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The Confluence of Life Cycle Assessment and Service Life Prediction

Permanent Link: http://ufdc.ufl.edu/UFE0042125/00001

Material Information

Title: The Confluence of Life Cycle Assessment and Service Life Prediction An Analysis of the Environmental Impact of Material Longevity in the Building Envelope
Physical Description: 1 online resource (231 p.)
Language: english
Creator: Grant, Aneurin
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: assessment, building, cycle, environmental, impact, life, materials, predicition, service
Design, Construction, and Planning -- Dissertations, Academic -- UF
Genre: Design, Construction, and Planning Doctorate thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This work examines the relationship between building material longevity, maintenance and life cycle environmental impact. Models for material and system maintenance and replacement over the life of a building have not been widely used in building life cycle assessment studies. This work has developed service life models for buildings that feature life cycle impact assessment metrics. The results of such building life cycle assessment analyses are anticipated to produce variation in accordance with the different service life intervals, and cumulative maintenance activities over time. A total of thirty-six roof and wall combinations have been modeled, using five alternative service life models. The results have been characterized with respect to Global Warming Potential, Atmospheric Ecotoxicity and Atmospheric Acidification as defined by the Tool for Reduction and Assessment of Chemical and other Environmental Impacts (TRACI).
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Aneurin Grant.
Thesis: Thesis (Ph.D.)--University of Florida, 2010.
Local: Adviser: Kibert, Charles J.
Local: Co-adviser: Ries, Robert J.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042125:00001

Permanent Link: http://ufdc.ufl.edu/UFE0042125/00001

Material Information

Title: The Confluence of Life Cycle Assessment and Service Life Prediction An Analysis of the Environmental Impact of Material Longevity in the Building Envelope
Physical Description: 1 online resource (231 p.)
Language: english
Creator: Grant, Aneurin
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: assessment, building, cycle, environmental, impact, life, materials, predicition, service
Design, Construction, and Planning -- Dissertations, Academic -- UF
Genre: Design, Construction, and Planning Doctorate thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This work examines the relationship between building material longevity, maintenance and life cycle environmental impact. Models for material and system maintenance and replacement over the life of a building have not been widely used in building life cycle assessment studies. This work has developed service life models for buildings that feature life cycle impact assessment metrics. The results of such building life cycle assessment analyses are anticipated to produce variation in accordance with the different service life intervals, and cumulative maintenance activities over time. A total of thirty-six roof and wall combinations have been modeled, using five alternative service life models. The results have been characterized with respect to Global Warming Potential, Atmospheric Ecotoxicity and Atmospheric Acidification as defined by the Tool for Reduction and Assessment of Chemical and other Environmental Impacts (TRACI).
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Aneurin Grant.
Thesis: Thesis (Ph.D.)--University of Florida, 2010.
Local: Adviser: Kibert, Charles J.
Local: Co-adviser: Ries, Robert J.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042125:00001


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THE CONFLUENCE OF LIFE CYCLE ASSESSMENT AND SERVICE LIFE
PREDICTION: AN ANALYSIS OF THE ENVIRONMENTAL IMPACT OF MATERIAL
LONGEVITY IN THE BUILDING ENVELOPE















By

ANEURIN THOMAS JAMES GRANT


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2010

































2010 Aneurin Thomas James Grant

































To my father, Brian Eric James Grant, who passed away unexpectedly on October 29,
2007-We all miss you









ACKNOWLEDGMENTS

I am extremely grateful for the time, effort and support of my advisors, friends and

family over the last five years. I would like to recognize Dr. Charles Kibert, who

introduced me to "green" building several years ago, and facilitated my admission to the

Ph. D. program as my main advisor. Dr. Kibert has empowered me, and given me the

rarest of opportunities. I will always be grateful for this. He has always provided support,

encouragement and inspiration. I would like to thank Dr. Robert Ries whom I met half

way through this journey. I am especially grateful to Dr. Ries for his persistence. During

a two-year hiatus, Dr. Ries kept in touch with me, provided crucial guidance, and never

let go. I dare say this document would remain incomplete without him. His investment in

this work was complete, and for me this created a personal obligation of sorts. I am

thankful to Dr. Abdol Chini, who has always been supportive of my research and career.

Dr. Chini has given me fair and realistic advice throughout my time at the University of

Florida. I am glad to have had him as an advisor and friend throughout this process. I

am sincerely grateful to Dr. Mang Tia. He has participated fully in the formation of this

dissertation, been extremely flexible and given valuable feedback during committee

meetings. I will always be thankful for his service.

I am grateful for all those who collaborated with this research process by providing

guidance, direction, or leads of any kind toward it conclusion. I am especially grateful to

those who have laid the scientific foundation for this work. I look forward to participating

in the discourse more in the future.

I am thankful to my older sister, who has always been supportive of everything I

do. Due to distance, her support does not always manifest in physical form, but moral









support is just as good as anything. My sister understands me in a way that few people

ever will. She has always been a constant upon which I know I can rely. I love her.

I would like to thank my mother who has been steadfast throughout my first thirty-

five years, and hopefully well beyond. She has adapted to her new role as dual-parent

quite well. I am always grateful for her guidance, love and support because it is

unconditional. I love her too.

I would like to thank Claudia, Olivia and Roque, who tolerate me every day. I am

not always the best I can be, but I certainly try. In many ways, the production of this

work is as much about you as it is about me. There is an added purpose to this work

that is not possible without your love, support and daily brilliance.

Finally, I would like to thank those who have contributed to this work indirectly. It is

not practical to list all of you by name of course, but I have certainly not come to this

point in my life alone. I have always been well-accompanied and have benefitted from

the many and diverse friendships that have formed my existence. Thank you.









TABLE OF CONTENTS

page

ACKNOW LEDGM ENTS ............. ........ .. ................... ......................................... 4

LIS T O F F IG U R E S .................................................................. 8

A BSTRA CT ..................................................................................................... 15

CHAPTER

1 INTRODUCTION ............... .......... .......... ......... 16

Statement of the Problem .......... ................................ 16
H y p o th e s is ................ ................ .............................................................. 1 7
Objective and Contribution........................ ....... ........ ......... 17

2 LITERATURE REVIEW ................ ................... ......... 19

A Tale of Two Methods ........... .......... .......... ...................... 21
Time as a Context.................................... ......... 23
The Durability and Service Life Argument............................................... 27
Survival and Metabolism ................... ............................ 33
Service Life Prediction ..................... .......... ........ ............... 41
The Factor Method ................... ............................ 44
Probabilistic Methods ............................. ............................... 51
Empirical Data and Reliability Models .......................................... ...... 54
Hybrids and the State of the Art ................ .. ............... ................ ......... 55
Life Cycle Assessment .................... ......... ........... ....... 56
Life Cycle Assessment in Buildings The Functional Unit ............................. 58
Life Cycle Assessment by Life Cycle Stage ............................................. 64
The Confluence of Service Life Prediction and Life Cycle Assessment ............... 67
V a ria b ility .......... .. .......... .. .......... .. .................... .................................... 7 1

3 M ETHO DO LOGY .............. ................................................................................ 75

Energy Modeling ................. .................................. ............. ... ....... 76
Life Cycle A ssessm ent ......................... ......... ......... .. .............................. 79
Service Life Models .............. .. ......... ... .. .........................81

4 R E S U L T S .......... .............. ................. ..................................................... 9 4

Life Cycle Impact Models with Energy Differentials .......................... ............. 94
G global W arm ing Potential................................... ................ ............... 94
A tm ospheric Ecotoxicity .............................. ....................... ................ 95
A tm osphe ric A cid ificatio n .............................. ......... ................ ............... 95
Life Cycle Impact Models Energy Neutral ........................... ................. ... 96


6









G lobal W arm ing Potential............................................... .................... 96
Atmospheric Ecotoxicity .............................................................................. 97
Atmospheric Acidification ...................... ....................... 98
Life Cycle Im pact Models Coarse Models.................................. .................... 99
G lobal W arm ing Potential............................................... .................... 99
Atmospheric Ecotoxicity .............................................................................. 99
A tm ospheric A cidification .............. ........... ... ........................ .................. 100
Averages of Cumulative Life Cycle Impacts Models.................................... 100
Cumulative Life Cycle Impact Envelope Combinations.............................. 101
Life Cycle Impact Per Year Individual Materials.............................. 103
Global W arm ing Potential.............................. ............... 104
A tm ospheric Ecotoxicity ....................................................... ..... ......... 105
Atm ospheric Acidification ................................ ................. ........ ....... 105
Maintenance Versus Coarse Models ..................................... ......... ........... 106

5 DISCUSSION, CONCLUSION, THE FUTURE .............................. ............... 174

C conclusions ........... ........... ................................................. ....... 175
The Future ......... ........... .......................................................... ........ 176

APPENDIX

A MATERIAL QUANTITY TAKE-OFF .............. ................ .................................. 179

B USACE MODEL SERVICE LIFE AND MAINTENANCE INTERVAL IMPACTS.... 183

C ATHENA MODEL SERVICE LIFE AND MAINTENANCE INTERVAL IMPACTS. 193

D DELL'ISOLA MODEL SERVICE LIFE AND MAINTENANCE INTERVAL
IM PACTS ................. .. ....... ..... .............. ..................... 201

E RS MEANS MODEL SERVICE LIFE AND MAINTENANCE INTERVAL
IM P A C T S .......................... ................. ....................................... 2 0 9

LIST OF REFERENCES ............................... ...................... 219

BIOGRAPHICAL SKETCH .......................................... 231









LIST OF FIGURES


Figure page

3-1 Building Envelope Combination Used in Energy Modeling Analysis................. 77

3-2 Wall Modifications Required to Equalize Thermal Performance of Walls .......... 78

3-3 Roof Modifications Required to Equalize Thermal Performance of Walls......... 79

3-5 Athena Service Life Model Activity Description and Frequency........................ 86

3-7 RS Means Service Life Model Activity Description and Frequency .................. 90

3-7 C continued ......... .. ....... ............................................................. 91

3-8 50 Year Static Service Life Model Activity Description and Frequency.............. 92

4-1 Energy Consumption of Building Envelope Combinations............................... 107

4-2 Global Warming Potential USACE Energy Differential.............................. 108

4-3 Global Warming Potential- Athena Energy Differential............................. 108

4-4 Global Warming Potential Dell'lsola and Kirk Energy Differential............ 109

4-5 Global Warming Potential Dell'lsola and Kirk Energy Differential............ 109

4-6 Global Warming Potential- 50-Year Static Energy Differential .......... ...... 110

4-7 Atmospheric Ecotoxicity USACE Energy Differential.............................. 110

4-8 Atmospheric Ecotoxicity- Athena Energy Differential.............................. 111

4-9 Atmospheric Ecotoxicity- Dell'Isola and Kirk Energy Differential................... 111

4-10 Atmospheric Ecotoxicity Dell'lsola and Kirk Energy Differential................. 112

4-11 Atmospheric Ecotoxicity 50-Year Static Energy Differential ................... 112

4-12 Atmospheric Acidification USACE Energy Differential............................. 113

4-13 Atmospheric Acidification- Athena Energy Differential................ ............... 113

4-14 Atmospheric Acidification- Dell'lsola and Kirk Energy Differential.............. 114

4-15 Atmospheric Acidification Dell'Isola and Kirk Energy Differential................ 114

4-16 Atmospheric Acidification 50-Year Static Energy Differential................... 115









4-17 Global Warming Potential USAGE Energy Neutral................................. 115

4-18 Global warming Potential Athena Energy Neutral.................................... 116

4-19 Global Warming Potential Dell'lsola and Kirk- Energy Neutral.................... 116

4-20 Global Warming Potential RS Means Energy Neutral .............................. 117

4-21 Global Warming Potential 50-Year Static Energy Neutral ..................... 117

4-22 Atmospheric Ecotoxicity USAGE Energy Neutral .............................. 118

4-23 Atmospheric Ecotoxicity Athena Energy Neutral ................... ............... 118

4-24 Atmospheric Ecotoxicity Dell'lsola and Kirk- Energy Neutral..................... 119

4-25 Atmospheric Ecotoxicity RS Means Energy Neutral.............. ........... 119

4-26 Atmospheric Ecotoxicity 50-Year Static Energy Neutral........................... 120

4-27 Atmospheric Acidification USAGE Energy Neutral ............................... 120

4-28 Atmospheric Acidification Athena Energy Neutral ................. ............... 121

4-29 Atmospheric Acidification Dell'lsola and Kirk- Energy Neutral .......... ...... 121

4-30 Atmospheric Acidification RS Means Energy Neutral............................. 122

4-31 Atmospheric Acidification 50-Year Static Energy Neutral........................ 122

4-32 Global Warming Potential USAGE Coarse Model ................................... 123

4-33 Global Warming Potential Athena Coarse Model ............................. 123

4-34 Global Warming Potential Dell'lsola and Kirk Coarse Model .......... ...... 124

4-35 Global Warming Potential RS Means Coarse Model.............................. 124

4-36 Atmospheric Ecotoxicity USAGE Coarse Model................................... 125

4-37 Atmospheric Ecotoxicity Athena Coarse Model ............... .. ........... .... 125

4-38 Atmospheric Ecotoxicity Dell'lsola and Kirk Coarse Model....................... 126

4-39 Atmospheric Ecotoxicity RS Means Coarse Model.................................. 126

4-40 Atmospheric Acidification USAGE Coarse Model.............................. 127

4-41 Atmospheric Acidification Athena Coarse Model................................ 127









4-42 Atmospheric Acidification Dell'lsola and Kirk Coarse Model..................... 128

4-43 Atmospheric Acidification- RS Means Coarse Model.................................. 128

4-44 Global Warming Potential All Models Energy Neutral.............................. 129

4-45 Atmospheric Ecotoxicity All Models Energy Neutral .............. ........... 129

4-46 Atmospheric Acidification All Models Energy Neutral .............. .......... 130

4-47 Global Warming Potential Aluminum with Green Roof Energy Neutral ...... 130

4-48 Global Warming Potential Aluminum with TPO Roof Energy Neutral......... 131

4-50 Global Warming Potential Brick with Green Roof Energy Neutral .......... 132

4-52 Global Warming Potential Brick with Built-Up Roof Energy Neutral............ 133

4-53 Global Warming Potential Wood with Green Roof Energy Neutral ............ 133

4-54 Global Warming Potential Wood with TPO Roof Energy Neutral.............. 134

4-55 Global Warming Potential Wood with Built-Up Roof Energy Neutral.......... 134

4-56 Atmospheric Ecotoxicity Aluminum with Green Roof Energy Neutral......... 135

4-57 Atmospheric Ecotoxicity- Aluminum with TPO Roof Energy Neutral............ 135

4-58 Atmospheric Ecotoxicity Aluminum with Built-Up Roof Energy Neutral...... 136

4-59 Atmospheric Ecotoxicity Brick with Green Roof Energy Neutral................ 136

4-60 Atmospheric Ecotoxicity Brick with TPO Roof Energy Neutral.................. 137

4-61 Atmospheric Ecotoxicity Brick with Built-Up Roof Energy Neutral ............. 137

4-62 Atmospheric Ecotoxicity Wood with Green Roof Energy Neutral.............. 138

4-63 Atmospheric Ecotoxicity Wood with TPO Roof Energy Neutral ............... 138

4-64 Atmospheric Ecotoxicity Wood with Built-Up Roof Energy Neutral ............ 139

4-65 Atmospheric Ecotoxicity Aluminum with Green Roof Energy Neutral......... 139

4-66 Atmospheric Ecotoxicity- Aluminum with TPO Roof Energy Neutral............ 140

4-67 Atmospheric Ecotoxicity Aluminum with Built-Up Roof Energy Neutral...... 140

4-68 Atmospheric Ecotoxicity Brick with Green Roof Energy Neutral................ 141









4-69 Atmospheric Ecotoxicity Brick with TPO Roof Energy Neutral.................. 141

4-70 Atmospheric Ecotoxicity Brick with Built-Up Roof Energy Neutral .............. 142

4-71 Atmospheric Ecotoxicity Wood with Green Roof Energy Neutral.............. 142

4-72 Atmospheric Ecotoxicity Wood with TPO Roof Energy Neutral................ 143

4-73 Atmospheric Ecotoxicity Wood with Built-Up Roof Energy Neutral......... 143

4-75 Global Warming Potential Life Cycle Impact Per Year Aluminum .............. 144

4-76 Global Warming Potential Life Cycle Impact Per Year Trendline Aluminum 144

4-77 Global Warming Potential Life Cycle Impact Per Year Brick ................... 145

4-78 Global Warming Potential Life Cycle Impact Per Year Trendline Brick ....... 145

4-79 Global Warming Potential Life Cycle Impact Per Year -Wood ................ 146

4-80 Global Warming Potential Life Cycle Impact Per Year Trendline Wood...... 146

4-81 Global Warming Potential Life Cycle Impact Per Year Green Roof............ 147

4-82 Global Warming Potential Life Cycle Impact Per Year Trendline Green
R o o f................... ................................. ....... .......... ...... 1 4 7

4-83 Global Warming Potential Life Cycle Impact Per Year TPO Roof............. 148

4-84 Global Warming Potential Life Cycle Impact Per Year Trendline TPO
R o o f................... ................................. ....... .......... ...... 1 4 8

4-85 Global Warming Potential Life Cycle Impact Per Year- Built-Up Roof......... 149

4-86 Global Warming Potential Life Cycle Impact Per Year Trendline Built-Up
R o o f................... ................................. ....... .......... ...... 1 4 9

4-87 Global Warming Potential Life Cycle Impact Per Year All Materials -
Average .................. .......... ........ ....... ........................ 150

4-88 Atmospheric Ecotoxicity Life Cycle Impact Per Year Aluminum ................ 150

4-89 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline- Aluminum .. 151

4-90 Atmospheric Ecotoxicity Life Cycle Impact Per Year Brick....................... 151

4-91 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Brick......... 152

4-92 Atmospheric Ecotoxicity Life Cycle Impact Per Year Wood...................... 152









4-93 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Wood........ 153

4-94 Atmospheric Ecotoxicity Life Cycle Impact Per Year Green Roof............. 153

4-95 Atmospheric Ecotoxicity Life Cycle Impact Per Year Green Roof............. 154

4-96 Atmospheric Ecotoxicity Life Cycle Impact Per Year TPO Roof ............... 154

4-97 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline- Green Roof 155

4-98 Atmospheric Ecotoxicity Life Cycle Impact Per Year Built-Up Roof............ 155

4-99 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Built-Up
R o o f................... ................................. ....... .......... ...... 1 5 6

4-100 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Average
A ll M materials .......... .... .... ................................ ..... ... .......... 156

4-101 Atmospheric Acidification Life Cycle Impact Per Year- Aluminum .............. 157


Atmospheric

Atmospheric

Atmospheric

Atmospheric

Atmospheric

Atmospheric

Atmospheric
Roof...........

Atmospheric

Atmospheric

Atmospheric


Acidification Life

Acidification Life

Acidification Life

Acidification Life

Acidification Life

Acidification Life

Acidification Life

Acidification Life

Acidification Life

Acidification Life
Acidification Life


Cycle Impact Per Year Trendline Aluminum 157

Cycle Impact Per Year- Brick .......... ....... 158

Cycle Impact Per Year Trendline Brick....... 158

Cycle Impact Per Year -Wood ................ 159

Cycle Impact Per Year Trendline Wood...... 159

Cycle Impact Per Year Green Roof............. 160

Cycle Impact Per Year Trendline Green
.......................................... ... ... ............ 1 6 0

Cycle Impact Per Year- TPO Roof............. 161

Cycle Impact Per Year Trendline TPO Roof 161

Cycle Impact Per Year- Built-Up Roof......... 162


4-112 Atmospheric Acidification Life Cycle Impact Per Year Trendline- Built-Up
R o o f................... ................................. ....... .......... ...... 1 6 2

4-113 Atmospheric Acidification Life Cycle Impact Per Year- Average All
M a te ria ls ............... .......................................... ........................... 1 6 3

4-114 Global Warming Potential Life Cycle Impact Per Year- Coarse Versus
Maintenance Models USACE .................. ........... .............. ............... 163


4-102

4-103

4-104

4-105

4-106

4-107

4-108


4-109

4-110

4-111









4-115 Global Warming Potential Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Athena ............... ...................... .............. 164

4-116 Global Warming Potential Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Dell'lsola and Kirk....................................................... 164

4-117 Global Warming Potential Life Cycle Impact Per Year- Coarse Versus
Maintenance Models RS Means..................... .... ................ 165

4-118 Atmospheric Ecotoxicity- Life Cycle Impact Per Year- Coarse Versus
Maintenance Models USACE .......... .. ....................... .... .............. 165

4-119 Atmospheric Ecotoxicity- Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Athena ............... ...................... .............. 166

4-120 Atmospheric Ecotoxicity- Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Dell'lsola and Kirk....................................................... 166

4-121 Atmospheric Ecotoxicity- Life Cycle Impact Per Year- Coarse Versus
Maintenance Models RS Means..................... .... ................ 167

4-122 Atmospheric Acidification Life Cycle Impact Per Year- Coarse Versus
Maintenance Models USACE .......... .. ....................... .... .............. 167

4-123 Atmospheric Acidification Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Athena ............... ...................... .............. 168

4-124 Atmospheric Acidification Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Dell'lsola and Kirk....................................................... 168

4-125 Atmospheric Acidification Life Cycle Impact Per Year- Coarse Versus
Maintenance Models RS Means..................... .... ................ 169

4-126 Envelope Combination Ranking USACE Energy Differential, Energy
Neutral and Coarse Global W arming Potential ............... ...................... 169

4-127 Envelope Combination Ranking -Athena Energy Differential, Energy
Neutral and Coarse Global W arming Potential ............... ...................... 170

4-128 Envelope Combination Ranking Dell'lsola and Kirk Energy Differential,
Energy Neutral and Coarse Global Warming Potential............................... 170

4-129 Envelope Combination Ranking RS Means Energy Differential, Energy
Neutral and Coarse Global W arming Potential ............... ...................... 170

4-130 Envelope Combination Ranking USACE Energy Differential, Energy
Neutral and Coarse Atmospheric Ecotoxicity ............................ ............... 171









4-131 Envelope Combination Ranking Athena Energy Differential, Energy
Neutral and Coarse Atmospheric Ecotoxicity.......................... ...... ............. 171

4-132 Envelope Combination Ranking Dell'lsola and Kirk Energy Differential,
Energy Neutral and Coarse Atmospheric Ecotoxicity ............................... 171

4-133 Envelope Combination Ranking RS Means Energy Differential, Energy
Neutral and Coarse Atmospheric Ecotoxicity.......................... ...... ............. 172

4-134 Envelope Combination Ranking USACE Energy Differential, Energy
Neutral and Coarse Atmospheric Acidification........................... .. 172

4-135 Envelope Combination Ranking Athena Energy Differential, Energy
Neutral and Coarse Atmospheric Acidification........................... .. 172

4-136 Envelope Combination Ranking Dell'lsola and Kirk Energy Differential,
Energy Neutral and Coarse Atmospheric Acidification .............. .......... 173

4-137 Envelope Combination Ranking RS Means Energy Differential, Energy
Neutral and Coarse Atmospheric Acidification........................... .. 173









Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

THE CONFLUENCE OF LIFE CYCLE ASSESSMENT AND SERVICE LIFE
PREDICTION: AN ANALYSIS OF THE ENVIRONMENTAL IMPACT OF MATERIAL
LONGEVITY IN THE BUILDING ENVELOPE

By

Aneurin Thomas James Grant

August 2010

Chair: Charles Kibert
Cochair: Robert Ries
Major: Design, Construction and Planning

This work examines the relationship between building material longevity,

maintenance and life cycle environmental impact. Models for material and system

maintenance and replacement over the life of a building have not been widely used in

building life cycle assessment studies. This work has developed service life models for

buildings that feature life cycle impact assessment metrics. The results of such building

life cycle assessment analyses are anticipated to produce variation in accordance with

the different service life intervals, and cumulative maintenance activities over time. A

total of thirty-six roof and wall combinations have been modeled, using five alternative

service life models. The results have been characterized with respect to Global

Warming Potential, Atmospheric Ecotoxicity and Atmospheric Acidification as defined by

the Tool for Reduction and Assessment of Chemical and other Environmental Impacts

(TRACI).









CHAPTER 1
INTRODUCTION

In the assessment of environmental impact, various forms of Life Cycle Analyses

have been developed to provide comprehensive evaluations of products, designs,

processes and materials. These analyses are intended to provide a systems-type

perspective and an inventory of mass and energy flow over the course of an entire

product life cycle. The methodological premises for Life Cycle Analyses however have

not been fully explored, nor conclusively established. Some standardization of method

has been implemented, but a fair amount of "scientific latitude" is still permitted. Within

the field of Life Cycle Analyses, it is widely believed that the proper constraint,

exploration and refinement of method will yield improvement and a better understanding

of the environmental impacts associated with human activity.

Statement of the Problem

Life Cycle Analyses have been employed at numerous scales to better understand

the metabolism of the built environment. To this end, analyses of the manufacture,

transportation, construction, operation, maintenance and end-of-life scenarios

associated with buildings and materials have achieved varying levels of success. Yet,

the analysis of environmental impact is heavily dependent on the principle of

assumption. Results will vary according to the particular method of Life Cycle Analysis,

the environmental indicators to be analyzed, practitioner interpretation, and perhaps

most importantly the scope of the study.

Issues of scope are especially important with respect to the analysis of a building.

For instance, the creation of a system boundary or a functional unit is based purely on

assumption, and is meaningful only insofar as it serves as a point of comparison









between subjective interpretations of conceptual models. In other words, the exclusion

or inclusion of a particular material or energy flow in Life Cycle Assessment may affect

the outcome of study significantly; the inputs may be derived from any number of

sources, and for buildings, the magnitude of material and energy flow is so large it can

be difficult to contain within a simple model. On another level, the scoping of building

analyses is complicated due to the prolonged service lives of buildings relative to other

systems. Differences in material durability for example suggest that buildings are

dynamic. Some components will last longer than others, and maintenance requirements

will vary according to the physical properties of the material. Intuition aside, many

practitioners approach the Life Cycle Assessment of buildings from a static viewpoint,

wherein dynamic material input and output are not considered. These assumptions

therefore lead to a certain kind of environmental outcome.

Hypothesis

If the static modeling of the life cycle of a building omits important material and

energy inputs, then the Life Cycle Impact will yield incomplete results. By contrast, a

dynamic life cycle model that includes the input, output and cycling of materials over the

building's lifetime would contain important environmental impacts and yield a more

accurate result. It is hypothesized therefore that Life Cycle Impact varies depending on

material longevity and differential durability, and that a dynamic Life Cycle Assessment

model, including service life of materials and systems is required to better represent the

environmental impact of the building life cycle and cumulative maintenance over time.

Objective and Contribution

The objective of this study is to examine the relationship between building material

longevity, maintenance and life cycle environmental impact. Dynamic models of









material and system maintenance and replacement over time have not been widely

used in building life cycle assessment studies. In comparison with static Life Cycle

Assessment models, it is believed that a dynamic study would yield a more

comprehensive result, and a more accurate representation of material and building Life

Cycle Impact.

Currently, there is no consensus as to the appropriate life cycle of a building.

Contemporary methods of Service Life Prediction are relatively inexact, and the

uniqueness of buildings prohibits any type of universal assumption. Perhaps more

fundamentally, the certainty of Life Cycle Impact projections over prolonged periods of

time is undermined by dynamic performance degradation and potential improvements in

technology. For instance, performance degradation is believed to accelerate toward the

end of service life, such that more frequent and intense maintenance is required.

Similarly, improvements in technology may lessen the impact of the manufacture,

operation and maintenance of a material or building, but this becomes more speculative

as predicted service life duration increases. As such, it is unclear as to whether

buildings should be designed and constructed to endure in relative permanence, or if

they should be designed and built as temporary structures with subsequent service

lives, adaptive reuse, deconstruction and recycling in mind.

Ultimately, the analysis contained within this document contributes to the body of

knowledge in that it demonstrates the importance of service life in the modeling of Life

Cycle Assessment in buildings. It is hoped that this study will lead toward more accurate

representations of material longevity in Life Cycle Assessment, and greater care in the

assumption of service life.









CHAPTER 2
LITERATURE REVIEW

The condition of the natural environment is changing. Human population continues

to grow amid concerns of global warming, deforestation, topsoil erosion, desertification,

water and food resource depletion, the pervasion and buildup of toxic and dangerous

substances, the thinning and perforation of the ozone layer and the irreversible loss of

biodiversity. As author Paul Hawken has stated, "every natural system on the planet is

in decline." (Hawken 1993).

The rate of population growth is particularly alarming. The human population

increased by 380,682 persons each day in 2009; an increase of 138,949,000 persons

for the year. Projections of these numbers suggest that the human population will reach

9,421,000,000 by mid-year 2050 (Population Reference Bureau 2010). At present, it is

not clear that the planet can sustain this population. Forecasts of lifestyle adjustment

range from complete collapse, austerity and darkness to the more palatable views of

technological optimism, resource conservation and modest belt-tightening. Only time

will tell which forecast is accurate. However, there is no doubt that the growth of the

human population is converging with the carrying capacity of the planet.

The debate intensifies when the rate of change is considered in conjunction with

equity, environmental justice and the allocation of natural resources. The consumption

of materials and energy, and the emission of waste is a lopsided affair. Marked

differences in the affluence and wealth of nations are often indicative of this disparity. In

contrast, environmental "externalities" are often pushed upon the disenfranchised.

Logically, issues of environmental sustainability are now discussed in combination with

those of global security.









The problem is complex; representations of environmental gloom and doom have

invoked a sense of urgency in many, yet economic and political interests are

entrenched, there are positively billions of stakeholders, and science does not fully

comprehend the issue of global sustainability, or the implications thereof. As such, any

meaningful consensus has been difficult to achieve. For instance, in the absence of "full

scientific certainty" (United Nations 1992), policy makers have relied upon the

precautionary principle in formulating environmental legislation. Legislation of this ilk

can be dubious as it is unclear whether the precautionary principle constitutes prudent

avoidance, a regulation of risk, or the implementation of laws of fear (Sunstein 2005).

Ultimately, further consensus and definition in sustainability as a whole are required.

On a qualitative level, the definition of sustainability requires the reconciliation of

dissimilar variables. Oftentimes, concessions and trade-offs are built-in to the

environmental decision making process. Comparisons are often likened to those

between apples and oranges (Piepkorn and Wilson 2005), or as in a more relevant

example, those between mercury emissions and habitat loss. For comparisons such as

these, there is no common unit of measurement. Furthermore, environmental priorities

vary from region to region. Where water conservation may be the most important

environmental concern in arid and overpopulated areas, global warming may be the

most pressing concern in low lying or island settlements.

Quantitative methods have also produced some discrepancy. Some suggest that

the human population on the planet can only be sustained by increasing present day

productivity by a factor of four (Von Weizsacker 1997) Competing viewpoints suggest

that an increase of this magnitude would be insufficient, and that present day









productivity would need to be improved by a factor of ten to be sustainable. Similarly,

models of ecological foot printing imply that an additional half planet of usable biomes

would be required to sustain current rates of global extraction and consumption (Center

for Sustainable Economy 2010). To complicate matters, the numbers are always

changing. The ecosphere is in a state of constant flux.

We are therefore confronted with an amorphous and inadequately defined problem

of gigantic proportions. Damage to the natural environment is well-documented. Yet,

there is no unification. The paradigm is fallible. We are left with speculation, potential

scenarios, an assortment of competing theories and some very compelling and

egregious anecdotal evidence. All in all, these are fragments of a much larger puzzle.

A Tale of Two Methods

The idea of testing the environmental impacts of building material longevity

requires the application of two complementary areas of research. In the assessment of

environmental impact, Life Cycle Assessment (LCA) is a commonly used and widely

accepted methodology. The results of a well-designed LCA can be very useful in

identifying or comparing the relative environmental impacts of a particular design,

material or process. The method is intended to provide a comprehensive and

informative assessment of materials flows from conception to the end of life. In the area

of Service Life Prediction, issues of material longevity, durability and context have been

clarified with the use of three principle approaches; the factor method, probabilistic

methods, and empirical reliability models. Each approach has positive and negative

attributes, and most agree that there is an appropriate application for each, depending

on the degree of accuracy required.









There are some methodological issues with both Life Cycle Assessment and

Service Life Prediction. For instance, Life Cycle Assessment has only recently been

applied to the study of buildings. The required analyses are extremely complex,

systems are comprised of thousand of components, and the magnitude of the mass and

energy flow is huge. When a building is analyzed in a temporally dynamic and

prolonged context, the complexity of the assessment becomes amplified. Consequently,

many researchers have struggled to find the appropriate "functional unit" of

measurement.

For Service Life Prediction, the main objectives are accuracy and utility.

Depending on the method that is used to predict or estimate service life, accuracy and

utility are said to vary accordingly. Empirical or reliability models are said to be the most

accurate, but the collection of data requires a substantial investment of time. Some

methods have been based on the logic of probabilistic distributions and have shown a

good range of accuracy, but require extended analysis and an expert knowledge of the

agents of degradation. In terms of utility, the factor method is preferred, although the

resultant predictions are said to be the least accurate of all the methods (Davies and

Wyatt 2004).

The semantics of service life have also been examined. Indeed, there is some

debate as to the exact definition of "functional obsolescence". Ostensibly, the definition

may vary significantly depending on the exact nature of the "function", and the design

parameter used to define the "obsolescence". For example, it has been noted that the

"reasons for the relinquishment are less a matter of material ageing and problems of

material preservation than the complex phenomenon of obsolescence." (Hassler 2009).









The American Institute of Architects has also acknowledged alternative reasons for

materials obsolescence citing a more insidious agent of deterioration, "changing styles"

(Dempkin 1996).

The inaccuracies of Service Life Prediction have a direct bearing on Life Cycle

Assessment methods. As the two are interconnected, improvements in Service Life

Prediction methodologies will only result in more accurate accounts of environmental

impact. In other words, the accurate assessment of environmental impact is dependent

on the realistic representation and assumption of time.

Time as a Context

There is a recurring theme in discussions of global sustainability and

environmental impact that is not all at once obvious to the casual observer. Allusions to

the future, predictions, estimations, forecasting and intervals pervade the literature. Of

course, the concept of time is implicit in each of these references. Reisch has argued

that time is an essential component of any would-be sustainable theory. He states that,

"currently there is no widely accepted meta-theory of sustainable consumption. In

whatever form such a theory is proposed, the time factor has to be systematically

included. (Reisch 2001). There are many reasons for including time as a context in the

analysis of environmental issues. It has been argued that implicit uncertainties make

future projections questionable, as articulated in the following:

Present investment tends to set the pattern for solving a particular problem
over many years, regardless of whether or not the problem or indeed
present knowledge about it will be equally long-lived, whether or not the
lifetime of the technical installation is appropriate for the lifetime of the basic
economic, social and ecological conditions, and whether or not the
ecological problems are classified as taking a period of exact, shorter or
longer time durations to solve (Kummerer 1996)









In reference to the economic and social conditions mentioned above, the analysis

of environmentally friendly construction becomes more challenging. Costs and building

function must also be considered. On another level, the traditional concept of a building

is typified by durability and permanence. Flexibility and adaptability have only recently

been introduced as considerations in design. This view is shared by Adam et al, who

state that "we must not lose sight of the larger temporal complexity which impresses on

us the need for caution, care and precaution for situations where actions and inactions

construct the present and delimit choices for an open number of future generations."

(Adam et al. 1997). In consideration of the relatively long service life of buildings, it

seems further consideration should be given to future scenarios, predictions and the

forecasting of adaptation and materials cycling. Many current studies and analyses

project a static snapshot, with no mention of dynamism or modification. This needs to

change. "It is not in spite of our limited perceptions of time (and of our location in time),

but rather because of it, that it is crucial to take account of time in ecological, economic

and social matters." (Kummerer 1996)

In Material Flow Analysis, the inclusion of a temporally dynamic context is

essential, and depending on a given set of scenarios, may cause wide variation in the

assessment of environmental impact. To paraphrase, Material Flow Analysis "must be

used in conjunction with other types of data, because it only illuminates some of the

issues that concern policy makers with regards to materials management." (Allen et al.

2009). So, the issue is one context.

Since considerations of material flow management or nature conservation,
for example, are centrally guided by the static thermodynamic
conceptualization of equilibrium, it is not surprising that changes over time
(of human-made material and energy flow, for example) are rarely









considered in discussions of type, degree and rate. Consequently, future
developments for the environment are largely ignored (Kummerer 1996)

In the analyses of buildings, it has also been recognized that temporal complexity

plays a significant role in determining both economic and environmental impact. There

are numerous examples of the importance of accurate Service Life Prediction

throughout the literature on Life Cycle Costing (Ashworth 1996; Rudbeck 2002; Barco

1994; Shohet and Laufer 1996; Dorris 1997; Dell'lsola and Kirk 2003). The principle

however is essentially the same; when materials are placed in the proper context of

time, a more accurate assessment of economic and environmental impact results.

In Life Cycle Assessment, it has been stated that "some basic hypotheses of the

LCA methodology, such as time stability, do not cope well with the characteristics of

buildings (Verbeeck and Hens 2010)". Ozel and Kohler give a more expansive

explanation, as follows:

In the life cycle analysis of buildings, the typical concern has to do with the
flow of energy and mass due to initial construction, remodeling and
demolition of buildings and their impact on the environment over a given
period of time. Therefore, any effort to simulate this process must also
incorporate spatial as well temporal data into its structure. Databases that
support such simulations must handle time-dependent as well as spatially
comprehensive data structures (Ozel and Kohler 2004).

In continuation of this reasoning, the authors provide the contrasting examples of

Life Cycle Energy Assessment "simulations" and static models. Herein, an assumption

based on stasis is questioned. "These models are based on the assumption that the

physical fabric of a building will remain static as the building ages, thus such simulations

do not take into account any potential changes in the physicality of the building." (Ozel

and Kohler 2004).









The point of temporal complexity and context is further supported by Elrandsson

and Borg, who argue that time-based scenarios are an essential part of long-lived

analyses.

A general impression is that it is considered that supplying marginal,
average and best-available technology LCI data satisfies the intention to
cover the time dependence of LCA studies of buildings. This can, however,
be insufficient if there is no possibility to build scenarios, which consider
technical development that can change the studied system and the context
of the studied system over time. This is especially important for long-lived
products as buildings, which can have a service life of about 100 years
(2003).

Trinius and Sjostrom have concluded that the performance of any meaningful

analysis is contingent upon the inclusion of a temporal context. Furthermore, they argue

that service life is one of the central parameters in building performance, as follows:

Consideration of sustainability aspects must relate to service life and
performance requirements, as the proper functionality and service duration
are cornerstones in the performance of a building. When comparing
different design options, performance aspects are the underlying factor.
This also means that quantification of costs or environmental impacts
without a common reference can be rather meaningless (2005).

Beyond discussions of a need for temporal context, Hovde and Moser have

concluded that Service Life Prediction can affect the results of a Life Cycle Assessment,

and must be thought of as an essential precursor to any form of life-cycle building

analysis. They state the following:

The service life of a specific part will have a great influence on the outcome
of an LCA of the complete object. Selection of alternative parts that have
different service lives or where the service life varies depending on
alternative maintenance procedures, may also have a great influence on
the overall outcome of the LCA (Hovde and Moser 2004).

The literature indicates a need for improved service life data, and the inclusion of

said data in temporally (and spatially) dynamic modeling techniques. Accurate service

life data is a "vital link in attaining sustainable and economically viable construction"









(2005). Indeed, the argument is clear; Life Cycle Assessment methodologies require a

temporal context to be meaningful.

The Durability and Service Life Argument

In the area of green building and sustainable construction, it is often opined that

buildings should be durable and long-lived. As Browning and Honour have pointed out,

"most large, complex, and expensive systems are anticipated to have a fairly long life

cycle (2008). Some have argued to the contrary, and growing bodies of research on

lean construction, adaptable architecture and deconstruction suggest a design

imperative other than permanence. A few have suggested that the only green building is

the one that is never built. Others endorse a less extreme version of this notion,

suggesting that the built environment should be geared toward more temporary

structures, prefabricated buildings or even yurts (McDonough and Braungart 2002).

Despite all of the argument and opinion, the idea of testing the environmental

impacts of building and material longevity is fairly new. In many ways therefore, it

seems premature to advocate one side or the other. As follows, a summary of the

literature on building and material durability and service life shows that the argument is

in full swing, although it is not clear how many of the claims can be substantiated.

For example, Nireki asserts that durability is an important performance factor in

buildings.

Durability is an important factor that cannot be ignored when considering
the performance of building. Moreover, the recent social requirements for
durability have become greater arising from various aspects such as the
effective use of natural resources and saving energy, improvement of
service life, effective use of existing stock in good condition as a social
investment (1996).









It is not altogether clear that durability results in energy savings or an improvement

in the existing building stock. When durability is used as a basis of comparison, one

might ascertain that differing service lives are appropriate based on a proportional

differential in environmental impact. However, the assertion requires some further

explanation.

The Canadian Green Building Council has implemented a LEED standard which

departs from the version set forth by the United States Green Building Council. One of

the most notable differences in the Canadian standard is the presence of Regional

Priority Credit 1, entitled "Durable Building". As stated in the latest version of the

Canadian standard for New Construction, achievement of the credit is dependent on the

development and implementation of a Building Durability Plan, "in accordance with the

principles in CSA S478-95 (R2007) Guideline on Durability in Buildings." The

Guideline is a Canadian Standards Association document, and provides some

suggestions on service and design life, maintenance and component replacement. The

potential technologies and strategies suggested to achieve the credit are stated as

follows:

Design strategies for building durability that will minimize premature
deterioration of the walls and roof, while harmonizing and integrating
Architectural, Mechanical, Landscape and Electrical performance
requirements, and meet the needs of the owner and contractor. Appropriate
technologies and strategies must be appropriate to the region (Canadian
Green Building Council 2009).

The wording of this green building credit is difficult to dispute. As is evident in the

literature on Service Life Prediction, regional appropriateness implies a lower degree of

maintenance. Similarly, the minimization of "premature deterioration" is ostensibly a

green building objective, although nothing is said here about design flexibility. Herein,









the concept of temporal dynamism is limited to appropriate maintenance and

replacement over time. In a similarly static manner of thinking, there is no

acknowledgment of potential scenarios built into this credit. Indeed, "premature

deterioration" is to be avoided, but that should not condemn an individual building

material to a single scenario over its lifetime. Spatial and temporal dynamism, as they

are characteristics of most buildings over their lifetimes, suggest otherwise.

Bogenstatter has taken a similar stance toward building material longevity, as follows:

An important criterion for external aspects and preservation of value is the
average useful life of buildings as well as their elements. A long-term use is
also an ecological target. The ecological value is the inverse of the sum of
impacts caused during the lifetime or over the lifetime of an element or
building. This means that properties should be used for as long as possible
to 'discount' their impact. (2000).

Taken by itself, Bogenstatter's statement is irrefutable. However, the process is

not a simple as the word "discounting" implies. Future scenarios may include advances

in technology and design retrofit options that cause the building to change. Furthermore,

extending the service life of a particular component requires more frequent and higher

quality maintenance, an aspect of materials cycling that Cooper has also overlooked, as

described in the following excerpt:

Increased product life spans, whether through greater intrinsic durability or
better care and maintenance, may enable such problems to be overcome
by providing for both efficiency and sufficiency. They are a means by which
materials are used more productively (i.e., the same quantity provides a
longer service) and throughput is slowed (i.e., products are replaced less
frequently) (2005).

While the comments above show inclination toward a particular point of view, the

author stops just short of concluding that "longer-lasting products are a prerequisite for

sustainable consumption." Rather, a suggestion is made for future research, "to









undertake life-cycle assessments of products with different life spans and publish the

findings." (Cooper 2005).

Mora argues that the extension of service life is linked and commensurate with

production impact. Mora states the following, "as far as construction is concerned, if we

were to increase the durability of concrete works from 50 to 500 years, factor 10 would

be a measure of the reduction of the environmental impact." (2007). However, the

assumption is too simplistic. A comparison of two mixes of concrete with such widely

different service lives would surely yield a different environmental impact, be made from

different proportions of Portland cement, and require different types and frequencies of

maintenance during the course of their lifetimes. Likewise, an assumption of 500 years

assumes a relatively static building function and virtually no potential scenario where

technological improvements warrant replacement or improvement. In fairness, Mora

points out that this comparison is "as far as construction is concerned, and thus an

understanding of temporal dynamism is implicit. Similar viewpoints and general

conclusions that durability is positive attribute of building performance have been

expressed by a number of other researchers (van de Flier 2009; Dorris 2007; Hassler

2009; Barco 1994)

Beyond basic durability, the discussion on service life turns toward adaptability.

There are many different forms of adaptation, including renovation, the replacement of

individual systems, facility expansion and simple upgrades. It is for reasons of

adaptability, that the modeling of building in Life Cycle Assessment is so challenging, as

alluded to in previous comments regarding scenarios. Slaughter has articulated the

adaptability argument, as follows:









The usefulness of these facilities is often compromised by their inability to
accommodate changes over time. It is not economical or resource efficient
to design and build facilities that have only a short functional life, since a
facility that prematurely reaches the end of its useful life reduces the
effective time period over which benefits could be obtained, and increases
the effective cost of demolition and waste disposal, thereby reducing the
return on the initial investment (2001).

The ideal of design for adaptability is also supported by Browning and Honour,

who state that, "designers must consider not only how to meet specifications that will

satisfy stakeholders today but also the trajectories of markets and technologies that will

determine what it takes to satisfy stakeholders in the future." (2008). Thomsen and van

der Flier have suggested that life cycle extension of any manifestation generally results

in a lower environmental impact, as described in the following:

The environmental impact of life cycle extension by renovation,
transformation and life cycle extension is, in general, less harmful than
replacement by new construction. Renovation, transformation and lifecycle
extension deserve public support. (2009).

An earnest assessment of the arguments for both simple durability and building

flexibility reveals a middle ground of sorts. It must be possible after all for a building to

be both durable and adaptable. Fishman et al. have warned that durability may lead to

technological stagnation. This is in line with the observations of Kummerer, who has

stated that future uncertainties require added precaution in current day design. Fishman

et al. explain the potential stagnation a follows:

Excess durability is associated with stagnation in two senses. First,
continuous innovation must be associated with the production of non-
durables and stagnation with the production of durables. Second, in the
intermediate range of development costs, for which both outcomes are
equilibria, stagnation results if the social convention is to produce durables,
while continuous innovation is enabled by the convention of producing non-
durables. Thus pressure from consumer groups that promote "excessive"
product durability may retard the development of new products and
technologies (1993).









The authors contend that stagnation and service life are inter-related, and indeed,

in the context of time, their argument regarding planned obsolescence is difficult to

refute, as follows. "Planned obsolescence may be a necessary condition for the

achievement of technological progress and that a pattern of rapidly deteriorating

products and fast innovation may be preferred to long-lasting products and slow

innovation (Fishman et al 1993).

An article by Horvath illustrates a more comprehensive assessment of durability

and longevity, stating that service life should be determined based on shorter life cycles

or planned maintenance. Horvath states the following:

Functional obsolescence of facilities (when they no longer serve their users
satisfactorily) dictates that they should be either designed for shorter life
spans or for continuous maintenance and periodic, complete renovations
that extend their useful life. Some facilities may be overdesigned given their
actual service life. It is commonly assumed that parts of the built
environment last for a long time. This is true for much of the infrastructure
that is perpetually maintained and periodically renovated or reconstructed
(e.g., roads, railways), but it is not necessarily true for all facilities (2004).

These comments are accurate insofar as certain types of buildings are more

conducive to long life, while others are expected to serve a particular purpose for a

shorter term. In essence, there are two sides to the debate on service life. Some feel

that buildings and their components should be durable, with extended service lives.

Others believe that extended service life may compromise our ability to make decisions

and adapt in the future. While opinions and assertions abound, the claims are largely

unsubstantiated. The idea itself therefore needs to be tested. A method needs to be

developed. A means of measuring the environmental impact of durability, service life

and material longevity needs to be implemented.









Survival and Metabolism

Examinations of material flows can be performed on individual buildings, or at a

much larger scale. In consideration of the literature on the metabolism of the built

environment and mortality models, an important contribution is noted in the form of

estimates of building stock survivability. Although these estimates make no

differentiation between building or material type, they are relevant in the sense that they

reiterate and thereby enforce the findings of other areas of service life research. In other

words, large variation in service life estimates are seen in the literature on mortality and

metabolism, a brief summary of which is as follows.

As noted by Kohler and Yang, an estimate of material flows can be accomplished

using a survival analysis. The authors state that this can be done by looking "at

building/infrastructure stocks backwards in time to find out how many objects have been

built and how many have disappeared." Using this method, Kohler and Yang were able

to determine a trend in building mortality, noting that "older age classes [of buildings]

have much higher survival probabilities and that the newer age classes will disappear

before the older ones". Yet, the conclusions of Kohler and Yang are somewhat static in

terms of temporal context, as is evident in the following excerpt.

From the analysis of the survival functions of other stocks it appears that
the Life Cycle Analysis allows to establish long-term balances of resource
consumption and environmental impacts showing that identical results can
be obtained either by reducing resource inputs and impacts or by raising
the lifetime of the functional unit (spreading the inputs/impacts over a longer
period (2007).

This conclusion promotes the slowing of metabolism, either through a reduction of

resource inputs or by extending service life, as the principle means of reducing

environmental impact. As previous discussions on the uncertainty of the future and









technological advancement have made clear, extending service life may also create

stagnation. It seems appropriate to extend the service life of the individual components

and materials, but not as part of an obsolescent system. Buildings are energy sinks, and

should be capable of technological adaptation, even if there are constructed of durable

materials.

A similar conclusion is drawn by Johnstone, who states the following:

The energy and mass flows required to sustain dwelling services are
dependent on the building materials used for housing, the durability and
economic life of building components, the mortality of the housing stock, the
proportion of surviving dwellings which undergo rehabilitation at each
successive event of rehabilitation, and the expansion rate of the housing
stock (Johnstone II 2001).

As in Kohler and Yang, Johnstone has concluded that energy and mass flows will be

diminished or slowed down through extensions of building stock service life. However,

this idea requires elaboration. The extension of the service lives of obsolete systems

may have an effect that is contrary to that desired. While the proportion of energy

associated with the mass flow of building materials may be diminished in this regard,

the flow of energy in the built environment is not uniquely driven by the production, use

and disposal of materials. Buildings require a tremendous and constant source of

energy to provide basic operation. Furthermore, innovations in technology suggest that

inflexible building designs are more likely to become obsolete with the passage of time.

Most have suggested that a combination of materials reduction, reuse and

recycling will help to slow the metabolism of the built environment. In turn,

measurements of materials throughput are a precursor to sustainable materials

management. Wernick has observed that material consumption trends in the U.S. are









decidedly hard to predict, owing the influence of technological innovation and the

inescapability of temporal context. Wernick writes the following.

Sustaining the U.S. economy requires consuming large amounts of
materials. The mix of materials changes with time, and these changes
matter from the perspective of environmental quality. The question of
whether Americans will consume more or less materials in the future
depends on demographic, economic, and technical variables difficult, if not
impossible to predict. One central question is: can increases in materials
efficiency keep pace with or even triumph over the forces driving increased
consumption? (1996).

It is widely believed that reductions in material throughput or the slowing of the

metabolism in the built environment embodies a movement toward sustainability.

Temporal context suggests a dichotomy: energy is embodied in the building materials

that comprise the built environment of course. However, energy is also required in the

operation of a building and therefore constitutes a bifurcation of the mass energy flow

as it is commonly understood. Thus, the solution to this problem is not as simple as

using less material. Reductions in material cycling must be measured in concert with

energy efficiency goals and the consumption of energy resources as they might be

utilized in the operations phase of a building.

Brattebo et al. have alluded to the dichotomy in the mass and energy flow of the

built environment, and is so doing, reinforced the idea of dynamism. If the main

objective of metabolic analysis is to move toward the sustainable consumption of

materials and energy, Brattebo et al. suggest that a greater understanding of change

over time is necessary.

These challenges, and the analytical approaches to meet them, will
probably be fairly similar for a different type of the built environment stocks.
Common to all such stocks are their long lifetimes, high material
consumption, high life cycle energy consumption, ageing phenomena, and
the fact that their overall role in society's sustainability performance is still
barely documented and not well understood. (2009)









Another article by Johnstone suggests dynamism and wide variation in housing

stock mortality. More importantly, Johnstone has indicated that building stock

survivability is often longer than a standard 50-year analysis would portend, and

dependent on many factors (2001). The application of these ideas in the standard Life

Cycle Assessment of buildings would be transformative. It suggests that an analysis

requires context, assessments of differential durability and detailed information about

the agents of degradation, especially so in the case of building analysis.

Additional work on stock mortality and survivability has been contributed by

several authors (Bradley and Kohler 2007; Bergsdal et al 2007; Bergsdal et al II 2007).

Bergsdal et al have noted that "information about the lifetime of dwellings is very scarce,

and there is no consensus in the literature on what distribution best reflects the actual

dwelling lifetime." (2007). Similarly, an analysis of the literature on Life Cycle

Assessment has revealed wide variation in materials durability data. Evidently, it has

become necessary to investigate the available data on service life more thoroughly, and

to apply these data through temporally dynamic life-cycle models.

Differential Durability

The concept of differential durability in building materials seems fairly

straightforward. Implicit differences in building material composition and decomposition

suggest that some materials last longer than others. The concept of differential

durability has been well illustrated by Kesik and Saleff, as exemplified in the following

passage.

A practical example of interdependent durability is the case of bricks and
brick ties, where the former often deliver a longer service life than the latter.
When the inferior durability component reaches the end of its useful service
life, the superior durability component is often replaced at the same time,









resulting in an underutilization of its durability. The lesser the degree of
durability harmonization, and the greater the degree of difference in initial
service quality between components, the greater the underutilized or
wasted durability (embodied energy) of the assembly. This underutilization
has a direct impact on the recurring embodied energy demand over the
building life cycle (2005).

Despite the authors' recognition of differential durability, or perhaps more accurately,

underutilized of wasted durability, the concepts are brought up as a preamble to a

discussion on structural longevity. As discussed previously, extended service life is of

questionable value if the system itself is obsolete. While the cycling of building

envelopes on a static and seemingly permanent structure connotes a limited flexibility of

sorts, structural adaptation and building function modification are not mentioned at all.

While this might be noted as a potential flaw in the authors' reasoning, it is not their

main point. Rather, Kesik and Saleff are referring to a sort of ancillary durability,

whereby the expiration of one material leads to the ancillary expiration of another. It is a

fairly straightforward point, further articulated in the following paragraph.

Differential durability is normally not desired within building envelope
components and assemblies, where it should ideally be harmonized, but it
can form part of a staged building sustainability strategy between systems.
Selection of an extremely durable structural system (armature) can
accommodate a succession of building envelope assemblies (skins)
provided their components exhibit harmonized durability and are designed
for obsolescence (i.e., ease of replacement) (2005).

Dimoudi and Tompa have also characterized differential durability as major concern in

the assessment of the environmental impact of buildings. Again, the authors recognize

the compatibility of adjacent components and materials, as follows:

As far as construction practices are concerned, additional criteria should be
considered like the lifetime of building materials, the compatibility of the
lifetime among the layers' building materials, the kind of assembly of
different materials and of the different layers, their maintenance needs over
the building life cycle (2008).









In the comparison of a single system, the concept of differential durability serves

an important role in the planning and design of buildings as they will be "designed for

obsolescence." (Kesik and Saleff 2005). In turn, the recognition of differential durability

prompts an immediate need for the comparison of distinct building materials and their

degradation subject to environmental conditions. Here, things get much trickier, as the

current science of service life prediction is imprecise.

For example, Bogenstatter has argued that there is very little scientific basis in the

assignment of some service life data, with ranges of 40 to 100 years being applied to

different buildings regardless of their composition, as described in the following excerpt:

Regulations presume a service life of buildings between 40 and 100 years.
Differences are made according to the use of buildings despite their
material composition. With regard to sustainable use of buildings, the time
span is the main point to be considered. In fact, the technical life span of
buildings is determined by the maintenance rate of its components. Nothing
prevents using the primary systems of a building for 100 years or more. It
also works out advantageously for the environment and costs (2000)

Bognestatter does not elaborate on the aggregated impacts of maintenance activities,

which can potentially increase service life and consequently environmental impact.

Conversely, decreased maintenance frequency may reduce building service life, while

simultaneously lowering environmental impact. As such, the benefits of system

longevity may be questionable.

Data of a similar range has been published by Brattebo et al. Again, it is not clear

where the data originated.

Assumed lifetimes for each application type in residential buildings are the
following: lighting fixtures, 20 years; small capacitors, 30 years; window
sealants, 25 years; and all others, 100 years. Assumed lifetimes for non-
residential buildings are: lighting fixtures, small capacitors and window
sealings, 30 years; and others, 100 years (2009).

Numbers in these ranges can be contrasted with a multitude of other studies. For









example, a study by Kosareo and Ries assumes a service life of 15 years for a

conventional ballasted roof and 45 years for a green roof, with the eventual conclusions

that "the materials needed to construct the roof are important when the energy needs

are reduced, and when roof replacement cycles are short" and that "green roofs are the

environmentally preferable choice when constructing a building due to the small

reduction in energy demand and the increased life of the roofing membrane." (2007).

Recognition of differential durability is also evident in the work of Rudbeck,

wherein proposed methodological modifications are suggested for the economic

assessment of low-slope roofing. The study schedules roofing replacement every 22

years (with a standard deviation of 7 years). This is contrasted with the building's

service life, which is assumed to 60 years according to the study (2002). Rudbeck does

not suggest that the service life of low-slope roofing ought to equal the service life of the

building. Rather, it is evident that the periodic replacement of roofing would affect the

economic assessment of building systems considerably.

Paulsen provides yet another example of differential durability in his assessment

of different flooring systems. Paulsen states that the service life for different flooring

systems may range from 5 40 years, depending on the particular determinants of the

technical service life, such as economical or aesthetic for example. The Paulsen study

is particularly relevant in that flooring maintenance activities are integrated into the Life

Cycle Assessment, and therefore become part of the Life Cycle Impact of the process.

These benefits of more frequent maintenance however are not seen to affect the

service life of the material in any way, while intuitively such maintenance extends

service life (Paulsen 2003).









Salazar and Sowlati provide another example of differential durability in their

analysis of window frame materials. The authors attained explicit service life data for the

different materials by distributing a survey to "'authorities" in which it was found that

aluminum-clad wood windows provided the longest service, 46.7 years, with aluminum

second. 43.6 years, wood third, 39.6 years, and PVC providing the shortest service,

24.1 years." (2008). In the resulting analysis, the authors make an important conclusion:

"PVC, aluminum clad wood, and fiberglass are all comparable in cradle-to-gate

emissions and that the primary determinant of a life cycle advantage stems from a

longer service life and lower replacement frequency." This conclusion is of course

dependent on the validity and the accuracy of the service life data retrieved from the

"authorities". Presumably, a survey of this type would yield an accurate representation

of material longevity. Yet, this cannot be confirmed with any degree of certainty. Service

life varies depending on factors of environmental degradation, assembly design and the

frequency of maintenance amongst a number other variables. These factors may also

be location specific. Therefore, the conclusions of this study are only as valid as the

determining data of window frame service life.

A number of other studies have recognized differentials in material longevity. In

Shohet and Laufer, the differential durability of like materials is shown to be dependent

on environmental exposure (1996). Although it is not the explicit focus of the study,

Kellenberger and Althaus recognize differential durability in their Life Cycle Assessment

study of building components. The authors allude to a constant influx and efflux of

materials by stating that certain layers of the building are replaced. (2009). In Scheuer

et al., a university building is modeled over the course of 75 years, per Dell'lsola and









Kirk's service life estimates (2003). The authors also recognize differential durability in

the study, as many of the materials are replaced at different intervals. As the authors

conclude, differential durability is one of the main difficulties in the modeling of a

building (Scheuer et al 2003).

Ultimately, the concept of differential durability is relevant to two scenarios in

particular. First, in the planning, design and assembly of composite building forms such

as walls and roofs, it is important to recognize the durability of each individual

component, as the failure of one material may cause the failure of the entire system.

Indeed, the inextricability of the individual components makes premature, wasted,

underutilized or ancillary durability an issue. Second, if individual components are

subject to implicit differences in durability, this is also true for building materials in

general. Thus, it is appropriate to view buildings as composites of individual materials,

and as groupings of material assembly systems with different service lives.

Service Life Prediction

The prediction of service life for a building or building material is at times depicted

as more of an art than a science (Foliente and Leicester 2008), or as Lacasse and

Sjostrom have put it, "not an exact science" (2005). Service Life Prediction is

challenging for a number of reasons. Primarily, Service Life Prediction is made difficult

in that it becomes necessary to ascribe numerical values to assessments of degradation

that are essentially defined by qualities. An extension of this idea is put forth by Bourke

and Davies who state that "the point at which service life ends is loosely defined."

(1997). Bourke and Davies may be alluding to the determinants of service life and

proffered by the International Organization for Standardization, who state that service

life can be determined by any one of the following factors: structural performance,









weather tightness, aesthetics, comfort and hygiene, health and safety, energy

efficiency, need for maintenance and repair, economic performance, response to

foreseeable hazards, and technical and physical obsolescence (ISO Part 1 2000). In

accordance with these determinants, Ashworth has observed that the conclusion of

service life may be based on several factors. "All components have widely different life

expectancies depending on whether the physical, economic, functional, technological or

social and legal obsolescence is the paramount factor influencing their life." (1996)

To characterize Service Life Prediction as more of an art than a science is

somewhat unfair. Many applications of service life prediction studies have yielded

plausible results. However, as high degrees of variability in Service Life Prediction are

encountered throughout the literature, further thought must be given to the refinement of

method, and the consideration of time and potential scenarios.

There are numerous approaches to the prediction of service life for buildings and

building materials. As described previously, there are three general methodological

areas: the factor method, probabilistic approaches, and empirical reliability models. The

methods are said to range in terms of difficulty and degree of accuracy, such that each

method has inherent strengths and weaknesses. For example, the factor method is said

to be the most utilitarian, expedient and accessible method, although the assignment

and appropriate quantification of qualitative factors has produced a fair amount of

debate. Methods focused on probabilistic methods are designed to provide an accurate

range of potential service life figures, although a fair amount labor and expertise are

required, and these are commodities not commonly possessed in the associated fields

of building construction. Reliability models based on empirical data gathering are widely









believed to be the most accurate, yet location specific surveys require a significant

investment in time. Two such studies have produced some counterintuitive results,

noting that the determinants of service life are not necessarily related to the technical or

mechanical properties of the materials. For example, Trusty and Argeles (2005), and

Aikivuori (1999) have argued that durability is much less of a factor in determining a

building's service life than are other factors. In the Trusty and Argeles study, the authors

based the termination of service life on the City of St. Paul Minnesota's demolition

records between 2000 and 2003. The authors contend that service life is often

determined by factors such as area redevelopment, fire damage, the building's physical

condition (non-structural), poor adaptability, or that the maintenance of the building is

too expensive.

