\>EPA
United States
Environmental Protection
Agency
Office of Research and
Development
Washington, DC 20460
EPA/600/R-00/095
October 2000
www.epa.gov
Framework for Responsible
Environmental Decision-
Making (FRED): Using Life
Cycle Assessment to Evaluate
Preferability of Products
^onmental Prsfe
Framework for
Responsible
Environmental
Decisionmaking #
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EPA/6o6/R-66Ate5
October 2000
Framework for Responsible Environmental
Decision-Making (FRED): Using Life Cycle
Assessment to Evaluate Preferability of
Products
by
Science Applications International Corporation
11251 Roger Bacon Drive
Reston, VA 20190
Prime Contract Number: 68-C6-0027
Research Triangle Institute
3040 Cornwallis Road
Research Triangle Park, NC 27709
Roy F. Weston, Inc.
1 Weston Way
West Chester, PA 19380
and
EcoSense, Inc.
P.O. Box 92
West Rutland, VT 05777
Five Winds International
626 Meadow Drive
West Chester, PA 19380
Project Officer
Mary Ann Curran
Sustainable Technology Division
National Risk Management Research Laboratory
Cincinnati, Ohio 45268
NATIONAL RISK MANAGEMENT RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
CINCINNATI, OHIO 45268
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Notice
This report has been subjected to U.S. Environmental Protection Agency internal peer and
administrative review and approved for publication. Approval does not signify that the contents
necessarily reflect the views and policies of the U.S. Environmental Protection Agency, nor does
mention of trade names or commercial products constitute endorsement or recommendation for use.
This document is intended as a reference guide on how to determine environmental preferability for
products purchased by the federal government.
Users are encouraged to duplicate portions of this publication as needed to implement an
environmental preferability-based procurement program. Organizations interested in reprinting and
distributing the entire report should contact the Life Cycle Assessment Team, National Risk
Management Research Laboratory, U.S. EnvironmentalProtection Agency, Cincinnati, Ohio, 45268,
to obtain a reproducible master.
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Foreword
The U.S. Environmental Protection Agency is charged by Congress with protecting the Nation's
land, air, and water resources. Under a mandate of national environmental laws, the Agency strives
to formulate and implement actions leading to a compatible balance between human activities and
the ability of natural systems to support and nurture life. To meet this mandate, EPA's research
program is providing data and technical support for solving environmental problems today and
building a science knowledge base necessary to manage our ecological resources wisely, understand
how pollutants affect our health, and prevent or reduce environmental risks in the future.
The National Risk Management Research Laboratory is the Agency's center for investigation of
technological and management approaches for reducing risks from threats to human health and the
environment. The focus of the Laboratory's research program is on methods for the prevention and
control of pollution to air, land, water and subsurface resources; protection of water quality in public
water systems; remediation of contaminated sites and groundwater; and prevention and control of
indoor air pollution. The goal of this research effort is to catalyze development and implementation
of innovative, cost-effective environmental technologies; develop scientific and engineering
information needed by EPA to support regulatory and policy decisions; and provide technical support
and information transfer to ensure effective implementation of environmental regulations and
strategies.
The approach outlined in this document, called the Framework for Responsible Environmental
Decision-Making (FRED), was developed in support of the EPA's Office of Pollution Prevention
and Toxics as they establish the Environmental Preferable Purchasing (EPP) program EPP is in
response to Executive Order 13101 which requires EPA to develop guidelines on environmentally
preferable purchasing by the federal government. The goal of the program is to make the
environmental aspects of products a factor in purchasing decisions, along with the traditional factors
of technical performance and cost. FRED provides the basis for an approach that may be used to
consistently compare the environmental profiles of products on the basis of their impacts to human
health and the environment from raw material acquisition through ultimate disposal.
This publication has been produced as part of the Laboratory's strategic long-term research plan.
It is published and made available by EPA's Office of Research and Development to assist the user
community and to link researchers with their clients.
E. Timothy Oppelt, Director
National Risk Management Research Laboratory
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Abstract
Historically, purchase price and technical performance have been the two primary criteria in the
product selection process. In September 1998, President Clinton signed Executive Order 13101,
"Greening the Government through Waste Prevention, Recycling, and Federal Acquisition" which
defines the federal government's preference for "environmentally preferable" products and services.
The U.S. Environmental Protection Agency (U.S. EPA) developed the Framework for Responsible
Environmental Decision- Making (FRED): Using Life Cycle Assessment to Evaluate Preferability
of Products to assist the Agency's Office of Pollution Prevention and Toxics in their development
of guidelines for procurement officials in meeting the intent of this Executive Order.
The FRED decision-making methodology introduced herein demonstrates how the life-cycle concept
can be used to quantify competing products' environmental performance so that this information may
be integrated with considerations of total ownership cost and technical performance. Specifically,
this report describes how life cycle assessment (referred to as the FRED LCA approach) can be
applied to determine and compare the environmental and human health impacts of competing
products.
This report provides guidance on how to conduct a relative comparison between product types to
determine environmental preferability. It identifies data collection needs and issues; and describes
how to calculate numeric impact indicators for a given product or service across eight human health
and environmental impact categories. The eight categories were selected specifically to meet the
goal of the effort and include the following: Global Climate Change, Stratospheric Ozone Depletion,
Acidification, Photochemical Smog Formation, Eutrophication, Human Health, Ecological Health,
and Resource Depletion.
Case studies were conducted on three product categories (motor oil, wall insulation, and asphalt
coating) to evaluate the process as well as the output. It was concluded that the FRED LCA
approach can be performed in a much shorter time period than is typical for a more detailed LCA.
This more practical duration for procurement decisions is achieved though the focusing of data
collection and a simplified impact assessment procedure.
