NIST Technical Note 1814

Building Industry Reporting and 

Design for Sustainability (BIRDS) 

Technical Manual and User Guide

Barbara C. Lippiatt

Joshua Kneifel 

Priya Lavappa

Sangwon Suh

Anne Landfield Greig

 

NIST Technical Note 1814

Building Industry Reporting and 

Design for Sustainability (BIRDS) 

Technical Manual and User Guide

Barbara C. Lippiatt

Joshua Kneifel 

Priya Lavappa

Applied Economics Office 

Engineering Laboratory 

Sangwon Suh

Industrial Ecology Research Services, LLC

Anne Landfield Greig

Four Elements Consulting, LLC

September 2013

U.S. Department of Commerce 

Penny Pritzker, Secretary

National Institute of Standards and Technology 

Patrick D. Gallagher, Under Secretary of Commerce for Standards and Technology and Director 
Certain commercial entities, equipment, or materials may be identified in this

document in order to describe an experimental procedure or concept adequately.

Such identification is not intended to imply recommendation or endorsement by the

National Institute of Standards and Technology, nor is it intended to imply that the

entities, materials, or equipment are necessarily the best available for the purpose.

National Institute of Standards and Technology Special Publication 1814

Natl. Inst. Stand. Technol. Tech. Note 1814, 143 pages (September 2013) 

CODEN: NSPUE2
iv

Abstract

Building stakeholders need practical metrics, data, and tools to support decisions related 

to sustainable building designs, technologies, standards, and codes. The Engineering 

Laboratory of the National Institute of Standards and Technology (NIST) has addressed

this high priority national need by extending its metrics and tool for sustainable building 

products, known as Building for Environmental and Economic Sustainability (BEES), to 

whole buildings. Whole building sustainability metrics have been developed based on 

innovative extensions to life-cycle assessment (LCA) and life-cycle costing (LCC)

approaches involving building energy simulations. The measurement system evaluates 

the sustainability of both the materials and the energy used by a building over time. It

assesses the “carbon footprint” of buildings as well as 11 other environmental 

performance metrics, and integrates economic performance metrics to yield sciencebased measures of the business case for investment choices in high-performance green 

buildings.

Building Industry Reporting and Design for Sustainability (BIRDS) applies the new 

sustainability measurement system to an extensive whole building performance database 

NIST has compiled for this purpose. The BIRDS database includes energy, 

environmental, and cost measurements for 12 540 new commercial and non low-rise 

residential buildings, covering 11 building prototypes in 228 cities across all U.S. states 

for 9 study period lengths. The sustainability performance of buildings designed to meet 

current state energy codes can be compared to their performance when meeting four 

alternative building energy standard editions to determine the impact of energy efficiency 

on sustainability performance. The impact of the building location and the investor’s time 

horizon on sustainability performance can also be measured. 

Keywords

Building economics; economic analysis; life-cycle costing; life-cycle assessment; energy 

efficiency; commercial buildings
v

Preface

This study was conducted by the Applied Economics Office in the Engineering 

Laboratory (EL) at the National Institute of Standards and Technology (NIST). The 

study is designed to assess the energy, environmental, and cost impacts from the adoption 

of new state energy codes based on more stringent building energy standard editions. The 

intended audience is researchers and decision makers in the commercial building sector, 

and others interested in building sustainability.

Disclaimer

The policy of the National Institute of Standards and Technology is to use metric units in 

all of its published materials. Because this report is intended for the U.S. construction 

industry that uses U.S. customary units, it is more practical and less confusing to include 

U.S. customary units as well as metric units. Measurement values in this report are 

therefore stated in metric units first, followed by the corresponding values in U.S. 

customary units within parentheses.
vi

Acknowledgements

The authors wish to thank all those who contributed ideas and suggestions for this report. They 

include Douglas Thomas and Dr. Robert Chapman of EL’s Applied Economics Office, Dr. 

William Healy of EL’s Energy and Environment Division, and Dr. Nicos S. Martys of EL’s 

Materials and Structural Systems Division. A special thanks to the Industrial Ecology Research 

Services team of Shivira Tomar, Christine Chen, and Matthew Leighton for their superb 

technical support in developing whole building life cycle assessments for BIRDS. Also 

deserving thanks is Mr. Nicholas Long and the EnergyPlus Team for generating the initial 

energy simulations for this project. Thanks to Mr. Brian Presser for adapting the energy 

simulations to meet the study requirements and generating the final simulations used in the 

database. Thanks to Mr. Nathaniel Soares for developing the initial version of the BIRDS 

database. Finally, the many Beta testers of BIRDS deserve a special thanks for contributing 

suggestions leading to substantial improvements in the tool.

Author Information

Joshua Kneifel

Economist

National Institute of Standards and Technology

Engineering Laboratory

100 Bureau Drive, Mailstop 8603

Gaithersburg, MD 20899-8603

Tel.: 301-975-6857

Email: joshua.kneifel@nist.gov

Priya Lavappa

Computer Specialist

National Institute of Standards and Technology

Engineering Laboratory

100 Bureau Drive, Mailstop 8603

Gaithersburg, MD 20899-8603

Tel.: 301-975-4522

Email: priya.lavappa@nist.gov
vii

Contents

Abstract.......................................................................................................................................... iv

Preface............................................................................................................................................. v

Acknowledgements........................................................................................................................ vi

Author Information ........................................................................................................................ vi

List of Tables ................................................................................................................................. ix

List of Figures................................................................................................................................ xi

1 Introduction............................................................................................................................. 1

1.1 Purpose.................................................................................................................. 1

1.2 Background ........................................................................................................... 1

2 BIRDS Approach.................................................................................................................... 3

2.1 Rethink Sustainability Measurement .................................................................... 3

2.2 Establish Consistency............................................................................................ 5

3 Energy Performance Measurement......................................................................................... 7

3.1 Building Types...................................................................................................... 7

3.2 Building Designs................................................................................................... 7

3.3 Energy Simulation Design .................................................................................. 12

3.3.1 4-Story Apartment Building................................................................................ 13

3.3.2 6-Story Apartment Building................................................................................ 15

3.3.3 4-Story Dormitory............................................................................................... 17

3.3.4 6-Story Dormitory............................................................................................... 19

3.3.5 15-Story Hotel..................................................................................................... 21

3.3.6 2-Story High School............................................................................................ 23

3.3.7 3-Story Office Building....................................................................................... 26

3.3.8 8-Story Office Building....................................................................................... 29

3.3.9 16-Story Office Building..................................................................................... 32

3.3.10 1-Story Retail Store............................................................................................. 35

3.3.11 1-Story Restaurant............................................................................................... 38

4 Environmental Performance Measurement........................................................................... 41

4.1 Goal and Scope Definition .................................................................................. 41

4.2 Life Cycle Inventory Analysis ............................................................................ 42
viii

4.3 Life Cycle Impact Assessment............................................................................ 46

4.3.1 BIRDS Impact Assessment ................................................................................. 47

4.3.2 BIRDS Normalization......................................................................................... 50

4.4 Life Cycle Interpretation ..................................................................................... 51

4.4.1 EPA Science Advisory Board study.................................................................... 52

4.4.2 BEES Stakeholder Panel judgments ................................................................... 54

4.5 BIRDS Energy Technologies.............................................................................. 57

4.5.1 General Information Regarding the Energy Technology LCIs........................... 58

4.5.2 Wall and Roof Insulation .................................................................................... 59

4.5.3 Windows.............................................................................................................. 74

4.5.4 HVAC Systems................................................................................................... 85

4.5.5 Overhangs.......................................................................................................... 104

4.5.6 Daylighting........................................................................................................ 106

5 Economic Performance Measurement ................................................................................ 111

5.1 First Cost ........................................................................................................... 111

5.1.1 Approach ........................................................................................................... 111

5.1.2 Data ................................................................................................................... 112

5.2 Future Costs....................................................................................................... 115

5.2.1 Approach ........................................................................................................... 115

5.2.2 Data ................................................................................................................... 116

5.3 Residual Value .................................................................................................. 117

5.4 Life-Cycle Cost Analysis.................................................................................. 117

6 BIRDS Tutorial................................................................................................................... 119

6.1 Selecting Building Prototype ............................................................................ 120

6.2 Selecting Comparisons...................................................................................... 121

6.3 Selecting Environmental Weighting Preferences.............................................. 122

6.4 Viewing Results ................................................................................................ 124

7 Limitations and Future Research ........................................................................................ 129

References................................................................................................................................... 133

Appendix. Interpreting BIRDS Environmental Impact Scores: A Primer.................................. 139
ix

List of Tables

Table 3-1 Building Characteristics ................................................................................................. 7

Table 3-2 Energy Code by State and City Exception .................................................................... 8

Table 3-3 ASHRAE 90.1-1999/2001 Climate Zone Definitions.................................................. 10

Table 3-4 Occupancy, Lighting, and Equipment......................................................................... 11

Table 3-5 HVAC Equipment by Building Type .......................................................................... 12

Table 3-6 Air Infiltration and Mechanical Ventilation................................................................. 12

Table 4-1. Construction Industry Outputs Mapped to BIRDS Building Types............................ 46

Table 4-2 BIRDS Life Cycle Impact Assessment Calculations by Building Component............ 50

Table 4-3. BIRDS Normalization References .............................................................................. 51

Table 4-4. Pairwise Comparison Values for Deriving Impact Category Importance Weights .... 53

Table 4-5. Relative Importance Weights based on Science Advisory Board Study..................... 54

Table 4-6. Relative Importance Weights based on BEES Stakeholder Panel Judgments............ 55

Table 4-7 Specified Insulation Types and R-Values – Wall Application.................................... 59

Table 4-8 Specified Insulation Types and R-Values – Roof Application ................................... 60

Table 4-9 Fiberglass Blanket Mass by Application..................................................................... 61

Table 4-10 Fiberglass Insulation Constituents............................................................................. 62

Table 4-11 Energy Requirements for Fiberglass Insulation Manufacturing ............................... 62

Table 4-12 Non Fuel Combustion-Related Emissions for Fiberglass Insulation Manufacturing 62

Table 4-13 EPS Foam Board Raw Materials............................................................................... 64

Table 4-14 EPS Foam Board Manufacturing Energy and Outputs.............................................. 64

Table 4-15 XPS Foam Board Production Data............................................................................ 66

Table 4-16 Raw Material Inputs to Produce Polyiso Foam......................................................... 69

Table 4-17 GRF Process Inputs and Outputs............................................................................... 70

Table 4-18 Energy Inputs and Process Outputs for 1 Board-Foot Polyiso Foam........................ 71

Table 4-19 Perlite Board Bill of Materials .................................................................................. 72

Table 4-20 DensDeck Bill of Materials....................................................................................... 73

Table 4-21 Window Types in BIRDS.......................................................................................... 74

Table 4-22 Characteristics and Components of the Aluminum Operable Window .................... 76

Table 4-23 Insulated Glass Unit Materials .................................................................................. 76

Table 4-24 Characteristics and Components of the Aluminum Fixed Window.......................... 78

Table 4-25 Characteristics and Components of the Aluminum Storefront Window................... 79

Table 4-26 Characteristics and Components of the Aluminum Storefront Window................... 80

Table 4-27 Bill of Materials of the Fiberglass Operable Window............................................... 81

Table 4-28 Bill of Materials of the Wood-PVC Composite Operable Window.......................... 82

Table 4-29 Wood-PVC Composite Window Manufacturing Energy.......................................... 83

Table 4-30 Boilers Included in BIRDS........................................................................................ 86

Table 4-31 Boiler Models............................................................................................................ 87

Table 4-32 Boiler Bill of Materials.............................................................................................. 88

Table 4-33 Boiler Manufacturing Data........................................................................................ 88
x

Table 4-34 Fin Tube Radiation Characteristics in BIRDS .......................................................... 89

Table 4-35 Fin Tube Radiation Summary of Materials............................................................... 92

Table 4-36 Packaged Units Characteristics in BIRDS ................................................................ 93

Table 4-37 Packaged Units Main Components ........................................................................... 94

Table 4-38 Compressor Bill of Materials .................................................................................... 94

Table 4-39 Packaged Unit Models............................................................................................... 96

Table 4-40 Split System Bill of Materials ................................................................................... 97

Table 4-41 Packaged Chillers Characteristics in BIRDS ............................................................ 99

Table 4-42 Air Scroll Packaged Chiller Model ........................................................................... 99

Table 4-43 Centrifugal Chiller Major Assemblies..................................................................... 100

Table 4-44 Centrifugal Chiller Materials................................................................................... 100

Table 4-45 Water-cooled Packaged Chiller Models.................................................................. 101

Table 4-46 Fan Coil Bill of Materials........................................................................................ 102

Table 4-47 Cooling Tower Components and Parts.................................................................... 103

Table 4-48 Cooling Tower Bill of Materials ............................................................................. 104

Table 4-49 Dimmer Controller LCD-203 Parts and Materials.................................................. 108

Table 4-50 Photo Sensor LS-290C Parts and Materials ............................................................ 109

Table 4-51 Power Pack BT-203 Parts and Materials................................................................. 109

Table 4-52 Wall Switch LS-5C Parts and Materials.................................................................. 109

Table 4-53 Ecoinvent Data Sets for Electronics Parts............................................................... 110

Table 5-1 Energy Efficiency Component Requirements for Alternative Building Designs ..... 113

Table 5-2 Energy Efficiency Component Requirements for the ASHRAE 90.1-2007, ASHRAE 

90.1-2010, and LEC Designs...................................................................................................... 114

Table 5-3 HVAC Energy Efficiency Requirements for Alternative Building Designs............. 114

Table 5-4 2009 SPV Discount Factors for Future Non-Fuel Costs, 3 % Real Discount Rate... 115
xi

List of Figures

Figure 2-1 BIRDS Overview .......................................................................................................... 5

Figure 3-1 State Commercial Energy Codes ................................................................................. 9

Figure 3-2 Cities and ASHRAE-2004/2007 Climate Zones.......................................................... 10

Figure 3-3 APART04 Setpoint Temperature Schedules.............................................................. 14

Figure 3-4 APART04 Occupancy Schedule ................................................................................ 14

Figure 3-5 APART04 Lighting Schedule .................................................................................... 15

Figure 3-6 APART04 Electrical Load Schedule ......................................................................... 15

Figure 3-7 APART06 Setpoint Temperature Schedules.............................................................. 16

Figure 3-8 APART06 Occupancy Schedule ................................................................................ 16

Figure 3-9 APART06 Lighting Schedule .................................................................................... 17

Figure 3-10 APART06 Electrical Load Schedule ....................................................................... 17

Figure 3-11 DORMI04 Setpoint Temperature Schedules ........................................................... 18

Figure 3-12 DORMI04 Occupancy Schedule.............................................................................. 18

Figure 3-13 DORMI04 Lighting Schedule .................................................................................. 19

Figure 3-14 DORMI04 Electrical Load Schedule ....................................................................... 19

Figure 3-15 DORMI06 Setpoint Temperature Schedules ........................................................... 20

Figure 3-16 DORMI06 Occupancy Schedule.............................................................................. 20

Figure 3-17 DORMI06 Lighting Schedule .................................................................................. 21

Figure 3-18 DORMI06 Electrical Load Schedule ....................................................................... 21

Figure 3-19 HOTEL15 Setpoint Temperature Schedules............................................................ 22

Figure 3-20 HOTEL15 Occupancy Schedule .............................................................................. 22

Figure 3-21 HOTEL15 Lighting Schedule .................................................................................. 23

Figure 3-22 HOTEL15 Electrical Load Schedule ....................................................................... 23

Figure 3-23 HIGHS02 Heating Setpoint Temperature Schedule ................................................. 24

Figure 3-24 HIGHS02 Cooling Setpoint Temperature Schedule ................................................ 24

Figure 3-25 HIGHS02 Occupancy Schedule............................................................................... 25

Figure 3-26 HIGHS02 Lighting Schedule ................................................................................... 25

Figure 3-27 HIGHS02 Electrical Load Schedule ........................................................................ 26

Figure 3-28 OFFIC03 Heating Setpoint Temperature Schedule ................................................. 27

Figure 3-29 OFFIC03 Cooling Setpoint Temperature Schedule ................................................. 27

Figure 3-30 OFFIC03 Occupancy Schedule................................................................................ 28

Figure 3-31 OFFIC03 Lighting Schedule .................................................................................... 28

Figure 3-32 OFFIC03 Electrical Load Schedule ......................................................................... 29

Figure 3-33 OFFIC08 Heating Setpoint Temperature Schedule ................................................. 30

Figure 3-34 OFFIC08 Cooling Setpoint Temperature Schedule ................................................. 30

Figure 3-35 OFFIC08 Occupancy Schedule................................................................................ 31

Figure 3-36 OFFIC08 Lighting Schedule .................................................................................... 31

Figure 3-37 OFFIC08 Electrical Load Schedule ......................................................................... 32

Figure 3-38 OFFIC16 Heating Setpoint Temperature Schedule ................................................. 33
xii

Figure 3-39 OFFIC16 Cooling Setpoint Temperature Schedule ................................................. 33

Figure 3-40 OFFIC16 Occupancy Schedule................................................................................ 34

Figure 3-41 OFFIC16 Lighting Schedule .................................................................................... 34

Figure 3-42 OFFIC16 Electrical Load Schedule ......................................................................... 35

Figure 3-43 RETAIL1 Heating Setpoint Temperature Schedule ................................................ 36

Figure 3-44 RETAIL1 Cooling Setpoint Temperature Schedule ................................................ 36

Figure 3-45 RETAIL1 Occupancy Schedule............................................................................... 37

Figure 3-46 RETAIL1 Lighting Schedule ................................................................................... 37

Figure 3-47 RETAIL1 Electrical Load Schedule ........................................................................ 37

Figure 3-48 RSTRNT1 Heating Setpoint Temperature Schedule ............................................... 38

Figure 3-49 RSTRNT1 Cooling Setpoint Temperature Schedule ............................................... 39

Figure 3-50 RSTRNT1 Occupancy Schedule.............................................................................. 39

Figure 3-51 RSTRNT1 Lighting Schedule .................................................................................. 40

Figure 3-52 RSTRNT1 Electrical Load Schedule ....................................................................... 40

Figure 4-1. Compiling LCA Inventories of Environmental Inputs and Outputs.......................... 43

Figure 4-2. Illustration of Supply Chain Contributions to U.S. Construction Industry................ 45

Figure 4-3. BEES Stakeholder Panel Importance Weights Synthesized across Voting Interest and 

Time Horizon................................................................................................................................ 56

Figure 4-4. BEES Stakeholder Panel Importance Weights by Stakeholder Voting Interest ........ 56

Figure 4-5. BEES Stakeholder Panel Importance Weights by Time Horizon.............................. 57

Figure 4-6 Insulation System Boundaries – Fiberglass Blanket Example................................... 61

Figure 4-7 Windows System Boundaries .................................................................................... 75

Figure 4-8 HVAC System Boundaries – Boiler Example ........................................................... 86

Figure 4-9 Fin Tube Radiator (Internal and External Components)............................................ 90

Figure 4-10 Overhang System Boundaries................................................................................ 105

Figure 4-11 Outrigger System ................................................................................................... 106

Figure 4-12 Components of the Dimming System .................................................................... 107

Figure 4-13 Daylighting System Boundaries............................................................................. 108

Figure 6-1 BIRDS Overview ..................................................................................................... 119

Figure 6-2 Selecting Building Prototype ................................................................................... 120

Figure 6-3 Building Prototype Details....................................................................................... 120

Figure 6-4 Selecting Comparisons............................................................................................. 121

Figure 6-5 Selecting Alternative Locations, Energy Standard Editions, and Study Periods..... 122

Figure 6-6 Selecting Environmental Weighting Preferences..................................................... 123

Figure 6-7 Defining a Custom Weightset.................................................................................. 124

Figure 6-8 Selecting Chart Options ........................................................................................... 125

Figure 6-9 Life-Cycle Cost Graph ............................................................................................. 126

Figure 6-10 Operating Energy Consumption Graph.................................................................. 127

Figure 6-11 Environmental Impact – Global Warming Potential Graph................................... 128
1

1 Introduction

1.1 Purpose

Building stakeholders need practical metrics, data, and tools to support decisions related to 

sustainable building designs, technologies, standards, and codes. The Engineering Laboratory of 

the National Institute of Standards and Technology (NIST) has addressed this high priority 

national need by extending its metrics and tool for sustainable building products, known as 

Building for Environmental and Economic Sustainability (BEES), to whole buildings. Whole 

building sustainability metrics have been developed based on innovative extensions to life-cycle 

assessment (LCA) and life-cycle costing (LCC) approaches involving building energy 

simulations. The measurement system evaluates the sustainability of both the materials and the 

energy used by a building over time. It assesses the “carbon footprint” of buildings as well as 11 

other environmental performance metrics, and integrates economic performance metrics to yield 

science-based measures of the business case for investment choices in high-performance green 

buildings.

Building Industry Reporting and Design for Sustainability (BIRDS) applies the new 

sustainability measurement system to an extensive whole building performance database NIST 

has compiled for this purpose. The BIRDS database includes energy, environmental, and cost 

measurements for 12 540 new commercial and non low-rise residential buildings, covering 11 

building prototypes in 228 cities across all U.S. states for 9 study period lengths. The 

sustainability performance of buildings designed to meet current state energy codes can be

compared to their performance when meeting four alternative building energy standard editions 

to determine the impact of energy efficiency on sustainability performance. The impact of the 

building location and the investor’s time horizon on sustainability performance can also be 

measured. 

The new idea is to address building sustainability measurement in a holistic, integrated manner 

that considers complex interactions among building materials, energy technologies, and systems 

across dimensions of performance, scale, and time. The energy, environment, and cost data in 

BIRDS measure building operating energy use through detailed energy simulations, building 

materials use through innovative life-cycle material inventories, and building costs over time. 

1.2 Background

A wave of interest in sustainability gathered momentum in 1992 with the Rio Earth Summit, 

during which the international community agreed upon a definition of sustainability in the 

Bruntland report: “meeting the needs of the present generation without compromising the ability 

of future generations to meet their own needs.” (Brundtland, 1987) In the context of sustainable 

development, needs can be thought to include the often-conflicting goals of environmental 

quality, economic well-being, and social justice. While the intent of the 1992 summit was to 
2

initiate environmental and social progress, it seemed to have instead brought about greater debate 

over the inherent conflict between sustainability and economic development.

This conflict is particularly apparent within the construction industry. Frequently, wellintentioned green development plans are not executed for economic reasons, and economic 

development plans fail to materialize over concerns for the environment and public health. Thus, 

an integrated approach to sustainable construction—one that simultaneously considers both 

environmental and economic performance—lies at the heart of reconciling the conflict. For this 

reason, the BIRDS approach considers both the environmental and economic dimensions of 

sustainability. BIRDS does not consider the social dimension of sustainability due to its current 

lack of rigorous measurement methods.
3

2 BIRDS Approach

2.1 Rethink Sustainability Measurement

One standardized and preferred approach for scientifically measuring the environmental 

performance of industrial products and systems is life cycle assessment (LCA). LCA is a 

“cradle-to-grave,” systems approach for measuring environmental performance. The approach is 

based on two principles. First, the belief that all stages in the life of a product generate 

environmental impacts and must be analyzed, including raw materials acquisition, product 

manufacture, transportation, installation, operation and maintenance, and ultimately recycling 

and waste management. An analysis that excludes any of these stages is limited because it 

ignores the full range of upstream and downstream impacts of stage-specific processes. LCA 

broadens the environmental discussion by accounting for shifts of environmental problems from 

one life-cycle stage to another. The second principle is that multiple environmental impacts must 

be considered over these life-cycle stages in order to implement a trade-off analysis that achieves

a genuine reduction in overall environmental impact, rather than a simple shift of impact. By 

considering a range of environmental impacts, LCA accounts for problem-shifting from one 

environmental medium (land, air, water) to another. 

The LCA method is typically applied to products, or simple product assemblies, in a “bottom up” 

manner. The environmental inputs and outputs to all the production processes throughout a 

product’s life cycle are compiled. These product life cycle “inventories” quantify hundreds, even 

thousands, of environmental inputs and outputs. This is a data-intensive, time-consuming, and 

expensive process that must be repeated for every product.

The bottom-up approach becomes unwieldy and cost prohibitive for complex systems, such as

buildings, that involve potentially hundreds of products. Furthermore, a building’s sustainability 

is not limited to the collective sustainability of its products. The manner in which designers 

integrate these products and systems at the whole building level has a large influence on another 

major dimension of its sustainability performance, operating energy use.

The many dimensions of whole building environmental performance are ultimately balanced 

against its economic performance. While a 2006 poll by the American Institute of Architects 

showed that 90 % of U.S. consumers would be willing to pay more to reduce their home’s 

environmental impact, they would pay only $4 000 to $5 000, or about 2 %, more.1 Even the 

most environmentally conscious policymaker or building designer will ultimately weigh 

environmental benefits against economic costs. To satisfy their stakeholders, the green building 

community needs to promote and design buildings with an attractive balance of environmental 

and economic performance.

 

1

January 2006 survey cited in Washington Post, 8/6/06, p M3 (Green Buildings article by Sacha Cohen).
4

These considerations require a different way of thinking about sustainability performance for 

buildings. In the BIRDS model, a unifying LCA framework developed for the U.S. economy is

applied to the U.S. construction sector and its constituent building types. Through this “topdown” LCA approach, a series of baseline sustainability measurements are made for prototypical 

buildings, yielding a common yardstick for measuring sustainability with roots in wellestablished national environmental and economic statistics. Using detailed “bottom-up” data 

compiled through traditional LCA approaches, the baseline measurements for prototypical 

buildings are then “hybridized” to reflect a range of improvements in building energy efficiency, 

enabling assessment of their energy, environmental, and economic benefits and costs. The idea is 

to provide a cohesive database and measurement system based on sound science that can be used 

to prioritize green building issues and to track progress over time as design and policy solutions 

are implemented.

The BIRDS hybrid LCA approach combines the advantages of both bottom-up and top-down 

approaches—namely the use of higher-resolution, bottom-up data and the use of regularlyupdated, top-down statistical data without truncation (Suh et al., 2004; Suh and Huppes, 2005).

The hybrid approach generally reduces the uncertainty of existing pure bottom up or pure top 

down systems: it helps reduce truncation error in the former and increases the resolution of the 

latter (Suh et al., 2004). 

Operating energy use—a key input to whole building LCAs—is assessed in BIRDS using the 

bottom-up approach. Energy use is highly dependent upon a building’s function, size, location, 

and the efficiency of its energy technologies. Energy efficiency requirements in current energy 

codes for commercial buildings vary across states, and many states have not yet adopted the 

newest energy standard editions. As of December 2011, state energy code adoptions range across 

all editions of the American Society of Heating, Refrigerating and Air-Conditioning Engineers 

Energy Standard for Buildings except Low-Rise Residential Buildings (ASHRAE90.1-1999, -2001, -2004, and -2007). Some states do not have a code requirement for energy 

efficiency, leaving it up to the locality or jurisdiction to set its own requirement. To address these 

issues, operating energy use in BIRDS is tailored to commercial and non low-rise residential

building types, locations, and energy codes. The BIRDS database includes operating energy use 

predicted though energy simulation of 5 alternative building designs for 11 building types in 228 

U.S. locations, with each design complying with some version of the energy code (90.1) or a 

higher-performing “Low Energy Case” building design based on ASHRAE 189.1-2009 (Standard 

for the Design of High-Performance Green Buildings Except Low-Rise Residential Buildings).

Like operating energy use, a building’s economic performance is dependent upon a building’s 

function, location, and the efficiency of its energy technologies. Construction material and labor 

costs vary by building type and location, as do maintenance, repair, and replacement costs over 

time. Energy technologies for compliance with a given ASHRAE energy code edition vary 

across U.S. climate zones, as do their costs. Finally, a building’s operating energy costs vary 

according to the quantity and price of energy use, which depend upon the building’s location and 
5

fluctuate over time. All these variables are accounted for in the BIRDS database, as shown in

Figure 2-1.

Environmental Energy Simulation

Life Cycle Assessment

Economic

Life Cycle Costing

Local Prices

•Construction

•Current Fuel Prices

•Fuel Price Projections

Function

Design

Size

Location

Energy Technologies

•HVAC

•Envelope

•Efficiency

Maintenance, Repair &

Replacement Schedules

Building Service Life

Energy Code

Climate

Building Type

•Commercial

•Non Low-Rise Residential

Sustainability

Performance

Economic

Performance

Environmental

Performance Energy

Performance

Materials Acquisition

Manufacturing

Transportation

Installation/Use

Service Life

End of Life

BIRDS Database

Fuel Type

•Heating

•Cooling

Building Specifications

Global Warming

Resource Use

Human Health

Water Pollution

Air Pollution

Figure 2-1 BIRDS Overview

2.2 Establish Consistency

This new way of measuring building sustainability performance requires that special attention be 

paid to establishing consistency among its many dimensions. While BIRDS develops separate 

performance metrics for building energy, environmental, and economic performance, they are all

developed using the same parameters and assumptions. For each of the 12 540 buildings 

included in the BIRDS database, consistent design specifications are used to estimate its 

operating energy use, environmental life-cycle impacts, and life-cycle costs. The building energy 

simulation, for example, specifies the same building envelope and HVAC technologies as do the 

bottom-up energy technology LCAs and the cost estimates. 

One of the most important dimensions requiring BIRDS modeling consistency is the study 

period. The study period is the number of years of building operation over which energy, 

environmental, and economic performance are assessed. In economic terms, the study period 
6

represents the investor’s time horizon. Over what period of time are the environmental and 

economic costs and benefits related to the capital investment decision of interest to the investor

or policymaker? Since different stakeholders have different time perspectives, there is no one 

correct study period for developing a business case for sustainability. For this reason, 9 different 

study period lengths are offered in BIRDS, ranging from 1 year to 40 years.

Nine study period lengths are chosen to represent the wide cross section of potential investment 

time horizons. A 1-year study period is representative of a developer that intends to sell a 

property soon after it is constructed. A 5-year to 15-year study period best represents a building 

owner’s time horizon because few owners are concerned about costs realized beyond a decade

into the future. The 20-year to 40-year study periods better represents institutions, such as 

colleges or government agencies, because these entities will own or lease buildings for 20 or 

more years. BIRDS sets the maximum study period at 40 years for consistency with 

requirements for federal building life-cycle cost analysis (Energy Independence and Security Act 

of 2007). Beyond 40 years, technological obsolescence becomes an issue, data become too 

uncertain, and the farther in the future, the less important the costs.

Once the BIRDS user sets the length of the study period, the energy, environmental, and 

economic data are all normalized to that period of time. This involves adjustments to a building’s

operating, maintenance, repair, and replacement data as well as to its remaining value at the end 

of the study period. This assures consistency and comparability among the three metrics, and is 

one of the strengths of the BIRDS approach. 

The next 3 chapters go into more detail regarding the modeling of energy, environmental, and 

economic performance in BIRDS.
7

3 Energy Performance Measurement

The operating energy component of the BIRDS database was built following the framework 

developed in Kneifel (2010) and further expanded in Kneifel (2011a) and Kneifel (2011b). It 

includes the results of 12 540 whole building energy simulations covering 5 energy efficiency

designs for 11 new commercial building types, 228 cities across the United States, and 9 study 

period lengths.

3.1 Building Types

The building characteristics in Table 3-1 describe the 11 building types included in BIRDS, 

which include 2 dormitories, 2 apartment buildings, a hotel, 3 office buildings, a school, a retail 

store, and a restaurant. These building types represent 46 % of the existing U.S. commercial 

building stock floor space.2 The prototype buildings range in size from 465 m2(5000 ft2) to 

41 806 m2(450 000 ft2). The building abbreviations defined in Table 3-1 are used to represent 

the building types in tables throughout this report.

Table 3-1 Building Characteristics

Building Type Bldg. Abbr. Floors

Floor 

Height

m (ft)

Wall Roof† Pct. 

Glazing

Building Size

m

2

(ft2)

Occupancy 

Type

U.S. Floor 

Space (%)

Dormitory DORMI04 4 3.66 (12) Mass IEAD 20 % 3097 (33 333) Lodging 7.1 %

Dormitory DORMI06 6 3.66 (12) Steel IEAD 20 % 7897 (85 000)

Hotel HOTEL15 15 3.05 (10) Steel IEAD 100 % 41 806 (450 000)

Apartment APART04 4 3.05 (10) Mass IEAD 12 % 2787 (30 000)

Apartment APART06 6 3.15 (10) Steel IEAD 14 % 5574 (60 000)

School, High HIGHS02 2 4.57 (15) Mass IEAD 25 % 12 077 (130 000) Education 13.8 %

Office OFFIC03 3 3.66 (12) Mass IEAD 20 % 1858 (20 000) Office 17.0 %

Office OFFIC08 8 3.66 (12) Mass IEAD 20 % 7432 (80 000)

Office OFFIC16 16 3.05 (10) Steel IEAD 100 % 24 155 (260 000)

Retail Store RETAIL1 1 4.27 (14) Mass IEAD 10 % 743 (8000) Mercantile* 6.0 %

Restaurant RSTRNT1 1 3.66 (12) Wood IEAD 30 % 465 (5000) Food Service 2.3 %

*Only includes non-mall floor area.

†IEAD = Insulation Entirely Above Deck

3.2 Building Designs

Current state energy codes are based on different editions of the International Energy 

Conservation Code (IECC) or ASHRAE 90.1 Standard, which have requirements that vary based 

on a building’s characteristics and the climate zone of the location. For the BIRDS database, the 

ASHRAE 90.1 Standard-equivalent design is used to meet current state energy codes and to 

define the alternative building designs. Additionally, a “Low Energy Case” building design 

based on ASHRAE 189.1-2009, and which goes beyond ASHRAE 90.1-2007 requirements, is 

 

2 Based on the Commercial Building Energy Consumption Survey (CBECS) database
8

included as a building design alternative. For simplicity, this design may be referred to as an 

“edition” of the energy standard throughout the remainder of this report.