As convincing as the results of this study may be, it seems premature to exclude

material degradation as a determining factor in service life, especially since "the

building's physical condition "non-structural" is given as a determinant of service life.

Furthermore, the analysis of City demolition records over the course of three years

involves a specific sample of the building stock. The study does not elaborate on

potential differences between the stock of building analyzed and other potential stocks.

Even so, the study confirms what the ISO standards profess; that service life is

determined by a number of factors, some of which do not necessarily pertain to material

degradation (2005).

The Aikivuori study brought similar conclusions, although in this case, the author

recognizes the influence of subjectivity.

Empirical research has been carried out to find out the actual reasons for
initiation of repair projects on buildings. This research has shown that the









owners of the buildings actually experienced the user requirements
predominantly outside of the range of durability failures. Only 17 % of the
repair projects were initiated primarily because of deterioration. The critical
loss of performance seems to primarily be in the range of a subjective
perception of the building. Very little technical or economical rationality can
be seen in the actual decisions made on building refurbishment. In most
cases the limiting factor for service life is not durability (1999).

Independent of the alternative determinants of service life offered by Trusty and

Argeles, and Aikivuou, the utilization of empirical data represents one of the most

effective means of predicting service life. Unfortunately, as Soronis has observed,

comprehensive sets of empirical data are in short supply (1996), not relevant to the

climatic region in question, or part of larger proprietary datasets. More often than not,

the researcher is left without a relevant source of empirical data.

The Factor Method

The factor method is perhaps the most commonly practiced form of service life

prediction. It has been the focus of several major national, international and private

organizations, and as compared with some of the other methods outlined above, has

the reputation of being the most user-friendly. The Architectural Institute of Japan (AIJ)

is often credited as the originator of the factor method, with the publication of the

Principal Guide for Service Life Planning of Buildings in 1989, an English edition of

which was published in 1993 (AIJ 1993). In turn, the AIJ publication was instrumental in

the formulation of the International Organization for Standardization (ISO) Standard

15686-1, Building and Constructed Assets- Service Life Planning-Part I, a widely

recognized guideline for the application of the factor method in the prediction of service

life of buildings (ISO Part 1 2000). Further discussion of the factors has been

contributed at the national level by the British Standards Institution (British Standards

Institution 1992) and the Canadian Standards Association (Canadian Standards









Association 1995) who has attempted to provide insight to the service life prediction of

buildings and buildings components according to local environmental factors, quality of

materials and construction practices. It should be noted however that the factors

described in the British and Canadian standards are also intended to be relevant to

other types of Service Life Prediction. Guidelines have also been produced by the

European Commission via the European Construction Products Directive, Guidance

Paper F-Durability and the Construction Products Directive (European Commission

2004).

Perhaps the most extensive body of work on the factor method stems from the

collaborative efforts of the International Council for Research and Innovation in Building

Construction's (CIB). The Council's participation in the series of International

Conferences on Durability of Building Materials and Components has ensured a steady

stream of publications and cutting-edge theory. In addition, CIB Working Commission

W080- Prediction of Service Life of Building Materials and Components, in conjunction

with the International Union of Laboratories and Experts in Construction Materials,

Systems and Structures (RILEM), has further compiled a comprehensive set of working

papers, reference materials and sources of data.

Variations of the factor method have also been used in the sphere of liability to

assess maintenance and insurance requirements and the potential for defects. For

example, the Chartered Institution of Building Services Engineers has compiled an

appendix of economic life factors for building services (CIBSE 2000), and the Building

Performance Group (BPG 1999) and Housing Association Property Mutual

(Construction Audit Limited 1992) have put together component life manuals with









listings of factors and reference service lives for a multitude of building components and

materials. However, it should be noted that the figures presented in these manuals

represent "insured" service lives, and are consequently conservative in nature.

The factor method is perhaps most widely recognized as stated in the ISO

Standard 15686-1, whereby the formula is laid out as follows:

ESLC = RSLC x factor A x factor B x factor C x factor D x factor E x factor F x factor G.

The factors are defined as follows

* factor A: quality of components
* factor B: design level
* factor C: work execution level
* factor D: indoor environment
* factor E: outdoor environment
* factor F: in-use conditions
* factor G: maintenance level (ISO Part 1 2000).

Herein, ESLC refers to the Estimated Service Life of the Component and RSLC

refers to the Reference Service Life of the Component. The factors, as mentioned

throughout the literature, are the main source of contention. Under "normal" conditions,

each factor will equal 1, and the Estimated Service Life of the Component will equal the

Reference Service Life of the Component. Under less favorable conditions, the factors

will be adjusted to a value less than one, and the Estimated Service Life of the

Component will decrease in relation to the Reference Service Life of the Component.

Conversely, more favorable conditions would assign factors greater than 1, thereby

increasing the Estimated Service Life of the component in relation to the Reference

Service Life of the Component. The factors themselves offer an overview of the science

of Service Life Prediction, since methods employing the principles of structural

engineering or probabilistic approaches will vary according to the same influences.









As defined in Factor A, the quality of the component is an important factor in

determining service life. For example, there is a great deal of difference between lumber

produced from a 10-year-old pine tree sapling and lumber produced from the heartwood

from a 100-year-old Giant Sequoia. By the same token, there is a great deal of

difference between the various alloys of steel, mixes of concrete and types of brick.

Theoretically, Factor A varies according to the quality of the component; the higher the

inherent quality of the material, the higher the value attributed to Factor A.

Factor B refers to the design level; in other words, the way which materials are

positioned in relation to or affixed to the larger structure and/or each other. For example,

service life may vary if materials are exposed to direct sun or protected by the shade, or

if the materials are compatible and do not engender premature degradation. Further,

Factor B may refer to the degree to which sealants and fixtures are designed into the

building, and the level at which materials are joined together. For example, a curtain

wall with poorly designed sealant and gaskets will logically have a shorter service life.

Another example is given in an article by Stazi et al, who observed differential durability

characteristics depending on environmental exposure. In their study, the authors

observe that "the cracks, which are present corresponding to the joints between the

insulation panels, are due to overheating and differential temperature dilatation; the

extent of the damage is greater on the south face where there are more temperature

changes." (2009). A similar example is given in Balocco et al, where the authors' study

examines differences in thermal stress related fatigue in the building envelope in

consideration of building orientation (2008). Again, the service life of the assembly is

dependent on the building orientation, and therefore the design might be adjusted to









achieve the desired service life. Service life is also dependent of the type of material

chosen in a specific location. As described by Berdahl et al, "roofing materials are

commonly believed to be less durable in hotter climates." The authors go on to clarify

that certain materials such as ceramics or clay materials, may be more resistant to the

effect of hotter climates (2008).

Factor C refers to the level of craftsmanship involved in the construction of the

building. As Assaf et al. have observed, the quality of construction and installation has a

direct bearing on the longevity of the materials and the building as a whole (1995).

Faulty construction is an obvious determinant of service life. However, it should not be

confused with the design level. For example, a comprehensive sealant plan may be part

of the building's design, but installed poorly. Thus, the corresponding factor for the

design level (Factor B) would be higher than 1, and the factor for work execution (Factor

C) would be lower than 1.

Factor D refers to the condition of the indoor environment. For some materials, this

factor may not be applicable, as their design function is strictly exterior. However, for

those materials that are affected by the interior condition of the building, Factor D would

account for differences in humidity or in the instance of an industrial application, the

presence of chemicals. In these instances, the ESLC would need to be adjusted

accordingly as these factors constitute an aggressive environment. Similarly, if the

indoor environment is favorable for a given material, the factor would need to be

adjusted to reflect conditions that are better than the norm.

Factor E is slightly more complex, owing to the multitude of factors that apply to

the external environment that may not necessarily apply to the indoor environment. For









example, ambient temperature, humidity, the frequency of driving rain or freeze-thaw

periods, the presence of Ultra-Violet (UV) radiation, air pollutants, pollutants present in

precipitation and driving wind may all be viewed as factors influencing the longevity of

service life vis-a-vis the exterior environment. Factor E is also complicated by the fact

that many of these factors may work in concert, compounding the appropriate

quantification. Westberg et al. have observed that the current use of environmental

degradation factors requires some adjustment to the site, and that "data is often

collected at some distance from any specific building and the actual exposure

environment adjacent to the building (i.e. at the micro level) can be substantially

different." The authors continue that general parametric adjustment is required.

While databases and models established for other purposes may be
employed for service life estimations, substantial adaptive work remains to
bring this method practical and general in terms of different materials and
locations. Issues not resolved concern, for instance, data format (time
intervals, type of values, statistical parameters, presentation methods etc),
accuracy of data (degree of approximation), data failure (errors, lack of data
etc). In future work, these problems will be addressed and the concept
developed and implemented into practical software tools for engineers.
Being selected as test materials, initially the applicability for different
materials will be studied for wood and rendered autoclaved aerated
concrete (2001).

Factor F refers to the in-use conditions, or the level of use to which a building is

subjected. In many circumstances, this factor is applied to the interior of the building,

but in some circumstances, may just as readily be applied to the exterior. For example,

in the case of a flooring material, the service life may vary widely depending on the

amount of traffic or punishment it is subjected to. In a study of flooring materials,

Paulsen has acknowledged that the degree of use plays is an important determinant of

service life (2003). Likewise, the lifespan of materials with operable or mechanical

components will vary significantly depending on use, and perhaps more importantly, the









intensity of use. Again, appropriate factors must be assigned according to the relative

degree and intensity of use.

Factor G, or the level of maintenance applied to a certain material, will also affect

service life significantly. Ashworth for example has observed that the service life of

building can be extended well beyond any predetermined average. "It can be argued

that if a building is properly designed and constructed then it can be maintained almost

indefinitely. There are many examples in buildings where the original components

remain in use for hundreds of years." (1996). Indeed, the level of maintenance can

affect the service life of a given building or building material in very profound way.

Another example of the effects of maintenance is offered by Ozel and Kohler. The

authors state that "the decision to paint a building component such as a door, controls

the aging process, thus affecting the component both directly and indirectly. Not only

will the door now have a new color, but will also age differently due to the protection

afforded by the paint" (2004).

Mirza warns that deferred maintenance can result is a host of building problems,

including compromised longevity.

Deterioration of infrastructure has a negative impact on facility performance.
The consequences of neglecting or deferring maintenance are reflected in a
shortened facility life, premature replacement, at high costs to society; high
operating costs; and a waste of natural and financial resources.
Maintenance is defined as the set of activities undertaken to keep a facility
in a fully functioning or operating condition or to return the facility to such a
state; and to ensure long-lasting benefits to the users. (2006)

Similarly, a number of studies have recognized the relationship between

maintenance and life cycle durability. Bogenstatter has concluded that "the technical life

span of buildings is determined by the maintenance rate of its components." (2000).









Likewise, Mendes Silva and Falorca have recognized a correlation between

maintenance and durability over time (2009).

In general, the factor method encompasses the logic of service life prediction,

such that the factors are generally recognized as the causes of degradation for every

service life prediction approach. The quantification of the causes of degradation

however constitutes the significant difference from one method to another. In many

cases, this quantification is much more scientific, derived from actual tests, or based on

the interaction of mechanical, mineralogical or chemical properties. Often times,

statistical methods are employed to make sense of the potential variance from scenario

to scenario.

Marteinsson argues that it is difficult to quantify the different variables in the factor

method. Marteinsson states that "clearly, a difficult aspect when applying the method is

deciding realistic values for factors A-F. The effect of changes in a single factor is

difficult to anticipate and there is considerable risk that synergy between factors can

affect the results unfavourably." (2003). Even some of the better known practitioners

have pointed out that the method is deficient, stating that "it is shown that service life

prediction is encumbered with considerable uncertainties in estimating factors affecting

the service life of materials and components." (Lacasse and Sjostrom 2005). Evidently,

a good deal of caution should be exercised in applying the factor method and the results

approached with due reservation.

Probabilistic Methods

Probabilistic methods in service life prediction are perhaps best described by

Lacasse and Sjostrom, as follows:









A basic "engineering" approach is described that can be applied to the
factorial method for standard cases as well as to other service life prediction
methods that employ mathematical relations for service life. As opposed to
using simple numerical factors, as is done in the original factor method, this
approach incorporates the use of probability density functions for factors as
well as for estimating the service life of individual components to arrive at
an overall estimate of a building system's service life (2005).

Most of the Service Life Prediction work involving probabilistic methods is

specifically geared toward the analysis of one material. This is especially true of

concrete for example, where numerous researchers have applied probabilistic methods

and distributions toward the estimation of service life. In particular, probabilistic methods

are more commonly found in large infrastructure type applications, where the service life

may vary significantly. For example, a bridge or tunnel may be constructed to last 100

years or more, and the longer the service life is anticipated to be, the more the

distribution of results may vary. A study by BreitenbCchner et al. is illustrative, wherein

the researchers used a probabilistic methodology to predict the service life of the

Western Scheldt Tunnel in the Netherlands. Owing to the massive public investment in

the project, a long service life was required. Thus, there was no pre-existing

methodology to accurately predict the potential outcomes, and in using a probabilistic

methodology, the authors hoped to adequately account for any expected variance

(1993). A similar rationale for using a probabilistic methodology is given by Siemes

(1999).

Additional studies have been initiated to garner a better understanding of concrete

under the influence of an aggressive environment (Biodini et al. 2004), such as those

involving chloride diffusion (Teply et al. 1999; Hong 2000), or severe temperatures and

chemical exposure (Wiseman and Kyle 1999), or in large infrastructure type projects

(Walbridge and Nussbaumer 2004; Furuta et al. 2004). Ultimately, probabilistic methods









are most well-suited to studies involving a fair degree of uncertainty, whereby a

stochastic distribution most adequately fits the variance in potential scenarios. As

Hovde and Moser have observed, "in many cases, data has been collected and

variables fitted to them." (2004)

Markov models for deterioration are a variation on standard probabilistic methods,

and often used in studies employing the basic principles of structural engineering. It

follows therefore, that Markov models are most well-suited to large infrastructure

projects, or projects with added uncertainty. To this end, Markov models seem

particularly relevant to buildings because of their relatively longer life spans, although

their application so far has been limited to large infrastructure projects (Abraham and

Wirahadikusumah 1999; Leira et al 1999; Ansell and Sundquist 2002).

The influence of the principles of structural engineering is also evident in a

multitude of other studies, where more sophisticated mathematical modeling techniques

are employed, mechanical properties of the material in question are considered

(Dotreppe 1999; Lair et al. 1999; Lair et al. 2001); and the complex chemical and

mineralogical relationships analyzed with respect to the progression of fatigue as in

Siemes and de Vries (2002). The Unites States Army Corps of Engineers has also

published the Building Materials Durability Model, wherein the relative life cycle

economies of different materials, including required maintenance and upkeep were

mapped over time. Herein, the US Army Corps of Engineers analyzes several different

types of structural materials including concrete and structural steel (Hjelmstad et al

1996).

Overall, the structural engineering methods employ a level of sophistication that is









not evident in the other methods. Again, practitioners of these methods are often

experts in very specialized areas, as in Fagerlund where the author analyzes the

impacts of structural design and freeze-thaw action on the fracturing of concrete (1999).

To this end, the methods are often too robust in nature, and as with all specialized

disciplines, often presumed to be as overly esoteric. A number of attempts have been

made to standardize this branch of service life prediction (Masters and Brandt 1989;

Frohnsdorff 1996; Frohnsdorff and Martin 1996). However, there is still a fair amount of

research that needs to be performed to harmonize the body of knowledge.

Empirical Data and Reliability Models

The Canada Mortgage and Housing Corporation (CMHC) research report entitled

Service Life of Multi-Unit Residential Building Elements and Equipment provides a fairly

comprehensive set of empirical data, based on a Delphi survey of noted building

managers throughout Canada. The implicit limitation however is that the climatic

conditions in Canada are much different than those of the State of Florida or other

regions in the continental United States. Hence, with the understanding that similar

materials may degrade at different rates elsewhere, the data can only be used as

anecdotal.

Another set of empirical data has been compiled by the Army Corps of Engineers

and is currently integrated into their BUILDER software program. The software is

capable of plotting service life curves, assessing the effects of maintenance, and

orchestrating the entire management of the building systems based on differential

durability. Other sources of data are more sporadic. The CIB for example has

undertaken the compilation of a large set of empirical data from field experience and









observed measurement. However, this document is still incomplete and has yet to be

published.

Hybrids and the State of the Art

One of the most innovative methods for predicting service life employs a

combination of the factor and probabilistic methods, essentially using the limitations of

the factors to construct a distribution. Moser's study of the relative service lives of

windows is a good example (1999), as is a study performed by Aarseth and Hovde

(1999). A similar method is proposed in the methodology section of this dissertation.

As stated previously, the prediction of service life is not an exact science. Many

researchers have offered alternative explanations for the premature end of the service

lives of buildings, including poor adaptability and land use change. Herein, these

researchers have found nothing more than alternative definitions for the obsolescence

of materials. Yet, insofar as science is able to accurately predict service life according to

a particular definition or perspective, the body of literature currently offers a great deal

more than that, i.e. an accurate depiction of the constantly changing condition of

building materials over time. The problem therefore is not one of accurately predicting

the service life of given material or building. Rather, the problem with service life

prediction is one of definition and misinterpretation. Indeed, the demolition of a building

according to poor adaptability suits is a specific segment of this definition. However, the

demolition of a building based on poor adaptability is not tantamount to a single,

overarching definition for "functional obsolescence". This is a kind of blind acceptance.

After all, the purpose of science is not accept the seeming or apparent. The purpose of

science is to constantly question. As in the definition of service life; it may be that

durability is not the prime determinant of service life. However, it is up to science to









question whether in fact durability should be the prime determinant. The argument

therefore is one of conditions.

Life Cycle Assessment

The first recognizable forms of Material Flow Analysis came about toward the end

of the 1960s and the beginning of the 1970s. These studies were pioneering, and as

such, were relatively unconstrained by definition or methodology. The original goal was

to analyze a product or process using a multi-criteria approach, and to measure the

impacts of the resultant material flows throughout the life of the respective product or

process. In subsequent years, divergent methodologies forged alternative paths and as

a consequence, LCA became more refined in terms of definition and more standardized

in terms of methodology. However, it was not until the early 1990s that official standards

and definitions were established. For example, the first works the Society of

Environmental Toxicology and Chemistry (SETAC) did not come about until 1991, and

the first standards by the International Organization for Standardization (ISO) were not

established until 1997 (Ecobilan 2010).

Although SETAC retains an advisory committee on the practice of LCA, it is the

ISO standards that are more frequently cited as the definitive guidelines. The ISO

documents cover all aspects of the LCA process, and guidelines are set for defining the

goal and scope of the study, the functional unit, the system boundaries, data quality and

requirements for comparisons between LCAs, data collection and calculation

procedures, impact and assessment, and the interpretation of results (ISO 1 1997).

Subsequent volumes of the standards deal with guidelines for Goal and Scope

Definition and Inventory Analysis (ISO 2 1997), Life Cycle Impact Assessment (ISO 3

1997) and Life Cycle Interpretation (ISO 4 1997).









However, insofar as Life Cycle Assessment is standardized, a significant amount

of latitude or scientific license is permitted. This is much more evident in the literature

than it is the ISO standards. LCA studies may begin with the ISO guidelines and

produce vastly different results. To some in the field, this is perceived as a weakness;

they believe that LCAs should be further standardized and that a lack of standardization

undermines the legitimacy of most, if not all LCA studies. As mentioned in the previous

section of this dissertation however, the true weakness of LCA stems from the

qualitative variety of its measures. For example, it is virtually impossible to compare

LCAs with different impacts without making a subjective judgment. Is water pollution a

more significant impact than air pollution? Is global warming a direr environmental

problem than ozone depletion? Ultimately, judgments made on this type of comparison

require a presumption of fact, and therein lays the true weakness of LCA.

Outside of the limitations, LCA continues to provide one of the most promising

areas for environmental improvement. As Cole and Sterner have observed,

Life-Cycle Assessment (LCA) methodologies have emerged as a means to
profile the environmental performance of materials, components and
buildings through time and have been generally accepted within the
environmental research community as the only legitimate basis to compare
competing alternatives. They have successfully entrenched the notion of an
extended time context for examining the environmental characteristics of
buildings beyond the short horizons that dominate current design and
construction (2000).

It is significant that Cole and Sterner refer to Life Cycle Assessment as a means to

analyze environmental impacts "through time", as this is variable that is commonly

omitted from a large number of LCA studies, particularly so in the realm of building

construction. Perhaps the effects of service life are often neglected because the first

LCAs were performed to assess the effects of manufacturing and industry over much









shorter life cycles. As such the practice of performing an LCA on a building is a

relatively new concept and an emerging field in and of itself.

Life Cycle Assessment in Buildings The Functional Unit

The application of Life Cycle Assessment on building systems has been

practiced only recently. As it is consistent with the characteristics of emerging fields, the

application of Life Cycle Assessment on buildings has required some adjustment from

"conventional" LCA methods. There are some aspects of the built environment and

buildings that are unique, prompting prolonged discussion the research community on

the appropriate functional unit for a building system.

For example Borg et al. have described the challenges of modeling a building in

Life Cycle Assessment at length.

Applying and developing the LCA methodology to the context of the building
sector makes several building-specific considerations necessary. These
considerations originate in the fact that some characteristics of products in
the building sector different considerably from those of other industrial
sectors. The largest difference is that the service life of a building can
stretch over centuries rather than decades or years, as for other industrial
products' service lives. The long service life of buildings has a consequence
that it is difficult to obtain accurate data and to make relevant assumptions
about future conditions regarding recycling. These problems have
implications on the issue of allocation in the building sector in the way that
several allocation procedures ascribe environmental loads to users of
recycled or reused products and materials in the future, which are unknown
today.

The authors contend that this allocation problem leads to problems in "the

definition of the product, and consequently the functional unit to be addressed by the

assessment (2001).

A similar viewpoint is held by Paulsen, who states that buildings are unique in that

their service lives are relatively long, and require periodic maintenance over the course

of their operation, as described in the following excerpt:









An analysis is often carried out on the product level, while in order to
include the usage phase, information is required on expected service life,
type of maintenance, interference with surroundings, etc. the necessary
information may depend on the context of the building product. One type of
environmental loads that may occur in the usage phase is due to
maintenance. Building products may have a significant longer service life
than most other product groups on which LCA methodology has been
applied. Accordingly the usage phase could be expected to cause a
significant contribution to the total impact over a building product's life cycle
(2003).

The author continues by stating methodological development is especially needed in the

area of building maintenance.

As stated by Salzar and Sowlati, buildings are unique and complex systems

(2008). Hens and Verbeeck have argued that "probably because of the complexity of

the course of life of a building, researchers in the past often opted for building materials,

building products or building components as subject for LCA research. The authors go

on to say that "decisions based on isolated LCA for materials or components might lead

to unexpected secondary effects when the materials or components are applied in

buildings without taking into account their impact on the performance of the building as

a whole." (2010). A similar point is evident in the work of Ortiz et al., wherein the

differences between whole building analysis and that of individual components is

discussed. The authors point out that differences between the analysis of whole building

or individual components are essentially differences in the functional unit (2009).

Verbeeck and Hens also suggest that the length of a building's service life makes

predictions of future outcomes and environmental assessment very uncertain, a view

that is shared with Brattebo et al. (2009). Scheuer et al have added temporal context to

their observations on the challenged of building modeling. The authors state that

buildings "are large in scale, complex in materials and function and temporally dynamic









due to limited service life of building components and changing user requirements."

(Scheuer et al 2003).

Itard and Klunder have stated that buildings are "unlike conventional consumer

goods" and "often change in the course of their life span." The authors contend that LCA

is a "static" method, whereas "the behaviour of buildings is more dynamic." The authors

state that it is for this reason that environmental impacts are difficult to track using LCA.

To paraphrase the authors, this relates to the functional unit of a building study, in that

"the dynamic and changing character of buildings, should be considered as processes

rather than as products." and that "studies of this type will also need to adjust for the

uncertainties in the data available." (2007)

Other researchers have pointed toward the unpredictability of future scenarios,

identifying the long service life of buildings as one of the main predicaments in LCA

analysis. Santos Viera and Horvath state the following:

The main challenge here is the difficulty of establishing the value of elapsed
time. These two issues are particularly complicated for buildings because
they are complex (with many involved materials, products, equipment,
utilities) and typically have a long lifetime (from a few years to several
decades or even centuries). (2008)

Nordby et al. have argued that change is implicit with the passage of time and

extended building service life, as described in the following excerpt:

A building rarely remains in the same physical state over such long time
spans. Modifications, demolition, and rebuilding caused by new functional
or technical needs will probably occur, and should be accommodated in the
whole technical lifetime of the components. In traditional brickwork, reuse
and recycling was allowed for. Weak mortar types made it possible to
deconstruct a wall so that the building blocks could be reclaimed, and this
practice was a natural basis for brick-building cultures throughout history.
(2009).

Erlandsson and Levin take a similar view to assessing the functional unit









suggesting that the analysis of buildings might be better geared toward a "service life

perspective oriented approach", wherein the functional unit might be more accurately

described as a process as opposed to a product (2005). The ideas of treating a building

as a process and not and product, the differential durability of materials and

components, along with the parallel idea of buildings as temporally dynamic systems is

consistently held throughout the literature. Again, Sheuer et al. have explored the

challenges of Life Cycle Assessment modeling in buildings as one might look at a

system, as a process and not a product.

Clearly high replacement rates of materials with high embodied energy will
have a greater impact on life cycle performance. The influence of
renovation material choices and schedules on the embodied energy of a
building are not typically considered in the design stage of a building, but as
these results indicate designing with renovation burdens in mind could
diminish long term embodied energy burdens. (2003)

In a similar manner of thinking, Dimoudi and Tompa allude to differential durability and

maintenance of materials as important considerations in the life cycle modeling of

buildings. In turn, maintenance and differential durability are concepts related to

dynamic systems. The authors advocate the inclusion of the concepts in the following

passage:

As far as construction practices are concerned, additional criteria should be
considered like the lifetime of building materials, the compatibility of the
lifetime among the layers' building materials, the kind of assembly of
different materials and of the different layers, their maintenance needs over
the building life cycle (2008).

Mirza has indicated that the eventuality of change requires proactive planning and

design strategies, stating that consideration of change and the associated factors

should be initiated in the design phase.

An engineer's ability to specify appropriate materials for specific use in a
component and a given environment requires knowledge of the materials,









the operating environment, and the various physical and chemical
characteristics of the materials, as well as the transformations caused by
the specific environment and the operation and maintenance of the facility.
(2006)

Schultmann and Sunke have gone beyond moderate maintenance and replacement,

stating that the reuse and recovery of materials ought to be considered in the design of

a building. The authors contend that "the reuse and recovery of building components

and materials is 'advisable' provided that a positive eco balance is supported by not

increasing the gross sum of energy use." (2007). In terms of planning for second service

lives, the integration of temporal context and change over time is implicit

Despite the newness of the field, Life Cycle Assessment has been used in the

analysis of buildings and building materials in a number of applications. The American

Institute of Architects is often cited as the first to attempt the use of Life Cycle

Assessment as a measuring stick for building materials, with the publication of the

Environmental Resource Guide in 1996 (Dempkin 1996). As described in previous

sections of this dissertation, comparisons in LCA are at times difficult. Even the

Environmental Resource Guide uses LCA to make simple and relative comparisons of

materials without delving too deeply into the touchy matter disparate variables.

Most research efforts in the field of building construction have effectively side-

stepped the importance of comparisons in LCA by either stating that it is a widely

recognized problem, or by focusing in on a more specific aspect or life cycle stage of

the building. A number of studies have evaded the comparison of disparate variables

altogether by employing a method known as Life Cycle Energy Assessment. A study by

Ball observes the following:

The holy grail of low energy has mesmerized many assessments of
ecological design to the virtual exclusion of other environmental impacts.









Energy is probably the most easily measured and addressed in the
construction industry but it is by no means the only factor of sustainability.
Indeed, it is probably the very fact that energy is an easily quantified
commodity that it is such a popular measure of the environmental
credentials of a material or building (2002).

A fair portion of the literature in Life Cycle Energy Assessment follows the same

format as the majority of the literature in Life Cycle Assessment, in that relatively little

importance is given to the importance of service life. This is evident in the work of

Adalberth (1997), Chen et al.(2001) Adalberth (Adalberth 2 1997), Lollini et al. (2006),

and Sartori and Hestnes (2007) who have each employed the typical building service

life of 50 or 60 years.

However, Life Cycle Energy Assessment makes a significant contribution through

the work of numerous researchers who have explicitly stated alternative life cycles for

buildings and materials, a practice which yields much different results. Although the

specific term is not used, these researchers have recognized the importance of

differential durability in what they point to as a need for recurring embodied energy; in

other words the energy that is required to maintain a building over its lifetime. As

Venkatarama et al. have attempted to define:

Energy in buildings can be categorised into two types: (1) energy for the
maintenance/servicing of a building during its useful life, and (2) energy
capital that goes into production of a building (embodied energy) using
various building materials. Study of both the types of energy consumption is
required for complete understanding of building energy needs (2003).

The concept of recurring embodied energy is observed in the work of several other

researchers, Cole and Kernan (1996) and Fay et al. (2000) to name a few.

Life Cycle Energy Assessment has also corroborated one of the principle findings

of Life Cycle Assessment, in that independent of the given building's lifetime, the

operating energy constitutes the single biggest impact. Several researchers have made









this observation including Adalberth (Adalberth 2 1997) and Cole and Kernan (1996). At

the same time, several researchers have noticed that the more efficient the building

envelope becomes, the more significant the impact of the materials becomes relative to

operating energy, as in Yohanis and Norton (2006), Sartori (2007), Chen et al. (2001)

and Keoleian et al. (2001).

Overall, the contribution of Life Cycle Energy Assessment is important in its

recognition of maintenance impacts and recurring embodied energy. Several authors

have alluded to service life in particular as the catalyst for accurate Life Cycle Impact

Assessments in general.

Life Cycle Assessment by Life Cycle Stage

The obvious application of Life Cycle Assessment is in the analysis of

manufacturing. In fact, Life Cycle Assessment was conceived as a means of evaluating

industrial and manufacturing processes. As stated previously, it is perhaps for this

reason that researchers have had trouble adjusting the methodology to better suit the

analysis of a building. Many practitioners in LCA seem fixated on either the initial

impacts of manufacturing, or the impacts of the operation of the building. Other studies

by contrast have sought to take a different perspective, considering the effects of

maintenance and end-of-life scenarios.

For instance, the impacts of maintenance on a building have been thoroughly

researched in the area of Life Cycle Costing. As Dunston and Williamson have

suggested:

Lack of owner funding can often result in poor material system
performance. Owners must recognize that insufficient funding of design and
construction will impact future maintenance capabilities. Lack of funding is a
common reason for the selection of alternative material systems that may
not meet performance standards. Designers must be able to demonstrate









that increases in design and construction costs due to designing for
maintainability can be offset by reduced maintenance costs (1999).

This view is echoed by Mirza, who states the following:

Increased durability should normally result in an increased initial cost but
lower maintenance costs over the service life of the facility. Unfortunately,
current design methods, which are basically for the construction stage only,
cannot be used to determine the cost-benefits that would be attained
during the service life of the facility (2006).

If indeed the impacts of maintenance are significant in the Life Cycle Costing of a

building, it seems logical that this would also be true of the environmental impacts

measured in a Life Cycle Assessment. In other words, choosing a material with low

maintenance requirements would logically benefit a building owner in terms of costs,

and benefit the environment by way of lower maintenance impacts, a view that is also

supported by Mirza (2006), Harris (1999), Pushkar et al. (2005) and Thormark (2006)

for example. Indeed, maintenance impacts are a good indicator of material suitability for

a given climate, or as Allen has theorized, "to keep a far-from-equilibrium system going,

there must be a constant input of energy or matter, as when an animal must eat to stay

alive." (2002) Hence, materials that require relatively higher levels of maintenance might

be characterized as "far-from-equilibrium" with respect to the natural environment.

A continuation on the theme of building maintenance is evident in a number of

studies that have focused on renovation or refurbishment. A study by Dong, Kennedy

and Pressnail for example has illustrated the apparent advantages of building

renovation as compared with demolition and replacement. The Dong, Kennedy,

Pressnail study also presents a question for future study, as described in the following

excerpt:

In comparing the relative environmental impacts of utilizing existing
buildings versus new construction, the results have identified areas that









need further attention. In comparison to rebuilding, retrofitting saves
building materials and avoids the creation of solid wastes and pollutants
from the production of those materials. On the other hand, rebuilding results
in significantly greater savings in energy and energy related environmental
impacts, most notably global warming potential. There are numerous ways
to renovate, just as there are numerous ways to build new housing. In
simple terms, the results indicate a trade off. Should we trade off material
related environmental impacts for improvements in greenhouse gas
emission reductions? Or should we trade off the existing poor performance
of buildings to make use of their material resources? (2005)

Similar studies have also contended this point, arguing that more emphasis should

be placed on the existing building stock and the renovation of existing structures, as

articulated in Johnstone (2001) and Kohler (1999).

Beyond the renovation buildings, Life Cycle Assessment has also been employed

to analyze the recycling of building materials and other end-of-life scenarios. In fact, the

analysis of the environmental impacts stemming from recycling is not limited to Life

Cycle Assessment. Other forms of Material Flow Analysis have also contributed. For

example, a study by Brown and Buranakarn sought to identify the most recyclable

building materials through emergy analysis (2003). A separate study McLaren,

Parkinson and Jackson sought to devise a new methodology for mapping the cycling of

materials through material cascades, as might occur through multiple service lives

(McLaren et al. 2000).

The justification and quantification of the recycling building materials however is

not so prevalent. Thormark has stated that recycling is justified, based on the following

observation. "There are several reasons to include the aspects of recycling is an

analysis of the energy use of buildings; for example, the increasing proportion of the

total energy use attributable to materials and a decreasing service life of buildings."

(2002). Of course, this view is grounded somewhat by the caveat provided by Boustead









(1998) and Bishop (2000), who state that even if recycling is justified, it is only so to the

extent that the recovery and reprocessing of materials is less damaging than simple

disposal. In other words, Boustead and Bishop have argued that there is an optimal

level of recycling, after which material recovery and reprocessing does more harm than

good. Bishop has further qualified the process of recycling by describing the most

favorable scenarios.

Products that can be easily and rapidly disassembled into their component
parts are more likely to be reused or remanufactured. Those that are
designed so that parts snap together are probably the easiest to
disassemble after use. Bolted or screwed components are also easily
disassembled. Ease of disassembly also makes repair of the product during
use easier, because the part can easily be removed to allow access to
other parts that need repair, or the removable part can readily be replaced,
if necessary (2000).

Although a considerable amount of research has been performed on the recycling

of materials, most of the theory does not translate well into practice. More often than

not, the practice of recycling is dictated by the market, and the affordability of recycling

technologies. Further problems arise when decisions need to be made for the

reprocessing of materials. Since the optimal cycling of materials is loosely defined,

many building experts are unsure of the necessary concentration of materials required

for recycling. Again, most of the decisions are based on economics and the capabilities

of the local market.

The Confluence of Service Life Prediction and Life Cycle Assessment

The integration of detailed service life data into Life Cycle Assessment models of

buildings has been fairly limited. In part, this is due to the uncertainties of Service Life

Prediction. As evidenced in the sections on the Life Cycle Assessments of building and

Life Cycle Assessment by Life Cycle stage, researchers have struggled to find the









appropriate functional unit for the analysis of a building, and some have opted to use

Life Cycle Assessment methods to analyze a specific aspect of the building life cycle.

However, the confluence of the concepts has been initiated by relatively few. As stated

by the Athena Institute,

Defining or judging service life has been problematic for the developers of
green building rating or assessment systems, and few tackle the subject
from a holistic perspective. Indeed, while much information exists worldwide
on building and material service life, building construction, and green
building systems, there is little discussion of all three subjects as an
interrelated whole.(Athena 2006)

As it has been mentioned previously, LCA studies of building with dynamic and

detailed service life data have been fairly limited. A demonstration of differential

durability and detailed service life was included in Salazar and Sowlati's work, wherein a

survey was distributed to "authorities" with questions about window frame material

longevity. The results of the survey show a wide distribution amongst the different

materials (2008).

A good example of confluence is given in the work of Thomsen and van der Flier.

Herein, the authors undertake a similar methodology to the one employed in this

dissertation. As the authors state, the purpose of the method is strictly theoretical.

The results show that the ratios between the ecological effects of materials
and energy consumption do not change significantly when the lifespan is
extended to 400 years (Figure 4). Of course, this approach is strictly
theoretical; replacement with exactly the same materials, installations, etc.
does not make sense, even over a short period. As innovations in
technology, building process, maintenance, and dwelling use play a crucial
but fully unknown role, the outcomes give only an indication. Regarding
only the ecological effects of lifespan extension, the conclusion is that other
factors will make the difference. This may explain replacement or
renovation of dwellings the differences between the outcomes of the
empirical and theoretical studies (2009).

This may in fact hold true, as Strand and Hovde have discovered that higher levels









of maintenance sometimes result in higher overall environmental impact (1999). Thus,

materials requiring less maintenance are greener, or the compromise of material

longevity may result in lower Life Cycle Impacts due to decreased maintenance.

The assumption however prompts further examination. The literature in LCA is

sprinkled with references to service life and its effects on environmental impacts.

Similarly, some of the literature in Service Life Prediction has made reference to a need

for better service life data in LCA. It seems this is not a new area of inquiry. However,

with the exception of Strand and Hovde (1999) and Graveline (2005), the confluence of

Service Life Prediction and Life Cycle Assessment is virtually absent from the larger

body of knowledge.

The concept of confluence therefore must be affirmed on the basis of like research

or general observations, such as in the work of Kesik and O'Connor. Kesik in particular

is quite adamant about the "greenness" of durable materials and buildings, as illustrated

in the following excerpt:

Another reason for the current focus on durability is the recognition that
sustainability is not possible without durability. If you double the life of a
building and you use the same amount of resources to construct it, the
building is twice as resource efficient. Therefore durability is a key
component of sustainability (2008).

Kesik qualifies this observation with a subsequent statement:

Once constructed a building becomes a machine that "needs to be
fed". The more durable the building the longer it is around. The longer the
building is around the more energy it consumes. Durable buildings need to
be ultra energy efficient in order to be sustainable. Durability and energy
efficiency are the cornerstones of sustainability (2008).

There is a whiff of tenuousness in these two statements. In the first statement,

resource impacts are halved by simply doubling the service life. In the second, there is

the recognition that a durable building also needs to be ultra energy-efficient lest the









impacts resulting from the operation of the building were to somehow trump the halving

of resource impacts. Indeed, the veracity of these statements must depend on the

efficiency of future buildings, and that they will not outperform the older, more durable

models. It is of course logical to question these statements: why would technology that

is over one hundred years old outperform the cutting-edge? Presumably there would be

a fair amount of materials and energy invested in keeping the older building abreast of

the latest technologies; technologies that may or may not fit with an older format. Would

the same type of upkeep be true for a less durable building?

Kesik's work seems to prompt more questions than it provides answers.

Unfortunately, although the statements provide great fodder for a debate on building

durability, they are also largely unsubstantiated. A more quantifiable approach is

presented by Graveline, who in the same fashion as Kesik, illustrates the benefits of

prolonging the service life of a given material.

For a building with a 75-year design life, a roof assembly with a 15-year life
expectancy would have to be replaced five times within that span versus
three time for a roof with a 25-year service life. This has obvious
implications for the magnitude of each of the impacts associated with the
system (Graveline 2005).

Although Graveline's observations seem much more quantitative than Kesik's, his

analysis is still distinctly linear in nature. There is no mention of performance

degradation over time, or of the cumulative maintenance required to keep a system in

service for 75 years.

Overall, the confluence of Service Life Prediction and Life Cycle Assessment is

best exemplified by the work of Strand and Hovde. In combination with the Moser's

hybrid method for Service Life Prediction, the articles will comprise the basis of the

methodology of this dissertation as described in the following chapter.









Variability

The range of available service life data is the driving force and main preoccupation

of this study. As Life Cycle Assessments of buildings continue to be refined, it is

expected that the accuracy of service life data will improve, that researchers performing

Life Cycle Assessments of buildings will incorporate the best available service life data

into their studies, and the validity of Life Cycle Impact results will improve based on a

smaller range of contextual data. As follows, Life Cycle Assessments of buildings have

employed a wide range of service life data.

Chevalier and La Teno have the following to say regarding variability is service life:

For a given building product, this phase commonly ranges from five to 100
years and more, depending on mostly unpredictable external conditions
(climate, type of user, change of use, etc.). This causes in most cases a
violation of the time stability hypothesis and calls for some sort of flow value
actualization. Again, depending on the same external conditions,
maintenance and replacement processes will occur at varying frequencies,
thus again violating the flow accuracy hypothesis (1996).

Additional studies show different service lives dependent of the type of building or

material as the case may be. For example, Mithraratne and Vale analyzed residential

buildings in New Zealand and used a service life of 100 years, along with periodic

replacement and maintenance over time (2004). A study by Kellenberger and Althaus

assumed a service life of 80 years, stating that "the deconstruction and recycling or

disposal of the buildings will take place about 80- 100 years after the construction."

(2009). Verbeeck and Hens employed a mean service life of 30 years, or as the authors

state, "since the life span of a dwelling exceeds the usage period by one generation,

resulting in large uncertainties on modifications and destination of the building

afterwards, the mean adopted time scale here is the usage phase by one generation,

during a period of 30 years. It should be noted that Verbeeck and Hens included service









lives of 60 years and 90 years in the same analysis to account for sensitivity (2010).

However, the wide variation in service life is what is of interest to this study.

Observations by Marteinsson suggest that service lives for houses in Iceland are often

calculated at 60-70 years, with specific service lives for windows ranging from 5-10, to

as high as 80 years (2003). Nordby et al have mentioned that "bricks achieve high

scores in terms of their technical lifetime; brick constructions from both the Chinese and

Roman empires have survived for more than 1500 years."(2009). As the focus of the

Nordby et al. article is material reuse, the authors suggest that second and third service

lives may be appropriate for some materials. An article by Paulsen shows a wide range

of service life data for flooring materials, ranging from 5-40 years, depending on

whether the determining factor of service life is economical, aesthetic or otherwise

(2003). In their modeling of a university building, Scheuer et al. employ a service life of

75 years (2003). An analysis by Radhi, although geared the environmental impact of

different envelope materials in the operations phase, assumed a value of 75 years for

service life (2010). The study did not recognize differential durability amongst any of the

wall form systems. Bergsdal et al. used a number of different figures for service life

projections of the Norwegian housing stock, including schedule renovations. For small

buildings, the study scheduled the first renovation at 30 years, a second renovation at

60 years and demolition at 90 years. For large buildings, the study scheduled a first

renovation at 20 years, a second renovation at 40 years, and demolition at 60 years.

For all other buildings, renovations and demolition were scheduled in accordance with

the values for large buildings (2007).

Many researchers have opted to frame Life Cycle Assessments of buildings within









a commonly held life span of 50 years. Sartori et al. has provided a supporting

argument for this length of analysis, stating the following:

It is largely accepted as common practice to perform energy analysis over a
period of 30-50 years. This because it is generally assumed that after such
a period an average building is either demolished or undergoes major
renovation works that will considerably alter its energy performance. A
simplified approach to energy demand analysis could consider an average
time after which the overall energy demand itself is 'renovated'. This is of
course an approximation, but would allow concentrating all the (2008)

Further examples this commonly held service life maxim are evident in the work of

Junnila and Horvath (2003), Kahhat et al, Kooworola an Gheewala (2009), Pulselli et al.

(2009), and Sazi et al. (2006). Both the Kahhat et al. and Pulselli et al. studies involved

wall comprised of different materials. Similarly, the Saiz et al study involved a

comparison of different roofing materials. In a Life Cycle Energy Assessment performed

by Hens and Verbeeck, a period of analysis of 30 years was assumed (2009).

It is difficult to say which service life numbers are accurate. Of course, a high

degree of variability in assumed longevity yields a corresponding degree of variability n

terms of impact. Bergsdal et al have noted that "information about the lifetime of

dwellings is very scarce, and there is no consensus in the literature on what distribution

best reflects the actual dwelling lifetime. (Bergsdal et al II 2007). Lacasse and Sjostrom

have supported this idea by stating that "it is shown that service life prediction is

encumbered with considerable uncertainties in estimating factors affecting the service

life of materials and components." (2005). Itard and Kluner have suggested that the

complexity of service life prediction goes beyond a mere analysis of the materials, and

the degree of variability is dependent on the behavior of the household as well, stating,

that "it is also important to keep in mind that for anything as quantifiable as energy use









and life span of components, the values found for a building can easily vary by a factor

two, depending on the behaviour of the household." (2007)

As such, the literature on the confluence Service Life Prediction and Life Cycle

Assessment is inconclusive. In the chapters that follow, it is hoped that a better

understanding of this confluence emerges, and modifications to the current application

of Life Cycle Assessments on building is in need of modification.









CHAPTER 3
METHODOLOGY

To test the environmental impact of longevity for the materials in the building

envelope, a selection of nine materials were analyzed according to a three-tiered

approach. Three wall forms and three roof types were analyzed. The three wall forms

included a brick wall assembly, an aluminum panel wall and a wood siding wall. The

three roofs consisted of a ballasted, built-up roof, a thermoplastic roof, and an extensive

green roof. These materials were selected based on perceived differences in durability,

thermal performance, solar absorptance, and Life Cycle Impact. These materials were

analyzed as potential envelope combinations to be applied to the exterior of an

institutional university building. For the purposes of comparison, the Rinker Hall building

on the University of Florida campus was used. Rinker Hall is clad with a combination of

aluminum panels and curtain walls. On the roof of Rinker Hall, a highly reflective

thermoplastic membrane is installed. These materials are often described as high

performance, although very little is known about their maintenance needs or durability.

As the focus of this study pertained to environmental performance and material

longevity, Rinker Hall was an ideal building model. Rinker Hall is one-hundred and

eighty (180) feet in length, eighty-two (82) feet wide, and forty-two (42) feet tall. In

actuality, Rinker Hall includes two triangular solids on the North and South Sides of the

building. The triangular solid on the North side of the building encompasses two floors

of the building. The triangular solid on the South side of the building contains the

mechanical room. These triangular solids were viewed to be superfluous to the main

focus of the study and were therefore omitted. As such, Rinker Hall was used as a

template for a rectangular solid building, with the dimensions described above.









The three-tiered approach consisted of energy modeling, Life Cycle Assessment,

and service life modeling. First, energy modeling was conducted to assess the relative

thermal performance of the materials. Second, Life Cycle Assessments of the modeled

operating energy and envelope materials was performed. Third, the resultant Life Cycle

Impacts were integrated into five service life models with differing values for inspections,

major replacements, minor replacements, major repairs and minor repairs.

Three types of Life Cycle Assessment models were produced: 1) an energy

differential model, 2) an energy neutral model, and 3) a coarse model. Each model was

projected over a period of 500 years, in accordance with United States Army Corps of

Engineers specified service life for a brick wall (USACE 1991).

Energy Modeling

It was believed that each of these envelope materials would affect the thermal

performance of the building. To measure the environmental impact of this thermal

performance, an energy modeling analysis was performed using Energy-10 software, a

commonly used and widely accepted software application. The external loading of the

building was based on the Jacksonville, Florida weather data set. Three wall forms were

constructed in Energy-10 which mimicked a typical wall cross-section in Rinker Hall.

Walls were constructed of 5/8 inch gypsum board, 6 inch cold formed steel studs at 16

inches on center, 6 inches of blown cellulose insulation, and 1-1/2 inches of

polyisocyanurate board on the exterior of the wall. These wall forms were clad with one

of the three envelope materials; brick, aluminum or wood. A similar approach was taken

for the roofs. Each roof form included a corrugated metal deck, 5-1/2 inches of

polyisocyanurate foam, with 3 inches of lightweight concrete comprising the top layer.

The roofs were then finished with one of the three roofing materials; the built-up roof,









the TPO membrane or the green roof. All other variables for each energy model

remained the same, including the building's square footage, volume, wall surface area,

roof surface area, windows, doors, lighting and mechanical equipment. The analysis

varied only by the type of wall form or roof that was used. The materials listed above

were paired off to include all possible combinations; brick/built-up roof,

brick/thermoplastic membrane, brick/vegetated roof, aluminum panel/built-up roof,

aluminum panel/thermoplastic membrane, aluminum panel/vegetated roof, cedar

siding/built-up roof, cedar siding/thermoplastic membrane and cedar siding/vegetated

roof.

A number of assumptions were made during the energy analysis portion of the

study. For example, the option for "DX Cooling with Electric Furnace" was selected for

the HVAC system. Buildings for each energy model had established set points of 76

degrees Fahrenheit for both heating and cooling seasons. The thermal performance

and characteristics of the windows and doors were also constant through each energy

model

During the first iteration of energy modeling, a total of nine envelope combinations

were analyzed, as follows:

Wall Form Material Roof Material
Brick Green
Brick TPO
Brick Built-Up
Aluminum Green
Aluminum TPO
Aluminum Built-Up
Wood Green
Wood TPO
Wood Built-Up
Figure 3-1. Building Envelope Combination Used in Energy Modeling Analysis









A second round of energy modeling was performed to make all envelope

combinations perform equally. The envelopes were equalized by establishing a baseline

level of performance. In the first iteration of energy modeling, the brick wall and

vegetated roof combination was the most thermally efficient. Varying amounts of

polyisocyanurate insulation board were added to the other envelope combinations to

make them perform as well as the brick and vegetated roof combination. Insulation was

added to the walls and roofs separately, and for the purposes of subsequent Life Cycle

Assessment modeling, an average value of the separate wall and roof modifications

was used to derive a material quantity. Based on these modifications, the second

iteration of energy modeling generated a greater number of permutations, such that the

modeling of an additional twenty-five building wall and roof forms was required. Since

the brick wall and green roof combination was used as the baseline model, baseline

insulation was based on the original design 1-1/2 inches of polyisocyanurate board for

the wall, 5-1/2 inches of polyisocyanurate board for the roof. Additional insulation was

added to each envelope combination such that the baseline thermal performance was

achieved. The additional quantities of insulation required for the wall forms is shown in

Figure 3.2. The additional quantities of insulation required for the roofs are shown in

Figure 3.3.

Wall Form Material Roof Material Wall Insulation Required for Equalization
Brick Green 1.5"
Brick TPO 2.5"
Brick Built-Up 8.0"
Aluminum Green 2.0"
Aluminum TPO 3.5"
Aluminum Built-Up 9.0"
Wood Green 2.5"
Wood TPO 4.5"
Wood Built-Up 10.0"
Figure 3-2. Wall Modifications Required to Equalize Thermal Performance of Walls









Roof Material Wall Material Roof Insulation Required for Equalization
Green Brick 5.5"
Green Aluminum 6.5"
Green Wood 8.0"
TPO Brick 7.0"
TPO Aluminum 8.0"
TPO Wood 10.0"
Built-Up Brick 10.0"
Built-Up Aluminum 12.0"
Built-Up Wood 14.0"
Figure 3-3. Roof Modifications Required to Equalize Thermal Performance of Walls

The two iterations of energy modeling produced two service life models; 1) a

model that included the operating energy into the analysis as the differential from a

baseline the energy differential model, and 2) a model that equalized operating energy

through a case-by-case increase in polyisocyanurate insulation board the energy

neutral model. A third coarse model was constructed as an extension of the energy

neutral model, and excluded any environmental impacts relating to maintenance or

inspections. Rather, the coarse model included only the impacts of the major material

replacements at the specified frequencies over time.

Life Cycle Assessment

The results of the energy modeling analyses represented the first step in

assessing the environmental impact of material and assembly longevity. In order to

measure environmental impact, Life Cycle Assessment methodology was used. Life

Cycle Impact data for operating energy and the different envelope combinations were

extracted from the Gabi 4 software database, a widely recognized software application.

The environmental impacts of operating energy were based on the standard North

American electrical grid mix. Beyond operating energy, the environmental impact of

each material and assembly was calculated in terms of the inputs and outputs

associated with extraction, manufacturing, and transportation to the construction site.









Inventories of the different construction methods and equipment required were omitted

from this analysis, as the differences were considered negligible for each wall form and

each roof type. End-of-life scenarios were also omitted. It must be acknowledged that

the end-of-life impacts for each of these materials are different, such that the results of

this study must be taken in context. The primary objective of this study however focused

on the operations and maintenance phase of the life cycle. Therefore, it was believed

that the projection of open-ended material cascades and scenarios would confound the

original research question.

Material estimates were calculated for each wall form and roofing material. For the

wall materials, each quantity take-off was based on the dimensions of the modified

Rinker Hall building described previously. Logically, the square footage of each window,

lintel and door was deducted from the quantity take-off. Quantities for roofing materials

were estimated in a similar way, based on the aforementioned dimensions, with the

square footage of the skylights deducted from the total quantity. A waste factor of five

percent was used for each material. Additional material take-offs were performed for the

different maintenance activities described in each model. A detailed representation of

these material quantities is shown in Appendix A.

Distances for material transportation were assumed based on a student authored

report prepared for the Athena Sustainable Materials Institute (Fillie et al. 2004),

wherein "gate-to-market" effects of typical building materials were calculated for the

Orlando, Florida area. As the building modeled for this study was located in Gainesville,

Florida, the transportation distances presented in this report were viewed as the most

accurate available. However, a minimal amount of potential inaccuracy must be









acknowledged due to the distance between the City of Gainesville and the City of

Orlando.

Based on the quantity take-offs and distance specifications described above, Life

Cycle inventories were generated using the Gabi 4 software. Impacts were calculated

for the initial manufacture of the material and any replacement, repair, maintenance or

inspections performed over time.

A total of thirty-six building wall and roof form combinations were modeled

according to the energy differential, energy neutral and coarse sets of models. Each

envelope combination and each individual material was assessed in terms of

environmental impacts according to Global Warming Potential (kg of C02 equivalent),

Atmospheric Acidification (mol of H+ equivalent) and Atmospheric Ecotoxicity (kg of 2,4

0 Dichlorophenoxyace equivalent) as characterized by the Tool for the Reduction and

Assessment of Chemical and Other Environmental Impacts (TRACI) set forth by the

United States Environmental Protection Agency (EPA).

Service Life Models

Five service life models were used. The first service life model was authored by

the Army Corps of Engineers (USACE 1991). The report describes inspections, major

replacements, minor replacements, major repairs and minor repairs at specific intervals

over the estimated service life. Descriptions of these activities and the specified

frequency of each are represented in Figure 3.4. The frequency of each activity is

shown in the light-blue cells in years.

A second service life prediction model was based on a report published by the

Athena Sustainable Materials Institute (Athena 2002). Although the Athena model did

not specify major replacement intervals for some of the materials in the study, instead









stating that many cladding materials would endure for the life of the structure, major

repair and maintenance intervals cited in the report offer insight into the Life Cycle

Impact of a particular materials with specific relevance to service life. In following the

format of the USAGE model, the descriptions and frequencies of each activity in the

Athena model are shown in Figure 3.5.

A third set of data was extracted from Life Cycle Costing for Facilities (Dell'lsola

and Kirk 2003). As opposed to the USACE and Athena models, the emphasis in the

Dell'lsola and Kirk text is on cost, although frequencies for material replacement and

maintenance are also given. Specifically, the Dell'lola and Kirk text offers frequencies

for each major replacement, and a material cost for each maintenance activity. In order

to translate material cost into quantity, the 2003 edition of RS Means Building

Construction Cost Data was used (RS Means 2003). As such, the material costs

specified in the Dell'lsola and Kirk text were translated into a material quantity using the

material cost figures presented in RS Means. These quantities are shown in Figure 3.6.

Another service life model was produced from RS Means Cost Planning and

Estimating for Facilities Maintenance (RS Means 1996). Herein, service life data are

also provided with associated costs. As in the Dell'lsola and Kirk model, a 1996 edition

of RS Means Building Construction Cost Data was used to translate material costs into

quantities. Descriptions and frequencies of the RS Means service life models are shown

in Figure 3.7.

The final service life model was based on a static 50-year model, which excluded

any maintenance activities from the analysis. Equal service life frequencies were

ascribed to each material, including all roofs and all walls. Essentially, the 50-year static









model shows the differences in the initial impacts of the material as projected over time.

The descriptions and frequencies of the 5-year static model are shown in Figure 3.8.

Since each model included maintenance activities of varying intensities, a third set

of models was produced for the purposes of comparison. A set of coarse models was

generated by omitting any maintenance activities included in the USAGE, Athena,

Dell'lsola and Kirk and RS Means energy neutral models. Essentially, the coarse

models were simplistic reproductions of the energy differential and energy neutral

models. The coarse models did not include any operating energy impacts, nor any

maintenance activities over time. Rather, major replacement impacts were projected in

adherence to the specified intervals according to the USAGE, Athena, Dell'lsola and

Kirk and RS Means.

Life Cycle Impact data for each of the models were used to project cumulative

environmental impacts over a period of 500 years. A 500 year study period was used

because it is the specified longevity of a brick wall assembly according to the USAGE

model. For the purposes of analysis, the relative order and magnitude of each envelope

combination was recorded. Further analysis was produced to assess the life cycle

impact of each envelope combination and each material per year.











Inspection/
Minor Clean Major Minor Major Minor
Up Inspections Replacement Replacement Repair Repair


Built Up
Roof 1 3 28 20 14 1
1 square 0.02
1 square foot 0.025 square foot square
Transport Transport membrane, foot Insulation, Insulation foot felt
Resource 0.75 gallons 0.75 gallons insulation & Sealant & & adhesi
Required gasoline gasoline ballast Membrane Membrane ve

Inspection/
Minor Clean Major Minor Major Minor
Up Inspections Replacement Replacement Repair Repair



TPO 1 3 20 10 1
0.02
square
foot
1 square foot Adhesi
Transport Transport Insulation, ve felt
Resource 0.75 gallons 0.75 gallons membrane & 0.25 ballast &
Required gasoline gasoline sealant adhesive Mastic

Inspection/
Minor Clean Major Minor Major Minor
Up Inspections Replacement Replacement Repair Repair


Green
Roof 1 3 40 10

Transport Transport -
Resource 0.75 gallons 0.75 gallons Roof 0.025 roof
Required gasoline gasoline replacement replacement


USAGE Service Life Model Activity Description and Frequency


Figure 3-4.











Inspection/
Minor Clean Major Minor Major Minor
Up Inspections Replacement Replacement Repair Repair


Clay
Brick 3 5 500 25 8
1
square
foot
Pressu
re
wash,
0.02 water
square foot proofin
Transport Transport brick, 1 SF g
Resource 0.75 gallons 0.75 gallons 1 square foot waterproof material
Required gasoline gasoline brick ng I

Inspection/
Minor Clean Major Minor Major Minor
Up Inspections Replacement Replacement Repair Repair
Wood
(Two
Coats
Paint) 1 3 125 25 5
Scrape
repair,
refinish
1 square foot 0.02 SF wood + 1
Transport Transport wood + 1 + 0.02 scrape, square
Resource 0.75 gallons 0.75 gallons square foot repair, foot
Required gasoline gasoline paint refinish, paint paint

Inspection/
Minor Clean Major Minor Major Minor
Up Inspections Replacement Replacement Repair Repair


Aluminum
m Siding 2 3 80 12 5

Transport Transport -
Resource 0.75 gallons 0.75 gallons 1 square foot 0.02 square Refinis
Required gasoline gasoline siding foot Siding h paint


Continued


Figure 3-4.