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Table of Contents
Notice ii
Foreword iii
Abstract iv
List of Exhibits vii
Acknowledgments viii
Chapter 1 - Introduction 1
Benefits of FRED 2
Appropriate Use of FRED 3
Roadmap to the Remainder of this Document 4
Chapter 2 - Framework for Responsible Environmental Decision-Making 5
Overview 5
Step 1: Goal and Scope Definition 5
Scope 6
System Function and Functional Units 6
Boundaries 8
Data Quality 9
Impact Categories and Indicator Models 15
Step 2: Life Cycle Inventory - Identification and Collection of Appropriate
Product Life-Cycle Data 16
Chapter 3 - FRED Impact Categories and Indicator Models 18
Step 3: Life Cycle Impact Assessment 18
Global Wanning 19
Stratospheric Ozone Depletion 23
Acidification 26
Photochemical Smog 29
Eutrophication 32
Human Toxicity 35
Ecological Toxicity 38
Resource Depletion 43
Other Issues Regarding the FRED Environmental Component 46
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Chapter 4 - Presentation and Interpretation of the Indicator 48
Overview 48
Presentation of Indicator Results 48
Weighting Among Indicators 50
Relative Weights Development Methods for the Weighting Step 51
Adopt an Existing Weighting Scheme 51
Analytic Hierarchy Process 52
Modified Delphi Technique 53
Decision Analysis Using Multi-Attribute Utility Theory (MAUT) 53
Linking FRED LCA with Technical Performance and Total Ownership Cost 54
Summary 55
Chapter 5 - Conclusions 56
Conclusions Regarding FRED 56
Conclusions Regarding the Environmental Component (i.e., FRED LCA System)
of FRED 56
Lessons Learned Regarding the Pilot Projects 57
Next Steps 58
References 59
Appendix A-l
Appendix A: Motor Oil Case Study A-2
Appendix B: Wall Insulation Case Study B-l
Appendix C: Asphalt Coating Case Study C-l
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List of Exhibits
Exhibit 1-1. FRED Methodology 1
Exhibit 2-1. Life Cycle Assessment Framework 5
Exhibit 2-2. Life Cycle Stages 6
Exhibit 2-3. Examples of System Function and Functional Units 7
Exhibit 2-4. Production Method Variability Analysis of LCI Data 11
Exhibit 2-5. Data Source Uncertainty Analysis of LCI Data 11
Exhibit 2-6. Variability/Uncertainty Analysis of LCI Data 12
Exhibit 2-7. Variability/Uncertainty Analysis of LCI Data 12
Exhibit 2-8. Classification of Product Types 14
Exhibit 2-9. Data Collection Requirements 15
Exhibit 2-10. Impact Categories and Indicator Models for the FRED LCA System 17
Exhibit 3-1. Global Wanning Potential Equivalency Factors 21
Exhibit 3-2. Stratospheric Ozone Depletion Potential Equivalency Factors 24
Exhibit 3-3. S02 Equivalency Factors for Acidification 27
Exhibit 3-4. Photochemical Smog Potential Equivalency Factors 30
Exhibit 3-5. Eutrophication Potential Equivalency Factors 33
Exhibit 3-6. Examples of Human Toxicity Potential Equivalency Factors 36
Exhibit 3-7. FRED Ecological Toxicity Method 40
Exhibit 3-8. Sample Ecological Toxicity Potential Equivalency Factors 41
Exhibit 3-9. Resource Depletion Factors 44
Exhibit 4-1. Graphical Presentation of Results 48
Exhibit 4-2. Spider-Web Footprint Display of Results 49
Exhibit 4-3. Rectangle Cut-out Footprint 50
Exhibit 4-4. Examples of Ranking within FRED 54
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Acknowledgments
This report was prepared under the direction and coordination of Mary Ann Curran of the U.S.
Environmental Protection Agency (U.S. EPA), Life Cycle Assessment Team Leader, National Risk
Management Research Laboratory, Cincinnati, Ohio.
Technical support was provided under prime contract to Science Application International
Corporation (SAIC). Authors of this document were Barry Leopold, Kim Mihalik, Steven Rolander,
and Timothy Skone of SAIC; Keith Weitz and Aarti Sharma of Research Triangle Institute; Agis
Veroutis of Roy F. Weston, Inc.; Rita Schenck, Ph.D. of Ecosense, Inc.; and James Fava, Ph.D. of
Five Winds International.
Life Cycle Inventory data for the pilot projects used in developing this reference guide were
graciously provided to the authors. Barbara C. Lippiatt, of the National Institute of Standards and
Technology (NIST), manages the BEES (Building for Economic and Environmental Sustainability)
program We recognize her generous support in time and in sharing the BEES database, specifically
wall insulation and motor oil data. Jose Garcia, of the National Highway Administration, was
instrumental in providing information for the asphalt pilot project, as was Jay Walters of Asphalt
Systems, Inc. Their support is also gratefully appreciated.
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Chapter 1 - Introduction
Choosing among competing products in the
marketplace can be a difficult process for the
federal procurement official. Although
purchase price and technical performance have
historically been the two primary criteria in
product selection process, as the result of
Executive Orders 12873 and 13101(see box),
and subsequent changes to the Federal
Acquisition Regulations (FAR), the
environmental performance of products has
also become an important selection criterion.
In response to these new directives, the EPA's Office of Research & Development conducted a
project to develop a practical methodology to guide environmentally preferable purchasing. The
overall approach is called FRED, the Framework for Responsible Environmental Decision-Making
and involves integrating price, technical performance and environmental information based on LCA
into purchasing decisions. This document focuses on the
approach for conducting the LCA component.
Life Cycle Assessment (LCA) is a cradle-to-grave
evaluation of the environmental effects of products and
services. It provides a holistic view of the
environmental aspects of products and services. The
FRED LCA model specifies many of the choices to be
taken in performing an LCA for environmental
preferability, thus reducing the variability between
studies. In addition, FRED provides baseline models for performing the impact assessment phase
of LCA for environmental preferability. These models were chosen as a balance among scientific
accuracy, simplicity of use and conformance with the international standards on LCA. As the science
of LCA improves, other models may prove to be more environmentally relevant without losing their
ease of use. For example, on-going research within the Office of Research & Development includes
the development of more sophisticated impact modeling called TRACI (Tool for the Reduction and
Assessment of Chemical and Other Impacts). The results of the TRACI model as it develops will be
incorporated into the FRED model as appropriate.
To the greatest extent feasible, FRED follows the requirements of the International Standards
Organization (ISO) 14040 series of standards.
It should be noted that the analysis will only be as good as the data that go into it. Hence, there may
be cases where FRED will not be able to draw a conclusion on environmental preferability, because
In October 1993, President Clinton signed Executive
Order 12873, "Federal Acquisition, Recycling, and
Waste Prevention," which directs Executive Agencies to
evaluate the environmental attributes of the $200 billion
in products and services purchased by the Federal
government each year. Executive Order 13101 entitled
"Greening the Government through Waste Prevention,
Recycling, and Federal Acquisition," signed September
14, 1998, further defines the Federal government's
preference for "environmentally preferable" products
and services.
