Additional timber sub-framing is used to form windows and doors.[1]
C.2.10. S5 Indonesia Steel The structure consists of a cold rolled, hot dip galvanised steel frame with a pitched roof of 24.3 degrees and
a raised floor. The height is 2.8m to the eaves and 4.15m to the ridge. The platform area of the shelter is
25m2 with a cantilevering balcony at opposite sides front and back and a cantilevering roof covering the
183
balconies. There are 6 columns fixed using column base plates nailed directly into the ground. Metal roof
sheets are screwed to steel purlins spanning between primary roof beams. Limited lateral stability is provided
by timber plank wall cladding fixed to timber studs that are in turn screwed to the steel frame. The floor
consists of timber planks spanning between steel joists.[1]
C.2.11. S10 Vietnam Steel The shelter is a galvanised lightweight steel frame with plywood walls and a corrugated steel sheet roof. It
has a covered area of 3.6 x 8.4m on plan including a living area of 3.6 x 7.2m. The roof has a pitch of 16.5
degrees. The height of the roof varies from 3.2m at the eaves to 4.6m at the ridge. There are two doors, one
at the side and one at the front, and a cantilevered canopy projecting 1.3m beyond the door to form a porch.
There are twelve columns, six of which have screw in ground anchor foundations, connected in pairs by a
braced truss to form a moment frame. The stability system is formed by these three moment frames tied
together by two further moment frames on each edge of the building. There is steel tie bracing underneath
the roof sheeting. The shelter has a 100mm thick concrete slab base cast over the screw anchor foundations
and floor tie beams. There is a low, non-structural, 0.5m, brickwork wall providing a degree of flood
protection.[1]
C.2.12. W3 Burkina Faso Timber This shelter is a rectangular timber frame with a pitched roof and a covered floor area of 2.7m x 1.8m. The
frame has plastic sheeting for both roof and wall covering, and one door on each short side. The wall frame
is made from timber panels that are pre-fabricated on the ground. The timber roof structure is nailed to these
panels. Both walls and roof are reinforced with wire cross bracing. There is a knee braced timber framed
along the roof ridge which supports the roof panels, and provides stability during construction. Wall and roof
covering is fastened to the timbers using flat-head nails.[2]
C.2.13. W4(A) Haiti Timber This shelter is a rectangular timber framed structure with a gable roof and a covered floor area of
approximately 21 square meters. Wall consists of wood studs with plywood sheathing, and the roof consists
of metal roofing on wood purlins and trusses. The trusses are supported on wood posts within in the perimeter
walls. The wood trusses can be pre-manufactured and shipped to the construction site. The foundation
consists of concrete piers in the four corners and a stone masonry wall in-between the piers. The floor is a
cast-in-place concrete slab. As designed, the shelter has only one door and one window.[2]
C.2.14. W4(B) Haiti Timber This shelter is a rectangular timber framed structure with a gable roof and a covered floor area of
approximately 3.6m x 4.9m with a covered porch measuring approximately 3.6m x 1.8m in front. The floor
is constructed with wood joists, and the walls are constructed with wood studs. Both are supported by built-
up timber posts. The roof is framed with wood trusses that can be pre-manufactured and shipped to the site.
184
The roof extends over the porch to provide cover. Floors and walls are covered with plywood, and the roof
is covered with metal panels. The bottom of the built-up timber posts are encased in concrete and embedded
in the ground. The design includes one door in the front and back walls, and louvred wall openings.[2]
C.2.15. W4(C) Haiti Timber This shelter is a rectangular timber framed structure with a gable roof and a covered floor area of
approximately 5.4m x 3.7m with a covered porch measuring approximately 1.8m x 3.7m. The roof has wood
and corrugated bituminous roofing supported on timber purlins and trusses. The exterior walls are wood
framed, and the wall infill is constructed using a traditional technique called clissage, which consists of thin
slats of wood woven between the wall framing. The foundation consists of wood posts embedded in concrete
piers, and the floor is an elevated concrete slab supported by a short masonry wall between the wood posts.