Inspection/
Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
Built Up
Roof 20 1
1 square foot
membrane,
Resource insulation & 1.5% of
Required ballast roof

Inspection/
Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
TPO 20
1 square foot
insulation,
Resource membrane & 1.5% of
Required sealant roof

Inspection/
Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
Green
Roof 30 2

Resource 1 square foot 1.5% of
Required green roof roof

Inspection/
Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
Clay
Brick 500 35 12

Repoint
Resource 1 square foot 25% of Recaulk 25%
Required brick wall of wall

Figure 3-5. Athena Service Life Model Activity Description and Frequency












Inspection/
Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
Wood
(Two
Coats
Paint) 25 12 5
1 square foot
wood + 1 Recaulk
Resource square foot 25% of Scrape, sand
Required paint wall + paint

Inspection/
Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
Aluminum
Siding 35 35 12
Resource 1 square foot Recaulk
Required siding Repaint wall


Figure 3-5. Continued












Inspectio
n/ Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
Built Up
Roof 1 20 1



Resource Transportati 1 square foot
e on- 0.75 membrane, 0.3min per ft2
Require gallons insulation & roof = 1% of
d gasoline Ballast roof

Inspectio
n/ Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
TPO 1 20 1



Resource Transportati 1 square foot
e on- 0.75 insulation, 0.2min per ft2
Require gallons membrane & roof = 0.5% of
d gasoline sealant roof

Inspectio
n/ Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
Green
Roof 1 30 1


Resource Transportati
e on- 0.75 0.5 min per
Require gallons ft2 roof = 1%
d gasoline 1 square foot of roof

Figure 3-6. Dell'lsola and Kirk Service Life Model Activity Description and Frequency












Inspectio
n/ Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
Clay
Brick 3 75 15
Repoint
4
min/ft2
Resourc Transportati = 14%
e on- 0.75 mortar
Require gallons 1 square foot replace
d gasoline brick ment

Inspectio
n/ Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
Wood
(Two
Coats
Paint) 2 40 5


Resourc Transportati 1 square foot
e on- 0.75 wood + 1
Require gallons square foot 0.5 min/ft2 =
d gasoline paint 1% of wall

Inspectio
n/ Minor Major Minor Major
Clean Up Inspections Replacement Replacement Repair Minor Repair
Alumin
um
Siding 2 50 8


Resourc Transportati
e on- 0.75
Require gallons 1 square foot 2 min clean/ft2
d gasoline siding + 0.2 % of wall


Figure 3-6. Continued












Inspection/ Minor
Minor Clean Major Replaceme Major Minor
Up Inspections Replacement nt Repair Repair
Built Up
Roof 1 5 28 20 15 1

Place new
membrane Repair 25
over % of roof: Repair 2%
Transportati Transportati existing: 4 4 plies of of roof: 2
on- 0.75 on- 0.75 ply bituminou plies of
Resource gallons gallons bitmuminou s roofing + glass
Required gasoline gasoline Replace Roof s roofing insulation mopped,


Inspection/ Minor
Minor Clean Major Replaceme Major Minor
Up Inspections Replacement nt Repair Repair
TPO 1 5 25 20 1
Replace
25% of
roof:
install Repair 2%
Transportati Transportati insulation of roof:
install 150
on- 0.75 on- 0.75 + 150 mils mils
Resource gallons gallons modified modified
Required gasoline gasoline Replace Roof bitumen bitumen


Inspection/ Minor
Minor Clean Major Replaceme Major Minor
Up Inspections Replacement nt Repair Repair
Green
Roof 1 5 35 25 19 5

Repair 25
% of roof: Repair 2 %
rubberized of roof:
asphalt, rubberized
Transportati Transportati root asphalt,
barrier, root barrier,
on- 0.75 on- 0.75 filter fabric filter fabric
Resource gallons gallons and and
Required gasoline gasoline Replace Roof insulation insulation

Figure 3-7. RS Means Service Life Model Activity Description and Frequency












Inspection/ Minor
Minor Clean Major Replaceme Major Minor
Up Inspections Replacement nt Repair Repair
Clay
Brick 75 25 25


Resource Repair = Repoint =
Required Replace brick 1% of wall 80% of wall


Inspection/ Minor
Minor Clean Major Replaceme Major Minor
Up Inspections Replacement nt Repair Repair
Wood
(Two
Coats
Paint) 40 5


Scrape,
repair,
Resource Replace wood refinish +
Required + Paint paint


Inspection/ Minor
Minor Clean Major Replaceme Major Minor
Up Inspections Replacement nt Repair Repair
Aluminum
m
Siding 50 8


Resource Clean +
Required Replace siding detergent


Figure 3-7. Continued












Inspection/
Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Built Up
Roof 50
Resource
Required Replace roof


Inspection/
Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
TPO 50
Resource
Required Replace roof


Inspection/
Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Green
Roof 50
Resource
Required Replace roof


Inspection/
Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Clay
Brick 50
Resource
Required Replace wall


Inspection/
Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Wood
(Two
Coats
Paint) 50
Resource
Required Replace wall

Figure 3-8. 50 Year Static Service Life Model Activity Description and Frequency











Inspection/
Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Aluminum
Siding 50
Resource
Required Replace wall


Figure 3-8. Continued









CHAPTER 4
RESULTS

In accordance with the majority of the literature on Life Cycle Assessment,

analyses of these data showed that operating energy was the dominant factor in Life

Cycle Impact, and that each outcome essentially mirrored the results of the thermal

performance analysis derived from the energy modeling, as shown in Figure 4.1. A

second model was constructed with added focus on the relative Life Cycle Impact of the

materials. Herein, additional insulation was added to the walls and roofs to nullify the

influence of the operating energy impacts. An additional twenty-five wall and roof forms

were required given the permutations of equalizing thermal performance according to

the original three walls and three roofs. A third model was constructed to assess the

relative impact of maintenance intensity and frequency, owing to qualitative differences

in prescribed maintenance activities from model to model. As in the energy neutral

model, the coarse model used a total of thirty-six wall and roof form combinations.

Life Cycle Impact Models with Energy Differentials

Global Warming Potential

The graphs produced during the Global Warming Potential analysis produced

relatively consistent results across all five service life models. Brick was universally

shown to be the preferred wall form material. For the Athena, Dell'lsola and Kirk and 50-

Year static models, aluminum was preferred to wood as a wall form material. However,

the USACE and RS Means models show relatively little difference between the impacts

of wood and aluminum. Similarly, the green roof was preferred to the TPO membrane

and Built-Up Roof options. This order was maintained across each of the five service life

models, despite perceptible differences in magnitude. The results of the Life Cycle









Impact Models with Energy Differentials for Global Warming Potential are shown in

Figures 4-2, 4-3, 4-4, 4-5 and 4-6.

Atmospheric Ecotoxicity

In terms of Atmospheric Ecotoxicity, all five energy differential models yielded the

same result. Again, brick was identified as the least harmful wall form material. In

contrast to the Global Warming Potential results, wood wall forms were preferred to

aluminum wall forms, due mostly to the qualitative differences between aluminum and

the other wall forms materials. In fact, the impacts of aluminum replacement and

maintenance are so high, that they influence the trajectories of the aluminum

combination envelopes to a greater degree than the material's operating energy

differential. All other material outcomes mirrored those of the energy modeling analysis,

with operating energy exerting the greatest influence in Life Cycle Impact.

For roofing materials, the green roof has the lowest impact, followed by the TPO

membrane and Built-Up roof. The order of both wall form and roofing materials did not

vary across all five models. However, as subsequent analysis will show, and in viewing

each individual graph, the magnitude of envelope combination impacts did vary

significantly from model to model with no effect to the respective order, as viewed in

Figures 4-7, 4-8, 4-9, 4-10 and 4-11.

Atmospheric Acidification

The results of the Atmospheric Acidification analysis show brick as the preferred

wall form material, followed by aluminum and wood. For roofing, the green roof yields

the lowest impact, followed by the TPO membrane and the Built-Up roof. This order is

maintained in each of the five service life models, although the range of impacts for

each envelope combination varies from one model to another. As in the analysis of









Global Warming Potential, these results are in accordance with those of the energy

modeling exercise, such that the trajectories are believed to be most influenced by

operating energy use impacts. The results of the Atmospheric Acidification analysis are

shown in figures 4-12. 4-13. 4-14, 4-15 and 4-16 respectively.

Life Cycle Impact Models Energy Neutral

Global Warming Potential

The results for the Global Warming Potential analysis with energy neutral building

envelopes yielded some conflicting results. The USAGE model showed brick as the

preferred wall form material, followed by wood and aluminum. For roofing materials, the

green roof had the lowest impact, followed by the built-up roof and the TPO membrane.

The order and impact of the wall forms becomes evident early on in the 500 year cycle.

However, there is only a slight difference between the built-up roof and TPO membrane,

with a visible trend becoming clear only after the first 100 years. A clearer trend is

evident in the trajectory of the green roof, which obviously has the lowest impact, as

shown in figure 4-17. In contrast, the Athena model maintained that the brick wall

yielded the lowest Global Warming Potential impact, however the aluminum wall was

preferred to the wood wall. The roofing materials also changed order from the USAGE

model to the Athena model. Although the green roof still had the lowest impact in the

Athena model, the TPO membrane was preferred to the Built-Up roof. The range of

impacts in the Athena model was also generally higher than the USAGE model, due in

part to more frequent replacement intervals and maintenance impacts. The cumulative

impacts of the Athena model are shown in Figure 4-18. The Dell'lsola and Kirk model

shows even more variance. Brick is still the lowest impact wall form material. However,

the differences between wood and aluminum are virtually indiscernible, with aluminum









resulting in a slightly lower impact over the course of the full 500 years. In terms of

roofing, the Dell'lsola and Kirk model shows only small differences between the roofing

types, with the green roof being the best option, followed by the TPO membrane and

the built-up roof. Again, the variance is largely due to the frequency of major

replacement. The results for this model are shown in Figure 4-19. The RS Means model

also indicates that brick is the best wall form material, followed by wood and aluminum.

As with the Dell'lsola and Kirk model, there are only slight differences between the

impacts of the roofing options, with the green roof resulting in a slightly lower impact

than the TPO membrane and built-up roof respectively. Again, the frequency of major

replacement and service life influenced the outcome. These differences are shown in

Figure 4-20. In accordance with the initial material impacts, the 50-Year Static model

shows brick to result in lower impact than wood and aluminum, although only slightly..

Similarly, the built-up roof is shown to be the best roofing option followed by the TPO

membrane and green roof. The order of these results essentially reflects the order of

the initial impact of each material as projected over multiple material cycles.

Consequently, the ordering of the wall and roofing material is based purely on the

frequency of the major replacement intervals. The results of the 50-year static model

are shown in Figure 4-21. Overall, the results of the Global Warming Potential analysis

reveal the importance of service life prediction in the performance of LCA. As

subsequent analyses will reveal, much of the variance in the models is attributable to

differences in replacement and maintenance frequencies.

Atmospheric Ecotoxicity

In all of the Atmospheric Ecotoxicity models, brick is identified as the lowest impact

wall form material, followed by wood and aluminum. Each of the models shows









aluminum to have the highest impact by a considerable margin due to the materials

inherent properties. For roofing, the USAGE, Athena, Dell'lsola and Kirk and RS Means

models show the green roof to have the lowest impact. In contrast, the 50-year static

model shows the Built-Up roof to have the lowest impact, followed by the TPO

membrane and the green roof. In each of the models, the effects of the roofing materials

are decisively less influential than the wall form types, as the order and magnitude of

the roofing impacts vary, and the differences are only slight. The impact of the wall

forms is much more significant, and each service life model yields the same order of

results. Graphic representations of the models for Atmospheric Ecotoxicity are shown in

Figures 4-22, 4-23, 4-24, 4-25 and 4-26.

Atmospheric Acidification

Each of the models for Atmospheric Acidification identifies brick as the least

harmful wall form material, followed by aluminum and wood. In fact, wood is shown to

be the most harmful wall form material by a considerable margin, and this is true in each

of the five models. This outcome is partly due to the transportation required for the wood

siding. In conducting the Life Cycle Assessment of this material, cedar siding was

specified to require transport from British Columbia in Canada. Essentially,

transportation distances for cedar siding were much greater than they were for either

brick or aluminum panels. With the exception of the 50-Year static model, the green roof

is the preferred roofing option, followed by the TPO membrane and the built-up roof. In

the 50-Year static model, the TPO roof has the lowest impact, followed by the green

roof and built-up roof. The ordering of the roofing materials in the 50-Year static model

is of course attributable to the fact that the service lives are equal. The model is indeed









a comparison of projected initial impacts. The results of these models is shown in

Figures 4-27, 4-28, 4-29, 4-30 and 4-31.

Life Cycle Impact Models Coarse Models

Global Warming Potential

All of the Global Warming Potential Coarse models identify brick as the least

harmful wall form material. The USAGE and RS Means models identify wood as the

second least harmful wall for material, whereas the Athena model shows that aluminum

is preferred to wood. The Dell'lsola and Kirk model shows virtually no difference in

Global Warming Potential impact for wood and aluminum. The analysis of roofing

materials is more consistent. Each of the models shows the green roof to have the

lowest impact, followed by the Built-Up roof and the TPO membrane. In effect, the order

of these results is differs from those of the energy neutral models, suggesting that the

intensity and frequency of maintenance activities influences the outcome. The results of

the coarse model analysis for Global Warming Potential are shown in Figures 4-32, 4-

33, 4-34 and 4-35.

Atmospheric Ecotoxicity

The models for Atmospheric Ecotoxicity show a mixture of results. All agree that

brick has the least impact, followed by wood and aluminum. The results of the roofing

materials show conflict between models. The USAGE, Dell'lsola and Kirk and RS

Means models show the green roof as the best material with the lowest impact.

However, the Athena model shows all of the roofs as virtually equal, with little if any

discernable difference in impact. As compared with the energy neutral models for

Atmospheric Ecotoxicity, the ordering of materials in influenced by the frequency and

intensity of maintenance activities. This is particularly true for the built-up roof, where









maintenance activities produce the most significant difference between the energy

neutral and coarse models. The results of the Atmospheric Ecotoxicity analysis are

shown in Figure 4-36, 4-37, 4-38 and 4-39.

Atmospheric Acidification

For Atmospheric Acidification, all models identified brick as the least harmful wall

form material, followed by aluminum and wood. These differences are all well

pronounced, and hold true across all models. All of the models show the green roof as

the preferred roofing system, and with the exception of the USAGE model, the TPO

model is preferred to the built-up roof. In the USAGE model, the built-up roof yields a

lesser impact than the TPO membrane, mostly due to the longer service life of the built-

up roof in this model. The results of the Atmospheric Acidification models are shown in

Figures 4-40, 4-41, 4-42 and 4-43.

Averages of Cumulative Life Cycle Impacts Models

For the purposes of identifying mean trajectories for each of the building envelope

combinations, the average value of each envelope combination was modeled for Global

Warming Potential, Atmospheric Ecotoxicity and Atmospheric Acidification. Mean

cumulative trajectories were assessed using input from the USAGE, Athena, Dell'lsola

and Kirk and RS Means energy neutral models. The results for the Global Warming

Potential analysis indicate the following order, from least harmful to most harmful: 1)

brick with green roof, 2) brick with TPO membrane, 3) brick with built-up roof, 4) wood

with green roof, 5) wood with TPO membrane, 6) aluminum with green roof, 7) wood

with built-up roof, 8) aluminum with TPO roof and 9) aluminum with built-up roof. From

this order, it is possible to determine the relative impact of the materials with respect to

other wall forms and roofs, as shown in Figure 4-44. For Atmospheric Ecotoxicity, the


100









order of the envelope combinations changes to the following: 1) brick with green roof, 2)

brick with TPO membrane, 3) brick with built-up roof, 4) wood with green roof, 5) wood

with TPO membrane, 6) wood with built-up roof, 7) aluminum with green roof, 8)

aluminum with TPO membrane and 9) aluminum with built-up roof. As with all of the

individual Atmospheric Ecotoxicity models, the impact of the aluminum and associated

envelope combinations is significantly higher than it is for the other materials, as shown

in Figure 4-45. For Atmospheric Acidification, the order of envelope materials was as

follows: 1) brick with green roof, 2) brick with TPO membrane, 3) brick with built-up roof,

4) aluminum with green roof, 5) aluminum with TPO membrane, 6) aluminum with built-

up roof, 7) wood with green roof, 8) wood with TPO membrane and 9) wood with built-

up roof, as shown in Figure 4-46.

Cumulative Life Cycle Impact Envelope Combinations

In the comparison of the five service life models, there are some notable

inconsistencies. To begin with, each service life model produced a different result for

each building envelope combination. There are several potential explanations for this

variability. First, the major replacement intervals for each service life model were

different. For example, in the USAGE model, brick replacement is suggested every 500

years, as compared with the Dell'lsola and Kirk model, which suggests that brick is

replaced every 75 years. Either scenario is plausible, yet in attempting to assess

environmental impact, the broad range of potential service life outcomes between these

two time frames leaves a lot to the imagination. In assessing these materials on a

cumulative basis, the range of potential impacts increases as time progresses, such that

the outcomes become less predictable the farther the models are projected into the

future. Subjective differences between models also contribute to the variability, with


101









some models suggesting more intense maintenance at more frequent intervals. The

production of coarse models provided some clarification in this regard, as the variability

between models was solely produced by the frequency of the major replacement

interval.

There are however other ways to view and analyze these data. In reviewing all of

the replacement and maintenance frequency estimates, each model has a relatively

consistent logic. For example, the RS Means and Dell'lsola and Kirk models are

characterized by more conservative measures of service life and maintenance. For a

single materials cycle, this provides a neat and tidy framework to conduct scenario

analyses without delving too far into the future where outcomes are likely to be less

certain as time progresses. In contrast, the USAGE model predicts materials and

assembly usage for periods of up to 500 years. In prior assessments of brick, this

seems as plausible an outcome as any, so long as the material is maintained. Yet, the

uncertainty associated with such a long term analysis makes it somewhat unrealistic,

more so when one considers the literature on building adaptation, spatial and temporal

flexibility and the concept of materials cycling.

It may be argued that the comparison of separate service life models is akin to the

comparison of different types of logic, with each model characterized by a sort of

internal rationale. It is in this way that the comparison of different building envelope

combinations across model type may reveal another type of variability altogether. A

tendency toward conservative estimates for example may belie the true behavior of the

materials. In many ways, it seems reasonable to combine the logic of the different

models, or at least consider the possibility that one has accurately predicted the service


102









life intervals for one material, and produced an inaccurate estimate for another.

Likewise, it must be considered that the USAGE one may be accurate for some of its

maintenance activities, and deficient as to the corresponding major replacement

intervals. As the graphs for each of the building envelope combinations illustrate, there

are a broad range of service life cycle impacts conceivable at each and every iteration

of a potential material cycle. There is little rhyme or reason to this variation. Rather, if

there is a consistent finding in the analysis of different building envelope combinations,

it is that the outcome of any given building is distinctly unclear, with uncertainty

increasing as time progresses. This is true across each combination of building

envelope materials, and across each metric of environmental impact. Figures 4-47

through 4-73 are illustrative of this point.

Life Cycle Impact Per Year Individual Materials

The effects of the individual materials were also extracted from each of the five

service life models. Much of the literature on Life Cycle Assessment on buildings points

toward a need to assess the functional unit as a process, rather than a product. It is

believed that the analysis of each individual material herein is representative of this

logic, in that the results were derived as the material was part of a process. Moreover,

the results of the individual material analyses in this document are not possible without

first performing energy modeling of the materials as part of a larger system, making

adjustment to wall forms and roofing types to equalize thermal efficiency, comparing

maintenance oriented models with coarse models, and examining the relative

differences between assembly and envelope combinations. Ultimately, the results of the

individual materials are properly part of a larger system or process.


103









Global Warming Potential

For wall form materials, a considerable amount of overlap is seen in the range of

Life Cycle Impact per year. For aluminum, the range of Global Warming Potential

Impact is from 1,781 kg of C02 equivalent to 3,279 kg of C02 equivalent. For brick, the

range is 219 kg of C02 equivalent to 1,580 kg of C02 equivalent. The range for wood is

855 kg of C02 equivalent to 3,536 kg of C02 equivalent. It should be noted that there is

no overlap between the highest Life Cycle Impact per year for the brick and the lowest

Life Cycle Impact per year for the aluminum. This shows that for the five service life

models that were used, all agree that brick is a superior material to aluminum in terms

of Global Warming Potential. There is however some overlap between wood and brick

and aluminum and wood, owing partially to the relatively large range in Global Warming

Potential impacts produced by the five service life models. The results of these analyses

are shown in Figures 4-74, 4-76, and 4-78. As a point of reference, these data were

projected into trend lines of Life Cycle Impacts per year, and these graphs appear in

Figures 4-75, 4-77 and 4-79.

For roofing materials, overlap is evident in each of the material ranges. The range

for the green roof was from 457 kg of C02 equivalent to 963 kg of C02 equivalent. For

the TPO membrane, the range of Global Warming Potential was from 358 kg of C02

equivalent to 1,254.12 kg of C02 equivalent. For the Built-Up roof, the range was from

384 to 1,160 kg of C02 equivalent. In taking the simple mean for each of these graphs,

the green roof seems to be preferred, and indeed this was the case in many of the

envelope combination assessments. However, the overlap between these models

illustrates the importance of the variability. As in the case of the wall forms, these data

were projected into linear graphs, and each of these visual representations is shown in


104









Figures 4-80, 4-81, 4-82, 4-83, 4-84 and 4-85. In figure 4-86, the mean of each model is

shown for each individual material.

Atmospheric Ecotoxicity

In terms of Atmospheric Ecotoxicity, there is no overlap between wall form

materials. The brick is shown to be the best material, followed by wood, with the highest

values for aluminum. Thus, of the five service life models examined, none have

identified sufficient amounts of variability to make the appropriate selection of materials

unclear. As with the previous sets of data, these Life Cycle Impact per year data were

projected into linear models over the course of multiple material cycles, as are shown in

Figures 4-86, 4-87, 4-88, 4-89, 4-90 and 4-91.

A less clear picture emerges from the examination of the data for roofing material,

with overlap shown amongst all three roofing materials. The range for the green roof is

from 1.43 of 2,4 Dichlorophenoxyace equivalent to 2.65 kg of 2,4 Dichlorophenoxyace

equivalent. The TPO membrane ranges from 1.28 to 4.48 kg of 2,4 Dichlorophenoxyace

equivalent, and the Built-Up roof ranges from 1.46 to 4.61 kg of 2,4 Dichlorophenoxyace

equivalent. Again, the overlap illustrates the importance of assumptions in service life.

Linear representations of this data were also produced and these shown in Figures 4-

92, 4-93, 4-94, 4-95, 4-96 and 4-97 respectively. A mean value representation for these

materials is shown in Figure 4-98.

Atmospheric Acidification

For wall form materials, a minimal amount of overlap is evident. The range for

aluminum is 312 mol of H+ equivalent to 568 mol of H+ equivalent. For the brick walls,

the range is from 37 mol of H+ equivalent to 267 mol of H+ equivalent. For wood, the

range is from 464 mol of H+ equivalent to 2,054 mol of H+ equivalent. There is no


105









overlap between the wood walls and the brick walls as projected by the five service life

models utilized in this analysis. However, there is overlap between the brick wall and

the aluminum wall, and between the wood wall and aluminum wall, such that it is not

possible to make conclusions on the material with the least impact. The data were

converted into linear projections as such and each of these ranges is shown in Figures

4-99, 4-100, 4-101, 4-102, 4-103 and 4-104.

For roofing materials, overlap is evident in each of the selected materials. The

range for the green roof is from 60 mol of H+ equivalent to 127 mol of H+ equivalent.

The range for the TPO membrane is from 55 mol of H+ equivalent to 192 mol of H+

equivalent. Finally, the range for the Built-Up roof goes from 68 mol of H+ equivalent to

277 ml of H+ equivalent. In effect, the relative impact of each of these materials is

based on the accuracy of assumption. Linear projections of these data show an

increasing range of possible outcomes as time progresses. The graphs are shown in

Figures 4-105, 4-106, 4-107, 4-108, 4-109 and 4-110. A mean measurement of each

service model for all materials is shown in Figure 4-111.

Maintenance Versus Coarse Models

In order to illustrate the differences in the maintenance effects in the five service

life models, the energy neutral models including maintenance impacts were

compared with the coarse models. Each service life model showed variation in terms of

the impact of maintenance activities. In fact, the percentage of maintenance impacts

varied with respect t the service life model that was used, and the particular

environmental indicator that was used. In comparing the outcomes of the energy neutral

and coarse models, it became evident that the order of the specific envelope

combinations changed. As presented in Figures 4-114 through 4-125, this is due to the


106










variation in percent impact of maintenance activities, and how these percent differences

further diverge across different environmental indicators.

This becomes most evident when the ranking of envelope outcomes is presented

in tabular format, and the ordering of envelope combinations varies between the energy

differential models, the energy neutral models, and the coarse models. In comparing

just the ranking of the energy neutral models and the coarse models, it becomes clear

that both maintenance activity frequency and intensity, as assumed by service life

model, have a direct bearing on the outcome and ranking of different envelope options.

These rankings are presented in Figures 4-126 through 4-137.



Energy Consumption of Building Envelope

Combinations

70,100

70,000

69,900

69,800

69,700
BTU per Sqare Foot
69,600
Per Year
69,500

69,400

69,300

69,200 -- -- -- -- -- -- -- -- -- -
69,200
69,100 -,--- o--- --- --- ---- --- --- --- ---

I I- CD I I- CD I I- CD
E l I | I I ._ |I
S9,1 0 0 0
E o
E E 0 0 0
< -z -z 0C

Envelope Combination
Figure 4-1. Energy Consumption of Building Envelope Combinations


107












Global Warming Potential (TRACI) USACE

6,000,000


5,000,000


4,000,000

KG of CO2
KG 023,000,000
Equivalent

2,000,000


1,000,000


0


0 Ln 0 Ln 0LnDLnDLnDLnDLnD Ln Ln Ln
r4 Ln rN~ 0 r4 U1 rN~ 0 r U1 r, 0 r-4 Ln rN~ 0 r\4 Ln rN

Years


-AL GR A

- AL TPO A

--- ALBUR A

- BRGR_A

- BR TPO A

- BR BUR A

-WD1 GR A

- WD1 TPO A

WD1 BUR A


-igure 4-2. Global Warming Potential USAGE Energy Differential



Global Warming Potential (TRACI) Athena

6,000,000 i


5,000,000


4,000,000


KG of CO2
KG 023,000,000
Equivalent


2,000,000


1,000,000


0


-AL GR A
- ALTPO_A

- AL BUR A

- BRGR_A

- BR TPO A

- BR BUR A

WD1 GR A

- WD1 TPO A

WD1 BUR A


0Ln LnLnnC LnCLn0LnLnCLnunuLn )Ln
SLn r\ U r r\ U Years r r\ L
Years


Figure 4-3. Global Warming Potential- Athena Energy Differential


108












Global Warming Potential (TRACI) -

Dell'lsola


6,000,000

5,000,000

4,000,000

KG of CO2
KG 023,000,000
Equivalent

2,000,000

1,000,000

0


SLn LnLnnD LnD LnD LnDLnDLn uLn )Ln
r,4 Ln r~ 0 r-4 U1 r~ 0 r U r Ln r Y r L rears

Years


- ALGR_A

- AL TPO A

- AL BUR A

- BRGR_A

- BR TPO A

- BR BUR A

- WD1 GR A

- WD1 TPO A

WD1 BUR A


Figure 4-4. Global Warming Potential Dell'lsola and Kirk Energy Differential


Global Warming Potential (TRACI) RS

Means


6,000,000

5,000,000

4,000,000

KG of C02 3,000,000 -
Equivalent

2,000,000

1,000,000

0


oLnLnLnnoLnLnoLnLnoLnuo ouLnLn
r,4 Ln r~ 0 r4 U1 r~ 0o r U1 r 0 r4 Ln r 0 r\4 Ln re
Years


- AL GR A
- AL TPO A

- AL BUR A

- BR_GR_A

- BR TPO A

- BR BUR A

- WD1_GR_A

- WD1 TPO A

WD1 BUR A


Figure 4-5. Global Warming Potential Dell'lsola and Kirk Energy Differential


109


I"'
Irl

I "












Global Warming Potential (TRACI) 50-Year

Static


6,000,000


5,000,000


4,000,000

KG of C02
KG 023,000,000
Equivalent

2,000,000


1,000,000


0


Ln Ln LnC Ln 0 Ln 0 Ln 0 Ln Ln Ln Ln
4N Ln r, 0 fN 4n U1 rO 0N rn 1 rC 0N Ln rO 0 4N Ln rN
Years


- ALGR_A
- AL TPO A

- ALBUR_A
- BRGR_A
- BR TPO A

- BR BUR A
- WD1_GR_A
- WD1 TPO A

WD1 BUR A


Figure 4-6. Global Warming Potential- 50-Year Static Energy Differential


Atmospheric Ecotoxicity (TRACI) USACE

25,000


20,000


15,000


10,000



5,000


0


- AL GR A

- AL TPO A
--AL BUR A
- BR GR A
- BR TPO A
- BR BUR A
- WD1 GR A
- WD1 TPO A

WD1 BUR A


On n o Lno LnO Lno Lno Lno Lno Lno0 Ln0 Ln
r-1 -1 r-1-1 r4 r4 Years,4 r4 M M M M
Years


Figure 4-7. Atmospheric Ecotoxicity USAGE Energy Differential


110


KG 2,4
Dichlorophe
noxyace
Equivalent












Atmospheric Ecotoxicity (TRACI) Athena


KG 2,4
Dichlorophe
noxyace
Equivalent


25,000


20,000


15,000


10,000


5,000


0


- AL GR A
- ALTPO_A
- AL BUR A
- BR GR A
- BR TPO A
- BR BUR A

-WD1 GR A
- WD1 TPO A

WD1 BUR A


0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln
r-1 r-1 11 or- n r r- o rj M M o M Me
Years


Figure 4-8. Atmospheric Ecotoxicity- Athena Energy Differential


Atmospheric Ecotoxicity (TRACI) Dell'lsola

and Kirk


25,000


20,000


15,000


10,000


5,000


0


o0 Lt 0 L 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 L
r-1 r-1 -1 -1 Y4 rs4 r4 r M M M 0
Years


ALGR_A
ALTPO_A
AL BUR A

BR GR A
BR TPO A
BR BUR A

WD1 GR A
-- WD1 TPOA

0 0 WD1 BUR A
0 ron LAt r
Sl- ^~l- l-^


Figure 4-9. Atmospheric Ecotoxicity- Dell'lsola and Kirk Energy Differential


111


KG 2,4
Dichlorophe
noxyace
Equivalent


.












Atmospheric Ecotoxicity (TRACI) RS Means


KG 2,4
Dichlorophe
noxyace
Equivalent


25,000


20,000


15,000


10,000


5,000


0


- AL GR A

- AL TPO A
- AL BUR A
- BR GR A

BR TPO A
- BR BUR A

-WD1 GR A

- WD1 TPO A

WD1 BUR A


r-1 1Z -1 1Z -1 1Z -1 1Z -1 1Z -1 1Z -q 1Z -q w. -q w. -q w.
r14J un r, 0 r14 un r, 0 r14 un r, 0 r14 un r, 0 r14 U1 r
Yrea Of4 r-s-4 M M OM M
Years


Figure 4-10. Atmospheric Ecotoxicity Dell'lsola and Kirk Energy Differential


Atmospheric Ecotoxicity (TRACI) 50-Year

Static


KG 2,4
Dichlorophenoxya
ce Equivalent


25,000


20,000


15,000


10,000


5,000


0


o Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln C
r-1 r~-l- r-or-4 4 nar-4 o M M M mM
Years


- ALGR_A

AL TPO A
AL BUR A
F -

I --BR GR A

- --BR TPO A
BR BUR A

WD1 GR A
WD1_TPO_A

/ WD1 BUR A
trU


Figure 4-11. Atmospheric Ecotoxicity 50-Year Static Energy Differential


112


I


I


'


~-~"P~.












Atmospheric Acidification (TRACI) USACE

2,500,000



2,000,000 ALGRA

AL TPO A
1,500,000 --AL BUR A
mol of H+
BR GR A
Equivalent
1,000,000 ..... .. BRTPO_A

.BR BUR A

500,000 WD1_GRA
WD1 TPO A

0 WD1 BUR A
0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 LnU 0 Ln 0 Lnu
r14 t t-n l l t0 r14 U N l rl 0 r14 U N O l0r1 un 0 r-1 Lu N

Years



Figure 4-12. Atmospheric Acidification USACE Energy Differential



Atmospheric Acidification (TRACI) Athena

2,500,000



2,000,000 ALGRA

AL TPO A
1,500,000 AL BUR A
mol of H +
Equivalent BR -GRA
1,000,000 BR_TPO_A
-BRBUR A

500,000 WD1_GRA
WD1 TPO A

WD1 BUR A
0
0 Ln Ln Ln Ln LnLn Ln Ln Ln Ln
N LnU C r\ nr-o U r\ 0 r U1 r C r4 ULnr C r-o Ln r
u 4 u 4 ou o on rm n M M o M M
Years



Figure 4-13. Atmospheric Acidification- Athena Energy Differential


113











Atmospheric Acidification (TRACI) -

Dell'lsola and Kirk

2,500,000


2,000,000 ALGRA
AL TPO A

1,500,000 --- AL_BUR_A
mol of H+
-BR GR A
Equivalent
1,000,000 BR TPO A

BR BUR A
500,000 -WD1 GRA
-WD1 GR A
WD1_TPO_A
ooooLnooooLnoLnLnLnn WD1 BUR A

Years


Figure 4-14. Atmospheric Acidification- Dell'lsola and Kirk Energy Differential


Atmospheric Acidification (TRACI) RS

Means

2,500,000


2,000,000 ALGR_A
AL TPO A
1,500,000 -- ALBUR_A
mol of H+
BR GR A
Equivalent
1,000,000 BR_TPO_A

BR BUR A
500,000 WD1 GR A

-WD1 TPO A
0 WD1 BUR A
rU1 Un C 0 U14 U 0 0 r1UJ Ul r, 0 rU1 Ul r,
Years


Figure 4-15. Atmospheric Acidification Dell'lsola and Kirk Energy Differential


114







































Figure 4-16.


Atmospheric Acidification 50-Year Static Energy Differential


Global Warming Potential (TRACI) -

USACE


3,500,000

3,000,000

2,500,000

2,000,000

1,500,000

1,000,000

500,000 __
,;;;......; ;...... ..
0
0 UL 0 Ul 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln
rf4Ln rU 0o r-4 U1 Nr 0 r4l U1 Nro 0 r4Ln U 0 r\4 Lnu1~

Years


-AL GR A
-ALTPO_A
---ALBUR A

- BR GR A

- BR TPO A

- BRBUR_A
-WD1 GR A
-WD1 TPO A

WD1 BUR A


Figure 4-17. Global Warming Potential USAGE Energy Neutral


115


Atmospheric Acidification (TRACI) 50-

Year Static

2,500,000


2,000,000 AL_GR_A
AL TPO A

1,500,000 AL_BUR_A
mol of H+
BR GR A
Equivalent -
1,000,000 BR TPO A

-BR BUR A
500,000 -M-- WD1 GR A

WD1 TPO A

0~000Ln0 0o0Ln ~0 oLn o L WD1_BUR_A
SLn or0 r\ Ln r 0 r\ Ln ur Ye a rs\l u r r\l u1 r
Years


KG of C02
Equivalent












Global Warming Potential (TRACI) -

Athena


3,500,000

3,000,000

2,500,000


KG of C02 2,000000
Equivalent 1,500,000


1,000,000

500,000

0


r- r- r-- r r-Yea rs
Years


- AL GR A

- ALTPO_A
- AL BUR A
-B-G R-
- BR GR A

- BR TPO A

- BR BUR A

WD1 GR A

- WD1 TPO A

WD1 BUR A


-igure 4-18. Global warming Potential Athena Energy Neutral


Global Warming Potential (TRACI) -

Dell'lsola and Kirk


3,500,000

3,000,000

2,500,000

2,000,000
KG of C02000000
Equivalent 1,500,000

1,000,000

500,000

0


I-----*-
.... -ONO i



O Ln0 Ln0 Ln0 Ln0 Ln0 Ln0 Ln0 Ln0 Ln0 Ln
r14 un r, 0 r1J4 U1 r, 0 r1J4 un N 0 1 C 4 rJ u 0 C 14 rJ u
r-1 -1f r-1 -1 n r1 Oe rs rm M M M O
Years


-AL GR A

-ALTPO_A

-AL BUR A
-B-G R-
- BR GR A

- BR TPO A

- BR BUR A

---WD1GR_A

-WD1 TPO A

WD1 BUR A


Figure 4-19. Global Warming Potential Dell'lsola and Kirk- Energy Neutral


116












Global Warming Potential (TRACI) RS

Means

3,500,000

3,000,000
-AL GR A
2,500,000 -AALTPO_A

-A L_BUR_A
KG of CO2 2,000,000 ALBURA
Equivalent -
Equivalent 1,500,000 M BRTPOA
BR TPO A

1,000,000 BR_BUR_A
-WD1 GR A
500,000
WD1_TPO_A
0 WD1 BUR A
r-4 Ln r, 0 r- 4 U1r 0l r U1r 0n r-4o Ln r 0 or\4 uLn r
~ r-4 r4 r-4 4m mm m M
Years

Figure 4-20. Global Warming Potential RS Means Energy Neutral


Global Warming Potential (TRACI) 50-

Year Static


"ii=""""";; "
..........
...............-.


- r-r- nr- r Years- m
Years


-AL GR A

- AL TPO A

- AL BUR A

- BR GR A

- BR TPO A

- BRBUR_A

--WD1_GR_A

- WD1 TPO A

WD1 BUR A


Figure 4-21. Global Warming Potential 50-Year Static Energy Neutral


117


KG of C02
Equivalent


3,500,000

3,000,000

2,500,000

2,000,000

1,500,000

1,000,000

500,000

n


v


0












Atmospheric Ecotoxicity (TRACI) USACE

25,000


20,000


15,000


10,000


5,000


0


- AL GR A

- AL TPO A

- AL BUR A

- BR GR A

- BR TPO A

- BR BUR A
- WD1_GR_A

- WD1 TPO A

WD1 BUR A


Figure 4-22. Atmospheric Ecotoxicity USAGE Energy Neutral



Atmospheric Ecotoxicity (TRACI) Athena

25,000 1


KG 2,4
Dichlorophenoxya
ce Equivalent


20,000



15,000



10,000



5,000



0


- AL GR A

- AL TPO A
--AL BUR A
-G R-
- BR_GR_A

- BR TPO A

- BR BUR A
- WD1 GR A

- WD1 TPO A

WD1 BUR A


0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln
r-r- nr- r Years- m
Years


Figure 4-23. Atmospheric Ecotoxicity Athena Energy Neutral


118


KG 2,4
Dichlorophe
noxyace
Equivalent


r-1r1N11 ar r-s rj mm mm o
Years


i


T


I~"~"""""

-~Pa~












Atmospheric Ecotoxicity (TRACI) Dell'lsola

and Kirk


KG 2,4
Dichlorophenoxya
ce Equivalent


25,000


20,000


15,000


10,000


5,000


0


- r-r- nr- r Yearsrmm
Years


- AL GR A

- AL TPO A
- ALBUR_A

- BRGR_A

- BR TPO A

- BR BUR A

I WD1_GR_A

- WD1 TPO A

WD1_BUR A


-igure 4-24. Atmospheric Ecotoxicity Dell'lsola and Kirk- Energy Neutral


Atmospheric Ecotoxicity (TRACI) RS

Means


KG 2,4
Dichlorophenoxya
ce Equivalent


25,000


20,000


15,000


10,000


5,000


0


r4 Lnr o r4 Lnr- 0 r4 YLn r-s r4 Lnr 0 r\ U1 r,
-i rea r-4 rs 4mmmm
Years


-AL GR A

- AL TPO A
- AL BUR A
-G R-
- BR_GR_A

BR TPO A
- BR BUR A

I WD1 GR A

- WD1_TPO_A

WD1 BUR A


Figure 4-25. Atmospheric Ecotoxicity RS Means Energy Neutral


119











Atmospheric Ecotoxicity (TRACI) 50-Year Static


12,000


10,000


8,000


6,000

4,000


2,000


Years200 300 400
Years


Figure 4-26. Atmospheric Ecotoxicity 50-Year Static Energy Neutral


Atmospheric Acidification (TRACI) USACE

1,200,000 i


1,000,000


800,000


600,000


400,000


200,000


0


- AL GR A
- AL TPO A
- AL BUR A

- BR_GR_A
- BR TPO A
- BR BUR A

- WD1_GR_A
- WD1 TPO A

WD1 BUR A


0-r~ ~N~CrJu ~ ~ ~N~CrJu I \ ~N


O Lnt0 Lnt0 Lnt0 Lnt0 Lnt0 Lnt0 Ln Ct" nO~ O M Ln0 Ult
r-1r- -1 nr-1 -1O rO4 rs m M M M M
Years


Figure 4-27. Atmospheric Acidification USAGE Energy Neutral


120


KG 2,4
Dichlorophenoxy
ace Equivalent


mol of H+
Equivalent


............... ... :,iiii.............. ..
.... ...... ::::::::.l i
j~ ............. :::....:::.












Atmospheric Acidification (TRACI) -

Athena


0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln

Years


- AL GR A

- AL TPO A

- AL BUR A

- BR GR A

- BR TPO A

- BR BUR A

- WD1_GR_A

- WD1 TPO A

WD1 BUR A


Figure 4-28. Atmospheric Acidification Athena Energy Neutral



Atmospheric Acidification (TRACI) -

Dell'lsola and Kirk

1,200,000


1,000,000 ALGRA

-AL TPO A
800,000 AL-TPO-
OW AL_BUR_A
mol of H+
600,000 ------ BR GR A
Equivalent -
S- BR TPO A
400,000 -RB _
,.,. BR BUR A

200,000 WD1-GR-A
WD1 TPO A
0 WD1 BUR A
0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln
r-4 Ln r, 0 r-4 U1r, 0l r4 U1 rNl 0 r~or, 0n N~or\J uLnr

Years

Figure 4-29. Atmospheric Acidification Dell'lsola and Kirk- Energy Neutral


121


mol of H +
Equivalent


1,200,000

1,000,000

800,000

600,000

400,000

200,000

n


Ind

9111
'pi
--------f----, -
,f-


I


0











Atmospheric Acidification (TRACI) RS

Means


1,200,000

1,000,000

800,000

600,000

400,000

200,000

0


O Ln0 Ln0 Ln0 Ln0 Ln0 Ln0 Ln0 Ln0
r-rN1 4 r4r-o r mm mm M
Years


-AL GR_A
s -ALTPOA
-'ALBUR_A
--BRGR_A
-BR TPO A
1 -BR_BUR_A
S -- WD1_GR_A
-WD1 TPO A
o- 0 LWD1_BURA
r4 Jn rN
^l-bl^l


Figure 4-30. Atmospheric Acidification RS Means Energy Neutral


Figure 4-31. Atmospheric Acidification 50-Year Static Energy Neutral


122


mol of H+
Equivalent


r~~J u~ N~ C r\J u~ N~ C r~J u~ N~ C r~J u~ N~ C


Atmospheric Acidification (TRACI) 50-

Year Static


- 600,000

S500,000

400,000 mol of H+
Equivalent
300,000
200,000
100,000
0


400 500
100 200 300
Years


- ~I~CCI


-

-


Ldw












Global Warming Potential (TRACI) -

USACE Coarse Model


1,400,000

1,200,000

1,000,000

kg of C02 800,000
equivalent 600,000

400,000

200,000

0


r- r- r- r Years r
Years


-AL GR A
-ALTPO A
-AL_BUR_A
-BR GR A
-BR TPO A

S-BR BUR A

-WD GR A
omomn -WD TPO A
o r\ In -- -
WDBUR A


Figure 4-32. Global Warming Potential USAGE Coarse Model



Global Warming Potential (TRACI) -

Athena

3,500,000

3,000,000
AL GR A
2,500,000 AL TPO A

-,71 -AL BUR A
2,000,000 -------- a -
KG of C2 2,000,000
-BR GR A
Equivalent -or ---BRGRA
1,500,000
BR TPO A
1,000,000 BR BUR A
SWD1 GR A
500,000 -W 1_GR_A
WD1_TPOA
0
oLnomoLnomoLnomoLnomoLnL n WD1 BUR A
r4 Lnr 0o r,4 Ln r 0o r,4 Ln r 0o r,4 Ln r 0o r,4 U1r
--i r-4 r14 r14 rmm mm b
Years



Figure 4-33. Global Warming Potential Athena Coarse Model


123












Global Warming Potential (TRACI) -

Dell'lsola and Kirk


3,500,000

3,000,000

2,500,000

2,000,000
KG of C02000000
Equivalent 1,500,000


1,000,000

500,000

0


.. .....







r-or-NN 1 ~or1 o r14 r4 r1omm mm b
Years


- ALGR_A

- ALTPO_A
--AL BUR A
-G R-
- BR GR A

- BR TPO A

- BRBUR_A

- WD1_GR_A

- WD1 TPO A

WD1 BUR A


Figure 4-34. Global Warming Potential Dell'lsola and Kirk Coarse Model


Global Warming Potential (TRACI) RS

Means Coarse Model


3,500,000

3,000,000

2,500,000

2,000,000
KG of C02 2,000,000
Equivalent 1

1,000,000

1,500,000
500,000
0-


o0o noLnoLno 0o noLnoLnoLno Ln
r-orN Yi ar4 r-s r4 mm mm o
Years


ALGR_A
ALTPO_A

AL BUR A
^ -BR GR A

BR TPO A

BR BUR A
WD1 GR A

WD1 TPO A

WD1 BUR A


Figure 4-35. Global Warming Potential RS Means Coarse Model


124












Atmospheric Ecotoxicity (TRACI) USACE


r-1 r- Nr-- rj r-jr mm mm s
Years


25,000


20,000


15,000


10,000


5,000


Figure 4-36. Atmospheric Ecotoxicity USAGE Coarse Model


Atmospheric Ecotoxicity (TRACI) -

Athena Coarse Model


KG 2,4
Dichlorophenoxy
ace Equivalent


25,000


20,000


15,000


10,000


5,000


0


I


OLnOLnOLnOLnOLnOLnOLnOLn OLn
-N r-NNr- r-4 r4 smm mm M
Years


ALGR_A

AL TPO A

AL_BUR_A
BR_GR_A
--BR TPO A

BRBUR_A
-=1
-WD1 GR A

. --WD1_TPO_A

fr-. WD1 BUR A


Figure 4-37. Atmospheric Ecotoxicity Athena Coarse Model


125


- ALGR_A
- ALTPO_A
--AL BUR A

-BR GR A
- BR TPO A

- BR BUR A
- WD1_GR_A

- WD1 TPO A

WD1 BUR A


KG 2,4
Dichlorophe
noxyace
Equivalent












Atmospheric Ecotoxicity (TRACI) -

Dell'lsola and Kirk Coarse Model


25,000


20,000

KG 2,4
15,000
Dichlorophe
noxyace 10,000
Equivalent
5,000


0


-N r-Nnr- -N r mmmm M
Title


- AL GR A

- AL TPO A

- ALBUR_A

- BR GR A

- BR TPO A
- BR BUR A

--WD1 GR A

- WD1 TPO A

WD1 BUR A


-igure 4-38. Atmospheric Ecotoxicity Dell'lsola and Kirk Coarse Model


Atmospheric Ecotoxicity (TRACI) RS

Means Coarse Model


....... ==, il



0n U 0Ln N U Nn 0 C U Nn 0 C U 0 Ln 0N U 0 Ln
-1 -1 r ON r r T m M
Title


- AL GR A

- ALTPO_A

- AL BUR A

- BR GR A

- BR TPO A

- BR BUR A

-WD1 GR A

- WD1 TPO A

WD1 BUR A


Figure 4-39.


Atmospheric Ecotoxicity RS Means Coarse Model


126


18,000
16,000
14,000
12,000
10,000
Title
8,000
6,000
4,000
2,000
0


... ...
...........
.......


,.....========il












Atmospheric Acidification (TRACI) -

USACE Coarse Model


1,200,000


1,000,000


800,000


600,000


400,000


200,000


0


- ALGR_A

- ALTPO_A

- ALBUR_A

- BR_GR_A

-BR TPO A

- BR BUR A

- WD1_GR_A

-WD1 TPO A

WD1 BUR A


Figure 4-40. Atmospheric Acidification USAGE Coarse Model


Atmospheric Acidification (TRACI) -

Athena


1,200,000


1,000,000


800,000


600,000


400,000


200,000

n


r,4 uh r, 0 r,4 U1 r, 0 r4 U1 r, 0 r,4 uL r, 0 r-4 uh r,
Years
Years


- ALGR_A

- ALTPO_A

-- ALBUR_A

- BR GR A
-G R-

- BR TPO A

- BR BUR_A

- WD1 GR A

- WD1 TPO A

WD1 BUR A


Figure 4-41. Atmospheric Acidification Athena Coarse Model


127


mol of H+
Equivalent


S-



S- r- -n r- Years r mm
Years


mol of H +
Equivalent


0-
JI

,5-.:


I


0












Atmospheric Acidification (TRACI) -

Dell'lsola and Kirk


1,200,000

1,000,000

800,000

mol of H+
600,000
Equivalent

400,000

200,000

0


r--1 O-r- -1 r4 r r4 r4 M M MM
Years


-ALGR_A

-AL TPO A

--AL_BURA
-BR GR A
-BR TPO A

-BR BUR A

WD1 _GR A

S WD1_TPO_A

D r-. WD1 BUR A
bbbi ^- i


-igure 4-42. Atmospheric Acidification Dell'lsola and Kirk Coarse Model


Atmospheric Acidification (TRACI) RS

Means Coarse Model


1,200,000

1,000,000


800,000

mol of H+
600,000
Equivalent

400,000

200,000


0


0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln 0 Ln
r-1 r-1 11 or4 r 4r-4o M Mr nM o Ma
Years


-AL GR A

-AL TPO A

-AL BUR A
S--BRGR_A

-BR TPO A
-BR_BUR_A
--WD1GR A

-WD1_TPO_A

WD1 BUR A


Figure 4-43. Atmospheric Acidification- RS Means Coarse Model


128


I FEW












Global Warming Potential (TRACI) All

Models


3,500,000

3,000,000

| 2,500,000
.2
S2,000,000
LU
O 1,500,000

( 1,000,000

500,000

0


Ln Ln LnC Ln 0 Ln 0 Ln 0 Ln Ln Ln Ln
r--- 1O 1 r- -1- r1 r J m M M M M
Years


- AL GR AVERAGE
- ALTPOAVERAGE
- AL BUR AVERAGE

- BR GR AVERAGE
- BR TPO AVERAGE

- BRBURAVERAGE
--WD GR AVERAGE

- WD TPO AVERAGE

WD BUR AVERAGE


-igure 4-44. Global Warming Potential All Models Energy Neutral


Atmospheric Ecotoxicity (TRACI) All

Models


16,000

14,000

12,000

10,000

Title 8,000

6,000

4,000

2,000

0


0 Ln Ln C Ln iLn CLn 0 Ln CLn 0 Ln CLn 0 Ln
r- r- r r Title
Title


Figure 4-45.


- AL GR AVERAGE

- AL TPO AVERAGE

- AL BUR AVERAGE
- BRGRAVERAGE
- BR TPO AVERAGE

- BR BUR AVERAGE

--WD GR AVERAGE

- WD TPO AVERAGE

WD BUR AVERAGE


Atmospheric Ecotoxicity All Models Energy Neutral


129












Atmospheric Acidification (TRACI) All

Models


Ln Ln LnC Ln 0 Ln 0 Ln 0 Ln Ln Ln Ln
4N Ln r~ 0 r4 U1n r~ 0 rC U1n r~ 0 r4 Ln r~ 0 rC 4 Ln rN
N O- r ON r4 Nm rO m M M
Years


- AL GR AVERAGE

- AL TPO AVERAGE

- AL BUR AVERAGE

- BR_GRAVERAGE
- BR TPO AVERAGE

- BRBURAVERAGE

- WDGRAVERAGE

- WD TPO AVERAGE

WD BUR AVERAGE


Figure 4-46.


Atmospheric Acidification All Models Energy Neutral


Global Warming Potential (TRACI) -Aluminum

Panel with Green Roof
3,500,000

3,000,000
AL_GR_RS MEANS


2,500,000
2,500,000 AL_GR_ARMY


KG of C2 2,000000 ALGR ATHENA
Equivalent 1,500,000
1,500,000 _AL_GR_50

1,000,000 ALGRDELL'ISOLA

500,000

0
0 Ln Ln C Ln iLn Ln C Ln i Ln C Ln i Ln C Ln C
-4 ULnr,-- o rr-4 U1 r- 0 r-4 U1 r- 0 1 Ln r, -0 r1 Lnr,- o
t t -i- r- 4 r-4 -4 mM M m M M Ln
Years
Figure 4-47. Global Warming Potential Aluminum with Green Roof Energy Neutral


130


800,000

700,000

600,000

500,000

400,000

300,000

200,000

100,000

0












Global Warming Potential (TRACI) -

Aluminum Panel with TPO Roof

3,500,000

3,000,000

2,500,000 -ALITP

2,000,000

1,500,000 AL_TP
-AL TP

1,000,000 AL_TP
AL TPo
500,000 .

0'
r4 uLn r- 0 r4 uLn r- 0 r4 uLn r- 0 r4 uLnr- 0 r\4 uLnr 0o
t- 4 r1 rl er1smm mm b Ln
Years


O_RS MEANS
O ARMY
O ATHENA
O DELL'ISOLA
0 50


-igure 4-48. Global Warming Potential Aluminum with TPO Roof Energy Neutral


Global Warming Potential (TRACI) -

Aluminum Panel with Built-Up Roof

3,500,000

3,000,000

2,500,000

-AL BU
KG of C02 2,000,000 AL
-AL BU
Equivalent 1,500,000 AL
AAL BU
1,000,000 AL_BL

500,000 ALBL

0
O Ln O Ln O Ln O Ln O Ln O Ln O Ln O Ln O Ln O Lno
r- Ln r r-4 Uo rl L r-4 Uo r- 0 r-4 oLn rC r-4 oLn r o
Years


IRRS MEANS
IR ARMY
IR ATHENA
IR_DELL'ISOLA
IR 50


Figure 4-49. Global Warming Potential Aluminum with Built-Up Roof Energy Neutral


131


KG of C02
Equivalent












Global Warming Potential (TRACI) Brick

with Green Roof


3,500,000

3,000,000

2,500,000

2,000,000
KG of C02000000
Equivalent 1,500,000


1,000,000

500,000


-- r


OuL)OuL)OuOunOunOuLn Ln Ln Ln OLnO
r1 uLnr 0o r4 Lnr 0o r4 Lnr 0o r1 U1 rY 0 r\ U1 r, 0
t-i--i-i r-4 r-4 r4J r4J mm mm b Ln
Years


- BR GR RS MEANS

- BR GR ARMY

BR GR ATHENA

- BR GR DELL'ISOLA

-BRGR_50


-igure 4-50. Global Warming Potential Brick with Green Roof Energy Neutral


Global Warming Potential (TRACI) Brick

with TPO Roof


3,500,000

3,000,000

2,500,000
2,000,000
KG of C02 2,000,000
Equivalent 1,500,000
1,500,000


1,000,000

500,000

0


- BR TPO RS MEANS
- BR TPO ARMY

BR TPO ATHENA

- BRTPODELL'ISOLA

BRTPO_50


- -


0Ln0Ln0Ln0Ln0Ln0Ln0Ln0Ln0Ln0Lno
r,4 uLn r- 0 r,4 U1 r 0 r s1r 0nC r4 Lnr 0 r\4 Lnr, 0
r-1 -1 -1 -1f r4 r4 r4 r4 Nmm mm rLn
Years


Figure 4-51. Global Warming Potential Brick with TPO Roof Energy Neutral


132












Global Warming Potential (TRACI) Brick

with Built-Up Roof


3,500,000

3,000,000

2,500,000


KG of C02 2,000000
Equivalent 1,500,000

1,000,000

500,000

0


- BR BUR RS MEANS
- BR BUR ARMY

BR BUR ATHENA

-BRBURDELL'ISOLA
- BR BUR 50


r1 Ln r-0 r Ln r- r ul Years- rul) r\ Lnr 0
t- -l -l -lr rJ rJ rJ mm mm b Ln
Years


-igure 4-52. Global Warming Potential Brick with Built-Up Roof Energy Neutral


Global Warming Potential (TRACI) Wood

with Green Roof


3,500,000

3,000,000

2,500,000

2,000,000
KG of C02 2000000
Equivalent 1,500,000

1,000,000

500,000

0


- WD GR RS MEANS

- WD GR ARMY

WD GR ATHENA
- WD GR DELL'ISOLA

-WD GR 50


O0 Ln 00 Ln 0Ln0Ln 0Ln 0Ln0LnOLn Ln Ln
rl Ln r-o 0 r\ l l rN 0 r\4l Nro 0 r\ Ln or 0 r\l uLn r 0
---- r MM Years r mm
Years


Figure 4-53. Global Warming Potential Wood with Green Roof Energy Neutral


133












Global Warming Potential (TRACI) Wood

with TPO Roof


3,500,000

3,000,000

2,500,000

2,000,000
KG of C02000000
Equivalent 1,500,000


1,000,000

500,000

0


- WD TPO RS MEANS

- WD TPO ARMY

WD TPO ATHENA
- WD TPO DELL'ISOLA

WD TPO-50


r1 uLnr 0 or\ uLnr, 0 r lu r, 0 r1 lu r, 0 r1 l re 0
---- r r re rmm mm Ln
Years


-igure 4-54. Global Warming Potential Wood with TPO Roof Energy Neutral


Global Warming Potential (TRACI) Wood

with Built-Up Roof


3,500,000

3,000,000

2,500,000

KGof2 2,000,000
Equivalent 1,500,000


1,000,000

500,000

0


- WD BUR RS MEANS
- WD BUR ARMY

WD BUR ATHENA
- WDBURDELL'ISOLA
- WD BUR 50


oLnoLnOLnOLnOLnOLnOLnOLn OLn no
r4 Ln r-~ 0 r\4 U1 r 0 r4 U1 r 0 r-4 Ln s r-4 Lnr 0
Years


Figure 4-55. Global Warming Potential Wood with Built-Up Roof Energy Neutral


134


:1-











Atmospheric Ecotoxicity (TRACI)

25,000


20,000


15,000


10,000


5,000


0


- AL GR RS MEANS
-AL GR ATHENA
AL GR 50
-AL GR DELL'ISOLA
- ALGRARMY


Years


-igure 4-56. Atmospheric Ecotoxicity Aluminum with Green Roof Energy Neutral


Atmospheric Ecotoxicity (TRACI)

25,000


20,000 -


OLnOLnOLnOLnOLnOLnOLnOLnOLnOLno

Years


- AL TPO RS MEANS
- AL TPO ARMY
AL TPO ATHENA
- ALTPODELL'ISOLA
AL TPO 50


Figure 4-57. Atmospheric Ecotoxicity Aluminum with TPO Roof Energy Neutral


135


KG 2,4
Dichlorophe
noxyace
Equivalent


KG 2,4
Dichlorophe
noxyace
Equivalent


15,000


10,000


5,000


0











Atmospheric Ecotoxicity (TRACI)


KG 2,4
Dichlorophe
noxyace
Equivalent


25,000


20,000


15,000


10,000


5,000


0


7


Iraw
CC


- AL BURRS MEANS
- ALBURARMY
AL BUR ATHENA
- AL BUR DELL'ISOLA
- AL BUR 50


r-I-rh--lrr h rNN r mm tmm t t-

Years


-igure 4-58. Atmospheric Ecotoxicity Aluminum with Built-Up Roof Energy Neutral


Atmospheric Ecotoxicity (TRACI)


KG 2,4
Dichloropheno
xyace
Equivalent


25,000


20,000


15,000


10,000


5,000


0


- BR GR RS MEANS
- BR GR ARMY
- BR GR ATHENA
- BR GR DELL'ISOLA
-BR GR 50


- Yearsmmmm b

Years


Figure 4-59. Atmospheric Ecotoxicity Brick with Green Roof Energy Neutral


136


.


i


-


I











Atmospheric Ecotoxicity (TRACI)

25,000


20,000


15,000


10,000


5,000


0


I


- BR TPO RS MEANS
- BR TPO ARMY
DBR TPO ATHENA
- BR TPO DELL'ISOLA
- BR TPO 50


OLOL OLOLOLOLOYears O

Years


Figure 4-60. Atmospheric Ecotoxicity Brick with TPO Roof Energy Neutral


Atmospheric Ecotoxicity (TRACI)


KG 2,4
Dichlorophe
noxyace
Equivalent


25,000


20,000


15,000


10,000


5,000


0


- BR BUR RS MEANS
BR BUR ARMY
BR BUR ATHENA
-BR BUR DELL'ISOLA
BR BUR 50


Yeasmmmm

Years


Figure 4-61. Atmospheric Ecotoxicity Brick with Built-Up Roof Energy Neutral


137


KG 2,4
Dichlorophe
noxyace
Equivalent


-



















KG 2,4
Dichlorophe
oxyace
Equivalent


Atmospheric Ecotoxicity (TRACI)

25,000


20,000


15,000WD
-WD
n
-WD
10,000 WD

-WD
5,000 W
WD


0


Years


GR RS MEANS
GRARMY
GR ATHENA
GR DELL'ISOLA
GR 50


Figure 4-62. Atmospheric Ecotoxicity Wood with Green Roof Energy Neutral


Atmospheric Ecotoxicity (TRACI) ARMY

25,000


20,000


2,4 15,000 WDTPORS
rophen
face WD_TPO_AF
/alent '10,00 WD TPO AT
WD TPO DE
5,000 WD_TPO-50


0


Years


MEANS
RMY
rHENA
ELL'ISOLA


Figure 4-63. Atmospheric Ecotoxicity Wood with TPO Roof Energy Neutral


138


KG
Dichlo
oxy
Equi












Atmospheric Ecotoxicity (TRACI) ARMY

25,000


20,000


15,000


10,000


5,00


- WD_BUR RS MEANS

- WD BUR ARMY

-WD BUR ATHENA

- WD BUR DELL'ISOLA

-WDBUR_50


0
0


Years


Figure 4-64. Atmospheric Ecotoxicity Wood with Built-Up Roof Energy Neutral


Atmospheric Acidification (TRACI) -

Aluminum Panel with Green Roof


1,200,000


1,000,000


800,000


600,000


400,000


200,000

n


O Ln0 Ln0 Ln0 Ln0 Ln0 Ln0 Ln0 Ln0 Ln0 Ln0
r,4 Ln n 0 r -4 U1) r 0 r -4 U1 r, 0 r-4 Ln r 0 r-4O Lnr, 0o
r Years r r M M Ln
Years


- AL GR RS MEANS

- AL GR ATHENA

- AL GR 50

- AL GR DELL'ISOLA

- ALGRARMY


Figure 4-65. Atmospheric Ecotoxicity Aluminum with Green Roof Energy Neutral


139


KG 2,4
Dichlorophen
oxyace
Equivalent


mol of H+
Equivalent


0












Atmospheric Acidification (TRACI) -

Aluminum Panel with TPO Roof


1,200,000

1,000,000

800,000

600,000

400,000

200,000

0


OlOLOLnOOOOOOYearsLnO
Years


- AL TPO RS MEANS

- ALTPOARMY
AL TPO ATHENA

-AL TPO DELL'ISOLA
-AL TPO 50


-igure 4-66. Atmospheric Ecotoxicity Aluminum with TPO Roof Energy Neutral


Atmospheric Acidification (TRACI) -

Aluminum Panel with Built-Up Roof


1,200,000


1,000,000


800,000


600,000


400,000


200,000


0 -


OLnOLnOLnOLnOLnnYears
Years


- ALBURRS MEANS
- ALBURARMY

-AL BUR ATHENA
- AL_BUR_DELL'ISOLA

AL_BUR_50


Figure 4-67. Atmospheric Ecotoxicity Aluminum with Built-Up Roof Energy Neutral


140


mol of H+
Equivalent


mol of H+
Equivalent


1.












Atmospheric Acidification (TRACI) -

Brick with Green Roof

1,200,000

1,000,000

800,000
BR GR RS MEANS
mol of H+
600,000 -BRGR ARMY
Equivalent
BR GR ATHENA
400,000
BR GR DELL'ISOLA

200,000 BR_GR_50



rLnro')NlLONr~lONr--or LnrlO')-orllr')I
-it-it-it-i mmmmbrubLn
Years

-igure 4-68. Atmospheric Ecotoxicity Brick with Green Roof Energy


Atmospheric Acidification (TRACI) -

Brick with TPO Roof

1,200,000

1,000,000

800,000
BR TPO RS MEANS
mol of H+
600,000 BRTPOARMY
Equivalent
0BR TPO ATHENA
400,000
BR TPO DELL'ISOLA
200,000 -BR TPO 50

0 --

r--O r--O l--Years-
Years


Neutral


Figure 4-69. Atmospheric Ecotoxicity Brick with TPO Roof Energy Neutral


141











Atmospheric Acidification (TRACI) Brick

with Built-Up Roof

1,200,000

1,000,000

800,000
BR BUR RS MEANS
mol of H+
molH+ 600,000 BR BUR ARMY
Equivalent
BR BUR ATHENA
400,000
BR BUR DELL'ISOLA

200,000 BR_BUR_50

0 -
tD r -4 r14 r1f rfM fM fM M ( D r L
Years

-igure 4-70. Atmospheric Ecotoxicity Brick with Built-Up Roof Energy


Atmospheric Acidification (TRACI) -

Wood with Green Roof

1,200,000

1,000,000

800,000
WD GR RS MEANS
mol of H+
Equivalent 600,000 WDGRARMY
Equivalent
SWD GR ATHENA
400,000
WD GR DELL'ISOLA
200,000 WD GR 50

0 -


Years


sleutral


Figure 4-71. Atmospheric Ecotoxicity Wood with Green Roof Energy Neutral


142




































-igure 4-72.