FRED
LCAJ I Price) 1 Performance
Exhibit 1-1. FRED Methodology
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the data are incomplete or uncertain, or the results of the impact assessment do not clearly point to
a preferable system In these cases, the decision-maker will need to consider other factors such as
product costs (i.e. total cost of ownership) and technical performance. Weighting across impact
categories may also be needed. The process of assigning numeric values to impacts is based on value
judgments (usually made by the decision maker or decision-making group) and tends to be a
controversial part of LCA applications. However, several approaches to weighting exist and can be
applied to LCA results. These are explored in detail in Chapter 4.
Some of the guidance provided by FRED includes:
• A list of eight core environmental impact categories
• Indicators and models for each impact category
• Data quality requirements for different types of products
• Minimum indicator reporting requirements
Executive Order 13101 places primary requirements on federal purchasing agents based on single
characteristics such as percent recycled content. However, it is recognized that in some
circumstances, a life cycle review of the multiple environmental attributes of a product or service
may identify environmentally preferable products which do not meet single attribute criteria. FRED
provides guidance for demonstrating the overall environmental preferability of products as a possible
alternative approach to single attribute requirements. In the absence of product-specific life cycle
assessments based on FRED, purchasing agents must comply with the requirements of the executive
order and the associated FAR (Federal Acquisition Regulation), interpreting them as appropriate for
their uses.
LCA is a systematic approach to evaluating the environmental effects associated with any given
activity from the initial gathering of raw materials from the earth to the point at which all materials
are returned to the earth. This evaluation includes the use of resources and releases to the air, water,
and soil. LCA provides a holistic review of the potential impacts associated with particular products
and services, providing indicators of the relevant environmental impacts. Studies have been
conducted since the 1960s, with many organizations using LCA to holistically identify and evaluate
environmental effects of the products and services they offer and/or procure.
In its application of LCA, FRED further defines specifically for the user what types of engineering
and environmental data to collect. This is an important aspect of the FRED LCA system because it
reduces the time and resources required to perform the LCA while ensuring that products are being
compared in a fair and consistent manner.
Benefits of FRED
The FRED LCA methodology has been designed to provide the ability for procurement officials and
vendors to apply a greater degree of specificity, complexity, and/or completeness to the evaluation
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of competing products or services. Key benefits of using FRED in choosing among competing
products include:
• Simplification of data collection and impact assessment, making the approach easier to conduct
and more helpful to procurement officials and vendors.
• Generation of results that can be integrated with information oil product technical performance
via the functional analysis step of LCA.
• Facilitated comparative assertions that will be more consistent and scientifically-based using
indicators on environmental performance.
• Meeting the needs of the federal government to assess environmental benefits of competing
products and services (per E.O. 13101).
Appropriate Use of FRED
FRED is designed to compare two or more product types performing the same function (e.g., R-15
fiberglass wall insulation, R-15 blown cellulose wall insulation, etc). As in any LCA study, one of
the first activities in FRED is a functional analysis which integrates product technical performance
into environmental performance. While an analysis of a single product may be interesting, at the
minimum, products must be compared against industry average data in order to evaluate whether
they represent an environmentally superior product.
Since it is based on LCA, the FRED LCA system is limited by the data availability and assumptions
of the LCA technique. Comparisons must be made on an indicator by indicator basis (without
combining the different environmental indicators to provide a single score). Because of the
uncertainty of the data, differences between products should be at least an order of magnitude to be
considered. See more discussion on data uncertainty and variability in the following section, "Data
Quality."
It may be that an LCA identifies no true "winner" in terms of environmental preferability, either
because the differences between the two product types are too small, or because one product is better
in some areas and worse in others. In this case, the procurement officer can either fall back on price
and performance to make the purchasing decision or can utilize a stakeholder analysis and a
weighting methodology that is described in Chapter 4.
FRED does not consider criteria of concern such as socioeconomic issues, or occupational safety.
To the extent that these criteria are relevant to the procurement process, additional analysis may be
necessary.
The application of FRED discussed in this guidance document has been targeted to promoting the
inclusion of holistic environmental performance evaluation in the federal agency purchasing
decision-making process. The FRED methodology has been designed to provide the ability for
procurement/purchasing officials and/or vendors to apply a greater degree of specificity, complexity
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and/or completeness to the evaluation of competing products. These applications of FRED along
with guidance on the use of more sophisticated indicator models of human health and environmental
impacts will be discussed in future EPA research efforts.
Roadmap to the Remainder of this Document
This reference guide focuses on the approach used to apply the FRED LCA system to develop an
approach for both federal procurement officials and product vendors on how to determine holistic
environmental preferability in a practical, cost-effective method by comparing products from a life
cycle perspective. Chapter 2 provides guidance on the first two steps in the FRED methodology,
defining the product comparison's goal and scope and identifying/collecting the necessary data for
the analysis and performing error analysis to ensure that the conclusions of the FRED LCA system
will be valid. Chapter 3 describes how to calculate numeric impact indicators for a given product or
services in each of the eight human health and environmental impact categories modeled by HIED,
step three (impact assessment)in the methodology. Issues related to total cost of ownership and
technical performance are covered briefly in Chapter 4. Chapter 4 also provides guidance on how
to present the results to compare the environmental preferability of products using FRED. Chapter
5 provides conclusions and future steps. Information about pilot projects, which were used to test
and refine the FRED LCA system, are found in the appendices.
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Chapter 2 - Framework for Responsible Environmental Decision-Making
Overview
The Framework for Responsible Environmental Decision-Making (FRED) provides a fair and
consistent method for comparing the holistic environmental performance of products on the basis
of their impacts to human health and the environment from raw material acquisition through ultimate
disposal. As described in Chapter 1, FRED uses life cycle assessment (LCA) to achieve this
objective. The steps of LCA include goal and scope definition, inventory analysis, impact
assessment, and interpretation. Exhibit 2-1 illustrates the life cycle assessment framework as defined
by the International Standards Organization (ISO). The key to the FRED LCA system for providing
a fair and consistent method to compare products is through the use of uniform system boundaries,
data quality requirements, and selection of impact categories and associated indicator models. By
defining the majority of the decision points in the LCA process, the result is a consistent, practical,
and user-friendly method for evaluating the human health and environmental effects of products.
The remainder of this document highlights
the LCA process defined for use in FRED
to evaluate environmental preferability.
Specifically, guidance on Goal and Scope
Definition and Inventory Analysis are
provided in this Chapter. The Impact
Assessment process is outlined in detail in
Chapter 3. Chapter 4 provides guidance on
Interpretation of the results to determine
environmental preferability.