Table 3-2 shows that commercial building energy codes as of December 2011 vary by state. In a 

few instances, local jurisdictions have adopted energy standard editions that are more stringent 

than the state energy codes.3 These cities are also included in Table 3-2.

Table 3-2 Energy Code by State and City Exception

Location Energy Code Location Energy Code Location Energy Code

AK None IN 2007 NV 2004

AL None KS None NY 2007

Huntsville 2001 KY 2007 OH 2007

AR 2001 LA 2007 OK None

AZ None MA 2007 OR 2007

Flagstaff 2004 MD 2007 PA 2007

Phoenix 2004 ME None RI 2007

Tucson 2004 MI 2007 SC 2004

CA 2007 MN 2004 SD None

CO 2001 MO None Huron 2001

Grand Junction 2004 St Louis 2001 TN 2004

CT 2007 MS None TX 2007

DE 2007 MT 2007 UT 2007

FL 2007 NC 2007 VA 2007

GA 2007 ND None VT 2007

HI 2004 NE 2007 WA 2007

IA 2007 NH 2007 WI 2007

ID 2007 NJ 2007 WV 2001

IL 2007 NM 2007 WY None

Note: Some city ordinances require energy codes that exceed state energy codes.

Note: State codes as of December 1, 2011.

State energy codes vary from ASHRAE 90.1-1999 to ASHRAE 90.1-2007 with some regional 

trends shown in Figure 3-1. The states in the central U.S. tend to wait longer to adopt newer 

ASHRAE 90.1 Standard editions. However, there are many cases in which energy codes of 

neighboring states vary drastically. For example, Missouri has no state energy code while of the 

8 surrounding states, 2 have no state energy code, 1 has adopted ASHRAE 90.1-2001, 1 has 

adopted ASHRAE 90.1-2004, and 4 have adopted ASHRAE 90.1-2007.

 

3 Local and jurisdictional requirements are obtained from the Database of State Incentives for Renewables and 

Efficiency (DSIRE). State energy code requirements targeting only public buildings and green standards are 

ignored.
9

Figure 3-1 State Commercial Energy Codes4

The prototype buildings are designed to meet the requirements for each of the editions of 

ASHRAE 90.1 (-1999, -2001, -2004, and -2007) and an additional building design option defined 

as the “Low Energy Case” (LEC). The LEC design is based on ASHRAE 189.1-2009 (Standard 

for the Design of High-Performance Green Buildings Except Low-Rise Residential Buildings)

and goes beyond ASHRAE 90.1-2007 in a number of ways. The LEC design increases the 

thermal efficiency of insulation and windows beyond ASHRAE 90.1-2007, reduces the lighting 

power density, and adds daylighting and window overhangs. The LEC design assumes the same 

HVAC equipment efficiency as required by ASHRAE 90.1-2007. For BIRDS, ASHRAE 

90.1-1999 is assumed to be “common practice,” and is used for the building design requirements 

in states with no statewide energy code.

The 228 cities and current ASHRAE climate zones for the United States are mapped in Figure 

3-2. These cities are selected for three reasons. First, the cities are spread out to represent the 

entire United States, and represent as many climate zones in each state as possible. Second, the 

locations cover all the major population centers in the country. Third, multiple locations for a 

climate zone within a state are included to allow building costs to vary for each building design.

 

4

Figure was obtained from the DOE Building Technologies Program in December 2011.
10

Figure 3-2 Cities and ASHRAE-2004/2007 Climate Zones

The ASHRAE-defined climate zones were consolidated from the 26 climate zones shown in 

Table 3-3 for ASHRAE 90.1-1999 and 90.1-2001 into 8 climate zones in ASHRAE 90.1-2004 and 

90.1-2007. The consolidation is more complex than simply grouping the 90.1-2001 climate 

zones together. The zones in Table 3-3 are based on a city’s cooling degree days at a base of 

10 °C (50 °F) (CDD50) and heating degree days at a base of 18 °C (65 °F) (HDD65) while the 

zones in Figure 3-2 are based on a county’s cooling and heating degree days. The generalization 

results in some cities, located in the same climate zone in ASHRAE 90.1-2001, being located in a 

different climate zone in ASHRAE 90.1-2004. The new climate zones are further separated into 

subzones, “wet,” “dry,” and “marine,” as shown in Figure 3-2, for a total of 16 subzones.

Table 3-3 ASHRAE 90.1-1999/2001 Climate Zone Definitions

CDD50 Climate Zone

10801+ 1

9001-10800 2

7201-9000 3 5

5401-7200 4 6 8 10

3601-5400 7 9 11 13 16

1801-3600 12 14 17 19 21

0-1800 15 18 20 22 23 24 25 26

HDD65 0-

900

901-

1800

1801-

2700

2701-

3600

3601-

5400

5401-

7200

7201-

9000

9001-

10800

10801-

12600

12601-

16200

16201-

19800 19801+

CDD50 = Annual Cooling Degree Days base 10 °C (50 °F)

HDD65 = Annual Heating Degree Days base 18 °C (65 °F)

Occupancy types for the prototype buildings are based on the 1999 Commercial Building Energy 

Consumption Survey (CBECS) “principal building activity” categories. The principal building 

activity determines the maximum people density, electrical plug density, and lighting power 
11

density, and the correlating density schedules. Table 3-4 summarizes each building type’s 

maximum densities. The maximum number of occupants varies between 1 person per 7.0 m

2

(75

ft2) to 1 person per 27.9 m2(300 ft2). The maximum interior lighting density and daily schedule 

vary based on the occupancy type and the edition of ASHRAE 90.1 or Low Energy Case (LEC)

building design. All building types are assumed to have zero external lighting loads. The 

maximum electrical equipment load varies between 1.08 W/m2(0.10 W/ft2) to 8.07 W/m2(0.75 

W/ft2).

Table 3-4 Occupancy, Lighting, and Equipment

Bldg. Abbr. ASHRAE 90.1 

Occupancy Type

Max. 

Occ.

m

2

(ft2) Per 

Occupant

Lighting

W/m2(W/ft2)

Equipment 

W/m2(W/ft2)

DORMI04 Dormitory 99 23.2 (250) 8.6 to 16.1 (0.8 to 1.5) 2.69 (0.25)

DORMI06 Dormitory 342 23.2 (250) 8.6 to 16.1 (0.8 to 1.5) 2.69 (0.25)

HOTEL15 Hotel 1800 23.2 (250) 8.6 to 18.3 (0.8 to 1.7) 2.69 (0.25)

APART04 Dormitory 90 23.2 (250) 8.6 to 18.3 (0.8 to 1.7) 2.69 (0.25)

APART06 Dormitory 240 23.2 (250) 8.6 to 18.3 (0.8 to 1.7) 2.69 (0.25)

ELEMS01 School 602 7.0 (75) 10.8 to 16.1 (1.0 to 1.5) 5.38 (0.50)

HIGHS02 School 1740 7.0 (75) 10.8 to 16.1 (1.0 to 1.5) 5.38 (0.50)

OFFIC03 Office 72 25.5 (275) 8.6 to 14.0 (0.8 to 1.3) 8.07 (0.75)

OFFIC08 Office 288 25.5 (275) 8.6 to 14.0 (0.8 to 1.3) 8.07 (0.75)

OFFIC16 Office 944 25.5 (275) 8.6 to 14.0 (0.8 to 1.3) 8.07 (0.75)

RETAIL1 Retail 27 27.9 (300) 16.1 to 20.5 (1.5 to 1.9) 2.69 (0.25)

RSTRNT1 Dining: Fast Food 50 9.3 (100) 14.0 to 19.4 (1.3 to 1.8) 1.08 (0.10)

The square footage, number of floors, floor height, wall type, roof type, percent glazing, and 

heating, ventilation, and air conditioning (HVAC) system for each building type are based on the 

RS Means Square Foot Cost Estimator (SFCE) default prototype specifications. The cooling 

system is assumed to run on electricity while the heating system is assumed to run on natural gas. 

Table 3-5 identifies the heating and cooling equipment for each building type.
12

Table 3-5 HVAC Equipment by Building Type

Building 

Type Cooling Equipment Heating Equipment

DORMI04 Rooftop Packaged Unit Furnace

DORMI06 Air-Cooled Chiller Hot Water Boiler

HOTEL15 Water-Cooled Chiller Hot Water Boiler

APART04 Air-Cooled Chiller Hot Water Boiler

APART06 Air-Cooled Chiller Hot Water Boiler

HIGHS02 Water-Cooled Chiller Hot Water Boiler

OFFIC03 Rooftop Packaged Unit Furnace

OFFIC08 Rooftop Packaged Unit Furnace

OFFIC16 Water-Cooled Chiller Hot Water Boiler

RETAIL1 Rooftop Packaged Unit Furnace

RSTRNT1 Rooftop Packaged Unit Furnace

Table 3-6 shows how air infiltration and mechanical ventilation rates vary by building type. 

Infiltration rates range between 0.3 air changes per hour (ACH) to 0.6 ACH. Minimum 

mechanical ventilation rates range between 0.4 ACH to 1.3 ACH. Total minimum ACH varies 

between 0.7 ACH to 1.9 ACH.

Table 3-6 Air Infiltration and Mechanical Ventilation

Bldg. Abbr. Building Size

m

2

(ft2)

Floor Height

m (ft)

CBECS 

Occupancy Type

Infiltration 

(ACH)

Ventilation 

(ACH)

Total 

ACH

DORMI04 3097 (33 333) 3.66 (12) Lodging 0.3 0.4 0.7

DORMI06 7432 (80 000) 3.66 (12) 0.3 0.4 0.7

HOTEL15 41 806 (450 000) 3.05 (10) 0.3 0.5 0.8

APART04 2787 (30 000) 3.05 (10) 0.3 0.5 0.8

APART06 5574 (60 000) 3.15 (10) 0.3 0.5 0.8

HIGHS02 12 077 (130 000) 4.57 (15) Education 0.3 1.0 1.3

OFFIC03 1858 (20 000) 3.66 (12) Office 0.3 0.4 0.7

OFFIC08 7432 (80 000) 3.66 (12) 0.3 0.4 0.7

OFFIC16 24 155 (260 000) 3.05 (10) 0.3 0.5 0.8

RETAIL1 743 (8000) 4.27 (14) Mercantile 0.4 0.6 1.0

RSTRNT1 465 (5000) 3.66 (12) Food Service 0.6 1.3 1.9

3.3 Energy Simulation Design

Operating energy use is simulated for the 12 540 BIRDS buildings using the U.S. Department of 

Energy’s EnergyPlus Example File Generator (EEFG). The EEFG narrows down a building’s 

description into simple, high-level characteristics: building geometry, orientation, number of 

floors, floor height, building type, wall and roof construction type, window-to-wall ratio, and 

location. The remaining building parameters are defined based on the chosen building energy 

standard and various default values based on the building type.
13

The original simulations obtained from the EEFG assumed a unitary HVAC system with gas 

heat for all building types. The HVAC system in the simulation was replaced with a system that 

best represents the system defined in the commercial prototype buildings in the cost database, the 

RSMeans CostWorks Square Foot Cost Estimator (SFCE). The cooling and heating systems 

defined in the RSMeans CostWorks SFCE are specified in Table 5-3 of the Economic 

Performance chapter.

The efficiency of a particular piece of HVAC equipment is determined by the selected building 

design, which in BIRDS equates to the selected edition of ASHRAE 90.1. The building envelope 

design determines the capacity necessary for the HVAC equipment to meet the thermal load, 

which in turn requires the simulation of the design days. Based on the HVAC equipment 

capacity and the HVAC equipment type, the ASHRAE 90.1 efficiency requirement reported in 

Table 5-3 was determined. 

The HVAC systems are automatically sized for each location by EnergyPlus based on three 

design day outdoor conditions that are more restrictive than those recommended in the ASHRAE 

Fundamentals Handbook. The cooling load is based on two sets of design conditions based on 

the Typical Meteorological Year (TMY2) data: 0.4 % design dry-bulb temperature and mean 

coincident wet bulb temperature, and 0.4 % design wet-bulb temperature and mean coincident 

dry bulb temperature. The heating load is based on the 99.6 % dry-bulb design conditions. Both 

the heating and cooling auto-sizing use a sizing factor of 1.2.

The simulations assume parameter values for the exterior envelope that represent the 

performance of each surface as a single material. For example, a window is represented as a 

single layer with parameter values that represent the combined performance characteristics of 

each layer of the window. The individual components of the window (e.g., panes, coatings, 

films, gas fill, etc.) are not specified in the simulation, only the overall U-factor, Solar Heat Gain 

Coefficient (SHGC), and Visual Transmittance (VT) of the window.

Following are the details of each building type summarized above.

3.3.1 4-Story Apartment Building

The 4-story apartment building has mass walls, insulation entirely above the roof deck, operable 

windows, and a window-to-wall ratio of 12 %.

5 The detailed assumptions used in the energy 

simulations are described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for operable windows for 10.1 % to 20.0 % glazing. 

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

 

5 Window to wall ratio is defined as the percentage of the exterior wall area represented by windows.
14

residential buildings with above grade, mass wall construction and insulation entirely above the 

roof deck. 

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is a packaged electric air-cooled chiller and natural gas-fired hot water boiler. Each 

building type that falls into the “Lodging” CBECS category has the same constant heating and 

cooling setpoint temperatures shown in Figure 3-3: 21 °C (70 °F) for heating and 24 °C (76 °F) 

for cooling.

Figure 3-3 APART04 Setpoint Temperature Schedules

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 0.177 m

3

/s per floor (0.30 ACH) and minimum 

mechanical ventilation of 0.284 m

3

/s per floor (0.48 ACH).

Occupancy, Lighting, and Electrical Loads

The peak occupancy for the 4-story apartment building is assumed to be 120 people or 1 person 

per 23.2 m2(250 ft2). The schedule in Figure 3-4 shows that the greatest occupancy occurs (i.e., 

highest fraction of peak) over the nighttime while the lowest occupancy is during the middle of 

the day.

Figure 3-4 APART04 Occupancy Schedule

18

20

22

24

26

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature 

(°C)

Hour of the Day

Heating Setpoint

Cooling Setpoint

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
15

The energy simulation assumes between 8.6 W/m2(0.8 W/ft2) and 18.3 W/m2(1.7 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedules, as a fraction of peak lighting loads, in Figure 3-5 are representative of 

typical residential occupant activity where the greatest loads are in the late evening between 7:00 

PM and 11:00 PM. There is also a spike in lighting loads in the morning between 7:00 AM and 

10:00 AM. The lighting loads also vary slightly based on the day of the week.

Figure 3-5 APART04 Lighting Schedule

The peak electrical equipment load is 7500 W, or 2.69 W/m2(0.25 W/ft2). Similar to lighting 

loads, the electrical load schedule in Figure 3-6 is highly correlated with occupant activity.

Figure 3-6 APART04 Electrical Load Schedule

3.3.2 6-Story Apartment Building

The 6-story apartment building has mass walls, insulation entirely above the roof deck, operable 

windows, and a window-to-wall ratio of 14 %. The detailed assumptions used in the energy 

simulations are described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for operable windows for 10.1 % to 20.0 % glazing. 

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hours of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
16

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

residential buildings with above grade, mass wall construction and insulation entirely above the 

roof deck.

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is a packaged electric air-cooled chiller and natural gas-fired hot water boiler. Each 

building type that falls into the “Lodging” CBECS category has the same constant heating and 

cooling setpoint temperatures shown in Figure 3-7: 21 °C (70 °F) for heating and 24 °C (76 °F) 

for cooling.

Figure 3-7 APART06 Setpoint Temperature Schedules

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 0.244 m

3

/s per floor (0.30 ACH) and minimum 

mechanical ventilation of 0.379 m

3

/s per floor (0.47 ACH).

Occupancy, Lighting, and Electrical Loads

The peak occupancy for the 6-story apartment building is assumed to be 240 people or 1 person 

per 23.2 m2(250 ft2). The schedule in Figure 3-8 shows that the greatest occupancy occurs over 

the nighttime while the lowest occupancy is during the middle of the day.

Figure 3-8 APART06 Occupancy Schedule

18

20

22

24

26

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Heating Setpoint

Cooling Setpoint

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
17

The energy simulation assumes between 8.6 W/m2(0.8 W/ft2) and 18.3 W/m2(1.7 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedules, as a fraction of peak lighting loads, in Figure 3-9 are representative of 

typical residential occupant activity where the greatest loads are in the late evening between 7:00 

PM and 11:00 PM. There is also a spike in lighting loads in the morning between 7:00 AM and 

10:00 AM. The lighting loads also vary slightly based on the day of the week. 

Figure 3-9 APART06 Lighting Schedule

The peak electrical equipment load is 5625 W, or 2.69 W/m2(0.25 W/ft2). Similar to lighting 

loads, the electrical load schedule in Figure 3-10 is highly correlated with occupant activity.

Figure 3-10 APART06 Electrical Load Schedule

3.3.3 4-Story Dormitory

The 4-story dormitory has mass walls, insulation entirely above the roof deck, operable 

windows, and a window-to-wall ratio of 20 %. The detailed assumptions used in the energy 

simulations are described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for operable windows for 10.1 % to 20.0 % glazing. 

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hours of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
18

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

residential buildings with above grade, mass wall construction and insulation entirely above the 

roof deck.

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is a packaged electric air-cooled chiller and natural gas-fired hot water boiler. Each 

building type that falls into the “Lodging” CBECS category has the same constant heating and 

cooling setpoint temperatures shown in Figure 3-11: 21 °C (70 °F) for heating and 24 °C (76 °F) 

for cooling.

Figure 3-11 DORMI04 Setpoint Temperature Schedules

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 0.236 m

3

/s per floor (0.30 ACH) and minimum 

mechanical ventilation of 0.316 m

3

/s per floor (0.40 ACH).

Occupancy, Lighting, and Electrical Loads

The peak occupancy for the 3-story dormitory is assumed to be 132 people or 1 person per 23.2 

m

2

(250 ft2). The schedule in Figure 3-12 shows that the greatest occupancy occurs over the 

nighttime while the lowest occupancy is during the middle of the day.

Figure 3-12 DORMI04 Occupancy Schedule

18

20

22

24

26

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)Hour of the Day

Heating Setpoint

Cooling Setpoint

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
19

The energy simulation assumes between 8.6 W/m2(0.8 W/ft2) and 18.3 W/m2(1.7 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedules, as a fraction of peak lighting loads, in Figure 3-13 are representative of 

typical residential occupant activity where the greatest loads are in the late evening between 7:00 

PM and 11:00 PM. There is also a spike in lighting loads in the morning between 7:00 AM and 

10:00 AM. The lighting loads also vary slightly based on the day of the week. 

Figure 3-13 DORMI04 Lighting Schedule

The peak electrical equipment load is 8331 W, or 2.69 W/m2(0.25 W/ft2). Similar to lighting 

loads, the electrical load schedule in Figure 3-14 is highly correlated with occupant activity.

Figure 3-14 DORMI04 Electrical Load Schedule

3.3.4 6-Story Dormitory

The 6-story dormitory has steel-framed walls, insulation entirely above the roof deck, operable 

windows, and a window-to-wall ratio of 20 %. The detailed assumptions used in the energy 

simulations are described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for operable windows for 10.1 % to 20.0 % glazing. 

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hours of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
20

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

residential buildings with above grade, steel-framed wall construction and insulation entirely 

above the roof deck.

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is a packaged electric air-cooled chiller and natural gas-fired hot water boiler. Each 

building type that falls into the “Lodging” CBECS category has the same constant heating and 

cooling setpoint temperatures shown in Figure 3-15: 21 °C (70 °F) for heating and 24 °C (76 °F) 

for cooling.

Figure 3-15 DORMI06 Setpoint Temperature Schedules

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 0.401 m

3

/s per floor (0.30 ACH) and minimum 

mechanical ventilation of 0.537 m

3

/s per floor (0.40 ACH).

Occupancy

The peak occupancy for the 6-story dormitory is assumed to be 342 people or 1 person per 23.2 

m

2

(250 ft2). The schedule in Figure 3-16 shows that the greatest occupancy occurs over the 

nighttime while the lowest occupancy is during the middle of the day.

Figure 3-16 DORMI06 Occupancy Schedule

18

20

22

24

26

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Heating Setpoint

Cooling Setpoint

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
21

The energy simulation assumes between 8.6 W/m2(0.8 W/ft2) and 18.3 W/m2(1.7 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedules, as a fraction of peak lighting loads, in Figure 3-17 are representative of 

typical residential occupant activity where the greatest loads are in the late evening between 7:00 

PM and 11:00 PM. There is also a spike in lighting loads in the morning between 7:00 AM and 

10:00 AM. The lighting loads also vary slightly based on the day of the week.

Figure 3-17 DORMI06 Lighting Schedule

The peak electrical equipment load is 21 243 W, or 2.69 W/m2(0.25 W/ft2). Similar to lighting 

loads, the electrical load schedule in Figure 3-18 is highly correlated with occupant activity.

Figure 3-18 DORMI06 Electrical Load Schedule

3.3.5 15-Story Hotel

The 15-story hotel has glass and metal curtain walls with steel framing, insulation entirely above 

the roof deck, and a window-to-wall ratio of 100 %. The detailed assumptions used in the energy 

simulations are described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for fixed windows for 40.1 % to 50.0 % glazing. 

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hours of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
22

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

residential buildings with above grade, steel-framed wall construction and insulation entirely 

above the roof deck.

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is a packaged electric water-cooled chiller and natural gas-fired hot water boiler. Each 

building type that falls into the “Lodging” CBECS category has the same constant heating and 

cooling setpoint temperatures shown in Figure 3-19: 21 °C (70 °F) for heating and 24 °C (76 °F) 

for cooling.

Figure 3-19 HOTEL15 Setpoint Temperature Schedules

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 0.708 m

3

/s per floor (0.30 ACH) and minimum 

mechanical ventilation of 1.136 m

3

/s per floor (0.48 ACH).

Occupancy, Lighting, and Electrical Loads

The peak occupancy for the 15-story hotel is assumed to be 1800 people or 1 person per 23.2 m2

(250 ft2). The schedule in Figure 3-20 shows that the greatest occupancy occurs over the 

nighttime while the lowest occupancy is during the middle of the day.

Figure 3-20 HOTEL15 Occupancy Schedule

18

20

22

24

26

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Heating Setpoint

Cooling Setpoint

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
23

The energy simulation assumes between 8.6 W/m2(0.8 W/ft2) and 18.3 W/m2(1.7 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedules, as a fraction of peak lighting loads, in Figure 3-21 are representative of 

typical residential occupant activity where the greatest loads are in the late evening between 7:00 

PM and 11:00 PM. There is also a spike in lighting loads in the morning between 7:00 AM and 

10:00 AM. The lighting loads also vary slightly based on the day of the week.

Figure 3-21 HOTEL15 Lighting Schedule

The peak electrical equipment load is 112 462 W, or 2.69 W/m2(0.25 W/ft2). Similar to lighting 

loads, the electrical load schedule in Figure 3-22 is highly correlated with occupant activity.

Figure 3-22 HOTEL15 Electrical Load Schedule

3.3.6 2-Story High School

The 2-story high school has mass walls, insulation entirely above the roof deck, operable 

windows, and a window-to-wall ratio of 25 %. The detailed assumptions used in the energy 

simulations are described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for operable windows for 20.1 % to 30.0 % glazing. 

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hours of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
24

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

nonresidential buildings with above grade, mass wall construction and insulation entirely above 

the roof deck.

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is a water-cooled chiller and a natural gas-fired hot water boiler. Each building type

that falls into the “Education” CBECS category has the same heating and cooling setpoint 

temperature schedules. Figure 3-23 shows that the heating setpoint temperature is a constant 

16 °C (61 °F) for weekends while it is 21 °C (70 °F) during the daytime and 16 °C (61 °F) during 

the nighttime on weekdays. Similarly, Figure 3-24 shows that the cooling setpoint temperature is 

a constant 31 °C (88 °F) for weekends while it is 25°C (77 °F) during the daytime and 31°C 

(88 °F) during the nighttime weekdays. These setpoints correlate with the building occupancy 

schedule.

Figure 3-23 HIGHS02 Heating Setpoint Temperature Schedule

Figure 3-24 HIGHS02 Cooling Setpoint Temperature Schedule

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 2.301 m

3

/s per floor (0.30 ACH) and minimum 

mechanical ventilation of 7.971 m

3

/s per floor (1.04 ACH).

15

17

19

21

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Weekends

24

26

28

30

32

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Weekends
25

Occupancy, Lighting, and Electrical Loads

The peak occupancy for the 2-story high school is assumed to be 1740 people or 1 person per 7.0 

m

2

(75 ft2). The schedule in Figure 3-25 shows that the greatest occupancy occurs on the 

weekdays during the school year. The high school is assumed to not be used during the nighttime 

or on weekends year-round. On weekdays during the summer, the occupancy is much lower than 

during the school year.

Figure 3-25 HIGHS02 Occupancy Schedule

The energy simulation assumes between 10.8 W/m2(1.0 W/ft2) and 16.1 W/m2(1.5 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedules, as a fraction of peak lighting loads, in Figure 3-26 are representative of 

typical school occupant activity. The loads are greatest during daytime hours on weekdays of the 

school year. Daytime loads are lower during the summer while school is out. There is no lighting 

use during the nighttime or on weekends year-round.

Figure 3-26 HIGHS02 Lighting Schedule

The peak electrical equipment load is 64 978 W, or 5.38 W/m2(0.5 W/ft2). The electrical load 

schedule in Figure 3-27 is highly correlated with the times of the year that children and teachers 

are at the school (9 AM to 5 PM).

0

0.2

0.4

0.6

0.8

1

1 3 5 7 9 11 13 15 17 19 21 23

Fraction of Peak

Hour of the Day

Weekdays - Sept. 15 to

June 15

Weekdays - June 16 to

Sept. 15

Weekends - All Year

0

0.2

0.4

0.6

0.8

1

1 3 5 7 9 11 13 15 17 19 21 23

Fraction of Peak

Hour of the Day

Weekdays - Sept. 2

through June 30

Weekends - All Year

Weekdays - July 1 through

Sept. 1
26

Figure 3-27 HIGHS02 Electrical Load Schedule

3.3.7 3-Story Office Building

The 3-story office building has mass walls, insulation entirely above the roof deck, operable 

windows, and a window-to-wall ratio of 20 %. The detailed assumptions used in the energy 

simulations are described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for operable windows for 10.1 % to 20.0 % glazing. 

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

nonresidential buildings with above grade, mass wall construction and insulation entirely above 

the roof deck.

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is an air-cooled electric chiller and a natural gas-fired hot water boiler. Each building 

type that falls into the “Office” CBECS category has the same heating and cooling setpoint 

temperature schedules. Figure 3-28 shows that the heating setpoint temperature varies by day of 

the week. The setpoint is a constant 15.6 °C (60 °F) for Sundays and holidays while it is 21 °C 

(70 °F) from 7 AM to 5 PM and 15.6 °C (60 °F) for the rest of the day on Saturdays. Weekdays 

have a similar schedule to Saturdays, with a setpoint of 21 °C (70 °F) from 6 AM to 7 PM and 

15.6 °C (60 °F) for all other hours. Similarly, Figure 3-29 shows that the cooling setpoint 

temperature is a constant 30 °C (86 °F) on Sundays and holidays while it is 24 °C (75 °F) from 

7 AM to 6 PM and 30 °C (86 °F) the remainder of the day on Saturdays. Weekdays have a 

setpoint of 24 °C (75 °F) from 7 AM to 10 PM and 30 °C (86 °F) for all other hours. These 

setpoints correlate with the building occupancy schedule.

0

0.2

0.4

0.6

0.8

1

1 3 5 7 9 11 13 15 17 19 21 23

Fraction of Peak

Hour of the Day

Weekdays - Sept. 2

through June 30

Weekends - All Year

Weekdays - July 1 through

Sept. 1
27

Figure 3-28 OFFIC03 Heating Setpoint Temperature Schedule

Figure 3-29 OFFIC03 Cooling Setpoint Temperature Schedule

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 0.189 m

3

/s per floor (0.30 ACH) and minimum 

mechanical ventilation of 0.246 m

3

/s per floor (0.39 ACH).

Occupancy, Lighting, and Electrical Loads

The peak occupancy for the 3-story office building is assumed to be 72 people or 1 person per 

25.5 m2(275 ft2). The schedule in Figure 3-30 shows that occupancy represents typical office 

activity, where the majority of people are in the building during typical “office hours” (9 AM to 

5 PM) on the weekdays with a drop in occupancy over the lunch hour. There is a relatively small 

amount of occupant activity on Saturdays during typical “office hours.” There is no occupancy 

on Sundays or holidays.

15

17

19

21

23

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Saturday

Sun./Holidays

23

25

27

29

31

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Saturday

Sun./Holidays
28

Figure 3-30 OFFIC03 Occupancy Schedule

The energy simulation assumes between 8.6 W/m2(0.8W/ft2) and 14.0 W/m2(1.3 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedules, as a fraction of peak lighting loads, in Figure 3-31 are representative of 

typical office occupant activity. The loads are greatest during “working” hours on weekdays. 

Daytime loads are lower on Saturdays. There is no lighting use during the nighttime or on 

Sundays or holidays.

Figure 3-31 OFFIC03 Lighting Schedule

The peak electrical equipment load is 14 996 W, or 8.07 W/m2(0.75 W/ft2). The electrical load 

schedule in Figure 3-32 is highly correlated with the occupancy schedule with the greatest 

electrical loads between 9 AM to 5 PM on weekdays.

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fractionof Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
29

Figure 3-32 OFFIC03 Electrical Load Schedule

3.3.8 8-Story Office Building

The 8-story office building has mass walls, insulation entirely above the roof deck, operable 

windows, and a window-to-wall ratio of 20 %. The detailed assumptions used in the energy 

simulations are described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for operable windows for 10.1 % to 20.0 % glazing.

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

nonresidential buildings with above grade, mass wall construction and insulation entirely above 

the roof deck.

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is a rooftop packaged air conditioner and a natural gas-fired furnace. Each building 

type that falls into the “Office” CBECS category has the same heating and cooling setpoint 

temperature schedules. Figure 3-33 shows that the heating setpoint temperature varies by day of 

the week. The setpoint is a constant 15.6 °C (60 °F) for Sundays and holidays while it is 21 °C 

(70 °F) from 7 AM to 5 PM and 15.6 °C (60 °F) for the rest of the day on Saturdays. Weekdays 

have a similar schedule to Saturdays, with a setpoint of 21 °C (70 °F) from 6 AM to 7 PM and 

15.6 °C (60 °F) for all other hours. Similarly, Figure 3-34 shows that the cooling setpoint 

temperature is a constant 30C on Sundays and holidays while it is 24 °C (75 °F) from 7 AM to 

6 PM and 30 °C (86 °F) the remainder of the day on Saturdays. Weekdays have a setpoint of 

24 °C (75 °F) from 7 AM to 10 PM and 30 °C (86 °F) for all other hours. These setpoints 

correlate with the building occupancy schedule.

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
30

Figure 3-33 OFFIC08 Heating Setpoint Temperature Schedule

Figure 3-34 OFFIC08 Cooling Setpoint Temperature Schedule

Air Infiltration and Mechanical Ventilation

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 0.283 m

3

/s per floor (0.30 ACH) and minimum 

mechanical ventilation of 0.370 m

3

/s per floor (0.39 ACH).

Occupancy, Lighting, and Electrical Loads

The peak occupancy for the 8-story office building is assumed to be 288 people or 1 person per 

25.5 m2(275 ft2). The schedule in Figure 3-35 shows that occupancy represents typical office 

activity, where the majority of people are in the building during typical “office hours” (9 AM to 

5 PM) on the weekdays with a drop in occupancy over the lunch hour. There is a relatively small 

amount of occupant activity on Saturdays during typical “office hours.” There is no occupancy 

on Sundays or holidays.

15

17

19

21

23

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Saturday

Sun./Holidays

23

25

27

29

31

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Saturday

Sun./Holidays
31

Figure 3-35 OFFIC08 Occupancy Schedule

The energy simulation assumes between 8.6 W/m2(0.8W/ft2) and 14.0 W/m2(1.3 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedules, as a fraction of peak lighting loads, in Figure 3-36 are representative of 

typical office occupant activity. The loads are greatest during “working” hours on weekdays. 

Daytime loads are lower on Saturdays. There is no lighting use during the nighttime or on 

Sundays or holidays.

Figure 3-36 OFFIC08 Lighting Schedule

The peak electrical equipment load is 59 978 W, or 8.07 W/m2(0.75 W/ft2). The electrical load 

schedule in Figure 3-37 is highly correlated with the occupancy schedule with the greatest 

electrical loads between 9 AM to 5 PM on weekdays.

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fractionof Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
32

Figure 3-37 OFFIC08 Electrical Load Schedule

3.3.9 16-Story Office Building

The 16-story office building has glass and metal curtain walls with steel framing, insulation 

entirely above the roof deck, and a window-to-wall ratio of 100 %. The detailed assumptions 

used in the energy simulations are described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for operable windows for 40.1 % to 50.0 % glazing. 

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

nonresidential buildings with above grade, steel-framed wall construction and insulation entirely 

above the roof deck.