Atmospheric Ecotoxicity Wood with TPO Roof Energy Neutral


Atmospheric Acidification (TRACI) Wood

with Built-

Up Roof

1,200,000

1,000,000

800,000
WD_BUR RS MEANS
mol of H+
molof H+ 600,000 WD BUR ARMY
Equivalent
SWD BUR ATHENA
400,000
WDBUR_DELL'ISOLA
200,000 WD_BUR_50

0'


Years

Figure 4-73. Atmospheric Ecotoxicity Wood with Built-Up Roof Energy Neutral


143


Atmospheric Acidification (TRACI) -

Wood with TPO Roof

1,200,000

1,000,000

800,000
8-- WDTPORS MEANS
mol of H+
oEquivalet 600,000 WD TPO ARMY
Equivalent -
SWDTPOATHENA
400,000
WD TPO DELL'ISOLA

200,000 WD_TPO_50

0
OLnOLnOLnOLnOLnOLnOLnOLnOLnOLno

Years












Life Cycle Impact Per Year Global

Warming Potential Aluminum


4,000

3,500

3,000

2,500
kg of C02
equivalent 2,000 -


1,500-

1,000-

500-


ARMY
S50
-- DELL'ISOLA
SATHENA
SRS MEANS


0 -l---------

-igure 4-75. Global Warming Potential Life Cycle Impact Per Year Aluminum


Global Warming Potential (TRACI) -

Aluminum Panels


2,000,000
1,800,000
1,600,000
1,400,000
1,200,000
kg of CO2
kgof021,000,000
equivalent
800,000
600,000
400,000
200,000
0


-RS MEANS
- DELL'ISOLA
-ATHENA
-ARMY
-50
-AVERAGE


r 4 Ln o r U r 0 r U r o r4 Lnr 0 r\u Ln
0-l0lt0t-lff0ff0i0oroo^-^^-^


Figure 4-76. Global Warming Potential Life Cycle Impact Per Year Trendline -
Aluminum


144




































Figure 4-77. Global Warming Potential Life Cycle Impact Per Year Brick


Global

2,000,000

1,800,000

1,600,000

1,400,000 -

1,200,000

1,000,000

800,000 -

600,000

400,000

200,000

0


Warming Potential (TRACI) Brick


- AVERAGE
-RS MEANS
- DELL'ISOLA
ATHENA
-ARMY
-50


i=--0


O oLn o ooLnooLnooLno Ln0Ln0Ln Ln
N Ln r) 0 r-4N L1 rN, 0 rN U1 rN, 0 C N Ln rI) 0 C N Ln r,
-1 -1 -1 -1 r44 r,4 M M M M D* ^- ^-:


Figure 4-78. Global Warming Potential Life Cycle Impact Per Year Trendline Brick


145


Life Cycle Impact Per Year Global

Warming Potential Brick


4,000

3,500

3,000

2,500

kg of C02 000
2,000
equivalent
1,500


* ARMY
SATHENA
- RS MEANS
a DELL'ISOLA
S50


1,000 -


500


Title












Life Cycle Impact Per Year Global

Warming Potential Wood


4,000

3,500

3,000

2,500

kg of CO2 000
2,000equivalent
equivalent


1,500 -


1,000 -


* ARMY


S50
-- RS MEANS
DELL'ISOLA
ATHENA


500 --


Figure 4-79. Global Warming Potential Life Cycle Impact Per Year Wood


Global Warming Potential (TRACI) -

Wood


2,000,000
1,800,000
1,600,000
1,400,000
1,200,000
kg of C02
kgof021,000,000
equivalent
800,000
600,000
400,000
200,000
0


-AVERAGE
- RS MEANS
- DELL'ISOLA
-ATHENA
-ARMY
-50


O Ln0 Ln0 Ln0 Ln0 Ln 0 Ln O Ln0 Ln O Ln O Ln
r4 uLn r- 0 r4 U1 r, 0 r,4 U1 nr- 0 r4 uLn r 0 or\4 uLnr 0o
Years


Figure 4-80. Global Warming Potential Life Cycle Impact Per Year Trendline Wood


146











Life Cycle Impact Per Year Global

Warming Potential Green Roof


4,000

3,500

3,000

2,500

kg of C02 000
2,000
equivalent

1,500

1,000

500


S50
* ARMY
SATHENA
* DELL'ISOLA
" RS MEANS


[ 0 0 1

Figure 4-81. Global Warming Potential Life Cycle Impact Per Year Green Roof


Global Warming Potential (TRACI) -

Green Roof


2,000,000
1,800,000
1,600,000
1,400,000
1,200,000
kg of CO2
kgof021,000,000
equivalent
800,000
600,000
400,000
200,000
0


- AVERAGE
- RS MEANS
- DELL'ISOLA
-ATHENA
- ARMY
-50


r Ln rr Years Ur rLnr r\Ln
Years


Figure 4-82. Global Warming Potential Life Cycle Impact Per Year
Roof


Frendline Green


147



















A


Life Cycle Impact Per Year Global

Warming Potential TPO Membrane


4,000.00

3,500.00

3,000.00

2,500.00
kg of C02000.00
2,000.00
equivalent
1,500.00


1,000.00 -


500.00 -


S50


SATHENA
m DELL'ISOLA
SRS MEANS
* ARMY


0.00 P
-igure 4-83. Global Warming Potential Life Cycle Impact Per Year TPO Roof


Global Warming Potential (TRACI) -

TPO Membrane


2,000,000
1,800,000
1,600,000
1,400,000
1,200,000
kg of C02
kgof021,000,000
equivalent
800,000
600,000
400,000
200,000
0


- AVERAGE
- RS MEANS
- DELL'ISOLA
- ATHENA
-ARMY
-50


r Ln rr Years Ur rLnr r\Ln
Years


Figure 4-84. Global Warming Potential Life Cycle Impact Per Year
Roof


-rendline TPO


148
































-igure 4-85. Global Warming Potential Life Cycle Impact Per Year Built-Up Roof


Global Warming Potential (TRACI) -

Built-Up Roof


2,000,000
1,800,000
1,600,000
1,400,000
1,200,000
kg of C02 1,000,000
equivalent
800,000
600,000
400,000
200,000
0


- AVERAGE
- RS MEANS
- DELL'ISOLA
ATHENA
-ARMY
-50


r4 Lnr o r4 U1 r o r Ur o rLnr r\ LYeanrrs
4 r4 r4Yrs4 mmmm M
Years


Figure 4-86. Global Warming Potential Life Cycle Impact Per Year Trendline Built-
Up Roof


149


Life Cycle Impact Per Year Global

Warming Potential Built-Up Roof


4,000

3,500

3,000

2,500
kg of C02 000
2,000
equivalent
1,500


S50
SRS MEANS
m DELL'ISOLA
SATHENA
* ARMY


1,000 -


500


~---~-











Global Warming Potential (TRACI) LCI per Year
4,000

3,500

3,000

2,500 0 Green Roof

KG of C02 2,0 Brick
2,000 -
Equivalent 20 TPO Roof

1,500 -- A BUR Roof
0 Wood
1,000 -
50 Aluminum
500

0


-igure 4-87. Global Warming Potential Life Cycle Impact Per Year Al
Average


Life Cycle Impact Per Year Atmospheric

Ecotoxicity Aluminum


Materials -


KG 2,4
Dichlorophen
oxyace
Equivalent


35

30

25


20

15 -




5

0


* ARMY
0 50
m DELL'ISOLA
SATHENA
M RS MEANS


20 ESO

15 TH N


Figure 4-88. Atmospheric Ecotoxicity Life Cycle Impact Per Year Aluminum


150











Atmosperic Ecotoxocity (TRACI) -

Aluminum


KG 2,4
Dichlorophen
oxyace
Equivalent


18,000
16,000
14,000
12,000
10,000
8,000
6,000
4,000
2,000
0


-AVERAGE
-RS MEANS
-DELL'ISOLA
-ATHENA
-ARMY
-50


r1 uLnr, 0o r U1 r 0 r1 U1 r 0 re r Lnr 0 r\J Lnur
r r4 r1Yrs4 mmmm
Years


-igure 4-89. Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendl
Aluminum


Life Cycle


KG 2,4
Dichlorophen
oxyace
Equivalent


35.00

30.00

25.00

20.00

15.00

10.00

5.00

0.00


Impact Per Year Atmospheric

Ecotoxicity- Brick


* ARMY
SATHENA
* DELL'ISOLA
" RS MEANS
S50


Figure 4-90. Atmospheric Ecotoxicity Life Cycle Impact Per Year Brick


151


I I











Atmospheric Ecotoxicity (TRACI) Brick

18000
16000
14000

2,4 12000 AVE
)rophen 10000 S IRS
yace 8000 -DEL
valent 6000 ATH

4000 -AR
2000 -50
0
O Ln O Ln0 OLn OLn OLn OLn OLn OLn OLn 0 Ln
r14 uLn r, 0 r4 U1 r Y 0 r s1r 0n ro Lnr 0 r\J Lnru
-i -i r-i r14 r14 mm mm b
Years


RAGE
MEANS
L'ISOLA
HENA
MY


Figure 4-91. Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Brick


KG 2,4
Dichlorophen
oxyace
Equivalent


Life Cycle Impact Per Year -

Atmospheric Ecotoxicity- Wood

35.00 i


30.00


25.00


20.00


15.00


10.00

c- r-r


* ARMY
0 50
SRS MEANS
1 DELL'ISOLA
SATHENA


20.00 ESO


J.UU


0.00


Figure 4-92. Atmospheric Ecotoxicity Life Cycle Impact Per Year Wood


152


K(
Dichl
ox
Equi


1












Atmospheric Ecotoxicity (TRACI) -

Wood


KG 2,4
Dichlorophen
oxyace
Equivalent


18,000
16,000
14,000
12,000
10,000
8,000
6,000
4,000
2,000
0


-AVERAGE
-RS MEANS
- DELL'ISOLA
-ATHENA
- ARMY
-50


r14 uLn r 0 r U1 Nr Y r s UON1 r0 rO Ln r1O Lnru ,
r r14e rs4 rmmmm
Years


Figure 4-93. Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Wood


KG 2,4
Dichlorophen
oxyace
Equivalent


Life Cycle Impact Per Year -

Atmospheric Ecotoxicity- Green Roof


35.00

30.00

25.00

20.00

15.00

10.00

5.00

0.00


S50
* ARMY
SATHENA
RS MEANS
* DELL'ISOLA


Figure 4-94. Atmospheric Ecotoxicity Life Cycle Impact Per Year Green Roof


153


I


I .


I I












Atmospheric Ecotoxicity (TRACI) -

Green Roof


KG 2,4
Dichlorophe
noxyace
Equivalent


18000

16000

14000

12000

10000
8000

6000

4000

2000
0


- AVERAGE
- RS MEANS
- DELL'ISOLA
- ATHENA
-ARMY
-50


r Years mmmm M
Years


Figure 4-95. Atmospheric Ecotoxicity Life Cycle Impact Per Year Green Roof


Figure 4-96. Atmospheric Ecotoxicity Life Cycle Impact Per Year TPO Roof


154


Life Cycle Impact Per Year -

Atmospheric Ecotoxicity- TPO

Membrane


35.00

30.00

25.00
KG 2,4
Dichlorophe 20 .0
noxyace 15.00
Equivalent
10.00

5.00


S50
SATHENA
m DELL'ISOLA
SRS MEANS
* ARMY


i


0.00


i


i


-1 _W_












Atmospheric Ecotoxicity (TRACI) TPO

Membrane


KG 2,4
Dichlorophenox
yace Equivalent


18,000

16,000

14,000

12,000

10,000

8,000

6,000

4,000

2,000

0


- AVERAGE
-RS MEANS
- DELL'ISOLA
ATHENA

-ARMY

-50


r4 uLn r-N 0 r4 Ln 0 r4 U) N 0 r-O U) NA r- U) N
_q A ri rT itlmm mm
Axis Title


Figure 4-97. Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline- Green
Roof


KG 2,4
Dichlorophen
oxyace
Equivalent


Life Cycle Impact Per Year -

Atmospheric Ecotoxicity- Built-Up Roof


35.00

30.00

25.00

20.00

15.00

10.00
rr


3.UU


0.00


S50
* ARMY

SRS MEANS

* DELL'ISOLA
ATHENA


Figure 4-98. Atmospheric Ecotoxicity Life Cycle Impact Per Year Built-Up Roof


155












Atmospheric Ecotoxicity (TRACI) Built-

Up Roof


18,000
16,000
14,000
12,000
10,000
8,000
6,000
4,000
2,000


- AVERAGE
-RS MEANS
- DELL'ISOLA
- ATHENA
- ARMY
-50


r-4 uLn 1 0 r4 U1 r 0 r s4 U1 n 0 r4 Ln 0 r\4 Ln 1
Y r4a rs4 mmmm
Years


-igure 4-99. Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Built-Up
Roof


LCI Impact Per Year Atmospheric

Ecotoxocity (TRACI)


-i


0 BRICK
* GREEN ROOF
TPO MEMBRANE
* BUILT-UP ROOF
* WOOD
- ALUMINUM


i-


Figure 4-100. Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline -
Average All Materials


156


KG 2,4
Dichlorophenox
yace Equivalent


KG 2,4
Dichlorophen
oxyace
Equivalent












Life Cycle Impact Per Year -

Atmospheric Acidification Aluminum

2,500


2,000

ARMY
1,500 50
mol of H+
ol ofH+ DELL'ISOLA
equivalent
1,000 ATHENA
RS MEANS

500 -


0

-igure 4-101. Atmospheric Acidification Life Cycle Impact Per Year Aluminum


Atmospheric Acidification (TRACI) -

Aluminum


1,200,000

1,000,000

800,000

600,000

400,000

200,000

n


O0 Lnt0 LnO Lnt0 LnO Ln0 LnO Ln OLnt0 Ln OLn
r4 lLn r, 0r4 U1 er\ U1 r r1o uLn 0 r14 uLnr
Years


-AVERAGE

-RS MEANS
- DELL'ISOLA
-ATHENA
-ARMY
-50


Figure 4-102. Atmospheric Acidification Life Cycle Impact Per Year Trendline -
Aluminum


157


mol of H+
equivalent


v











Life Cycle Impact Per Year Atmospheric

Acidification Brick

2,500


2,000

ARMY
1,500 ATHENA
mol of H+DELISOLA
DELL'ISOLA
equivalent
1,000- RS MEANS
S50

500


0

Figure 4-103. Atmospheric Acidification Life Cycle Impact Per Year Brick


Atmospheric Acidification (TRACI) Brick

1,200,000

1,000,000

800,000 AVERAGE

mol of H+ RS MEANS
600,000
equivalent DELL'ISOLA

400,000 ATH ENA
-ARMY
200,000 50

0
r14 n Cr 0 r14 C1 r \J 0r1 C1 r, u0 01 CN rJ u0 4 n
Years

Figure 4-104. Atmospheric Acidification Life Cycle Impact Per Year Trendline Brick


158











Life Cycle Impact Per Year -

Atmospheric Acidification Wood

2,500



2,000 -

ARMY
1,500 -- 50
mol of H+ RS MEANS
equivalent
1,000 DELL'ISOLA
SATHENA

500 -



0

-igure 4-105. Atmospheric Acidification Life Cycle Impact Per Year Wood


mol of H+
equivalent


Atmospheric Acidification (TRACI) -

Wood


1,200,000


1,000,000


800,000

600,000


400,000 -


200,000


0


SLnr 0 4 N Years U Lnr Ln
Years


- AVERAGE
-RS MEANS
- DELL'ISOLA
-ATHENA
-ARMY
-50


Figure 4-106. Atmospheric Acidification Life Cycle Impact Per Year Trendline Wood


159


zl,











Life Cycle Impact Per Year Atmospheric

Acidification Green Roof

2,500


2,000

*50
1,500 ARMY
mol of H+ ATHENA
equivalent
1,000 DELL'ISOLA
RS MEANS

500


0

Figure 4-107. Atmospheric Acidification Life Cycle Impact Per Year Green Roof


Atmospheric Acidification (TRACI) -

Green Roof

1,200,000

1,000,000

800,000 AVERAGE

mol of H+ 0RS MEANS
600,000
equivalent DELL'ISOLA

400,000 ATH E NA
-ARMY
200,000
-50
0 L
4 Ln r 0 r4Ln or\, 0 4Ln r r-4o uLn r 0 r-4o Lnr
Years

Figure 4-108. Atmospheric Acidification Life Cycle Impact Per Year Trendline -
Green Roof


160











Life Cycle Impact Per Year Atmospheric

Acidification TPO Membrane

2,500


2,000

S50
1,500 ATHENA
mol of H+
+ DELL'ISOLA
equivalent
1,000 RS MEANS
ARMY

500


0

Figure 4-109. Atmospheric Acidification Life Cycle Impact Per Year TPO Roof


Atmospheric Acidification

Membrane


mol of H+
equivalent


1,200,000

1,000,000

800,000

600,000

400,000

200,000

0


SLn Ln Ln Ln Ln Ln Ln Ln Ln Ln
r14 Ln r 0o r14 Ln r 0o r14 Ln r, 0 r1o Ln r 0 or\J uLn r
Years


- AVERAGE
SRS MEANS
- DELL'ISOLA
ATHENA
-ARMY
-50


Figure 4-110. Atmospheric Acidification Life Cycle Impact Per Year Trendline TPO
Roof


161


(TRACI) TPO











Life Cycle Impact Per Year Atmospheric

Acidification Built-Up Roof

2,500


2,000

*50
1,500- RS MEANS
mol of H+
ol ofH+ DELL'ISOLA
equivalent
1,000 ATHENA
ARMY

500


0

-igure 4-111. Atmospheric Acidification Life Cycle Impact Per Year Built-


Atmospheric Acidification (TRACI) Built-

Up Roof

1,200,000

1,000,000

800,000 AVERAGE

mol of H+ -- RS MEANS
600,000
equivalent DELL'ISOLA
400,000 ATH ENA

200,000 ARMY
-50
0
0 Ln LnDLnDLn DLn DLn DLn Ln Ln Ln
fN Ln r- C r4l U r- o r\l U)r- 0 l l r -4U) O r14l U- ri
Years


Jp Roof


Figure 4-112. Atmospheric Acidification Life Cycle Impact Per Year Trendline- Built-
Up Roof


162











Atmospheric Acidification (TRACI) Life

Cycle Impact Per Year
1,400

1,200

1,000 U- Green Roof
NTPO Membrane
800
mol of H+ 800 Brick
equivalent 600 Built-Up Roof
E Aluminum
400 Wood

200

0
Figure 4-113. Atmospheric Acidification Life Cycle Impact Per Year- Average All
Materials


Global Warming Potential USACE LCI

Contributions Coarse Versus

Maintenance Model
100%
90%
80% -
70% -
Percentage Life 60%
50% -
Cycle Impact 40% -
30% Maintenance
20%
10% N- Coarse Model
0%

-o ,,, 440/ OR,,

Envelope Combination


Figure 4-114. Global Warming Potential Life Cycle Impact Per Year- Coarse Versus
Maintenance Models USACE


163










Global Warming Potential Athena LCI
Contributions Coarse Versus
Maintenance Model


100%
90% -
80% -
70% -
60% -
Percentage 50% -
40%
30% -
20% -
10% -
no% -


* Maintenance
* Coarse Model


V,-'0' 1/40, V V, V 0/ V., ^



Envelope Combination


Figure 4-115. Global Warming Potential Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Athena


Global Warming Potential Dell'lsola
and Kirk LCI Contributions Coarse
Versus Maintenance Model


100%
90% -
80% -
70% -
60% -
Axis Title 50% -
40% -
30% -
20% -
10% -
0%


Envelope Combination
Envelope Combination


* Maintenance Model
* Coarse Model


Figure 4-116. Global Warming Potential Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Dell'lsola and Kirk


164


v


mm mm m











Global Warming Potential RS Means -

LCI Contributions Coarse Versus

Maintenance Model


100%
90% -
80% -
70% -
60% -
Percentage 50% -
40%
30% -
20% -
10% -
0%




Envelope Combinations


* Maintenance Model
* Coarse Model


Figure 4-117. Global Warming Potential Life Cycle Impact Per Year- Coarse Versus
Maintenance Models RS Means


Atmospheric Ecotoxicity USACE LCI

Contributions Coarse Versus

Maintenance Model


100%
90%
80% -
70% -
Percentage Life 60%
50% -
Cycle Impact 40% -
30%
20% -
10% -
0%

EVe- V, V V, Vto, V


Envelope Combination


* Maintenance
* Coarse Model


Figure 4-118. Atmospheric Ecotoxicity- Life Cycle Impact Per Year- Coarse Versus
Maintenance Models USACE


165











Atmospheric Ecotoxicity Athena LCI

Contributions Coarse Versus

Maintenance Model


100%
90% -
80% -
70% -
60% -
Percentage 50% -
40%
30%
20% -
10% -
0% -




Envelope Combination


* Maintenance
* Coarse Model


Figure 4-119. Atmospheric Ecotoxicity- Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Athena


Atmosperic Ecotoxicity Dell'lsola and

Kirk LCI Contributions Coarse Versus

Maintenance Model


100%
90% -
80% -
70% -
60% -
Axis Title 50% -
40% -
30% -
20% -
10%
0% -


V, En, VN.Vel Combinato

Envelope Combination


* Maintenance Model
* Coarse Model


Figure 4-120. Atmospheric Ecotoxicity- Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Dell'lsola and Kirk


166











Global Warming Potential RS Means -

LCI Contributions Coarse Versus

Maintenance Model


100%
90% -
80% -
70% -
60% -
Percentage 50% -
40%
30% -
20%
10% -
0% -

En elq C i o m i i n


Envelope Combinations


* Maintenance Model
* Coarse Model


Figure 4-121. Atmospheric Ecotoxicity- Life Cycle Impact Per Year- Coarse Versus
Maintenance Models RS Means


Atmospheric Acidification- USACE LCI

Contributions Coarse Versus

Maintenance Model

100%
90%
80% -
70% -
Percentage Life 60%
50% -
Cycle Impact 40%

20% -
2o0% H Maintenance
10% -- Coarse Model
0%




Envelope Combination


Figure 4-122. Atmospheric Acidification Life Cycle Impact Per Year- Coarse Versus
Maintenance Models USACE


167










Atmospheric Acidification Athena LCI

Contributions Coarse Versus

Maintenance Model


100%
90% -
80% -
70% -
60% -
Percentage 50% -
40%
30%
20% -
10% -
0%


- -


I'll''''


* Maintenance
* Coarse Model


V?-- '?- V, 1 .I



Envelope Combination


Figure 4-123. Atmospheric Acidification Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Athena


Atmospheric Acidification- Dell'lsola and

Kirk LCI Contributions Coarse Versus

Maintenance Model


100%
95% -
90%
Axis Title
85%
80% -
75%

V,' I V- VE, le Vo Vinat'i

Envelope Combination


* Maintenance Model
* Coarse Model


Figure 4-124. Atmospheric Acidification Life Cycle Impact Per Year- Coarse Versus
Maintenance Models Dell'lsola and Kirk


168











Atmosperic Acidification- RS Means LCI

Contributions Coarse Versus

Maintenance Model


100%
90% -
80% -
70% -
60% -
Percentage 50% -
40% -
30% -
20% -
10%
0% -
Envelope Combinations



Envelope Combinations


* Maintenance Model
* Coarse Model


Figure 4-125. Atmospheric Acidification Life Cycle Impact Per Year- Coarse Versus
Maintenance Models RS Means

USACE Global Warming Potential Ranking
Energy Differential Energy Neutral Coarse
AL GR 3 7 7
AL TPO 5 9 9
ALBUR 8 8 8
BR GR 1 1 1
BR TPO 2 4 3
BRBUR 7 2 2
WD GR 4 3 4
WDTPO 6 6 6
WDBUR 9 5 5
Figure 4-126. Envelope Combination Ranking USACE Energy Differential, Energy
Neutral and Coarse Global Warming Potential


169










ATHENA Global Warming Potential Ranking
Energy Differential Energy Neutral Coarse
AL GR 3 4 4
AL TPO 5 5 7
AL BUR 8 8 5
BR GR 1 1 1
BR TPO 2 2 3
BR BUR 4 3 2
WD GR 6 6 6
WD TPO 7 7 9
WD BUR 9 9 8
Figure 4-127. Envelope Combination Ranking Athena Energy Differential, Energy
Neutral and Coarse Global Warming Potential

DELL'ISOLA Global Warming Potential Ranking
Energy Differential Energy Neutral Coarse
AL GR 3 3 4
AL TPO 4 4 7
ALBUR 8 7 6
BR GR 1 1 1
BRTPO 2 2 3
BR BUR 6 5 2
WD GR 5 6 5
WDTPO 7 8 9
WDBUR 9 9 8
Figure 4-128. Envelope Combination Ranking Dell'lsola and Kirk Energy
Differential, Energy Neutral and Coarse Global Warming Potential

RS MEANS Global Warming Potential Ranking
Energy Differential Energy Neutral Coarse
AL GR 4 7 8
ALTPO 7 8 9
AL BUR 9 9 7
BRGR 1 1 2
BR TPO 2 2 3
BRBUR 6 3 1
WD GR 3 4 5
WD TPO 5 5 6
WDBUR 8 6 4
Figure 4-129. Envelope Combination Ranking RS Means Energy Differential,
Energy Neutral and Coarse Global Warming Potential


170










USACE Atmospheric Ecotoxicity Ranking
Energy Energy
Differential Neutral Coarse
AL GR 7 8 7
AL TPO 8 9 9
AL BUR 9 7 8
BR GR 1 1 1
BR TPO 2 4 3
BR BUR 4 2 2
WD GR 3 3 4
WD TPO 5 6 6
WD BUR 6 5 5
Figure 4-130. Envelope Combination Ranking USAGE Energy Differential, Energy
Neutral and Coarse Atmospheric Ecotoxicity

ATHENA Atmospheric Ecotoxicity Ranking
Energy Differential Energy Neutral Coarse
AL GR 7 7 4
AL TPO 8 8 7
ALBUR 9 9 5
BR GR 1 1 1
BRTPO 2 2 3
BR BUR 3 3 2
WDGR 4 4 6
WD TPO 5 5 9
WDBUR 6 6 8
Figure 4-131. Envelope Combination Ranking Athena Energy Differential, Energy
Neutral and Coarse Atmospheric Ecotoxicity

DELL'ISOLA Atmospheric Ecotoxicity Ranking
Energy Differential Energy Neutral Coarse
AL GR 7 7 7
AL TPO 8 8 8
AL BUR 9 9 9
BRGR 1 1 1
BR TPO 2 2 2
BRBUR 3 3 3
WD GR 4 4 4
WD TPO 5 5 5
WDBUR 6 6 6
Figure 4-132. Envelope Combination Ranking Dell'lsola and Kirk Energy
Differential, Energy Neutral and Coarse Atmospheric Ecotoxicity


171










RS MEANS Atmospheric Ecotoxicity Ranking
Energy Differential Energy Neutral Coarse
AL GR 7 7 7
ALTPO 8 8 8
AL BUR 9 9 9
BR GR 1 1 1
BR TPO 2 2 2
BR BUR 4 3 3
WDGR 3 4 4
WD TPO 5 5 5
WDBUR 6 6 6
Figure 4-133. Envelope Combination Ranking RS Means Energy Differential,
Energy Neutral and Coarse Atmospheric Ecotoxicity

USACE Atmospheric Acidification Ranking
Energy Differential Energy Neutral Coarse
AL GR 3 4 4
AL TPO 4 5 6
ALBUR 8 6 5
BR GR 1 1 1
BRTPO 2 2 3
BR BUR 6 3 2
WD GR 5 6 7
WDTPO 7 8 9
WDBUR 9 9 8
Figure 4-134. Envelope Combination Ranking USACE Energy Differential, Energy
Neutral and Coarse Atmospheric Acidification

ATHENA Atmospheric Acidification Ranking
Energy Differential Energy Neutral Coarse
AL GR 3 4 4
ALTPO 4 5 5
AL BUR 6 6 6
BRGR 1 1 1
BR TPO 2 2 2
BRBUR 5 3 3
WD GR 7 7 7
WD TPO 8 8 8
WDBUR 9 9 9
Figure 4-135. Envelope Combination Ranking Athena Energy Differential, Energy
Neutral and Coarse Atmospheric Acidification


172










DELL'ISOLA Atmospheric Acidification Ranking
Energy Differential Energy Neutral Coarse
AL GR 3 4 4
ALTPO 4 5 5
AL BUR 7 6 6
BRGR 1 1 1
BR TPO 2 2 2
BR BUR 5 3 3
WDGR 6 7 7
WD TPO 8 8 8
WDBUR 9 9 9
Figure 4-136. Envelope Combination Ranking Dell'lsola and Kirk Energy
Differential, Energy Neutral and Coarse Atmospheric Acidification

RS MEANS Atmospheric Acidification Ranking
Energy Differential Energy Neutral Coarse
AL GR 3 4 4
AL TPO 4 5 5
ALBUR 8 6 6
BR GR 1 1 1
BRTPO 2 2 2
BR BUR 5 3 3
WD GR 6 7 7
WD TPO 7 8 8
WDBUR 9 9 9
Figure 4-137. Envelope Combination Ranking RS Means Energy Differential,
Energy Neutral and Coarse Atmospheric Acidification


173









CHAPTER 5
DISCUSSION, CONCLUSION, THE FUTURE

The first part of this research involved the construction of Life Cycle Assessments

using nine building envelope combinations. These envelopes were integrated into the

context of a larger building to provide a more complete analysis. It was concluded that

the choice of wall and roof materials has a significant effect on the Life Cycle Impact of

a building due to the associated consumption of operating energy. Much of the literature

has stated that operating energy is the dominant variable in assessing Life Cycle

Impact. Some have stated that upwards of 90% of the Life Cycle Impact is attributable

to operating energy consumption. This may be true in the analysis of a single building.

Generally speaking, the operating energy is the dominant impact. However, when

assessing different wall forms and roofing options for example, a means of comparison

is necessary. It is for this reason that this study opted to assess the impacts of operating

energy differentials in the analysis of wall forms and roofing. As shown in the section of

this document detailing the Life Cycle Impact and service life models with energy

differentials, the comparison of operating energy impacts is highly influential, but not

completely dominant. The noted exception was with aluminum as measured for

Atmospheric Ecotoxicity. Here, the impact of the material superseded the impact of the

operating energy differential, as indicated by a change in order from the energy analysis

results to those of the energy differential models, including maintenance.

The equalization of Life Cycle Impact models has also revealed some important

findings. Since operating energy impacts contribute so heavily, the selection of wall form

and roofing materials becomes all the more important. Modifications to walls and roofs

can be accomplished, such that thermal performance can be equalized, but this may


174









involve considerable change to conventional construction techniques. The modification

of walls and roofs in this manner is seen as a means of honing in on the impact of the

maintenance and major replacement intervals. Indeed, the results of this stage of the

analysis varied as compared with the results of the energy differential models. To

further isolate the effects of maintenance, the coarse models were constructed and

again yielded a different ordering and magnitude of the outcomes. These differences

were entirely attributable to the subjective differences in each model's maintenance

interval frequency and intensity, as all other variables remained the same.

Ultimately, a significant amount of variation is evident in the results produced by

the five service life models employed in the study. An examination of Life Cycle Impacts

per year makes this clearer. Some of the individual wall form and roofing materials

showed overlap from model to model, and the best choice in terms of environmental

impact is not always clear. In reference to the coarse models, some of this overlap was

attributable to subjective difference in the models' maintenance intervals frequency and

intensity. However, it is safe to say that the overlap is representative of a number of

factors, including the differences in major replacement frequency and inherent material

properties.

Conclusions

As the original hypothesis proposed, variations in the Life Cycle Impacts of

building envelope materials are dependent on longevity, differential durability and

cumulative maintenance over time. For the five service life models that were

constructed for this analysis, this hypothesis must be upheld. As shown in the

representation of Life Cycle Impact per year, the impact of an individual material can

vary such that it cannot conclusively be preferred to another material of similar purpose.


175









To make conclusions beyond the five service life models used in this study however

would be premature. The external validity of this study cannot be verified without further

analysis and perhaps the integration of additional service life models. As such, the

hypothesis holds true with consideration to the scope of the study, and not beyond.

Conclusions may also be drawn on the contributions of operating energy usage

and the impacts of maintenance over time. As stated previously, the operating energy

usage of a building produces a highly influential environmental impact. At least, this is

true for the building envelope combinations and ancillary mechanical equipment and

systems analyzed in this study. Likewise, maintenance is a determining factor in

assessing the relative impacts of building envelope materials, as the ordering and

magnitude of the results changed from the energy neutral to the coarse models.

It must also be conceded that other factors play a role in the cumulative

environmental impacts of building envelope materials, such as the physical and

chemical properties of the materials themselves. However, these differences do not

account for the variability that is evident in the analysis of a single wall or roof form

material across the five different service life models. Nor does it account for the

differences in results from the energy differential model, the energy neutral model and

the coarse model. Ultimately, some of the variation is attributable to the differences

material longevity and cumulative maintenance over time.

The Future

For Life Cycle Assessment as an individual area of study, future research

endeavors should focus on improving the methodology. This can be accomplished

using two distinct approaches. First, the Life Cycle Assessment method is continually

enhanced by the gathering of increasingly higher quality, primary data. As such, there


176









are a multitude of studies that could be performed with the simple objective of providing

additional and improved points of comparison. Second, methodological improvements in

Life Cycle Assessment can be accomplished through the statistical analysis of existing,

secondary data sources. As in the case of this research, the analysis of existing data

sets offers a good deal of potential. Certainly, future research should entail the inclusion

of service life analyses.

Similar improvements could be made to the various methods of Service Life

Prediction. Within the area of damage mechanics, current models allow for reasonable

predictions of expected service life. Yet, competing methodologies and built-in

assumptions have led to a lack of consensus. Consequently, there is a need for better

and universally applicable empirical data. Since empirical studies are often used to

buttress or negate the hypotheses of prediction models, they are of course the logical

precursors to consensus-building. In addition, improvements in empirical data would

provide a mathematical basis for a wide range of service life factors, including climate,

design, installation quality, material quality, in-use conditions and maintenance. With

improvement of the existing methods in mind, the focus should be on the gathering of

empirical data through a combination of materials testing and surveys of existing

building department and facility operations databases. This would also provide valuable

insight for practitioners of Life Cycle Assessment, as we have already concluded that

the accuracy of a Life Cycle Impact study is contingent, at least in part, on the accuracy

of the assumed service life and maintenance values and descriptions.

The confluence of these two methods generates yet another set of questions. For

instance, when Life Cycle Assessment Impacts are quantified in relation to Service Life


177









Predictions, durable and long-lived building materials and assemblies are not

necessarily the preferred options. In many circumstances, cheaper, less durable and

short-lived materials and assemblies yield a lesser impact. With this idea in mind,

research on recycling, deconstruction, adaptive architecture, modular and prefabricated

construction takes on a new meaning. A combination of Life Cycle Energy Assessment,

energy modeling, and periodic thermal imaging could be used to determine assembly

and performance degradation over time. From a facility operations standpoint, this type

of analysis would provide important maintenance data, and differentiate between high

and low maintenance materials and assemblies. Further, a simple translation of the

resulting data into Life Cycle Costing would provide prospective owners with a more

realistic expectation of potential costs

Additional work should also be performed on buildings in the context of time.

Materials degradation is of course one aspect of this type of analysis. However, this

area of research also involves a certain type of "technological forecasting".

Understandably, work in this area is somewhat restrained due to perceived risk. It is

indeed difficult to predict the future. However, the production of Life Cycle Assessment

models including estimations of risk would provide valuable insight into the

appropriateness of building and material service lives. Ultimately, research in this area

must acknowledge spatial and temporal dynamism. We must make assumptions on

potential improvements in efficiency and the potential degradation of services over time.

It is hoped that future analyses in Life Cycle Assessment are based well-founded

assumptions, and that an improved representation of Life Cycle Impact will result.


178









APPENDIX A
MATERIAL QUANTITY TAKE-OFF


Brick Wall Assembly


Bricks
Wall Total Gross Area Square Feet 23,585 Square Feet
Window Total Gross Area Square Feet 9,662 Square Feet
Wall Total Gross Area (Brick) Square Feet 13,923 Square Feet
Convert Square Feet to Square Meters 13, 923 0.09 1,253 Square Meters
Convert Square Meters to Cubic Meters 1,253 0.09 113 Cubic Meter
Assume 2,403 Kilogram Per Cubic Meter Kilograms 271,539 Kilograms


Mortar

Wall Total Gross Area Square Feet 23,585 Square Feet
Window Total Gross Area Square Feet 9,662 Square Feet
Wall Total Gross Area (Brick) Square Feet 13,923 Square Feet
Assume 6.75 Bricks Square Foot 93,981 Bricks
Assume 0.60 Cubic Meters of Mortar Per 1000 Bricks 56.39 Cubic Meters
Assume 2,403 Kilogram Per Cubic Meter Kilograms 135,501 Kilograms

Caulk

Assume Building Perimeter 524 Linear Feet
Assume Caulk Joint Every 20 Feet 40 Feet Height 1,048 Linear Feet
Assume 15% Waste 1205 Linear Feet
Assume 0.032 Pounds Per Linear Foot 38.56 Pounds
Convert Pounds to Kilograms 17.5 Kilograms


Aluminum Wall Assembly

Aluminum
Wall Total Gross Area Square Feet 23,585 Square Feet
Window Total Gross Area Square Feet 9,662 Square Feet
Wall Total Gross Area (Aluminum) Square Feet 13,923 Square Feet
Assume 20 Gage Thickness 0.0508 Inches
Convert Square Feet to Cubic Feet 58.94 Cubic Feet
Assume 169 Pounds Per Cubic Foot 9,902.15 Pounds
Convert to Kilograms 4,491.5 Kilograms

Caulk

Assume Building Perimeter 524 Linear Feet


179









Assume Caulk Joint Every 20 Feet 40 Feet Height 1,048 Linear Feet
Assume 15% Waste 1205 Linear Feet
Assume 0.032 Pounds Per Linear Foot 38.56 Pounds
Convert Pounds to Kilograms 17.5 Kilograms


Wood Wall Assembly

Wood

Wall Total Gross Area Square Feet 23,585 Square Feet
Window Total Gross Area Square Feet 9,662 Square Feet
Wall Total Gross Area (Wood) Square Feet 13,923 Square Feet
Assume 8' wide Board, 12" Overlap 17,136 Square Feet
Assume 1/2" Thickness 8,568 Cubic Feet
Assume 21 Pounds Per Cubic Foot 179,928 Pounds
Convert to Kilograms 81,614 Kilograms


Caulk

Assume Building Perimeter 524 Linear Feet
Assume Caulk Joint Every 20 Feet 40 Feet Height 1,048 Linear Feet
Assume 15% Waste 1205 Linear Feet
Assume 0.032 Pounds Per Linear Foot 38.56 Pounds
Convert Pounds to Kilograms 17.5 Kilograms


Paint Two Coats
Wall Total Gross Area Square Feet 23,585 Square Feet
Window Total Gross Area Square Feet 9,662 Square Feet
Wall Total Gross Area Square Feet 13,923 Square Feet
Assume Coverage of 420 Square Feet Per Gallon 1st Coat 33.15 Gallons
Assume Coverage of 520 Square Feet Per Gallon 2nd Coat 26.78 Gallons
Convert 33.15 Gallons to Cubic Feet 4.43 Cubic Feet
Convert 26.78 Gallons to Cubic Feet 3.58 Cubic Feet
Assume 62.4 Pounds Per Cubic Foot 4.43 Cubic Feet 276.55 Pounds
Assume 62.4 Pounds Per Cubic Foot 3.58 Cubic Feet 223.39 Pounds
Convert 276.55 Pounds To Kilograms 125.44 Kilograms
Assume 0.032 Pounds Per Linear Foot 101.33 Kilograms

Paint Three Coats
Wall Total Gross Area Square Feet 23,585 Square Feet
Window Total Gross Area Square Feet 9,662 Square Feet
Wall Total Gross Area Square Feet 13,923 Square Feet


180









Assume Coverage of 420 Square Feet Per Gallon 1st Coat 33.15 Gallons
Assume Coverage of 520 Square Feet Per Gallon 2nd Coat 26.78 Gallons
Assume Coverage of 520 Square Feet Per Gallon 3rd Coat 26.78 Gallons
Convert 33.15 Gallons to Cubic Feet 4.43 Cubic Feet
Convert 26.78 Gallons to Cubic Feet 3.58 Cubic Feet
Convert 26.78 Gallons to Cubic Feet 3.58 Cubic Feet
Assume 62.4 Pounds Per Cubic Foot 4.43 Cubic Feet 276.55 Pounds
Assume 62.4 Pounds Per Cubic Foot 3.58 Cubic Feet 223.39 Pounds
Assume 62.4 Pounds Per Cubic Foot 3.58 Cubic Feet 223.39 Pounds
Convert 276.55 Pounds To Kilograms 125.44 Kilograms
Convert 223.39 Pounds To Kilograms 101.33 Kilograms
Convert 223.39 Pounds To Kilograms 101.33 Kilograms



Built-Up Roof Assembly
Roof Total Gross Area Square Feet 14,760 Square Feet
Skylight Total Gross Area Square Feet 768 Square Feet
Roof Total Gross Area (Built-Up Roof) Square Feet 13,992 Square Feet
Convert Square Feet to Square Meters 1,259.28 Square Meters
Assume 385 grams Per Square Meter (Type IV BUR Felt)*4 1,939.29 Kilograms
Layers
Assume Inter-ply Bitumen 20.5 Pounds Per square Foot 3 907,740 Pounds
Coats
Convert to Kilograms 411,744 Kilograms
Assume Surface Coat at 60.5 Pounds Per Square Foot 892,980 Pounds
Convert to Kilograms 405,049 Kilograms
Assume Gravel 400 Pounds Per square Foot 5,904,000 Pounds
Convert to Kilograms 2,678,009 Kilograms

TPO Assembly

Roof Total Gross Area Square Feet 14,760 Square Feet
Skylight Total Gross Area Square Feet 768 Square Feet
Roof Total Gross Area (TPO Roof) Square Feet 13,992 Square Feet
Convert Square Feet to Square Meters 1,259.28 Square Meters
Assume 1.13 Kilograms TPO Membrane Per Square Meter 1,424 Kilograms
Assume 7.03 Kilograms Bitumen Per Square Meter 8,856 Kilograms


Green Roof Assembly

Roof Total Gross Area Square Feet 14,760 Square Feet
Skylight Total Gross Area Square Feet 768 Square Feet
Roof Total Gross Area (Built-Up Roof) Square Feet 13,992 Square Feet


181




























































182


Convert Square Feet to Square Meters 1,259.28 Square Meters
Assume 48.8 Kilograms Per Square Meter Growing 61,414 Kilograms
Medium
Assume 0.088 Kilograms Per Square Meter Filter Fabric 112 Kilograms
Assume 0.54 Kilograms Per Square Meter Root Barrier 680 Kilograms
Assume 6.71 Kilograms Per Square Meter Rubberized 8,458.6 Kilograms
Roofing Asphalt









APPENDIX B
USAGE MODEL SERVICE LIFE AND MAINTENANCE INTERVAL IMPACTS


183










Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Built Up Roof w/ Brick Wall 1 3 28 20 14 1
0.025 SF
Transportation 1 SF Membrane, Insulation, 1 SF
Transportation- 0.75 0.75 gallons Insulation & Sealant & Insulation & 0.02 SF felt
Resource Required gallons gasoline gasoline Ballast Membrane Membrane adhesive
GWP 0.35 0.35 17,009.22 425.23 5,664.94 113.30
Ecotox 0.00 0.00 68.90 1.72 10.76 0.22
Acid 0.11 0.11 3,406.41 85.16 1,803.42 36.07

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Built Up Roof w/ Aluminum
Wall 1 3 28 20 14 1
0.025 SF
Transportation 1 SF Membrane, Insulation, 1 SF
Transportation- 0.75 0.75 gallons Insulation & Sealant & Insulation & 0.02 SF felt
Resource Required gallons gasoline gasoline Ballast Membrane Membrane adhesive
GWP 0.35 0.35 17,094.98 427.37 5,664.94 113.30
Ecotox 0.00 0.00 68.95 1.72 10.76 0.22
Acid 0.11 0.11 3,425.79 85.64 1,803.42 36.07

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Built Up Roof w/ Wood Wall 1 3 28 20 14 1
0.025 SF
Transportation 1 SF Membrane, Insulation, 1 SF
Transportation- 0.75 0.75 gallons Insulation & Sealant & Insulation & 0.02 SF felt
Resource Required gallons gasoline gasoline Ballast Membrane Membrane adhesive
GWP 0.35 0.35 17,179.06 429.48 5,664.94 113.30
Ecotox 0.00 0.00 69.00 1.72 10.76 0.22
Acid 0.11 0.11 3,444.79 86.12 1,803.42 36.07

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Built Up Roof w/ No
Modification 1 3 28 20 14 1













Resource Required


Transportation- 0.75
gallons gasoline


Transportation
- 0.75 gallons
gasoline


1 SF Membrane,
Insulation &
Ballast


0.025 SF
Insulation,
Sealant &
Membrane


1 SF
Insulation &
Membrane


0.02 SF felt
adhesive


GWP 0.35 0.35 17,849.72 446.24 5,664.94 113.30
Ecotox 0.00 0.00 63.92 1.60 10.76 0.22
Acid 0.11 0.11 2,721.11 68.03 1,803.42 36.07

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Thermoplastic w/ Brick Wall 1 3 20 10 1
Transportation 1 SF Insulation, 0.02 SF
Transportation- 0.75 0.75 gallons membrane & 0.25 ballast Adhesive felt
Resource Required gallons gasoline gasoline sealant adhesive & Mastic
GWP 0.35 0.35 17,912.74 0.00 358.25
Ecotox 0.00 0.00 63.96 0.00 1.28
Acid 0.11 0.11 2,735.35 0.00 54.71

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Thermoplastic w/ Aluminum
Wall 1 3 20 10 1
Transportation 1 SF Insulation, 0.02 SF
Transportation- 0.75 0.75 gallons membrane & 0.25 ballast Adhesive felt
Resource Required gallons gasoline gasoline sealant adhesive & Mastic
GWP 0.35 0.35 17,956.50 0.00 359.13
Ecotox 0.00 0.00 63.99 0.00 1.28
Acid 0.11 0.11 2,745.24 0.00 54.90

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Thermoplastic w/ Wood Wall 1 3 20 10 1
Transportation 1 SF Insulation, 0.02 SF
Transportation- 0.75 0.75 gallons membrane & 0.25 ballast Adhesive felt
Resource Required gallons gasoline gasoline sealant adhesive & Mastic
GWP 0.35 0.35 18,037.21 0.00 360.74


Ecotox


0.00


0.00


64.04


0.00


1.28


185












Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Thermoplastic w/ No
Modification 1 3 20 10 1
Transportation 1 SF Insulation, 0.02 SF
Transportation- 0.75 0.75 gallons membrane & 0.25 ballast Adhesive felt
Resource Required gallons gasoline gasoline sealant adhesive & Mastic
GWP 0.35 0.35 17,849.72 0.00 356.99
Ecotox 0.00 0.00 63.92 0.00 1.28
Acid 0.11 0.11 2,721.11 0.00 54.42

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Green Roof w/ Brick Wall 1 3 40 10
Transportation
Transportation- 0.75 0.75 gallons
Resource Required gallons gasoline gasoline 1 SF 0.025 SF
GWP 0.35 0.35 20,743.92 518.60
Ecotox 0.00 0.00 64.90 1.62
Acid 0.11 0.11 2,732.18 68.30

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Green Roof w/ Aluminum
Wall 1 3 40 10
Transportation
Transportation- 0.75 0.75 gallons
Resource Required gallons gasoline gasoline 1 SF 0.025 SF
GWP 0.35 0.35 20,785.96 519.65
Ecotox 0.00 0.00 64.92 1.62
Acid 0.11 0.11 2,741.68 68.54

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Green Roof w/ Wood Wall 1 3 40 10


186


Acid


2,763.48


0.00


55.27












Resource Required


Transportation- 0.75
gallons gasoline


Transportation
- 0.75 gallons
gasoline


1 SF


0.025 SF


GWP 0.35 0.35 20,850.70 521.27
Ecotox 0.00 0.00 64.96 1.62
Acid 0.11 0.11 2,756.31 68.91

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Green Roof w/ No
Modification 1 3 40 10
Transportation
Transportation- 0.75 0.75 gallons
Resource Required gallons gasoline gasoline 1 SF 0.025 SF
GWP 0.35 0.35 20,743.92 518.60
Ecotox 0.00 0.00 64.90 1.62
Acid 0.11 0.11 2,732.18 68.30

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Clay Brick w/ Green Roof 3 5 500 25 8
1 SF
0.02 SF Pressure
Transportation Brick, 1 SF wash,
Transportation- 0.75 0.75 gallons Waterproofin waterproofin
gallons gasoline gasoline 1 SF Brick g g material
GWP 0.35 0.35 78,953.63 1,579.07 4.73
Ecotox 0.00 0.00 69.33 1.39 0.03
Acid 0.11 0.11 13,356.52 267.13 1.05

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Clay Brick w/ TPO Roof 3 5 500 25 8
1 SF
0.02 SF Pressure
Transportation Brick, 1 SF wash,
Transportation- 0.75 0.75 gallons Waterproofin waterproofin
gallons gasoline gasoline 1 SF Brick g g material











Ecotox 0.00 0.00 69.35 1.39 0.03
Acid 0.11 0.11 13,364.45 267.29 1.05

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Clay Brick w/ BUR Roof 3 5 500 25 8
1 SF
0.02 SF Pressure
Transportation Brick, 1 SF wash,
Transportation- 0.75 0.75 gallons Waterproofin waterproofin
gallons gasoline gasoline 1 SF Brick g g material
GWP 0.35 0.35 79,171.41 1,583.43 4.73
Ecotox 0.00 0.00 69.46 1.39 0.03
Acid 0.11 0.11 13,408.12 268.16 1.05

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Clay Brick w/ No
Modification 3 5 500 25 8
1 SF
0.02 SF Pressure
Transportation Brick, 1 SF wash,
Transportation- 0.75 0.75 gallons Waterproofin waterproofin
gallons gasoline gasoline 1 SF Brick g g material
GWP 0.35 0.35 78,953.63 1,579.07 4.73
Ecotox 0.00 0.00 69.33 1.39 0.03
Acid 0.11 0.11 13,356.52 267.13 1.05

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Wood (Single Coat) w/ Green
Roof 1 3 125 25 5
0.02 SF Wood + Scrape,
Transportation 0.02 scrape, repair,
Transportation- 0.75 0.75 gallons 1 SF Wood + 1 repair, refinish, refinish + 1
gallons gasoline gasoline SF Paint paint SF paint
GWP 0.35 0.35 85,818.87 1,716.38 515.41


188


GWP


0.35


0.35


78,987.12


1,579.74


4.73











Acid 0.11 0.11 50,549.06 1,010.98 105.80

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Wood (Single Coat) w/ TPO
Roof 1 3 125 25 5
0.02 SF Wood + Scrape,
Transportation 0.02 scrape, repair,
Transportation- 0.75 0.75 gallons 1 SF Wood + 1 repair, refinish, refinish + 1
gallons gasoline gasoline SF Paint paint SF paint
GWP 0.35 0.35 85,885.87 1,717.72 515.41
Ecotox 0.00 0.00 211.22 4.22 1.50
Acid 0.11 0.11 50,564.93 1,011.30 105.80

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Wood (Single Coat) w/ BUR
Roof 1 3 125 25 5
0.02 SF Wood + Scrape,
Transportation 0.02 scrape, repair,
Transportation- 0.75 0.75 gallons 1 SF Wood + 1 repair, refinish, refinish + 1
gallons gasoline gasoline SF Paint paint SF paint
GWP 0.35 0.35 86,070.18 1,721.40 515.41
Ecotox 0.00 0.00 211.33 4.23 1.50
Acid 0.11 0.11 50,608.61 1,012.17 105.80

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Wood (Single Coat) w/ No
Modification 1 3 125 25 5
0.02 SF Wood + Scrape,
Transportation 0.02 scrape, repair,
Transportation- 0.75 0.75 gallons 1 SF Wood + 1 repair, refinish, refinish + 1
gallons gasoline gasoline SF Paint paint SF paint
GWP 0.35 0.35 85,785.37 1,715.71 515.41
Ecotox 0.00 0.00 211.15 4.22 1.50
Acid 0.11 0.11 50,541.12 1,010.82 105.80


189


Ecotox


0.00


0.00


211.18


4.22


1.50











Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Wood (Multi-Coat) w/ Green
Roof 2 5 125 25 8
0.02 SF Wood + Scrape,
Transportation 0.02 scrape, repair,
Transportation- 0.75 0.75 gallons 1 SF Wood + 1 repair, refinish, refinish + 1
gallons gasoline gasoline SF Paint paint SF paint
GWP 0.35 0.35 86,175.30 1,723.51 773.11
Ecotox 0.00 0.00 212.17 4.24 2.24
Acid 0.11 0.11 50,663.74 1,013.27 158.70

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Wood (Multi-Coat) w/ TPO
Roof 2 5 125 25 8
0.02 SF Wood + Scrape,
Transportation 0.02 scrape, repair,
Transportation- 0.75 0.75 gallons 1 SF Wood + 1 repair, refinish, refinish + 1
gallons gasoline gasoline SF Paint paint SF paint
GWP 0.35 0.35 86,242.31 1,724.85 773.11
Ecotox 0.00 0.00 212.22 4.24 2.24
Acid 0.11 0.11 50,679.62 1,013.59 158.70

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Wood (Multi-Coat) w/ BUR
Roof 2 5 125 25 8
0.02 SF Wood + Scrape,
Transportation 0.02 scrape, repair,
Transportation- 0.75 0.75 gallons 1 SF Wood + 1 repair, refinish, refinish + 1
gallons gasoline gasoline SF Paint paint SF paint
GWP 0.35 0.35 86,426.62 1,728.53 773.11
Ecotox 0.00 0.00 212.33 4.25 2.24
Acid 0.11 0.11 50,723.29 1,014.47 158.70

Inspection/ Minor Inspections Major Minor Major Repair Minor


190











Wood (Multi-Coat) w/ No
Modification 2 5 125 25 8
0.02 SF Wood + Scrape,
Transportation 0.02 scrape, repair,
Transportation- 0.75 0.75 gallons 1 SF Wood + 1 repair, refinish, refinish + 1
gallons gasoline gasoline SF Paint paint SF paint
GWP 0.35 0.35 86,141.81 1,722.84 773.11
Ecotox 0.00 0.00 212.15 4.24 2.24
Acid 0.11 0.11 50,655.81 1,013.12 158.70

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Aluminum Siding w/ Green
Roof 2 3 80 12 5
Transportation
Transportation- 0.75 0.75 gallons Refinish
gallons gasoline gasoline 1 SF Siding 0.02 SF Siding Paint
GWP 0.35 0.35 108,422.03 2,168.44 427.43
Ecotox 0.00 0.00 1,021.84 20.44 1.39
Acid 0.11 0.11 18,725.52 374.51 97.26

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Aluminum Siding w/ TPO
Roof 2 3 80 12 5
Transportation
Transportation- 0.75 0.75 gallons Refinish
gallons gasoline gasoline 1 SF Siding 0.02 SF Siding Paint
GWP 0.35 0.35 108,472.15 2,169.44 427.43
Ecotox 0.00 0.00 1,013.31 20.27 1.39
Acid 0.11 0.11 18,031.32 360.63 97.26

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Aluminum Siding w/ BUR
Roof 2 3 80 12 5


Clean Up


Replacement


Replacement


Repair











Transportation- 0.75
gallons gasoline


Transportation
- 0.75 gallons
gasoline


1 SF Siding


0.02 SF Siding


Refinish
Paint


GWP 0.35 0.35 108,656.44 2,173.13 427.43
Ecotox 0.00 0.00 1,021.99 20.44 1.39
Acid 0.11 0.11 18,781.06 375.62 97.26

Inspection/ Minor Major Minor Minor
Clean Up Inspections Replacement Replacement Major Repair Repair
Aluminum Siding w/ No
Modification 2 3 80 12 5
Transportation
Transportation- 0.75 0.75 gallons Refinish
gallons gasoline gasoline 1 SF Siding 0.02 SF Siding Paint
GWP 0.35 0.35 108,405.14 2,168.10 427.43
Ecotox 0.00 0.00 1,021.83 20.44 1.39
Acid 0.11 0.11 18,721.52 374.43 97.26


192









APPENDIX C


ATHENA MODEL SERVICE LIFE AND MAINTENANCE INTERVAL IMPACTS


193










Built Up Roof w/ Brick Wall 1 20 1
1 square foot
membrane,
insulation &
Resource Required ballast 1.5% of roof
GWP 0.00000 17,009.22112 255.13832
Ecotox 0.00000 68.89527 1.03343
Acid 0.00000 3,406.41472 51.09622

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Built Up Roof w/ Aluminum
Wall 1 20 1
1 SF Membrane,
Transportation- 0.75 Insulation &
Resource Required gallons gasoline Ballast 1.5% of roof
GWP 0.00000 17,094.97845 256.42468
Ecotox 0.00000 68.94739 1.03421
Acid 0.00000 3,425.79302 51.38690

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Built Up Roof w/ Wood Wall 1 20 1
1 SF Membrane,
Transportation- 0.75 Insulation &
Resource Required gallons gasoline Ballast 1.5% of roof
GWP 0.00000 17,179.06298 257.68594
Ecotox 0.00000 68.99849 1.03498
Acid 0.00000 3,444.79333 51.67190

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Built Up Roof w/ No
Modification 1 20 1
1 SF Membrane,
Transportation- 0.75 Insulation &
Resource Required gallons gasoline Ballast 1.5% of roof











Ecotox 0.00000 68.78132 1.03172
Acid 0.00000 3,364.04671 50.46070

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Thermoplastic w/ Brick Wall 1 19 1
1 SF Insulation,
Transportation- 0.75 membrane & 1.5% of
Resource Required gallons gasoline sealant Roof
GWP 0.00000 17,912.74 268.69108
Ecotox 0.00000 63.96 0.95944
Acid 0.00000 2,735.35 41.03032

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Thermoplastic w/ Aluminum
Wall 1 19 1
1 SF Insulation,
Transportation- 0.75 membrane & 1.5% of
Resource Required gallons gasoline sealant Roof
GWP 0.00000 17,956.50 269.34743
Ecotox 0.00000 63.99 0.95984
Acid 0.00000 2,745.24 41.17863

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Thermoplastic w/ Wood Wall 1 19 1
1 SF Insulation,
Transportation- 0.75 membrane & 1.5% of
Resource Required gallons gasoline sealant Roof
GWP 0.00000 18,037.21 270.55818
Ecotox 0.00000 64.04 0.96058
Acid 0.00000 2,763.48 41.45222

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair


195


GWP


0.00000


16,821.72444


252.32587










Thermoplastic w/ No
Modification 1 19 1
1 SF Insulation,
Transportation- 0.75 membrane & 1.5% of
Resource Required gallons gasoline sealant Roof
GWP 0.00000 17,849.72 267.74573
Ecotox 0.00000 63.92 0.95887
Acid 0.00000 2,721.11 40.81670

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Green Roof w/ Brick Wall 1 30 2
Transportation- 0.75 1.5% of
Resource Required gallons gasoline 1 SF Roof
GWP 0.00000 20,743.91823 311.15877
Ecotox 0.00000 64.89621 0.97344
Acid 0.00000 2,732.18054 40.98271

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Green Roof w/ Aluminum
Wall 1 30 2 N/A
Transportation- 0.75 1.5% of
Resource Required gallons gasoline 1 SF Roof N/A
GWP 0.00000 20,785.95672 311.78935
Ecotox 0.00000 64.92176 0.97383
Acid 0.00000 2,741.67984 41.12520

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Green Roof w/ Wood Wall 1 30 2 N/A
Transportation- 0.75 1.5% of
Resource Required gallons gasoline 1 SF Roof N/A
GWP 0.00000 20,850.69857 312.76048
Ecotox 0.00000 64.96111 0.97442
Acid 0.00000 2,756.30934 41.34464


196











Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Green Roof w/ No
Modification 1 30 2 N/A
Transportation- 0.75 1.5% of
Resource Required gallons gasoline 1 SF Roof N/A
GWP 0.00000 20,743.91823 311.15877
Ecotox 0.00000 64.89621 0.97344
Acid 0.00000 1,861.74791 27.92622

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Clay Brick w/ Green Roof 3 500 35 12
Repoint Recaulk
N/A 1 SF Brick 25% of wall 25% of wall
GWP 0.00000 78,953.62842 4,192.20575 0.82005
Ecotox 0.00000 69.32714 10.53279 0.00050
Acid 0.00000 13,356.51772 536.71512 0.19511

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Clay Brick w/ TPO Roof 3 500 35 12
Repoint Recaulk
N/A 1 SF Brick 25% of wall 25% of wall
GWP 0.00000 0.00000 78,987.12357 4,192.20575 0.82005
Ecotox 0.00000 0.00000 69.34746 10.53279 0.00050
Acid 0.00000 0.00000 13,364.45456 536.71512 0.19511

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Clay Brick w/ BUR Roof 3 500 35 12
Repoint Recaulk
N/A 1 SF Brick 25% of wall 25% of wall
GWP 0.00000 79,171.40738 4,192.20575 0.82005
Ecotox 0.00000 69.45923 10.53279 0.00050












Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Clay Brick w/ No Modification 3 500 35 12
Repoint Recaulk
N/A 1 SF Brick 25% of wall 25% of wall
GWP 0.00000 78,953.62842 4,192.20575 0.82005
Ecotox 0.00000 69.32714 10.53279 0.00050
Acid 0.00000 13,356.51772 536.71512 0.19511