Step 1: Goal and Scope Definition
The goal and scope definition phase of the
FRED LCA system helps the user define
what data must be collected (boundary
definition), the functional unit by which
data are going to be collected, and the
quality of the data required to make an
accurate decision (accurately reflecting the
goal of the project).
/ Life Cyle Assessment Framework
/ [ Goal and Scope]^ / \ \
' I Definition
It
Inventory
Analysis
11
Exhibit 2-1. Life Cycle Assessment Framework
(Source: ISO 14040)
)
Interpretation
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Scope
As stated earlier in Chapter 1, the FRED LCA
system is based on the principle of evaluating
environmental impacts across the life cycle of
a product or service; i.e., raw materials
acquisition, manufacturing, use/reuse/
maintenance, and recycle/waste management.
These life cycle stages are illustrated in Exhibit
2-2. To consistently and fairly compare the
All products or services shall consider the
environmental impacts from raw materials
acquisition, production, manufacturing,
packaging, distribution, reuse, operation,
maintenance, and disposal to the greatest
extent feasible.
Inputs
Raw
Materials
Energy
Raw Materials Acquisition
lllllll
Manufacturing
Use / Reuse / Maintenance
r
Recycle / Waste Management
Outputs
, Atmospheric
Emissions
. Wateiborne
Wastes
. Solid
Wastes
- Coproducts
~ Other
Releases
System Boundaiy
environmental impacts
from competing products, it
is important that material,
energy, and environmental
release data, also referred to
as life cycle inventory (LCI)
data, are collected for all
life cycle stages. The scope
of each product's LCI must
be verified for similarity
prior to evaluating
environmental preferability.
System Function
Functional Unit
and
Exhibit 2-2. Life Cycle Stages (Source: EPA 1993)
As a first step in performing
an LCA, an analysis of the
function performed by the
different product systems
must be performed. It is this first step which
assures that the technical performance of
products is taken into account in evaluating the
environmental performance of competing
products. Sometimes, this analysis is a
straightforward exercise, but sometimes it is
quite complex. For example, in comparing two
different motor oils, one might take into
account the miles of protection provided (e.g.,
3,000 miles) without viscosity breakdown. On the other hand, one might compare the use of wall
insulation with different insulating factors. Here one must include the area to be covered, the
building construction, the average outside temperature (winter and summer), and the temperature
maintained and life-span of the product.
Comparisons between products or services
shall be made on the basis of the same system
function, quantified by each products
functional unit (i.e., the amount of product
required to fulfill the function).
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At a minimum, one must consider the following aspects of a system function in order to make a
legitimate comparison of two products:
• What is the intended function of the product? (Why does one wish to purchase a product or
service)
• What are the spatial characteristics of the function? (Area, volume, linear characteristics)
• What are the temporal characteristics of the function? (How long must it last, is the use
intermittent?)
• What are the specific technical performance requirements for this function? (Often spelled out
in technical requirements)
LCA practitioners define how data should be reported in terms of a functional unit. The functional
unit quantifies the amount of product required to fulfill the function. Comparisons between products
for environmental preferability must be made on the basis of the same function, and the LCI data
must be collected on the basis of each products functional unit. Exhibit 2-3 provides examples of
system functions and functional units for the 3 pilot projects used in generating this reference guide.
Exhibit 2-3. Examples of System Function and Functional Units
Product
System Function
Functional Unit
Motor Oil
(petroleum based)
10W30 motor oil that provides
3,000 mile protection without
viscosity breakdown to an
automobile engine.
1 quart of 10W30 Motor Oil
Motor Oil (vegetable
oil based)
10W30 motor oil that provides
3,000 mile protection without
viscosity breakdown to an
automobile engine.
1 quart of 10W30 Motor Oil
Asphalt (thin-layer)
Provide usable road surface (at
least a quality rating of 5 on a
scale of 10) for one lane mile of
asphalt cement road for 20 years.
2 applications of 1.5 inches of
asphalt cement and tack coat.
Asphalt (emulsion)
Provide usable road surface (at
least a quality rating of 5 on a
scale of 10) for one lane mile of
asphalt cement road for 20 years.
5 applications of asphalt
emulsion
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Product
System Function
Functional Unit
Wall Insulation (R-
13 Cellulose)
Provide a 70° F environment for
a 9,600 ft3 (1,200 ft2 x 8 ft.
ceilings) wood-frame residential
house with an avg. outside temp,
of 55° F, avg. winter temp, of 32°
F, and an avg summer temp, of
85° F. 50 year life-span.
1,200 ft2
Wall Insulation (R-
11 Fiberglass)
Provide a 70° F environment for
a 9,600 ft3 (1,200 ft2 x 8 ft.
ceilings) wood-frame residential
house with an avg. outside temp,
of 55° F, avg. winter temp, of 32°
F, and an avg summer temp, of
85° F. 50 year life-span.
1,200 ft2
Comparisons between products or systems must be made on the basis of the same system function,
quantified by each products' functional unit. If they are not based equally, environmental
preferability can not be determined from the results.
Boundaries
The system boundaries define which unit
process should be included in the life cycle
inventory (LCI) data collection to accurately
inform the decision making process. The
fundamental approach to collecting LCI data relies on the identification and quantification of
material, energy, and environmental release data using the engineering principle of a mass and
energy balance. Pre-defined boundaries are used to guide the LCI data collection process to direct
the amount of time and resources required to complete the mass and energy balance while
maintaining the study's ability to judge environmental preferability. Refer to EPA, LCI guidance
"Life-Cycle Assessment: Inventory Guidelines and Principles," EPA/600/R-92/245.
Since completing a full mass and energy balance can be quite time-consuming, certain simplifying
rules can be applied to data collection (as long as the goal of the study is not compromised). For
example, the following can be considered when setting boundaries for data collection:
• Mass - include all inputs that cumulatively contribute more than one percent (1%) to the total
mass input of the product system being evaluated.
• Energy - include all inputs that cumulatively contribute more than one percent (1%) to the total
energy input of the product system being evaluated.
Comparisons between products or services
shall be of equal breadth and depth.
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• Environmental Contribution - include all inputs that cumulatively contribute more than one
percent (1%) to the estimated quantity of each type of environmental release or impact
assessment category.