As designed, the shelter has one door and two windows. The shelters were designed to be accessible by
persons with reduced mobility and individual modifications were made according to personal needs.[2]
C.2.16. W5 Indonesia Timber The shelter is a timber framed structure with palm roofing and walls. It measures 4.5m x 4m on plan and is
3.35m tall to the ridge beam and 2.4m to the eaves. It has a pitched roof of 23.6 degrees. There is no bracing,
but some stability is provided by three portal frames tied together by horizontal members at ground, eaves
and ridge level. Each portal frame is made up of two or three columns and a roof truss with rafters and corner
bracing members. The corner bracing in the frames provides lateral stiffness. Secondary non-structural
members include: floor joists, roof joists spanning between rafters and transoms to support palm matting wall
panels. The shelter has a suspended floor. This is assumed to be coconut wood boarding spanning between
the floor joists. The columns are embedded into concrete bucket foundations that sit directly on the ground.[1]
C.2.17. W6 Pakistan Timber The shelter consists of 7 triangular frames, connected by a ridge pole. The ridge pole is supported by two
2.74m high vertical columns at each end. The shelter is 4.3m x 5.7m on plan. It has a low (0.9m) brick wall
constructed inside the frame to provide protection against flood damage and retain warmth. The roof is
pitched at 44 degrees and is made of corrugated steel sheeting. The sheeting is nailed to purlins that span
between the frames. The roof sheeting is laid on top of locally available insulating material and plastic
sheeting. The foundation of the shelter is provided by burying the rafters and columns approximately 0.3m
in to the ground on top of stone footings. Guy ropes over the roof sheeting have been used to help prevent
uplift under wind loads.[1]
C.2.18. W7(A) Peru Timber The shelter has a Bolaina (Bolayna) timber braced frame, measuring 3m x 6m on plan with a single pitched
roof at four degrees. The shelter is clad with tongue and groove solid timber board walls and a corrugated
fibre cement sheet roof. It is 2.4m high and stands on a new or existing concrete floor slab. In instances where
a new slab has been used, wire ties wrapped around nails have been cast into the slab and attached to the
frame at all column locations to resist uplift. Where existing slabs have been used the shelter has been staked
185
to posts installed outside the slab. The shelter is constructed as 6 panels which are then nailed together using
connecting wooden members, connecting plates and plastic strapping. A central roof edge beam is attached
to the panels and are purlins nailed on top of this to support the roof.[1]
C.2.19. W7(B) Peru Timber The structure is a rigid box consisting of braced frames in both directions. The braced frames provide lateral
stability. The eucalyptus timber frame has a flat roof and is covered with stapled plastic sheeting and nailed
palm matting on all faces. The shelter is 2m high and 3m x 6m on plan. The bracing consists of crossed
twisted wires. The 75mm diameter columns are connected horizontally with 50mm diameter horizontal
members. The foundation and floor consists of an unreinforced concrete slab with cast in wire ties. The
connections between members are made using bent nails.[1]
C.2.10. W8 Philippines Timber This shelter is a rectangular structure with a gable roof and a covered floor area of approximately 4.0m x
5.0m with a covered bathroom and vestibule of approximately 4.0m x 1.5m. The exterior walls have a half
height concrete masonry wall with wood framing on top up to the eaves. The roof consists of timber trusses
and purlins supporting corrugated metal roofing. The roof framing is supported by eight precast concrete
columns located within the exterior walls. The concrete columns and masonry walls are embedded in the
ground, and the plans do not specifically call for footings. The floor is a cast in place concrete slab, and the
bathroom has a below grade septic tank. The modular construction for the shelter allows for expansion in
both horizontal directions with only minor modifications to the core shelter. It is also possible to deconstruct
the shelter for relocation and/or to be included in permanent construction. As designed, the shelter has two
doors and two windows.[2]
C.3. Methods The methodology to produce the data here presented is described on the article “Global or local construction
materials for post-disaster reconstruction? Sustainability assessment of twenty post-disaster shelter designs“
[5].
C.4. Value of the data
Describe the material demand (life cycle inventories) of several transitional shelters
The data comes from experiences on the field
Describes the cost and technical performance of transitional shelter, which is needed for their assessment
C.5. Acknowledgements The authors would like to thank the students that took part in the BSc and MSc Project in 2013-14 that
contributed to this project. In addition, we thank the International Federation of the Red Cross and Red
Crescent Societies for support and advice. Finally, we thank EcoSur for their invaluable contributions to this
research and HILTI AG for their long-term support in the development of the present research project.