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is a water-cooled electric chiller and a natural gas-fired hot-water boiler. Each 

building type that falls into the “Office” CBECS category has the same heating and cooling 

setpoint temperature schedules. Figure 3-38 shows that the heating setpoint temperature varies 

by day of the week. The setpoint is a constant 15.6 °C (60 °F) for Sundays and holidays while it 

is 21 °C (70 °F) from 7 AM to 5 PM and 15.6 °C (60 °F) for the rest of the day on Saturdays. 

Weekdays have a similar schedule to Saturdays, with a setpoint of 21 °C (70 °F) from 6 AM to 

7 PM and 15.6 °C (60 °F) for all other hours. Similarly, Figure 3-39 shows that the cooling 

setpoint temperature is a constant 30 °C (86 °F) on Sundays and holidays while it is 24 °C 

(75 °F) from 7 AM to 6 PM and 30 °C (86 °F) the remainder of the day on Saturdays. Weekdays 

have a setpoint of 24 °C (75 °F) from 7 AM to 10 PM and 30 °C (86 °F) for all other hours. 

These setpoints correlate with the building occupancy schedule.

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
33

Figure 3-38 OFFIC16 Heating Setpoint Temperature Schedule

Figure 3-39 OFFIC16 Cooling Setpoint Temperature Schedule

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 0.384 m

3

/s per floor (0.30 ACH) and minimum 

mechanical ventilation of 0.600 m

3

/s per floor (0.47 ACH).

Occupancy, Lighting, and Electrical Loads

The peak occupancy for the 16-story office building is assumed to be 944 people or 1 person per 

25.5 m2(275 ft2). The schedule in Figure 3-40 shows that occupancy represents typical office 

activity, where the majority of people are in the building during typical “office hours” (9 AM to 

5 PM) on the weekdays with a drop in occupancy over the lunch hour. There is a relatively small 

amount of occupant activity on Saturdays during typical “office hours.” There is no occupancy 

on Sundays or holidays.

15

17

19

21

23

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Saturday

Sun./Holidays

23

25

27

29

31

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Saturday

Sun./Holidays
34

Figure 3-40 OFFIC16 Occupancy Schedule

The energy simulation assumes between 8.6 W/m2(0.8W/ft2) and 14.0 W/m2(1.3 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedules, as a fraction of peak lighting loads, in Figure 3-41 are representative of 

typical office occupant activity. The loads are greatest during “working” hours on weekdays. 

Daytime loads are lower on Saturdays. There is no lighting use during the nighttime or on 

Sundays or holidays.

Figure 3-41 OFFIC16 Lighting Schedule

The peak electrical equipment load is 194 934 W, or 8.07 W/m2(0.75 W/ft2). The electrical load 

schedule in Figure 3-42 is highly correlated with the occupancy schedule with the greatest 

electrical loads between 9 AM to 5 PM on weekdays.

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fractionof Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
35

Figure 3-42 OFFIC16 Electrical Load Schedule

3.3.10 1-Story Retail Store

The 1-story retail store has mass walls, insulation entirely above the roof deck, fixed windows, 

and a window-to-wall ratio of 10 %. The detailed assumptions used in the energy simulations are 

described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for operable windows for 0.0 % to 10.0 % glazing. 

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

nonresidential buildings with above grade, mass wall construction and insulation entirely above 

the roof deck.

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is a rooftop packaged electric air conditioner and a natural gas-fired furnace. Figure 

3-43 show that the heating setpoint temperature for the retail store varies slightly by day of the 

week. For all days, the setpoint is 21 °C (70 °F) while the store is open and 15.6 °C (60 °F) when 

the store is closed. The store is open from 7 AM to 10 PM on weekdays and 7 AM to 11 PM on 

Saturdays. The store hour on Sundays and holidays are 9 AM to 8 PM. These setpoints correlate 

with the building occupancy schedule. Figure 3-44 shows a nearly identical pattern for the 

cooling setpoint temperature. The setpoint is 24 °C (75 °F) for 7 AM to 9 PM on weekdays, 

7 AM to 10 PM on Saturdays, and 9 AM to 7 PM on Sundays and holidays. The setpoint is 30 °C 

(86 °F) while the store is closed.

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
36

Figure 3-43 RETAIL1 Heating Setpoint Temperature Schedule

Figure 3-44 RETAIL1 Cooling Setpoint Temperature Schedule

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 0.378 m

3

/s per floor (0.43 ACH) and minimum 

mechanical ventilation of 0.547 m

3

/s per floor (0.62 ACH).

Occupancy, Lighting, and Electrical Loads

The peak occupancy for the 1-story retail store is assumed to be 27 people or 1 person per 25.5 

m

2

(300 ft2). The schedule in Figure 3-45 shows that occupancy varies significantly both within a 

given day and across days of the week. In general, the afternoon and early evening is the busy 

time over all days, which is the most common time of the day for people to shop. The afternoon 

is the busiest time on the weekends and holidays while the early evening has the greatest 

occupancy on weekdays. The greatest occupancy occurs on Saturday followed by weekdays and 

then Sundays and holidays.

15

17

19

21

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Saturday

Sun./Holidays

23

25

27

29

31

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Saturday

Sun./Holidays
37

Figure 3-45 RETAIL1 Occupancy Schedule

The energy simulation assumes between 16.1 W/m2(1.5 W/ft2) and 20.5 W/m2(1.9 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedule, as a fraction of peak lighting loads, in Figure 3-46 is highly correlated 

with the occupancy schedule. However, lighting is an on/off decision. So when the retail store is 

open, the lighting load is fairly constant and has less variability than the occupancy schedule.

Figure 3-46 RETAIL1 Lighting Schedule

The peak electrical equipment load is 1999 W, or 2.69 W/m2(0.25 W/ft2). The electrical load 

schedule in Figure 3-47 is highly correlated with the occupancy and lighting schedules, but has 

less variability across days of the week because most electrical loads are constant when a 

building is occupied.

Figure 3-47 RETAIL1 Electrical Load Schedule

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
38

3.3.11 1-Story Restaurant

The 1-story restaurant has wood frame wall construction, insulation entirely above the roof deck, 

fixed windows, and a window-to-wall ratio of 30 %. The detailed assumptions used in the energy 

simulations are described below.

Building Envelope

The energy efficiency characteristics of the building envelope are determined by the building’s 

location and the edition of ASHRAE 90.1. The window characteristics (U-factor, SHGC, and VT) 

are based on the ASHRAE 90.1 requirements for operable windows for 20.1 % to 30.0 % glazing. 

The wall and roof efficiency characteristics are based on the ASHRAE 90.1 requirements for 

nonresidential buildings with above grade, wood-framed wall construction and insulation 

entirely above the roof deck.

Heating, Ventilation, and Air Conditioning

There are four main aspects to the heating, ventilation, and air conditioning of a building: 

equipment, operating conditions, air infiltration, and mechanical ventilation. The HVAC 

equipment is a rooftop packaged electric air conditioner and a natural gas-fired furnace. Figure 

3-48 shows that the heating setpoint temperature for the restaurant varies slightly by day of the 

week. The setpoint is 21 °C (70 °F) from midnight to 3 AM and 7 AM to midnight on weekdays,

midnight to 3 AM and 9 AM to midnight on Saturdays, and midnight to 3 AM and 10 AM to 

midnight on Sundays and holidays. The heating setpoint is 15.6 °C (60 °F) for all other times. 

Figure 3-49 shows a mirror image for the cooling setpoint temperature. The setpoint is 24 °C 

(75 °F) from midnight to 3 AM and 7 AM to midnight on weekdays, midnight to 3 AM and 

9 AM to midnight on Saturdays, and midnight to 3 AM and 10 AM to midnight on Sundays and 

holidays. The cooling setpoint is 30 °C (86 °F) for all other times.

Figure 3-48 RSTRNT1 Heating Setpoint Temperature Schedule

15

17

19

21

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Saturday

Sun./Holidays
39

Figure 3-49 RSTRNT1 Cooling Setpoint Temperature Schedule

Air infiltration and mechanical ventilation are assumed to be constant across all editions of 

ASHRAE 90.1, with an infiltration rate of 0.275 m

3

/s per floor (0.58 ACH) and minimum 

mechanical ventilation of 0.609 m

3

/s per floor (1.29 ACH).

Occupancy, Lighting, and Electrical Loads

The peak occupancy for the 1-story restaurant is assumed to be 50 people or 1 person per 25.5 

m

2

(100 ft2). The schedule in Figure 3-50 shows that occupancy varies significantly both within a 

given day and across days of the week. As would be expected, lunchtime and dinnertime are the 

busiest times over all days.

Figure 3-50 RSTRNT1 Occupancy Schedule

The energy simulation assumes between 14.0 W/m2(1.3 W/ft2) and 19.4 W/m2(1.8 W/ft2) of 

lighting density depending on the building design (e.g., edition of ASHRAE 90.1 or LEC). The 

lighting load schedules, as a fraction of peak lighting loads, in Figure 3-51 is correlated with the 

occupancy schedule. However, lighting has less variability than the occupancy schedule.

23

25

27

29

31

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Setpoint 

Temperature (°C)

Hour of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays
40

Figure 3-51 RSTRNT1 Lighting Schedule

The peak electrical equipment load is 502 W, or 1.08 W/m2(0.10 W/ft2). The electrical load 

schedule in Figure 3-52 is highly correlated with the lighting schedules, but does not vary across 

days of the week because most electrical loads tend to be constant when a building is occupied 

no matter the amount of occupancy.

Figure 3-52 RSTRNT1 Electrical Load Schedule

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Fraction of Peak

Hour of the Day

Weekdays

Saturday

Sun./Holidays

0

0.2

0.4

0.6

0.8

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Fraction of Peak

Hour of the Day

All Days
41

4 Environmental Performance Measurement

BIRDS evaluates the environmental performance of whole buildings using a life cycle 

assessment (LCA) approach. The general LCA methodology involves four steps (ISO, 2006). 

The goal and scope definition step spells out the purpose of the study and its breadth and depth. 

The inventory analysis step identifies and quantifies the environmental inputs and outputs 

associated with a building over its entire life cycle. Environmental inputs include water, energy, 

land, and other resources; outputs include releases to air, land, and water. However, it is not 

these inputs and outputs, or inventory flows, which are of primary interest. We are more 

interested in their consequences, or impacts on the environment. Thus, the next LCA step, impact 

assessment, characterizes these inventory flows in relation to a set of environmental impacts. For 

example, the impact assessment step might relate carbon dioxide emissions, a flow, to global 

warming, an impact. Finally, the interpretation step combines the environmental impacts in 

accordance with the goals of the LCA study.

4.1 Goal and Scope Definition

The goal of BIRDS LCAs is to generate environmental performance scores for a range of U.S. 

building types, each designed to meet 5 alternative levels of operating energy efficiency. These 

results will be reported alongside economic performance scores to help designers, investors, and 

policymakers develop business cases for high-performance green buildings.

The scoping phase of any LCA involves defining the boundaries of the product system—or, in 

the case of BIRDS, the building—under study. In traditional bottom-up LCAs, boundary setting 

requires expert judgment by the analyst. The construction of a building involves a number of unit 

processes (e.g., asphalt production for input to the manufacture of facing for fiberglass batt 

insulation). Each unit process involves many inventory flows, some of which themselves involve 

other, subsidiary unit processes. Because including an ever-expanding number of unit processes 

in LCAs is not feasible, the product system’s supply chain links are truncated at some point to 

include only those judged to make non-negligible contributions to the product system. The 

analyst typically uses mass, energy, and/or cost contributions as decision criteria. Use of 

different boundary setting criteria is one of the main reasons LCA results from different studies 

are often found incomparable.

One important advantage of the BIRDS hybrid approach is that it addresses the bottom-up issue 

of truncation in supply chain links, thereby improving consistency in system boundary 

selections. Through the hybridization process, truncated supply chain links are connected to the 

background U.S. economic system represented by the top-down data. These linkages follow the 

metabolic structure of the U.S. economy, thereby benefitting from a more complete system 

definition including potentially thousands of supply chain interactions. 

Due to their long service lives, buildings are somewhat unique when it comes to the end-of-life 

stage of the life cycle. For most non-consumable product LCAs, end-of-life waste flows are 

included in the inventory analysis for full coverage of the life cycle. If there is an active
42

recycling market that diverts some of the product from the waste stream, that portion of the 

product’s end-of-life flows can be ignored. In BIRDS, however, building lifetimes range from 41 

to 65 years, longer than the 40-year maximum length for the study period. Therefore, 100 % of 

each building is considered to be “recycled” at the end of the study period and there are no endof-life waste flows allocated to the building at the end of the BIRDS study period. Rather, endof-life waste flows should be allocated to a different “product,” representing use of the building 

from the end of the study period to the end of the building service life. Similarly, the 

environmental burdens from building construction are allocated only to its first use (over the 

BIRDS study period); LCAs for all subsequent uses should be treated as free of these initial 

construction burdens. This effectively credits the use of existing buildings over new construction 

and ensures there will be no double counting once existing building LCAs are included in future 

versions of BIRDS as planned.

Defining the unit of comparison is an important task in the goal and scoping phase of LCA. The 

basis for all units of comparison is the functional unit, defined so that the systems compared are 

true substitutes for one another. In the BIRDS model, the functional unit is construction and 

use of one building prototype over a user-defined study period. The functional unit provides 

the critical reference point to which the LCA results are scaled. 

Scoping also involves setting data requirements. With respect to geographic coverage, the 

BIRDS inventory data are generally U.S. average data. An exception is made for the electricity 

production inventory data applied to a building’s use of electricity. These data are customized to 

each U.S. state. In terms of technology coverage, the top-down inventory data represent the mix 

of technologies in place as of 2002, the year of the most recent top-down data available from the 

U.S. Economic Census. For the bottom-up inventory data on building energy technologies, the 

most representative technology for which data are available is evaluated.

4.2 Life Cycle Inventory Analysis

BIRDS applies a hybridized life-cycle assessment approach. The approach is hybridized in the 

sense that a mixture of top-down and bottom-up data are collected and systematically integrated

in the inventory analysis LCA step. Traditional process-based LCAs gather data by modeling all 

the in-scope industrial processes involved in a product’s production (raw materials acquisition, 

materials processing, manufacture, transportation), use, and waste management. For each 

industrial process, the analyst collects very detailed, bottom-up data on all its inputs from the 

environment (e.g., materials, fuel, water, land) and outputs to the environment (e.g., products, 

water effluents, air emissions, waste). This process is summarized in Figure 4-1. 

To address the complexities of a whole building, BIRDS takes a new, multi-layered approach to 

inventory analysis. Since a building’s operating energy efficiency has an important influence on 

its sustainability performance, and energy efficiency is largely driven by the building’s energy 

technologies, BIRDS pays special attention to the materials used in them. Specifically, BIRDS 

uses detailed life cycle inventory data for a range of energy technology packages that have been 
43

analyzed at the traditional, bottom-up LCA level. These energy technology packages are used to 

meet the 5 levels of energy efficiency simulated for each building type in 228 different U.S. 

locations. The bottom-up approach is also used to gather inventory data for a building’s use of 

electricity and natural gas over the study period. These bottom-up BIRDS data were developed 

under contract to NIST by Four Elements Consulting, LLC, of Seattle, Washington, and are 

documented in section 4.5. For all other building constituents, industry average life cycle 

inventory data are gathered from the top down and then systematically combined with bottom up 

data into a comprehensive, hybrid life cycle inventory for a whole building.

Figure 4-1. Compiling LCA Inventories of Environmental Inputs and Outputs

The inventory data items collected through the bottom up and top down approaches are 

identical—for example, kg carbon dioxide, kWh primary energy consumption—but some of the 

data sources are quite different. The systematic hybridization of the data sets bridges these 

differences to yield coherent and consistent BIRDS life cycle inventories for a wide variety of 

new commercial buildings. The LCAs for the buildings are then completed by applying 

conventional methods of life cycle impact assessment and interpretation to the hybrid inventory 

data. 

Top-Down Inventory Analysis. An economy’s accounting structure provides a cost-effective topdown approach to LCA inventory data collection. Many developed economies maintain 

economic input-output (I-O) accounts that trace the flow of goods and services throughout 

industries. Much the same way that a product’s production can be traced upstream through its 

supply chain, an industry’s production can be traced upstream through its supply chain. The U.S. 

Census Bureau conducts an Economic Census of U.S. industry every five years that does just 

that. Covering 97 % of business receipts, the census reaches nearly all U.S. business 

recycle remanufacture reuse

INPUTS:

OUTPUTS: Products, Water Effluents, Air Emissions, Waste, Other Outputs

Materials, Fuel, Water, Other Inputs

raw material 

acquisition

material 

processing manufacturing use

waste 

management
44

establishments. Based on the detailed data collected, the U.S. Bureau of Economic Analysis 

(BEA) creates what are called Input-Output Accounts, or “I-O tables,” for the U.S. economy. 

The U.S. I-O tables show how around 500 industries provide input to, and use output from, each 

other to produce Gross Domestic Product (GDP). These tables, for example, can show how $100 

million of U.S. economic output in the residential building construction sector traces back 

through its direct monetary inputs—from the construction process itself—to its indirect inputs 

from contributing sectors such as the steel, concrete, lumber, and plastics industries. Economic 

output from the steel, concrete, lumber, and plastics industries, in turn, can be traced back 

through those supply chains such as mining, forestry, and fuel extraction. And so on. 

While BEA provides these I-O tables in purely monetary terms, academics have successfully 

developed “environmentally-extended” I-O tables (Suh, 2005; Hendrickson, 2006; Suh, 2010).

These top-down tables tap into a wide range of national environmental statistics to associate 

environmental inputs and outputs with economic activity in industry sectors, including use of 

raw materials, fuel, water, and land and releases of water effluents, air emissions, and waste. 

BIRDS uses environmentally-extended I-O tables for the U.S. construction industry developed 

under contract to NIST by Industrial Ecology Research Services of Goleta, California. These 

tables are based on the 2007 release of the 2002 BEA I-O data, the latest available, and quantify 

6204 environmental inputs and outputs occurring throughout production supply chains.

To understand the contribution of building construction to the nation’s environmental footprint 

(impact), it is useful to focus on the concept of “final demand.” The BEA’s monetary I-O tables 

use GDP—the total value of the consumption of goods and services in a year—to measure final 

demand. This value consists of spending and investment by consumers, businesses, and 

government, as well as net exports. Since final demand is satisfied through annual production—

goods and services need to be produced before they can be bought—each industry’s value-added, 

or “direct” contribution to GDP, reflects its share of final demand.

The environmentally-extended I-O tables translate economic activity into environmental terms, 

or monetary GDP into environmental GDP (eGDP). In LCA terms, the construction industry’s 

contribution to eGDP is not limited to the direct impact from value-added construction processes 

and activities. Its contribution to eGDP also includes the indirect impacts stemming from 

contributions by upstream construction supply chains up to and including raw materials 

acquisition. The supply chain relationships built into the environmentally-extended I-O tables 

enable estimation of construction industry impacts on this cumulative, life-cycle basis. Figure 

4-2 illustrates these supply chain relationships for some of the inputs to ready-mix concrete 

manufacturing, an indirect construction industry input. 
45

U.S. 

Construction 

Industry

Inputs

Design & 

related 

services

Retail trade 

Wholesale trade Ready-mix concrete 

mfg Metal products

Trucking Plastics mfg 

Petroleum refining Machinery/ 

equipment rental

Fabricated 

structural prods

Etc.

Outputs

Offices

Hospitals 

Lodging

Education

SingleFamily

Highways

Etc.

Ready-mix 

concrete 

mfg 

Cement 

mfg

Mining 

machinery 

mfg

Sand, 

gravel, 

clay 

mining

Gypsum 

mfg

Lime mfg

Direct 

Inputs Indirect Inputs

Value 

Added 

Outputs

Figure 4-2. Illustration of Supply Chain Contributions to U.S. Construction Industry

The environmentally extended I-O tables classify U.S. construction into 42 distinct industry 

outputs. In this first version of BIRDS, top-down inventory data represent this level of detail for 

the construction, maintenance, and repair associated with the 9 industry outputs shown in Table 

4-1. The first 7 outputs correspond to the occupancy types covered by the 11 building prototypes 

in BIRDS. The last 2 correspond to maintenance and repair (M&R) activities in those buildings. 

For routine M&R, nonresidential M&R output applies to all but the lodging occupancy 

prototypes. For these, residential M&R output applies. For all the construction industry outputs, 

the baseline top-down inventory data are expressed in terms of life-cycle environmental flows

per dollar of construction.
46

Table 4-1. Construction Industry Outputs Mapped to BIRDS Building Types

Construction 

Type Industry Output Occupancy BIRDS Building Type

New 

Construction

New office buildings, including financial buildings Office

OFFIC03

OFFIC08

OFFIC16

New multi-merchandise shopping Mercantile RETAIL1

New food and beverage establishments Food Service RSTRNT1

New educational and vocational structures Education HIGHS02

New lodging

Lodging

HOTEL15

New multifamily residential structures

APART04

APART06

New dormitories

DORMI04

DORMI06

M&R 

Construction

Residential maintenance and repair construction Lodging

HOTEL15

APART04

APART06

DORMI04

DORMI06

Nonresidential maintenance and repair construction All Others All Others

One advantage of the BIRDS approach is the economic dimension built into the top-down 

inventory data. These data are directly associated with U.S. economic data, permitting seamless 

integration of the economic dimension in the BIRDS sustainability measurement system. The 

top-down inventory values on a per-dollar basis are multiplied by the corresponding BIRDS 

construction, maintenance, and repair costs to translate them into the LCA functional unit

representing the whole building over a user-defined study period.

For more information on the mathematics, accounting structure, and step-by-step process under 

which the BIRDS hybrid environmental database is built, see Suh and Lippiatt 2012.

4.3 Life Cycle Impact Assessment

Environmental impacts from building construction and use derive from the 6204 inputs and 

outputs occurring throughout production supply chains, as quantified in the hybrid BIRDS life 

cycle inventory. The impact assessment step of LCA quantifies the potential contribution of 

these inventory items to a range of environmental impacts. The approach preferred by most LCA 

practitioners and scientists today involves a two-step process: 
47

 Classification of inventory flows that contribute to specific environmental impacts. For 

example, greenhouse gases such as carbon dioxide, methane, and nitrous oxide are 

classified as contributing to global warming.

 Characterization of the potential contribution of each classified inventory flow to the 

corresponding environmental impact. This results in a set of indices, one for each impact,

which is obtained by weighting each classified inventory flow by its relative contribution 

to the impact. For instance, the Global Warming Potential index is derived by expressing 

each greenhouse gas in terms of its equivalent amount of carbon dioxide heat trapping 

potential.

There are two general applications of this life cycle impact assessment (LCIA) approach: 

midpoint-level and endpoint-level analyses. An endpoint-level analysis attempts to measure the 

ultimate damage that each environmental input and output in the inventory will have along the 

cause-effect chain. Methods of this type include just a few impact categories, such as damage to 

human health, ecosystems, and resource availability, that are easier to interpret in the final step 

of life cycle assessment. This approach is criticized for the numerous assumptions, value 

judgments, and gaps in coverage of the underlying damage models. A midpoint-level analysis, 

on the other hand, selects points along the cause-effect chain at which more certain and 

comprehensive assessments may be carried out. While this approach generates many impact 

categories, making life-cycle interpretation more difficult, it is more scientifically defensible. 

Even so, a midpoint-level analysis does not offer the same degree of relevance for all 

environmental impacts. For global and regional effects (e.g., global warming and acidification) 

the method provides an accurate description of the potential impact. For impacts dependent upon 

local conditions (e.g., smog), it may result in an oversimplification of the actual impacts because 

the indices are not tailored to localities. Note that some impact assessments apply a mix of 

midpoint and endpoint approaches.

4.3.1 BIRDS Impact Assessment

BIRDS uses a midpoint-level analysis to translate its 6204 environmental inputs and outputs into 

a manageable set of science-based measurements across 12 environmental impacts. BIRDS 

primarily uses the U.S. Environmental Protection Agency’s TRACI (Tool for the Reduction and 

Assessment of Chemical and other environmental Impacts) version 2.0 set of state-of-the-art, 

peer-reviewed U.S. life cycle impact assessment methods (Bare 2011). Since TRACI 2.0 does 

not include land and water use, these two important resource depletion impacts are assessed 

using other characterization methods (Guinee 2002, Goedkoop 2009). Together these methods 

are used to develop BIRDS performance metrics indicating the degree to which construction and 

use of a building contributes to each environmental impact. Following are brief descriptions of 

the 12 BIRDS impact categories.
48

Impact Categories

Global Warming. The Earth absorbs radiation from the Sun, mainly at the surface. This energy is 

then redistributed by the atmosphere and ocean and re-radiated to space at longer wavelengths. 

Some of the thermal radiation is absorbed by "greenhouse" gases in the atmosphere, principally 

water vapor, but also carbon dioxide, methane, the chlorofluorocarbons, and ozone. The 

absorbed energy is re-radiated in all directions, downwards as well as upwards, such that the 

radiation that is eventually lost to space is from higher, colder levels in the atmosphere. The 

result is that the surface loses less heat to space than it would in the absence of the greenhouse 

gases and consequently stays warmer than it would be otherwise. This phenomenon, which acts 

rather like a ‘blanket’ around the Earth, is known as the greenhouse effect.

The greenhouse effect is a natural phenomenon. The environmental issue is the change in the 

greenhouse effect due to emissions (an increase in the effect) and absorptions (a decrease) 

attributable to humans. A general increase in temperature can alter atmospheric and oceanic 

temperatures, which can potentially lead to alteration of circulation and weather patterns. A rise 

in sea level is also predicted from an increase in temperature due to thermal expansion of the 

oceans and melting of polar ice sheets.

Primary Energy Consumption. Primary energy consumption leads to fossil fuel depletion when 

fossil fuel resources are consumed at rates faster than nature renews them. Some experts believe 

fossil fuel depletion is fully accounted for in market prices. That is, market price mechanisms are 

believed to take care of the scarcity issue, price being a measure of the level of depletion of a 

resource and the value society places on that depletion. However, price is influenced by many 

factors other than resource supply, such as resource demand and non-perfect markets (e.g., 

monopolies and subsidies). The primary energy consumption metric is used to account for the 

resource depletion aspect of fossil fuel extraction. 

Human Health—Criteria Air Pollutants can arise from many activities including combustion, 

vehicle operation, power generation, materials handling, and crushing and grinding operations. 

They include coarse particles known to aggravate respiratory conditions such as asthma, and fine 

particles that can lead to more serious respiratory symptoms and disease.

Human Health—Cancer Effects can arise from exposure to industrial and natural substances, and 

can lead to illness, disability, and death. Its assessment is based on the global consensus model 

known as USEtox, which describes the fate, exposure and effects of thousands of chemicals.

Water Consumption. Water resource depletion has not been routinely assessed in LCAs to date, 

but researchers are beginning to address this issue to account for areas where water is scarce,

such as the Western United States. While some studies use water withdrawals to evaluate this 

impact, a more refined analysis considers that a portion of water withdrawn may be returned 

through evapotranspiration (the sum of evaporation from surface water, soil, and plant leaves). 

BIRDS uses the latter approach to measure water consumption, or water withdrawn net of 
49

evapotranspiration. BIRDS evaluates water consumption from cradle to grave, including water 

consumption during building use.

Ecological Toxicity measures the potential of pollutants from industrial sources to harm landand water-based ecosystems. Its assessment is based on the global consensus model known as 

USEtox, which describes the fate, exposure and effects of thousands of chemicals. 

Eutrophication Potential. Eutrophication is the addition of mineral nutrients to the soil or water. 

In both media, the addition of large quantities of mineral nutrients, such as nitrogen and 

phosphorous, results in generally undesirable shifts in the number of species in ecosystems and a 

reduction in ecological diversity. In water, it tends to increase algae growth, which can lead to 

lack of oxygen and therefore death of species like fish. 

Land Use. This impact category measures the use of land resources by humans which can lead to 

undesirable changes in habitats. Note that the BIRDS land use approach does not consider the 

original condition of the land, the extent to which human activity changes the land, or the length 

of time required to restore the land to its original condition. As impact assessment science 

continues to evolve, it is hoped that these potentially important factors will become part of

BIRDS land use assessment.

Human Health—Noncancer Effects can arise from exposure to industrial and natural substances, 

and range from transient irritation to permanent disability and even death. Its assessment is based 

on the global consensus model known as USEtox, which describes the fate, exposure and effects 

of thousands of chemicals. 

Smog Formation. Smog forms under certain climatic conditions when air emissions from 

industry and transportation are trapped at ground level where they react with sunlight. Smog 

leads to harmful impacts on human health and vegetation.

Acidification Potential. Acidifying compounds may in a gaseous state either dissolve in water or 

fix on solid particles. They reach ecosystems through dissolution in rain or wet deposition. 

Acidification affects trees, soil, buildings, animals, and humans. The two compounds principally 

involved in acidification are sulfur and nitrogen compounds. Their principal human source is 

fossil fuel and biomass combustion. Other compounds released by human sources, such as 

hydrogen chloride and ammonia, also contribute to acidification.

Ozone Depletion, or a thinning of the stratospheric ozone layer, allows more harmful short wave 

radiation to reach the Earth’s surface, potentially causing undesirable changes in ecosystems, 

agricultural productivity, skin cancer rates, and eye cataracts, among other issues.

Computational Algorithms

There are six building components represented in the BIRDS life-cycle impact assessment 

(LCIA) calculations for whole buildings: 
50

 Baseline building: new construction (Base_New)

 Baseline building: maintenance and repair over study period (Base_M&R)

 Energy technology package: new construction (ETP_New)

 Energy technology package: annual maintenance and repair (ETP_M&R)

 Annual operating energy use: electricity (ELEC)

 Annual operating energy use: natural gas (NG)

The hybridized life cycle inventory data for each component are expressed in different units For 

example, the baseline building inventories are given on a per-dollar basis, the energy technology 

package inventories on a per-physical unit basis (usually area), and the operating energy use 

inventories on a per-BTU basis. Thus, each requires its own LCIA computational algorithm as 

shown in Table 4-2. These calculations ensure that after adjusting for study period length, all 

LCIA results are expressed in the consistent functional unit defined for BIRDS: construction and 

use of one building prototype over a user-defined study period.

Table 4-2 BIRDS Life Cycle Impact Assessment Calculations by Building Component

Building 

Component LCIA Equation Notation

Base_New LCIAi,j,c=1 = (LCIAi,j,c=1/$)*$i,c=1

LCIA=classified and characterized life cycle 

inventories

c=construction type code, 1=new, 2=M&R

E=electricity

ET=energy technology product

FU=functional unit*

i = building type, i=1 to 11

j=environmental impact, j=1 to 12

K=energy standard, K=1 to 5

n=study period length in years, n=1 to 40

NG=natural gas

s=U.S. state, s=1 to 50

T = energy technology group, T=1 to 6*

x= building location, x=1 to 228

Base_M&R LCIAi,j,c=2,yr = (LCIAi,j,c=2/$)*$i,c=2,yr

ETP_New LCIAi,j,c=1,x,K,T =

(LCIAj,c=1,ET(i,x,K,T)/FU)*FUi,T

from T=1 to 6

ETP_M&R LCIAi,j,c=2,x,K,T/yr 

(LCIAj,c=2,ET(i,x,K,T)/FU/yr)*FUi,T

from T=1 to 6

ELEC LCIAi,j,x,K/yr = (LCIAj,s/BTUE)*(BTUE,i,x,K/yr)

NG LCIAi,j,x,K/yr  (LCIAj/BTUNG)*(BTUNG,i,x,K/yr)

*energy technology groups and their functional units are wall insulation (ft2), roof insulation (ft2), windows (ft2), 

HVAC (no. of units), overhangs (ft2), and daylighting (ft2).

4.3.2 BIRDS Normalization

Once impacts have been classified and characterized, the resulting LCIA metrics are expressed in 

incommensurate units. Global warming is expressed in carbon dioxide equivalents, acidification 

in hydrogen ion equivalents, eutrophication in nitrogen equivalents, and so on. In order to assist 

in the next LCA step, interpretation, these metrics are often placed on the same scale through 

normalization. 
51

The U.S. EPA has developed “normalization references” corresponding to its TRACI set of 

impact assessment methods (Bare et al. 2006). These U.S. data are updated and expanded for use 

in BIRDS. Shown in Table 4-3, these values quantify the U.S. economy’s annual contributions to 

each impact category. As such, they represent a “U.S. impact yardstick” against which to 

evaluate the significance of building-specific impacts. Normalization is accomplished by 

dividing BEES building-specific impact assessment results by the fixed U.S.-scale normalization 

references, expressed in the same units, yielding an impact category score for a building that has 

been placed in the context of annual U.S. contributions to that impact. By placing each buildingspecific impact result in the context of its associated U.S. impact result, the measures are all 

reduced to the same scale, allowing comparison across impacts.

Table 4-3. BIRDS Normalization References

Impact Category

Normalization 

reference

(U.S. total/yr)

Units

Global Warming 7.16E+12 kg carbon dioxide equivalents

Primary Energy Consumption 3.52E+13

(1.20E+14)

kWh

(kBTU)

HH Criteria Air 2.24E+10 kg particulate matter 10 equivalents

(PM10 = particulate matter <10 microns)

HH Cancer 1.05E+04 comparative human toxicity units

Water Consumption 1.69E+14 L

Ecological Toxicity 3.82E+13 comparative ecotoxicity units

Eutrophication 1.01E+10 kg nitrogen equivalents

Land Use 7.32E+08

(1.81E+09)

hectare

(acre)

HH Noncancer 5.03E+05 comparative human toxicity units

Smog Formation 4.64E+11 kg ozone equivalents

Acidification 1.66E+12 moles hydrogen ion equivalents

Ozone Depletion 5.10E+07 kg CFC-11 equivalents (CFC-11 = 

trichlorofluoromethane)

Normalized BIRDS impact scores have powerful implications. By evaluating a building’s 

impacts with reference to their importance in a larger context, an impact to which one building

design contributes little will not appear important when, by comparison, competing designs 

contribute even less to that impact.