The 1% cut-off may be disregarded if a critical emission (such as a chemical that is toxic in small
quantities) is known to be part of the system and its omissions would not accurately reflect the
results of the impact modeling. The above guidelines for setting the required percent contribution
are to be investigated for accuracy and practicality for determining environmental preferability
during future pilot projects. Regardless of where the boundary lines are drawn for data collection,
it is important to ensure that equal boundaries (same breadth and depth) are used when comparing
products for environmental preferability to prevent misrepresentation of the final results.
Data Quality
The quality of data used to determine
environmental preferability can significantly
influence the results. The FRED LCA system
compares products to guide environmentally
preferable purchasing. As such, the quality of
data used must be sufficient to support such a
public decision. In addition, the quality of data collected for both products must be appropriate.
The reason why data quality is important for any comparative LCA application is that unless there
are meaningful and discernable differences among the data values of the products being compared,
the results of the comparison will be inconclusive. Error analysis determines mathematically and
statistically whether any differences in data values are indeed sufficient to rank the data values in a
meaningful manner, and thus facilitate conclusive results of the comparison.
As a general rule, the closer together the values of the LCI data are, the higher the data quality needs
to be. This simply translates as a need for smaller "error bars" as performance of products is closer
together. For example, if the difference between C02 emissions of two products is two orders of
magnitude, then conclusive results may be derived even if data quality is not very good, or data
sources for the two values are incomparable. On the other hand, improvement in precision of
measurements may not result in conclusive results if production process variability is greater than
the difference among the measured values. Therefore, careful attention must be given to the quality
of the data collected to ensure that a determination of environmental preferability can be reached at
the conclusion of the study.
Data quality characteristics include data uncertainty (based on data source), completeness,
comparability and variability. Completeness of a data set is evaluated by identifying data gaps. All
data gaps that exceed the system boundary thresholds noted above should be filled, either through
Comparison between products and services
shall be made with data of equal quality and
caliber to judge environmental preferability in
a public forum.
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additional data collection, or through the use of industry average data or surrogate data or
professional judgement.
Error Analysis
Error analysis is applied to a dataset to determine the range of possible overlap of inventory
emissions numbers. Without error analysis, inventory values that may seemingly appear different
enough to base a decision of environmental preferability, may prove to be too close to characterize
one alternative as preferable to another.
Once the error ranges have been determined, the analyst can identify which differences among
product alternatives are large enough and meaningful as to the performance of the product to justify
an EPP characterization of a product with the FRED LCA system
In the following sections we will discuss variability, precision, confidence, and data source
uncertainty. These data quality characteristics should help the user arrive at scientifically defensible
results, in the process of applying the FRED LCA framework to compare products. In those instances
when the datasets collected cannot support a defensible comparison, the error analysis will be able
to point this out in a clear and straightforward manner. The following is a reference discussion
intended to describe what are the implications of error analysis to comparisons of the environmental
performance of alternative products, but not how to perform it. (Additional information on how to
conduct an uncertainty analysis to verify the quality of life cycle inventory data can be found in the
EPA document, "Guidelines for Assessing the Quality of Life-Cycle Inventory Analysis," EPA530-
R-95-010.)
Variability Analysis
The variability of the actual inventory data values may be related to different production methods
available to produce the same components or ingredients. Variability may also arise by use of
variable grade input materials, differences in process performance based on ambient temperature
variations, scrap-rate of the process, ambient air humidity, and numerous other variables that may
affect process efficiency and effectiveness.
10
-------
That variation may produce a
variability spread (range) for
the outputs of a data category
for the production stage such
as those shown in Exhibit 2-
4. These should be discussed
and analyzed. This approach
is appropriate in a public
assertion LCA.
Precision, Validity, and
Data Source Uncertainty
Different data types that are
used in a life-cycle inventory
have different validity. Site-
specific data are collected by a practitioner at individual sites wnere tne specific unit processes are
situated and are operating. Non-site-specific data come fromother available sources. Surrogate data
is collected from different but reasonably similar processes which may be used in absence of Primary
data. Estimated data represent the
Life Cycle Inventory practitioner's
best judgment as to what the unit
operation's environmental releases
may be like in reality. The different
levels of data source uncertainty
associated with values of different
data types will affect the assurance
one has in the conclusions that can
be derived from any given data set.
An error analysis performed for the
specific data set used in a study
will determine the uncertainty
ranges for any two values based on
the data type of these specific
values. The approach is similar to
that of variability analysis, with the
added complexity of determining the validity corresponding to each data type, stemming from
possible lack of consistency in the data collection/generation, unequal resolution/significant digits
of the data values used, limits to detection, etc.
Exhibit 2-5 conceptually shows the error associated with different data (for products A and B, with
B produced two ways), and how these may be represented graphically.
5
~0
Production Method Variability Analysis of LCI Data
Product System B
Production
Method B1
_ Weighted_
Average B
Production
Method B2
Production
^^MethadBL <>_
Weighted Production
Average B Variability
Range
Produaion
Method B2
Exhibit 2-4. Production Method Variability Analysis
of LCI Data
I
I
Q
Data Si
(+) Qtta Source
Uncertainty for A
Weighted
Average A ~
(-) DanrSourte
Uncertainty for A
m
1
1
rce Uncertainty An
(4) BqtaSourc*
Uncertib&Jor Bi
Production
Method Bl ^
(•) D0*Source
\ Uncertainty for B.
a,
H
1
'ysis of LCI D
(+) Data Source
UitcertMtty-fgrBl
Production ^
Method B2 ^
(-)DtOrSMrce
C/ncertoJnty for B.
ai
i
ta
0
Product System A Product System E
Exhibit 2-5. Data Source Uncertainty Analysis
of LCI Data
11
-------
Combining the data source uncertainty, process data variability and production variability ranges -will
provide one with the overall uncertainty/variability range for the data point, that determines the
overall "ftizziness" of the data point. Exhibit 2-6 illustrates how the overall uncertainty/ variability
range may be conceptually
represented graphically.
VariabilityAJncertainty Analysis of LCI Data
(+) Dats^iource
UacertaintytorB!
*
I
¦s
3
1
a
Exhibit 2-7 demonstrates how the
inclusion of the variability ranges
could affect the resulting
conclusions in any of the categories
where a mass or energy
difference is identified by
introducing overlap of the value
ranges where there had been
differences before.
Mathematical methods, such as
error analysis, should be used to
verify that the difference in the
values used to determine
environmental preferability is
appropriate to interpret the results
of the study. Variability of
environmental data commonly
falls into the 0 to 100 percent
range. This natural variability is
one reason why comparison
between systems may not distinguish between systems that are less than an order of magnitude.