186
C.6. Shelters LCIs
Environmental Impact
Shelter Amount Unit Amount Unit
B1 AFGHANISTAN BAMBOO 1 Shelter
Materials
bamboo pole, gen 8.44 kg 2.91 mPt
Plywood, outdoor use 38.37 kg 26.35 mPt
Packaging film, LDPE 128.94 kg 135.36 mPt
Transport
Transport, lorry 3.5-16t 0.5 tkm Bamboo pole
0.05 mPt
Transport, lorry 3.5-16t 2.5 tkm Plywood 0.25 mPt
Transport, lorry 3.5-16t 8.4 tkm Packaging film
0.84 mPt
187
Assessment
Contribution to Env. Impact
188
Environmental Impact
Shelter Amount Unit Amount Unit
B5 INDONESIA BAMBOO 1 Shelter
Materials bamboo pole 375.2 kg 148.45 mPt bamboo mats 67.7 kg 0.0019 mPt Ceramic tiles 1087.5 kg 309.26 mPt Concrete, normal 856.8 kg 15.67 mPt Reinforcing steel 1.2 kg 0.64 mPt
Steel, electric, un- and low-alloyed 1.0 kg 0.22 mPt
Transport
Transport, lorry 3.5-16t 37.5 tkm Bamboo pole
3.75 mPt
Transport, lorry 3.5-16t 108.8 tkm tiles 10.89 mPt Transport, lorry 3.5-16t 85.7 tkm concrete 8.58 mPt Transport, lorry 3.5-16t 0.1 tkm reinf steel 0.01 mPt Transport, lorry 3.5-16t 0.1 tkm Steel 0.01 mPt
Transport, lorry 3.5-16t 6.8 tkm bamboo mats
0.68 mPt
Transport, transoceanic freight ship 4.3 tkm reinf steel 0.02 mPt
Transport, transoceanic freight ship 2.1 tkm Steel 0.01 mPt
189
Assessment
Contribution to Env. Impact
190
Environmental Impact
Shelter Amount Unit Amount Unit
B8 PHILIPINES BAMBOO 1 Shelter Materials bamboo pole 160.0 kg 63.31 mPt bamboo mats 3370.0 kg 0.092 mPt Galvanized steel sheet 130 kg 25.16 mPt Concrete, normal 4190.0 kg 76.65 mPt Reinforcing steel 350.0 kg 186.61 mPt
Steel, electric, un- and low-alloyed 10.0 kg 5.33 mPt
Transport Transport, lorry 3.5-16t 37.5 tkm Bamboo pole 3.75 mPt Transport, lorry 3.5-16t 108.8 tkm Galvanized steel 10.89 mPt Transport, lorry 3.5-16t 85.7 tkm concrete 8.58 mPt Transport, lorry 3.5-16t 0.1 tkm reinf steel 0.01 mPt Transport, lorry 3.5-16t 0.1 tkm Steel 0.01 mPt Transport, lorry 3.5-16t 6.8 tkm bamboo mats 0.68 mPt Transport, transoceanic freight ship 4.3 tkm reinf steel 0.02 mPt
Transport, transoceanic freight ship 2.1 tkm Steel 0.01 mPt
191
Assessment
Contribution to Env. Impact
192
Environmental Impact
Shelter Amount Unit Amount Unit
C2 BANGLADESH CONCRETE / STEEL 1 Shelter Materials Concrete, normal 446.3 kg 7.83 mPt Hot rolling, steel 308.0 kg 35.069 mPt Reinforcing steel 354.0 kg 188.75 mPt Light clay brick 1265.0 kg 44.84 mPt Sawn timber, hardwood, planed, kiln dried 148.0 kg 31.92
mPt
bamboo mats 590.0 kg 0.02 mPt Galvanized steel sheet 177.0 kg 34.25 mPt
Galvanized steel sheet 40.0 kg 7.74 mPt
Transport Transport, transoceanic freight ship
6133.0 tkm Steel 34.75
mPt
Transport, lorry 3.5-16t 29.0 tkm Concrete 2.90 mPt Transport, lorry 3.5-16t 82.2 tkm Light clay brick 8.23 mPt
Transport, lorry 3.5-16t 9.6 tkm
Sawn timber, hardwood 0.96
mPt
Transport, lorry 3.5-16t 38.4 tkm Bamboo mats 3.84 mPt
Transport, lorry 3.5-16t 57.1 tkm Steel 5.72 mPt
193
Assessment
Contribution to Env. Impact
194