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Wood (Two Coats) w/ Green
Roof 1 25 12 5
1 SF Wood + 1 Recaulk Scrape,
N/A SF Paint 25% of wall sand + paint
GWP 0.00000 85,818.86551 0.82005 515.40650
Ecotox 0.00000 211.17507 0.00050 1.49603
Acid 0.00000 50,549.05671 0.19511 158.70143

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Wood (Two Coats) w/ TPO
Roof 1 25 12 5
1 SF Wood + 1 Recaulk Scrape,
N/A SF Paint 25% of wall sand + paint
GWP 0.00000 85,885.87491 0.82005 515.40650
Ecotox 0.00000 211.21572 0.00050 1.49603
Acid 0.00000 50,564.93491 0.19511 158.70143

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Wood (Two Coats) w/ BUR
Roof 1 25 12 5
1 SF Wood + 1 Recaulk Scrape,
N/A SF Paint 25% of wall sand + paint


198


Acid


0.00000


13,408.12151


536.71512


0.19511











Ecotox 0.00000 211.32750 0.00050 1.49603
Acid 0.00000 50,608.60639 0.19511 158.70143

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Wood (Two Coats) w/ No
Modification 1 25 12 5
1 SF Wood + 1 Recaulk Scrape,
N/A SF Paint 25% of wall sand + paint
GWP 0.00000 85,785.37036 0.82005 515.40650
Ecotox 0.00000 211.15476 0.00050 1.49603
Acid 0.00000 50,541.11987 0.19511 158.70143

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Aluminum Siding w/ Green
Roof 2 35 35 12
N/A 1 SF Siding Repaint Recaulk wall
GWP 0.00000 108,422.02665 427.42942 0.82005
Ecotox 0.00000 1,021.84465 1.38848 0.00050
Acid 0.00000 18,725.51690 97.26076 0.19511

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Aluminum Siding w/ TPO
Roof 2 35 35 12
N/A 1 SF Siding Repaint Recaulk wall
GWP 0.00000 108,472.15414 427.42942 0.82005
Ecotox 0.00000 1,021.87505 1.38848 0.00050
Acid 0.00000 18,737.39485 97.26076 0.19511

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Aluminum Siding w/ BUR
Roof 2 35 35 12
N/A 1 SF Siding Repaint Recaulk wall


199


GWP


0.00000


86,070.17783


0.82005


515.40650











Ecotox 0.00000 1,021.98683 1.38848 0.00050
Acid 0.00000 18,781.06179 97.26076 0.19511

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Aluminum Siding w/ No
Modification 2 35 35 12
N/A 1 SF Siding Repaint Recaulk wall
GWP 0.00000 108,405.13838 427.42942 0.82005
Ecotox 0.00000 1,021.83441 1.38848 0.00050
Acid 0.00000 18,721.51514 97.26076 0.19511


200


GWP


0.00000


108,656.43796


427.42942


0.82005









APPENDIX D
DELL'ISOLA MODEL SERVICE LIFE AND MAINTENANCE INTERVAL IMPACTS


201










Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Built Up Roof w/ Brick Wall 1 20 1
Transportation- 1 SF Membrane,
0.75 gallons Insulation & 0.3min per ft2
Resource Required gasoline Ballast Roof = 1% of roof
GWP 0.35 17,009.22112 170.09221
Ecotox 0.00 68.89527 0.68895
Acid 0.11 3,406.41472 34.06415

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Built Up Roof w/ Aluminum
Wall 1 20 1
Transportation- 1 SF Membrane,
0.75 gallons Insulation & 0.3min per ft2
Resource Required gasoline Ballast Roof = 1% of roof
GWP 0.35 17,094.97845 170.94978
Ecotox 0.00 68.94739 0.68947
Acid 0.11 3,425.79302 34.25793

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Built Up Roof w/ Wood Wall 1 20 1
Transportation- 1 SF Membrane,
0.75 gallons Insulation & 0.3min per ft2
Resource Required gasoline Ballast Roof = 1% of roof
GWP 0.35 17,179.06298 171.79063
Ecotox 0.00 68.99849 0.68998
Acid 0.11 3,444.79333 34.44793

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Built Up Roof w/ No
Modification 1 20 1
Transportation- 1 SF Membrane,
0.75 gallons Insulation & 0.3min per ft2
Resource Required gasoline Ballast Roof = 1% of roof


202











Ecotox 0.00 68.78132 0.68781
Acid 0.11 3,364.04671 33.64047

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Thermoplastic w/ Brick Wall 1 20 1
Transportation- 1 SF Insulation, 0.2min per ft2
0.75 gallons membrane & Roof = 0.5% of
Resource Required gasoline sealant roof
GWP 0.35 17,912.74 89.56369
Ecotox 0.00 63.96 0.31981
Acid 0.11 2,735.35 13.67677

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Thermoplastic w/ Aluminum
Wall 1 20 1
Transportation- 1 SF Insulation, 0.2min per ft2
0.75 gallons membrane & Roof = 0.5% of
Resource Required gasoline sealant roof
GWP 0.35 17,956.50 89.78248
Ecotox 0.00 63.99 0.31995
Acid 0.11 2,745.24 13.72621

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Thermoplastic w/ Wood Wall 1 20 1
Transportation- 1 SF Insulation, 0.2min per ft2
0.75 gallons membrane & Roof = 0.5% of
Resource Required gasoline sealant roof
GWP 0.35 18,037.21 90.18606
Ecotox 0.00 64.04 0.32019
Acid 0.11 2,763.48 13.81741

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair


203


GWP


0.35


16,821.72444


168.21724










Thermoplastic w/ No
Modification 1 20 1
Transportation- 1 SF Insulation, 0.2min per ft2
0.75 gallons membrane & Roof = 0.5% of
Resource Required gasoline sealant roof
GWP 0.35 17,849.72 89.24858
Ecotox 0.00 63.92 0.31962
Acid 0.11 2,721.11 13.60557

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Green Roof w/ Brick Wall 1 30 1
Transportation-
0.75 gallons 0.5 min per ft2
Resource Required gasoline 1 SF Roof = 1% of roof
GWP 0.35 20,743.91823 207.43918
Ecotox 0.00 64.89621 0.64896
Acid 0.11 2,732.18054 27.32181

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Green Roof w/ Aluminum
Wall 1 30 1
Transportation-
0.75 gallons 0.5 min per ft2
Resource Required gasoline 1 SF Roof = 1% of roof
GWP 0.35 20,785.95672 207.85957
Ecotox 0.00 64.92176 0.64922
Acid 0.11 2,741.67984 27.41680

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Green Roof w/ Wood Wall 1 30 1
Transportation-
0.75 gallons 0.5 min per ft2
Resource Required gasoline 1 SF Roof = 1% of roof
GWP 0.35 20,850.69857 208.50699


204











Acid 0.11 2,756.30934 27.56309

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Green Roof w/ No
Modification 1 30 1
Transportation-
0.75 gallons 0.5 min per ft2
Resource Required gasoline 1 SF Roof = 1% of roof
GWP 0.35 20,743.91823 207.43918
Ecotox 0.00 58.02882 0.58029
Acid 0.11 2,732.18054 27.32181

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Clay Brick w/ Green Roof 3 75 15
Repoint 4
Transportation- min/ft2 =
0.75 gallons 14% mortar
Resource Required gasoline 1 SF Brick replacement
GWP 0.00000 78,953.62842 2,437.52
Ecotox 0.00000 69.32714 5.90
Acid 0.00000 13,356.51772 300.56

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Clay Brick w/ TPO Roof 3 75 15
Repoint 4
Transportation- min/ft2 =
0.75 gallons 14% mortar
Resource Required gasoline 1 SF Brick replacement
GWP 0.00000 78,987.12357 2,437.52
Ecotox 0.00000 69.34746 5.90
Acid 0.00000 13,364.45456 300.56

Inspection/ Minor Inspections Major Minor Major Minor


205


Ecotox


0.00


64.96111


0.64961











Clay Brick w/ BUR Roof 3 75 15
Repoint 4
Transportation- min/ft2 =
0.75 gallons 14% mortar
Resource Required gasoline 1 SF Brick replacement
GWP 0.00000 79,171.40738 2,437.52
Ecotox 0.00000 69.45923 5.90
Acid 0.00000 13,408.12151 300.56

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Clay Brick w/ No
Modification 3 75 15
Repoint 4
Transportation- min/ft2 =
0.75 gallons 14% mortar
Resource Required gasoline 1 SF Brick replacement
GWP 0.00000 78,953.62842 2,437.52
Ecotox 0.00000 69.32714 5.90
Acid 0.00000 13,356.51772 300.56

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Wood (Two Coats) w/ Green
Roof 2 40 5
Transportation-
0.75 gallons 1 SF Wood + 1 0.5 min/ft2 =
Resource Required gasoline SF Paint 1% of wall

GWP 0.00000 85,818.86551 858.1886551
Ecotox 0.00000 211.17507 2.111750717
Acid 0.00000 50,549.05671 505.4905671

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Wood (Two Coats) w/ TPO
Roof 2 40 5


206


Clean Up


Replacement


Replacement


Repair


Repair












Resource Required


Transportation-
0.75 gallons
gasoline


1 SF Wood + 1
SF Paint


0.5 min/ft2 =
1% of wall


GWP 0.00000 85,885.87491 858.8587491
Ecotox 0.00000 211.21572 2.11215716
Acid 0.00000 50,564.93491 505.6493491

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Wood (Two Coats) w/ BUR
Roof 2 40 5
Transportation-
0.75 gallons 1 SF Wood + 1 0.5 min/ft2 =
Resource Required gasoline SF Paint 1% of wall
GWP 0.00000 86,070.17783 860.7017783
Ecotox 0.00000 211.32750 2.113275041
Acid 0.00000 50,608.60639 506.0860639

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Wood (Two Coats) w/ No
Modification 2 40 5
Transportation-
0.75 gallons 1 SF Wood + 1 0.5 min/ft2 =
Resource Required gasoline SF Paint 1% of wall
GWP 0.00000 85,785.37036 857.8537036
Ecotox 0.00000 211.15476 2.111547554
Acid 0.00000 50,541.11987 505.4111987

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Aluminum Siding w/ Green
Roof 2 50 8
Transportation- 2 min
0.75 gallons clean/ft2 +
Resource Required gasoline 1 SF Siding 0.2 % of wall
GWP 0.00000 108,422.02665 652.78


Ecotox


0.00000


1,021.84465


4.99


207












Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Aluminum Siding w/ TPO
Roof 2 50 8
Transportation- 2 min
0.75 gallons clean/ft2 +
Resource Required gasoline 1 SF Siding 0.2 % of wall
GWP 0.00000 108,472.15414 652.88
Ecotox 0.00000 1,021.87505 4.99
Acid 0.00000 18,737.39485 133.63

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Aluminum Siding w/ BUR
Roof 2 50 8
Transportation- 2 min
0.75 gallons clean/ft2 +
Resource Required gasoline 1 SF Siding 0.2 % of wall
GWP 0.00000 108,656.43796 653.25
Ecotox 0.00000 1,021.98683 4.99
Acid 0.00000 18,781.06179 133.72

Inspection/ Minor Major Minor Major Minor
Clean Up Inspections Replacement Replacement Repair Repair
Aluminum Siding w/ No
Modification 2 50 8
Transportation- 2 min
0.75 gallons clean/ft2 +
Resource Required gasoline 1 SF Siding 0.2 % of wall
GWP 0.00000 108,405.13838 652.75
Ecotox 0.00000 1,021.83441 4.99
Acid 0.00000 18,721.51514 133.60


208


Acid


0.00000


18,725.51690


133.61









APPENDIX E
RS MEANS MODEL SERVICE LIFE AND MAINTENANCE INTERVAL IMPACTS


209










Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Built Up Roof
w/ Brick Wall 1 5 28 20 15 1
Repair 25 %
Place new of roof: 4
membrane over plies of
Transportation- Transportation- existing: 4 ply bituminous Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons bituminous roofing + 2 plies of glass
Required gasoline gasoline Replace Roof roofing insulation mopped,
GWP 0.71 0.35 17,009.22112 574.80453 4,252.30528 5.74805
Ecotox 0.00 0.00 68.89527 0.36132 17.22382 0.00361
Acid 0.22 0.11 3,406.41472 137.33188 851.60368 1.37332

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Built Up Roof
w/ Aluminum
Wall 1 5 28 20 15 1
Repair 25 %
Place new of roof: 4
membrane over plies of
Transportation- Transportation- existing: 4 ply bituminous Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons bituminous roofing + 2 plies of glass
Required gasoline gasoline Replace Roof roofing insulation mopped,
GWP 0.71 0.35 17,094.97845 574.80453 4,273.74461 5.74805
Ecotox 0.00 0.00 68.94739 0.36132 17.23685 0.00361
Acid 0.22 0.11 3,425.79302 137.33188 856.44826 1.37332

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Built Up Roof
w/Wood Wall 1 5 28 20 15 1


210













Transportation-
0.75 gallons
gasoline


Transportation-
0.75 gallons
gasoline


Replace Roof


Place new
membrane over
existing: 4 ply
bituminous
roofing


Repair 25 %
of roof: 4
plies of
bituminous
roofing +
insulation


Repair 2% of roof:
2 plies of glass
mopped,


GWP 0.71 0.35 17,179.06298 574.80453 4,294.76575 5.74805
Ecotox 0.00 0.00 68.99849 0.36132 17.24962 0.00361
Acid 0.22 0.11 3,444.79333 137.33188 861.19833 1.37332

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Built Up Roof
w/ No
Modification 1 5 28 20 15 1
Repair 25 %
Place new of roof: 4
membrane over plies of
Transportation- Transportation- existing: 4 ply bituminous Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons bituminous roofing + 2 plies of glass
Required gasoline gasoline Replace Roof roofing insulation mopped,
GWP 0.71 0.35 16,821.72444 574.80453 4,205.43111 5.74805
Ecotox 0.00 0.00 68.78132 0.36132 17.19533 0.00361
Acid 0.22 0.11 3,364.04671 137.33188 841.01168 1.37332

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Thermoplastic
w/ Brick Wall 1 5 25 20 1
Replace 25%
of roof: install
insulation +
Transportation- Transportation- 150 mils Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons modified install 150 mils
Required gasoline gasoline Replace Roof bitumen modified bitumen
GWP 0.71 0.35 17,912.74 4,478.18471 358.25478


211


Resource
Required











Acid 0.22 0.11 2,735.35 683.83862 54.70709

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Thermoplastic
w/ Aluminum
Wall 1 5 25 20 1
Replace 25%
of roof: install
insulation +
Transportation- Transportation- 150 mils Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons modified install 150 mils
Required gasoline gasoline Replace Roof bitumen modified bitumen
GWP 0.71 0.35 17,956.50 4,489.12384 359.12991
Ecotox 0.00 0.00 63.99 15.99737 1.27979
Acid 0.22 0.11 2,745.24 686.31050 54.90484

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Thermoplastic
w/Wood Wall 1 5 25 20 1
Replace 25%
of roof: install
insulation +
Transportation- Transportation- 150 mils Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons modified install 150 mils
Required gasoline gasoline Replace Roof bitumen modified bitumen
GWP 0.71 0.35 18,037.21 4,509.30292 360.74423
Ecotox 0.00 0.00 64.04 16.00964 1.28077
Acid 0.22 0.11 2,763.48 690.87030 55.26962

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Thermoplastic 1 5 25 20 1


212


Ecotox


0.00


0.00


63.96


15.99072


1.27926










w/ No
Modification
Replace 25%
of roof: install
insulation +
Transportation- Transportation- 150 mils Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons modified install 150 mils
Required gasoline gasoline Replace Roof bitumen modified bitumen
GWP 0.71 0.35 17,849.72 4,462.42875 356.99430
Ecotox 0.00 0.00 63.92 15.98115 1.27849
Acid 0.22 0.11 2,721.11 680.27830 54.42226

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Green Roof w/
Brick Wall 1 5 35 25 19 5
Repair 25 %
Place new of roof: 4
membrane over plies of
Transportation- Transportation- existing: 4 ply bituminous Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons bituminous roofing + 2 plies of glass
Required gasoline gasoline Replace Roof roofing insulation mopped,
GWP 0.71 0.35 20,743.91823 9,587.13240 2,396.78310 95.87132
Ecotox 0.00 0.00 64.89621 6.87039 1.71760 0.06870
Acid 0.22 0.11 2,732.18054 1,171.55087 292.88772 11.71551

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Green Roof w/
Aluminum
Wall 1 5 35 25 19 5
Repair 25 %
Place new of roof: 4
membrane over plies of
Transportation- Transportation- existing: 4 ply bituminous Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons bituminous roofing + 2 plies of glass
Required gasoline gasoline Replace Roof roofing insulation mopped,


213











Ecotox 0.00 0.00 64.92176 6.87039 1.71760 0.06870
Acid 0.22 0.11 2,741.67984 1,171.55087 292.88772 11.71551

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Green Roof w/
Wood Wall 1 5 35 25 19 5
Repair 25 %
Place new of roof: 4
membrane over plies of
Transportation- Transportation- existing: 4 ply bituminous Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons bituminous roofing + 2 plies of glass
Required gasoline gasoline Replace Roof roofing insulation mopped,
GWP 0.71 0.35 20,850.69857 9,587.13240 2,396.78310 95.87132
Ecotox 0.00 0.00 64.96111 6.87039 1.71760 0.06870
Acid 0.22 0.11 2,756.30934 1,171.55087 292.88772 11.71551

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Green Roof w/
No
Modification 1 5 35 25 19 5
Repair 25 %
Place new of roof: 4
membrane over plies of
Transportation- Transportation- existing: 4 ply bituminous Repair 2% of roof:
Resource 0.75 gallons 0.75 gallons bituminous roofing + 2 plies of glass
Required gasoline gasoline Replace Roof roofing insulation mopped,
GWP 0.71 0.35 20,743.91823 9,587.13240 2,396.78310 95.87132
Ecotox 0.00 0.00 64.89621 6.87039 1.71760 0.06870
Acid 0.22 0.11 2,732.18054 1,171.55087 292.88772 11.71551

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair


214


0.711


GWP


0.35


20,785.95672


9,587.13240


2,396.78310


95.87132










Clay Brick w/
Green Roof 3 75 25 25
Transportation-
0.75 gallons Repair = 1% Repoint = 80% of
gasoline 1 SF Brick of wall wall
GWP 78,953.62842 4192.205753 3,353.76460
Ecotox 69.32714 10.53279 8.42623
Acid 13,356.51772 536.71512 429.37209

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Clay Brick w/
TPO Roof 3 75 25 25
Transportation-
0.75 gallons Repair = 1% Repoint = 80% of
gasoline 1 SF Brick of wall wall
GWP 78,987.12357 4192.205753 3,353.76460
Ecotox 69.34746 10.53279 8.42623
Acid 13,364.45456 536.71512 429.37209

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Clay Brick w/
BUR Roof 3 75 25 25
Transportation-
0.75 gallons Repair = 1% Repoint = 80% of
gasoline 1 SF Brick of wall wall
GWP 79,171.40738 4192.205753 3,353.76460
Ecotox 69.45923 10.53279 8.42623
Acid 13,408.12151 536.71512 429.37209

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Clay Brick w/
No 3 75 25 25


215










Modification
Transportation-
0.75 gallons Repair = 1% Repoint = 80% of
gasoline 1 SF Brick of wall wall
GWP 78,953.62842 4192.205753 3,353.76460
Ecotox 69.32714 10.53279 8.42623
Acid 13,356.51772 536.71512 429.37209

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Wood (Two
Coats) w/
Green Roof 1 45 5
Transportation- Scrape, repair,
0.75 gallons 1 SF Wood + 1 refinish + 1 SF
gasoline SF Paint paint
GWP 85,818.86551 515.40650
Ecotox 211.17507 1.49603
Acid 50,549.05671 105.80095

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Wood (Two
Coats) w/ TPO
Roof 1 45 5
Transportation- Scrape, repair,
0.75 gallons 1 SF Wood + 1 refinish + 1 SF
gasoline SF Paint paint
GWP 85,885.87491 515.40650
Ecotox 211.21572 1.49603
Acid 50,564.93491 105.80095

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair


216










Wood (Two
Coats) w/
BUR Roof 1 45 5
Transportation- Scrape, repair,
0.75 gallons 1 SF Wood + 1 refinish + 1 SF
gasoline SF Paint paint
GWP 86,070.17783 515.40650
Ecotox 211.32750 1.49603
Acid 50,608.60639 105.80095

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Wood (Two
Coats) w/ No
Modification 1 45 5
Transportation- Scrape, repair,
0.75 gallons 1 SF Wood + 1 refinish + 1 SF
gasoline SF Paint paint
GWP 85,785.37036 515.40650
Ecotox 211.15476 1.49603
Acid 50,541.11987 105.80095

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Aluminum
Siding w/
Green Roof 35 20
1 SF Siding Clean + detergent
GWP 108,422.02665 520.09942
Ecotox 1,021.84465 1.38849
Acid 18,725.51690 118.34876

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair


217










Aluminum
Siding w/ TPO
Roof 35 20
1 SF Siding Clean + detergent
GWP 108,472.15414 520.09942
Ecotox 1,021.87505 1.38849
Acid 18,737.39485 118.34876

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Aluminum
Siding w/ BUR
Roof 35 20
Clean + detergent
1 SF Siding + refinish
GWP 108,656.43796 520.09942
Ecotox 1,021.98683 1.38849
Acid 18,781.06179 118.34876

Inspection/
Minor Clean Major Minor Major
Up Inspections Replacement Replacement Repair Minor Repair
Aluminum
Siding w/ No
Modification 35 20
1 SF Siding Clean + detergent
GWP 108,405.13838 520.09942
Ecotox 1,021.83441 1.38849
Acid 18,721.51514 118.34876


218









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BIOGRAPHICAL SKETCH

Aneurin Grant is currently a Ph.D. student in the School of Building Construction.

He is interested in the topics of global sustainability, green construction techniques,

urban planning, and legal and policy issues. His current area of specialization includes

Life Cycle Assessment and building assessment methods, with particular emphasis on

temporal and spatial context.


231





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1 THE CONFLUENCE OF LIFE CYCLE ASSESSMENT AND SERVICE LIFE PREDICTION: AN ANALYIS OF THE ENVIRONMENTAL IMPACT OF MATERIAL LONGEVITY IN THE BUILDING ENVELOPE By ANEURIN THOMAS JAMES GRANT A DISSERTATION PRESENTED TO THE GRADU ATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2010

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2 2010 Aneurin Thomas James Grant

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3 T o my father, Brian Eric James Grant who passed away u nex pectedly on October 29, 2007 We all miss you

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4 ACKNOWLEDGMENTS I am extremely grateful for the time, effort and support of my advisors, friends and family over the last five years. I would like to recognize Dr. Charles Kibert who several years ago and facilitated my admission to the Ph. D. program as my main advisor. Dr. Kibert has empowered me, and given me the rarest of opportunities. I will always be grateful for t his He has always provided support, encouragement an d inspiration. I would like to thank Dr. Robert Ries who m I met half way through this journey I am especially grateful to Dr. Ries for his persistence. During a two year hiatus, Dr. Ries kept in touch with me, provided crucial guidance, and never let go. I dare say this document would remain incomplete without hi m. Hi s investment in this work was complete, and for me this created a personal obligation of sorts I am thankful to Dr. Abdol Chini, who has always been supportive of my research and career. Dr. Chini has given me fair and realistic advice throughout my time at the University of Florida I am glad to have had him as an advisor and friend throughout this process. I am sincerely grateful to Dr. Mang Tia. He has participated fully in the formati on of this dissertation, been extremely flexible and given valuable feedback during committee meetings. I will always be thankful for his service. I am grateful for all those who collaborated with this research process by providing guidance, direction, or leads of any kind toward it conclusion I am especially grateful t o those who have laid the scientific foundation for this work. I look forward to participating in the discourse more in the future. I am thankful to my older sister, who has always been supporti ve of everything I do Due to distance, her support does not always manifest in physical form, but moral

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5 support is just as good as anything My sister understands me in a way that few people ever will She has always been a constant upon which I know I ca n rely. I love her. I would like to thank my mother who has been steadfast throughout my first thirty five years, and hopefully well beyond She has adapted to her new role as dual parent quite well. I am always grateful for her guidance, love and support because it is unconditional I love her too. I would like to thank Claudia, Olivia and Roque who tolerate me every day. I am not always the best I can be, but I certainly try. In many ways, the production of this work is as much about you as it is about m e. There is an added purpose to this work that is not possible without your love, support and daily brilliance. Finally, I would like to thank those who have contributed to this work indirectly. It is not practical to list all of you by name of course, but I have certainly not come to this point in my life alone. I have always been well accompanied and have benefitted from the many and diverse friendships that have formed my existence Thank you.

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6 TABLE OF CONTENTS page AC KNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF FIGURES ................................ ................................ ................................ .......... 8 ABSTRACT ................................ ................................ ................................ ................... 15 CHAPTER 1 INTRODUCTIO N ................................ ................................ ................................ .... 16 Statement of the Problem ................................ ................................ ....................... 16 Hypothesis ................................ ................................ ................................ .............. 17 Objective and Contri bution ................................ ................................ ...................... 17 2 LITERATURE REVIEW ................................ ................................ .......................... 19 A Tale of Two Methods ................................ ................................ ........................... 21 Time as a Context ................................ ................................ ................................ ... 23 The Durability and Service Life Argument ................................ ............................... 27 Survival and Metabolism ................................ ................................ ......................... 33 Service Life Prediction ................................ ................................ ............................ 41 The Factor Method ................................ ................................ ........................... 44 Probabilistic Methods ................................ ................................ ....................... 51 Empirical Data and Reliability Models ................................ .............................. 54 Hybrids and the State of the Art ................................ ................................ ....... 55 Life Cycle Assessment ................................ ................................ ............................ 56 Life Cycle Assessment in Buildings The Functional Unit ............................... 58 Life Cycle Assessment by Life Cycle Stage ................................ ..................... 64 The Confluence of Service Life Prediction and Life Cycle Assessment .................. 67 Variability ................................ ................................ ................................ ................ 71 3 METHODOLOG Y ................................ ................................ ................................ ... 75 Energy Modeling ................................ ................................ ................................ ..... 76 Life Cycle Assessment ................................ ................................ ............................ 79 Service Life Model s ................................ ................................ ................................ 81 4 RESULTS ................................ ................................ ................................ ............... 94 Life Cycle Impact Models with Energy Differentials ................................ ................ 94 Global Warming Potential ................................ ................................ ................. 94 Atmospheric Ecotoxicity ................................ ................................ ................... 95 Atmospheric Acidification ................................ ................................ ................. 95 Life Cycle Impact Models Energy Neutral ................................ ............................. 96

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7 Global Warming Potential ................................ ................................ ................. 96 Atmospheric Ecotoxicity ................................ ................................ ................... 97 Atmospheric Acidification ................................ ................................ ................. 98 Life Cycle Impact Models Coarse Models ................................ ............................ 99 Gl obal Warming Potential ................................ ................................ ................. 99 Atmospheric Ecotoxicity ................................ ................................ ................... 99 Atmospheric Acidification ................................ ................................ ............... 1 00 Averages of Cumulative Life Cycle Impacts Models ................................ ............. 100 Cumulative Life Cycle Impact Envelope Combinations ................................ ...... 101 Life Cy cle Impact Per Year Individual Materials ................................ ................. 103 Global Warming Potential ................................ ................................ ............... 104 Atmospheric Ecotoxicity ................................ ................................ ................. 105 Atmospheric Acidification ................................ ................................ ............... 105 Maintenance Versus Coarse Models ................................ ................................ .... 106 5 DISCUSSION, CONCLUSION, T HE FUTURE ................................ ..................... 174 Conclusions ................................ ................................ ................................ .......... 175 The Future ................................ ................................ ................................ ............ 176 APPENDIX A MATERIAL QU ANTITY TAKE OFF ................................ ................................ ...... 179 B USACE MODEL SERVICE LIFE AND MAINTENANCE INTERVAL IMPACTS .... 183 C ATHENA MODEL SERVICE LIFE AND MAINTENANCE IN TERVAL IMPACTS 193 D IMPACTS ................................ ................................ ................................ .............. 201 E RS MEANS MODEL SERVICE LIFE AND MAINTENA NCE INTERVAL IMPACTS ................................ ................................ ................................ .............. 209 LIST OF REFERENCES ................................ ................................ ............................. 219 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 231

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8 LIST OF FIGURES Figure p age 3 1 Building Envelope Combination Used in Energy Modeling Analysis ................... 77 3 2 Wall Modifications Required to Equalize T hermal Performance of Walls ........... 78 3 3 Roof Modifications Required to Equalize Thermal Performance of Walls ........... 79 3 5 Athena Service Li fe Model Activity Description and Frequency .......................... 86 3 7 RS Means Service Life Model Activity Description and Frequency .................... 90 3 7 Continu ed ................................ ................................ ................................ ........... 91 3 8 50 Year Static Service Life Model Activity Description and Frequency ............... 92 4 1 Energy Consumption of Building Envelope Co mbinations ................................ 107 4 2 Global Warming Potential USACE Energy Differential ............................... 108 4 3 Global Warming Potential Athena Energy Diff erential ................................ 108 4 4 Global Warming Potential Energy Differential ............... 109 4 5 Global Warming Potential ola and Kirk Energy Differential ............... 109 4 6 Global Warming Potential 50 Year Static Energy Differential ...................... 110 4 7 Atmospheric Ec otoxicity USACE Energy Differential ................................ .. 110 4 8 Atmospheric Ecotoxicity Athena Energy Differential ................................ .... 111 4 9 Atmospheric Ecotox icity Energy Differential ................... 111 4 10 Atmospheric Ecotoxicity Energy Differential .................. 112 4 11 Atmospheric Ecotoxicity 50 Year Static Energy Differential ....................... 112 4 12 Atmospheric Acidification USACE Energy Differential ................................ 113 4 13 Atmospheric Acidification Athena Energy Differential ................................ .. 113 4 14 Atmospheric Acidification Energy Differential ................. 114 4 15 Atmospheric Acidification Energy Differential ................ 114 4 16 Atmospheric Acidification 50 Year Static Energy Differential ...................... 115

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9 4 17 Global Warming Potential USACE Energy Neutral ................................ ..... 115 4 18 Global warming Potential Athena Energy Neutral ................................ ....... 116 4 19 Global Warming Potential Energy Neutral ...................... 116 4 20 Global Warming Potential RS Means Energy Neutral ................................ 117 4 21 Global Warming Potential 50 Year Static Energy Neutral .......................... 117 4 22 Atmospheric Ecotoxicity USACE Energy Neutral ................................ ....... 118 4 23 Atmospheric Ecotoxicity Athena Energy Neutral ................................ ........ 118 4 24 Atmospheric Ecotoxicity Energy Neutral ........................ 119 4 25 Atmospheric Ecotoxicity RS Means Energy Neutral ................................ ... 119 4 26 Atmospheric Ecotoxicity 50 Year Static Energy Neutral ............................. 120 4 27 Atmospheric Acidification USACE Energy Neutral ................................ ..... 120 4 28 Atmospheric Acidification Athena Energy Neutral ................................ ...... 121 4 29 Atmospheric Acidification Energy Neutral ...................... 121 4 30 Atmospheric Acidification RS Means Energy Neutral ................................ 122 4 31 Atmospheric Acidification 50 Year Static Energy Neutral ........................... 122 4 32 Global Warming Potential USACE Coarse Model ................................ ...... 123 4 33 Global Warming Potential Athena Coarse Model ................................ ....... 123 4 34 Global Warming Potential Coarse Model ...................... 124 4 35 Global Warming Potential RS Means Coarse Model ................................ .. 124 4 36 Atmospheric Ecotoxicity USACE Coarse Model ................................ ......... 125 4 37 Atmospheric Ecotoxicity Athena Coarse Model ................................ .......... 125 4 38 Atmospheric Ecotoxicity Coarse Model ......................... 126 4 39 Atmospheric Ecotoxicity RS Means Coarse Model ................................ ..... 126 4 40 Atmospheric Acidification USACE Coarse Model ................................ ....... 127 4 41 Atmospheric Acidification Athena Coarse Model ................................ ........ 127

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10 4 42 Atmospheric Acidification Coarse Model ....................... 128 4 43 Atmospheric Acidification RS Means Coarse Model ................................ .... 128 4 44 Global Warming Potential All Models Energy Neutral ................................ 129 4 45 Atmospheric Ecotoxicity All Models Energy Neutral ................................ ... 129 4 46 Atmospheric Acidification All Models Energy Neutral ................................ 130 4 47 Global Warming Potential Aluminum with Green Roof Energy Neutral ...... 130 4 48 Global Warming Potential Aluminum with TPO Roof Energy Neutral ......... 131 4 50 Global Warming Potential Brick with Green Roof Energy Neutral .............. 132 4 52 Global Warming Potential Brick with Built Up Roof Energy Ne utral ............ 133 4 53 Global Warming Potential Wood with Green Roof Energy Neutral ............. 133 4 54 Global Warming Potential Wood with TP O Roof Energy Neutral ................ 134 4 55 Global Warming Potential Wood with Built Up Roof Energy Neutral .......... 134 4 56 Atmospheric Ecotox icity Aluminum with Green Roof Energy Neutral ......... 135 4 57 Atmospheric Ecotoxicity Aluminum with TPO Roof Energy Neutral ............ 135 4 58 Atmospheric Ecotoxicity Aluminum with Built Up Roof Energy Neutral ...... 136 4 59 Atmospheric Ecotoxicity Brick with Green Roof Energy Neutral ................. 136 4 60 Atmospheric Ecotoxicity Brick with TPO Roof Energy Neutral .................... 137 4 61 Atmospheric Ecotoxicity Brick with Built Up Roof Energy Neutral .............. 137 4 62 Atmospheric Ecotoxicity Wood with Green Roof Energy Neutral ................ 138 4 63 Atmospheric Ecotoxicity Wood with TPO Roof Energy Neutral .................. 138 4 64 Atmospheric Ecotoxicity Wood with Built Up Roof Energy Neutral ............. 139 4 65 Atmospheric Ecotoxicity Aluminum with Green R oof Energy Neutral ......... 139 4 66 Atmospheric Ecotoxicity Aluminum with TPO Roof Energy Neutral ............ 140 4 67 Atmospheric Ecotoxicity Aluminum with Built Up Roof Energy Neutral ...... 140 4 68 Atmospheric Ecotoxicity Brick with Green Roof Energy Neutral ................. 141

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11 4 69 Atmospheric Ecotoxicity Brick with TPO Roof Energy Neutral .................... 141 4 70 Atmospheric Ecotoxicity Brick with Built Up Roof Energy Neutral .............. 142 4 71 Atmospheric Ecotoxicity Wood with Green Roof Energy Neutral ................ 142 4 72 Atmospheric Ecotoxicity Wood with TPO Roof Energy Neutral .................. 143 4 73 Atmospheric Ecotoxicity Wood with Built Up Roof Energy Neutral ............. 143 4 75 Global Warming Potential Life Cycle Impact Per Year Aluminum ............... 144 4 76 Global Warming Potential Life Cycle Impact Per Year Trendline Aluminum 144 4 77 Global Warming Potential Life Cycle Impact P er Year Brick ....................... 145 4 78 Global Warming Potential Life Cycle Impact Per Year Trendline Brick ....... 145 4 79 Global Warming Potenti al Life Cycle Impact Per Year Wood ...................... 146 4 80 Global Warming Potential Life Cycle Impact Per Year Trendline Wood ...... 146 4 81 Global Warming Potential Life Cycle Impact Per Year Green Roof ............ 147 4 82 Global Warming Potential Life Cycle Impact Per Year Trendline Green Roof ................................ ................................ ................................ .................. 147 4 83 Global Warming Potential Life Cycle Impact Per Year TPO Roof ............... 148 4 84 Global Warming Potential Life Cycle Impact Per Year Trendline TPO Roof ................................ ................................ ................................ .................. 148 4 85 Global Warming Potential Life Cycle Impact Per Year Built Up Roof ......... 149 4 86 Global Warming Potential Life Cycle Impac t Per Year Trendline Built Up Roof ................................ ................................ ................................ .................. 149 4 87 Global Warming Potential Life Cycle Impact Per Year All Materials Average ................................ ................................ ................................ ............ 150 4 88 Atmospheric Ecotoxicity Life Cycle Impact Per Year Aluminum ................. 150 4 89 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Aluminum .. 151 4 90 Atmospheric Ecotoxicity Life Cycle Impact Per Year Brick ......................... 151 4 91 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Brick ......... 152 4 92 Atmospheric Ecotoxicity Life Cycle Impact Per Year Wood ........................ 152

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12 4 93 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Wo od ........ 153 4 94 Atmospheric Ecotoxicity Life Cycle Impact Per Year Green Roof ............... 153 4 95 Atmospheric Ecotoxicity Life Cycle Impa ct Per Year Green Roof ............... 154 4 96 Atmospheric Ecotoxicity Life Cycle Impact Per Year TPO Roof ................. 154 4 97 Atmospheric Ecotoxici ty Life Cycle Impact Per Year Trendline Green Roof 155 4 98 Atmospheric Ecotoxicity Life Cycle Impact Per Year Built Up Roof ............ 155 4 99 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Built Up Roof ................................ ................................ ................................ .................. 156 4 100 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Average All Materials ................................ ................................ ................................ ...... 156 4 101 Atmospheric Acidification Life Cycle Impact Per Year Aluminum ............... 157 4 102 Atmospheric Acidification Life Cycle Impact Per Year Trendline Aluminum 157 4 103 Atmospheric Acidification Life Cycle Impact Per Year Brick ....................... 158 4 104 Atmospheric Ac idification Life Cycle Impact Per Year Trendline Brick ....... 158 4 105 Atmospheric Acidification Life Cycle Impact Per Year Wood ...................... 159 4 106 Atmospheric Acidification Life Cycle Impact Per Year Trendline Wood ...... 159 4 107 Atmospheric Acidification Life Cycle Impact Per Year Green Roof ............. 160 4 108 Atmospheric Acidification Life Cycle Impact Per Year Trendline Green Roof ................................ ................................ ................................ .................. 160 4 109 Atmospheric Acidification Life Cycle Impact Per Year TP O Roof ............... 161 4 110 Atmospheric Acidification Life Cycle Impact Per Year Trendline TPO Roof 161 4 111 Atmospheric Acidification Life Cycle Impact Per Year Built Up Roof .......... 162 4 112 Atmospheric Acidification Life Cycle Impact Per Year Trendline Built Up Roof ................................ ................................ ................................ .................. 162 4 113 Atmospheric Acidification Life Cycle Impact Per Year Average All Materials ................................ ................................ ................................ ........... 163 4 114 Global Warming Potential Life Cycle Impact Per Year Coarse Versus Maintenance Model s USACE ................................ ................................ ......... 163

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13 4 115 Global Warming Potential Life Cycle Impact Per Year Coarse Versus Maintenance Models Athena ................................ ................................ ......... 164 4 116 G lobal Warming Potential Life Cycle Impact Per Year Coarse Versus Maintenance Models ................................ ........................ 164 4 117 Global Warming Potential Life Cycle Impact Per Year Coarse Versus Main tenance Models RS Means ................................ ................................ .... 165 4 118 Atmospheric Ecotoxicity Life Cycle Impact Per Year Coarse Versus Maintenance Models USACE ................................ ................................ ........ 165 4 119 Atmospheric Ecotoxicity Life Cycle Impact Per Year Coarse Versus Maintenance Models Athena ................................ ................................ ......... 166 4 120 Atmospheric Ecotoxicity Life Cycle Impact Per Year Coarse Versus Maintena nce Models ................................ ........................ 166 4 121 Atmospheric Ecotoxicity Life Cycle Impact Per Year Coarse Versus Maintenance Models RS Means ................................ ................................ .... 167 4 122 Atmospheric Acidification Life Cycle Impact Per Year Coarse Versus Maintenance Models USACE ................................ ................................ ........ 167 4 123 Atmospheric Acidification Life Cycle Impact Per Year Coarse Versus Maintenance Models Athena ................................ ................................ ......... 168 4 124 Atmospheric Acidification Life Cycle Impact Per Year Coarse Versus Maintenance Models ................................ ........................ 168 4 125 Atmospheric Acidification Life Cycle Impact Per Year Coarse Versus Maintenance Models RS Means ................................ ................................ .... 169 4 126 Envelope Combination Ranking USACE Ener gy Differential, Energy Neutral and Coarse Global Warming Potential ................................ .............. 169 4 127 Envelope Combination Ranking Athena Energy Differential, Energy Neutral and Coarse Global Warming Potenti al ................................ .............. 170 4 128 Envelope Combination Ranking Energy Differential, Energy Neutral and Coarse Global Warming Potential ................................ .. 170 4 129 Envelope Combination Ranking RS Means Energy Differential, Energy Neutral and Coarse Global Warming Potential ................................ .............. 170 4 130 Envelope Combination Ranking USACE Ene rgy Differential, Energy Neutral and Coarse Atmospheric Ecotoxicity ................................ ................. 171

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14 4 131 Envelope Combination Ranking Athena Energy Differential, Energy Neutral and Coarse Atmospheric Ecotoxicity ................................ ................. 171 4 132 Envelope Combination Ranking Energy Differential, Energy Neutral and Coarse Atmospheric Ecotoxicity ................................ .... 171 4 133 Envelope Combination Ranking RS Means Energy Differential, Energy Neutral and Coarse Atmospheric Ecotoxicity ................................ ................. 172 4 134 Envelope Combination Ranking USACE Energy Di fferential, Energy Neutral and Coarse Atmospheric Acidification ................................ ............... 172 4 135 Envelope Combination Ranking Athena Energy Differential, Energy Neutral and Coarse Atmospheric Acidification ................................ ............... 172 4 136 Envelope Combination Ranking Energy Differential, Energy Neutral and Coarse Atmospheric Acidification ................................ .. 173 4 137 Envelope Combination Ranking RS Means Energy Differential, Energy Neutral and Coarse Atmospheric Acidification ................................ ............... 173

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15 Abstract of Dissertation Presented to the Graduate School of the University of Flo rida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy THE CONFLUENCE OF LIFE CYCLE ASSESSMENT AND SERVICE LIFE PREDICTION: AN ANALYIS OF THE ENVIRONMENTAL IMPACT OF MATERIAL LONGEVITY IN THE BUILDING ENVELO PE By Aneurin Thomas James Grant August 2010 Chair: Charles Kibert Cochair: Robert Ries Major: Design, Construction and Planning This work examine s the relationship between b uilding material longevity maintenance and life cycle environmental impact. M odels for material and system maintenance and replacement over the life of a building have not been widely used in building life cycle assessment st udies. This work has developed service life model s for buildings that feature life cy cle impact assessm ent m etrics. The results of such building life cycle assessment analyses are anticipated t o produce variation in accordance with the different service life intervals, and cumulative maintenance activities over time A total of thirty six roof and wall combinati ons have been modeled, using f ive alternative service life models. The results have been characterized with respect to Global Warming Potential, Atmospheric Ecotoxicity and Atmospheric Acidification as defined by the Tool for Reduction and Assessment of Ch emical and other Environmental Impacts (TRACI).

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16 CHAPTER 1 INTRODUCTION In the assessment of environmental impact various forms of Life Cycle Analyses have been developed to provi de comprehensive evaluations of products, designs, processes and material s These analyses are intended to pro vide a systems type perspective and an inventory of mass and energy flow over the cour se of an entire product life cycle. T he methodological premises for Life Cycle Analyses however have not been fully explored, nor con clusively established. Some standardization of method has been implemented the field of Life Cycle Analyses i t is widely believed that the proper constraint, exploration and refinement of method will yield improvement and a better understanding of the environmental impacts associated with human activity Statement of the Problem Life Cycle Analyses have been employed at numerous scales to better understand the metabolism of the built en vironment. To this end, analyses of the manufacture, transportation, construction, operation, maintenance and end of life scenarios associated with buildings and materials have achieved varying levels of success Yet, t he analysis of environmental impact i s heavily dependent on the principle of assumption Results will vary according to the particular method of Life Cycle Analysis, the environmental indicators to be analyzed practitioner interpretation and perhaps most importantly the scope of the study Issues of scope are especially important with respect to the analysis of a building. For instance, the creation of a system boundary or a functional unit is based purely on assumption and is meaningful only insofar as it serves as a point of comparison

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17 be tween subjective interpretations of conceptual models In other words, t he exclusion or inclusion of a particular mat erial or energy flow in Life Cycle Assessment may affect the outcome of study significantly; the inputs may be derived from any number of s ources, and for buildings, the magnitude of material and energy flow is so large it can be difficult to contain within a simple model On another level, the scoping of building analyses is complicated due to the prolonged service lives of buildings relativ e t o other systems Differences in material durability for example suggest that buildings are dynamic. Some components will last longer than others and maintenance requirements will vary according to the physical properties of the material Intuition asid e, many practitioners approach the Life Cycle Assessment of buildings from a static viewpoint, wherein dynamic material input and output are not considered. T hese assumptions therefore lead to a certain kind of environmental outcome. Hypothesis If the sta tic modeling of the life cycle of a building omits important material and energy inputs, then the Life Cycle I mpact will yield in complete results. By contrast, a dynamic life cycle model that includ e s the input, output and cycling of materials over the bui would contain important environmental impacts and yield a more accurate result It is hypothesized therefore that Life Cycle Impact varies depending on material longevity and differential durability, and that a dynamic Life Cycle Assessmen t model, including service life of materials and systems is required to better represent the environmental impact of the building life cycle and cumulative maintenance over time. Objective and Contribution The objective of this study is to examine the rela tionship between building material longevity maintenance and lif e cycle environmental impact. Dynamic m odels of

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18 material and system maintenance and replacement over time have not been widely used in building life cycle assessment st udies. In comparison w ith static Life Cycle Assessment models, it is believed that a dynamic study would yield a more comprehensive result, and a more accurate representation of material and building Life Cycle Impact Currently, there is no consensus as to the appropriate lif e cycle of a building. Contemporary methods of Service Life Prediction are relatively inexact, and the uniqueness of buildings prohibits any type of universal assumption. Perhaps more fundamentally, the certainty of Life Cycle Impact projections over prolo nged periods of time is undermined by dynamic performance degradation and potential improvements in technology. For instance, performance degradation is believed to accelerate toward the end of service life, such that more frequent and intense maintenance is required. Similarly, improvement s in technology may lessen the impact of the manufacture, operation and maintenance of a material or building but this becomes more speculative as predicted service life duration increases As such it is unclear as to whether buildings should be designed and constructed to endure in relative permanence, or if they should be designed and built as temporary structure s with subsequent service lives, adaptive reuse, deconstruction and recycling in mind. Ultimately, t he anal ysis contained within this document contributes to the body of knowledge in that it demonstrates the importance of service life in the modeling of Life Cycle Assessment in building s It is hoped that this study will lead toward more accurate representation s of material longevity in Life Cycle Assessment and greater care in the assumption of service life.

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19 CHAPTER 2 LITERATURE REVIEW The condition of the natural environment is changing. Human population continues to grow amid concerns of global warming, def orestation, topsoil erosion, desertification, water and food resource depletion, the pervasion and buildup of toxic and dangerous substances, the thinning and perforation of the ozone layer and the irreversible loss of biodiversity. As author Paul Hawken h The rate of population growth is particularly alarming. T he human population increased by 380,682 persons each day in 2009; an increase of 138,949,000 persons for the year. Proj ections of these numbers suggest that the human population will reach 9,421,000,000 by mid year 2050 (Population Reference Bureau 2010). At present, it is not clear that the planet can sustain this population. Forecasts of lifestyle adjustment range from c omplete collapse, austerity and darkness to the more palatable views of technological optimism, resource conservation and modest belt tightening. Only time will tell which forecast is accurate. However, there is no doubt that the growth of the human popula tion is converging with the carrying capacity of the planet. The debate intensifies when the rate of change is considered in conjunction with equity, environmental justice and the allocation of natural resources. The consumption of materials and energy, a nd the emission of waste is a lopsided affair. Marked differences in the affluence and wealth of nations are often indicative of this disparity. In Logically, issues of envi ronmental sustainability are now discussed in combination with those of global security.

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20 The problem is complex; representations of environmental gloom and doom have invoked a sense of urgency in many, yet economic and political interests are entrenched, there are positively billions of stakeholders, and science does not fully comprehend the issue of global sustainability, or the implications thereof. As such, any sc precautionary principle in formulating environmental legislation. L egislation of this ilk can be dubious as it is unclear whether the precautionary principle constitutes prudent avoidance, a regulation of risk, or the implementation of laws of fear (Sunstein 2005). Ultimately, further consensus and definition in sustainability as a whole are required. On a qualitative level, the definition of sustainability requires the reconcilia tion of dissimilar variables. Oftentimes, concessions and trade offs are built in to the environmental decision making process. Comparisons are often likened to those between apples and oranges (Piepkorn and Wilson 2005), or as in a more relevant example, those between mercury emissions and habitat loss. For comparisons such as these, there is no common unit of measurement. Furthermore, environmental priorities vary from region to region. Where water conservation may be the most important environmental conc ern in arid and overpopulated areas, global warming may be the most pressing concern in low lying or island settlements. Quantitative methods have also produced some discrepancy. Some suggest that the human population on the planet can only be sustained b y increasing present day productivity by a factor of four (Von Weizscker 1997) Competing viewpoints suggest that an increase of this magnitude would be insufficient, and that present day

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21 productivity would need to be improved by a factor of ten to be sust ainable. Similarly, models of ecological foot printing imply that an additional half planet of usable biomes would be required to sustain current rates of global extraction and consumption (Center for Sustainable Economy 2010). To complicate matters, the n umbers are always changing. The ecosphere is in a state of constant flux. We are therefore confronted with an amorphous and inadequately defined problem of gigantic proportions. Damage to the natural environment is well documented. Yet, there is no unifi cation. The paradigm is fallible. We are left with speculation, potential scenarios, an assortment of competing theories and some very compelling and egregious anecdotal evidence. All in all, these are fragments of a much larger puzzle. A Tale of Two Meth ods The idea of testing the environmental impacts of building material longevity requires the application of two complementary areas of research. In the assessment of environmental impact, Life Cycle Assessment (LCA) is a commonly used and widely accepted methodology. The results of a well designed LCA can be very useful in identifying or comparing the relative environmental impacts of a particular design, material or process. The method is intended to provide a comprehensive and informative assessment of m aterials flows from conception to the end of life In the area of Service Life Prediction issues of material longevity, durability and context have been clarified with the use of three principle approaches ; the factor method, p robabilistic methods and e mpirical reliability models. Each approach has positive and negative attributes, and most agree that there is an appropriate application for each depending on the degree of accuracy required

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22 There are some methodological issues with both Life Cycle Ass essment and Service Life Prediction. For instance Life Cycle Assessment has only recently been a pplied to the study of building s The required analyses are extremely complex systems are comprised of thousand of components and the magnitude of the mass a nd energy flow is huge. W hen a building is analyzed in a temporally dynamic and prolonged context the complexity of the assessment becomes amplified. Consequently, measurement F or Service Life Prediction, the main objective s are accuracy and utility D epending on the method that is used to predict or estimate service life accuracy and utility are said to vary accordingly Empirical or r eliability models are said to be the most accurate, but the collection of data requires a substantial investment of time Some methods have been based on the logic of probabilistic distributions and have shown a good range of accuracy, but require extended analysis and an expert knowledge of the agents of degradation In terms of utility, the factor method is preferred a lthough the resultant predictions are said to be the least accurate of a ll the methods (Davies and Wyatt 2004). The semantics of service li f e have also been examined. Indeed, t he re is some d ebate Ostensibly, the definition and the design F or e xam ple it has be en noted that the and problems of material preservation than

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23 The American Institute of Architects has also acknowledged alternativ e reasons for materials obsolescence citing a more insidious agent of deterioration, (Dempkin 1996). T he inaccuracies of Service Life Prediction have a direct bearing on Life Cycle Assessment methods As the two are interconnected, improv ements in Service Life Prediction methodologies will only result in more accurate accounts of environmental impact. In other words, the accurate assessment of environmental impact is dependent on the realistic representation and assumption of time. Time a s a Context There is a recurring theme in discussions of global sustainability and environmental impact that is not all at once obvious to the casual observer. Allusions to the future, predictions, estimations, forecasting and intervals pervade the literat ure. Of course, t he concept of time is implicit in each of these references. Reisch has argued that time is an e ssential component of any would be sustainable theory. He states that, currently there is no widely accepted meta theory of sustainable consump tion. In whatever form such a theory is proposed, the time factor has to be systematically included. (Reisch 2001). The re are many re a sons for including time as a context in the analysis of environmental issues. It has been argued that implicit uncertainti es make future projections questionable, as articulated in the following: Present investment tends to set the pattern for solving a particular problem over many years, regardless of whether or not the problem or indeed present knowledge about it will b e equally long lived, whether or not the lifetime of the technical installation is appropriate for the lifetime of the basic economic, social and ecological conditions, and whether or not the ecological problems are classified as taking a period o f exact, shorter or longer time durations to solve (Kummerer 1996)

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24 In reference to the economic and social conditions mentioned above, the analysis of environmentally friendly construction becomes more challenging. Costs and building function must also be considere d. On another level, the traditional concept of a building is typified by durability and permanence. Flexibility and adaptability have only recently been introduced as considerations in design. This view is shared by Adam et al, who lose sight of the larger temporal complexity which impresses on us the need for caution, care and precaution for situations where actions and inactions (Adam et al. 1997) In consideration of the relatively long service life of buildings, it seems further consideration should be given to future scenarios, predictions and the forecasting of adaptation and materials cycling. Many current studies and analyses project a static snap s hot, with no mention of dynamism or modification This needs to change. t is not in spite of our limited perceptions of time (and of our location in time), but rather because of it, that it is crucial to take account of time in ecological, economic In Material Flow Analysis, the inclusion of a temporally dynamic context is essential, and depending on a given set of scenarios, may cause wide variation in the assessment of environmental impact. To paraphrase Mater used in conjunction with other types of data, because it only illuminates some of the 2009). So, the issue is one context. Since consideration s of material flow management or nature conservation, for example, are centrally guided by the static thermodynamic conceptualization of equilibrium it is not surprising that changes over time (of human made material and energy flow, for example) are rare ly

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25 considered in discussions of type, degree and rate. Consequently, future developments for the environment are largely ignored (Kummerer 1996) In the analyses of building s it has also been recognized that temporal complexity plays a significant role in determining both economic and environmental impact. There are numerous examples of the importance of accurate Service Life Prediction throughout the literature on Life Cycle Costing ( Ashworth 1996; Rudbeck 2002; Barco 1994; Shohet and Laufer 1996; Dorris 1997; however is essentially the same ; when materials are placed i n the proper context of time, a more accurate assessment of economic and environmental impact results In Life Cycle Assessment, it has been stated t hat some basic hypotheses of the LCA methodology, such as time stability, do not cope well with the characteristics of buildings (Verbeeck and Hens 2010) Ozel and Kohler give a more expansive explanation, as follows: In the life cycle analysis of buildi ngs, the typical concern has to do with the flow of energy and mass due to initial construction, remodeling and demolition of buildings and their impact on the environment over a given period of time. Therefore, any effort to simulate this process must als o incorporate spatial as well temporal data into its structure. Databases that support such simulations must handle time dependent as well as spatially comprehensive data structures (Ozel and Kohler 2004) In continuation of this reasoning, the authors pr ovide the contrasting example s o f Life Cycle E nergy Assessment and static model s Herein, an assumption based on stasis is questioned These models are based on the assumption that the physical fabric of a building will remain static as the building ages, thus such simulations and Kohler 2004).