Production„
Method B1
Weights
Average B
Production
Method Bi
(-)Da i
Uac&
wurce
ntytorB2
~ Overall
Production Uncertainty/
Variability Variability
Range Range
~
-------
sources). For product comparison it is preferable that site-specific data be collected for unit processes
that contribute the majority of either mass, energy, or environmental relevance to the overall study
because the extent of data precision, completeness and representativeness can be determined.
Exhibits 2-8 and 2-9 provide additional guidance on prioritizing the need for site-specific versus
lion-site-specific data for different product types by life-cycle stage. The guidance provided below
is intended to reduce the time and resources required to collect LCI data for different product types
by focusing data collection efforts on life-cycle stages with the greatest suspected impact. Exhibit
2-8 can be used to classify a product based on its durability, energy consumption in the use stage,
and dispersion by use. Then, Exhibit 2-9 can be utilized to receive guidance on what data sources
should be used for the inventory portion of data collection.
13
-------
Exhibit 2-8. Classification of Product Types
Product Type
Energy
Characteristic1'2
Examples
Durable
Products that have a
long life-span (i.e.,
greater than 1 year).
Energy Intensive (in
Use stage)
• Vehicles • Buildings
• Computers • Appliances
Non-Energy Intensive
(in Use stage)
• Roads • Furniture
• Paint • Books
Non-Durable,
Dispersed
Products that have a
short life-span (i.e.,
less than 1 year), and
are dispersed in the
environment and can
not be recovered or
reused.
Energy Intensive (in
Use stage)
• Cryogenic paint stripping
• Fertilizer, commercial application (i.e.,
dispensed from motorized vehicle)
• Pesticide, commercial application (i.e.,
dispensed from motorized vehicle or
aircraft)
Non-Energy Intensive
(in Use stage)
• Detergents • Solvents
• Cleaners • Hair spray
• Cosmetics • Soap
Non-Durable, Non-
Dispersed
Products that have a
short life-span (i.e.,
less than 1 year), and
can be collected for
disposal at the end of
their life-span.
Energy Intensive (in
Use stage)
• Light bulbs • Dry-cell non-
• Disposable rechargeable
watch batteries
Non-Energy Intensive
(in Use stage)
• Razor blades • Paper cups
• Engine oil • Pencils
• Printer paper • Toothbrush
Note: 1. Energy Intensive - Products that require energy to perform their intended function.
2. Non-Energy Intensive - Products that require minimal energy to perform their intended
function.
14
-------
Exhibit 2-9. Data Collection Requirements
Life Cycle Stage
Site-Specific Data
Non-site-specific Data
Raw Materials
Acquisition
• None
• All Product Categories
Manufacture
• All Product Categories
Use/Reuse/
Maintenance
• Durable, Energy Intensive (in Use
stage)
• Non-Durable, Dispersed, Energy
Intensive (in Use stage)
• Non-Durable, Dispersed, Non-Energy
Intensive (in Use stage)
• Durable, Non-Energy
Intensive (in Use stage)
• Non-Durable, Non-
Dispersed, Energy
Intensive (in Use stage)
• Non-Durable, Non-
Dispersed, Non-Energy
Intensive (in Use stage)
Recycle/Waste
Management
• Durable, Non-Energy Intensive (in
Use stage)
• Non-Durable, Non-Dispersed, Energy
Intensive (in Use stage)
• Non-Durable, Non-Dispersed, Non-
Energy Intensive (in Use stage)
• Durable, Energy Intensive
(in Use stage)
• Non-Durable, Dispersed,
Energy Intensive (in Use
stage)
• Non-Durable, Dispersed,
Non-Energy Intensive (in
Use stage)
Transportation
(all LC stages)
• None
• All Product Categories
Impact Categories and Indicator Models
Environmental preferability is determined by
comparing the potential impacts to human
health and environment of products, and
selecting the product with the least potential
impact. How one measures the potential effects
on human health and the environment from a product is a point of great controversy in society and
a source of significant inconsistency in developing product comparisons. While there are many other
models and systems available for use to model environmental impact (see Chapter 4 for further
discussion), the FRED LCA system attempts to resolve issues of inconsistency by defining a group
of eight "core" impact categories (and associated indicator models) that model a product's human
15
All products or services shall be compared
using a minimum "core " group of eight impact
categories using prescribed indicator models.
-------
health and environmental effects to promote a fair and consistent system for comparison. Exhibit 2-
10 identifies the impact categories, indicator models, and the underlying data needed to assess the
different categories.
Collected LCI data may contribute to one or more impact category. For example,
chlorofluorocarbons (CFC's) released to the air may cause both global warming and stratospheric
ozone depletion. The FRED LCA system applies the total amount of CFC's released (100%) to both
impact categories to estimate the maximum potential impact to each category. This assignment is
appropriate because CFC's participate at full potency in both environmental mechanisms
simultaneously.
Step 2: Life Cycle Inventory - Identification and Collection of Appropriate Product Life-Cycle
Data
The second step in the FRED LCA system is to identify and collect all product life-cycle data that
will be used to estimate indicators of impacts to human health and the environment. To support the
calculation of impact indicators, data must be gathered describing the inputs (e.g., energy, materials,
water) and outputs (e.g., environmental releases, by-products, co-products) from all of a product's
life-cycle stages identified during Step 1, Goal and Scope Definition. A procedural framework for
life cycle inventory data collection can be found in the US EPA document, "Life Cycle Assessment:
Inventory Guidelines and Principles," (EPA/600/R-92/245). This work has been updated through the
development of the ISO 14041 document, "LCA Principles and Framework" finalized in September
1998.
As stated in the previous section, this data collection exercise can involve collecting both site-
specific data as well as the use of non-site-specific data in describing the impacts from each life cycle
stage of a given product. Both site-specific and non-site-specific data should be collected according
to life cycle stages and by environmental media in order to facilitate an increased interpretation and
presentation of results. Following the completion of the data collection process (LCI) the next step
is to transfer the data quantities of environmental releases and resources used into corresponding
impact categories.