Environmental Impact
Shelter Amount Unit Amount Unit
C6 PAKISTAN CONCRETE 1 Shelter Materials Concrete, normal 2815.8 kg 49.33 mPt Light clay brick 20140.0 kg 710.71 mPt Hot rolling, steel 264.0 kg 30.06 mPt
Ceramic tiles 714.0 kg 171.41 mPt
Transport Transport, transoceanic freight ship 2473.7 tkm Steel 14.02
mPt
Transport, lorry 3.5-16t 369.6 tkm Steel 36.99 mPt Transport, lorry 3.5-16t 357.6 tkm Concrete 35.80 mPt Transport, lorry 3.5-16t 2557.8 tkm Light clay brick 256.01 mPt
Transport, lorry 3.5-16t 90.7 tkm Ceramic tiles 9.08 mPt
195
Assessment
Contribution to Env. Impact
196
Environmental Impact
Shelter Amount Unit Amount Unit
C8 PHILIPPINES CONCRETE / WOOD 1 Shelter Materials Concrete, normal 771.1 kg 13.52 mPt Sawn timber, softwood, planed, kiln dried 395.0 kg 70.33
mPt
Plywood, outdoor use 109.0 kg 82.14 mPt
Galvanized steel sheet 135.0 kg 26.12 mPt
Transport
Transport, lorry 3.5-16t 280.8 tkm Galvanized steel 1.59 mPt Transport, lorry 3.5-16t 97.9 tkm Concrete 9.80 mPt
Transport, lorry 3.5-16t 50.2 tkm Sawn timber, softwood 5.02
mPt
Transport, lorry 3.5-16t 13.8 tkm Plywood 1.39 mPt
Transport, lorry 3.5-16t 17.1 tkm Galvanized steel 1.72 mPt
197
Assessment
Contribution to Env. Impact
198
Environmental Impact
Shelter Amount Unit Amount Unit
C9 SRI LANKA BRICK/CONCRETE/WOOD 1 Shelter Materials Concrete, normal 3449.0 kg 59.85 mPt Reinforcing steel 12.0 kg 6.40 mPt Sawn timber, hardwood, planed, kiln dried 122.0 kg 26.44
mPt
Bitumen sealing V60 14.0 kg 6.77 mPt
Galvanized steel sheet 130.0 kg 25.16
Transport Transport, transoceanic freight ship 982.64 tkm Steel 5.57
mPt
Transport, lorry 3.5-16t 4.26 tkm Steel 0.43 mPt Transport, lorry 3.5-16t 103.47 tkm Concrete 10.36 mPt
Transport, lorry 3.5-16t 3.66 tkm Sawn timber, hardwood 0.37
mPt
Transport, lorry 3.5-16t 0.42 tkm Bitumen sealing V60 0.042 mPt
199
Assessment
Contribution to Env. Impact
200
Environmental Impact
Shelter Amount Unit Amount Unit
C 11 NICARAGUA FERROCEMENT 1 Shelter Materials Concrete, normal 3449.0 kg 59.85 mPt Reinforcing steel 12.0 kg 6.40 mPt Ferro cement panels 3543.0 kg mPt
Galvanized steel sheet 130.0 kg 25.16 mPt
Transport 317.38 mPt Transport, transoceanic freight ship 982.6 tkm Reinforcing steel 5.57
mPt
Transport, lorry 3.5-16t 4.3 tkm Reinforcing steel 0.43 mPt Transport, lorry 3.5-16t 103.5 tkm Concrete 10.36 mPt
Transport, lorry 3.5-16t 3.7 tkm Timber 0.37 mPt
201
Assessment
Contribution to Env. Impact
202
Environmental Impact
Shelter Amount Unit Amount Unit
S4 HAITI STEEL 1 Shelter Materials Concrete, normal 3655.7 kg 64.70 mPt Steel, electric, un- and low-alloyed 4973.8 kg 1098.78
mPt
Reinforcing steel 22.2 kg 11.00 mPt Sawn timber, hardwood, planed, kiln dried 272.9 kg 59.15
mPt
Plywood, outdoor use 159.7 kg 117.39 mPt
Packaging film 8.6 kg 9.45 mPt
Transport Transport, transoceanic freight ship 12434.5 tkm Steel 70.46
mPt
Transport, transoceanic freight ship 55.5 tkm Reinforcing steel 0.31