4.4 Life Cycle Interpretation

At the BIRDS LCA interpretation step, a building’s normalized impact scores are evaluated. The 

midpoint-level impact assessment yields scores for twelve impact categories, making 

interpretation at this level difficult. To enable comparisons across buildings, the scores across
52

impact categories may be synthesized. Note that in BIRDS, synthesis of impact scores is 

optional.

Impact scores may be synthesized by weighting each impact category by its relative importance 

to overall environmental performance, then computing the weighted average impact score. In the 

BIRDS software, the set of importance weights is selected by the user. Several alternative weight 

sets are provided as guidance, and may be either used directly or as a starting point for 

developing user-defined weights. The alternative weights sets are based on an EPA Science 

Advisory Board study, a BEES Stakeholder Panel’s structured judgments, a set of equal weights, 

and a set exclusively focusing on the global warming impact, representing a spectrum of ways in 

which people value diverse aspects of the environment.

4.4.1 EPA Science Advisory Board study

In 1990 and again in 2000, EPA’s Science Advisory Board (SAB) developed lists of the relative 

importance of various environmental impacts to help EPA best allocate its resources. (U.S. EPA 

1990, U.S. EPA 2000). The following criteria were used to develop the lists:

• The spatial scale of the impact

• The severity of the hazard

• The degree of exposure

• The penalty for being wrong

Ten of the twelve BIRDS impact categories were covered by the SAB lists of relative 

importance:

• Highest-Risk Problems: global warming, land use

• High-Risk Problems: ecological toxicity, human health (cancer and noncancer effects)

• Medium-Risk Problems: ozone depletion, smog, acidification, eutrophication, human 

health—criteria air pollutants

The SAB did not explicitly consider primary energy consumption or water consumption. For this 

exercise, these impacts are assumed to be relatively medium-risk and low-risk problems, 

respectively, based on other relative importance lists. (Levin 1996).

Verbal importance rankings, such as “highest risk,” may be translated into numerical importance 

weights by following ASTM International standard guidance for applying a Multiattribute 

Decision Analysis method known as the Analytic Hierarchy Process. (ASTM, 2011). The AHP 

methodology suggests the following numerical comparison scale:
53

1 Two impacts contribute equally to the objective (in this case environmental performance)

3 Experience and judgment slightly favor one impact over another

5 Experience and judgment strongly favor one impact over another

7 One impact is favored very strongly over another, its dominance demonstrated in practice

9 The evidence favoring one impact over another is of the highest possible order of 

affirmation

2, 4, 6, and 8 can be selected when compromise between values of 1, 3, 5, 7, and 9, is needed.

Through an AHP process known as pairwise comparison, numerical comparison values are 

assigned to each possible pair of environmental impacts. Relative importance weights can then 

be derived by computing the normalized eigenvector of the largest eigenvalue of the matrix of 

pairwise comparison values. Table 4-4 and Table 4-5 list the pairwise comparison values 

assigned to the verbal importance rankings, and the resulting SAB importance weights computed 

for the BIRDS impacts, respectively. Note that the pairwise comparison values were assigned 

through an iterative process based on NIST’s background and experience in applying the AHP 

technique. Furthermore, while the SAB evaluated cancer and noncancer effects as a group, the 

resulting 13 % weight was apportioned between the two based on the relative judgments of the 

BEES Stakeholder Panel discussed in the next section. 

Table 4-4. Pairwise Comparison Values for Deriving Impact Category Importance Weights

Verbal 

Importance 

Comparison

Pairwise 

Comparison 

Value

Highest vs. Low 6

Highest vs. Medium 3

Highest vs. High 1.5

High vs. Low 4

High vs. Medium 2

Medium vs. Low 2
54

Table 4-5. Relative Importance Weights based on Science Advisory Board Study

Impact Category Relative Importance 

Weight (%)

Global Warming 18

Primary Energy Consumption 7

HH Criteria Air 7

HH Cancer 8

Water Consumption 3

Ecological Toxicity 12

Eutrophication 5

Land Use 18

HH Noncancer 5

Smog Formation 7

Acidification 5

Ozone Depletion 5

4.4.2 BEES Stakeholder Panel judgments

While the derived EPA SAB-based weight set is helpful and offers expert guidance, several 

interpretations and assumptions were required in order to translate SAB findings into numerical 

weights for interpreting LCA-based analyses. A more direct approach to weight development 

would consider a closer match to the context of the application; that is, environmentally 

preferable purchasing in the United States based on life-cycle impact assessment results, as 

reported by BIRDS.

In order to develop such a weight set, NIST assembled a volunteer stakeholder panel that met at 

its facilities in Gaithersburg, Maryland, for a full day in May 2006. To convene the panel, 

invitations were sent to individuals representing one of three “voting interests:” producers (e.g., 

building product manufacturers), users (e.g., green building designers), and LCA experts. 

Nineteen individuals participated in the panel: seven producers, seven users, and five LCA 

experts. These “voting interests” were adapted from the groupings ASTM International employs 

for developing voluntary standards, in order to promote balance and support a consensus process.

The BEES Stakeholder Panel was led by Dr. Ernest Forman, founder of the AHP firm Expert 

Choice Inc. Dr. Forman facilitated panelists in weighting the BEES impact categories using the 

AHP pairwise comparison process. The panel weighted all impacts in the Short Term (0 years to 

10 years), Medium Term (10 years to 100 years), and Long Term (>100 years). One year’s worth 

of U.S. flows for each pair of impacts was compared, with respect to their contributions to 

environmental performance. For example, for an impact comparison over the Long Term, the 

panel was evaluating the effect that this year’s U.S. emissions would have more than 100 years 

hence.

Once the panel pairwise-compared impacts for the three time horizons, its judgments were 

synthesized across these time horizons. Note that when synthesizing judgments across voting 
55

interests and time horizons, all panelists were assigned equal importance, while the short, 

medium, and long-term time horizons were assigned by the panel to carry 24 %, 31 %, and 45 % 

of the weight, respectively.

The environmental impact importance weights developed through application of the AHP 

technique at the facilitated BEES Stakeholder Panel event are shown in Table 4-6. These weights 

reflect a synthesis of panelists’ perspectives across all combinations of stakeholder voting 

interest and time horizon. The weight set draws on each panelist’s personal and professional 

understanding of, and value attributed to, each impact category. While the synthesized weight set 

may not equally satisfy each panelist’s view of impact importance, it does reflect contemporary 

values in applying LCA to real world decisions. This synthesized BEES Stakeholder Panel 

weight set is offered as an option in BIRDS online.

The panel’s application of the AHP process to derive environmental impact importance weights 

is documented in an appendix to ASTM Standard E1765-11 and in Gloria et al. 2007. 

Table 4-6. Relative Importance Weights based on BEES Stakeholder Panel Judgments

Impact Category Relative 

Importance 

Weight (%) 

Global Warming 29.9

Primary Energy Consumption 10.3

HH Criteria Air 9.3

HH Cancer 8.2

Water Consumption 8.2

Ecological Toxicity 7.2

Eutrophication 6.2

Land Use 6.2

HH Noncancer 5.2

Smog Formation 4.1

Acidification 3.1

Ozone Depletion 2.1

Note: Since BIRDS does not currently include an Indoor Air Quality impact category, its 3 % BEES 

Stakeholder Panel weight has been redistributed among the remaining 12 impacts.

The three figures below display in graphical form the BEES Stakeholder Panel weights used in 

BIRDS. Figure 4-3 displays the synthesized weight set, Figure 4-4 the weights specific to 

panelist voting interest, and Figure 4-5 the weights specific to time horizon. The BIRDS user is 

free to interpret results using either of the weight sets displayed in Figure 4-4 and Figure 4-5 by 

entering them as a user-defined weight set.
56

Figure 4-3. BEES Stakeholder Panel Importance Weights Synthesized across Voting 

Interest and Time Horizon

0%

10%

20%

30%

40%

50%

Producers

Users

LCA Experts

Figure 4-4. BEES Stakeholder Panel Importance Weights by Stakeholder Voting Interest

0%

5%

10%

15%

20%

25%

30%

35%

Impact Category
57

Figure 4-5. BEES Stakeholder Panel Importance Weights by Time Horizon

4.5 BIRDS Energy Technologies

Since buildings have very long lives, operating energy efficiency has an important influence on 

their sustainability performance. Energy efficiency is largely driven by a building’s energy 

technologies, but top-down inventory data are not readily available at this level of resolution. 

Therefore, BIRDS includes detailed life cycle inventory data for a range of energy technology 

packages that have been compiled at the traditional, bottom-up LCA level. These energy 

technology packages are used to meet the 5 levels of energy efficiency simulated for each of 11 

building types in 228 different U.S. locations. The bottom-up BIRDS data were developed under 

contract to NIST by Four Elements Consulting, LLC, of Seattle, Washington. Energy 

technologies include wall and roof insulation, windows, HVAC systems, overhangs, and 

daylighting.6

 

6 Besides daylighting, the “Low Energy Case” building design decreases lighting density by first increasing the 

efficiency of the lighting system and then decreasing the number of fixtures in the lighting system. These actions are 

thought to qualitatively offset one another and so are not included in the life-cycle inventory analysis in this first 

version of BIRDS.
58

4.5.1 General Information Regarding the Energy Technology LCIs

Standards Used

The LCAs in BIRDS have been built based on the principles and framework in the International 

Organization for Standardization (ISO) 14040 (2006) and the guidelines specified in ISO 14044 

(2006). 

Primary and Secondary Data Sources 

Both primary data (collected directly from a manufacturing facility) and secondary data 

(publicly-available literature sources) can be used to build LCAs, and it is common to see a 

combination of both data types, based on data availability. Sources of data on the energy 

technologies in BIRDS vary from one category to the next, and within categories themselves for 

the different products. Data were based on:

 Primary data from a group of companies and/or an industry association, compiled into an 

industry average product; 

 Primary data on a product provided by one company;

 Secondary data that represent an average or typical product; and

 Secondary data that represent one product in a category.

For optimal data quality of an LCA, the preference is to have the most representative data –

temporally, technologically, and geographically – on a product or system, so that the model 

produced most closely represents the product. But this is often not possible to achieve due to 

data availability constraints. It is also not always possible to have a data set that represents an 

entire category of products. For example, high quality, current, company-specific data might be 

collected and used to build the LCA for a given product. Likewise, data for another product 

might be compiled from literature sources due to lack of other available data. In both cases, the 

LCI profiles may be used to represent the full product category, even though they may not be 

representative of all products within the category, based on market share, technology, 

geographical source, etc. As a result, the reader should be aware of this limitation. 

Data Sources Used for the Background Data 

Secondary data have been applied to production of material inputs, production and combustion 

of fuels used for process energy, and transportation processes. The U.S. LCI Database (NREL, 

2005-present, hereinafter referred to as “U.S. LCI Database”) and the ecoinvent Data v.2.2 

database (ecoinvent, 2007) are the main sources of background data throughout the various life 

cycle stages. Other sources of data are used where data were not available from U.S. LCI 

Database or ecoinvent, and/or where they were deemed to be of better quality than these latter 

sources. 

The following subsections describe modeling, assumptions, and data sources of the product life 

cycle data. Data for the production of material inputs for each product are described in the 
59

subchapters since these may vary for different industries. The following data aspects are 

consistent for all products except where noted differently in the text:

 All energy production, including production of fuels and conversion into energy and 

electricity production come from the U.S. LCI Database. 

 All transportation data come from the U.S. LCI Database. 

 Where ecoinvent or other non-North American data sets were used, they were customized 

into North American processes by switching out foreign energy, electricity, 

transportation, and other processes for comparable North American based data sets from 

the U.S. LCI databases. Exceptions to this are noted.

4.5.2 Wall and Roof Insulation

The insulation categories considered for the commercial building walls and roof are presented in 

the tables below along with the R-values needed to meet the necessary thickness of insulation 

products to meet the requirements of the building design (e.g., edition of ASHRAE 90.1 or LEC). 

Characteristics of each insulation type, including density and R-values (

  

 

per cm or 

  

 

per inch) are presented in the specific products’ subsections.

Table 4-7 Specified Insulation Types and R-Values – Wall Application

Wall Insulation type R-value specified by NIST

per-cm (per-inch)

Kraft faced fiberglass blanket 4.33 (11.00)

Kraft faced fiberglass blanket 5.12 (13.00)

Kraft faced fiberglass blanket 5.91 (15.00)

Kraft faced fiberglass + polyiso foam board 7.44 (18.90)

Kraft faced fiberglass + polyiso foam board 7.68 (19.50)

Kraft faced fiberglass + polyiso foam board 8.03 (20.40)

Kraft faced fiberglass + XPS foam board 9.84 (25.00)

Kraft faced fiberglass + XPS foam board 11.81 (30.00)

Kraft faced fiberglass + XPS foam board 13.78 (35.00)
60

Table 4-8 Specified Insulation Types and R-Values – Roof Application

Roof Insulation type R-value specified by NIST

per-cm (per-inch)

EPS with perlite 4.12 (10.47)

XPS foam board 5.91 (15.00)

XPS foam board 7.87 (20.00)

XPS foam board 9.84 (25.00)

XPS foam board 11.81 (30.00)

XPS foam board 13.78 (35.00)

XPS foam board 15.75 (40.00)

XPS foam board 17.72 (45.00)

XPS foam board 19.69 (50.00)

XPS foam board 21.65 (55.00)

XPS foam board 23.62 (60.00)

Polyiso foam board 2.01 (5.10)

Polyiso foam board 2.81 (7.14)

Polyiso foam board 4.28 (10.87)

Polyiso foam board 5.63 (14.29)

Polyiso foam board 6.56 (16.67)

Polyiso foam board 8.56 (21.74)

Polyiso foam board 9.84 (25.00)

BIRDS performance data for the insulation category was provided on the basis of 0.09 m2(1 ft2) 

of the specified R-value of insulation, which was then multiplied by the needed amount of square 

area for each building. The flow diagram below presents the general system boundaries for the 

insulation category, as it is modeled for BIRDS. 
61

Figure 4-6 Insulation System Boundaries – Fiberglass Blanket Example 

The modeling and assumptions for each type of insulation are presented below. 

Fiberglass Blanket 

Thermal efficiencies of R-11, R-13, and R-15 are used for wall insulation. R-15 is also used in 

the wall with polyisocyanurate and extruded polystyrene (XPS) foam boards. The table below 

specifies fiberglass insulation by type and R-value:

Table 4-9 Fiberglass Blanket Mass by Application 

Application Thickness 

cm (in)

Density 

kg/m3(lb/ft3)

Mass per Functional Unit 

kg/m2(oz/ft2)

Wall--R-11 8.9 (3.5) 12.1 (0.76) 1.07 (3.52)

Wall--R-13 8.9 (3.5) 12.1 (0.76) 1.07 (3.52)

Wall--R-15 8.9 (3.5) 22.6 (1.41) 2.01 (6.58)

Upstream Materials Production through Manufacturing

Fiberglass insulation is made with a blend of sand, limestone, soda ash, and recycled glass cullet. 

Recycled window, automotive, or bottle glass is increasingly used in the manufacture of glass 

fiber, and it accounts for 30 % to 50 % of the raw material input. The recycled content is limited 

by the amount of usable recycled material available in the market – not all glass cullet is of 

sufficient quality to be used in the glass fiber manufacturing process. The use of recycled 

material has helped to steadily reduce the energy required to produce insulation products. The 

raw materials used to produce fiberglass insulation are broken down by the glass and facing 

contents, shown in Table 4-10.

Use Phase EOL (landfilling)

Fiberglass Blanket 

assembly

Glass fiber 

production 

Facing 

production

Raw Materials 

Production

Transport to building site

Process 

Energy

Process aids

Emissions to air, 

water, soil

Raw Materials 

Production

Production

Transport 

to manuf.

Transport 

to manuf.
62

Table 4-10 Fiberglass Insulation Constituents

Glass Constituent Mass Fraction (%)

Soda Ash 9

Borax 12

Glass Cullet 34

Limestone 9

Phenolic resin (binder coating) 5

Sand 31

Facing Mass Fraction (%)

Kraft paper 25

Asphalt 75

The production data for the soda ash, limestone, and phenol formaldehyde resin come from the 

U.S. LCI Database. The borax, glass cullet, and silica sand come from ecoinvent. For the 

facing, Kraft paper comes from ecoinvent and the asphalt comes from U.S. LCI Database. 

The raw materials are transported to the manufacturing plant via diesel truck. Materials are 

sourced domestically, and transportation distances range on average from 161 km (100 mi) to 

805 km (500 mi).

The energy requirements for melting the glass constituents into fibers and drying of the 

completed blanket involve use of natural gas and electricity, shown in the following Table.

Table 4-11 Energy Requirements for Fiberglass Insulation Manufacturing

Energy Carrier MJ/kg (Btu/lb)

Natural Gas 1.99 (857)

Electricity 1.37 (591)

Total 3.36 (1 448)

Besides combustion emissions from fuel usage at manufacturing, additional emissions are listed 

in the Table below.

Table 4-12 Non Fuel Combustion-Related Emissions for Fiberglass Insulation 

Manufacturing

Emission Bonded Blankets g/kg (lb/ton)

Particulates 2.380 (4.759)

VOC 0.759 (1.518)
63

All waste produced during the cutting and blending process is either recycled into other 

insulation materials or added back into the glass mix. Thus, no solid waste is assumed to be 

generated during the production process.

Transportation to the Building Site through End of Life

Transportation of the insulation to the building site is modeled by an assumed average of 805 km 

(500 mi) by heavy-duty diesel-fueled truck. 

Installing fiberglass blanket insulation is primarily a manual process; no energy or emissions are 

included in the model for this. During installation, any waste material is added into the building 

shell where the insulation is installed - there is effectively no installation waste. 

Fiberglass insulation has a functional lifetime of over 50 years so no replacement is needed 

during the 40 year study period. How this product affects operating energy during the prototype 

buildings’ use phase is addressed in other sections of this report. 

While fiberglass insulation is recyclable, it is assumed that it is disposed of in a landfill at end of 

life. End-of-life modeling includes transportation by heavy-duty diesel-fuel powered truck 

approximately 80 km (50 mi) to a construction & demolition (C&D) landfill. Insulation in a 

landfill is modeled based on ecoinvent end of life waste management process data. 

EPS Foam Insulation

Expanded polystyrene foam is rigid board stock used to provide wall, ceiling, roof, foundation 

perimeter and sub-slab insulation. EPS is also used in construction application systems such as 

exterior insulation finishes (EIFS), insulating concrete forms (ICF), and structural insulated 

panels (SIP). These applications combine EPS foam with a stucco finish, a poured concrete core 

or OSB or metal skins over an EPS core.

ASTM C-578 recognizes EPS foam as Type I, II, VIII, IX, XI, XIV, and XV. Densities of the 

various Types range from 11 kg/m3to 48 kg/m3(0.7 lb/ft3to 3.0 lb/ft3) and R-values range from 

1.22 per cm to 1.69 per cm (3.1 per inch to 4.3 per inch). Types I, VIII, II, and IX are the 

predominant types used for construction applications and deliver R values of at least (1.42, 1.50, 

1.57, and 1.65) per cm ((3.6, 3.8, 4.0 and 4.2) per inch) at densities of (14.4, 18.4, 21.6, and 28.8)

kg/m3((0.90, 1.15, 1.35 and 1.80) lb/ft3), respectively. 

Upstream Materials Production through Manufacturing

Cradle-to-gate data on production through manufacturing is based on a 2009 study by Franklin 

Associates, A Division of ERG (Eastern Research Group) for the EPS Molders Association 

(Franklin, 2009). The scope of this study included collecting 2008 production data from 10 

manufacturing facilities in the U.S. and Canada and compiling it into an industry average EPS 

foam board. The resulting cradle-to-gate unit process data has been published in U.S. LCI 
64

Database. The following table presents the raw material inputs associated with the production of 

EPS insulation board (NREL 2005-present). 

Table 4-13 EPS Foam Board Raw Materials

Raw Material Input kg/kg foam (lb/lb foam) 

Ethylbenzene/styrene 1.01 (1.01)

Processed natural gas 0.043 (0.043)

Petroleum 0.029 (0.029)

Production data for all inputs come from the U.S. LCI Database. Other inputs may be present in 

smaller quantities, and these may include flame retardant and/or other additives. No data were 

provided on these. The raw materials are transported to the manufacturing plant via diesel truck 

or pipeline. Materials are sourced domestically, and transportation distances range on average 

from 161 km (100 mi) to 805 km (500 mi).

The next table presents the manufacturing energy, air emissions, and solid waste data associated 

with production of EPS insulation board (NREL 2005-present). 

Table 4-14 EPS Foam Board Manufacturing Energy and Outputs 

Manufacturing Energy Unit Quantity/kg foam Unit Quantity/lb foam

Electricity from grid kWh 0.79 kWh 0.36

LPG in industrial boiler L 2.00 E-03 gal 2.40 E-04

Natural gas in industrial boiler m3 0.28 ft3 4.49

Outputs to air

Carbon dioxide, fossil kg 3.90E-03 lb 3.90E-03

Carbon monoxide, fossil kg 2.10E-05 lb 2.10E-05

HFCs and HCFCs, unspecified kg 1.10E-06 lb 1.10E-06

Nitrogen oxides kg 4.60E-05 lb 4.60E-05

NMVOC, non-methane volatile organic 

compounds kg

1.30E-04 lb 1.30E-04

Organic substances, unspecified kg 1.10E-05 lb 1.10E-05

Particulates, unspecified kg 3.20E-05 lb 3.20E-05

Pentane kg 4.10E-02 lb 4.10E-02

Styrene kg 2.20E-04 lb 2.20E-04

Sulfur oxides kg 3.60E-07 lb 3.60E-07

Solid waste

Solid waste to incineration with energy recovery kg 1.70E-03 lb 1.70E-03

Solid waste to incineration without energy 

recovery kg

1.80E-05 lb 1.80E-05

Solid waste to sanitary landfill kg 2.10E-02 lb 2.10E-02
65

Regarding the pentane release, according to a document by the European Manufacturers of 

Expanded Polystyrene (EUMEPS, 2002), pentane is unstable and decomposes in the atmosphere 

into carbon dioxide and water within a few hours. Thus, all pentane, other than pentane captured 

and destroyed by onsite emission controls in place at many manufacturers, is assumed to be 

released at the manufacturing stage. This is consistent with Franklin (2009).

The solid waste is modeled as going to the landfill, incinerator, or WTE facility using ecoinvent 

data sets on waste management.

Transportation to the Building Site through End of Life

According to Franklin (2009), transportation of EPS to the building site is modeled to be an 

average of 483 km (300 mi) by heavy-duty diesel-fueled truck. 

EPS is installed with an installation tape, but it is excluded since the tape makes up less than 1 % 

by weight so may be considered negligible. Pentane release at installation is considered 

negligible. Scrap EPS generated at installation is assumed to be 2 % of the total, consistent with 

other foam products in this category. While the product may be recyclable, it is modeled as 

being sent to a landfill 32 km (20 mi) from the building site. Data for the landfill come from 

waste management datasets in ecoinvent. 

EPS foam board has a functional lifetime of over 40 years so no replacement is needed during 

the 40 year study period. How insulation in the buildings affects operating energy during the 

prototype buildings’ use phase is addressed in other sections of this report. 

While EPS foam is recyclable, it is assumed that it is disposed of in a landfill at end of life. 

End-of-life modeling includes transportation by heavy-duty diesel-fuel powered truck 

approximately 80 km (50 mi) to a C&D landfill. Insulation in a landfill is modeled based on 

ecoinvent end of life waste management process data. 

Industry contact: 

Walter A. Reiter, III, Esq., EPS Industry Alliance (2013)
66

XPS Foam Insulation

XPS foam insulation has been modeled for the exterior wall and roofing applications. Type IV 

XPS products used for roofing and commercial wall applications have a typical average density 

of 26.2 kg/m3 (1.63 lb/ft3). The following R-values are used in this study:7

 2.5 cm (1 in): R = 5.0 

 5.1 cm (2 in): R = 10.6 

 7.6 cm (3 in): R = 16.2

 10.2 cm (4 in): R = 22.0

Upstream Materials Production through Manufacturing

XPSA member companies provided representative industry average production data on XPS 

foam boards. XPSA represents the three largest producers in North America and accounts for 

over 95 % of XPS products produced and sold. The following table provides a 2010 

representative average of the raw material and processing energy inputs and process outputs to 

produce one kg XPS foam board. 

Table 4-15 XPS Foam Board Production Data 

Inputs Quantity/kg (Quantity/lb)

Blowing agents HFC-134a kg (lb) 0.060 (0. 060)

HFC-152a kg (lb) 0.017 (0. 017)

CO2 kg (lb) 0.012 (0.012)

Solid additives PS resin kg (lb) 0.907 (0. 907)

Additives kg (lb) 0.018 (0. 018)

Energy Electricity kWh 1.00 (0.454)

Outputs

Air HFC-134a kg (lb) 0.0105 (0. 0105)

HFC-152a kg (lb) 0.0029 (0.0029)

Waste Waste kg (lb) 1.0 E-4 (1.0 E-4)

The table presents the current representative blowing agent usage. It should be noted that HFCs 

began to replace HCFC-142b as the principal blowing agent in 2009, as the industry complied 

with U.S. EPA and Environment Canada ODS phase-out regulations requiring the XPS sector to 

exit HCFC use by the end of 2009. By 2010, all XPSA members had converted to non-HCFC 

blowing agents and have been using only HFC materials ever since.

The additives in the table include the flame retardant widely used in all XPS/EPS foams 

(hexabromocyclododecane (HBCD)) and colorants or dyes/pigments used to produce the 

characteristic color of each XPSA member’s foam. Additives may also include a nucleation 

control agent, process lubricant, acid scavenger, or others.

 

7 Extruded Polystyrene Foam Association (XPSA) website. http://www.xpsa.com. Values are based on a roundrobin study in 2003 using the CAN/ULC S770-00 LTTR standard.
67

The blowing agent conversion/trim losses during manufacturing are assumed to be on average 

17.5 % for North American XPS foam production (IPCC/TEAP, 2005, Table 7.7). All of the PS 

trim waste at the manufacturing plant is reused internally in the process. Only a very small 

amount of foam and other materials are occasionally sent off-site for disposal in a landfill. 

Raw Materials Production

Data for polystyrene come from the U.S. LCI Database. Data for all three blowing agents and 

some of the additives come from ecoinvent. Data were not available for all of the additives; 

where data were not available proxy data were used. 

All the raw materials are produced in the U.S., and most of the raw materials are centrally 

located as are the XPS manufacturer's largest plants. The estimated weighted average distance 

from the main suppliers to the majority of XPS manufacturing plants are 805 km (500 mi) for 

polystyrene, HFC-134a, flame retardant, and CO2. HFC-152a and other additives are transported 

an average distance of 1609 km (1000 mi) to manufacturing plants. All but the blowing agents 

and polystyrene are transported by diesel truck; the blowing agents and polystyrene are 

transported by rail.

Transportation to the Building Site through End of Life

Transportation of the insulation to the building site is modeled as 563 km (350 mi), an average 

factoring in the various plants around the U.S. Transportation is by heavy-duty (combination) 

diesel-fueled truck.

Foam boards are installed with installation tape but tape is excluded since it is considered 

negligible. Scrap XPS foam board generated at installation is assumed to be 2 % of the total, 

consistent with other foam products in this category. While the product may be recyclable, it is 

modeled as being sent to a landfill 32 km (20 mi) from the building site. Data for the landfill 

come from waste management datasets in ecoinvent. Blowing agent escape during installation is 

insignificant. Minimal cutting to size on the jobsite is done and, even then, a sharp tool is 

typically used so that very few cells are opened.

XPS insulation has a functional lifetime of over 40 years so no replacement is needed during the 

40 year study period. How insulation in the buildings affects operating energy during the 

prototype buildings’ use phase is addressed in other sections of this report. 

The diffusion of HFC-134a from XPS during use is 0.75 % +/-0.25 % per year (IPCC/TEAP, 

2005, Table 7.7). The blowing agent emission loss during the use phase is complex and nonlinear but can be represented for simplicity as a linear function after the first year. The rate is a 

function of the product thickness, properties (density, cell size, skins), blowing agent type(s) and 

transport properties (solubility, diffusion coefficient), and the installed application details (mean 

temperature, permeability of applied facings). The diffusion rate of HFC-152a is 15 % per year 

(IPCC/TEAP, 2005, Table 7.7). 
68

Reuse of the foam is possible after building decommissioning, but the model assumes that at end 

of life the foam is disposed of in a landfill. End-of-life modeling includes transportation by 

heavy-duty diesel-fuel powered truck approximately 80 km (50 mi) to a C&D landfill. 

Insulation in a landfill is modeled based on ecoinvent end of life waste management process 

data. 

For a typical NA building demolition followed by disposal in a landfill, it is reasonable to 

assume an initial blowing agent end of life loss of 20 % followed by annual losses of 1 % 

(UNEP/TEAP, 2005, Table 4.2).

Industry contact:

Comments and data provided by XPSA member companies and compiled by John Mutton, 

consultant to XPSA. 

Polyisocyanurate (Polyiso) Foam Insulation

Polyiso foam insulation has been modeled for the exterior wall and roofing applications. The 

thermal resistance value for wall polyiso board is 2.9 

 

 

per cm (6.5 

 

 

per inch), and for 

the roof it is 2.7 

 

 

per cm (6.1 

 

 

per inch); the difference is due to the impermeable 

wall board facer vs. the permeable roof board facer. These R values are based on a 6-month 

accelerated aging test and were provided by representatives at Bayer MaterialScience.8 The 

foam has a wet, or pre-yield, density of 29.2 kg/m3(1.82 lb/ft3). The final product, which 

includes the weight of the facers, has a nominal density of 32.0 kg/m3(2.0 lb/ft3).

Upstream Materials Production through Manufacturing

Upstream Materials Production

Cradle-to-gate data on production through manufacturing is based on a 2010 study performed for 

the Polyisocyanurate Insulation Manufacturers Association (PIMA) (Bayer MaterialScience, 

2010). The scope of this study included collecting and compiling primarily 2007 production data 

from the six PIMA member companies and compiling it into an industry average polyiso 

insulation board. Process energy data came from 29 out of 31 polyiso plants in the U.S. and 

Canada, representing approximately 94 % of production in those geographies. 

The chemicals to produce polyiso foam make up an “A” side (MDI) and a “B” side (polyester 

polyol with various additives such as catalysts, surfactants and flame retardants) plus a blowing 

agent (pentane). The table below presents the raw material inputs associated with polyiso foam 

production, provided on the basis of 2.54 cm (1 in) in Bayer MaterialScience (2010, Sec. 7.2).9 

 

8 Verbal communication with Bayer MaterialScience representatives, July 2013.

9 The polyiso report presents corresponding values based on 6.2 cm (2.45 in) foam, the thickness used in the 

Polyiso LCA. 
69

Table 4-16 Raw Material Inputs to Produce Polyiso Foam 

Inputs:

% in foam 

(wt)

kg per 0.09 m2, 

2.54 cm thick

lb per 1 ft2, 

1 in thick

MDI 55.5 0.0382 0.0842

Polyester Polyol 31 0.0213 0.0470

TCPP 3.4 0.0023 0.0051

Catalyst K15 1.4 0.0010 0.0022

Catalyst PC46 0.16 1.38 E-04 0.0003

Catalyst PV 0.08 6.90 E-05 0.0002

Surfactant 0.63 5.51 E-04 0.0012

Pentane (blowing agent) 7.5 0.0052 0.0115

process water 0.1 0.0001 0.0002

The MDI comes from the U.S. LCI Database. Data for the polyester polyol comes from a 2010 

Eco-Profile study of Aromatic Polyester Polyols (PE International, 2010). Data for Tris(2-

chloroisopropyl)phosphate (TCPP) are U.S. data compiled from literature sources (PE 

International, 2011). Pentane data come from ecoinvent. No data were available to include the 

three catalysts or silicone surfactant; they total 2.3 % of the total input, so a total of 97.7 % of 

the inputs were included in the model. 

There are two types of facers for polyiso foam insulation. Glass reinforced facer (GRF) is 

normally used in roofing applications and aluminum Kraft paper (foil) is normally used in wall 

applications. The GRF weighs 0.254 kg/m2(0.052 lb/ft2) per layer, and 2 layers are used per 

foam board (totaling up to 13 cm or 5 in). The following table provides material and production 

energy for the GRF. The energy data come from an earlier version of the Polyiso LCA (Phelan, 

2008), and materials and quantities have been compiled based on data from an MSDS (Atlas 

Roofing Corporation, 2008). 
70

Table 4-17 GRF Process Inputs and Outputs 

Energy and Material Inputs per 1 kg (per 2.2 lb):

Corrugated cardboard and mixed fiber kg (lb) 0.89 (1.96)note 1

Glass fiber kg (lb) 0.10 (0.22)

Carbon black kg (lb) 0.01 (0.02)

Electricity MJ (Btu) 1.43 (1 355)

Nat gas MJ (Btu) 9.08 (8 606)

Propane MJ (Btu) 0.023 (21.8)

Outputs:

Waste kg (lb) 0.027 (0.06)

Note: the MSDS says 85 % comes from corrugated cardboard and 

mixed fiber, but 89 % are modeled to close the mass balance

According to Bayer MaterialScience (2010), 100 % of the fiber and glass (old corrugated 

cardboard, mixed paper, waste glass) are recycled materials, so their embodied contribution is 

burden-free. However, the energy to transport these materials to the facer manufacturing plant 

was included. Data for carbon black come from ecoinvent. 