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26 The point of temporal complexity and context is further supported by Elrandsson and Borg, who argue that time based scenarios are an essential part of long lived analyses. A general impression is that it is considered that supplying marginal, average and best available technology LCI data satisfies the intention to cover the time dependence of LCA studies of build ings. This can, however, be insufficient if there is no possibility to build scenarios, which consider technical development that can change the studied system and the context of the studied system over time. This is especially important for long lived pro ducts as buildings, which can have a service life of about 100 years (2003). Trinius and Sjostrom have concluded that the performance of any meaningful analysis is contingent upon the inclusion of a temporal context. Furthermore, t hey argue that service li fe is one of the central parameters in building performance, as follows: Consideration of sustainability aspects must relate to service life and performance requirements, as the proper functionality and service duration are cornerstones in the performance of a building. When comparing different design options, performance aspects are the underlying factor. This also means that quantification of costs or environmental impacts without a common reference can be rather meaningless ( 2005). Beyond discussions of a need for temporal context, Hovde and Moser have concluded that Service Life Prediction can a ffect the results of a Life Cycle Assessment, and must be thought of as an essential pr ecursor to any form of life cycle building analysis They state the followi ng: The service life of a specific part will have a great influence on the outcome of an LCA of the complete object. Selection of alternative parts that have different service lives or where the service life varies depending on alternative maintenance proc edures, may also have a great influence on the overall outcome of the LCA (Hovde and Moser 2004). The literature indicate s a need for improved service life data, and the inclusion of said data in temporally (and spatially) dynamic modeling techniques. A ccu rate service life data is a

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27 (2005). Indeed, the argument is clear; Life Cycle Assessment methodologies require a temporal context to be meaningful. The Durability and Service Life A rgument In the area of green building and sustainable construction, it is often opined t hat buildings should be durable and long lived. As Browning and Honour have pointed out, most large, complex, and expensive systems are anticipated to have a fairly lo ng life cycle (2008). Some have argued to the contrary, and growing bodies of research on lean construction, adaptable architecture and deconstruction suggest a design imperative other than permanence A few have suggested that the only green building is t he one that is never built. O ther s endorse a l ess extreme version of this notion, suggest ing that the built environment should be geared toward more temporary structures, prefabricated buildings or even yurts (McDonough and Braungart 2002) Despite all of the argument and opinion, the idea of testing the environmental impacts of building and material longevity is fairly new. In many ways therefore, it seems premature to advocate one side or the other. As follows, a summary of the literature on building and material durability and service life shows that the argument is in full swing, although it is not clear how many of the claims can be substantiated. For example, Nireki asserts that durability is an important performance factor in buildings. Durability is an important factor that cannot be ignored when considering the performance of building. Moreover, the recent social requirements for durability have become greater arising from various aspects such as the effective use of natural resources and saving ene rgy, improvement of service life, effective use of existing stock in good condition as a social investm ent ( 1996)

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28 It is not altogether clear that durability results in energy savings or an improvement in the existing building stock. When durability is use d as a basis of comparison, on e might ascertain that differing service lives are appropriate based on a proportional differential i n environmental impact. However the assertion requires some further explanation. T he Canadian Green Building Council has imp lemented a LEED standard which departs from the version set forth by the United States Green Building Council. One of the most notable differences in the Canadian standard is the presence of Regional Priority Credit 1 As state d in the latest version o f the Canadian standard for New Construction achievement of the credit is dependent on the development and implementation of a Building Durability principles in CSA S478 95 (R2007) Guideline on Dura bility in Buildings The Guideline is a Canadian Standards Association document, and provides some suggestions on service and design life, maintenance and component replacement. The potential technologies and strategies suggested to achieve the credit are stated as follows: Design strategies for building durability that will minimize premature deterioration of the walls and roof, while harmonizing and integrating Architectural, Mechanical, Landscape and Electrical performance requirements, and meet the nee ds of the owner and contractor Appropriate technologies and strategies must be appropriate to the region (Canadian Green Building Council 2009). The wording of this green building credit is difficult to dispute. As is evident in the literature on Servic e Life Prediction, regional appropriateness implies a lower degree of green building objective, although nothing is said here about design flexibility. Herein,

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29 the concep t of temporal dynamism is limited to appropriate maintenance and replacement over time. In a similarly static manner of thinking, there is no but that should not condemn an individual building material to a single scenario over its lifetime. Spat ial and temporal dynamism, as they are characteristics of most buildings over their lifetimes, suggest otherwise. Bogenstatter has taken a similar stanc e toward building material longevity, as follows: An important criterion for external aspects and preservation of value is the average useful life of buildings as well as their elements. A long term use is also an ecological target. The ecological value is the inverse of the sum of impacts caused during the lifetime or over the lifetime of an element or building. This means that properties should be used for as long as possi ble ( 2000) irrefutable. However, the process is implies. Future scenarios may include advances in technology and design retrofit options that cause the building to change. Furthermore, e xtending the service life of a particular component requires more frequent and higher quality maintenance an aspect of materials cycling that Coop er has also overlooked, as described in the following excerpt: Increased product life spans, whether through greater intrinsic durability or better c are and maintenance, may enable such problems to be overcome by providing for both efficiency and sufficiency. They are a means by which materials are used more productively (i.e., the same quantity provides a longer service) and throughput is slowed (i.e. products are replaced less frequently) ( 2005 ). While the comments above show inclination tow ard a particular point of view, the author longer lasting products are a prerequisite for sustainable consumption to

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30 undertake life cycle assessments of products with different life spans and publish the findings (Cooper 2005). Mora argues that the extension of service life is linked and commensurate with production impact Mora states the s far as construction is concerned, if we were to increase the durability of concrete works from 50 to 500 years, factor 10 would be a measure of the reduction of the environmental impact ( 2007). However, t he assumption is too simplistic. A comparison of two mixes of concrete with such widely different service lives would surely yield a different environmental impact, be made from different proportions of Portland cement and require different types and frequencies of mainte nance during the course of their lifetimes. Likewise, an assumption of 500 years assumes a relatively static building function and virtually no potential scenario where technological improvements warrant replacement or improvement In fairness, Mora points understanding of temporal dynamism is implicit. Similar viewpoints and general conclusions that durability is positive attribute of building performance have been expressed by a number of other researchers (van de Flier 2009; Dorris 2007; Hassler 2009; Barco 1994) Beyond basic durability, the discussion on service life turns toward adaptability. There are many different forms of adaptation, including renovation, the replacement of individual systems, facility expansion and simple upgrades. It is for reasons of adaptability, that the modeling of building in Life Cycle Assessment is so challenging, as alluded to in previous comments regarding scenarios. Slaughter has articulated th e adaptability argument, as follows:

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31 The usefulness of these facilities is often compromised by their inability to accommodate changes over time. It is not economical or resource efficient to design and build facilities that have only a short functional li fe, since a facility that prematurely reaches the end of its useful life reduces the effective time period over which benefits could be obtained, and increases the effective cost of demolition and waste disposal, thereby reducing the return on the initial investment ( 2001) The ideal of design for adaptability is also supported by Brown ing and Honour, designers must consider not only how to meet specifications that will satisfy stakeholders today but also the trajectories of markets and tec hnologies that will Thomsen and van der Flier have suggested that life cycle extension of any manifestation generally results in a lower environmental impact, as described in the follo wing: The environmental impact of life cycle extension by renovation, transformation and life cycle extension is, in general, less harmful than replacement by new construction. Renovation, transformation and lifecycle extension deserve public support. (200 9). An earnest assessment of the arguments for both simple durability and building flexibility reveals a middle ground of sorts. It must be possible after all for a building to be both durable and adaptable. Fishman et al have warned that durability may l ead to technological stagnation. This is in line with the observations of Kummerer, who has stated that future uncertainties require added precaution in current day design. Fishman et al. explain the potential stagnation a follows: Excess durability is ass ociated with stagnation in two senses. First, continuous innovation must be associated with the production of non durables and stagnation with the production of durables. Second, in the intermediate range of development costs, for which both outcomes are e quilibria, stagnation results if the social convention is to produce durables, while continuous innovation is enabled by the convention of producing non durables. Thus pressure from consumer groups that promote "excessive" product durability may retard the development of new products and technologies (1993)

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32 The authors contend that stagnation and service life are inter related, and indeed, in the context of time, their argument regarding planned obsolescence is difficult to refute as follows lanned obs olescence may be a necessary condition for the achievement of technological progress and that a pattern of rapidly deteriorating products and fast innovation may be preferred to long lasting products and slow innovation (Fishman et al 1993) An article by Horvath illustrates a more comprehensive assessment of durability and longevity, stating that service life should be determined based on shorter life cycles or planned maintenance Horvath states the following: Functional obsolescence of facilities (when t hey no longer serve their users satisfactorily) dictates that they should be either designed for shorter life spans or for continuous maintenance and periodic, complete renovations that extend their useful life. Some facilities may be overdesigned given th eir actual service life. It is commonly assumed that parts of the built environment last for a long time. This is true for much of the infrastructure that is perpetually maintained and periodically renovated or reconstructed (e.g., roads, railways), but it is not necessarily true for all facilities (2004). These comments are accurate insofar as certain types of buildings are more conducive to long life, while others are expected to serve a particular purpose for a shorter term In essence, there are two sid es to the debate on service life Some feel that building s and their components should be durable, with extended service lives. Others believe that extended service life may compromise our ability to make decisions and adapt in the future While opinions a nd assertions abound, the claims are largely unsubstantiated. The idea itself therefore need s to be tested. A method needs to be developed. A means of measuring the environmental impact of durability, service life and material longevity needs to be impleme nted

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33 Survival and Metabolism Examinations of material flows can be performed on individual buildings, or at a much larger scale. In consideration of the literature on the metabolism of the built environment and mortality models, an important contribution is noted in the form of estimates of building stock survivability A lthough these estimates make no differentiation between building or material type, they are relevant in the sense that they reiterate and ther eby enforce the findings o f other areas of ser vice life research. In other words, large variation in service life estimates are seen in the literature on mortality and metabolism, a brief summary of which is as follows. As noted by Kohler and Yang, an estimate of material flows can be accomplished us ing a survival analysis. The authors state that this can be done building/infrastructure stocks backwards in time to find out how many objects have been built and how many have disappeared Using this method, Kohler and Yang were able t o de termine a trend in building mortality, noting that [of buildings] have much higher survival probabilities and that the newer age classes will disappear Yet, the conclusions of Kohler and Yang are somewhat static i n terms of temporal context, as is evident in the following excerpt. From the analysis of the survival functions of other stocks it appears that the Life Cycle Analysis allows to establish long term balances of resource consumption and environmental impact s showing that identical results can be obtained either by reducing resource inputs and impacts or by raising the lifetime of the functional unit (spreading the inputs/impacts over a longer period (2007). This conclusion promotes the slowing of metabolism, either through a reduction of resource inputs or by extending service life as the principle means of reducing environmental impact. As previous discussions on the uncertainty of the future and

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34 technological advancement have made clear, extending service life may also create stagnation. It seems appropriate to extend the service life of the individual components and materials, but not as part of an obsolescent system. B uildings are energy sinks, and should be capable of technological adaptation, even if th ere are constructed of durable materials. A similar conclusion is drawn by Johnstone, who states the following: The energy and mass flows required to sustain dwelling services are dependent on the building materials used for housing, the durability and eco nomic life of building components, the mortality of the housing stock, the proportion of surviving dwellings which undergo rehabilitation at each successive event of rehabilitation, and the expa nsion rate of the housing stock (Johnstone II 2001) As in Koh ler and Yang, Johnstone has concluded that energy and mass flows will be diminished or slow ed down through extensions of building stock service life. However, this idea requires elaboration The extension of the service lives of obsolete systems may have a n effect that is contrary to that desired While the proportion of energy associated with the mass flow of building materials may be dimi ni shed in this regard the flow of energy in the built environment is not uniquely driven by the production, use and di sposal of materials. Buildings require a tremendous and constant source of energy to provide basic operation Furthermore, i nnovations in technology suggest that inflexible building designs are more likely to become obsolete with the passage of time. M ost have suggested that a combination of materials reduction, reuse and recycling will help to slow t he metabolism of the built environment In turn, measurements of materials throughp ut are a precursor to sustainable materials management. Wernick has observe d that material consumption trends in the U.S. are

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35 decidedly hard to predict, owing the influence of technological innovation and the inescapability of temporal context. Wernick writes the following Sustaining the U.S. economy requires consuming large amo unts of materials. The mix of materials changes with time, and these changes matter from the perspective of environmental quality. The question of whether Americans will consume more or less materials i n the future depends on demographic, economic, and tec hnical variables difficult, if not impossible to predict. One central question is: can increases in materials efficiency keep pace with or even triumph over the forces driving increased consumption ? (1996). It is widely believed that reductions in material throughput or the slowing of the metabolism in the built environment embodies a movement toward sustainab ility Temporal context suggests a dichotomy: energy is embodied in the building materials that comprise the built environment of course However, ene rgy is also required in the operation of a building and therefore constitutes a bifurcation of the mass energy flow as it is commonly understood Thus, t he solution to this problem is not as simple as using less material. Reductions in material cycling mus t be measured in concert with energy efficiency goals and the consumption of energy resources as they might be utilized in the operations phase of a building Brattebo et al. have alluded to the dichotomy in the mass and energy flow of the built environmen t, and is so doing, reinforced the idea of dynamism. If the main objective of metabolic analysis is to move toward the sustainable consumption of materials and energy, Brattebo et al. suggest that a greater understanding of change over time is necessary. T hese challenges, and the analytical approaches to meet them, will probably be fairly similar for a different type of the built environment stocks. Common to all such stocks are their long lifetimes, high material consumption, high life cycle energy consump tion, ageing phenomena, and barely documented and not w ell understood. ( 2009)

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36 Another article by Joh n stone suggests dynamism and wide variation in housing stock mortality. Mo re importantly, Joh n stone has indicated that building stock survivability is often longer than a standard 50 year analysis would portend and dependent on many factors (2001 ) The application of these ideas in the standard Life Cycle Assessment of building s would be transformative. It suggests that a n analysis requires context, assessments of differential durability and detailed information about the agents of degradation especially so in the case of building analysis Additional work on stock mortality a nd survivability has been contribut ed by several authors (Bradley and Kohler 2007; Bergsdal et al 2007 ; Bergsdal et al II 2007 ). information about the lifetime of dwellings is very scarce, and there is no consensus in the li terature o n what distribution best reflects the actual dwelling lifetime. ( 2007) Similarly, an analysis of the literature on Life Cycle Assessment has revealed wide variation in materials durability data. Evidently, it has become necessary to investigate the available data on service life more thoroughly, and to apply these data through temporally dynamic life cycle models. Differential Durability The concept of differential durability in building materials seems fairly straightforward. Implicit differenc es in building material composition and decomposition suggest that some materials last longer than others. The concept of differential durability has been well illustrated by Kesik and Saleff, as exemplified in the following passage. A practical example of interdependent durability is the case of bricks and brick ties, where the former often deliver a longer service life than the latter. When the inferior durability component reaches the end of its useful service life, the superior durability component is o ften replaced at the same time,

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37 resulting in an underutilization of its durability. The lesser the degree of durability harmonization, and the greater the degree of difference in initial service quality between components, the greater the underutilized or wasted durability (embodied energy) of the assembly. This underutilization has a direct impact on the recurring embodied energy demand over the building life cycle (2005) ely, underutilized of wasted durability, the concepts are brought up as a preamble to a discussion on structural longevity. As discussed previously, extended service life is of questionable value if the system itself is obsolete. While the cycling of build ing envelopes on a static and seemingly permanent structure connotes a limited flexibility of sorts s tructural adaptation and building function modification are not mentioned at all. it is not their main point. Rather, Kesik and Saleff are referring to a sort of ancillary durability, whereby the expiration of one material leads to the ancillary expiration of another. It is a fairly straightforward point, further articulated in the fo llowing paragraph Differential durability is normally not desired within building envelope components and assemblies, where it should ideally be harmonized, but it can form part of a staged building sustainability strategy between systems. Selection of an extremely durable structural system (armature) can accommodate a succession of building envelope assemblies (skins) provided their components exhibit harmonized durability and are designed for obsolesce nce (i.e., ease of replacement) (2005) Dimoudi and Tompa have also characterized differential durability as major concern in the assessment of the environmental impact of buildings. Again, the authors recognize the compatibility of adjacent components and materials, as follows: As far as construction pra ctices are concerned, additional criteria should be considered like the lifetime of building materials, the compatibility of the different materials and of the different layers, their m aintenance nee ds over the building life cycle (2008)

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38 In the comparison of a single system, the concept of differential durability serves an important role in the pl (Kesik and Sale ff 2005) In turn, the recognition of differential durability prompts an immediate need for the comparison of distinct building materials and their degradation subject to environmental conditions. Here, things get much trickier, as the current science of s ervice life prediction is imprecise For example, Bogenstatter has argued that there is very little scientific basis in the assignment of some service life data, with ranges of 40 to 100 years being applied to different buildings regardless of their com position, as described in the following excerpt: Regulations presume a service life of buildings between 40 and 100 years. Differences are made according to the use of buildings despite their material composition. With regard to sustainable use of building s, the time span is the main point to be considered. In fact, the technical life span of buildings is determined by the maintenance rate of its components. Nothing prevents using the primary systems of a building for 100 years or more. It also works out ad vantageously for the environment and costs ( 2000) Bognestatter does not elaborate on the aggregated impacts of maintenance activities, which can potentially increase service life and consequently environmental impact Conversely, decreased maintenance freq uency may reduce building service life, while simultaneously lowering environmental impact. As such, the benefits of system longevity may be questionable. Data of a similar range has been published by Brattebo et al. Again, it is not clear where the data originated. Assumed lifetimes for each application type in residential buildings are the following: lighting fixtures, 20 years; small capacitors, 30 years; window sealants, 25 years; and all others, 100 years. Assumed lifetimes for non residential buildi ngs are: lighting fixtures, small capacitors and window sealings, 30 years; and others, 100 years ( 2009) Numbers in these ranges can be contrasted with a multitude of other studies. For

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39 example, a study by Kosareo and Ries assumes a service life of 15 yea rs for a conventional ballasted roof and 45 years for a green roof, with the eventual conclusions t he materials needed to construct the roof are important when the energy needs are reduced, and when roof replacement cycles are short green roofs are the environmentally preferable choice when constructing a building due to the small reduction in energy demand and the increased life of the roofing membrane ( 2007) R ecognition of differential durability is also evident in the work of Rudbeck, wherein proposed method ological modifications are suggested for the economic assessment of low slope roofing. The study schedules roofing replacement every 22 service lif e, which is assumed to 60 years according to the study ( 2002) Rudbeck does not suggest that the service life of low slope roofing ought to equal the service life of the building. Rather it is evident that the periodic replacement of roofing would affect the economic assessment of building systems considerably. Paulsen provides yet another example of differential durability in his assessment of different flooring systems. Paulsen states that the service life for different flooring systems may range from 5 40 years, depending on the particular determinants of the technical service life, such as economical or aesthetic for example. The Paulsen study is particularly relevant in that flooring maintenance activities are integrated into the Life Cycle Assessme nt, and therefore become part of the Li fe Cycle Impact of the process. These benefits of more frequent maintenance however are not seen to affect the service life of the material in any way, while intuitively such maintenance extends service life (Paulsen 2003)

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40 Salazar and Sowlati provide another example of differential durability in their analysis of window frame material s The authors attained explicit service life data for the different materials by distributing in which it w as found that aluminum clad wood windows provided the longest service, 46.7 years, with aluminum second. 43.6 years, wood third, 39.6 years, and PVC providing the shortest service, 24.1 years. 2008). In the resulting analysis, the authors make an importa nt conclusion: PVC, aluminum clad wood, and fiberglass are all comparable in cradle to gate emissions and that the primary determinant of a life cycle advantage stems from a longer service life and lower replacement frequency. This conclusion is of cours e dependent on the validity and the accuracy of the service life data retrieved from the Presumably a survey of this type would yield an accurate representation of material longevity. Yet, this cannot be confirmed with an y degree of certain ty. Service l ife varies depending on factors of environmental degradation, assembly design and the frequency of maintenance amongst a number other variables. The se factors may also be location specific. Therefore, the conclusions of this study are only as valid as the determining data of window frame service life. A number of other studies have recognized differential s in material longevity In Shohet and Laufer, the differential durability of like materials is shown to be depen dent on environmental exposu re ( 1996) Although it is not the e x plicit f o cus o f the study, Kellenberger and Althaus r ecogni ze differential durability in their Life Cycle Assessment study o f building components. The authors allude to a constant influx and efflux of materials by statin g that certain layers of the building are replaced. ( 2009) In Scheuer et al., a university building i s modeled over the course of 75 years

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41 ( 2003) The authors als o recognize differential durability in the study as many of the materials are replaced at different intervals. As the authors con clude differential durability is one of the main difficulties in the modeling of a building (Scheuer et al 2003) Ultimately, t he concept of differential durability is relevant to two scenarios in particular. First, in the planning, design and assembly of composite building forms such as walls and roofs, it is important to recognize the durability of each individual component, as the failure of one material may cause the failure of the entire system Indeed, t he inextricability of the individual components makes prem ature, wasted, underutilized or ancillary durability an issue Second, if individual components are subject to implicit difference s in durability, this is als o true for building materials in general. Thus, it i s appropriate to view building s as composites of individual materials, and a s groupings of material assembly systems with different service lives Service Life Prediction The prediction of service life for a building or building material is at times depicted as more of an art than a science (Foliente and Leicester 2008) or as Lacasse and Sjostrom have put it, 2005) Service Life Prediction is challenging for a number of reasons. Primarily, Service Life Prediction is made difficult in that it becomes necessary to ascribe numerical values to assessments of degradation that are essentially defined by qualities. An extension of this idea is put forth by Bourke and Davies who state tha the point at which service life ends is loosely defined ( 1997) Bourke and Davies may be alluding to the determinants of service life and proffered by the International O rganization for Standardization who state that service life can be determined by any one of the following factors: structural performance,

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42 weather tightness, aesthetics, comfort and hygiene, health and safety, energy efficiency, need for maintenance and repair, economic performance, response to foreseeable hazards, and technical and p hysical o bsolescence (ISO Part 1 2000). In accordance with the se determinants A shworth has observed that the conclusion of expectancies depending on whether the physi cal, economic, functional, technological or social and legal obsolescence is the paramount factor in 1996) To characterize Service Life Prediction as more of an art than a science is somewhat unfair. Many applications of service life prediction studies have yielded plausible results. Howe ver, as high degrees of variability in Service Life Prediction are encountered throughout the literature further thought must be given to the refinement of method, and the consideration of time and p otential scenarios. T here are numerous approaches to the prediction of service life for buildings and building mate rials. As desc ribed previously, there are three general methodological areas: the factor me thod, probabilistic approaches and empirical reli ability models. The met h ods are said to range in terms of difficulty and degree of accuracy, such that e ach method has inherent strengths and weaknesses. For example, the factor method is said to be the most utilitarian, expedient and accessible method, al though the assignment and appropriate quantification of qualitative factors has produced a fair amount of debate Methods focused on probabilistic methods are designed to provide an accurate range of potential service life figures, although a fair amount l abor and expertise are required, and these are commodities not commonly possessed in the associated fields of building construction. Reliability models based on empirical data gathering are widely

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43 believed to be the most accurate, yet location specific sur veys require a significant investment in time Two such studies have produced some counterintuitive results, noting that the determinants of service life are not necessarily related to the technical or mechanical properties of the materials For example, T rusty and Argeles ( 2005) and Aikivuori ( 1999) have argued that durability is much less of a factor in determining a based the termination of service life on the C records between 2000 and 2003. The authors contend that service life is often condition (non structural), poor adaptability, or th at the maintenance of the bui lding is too expensive. As convincing as the results of this study may be, it seems premature to exclude material degradation as a determining factor in service life st Furthermore, t he analysis of City demolition records over the course of three years involves a specific sample of the building stock. The study does not elaborate on potential differences between the sto ck of building analyzed and other potential stocks. Even so, the study confirms what the ISO standards profess; that service life is determined b y a number of factors, some of w hich do not necessarily pertai n to material degradation ( 2005) The Aikivuori study brought similar conclusions, although in this case, the author recognize s the influence of subjectivity. Empirical research has been carried out to find out the actual reasons for initiation of repair projects on buildings. This research has shown t hat the

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44 owners of the buildings actually experienced the user requirements predominantly outside of the range of durability failures. Only 17 % of the repair projects were initiated primarily because of deterioration. The critical loss of performance seems to primarily be in the range of a subjective perception of the building. Very little technical or economical rationality can be seen in the actual decisions made on building refurbishment. In most cases the limiting factor for service life is not durabili ty ( 1999) Independent of the alternative determinants of service life offered by Trus ty and Argeles, and Aikivuou the utilization of empirical data represents one of the most effective means of predicting service life. Unfortunately, as Soronis has obser ved, comprehensive sets of empirical data are in short supply ( 1996) not relevant to the climatic region in question, or part of larger proprietary datasets. More often than not, the researcher is left without a relevant source of empirical data. The Fact or Method The factor method is perhaps the most commonly practiced form of service life prediction. It has been the focus of several major national, international and private organizations, and as compared with some of the other methods outlined above, has the reputation of being the most user friendly. The Architectural Institute of Japan (AIJ) is often credited as the originator of the factor method, with the publication of the Principal Guide for Service Life Planning of Buildings in 1989, an English edi tion of which was published in 1993 (AIJ 1993) In turn, the AIJ publication was instrumental in the formulation of the International Organization for Standardization (ISO) Standard 15686 1, Building and Constructed Assets Service Life Planning Part I, a widely recognized guideline for the application of the factor method in the prediction of service life of buildings (ISO Part 1 2000) Further discussion of the factors has been contributed at the national level by the British Standards Institution (Britis h Standards Institution 1992) and the Canadian Standards Association (Canadian Standards

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45 Association 1995) who has attempted to provide insight to the service life prediction of buildings and buildings components according to local environmental factors, q uality of materials and construction practices. It should be noted however that the factors described in the British and Canadian standards are also intended to be relevant to other types of Service Life Prediction. Guidelines have also been produced by th e European Commission via the European Construction Products Directive, Guidance Paper F Durability and the Construction Products Directive (European Commission 2004) Perhaps the most extensive body of work on the factor method stems from the collaborativ e efforts of the International Council for Research and Innovation in Building Conferences on Durability of Building Materials and Components has ensured a steady stream of pu blications and cutting edge theory. In addition, CIB Working Commission W080 Prediction of Service Life of Building Materials and Components, in conjunction with the International Union of Laboratories and Experts in Construction Materials, Systems and St ructures (RILEM), has further compiled a comprehensive set of working papers, reference materials and sources of data. Variations of the factor method have also been used in the sphere of liability to assess maintenance and insurance requirements and the p otential for defects. For example, the Chartered Institution of Building Services Engineers has compiled an appendix of economic life factors for building services (CIBSE 2000) and the Building Performance Group (BPG 1999) and Housing Association Property Mutual ( Construction Audit Limited 1992 ) have put together component life manuals with

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46 listings of factors and reference service lives for a multitude of building components and materials. However, it should be noted that the figures presented in these ma nuals represent insured service lives, and are consequently conservative in nature. The factor method is perhaps most widely recognized as stated in the ISO Standard 15686 1, whereby the formula is laid out as follows: ESLC = RSLC x factor A x factor B x factor C x factor D x factor E x factor F x factor G. The factors are defined as follows factor A: quality of components factor B: design level factor C: work execution level factor D: indoor environment factor E: outdoor environment factor F: in use cond itions factor G: maintenance level (ISO Part 1 2000). Herein, ESLC refers to the Estimated Service Life of the Component and RSLC refers to the Reference Service Life of the Component. The factors, as mentioned throughout the literature are the main sour each factor will equal 1, and the Estimated Service Life of the Component will equal the Reference Service Life of the Component. Under less favorable conditions, the factors will be adjusted to a value less tha n one, and the Estimated Service Life of the Component will decrease in relation to the Reference Service Life of the Component. Conversely, more favorable conditions would assign factors greater than 1, thereby increasing the Estimated Service Life of the component in relation to the Reference Service Life of the Component. The factors themselves offer an overview of the science of Service Life Prediction, since methods employing the principles of structural engineering or probabilistic approaches will var y according to the same influences.

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47 As defined in Factor A, the quality of the component is an important factor in determining service life. For example, there is a great deal of difference between lumber produced from a 10 year old pine tree sapling and lumber produced from the heartwood from a 100 year old Giant Sequoia. By the same token, there is a great deal of difference between the various alloys of steel, mixes of concrete and types of brick. Theoretically, Factor A varies according to the quality of the component; the higher the inherent quality of the material, the higher the value attributed to Factor A. Factor B refers to the design level; in other words, the way which materials are positioned in relation to or affixed to the larger structure an d/or each other. For example, service life may vary if materials are exposed to direct sun or protected by the shade, or if the materials are compatible and do not engender premature degradation. Further, Factor B may refer to the degree to which sealants and fixtures are designed into the building, and the level at which materials are joined together. For example, a curtain wall with poorly designed sealant and gaskets will logically have a shorter service life. Another example is given in an article by St azi et al, who observed differential durability characteristics depending on environmental exposure. In their study, the authors cracks, which are present corresponding to the joints between the insulation panels, are due to overheating a nd differential temperature dilatation; the extent of the damage is greater on the south face where there are more temperature changes. ( 2009) study examines differences in thermal stress re lated fatigue in the building envelope in consideration of building orientation ( 2008). Again, the service life of the assembly is dependent on the building orientation, and therefore the design might be adjusted to

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48 achieve the desired service life. Servic e life is also dependent of the type of material that certain materials such as cera mics or clay materials, may be more resistant to the effect of hotter climates ( 2008). Factor C refers to the level of craftsmanship involved in the construction of the building. As Assaf et al. have observed, the quality of construction and installation h as a direct bearing on the longevity of the materials and the building as a whole ( 1995) F aulty construction is an obvious determinant of service life. However, it should not be confused with the design level. For example, a comprehensive sealant plan may be part design level (Factor B) would be higher than 1, and the factor for work execution (Factor C) would be lower than 1. Factor D refers to the condition of the in door environment. For some materials, this factor may not be applicable, as their design function is strictly exterior. However, for those materials that are affected by the interior condition of the building, Factor D would account for differences in humi dity or in the instance of an industrial application, the presence of chemicals. In these instances, the ESLC would need to be adjusted accordingly as these factors constitute an aggressive environment. Similarly, if the indoor environment is favorable for a given material, the factor would need to be adjusted to reflect conditions that are better than the norm. Factor E is slightly more complex, owing to the multitude of factors that apply to the external environment that may not necessarily apply to the i ndoor environment. For

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49 example, ambient temperature, humidity, the frequency of driving rain or freeze thaw periods, the presence of Ultra Violet (UV) radiation, air pollutants, pollutants present in precipitation and driving wind may all be viewed as fact ors influencing the longevity of service life vis vis the exterior environment. Factor E is also complicated by the fact that many of these factors may work in concert, compounding the appropriate quantification. Westberg et al have observed that the cu rrent use of environmental degradation factors requires some adjustment to the site, and tha data is often collected at some distance from any specific building and the actual exposure environment adjacent to the building (i.e. at the micro level) can be substantially different. While databases and models established for other purposes may be employed for service life estimations, substantial adaptive work remains to bring this method p ractical and general in terms of different materials and locations. Issues not resolved concern, for instance, data format (time intervals, type of values, statistical parameters, presentation methods etc), accuracy of data (degree of approximation), data failure (errors, lack of data etc). In future work, these problems will be addressed and the concept developed and implemented into practical software tools for engineers. Being selected as test materials, initially the applicability for different material s will be studied for wood and rende red autoclaved aerated concrete (2001) Factor F refers to the in use conditions, or the level of use to which a building is subjected. In many circumstances, this factor is applied to the interior of the building, but i n some circumstances, may just as readily be applied to the exterior. For example, in the case of a flooring material, the service life may vary widely depending on the amount of traffic or punishment it is subjected to. In a study of flooring materials, P aulsen has acknowledged that the degree of use plays is an important deter minant of service life ( 2003). Likewise, the lifespan of materials with operable or mechanical components will vary significantly depending on use, and perhaps more importantly, the

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50 intensity of use. Again, appropriate factors must be assigned according to the relative degree and intensity of use Factor G, or the level of maintenance applied to a certain material, will also affect service life significantly. Ashworth for example has observed that the service life of It can be argued that if a building is properly designed and constructed then it can be maintained almost indefinitely. There are many examples in buildings where the original components remain in use for hundreds of years ( 1996) Indeed, the level of maintenance can affect the service life of a given building or building material in very profound way. Another example of the effe c ts of maintenance is offere d by Ozel and Kohler. The the decision to paint a building component such as a door, controls the aging process, thus affecting the component both directly and indirectly. Not only will the door now have a new color, but will also age d ifferently due to the protection afforded by the paint ( 2004). Mirza warns that deferred maintenance can result is a host of building problems, including compromised longevity. Deterioration of infrastructure has a negative impact on facility performance The consequences of neglecting or deferring maintenance are reflected in a shortened facility life, premature replacement, at high costs to society; high operating costs; and a waste of natural and financial resources. Maintenance is defined as the set o f activities undertaken to keep a facility in a fully functioning or operating condition or to return the facility to such a state; and to ensure long lastin g benefits to the users. ( 2006) Similarly, a number of studies have recognized the relationship bet ween maintenance and life cycle the technical life span of buildings is determined by the maintenance rate of its components. ( 2000)

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51 Likewise, Mendes Silva and Falorca have recognized a correlation between mai ntenance and durability over time ( 2009). In general, the factor method encompasses the logic of service life prediction, such that the factors are generally recognized as the causes of degradation for every service life prediction approach. The quantifica tion of the causes of degradation however constitutes the significant difference from one method to another. In many cases, this quantification is much more scientific, derived from actual tests, or based on the interaction of mechanical, mineralogical or chemical properties. Often times, statistical methods are employed to make sense of the potential variance from scenario to scenario. Marteinsson argues that it is difficult t o quantify the different variables in the factor method. Marteinsson states that c learly a difficult aspect when applying the method is deciding realistic values for factors A F. The effect of changes in a single factor is difficult to anticipate and there is considerable risk that synergy between factors can a ffect the results unfav ( 2003) Even s ome of the better known practitioners have pointed out that the method is deficient, stating that it is shown that service life prediction is encumbered with considerable uncertainties in estimating factors affecting the service li fe of mat (Lacasse and Sjostrom 2005) Evidently, a good deal of caution should be exercised in applying the factor method and the results approached with due reservation. Probabilistic Methods Probabilistic methods in service life prediction are perhaps best described by Lacasse and Sjostrom, as follows:

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52 factorial method for standard cases as well as to other service life prediction methods that employ mathematic al relations for service life. As opposed to using simple numerical factors, as is done in the original factor method, this approach incorporates the use of probability density functions for factors as well as for estimating the service life of individual components to arrive at an overall estimate of a building system's service life ( 2005) Most of the Service Life Prediction work involving probabilistic methods is specifically geared toward the analysis of one material. This is especially true of concrete for example, where numerous researchers have applied probabilistic methods and distributions toward the estimation of service life. In particular, probabilistic meth ods are more commonly found in large infrastructure type applications, where the service l ife may vary significantly. For example, a bridge or tunnel may be constructed to last 100 years or more, and the longer the service life is anticipated to be, the more the distribution of results may vary. A study by Breitenbchner et al. is illustrative, wherein the researchers used a probabilistic methodology to predict the service life of the Western Scheldt Tunnel in the Netherlands. Owing to the massive public investment in the project, a long service life was required. Thus, there was no pre existing methodology to accurately predict the potential outcomes, and in using a probabilistic methodology, the authors hoped to adequately account for any expected variance ( 1993). A similar rationale for using a probabilistic methodology is given by Siemes ( 199 9) Additional studies have been initiated to garner a better understanding of concrete under the influence of an aggressive environment (Biodini et al. 2004) such as those involving chloride diffusion (Teply et al. 1999 ; Hong 2000) or severe temperature s and chemical exposure (Wiseman and Kyle 1999) or in large infrastructure type projects (Walbridge and Nussbaumer 2004; Furuta et al. 2004) Ultimately, probabilistic methods

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53 are most well suited to studies involving a fair degree of uncertainty, whereby a stochastic distribution most adequately fits the variance in potential scenarios. As Hovde and Moser have (2004) Markov models for deterioration are a variation on standard probabilistic methods, and often used in studies employing the basic principles of structural engineering. It follows therefore, that Markov models are most well suited to large infrastructure projects, or projects with added uncertainty. To this end, Mar kov models seem particularly relevant to buildings because of their relatively longer life spans, although their application so far has been limited to large infrastructure projects (Abraham and Wirahadikusumah 1999; Leira et al 1999; Ansell and Sundquist 2002) The influence of the principles of structural engineering is also evident in a multitude of other studies, where more sophisticated mathematical modeling techniques are employed, mechanical properties of the material in question are consi dered (Dotr eppe 1999; Lair et al. 1999; Lair et al. 2001) ; and the complex chemical and mineralogical relationships analyzed with respect to the progression of fatigue as in Siemes and de Vries (2002) The Unites States Army Corps of Engineers has also published the Building Materials Durability Model, wherein the relative life cycle economies of different materials, including required maintenance and upkeep were mapped over time. Herein, the US Army Corps of Engineers analyzes several different types of structural ma terials including concrete and structural steel (Hjelmstad et al 1996) Overall, the structural engineering methods employ a level of sophistication that is

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54 not evident in the other methods. Again, practitioners of these methods are often experts in very s pecialized areas, as in Fagerlund where the author analyzes the impacts of structural design and freeze thaw action on the fracturing of concrete (1999) To this end, the methods are often too robust in nature, and as with all specialized disciplines, ofte n presumed to be as overly esoteric. A number of attempts have been made to standardize this branch of service life prediction (Masters and Brandt 1989 ; Frohnsdorff 1996 ; Frohnsdorff and Martin 1996) However, there is still a fair amount of research that needs to be performed to harmonize the body of knowledge. Empirical Data and Reliability Models The Canada Mortgage and Housing Corporation (CMHC) research report entitled Service Life of Multi Unit Residential Building Elements and Equipment provides a fa irly comprehensive set of empirical data, based on a Delphi survey of noted building managers throughout Canada. The implicit limitation however is that the climatic conditions in Canada are much different than those of the State of Florida or other region s in the continental United States. Hence, with the understanding that similar materials may degrade at different rates elsewhere, the data can only be used as anecdotal. Another set of empirical data has been compiled by the Army Corps of Engineers and is currently integrated into their BUILDER software program. The software is capable of plotting service life curves, assessing the effects of maintenance, and orchestrating the entire management of the building systems based on differential durability. Othe r sources of data are more sporadic. The CIB for example has undertaken the compilation of a large set of empirical data from field experience and

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55 observed measurement. However, this document is still incomplete and has yet to be published. Hybrids and the State of the Art One of the most innovative methods for predicting service life employs a combination of the factor and probabilistic methods, essentially using the limitations of ice lives of windows is a good example ( 1999) as is a study performed by Aarseth and Hovde ( 1999) A similar method is proposed in the methodology section of this dissertation. As stated previously, t he prediction of service life is not an exact science. Many researchers have offered alternative explanations for the premature end of the service lives of buildings, including poor adaptability and land use change. Herein, these researchers have found nothing more than alternative definitions for the obsolesc ence of materials. Yet, insofar as science is able to accurately predict service life according to a particular definition or perspective, the body of literature currently offers a great deal more than that, i.e. an accurate depiction of the constantly cha nging condition of building materials over time. The problem therefore is not one of accurately predicting the service life of given material or building. Rather, the problem with service life prediction is one of definition and misinterpretation. Indeed, the demolition of a building according to poor adaptability suits is a specific segment of this definition. However, the demolition of a building based on poor adaptability is not tantamount to a single, This is a kind of blind acceptance. After all, the purpose of science is not accept the seeming or apparent. The purpose of science is to constantly question. As in the definition of service life; it may be that durability is not the prime determinant of service life. However it is up to science to

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56 question whether in fact durability should be the prime determinant The argument therefore is one of conditions. Life Cycle Assessment The first recognizable forms of Material Flow Analysis came about toward the end of the 1960s and the beginning of the 1970s. These studies were pioneering, and as such, were relatively unconstrained by definition or methodology. The original goal was to analyze a product or process using a multi criteria approach, and to meas ure the impacts of the resultant material flows throughout the life of the respective product or process. In subsequent years, divergent methodologies forged alternative paths and as a consequence, LCA became more refined in terms of definition and more st andardized in terms of methodology. However, it was not until the early 1990s that official standards and definitions were established. For example, the first works the Society of Environmental Toxicology and Chemistry (SETAC) did not come about until 1991 and the first standards by the International Organization for Standardization (ISO) were not established until 1997 (Ecobilan 2010) Although SETAC retains an advisory committee on the practice of LCA, it is the ISO standards that are more frequently cit ed as the definitive guidelines. The ISO documents cover all aspects of the LCA process, and guidelines are set for defining the goal and scope of the study, the functional unit, the system boundaries, data quality and requirements for comparisons between LCAs, data collection and calculation procedures, impact and assessment, and the interpretation of results (ISO 1 1997) Subsequent volumes of the standards deal with guidelines for Goal and Scope Definition and Inventory Analysis (ISO 2 1997) Life Cycle Impact Assessment (ISO 3 1997) and Life Cycle Interpretation (ISO 4 1997)

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57 However, insofar as Life Cycle Assessment is standardized, a significant amount of latitude or scientific license is permitted. This is much more evident in the literature than it i s the ISO standards. LCA studies may begin with the ISO guidelines and produce vastly different results. To some in the field, this is perceived as a weakness; they believe that LCAs should be further standardized and that a lack of standardization undermi nes the legitimacy of most, if not all LCA studies. As mentioned in the previous section of this dissertation however, the true weakness of LCA stems from the qualitative variety of its measures. For example, it is virtually impossible to compare LCAs with different impacts without making a subjective judgment. Is water pollution a more significant impact than air pollution? Is global warming a direr environmental problem than ozone depletion? Ultimately, judgments made on th is type of comparison require a presumption of fact, and therein lays the true weakness of LCA. Outside of the limitations, LCA continues to provide one of the most promising areas for environmental improvement. As Cole and Sterner have observed, Life Cycle Assessment (LCA) methodologies have emerged as a means to profile the environmental performance of materials, components and buildings through time and have been generally accepted within the environmental research community as the only legitimate basis to compare competing alternative s. They have successfully entrenched the notion of an extended time context for examining the environmental characteristics of buildings beyond the short horizons that dominate current design and construction ( 2000) It is significant that Cole and Sterner refer to Life Cycle Assessment as a means to omitted from a large number of LCA studies, particularly so in the realm of building construction. Perhaps the effects of servi ce life are often neglected because the first LCAs were performed to assess the effects of manufacturing and industry over much

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58 shorter life cycles. As such the practice of performing an LCA on a building is a relat ively new concept and an emer g ing field i n and of itself. Life Cycle Assessment in Buildings The Functional Unit The application of Life Cycle Assessment on building systems has been practiced only recently. As it is consistent with the characteristics of emerging fields, the application of Li fe Cycle Assessment on buildings has required some adjustment from building s that are unique, prompting prolonged discussion the research community on the appropriate functiona l unit for a building system. For example Borg et al have described the cha llenges of modeling a building in Life Cycle Assessment at length. Applying and developing the LCA methodology to the conte xt of the building sector makes several building specifi c considerations necessary. These considerations o riginate in the fact that some characteristics of products in the building sector different considerably from those of other industrial sectors. The largest difference is that the service life of a building can stretch over centuries rather than decades or years, as for other industrial that it is difficult to obtain accurate data and to make relevant assumptions about future condi tions regarding recycling. These problems have implications on the issue of allocation in the building sector in the way that several allocation procedures ascribe environmental loads to users of recycled or reused products and materials in the future, whi ch are unknown today the definition of the product, and consequently the functional unit to be addressed by the assessment (2001). A similar viewpoint is held by Paulsen, who states th at buildings are unique in that their service lives are relatively long, and require periodic maintenance over the course of their operation, as described in the following excerpt:

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59 An analysis is often carried out on the product level, while in order to i nclude the usage phase, information is required on expected service life, type of maintenance, interference with surroundings, etc. the necessary information may depend on the context of the building product. One type of environmental loads that may occur in the usage phase is due to maintenance. Building products may have a significant longer service life than most other product groups on which LCA methodology has been applied. Accordingly the usage phase could be expected to cause a significant contributi s life cycle (2003) The author continues by stating methodological development is especially needed in the area of building maintenance. As stated by Salzar and Sowlati, buildings are unique and complex syst ems (2008). the course of life of a building, researchers in the past often opted for building materials, building products or building components as subject for LCA research. The au thors go to unexpected secondary effects when the materials or components are applied in buildings without taking into account their impact on the performance of the bui lding as ) A similar point is evident in the work of Ortiz et al., wherein the differences between whole building analysis and that of individual components is discussed. The authors point out that differences between the analysis of whole building or individual components are essentially differences in the functional unit (2009). Verbeeck predictions of future o utcomes and environmental assessment very uncertain, a vie w that is shared with Brattebo et al. (2009) Scheuer et al have added temporal context to their observations on the challenged of building modeling. The authors state that buildings are large in scale, complex in materials and function and temporally dyn amic

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60 due to limited service life of building components and changing user requirements (Scheuer et al 2003). u nlike conventional consumer goods often change in the course of their life span. uthors contend that LCA the behaviour of buildings is more dynamic. stat e that it is for this reason that environmental impact s are difficult to track using LCA To paraphrase the authors, this relates to the fun ctional unit of a building study, in that the dynamic and changing character of buildings, should be considered as processes rather than as products. will also need to adjust for the uncertainties in the data available. (2 0 0 7) Other researchers have pointed toward the unpredictability of future scenar ios, identifying the long service life of buildings as one of the main predicaments in LCA analysis Santos Viera and Horvath state the following: The main challenge here is th e difficulty of establishing the value of elapsed time. These two issues are particularly complicated for buildings because they are complex (with many involved materials, products, equipment, utilities) and typically have a long lifetime (from a few years to several decades or even centuries). (2008) Nordby et al. have argued that change is implicit with the passage of time and extended building service life, as described in the following excerpt: A building rarely remains in the same physical state over such long time spans. Modifications, demolition, and rebuilding caused by new functional or technical needs will probably occur, and should be accommodated in the whole technical lifetime of the components. In traditional brickwork, reuse and recycling was allowed for. Weak mortar types made it possible to deconstruct a wall so that the building blocks could be reclaimed, and this practice was a natural basis for brick building cultures throughout history. (2009) Erlandsson and Levin take a similar view to assessing the functional unit

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61 described as a process as opposed to a product (2005 ) The ideas of treating a building as a process and not and product, the differential durability of materials and components, along with the parallel idea of buildings as temporally dynamic systems is consistently held throughout the literature. Again, S heuer et al have explored the challenges of Life Cycle Assessment modeling in buildings as one might look at a system, as a process and not a product. Clearly high replacement rates of materials with high embodied energy will have a greater impact on life cycle performance. The influence of renovation material choices and schedules on the embodied energy of a building are not typically considered in the design stage of a building, but as these results indicate designing with renovation burdens in mind coul d diminish long term embodied energy burdens. (2003) In a similar manner of thinking, Dimoudi and Tompa allude to differential durability and maintenance of materials as important considerations in the life cycle modeling of buildings. In turn, maintenance and differential durability are concepts related to dynamic systems. The authors advocate the inclusion of the concepts in the following passage: As far as construction practices are concerned, additional criteria should be considered like the lifetime of building materials, the compatibility of the different materials and of the different layers, their maintenance nee ds over the building life cycle (2008) Mirza has indicated that th e eventuality of change requires proactive planning and design strategies, stating that consideration of change and the associated factors should be initiated in the design phase. A a component and a given environment requires knowledge of the materials,

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62 the operating environment, and the various physical and chemical characteristics of the materials, as well as the transformations caused by the specific environment and the operation and maintenance of the facility. ( 2006) Schultmann and Sunke have gone beyond moderate maintenance and replacement, stating that the reuse and recovery of materials ought to be considered in the design of a building. the reuse and recovery of building components increasing the gross sum of ene 2007). In terms of planning for second service lives, the integration of temporal context a nd c hange over time is implicit Despite the newness of the field, Life Cycle Assessment has been used in the analysis of buildings and building materials in a number of applications. The American Institute of Architects is often cited as the first to attempt t he use of Life Cycle Assessment as a measuring stick for building materials, with the publication of the Envi ronmental Resource Guide in 1996 (Dempkin 1996) As described in previous sections of this dissertation, comparisons in LCA are at times difficult. Even the Environmental Resource Guide uses LCA to make simple and relative comparisons of materials without delving too deeply into the touchy matter disparate variables. Most research efforts in the field of building construction have effectively side st epped the importance of comparisons in LCA by either stating that it is a widely recognized problem, or by focusing in on a more specific aspect or life cycle stage of the building. A number of studies have evaded the comparison of disparate variables alto gether by employing a method known as Life Cycle Energy Assessment. A study by Ball observes the following: The holy grail of low energy has mesmerized many assessments of ecological design to the virtual exclusion of other environmental impacts.

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63 Energy is probably the most easily measured and addressed in the construction industry but it is by no means the only factor of sustainability. Indeed, it is probably the very fact that energy is an easily quantified commodity that it is such a popular measure of t he environmental credentials of a material or building ( 2002) A fair portion of the literature in Life Cycle Energy Assessment follows the same format as the majority of the literature in Life Cycle Assessment, in that relatively little importance is give n to the importance of service life. This is evident in the work of Adalberth ( 1997) Chen et al. ( 2001) Adalberth (Adalberth 2 1997) Lollini et al. ( 2006) and Sartori a nd Hestnes ( 2007) who have each employed the typical building service life of 50 or 60 years. However, Life Cycle Energy Assessment makes a significant contribution through the work of numerous researchers who have explicitly stated alternative life cycles for buildings and materials, a practice which yields much different results. Although the specific term is not used, these researchers have recognized the importance of differential durability in what they point to as a need for recurring embodied energy; in other words the energy that is required to maintain a building over its lifetime. As Venkatarama et al. have attempted to define: Energy in buildings can be categorised into two types: (1) energy for the maintenance/servicing of a building during its useful life, and (2) energy capital that goes into production of a building (embodied e nergy) using various building materials. Study of both the types of energy consumption is required for complete understanding of building energy needs (2003) The concept of recurring embodied energy is observed in the work of several other researchers, Co le and Kernan (1996) and Fay et al. (2000) to name a few. Life Cycle Energy Assessment has also corroborated one of the principle findings operating energy constitutes the single biggest impact. Several researchers have made

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64 this observation including Adalberth (Adalberth 2 1997) and Cole and Kernan (1996) At the same time, several researchers have noticed that the more efficient the building envelope becomes, the more sign ificant the impact of the materials becomes relative to operating energy, as in Yohanis and Norton (2006) Sartori (2007) Chen et al. (2001) and Keoleian et al. (2001) Overall, the contribution of Life Cycle Energy Assessment is important in its recognit ion of maintenance impacts and recurring embodied energy. Several authors have alluded to service life in particular as the catalyst for accurate Life Cycle Impact Assessments in general. Life Cycle Assessment by Life Cycle Stage The obvious application of Life Cycle Assessment is in the analysis of manufacturing. In fact, Life Cycle Assessment was conceived as a means of evaluating industrial and manufacturing processes. As stated previously, it is perhaps for this reason that researchers have had trouble adjusting the methodology to better suit the analysis of a building. Many practitioners in LCA seem fixated on either the initial impacts of manufacturing, or the impacts of the operation of the building. Other studies by contrast have sought to take a dif ferent perspective, considering the effects of maintenance and end of life scenarios. For instance, the impacts of maintenance on a building have been thoroughly researched in the area of Life Cycle Costing. As Dunston and Williamson have suggested: Lack of owner funding can often result in poor material system performance. Owners must recognize that insufficient funding of design and construction will impact future maintenance capabilities. Lack of funding is a common reason for the selection of alternat ive material systems that may not meet performance standards. Designers must be able to demonstrate

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65 that increases in design and construction costs due to designing for maintainability can be offset by reduced maintenance costs (1999) This view is echoed by Mirza, who states the following: Increased durability should normally result in an increased initial cost but lower maintenance costs over the service life of the facility. Unfortunately, current design methods, which are basically for the construction stage only, cannot be used to determine the cost benefits that would be attained during the service life of the facility ( 2006) If indeed the impacts of maintenance are significant in the Life Cycle Costing of a building, it seems logical that this would also be true of the environmental impacts measured in a Life Cycle Assessment. In other words, choosing a material with low maintenance requirements would logically benefit a building owner in terms of costs, and benefit the environment by way of lower mai ntenance impacts, a view that is also supported by Mirza ( 2006) Harris ( 1999) Pushkar et al. ( 2005) and Thormark ( 2006) for example. Indeed, maintenance impacts are a good indicator of material suitability for a given climate, or as Allen has theorized from equilibrium system going, there must be a constant input of energy or matter, as when an animal must eat to stay ( 2002) Hence, materials that require relatively higher levels of maintenance might from eq A continuation on the theme of building maintenance is evident in a number of studies that have focused on renovation or refurbishment. A study by Dong, Kennedy and Pressnail for example has illustrated t he apparent advantages of building renovation as compared with demolition and replacement. The Dong, Kennedy, Pressnail study also presents a question for future study, as described in the following excerpt: In comparing the relative environmental impacts of utilizing existing buildings versus new construction, the results have identified areas that

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66 need further attention. In comparison to rebuilding, retrofitting saves building materials and avoids the creation of solid wastes and pollutants from the produ ction of those materials. On the other hand, rebuilding results in significantly greater savings in energy and energy related environmental impacts, most notably global warming potential. There are numerous ways to renovate, just as there are numerous ways to build new housing. In simple terms, the results indicate a trade off. Should we trade off material related environmental impacts for improvements in greenhouse gas emission reductions? Or should we trade off the existing poor performance of buildings t o make use of their material resources ? (2005) Similar studies have also contended this point, arguing that more emphasis should be placed on the existing building stock and the renovation of existing structures, as articulated in Johnstone ( 2001) and Kohl er ( 1999) Beyond the renovation buildings, Life Cycle Assessment has also been employed to analyze the recycling of building materials and other end of life scenarios. In fact, the analysis of the environmental impacts stemming from recycling is not limit ed to Life Cycle Assessment. Other forms of Material Flow Analysis have also contributed. For example, a study by Brown and Buranakarn sought to identify the most recyclable building materials through emergy analysis (2003) A separate study McLaren, Park inson and Jackson sought to devise a new methodology for mapping the cycling of materials through material cascades, as might occur through multiple service lives (McLaren et al. 2000) The justification and quantification of the recycling building materia ls however is not so prevalent. Thormark has stated that recycling is justified, based on the following analysis of the energy use of buildings; for example, the increasing p roportion of the ( 2002). Of course, this view is grounded somewhat by the caveat provided by Boustead

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67 ( 1998) and Bishop ( 2000) who state that even if recycling is just ified, it is only so to the extent that the recovery and reprocessing of materials is less damaging than simple disposal. In other words, Boustead and Bishop have argued that there is an optimal level of recycling, after which material recovery and reproce ssing does more harm than good. Bishop has further qualified the process of recycling by describing the most favorable scenarios. Products that can be easily and rapidly disassembled into their component parts are more likely to be reused or remanufactured Those that are designed so that parts snap together are probably the easiest to disassemble after use. Bolted or screwed components are also easily disassembled. Ease of disassembly also makes repair of the product during use easier, because the part can easily be removed to allow access to other parts that need repair, or the removable part can readily be replaced, if necessary ( 2000) Although a considerable amount of research has been performed on the recycling of materials, most of the theory does not translate well into practice. More often than not, the practice of recycling is dictated by the market, and the affordability of recycling technologies. Further problems arise when decisions need to be made for the reprocessing of materials. Since the opt imal cycling of materials is loosely defined, many building experts are unsure of the necessary concentration of materials required for recycling. Again, most of the decisions are based on economics and the capabilities of the local market. The Confluence of Service Life Prediction and Life Cycle Assessment The integration of detailed service life data into Life Cycle Assessment models of buildings has been fairly limited. In part, this is due to the uncertainties of Service Life Prediction. As evidenced in the sections on the Life Cycle Assessments of building and Life Cycle Assessment by Life Cycle stage, researchers have struggled to find the

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68 appropriate functional unit for the analysis of a building, and some have opted to use Life Cycle Assessment metho ds to analyze a specific aspect of the building life cycle. However, the confluence of the concepts has been initiated by relatively few. As stated by the Athena Institute, Defining or judging service life has been problematic for the developers of green b uilding rating or assessment systems, and few tackle the subject from a holistic perspective. Indeed, while much information exists worldwide on building and material service life, building construction, and green building systems, there is little discussi on of all three subjects as an interrelated whole. (Athena 2006) As it has been mentioned previously, LCA studies of building with dynamic and detailed service life data have been fairly limited. A demonstration of differential durability and detailed servi longevity. The results of the survey show a wide distribution amongst the different materials (2008) A good ex ample of confluence is given in the work of Thomsen and van der Flier. Herein, the authors undertake a similar methodology to the one employed in this dissertation. As the authors state, the purpose of the method is s trictly theoretical The results show that the ratios between the ecological effects of materials and energy consumption do not change significantly when the lifespan is extended to 400 years (Figure 4). Of course, this approach is strictly theoretical; replacement with exactly the same materi als, installations, etc. does not make sense, even over a short period. As innovations in technology, building process, maintenance, and dwelling use play a crucial but fully unknown role, the outcomes give only an indication. Regarding only the ecological effects of lifespan extension, the conclusion is that other factors will make the difference. This may explain r eplacement or renovation of dwellings the differences between the outcomes of the empirical and theoretical studies (2009). This may in fact ho ld true, as Strand and Hovde have discovered that hi gher levels

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69 of maintenance some times result in higher overall environmental impact (1999) Thus, materials requiring less maintenance are greener or the compromise of material longevity may result in low er Life Cycle Impacts due to decreased maintenance The assumption however prompts further examination. The literature in LCA is sprinkled with references to service life and its effects on environmental impacts. Similarly, some of the literature in Servic e Life Prediction has made reference to a need for better service life data in LCA. It seems this is not a new area of inquiry. However, with the exception of Strand and Hovde (1999) and Graveline (2005) the confluence of Service Life Prediction and Life Cycle Assessment is virtually absent from the larger body of knowledge. The concept of confluence therefore must be affirmed on the basis of like research is quite adam in the following excerpt: Another reason for the current focus on durability is the recognition that sustainability is not possible without durability. If you double the life of a building and you use the same amount of resources to construct it, the building is twice as resource efficient. Therefore durability is a key component of sustainability ( 2008) Kesik qualifies this observation with a subsequent statement: Once construc The more durable the building the longer it is around. The longer the building is around the more energy it consumes. Durable buildings need to be ultra energy efficient in order to be sustainabl e. Durability and energy efficiency are the cornerstones of sustainability ( 2008) There is a whiff of tenuousness in these two statements. In the first statement, resource impacts are halved by simply doubling the service life. In the second, there is t he recognition that a durable building also needs to be ultra energy efficient lest the

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70 impacts resulting from the operation of the building were to somehow trump the halving of resource impacts. Indeed, the veracity of these statements must depend on the efficiency of future buildings, and that they will not outperform the older, more durable models. It is of course logical to question these statements: why would technology that is over one hundred years old outperform the cutting edge? Presumably there wo uld be a fair amount of materials and energy invested in keeping the older building abreast of the latest technologies; technologies that may or may not fit with an older format. Would the same type of upkeep be true for a less durable building? rk seems to prompt more questions than it provides answers. Unfortunately, although the statements provide great fodder for a debate on building durability, they are also largely unsubstantiated. A more quantifiable approach is presented by Graveline, who in the same fashion as Kesik, illustrates the benefits of prolonging the service life of a given material. For a building with a 75 year design life, a roof assembly with a 15 year life expectancy would have to be replaced five times within that span versu s three time for a roof with a 25 year service life. This has obvious implications for the magnitude of each of the impacts associated with the system (Graveline 2005) analysi s is still distinctly linear in nature. There is no mention of performance degradation over time, or of the cumulative maintenance required to keep a system in service for 75 years. Overall, the confluence of Service Life Prediction and Life Cycle Assessme nt is hybrid method for Service Life Prediction, the articles will comprise the basis of the methodology of this dissertation as described in the following chapter.

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71 Variabili ty The range of available service life data is the driving force and main preoccupation of this study. As Life Cycle Assessments of buildings continue to be refined, it is expected that the accuracy of service life data will improve, that researchers perfo rming Life Cycle Assessments of buildings will incorporate the best available service life data into their studies, and the validity of Life Cycle Impact results will improve based on a smaller range of contextual data. As follows, Life Cycle Assessments o f buildings have employed a wide range of service life data. Chevalier and La Teno have the following to say regarding variability is service life: For a given building product, this phase commonly ranges from five to 100 years and more, depending on mostl y unpredictable exter nal conditions (climate, type of user, change of use, etc.). This causes in most cases a violation of the time stability hypothesis and calls for some sort of flow value actualization. Again, depending on the same external conditions, maintenance and replacement processes will occur at varying frequencies, thus again violating the flow accuracy hypothesis (1996) Additional studies show different service lives dependent of the type of building or material as the case may be. For exampl e, Mithraratne and Vale analyzed residential buildings in New Zealand and used a service life of 100 years, along with periodic replacement and maintenance over time ( 2004) A study by Kellenberger and Althaus assumed a service life of 80 years, stating th disposal of the buildings will take place about 80 (2009). Verbeeck and Hens employed a mean service life of 30 years or as the authors xceeds the usage period by one generation, resulting in large uncertainties on modifications and destination of the building afterwards, the mean adopted time scale here is the usage phase by one generation, during a period of 30 years. It should be noted that Verbeeck and Hens included service

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72 lives of 60 years and 90 years in the same analysis to account for sensitivity ( 2010). However, the wide variation in service life is what is of interest to this study Observations by Marteinsson suggest that servi ce lives for houses in Iceland are often calculated at 60 70 years, with specific service lives for windows ranging from 5 10, to a s high as 80 years ( 2003). Nord b y et al have mentioned th at ricks achieve high scores in terms of their technical lifetime; brick constructions from both the Chinese and Roman empires have survived for more than 1500 years ( 2009) A s the focus of the Nordby et al. article is material reuse, the authors suggest that second and third service lives may be appropriate for some ma terials. An article by Paulsen shows a wide range of service life data for flooring materials, ranging from 5 40 years, depending on w hether the determining factor of service life is economical, aesthetic or otherwise ( 2003) In their modeling of a un ivers ity building, Scheuer et a l employ a service life of 75 years ( 2003) A n analysis by Radhi, although geared the environmental impact of different envelope materials in the operations phase, assumed a value of 75 years for service life ( 2010) The study di d not recognize differential durability amongst any of the wall form systems. Bergsdal et al used a number of different figures for service life projections of the Norwegian housing stock, including schedule renovations. For small buildings, the study sch eduled the first renovation at 30 years, a second renovation at 60 years and demolition at 90 years. For large buildings, the study scheduled a first renovation at 20 years, a second renovation at 40 years, and demolition at 60 years. For all other buildin gs, renovations and demolition were scheduled in accordance with the values for large buildings ( 2007). Many researchers have opted to frame Life Cycle Assessments of buildings within

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73 a commonly held life span of 50 years. Sartori et al has provided a sup porting argument for this length of analysis, stating the f ol lowing: I t is largely accepted as common practice to perform energy analysis over a period of 30 50 years. This because it is generally assumed that after such a period an average building is eit her demolished or undergoes major renovation works that will considerably alter its energy performance. A simplified approach to energy demand analysis could consider an average c ourse an approximation, but would allow concentrating all the (2008) Further examples this commonly held service life maxim are evident in the work of Junnila and Horvath ( 2003 ) Kahhat et al, Kooworola an Gheewala (2009) Pulselli et al (2009) and Sazi et al. (2006). Both the Kahhat et al and Pulselli et al studies involved wall comprised of different materials. Similarly the Saiz et al study involved a comparison of different roofing materials. In a Life Cycle Energy Assessment performed by Hens and Verbeeck, a period of analysis of 30 years was assumed (2009). It is difficult to say which service life numbers are accurate. Of course, a high degree of variability in assumed longevity yields a corresponding degree of variability n terms of impact. Berg sdal et al have noted i nformation about the lifetime of dwellings is very scarce, and there is no consensus in the literature on what distribution best reflects the actual dwelling lifetime. (Bergsdal et al II 2007) Lacasse and Sjostrom have support ed this idea by stating it is shown that service life prediction is encumbered with considerable uncertainties in estimating factors affecting the service life of materials and components 2005). Itard and Kluner have s uggested that the complexity of service life prediction goes beyond a mere analysis of the materials, and the degree of variability is dependent on the behavior of the household as well, stating, s also important to keep in mind that for anything as quantifiable as energy us e

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74 and life span of components, the values found for a building can easily vary by a factor two, depending on the behaviour of the household. ( 2007) As such, the literature on the confluence Service Life Prediction and Life Cycle Assessment is inconclusive In the chapters that follow, it is hoped that a better understanding of this confluence emerges, and modifications to the current application of Life Cycle Assessments on building is in need of modification.

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75 CHAPTER 3 METHODOLOGY T o test the environment al impact of longevity for the materials in the building envelope a selection of nine materials were analyzed according to a three tiered approach. Three wa ll forms and three roof types were analyzed. The three wall forms included a brick wall assembly, a n aluminum panel wall and a wood siding wall. The three roofs consisted of a ballasted, built up roof, a thermoplastic roof, and an extensive green roof. These materials were selected based on perceived differences in durability, thermal performance, solar absorptance, and Life Cycle Impact. These materials were analyzed as potential envelope combinations to be applied to the exterior of an institutional university building. For the purposes of comparison, the Rinker Hall building on the University of Flori da campus was used. Rinker Hall is clad with a combination of aluminum panels and curtain walls. On the roof of Rinker Hall, a highly reflective thermoplastic membrane is installed. These materials are often described as high performance, although very lit tle is known about their maintenance needs or durability. As the focus of this study pertained to environmental performance and material longevity, Rinker Hall was an ideal building model. Rinker Hall is one hundred and eighty (180) feet in length, eighty two (82) feet wide, and forty two (42) feet tall. In actuality, Rinker Hall includes two triangular solids on the North and South Sides of the building. The triangular solid on the North side of the building encompasses two floors of the building. The tria ngular solid on the South side of the building contains the mechanical room. These triangular solids were viewed to be superfluous to the main focus of the study and were therefore omitted. As such, Rinker Hall was used as a template for a rectangular sol id building, with the dimensions described above.

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76 The three tiered approach consisted of energy modeling, Life Cycle Assessment, and service life modeling. First energy modeling was conducted to assess the relative thermal performance of the materials. S econd, Life Cycle Assessments of the modeled operating energy and envelope materials was performed. Third, the resultant Life Cycle Impacts were integrated into five service life model s with differing values for inspections, major replacements, minor repla cements, major repairs and minor repairs. Three types of Life Cycle Assessment models were produced: 1) an energy d ifferential model, 2) an energy neutral model, and 3) a coarse model. Each model was projected over a period of 500 years, in accordance wit h United States Army Corps of Engineers specified service life for a brick wall ( USACE 1991 ) Energy Modeling It was believed that each of these envelope materials would affect the thermal performance of the building. To measure the environmental impact of this thermal performance, an energy modeling analysis was perf ormed using Energy 10 software a commonly used and widely accepted software application The external loading of the building was based on the Jackson ville, Florida weather dat a set. Three wal l forms were constructed in Energy 10 which mimicked a typical wall cros s section in Rinker Hall. Walls were constructed of 5/8 inch gypsum board, 6 inch cold formed steel studs at 16 inches on center, 6 inches of blown cellulose insulation, and 1 1/2 inch es of polyisocyanurate board on the exterior of the wall. These wall forms were clad with one of the three envelope materials; brick, aluminum or wood. A similar approach was taken for the roofs. Each roof form included a corrugated metal deck, 5 1/2 inche s of p olyisocyanurate foam, with 3 inches of li ghtweight concrete comprising the top layer. The roofs were then finished with one of the three roofing materials; the built up roof,

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77 the TPO membrane or the green roof. All other variables for each energy mod el square footage, volume, wall surface area, roof surface area, windows, d oors lighting and mechanical equipment. T he analysis varied only by the type of wall form or roof that was used. The materials listed ab ove were paired off to include all possible combinations; brick/built up roof, brick/thermoplastic membrane, brick/vegetated roof, aluminum panel/built up roof, aluminum panel/thermoplastic membrane, aluminum panel/vegetated roof, cedar siding/built up roo f, cedar siding/thermoplastic membrane and cedar siding/vegetated roof. A nu mber of assumptions were made during the energy analysis portion of the study. For example DX Cooling with Elect ric Furn selected for the HVAC system. Bui ldings for each energy model had established set points of 76 degrees Fahrenheit for bot h heating and cooling seasons The thermal performance and characteristics of the w indows and doors were also constant through each energy model During the first iterat ion of energy modeling, a total of nine envelope combinations were analyzed, as follows: Wall Form Material Roof Material Brick Green Brick TPO Brick Built Up Aluminum Green Aluminum TPO Aluminum Built Up Wood Green Wood TPO Wood Built Up Fig ure 3 1. Building Envelope Combination Use d in Energy Modeling Analysis

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78 A second round of energy modeling was performed to make all envelope combinations perform equally The envelopes were equalized by establishing a baseline level of performance. In the firs t iteration of energy modeling, the brick wall and vegetated roof combination was the most thermally efficient. Varying amounts of polyisocyanurate insulation board were added to the other envelope combinations to make them perform as well as the brick and vegetated roof combination Insulation was added to the walls and roofs separately, and for the purposes of subsequent Life Cycle Assessment modeling, an average value of the separate wall and roof modifications was used to derive a material quantity. Bas ed on these modifications, t he second iteration of energy modeling generated a greater number of permutations, such that the modeling of an additional twenty five building wall and roof forms was required Since the brick wall and green roof combination wa s used as the baseline model, baseline insulation was based on the original design 1 1/2 inches of polyisocyanurate board for the wall 5 1/2 inches of polyisocyanurate board for the roof. Additional insulation was added to each envelope combination such that the baseline thermal performance was achieved The additional quantities of insulation required for the wall forms is shown in Figure 3.2. The additional quantities of ins ulation required for the roofs are shown in Figure 3.3. Wall Form Material Roof Material Wall Insulation Required for Equalization Brick Green Brick TPO Brick Built Up Aluminum Green Aluminum TPO Aluminum Built Up Wood Green Wood TPO Wood Built Up Figure 3 2. Wall Modifications Required to Equalize Thermal Performance of Walls

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79 Roof Material Wall Material Roof Insulation Required for Equalization Green Brick Green Aluminum Green Wood TPO Brick TPO Aluminum TPO Wood Built Up Brick Buil t Up Aluminum Built Up Wood Figure 3 3. Roof Modifications Required to Equalize Thermal Performance of Walls T he t wo iterations of energy modeling produced two service life models; 1) a model that in cluded the operating energy into the anal ysis as the differential from a baseline the energy differential model, and 2) a model that equalized operating energy through a case by case increase in polyisocyanurate insulation board the energy neutral model. A third coarse model was constructed a s an extension of the energy neutral model, and excluded any environmental impacts relating to maintenance or inspections. Rather, the coarse model included only the impacts of the major material replacements at the specified frequencies over time. Life Cy cle Assessment The results of the energy modeling analyses represented the first step in assessing the environmental impact of material and assembly longevity. In order to measure environmental impact, Life Cycle Assessment methodology was used. Life Cycle Impact d ata for operating energy and the different envelope combinations were extracted fro m the Gabi 4 software database a widely recognized software application T he environmental impacts of o perating energy were based on the standard North American el ectrical grid mix. Beyond operating energy, t he environmental impact of each material and assembly was calculated in terms of the inputs and outputs associated with extraction, manufacturing, and transportatio n to the construction site.