mPt
Transport, transoceanic freight ship 682.2 tkm Timber 3.87
mPt
Transport, transoceanic freight ship 399.3 tkm Plywood 2.26
mPt
Transport, lorry 3.5-16t 767.7 tkm Concrete 76.84 mPt Transport, lorry 3.5-16t 1044.5 tkm Steel 104.54 mPt Transport, lorry 3.5-16t 4.7 tkm Reinforcing steel 0.47 mPt Transport, lorry 3.5-16t 57.3 tkm Timber 5.74 mPt Transport, lorry 3.5-16t 33.5 tkm Plywood 3.35 mPt
Transport, lorry 3.5-16t 1.8 tkm Packing film 0.18 mPt
203
Assessment
Contribution to Env. Impact
204
Environmental Impact
Shelter Amount Unit Amount Unit
S5 INDONESIA STEEL 1 Shelter Materials Steel, electric, un- and low-alloyed 60.3 kg 13.32
mPt
Steel, electric, un- and low-alloyed 656.1 kg 144.94
mPt
Reinforcing steel 102 kg 54.38 mPt Sawn timber, softwood, planed, kiln dried 956.8 kg 174.70
mPt
Galvanized steel sheet 159.9 kg 30.94 mPt
Concrete, normal 856.8 kg 15.67 mPt
Transport
Transport, lorry 3.5-16t 6 tkm Steel 0.60 mPt Transport, lorry 3.5-16t 65.6 tkm Steel 6.57 mPt Transport, lorry 3.5-16t 10.2 tkm Reinforcing steel 1.02 mPt Transport, lorry 3.5-16t 382.7 tkm Timber 38.30 mPt Transport, lorry 3.5-16t 16 tkm Galvanized steel sheet 1.60 mPt Transport, lorry 3.5-16t 265.6 tkm Concrete 26.58 mPt Transport, transoceanic freight ship 204 tkm Steel 1.16
mPt
Transport, transoceanic freight ship 2220.2 tkm Steel 12.58
mPt
Transport, transoceanic freight ship 345.2 tkm Reinforcing steel 1.96
mPt
Transport, transoceanic freight ship 291.8 tkm Galvanized steel sheet 1.65
mPt
205
Assessment
Contribution to Env. Impact
206
Environmental Impact
Shelter Amount Unit Amount Unit
S10 VIETNAM STEEL 1 Shelter Materials Steel, electric, un- and low-alloyed 7776.9 kg 1.72
mPt
Plywood, outdoor use 74.3 kg 0.06 mPt Galvanized steel sheet 164.3 kg 0.03 mPt Concrete, normal 7197.1 kg 0.13 mPt Sawn timber, hardwood, planed, kiln dried 2.0 kg 0.00044
mPt
Transport Transport, transoceanic freight ship 14192.9 tkm Steel 0.08
mPt
Transport, transoceanic freight ship 148.5 tkm Plywood 0.00
mPt
Transport, transoceanic freight ship 296.7 tkm Galvanized steel 0.00
mPt
Transport, lorry 3.5-16t 2333.1 tkm Steel 0.23 mPt Transport, lorry 3.5-16t 22.3 tkm Plywood 0.0022 mPt Transport, lorry 3.5-16t 49.3 tkm Galvanized steel 0.0049 mPt Transport, lorry 3.5-16t 2950.8 tkm Concrete 0.29534993 mPt
Transport, lorry 3.5-16t 1.4 tkm Timber 0.00014013 mPt
207
Assessment
Contribution to Env. Impact
208
Environmental Impact
Shelter Amount Unit Amount Unit
W3 BURKINA FASO TIMBER 1 Shelter Materials Concrete, normal 6578.6 kg 117.18 mPt Sawn timber, softwood, planed, kiln dried 139.7 kg 24.60
mPt
Packaging film, LDPE 99.5 kg 110.70 mPt
Transport
Transport, lorry 3.5-16t 197.4 tkm Concrete 19.75 mPt Transport, lorry 3.5-16t 4.2 tkm Sawn timber 0.42 mPt Transport, lorry 3.5-16t 19.9 tkm Packaging film 1.99 mPt
209
Assessment
Contribution to Env. Impact
210
Environmental Impact
Shelter Amount Unit Amount Unit