For the wall application, the foil facer raw materials include paper, aluminum foil, adhesives and 

coatings, and has a mass of 0.098 kg/m2(0.02 lb/ft2) (Phelan, 2008). Data on material 

composition come from an MSDS; based on this limited data source, the facer is modeled as 

77 % foil and 23 % Kraft (Atlas Roofing Corporation, 2012). Data for foil is modeled as 50/50 

primary and secondary aluminum from the U.S. LCI Database, plus sheet rolling (ecoinvent). 

Data for Kraft paper come from ecoinvent.

Manufacturing

According to the Polyiso LCA, polyiso plants consume primarily electricity and natural gas used 

to operate the laminator and associated operations support equipment, such as thermal oxidizers, 

storage areas, packaging machines, raw material pumps, offices etc. A small amount of propane 

is used for fork lift trucks. The following table presents energy inputs and process outputs to 

produce 1 board-foot of foam, or 0.09 m2(1 ft2) of 2.54 cm (1 in) thick polyiso foam.
71

Table 4-18 Energy Inputs and Process Outputs for 1 Board-Foot Polyiso Foam 

Energy inputs Unit Quantity

Electricity MJ (kWh) 0.0497 (0.0138)

Nat gas MJ (Btu) 0.0913 (86.55)

Propane kg (lb) 0.00015 (0.00031)

Outputs Unit Quantity

Pentane to air kg (lb) 0.00013 (0.00030)

Waste scrap board-foot 0.01

Based on review with polyiso plant manufacturers, approximately 2.5 % of the pentane added to

the foam is lost to air during manufacturing. Depending on the plant and local regulatory 

requirements, pentane is emitted directly to the atmosphere or to a thermal oxidizer for 

combustion. Only 13 plants out of 31 use thermal oxidizers to combust the pentane emissions. 

Since the majority of polyiso plants in North America do not use thermal oxidizers, the pentane 

is modeled as going directly to atmosphere (Bayer MaterialScience, 2010).

Transportation and disposal of manufacturing waste scrap was modeled as going to an industrial 

landfill. It is assumed that a landfill for such non-hazardous waste is within 32 km (20 mi) of the 

polyiso plant.

Raw materials are transported to the manufacturing plant via diesel truck or rail. The following 

distances and modes of transport were modeled: 

 MDI: 2 414 km (1 500 mi) by rail; 

 Polyester polyol: 1 384 km (860 mi) by rail (90 %), 1 384 km (860 mi) by truck (10 %);

 Pentane: 2 414 km (1 500 mi) by truck; 

 Remaining materials: 1 609 km (1 000 mi) by truck.

Transportation to the Building Site through End of Life

According to Bayer MaterialScience (2010), transportation to the building site is modeled as 400 

km (250 mi) by heavy-duty (combination) diesel truck. 

Installation tape is used but is excluded since it is considered negligible. Scrap polyiso generated 

at installation is assumed to be 2 % of the total, consistent with other foam products in this 

category. While the product may be recyclable, it is modeled as being sent to a landfill 32 km 

(20 mi) from the building site. Data for the landfill come from waste management datasets in 

ecoinvent. Pentane release at installation is negligible.

Polyiso insulation has a functional lifetime of over 40 years so no replacement is needed during 

the 40 year study period. How insulation in the buildings affects operating energy during the 

prototype buildings’ use phase is addressed in other sections of this report. 
72

Polyiso insulation is modeled as disposed of in a landfill at end of life. End-of-life modeling 

includes transportation by heavy-duty diesel-fuel powered truck approximately 80 km (50 mi) to 

a C&D landfill. Insulation in a landfill is modeled based on ecoinvent end of life waste 

management process data. According to Bayer MaterialScience (2010), 50 % of the total 

pentane in the product will have been released by end of life and 50 % remains in the product. 

Roof Cover Boards

While a cover board may not be absolutely necessary, it is generally recommended to use over 

foam insulation as it creates a more durable roof system and better protects the underlying 

insulation board. As specified in RS Means for this study, perlite roof insulation was modeled in 

conjunction with the EPS; the function of which is to insulate in addition to being a protective 

covering. While these may legitimately still be used together, perlite is no longer commonly 

used in this application, according to industry experts. Gypsum/fiberglass products are more 

commonly used. DensDeck is one such product, and primary data were provided for this. Both 

perlite insulation and DensDeck are discussed below. Perlite is modeled only with the EPS 

while DensDeck is modeled with the XPS, and polyiso systems. DensDeck is modeled with EPS 

as an alternative scenario. 

Perlite

Perlite roof insulation board is composed of expanded perlite particles, cellulose fibers, and 

binders. A one-inch board of perlite, with an R-value of 0.5 

 

 

per cm (2.78 

 

 

per inch), 

is modeled with the EPS foam board. Perlite’s density is 144 kg/m3(9 lb/ft

3

) (GAF Materials 

Corporation, 2010). The table below presents the bill of materials in a perlite board. Data were 

compiled based on information from two MSDS’s (GAF Materials Corporation, 2008; Johns 

Manville, 2010) so these estimated figures make more of a theoretical average. 

Table 4-19 Perlite Board Bill of Materials 

Materials % (w/w)

Perlite (expanded) 68

Cellulose fiber 25

Asphalt, oxidized 5

Starch 2

Data for perlite come from ecoinvent. GAF, one perlite board manufacturer, states that 

minimum recycled content of its product is 25 %, so the cellulose fiber is modeled as postconsumer recycled paper. Data for the waste paper include transportation to a recycled paper 

processing facility and treatment (e.g., sorting). Data for asphalt come from the U.S. LCI 

Database. For starch, a potato starch data set from a Danish food LCA database is used 

(LCAFood database). 
73

The raw materials are modeled as transported to the manufacturing plant via combination diesel 

truck. Materials are assumed to be sourced domestically; it is assumed the average 

transportation distance is 805 km (500 mi).

Generally, perlite board may be made by expanding the perlite, adding a tacky resin emulsion to 

the perlite, drying the mixture and forming it into a board-like product (Nath, 1982). The 

ecoinvent data set for perlite includes processing of perlite, so this is included in the model. 

Additionally, some of data for manufacturing particle board were used as proxy manufacturing 

data since the processes have similarities (Wilson, 2008).

Transportation of the final product to the building site is modeled as 1 609 km (1 000 mi) by 

heavy-duty diesel-fueled truck. 

At end of life, it is assumed that it is disposed of in a landfill. End-of-life modeling includes 

transportation by heavy-duty diesel-fuel powered truck approximately 80 km (50 mi) to a C&D 

landfill. The product in a landfill is modeled based on ecoinvent end of life waste management 

process data. 

Gypsum/Fiberglass Coverboard

DensDeck is a fiberglass mat-faced, treated gypsum core panel. A 0.64 cm (0.25 in) DensDeck 

product has been modeled in all the foam insulation board systems. The main bill of materials 

for DensDeck is presented in the table below. The full bill of materials was provided by Georgia 

Pacific for use in this specific project but these data are not presented to protect confidentiality. 

The table therefore contains data from a Georgia Pacific MSDS (2009). 

Table 4-20 DensDeck Bill of Materials 

Materials % Comments

Gypsum 60 % to 100 % 95 * The MSDS says the gypsum contains naturally occurring silica 

crystalline (quartz), in the amount of 0.1 % to 1 % of total product

Continuous filament GF: 1 % to 5 % 5

Both gypsum and glass fiber are modeled based on ecoinvent data sets. Materials to manufacture 

DensDeck come from domestic and foreign sources. For the domestic transportation, a distance 

of 805 km (500 mi) by heavy-duty diesel truck was assumed. For foreign sources, an average of 

2 414 km (1 500 mi) by barge has been assumed. Actual distances were provided and modeled 

for this project but these data are not presented to protect confidentiality. 

Transportation of the final product to the building sites is done by truck (95 %) and rail (5 %). 

Due to the several Georgia Pacific plants producing DensDeck, an average of 402 km (250 mi) 

by truck and 1 127 km (700 mi) by rail has been modeled. 
74

At end of life, it is assumed that it is disposed of in a landfill. End-of-life modeling includes 

transportation by heavy-duty diesel-fuel powered truck approximately 80 km (50 mi) to a C&D 

landfill. Insulation in a landfill is modeled based on ecoinvent end of life waste management 

process data. 

4.5.3 Windows 

Introduction 

BIRDS evaluates aluminum single- and double-pane windows and double- and triple-pane 

windows with thermal breaks, as shown in the table below. Not shown in the table are fiberglass 

and wood-PVC composite frame operable windows which are used for some of the high energy 

efficient applications in BIRDS. Also not included in the table are low-emissivity (low-E) 

coating, tint, and reflective coatings, which were modeled as part of the window systems in order 

to meet the windows’ U-factor, solar heat gain coefficient (SHGC), and visible transmittance 

(VT) performance requirements for each particular climate zone and code edition. 

Table 4-21 Window Types in BIRDS 

Type of Building

Window 

Type

Frame Type(s) and # 

Panes

Area

Window to Wall 

Ratio (WWR)

4-story & 6-story apt 

buildings, 4-story & 6-

story dorms 

Operable 

sliding 

windows

Al frame - single pane 152 cm (5 ft) 

by 91 cm (3 

ft)

4-story apt building 

= 12 %; 6-story apt 

building = 14 %; 4-

story & 6-story 

dorms = 20 %

Al frame - double pane

Thermo-break Al frame -

double pane

Elementary school, 8-

story office building, 3-

story office building, 

high school

Punched 

opening, 

fixed 

windows

Al frame - single pane 135 cm (4 ft 5 

in) by 160 cm 

(5 ft 3 in)

Elementary & high 

schools = 25 %; 8-

story & 3-story 

office = 20 %

Al frame - double pane

Thermo-break Al frame -

double pane

Retail store, restaurant Fixed 

storefront

Al frame - single pane

Typical/comm

on storefront 

fixed window 

area

Retail store = 10 %; 

Restaurant = 30 %

Al frame - double pane

Thermo-break Al frame -

double pane

16-story office building, 

15-story hotel Curtain wall

Al frame - single pane Common 

lengths of 

sticks, 

components, 

pieces for a 

curtain wall 

Office building & 

hotel = 100 %

Al frame - double pane

Thermo-break Al frame -

double pane

Thermo-break Al frame -

triple pane

It is acknowledged that there are multiple window assembly options (combination of frame 

material, glass in-fill, and operability) for any building type in any climate zone; multiple 
75

window assembly options can be nearly identical in performance. The window assembly types 

presented in these tables are only one of many options available. As such, the particular window 

assembly combinations presented in this documentation are not endorsed or preferred over any 

other type of window assembly for the respective buildings in which they are used in BIRDS. 

It should also be noted that window to wall ratios (WWRs) vary greatly for many different 

reasons. Those selected for use in BIRDS are based solely on information provided by the RS 

Means Costworks, and may not be representative of WWRs for actual buildings of similar types. 

The next iteration of BIRDS will include additional prototypes such as the DOE Benchmark 

Buildings, which are expected to provide more representative WWRs. Additionally, industry 

members will be able to advise on the WWR aspect of the prototype buildings. 

BIRDS environmental performance data for the windows category was provided on a perwindow basis for the operable sliding windows and fixed windows, and per 0.09 m2

(1 ft2) of 

typical or common size of fixed storefront and curtain wall windows. The flow diagram below 

presents the general system boundaries for the window category as it is modeled for BIRDS. 

Figure 4-7 Windows System Boundaries

Aluminum Operable Sliding Window

Material take-off data for 2010 production were provided for an aluminum operable sliding 

window of dimensions 152.4 cm (5 ft) by 91.4 cm (3 ft). The following table provides general 

data on the dimensions and main components of a single- and double-pane window, and a 

double-pane window with a thermal break frame. A thermal break is a material that separates 

the interior and exterior of an aluminum (or other metal) frame. The low thermal conductivity of 

the material reduces heat transfer, making the metal window energy efficient. Due to the 

proprietary nature of the data, the full details of all of the materials have been removed.

Maintenance Use Phase

Window Assembly

Window components 

production (cutting 

lineals, etc)

IGU Production

Raw Materials 

Production

Transport to building site

Process 

Energy

Process aids

Emissions to air, 

water, soil

Raw Materials 

Production

Production

Transport 

to manuf.

Transport 

to manuf.

EOL (recycling, 

landfilling)
76

Table 4-22 Characteristics and Components of the Aluminum Operable Window

Description Units

Quantity

Single pane Double pane Double pane w/ 

thermo-br

Weight of the finished sealed unit kg (lb) 33 (72) 47 (103) 48 (105)

Dimension of the window m2 (ft2) 1.4 (15) 1.4 (15) 1.4 (15)

Depth of the finished sealed unit cm (in) 8.3 (3.25) 8.3 (3.25) 8.3 (3.25)

Extruded aluminum (frame) kg (lb) 16 (35) 15 (33) 15 (33)

IGU kg (lb) 15 (32) 29 (65) 29 (65)

Other components kg (lb) 2.10 (4.64) 2.11 (4.65) 2.95 (6.50)

Greater than 99 % of the mass of materials in the window were included and modeled for this 

window system. The aluminum frame is modeled as 50 % primary and 50 % secondary extruded 

aluminum, with the LCI data coming from the U.S. LCI Database. “Other components” include 

clips, weatherstrip, gaskets, hardware, sealant, and thermobreak materials. Clips, weatherstrip, 

and gaskets are modeled as PVC and rubber parts. Hardware is custom ordered so may vary 

with the window. For BIRDS, a mix of 50 % stainless steel and 50 % bronze has been modeled. 

The sealant is assumed to be silicone-based, and thermal break materials include glass-reinforced 

polyamide and PUR resin. U.S. LCI Database provided the production data for PVC while the 

ecoinvent database provided the data for the remaining materials. 

Data for the insulated glass units (IGU) are compiled from two sources: the commercial window 

manufacturer and Salazar (2007, Table 5.4). These two data sources have been averaged into one 

“hypothetical” IGU with some categories having combinations of materials in order to increase 

representation of an IGU in the marketplace, which has an array of materials that can be used for 

various parts of the IGU. The bill of materials on the basis of 0.09 m2(1 ft2) of the IGU is as 

follows: 

Table 4-23 Insulated Glass Unit Materials 

IGU category Material kg / m2lb / ft2

Glass (2 panes) Glass (0.25”) 14.1 2.9

Gas filler Argon 2.01E-02 4.12E-03

Spacer 50/50 Stainless St/Alum 1.86E-01 3.81E-02

Primary sealant Polyisobutylene 7.70E-03 1.58E-03

Secondary sealant 50/50 Polysulfide/PUR 1.71E-01 3.51E-02

Desiccant Silicone 8.98E-02 1.84E-02
77

The argon was calculated based on the volume between the panes of glass separated by 1.27 cm 

(0.5 in) and an argon density of 1.65 kg/m3(0.103 lb/ft3). Salazar (2007) reported an escape of 

argon when the cavity is flushed prior to being sealed – approximately 95 % more than the quantity 

in the finished unit. The manufacturer did not provide data on material losses. Since it is 

unknown if this quantity of escaped argon is high or low, a 50 % escape is assumed for this 

model. The spacer, which separates the two panes of glass, can be made of an array of materials, 

including aluminum, stainless steel, and structural foam. Since no data were provided on an IGU 

with structural foam, a 50/50 assumption of aluminum and stainless steel was used. Salazar 

(2007) reported a loss of approximately 10 % of the spacer; this has been factored in to the 

model. However, for both materials, the loss is recycled and not actually waste. The inner 

primary sealant, commonly polyisobutylene (PIB), is used to prevent leakage of the argon gas as 

well as penetration of water vapor into the space between the panes. An assumption of 50/50 

polysulphide polymer and polyurethane as secondary sealants were used. The desiccant in the 

spacer, assumed to be a silicone product, is used to absorb moisture. Salazar (2007) reported a 

loss of approximately 0.7 % and this has been factored into the model. Losses discussed in this 

paragraph are not included in the table above.

Note that for windows specified without argon filling, the IGU bill of materials is the same as the 

table above without the argon filling. Also, coatings and tints, when applicable, have been 

included in the model but are not included in the table. 

The data for float glass come from ecoinvent, based on early 2000’s European processes and 

technologies. Due to lack of available data on U.S. float glass production, the older European 

data were used. Processes in the data set include melting, cullet addition, forming (on a float 

bath), annealing by cooling in an oven (lehr), cutting of the glass, and storage. While this data 

set may not be representative of current U.S. production, it has been customized using U.S. 

energy and transportation data sets. Also, some transportation impacts have been removed, 

including transport between manufacturing plants and coating facilities, which, according to U.S. 

windows industry representatives, exists for European operations but not for U.S. operations. 

The next version of BIRDS is expected to have more improved data on glass production. 

The argon, stainless steel, polysulfide, and desiccant data come from ecoinvent. PIB come from 

ecoinvent; synthetic rubber is used as a general proxy for PIB. Aluminum and PUR data come 

from the U.S. LCI Database. 

No data were provided on the supplier distances to the manufacturer, so it is assumed that the 

materials to the manufacturing plant are transported an average of 600 km (373 mi) by heavyduty diesel-fueled truck. 

Aluminum Punched Opening, Fixed Window Production

Material take-off data for 2010 production were provided for an aluminum punched opening, 

fixed window of dimensions 135 cm (4 ft 5 in) by 160 cm (5 ft 3 in). The following table 
78

provides general data on the dimensions and main components of a single- and double-pane 

window, and a double-pane window with a thermal break frame. Due to the proprietary nature 

of the data, the full details of all of the materials have been removed.

Table 4-24 Characteristics and Components of the Aluminum Fixed Window

Description Units

Quantity

Single pane Double pane Double pane w/ 

thermo-br

Weight of the finished sealed unit kg (lb) 39 (85) 66 (145) 67 (148)

Dimension of the window m

2

(ft2) 1.4 (15) 1.4 (15) 1.4 (15)

Depth of the finished sealed unit cm (in) 5.1 (2.0) 5.1 (2.0) 5.1 (2.0)

Extruded aluminum (frame) kg (lb) 10 (23) 10 (22) 11 (24)

IGU kg (lb) 27 (60) 55 (122) 55 (122)

Other components kg (lb) 0.93 (2.05) 0.78 (1.72) 0.78 (1.72)

Greater than 99 % of the mass of materials in the window were included and modeled for this 

window system. The aluminum frame is modeled as 50/50 primary and secondary extruded 

aluminum, with the LCI data coming from the U.S. LCI Database. “Other components” include 

clips, gaskets, sealant, and thermal break materials. Clips and gaskets are modeled as PVC and 

rubber parts. The sealant is assumed to be silicone-based, and thermal break materials include 

glass-reinforced polyamide and PUR resin. U.S. LCI Database provided the production data for 

PVC while the ecoinvent database provided the data for the remaining materials. No data were 

provided on the supplier distances to the manufacturer, so it is assumed that the materials to the 

manufacturing plant are transported an average of 600 km (373 mi) by heavy-duty diesel-fueled 

truck. 

The IGU for the fixed, punched opening window is the same as for the operable sliding window. 

Please refer to that section above.

Aluminum Fixed Storefront Window Production

Material take-off data for 2010 production were provided for an aluminum fixed storefront 

window of dimensions 203 cm (80 in) by 203 cm (80 in). The following table provides general 

data on the dimensions and main components of a single- and double-pane window, and a 

double-pane window with a thermal break frame. Due to the proprietary nature of the data, the 

full details of all of the materials have been removed.
79

Table 4-25 Characteristics and Components of the Aluminum Storefront Window

Description Units

Quantity

Single 

pane

Double pane Double pane 

w/ thermal-br

Weight of the finished sealed unit kg (lb) 78 (173) 141 (310) 133 (293)

Dimension of the window m

2

(ft2) 4.1 (44) 4.1 (44) 4.1 (44)

Depth of the finished sealed unit cm (in) 11.4 (4.5) 11.4 (4.5) 11.4 (4.5)

Extruded aluminum (frame) kg (lb) 24 (52) 30 (66) 21 (46)

IGU kg (lb) 54 (118) 109 (240) 109 (240)

Other components kg (lb) 1.8 (4.0) 1.9 (4.3) 3.2 (7.2)

Greater than 99 % of the mass of materials in the window were included and modeled for this 

window system. The aluminum frame is modeled as 50/50 primary and secondary extruded 

aluminum, with the LCI data coming from the U.S. LCI Database. “Other components” include 

clips, gaskets, sealant, and thermal break materials. Clips and gaskets are modeled as PVC and 

rubber parts. Thermal break materials include glass-reinforced polyamide and PUR resin. U.S. 

LCI Database provided the production data for PVC while the ecoinvent database provided the 

data for the remaining materials. No data were provided on the supplier distances to the 

manufacturer, so it is assumed that all materials to the manufacturing plant are transported 600 

km (373 mi) by heavy-duty diesel-fueled truck. 

The IGU for the fixed storefront window is the same as for the operable sliding window. Please 

refer to that section above.

Aluminum Curtain Wall Window Production

Material take-off data for 2010 production were provided for an aluminum curtain wall window 

of dimensions 203 cm (80 in) by 203 cm (80 in). The following table provides general data on 

the dimensions and main components of a single- and double-pane window, a double-pane 

window with a thermal break frame, and a triple-pane window with a thermal break frame. Due 

to the proprietary nature of the data, the full details of all of the materials have been removed.
80

Table 4-26 Characteristics and Components of the Aluminum Storefront Window

Description Units

Quantity

Single pane Double 

pane

Double pane 

w/ thermal-br

Triple pane w/ 

thermal-br

Weight of the finished sealed unit kg (lb) 105 (232) 157 (346) 158 (348) 213 (469)

Dimension of the window m

2

(ft2) 4.1 (44) 4.1 (44) 4.1 (44) 4.1 (44)

Depth of the finished sealed unit cm (in) 17.8 (7.0) 17.8 (7.0) 17.8 (7.0) 17.8 (7.0)

Extruded aluminum (frame) kg (lb) 49 (108) 47 (103) 49 (107) 51 (112)

IGU kg (lb) 53 (116) 107 (236) 107 (236) 159 (350)

Other components kg (lb) 3.4 (7.5) 3.5 (7.8) 2.3 (5.1) 3.1 (6.7)

Greater than 99 % of the mass of materials in the window were included and modeled for this 

window system. The aluminum is modeled as primary extruded aluminum, with the LCI data 

coming from the U.S. LCI Database. “Other components” include clips, gaskets, sealant, and 

thermal break materials. Clips and gaskets are modeled as PVC and rubber parts. Thermal break 

materials include glass-reinforced polyamide and PUR resin. U.S. LCI Database provided the 

production data for PVC while the ecoinvent database provided the data for the remaining 

materials. No data were provided on the supplier distances to the manufacturer, so it is assumed 

that all materials to the manufacturing plant are transported 600 km (373 mi) by heavy-duty 

diesel-fueled truck. 

The IGU for the curtain wall is essentially the same as for the operable sliding window. Please 

refer to that section above.

Fiberglass Frame Operable Window

Salazar (2007, Sec. 5.1.3) provided the bill of materials and production details for a fiberglass 

casement window with dimensions 60 cm (1.97 ft) by 120 cm (3.94 ft). Data are from 2004 and 

came from a manufacturer who produces fiberglass pultrusions and pultrusion machinery in 

addition to windows. The finished frame includes the fiberglass lineals, polyester bracing in the 

corners, and a PVC glazing stop. The following table provides the bill of materials in the 

window (Salazar, 2007, Table 5.8). Since these materials were based on a perimeter of 3.6 m 

(11.7 ft), the quantities of the lineal materials were scaled up a factor of 1.4 to meet the 4.9 m 

(16.0 ft) perimeter used in the BIRDS tool. 
81

Table 4-27 Bill of Materials of the Fiberglass Operable Window

Material / component 

Window

0.6 m (2.0 ft) x 1.2 m (3.9 ft) 

Window

0.9 m (3 ft) x 1.5 m (5 ft) 

kg (lb) kg (lb)

Textile Glass (Roving)* 2.80 (6.17) 3.82 (8.43)

Textile Glass (Mat)* 1.40 (3.09) 1.91 (4.21)

Polystyrene Resin* 2.10 (4.63) 2.87 (6.32)

Calcium Carbonate* 0.70 (1.54) 0.96 (2.11)

PVC 0.497 (1.10) 0.497 (1.10)

Polyester 0.37 (0.82) 0.37 (0.82)

Steel (Operator) 1.88 (4.14) 1.88 (4.14)

Steel (Fasteners) 0.088 (0.19) 0.088 (0.19)

* Data for these materials are approximate to protect proprietary manufacturer data

The fiberglass pultrusion lineals are assembled with a purchased sealed unit measuring 0.48 m2

(5.2 ft2). 

Textile glass is modeled using ecoinvent data for glass fiber. The glass mat is modeled as it is in 

Salazar (2007), i.e., containing 100 % recycled A-glass from light bulbs. Polystyrene resin is based 

on the general purpose polystyrene data set from the U.S. LCI Database. U.S. LCI Database also 

provided the data for the PVC resin and CaCO3. Polyester resin comes from ecoinvent. Steel 

fasteners and the operator come from World Steel Association (2011), with steel profiles 

customized to U.S. using the U.S. electricity grid.

The IGU is modeled the same as the other IGUs in the window category (described above).

It is assumed that materials are transported to the manufacturing plant an average of 600 km 

(373 mi) by heavy-duty diesel-fueled truck. 

Wood- PVC Composite Frame Operable Window

Limited data were available for a wood-PVC composite window frame, so some data were 

extrapolated from Salazar (2007)’s aluminum clad wood window (Sections 5.1.1, 5.2.1). 

Assuming that the wood-PVC composite window has the same volume of material in the frame, 

the volume of wood in the Salazar window was used to estimate the quantity of composite 

material in the frame. Other components from the wood window were used in this model, 

including the fasteners, hardware, and weatherstrip. Since these materials were based on a 

perimeter of 357 cm (11.7 ft), the quantities relating to the perimeter of the frame were scaled up 

a factor of 1.4 to meet the 488 cm (16 ft) perimeter used in the BIRDS tool. The following table 

presents the bill of materials in the window. 
82

Table 4-28 Bill of Materials of the Wood-PVC Composite Operable Window

Material / component

Window

0.6 m (2.0 ft) x 1.2 m (3.9 ft) 

Window

0.9 m (3 ft) x 1.5 m (5 ft) 

kg (lb) kg (lb)

Wood-PVC Composite: 0.07 m3*63.0 (138.9) 86.0 (189.6)

Paint 0.30 (0.66) 0.41 (0.90)

Polypropylene 0.12 (0.26) 0.16 (0.36)

Thermoplastic Elastomer 0.09 (0.20) 0.12 (0.27)

Steel (Operator) 1.79 (3.95) 1.79 (3.95)

Steel (Fasteners) 0.16 (0.35) 0.16 (0.35)

*Composite density = 900 kg/m3 (56.2 lb/ft3) (Flakeboard, www.flakeboard.com)

 

Composite material is modeled as being made up of 40 % fine wood fiber (flour or particles) and 

60 % thermoplastic polymer by weight10 (assuming to be PVC in this case). The composite is 

produced by mixing the wood fiber with the heated resin. It is assumed that the wood fiber is 

pre-consumer recycled content. One provider of wood-PVC composite windows stated that 

“some” of the polymer has been reclaimed so 10 % was modeled as pre-consumer reclaimed 

PVC. Data for virgin PVC come from the U.S. LCI Database. The formation of the composite 

lineals is assumed to be done by extrusion, and this is based on ecoinvent data.

Paint is modeled as alkyd paint and comes from ecoinvent. Data for polypropylene come from 

the U.S. LCI Database. Data for the thermoplastic elastomer, as ethylene propylene diene 

monomer (EPDM) rubber, come from ecoinvent. Steel fasteners and the operator are based on 

cold rolled steel data from World Steel Association (2011). 

The IGU is modeled the same as the other IGUs in the window category (described above).

It is assumed that materials are transported to the manufacturing plant an average of 600 km (373 

mi) by heavy-duty diesel-fueled truck. 

Window Manufacturing 

Aluminum Windows

The large commercial window manufacturer provided electricity, natural gas energy, and net 

water use data on the basis of one operable or fixed window, storefront window, and curtainwall 

window. For confidentiality purposes, these data are not shared in this documentation, however, 

they have been included in the models for all of the window types. 

 

10 Website information on Fibrex Material. Found at: 

http://www.andersenwindows.com/planning/articles/fibrex-material/.
83

Fiberglass Windows

Manufacturing energy was provided by the fiberglass manufacturer, but the data were limited 

due to unavailable data on total windows produced in the given year as well as the broad 

variation of business practices of this manufacturer. Nonetheless, an allocation was made for the 

pultrusion energy in Salazar (2007), so those data were used for pultrusion: 20 MJ (18 956 Btu) 

natural gas and 24.2 MJ (22 937 Btu) electricity per window (Table 5.15). Energy data used for 

the aluminum windows were applied for the remaining processes, i.e., window assembly and 

IGU production. These energy data are not disclosed to protect confidential data. 

According to Salazar (2007), the heat curing during pultrusion liberates approximately 5.5 % of 

the styrene into the air, or 0.112 kg (0.247 lb). Waste is also generated and included in the model: 

waste comes from the cutting of lineals (0.486 kg (1.07 lb)) and glazing stops (0.008 kg (0.018 lb)) to 

length. This waste is modeled as going to a landfill.

Wood-PVC Composite Windows

Total facility energy was provided by the wood window manufacturer, and the Salazar study 

allocated these totals to four “departments”: lineal production, assembly, overhead, and sealed 

units. As mentioned above, the lineals were produced by way of extrusion, and this is accounted 

for in the production of upstream materials. The same energy data used to produce the IGUs for 

the aluminum windows were used here. Assembly energy, which included cutting lineals to 

length, installing hardware, and placing the sealed unit in the frame, plus overhead energy, were 

taken from the Salazar study. Manufacturing energy was as follows:

Table 4-29 Wood-PVC Composite Window Manufacturing Energy 

Facility Aspect Natural Gas MJ

(Btu)11

Electricity MJ

(Btu)

Window Assembly 90.4 (85 683) 61.5 (58 291)

Overhead 43.0 (40 756) 29.2 (27 676)

It is assumed that 5 % to 10 % (average 7.5 %) of the lineal is wasted during cutting to size, but this 

material can be re-melted and re-extruded so is not considered as a waste. 

Coatings

Low-emissivity (low-E) coatings, reflective coatings, and tinted windows have been included in 

the windows modeling to meet different performance characteristics of the windows. Coatings 

are used to improve the insulation properties of the glass by reflecting visible light and infrared 

 

11 The manufacturer in Salazar (2007) used wood as a significant source of energy. Since a manufacturer of 

composite windows may not necessarily produce wood windows (nor have wood waste as a readily available energy 

source), the wood and natural gas energy quantities were combined into only natural gas.
84

radiation. Low-E coating is modeled using the coating details of ecoinvent’s “flat glass, coated” 

data set as a starting point. The technology used at this plant is based on a cathodic sputtering 

technology which involves depositing thin silver and other layer(s) on the glass. According to 

the ecoinvent documentation, the raw materials used for sputtering are bismuth, silver and 

nickel-chrome. The quantity of 1.19 E-4 kg (2.62 E-4 lb) metals per kg was divided into three to 

account for 1/3 nickel, 1/3 chromium, and 1/3 silver. It is acknowledged that these data are 

approximate. 

According to the Windows for High Performance Commercial Buildings website, reflective 

coatings usually consist of thin metallic or metal oxide layers and come in various metallic 

colors including silver, gold, and bronze.12 Due to lack of available other data, the reflective 

coating data use the same quantity of coating as low-E but apply silver, gold and bronze data sets 

to account for a range of reflective coatings. 

Tint is obtained by adding small amounts of metal oxides during glass manufacturing, coloring 

the glass uniformly. For BIRDS, iron oxide has been assumed to be the mineral additive for the 

tint, and it is modeled as applied at an assumed rate of 0.1 % of the weight of glass.

Transportation to the Building Site, Use and Maintenance

Transportation of the window to the building site is modeled an average of 805 km (500 mi) by 

heavy-duty (combination) diesel fuel-powered truck. 

Installing windows is primarily a manual process; no energy or emissions are included in the 

model for this. Windows come to the building fully assembled and custom-ordered to fit so 

there is generally no installation waste. 

The commercial windows are modeled as having a functional lifetime of over 40 years so no 

replacement is needed during the 40 year study period. Maintenance in the model includes 

weatherstripping and sealing (discussed below). All operational energy-related aspects of the 

window are addressed in other sections of this report. 

Weatherstripping

Weatherstrip is modeled as a thermoplastic elastomer. Data for the thermoplastic, as ethylene 

propylene diene monomer (EPDM) rubber, come from ecoinvent (as synthetic rubber). For 

BIRDS, an EPDM weatherstrip has been modeled in the amount of 0.0064 kg per 0.3 m 

(0.014 lb per ft). 

Weatherstrip is assumed to perform at its optimal level an average of 7.5 years (Vigener, 2012) 

so is modeled as replaced every 7.5 years. 

 

12 Site developed jointly by the University of Minnesota and Lawrence Berkeley National Laboratory. Found at: 

http://www.commercialwindows.org/reflective.php. 
85

Different perimeter sealants can be used for different applications. For BIRDS, a silicone sealant 

has been modeled in the amount of 0.018 kg per 0.3 m (0.04 lb per ft). This is based on the 

average amount of sealant needed for perimeter depth/width gaps of 0.64 cm/0.64 cm 

(0.25 in/0.25 in) and 0.64 cm/1.27 cm (0.25 in/0.5 in).13 Data for the sealant comes from 

ecoinvent, primarily its silicone product. The sealant is modeled as being replaced every 15 

years (Vigener, 2012).