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80 I nventories of the different construction methods and equipment required were omitted from this analysis, as the differences were considered negligible for each wall form and each roof type. E nd of life sc enarios were also omitted. I t must be acknowledged that the end of lif e impact s for each of these materials are different, such that the results of this study must be taken in context. The primary objective of this study however focused on the operations and maintenance phase of the life cycle. Therefore it was believed tha t t he projection of open ended material cascades and scenarios would confound the original research question Material estimates were calculated for each w all form and roofing material. For the wall materials, e ach quantity take off was based on the dimen sions of the modified Rinker Hall building described previously. Logically, the square footage of each window, lintel and door was deducted from the quantity take off. Quantities for roofing materials were estimated in a similar way, based on the aforement ioned dimensions, with the square footage of the skylights deducted from the total quantity. A waste factor of five percent was used for each material Additional material take offs were performed for the different maintenance activities described in each model. A d etailed representation of these material quantities is shown in Appendix A. Distances for material transportation were assum ed based on a student authored report prepared for the Athena Sustainable Materials Institute (Fillie et al 2004) wherei to of typical building materials we re calculated for the Orlando, Florida area. As the building modeled for this study was located in Gainesville, Florida the transportation distances presented in this report w ere viewed as the mos t accurate available However, a minimal amount of potential inaccuracy must be

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81 acknowledged due to the distance between the City of Gainesville and the City of Orlando. Based on the quantity take offs and distance specifications described above, Life Cycl e inventories were generated using the Gabi 4 software. Impacts were calculated for the initial manufacture of the material and any replacement, repair, maintenance or inspections performed over time. A total of thirty six building wall and roof form comb inations were modeled according to the energy differential, energy neutral and coarse sets of models. Each envelope combination and each individual material was assessed in terms of environmental impacts according to Global Warming Potential (kg of CO2 equ ivalent), Atmospheric Acidification (mol of H+ equivalent) and Atmospheric Ecotoxicity (kg of 2,4 0 Dichlorophenoxyace equivalent) as characterized by the Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts (TRACI) set fort h by the United States Environmental Protection Agency (EPA). Service Life Models Five service life models were used The first service life model was authored by the Army Corps of Engineers (USACE 1991) The report describes inspections, major replacemen ts, minor replacements, major repairs and minor repairs at specific intervals over the estimated service life Descriptions of these activities and the specified frequency of each are represented in Figure 3.4 The frequency of each activity is shown in th e light blue cells in years A second service life prediction model was based on a report published by the Athena Sustainable Materials Institute (Athena 2002). Although the Athena model did not specify major replacement intervals for some of the materials in the study, instead

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82 stating that many cladding materials would endure for the life of the structure, major repair and maintenance intervals cited in the report offer insight into the Life Cycle Impact of a particular materials with specific relevance to service life. In following the format of the USACE model, the descriptions and frequencies of each activity in the Athena model are shown in Figure 3.5. and Kirk 2003) A s opposed to the USACE and Athena models the emphasis in the is on cost, although frequencies for material replacement and maintenance are also given. for each major rep lacement, and a material cost for each maintenance activity In order to translate material cost into quantity, the 2003 edition of RS Means Building Construction Cost Data was used (RS Means 2003) As such, the material costs nd Kirk text were translated into a material quantity using the material cost figures presented in RS Means. These quantities are shown in Figure 3.6. A nother service life model was produced from RS Means Cost Planning and Estimating for Facilities Mainten ance (RS Means 1996) Herein, service life data are also provided with associated costs of RS Means Building Construction Cost Data was used to translate material costs into quantities. D escription s and frequencies of the RS Means service life models are shown in Figure 3.7. The final service life model was based on a static 50 year model, which excluded any maintenance activities from the analysis. Equal service life frequencies were ascribed to each ma terial, including all roofs and all walls. Essentially, the 50 year static

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83 model shows the differences in the initial impacts of the material as projected over time. The descriptions and frequencies of the 5 year static model are shown in Figure 3.8. Since each model included maintenance activities of varying intensities, a third set of models was produced for the purposes of comparison A set of coarse models was generated by omitting any maintenance activities included in the USACE, Athena, la and Kirk and RS Means energy neutral models Essentially, the coarse models were simplistic reproductions of the energy differential and energy neutral models. The coarse models did not include any operating energy impacts, nor any maintenance activities over time. Rather, major r eplacement impacts were projected in Kirk and RS Means. Life Cycle Impact data for each of the models were used to project cumulative environmental i mpa cts over a period of 500 years. A 500 year study period was used because it is the specified longevity of a brick wall assembly according to the USACE model. For the purposes of analysis, the relative order and magnitude of each envelope combination was recorded. Further analysis was produced to assess the life cycle impact of each envelope combination and each material per year.

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84 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof 1 3 28 20 14 1 Resource Required Transport 0.75 gallons gasoline Transport 0.75 gallons gasoline 1 square foot membrane, insulation & ballast 0.025 square foot Insulation, Sealant & Membrane 1 square foot Insulation & Membrane 0.02 square foot felt adhe si ve Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair TPO 1 3 20 10 1 Resource Required Transport 0.75 gallons gasoline Transport 0.75 gallons gasoline 1 square foot Insulation, membrane & seal ant 0.25 ballast adhesive 0.02 square foot Adhesi ve felt & Mastic Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof 1 3 40 10 Resource Required Transport 0.75 gallons gasoline Trans port 0.75 gallons gasoline Roof replacement 0.025 roof replacement Figure 3 4. USACE Service Life Model Activity Description and Frequency

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85 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor R epair Clay Brick 3 5 500 25 8 Resource Required Transport 0.75 gallons gasoline Transport 0.75 gallons gasoline 1 square foot brick 0.02 square foot brick, 1 SF waterproofi ng 1 square foot Pressu re wash, water proofin g materia l Inspection/ Min or Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats Paint) 1 3 125 25 5 Resource Required Transport 0.75 gallons gasoline Transport 0.75 gallons gasoline 1 square foot wood + 1 square foot paint 0.0 2 SF wood + 0.02 scrape, repair, refinish, paint Scrape repair, refinish + 1 square foot paint Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminu m Siding 2 3 80 12 5 Resource Required Tran sport 0.75 gallons gasoline Transport 0.75 gallons gasoline 1 square foot siding 0.02 square foot Siding Refinis h paint Figure 3 4. Continued

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86 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof 20 1 Resource Required 1 square foot membrane, insulation & ballast 1.5% of roof Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair TPO 20 Resource Required 1 square foot insulation, membrane & sealant 1.5% of roof Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof 30 2 Resource Required 1 square foot green roof 1.5% of roof Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick 500 35 12 Resource Required 1 square foot brick Repoint 25% of wall Recaulk 25% of wall Figure 3 5. Athena Service Life Mod el Activity Description and Frequency

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87 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats Paint) 25 12 5 Resource Required 1 square foot wood + 1 square foot paint Rec aulk 25% of wall Scrape, sand + paint Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding 35 35 12 Resource Required 1 square foot siding Repaint Recaulk wall Figure 3 5. Continued

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88 Inspectio n/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof 1 20 1 Resourc e Require d Transportati on 0.75 gallons gasoline 1 square foot membrane, i nsulation & Ballast 0.3min per ft2 r oof = 1% of roof Inspectio n/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair TPO 1 20 1 Resourc e Require d Transportati on 0.75 gallons gasoline 1 square foot i nsulation, membrane & s ealant 0.2min per ft2 r oof = 0.5% of roof Inspectio n/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof 1 30 1 Resourc e Require d Transportati on 0.75 gallons gasoline 1 square foot 0.5 min per ft2 r oof = 1% of roof Figure 3

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89 Inspectio n/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick 3 75 15 Resourc e Require d Transportati on 0.75 gallons gasoline 1 square foot b rick Repoint 4 min/ft2 = 14% mortar replace ment Inspectio n/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats Paint) 2 40 5 Resourc e Require d Transportati on 0.75 gallons gasoline 1 square foot w ood + 1 square foot p aint 0.5 min/ft2 = 1% of wall Inspectio n/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Alumin um Sid ing 2 50 8 Resourc e Require d Transportati on 0.75 gallons gasoline 1 square foot s iding 2 min clean/ft2 + 0.2 % of wall Figure 3 6. Continued

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90 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replaceme nt Major Repair Minor Repair Built Up Roof 1 5 28 20 15 1 Resource Required Transportati on 0.75 gallons gasoline Transportati on 0.75 gallons gasoline Replace Roof Place new membrane over existing: 4 ply bitmuminou s roofing Repair 25 % of roof: 4 plies of bituminou s roofing + insulation Repair 2% of roof: 2 plies of glass mopped, Inspection/ Minor Clean Up Inspections Major Replacement Minor Replaceme nt Major Repair Minor Repair TPO 1 5 25 20 1 Resource Required Transportati on 0.75 gallons gasoline Transportati on 0. 75 gallons gasoline Replace Roof Replace 25% of roof: install insulation + 150 mils modified bitumen Repair 2% of roof: install 150 mils modified bitumen Inspection/ Minor Clean Up Inspections Major Replacement Minor Replaceme nt Major Repair Minor Rep air Green Roof 1 5 35 25 19 5 Resource Required Transportati on 0.75 gallons gasoline Transportati on 0.75 gallons gasoline Replace Roof Repair 25 % of roof: rubber ized asphalt, root barrier, fil ter fabric and insulation Repair 2 % of roof: rubber ized asphalt, root barrier, fil ter fabric and insulation Figure 3 7. RS Means Service Life Model Activity Description and Frequency

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91 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replaceme nt Major Repair Minor Repair Clay Brick 75 25 25 Resource Required Replace b rick Repair = 1% of wall Repoint = 80% of wall Inspection/ Minor Clean Up Inspections Major Replacement Minor Replaceme nt Major Repair Minor Repair Wood (Two Coats Paint) 40 5 Resource Required Rep lace wood + Paint Scrape, repair, refinish + paint Inspection/ Minor Clean Up Inspections Major Replacement Minor Replaceme nt Major Repair Minor Repair Aluminu m Siding 50 8 Resource Required Replace siding Clean + detergent Figur e 3 7. Continued

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92 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof 50 Resource Required Replace roof Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair TPO 50 Resource Required Replace roof Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof 50 Resource Required Replace roof Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick 50 Resource Required Replace wall Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats Paint) 50 Resource Required Replace wall Figure 3 8. 50 Year Static Service Life Model Activity Description and Frequency

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93 Inspection/ Minor Clean Up Inspections Major Replac ement Minor Replacement Major Repair Minor Repair Aluminum Siding 50 Resource Required Replace wall Figure 3 8. Continued

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94 CHAPTER 4 RESULTS In accordance with the majority of the literature on Life Cycle Assessment, analyses of t hese data showed that operating energy was the dominant factor in Life Cycle Impact, and that each outcome essentially mirrored the results of the thermal performance analysis derived from the energy modeling as shown in Figure 4.1. A second model was con structed with added focus on the relative Life Cycle Impact of the materials. Herein, additional insulation was added to the walls and roofs to nullify the influence of the operating energy impacts. An additional twenty five wall and roof forms were requir ed given the permutations of equalizing thermal performance according to the original three walls and three roofs. A third model was constructed to assess the relative impact of maintenance intensity and frequency owing to qualitative difference s in presc ribed maintenance activities from model to model. As in the energy neutral model, the coarse model used a total o f thirty six wall and roof form combinations. Life Cycle Impact Models with Energy Differentials Global Warming Potential The graphs produced d uring the Global Warming P otential analysis produced relatively consistent results across all five service life models. Brick was universally Year static models, alumi num was preferred to wood as a wall form material. However the US A CE and RS Means model s show relatively little difference between the impacts of wood and aluminum Similarly, the green roof was preferred to the TPO membrane and Built Up Roof options. Th is order was maintained across each of the five service life models, despite perceptible differences in magnitude. The results of the Life Cycle

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95 Impact Models with Energy Differentials for Global Warming Potential are shown in Figures 4 2, 4 3, 4 4, 4 5 an d 4 6. Atmospheric Ecotoxicity In terms of Atmospheric Ecotoxicity, all five energy differential models yielded the same result. Again, brick was identified as the least harmful wall form material. In contrast to the Global Warming Potential results wood wall forms were preferred to aluminum wall forms, due mostly to the qualitative differences between aluminum and the other wall forms materials. In fact, the impacts of aluminum replacement and maintenance are so high, that they influence the trajectories of the aluminum operating energy differential. All other material outcomes mirrored those of the energy modeling analysis, with operating energy exerting the greatest influence in Life Cycle Im pact. For roofing materials, the green roof has the lowest impact, followed by the TPO membrane and Built Up roof. The order of both wall form and roofing materials did not vary across all five models. However, as subsequent analysis will show, and in vie wing each individual graph, the magnitude of envelope combination impacts did vary significantly from model to model with no effect to the respective order, as viewed in Figures 4 7, 4 8, 4 9, 4 10 and 4 11. Atmospheric Acidification The results of the Atm ospheric Acidification analysis show brick as the preferred wall form material, followed by aluminum and wood. For roofing, the green roof yields the lowest impact, followed by the TPO membrane and the Built Up roof. This order is maintained in each of the five service life models, although the range of impact s for each envelope combination varies from one model to another. As in the analysis o f

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96 Global Warming Potential, the se results are in accordance with those of the energy modeling exercise, such that t he trajectories are believed to be most influenced by operating energy use impacts. The results of the Atmospheric Acidification analysis are shown in figures 4 12. 4 13. 4 14, 4 15 and 4 16 respectively. Life Cycle Impact Models Energy Neutral Global Wa rming Potential The results for the Global Warming Potential analysis with energy neutral building envelopes yielded some conflicting results. The USACE model showed brick as the preferred wall form material, followed by wood and aluminum. F or roofing mate rials the green roof had the lowest impact, followed by the built up roof and the TPO membrane. The order and impact of the wall forms becomes evident early on in the 500 year cycle. However, there is only a slight difference between the built up roof and TPO membrane, with a visible trend becoming clear only after the first 100 years. A clearer trend is evident in the trajectory of the gr een roof, which obviously has the lowest impact, as shown in figure 4 17. In contrast, the Athena model maintained that the brick wall yielded the lowest Global Warming Potential impact, however the aluminum wall was preferred to the wood wall. The roofing materials also changed order from the USACE model to the Athena model. Although the green roof still had the lowest im pact in the Athena model, the TPO membrane was preferred to the Built Up roof. T he range of impacts in the Athena model was also g e nerally higher than the USACE model, due in part to more frequent replacement intervals and maintenance impacts. The cumulati ve impacts of the Athena model are shown in Figure 4 18 shows even more variance B rick is still the low est impact wall form material. However, t he differences between wood and aluminum are virtually indiscernible with alumi num

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97 resulting in a slightly lower impact over the course of the full 500 years. In terms of types, with the green roof being the best option, followed by the TPO membra ne and the built up roof. Again, the variance is largely due to the frequency of major replacement. The results for this model are shown in Figure 4 19. The RS Means model also indicates that brick is the best wall form material followed by wood and alumi num. impacts of the roofing options, with the green roof resulting in a slightly lower impact than the TPO membrane and built up roof respectively. Again, the frequency of major replacement and service life influenced the outcome. These differences are shown in Figure 4 20. I n accordance with the initial material impacts, the 50 Year Static model shows brick to result in lower impact than wood and aluminum although only sl ightly. Similarly, the built up roof is shown to be the best roofing option followed by the TP O membrane and green roof. The order of these results essentially reflects the order of the initial impact of each material as projected over multiple material c ycles. Consequently, the ordering of the wall and roofing material is based purely on the frequency of the major replacement intervals. The results of the 50 year static model are shown in Figure 4 21. Overall, the results of the Global Warming Potential a nalysis reveal the importance of service life prediction in the performance of LCA. As subsequent analyses will reveal, much of the variance in the models is attributable to differences in replacement and maintenance frequencies. Atmospheric Ecotoxicity I n all of the Atmospheric Ecotoxicity models, brick is identified as the lowest impact wall form material, followed by wood and aluminum. Each of the models shows

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98 aluminum to have the highest impact by a considerable margin due to the materials inherent pro perties models show the green roof to have the lowest impact. In contrast, t he 50 year static model shows the Built Up roof to have the lowest impact, followed by the TPO membrane and the gr een roof. In each of the models, the effects of the roofing materials are decisively less influential than the wall form types, as the order and magnitude of the roofing impacts vary, and the differences are only slight. The impact of the wall forms is mu ch more significant, and each service life model yields the same order of results. Graphic representations of the models for Atmospheric Ecotoxicity are shown in Figures 4 22, 4 23, 4 24, 4 25 and 4 26. Atmospheric Acidification Each of the models for At mo spheric Acidification identifies brick as the least harmful wall form material, followed by aluminum and wood. In fact, wood is shown to be the most harmful wall for m material by a considerable margin, and this is true in each of the five models. This outc ome is partly due to the transportation required for the wood siding. In conducting the Life Cycle Assessment of this material, cedar siding was specified to require transport from British Columbia in Canada. Essentially, transportation distances for cedar siding were much greater than they were for either brick or aluminum panels. With the exception of the 50 Year static model, the green roof is the preferred roofing option, followed by the TPO membrane and the built up roof. In the 50 Year static model, t he TPO roof has the lowest impact, followed by the green roof and built up roof. The ordering of the roofing materials in the 50 Year static model is of course attributable to the fact that the service lives are equal. T he model is indeed

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99 a comparison of projected initial impacts. The results of these models is shown in Figures 4 27, 4 28, 4 29, 4 30 and 4 31. Life Cycle Impact Models Coarse Models Global Warming Potential All of the Global Warming Potential Coarse mo dels identify brick as the least harm ful wall form material. The USACE and RS Means models identify wood as the second least harmful wall for material, whereas the Athena model show s that aluminum is preferred to wood. Global Warm ing Potential impact for wood and aluminum. The analysis of roofing materials is more consistent. Each of the models shows the green roof to have the lowest impact, followed by the Built Up roof and the TPO membrane. In effect, the order of these results i s differs from those of the energy neutral models, suggesting that the intensity and frequency of maintenance activities influences the outcome. The results of the coarse model analysis for Global Warming Potential are shown in Figures 4 32, 4 33, 4 34 and 4 35. Atmospheric Ecotoxicity The models for Atmospheric Ecotoxicity show a mixture of results. All agree that brick has the least impact, followed by wood and aluminum. The results of the roofing materials show conflict between models ola and Kirk and RS Means models show the green roof as the best material with the lowest impact. However, the Athena model shows all of the roofs as virtually equal, with little if any discernable difference i n impact As compared with the energy neutral models for Atmospheric Ecotoxicity, the ordering of materials in influenced by the frequency and intensity of maintenance activities. This is particularly true for the built up roof, where

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100 maintenance activities produce the most significant difference betw een the energy neutral and coarse models. The results of the Atmospheric Ecotoxicity analysis are shown in Figure 4 36, 4 37, 4 38 and 4 39. Atmospheric Acidification For Atmospheric Acidification, all models identified brick as the least harmful wall form material, followed by aluminum and wood. These differences are all well pronounced, and hold true across all models. All of the models show the green roof as the preferred roofing system, and with the exception of the USACE model, the TPO model is preferr ed to the built up roof. I n the USACE model, the built up roof yields a lesser impact than the TPO membrane, mostly due to the longer service life of the built up roof in this model. The results of the Atmospheric Acidification models are shown in Figures 4 40, 4 41, 4 42 and 4 43. Averages of Cumulative Life Cycle Impacts Models For the purposes of identifying mean trajectories for each of the building envelope combinations, the average value of each envelope combination was modeled for Global Warming Pote ntial, Atmospheric Ecotoxicity and Atmospheric Acidification. Mean cumulative trajectories were assessed using input from the and Kirk and RS Means energy neutral models The results for the Global Warming Potential analysis i ndic ate the following order, fro m least harmful to most harmful: 1) brick with green roof, 2) brick with TPO membrane, 3) brick with built up roof, 4) wood with green roof, 5) wood with TPO membrane, 6) aluminum with green roof, 7) wood with built up roof, 8) aluminum with TPO roof and 9) aluminum with built up roof. From this order, it is possible to determine the relative impact of the materials with respect to oth er wall forms and roofs, as shown in Figure 4 44. For Atmospheric Ecotoxicity, the

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101 order of the envelope combinations changes to the following: 1) brick with green roof, 2) brick with TPO membrane, 3) brick with built up roof, 4) wood with green roof, 5) wood with TPO membrane, 6) wood with built up roof, 7) aluminum with green roof, 8) aluminum with TPO membrane and 9) aluminum with built up roof. As with all of the individual Atmospheric Ecotoxicity models, the impact of the aluminum and associated envelope combinations is significantly higher than it is for the other materials, as shown in Figure 4 45. For Atmospheric Acidification, the order of envelope materials was as follows: 1) brick with green roof, 2) brick with TPO membrane, 3) brick with built up roof, 4) aluminum with green roof, 5) aluminum with TPO membrane, 6) aluminum with built up ro of, 7) wood with green roof, 8) wood with TPO membrane and 9) wood with built up roof, as shown in Figure 4 46. Cumulative Life Cycle Impact Envelope Combinations In the comparison of the five service life models, there are some notable inconsistencies. To begin with, each service life model produced a different result for each building envelope combination. There are several potential explanations for this variability. First, the major replacement intervals for each se rvice life model were different. For example, in the USACE model, brick replacement is suggested every 500 replaced every 75 years. Either scenario is plausible, yet in attempting to assess environmental impa ct, the broad range of potential service life outcomes between these two time frames leaves a lot to the imagination. In assessing these materials on a cumulative basis, the range of potential impacts increases as time progresses, such that the outcomes be come less predictable the farther the models are projected into the future. Subjective differences between models also contribute to the variability, with

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102 some models suggesting more intense maintenance at more frequent intervals. The production of coarse models provided some clarification in this regard, as the variability between models was solely produced by the frequency of the major replacement interval. There are however other ways to view and analyze these data. In reviewing all of the replacement a nd maintenance frequency estimates, each model has a relatively characterized by more conservative measures of service life and maintenance. For a single materials cycle, this p rovides a neat and tidy framework to conduct scenario analyses without delving too far into the future where outcomes are likely to be less certain as time progresses. In contrast, the USACE model predicts materials and assembly usage for periods of up t o 500 years. In prior assessments of brick, this seems as plausible an outcome as any, so long as the material is maintained. Yet, the unc ertainty associated with such a long term analysis makes it somewhat unrealistic, more so when one considers the liter ature on building adaptation, spatial and temporal flexibility and the concept of materials cycling. It may be argued that the comparison of separate service life models is akin to the comparison of different types of logic, with each model characterized by a sort of internal rationale. It is in this way that the comparison of different building envelope combinations across model type may reveal another type of variability altogether. A tendency toward conservative estimates for example may belie the true behavior of the materials. In many ways, it seems reasonable to combine the logic of the different models, or at least consider the possibility that one has accurately predicted the service

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103 life interval s for one material and produced an inaccurate estima te for another. Likewise, it must be considered that the USACE one may be accurate for some of its maintenance activities, and deficient as to the corresponding major replacement intervals. As the graphs for each of the building envelope combinations illus trate, there are a broad range of service life cycle impacts conceivable at each and every iteration of a potential material cycle. There is little rhyme or reason to this variation. Rather, if there is a consistent finding in the analysis of different bui lding envelope combinations, it is that the outcome of any given building is distinctly unclear with uncertainty incre asing as time progresses. This is true across each combination of building envelope materials, and across each metric of environmental im pact Figures 4 47 through 4 73 are illustrative of this point. Life Cycle Impact Per Year Individual Materials The effects of the individual materials were also extracted from each of the five service life models. Much of the literature on Life Cycle As sessment on buildings points toward a need to assess the functional unit as a process, rather than a product. It is believed that the analysis of each individual material herein is representative of this logic, in that the results were derived as the mater ial was part of a process. Moreover, the results o f the individual material analyses in this document are not possible without first performing energy modeling of the materials as part of a larger system, making adjustment to wall forms and roofing types t o equalize thermal efficiency, comparing maintenance oriented models with coarse models, and examining the relative differences between assembly and envelope combinations. Ultimately, the results of the individual materials are properly part of a larger sy stem or process

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104 Global Warming Potential For wall form materials, a considerable amount of overlap is seen in the range of Life Cycle Impact per year. For aluminum, the range of Global Warming P otential Impact is from 1,781 kg of CO2 equivalent to 3,27 9 kg of CO2 equivalen t. For brick, the range is 219 kg of CO2 equivalent to 1,580 kg of CO2 equivale nt. The range for wood is 855 kg of CO2 equivalent to 3,536 kg of CO2 equivalent. It should be noted that there is no overlap between the highest Life Cycle I mpact per year for the brick and the lowest Life Cycle Impact per year for the aluminum. This shows that for the five service life models that were used, all agree that brick is a superior material to aluminum in terms of Global Warming Potential. There is however some overlap between wood and brick and aluminum and wood, owing partially to the relatively large range in Global Warming Potenti al impacts produced by the five service life models. The results of these analyses are shown in Figures 4 74, 4 76, a nd 4 78. As a point of reference, these data were projected into trend lines of Life Cycle Impacts per year, and these graphs appear in Figures 4 75, 4 77 and 4 79. For roofing materials, overlap is evident in each of the material ranges. The range for the green roof was from 457 kg of CO2 equivalent to 963 kg of CO2 equivalent. For the TPO membrane, the range of Global W arming Potential was from 358 kg of CO2 equivalent to 1,254.12 kg of CO2 equivalent. For the Built Up roof, the range was from 384 to 1,16 0 kg of CO2 equivalent. In taking the simple mean for each of these graphs, the green roof seems to be preferred, and indeed this was the case in many of the envelope combination assessments. However, the overlap between these models illustrate s the import ance of the variability. As in the case of the wall forms, these data were projected into linear graphs, and each of these visual representations is shown in

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105 Figures 4 80, 4 81, 4 82, 4 83, 4 84 and 4 85. In figure 4 86, the mean of each model is shown for each individual material Atmospheric Ecotoxicity In terms of Atmospheric Ecotoxicity, there is no overlap between wall form materials The brick is shown to be the best material, followed by wood, with the highest values for aluminum. Thus, o f the five s ervice life models examined, none have identified sufficient amounts of variability to make the appropriate selection of materials unclear. As with the previous sets of data, these Life Cycle Impact per year data were projected into linear models over the course of multiple material cycles, as are shown in Figures 4 86, 4 87, 4 88, 4 89, 4 90 and 4 91. A less clear picture emerges from the examination of the data for roofing material, with overlap shown amongst all three roofing materials. The range for t he green roof is from 1.43 of 2,4 Dichlorophenoxyace equivalent to 2.65 kg of 2,4 Dichlorophenoxyace equivalent. The TPO membrane ranges from 1.28 to 4.48 kg of 2,4 Dichlorophenoxyace equivalent, and the Built Up roof ranges from 1.46 to 4.61 kg of 2,4 Dic hlorophenoxyace equivalent. Again, the overlap illustrates the importance of assumptions in service life. Linear representations of this data were also produced and these shown in Figures 4 92, 4 93, 4 94, 4 95, 4 96 and 4 97 respectively. A mean value rep resentation for these mat erials is shown in Figure 4 98. Atmospheric Acidification For wall form materials, a minimal amount of overlap is evident. The range for aluminum is 312 mol of H+ equivalent to 568 mol of H+ equivalent. For the bric k walls, the ran ge is from 37 mol of H+ equivalent to 267 mol of H+ equivalent. Fo r wood, the range is from 464 mol of H+ equivalent to 2,054 mol of H+ equivalent. There is no

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106 overlap between the wood walls and the brick walls as projected by the five service life models utilized in this analysis. However, there is overlap between the brick wall and the aluminum wall, and between t he wood wall and aluminum wall, such that it is not possible to make conclusions on the material with the least impact. The data were converted into linear projections a s such and each of these ranges is shown in Figures 4 99, 4 100, 4 101, 4 102, 4 103 and 4 104. For roofing materials, overlap is evident in each of the selected materials. The range for the green roof is from 60 mol of H+ equival ent to 127 mol of H+ equivalent. The range fo r the TPO membrane is from 55 mol of H+ equivalent to 192 mol of H+ equivalent. Finally, the range for t he Built Up roof goes from 68 mol of H+ equivalent to 277 ml of H+ equivalent. In effect, the relative impa ct of each of these materials is based on the accuracy of assumption. L inear projections o f these data show an increasing range of possible outcomes a s time progresses. The graphs are shown in Figures 4 105, 4 106, 4 107, 4 108, 4 109 and 4 110. A mean mea surement of each service model for all materials is shown in Figure 4 11 1 Maintenance Versus Coarse Models In order to illustrate the differences in the maintenance effects in the five service life models, the energy neutral models including maintenance impacts were compared with the coarse models. Each service life model showed variation in terms of the impact of maintenance activities. In fact, the percentage of maintenance impacts varied with respect t the service life model that was used, and the particular environmental indicator that was used. In comparing the outcomes of the energy neutral and coarse models, it became evident that the order of the specific envelope combinations changed. As presented in Figures 4 114 through 4 125 this is due to the

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107 variation in percent impact of maintenance activities, and how these percent differences further diverge across different environmental indicators. This becomes most evident when the ranking of envelope outcomes is presented in tabular format, and t he ordering of envelope combinations varies between the energy differential models, the energy neutral models, and the coarse models. In comparing just the ranking of the energy neutral models and the coarse models, it becomes clear that both maintenance a ctivity frequency and intensity, as assumed by service life model, have a direct bearing on the outcome and ranking of different envelope options. These rankings are presented in Figures 4 126 through 4 137. Figure 4 1. Energy Consumption of Building Envelope Combinations 69,100 69,200 69,300 69,400 69,500 69,600 69,700 69,800 69,900 70,000 70,100 Alum_GR Alum_TPO Alum_BUR Wood_GR Wood_TPO Wood_BUR Brick_GR Brick_TPO Brick_BUR BTU per Sqare Foot Per Year Envelope Combination Energy Consumption of Building Envelope Combinations

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108 Figure 4 2. Global Warming Potential USACE Energy Differential Figure 4 3. Global Warming Potential Athena Energy Differential 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) USACE AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Athena AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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109 Figure 4 4. Global Warming Potential Energy Differential Figure 4 5. Global Warming Potential Energy Differential 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Dell'Isola AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) RS Means AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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110 Figure 4 6. Global Warming Potential 50 Year Static Energy Differential Figure 4 7 Atmospheric Ecotoxicity USACE Energy Differential 0 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) 50 Year Static AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) USACE AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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1 11 Figure 4 8. Atmospheric Ecotoxi city Athena Energy Differential Figure 4 9. Atmospheric Ecotoxic i ty Energy Differential 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) Athena AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) Dell'Isola and Kirk AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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112 Figure 4 10. Atmospheric Ecotoxicity Energy Differential Figure 4 11. Atmospheric Ecotoxicity 50 Year Stati c Energy Differential 0 5,000 10,000 15,000 20,000 25,000 1 26 51 76 101 126 151 176 201 226 251 276 301 326 351 376 401 426 451 476 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) RS Means AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophenoxya ce Equivalent Years Atmospheric Ecotoxicity (TRACI) 50 Year Static AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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113 Figure 4 12 Atmospheric Acidification USACE Energy Differential Figure 4 13 Atmospheric Acidification Athena Energy Differential 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) USACE AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H + Equivalent Years Atmospheric Acidification (TRACI) Athena AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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114 Figure 4 14 Atmospheric Acidification Energy Differential F igure 4 15 Atmospheric Acidification Energy Differential 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Dell'Isola and Kirk AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) RS Means AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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115 Figure 4 16. Atmospheric Acidification 50 Year Static Energy Differential Figure 4 17. Global Warming Potential USACE Energy Neutral 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) 50 Year Static AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) USACE AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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116 Figure 4 18. Global war ming Potential Athena Energy Neutral Figure 4 19. Global Warming Potential Energy Neutral 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Athena AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Dell'Isola and Kirk AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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117 Figure 4 20. Global Warming Potential RS Means Energy Neutral Figure 4 21. Global Warming Potential 50 Year Static Energy Neutral 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) RS Means AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) 50 Year Static AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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118 Figure 4 22. Atmospheric Ecotoxicity USACE Energy Neutral Figure 4 23 Atmospheric Ecotoxicity Athena Energy Neutral 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) USACE AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophenoxya ce Equivalent Years Atmospheric Ecotoxicity (TRACI) Athena AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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119 Figure 4 24. Atmospheric Ecotoxicity Energy Neutral Figure 4 25. Atmospheric Ecotoxicity RS Means Energy Neutral 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophenoxya ce Equivalent Years Atmospheric Ecotoxicity (TRACI) Dell'Isola and Kirk AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 5,000 10,000 15,000 20,000 25,000 1 26 51 76 101 126 151 176 201 226 251 276 301 326 351 376 401 426 451 476 KG 2,4 Dichlorophenoxya ce Equivalent Years Atmospheric Ecotoxicity (TRACI) RS Means AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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120 Figure 4 26. Atmospheric Ecotoxicity 50 Year Static Energy Neutral Figure 4 27 Atmospheric Acidification USACE Energy Neutral 0 2,000 4,000 6,000 8,000 10,000 12,000 500 400 300 200 100 KG 2,4 Dichlorophenoxy ace Equivalent Years Atmospheric Ecotoxicity (TRACI) 50 Year Static 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) USACE AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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121 F igure 4 28 Atmospheric Acidification Athena Energy Neutra l Figure 4 2 9 At mospheric Acidification Energy Neutral 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H + Equivalent Years Atmospheric Acidification (TRACI) Athena AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Dell'Isola and Kirk AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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122 Figure 4 30 Atmospheric Acidification RS Means Energy Neutral Figure 4 31 Atmospheric Acidification 50 Year Static Energy Neutral 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) RS Means AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 100,000 200,000 300,000 400,000 500,000 600,000 500 400 300 200 100 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) 50 Year Static

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123 Figure 4 32 Global Warming Potential USA CE Coarse Model Figure 4 33. Global Warming Potential Athena Coarse Model 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 kg of CO2 equivalent Years Global Warming Potential (TRACI) USACE Coarse Model AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD_GR_A WD_TPO_A WD_BUR_A 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Athena AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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124 Figure 4 34. Global Warming Potential Coarse Model Figure 4 35. Global Warming Potential RS Means Coarse Model 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Dell'Isola and Kirk AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) RS Means Coarse Model AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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125 Figure 4 36 Atmospheric Ecotoxicity USACE Coarse Model Figure 4 37. Atmospheric Ecotoxicity Athena Coarse Model 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) USACE AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophenoxy ace Equivalent Years Atmospheric Ecotoxicity (TRACI) Athena Coarse Model AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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126 Figure 4 38. Atmospheric Ecotoxicity Coarse Model Figure 4 39. Atmospheric Ecotoxicity RS Means Coarse Model 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophe noxyace Equivalent Title Atmospheric Ecotoxicity (TRACI) Dell'Isola and Kirk Coarse Model AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 Title Title Atmospheric Ecotoxicity (TRACI) RS Means Coarse Model AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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127 Figure 4 40 Atmospheric Acidification USACE Coarse Model Figure 4 41 Atmospheric Acidification Athena Coarse Model 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) USACE Coarse Model AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H + Equivalent Years Atmospheric Acidification (TRACI) Athena AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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128 Figure 4 42 Atmospheric Acidification Coarse Model Figure 4 4 3 Atmospheric Acidification RS Means Coa rse Model 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Dell'Isola and Kirk AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) RS Means Coarse Model AL_GR_A AL_TPO_A AL_BUR_A BR_GR_A BR_TPO_A BR_BUR_A WD1_GR_A WD1_TPO_A WD1_BUR_A

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129 Figure 4 44 Global Warming Potential All Models Energy Neutral Figure 4 45 Atmospheric Ecotoxicity All Models Energy Neutral 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG of CO2 Equivalent Years Global Warming Potential (TRACI) All Models AL_GR_AVERAGE AL_TPO_AVERAGE AL_BUR_AVERAGE BR_GR_AVERAGE BR_TPO_AVERAGE BR_BUR_AVERAGE WD_GR_AVERAGE WD_TPO_AVERAGE WD_BUR_AVERAGE 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 Title Title Atmospheric Ecotoxicity (TRACI) All Models AL_GR_AVERAGE AL_TPO_AVERAGE AL_BUR_AVERAGE BR_GR_AVERAGE BR_TPO_AVERAGE BR_BUR_AVERAGE WD_GR_AVERAGE WD_TPO_AVERAGE WD_BUR_AVERAGE

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130 Figure 4 46 Atmospheric Acidification All Models Energy Neutral Figure 4 47 Global Warming Po tential Aluminum with Green Roof Energy Neutral 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) All Models AL_GR_AVERAGE AL_TPO_AVERAGE AL_BUR_AVERAGE BR_GR_AVERAGE BR_TPO_AVERAGE BR_BUR_AVERAGE WD_GR_AVERAGE WD_TPO_AVERAGE WD_BUR_AVERAGE 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Aluminum Panel with Green Roof AL_GR_RS MEANS AL_GR_ARMY AL_GR_ATHENA AL_GR_50 AL_GR_DELL'ISOLA

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131 Figure 4 48 Global Warming Potential Aluminum with TPO Roof Energy Neutral Figure 4 49 Global Warming Potential Aluminum with Built Up Roof Energy Neutral 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Aluminum Panel with TPO Roof AL_TPO_RS MEANS AL_TPO_ARMY AL_TPO_ATHENA AL_TPO_DELL'ISOLA AL_TPO_50 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Aluminum Panel with Built Up Roof AL_BUR_RS MEANS AL_BUR_ARMY AL_BUR_ATHENA AL_BUR_DELL'ISOLA AL_BUR_50

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132 Figure 4 50 Global Warming Po tential Brick with Green Roof Energy Neutral Figure 4 51 Global Warming Potential Brick with TPO Roof Energy Neutral 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Brick with Green Roof BR_GR_RS MEANS BR_GR_ARMY BR_GR_ATHENA BR_GR_DELL'ISOLA BR_GR_50 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Brick with TPO Roof BR_TPO_RS MEANS BR_TPO_ARMY BR_TPO_ATHENA BR_TPO_DELL'ISOLA BR_TPO_50

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133 Figure 4 52 Global Warming Potential Brick with Built Up Roof Energy Neutral Figure 4 53 Global Warming Potential Wood with Green Roof Energy Neutral 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Brick with Built Up Roof BR_BUR_RS MEANS BR_BUR_ARMY BR_BUR_ATHENA BR_BUR_DELL'ISOLA BR_BUR_50 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Wood with Green Roof WD_GR_RS MEANS WD_GR_ARMY WD_GR_ATHENA WD_GR_DELL'ISOLA WD_GR_50

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134 Figure 4 54 Global Warming Potential Wood with TPO Roof Energy Neutral Figure 4 55 Global Warming Potential Wood with Built Up Roof Energy Neutral 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Wood with TPO Roof WD_TPO_RS MEANS WD_TPO_ARMY WD_TPO_ATHENA WD_TPO_DELL'ISOLA WD_TPO-50 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG of CO2 Equivalent Years Global Warming Potential (TRACI) Wood with Built Up Roof WD_BUR RS MEANS WD_BUR_ARMY WD_BUR_ATHENA WD_BUR_DELL'ISOLA WD_BUR_50

PAGE 135

135 Figure 4 56 Atmospheric Ecotoxicity Aluminum wit h Green Roof Energy Neutral Figure 4 57 Atmospheric Ecotoxicity Aluminum with TPO Roof Energy Neutral 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) AL_GR_RS MEANS AL_GR_ATHENA AL_GR_50 AL_GR_DELL'ISOLA AL_GR_ARMY 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) AL_TPO_RS MEANS AL_TPO_ARMY AL_TPO_ATHENA AL_TPO_DELL'ISOLA AL_TPO_50

PAGE 136

136 Figure 4 58 Atmospheric Ecotoxicity Aluminum with Built Up Roof Energy Neutral Figure 4 59 Atmospheric Ecotoxicity Brick with Gree n Roof Energy Neutral 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) AL_BUR_RS MEANS AL_BUR_ARMY AL_BUR_ATHENA AL_BUR_DELL'ISOLA AL_BUR_50 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG 2,4 Dichloropheno xyace Equivalent Years Atmospheric Ecotoxicity (TRACI) BR_GR_RS MEANS BR_GR_ARMY BR_GR_ATHENA BR_GR_DELL'ISOLA BR_GR_50

PAGE 137

137 Figure 4 60 Atmospheric Ecotoxicity Brick with TPO Roof Energy Neutral Figure 4 61 Atmospheric Ecotoxicity Brick with Built Up Roof Energy Neutral 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) BR_TPO_RS MEANS BR_TPO_ARMY BR_TPO_ATHENA BR_TPO_DELL'ISOLA BR_TPO_50 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) BR_BUR_RS MEANS BR_BUR_ARMY BR_BUR_ATHENA BR_BUR_DELL'ISOLA BR_BUR_50

PAGE 138

138 Figure 4 62 Atmospheric Ecotoxicity Wood with Green Roof Ener gy Neutral Figure 4 63 Atmospheric Ecotoxicity Wood with TPO Roof Energy Neutral 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG 2,4 Dichlorophen oxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) WD_GR_RS MEANS WD_GR_ARMY WD_GR_ATHENA WD_GR_DELL'ISOLA WD_GR_50 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG 2,4 Dichlorophen oxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) ARMY WD_TPO_RS MEANS WD_TPO_ARMY WD_TPO_ATHENA WD_TPO_DELL'ISOLA WD_TPO-50

PAGE 139

139 Figure 4 64 Atmospheric Ecotoxicity Wood with Built Up Roof Energy Neutral Figure 4 65 Atmospheric Ecotoxicity Aluminum with Green Roof Energy Neutral 0 5,000 10,000 15,000 20,000 25,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 KG 2,4 Dichlorophen oxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) ARMY WD_BUR RS MEANS WD_BUR_ARMY WD_BUR_ATHENA WD_BUR_DELL'ISOLA WD_BUR_50 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Aluminum Panel with Green Roof AL_GR_RS MEANS AL_GR_ATHENA AL_GR_50 AL_GR_DELL'ISOLA AL_GR_ARMY

PAGE 140

140 Figure 4 66 Atmospheric Ecotoxicity Aluminum with TPO Roof Energy Neutral Figure 4 67 Atmospheric Ecotoxicity Aluminum with Built Up Roof Energy Neutral 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Aluminum Panel with TPO Roof AL_TPO_RS MEANS AL_TPO_ARMY AL_TPO_ATHENA AL_TPO_DELL'ISOLA AL_TPO_50 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Aluminum Panel with Built Up Roof AL_BUR_RS MEANS AL_BUR_ARMY AL_BUR_ATHENA AL_BUR_DELL'ISOLA AL_BUR_50

PAGE 141

141 Figure 4 68 Atmospheric Ecotoxicity Brick with Green Roof Energy Neutral Figu re 4 69 Atmospheric Ecotoxicity Brick with TPO Roof Energy Neutral 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Brick with Green Roof BR_GR_RS MEANS BR_GR_ARMY BR_GR_ATHENA BR_GR_DELL'ISOLA BR_GR_50 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Brick with TPO Roof BR_TPO_RS MEANS BR_TPO_ARMY BR_TPO_ATHENA BR_TPO_DELL'ISOLA BR_TPO_50

PAGE 142

142 Fig ure 4 70 Atmospheric Ecotoxicity Brick with Built Up Roof Energy Neutral Figure 4 71 Atmospheric Ecotoxicity Wood with Green Roof Energy Neutral 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Brick with Built Up Roof BR_BUR_RS MEANS BR_BUR_ARMY BR_BUR_ATHENA BR_BUR_DELL'ISOLA BR_BUR_50 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Wood with Green Roof WD_GR_RS MEANS WD_GR_ARMY WD_GR_ATHENA WD_GR_DELL'ISOLA WD_GR_50

PAGE 143

143 Figure 4 72 Atm ospheric Ecotoxicity Wood with TPO Roof Energy Neutral Figure 4 73 Atmospheric Ecotoxicity Wood with Built Up Roof Energy Neutral 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Wood with TPO Roof WD_TPO_RS MEANS WD_TPO_ARMY WD_TPO_ATHENA WD_TPO_DELL'ISOLA WD_TPO_50 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 mol of H+ Equivalent Years Atmospheric Acidification (TRACI) Wood with Built Up Roof WD_BUR RS MEANS WD_BUR_ARMY WD_BUR_ATHENA WD_BUR_DELL'ISOLA WD_BUR_50

PAGE 144

144 Figure 4 75. Global Warming Potential Life Cycle Impact Per Year Aluminum Figure 4 76. Global Warming Po tential Life Cycle Impact Per Year Trendline Aluminum 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 kg of CO2 equivalent Life Cycle Impact Per Year Global Warming Potential Aluminum ARMY 50 DELL'ISOLA ATHENA RS MEANS 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 2,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 kg of CO2 equivalent Global Warming Potential (TRACI) Aluminum Panels RS MEANS DELL'ISOLA ATHENA ARMY 50 AVERAGE

PAGE 145

145 Figure 4 77. Global Warming Potential Life Cycle Impact Per Year Brick Figure 4 78. Global Warming Potential Life Cycle Impact Per Year Trendline Brick 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 kg of CO2 equivalent Life Cycle Impact Per Year Global Warming Potential Brick ARMY ATHENA RS MEANS DELL'ISOLA 50 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 2,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 Title Title Global Warming Potential (TRACI) Brick AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 146

146 Figure 4 79. Global Warming P otential Life Cycle Impact Per Year Wood Figure 4 80. Global Warming Potential Life Cycle Impact Per Year Trendline Wood 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 kg of CO2 equivalent Life Cycle Impact Per Year Global Warming Potential Wood ARMY 50 RS MEANS DELL'ISOLA ATHENA 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 2,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500 kg of CO2 equivalent Years Global Warming Potential (TRACI) Wood AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 147

147 Figure 4 81. Global Warming Potential Life Cycle Impact Per Year Green Roof F igure 4 82. Global Warming Potential Life Cycle Impact Per Year Trendline Green Roof 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 kg of CO2 equivalent Life Cycle Impact Per Year Global Warming Potential Green Roof 50 ARMY ATHENA DELL'ISOLA RS MEANS 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 2,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 kg of CO2 equivalent Years Global Warming Potential (TRACI) Green Roof AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 148

148 Figure 4 83. Global Warming Potential Life Cycle Impact Per Year TPO Roof Figure 4 84. Global Warming Potential Life Cycle Impact Per Year Trendline TPO Roof 0.00 500.00 1,000.00 1,500.00 2,000.00 2,500.00 3,000.00 3,500.00 4,000.00 kg of CO2 equivalent Life Cycle Impact Per Year Global Warming Potential TPO Membrane 50 ATHENA DELL'ISOLA RS MEANS ARMY 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 2,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 kg of CO2 equivalent Years Global Warming Potential (TRACI) TPO Membrane AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 149

149 Figure 4 85. Global Warming Po tential Life Cycle Impact Per Year Built Up Roof Figure 4 86. Global Warming Potential Life Cycle Impact Per Year Trendline Built Up Roof 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 kg of CO2 equivalent Life Cycle Impact Per Year Global Warming Potential Built Up Roof 50 RS MEANS DELL'ISOLA ATHENA ARMY 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 2,000,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 kg of CO2 equivalent Years Global Warming Potential (TRACI) Built Up Roof AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 150

150 Figure 4 87. Global Warming Potential Life Cycle Impact Per Year All Materials Average Figure 4 88. Atmospheric Ecotoxicity Life Cycle Impact Per Year Aluminum 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 KG of CO2 Equivalent Global Warming Potential (TRACI) LCI per Year Green Roof Brick TPO Roof BUR Roof Wood Aluminum 0 5 10 15 20 25 30 35 KG 2,4 Dichlorophen oxyace Equivalent Life Cycle Impact Per Year Atmospheric Ecotoxicity Aluminum ARMY 50 DELL'ISOLA ATHENA RS MEANS

PAGE 151

151 Figure 4 89. Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Aluminum Figure 4 90. Atmospheric Ecotoxicity Life Cycle Impact Per Year Brick 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophen oxyace Equivalent Years Atmosperic Ecotoxocity (TRACI) Aluminum AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 KG 2,4 Dichlorophen oxyace Equivalent Life Cycle Impact Per Year Atmospheric Ecotoxicity Brick ARMY ATHENA DELL'ISOLA RS MEANS 50

PAGE 152

152 Figure 4 91. Atmos pheric Ecotoxicity Life Cycle Impact Per Year Trendline Brick Figure 4 92 Atmospheric Ecotoxicity Life Cycle Impact Per Year Wood 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophen oxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) Brick AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 KG 2,4 Dichlorophen oxyace Equivalent Life Cycle Impact Per Year Atmospheric Ecotoxicity Wood ARMY 50 RS MEANS DELL'ISOLA ATHENA

PAGE 153

153 Figure 4 93 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Wood Figure 4 94. Atmospheric Ecotoxicity Life Cycle Impact Per Year Green Roof 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophen oxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) Wood AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 KG 2,4 Dichlorophen oxyace Equivalent Life Cycle Impact Per Year Atmospheric Ecotoxicity Green Roof 50 ARMY ATHENA RS MEANS DELL'ISOLA

PAGE 154

154 Figure 4 95. Atmospheric Ecotoxicity Life Cycle Impact Per Year Green Roof Figure 4 96 Atmospheric Ecotoxicity Life Cycle Impact Per Year TPO Roof 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophe noxyace Equivalent Years Atmospheric Ecotoxicity (TRACI) Green Roof AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 KG 2,4 Dichlorophe noxyace Equivalent Life Cycle Impact Per Year Atmospheric Ecotoxicity TPO Membrane 50 ATHENA DELL'ISOLA RS MEANS ARMY

PAGE 155

155 Figure 4 97 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Green Roof Figure 4 98 Atmospheric Ecotoxicity Life Cycle Impact Per Year Built Up Roof 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophenox yace Equivalent Axis Title Atmospheric Ecotoxicity (TRACI) TPO Membrane AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 KG 2,4 Dichlorophen oxyace Equivalent Life Cycle Impact Per Year Atmospheric Ecotoxicity Built Up Roof 50 ARMY RS MEANS DELL'ISOLA ATHENA

PAGE 156

156 Figure 4 99 Atmospheric Ecotoxicity Life Cycle Impact Per Year Trendline Built Up Roof Figure 4 100 Atmosphe ric Ecotoxicity Life Cycle Impact Per Year Trendline Average All Materials 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 KG 2,4 Dichlorophenox yace Equivalent Years Atmospheric Ecotoxicity (TRACI) Built Up Roof AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50 0 5 10 15 20 25 30 35 KG 2,4 Dichlorophen oxyace Equivalent LCI Impact Per Year Atmospheric Ecotoxocity (TRACI) BRICK GREEN ROOF TPO MEMBRANE BUILT-UP ROOF WOOD ALUMINUM

PAGE 157

157 Figure 4 101 Atmospheric Acidification Life Cycle Impact Per Year Alumin um Figure 4 102 Atmospheric Acidification Life Cycle Impact Per Year Trendline Aluminum 0 500 1,000 1,500 2,000 2,500 mol of H+ equivalent Life Cycle Impact Per Year Atmospheric Acidification Aluminum ARMY 50 DELL'ISOLA ATHENA RS MEANS 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ equivalent Years Atmospheric Acidification (TRACI) Aluminum AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 158

158 Figure 4 103 Atmospheric Acidification Life Cycle Impact Per Year Brick Figure 4 104 Atmospheric Acidification Life Cycle Impact Per Year Trendline Brick 0 500 1,000 1,500 2,000 2,500 mol of H+ equivalent Life Cycle Impact Per Year Atmospheric Acidification Brick ARMY ATHENA DELL'ISOLA RS MEANS 50 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ equivalent Years Atmospheric Acidification (TRACI) Brick AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 159

159 Figure 4 105 Atmospheric Acidification Life Cycle Impact Per Year Wood Figure 4 106 Atmospheric Acidification Life Cycle Impact Per Year Trendline Wood 0 500 1,000 1,500 2,000 2,500 mol of H+ equivalent Life Cycle Impact Per Year Atmospheric Acidification Wood ARMY 50 RS MEANS DELL'ISOLA ATHENA 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ equivalent Years Atmospheric Acidification (TRACI) Wood AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 160

160 Figure 4 107 Atmospheric Acidification Life Cycle Impact Per Year Green Roof Figure 4 108 Atmospheric Acidification Life Cycle Impact Per Year Trendline Green Roof 0 500 1,000 1,500 2,000 2,500 mol of H+ equivalent Life Cycle Impact Per Year Atmospheric Acidification Green Roof 50 ARMY ATHENA DELL'ISOLA RS MEANS 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ equivalent Years Atmospheric Acidification (TRACI) Green Roof AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 161

161 Figure 4 1 09 Atmospheric Acidification Life Cycle Impact Per Year TPO Roof Figure 4 11 0 Atmospheric Acidification Life Cycle Impact Per Year Trendline TPO Roof 0 500 1,000 1,500 2,000 2,500 mol of H+ equivalent Life Cycle Impact Per Year Atmospheric Acidification TPO Membrane 50 ATHENA DELL'ISOLA RS MEANS ARMY 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ equivalent Years Atmospheric Acidification (TRACI) TPO Membrane AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 162

162 Figure 4 11 1 Atmospheric Acidification Life Cycle Impact Per Year B uilt Up Roof Figure 4 11 2 Atmospheric Acidification Life Cycle Impact Per Year Trendline Built Up Roof 0 500 1,000 1,500 2,000 2,500 mol of H+ equivalent Life Cycle Impact Per Year Atmospheric Acidification Built Up Roof 50 RS MEANS DELL'ISOLA ATHENA ARMY 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 mol of H+ equivalent Years Atmospheric Acidification (TRACI) Built Up Roof AVERAGE RS MEANS DELL'ISOLA ATHENA ARMY 50

PAGE 163

163 Figure 4 11 3 Atmospheric Acidification Life Cycle Impact Per Year Average All Materials Figure 4 114. Global Warming Potential Life Cy cle Impact Per Year Coarse Versus Maintenance Models USACE 0 200 400 600 800 1,000 1,200 1,400 mol of H+ equivalent Atmospheric Acidification (TRACI) Life Cycle Impact Per Year Green Roof TPO Membrane Brick Built-Up Roof Aluminum Wood 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage Life Cycle Impact Envelope Combination Global Warming Potential USACE LCI Contributions Coarse Versus Maintenance Model Maintenance Coarse Model

PAGE 164

164 Figure 4 115. Global Warming Potential Life Cycle Impact Per Year Coarse Versus Maintenance Models Athena Figure 4 116. Global Warming Potential Life Cycle Impact Per Year Coarse V ersus Maintenance Models 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage Envelope Combination Global Warming Potential Athena LCI Contributions Coarse Versus Maintenance Model Maintenance Coarse Model 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Axis Title Envelope Combination Global Warming Potential Dell'Isola and Kirk LCI Contributions Coarse Versus Maintenance Model Maintenance Model Coarse Model

PAGE 165

165 Figure 4 11 7 Global Warming Potential Life Cycle Impact Per Year Coarse Versus Maintenance Models RS Means Figure 4 118. Atmospheric Ecotoxicity Life Cycle Impact Per Year Coarse Versus Maintenan ce Models USACE 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage Envelope Combinations Global Warming Potential RS Means LCI Contributions Coarse Versus Maintenance Model Maintenance Model Coarse Model 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage Life Cycle Impact Envelope Combination Atmospheric Ecotoxicity USACE LCI Contributions Coarse Versus Maintenance Model Maintenance Coarse Model

PAGE 166

166 Figure 4 119. Atmospheric Ecotoxicity Life Cycle Impact Per Year Coarse Versus Maintenance Models Athena Figure 4 120. Atmospheric Ecotoxicity Life Cycle Impact Per Year Coarse Versus Maintenance Models 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage Envelope Combination Atmospheric Ecotoxicity Athena LCI Contributions Coarse Versus Maintenance Model Maintenance Coarse Model 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Axis Title Envelope Combination Atmosperic Ecotoxicity Dell'Isola and Kirk LCI Contributions Coarse Versus Maintenance Model Maintenance Model Coarse Model

PAGE 167

167 Figure 4 121. Atmospheric Ecotoxicity Life Cycle Impact Per Year Coarse Versus Maintenance Models RS Means Figure 4 122. Atmospheric Acidification Life Cycle Impact Per Year Coarse Versus Maintenance Models USACE 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage Envelope Combinations Global Warming Potential RS Means LCI Contributions Coarse Versus Maintenance Model Maintenance Model Coarse Model 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage Life Cycle Impact Envelope Combination Atmospheric Acidification USACE LCI Contributions Coarse Versus Maintenance Model Maintenance Coarse Model

PAGE 168

168 Figure 4 123. Atmospheric Acidification Life Cycle Impact Per Year Coarse Versus Maintenance Models Athena Figure 4 124. Atmospheric Acidification Life Cycle Impact Per Year Coarse Versus Maintenance Models 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage Envelope Combination Atmospheric Acidification Athena LCI Contributions Coarse Versus Maintenance Model Maintenance Coarse Model 75% 80% 85% 90% 95% 100% Axis Title Envelope Combination Atmospheric Acidification Dell'Isola and Kirk LCI Contributions Coarse Versus Maintenance Model Maintenance Model Coarse Model

PAGE 169

169 Figure 4 125. Atmospheric Acidificatio n Life Cycle Impact Per Year Coarse Versus Maintenance Models RS Means USACE Global Warming Potential Ranking Energy Differential Energy Neutral Coarse AL_GR 3 7 7 AL_TPO 5 9 9 AL_BUR 8 8 8 BR_GR 1 1 1 BR_TPO 2 4 3 BR_BUR 7 2 2 WD_GR 4 3 4 WD_TPO 6 6 6 WD_BUR 9 5 5 Figure 4 126. Envelope Combination Ranking USACE Energy Differential, Energy Neutral and Coarse Global Warming Potential 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage Envelope Combinations Atmosperic Acidification RS Means LCI Contributions Coarse Versus Maintenance Model Maintenance Model Coarse Model

PAGE 170

170 ATHENA Global Warming Potential Ranking Energy Differential Energy Neutral Coarse A L_GR 3 4 4 AL_TPO 5 5 7 AL_BUR 8 8 5 BR_GR 1 1 1 BR_TPO 2 2 3 BR_BUR 4 3 2 WD_GR 6 6 6 WD_TPO 7 7 9 WD_BUR 9 9 8 Figure 4 127. Envelope Combination Ranking Athena Energy Differential, Energy Neutral and Coarse Global Warming Potential DELL 'ISOLA Global Warming Potential Ranking Energy Differential Energy Neutral Coarse AL_GR 3 3 4 AL_TPO 4 4 7 AL_BUR 8 7 6 BR_GR 1 1 1 BR_TPO 2 2 3 BR_BUR 6 5 2 WD_GR 5 6 5 WD_TPO 7 8 9 WD_BUR 9 9 8 Figure 4 128. Envelope Combination Rankin g Energy Differential, Energy Neutral and Coarse Global Warming Potential RS MEANS Global Warming Potential Ranking Energy Differential Energy Neutral Coarse AL_GR 4 7 8 AL_TPO 7 8 9 AL_BUR 9 9 7 BR_GR 1 1 2 BR_TPO 2 2 3 BR_BUR 6 3 1 WD_GR 3 4 5 WD_TPO 5 5 6 WD_BUR 8 6 4 Figure 4 129. Envelope Combination Ranking RS Means Energy Differential, Energy Neutral and Coarse Global Warming Potential

PAGE 171

171 USACE Atmospheric Ecotoxicity Ranking Energy Different ial Energy Neutral Coarse AL_GR 7 8 7 AL_TPO 8 9 9 AL_BUR 9 7 8 BR_GR 1 1 1 BR_TPO 2 4 3 BR_BUR 4 2 2 WD_GR 3 3 4 WD_TPO 5 6 6 WD_BUR 6 5 5 Figure 4 130. Envelope Combination Ranking USACE Energy Differential, Energy Neutral and Coarse At mospheric Ecotoxicity ATHENA Atmospheric Ecotoxicity Ranking Energy Differential Energy Neutral Coarse AL_GR 7 7 4 AL_TPO 8 8 7 AL_BUR 9 9 5 BR_GR 1 1 1 BR_TPO 2 2 3 BR_BUR 3 3 2 WD_GR 4 4 6 WD_TPO 5 5 9 WD_BUR 6 6 8 Figure 4 131. Envelo pe Combination Ranking Athena Energy Differential, Energy Neutral and Coarse Atmospheric Ecotoxicity DELL'ISOLA Atmospheric Ecotoxicity Ranking Energy Differential Energy Neutral Coarse AL_GR 7 7 7 AL_TPO 8 8 8 AL_BUR 9 9 9 BR_GR 1 1 1 B R_TPO 2 2 2 BR_BUR 3 3 3 WD_GR 4 4 4 WD_TPO 5 5 5 WD_BUR 6 6 6 Figure 4 132. Envelope Combination Ranking Energy Differential, Energy Neutral and Coarse Atmospheric Ecotoxicity

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172 RS MEANS Atmospheric Ecotoxicity Ranking Energy Differential Energy Neutral Coarse AL_GR 7 7 7 AL_TPO 8 8 8 AL_BUR 9 9 9 BR_GR 1 1 1 BR_TPO 2 2 2 BR_BUR 4 3 3 WD_GR 3 4 4 WD_TPO 5 5 5 WD_BUR 6 6 6 Figure 4 133. Envelope Combination Ranking RS Means Energy Differential, Energy Neu tral and Coarse Atmospheric Ecotoxicity USACE Atmospheric Acidification Ranking Energy Differential Energy Neutral Coarse AL_GR 3 4 4 AL_TPO 4 5 6 AL_BUR 8 6 5 BR_GR 1 1 1 BR_TPO 2 2 3 BR_BUR 6 3 2 WD_GR 5 6 7 WD_TPO 7 8 9 WD_BUR 9 9 8 Figure 4 134. Envelope Combination Ranking USACE Energy Differential, Energy Neutral and Coarse Atmospheric Acidification ATHENA Atmospheric Acidification Ranking Energy Differential Energy Neutral Coarse AL_GR 3 4 4 AL_TPO 4 5 5 AL_BUR 6 6 6 BR_GR 1 1 1 BR_TPO 2 2 2 BR_BUR 5 3 3 WD_GR 7 7 7 WD_TPO 8 8 8 WD_BUR 9 9 9 Figure 4 135. Envelope Combination Ranking Athena Energy Differential, Energy Neutral and Coarse Atmospheric Acidification

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173 DELL'ISOLA Atmospheric Acidificati on Ranking Energy Differential Energy Neutral Coarse AL_GR 3 4 4 AL_TPO 4 5 5 AL_BUR 7 6 6 BR_GR 1 1 1 BR_TPO 2 2 2 BR_BUR 5 3 3 WD_GR 6 7 7 WD_TPO 8 8 8 WD_BUR 9 9 9 Figure 4 136. Envelope Combination Ranking Energ y Differential, Energy Neutral and Coarse Atmospheric Acidification RS MEANS Atmospheric Acidification Ranking Energy Differential Energy Neutral Coarse AL_GR 3 4 4 AL_TPO 4 5 5 AL_BUR 8 6 6 BR_GR 1 1 1 BR_TPO 2 2 2 BR_BUR 5 3 3 WD_GR 6 7 7 WD_TPO 7 8 8 WD_BUR 9 9 9 Figure 4 137. Envelope Combination Ranking RS Means Energy Differential, Energy Neutral and Coarse Atmospheric Acidification

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174 CHAPTER 5 DISCUSSION, CONCLUSI ON, THE FUTURE The first part of this research involved the c onstruction of Life Cycle Assessments using nine building envelope combinations. These envelopes were integrated into the context of a larger building to provide a more complete analysis It was concluded that the choice of wall and roof materials has a si gnificant effect on the Life Cycle Impact of a building due to the associated consumption of operating energy Much of the literature has stated that operating energy is the dominant variable in assessing Life Cycle Impact. Some have stated that upwards of 90% of the Life Cycle Impact is attributable to operating energy consumption. This may be true in the analysis of a single building. Generally speaking, t he operating energy is the dominant impact. However, when assessing different wall form s and roofing options for example, a means of comparison is necessary. It is for this reason that this study opted to assess the impacts of operating energy differentials in the analysis of wall forms and roofing. As shown in the section of this document detailing the L ife Cycle Impact and service life models with energy differentials, the comparison of operating energy impacts is highly influential, but not completely dominant. The noted exception was with aluminum as measured for Atmospheric Ecotoxicity. Here, the impa ct of the material superseded the impact of the operating energy differential, as indicated by a change in order from the energy analysis results to those of the energy differential models, including maintenance. The equalization of Life Cycle Impact mode ls has also revealed some important findings. Since operating energy impacts contribute so heavily, the selection of wall form and roofing materials becomes all the more important. Modifications to walls and roofs can be accomplished, such that thermal per formance can be equalized, but this may

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175 involve considerable change to conventional construction techniques. T he modification of walls and roofs in this manner is seen as a means of honing in on the impact of the maintenance and major replacement intervals Indeed, the results of this stage of the analysis varied as compared with the results of the energy differential model s To further isolate the effects of maintenance, the coarse models were constructed and again yielded a different ordering and magnitud e of the outcomes. Th ese differences were entirely attributable to the subjective differences in each model s maintenance interval frequency and intensity as all other variables remained the same Ultimately, a significant amount of variation is evident in the results produced by the five service life models employed i n the study. An examination of Life Cycle Impacts per year makes this clearer. Some of the individual wall form and roofing materials showed overlap from model to model and the best choice in terms of environmental impact is not always clear In reference to the coarse models, some of this overlap was intensity. However, it is safe to say that the overla p is representative of a number of factors, including the differences in major replacement frequency and inherent material properties Conclusions As the original hypothesis proposed, variations in the Life Cycle Impacts of building envelope materials are dependent on longevity, differential durability and cumulative maintenance over time For the five service life models that were constructed for this analysis, this hypothesis must be upheld As shown in the representation of Life Cycle Impact per year, t he impact of an individual material can vary such that it cannot conclusively be preferred to another material of similar purpose.