W4(A) HAITI WOOD 1 Shelter Materials Concrete, normal 6136.12 kg 108.60 mPt Sawn timber, softwood, planed, kiln dried 629.4 kg 109.86
mPt
Plywood, outdoor use 161.57 kg 117.48 mPt
Galvanized steel sheet 183.1 kg 35.43 mPt
Transport Transport, transoceanic freight ship/OCE U 3138.85 tkm Galvanized steel 17.79
mPt
Transport, transoceanic freight ship 9978.87 tkm Concrete 6.14
mPt
Transport, transoceanic freight ship 1023.56 tkm Timber 0.63
mPt
Transport, transoceanic freight ship 262.753 tkm Plywood 0.16
mPt
Transport, lorry 3.5-16t 61.3612 tkm Concrete 56.55 mPt Transport, lorry 3.5-16t 6.294 tkm Timber 5.80 mPt Transport, lorry 3.5-16t 1.6157 tkm Plywood 1.49 mPt
Transport, lorry 3.5-16t 1.831 tkm Galvanized steel 0.18 mPt
211
Assessment
Contribution to Env. Impact
212
Environmental Impact
Shelter Amount Unit Amount Unit
W4(B) HAITI WOOD 1 Shelter Materials Concrete, normal 1399.4 kg 24.77 mPt Sawn timber, softwood, planed, kiln dried 836.8 kg 146.07
mPt
Plywood, outdoor use 576.6 kg 419.24 mPt
Galvanized steel sheet 135.6 kg 26.24 mPt
Transport Transport, transoceanic freight ship 2324.6 tkm Galvanized steel 13.17
mPt
Transport, transoceanic freight ship 2275.8 tkm Concrete 0.14
mPt
Transport, transoceanic freight ship 1360.8 tkm Timber 1.40
mPt
Transport, transoceanic freight ship 937.7 tkm Plywood 0.84
mPt
Transport, lorry 3.5-16t 1.4 tkm Galvanized steel 0.58 mPt Transport, lorry 3.5-16t 14.0 tkm Concrete 12.90 mPt Transport, lorry 3.5-16t 8.4 tkm Timber 7.71 mPt
Transport, lorry 3.5-16t 5.8 tkm Plywood 5.31 mPt
213
Assessment
Contribution to Env. Impact
214
Environmental Impact
Shelter Amount Unit Amount Unit
W4(C) HAITI WOOD 1 Shelter Materials Concrete, normal 5355 kg 94.77 mPt Sawn timber, softwood, planed, kiln dried 950.67 kg 165.94
mPt
Plywood, outdoor use 61.78 kg 44.92 mPt Fibre cement corrugated slab 376.2 kg 75.40
mPt
Transport Transport, transoceanic freight ship 8707.23 tkm Concrete 5.36
mPt
Transport, transoceanic freight ship 1546.33 tkm Timber 0.95
mPt
Transport, transoceanic freight ship 100.812 tkm Plywood 0.06
mPt
Transport, transoceanic freight ship 611.376 tkm Fibre cement slab 0.38
mPt
Transport, lorry 3.5-16t 53.55 tkm Concrete 49.34 mPt Transport, lorry 3.5-16t 9.51 tkm Timber 8.76 mPt Transport, lorry 3.5-16t 0.62 tkm Plywood 0.57 mPt
Transport, lorry 3.5-16t 3.76 tkm Fibre cement slab 3.46 mPt
215
Assessment
Contribution to Env. Impact
216
Environmental Impact
Shelter Amount Unit Amount Unit
W5 INDONESIA TIMBER 1 Shelter Materials Sawn timber, softwood, planed, kiln dried 324.1 kg 59.18
mPt
Concrete, normal 1066.2 kg 19.51 mPt Palm leaves 124.8 kg 38.03 mPt Packaging film 3.4 kg 3.94 mPt Chromium steel 18/8 3.9 kg 10.73 mPt
Bamboo mats 7.1 kg 0.00019 mPt
Transport Transport, transoceanic freight ship 24.5 tkm Chromium Steel 0.14
mPt