Other maintenance, such as glass and/or window frame cleaning, frame repainting or recoating, 

hardware adjustment or replacement, etc., are not included in the analysis. 

End of Life

The aluminum frame portion of the window is modeled as recycled at end of life, and the 0-100 

recycling methodology has been applied. For this, system expansion is applied; the production 

of the same amount of virgin aluminum that is in the frame is subtracted out of the system, 

crediting the system with an avoided burden based on the reduced requirement for virgin 

material production in the next life cycle. Likewise, recycled content in the aluminum adds 

some of the burden to the product system in order to share the burden with the previous life 

cycle.14 

The remaining parts of the window, including the IGU, are disposed of in a landfill. Fiberglass 

and composite frames are modeled as disposed of in a landfill. End-of-life modeling includes 

transportation by diesel-fuel powered truck approximately 80 km (50 mi) to a C&D landfill or to 

recycling. The portions of the window going to landfill are modeled based on ecoinvent end of 

life waste management process data. 

4.5.4 HVAC Systems

The HVAC systems for each building type in BIRDS were based on the default prototype 

specifications provided by the RS Means Square Foot Cost Estimator (SFCE). BIRDS evaluates 

four main categories of HVAC systems: fin tube radiation, boilers, packaged chillers, and 

rooftop air conditioners. Data presented in Section 3 lay out the operational characteristics and 

applications in the prototype buildings. The subsections below describe the life cycle modeling 

of the equipment. 

BIRDS environmental performance data for the HVAC equipment evaluated was provided on a 

per-unit basis. The flow diagram below presents the general system boundaries for the HVAC 

equipment as it is modeled for BIRDS. 

 

13 Amount calculated on an on-line sealant usage calculator, found at http://www.tremcosealants.com/technicalresources/calculators/sealant-calculator.aspx. 

14 For more information on the approach to modeling metals at end of life, see Atherton (2006) and 

Association 
86

Figure 4-8 HVAC System Boundaries – Boiler Example 

Boilers

Boilers provide the steam or hot water to various parts of the buildings. The following types of 

boilers were evaluated:

Table 4-30 Boilers Included in BIRDS

Type of Boiler, construction Gross output in kW

(MBH15)

Notes

Cast iron, natural gas- or propane-fired Steam, 70 (240) Includes standard controls and insulated jacket

Cast iron, natural gas- or propane-fired Steam, 82 (280) Includes standard controls and insulated jacket

Cast iron, natural gas- or propane-fired Steam, 48 (163) Includes standard controls and insulated jacket

Cast iron, natural gas- or propane-fired Steam, 448 (1 530) Includes standard controls and insulated jacket

Cast iron, natural gas- or propane-fired Steam, 1 958 (6 680) Includes standard controls and insulated jacket

Cast iron, gas- and oil-fired Hot water, 1 758 (6 000)

Upstream Materials Production through Manufacturing

Data were compiled from publicly-available manufacturer-specific literature data (table below). 

These specific models were chosen since their literature provided adequate data to compile a 

rough estimate of the material quantities. 

 

15 MBH = 1 000 Btu/hr. 

Use Phase EOL (recycling, 

some landfilling)

Maintenance 

(service technician 

visits)

Boiler Production

Raw Materials 

Production

Transport to building site

Process 

Energy

Process aids

Emissions to air, 

water, soil

Transport to manufacturing
87

Table 4-31 Boiler Models

Output, kW 

(MBH)

Manufacturer & model Data Source for dimensions, weight*

Steam, 70 (240) Weil McClain, EGH 65-75 Weil McClain EG-PEG-EGH

Gas Fired Boilers Series 4 – Boiler Manual, 

Part No. 550-110-639/0706, Table 15 & p. 34 diagrams. 

Steam, 82 (280) Weil McClain, EGH 75-85

Steam, 48 (163) Weil McClain, EGH 50-55

Steam, 448 (1 530) Weil McClain, LGB 12-13 Weil McClain LGB 

Gas Fired Boiler – Boiler Manual, 

Part Number 550-141-186/0703, Sections 12, 14.

Steam, 1 958 (6 680) Weil McClain, (94)H2494 Weil-McLain 94 

Water and steam boilers — for Gas, Light Oil, & 

Gas/Light Oil-Fired Burners – Boiler Manual, 

Part No. 550-110-275/0810, p.42 & Fig 5.

Water, 1 758 (6 000) Weil McClain, (94)H2194-2294

*Weil-McLain boiler manuals retrieved at: http://www.weil-mclain.com/en/our-products/boilers/commercialboilers.aspx

As a starting point for the bill of materials, data on the cast iron content of a 938 kW (3 200 

MBH) Veissmann water boiler which has a cast iron heat exchanger was assumed (Veissmann 

Vitorond, July 2010),16 and this content was approximately 96 %. The assumption was then 

made that this percentage was the same for other boilers with cast iron heat exchangers, and a 

representative from Weil McClain confirmed that it is “roughly 95 %”.17 Thus, cast iron was 

assumed for 94 % for smaller output boilers and 96 % for larger ones. The remaining 4 % to 6 % 

of the total weights for the steel jacket and volume of insulation were calculated based on 

dimensions of the units and an insulation thickness of 1.3 cm (0.5 in) of fiberglass batt (thickness 

confirmed by Weil McClain). The weight of fiberglass was calculated using a density of 

22.6 kg/m3(1.41 lb/ft3) (see insulation section). The remaining weight was assumed to be cold 

rolled steel and a small amount of copper in the controls. The following table provides the bill of 

materials for each boiler based on the above assumptions and boiler weight data from literature.

 

16 For example: the Viessmann model Vitorond VD2 1080. 

17 Correspondence with Weil McClain, February 2012.
88

Table 4-32 Boiler Bill of Materials

Output, kW (MBH) Total kg (lb)

Cast Iron 

kg (lb)

Steel 

kg (lb)

Insulation

kg (lb)

Copper

kg (lb)

Steam, 70 (240) 320 (705) 301 (663) 18 (40) 1.0 (2.3) 0.11 (0.25)

Steam, 82 (280) 358 (789) 337 (742) 20 (45) 1.1 (2.5) 0.11 (0.25)

Steam, 48 (163) 265 (585) 249 (550) 15 (33) 0.9 (2.0) 0.11 (0.25)

Steam, 448 (1 530) 2 064 (4 551) 1 981 (4 368) 79 (175) 3.1 (6.9) 0.36 (0.8)

Steam, 1 958 (6 680) 10 161 (22 400) 9 754 (21 503) 397 (876) 9.1 (20.0) 0.45 (1.0)

Water, 1 758 (6 000) 9 219 (20 324) 8 850 (19 510) 361 (795) 8.4 (18.5) 0.45 (1.0)

Ecoinvent data were used for the cast iron. Data for the cold rolled steel come from World Steel 

Association (2011), and data for copper come from ICA (2012). The fiberglass insulation was 

modeled as described in the insulation section. 

Raw materials are modeled as transported to the manufacturing plant via diesel truck an assumed 

average distance of 805 km (500 mi).

No manufacturing data were available for commercial boilers, so as proxy, an ecoinvent data set 

for a 100 kW (341 MBH) oil boiler was used (ecoinvent Report No. 5, 2007). The ecoinvent 

data summary describes data for the production energy to be estimated and coming from a 1998 

environmental report. In general, the data, being estimated and of older vintage, are considered 

to be not representative. Nonetheless, the use of these data was considered to be better than no 

data at all.

Table 4-33 Boiler Manufacturing Data

Energy source

Quantity for 580 kg boiler

100 kW

Electricity, medium voltage MJ (Btu) 1 195 (1 132 831)

Natural gas in industrial furnace MJ (Btu) 1 920 (1 819 809)

Light fuel oil in industrial furnace MJ (Btu) 1 010 (957 295)

Tap water liter (gal) 741 (196)

Since manufacturing larger or smaller units requires more or less energy, respectively, these data 

were normalized up or down based on the total weights of the units.

Transportation to the Building Site through End of Life

Transportation of the equipment to the building site is modeled to be an assumed average of 644 

km (400 mi) by heavy-duty diesel fuel-powered truck. 
89

It is assumed that a qualified service technician comes to the building site to check and/or service 

the unit one time per year to ensure optimal performance and lifetime. It is assumed that the 

qualified technician is within a 24 km (15 mi) service radius. The 24 km (15 mi), driven in a 

gasoline-powered van, is allocated amongst other service visits for that technician, assuming that 

the same technician is making more than one service call during that trip. Assuming the 

technician makes 5 service calls in one day, one-fifth of the impacts from driving 24 km (15 mi) 

are allocated to the product, or 4.8 km (3 mi). Data for a van come from ecoinvent. Unplanned 

service visits (i.e., unanticipated issues that require a service technician) are not included in the 

modeling assuming that the building personnel follow the maintenance and care correctly.

A lifetime of 35 years has been assumed, based on the statement in a boiler brochure: “It's not 

uncommon for Weil-McLain cast iron boilers to last 35 years or more."18 Shah (2008) backs this 

number up as well. 

At the end of life, it is assumed that the packaged unit is removed from the building and its metal 

parts are recycled, especially since the vast majority is recoverable metal, fully recyclable, and 

the equipment is easy to recover and remove from the building. See Footnote 14 for the 

recycling methodology used. The fiberglass is modeled as landfilled, and a distance of 48 km 

(30 mi) to the landfill in a heavy-duty diesel truck has been modeled. The landfill is modeled 

based on ecoinvent end of life waste management process data. 

Fin Tube Radiation

Fin tube radiation is characterized by hot water heated by boiler and piped to "fin-tube" 

baseboard units mounted along walls. Fin tubes’ heating elements are copper tubes with 

aluminum fins. Fin tube radiation is modeled for 5 heating applications which are used in the 

tool: 

Table 4-34 Fin Tube Radiation Characteristics in BIRDS

Application of Fin Tube Radiation Space being Heated: Area & Volume Notes

Apartment building, forced hot water 1 858 m

2

, 5 663 m

3

(20 000 ft2, 200 000 ft3)

Apartment building, forced hot water 2 787 m

2

, 8 495 m

3

(30 000 ft2,300 000 ft3)

Commercial building, forced hot water 929 m

2

, 2 832 m

3

(10 000 ft2, 100 000 ft3)

2 floors

Commercial building, forced hot water 9 290 m

2

, 28 317 m

3

(100 000 ft2, 1 000 000 ft3)

3 floors

Commercial building, forced hot water 92 903 m

2

, 283 168 m

3

(1 000 000 ft2, 10 000 000 ft3)

5 floors

 

18 Boiler lifetime from Weil-McLain LGB brochure - C-805 (1111).
90

A material quantity surveyor estimated the bill of materials of the radiation system, based on the 

square footage and number of floors of the buildings using fin tube radiation (Dewhurst, 2012). 

For the apartment building applications, the estimates were based on a baseboard product by 

Slant/Fin (2004). For the commercial buildings, the Trane Architectural Hydronic Wall Fin 

(2001) was used. These were used because they were considered by the surveyor to be 

representative of current products used in today’s buildings. Also, enough data were available 

from company literature to provide good estimates of the materials. 

Upstream Materials Production through Manufacturing

The fin tube radiation bill of materials includes three aspects: fin tubes, their enclosures, and the 

distribution system which delivers steam from the boiler, through the building, to the rooms 

where the radiators provide heat. The boiler is described in another section. The figure below 

shows a close-up of the radiator (excludes the distribution system).

Figure 4-9 Fin Tube Radiator (Internal and External Components)19 

The materials surveyor first defined the buildings’ heating systems, including the boiler(s) and its 

output(s) and other elements that would be typical in that size of building. Then for each 

building type, he calculated the total lengths of fin tubes, horizontal piping, and risers needed, 

based on the intended use of the building (apartments or open commercial spaces) and size of the 

buildings. To do this, the surveyor took the total square meters (square feet) of building and 

divided by number of floors to get per floor square meters (square footage). Then he took the 

square root of per floor square meters (square footage) to determine perimeter wall lengths, and 

the horizontal distribution on each floor was assumed to run along this perimeter wall length on 

 

19 Slant/Fin, 2004. 
91

each floor. The fin tube length to heat the buildings was estimated using 2.95 MJ/m (900 Btu/ft) 

of fin tube, based on the calculated heat demand for the building. 

The distribution system included pipework for the risers, which run vertically from the boiler to 

each heated floor, the horizontal ring main on each floor, and the pieces connecting the 

distribution pipework to the fin tube radiators. The risers included the pipes, insulation, clamps 

and fittings. The horizontal ring main included the pipes, insulation, hangers, and fittings. Floor 

heights were assumed to be on average 3.5 m (11.5 ft), which was used to determine the length of vertical 

distribution. Fittings, connections, and installation components were calculated based on lengths. 

Gauge and weight charts for the sheet metals and other standard pipe tables were used 

(Greenheck, 2004). Table 4-36 summarizes the bill of materials for the three aspects.

Data for copper come from ICA (2012). Aluminum is modeled as a 50/50 mix of primary and 

secondary extruded aluminum which come from the U.S. LCI Database. Data for cold rolled 

steel and steel pipes come from World Steel Association (2011). Ecoinvent data were used for 

steel enameling and cast iron. The fiberglass insulation was modeled as described in the 

insulation section. Raw materials are modeled as transported to the manufacturing plant via 

diesel truck an assumed average distance of 805 km (500 mi).

Data for parts forming, sheet rolling, enameling, and pipe forming (drawing of pipes, steel, from 

ecoinvent) are included in raw materials production. No data were available to model assembly 

of the fin tubes.
92

Table 4-35 Fin Tube Radiation Summary of Materials

Area

929 m2

(10 000 ft2)

1 858 m2

(20 000 ft2)

2 787 m2

(30 000 ft2)

9 292 m2

(100 000 ft2)

92 903 m2

(1 000 000 ft2)

Building Type Commercial Apartment Apartment Commercial Commercial

Number of Floors 2 3 4 3 5

Assembly Part/Material kg (lb) kg (lb) kg (lb) kg (lb) kg (lb)

Fin Tube Pipe (copper) 66 (146) 102 (224) 142 (313) 439 (967)

3 192

(7 038)

Fins (Al) 144 (318) 96 (212) 135 (297)

954

(2 104)

6 944

(15 310)

Wallfin Installation 

Sheet (cold rolled 

steel)

2.0 (4.4) 4.4 (10) 6.2 (14) 13 (29) 97 (213)

Wallfin Installation 

Bolts (carbon steel) 1.9 (4.3) 4.3 (9.4) 6.0 (13) 13 (28) 93 (205)

Enclosure

Sheet (cold rolled 

steel)

1 112

(2 452)

762

(1 680)

1 067

(2 353)

4 278

(9 432)

29 948

(66 024)

Enclosure Installation 

Sheet (cold rolled 

steel)

174 (385) 329 (727) 461 (1 017)

672

(1 481)

4 704

(10 370)

Paint (baked enamel) 8.8 (19) 6.0 (13) 8.4 (19) 34 (75)

2 367

(522)

Enclosure Installation 

Bolts (carbon steel) 3.7 (8.1) 4.3 (9.4) 6.0 (13) 14 (31) 99 (219)

Distribution

System 

Pipe (sched 40 steel) 1 018

(2 244)

1 589

(3 505)

2 308

(5 089)

4 617

(10 179)

38 927

(85 820)

Insulation (fiberglass) 75 (165) 118 (259) 169 (373) 296.(653)

2 206

(4 864)

Riser Clamp (carbon 

steel) 4.5 (10) 7.5 (16) 10.5 (23) 11 (25) 69 (153)

Hanger (carbon steel) 41 (90) 68 (150) 118 (259) 151 (333)

1 025

(2 262)

Pipe fittings (black 

malleable Iron) 165 (163) 263 (580) 379 (835)

743

(1 639)

6 158

(13 575)

Pipe (connect dist. to 

fin tube)

726

(1 600)

817

(1 800)

1 451

(3 200)

2 177

(4 800)

5 443

(12 000)

Ready Rod for the 

hanger (carbon steel) 15 (34) 24 (53) 34 (76) 54 (119) 220 (484)

 

Transportation to the Building Site through End of Life

Transportation of the equipment to the building site is modeled to be an assumed average of 

644 km (400 mi) by heavy-duty diesel fuel-powered truck. 

Fin tube radiation lasts well over 40 years, so no replacement is needed for the 40-year study 

period. Maintenance of the radiators is minimal; bleeding the radiators may need to be done to 
93

let out air that has gotten trapped inside, and this is done manually so is not included in the 

model. 

At the end of life, it is assumed that the fin tube radiators are removed from the building and 

recycled, especially since most of the parts are valuable recoverable metal, fully recyclable, and 

relatively easy to recover and remove from the building. The recycling methodology used is 

described in Footnote 14. 

Additional Reference

Air-Conditioning, Heating, and Refrigeration Institute (AHRI), I=B=R Ratings Directory for 

Boilers, Baseboard Radiation, Finned Tube (Commercial) Radiation, Indirect-fired Water 

Heaters, Updated April 2009.

Packaged Units 

Packaged units, or rooftop units, are air handlers designed to be installed for use on rooftops. An 

air handler is an appliance used to condition and circulate air through a building as part of the 

building’s HVAC system. A split system is an air conditioner split by the condensing unit 

located on the outside of the building and the evaporator in a furnace or air handler inside the 

building. Four packaged units and one split system condensing unit were evaluated: 

Table 4-36 Packaged Units Characteristics in BIRDS

Type of HVAC System Application & Square Area Designated Tonnage

Rooftop air conditioner – single zone Department stores

929 m2(10 000 ft2)

29.17 

Rooftop air conditioner – multizone Restaurants

279 m2(3 000 ft2)

15.00 

Rooftop air conditioner – multizone Medical centers

2 323 m2(25 000 ft2)

58.33 

Rooftop air conditioner – multizone Offices

2 323 m

2

(25 000 ft2)

79.16 

Air cooled condensing unit – split system Schools and colleges

1 858 m

2

(20 000 ft2)

76.66 

Upstream Materials Production through Manufacturing

Rooftop Air Conditioner Production

Data for a commercial sized rooftop air conditioner were provided by a global producer of 

commercial HVAC equipment. The full bill of materials for the system was provided for 

BIRDS. The table below provides general data on the main components of the equipment but due 
94

to the proprietary nature of the data, the full details of all of the materials and the weight of the 

components have been removed.

Table 4-37 Packaged Units Main Components 

Component name Description & Material Notes

Housing Painted galvanized steel of varying thicknesses

Condenser Coils Aluminum

Supply Fan Mostly steel & a 10 HP motor Assume 20 % motor, 80 % steel

Evaporator Coil Copper tubing, Aluminum fin stock

Condenser Fans Includes 1-hp motors, fan blades, basket. Assume 80 % motors, 20 % steel

Economizer Damper Aluminum

Control Panel Sheet metal housing, electrical components

Compressor Steel, motors, copper

Refrigerant R410A

Misc parts Nuts, bolts, gaskets Assume 90 % steel, 10 % rubber

This product requires a roof curb, which is a steel structure that supports HVAC equipment on 

top of a building. The curb is included in the model and is assumed to be galvanized steel. 

Data for galvanized steel sheet for the housing come from World Steel Association (2011). The 

total weight for the compressor was given without a breakdown of the individual components. 

Data for a compressor was therefore modeled based on the percentages of the materials in a 

compressor reported in Biswas (2011):

Table 4-38 Compressor Bill of Materials

Material Weight kg (lb) %

Steel 15.5 (34) 9

Copper 7.5 (17) 4

Aluminum 3.0 (6.6) 2

Cast iron 141 (311) 84

Total 167 (368) 100

Aluminum for the condenser coils, evaporator coil, and economizer damper is modeled as a 

50/50 mix of primary and secondary extruded aluminum which come from the U.S. LCI 

Database. 

For the motors, a data set for an electric car motor, from ecoinvent, has been used as a guideline 

for the general material make-up for an electric motor. This data set includes the general 
95

materials in the motor, including rolled steel (75 % of total), aluminum (approximately 16 %), 

and copper wire (9 %). U.S. LCI data sets were used for the aluminum, World Steel Association 

(2011) for the steel, and ICA (2012) for the copper. 

Steel in the supply fan, compressor, and miscellaneous parts comes from cold rolled steel from 

World Steel Association (2011) and data for copper come from ICA (2012).

Control panel: The World Steel Association (2011) data for cold rolled steel was used for the 

sheet metal housing component of the control panel, which made up 80 %. Not enough data 

were available on the contents of this remaining part to model the electrical components. 

Synthetic rubber data come from ecoinvent.

R-410a data are based on a 50/50 share of difluoromethane (R-32) and pentafluoroethane (R125). Due to lack of available production data on both of these chemicals, proxies were used. 

Trifluoromethane (HFC-23) was used as a proxy for difluoromethane and 1,1,difluoroethane 

(HFC 152a) was used as proxy for R125. While proxies were used for the production aspect of 

the chemicals, any release of these was based on the release of R-32 and R-125, not the proxy 

chemicals, so that ozone depletion impact remains zero and global warming potential impact is 

calculated appropriate to R-410A. 

Raw materials are modeled as transported to the manufacturing plant via diesel truck an assumed 

average distance of 805 km (500 mi). 

Production of Other Packaged Units

For lack of available data for the other products in this category, this bill of materials was 

normalized for each size of packaged unit included in BIRDS. The exception to this was the 

quantity of refrigerant used for each and the unit weights, both of which could be obtained or 

extrapolated for different models of rooftop air conditioners. The table below summarizes the 

data sources and details of the rooftop air conditioner units to meet the NIST specs: 
96

Table 4-39 Packaged Unit Models

HVAC System Product this is based on20 Weight 

kg (lb)

R-410a 

charge

kg (lb)

Curb 

weight

kg (lb)

Rooftop air conditioner – single 

zone (929 m2(10 000 ft2), 

29.17 ton)

Maverick II commercial packaged 

rooftop system, 30 ton21 1 637 

(3 610)

11.3 (25) 192 (423)

Rooftop air conditioner – multizone 

(279 m2(3 000 ft2), 15.00 ton)

Voyager Packaged Rooftop Air 

Conditioners, 15 ton22

1 035 

(2 281)

5.2 (11.4) 192 (423)

Rooftop air conditioner – multizone 

(2 323 m2(25 000 ft2), 58.33 ton)

IntelliPak Packaged Rooftop Air 

Conditioners, 60 ton23

3 782 

(8 338)

20.1 (44.4) 234 (515)

Rooftop air conditioner – multizone 

(2 323 m2(25 000 ft2), 79.16 ton)

IntelliPak Packaged Rooftop Air 

Conditioners, 75 ton24

4 011 

(8 843)

25.2 (55.6) 277 (610)

Production of Air Cooled Condensing Unit – Split System 

Bill of materials for the split system air cooled condensing unit were based on data for a Carrier 

Corporation air conditioner from Shah (2008). The mass of the Carrier Corporation 24ACR3 

Comfort 13 Series (1-1/2 to 5 nominal tons) condenser unit in the article was normalized up to 

the mass of a commercial split system air-cooled condensing unit available on the market. The 

Trane split system condensing unit with remote evaporator chiller was chosen based on available 

data on weight and refrigerant quantity provided in company literature. 

Legutko (2000, p.3) describes an evaporator as “a direct-expansion, finned, tubular coil that has 

refrigerant inside the tubes. A fan draws air across the finned exterior of the tubes and delivers it 

to the spaces being conditioned. Standard coil construction consists of copper tubes with 

aluminum fins mounted in a galvanized steel frame.” The remote evaporator’s bill of materials 

was based on Legutko (2000); the dimensions of the Trane remote evaporator and a gauge chart 

were used to estimate the galvanized steel frame, and assumptions were made on the remaining 

 

20 The packaged units in the table representing the NIST systems were chosen based on available data on weight 

and/or refrigerant quantity provided in company literature. The products listed do not imply endorsement or product 

preference or quality.

21 Daikin McQuay Catalog 250-6: Maverick II commercial packaged rooftop systems: Heating & Cooling Models 

MPS015F – 075E, base weight from Table 36, curb weight from Table 37. Refrigerant data extrapolated based on 

other sources.

22 Trane Product Catalog: Packaged Rooftop Air Conditioners: VoyagerTM Cooling and Gas/Electric - 121⁄2–25 Tons, 

60 Hz, RT-PRC028-EN, Nov. 2011. Weight Table 88, refrigerant Table 1.

23 Trane Product Catalog, Packaged Rooftop Air Conditioners IntelliPakTM — S*HL, S*HK - 20 - 130Tons —AirCooled Condensers — 60 Hz, RT-PRC036-EN, April 2012, weights from Table 84. Refrigerant is extrapolated 

based on other Trane systems.

24 Trane Product Catalog, Packaged Rooftop Air Conditioners IntelliPakTM — S*HL, S*HK - 20 - 130Tons —AirCooled Condensers — 60 Hz, RT-PRC036-EN, April 2012, weights from Table 84. Refrigerant is extrapolated 

based on other Trane systems.
97

components.25 The table below presents the bill of materials for the condenser unit and remote 

evaporator. 

Table 4-40 Split System Bill of Materials 

Unit Material Quantity in Residential System 

kg (lb)

Quantity in 80-ton Compressor 

kg (lb)

Condenser unit Steel 78 (172) 1 189 (2 621)

Galvanized steel 35 (77) 534 (1 176)

Copper 17 (37) 259 (571)

Aluminum 17 (37) 259 (571)

Total 147 (324) 2 241 (4 940)

Refrigerant R-22 6 (13) n/a

Refrigerant R-410a n/a 26 (57)

Unit Material Quantity in Residential System 

kg (lb)

Quantity in Evaporator

kg (lb)

Remote Evaporator Galvanized steel n/a 20 (45)

Copper n/a 54 (120)

Aluminum n/a 6 (13)

Other steel parts n/a 14 (30)

Total n/a 94 (208)

The material data for elements in the systems are described above. 

Packaged Units Manufacturing 

The commercial HVAC equipment manufacturer provided electricity for assembly (punching, 

shearing, forming parts), lights, and fans, natural gas usage, and propane for forklifts. Data were 

provided on a full-facility basis for 2010 and calculated on the basis of one unit, based on total 

production time for the various lines of HVAC equipment produced at the facility. For 

confidentiality purposes, these manufacturing data are not shared in this documentation, 

however, they have been included in the model, i.e., normalized for each size of unit in this 

category.

Transportation to the Building Site through End of Life

Transportation of the equipment to the building site is modeled to be an assumed average of 644 

km (400 mi) by heavy-duty diesel fuel-powered truck. 

 

25 Trane Product Catalog: Split System Condensing Units, Fig. 41 (assumed 14 gauge), Tables 1, 11, 12.
98

It is assumed that a qualified service technician comes to the building site to check and service 

the unit every three years to ensure optimal performance and lifetime. It is assumed that the 

qualified technician is within a 24 km (15 mi) service radius. The 24 km (15 mi), driven in a 

gasoline-powered van, is shared amongst other service visits for that technician, assuming that 

the same technician is making more than one service call during that trip. Assuming the 

technician makes 5 service calls in one day, one-fifth of the impacts from driving 24 km (15 mi) 

are allocated to the product, or 4.8 km (3 mi). Data for a van come from ecoinvent. Unplanned 

service visits (i.e., unanticipated issues that require a service technician) are not included in the 

modeling assuming that the building personnel follow the maintenance and care correctly.

For the packaged units, a lifetime of 15 years has been assumed, based on an average of a 10 to 

20 year life span for a non-coastal application.26 For the split system unit, a lifetime of 20 years 

for the condenser unit and 25 years for the air handler have been assumed, based on the lifetimes 

reported by Shah (2008). 

For this analysis, 0.5 % per year of the total refrigerant for each unit is assumed to leak.

End of Life

At the end of life, it is assumed that the packaged unit is removed from the building and 

recycled, especially since most of the parts are valuable recoverable metal, fully recyclable, and 

relatively easy to recover and remove from the building. The recycling methodology used is 

described in Footnote 14. The curb is not removed, as a new unit is installed in its place. The 

non-metal components are modeled as landfilled. A distance of 48 km (30 mi) to the landfill in a 

heavy-duty diesel truck has been modeled. The landfill is based on ecoinvent waste management 

process data.

Packaged Chillers

Air-cooled packaged chillers with scroll compressors and water-cooled packaged chillers with 

screw compressors were modeled for BIRDS. Additionally, these chillers were modeled with a 

fan coil unit, and the water cooled chillers included a cooling tower. These were evaluated for 

the following applications:

 

26 Based on discussions with a manufacturer of packaged units.
99

Table 4-41 Packaged Chillers Characteristics in BIRDS

Type of HVAC System Application & Square Area Designated 

Tonnage

Air-cooled packaged chiller with scroll compressor Medical centers or similar application, 

1 858 m2(20 000 ft2)

46.66

Air-cooled packaged chiller with scroll compressor Medical centers or similar application, 

3 716 m

2

(40 000 ft2)

93.33

Water-cooled packaged chiller with screw compressor Medical centers or similar application, 

5 574 m2(60 000 ft2)

140.00

Water-cooled packaged chiller with screw compressor Offices, 5 574 m2(60 000 ft2) 190.00

Water-cooled packaged chiller with screw compressor Schools & colleges, 5 574 m

2

(60 000 ft2) 230.00

Upstream Materials Production – Air-Cooled Chillers

No data were available for specifically the air-cooled packaged chiller, so the bill of materials 

used for the rooftop air conditioner in the previous section was used as a proxy (see Table 4-37). 

The data were customized to these packaged chillers in terms of the unit weights and quantity of 

refrigerant used, both of which could be obtained for models of air cooled packaged chillers that 

would meet the NIST specifications. The table below summarizes the data sources and details of 

the air-cooled packaged chillers to meet the NIST specs:

Table 4-42 Air Scroll Packaged Chiller Model 

HVAC System Product this is based on Weight

kg (lb)*

R-410a charge

kg (lb)*

Air scroll packaged chiller with fan coil unit, 

1 858 m2(20 000 ft2), 46.66 ton

McQuay AGZ 045D (45 ton) 1551 (3420) 40 (88)

Air scroll packaged chiller with fan coil unit, 

3 716 m2(40 000 ft2), 93.33 ton

McQuay AGZ 090 (90 ton) 2539 (5605) 78 (172)

* McQuay International Product Catalog 611-1, Tables 33, 35

The data and assumptions used for the air scroll chillers, including production of raw materials 

and transportation of materials to the manufacturing facility, are found in the section above on 

rooftop air conditioners. 

Upstream Materials Production – Water-Cooled Chillers

No data on water-cooled screw compressor chillers with a range of tonnage of 140 to 230 were 

available, so the bill of materials for a 2500-ton water-cooled centrifugal chiller from Institute 

for Construction and Environment (2011) was used as a proxy. It is acknowledged that water 
100

screw compressors and centrifugal chillers are different technologies but these data were used for 

lack of other data available and because they perform the function of cooling.

Data in the EPD were collected in 2010; the EPD provided the major assemblies of the unit in 

terms of weights of each, shown in the table below. Even though major assemblies were 

identified, the EPD provided the material composition in terms of percentage of the total mass, 

not in terms of materials within each assembly (next table). Thus, it was impossible to switch 

out assemblies to be able to better customize the data for the water screw chillers.

Table 4-43 Centrifugal Chiller Major Assemblies

Major Assemblies kg (lb) % of total

Compressor 13 226 (29 157) 36

Compressor Install 2 300 (5 070) 6

Condenser 11 460 (25 265) 31

Controls 14 (31) 0.003

Economizer 303 (668) 1

Evaporator Tubes 7 463 (16 453) 20

Motors 165 (363) 0.4

Oil Tank 232 (511) 1

Purge 585 (1 290) 2

Shell 581 (1 281) 2

Unit Assembly 417 (919) 1

TOTAL 36 745 (81 008) 100

Table 4-44 Centrifugal Chiller Materials

Material / subcomponent kg (lb) % of total

Steel 16 536 36 454 45

Copper 10 656 23 492 29

cast iron 8 084 17 822 22

Aluminum 735 1 620 2

Motor 735 1 620 2

TOTAL 36 745 81 008 100

Note: brass was listed but as 0 % so is not included in the table.

The material quantities were normalized to the weights of different models of water screw 

packaged chillers, and were customized in terms of the quantity of refrigerant used for each. The 

table below summarizes the data sources and details of the water-cooled packaged chillers to 

meet the NIST specs:
101

Table 4-45 Water-cooled Packaged Chiller Models 

HVAC System Product this is based on* Weight

kg (lb)

R-134a Charge 

(Both Circuits)

Water- cooled packaged chiller, medical 

centers, 5 574 m2(60 000 ft2), 140.00 ton

Trane RTWD 60 Hz standard 

efficiency (140 Ton)

3 016 (6 650) 118 (260)

Water- cooled packaged chiller, offices, 

5 574 m2(60 000 ft2), 190.00 ton

Trane RTWD 60 Hz high 

efficiency (200 Ton)

3 705 (8 168) 124 (273)

Water- cooled packaged chiller, schools &

colleges, 5 574 m2(60 000 ft2), 230.00 ton

Trane RTWD 60 Hz high 

efficiency (220 Ton)

4 079 (8 993) 165 (364)

* Trane Catalog Series R Helical Rotary Liquid Chillers, Tables 1, 67.

Data on cold rolled steel come from World Steel Association (2011) and data on copper come 

from ICA (2012). Ecoinvent data were used for the cast iron. Aluminum is modeled as a mix of 

primary and secondary extruded aluminum which comes from the U.S. LCI Database. 