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176 To make conclusions beyond the five service life models used in this study however would be premature. T he external validity of this study cannot be verified without further analysis and perhaps the integration of additional service life models. As such, the hypothesis holds true with consideration to the scope of the study, and not beyond. Conclusions may also be drawn on the contributions of operating energy usage and the impacts of maintenance over time. As stated previously the operating energy usage of a building produces a highly influential environmental impact. At least, this is true for the building envelope combinatio ns and ancillary mechanical equipment and systems analyzed in this study. Likewise, m aintenance is a determining factor in assessing the relative impacts of building envelope materials, as the ordering and magnitude of the results changed from the energy n eutral to the coarse models. It must also be conceded that other factors play a role in the cumulative environmental impacts of building envelope materials, such as the physical and chemical properties of the materials themselves. However, these differenc es do not account for the variability that is evident in the analysis of a single wall or roof form material across the five different service life models. Nor does it account for the differences in results from the energy differential model, the energy ne utral model and the coarse model. Ultimately, some of the variation is attributable to the differences material long evity and cumulative maintenance over time The Future For Life Cycle Assessment as an individual area of study, future research endeavors s hould focus on improving the methodology. This can be accomplished using two distinct approaches. First, the Life Cycle Assessment method is continually enhanced by the gathering of increasingly higher quality, primary data. As such, there

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177 are a multitude of studies that could be performed with the simple objective of providing additional and improved points of comparison. Second, methodological improvements in Life Cycle Assessment can be accomplished through the statistical analysis of existing, secondary data sources. As in the case of this research, the analysis of existing data sets offers a good deal of potential. Certainly, f uture research should entail the inclusion of service life analyses. Similar improvements could be made to the various methods of Service Life Prediction. Within the area of damage mechanics, current models allow for reasonable predictions of expected service life. Yet, competing methodologies and built in assumptions have led to a lack of consensus. Consequently, there is a need for better and universally applicable empirical data. Since empirical studies are often used to buttress or negate the hypotheses of prediction models, they are of course the logical precursors to consensus building. In addition, improvements in empirical data would provide a mathematical basis for a wide range of service life factors, including climate, design, installation quality, material quality, in use conditions and maintenance. With improvement of the existing methods in mind, the focus should be on the gathering of empirical data through a combination of materials testing and surveys of existing building department and facility operations databases. This would also provide valuable insight for practitioners of Life Cycle Assessment, as we have alrea dy conclude d that the accuracy of a Life Cycle Impact study is contingent, at least in part, on the accuracy of the assumed service life and maintenance values and descriptions. The confluence of these two methods generates yet another set of questions. Fo r instance, when Life Cycle Assessment Impacts are quantified in relation to Service Life

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178 Predictions, durable and long lived building materials and assemblies are not necessarily the preferred options. In many circumstances, cheaper, less durable and shor t lived materials and assemblies yield a lesser impact. With this idea in mind, research on recycling, deconstruction, adaptive architecture modular and prefabri c ated construction takes on a new meaning. A combination of Life Cycle Energy Assessment, ener gy modeling, and periodic thermal imaging could be used to determine assembly and performance degradation over time. From a facility operations standpoint, this type of analysis would provide important maintenance data, and differentiate between high and l ow maintenance materials and assemblies. Further, a simple translation of the resulting data into Life Cycle Costing would provide prospective owners with a more realistic expectation of potential costs Additional work should also be performed on buildings in the context of time. Materials degradation is of course one aspect of this type of analysis. However, this area of research also involves technological forecasting Understandably, work in this area is somewhat restrained due to per ceived risk It is indeed difficult to predict the future However the production of Life Cycle Assessment models including estimations of risk would provide valuable insight into the appropriateness of buil ding and material service lives Ultimately, res earch in this area must acknowledge spatial and temporal dynamism. We must make a ssumptions on poten tial improvements in efficiency and the potential degradation of services over time. It is hoped that future analyses in Life Cycle Assessment are based wel l founded assumptions and that an improved representation of Life Cycle Impact will result.

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179 APPENDIX A MATERIAL QUANTITY TA KE OFF Brick Wall Assembly Bricks Wall Total Gross Area Square Feet 23,585 Square Feet Window Total Gross Area Square Feet 9 ,662 Square Feet Wall Total Gross Area (Brick) Square Feet 13,923 Square Feet Convert Square Feet to Square Meters 13, 923 0.09 1,253 Square Meters Convert Square Meters to Cubic Meters 1,253 0.09 113 Cubic Meter Assume 2,403 Kilogram Per Cub ic Meter Kilograms 271,539 Kilograms Mortar Wall Total Gross Area Square Feet 23,585 Square Feet Window Total Gross Area Square Feet 9,662 Square Feet Wall Total Gross Area (Brick) Square Feet 13,923 Square Feet Assume 6.75 Bricks Square Foot 93,981 Bricks Assume 0.60 Cubic Meters of Mortar Per 1000 Bricks 56.39 Cubic Meters Assume 2,403 Kilogram Per Cubic Meter Kilograms 135,501 Kilograms Caulk Assume Building Perimeter 524 Linear Feet Assume Caulk Joint Every 20 Feet 40 Feet Heigh t 1,048 Linear Feet Assume 15% Waste 1205 Linear Feet Assume 0.032 Pounds Per Linear Foot 38.56 Pounds Convert Pounds to Kilograms 17.5 Kilograms Aluminum Wall Assembly Aluminum Wall Total Gross Area Square Feet 23,585 Square Feet Window Total Gr oss Area Square Feet 9,662 Square Feet Wall Total Gross Area (Aluminum) Square Feet 13,923 Square Feet Assume 20 Gage Thickness 0.0 508 Inches Convert Square Feet to Cubic Feet 58.94 Cubic Feet Assume 169 Pounds Per Cubic Foot 9,902.15 Pounds Conv ert to Kilograms 4,491.5 Kilograms Caulk Assume Building Perimeter 524 Linear Feet

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180 Assume Caulk Joint Every 20 Feet 40 Feet Height 1,048 Linear Feet Assume 15% Waste 1205 Linear Feet Assume 0.032 Pounds Per Linear Foot 38.56 Pounds Convert Pounds to Kilograms 17.5 Kilograms Wood Wall Assembly Wood Wall Total Gross Area Square Feet 23,585 Square Feet Window Total Gross Area Square Feet 9,662 Square Feet Wall Total Gross Area (Wood) Square Feet 13,923 Square Feet 17,136 Square Feet 8,568 Cubic Feet Assume 21 Pounds Per Cubic Foot 179,928 Pounds Convert to Kilograms 81,614 Kilograms Caulk Assume Building Perimeter 524 Linear Feet Assume Caulk Joint Every 20 Feet 40 Feet Heig ht 1,048 Linear Feet Assume 15% Waste 1205 Linear Feet Assume 0.032 Pounds Per Linear Foot 38.56 Pounds Convert Pounds to Kilograms 17.5 Kilograms Paint Two Coats Wall Total Gross Area Square Feet 23,585 Square Feet Window Total Gross Area Squ are Feet 9,662 Square Feet Wall Total Gross Area Square Feet 13,923 Square Feet Assume Coverage of 420 Square Feet Per Gallon 1 st Coat 33.15 Gallons Assume Coverage of 520 Square Feet Per Gallon 2 nd Coat 26.78 Gallons Convert 33.15 Gallons to Cubic Feet 4.43 Cubic Feet Convert 26.78 Gallons to Cubic Feet 3.58 Cubic Feet Assume 62.4 Pounds Per Cubic Foot 4.43 Cubic Feet 276.55 Pounds Assume 62.4 Pounds Per Cubic Foot 3.58 Cubic Feet 223.39 Pounds Convert 276.55 Pounds To Kilograms 125.44 Kilog rams Assume 0.032 Pounds Per Linear Foot 101.33 Kilograms Paint Three Coats Wall Total Gross Area Square Feet 23,585 Square Feet Window Total Gross Area Square Feet 9,662 Square Feet Wall Total Gross Area Square Feet 13,923 Square Feet

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181 Assum e Coverage of 420 Square Feet Per Gallon 1 st Coat 33.15 Gallons Assume Coverage of 520 Square Feet Per Gallon 2 nd Coat 26.78 Gallons Assume Coverage of 520 Square Feet Per Gallon 3 rd Coat 26.78 Gallons Convert 33.15 Gallons to Cubic Feet 4.43 Cubic Feet Convert 26.78 Gallons to Cubic Feet 3.58 Cubic Feet Convert 26.78 Gallons to Cubic Feet 3.58 Cubic Feet Assume 62.4 Pounds Per Cubic Foot 4.43 Cubic Feet 276.55 Pounds Assume 62.4 Pounds Per Cubic Foot 3.58 Cubic Feet 223.39 Pounds Assume 62.4 Po unds Per Cubic Foot 3.58 Cubic Feet 223.39 Pounds Convert 276.55 Pounds To Kilograms 125.44 Kilograms Convert 223.39 Pounds To Kilograms 101.33 Kilograms Convert 223.39 Pounds To Kilograms 101.33 Kilograms Built Up Roof Assembly Roof Total Gross A rea Square Feet 14,760 Square Feet Skylight Total Gross Area Square Feet 768 Square Feet Roof Total Gross Area (Built Up Roof) Square Feet 13,992 Square Feet Convert Square Feet to Square Meters 1,259.28 Square Meters Assume 385 grams Per Square Meter (Type IV BUR Felt)*4 Layers 1,939.29 Kilograms Assume Inter ply Bitumen 20.5 Pounds Per square Foot 3 Coats 907,740 Pounds Convert to Kilograms 411,744 Kilograms Assume Surface Coat at 60.5 Pounds Per Square Foot 892,980 Pounds Convert to Kilog rams 405,049 Kilograms Assume Gravel 400 Pounds Per square Foot 5,904,000 Pounds Convert to Kilograms 2,678,009 Kilograms TPO Assembly Roof Total Gross Area Square Feet 14,760 Square Feet Skylight Total Gross Area Square Feet 768 Square Feet Roo f Total Gross Area (TPO Roof) Square Feet 13,992 Square Feet Convert Square Feet to Square Meters 1,259.28 Square Meters Assume 1.13 Kilograms TPO Membrane Per Square Meter 1,424 Kilograms Assume 7.03 Kilograms Bitumen Per Square Meter 8,856 Kilogram s Green Roof Assembly Roof Total Gross Area Square Feet 14,760 Square Feet Skylight Total Gross Area Square Feet 768 Square Feet Roof Total Gross Area (Built Up Roof) Square Feet 13,992 Square Feet

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182 Convert Square Feet to Square Meters 1,259.28 Square Meters Assume 48.8 Kilograms Per Square Meter Growing Medium 61,414 Kilograms Assume 0.088 Kilograms Per Square Meter Filter Fabric 112 Kilograms Assume 0.54 Kilograms Per Square Meter Root Barrier 680 Kilograms Assume 6.71 Kilograms Per Square Meter Rubberized Roofing Asphalt 8,458.6 Kilograms

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183 APPENDIX B USACE MODEL SERVICE LIFE AND MAINTENANCE INTERVAL IMPACTS

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184 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ Brick Wall 1 3 28 20 14 1 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Membrane, Insulation & Ballast 0.025 SF Insulation, Sealant & Membrane 1 SF Insulation & Membrane 0.02 SF felt adhesive GWP 0.35 0.35 17,009.22 425.23 5,664.94 113.30 Ecotox 0.00 0.00 68.90 1.72 10.76 0.22 Acid 0.11 0.11 3,406.41 85.16 1,803.42 36.07 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ Aluminum Wall 1 3 28 20 14 1 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Membrane, Insulation & Ballast 0.025 SF Insulation, Sealant & Membrane 1 SF Insulation & Membrane 0.02 SF felt adhesive GWP 0. 35 0.35 17,094.98 427.37 5,664.94 113.30 Ecotox 0.00 0.00 68.95 1.72 10.76 0.22 Acid 0.11 0.11 3,425.79 85.64 1,803.42 36.07 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ Wood Wall 1 3 28 20 14 1 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Membrane, Insulation & Ballast 0.025 SF Insulation, Sealant & Membrane 1 SF Insulation & Membrane 0.02 SF felt adhesive GW P 0.35 0.35 17,179.06 429.48 5,664.94 113.30 Ecotox 0.00 0.00 69.00 1.72 10.76 0.22 Acid 0.11 0.11 3,444.79 86.12 1,803.42 36.07 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ No Modification 1 3 28 20 14 1

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185 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Membrane, Insulation & Ballast 0.025 SF Insulation, Sealant & Membrane 1 SF Insulation & Membrane 0.02 SF felt ad hesive GWP 0.35 0.35 17,849.72 446.24 5,664.94 113.30 Ecotox 0.00 0.00 63.92 1.60 10.76 0.22 Acid 0.11 0.11 2,721.11 68.03 1,803.42 36.07 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Rep air Thermoplastic w/ Brick Wall 1 3 20 10 1 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 0.25 ballast adhesive 0.02 SF Adhesive felt & Mastic GWP 0.35 0.35 17,912.7 4 0.00 358.25 Ecotox 0.00 0.00 63.96 0.00 1.28 Acid 0.11 0.11 2,735.35 0.00 54.71 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ Aluminum Wall 1 3 20 10 1 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 0.25 ballast adhesive 0.02 SF Adhesive felt & Mastic GWP 0.35 0.35 17,956.50 0.00 359.13 Ecotox 0.00 0.00 63.99 0.00 1 .28 Acid 0.11 0.11 2,745.24 0.00 54.90 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ Wood Wall 1 3 20 10 1 Resource Required Transportation 0.75 gallons gasol ine Transportation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 0.25 ballast adhesive 0.02 SF Adhesive felt & Mastic GWP 0.35 0.35 18,037.21 0.00 360.74 Ecotox 0.00 0.00 64.04 0.00 1.28

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186 Acid 0.11 0.11 2,763.48 0.00 55.27 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ No Modification 1 3 20 10 1 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 0.25 ballast adhesive 0.02 SF Adhesive felt & Mastic GWP 0.35 0.35 17,849.72 0.00 356.99 Ecotox 0.00 0.00 63.92 0.00 1.28 Acid 0.11 0.11 2,721.11 0.00 54.42 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ Brick Wall 1 3 40 10 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF 0.025 SF GWP 0.35 0.35 20,743.92 518.60 Eco tox 0.00 0.00 64.90 1.62 Acid 0.11 0.11 2,732.18 68.30 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ Aluminum Wall 1 3 40 10 Resource Required Transportat ion 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF 0.025 SF GWP 0.35 0.35 20,785.96 519.65 Ecotox 0.00 0.00 64.92 1.62 Acid 0.11 0.11 2,741.68 68.54 Inspection/ Minor Clean Up Inspections Major Replac ement Minor Replacement Major Repair Minor Repair Green Roof w/ Wood Wall 1 3 40 10

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187 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF 0.025 SF GWP 0.35 0.35 20,850.70 521.27 Ecotox 0.00 0.00 64.96 1.62 Acid 0.11 0.11 2,756.31 68.91 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ No Modification 1 3 40 10 Resource Required Transportation 0.75 ga llons gasoline Transportation 0.75 gallons gasoline 1 SF 0.025 SF GWP 0.35 0.35 20,743.92 518.60 Ecotox 0.00 0.00 64.90 1.62 Acid 0.11 0.11 2,732.18 68.30 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ Green Roof 3 5 500 25 8 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Brick 0.02 SF Brick, 1 SF Waterproofin g 1 SF Pressure wash, waterproofin g material GWP 0.3 5 0.35 78,953.63 1,579.07 4.73 Ecotox 0.00 0.00 69.33 1.39 0.03 Acid 0.11 0.11 13,356.52 267.13 1.05 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ TPO Roof 3 5 500 25 8 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Brick 0.02 SF Brick, 1 SF Waterproofin g 1 SF Pressure wash, waterproofin g material

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188 GWP 0.35 0.35 78,987.12 1,579.74 4.73 Ecotox 0.00 0.00 69.35 1.39 0.03 Acid 0.11 0.11 13,364.45 267.29 1.05 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ BUR Roof 3 5 500 25 8 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Brick 0.02 SF Brick, 1 SF Waterproofin g 1 SF Pressure wash, waterproofin g material GWP 0.35 0.35 79,171.41 1,583.43 4.73 Ecotox 0.00 0.00 69.46 1.39 0.03 Acid 0.11 0.11 13,408.12 268.16 1.05 Inspectio n/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ No Modification 3 5 500 25 8 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Brick 0.02 SF Brick, 1 SF Waterp roofin g 1 SF Pressure wash, waterproofin g material GWP 0.35 0.35 78,953.63 1,579.07 4.73 Ecotox 0.00 0.00 69.33 1.39 0.03 Acid 0.11 0.11 13,356.52 267.13 1.05 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replace ment Major Repair Minor Repair Wood (Single Coat) w/ Green Roof 1 3 125 25 5 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0.02 SF Wood + 0.02 scrape, repair, refinish, paint Scrape, repair, refi nish + 1 SF paint GWP 0.35 0.35 85,818.87 1,716.38 515.41

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189 Ecotox 0.00 0.00 211.18 4.22 1.50 Acid 0.11 0.11 50,549.06 1,010.98 105.80 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Re pair Wood (Single Coat) w/ TPO Roof 1 3 125 25 5 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0.02 SF Wood + 0.02 scrape, repair, refinish, paint Scrape, repair, refinish + 1 SF paint GWP 0.35 0.35 85,885.87 1,717.72 515.41 Ecotox 0.00 0.00 211.22 4.22 1.50 Acid 0.11 0.11 50,564.93 1,011.30 105.80 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Single Coat) w/ BUR Roof 1 3 125 25 5 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0.02 SF Wood + 0.02 scrape, repair, refinish, paint Scrape, repair, refinish + 1 SF paint GWP 0.35 0.35 86,070.18 1,721.40 51 5.41 Ecotox 0.00 0.00 211.33 4.23 1.50 Acid 0.11 0.11 50,608.61 1,012.17 105.80 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Single Coat) w/ No Modification 1 3 125 25 5 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0.02 SF Wood + 0.02 scrape, repair, refinish, paint Scrape, repair, refinish + 1 SF paint GWP 0.35 0.35 85,785.37 1,715.71 515.41 Ecotox 0.00 0.0 0 211.15 4.22 1.50 Acid 0.11 0.11 50,541.12 1,010.82 105.80

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190 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Multi Coat) w/ Green Roof 2 5 125 25 8 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0.02 SF Wood + 0.02 scrape, repair, refinish, paint Scrape, repair, refinish + 1 SF paint GWP 0.35 0.35 86,175.30 1,723.51 773.11 Ecotox 0.00 0.00 212.17 4.24 2.24 Acid 0.11 0.11 50,663.74 1,013.27 158.70 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Multi Coat) w/ TPO Roof 2 5 125 25 8 Transportation 0.75 gallons gasoline Transportati on 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0.02 SF Wood + 0.02 scrape, repair, refinish, paint Scrape, repair, refinish + 1 SF paint GWP 0.35 0.35 86,242.31 1,724.85 773.11 Ecotox 0.00 0.00 212.22 4.24 2.24 Acid 0.11 0.11 50,679.62 1,013.59 158.70 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Multi Coat) w/ BUR Roof 2 5 125 25 8 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 S F Wood + 1 SF Paint 0.02 SF Wood + 0.02 scrape, repair, refinish, paint Scrape, repair, refinish + 1 SF paint GWP 0.35 0.35 86,426.62 1,728.53 773.11 Ecotox 0.00 0.00 212.33 4.25 2.24 Acid 0.11 0.11 50,723.29 1,014.47 158.70 In spection/ Minor Inspections Major Minor Major Repair Minor

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191 Clean Up Replacement Replacement Repair Wood (Multi Coat) w/ No Modification 2 5 125 25 8 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0. 02 SF Wood + 0.02 scrape, repair, refinish, paint Scrape, repair, refinish + 1 SF paint GWP 0.35 0.35 86,141.81 1,722.84 773.11 Ecotox 0.00 0.00 212.15 4.24 2.24 Acid 0.11 0.11 50,655.81 1,013.12 158.70 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ Green Roof 2 3 80 12 5 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Siding 0.02 SF Siding Refinish Paint GWP 0.35 0 .35 108,422.03 2,168.44 427.43 Ecotox 0.00 0.00 1,021.84 20.44 1.39 Acid 0.11 0.11 18,725.52 374.51 97.26 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ TPO Roof 2 3 80 12 5 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Siding 0.02 SF Siding Refinish Paint GWP 0.35 0.35 108,472.15 2,169.44 427.43 Ecotox 0.00 0.00 1,013.31 20.27 1.39 Acid 0.11 0.11 18,031.32 360 .63 97.26 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ BUR Roof 2 3 80 12 5

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192 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 S F Siding 0.02 SF Siding Refinish Paint GWP 0.35 0.35 108,656.44 2,173.13 427.43 Ecotox 0.00 0.00 1,021.99 20.44 1.39 Acid 0.11 0.11 18,781.06 375.62 97.26 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replaceme nt Major Repair Minor Repair Aluminum Siding w/ No Modification 2 3 80 12 5 Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline 1 SF Siding 0.02 SF Siding Refinish Paint GWP 0.35 0.35 108,405.14 2,168.10 427.43 Ecotox 0. 00 0.00 1,021.83 20.44 1.39 Acid 0.11 0.11 18,721.52 374.43 97.26

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193 APPENDIX C ATHENA MODEL SERVICE LIFE AND MAINTENANCE INTERVAL IMPACTS

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194 Built Up Roof w/ Brick Wall 1 20 1 Resource Required 1 square foot membrane, insulation & ballast 1.5% of roof GWP 0.00000 17,009.22112 255.13832 Ecotox 0.00000 68.89527 1.03343 Acid 0.00000 3,406.41472 51.09622 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Majo r Repair Minor Repair Built Up Roof w/ Aluminum Wall 1 20 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Membrane, Insulation & Ballast 1.5% of roof GWP 0.00000 17,094.97845 256.42468 Ecotox 0.00000 68.94739 1.03421 Acid 0.00000 3,425.79302 51.38690 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ Wood Wall 1 20 1 Resource Required Transportation 0.75 gallons gaso line 1 SF Membrane, Insulation & Ballast 1.5% of roof GWP 0.00000 17,179.06298 257.68594 Ecotox 0.00000 68.99849 1.03498 Acid 0.00000 3,444.79333 51.67190 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ No Modification 1 20 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Membrane, Insulation & Ballast 1.5% of roof

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195 GWP 0.00000 16,821.72444 252.32587 Ecotox 0.0 0000 68.78132 1.03172 Acid 0.00000 3,364.04671 50.46070 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ Brick Wall 1 19 1 Resource Required Transpor tation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 1.5% of Roof GWP 0.00000 17,912.74 268.69108 Ecotox 0.00000 63.96 0.95944 Acid 0.00000 2,735.35 41.03032 Inspection/ Minor Clean Up Inspections Ma jor Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ Aluminum Wall 1 19 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 1.5% of Roof GWP 0.00000 17,956.50 269.34743 Ecotox 0.00000 63.99 0.95984 Acid 0.00000 2,745.24 41.17863 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ Wood Wall 1 19 1 Resource Required Tran sportation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 1.5% of Roof GWP 0.00000 18,037.21 270.55818 Ecotox 0.00000 64.04 0.96058 Acid 0.00000 2,763.48 41.45222 Inspection/ Minor Clean Up Inspection s Major Replacement Minor Replacement Major Repair Minor Repair

PAGE 196

19 6 Thermoplastic w/ No Modification 1 19 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 1.5% of Roof GWP 0.00000 17,849.72 267.74 573 Ecotox 0.00000 63.92 0.95887 Acid 0.00000 2,721.11 40.81670 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ Brick Wall 1 30 2 Resource Required Transportation 0.75 gallons gasoline 1 SF 1.5% of Roof GWP 0.00000 20,743.91823 311.15877 Ecotox 0.00000 64.89621 0.97344 Acid 0.00000 2,732.18054 40.98271 Inspection/ Minor Clean Up Inspections Major Replacemen t Minor Replacement Major Repair Minor Repair Green Roof w/ Aluminum Wall 1 30 2 N/A Resource Required Transportation 0.75 gallons gasoline 1 SF 1.5% of Roof N/A GWP 0.00000 20,785.95672 311.78935 Ecotox 0.00000 64.92176 0.97383 Ac id 0.00000 2,741.67984 41.12520 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ Wood Wall 1 30 2 N/A Resource Required Transportation 0.75 gallons gasoline 1 SF 1.5% of Roof N/A GWP 0.00000 20,850.69857 312.76048 Ecotox 0.00000 64.96111 0.97442 Acid 0.00000 2,756.30934 41.34464

PAGE 197

197 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Mino r Repair Green Roof w/ No Modification 1 30 2 N/A Resource Required Transportation 0.75 gallons gasoline 1 SF 1.5% of Roof N/A GWP 0.00000 20,743.91823 311.15877 Ecotox 0.00000 64.89621 0.97344 Acid 0.00000 1,861.74791 27.9262 2 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ Green Roof 3 500 35 12 N/A 1 SF Brick Repoint 25% of wall Recaulk 25% of wall GWP 0.00000 78,953.62842 4,192.20575 0.82005 Ecotox 0.00000 69.32714 10.53279 0.00050 Acid 0.00000 13,356.51772 536.71512 0.19511 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ TPO Roo f 3 500 35 12 N/A 1 SF Brick Repoint 25% of wall Recaulk 25% of wall GWP 0.00000 0.00000 78,987.12357 4,192.20575 0.82005 Ecotox 0.00000 0.00000 69.34746 10.53279 0.00050 Acid 0.00000 0.00000 13,364.45456 536.71512 0.19511 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ BUR Roof 3 500 35 12 N/A 1 SF Brick Repoint 25% of wall Recaulk 25% of wall GWP 0.00000 79,171.40738 4,192.20575 0.8200 5 Ecotox 0.00000 69.45923 10.53279 0.00050

PAGE 198

198 Acid 0.00000 13,408.12151 536.71512 0.19511 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ No Modification 3 500 35 12 N/A 1 SF Brick Repoint 25% of wall Recaulk 25% of wall GWP 0.00000 78,953.62842 4,192.20575 0.82005 Ecotox 0.00000 69.32714 10.53279 0.00050 Acid 0.00000 13,356.51772 536.71512 0.19511 Inspection/ Minor Clean U p Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ Green Roof 1 25 12 5 N/A 1 SF Wood + 1 SF Paint Recaulk 25% of wall Scrape, sand + paint GWP 0.00000 85,818.86551 0.82005 515.40650 Ecotox 0.0 0000 211.17507 0.00050 1.49603 Acid 0.00000 50,549.05671 0.19511 158.70143 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ TPO Roof 1 25 12 5 N/A 1 SF Wood + 1 SF Paint Recaulk 25% of wall Scrape, sand + paint GWP 0.00000 85,885.87491 0.82005 515.40650 Ecotox 0.00000 211.21572 0.00050 1.49603 Acid 0.00000 50,564.93491 0.19511 158.70143 Inspection/ Minor Clean Up In spections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ BUR Roof 1 25 12 5 N/A 1 SF Wood + 1 SF Paint Recaulk 25% of wall Scrape, sand + paint

PAGE 199

199 GWP 0.00000 86,070.17783 0.82005 515.40650 Ecotox 0.00000 211.32750 0.00050 1.49603 Acid 0.00000 50,608.60639 0.19511 158.70143 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ No Modification 1 25 12 5 N/A 1 SF Wood + 1 SF Paint Recaulk 25% of wall Scrape, sand + paint GWP 0.00000 85,785.37036 0.82005 515.40650 Ecotox 0.00000 211.15476 0.00050 1.49603 Acid 0.00000 50,541.11987 0.19511 158.70143 Inspection/ Minor Clean Up I nspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ Green Roof 2 35 35 12 N/A 1 SF Siding Repaint Recaulk wall GWP 0.00000 108,422.02665 427.42942 0.82005 Ecotox 0.00000 1,021.84465 1.38848 0.00050 Acid 0.00000 18,725.51690 97.26076 0.19511 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ TPO Roof 2 35 35 12 N/A 1 SF Siding Repaint Recaulk wall GWP 0.00000 108,472.15414 427.42942 0.82005 Ecotox 0.00000 1,021.87505 1.38848 0.00050 Acid 0.00000 18,737.39485 97.26076 0.19511 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Mino r Repair Aluminum Siding w/ BUR Roof 2 35 35 12 N/A 1 SF Siding Repaint Recaulk wall

PAGE 200

200 GWP 0.00000 108,656.43796 427.42942 0.82005 Ecotox 0.00000 1,021.98683 1.38848 0.00050 Acid 0.00000 18,781.06179 97.26076 0.19511 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ No Modification 2 35 35 12 N/A 1 SF Siding Repaint Recaulk wall GWP 0.00000 108,405.13838 427.42942 0.82005 Ecotox 0.00000 1,021.83441 1.38848 0.00050 Acid 0.00000 18,721.51514 97.26076 0.19511

PAGE 201

201 APPENDIX D VICE LIFE AND MAINTE NANCE INTERVAL IMPAC TS

PAGE 202

202 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replace ment Major Repair Minor Repair Built Up Roof w/ Brick Wall 1 20 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Membrane, Insulation & Ballast 0.3min per ft2 Roof = 1% of roof GWP 0.35 17,009.22112 170.09221 Ecotox 0.0 0 68.89527 0.68895 Acid 0.11 3,406.41472 34.06415 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ Aluminum Wall 1 20 1 Resource Required Transporta tion 0.75 gallons gasoline 1 SF Membrane, Insulation & Ballast 0.3min per ft2 Roof = 1% of roof GWP 0.35 17,094.97845 170.94978 Ecotox 0.00 68.94739 0.68947 Acid 0.11 3,425.79302 34.25793 Inspection/ Minor Clean U p Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ Wood Wall 1 20 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Membrane, Insulation & Ballast 0.3min per ft2 Roof = 1% of roof GWP 0.35 17,179.06298 171.79063 Ecotox 0.00 68.99849 0.68998 Acid 0.11 3,444.79333 34.44793 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ No Modificatio n 1 20 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Membrane, Insulation & Ballast 0.3min per ft2 Roof = 1% of roof

PAGE 203

203 GWP 0.35 16,821.72444 168.21724 Ecotox 0.00 68.78132 0.68781 Acid 0.11 3,364.04671 33.64047 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ Brick Wall 1 20 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Insulation, membrane & seala nt 0.2min per ft2 Roof = 0.5% of roof GWP 0.35 17,912.74 89.56369 Ecotox 0.00 63.96 0.31981 Acid 0.11 2,735.35 13.67677 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ Aluminum Wall 1 20 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 0.2min per ft2 Roof = 0.5% of roof GWP 0.35 17,956.50 89.78248 Ecotox 0.00 63.99 0.31995 Ac id 0.11 2,745.24 13.72621 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ Wood Wall 1 20 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 0.2min per ft2 Roof = 0.5% of roof GWP 0.35 18,037.21 90.18606 Ecotox 0.00 64.04 0.32019 Acid 0.11 2,763.48 13.81741 Inspection/ Minor Clean Up Inspections Major Replacement Minor Rep lacement Major Repair Minor Repair

PAGE 204

204 Thermoplastic w/ No Modification 1 20 1 Resource Required Transportation 0.75 gallons gasoline 1 SF Insulation, membrane & sealant 0.2min per ft2 Roof = 0.5% of roof GWP 0.35 17,849.72 89.24858 Ecot ox 0.00 63.92 0.31962 Acid 0.11 2,721.11 13.60557 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ Brick Wall 1 30 1 Resource Required Transportation 0.75 gallons gasoline 1 SF 0.5 min per ft2 Roof = 1% of roof GWP 0.35 20,743.91823 207.43918 Ecotox 0.00 64.89621 0.64896 Acid 0.11 2,732.18054 27.32181 Inspection/ Minor Clean Up Inspections Major Replacement Min or Replacement Major Repair Minor Repair Green Roof w/ Aluminum Wall 1 30 1 Resource Required Transportation 0.75 gallons gasoline 1 SF 0.5 min per ft2 Roof = 1% of roof GWP 0.35 20,785.95672 207.85957 Ecotox 0.00 64.92176 0.64922 Acid 0.11 2,741.67984 27.41680 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ Wood Wall 1 30 1 Resource Required Transportation 0.75 gallons gasoline 1 SF 0.5 min per ft2 Roof = 1% of roof GWP 0.35 20,850.69857 208.50699

PAGE 205

205 Ecotox 0.00 64.96111 0.64961 Acid 0.11 2,756.30934 27.56309 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ No Modification 1 30 1 Resource Required Transportation 0.75 gallons gasoline 1 SF 0.5 min per ft2 Roof = 1% of roof GWP 0.35 20,743.91823 207.43918 Ecotox 0.00 58.02882 0.58029 Acid 0.11 2, 732.18054 27.32181 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ Green Roof 3 75 15 Resource Required Transportation 0.75 gallons gasoline 1 SF Brick Re point 4 min/ft2 = 14% mortar replacement GWP 0.00000 78,953.62842 2,437.52 Ecotox 0.00000 69.32714 5.90 Acid 0.00000 13,356.51772 300.56 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Majo r Repair Minor Repair Clay Brick w/ TPO Roof 3 75 15 Resource Required Transportation 0.75 gallons gasoline 1 SF Brick Repoint 4 min/ft2 = 14% mortar replacement GWP 0.00000 78,987.12357 2,437.52 Ecotox 0.00000 69.34746 5.90 A cid 0.00000 13,364.45456 300.56 Inspection/ Minor Inspections Major Minor Major Minor

PAGE 206

206 Clean Up Replacement Replacement Repair Repair Clay Brick w/ BUR Roof 3 75 15 Resource Required Transportation 0.75 gallons gasoline 1 SF Brick Repoint 4 min/ft2 = 14% mortar replacement GWP 0.00000 79,171.40738 2,437.52 Ecotox 0.00000 69.45923 5.90 Acid 0.00000 13,408.12151 300.56 Inspection/ Minor Clean Up Inspections Major Replacement Minor Re placement Major Repair Minor Repair Clay Brick w/ No Modification 3 75 15 Resource Required Transportation 0.75 gallons gasoline 1 SF Brick Repoint 4 min/ft2 = 14% mortar replacement GWP 0.00000 78,953.62842 2,437.52 Ecotox 0.00000 69.32714 5.90 Acid 0.00000 13,356.51772 300.56 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ Green Roof 2 40 5 Resource Required Transportati on 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0.5 min/ft2 = 1% of wall GWP 0.00000 85,818.86551 858.1886551 Ecotox 0.00000 211.17507 2.111750717 Acid 0.00000 50,549.05671 505.4905671 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ TPO Roof 2 40 5

PAGE 207

207 Resource Required Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0.5 min/ft2 = 1% of wall GWP 0.00000 85,885.87491 858.8587491 Ecotox 0.00000 211.21572 2.11215716 Acid 0.00000 50,564.93491 505.6493491 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ BUR Roof 2 40 5 Resource Required Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0.5 min/ft2 = 1% of wall GWP 0.00000 86,070.17783 860.7017783 Ecotox 0.00000 211.32750 2.113275041 Acid 0.00000 50,608.60639 506.0860639 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ No Modification 2 40 5 Resource Required Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint 0.5 min/ft2 = 1% of wall GWP 0.00000 85,785.37036 857.8537036 Ecotox 0.00000 211.15476 2.111547554 Acid 0.00000 50,541.11987 505.4111987 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Re pair Minor Repair Aluminum Siding w/ Green Roof 2 50 8 Resource Required Transportation 0.75 gallons gasoline 1 SF Siding 2 min clean/ft2 + 0.2 % of wall GWP 0.00000 108,422.02665 652.78 Ecotox 0.00000 1,021.84465 4.99

PAGE 208

208 Acid 0 .00000 18,725.51690 133.61 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ TPO Roof 2 50 8 Resource Required Transportation 0.75 gallons gasoline 1 SF Siding 2 min clean/ft2 + 0.2 % of wall GWP 0.00000 108,472.15414 652.88 Ecotox 0.00000 1,021.87505 4.99 Acid 0.00000 18,737.39485 133.63 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Ma jor Repair Minor Repair Aluminum Siding w/ BUR Roof 2 50 8 Resource Required Transportation 0.75 gallons gasoline 1 SF Siding 2 min clean/ft2 + 0.2 % of wall GWP 0.00000 108,656.43796 653.25 Ecotox 0.00000 1,021.98683 4.99 Aci d 0.00000 18,781.06179 133.72 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ No Modification 2 50 8 Resource Required Transportation 0.75 gallons ga soline 1 SF Siding 2 min clean/ft2 + 0.2 % of wall GWP 0.00000 108,405.13838 652.75 Ecotox 0.00000 1,021.83441 4.99 Acid 0.00000 18,721.51514 133.60

PAGE 209

209 APPENDIX E RS MEANS MODEL SERVI CE LIFE AND MAINTENA NCE INTERVAL I MPACTS

PAGE 210

210 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ Brick Wall 1 5 28 20 15 1 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline Repla ce Roof Place new membrane over existing: 4 ply bituminous roofing Repair 25 % of roof: 4 plies of bituminous roofing + insulation Repair 2% of roof: 2 plies of glass mopped, GWP 0.71 0.35 17,009.22112 574.80453 4,252.30528 5.74805 Ecotox 0.00 0.00 68.8 9527 0.36132 17.22382 0.00361 Acid 0.22 0.11 3,406.41472 137.33188 851.60368 1.37332 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ Aluminum Wall 1 5 28 20 15 1 Res ource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline Replace Roof Place new membrane over existing: 4 ply bituminous roofing Repair 25 % of roof: 4 plies of bituminous roofing + insulation Repair 2% of roof: 2 plies of glass mopped, GWP 0.71 0.35 17,094.97845 574.80453 4,273.74461 5.74805 Ecotox 0.00 0.00 68.94739 0.36132 17.23685 0.00361 Acid 0.22 0.11 3,425.79302 137.33188 856.44826 1.37332 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ Wood Wall 1 5 28 20 15 1

PAGE 211

211 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline Replace Roof Place new membrane over existing: 4 ply bituminous roofing R epair 25 % of roof: 4 plies of bituminous roofing + insulation Repair 2% of roof: 2 plies of glass mopped, GWP 0.71 0.35 17,179.06298 574.80453 4,294.76575 5.74805 Ecotox 0.00 0.00 68.99849 0.36132 17.24962 0.00361 Acid 0.22 0.11 3,444.79333 137.33188 861.19833 1.37332 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Built Up Roof w/ No Modification 1 5 28 20 15 1 Resource Required Transportation 0.75 gallons gasoline Transportatio n 0.75 gallons gasoline Replace Roof Place new membrane over existing: 4 ply bituminous roofing Repair 25 % of roof: 4 plies of bituminous roofing + insulation Repair 2% of roof: 2 plies of glass mopped, GWP 0.71 0.35 16,821.72444 574.80453 4,205.43111 5.74805 Ecotox 0.00 0.00 68.78132 0.36132 17.19533 0.00361 Acid 0.22 0.11 3,364.04671 137.33188 841.01168 1.37332 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ Bri ck Wall 1 5 25 20 1 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline Replace Roof Replace 25% of roof: install insulation + 150 mils modified bitumen Repair 2% of roof: install 150 mils modified bitumen GW P 0.71 0.35 17,912.74 4,478.18471 358.25478

PAGE 212

212 Ecotox 0.00 0.00 63.96 15.99072 1.27926 Acid 0.22 0.11 2,735.35 683.83862 54.70709 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair T hermoplastic w/ Aluminum Wall 1 5 25 20 1 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline Replace Roof Replace 25% of roof: install insulation + 150 mils modified bitumen Repair 2% of roof: install 150 mil s modified bitumen GWP 0.71 0.35 17,956.50 4,489.12384 359.12991 Ecotox 0.00 0.00 63.99 15.99737 1.27979 Acid 0.22 0.11 2,745.24 686.31050 54.90484 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic w/ Wood Wall 1 5 25 20 1 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline Replace Roof Replace 25% of roof: install insulation + 150 mils modified bitumen Repair 2% of roo f: install 150 mils modified bitumen GWP 0.71 0.35 18,037.21 4,509.30292 360.74423 Ecotox 0.00 0.00 64.04 16.00964 1.28077 Acid 0.22 0.11 2,763.48 690.87030 55.26962 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Thermoplastic 1 5 25 20 1

PAGE 213

213 w/ No Modification Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline Replace Roof Replace 25% of roof: install insulation + 150 mils modified bitumen Repair 2% of roof: install 150 mils modified bitumen GWP 0.71 0.35 17,849.72 4,462.42875 356.99430 Ecotox 0.00 0.00 63.92 15.98115 1.27849 Acid 0.22 0.11 2,721.11 680.27830 54.42226 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ Brick Wall 1 5 35 25 19 5 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline Replace Roof Place new membrane over existing: 4 ply bitum inous roofing Repair 25 % of roof: 4 plies of bituminous roofing + insulation Repair 2% of roof: 2 plies of glass mopped, GWP 0.71 0.35 20,743.91823 9,587.13240 2,396.78310 95.87132 Ecotox 0.00 0.00 64.89621 6.87039 1.71760 0.06870 Acid 0.22 0.11 2,732 .18054 1,171.55087 292.88772 11.71551 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ Aluminum Wall 1 5 35 25 19 5 Resource Required Transportation 0.75 gallons gasolin e Transportation 0.75 gallons gasoline Replace Roof Place new membrane over existing: 4 ply bituminous roofing Repair 25 % of roof: 4 plies of bituminous roofing + insulation Repair 2% of roof: 2 plies of glass mopped,

PAGE 214

214 GWP 0.71 0.35 20,785.95672 9,587.1 3240 2,396.78310 95.87132 Ecotox 0.00 0.00 64.92176 6.87039 1.71760 0.06870 Acid 0.22 0.11 2,741.67984 1,171.55087 292.88772 11.71551 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ Wood Wall 1 5 35 25 19 5 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline Replace Roof Place new membrane over existing: 4 ply bituminous roofing Repair 25 % of roof: 4 plies of bituminous roofing + insulation Repair 2% of roof: 2 plies of glass mopped, GWP 0.71 0.35 20,850.69857 9,587.13240 2,396.78310 95.87132 Ecotox 0.00 0.00 64.96111 6.87039 1.71760 0.06870 Acid 0.22 0.11 2,756.30934 1,171.55087 292.88772 11.71551 Inspecti on/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Green Roof w/ No Modification 1 5 35 25 19 5 Resource Required Transportation 0.75 gallons gasoline Transportation 0.75 gallons gasoline Replace Roof Place new membrane over existing: 4 ply bituminous roofing Repair 25 % of roof: 4 plies of bituminous roofing + insulation Repair 2% of roof: 2 plies of glass mopped, GWP 0.71 0.35 20,743.91823 9,587.13240 2,396.78310 95.87132 Ecotox 0.00 0.00 64.89621 6.87039 1 .71760 0.06870 Acid 0.22 0.11 2,732.18054 1,171.55087 292.88772 11.71551 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair

PAGE 215

215 Clay Brick w/ Green Roof 3 75 25 25 Transportation 0 .75 gallons gasoline 1 SF Brick Repair = 1% of wall Repoint = 80% of wall GWP 78,953.62842 4192.205753 3,353.76460 Ecotox 69.32714 10.53279 8.42623 Acid 13,356.51772 536.71512 429.37209 Inspection/ Minor Clean Up Ins pections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ TPO Roof 3 75 25 25 Transportation 0.75 gallons gasoline 1 SF Brick Repair = 1% of wall Repoint = 80% of wall GWP 78,987.12357 4192.205753 3,353.76460 Ecotox 69.34746 10.53279 8.42623 Acid 13,364.45456 536.71512 429.37209 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ BUR Roof 3 75 25 25 Transpor tation 0.75 gallons gasoline 1 SF Brick Repair = 1% of wall Repoint = 80% of wall GWP 79,171.40738 4192.205753 3,353.76460 Ecotox 69.45923 10.53279 8.42623 Acid 13,408.12151 536.71512 429.37209 Inspection/ Minor Cl ean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Clay Brick w/ No 3 75 25 25

PAGE 216

216 Modification Transportation 0.75 gallons gasoline 1 SF Brick Repair = 1% of wall Repoint = 80% of wall GWP 78,953.62842 4192.20 5753 3,353.76460 Ecotox 69.32714 10.53279 8.42623 Acid 13,356.51772 536.71512 429.37209 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ Green Roof 1 45 5 Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint Scrape, repair, refinish + 1 SF paint GWP 85,818.86551 515.40650 Ecotox 211.17507 1.49603 Acid 50,549.05671 105.80095 Inspection/ Mi nor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ TPO Roof 1 45 5 Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint Scrape, repair, refinish + 1 SF paint GWP 85,885.87 491 515.40650 Ecotox 211.21572 1.49603 Acid 50,564.93491 105.80095 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair

PAGE 217

217 Wood (Two Coats) w/ BUR Roof 1 45 5 Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint Scrape, repair, refinish + 1 SF paint GWP 86,070.17783 515.40650 Ecotox 211.32750 1.49603 Acid 50,608.60639 105.80095 Inspection/ Minor Clean Up I nspections Major Replacement Minor Replacement Major Repair Minor Repair Wood (Two Coats) w/ No Modification 1 45 5 Transportation 0.75 gallons gasoline 1 SF Wood + 1 SF Paint Scrape, repair, refinish + 1 SF paint GWP 85,785.37036 515.40650 Ecotox 211.15476 1.49603 Acid 50,541.11987 105.80095 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ Green Roof 35 20 1 S F Siding Clean + detergent GWP 108,422.02665 520.09942 Ecotox 1,021.84465 1.38849 Acid 18,725.51690 118.34876 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repa ir

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218 Aluminum Siding w/ TPO Roof 35 20 1 SF Siding Clean + detergent GWP 108,472.15414 520.09942 Ecotox 1,021.87505 1.38849 Acid 18,737.39485 118.34876 Inspection/ Minor Clean Up Inspections Maj or Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ BUR Roof 35 20 1 SF Siding Clean + detergent + refinish GWP 108,656.43796 520.09942 Ecotox 1,021.98683 1.38849 Acid 18,781.06179 11 8.34876 Inspection/ Minor Clean Up Inspections Major Replacement Minor Replacement Major Repair Minor Repair Aluminum Siding w/ No Modification 35 20 1 SF Siding Clean + detergent GWP 108,405.13838 520.09942 Ecotox 1,021.83441 1.38849 Acid 18,721.51514 118.34876

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219 LIST OF REFERENCES Aarseth, L.I., Hovde, P.J. ( 1999 ) Stochastic Approach of the Factor Method for Estimating Service Life 8DBMC, pp. 1247 1256. Abraham, D.M., Wi rahadikusumah, R. 1999. Development of Prediction Models for Sewer Deterioration 8DBMC, pp. 1257 1267. Adalberth, k. 1997. Energy Use During the Life Cycle of Buildings: a Method. Building and Environment 32, (4) (7), 317 20 Adalberth K. 1997. Energy U se During the Life Cycle of Single Unit Dwellings : Examples. Building and Environment 32, (4) (7), 321 9. Adam, Barabara, Geibler, Karlheinz, Held, Martin, Kummerer, Klaus and Manuel The Tutzing Time Ecology 84. A ikivuori, A.M. (1999). Critical Loss of Performance what Fails before Durability 8 th International Conference on Durability of Building Materials and Components Vancouver, Canada Allen, T. F. H. ( 2002 ). Appl ying the Principles of Ecological Emergence to Building Design and Construction Ch 4, In: C. Kibert, J. Sendzimir and G. B. Guy, Construction Ecology : Nature as the Basis for Green Buildings Spon Press, London. Allen, F.W., Halloran, P.A., Leith, A.H. and M. Clare Lindsay. (2009). Using Material Flow Analysis for Sustainable Materials Management. Journal of Industrial Ecology. 13(5), 662 665. Ansell, A, Racutanu, G., Sundquist, H. 2002. A Markov Approach in Estimating the Service Life of Bridge Element s in Sweden, 9DBMC, paper 142. Architectural Institute of Japan (1993). The English Edition of Principal Guide for Service Life Planning of Buildings Archite ctural Institute of Japan Athena Sustainable Materials Institute in collaboration with Morri son He rshfield. (2002 ). Maintenance Repair and Replacement Effects for Building Envelope Materials Prepared by Morrison Hershfield for Athena Sustainable Materials Institute, Merrickville, Ontario, Canada January 2002 Athena Sustainable Materials In stitute in collaboration with Morrison Hershfield. (2006). An Athena Sustainable Materials Institute, Merrickville, Ontario, Canada.

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220 stimating the Life Expectancies of Building Components in Life 8. Assaf, Sadi, Abdulmohsen Al Hammad, and Mansoor Al Shihah. ( 1995 ) The Effect of Faulty Construction on Building Maintenance Bui lding Research & Information 23, (3), 175. Ball, Jonathan. ( 2002 ) Can ISO 14000 and Eco labeling Turn the Construction Industry Green Building and Environment 37, (4 ) (4), 421 8. ournal of Management in Engineering. 10 (4), 28 34. Berdahl P., Akbari H., Levinson R. thering of Roofing Materials 433. Bergsdal, H., Bihne, R.A. and Helge Bratteb (2007). Projection of Construction and Demolition Waste in Norway. Journal of Industrial Ecology. 11(3), 27 39. Bergsdal, H., Bratteb H., Bohne, R.A. and Daniel B. Muller. ( Material Flow Analysis for Norway's Dwelling Stock uilding Research & Information. 35(5), 557 570. Biondini, Fabio, Bontempi, Franco and Dan M. Frangopol. ( 2004 ) A Probabilistic Study of the Fatigue Behavior of Improved Tubular Bridge Joints Life Cycle Performance of deteriorating Structures. Edited b y Dan M. Frangopol, Eugene Bruhwiler, Michael H. Faber and Bryan Adey. American Society of Civil Engineers. Reston, VA. Bishop, P.L., Pollution Prevention: Fundamentals and Practice, McGraw Hill, New York, 717 pp., 2000 PP. 394 Bogenstatter, U. ( 2000). Optimization of Life Cycle Costs in Early Design 386. Borg, M., Paulsen, J. and Wolfram Trinius. (2001). Proposal of a Method for Allocation in Building Related Environmental LCA Based on Economic Parameters International Journal of Life Cycle Assessment. 6(4), 219 230. Bourke, Kathryn and Hywell Davies. ( 1997 ) Factors Affecting Service Life Predictions of Buildings: A Discussion Paper Building Research Establishment Laboratory Repor t. Construction Audit Limited. London, England. Boustead, I. ( 1998 ) Plastic and the Environment Radiation Physics and Chemistry 51 (1): 23 30.

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221 Survival Analysis of Urban Building Stocks Building Research & Information. 35(5), 529 542. Bratteb, H., Bergsdal, H., Sandberg, N.H., Hammervold, J. and Daniel B. Mu ller. Built Environment Stock Metabolism and Sustainability by Systems Analysis Approaches 582 Breitenbchner, R., Gehlen, C., Schiessl, P., Van den Hoonard, J., Siemes, T. ( 1999 ) Service Life Design of the Western Scheldt Tunnel 8DBMC, pp. 3 15. Briti sh Standards Institution. (1992). BS 7543:1992 Guide to Durability of Buildings and Building Elements, Products and Components London, UK. Brown, M. T., a nd Vorasun Buranakarn. 2003. Energy Indices and Ratios for Sustainable Material Cycles and Recycle Options Resources, Conservation and Recycling 38, (1) (4): 1 22. Canadian Green Building Council. LEED for New Construction and Major Renovation, Regiona l priority credit 1 Durable Building. http://www.cagbc.org/leed/systems/new_construction/index.php ( May 21, 2010 ). Canadi an Standards Association. (1995). CSA S478 1995 Guide line on Durability in Buildings Ottawa, Canada. Center Ecological Footprint http://www.myfootprint.org/en/about_the_quiz/what_it_measures// ( March 11, 2010) Chen, T. Y., J. Burnett, and C. K. Chau. 2001. Analysis of Embodied Energy Use in the Residential Building of Hong Kong. Energy 26, (4) (4), 323 40. Based Model for the Evalua Environment. 31(5), 487 491. Cole, Raymond J, and Paul C Kernan. ( 1996 ) Life Cycle Energy Use in Office Buildings Building and Environment 31, (4) (7), 307 17. Cole, Raymond J., an d Eva Sterner. ( 2000 ) Reconciling Theory and Practice of Life Cycle Costing Building Research & I nformation 28, (5) (09), 368 75 Construction Audit Limited. ( 1992 ) HAPM Component Life Manual E & FN Spon. London, England

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223 European Commission, Enterprise and Industry Directorate. (2004). Guidance Paper F Durability and the Construction Products Directive http://eurocodes.jrc.ec.europa.eu/doc/gpf.pdf (February 25 20 08. Fagerlund, G. (1999). Service Life with Regard to Frost Attack A Probabilistic Approach proc. 8DBMC, pp. 1268 1279. Fay, Roger, Graham Treloar, and Usha Iyer Raniga. ( 2000 ) Life Cycle Energy Analysis of Buildings: a Case Study Building Research & Information 28, (1) (01), 31 41. Fillie, C., Lane, S., Parham, A., Sullivan, J. and Jay W ahl. (2004 Analysis for Gate to Market E ffects for Building Materials in the Orlando, Fl Region Report prepared for the Athena Sustainable Materials Institute, Merrickville, Ontario, Canada. e Journal of Industrial Economics. 41(4), 361 370. Foliente, Greg and Bob Leicester. Service Life Prediction and Design of Timber Construction http://www.forestprod.org/durtability04fol iente.pdf (February 24, 20 08 ) Frangopol, Eugen Bruhwiler, Michael H. Faber and Bryan Adey. American Society of Civil Engineers. Reston, VA Frohnsdorff, G.J.C. ( 1996 ) Predicting The Service Lives of Materials in Construction 4th Materials Engineer ing Conference: Materials for the new millennium, Washington DC 1776 p., pp. 38 53, ASCE, Nov 10 14 1996. Frohnsdorff, G.J.C., Martin J.W. ( 1996 ) Towards Prediction of Building Service Life : The Standards Imperative 7DMBC, pp. 1417 1428. Furuta, Hit shi, Kameda, Takahiro, Fukuda, Yoshiki and Dan M. Frangopol. ( 2004 ) A Probabilistic Study of the Fatigue Behavior of Improved Tubular Bridge Joints Life Cycle Performance of Deteriorating Structures Edited by Dan M. Frangopol, Eugen Bruhwiler, Michael H. Faber and Bryan Adey. American Society of Civil Engineers. Reston, VA. Graedel, T.E. (2002). Material Substitution: A Resource Supply Perspective Resources, Conservation and Recycling. 34(2), 107 115. Graveline, Stanley P. ( 2005 ) Life Cycle Ass the Manufacture of Building Materials Conference Proceedings for Greenbuild 2005, Atlanta, GA 2005

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224 Harris, D. J. ( 1999 ) A Quantitative Approach to the Assessment of the Environmental Impact of Building Materia ls Building and Environment 34, (6) (11), 751 8. Hawken, Paul. (1993). The Ecology of Commerce. Harper Collins New York, New York. Term Building Stock Survival and Intergenerational Management : the Role of Institutional Regime s Information. 37(5), 552 568. Hjelmstad, K.D., Lange, D.A.., Lawrence, F.V., Parsons, I.D., Quattrone, R.F., Trouvillion, J.C. and D.M. Bailey. 1996. The Building Materials Durability Model (BMDM). United States Army Corps of Eng ineers Construction Engineering Research Laboratories. Hong, H.P. 2000. Assessment of Reliability of Aging Reinforced Concrete Structures Journal of Structural Engineering, December 2000, pp. 1458 1465. Horvath, A. (2004). Construction Materials and the Environment. Annual Review of Environment and Resources. 29, 181 204. Hovde, Per Jostein and Konrad Moser. ( 2004 ) Performance Based Methods for Service Life Prediction State of the Art Reports Part A and Part B. CIB Report: Publication 294. CIB, R otterdam, The Netherlands. International Organization for Standardization. ( 1997 ) Environmental Management Life Cycle Assessment Principles and Framework. ISO 14040. International Organization for Standardization. ( 1997 ) Environmental Management Life Cycle Assessment Goal and Scope Definition and Inventory Analysis ISO 14041. International Organization for Standardization. ( 1997 ) Environmental Management Life Cycle Assessment Life Cycle Impact Assessment ISO 14042. International Organization for Standardization. ( 1997 ) Environmental Management Life Cycle Assessment Life Cycle Impact Assessment ISO 14043. International Organiza tion for Standardization. (2000). ISO 15686 1 Buildings and Constructed Assets Service Life Planning Part 1: General Principles International O rganization for Standardization, Geneve, Switzerland. Environmental Impacts of Renovated Housing Stock with New Construction 252 267. Johnstone, Ivan M. ( 2001 ) Energy and Mass Flows of Housing : A Model and Example Building and Environment 36, (1) (1/1): 27 41.

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231 BIOGRAPHICAL SKETCH Aneurin Grant is currently a Ph.D. student in the School of Building Construction. He is interested in the topics of global sustainability, green construction techniques, urban planning, and legal and policy issues. His current area of specialization includes Life Cycle Assessment and building assessment methods, with particular emphasis on temporal and spatial context.