16
-------
Exhibit 2-10. Impact Categories and Indicator Models for the FRED LCA System
Impact
Category
Impact Indicator
Model
Indicator
LCI Data Needed for Model1
Global Wanning
Intergovern-
mental Panel on
Climate Control
(IPCC)
C02
Equivalents
(kg)
Carbon Dioxide (C02)
Nitrogen Dioxide (N02)
Methane (CH4)
Chlorofluorocarbons (CFC's)
Hydrochlorotluorocarbons (HCFC's)
Methyl Bromide (CH,Br)
Stratospheric
Ozone Depletion
World
Meteorological
Organization
(WMO)
CFC-11
Equivalents
(kg)
Chlorofluorocarbons (CFC's)
Hydrochlorofluorocarbons (HCFC's)
Halons
Methyl Bromide (CH,Br)
Acidification
Chemical
Equivalents
Acidification
Potential
Sulfur Oxides (SOx)
Nitrogen Oxides (NOx)
Hydrochloric Acid (HCL)
Hydrofluoric Acid (HF)
Ammonia (NH4)
Photochemical
Smog
Empirical Kinetic
Modeling
Approach (EKMA)
Maximum
Incremental
Reactivity
Non-Methane Hydrocarbons
(NMHC's)
Eutrophication
Redfield Ratio
po4
Equivalents
(kg)
Phosphate (P04)
Nitrogen Oxide (NO)
Nitrogen Dioxide (N02)
Nitrates
Ammonia (NH4)
Human Health
University of
California -
Berkeley TEP's
Benzene,
Toluene,
TEP's
Toxic Chemicals
Ecological
Health
Research Triangle
Institute's LCI A
Expert Version 1
Toxic Chemicals
Resource
Depletion
Life Cycle Stressor
Environmental
Assessment
(LCSEA) Model
Quantity of Minerals Used
Quantity of Fossil fuels Used
Quantity of Precious Metals
Note: 1. The following are a sample of typical LCI items for each model. There are other LCI
items that may fall under one category or another that are not listed.
17
-------
Chapter 3 - FRED Impact Categories and Indicator Models
A variety of environmental impact categories and associated indicators have been developed and
more continue to be identified as the science evolves. The categories range from global impacts, such
as global wanning, to local impacts, such as photochemical smog. After completing a review of the
most common categories, eight impact categories were selected for use in the FRED LCA system
These categories were selected based on the goals of the effort, the breadth of the project's scope,
and the level of acceptance within the impact assessment community.
Step 3: Life Cycle Impact Assessment
A life cycle impact assessment (LCIA) can be used to evaluate a product's potential effect on human
health and environment. To accomplish this goal, the LCA principles of impact categories and
impact indicator models are used.
Impact categories are defined classifications of human health and environmental effects caused by
a product through out its life cycle. The FRED LCA system defines the following "core" group of
eight impact categories.
Global Warming
Stratospheric Ozone Depletion
Acidification
Photochemical Smog
Eutrophication
Human Toxicity
Ecological Toxicity
Resource Depletion
Impact indicators measure the potential for the impact to occur, rather than attempting to directly
quantify the actual impact. This approach works well in the FRED LCA system, because it is a
comparative method using relative magnitude to determine which product has less of a potential
impact, as opposed to a measure of a single product's absolute environmental impact. An impact
indicator is generally an intermediate node (i.e. a mid-point) on the environmental mechanism for
which there is a science-based correlation to the environmental impact. For example, one of the ways
global warming potential is quantified is to evaluate the radiative forcing potential of the greenhouse
gases in the atmosphere, because this measure integrates the forcing function on the earth's climate:
GHGs
Radiative
Forcing
Global Climate Change
(increasing temperature, etc.)
Environmental
Damage
18
-------
The ISO 14042 guidelines for impact assessment describe the need for environmentally relevant
indicators and that the indicator results should be clearly stated in terms of the following criteria:
a) The ability of the category indicator to reflect the consequences of the LCI results on the category
endpoint(s), at least qualitatively; and
b) The addition of environmental data or information to the characterization model, with respect
to the category endpoint(s), including:
- the condition of the category endpoint(s),
- the relative magnitude of the assessed change in the category endpoint(s),
- the spatial aspects, such as area and scale,
- the temporal aspects, such as duration, residence time, persistence, timing, etc.,
- the reversibility of the environmental mechanism, and
- the uncertainty of the linkages between the characterization model and the changes in the
category endpoints.
These criteria for environmental relevance were used to help select the impact indicators for the LCA
component of FRED. LCIA is a developing area and the FRED LCA system relies only on existing
methods and models. Therefore, not all of the criteria for environmental relevance were able to be
met. Each impact indicator has a checklist and description of how the indicator meets or does not
meet the ISO criteria for environmental relevance.
The following sections describe in detail the meaning of each impact category, the indicator which
represents the potential for the impact to occur, the model selected to quantify the associated affects
to human health or the environment, as well as the environmental relevance mentioned above.
Global Warming
Background
Global warming , or the "greenhouse effect," is defined as the changes in the Earth's climate caused
by a changed heat balance in the Earth's atmosphere. After water vapor, C02 is the most important
greenhouse gas. Normally, billions of tons of carbon in the form of C02 are absorbed by the oceans
and vegetation and are emitted to the atmosphere annually through natural processes. When at
equilibrium, the changes between absorption and emission are roughly balanced. The additional
anthropogenic sources of greenhouse gases (GHG's) present in the atmosphere may have shifted that
equilibrium, acting as a "thermal blanket"and trapping heat from reflected sunlight that would
otherwise pass through the atmosphere.
Altering the atmosphere by trapping more heat has been modeled to have a wide variety of effects
on the earth's climate, including longer growing seasons, droughts, floods, increased glaciation, loss
of the polar ice caps, sea level rise and other displacements, including direct effects on human health
19
-------
through biological agents. The speed of these projected effects, coupled with their widespread nature,
imply a devastating effect on the entire biosphere.
Calculating the FRED Global Warming Indicator
The Intergovernmental Panel on Climate Change (IPCC) global climate change model is used to
estimate the potential impacts to the environment from global warming. This model converts
quantities of GHG's into carbon dioxide (C02) equivalents using IPCC-defmed global warming
potential equivalency factors. Global Wanning Potential Equivalency Factors (GWP's) compare the
ability of each greenhouse gas to trap heat in the atmosphere relative to the heat-trapping ability of
C02.
GHG data obtained for each LCA stage are multiplied by the relevant GWP10„ (over a 100 year
lifespan) to produce C02 equivalent values. As the equivalency factors are unitless values, any unit
of weight can be used, as long as the unit of measurement is stated explicitly and are consistent
throughout the calculation. This process is done for each GHG, with the final step being the
summation of all C02 equivalents. The final sum, known as the Global Wanning Index (GW1),
indicates the product's potential contribution to global warming for each life cycle stage.