For the motors, a data set for an electric car motor, from ecoinvent, has been used as a guideline 

for the general material make-up for an electric motor. This data set includes the general 

materials in the motor, including rolled steel (75 % of total), aluminum (approximately 16 %), 

and copper wire (9 %). U.S. LCI data sets were used for the aluminum, World Steel Association 

(2011) for the steel, and ICA (2012) for the copper. 

Data for 134a come from ecoinvent. Raw materials are modeled as transported to the 

manufacturing plant via diesel truck an assumed average distance of 805 km (500 mi).

Manufacturing 

One manufacturer of water-cooled packaged chillers provided electricity and other energy data 

on a full-facility basis for 2010. From those data, the energy data were calculated on the basis of 

one unit, based on total production time for the various lines of HVAC equipment produced at 

the facility. For confidentiality purposes, these manufacturing data are not shared in this 

documentation, however, they have been included in the model. 

Transportation to the Building Site through End of Life

Transportation of the equipment to the building site is modeled based on an assumed average of 

644 km (400 mi) by heavy-duty diesel fuel-powered truck. 

It is assumed that a qualified service technician comes to the building site to check and service 

the unit one time per year to ensure optimal performance and lifetime. It is assumed that the 

qualified technician is within a 24 km (15 mi) service radius. The 24 km (15 mi), driven in a 
102

gasoline-powered van, is shared amongst other service visits for that technician, assuming that 

the same technician is making more than one service call during that trip. Assuming the 

technician makes 5 service calls in one day, one-fifth of the impacts from driving 24 km (15 mi) 

are allocated to the product, or 4.8 km (3 mi). Data for a van come from ecoinvent. Unplanned 

service visits (i.e., unanticipated issues that require a service technician) are not included in the 

modeling assuming that the building personnel follow the maintenance and care correctly.

Bakane (2009) estimates a lifetime of 10 years for the scroll chiller and 17.5 years for the screw 

compressor (based on an average of 15 yrs to 20 yrs). For this analysis, 0.5 percent per year of 

the total refrigerant in each is assumed to leak, and this is modeled as recharged by the service 

technician. 

At the end of life, it is assumed that these chillers are removed from the building and recycled, 

especially since most of the parts are valuable recoverable metal, fully recyclable, and relatively 

easy to recover and remove from the building. The recycling methodology used is described in 

Footnote 14. The non-metal components are modeled as landfilled; landfill data are come from 

ecoinvent. A distance of 48 km (30 mi) to the landfill in a heavy-duty diesel truck has been 

modeled.

Fan Coil

A fan coil is a device that has a heating or cooling coil and a fan, and is used to provide heat or 

air conditioning to the space in which it is installed. The bill of materials for the fan coil comes 

from Shah (2008, Table 3), as follows:

Table 4-46 Fan Coil Bill of Materials 

Material

Weight

kg (lb)

Steel 48 (106)

Galvanized steel 26 (57)

Copper 2 (4)

Total 76 (168)

Data for both cold rolled steel and galvanized steel come World Steel Association (2011) and 

data for copper come from ICA (2012). The fan coil is modeled as having a lifetime of 25 years, 

consistent with Shah (2008). At the end of life, it is assumed that the fan coil is recycled; the 

recycling methodology used is described in Footnote 14. 

Cooling Tower

One cooling tower has been modeled to be used in conjunction with the water-cooled chillers in 

BIRDS. According to a Baltimore Aircoil Company (BAC) sales representative, the BAC Series 

1500 cooling tower is the most appropriate for a commercial application needing a nominal 

tonnage in the range of 190 to 200 which generally represents an average for the water-cooled 
103

chillers in BIRDS). The bill of materials was compiled for the BAC 15201 (a single cell unit) 

from BAC Series 1500 Cooling Tower Specification (2010), which provided the following major 

components and subcomponents/parts. 

Table 4-47 Cooling Tower Components and Parts

Component Subcomponents / Parts

Cooling Tower Panels, Panel edges, Panel finish

Cold Water Basin Panels, Drain/Clean out connection, Make-up valve, Float shell, Float fill, Float 

connection

Water Outlet Water outlet connection, Lift out strainers, Anti-vortexing device

Water Distribution System Water inlet, Integral strainer, Open gravity type basin, Gravity flow nozzle, Basin 

weir, Metering orifice, Lift-off distribution covers

Fans Fan blades, Fan cylinder, Fan guard

Bearings Bearings, Grease, Seals

Fan Drive Powerband

Sheaves Sheaves

Fan Motor Motor, Enclosure, Finish on winding, shafts and bearings

Fill and Drift Eliminators Fill & Integral drift eliminators

Air Inlet Louvers Air inlet louvers

Basin Water Level Sensing 

and Control

Enclosure, controls, water level, standpipe Venting, Standpipe mounting hardware

Accessories Basin heaters, vibration cutout switch, basin sweeper piping, air intake option, 

platform, ladder, louver face platform, internal platform

Equipment Controls Enclosed controls

Mounting Support Support Structure

Any available data on these items, including specified surface areas, volumes, and weights were 

recorded. Some data on materials were provided by the literature while materials for other 

subcomponents and parts were assumed. The masses of the parts and materials were calculated 

using material densities and the manufacturer’s published data. The following table presents the 

compiled bill of materials totaling the published mass of the BAC 15201 (1 942 kg (4 280 lb)).27

 

27 BAC Product and Application Handbook –Series 1500 Engineering Data on Cooling Tower (no date), p. B58.
104

Table 4-48 Cooling Tower Bill of Materials

Material / component 

description

Mass

kg (lb)

Galvanized steel sheet 1 060 (2 337)

cold rolled steel 146 (321)

Aluminum 38 (84)

Cast iron 2.3 (5.0)

Equipment control assemblies 6.4 (14)

electric heater 6.8 (15)

Epoxy polyester 3.7 (8.2)

HDPE 1.8 (4.0)

Heavy-gauge steel 161 (354)

Polypropylene 1.8 (4.0)

Polystyrene 0.1 (0.2)

PVC 379 (835)

Stainless Steel 8.7 (19)

Fiberglass reinforced polyester 109 (239)

Motor 18 (40)

Total 1 942 (4 280)

Data for the galvanized steel sheet, cold rolled steel, and heavy-gauge steel come from World 

Steel (2011). U.S. LCI Database provided data for HDPE, PVC, general purpose polystyrene, 

polypropylene, and aluminum (assumed 50/50 primary and secondary). 

Ecoinvent provided data on the cast iron, control assemblies, stainless steel, epoxy resin (for the 

epoxy polyester), and fiberglass reinforced polyester. For the motor, a data set for an electric car 

motor, from ecoinvent, has been used as a guideline for the general material make-up of an 

electric motor. This data set includes the general materials in the motor, including rolled steel 

(75 % of total), aluminum (approximately 16 %), and copper wire (9 %). 

At the end of life, it is assumed that the cooling tower is removed from the building and recycled, 

especially since most of the materials are valuable recoverable metal and relatively easy to 

recover and remove from the building. The recycling methodology used is described in Footnote 

14. 

4.5.5 Overhangs

Overhangs can be used to block the entry of direct sunshine into a building throughout the warm 

summer months and allow in direct sunlight during the winter. The optimal application of an 

overhang can be calculated based on latitude, to maximize shade during the warm summer 

months and maximize sunshine in the winter. For example, this can be accomplished using a 

45.7 cm (18 in) overhang in Philadelphia where the sun is 85 % off the horizon in the summer at 
105

noon and drops to 25 % over the winter.28 Specifications for an overhang on a particular building 

in one part of the country may vary greatly from that in another part. 

For BIRDS, 0.09 m2 (1 ft2) of an overhang has been modeled for the LEC scenario. Overhangs 

are placed on the east, west, and south sides of the building for each floor in Climate Zone 1 

through Climate Zone 5 because these warmer climates are the zones that benefit from blocking 

solar radiation. The flow diagram below presents the general system boundaries for the 

overhang category, as it is modeled for BIRDS. 

Figure 4-10 Overhang System Boundaries 

Upstream Materials Production through Manufacturing

An aluminum overhang used on commercial buildings, including on curtain walls and storefront 

windows, has been modeled. The overhang modeled for BIRDS is meant to be an average, not 

one specifically designed for every building in every geographical location. The data are based 

on a product manufactured by Kawneer Company, Inc., the Outrigger System Versoleil 

SunShade, as shown in the figure below. According to a Kawneer architectural representative, 

the outrigger side piece, the fascia (end-piece), louvers (blades), and hardware that affix to the 

building are approximately 14.9 kg/m (10 lb/ft) for the 76.2 cm (30 in) deep outrigger 

model. For 1 ft2, this amounts to 1.8 kg (4.0 lb). 

Aluminum is modeled based on a 50/50 mix of primary and secondary extruded aluminum from 

the U.S. LCI Database. Manufacturing includes forming of the parts, and assembly. Parts 

forming data come from ecoinvent. Given its relatively simple design as shown in the figure 

below (taken from Kawneer, 2011), assembly is not expected to be a significant part of 

manufacturing impacts.

 

28 “Southern Overhangs”, retrieved July 2013 from 

http://www.greenandsave.com/cooling/c/southern_overhangs.html.

Use Phase EOL (recycling)

Overhang 

Production

Raw Materials 

Production

Transport to building site

Process 

Energy

Process aids

Emissions to air, 

water, soil

Transport to manufacturing
106

Figure 4-11 Outrigger System 

Transportation to the Building Site through End of Life

Transportation of the equipment to the building site is modeled based on an assumed average of 

805 km (500 mi) by heavy-duty diesel fuel-powered truck. Installation includes welding to affix 

the piece onto the building. The product lifetime is over 40 years so no replacement is 

necessary. Any maintenance needed, such as cleaning or refinishing the overhang, is not 

included. 

At the end of life, it is assumed that the aluminum overhang is removed from the building and 

recycled, especially since aluminum is a valuable, fully recyclable metal. See Footnote 14 for 

the recycling methodology used. 

4.5.6 Daylighting

A daylighting dimming control system is modeled for all of the climate zones for the LEC 

scenario. A dimming control system is used to adjust the level of electric light in a building 

when enough daylight can compensate for the electric source. Ander (2012) describes dimming 

controls as “continuously adjust[ing] electric lighting by modulating the power input to lamps to 

complement the illumination level provided by daylight.” A photo sensor is used to sense the 

natural daylight and match that to the lighting system output.

The system modeled in BIRDS is a dimming control system that can control several lighting 

zones. The functional unit is one square foot of light adjusted by a dimming system, based on 

the use of approximately 10 fixtures per 92.9 m2(1 000 ft2). 

Daylighting systems come in many configurations and range from very complex systems to very 

simple devices. The WattStopper LightSaver daylighting sensors and control system was chosen 

for data collection since it is being put into use in a range of buildings and applications and is a 
107

fairly commonly used system.29 The components included in the dimming system modeled for 

BIRDS include:30

 LightSaver LCD-203 Dimming Controller which “provides automatic dimming control 

for fluorescent and high-intensity discharge (HID) fixtures. It is an open loop controller 

providing up to three zones of control from a single photocell.” 

 LightSaver LS-290C Photosensor which “provides the daylight data necessary for 

operation of the LCD-203 daylighting control systems.”

 LightSaver BT-203 Power Pack which “powers the LightSaver LCD-203 control 

module.” 

 LightSaver Wall Switches which “allow occupants to temporarily override WattStopper’s 

automatic multizone daylighting control systems.”

Figure 4-12 Components of the Dimming System 

Three photo sensors and wall switches are used for one dimming controller and power pack. To 

meet the goal of approximately 10 fixtures per 93 m2(1000 ft2), three sets of systems have been 

modeled, i.e., three dimming controllers and power packs and nine photo sensors and wall 

switches. These were then normalized to 0.09 m2(1 ft2) of space.

The system requires the use of dimmable ballasts. In a retrofit application or upgrade where 

daylighting was not originally specified, then dimming ballasts need to be ordered with the 

dimming system and sockets in the existing fixture (fluorescent fixtures) need to be changed to 

accommodate for the dimming. However, in a new building in which a dimming system is 

 

29 Based on conversation with a representative at Stoneway Electric, Seattle, WA, April 2012.

30 Wattstopper product descriptions, accessed June 2013 from: 

http://www.wattstopper.com/categories/daylighting-sensors-and-controls/systems.aspx. 

LCD-203 Dimming Controller LS-290C Photo Sensor

BT-203 Power Pack Wall Switch

Source of each picture: http://www.wattstopper.com
108

specified, dimming ballasts are already installed. This system does not include the production of 

dimming ballasts in the new buildings. The flow diagram below presents the general system 

boundaries for the daylighting system, as it is modeled for BIRDS. 

Figure 4-13 Daylighting System Boundaries 

Upstream Materials Production through Manufacturing

The bill of materials for each component was obtained by way of complete tear-downs of each, 

presented in the tables below.

Table 4-49 Dimmer Controller LCD-203 Parts and Materials

Part Description Dimension MAss g (lb) Material

RJ12 cable

30.2 cm x 0.7 cm

(77 in x 1.8 in)

8.63 0.019 Cable

Case 54.34 0.120 Polycarbonate

Controller buttons 1.27 0.003 Rubber

Circuit board

8.7 cm x 6.7 cm

(22 in x 17 in)

57.59 0.127 Polychlorinated biphenyls

Circuit board

6.7 cm x 6.7 cm

(17 in x 17 in)

43.58 0.096 Polychlorinated biphenyls

Circuit board

6.7 cm x 3.8 cm

(17 in x 9.7 in)

11.18 0.025 Polychlorinated biphenyls

Display 

4.2 cm x 2.0 cm

(11 in x 5.1 in)

11.04 0.024 Liquid crystal display

Ribbon cable

7.5 cm x 1.7 cm

(19 in x 4.3 in)

1.13 0.002 flat cable

Use Phase EOL (recycling)

Dimming 

controller 

Production

Raw Materials 

Production

Transport to building site

Process 

Energy

Process aids

Emissions to air, 

water, soil

Transport to manufacturing

Photo sensor 

Production

Power pack 

Production

Wall switch 

Production

Production
109

Table 4-50 Photo Sensor LS-290C Parts and Materials 

Part Description Dimension Mass g (lb) Material

Circuit board 4.6 cm x 3.4 cm

(11.7 in x 8.6 in) 7.78 0.017 Polychlorinated biphenyls

White opaque cover 4.67 0.010 Polycarbonate

Translucent lense 8.21 0.018 Polycarbonate

Base 4.67 0.010 Polycarbonate

Adhesive circle 0.28 0.001 Acrylic

Table 4-51 Power Pack BT-203 Parts and Materials 

Part Description Dimension Mass g (lb) Material

Case 54.19 0.119 Polycarbonate

Circuit Board 1 6.6 cm x 6.6 cm

(16.8 in x 16.8 in) 33.25 0.073 Polychlorinated biphenyls

Circuit Board 2 8.7 cm x 6.7 cm

(22 in x 17 in) 117.02 0.258 Polychlorinated biphenyls

Table 4-52 Wall Switch LS-5C Parts and Materials 

Part Description Dimension Mass g (lb) Material

Cover plate 19.95 0.044 Polycarbonate

Push buttons 1.40 0.003 Polycarbonate

Mounting screws 3.11 0.007 Steel

Circuit board mounting screws 1.13 0.002 Steel

Circuit board 7.0 cm x 4.1 cm

(17.8 in x 10.4 in) 20.09 0.044 Polychlorinated biphenyls

Back plate cover 19.81 0.044 Polycarbonate

Materials

It should be noted that in the vast majority of cases, there were no material identifiers on the 

parts, so often a best-guess was made as to the actual material. Data for steel come from World 

Steel Association (2011). Data for acrylic binder, synthetic rubber, and polycarbonate come 

from ecoinvent, as does injection molding of the plastic parts. Ecoinvent electronics data 

modules were used for the electronics parts, and the following data sets were used for the 

specified parts:
110

Table 4-53 Ecoinvent Data Sets for Electronics Parts

Part Corresponding Ecoinvent Data Set(s) Unit 

Circuit board (PCB) Printed wiring board, surface mount Square area

Cable Cable, network cable, category 5, without plugs Length 

Plugs, inlet and outlet, for network cable Per piece

LCD display LCD glass Mass 

Ribbon cable Cable, ribbon cable, 20-pin, with plugs Mass 

Raw materials are modeled as transported to the manufacturing plant via combination diesel 

truck an assumed average distance of 805 km (500 mi).

Manufacturing data are included in the electronics components data sets, and parts forming (i.e., 

injection molding of plastics) is included with much of the raw materials production data. 

Assembly of these pieces of equipment is not included, however.

Transportation to the Building Site through End of Life

It is assumed that these components are manufactured in Asia, and Shanghai, China has been 

assumed. The transportation distance of 10 600 km (5 720 mi) by ocean freighter from Shanghai 

to Los Angeles, and then an average of 2 414 km (1 500 mi) by heavy-duty (combination) diesel 

fuel-powered truck to users in the U.S. has been modeled. 

Lighting loads in the buildings are discussed in Chapter 3. The energy simulations for the 

prototype buildings take into account lighting density, in watts per unit of conditioned floor area, 

appropriate to the building design (e.g., edition of ASHRAE 90.1 or LEC). The lighting load 

schedules take into account occupancy usage appropriate to the building types. For LEC cases, 

the dimming system is incorporated in these calculations.

Lighting systems, including daylighting controls for the LEC design, are assumed to be replaced 

every 20 years. At end of life, the components are removed from the building and are recycled 

with other electronic waste. 
111

5 Economic Performance Measurement

When a decision maker wants a dollar measure of cost effectiveness and cash flows are primarily 

costs, the most appropriate method for measuring the economic performance of a building is the 

life-cycle cost (LCC) method (ASTM, 2012). BIRDS follows the ASTM International standard 

method for life-cycle costing of building-related investments (ASTM, 2010). It involves 

calculating a cost’s present value (PV) by discounting its future value into 2009 dollars based on 

the year the cost occurs and the assumed discount rate. The formulas and discount factors used to 

calculate the present values will vary depending on the type of cost. The different cost types and 

related formulas, discount factors, and data sources are described below. 31

5.1 First Cost

5.1.1 Approach

The first costs of a building are the total costs of constructing a building in a particular city. First 

costs include costs for labor, materials, equipment, overhead, and profit. The construction costs 

for a prototype building are estimated by summing the costs of the baseline building (CNatAvg) and 

the changes in costs required to meet the prototype building design (ΔCx), adjusted for locationrelated cost variation as well as contractor and architectural profits. Both the baseline building 

costs and component cost estimates are based on national average construction cost data, and 

must be adjusted with the 2009 RS Means CostWorks City Indexes to control for local material 

and labor price variations in the 228 locations for which energy simulations are run. The 

“weighted average” city construction cost index (IWAvg) is used to adjust the costs for the baseline 

prototypical building while “component” city indexes (Ix) are used to adjust the costs for the 

change in component designs. The formula below shows the indexed construction cost (CIndex) 

calculation.

 ( ) ( ) ( ) ( ) 

 ( ) 

Where CIndex = Indexed construction costs

CNatAvg = National average construction costs

ΔCHVAC = Change in HVAC costs

ΔCWall = Change in wall insulation costs

ΔCRoof = Change in roof insulation costs

ΔCLight = Change in lighting costs

ΔCDaylight = Change in daylighting system costs

ΔCWindow = Change in window costs

ΔCOverhang = Change in overhang costs

IH = “Fire Suppression, Plumbing, & HVAC” cost index

IT = “Thermal and Moisture Protection” cost index

IE = “Electrical, Communications, & Utilities” cost index

IO = “Openings” cost index

 

31 See Kneifel (2012) for additional details on the cost data used in the BIRDS database.
112

Once the indexed construction costs of the building are calculated, it is necessary to adjust for 

the contractor and architect profits by multiplying the costs by the contractor “mark-up” rate

(IM), assumed to be 25 %, and then the architectural fees rate (IA), assumed to be 7 %, as shown 

in the following equation. 

 ( ( )) ( 

)

These mark-up rates are based on the default values used by the RS Means Square Foot Cost 

Estimator (SFCE). The marked-up, indexed construction costs are the first costs of constructing 

the prototype building in the particular city (CFirst).

5.1.2 Data

Building construction costs are obtained from the RS Means CostWorks online databases. The 

costs of a prototypical building are estimated by the RS Means CostWorks SFCE to obtain the 

default costs for each BIRDS building type for each component. The RS Means default building 

is the baseline used to create a building that is compliant with each of the five energy efficiency 

design alternatives: ASHRAE 90.1-1999, ASHRAE 90.1-2001, ASHRAE 90.1-2004, ASHRAE 

90.1-2007, and the higher efficiency “Low Energy Case" (LEC) design based on ASHRAE 

189.1-2009. The RS Means default buildings are adapted to match the five prototype building 

designs by using the RS Means CostWorks Cost Books databases. 

Five components -- roof insulation, wall insulation, windows, lighting, and HVAC efficiency --

are changed to make the prototypical designs compliant with ASHRAE 90.1-1999, -2001, -2004, 

and -2007. A summary of the minimum requirement ranges, excluding HVAC efficiency, for 

each building design are shown in Table 5-1. The windows are selected to meet the minimum 

window characteristics (U-factor, solar heat gain coefficient (SHGC), and visible transmittance 

(VT)) required by the building design at the lowest possible cost. The lighting density in watts 

per unit of conditioned floor area is adjusted to meet each standard edition’s requirements.
113

Table 5-1 Energy Efficiency Component Requirements for Alternative Building Designs

Design 

Component Parameter Units

ASHRAE 

90.1-1999

ASHRAE 

90.1-2001

ASHRAE 

90.1-2004

ASHRAE 

90.1-2007

Low Energy 

Case*

Roof Insulation R-Value m

2

∙K/W 

(ft2∙°F∙h/Btu)

1.7 to 4.4 

(10.0 to 25.0)

1.7 to 4.4 

(10.0 to 25.0)

2.6 to 3.5 

(15.0 to 20.0)

2.6 to 3.5 

(15.0 to 20.0)

4.4 to 6.2 

(25.0 to 35.0)

Wall Insulation R-Value m

2

∙K/W 

(ft2∙°F∙h/Btu)

0.0 to 3.8

(0.0 to 21.6)

0.0 to 3.8

(0.0 to 21.6)

0.0 to 2.7

(0.0 to 15.2)

0.0 to 2.7

(0.0 to 15.2)

0.7 to 5.5

(3.8 to 31.3)

Windows U-Factor

W/(m2∙K) 

(Btu/(h∙ft2∙°F))

1.42 to 7.21 

(0.25 to 1.27)

1.42 to 7.21 

(0.25 to 1.27)

1.99 to 6.47 

(0.35 to 1.14)

2.50 to 6.47 

(0.44 to 1.14)

1.97 to 6.42 

(0.35 to 1.13)

SHGC Fraction 0.14 to NR† 0.14 to NR† 0.17 to NR† 0.25 to NR 0.25 to 0.47

Lighting Power 

Density W/m2

(W/ft2)

14.0 to 20.5 

(1.3 to 1.9)

14.0 to 20.5 

(1.3 to 1.9)

10.8 to 16.1 

(1.0 to 1.5)

10.8 to 16.1 

(1.0 to 1.5)

8.6 to 16.1 

(0.8 to 1.5)

Overhangs None None None None Zones 1 to 5

Daylighting None None None None Zones 1 to 8

†North facing SHGC requirements are less restrictive than the requirements for the other 3 orientations.

* Low Energy Case design requirements are taken from the EnergyPlus simulations.

NR = No Requirement for one or more climate zones. By definition, the value of SHGC cannot exceed 1.0.

The LEC design increases the thermal efficiency of insulation and windows beyond ASHRAE 

90.1-2007, further reduces the lighting power density, and adds daylighting and window 

overhangs. The lighting density of the lighting system is decreased by first increasing the 

efficiency of the lighting system and then decreasing the number of fixtures in the lighting 

system.32 Daylighting is included for all building types and climate zones. Overhangs are placed 

on the east, west, and south sides of the building for each floor in Climate Zone 1 through 

Climate Zone 5 because these warmer climates are the zones that benefit from blocking solar 

radiation.33

Since the design of the BIRDS database, ASHRAE 90.1-2010 has been finalized and published. 

Table 5-2 gives a perspective of how the ASHRAE 90.1-2007 and LEC designs compare to 

ASHRAE 90.1-2010. In general, the requirements for ASHRAE 90.1-2010 are more strict than 

ASHRAE 90.1-2007 and less strict than the LEC design. The key exception is the lighting power 

density requirements for mid-rise and high-rise residential buildings, and wall insulation 

requirements for steel-framed mid-rise and high-rise residential buildings, where the 

requirements for ASHRAE 90.1-2010 are more restrictive than for the LEC design.

 

32 First, incandescent lighting is replaced with compact fluorescent lighting while typical T-12 fluorescent tube 

lighting is replaced with more efficient T-8 fluorescent tube lighting to decrease the lighting density of the lighting 

system. Second, the number of fixtures is reduced to meet the remainder of the required reduction in watts per unit 

of floor area. Increasing the efficiency of the lighting increases the costs of construction. The first approach 

increases first costs while the second approach decreases first costs for the lighting system. This approach is based 

on Belzer et al. (2005) and Halverson et al. (2006).

33 Overhang cost source is Winiarski et al. (2003)
114

Table 5-2 Energy Efficiency Component Requirements for the ASHRAE 90.1-2007, 

ASHRAE 90.1-2010, and LEC Designs

Design Component Parameter Units

ASHRAE

90.1-2007

ASHRAE

90.1-2010

Low Energy

Case*

Roof Insulation R-Value m

2

∙K/W 

(ft2∙°F∙h/Btu)

2.6 to 3.5

(15.0 to 20.0)

2.6 to 3.5

(15.0 to 20.0)

4.4 to 6.2

(25.0 to 35.0)

Wall Insulation R-Value m

2

*K/W 

(ft2∙°F∙h/Btu)

0.0 to 2.7

(0.0 to 15.2)

0.0 to 2.7

(0.0 to 25.0)

0.7 to 5.5

(3.8 to 31.3)

Windows U-Factor W/(m2∙K) 

(Btu/(h∙ft2∙°F))

2.50 to 6.47

(0.44 to 1.14)

1.99 to 6.47

(0.35 to 1.2)

1.97 to 6.42

(0.35 to 1.13)

SHGC Fraction 0.25 to NR 0.25 to NR† 0.25 to 0.47

Lighting Power Density W/m2(W/ft2)

10.8 to 16.1

(1.0 to 1.5)

10.8 to 16.1

(0.6 to 1.4)

8.6 to 16.1

(0.8 to 1.5)

Overhangs None None Zones 1 to 5

Daylighting None Zones 1 to 8 Zones 1 to 8

* Low Energy Case design requirements are taken from the EnergyPlus simulations, and are based on ASHRAE 189.1-2009.

NR = No Requirement for one or more climate zones. By definition, the value of SHGC cannot exceed 1.0.

Table 5-3 summarizes the HVAC efficiency requirements for each building design option across 

the different types of HVAC equipment.34 This first version of BIRDS assumes that cooling 

equipment is run on electricity while heating equipment is run on natural gas. Note that the LEC 

design assumes the same efficiency as ASHRAE 90.1-2007. The most significant increases in 

HVAC efficiency requirements occur between ASHRAE 90.1-1999 and ASHRAE 90.1-2001

except for rooftop packaged units, which have consistently increasing requirements across 

multiple ASHRAE 90.1 Standard editions.

Table 5-3 HVAC Energy Efficiency Requirements for Alternative Building Designs

HVAC 

Type

Equipment Type Unit ASHRAE 

90.1-1999

ASHRAE 

90.1-2001

ASHRAE 

90.1-2004

ASHRAE 

90.1-2007

Low Energy 

Case

Cooling Rooftop Packaged Unit EER 8.2 to 9.0 9.0 to 9.9 9.2 to 10.1 9.5 to 13.0 9.5 to 13.0

Air-Cooled Chiller COP 2.5 to 2.7 2.8 2.8 2.8 2.8

Water-Cooled Chiller COP 3.80 to 5.20 4.45 to 5.50 4.45 to 5.50 4.45 to 5.50 4.45 to 5.50

Split System with 

Condensing Unit

EER 8.7 to 9.9 9.9 to 10.1 10.1 10.1 10.1

Heating Hot Water Boiler Et 75 % to 80 % 75 % to 80 % 75 % to 80 % 75 % to 80 % 75 % to 80 %

Furnace Et 80 % 75 % to 80 % 75 % to 80 % 75 % to 80 % 75 % to 80 %

Assume that Ec = 75% Et and AFUE = Et, where Ec = combustion efficiency; Et = thermal efficiency; AFUE = Annual Fuel 

Utilization Efficiency

EER = Energy Efficiency Ratio

COP = Coefficient of Performance

Note: Efficiency requirement ranges are based on the system sizes calculated in the whole building energy simulations.

The HVAC system size varies across the five building designs because changing the thermal 

characteristics of the building envelope alters the heating and cooling loads of the building. The 

 

34 This study does not account for new HVAC efficiency requirements set by federal regulations.
115

EnergyPlus whole building energy simulations “autosize” the HVAC system to determine the 

appropriate system size to efficiently maintain the thermal comfort and ventilation requirements. 

For each building design, the HVAC cost for the default HVAC system is replaced with the cost 

of the “autosized” HVAC system. An HVAC efficiency cost multiplier is used to adjust the 

HVAC costs in accordance with the standard efficiency requirements shown in Table 5-3.

5.2 Future Costs

5.2.1 Approach

Building maintenance, repair, and replacement (MRR) costs are discounted to equivalent present 

values using the Single Present Value (SPV) factors for future non-fuel costs reported in Rushing 

and Lippiatt (2009). These factors are calculated using the DOE Federal Energy Management 

Program (FEMP) 2009 real discount rate for federal energy conservation projects (3 %). Table 

5-4 reports the SPV factors used in BIRDS. The MRR costs for each year (CMRR,i) are multiplied 

by the SPV for that year and then summed and indexed to determine the total present value MRR 

costs (CMRR).

Table 5-4 2009 SPV Discount Factors for Future Non-Fuel Costs, 3 % Real Discount Rate 

Yrs SPV Factor Yrs SPV Factor Yrs SPV Factor Yrs SPV Factor

1 0.971 11 0.722 21 0.538 31 0.400

2 0.943 12 0.701 22 0.522 32 0.388

3 0.915 13 0.681 23 0.507 33 0.377

4 0.888 14 0.661 24 0.492 34 0.366

5 0.863 15 0.642 25 0.478 35 0.355

6 0.837 16 0.623 26 0.464 36 0.345

7 0.813 17 0.605 27 0.450 37 0.335

8 0.789 18 0.587 28 0.437 38 0.325

9 0.766 19 0.570 29 0.424 39 0.316

10 0.744 20 0.554 30 0.412 40 0.307

The electricity and natural gas use predicted by the building’s energy simulation is used as the 

annual energy use of the building for each year of the selected study period. Electricity and 

natural gas prices are assumed to change over time according to U.S. Energy Information 

Administration forecasts from 2009 to 2039. These forecasts are embodied in the FEMP

Modified Uniform Present Value Discount Factors for energy price estimates (UPV*) reported in 

Rushing and Lippiatt (2009).35 Multiplying the annual electricity costs and natural gas costs by 

the associated UPV* value for the study period of interest estimates the present value total 

electricity costs (CElect) and natural gas costs (CGas). The discount factors vary by Census region, 

end use, and fuel type.

Total present value future costs (CFuture) is the sum of present value location-indexed MRR costs 

and present value energy costs, as shown in the following equation:

 

35 Since the U.S. Energy Information Administration forecasts end at year 30, the escalation rates for years 31-40 

are assumed to be the same as for year 30.
116

 

5.2.2 Data

Component and building lifetimes and component repair requirements are based on data from 

Whitestone (2008). Building service lifetimes are assumed constant across climate zones: 

apartment buildings last for 65 years; dormitories for 44 years; and hotels, schools, office 

buildings, retail stores, and restaurants for 41 years.

Building component maintenance, repair, and replacement (MRR) rates are from Kneifel (2010) 

and Kneifel (2011a). Insulation and windows are assumed to have a lifespan greater than 40 

years and have no maintenance requirements. Insulation is assumed to have no repair costs.

Windows have an assumed annual repair cost equal to replacing 1 % of all window panes, with 

costs that vary depending on the required window specifications. The heating and cooling units 

have different lifespans and repair rates based on climate, ranging from 4 to 33 years for repairs 

and 13 to 50 years for replacements.

Maintenance, repair, and replacement cost data are collected from two sources. The total 

maintenance and repair costs per square foot of conditioned floor area (minus the HVAC 

maintenance and repair costs) represent the baseline MRR costs per unit of floor area, which 

occur for a building type regardless of the energy efficiency measures incorporated into the 

design. These data are collected from Whitestone (2008), which reports average maintenance and 

repair costs per unit of floor area by building component for each year of service life for each 

building type. The building types in Whitestone do not match exactly to the 11 building types 

selected for this study, and the most comparable profile is selected.

RS Means CostWorks is the source of MRR costs for the individual components for which MRR 

costs change across alternative building designs, which in this analysis are the HVAC system, 

lighting system, and windows. Lighting systems, including daylighting controls for the LEC 

design, are assumed to be replaced every 20 years. The HVAC system size varies based on the 

thermal performance of the building design, which results in varying MRR costs because smaller 

systems are relatively cheaper to maintain, repair, and replace.

Future MRR costs are discounted to equivalent present values using the Single Present Value 

(SPV) factors for future non-fuel costs reported in Rushing and Lippiatt (2009), which are 

calculated using the U.S. Department of Energy's 2009 real discount rate for energy conservation 

projects (3 %). 