Transport, lorry 3.5-16t 230.1 tkm Timber 23.03 mPt Transport, lorry 3.5-16t 319.9 tkm Concrete 32.02 mPt Transport, lorry 3.5-16t 12.5 tkm Palm leaves 1.25 mPt Transport, lorry 3.5-16t 1.0 tkm Packing film 0.10 mPt Transport, lorry 3.5-16t 1.6 tkm Chromium Steel 0.16 mPt
Transport, lorry 3.5-16t 0.7 tkm Bambo mats 0.07 mPt
217
Assessment
Contribution to Env. Impact
218
Environmental Impact
Shelter Amount Unit Amount Unit
W6 PAKISTAN TIMBER 1 Shelter Materials Packaging film 139.0 kg 149.66 mPt Light clay brick 7980.0 kg 281.60 mPt Natural stone plate, cut 11.0 kg 2.04 mPt Polystyrene foam slab 81.0 kg 66.73 mPt Steel, electric, un- and low-alloyed 190.0 kg 41.97
mPt
Sawn timber, softwood, planed, kiln dried 215.6 kg 37.12
mPt
Transport Transport, transoceanic freight ship 791.6 tkm Foam 1.39
mPt
Transport, transoceanic freight ship 1856.9 tkm Steel 79.87
mPt
Transport, lorry 3.5-16t 13.9 tkm Packing film 0.11 mPt Transport, lorry 3.5-16t 798.0 tkm Bricks 0.81 mPt Transport, lorry 3.5-16t 1.1 tkm Stone 1.90 mPt Transport, lorry 3.5-16t 8.1 tkm Foam 15.32 mPt Transport, lorry 3.5-16t 19.0 tkm Steel 4.49 mPt
Transport, lorry 3.5-16t 153.1 tkm Timber 10.52 mPt
219
Assessment
Contribution to Env. Impact
220
Environmental Impact
Shelter Amount Unit Amount Unit
W7(A) PERU TIMBER PERU 1 Shelter Materials Fibre cement corrugated slab 306.0 kg 62.50
mPt
Concrete, normal 4284.0 kg 76.15 mPt Packaging film 0.0 kg 0.01 mPt Reinforcing steel 65.0 kg 32.22 mPt Sawn timber, softwood, planed, kiln dried 1643.1 kg 288.53
mPt
Chromium steel 18/8 28.1 kg 75.69 mPt
Transport Transport, transoceanic freight ship 333.0 tkm Steel 1.89
mPt
Transport, transoceanic freight ship 144.2 tkm Chromium Steel 0.82
mPt
Transport, lorry 3.5-16t 30.6 tkm Fibre cement slab 3.06 mPt Transport, lorry 3.5-16t 428.4 tkm Concrete 42.88 mPt Transport, lorry 3.5-16t 0.0 tkm Packing film 0.0001111 mPt Transport, lorry 3.5-16t 6.5 tkm Reinforcing steel 0.65 mPt Transport, lorry 3.5-16t 164.3 tkm Timber 16.45 mPt
Transport, lorry 3.5-16t 2.8 tkm Chromium Steel 0.28 mPt
221
Assessment
Contribution to Env. Impact
222
Environmental Impact
Shelter Amount Unit Amount Unit
W7(B)PERU TIMBER 1 Shelter Materials Concrete, normal 4284.0 kg 76.15 mPt Packaging film, LDPE 50.0 kg 55.42 mPt bamboo mats 29.0 kg 0.0008 mPt Steel, electric, un- and low-alloyed 50.0 kg 11.05
mPt
Sawn timber, hardwood, planed, kiln dried 101.0 kg 21.89
mPt
Chromium steel 18/8 28.1 kg 75.69 mPt
Transport Transport, transoceanic freight ship 258.1 tkm Steel 42.84
mPt
Transport, transoceanic freight ship 515.2 tkm Chromium steel 2.05
mPt
Transport, lorry 3.5-16t 428.0 tkm Concrete 0.87 mPt Transport, lorry 3.5-16t 20.5 tkm Packing film 1.87 mPt Transport, lorry 3.5-16t 8.7 tkm Bamboo Mat 7.15 mPt Transport, lorry 3.5-16t 18.6 tkm Steel 1.46 mPt Transport, lorry 3.5-16t 71.4 tkm Timber 1.01 mPt
Transport, lorry 3.5-16t 10.1 tkm Chromium steel 2.92 mPt
223
Assessment
Contribution to Env. Impact
224
Environmental Impact
Shelter Amount Unit Amount Unit
W8 PHILIPPINES WOOD 1 Shelter Materials Concrete, normal 1373.6 kg 24.09 mPt Sawn timber, softwood, planed, kiln dried 339.7 kg 60.48
mPt
flattened bamboo 32.0 kg 0.14 mPt bamboo mats, gen 314.0 kg 0.01 mPt Plywood, indoor use 241.4 kg 161.58 mPt Reinforcing steel 51.0 kg 27.19 mPt
Galvanized steel sheet 124.0 kg 23.99 mPt
Transport Transport, transoceanic freight ship 364.0 tkm Reinforcing steel 2.06
mPt
Transport, lorry 3.5-16t 174.5 tkm Concrete 17.47 mPt Transport, lorry 3.5-16t 43.1 tkm Timber 4.32 mPt Transport, lorry 3.5-16t 4.1 tkm Flattened bamboo 0.41 mPt Transport, lorry 3.5-16t 39.9 tkm Bamboo mats 3.99 mPt Transport, lorry 3.5-16t 30.6 tkm Plywood 3.06 mPt
Transport, lorry 3.5-16t 22.2 tkm Reinforcing steel 2.22 mPt
225
Assessment
Contribution to Env. Impact
226
C.7. References 1. IFRC, Transitional shelters – eight designs. 2011, International Federation of Red Cross and Red
Crescent Societies: Geneva, Swtizerland. 2. IFRC, Post-disaster shelter: ten designs. 2013, International Federation of Red Cross and Red
Crescent Societies: Geneva, Swtizerland. 3. Balzarini, A., Environmental impact of brick production outside Europe, in Department of Civil,
Environmental and Geomatic Engineering. 2013, Swiss Federal Institute of Technology ETH Zürich: Zürich.
4. Zea Escamilla, E., G. Habert, and L. Lopez Muñoz, Optimization of bamboo based post disaster housing units for tropical and subtropical regions through the use of Life Cycle Assessment methodologies. 2014, Swiss Federal Institute of Technology ETH Zürich: Zürich.
5. Zea Escamilla, E. and G. Habert, Global or local construction materials for post-disaster reconstruction? Sustainability assessment of twenty post-disaster shelter designs. building and Environment, 2015.
6. Zea Escamilla, E. and G. Habert, Environmental Impacts of Bamboo-based Construction Materials Representing Global Production Diversity. Journal of Cleaner Production, 2014.
7. Zea Escamilla, E., G. Habert, and L.F. Lopez Muñoz, Environmental Savings Potential from the Use of Bahareque (Mortar Cement Plastered Bamboo) in Switzerland. Key Engineering Materials, 2014. 600: p. 21-33.
227
D. Technical performance assessment 20 shelters
Table D 1 Technical performance results --20 Shelters
Shelter location - Material
Perf. Earthquake
Perf. Wind
Perf. Flood
Technical performance
B1 Afghanistan Bamboo 6 5 2 13.0
B5 Indonesia Bamboo 4 2 4 10.0
B8 Philippines Bamboo 6 6 5 17.0
C2 Bangladesh Steel 6 4 6 16.0
C6 Pakistan Steel 5 4 6 15.0
C8 Philippines Wood(2) 5 4 3 12.0
C9 Sri Lanka Timber 5 3 6 14.0
C11 Nicaragua Ferrocement 5 5 4 14.0
S4 Haiti Steel 4 5 6 15.0
S5 Indonesia Steel 4 2 6 12.0
S10 Vietnam Steel 2 3 6 11.0
W3 Burkina Faso Timber 4 4 4 12.0
W4(A) Haiti Wood(3) 6 5 6 17.0
W4(B) Haiti Wood(4) 6 5 6 17.0
W4(C) Haiti Wood(5) 5 5 6 16.0
W5 Indonesia Timber 4 4 6 14.0
W6 Pakistan Timber 4 2 4 10.0
W7(A) Peru Timber 4 3 3 10.0
W7(B) Peru Timber 4 3 3 10.0
W8 Philippines Wood 6 5 4 15.0
top related