Annual energy costs are estimated by multiplying annual electricity and natural gas use predicted 

by the building’s energy simulation by the average state retail commercial electricity and natural 

gas prices, respectively. Average state commercial electricity and natural gas prices for 2009 are 

collected from the Energy Information Administration (EIA) Electric Power Annual State Data 

Tables and Natural Gas Navigator, respectively. 
117

5.3 Residual Value

A building's residual value is its value remaining at the end of the study period. In life-cycle 

costing it is treated as a negative cost item. In BIRDS, it is estimated in three parts, for the 

building (excluding HVAC and lighting), the HVAC system, and the lighting system, based on 

the approach defined in Fuller and Petersen (1996). The building's residual value is calculated as

the building's location-indexed first cost multiplied by one minus the ratio of the study period to 

the service life of the building, discounted from the end of the study period. For example, if a 

building has first costs (excluding HVAC and lighting) of $1 million, a 41 year service life, and 

the study period length is 10 years, the residual value of the building in year 10 (excluding 

HVAC and lighting) is ( 

 

 ) . The value is then discounted into 

present value terms.

Because they may be replaced during the study period, residual values for the HVAC and 

lighting systems are computed separately. Residual values for the HVAC system components, 

which have different lifespans across locations, are computed for each location. The remaining 

“life” of the HVAC equipment is determined by taking its service life minus the number of years 

since its last installation (as of the end of the study period), whether it occurred during building 

construction or replacement. The ratio of remaining life to service life is multiplied by the 

location-indexed installed cost of the system and discounted from the end of the study period. 

For example, assume an HVAC system’s installed costs are $100 000 with a service life in the 

selected location of 8 years, and a 10-year study period length. After one replacement, the system 

is 2 years old at the end of the study period, leaving 6 years remaining in its service life. The 

residual value in year 10 is 

 

 

 . 

While its lifespan does not vary across locations, the residual value for the lighting system is 

computed in a similar manner. The lighting system service life is 20 years.

The total residual value of the building and its HVAC and lighting systems, multiplied by the 

SPV factor for the number of years in the study period, estimates the present value residual value 

(CResidual).

5.4 Life-Cycle Cost Analysis

The total life-cycle cost of a prototype building (CLCC) is the sum of the present values of first 

cost and future costs minus the residual value as shown in the following equation:

 

LCC analysis of buildings typically compares the LCC for a “base case” building design to the 

costs for alternative, more energy efficient building design(s) to determine if future operational 
118

savings justify higher initial investments. For BIRDS, total life-cycle costs are calculated as 

described above for all building design options for all study periods. The user of the tool has the 

option to select any of the building designs as the “base case,” and compare it to any of the 

alternative designs. For an investor comparing mutually exclusive design alternatives, the same 

study period must be used for all alternatives. For those interested in the sensitivity of LCC 

results to the assumed study period length, BIRDS permits the study period length for a given 

building design to vary.

Two metrics are used to analyze changes in life-cycle costs: net LCC savings and net LCC 

savings as a percentage of base case LCC. Net LCC savings (NS) is the difference between the 

base case LCC (CBase) and alternative design LCC (CAlt) as shown in the following equation:

 

Net LCC savings as a percentage of base case LCC (PNS) is the net LCC savings divided by the 

base case LCC. This metric, shown in the equation below, allows for comparisons across 

building types that vary significantly in terms of floor area.

 

 

 

 
119

6 BIRDS Tutorial

BIRDS is a web-application designed for sustainability performance (energy, cost, and 

environmental impacts) comparisons for eleven different U.S. commercial building types. 

BIRDS provides the framework to take an initial building design and make comparisons across 

different locations, energy standard editions, and/or study periods. 

The comparison process has four steps:

1. Select the building prototype to evaluate. 

2. Select baseline values and alternatives for comparison (location, standard edition, and 

study period).

3. Select baseline and alternative weighting preferences for environmental performance.

4. View results graph and data.

BIRDS begins on the “BIRDS-Overview” tab shown in Figure 6-1, which describes the basic

information about the purpose of the tool. Once a user is familiar with the purpose of the tool, the 

user can begin the evaluation process.

Figure 6-1 BIRDS Overview
120

6.1 Selecting Building Prototype

From the “BIRDS – Overview” tab the user clicks on the “About Your Building” tab. The 

section expands, as shown in Figure 6-2. The user selects the My Building Prototype 

information by selecting Building Type and Number of Floors from the dropdown menus. Note 

that only apartments, dormitories, and office buildings have more than one option for the number 

of floors. The remaining building types have a default number of floors.

Figure 6-2 Selecting Building Prototype

By clicking on the red information icon, the building details are expanded as shown in Figure 

6-3. After selecting the building type the user wants to analyze, it is time to select what the user 

wants to compare.

Figure 6-3 Building Prototype Details
121

6.2 Selecting Comparisons

Clicking on the “About Your Comparisons” tab displays dropdown menus for the preferred 

Baseline Values for the building’s State, City, Standard Edition, and Study Period as shown in 

Figure 6-4. These are the baseline values that will be used for all comparisons. Note that all 

baseline values must be defined or an error will occur in the results. For illustration purposes, the 

Baseline Values are Anchorage, Alaska, using ASHRAE 90.1-1999 and a 10-year study period.

Figure 6-4 Selecting Comparisons

Next, the user can select alternative locations for comparison. After selecting a state from the 

scroll box, a checkbox list of available cities in that state will appear. The city/state combination 

will be added to the list to the right, which can contain up to 5 locations for comparison, as 

shown in Figure 6-5. The user can select up to 5 alternative Energy Standard editions from the 

checkbox list at the top right, which include ASHRAE Standards 90.1-1999, 90.1-2001, 

90.1-2004, 90.1-2007, and a Low Energy Case (LEC) based on ASHRAE 189.1-2009. Finally, 

the user can select up to 9 alternative Study Periods in the checkbox list at the bottom right, 

which range from 1 year to 40 years. Once the user has defined the baseline values and the 

alternative values for comparison, the user needs to define environmental weighting preferences.
122

Figure 6-5 Selecting Alternative Locations, Energy Standard Editions, and Study Periods

6.3 Selecting Environmental Weighting Preferences

Clicking on the “About Your Preferences” section displays the Baseline Environmental Impact 

Weightset dropdown menu, which includes 5 options as shown in Figure 6-6. Below the Baseline 

Weightset are the alternative weight-sets that will be available for comparison. By selecting the 

red information icon in the Pre-defined weights, the user can view the environmental impact 

values for pre-defined weight-sets.
123

Figure 6-6 Selecting Environmental Weighting Preferences

The user is given flexibility to create a custom weight-set by checking the Create Weightset

checkbox, which can be used as the baseline or as an alternative. As shown in Figure 6-7,

checking the box brings up a list of the 12 environmental impact categories. Each category must 

be given a weight between 0 and 100, with the sum of all 12 weights adding up to 100. Once a 

custom weight-set is defined it will become a selection available in the Baseline Weightset 

dropdown and as a checkbox in the My Weightsets alternative options. At this point, all the 

necessary user inputs have been defined and the user can now look at the results.
124

Figure 6-7 Defining a Custom Weightset

6.4 Viewing Results

Clicking on the “My Results” tab will display the “Select Chart Options” section. Three different 

chart types are available in the application: Life-Cycle Cost, Operating Energy, or Environmental 

Impact Score (EIS). As shown in Figure 6-8, the user must select the Chart Type from the 

dropdown menu, the Baseline for the comparison to be made, and the Units in which the user 

prefers the results. Note that the units include a per unit of floor area impact, which is only 
125

reported in square feet and not square meters because the tool is designed for use domestically, 

which predominantly uses I-P unit instead of metric units.

Figure 6-8 Selecting Chart Options

Once the user has made these selections, the user presses the “View Graph” button. The graph 

with corresponding data table is displayed. Figure 6-9 shows an example of the Life-Cycle Cost

results with a graph of the total life-cycle costs in present value dollars for a 4-story apartment 

building built to meet ASHRAE 90.1-1999 across the different study periods selected by the user
126

(10, 15, 20, and 25 years). As can be seen in the graph, total present value life-cycle costs 

increase as the study period increases in length, which is a result of additional operational energy 

costs and maintenance, repair, and replacement costs during those additional years.

Figure 6-9 Life-Cycle Cost Graph

The data table is more comprehensive, and includes all of the potential metrics available for 

comparisons across study periods for the baseline location, which include total life-cycle costs, 

change in total life-cycle costs relative to the 10-year baseline, total life-cycle costs per square 

foot of floor area, change in total life-cycle costs from the baseline per square foot of floor area, 

and percentage change in life-cycle costs relative to the 10-year baseline.

Figure 6-10 shows an example of the Operating Energy results with a graph of the change in 

annual energy consumption per square foot of floor area for a 4-story apartment building built to 
127

meet ASHRAE 90.1-1999 across the different locations selected by the user, including cities in 

Alabama, Alaska, Arizona, and Colorado. As can be seen in the graph, Anchorage, Alaska 

consumes more energy per unit of floor area than any of the other cities considered in the 

analysis. Colorado Springs consumes 5 kBtu/year/ft2less energy than the same building in 

Anchorage.

Figure 6-10 Operating Energy Consumption Graph

The data table shows all the metrics a user can use for comparisons: total annual energy 

consumption, change in total annual energy consumption, total annual energy consumption per 

square foot of floor area, change in total annual energy consumption per square foot of floor 

area, and percentage change in energy consumption relative to the baseline.
128

When the EIS Chart is selected an additional drop down menu is displayed that allows the user to 

select either the EIS or the total flows for one of the 12 environmental impact categories. Figure 

6-11 shows a graph of the total global warming potential impacts in kilograms of CO2e 

emissions. The newest edition of ASHRAE 90.1 considered in the analysis (ASHRAE 90.1-2004) 

realizes the lowest impact on global warming potential. The data table shows all the metrics a 

user can use for comparisons: total CO2e flows, change in total CO2e flows, total CO2e flows per 

square foot of floor area, change in total CO2e flows per square foot of floor area, and percentage 

change in total flows relative to the total flows for the baseline.

Figure 6-11 Environmental Impact – Global Warming Potential Graph
129

7 Limitations and Future Research

BIRDS is limited in scope and would be strengthened by including uncertainty analysis, 

expanding the database and metrics, and adding design flexibility to the tool.

Uncertainty analysis is needed for at least three elements of the analysis. First, consider the

assumed discount rate. Although 3 % is a reasonable discount rate, in real terms, for federal 

government investment decisions, it may be too low of a value for an expected real return on an 

alternative investment in the private sector. Sensitivity analysis on the assumed discount rate is 

needed to determine the robustness of the cost results. Second, the current analysis assumes that 

building cooling loads are met by equipment running on electricity while heating loads are met 

by equipment running on natural gas, which is not the typical fuel mix for some areas of the 

nation. The database should be expanded to include alternative fuel source options, such as 

heating oil use in the New England area. Third, the BIRDS environmental impact scores do not 

incorporate uncertainty analysis as required by international standards (ISO, 2006). While

incorporating uncertainty analysis is problematic due to a lack of underlying uncertainty data, 

this omission should be brought into the interpretation of the BIRDS results.

Additional data are needed to refine and expand the BIRDS database. The 11 prototypical 

buildings analyzed in this study may not be representative of the entire building stock for each 

building type. For example, all high-rise buildings are not 100 % glazed. For this reason, the 

results should be considered as general magnitudes for making reasonable comparisons instead 

of hard numbers. Future research should include additional prototypes, such as the DOE 

Benchmark Buildings, in the database. Additionally, since existing buildings account for nearly 

the entire building stock, prototypes for energy retrofits to buildings should be incorporated into 

the BIRDS database as well. The state average energy cost rates and energy-related carbon 

emissions rates do not control for local variation in energy tariffs or electricity fuel mixes. By 

using utility-level energy cost and emissions rate data, the accuracy of the estimates in BIRDS 

could be improved.

The analysis in this study ignores the impacts that plug and process loads have on the reductions 

in energy use. Buildings with greater plug and process loads will realize smaller percentage 

changes in energy use because the energy efficiency measures considered in this study focus on 

the building envelope and HVAC equipment, holding constant the energy use from other 

equipment used in the building. As building energy efficiency improves, the plug and process 

loads become a larger fraction of the overall energy load. Future research should consider the 

impact the assumed plug and process loads have on the overall energy savings realized by energy 

efficiency improvements to buildings.

Properly interpreting the BIRDS environmental performance results requires placing them in 

perspective. The environmental impact scores assess the life-cycle impacts of operating energy 
130

use based on inventories of localized energy simulation results and regional electricity grids. All 

other elements of the scores—including a building’s use of materials and its water consumption 

over the study period—are based on U.S. average life-cycle inventory data for prototypical 

buildings. The baseline data for these buildings represent status quo building technologies as of 

2002, the year of the latest available input-output data from the U.S. Bureau of Economic 

Analysis. To account for evolution in status quo technologies over time, future versions of 

BIRDS should incorporate newer releases of these data as they become available.

The BIRDS results do not apply to buildings constructed in other countries where industry 

practices, fuel mixes, environmental regulations, transportation distances, and labor and material 

markets may differ. Furthermore, all buildings of a given type are not created equal. Building 

designs, sizes, useful lives, materials compositions, and costs will all vary for an individual 

building. The BIRDS results for a building prototype do not necessarily represent the 

performance of an individual building of that type. Future versions of the tool should permit 

flexibility in building design and use of materials.

The BIRDS LCAs use selected inventory flows converted to selected local, regional, and global 

environmental impacts to assess environmental performance. Those inventory flows which 

currently do not have scientifically proven or quantifiable impacts on the environment are 

excluded, such as mineral extraction and wood harvesting which are qualitatively thought to lead 

to loss of habitat and an accompanying loss of biodiversity. If the BIRDS user has important 

knowledge about these issues, it should be brought into the interpretation of the BIRDS results. 

The Environmental Problems approach that BIRDS uses for impact assessment does not offer the 

same degree of relevance for all environmental impacts. For global and regional effects (e.g., 

global warming and acidification) the method may result in an accurate description of the 

potential impact. For impacts dependent upon local conditions (e.g., smog, ecological toxicity, 

and human health impacts) it may result in an oversimplification of the actual impacts because 

the indices are not tailored to localities. 

Life cycle impact assessment is a rapidly evolving science. Assessment methods unheard of a 

decade ago have since been developed and are now being used routinely in LCAs. While BIRDS

incorporates state-of-the-art impact assessment methods, the science will continue to evolve and 

methods in use today—particularly those for land and water use—are likely to change and 

improve over time. Future versions of BIRDS should incorporate these improved methods as 

they become available. 

During the interpretation step of the BIRDS LCAs, environmental impact results are optionally 

combined into a single environmental performance score using relative importance weights. 

These weights necessarily incorporate values and subjectivity. BIRDS users should routinely test 

the effects on the environmental impact scores of changes in the set of importance weights. 
131

Energy, environmental, and economic performance are but three attributes of building 

performance. The BIRDS model assumes that its building prototypes all meet minimum 

technical performance requirements. However, there may be significant differences in technical 

performance not evaluated in BIRDS, such as acoustic or fire performance, which may outweigh 

energy, environmental, and economic considerations. 
132
133

References

Ander, G.D. (2012). Daylighting, written for the Whole Building Design Guide, a program of the 

National Institute of Building Sciences. http://www.wbdg.org/resources/daylighting.php.

ASHRAE/IESNA Standard Project Committee 90.1, ASHRAE 90.1-1999 Standard- Energy 

Standard for Buildings Except Low-Rise Residential Buildings, 1999, ASHRAE, Inc.

ASHRAE/IESNA Standard Project Committee 90.1, ASHRAE 90.1-2001 Standard- Energy 

Standard for Buildings Except Low-Rise Residential Buildings, 2001, ASHRAE, Inc.

ASHRAE/IESNA Standard Project Committee 90.1, ASHRAE 90.1-2004 Standard- Energy 

Standard for Buildings Except Low-Rise Residential Buildings, 2004, ASHRAE, Inc.

ASHRAE/IESNA Standard Project Committee 90.1, ASHRAE 90.1-2007 Standard- Energy 

Standard for Buildings Except Low-Rise Residential Buildings, 2007, ASHRAE, Inc.

ASTM International (2011), Standard Practice for Applying the Analytic Hierarchy Process to 

Multiattribute Decision Analysis of Investments Related to Buildings and Building Systems, 

ASTM Designation E1765-11, West Conshohocken, PA.

ASTM International (2010), Standard Practice for Measuring Life-Cycle Costs of Buildings and 

Building Systems, ASTM Designation E917-05, West Conshohocken, PA.

ASTM International (2012), Standard Guide for Selecting Economic Methods for Evaluating 

Investments in Buildings and Building Systems, ASTM Designation E1185-12, West 

Conshohocken, PA.

Atherton, J., International Council on Mining & Metals (ICMM) (2006). Declaration by the 

Metals Industry on Recycling Principles, International Journal of Life Cycle Assessment,

January 2007, Volume 12, Issue 1, pp 59-60.

Atlas Roofing Corporation (2008). MSDS - Glass Reinforced Facer (GRF).

Atlas Roofing Corporation (2012). MSDS - Energy Shield/Energy Shield Plus/Cavity Wall.

Bakane, T. (2009). Properly Diagnosing Chiller Life Cycles. 

http://www.facilitiesnet.com/hvac/article/Properly-Diagnosing-Chiller-Life-Cycles--10645#

Baltimore Aircoil Company (BAC) Product and Application Handbook –Series 1500 

Engineering Data on Cooling Tower (no date). Accessed in May 2012 

from http://www.baltimoreaircoil.com/english/resource-library/file/543

Baltimore Aircoil Company (BAC) (2010). MS Word Document entitled “Series 1500 Cooling 

Tower Specification” (no date), Accessed in May 2012 from 

http://www.baltimoreaircoil.com/english/products/cooling-towers/series-1500/specifications. 
134

Bare, J. (2011), “TRACI 2.0: The Tool for the Reduction and Assessment of Chemical and Other 

Environmental Impacts 2.0,” Clean Technologies and Environmental Policy, published online 

January 2011. 

Bare, J. et al. (2006) “Development of the Method and U.S. Normalization Database for Life 

Cycle Impact Assessment and Sustainability Metrics,” Environmental Science and Technology, 

40: 16, 5108-5115.

Belzer, D.B., et al. (2005). Analysis of Potential Benefits and Costs of Adopting a Commercial 

Building Energy Standard in South Dakota, Pacific Northwest National Laboratory, PNNL15101.

Biswas, W. and M. Rosano, Curtin University (Perth) (2011). “A life cycle greenhouse gas 

assessment of remanufactured refrigeration and air conditioning compressors", Int. J. Sustainable 

Manufacturing, Vol. 2, Nos. 2/3.

Brundtland Commision, Our Common Future: Report of the UN Commission on Environment 

and Development, Oxford University Press, 1987.

Dewhurst, D., Smith Mechanical Quantity Survey Ltd., Jan 2012 data compilation. 

Energy Independence and Security Act of 2007, P.L. 110-140, Sec 441.

EUMEPS (2002). Behaviour of EPS in case of fire. Retrieved July 2012 at 

http://www.eumeps.org/show.php?ID=4471&psid=hmotjteo. 

Extruded Polystyrene Foam Association (XPSA) website. http://www.xpsa.com/. 

Flakeboard, no date. Product Data Sheet: FIBREX thin high density fiberboard. 

http://www.flakeboard.com.

Franklin Associates, A Division of ERG (Eastern Research Group) (2009). Energy and 

Greenhouse Gas Savings for EPS Roam Insulation Applied to Exterior Walls of Single Family 

Residential Housing in the U.S. and Canada, prepared for the EPS Molders Association. 

Fuller, S. and Petersen, S. (1996) Life-Cycle Costing Manual for the Federal Energy 

Management Program, NIST Handbook 135, 1995 Edition.

GAF Materials Corporation (2010). EnergyGuard Perlite Roof Insulation Data Sheet.

GAF Materials Corporation (2008). EnergyGuard MSDS #2060. 

Georgia Pacific (2009). Material Safety Data Sheet: Glass Mat-Faced Gypsum Panels.

Gloria, T. P., Lippiatt, B. C., and Cooper J. (2007) “Life Cycle Impact Assessment Weights to 

Support Environmentally Preferable Purchasing in the United States,” Environmental Science 

and Technology, 41, 7551-7557.
135

Goedkoop, M.J. et al., Recipe 2008, A Life Cycle Impact Assessment Method which comprises 

Harmonized Category Indicators at the Midpoint and the Endpoint Level; First edition Report I: 

Characterisation; http://www.lcia-recipe.net/, 2009.

Greenheck, Engineering Update (Summer 2004), “Gauge and Weight Chart for Sheet Steel, 

Galvanized Steel, Stainless Steel, and Aluminum.”

Guinee, J.B, et al., Handbook on Life Cycle Assessment: Operational Guide to the ISO 

Standards, Kluwer Academic Publisher, 2002.

Halverson, M.A., Gowri, K., and Richman, E.E. (2006). Analysis of Energy Savings Impacts of 

New Commercial Energy Codes for the Gulf Coast, Pacific Northwest National Laboratory, 

PNNL-16282.

Hendrickson, C. T., Lave, L. B., and Matthews, H. S. Environmental Life Cycle Assessment of 

Goods and Services: An Input-Output Approach, Resources for the Future Press, 2006.

Institute for Construction and Environment (2011), EPD according to ISO 14025: Trane 

Centrifugal Chiller 2500 Ton, EPD-TRA-2011111-E. http://www.bau-umwelt.com.

Intergovernmental Panel on Climate Change (IPCC) and the Montreal Protocol’s Technology 

and Economic Assessment Panel (2005). IPCC/TEAP Special Report: “Safeguarding the Ozone 

Layer and the Global Climate System.”

International Copper Association (ICA) (2012). Life Cycle Assessment of Primary Copper 

Cathode.

International Organization for Standardization (ISO), Environmental Management--Life-Cycle 

Assessment--Principles and Framework, International Standard 14040, 2006.

International Organization for Standardization (ISO), Environmental Management – Life Cycle 

Assessment – Requirements and Guidelines, International Standard 14044, 2006.

Johns Manville (2010). Fesco Roof Insulation Safety Data Sheet ID 3002.

Kawneer, an Alcoa Company (2011). Versoleil SunShade - Outrigger System, No. EC 97911-34.

Kneifel, J. (2010), “Life-cycle Carbon and Cost Analysis of Energy Efficiency Measures in New 

Commercial Buildings,” Energy and Buildings 42: 3, 333-340.

Kneifel, J. (2011a), “Beyond the Code: Energy, Carbon, and Cost Savings using Conventional 

Technologies,” Energy and Buildings, 43: 951-959.

Kneifel, J. (2011b). Prototype Commercial Buildings for Energy and Sustainability Assessment: 

Whole Building Energy Simulation Design, NIST Technical Note 1716.
136

Kneifel, J. (2012). Prototype Commercial Buildings for Energy and Sustainability Assessment: 

Design Specification, Life-Cycle Costing and Carbon Assessment, NIST Technical Note 1732.

LCAFood database, found at 

http://www.lcafood.dk/processes/industry/potatoflourproduction.htm.

Legutko, T. and M. Taylor, Carrier Corporation (2000). Split Systems: A Primer.

Levin, L. “Best Sustainable Indoor Air Quality Practices in Commercial Buildings,” Third 

International Green Building Conference and Exposition--1996, NIST Special Publication 908, 

Gaithersburg, MD, November 1996, p. 148.

McQuay International Product Catalog 611-1: Air-Cooled Scroll-Compressor Chillers, Model 

AGZ-D • 25 to 190 Tons • R-410A • 60Hz/50Hz.

Nath, N.G. & D.L. Ruff (1982). Perlite boards and method for making same. Publication No. 

U.S. 4313997 A. Found at: http://www.google.com/patents/US4313997.

National Renewable Energy Laboratory (NREL) (2005-present). U.S. Life-Cycle Inventory 

Database, Golden, CO. Found at: http://www.nrel.gov/lci/database.

PE International (2010). Eco-Profile of Aromatic Polyester Polyols (APP), performed for PU 

Europe, Federation of European rigid Polyurethane Foam Associations.

PE International, GaBi database (2011).

Phelan J. and G. Pavlovich, Bayer MaterialScience (2008) “Energy and Environmental Benefits 

of Insulating Commercial Buildings with Polyiso.” (Phelan, 2008)

Phelan J. and G. Pavlovich (Bayer MaterialScience), and J. Jewell (PE Americas) (2010). Life 

Cycle Assessment of Polyiso Insulation – Final Report, prepared for Polyisocyanurate Insulation 

Manufacturers Association (PIMA) (Bayer MaterialScience, 2010).

RS Means CostWorks databases, accessed 2009, http://www.meanscostworks.com/.

Rushing, A., and Lippiatt, B. (2009) Energy Price Indices and Discount Factors for Life-Cycle 

Cost Analysis-April 2009, NISTIR 85-3273-24.

Salazar, James, University of British Columbia (2007). Life Cycle Assessment Case Study of 

North American Residential Windows – A Thesis Submitted in Partial Fulfilment of the 

Requirements for the Degree of Master of Science in the Faculty of Graduate Studies.

Shah, V.P. et al., 2008. Life cycle assessment of residential heating and cooling systems in four 

regions in the United States. Energy and Buildings 40, 503–513. 

Slant/Fin Fine/Line 30 catalog, no. 30-10C (November 2004).
137

Suh, S. (2005) “Developing a Sectoral Environmental Database for Input-Output Analysis: The 

Comprehensive Environmental Data Archive of the U.S.,” Economic Systems Research, 17: 4, 

449-469.

Suh, S., (2010) “Comprehensive Environmental Data Archive (CEDA),” In: Murray J, Wood R 

(Eds.) The Sustainability Practitioner's Guide to Input-Output Analysis, Common Ground 

Publishing.

Suh S, et al. (2004) “System boundary selection in life-cycle inventories using hybrid 

approaches,” Environmental Science & Technology, 38: 657-664.

Suh S. and Huppes G (2005) “Methods for Life Cycle Inventory of a Product,” Journal of 

Cleaner Production, 13:687-697.

Suh, S. and Lippiatt, B. (2012) “Framework for Hybrid Life Cycle Inventory Databases: A Case 

Study on the Building for Environmental and Economic Sustainability (BEES) Database,” 

International Journal of Life Cycle Assessment, 17: 604-612.

Swiss Centre for Life Cycle Inventories (2007). ecoinvent Data v.2.2, Dubendorf. Found at: 

http://www.ecoinvent.org.

Swiss Centre for Life Cycle Inventories (2007). ecoInvent Data v.2.2 “Oil boiler 100kW/CH/I 

U”, from EcoInvent Report No 5: Life Cycle Inventories of Energy Systems: Results for Current 

Systems in Switzerland and other UTCE Countries (ecoinvent Report No. 5, 2007).

Trane Architectural Hydronic Wall Fin brochure, FIN-PRC004-EN (October 2001).

Trane Product Catalog: Split System Condensing Units —RAUJ; Remote Chiller Evaporators 20 

- 120 Tons — 50/60 Hz — R-410A.

Trane Catalog Series R Helical Rotary Liquid Chillers, 70-250 Tons Model RTWD WaterCooled (February 2010). No. RLC-PRC029-EN.

U.S. Department of Energy, Building Technologies Program, EnergyPlus Energy Simulation 

Software, 2009, http://apps1.eere.energy.gov/buildings/energyplus/.

U.S. Energy Information Administration, Electric Power Annual State Data Tables, accessed 

2009 and 2010, http://www.eia.doe.gov/fuelelectric.html.

U.S. Energy Information Administration, Natural Gas Navigator, accessed 2009 and 2010, 

http://www.eia.doe.gov/oil_gas/natural_gas/info_glance/natural_gas.html.

U.S. EPA Science Advisory Board, Toward Integrated Environmental Decision-Making, EPASAB-EC-00-011, Washington, D.C., August 2000.

U.S. EPA Science Advisory Board, Reducing Risk: Setting Priorities and Strategies for 

Environmental Protection, SAB-EC-90-021, Washington, D.C., September 1990. 
138

United Nations Environment Programme (UNEP) Report of the Technology and Economic 

Assessment Panel (TEAP) (2005). Volume 3: Report of the Task Force on Foam End-of-Life 

Issues.

Veissmann Vitorond 200 Triple-pass hot water heating boiler 1255 to 4387 MBH / 368 to 1285 

kW Technical Data Manual, No. 5285 428 v1.6. (July 2010).

Vigener, N. & M.A. Brown (2012). Building Envelope Design Guide – Windows, written for the 

Whole Building Design Guide, a program of the National Institute of Building Sciences. 

http://www.wbdg.org/design/env_fenestration_win.php

Whitestone Research (2008). The Whitestone Building Maintenance and Repair Cost Reference 

2008-2009, 13th Annual Edition.

Wilson, J.B., Oregon State University (2008). CORRIM: Phase II Final Report, Module F, 

Particleboard: A Life-Cycle Inventory of Manufacturing Panels from Resource through Product. 

Found at http://www.corrim.org/pubs/reports/2010/phase2/Module_F.pdf. 

Winiarski, D. et al. (2003) The Business Case for Sustainable Design in Federal Facilities: 

Appendix B: Energy and Construction Cost Estimates, Pacific Northwest National Laboratory 

and National Renewable Energy Laboratory.

World Steel Association (2011), Methodology report – Life cycle inventory study for steel 

products. http://www.worldsteel.org/
139

Appendix. Interpreting BIRDS Environmental Impact Scores: A Primer

Building ABC has a BIRDS Environmental Impact Score of 0.023 % and Building XYZ a score of 0.045 %. 

What does that mean?

Let’s start from the beginning, considering just one building and one environmental impact at a time. Let’s take a look, say, at the 

Global Warming performance of Building ABC, and ask:

Q. How much does the production and use of Building ABC over 40 years contribute to Global Warming?

A. BIRDS tells me that Building ABC contributes 8,520,000 kilograms of carbon dioxide-equivalent greenhouse gases over its life 

cycle.

Q. So what? All Buildings contribute greenhouse gases over their life cycle. Is 8,520,000 kilograms a lot or a little? How can I make 

sense of this number?

A. By relating the number to the total amount of greenhouse gases released every year in the United States. Let’s name these annual 

U.S. releases “John Q. Public” and have him represent our yardstick. Now let’s mark the spot showing Building ABC’s greenhouse 

gases relative to his.
140

Q. Okay. Let’s say you do that for Building ABC for all 12 environmental impacts. But then what? How can you combine all 12 

yardsticks when they’re measuring different things? Wouldn’t you be mixing apples and oranges?

7.16E+12

1

0.00E+00

1.00E+12

2.00E+12

3.00E+12

4.00E+12

5.00E+12

6.00E+12

7.00E+12

8.00E+12

Global Warming

kg CO2 equivalents

Environmental Impact
141

A. Yes, you would be, unless you made a single, common yardstick for all impacts—one based on Building ABC’s percentage share 

of John Q. Public’s impacts. That way, you could plot all impacts on the same graph. It’s like a nutrition label, but instead of reporting 

a building’s percentages of recommended daily allowances, we’re reporting its percentages of John Q. Public’s annual environmental 

impacts. Let’s do this for Building ABC and Building XYZ. 7.16E+12 kg CO2 eq 3.52E+13 kWh 2.24E+10 kg PM10 eq

1.05E+04 CTUHcan

1.69E+14 L

3.82E+13 CTUE

1.01E+10 kg N eq

1.81E+09 acre

5.03E+05 CTUHnoncan

4.64E+11 kg O3 eq

1.66E+12 H+ moles eq

5.10E+07 kg CFC-11 eq

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2.0E-6%

Share of Annual

U.S. Impact

Environmental Impact
142

Q. I’m still confused. It looks like Building ABC scores better on Global Warming, but worse on Water Consumption, than Building 

XYZ. How do I know which Building is environmentally preferred, all things considered? Can’t you just give me a simple average 

score? 

A. I could, but that would mean all environmental impacts are of the same importance. Most experts say that’s not the case, so I’ll give 

you a weighted average score instead. Then you can compare Building ABC side-by-side with Building XYZ when you’re shopping 

for “green” Buildings. But always remember, it’s better to have a lower BIRDS Environmental Impact Score. Think of the BIRDS 

Score as a penalty score—the higher it is, the worse it is. 7.16E+12 kg CO2 eq 3.52E+13 kWh 2.24E+10 kg PM10 eq

1.05E+04 CTUHcan

1.69E+14 L

3.82E+13 CTUE

1.01E+10 kg N eq

1.81E+09 acre

5.03E+05 CTUHnoncan

4.64E+11 kg O3 eq

1.66E+12 H+ moles eq

5.10E+07 kg CFC-11 eq

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Environmental Impact

Share of Annual

U.S. Impact

2.0E-6%
143

Percentage

points/unit

Q. Okay. But after all this, when I tell my colleagues that Building ABC, with a BIRDS Environmental Impact Score of 0.023 %, is 

greener than Building XYZ, with a score of 0.045 %, what am I really saying?

A. You’re saying that, over its life cycle, Building ABC does less damage to the environment than does Building XYZ. If your 

colleague’s eyes start to glaze over, quickly finish by saying that Buildings with lower BIRDS scores are greener. Otherwise, explain 

that Building ABC is greener because it contributes, on average, 0.023 % of annual U.S. environmental impacts, while Building XYZ 

contributes a larger share, 0.045 %.

0.0000

0.0100

0.0200

0.0300

0.0400

0.0500

0.0600

0.0700

0.0800

0.0900

0.1000

Building ABC Building XYZ John Q. Public

Score

Alternatives

Environmental Performance Global Warming

Primary Energy

Consumption

HH Criteria Air

HH Cancer

Water Consumption

Ecological Toxicity

Eutrophication

Land Use

HH Noncancer

Smog

Acidification

Ozone Depletion