The following equation is used to calculate the GWI:
Global Wanning Index = Ij W; x GWPi( where
w; = weight of inventory flow i per functional unit of product
GWP; = Global Warming Potential Equivalency Factor evaluated at 100 years
= weight of C02 with the same heat-trapping potential as a gram of inventory flow i
Exhibit 3-1 shows the GWP's for some substances that are considered to contribute to global warming.
A 100-year lifespan was selected as the most suitable for the goal of this effort, although other bases
for calculating potential equivalency (such as 20-year or 50-year factors) are available.
20
-------
Exhibit 3-1. Global Wanning Potential Equivalency Factors
Substance
Formula
GWP
\vt C02/wt substance
over a 100-year lifespan
Carbon dioxide
C02
1
HFC-23
chf3
11700
HFC-32
ch2f2
650
HFC-41
ch3f
150
HFC-43-10mee
C-5H2f10
1300
HFC-125
C2HF5
2800
HFC-134
c2h2f4
1000
HFC 134a
ch2fcf3
1300
HFC-152a
c2h4f2
140
HFC-143
c2h3f3
300
HFC-143a
c2h3f3
3800
HFC-227ea
c3hf7
2900
HFC-236fa
c3h2f6
6300
HFC-245ca
C3H3F5
560
Chloroform
ch3ci
9
Methylene chloride
ch2ci2
1300
Sulfur hexafluoride
sf6
23900
Perfluoromethane
cf4
6500
Perfluoroethane
C2F6
9200
Perfluoropropane
C3F8
7000
Perfluorobutane
c4f10
7000
Perfluorocyclobutane
c-C4F8
8700
Methane
ch4
21
Nitrous oxide
n2o
310
(IPCC, 1995)
21
-------
Example
The following example uses LCI data from the BEES motor oil study (listed in Appendix A) to calculate the
Substance
T ransport
of Re-
refined Oil
for
Manufactu
re
W
P
, lgw) „„
rv
refined
Oil
productio
n
w
p
ewi
1 ranspor
t of Re-
refined
Oil for
Use
¦<3 W
P
m
Use
WF
-mi -
End of
Life
W
Iflll
GWl
C02
(biomass)
0
iiiill
0
0
i
0
0
WmM
0
0
I
Illiit
0
gill
ft
C02 (fossil)
13.000
i
noo-j
2.48E+02
l
24? COO
61.800
1
61 #00
0
|||||;
<3
0
111!
Q
Methane
0.005
(J 10S
1.23E-01
BiSliSgg:
0.021
zi
0.441
0
iKpjl
mm
0
0
N20
0.024
3JO
7 44.1
5.39E-03
0.011
310
3,4f0
0
mmmM
0
mm
0
Subtotal
20 600
3stm
6$ 701)
o
a
Total for all LC staves: 338.6e emiivalent CO,
Environmental Relevance
ISO Criteria
Met by
Indicator
Description
Consequence
Link
~
All greenhouse gases in the LCI are evaluated for their
radiative forcing potential. Changes in the heat balance of the
atmosphere are the forcing function for global climate change.
No attempt is made to calculate the effects on endpoints.
Environmental
Condition and
Intensity
NA
Does account for ambient concentrations of GHG's in the
atmosphere and the intensity of the global warming effect.
Does consider the variation in potency of different GHG's
(e.g., methane is a more potent GHG than C02) and the
absolute contribution of GHG's to global warming in terms of
C02 equivalents. Not applicable to location-specific projected
effects.
Spatial Aspects
~
Considers the potential impact on the global climate. However,
more refined spatial characterization, such as regional climate
change, is not captured.
Temporal
Aspects
~
Based on the 100 year time horizon.
22
-------
ISO Criteria
Met by
Indicator
Description
Reversibility
Does not consider the reversibility of global warming.
Uncertainty
Does not consider the uncertainty of global warming.
Stratospheric Ozone Depletion
Background
Stratospheric ozone depletion is the unnatural reduction of the protective ozone (03) layer, due in
part to chemical reactions with man-made substances. Stratospheric ozone is constantly being
created and destroyed thro ugh natural cycles. Various ozone-depleting substances (ODS's), however,
accelerate the destruction processes, resulting in lower than normal ozone levels. For example, when
a particular type of ODS known as chlorofluorocarbons (CFC's) reach the stratosphere, the
ultraviolet radiation from the sun causes them to break apart and release chlorine atoms which react
with ozone, starting chemical cycles of ozone destruction that deplete the ozone layer.
Reductions in ozone levels will lead to higher levels of UVB (a kind of ultraviolet light from the sun)
reaching the Earth's surface. Laboratory and epidemiological studies demonstrate that UVB causes
nonmelanoma skin cancer and plays a major role in malignant melanoma development. In addition,
UVB has been linked to cataracts. UVB also harms some crops, plastics and other materials, and
certain types of marine life.
Calculating the FRED Stratospheric Ozone Depletion Indicator
The Montreal Protocol Handbook, a primary guidance document on stratospheric ozone depletion,
uses ozone depletion potential, expressed as CFC-11 equivalents, as the indicator of the potential
for depletion to occur. The technique used for converting ODC's obtained fromLCI data to CFC-11
equivalents is the same as the method demonstrated for global climate change: multiply the
emissions values by the equivalency factor, and add the resultant equivalencies to arrive at the
product's overall potential contribution to stratospheric ozone depletion.
The model established by the Montreal Protocol uses the following technique for calculating the
equivalency potential (EP):
EP = £w; X EF;
where w, = weight of inventory flow i per functional unit of product
EF; = ozone depletion potential equivalency factor
= weight of CFC11 with the same potential ozone depleting effect as a gram of
inventory flow i
23
-------
Exhibit 3-2 shows the equivalency factors (EF's) for ODC's developed by the Protocol.
Exhibit 3-2. Stratospheric Ozone Depletion Potential Equivalency Factors
EF
wt CFCll/wt substance
Substance
Formula
°°(at infinity*)
CFC11
CFC1,
1
CFC12
CF2C12
0.82
CFC113
CF2C1CFC12
0.90
CFC114
CF2C1CF2C1
0.85
CFC115
cf2cicf3
0.40
T etrachloro methane
CC14
1.20
HCFC22
chf2ci
0.04
HCFC123
cf3chci2
0.014
HCFC124
CF3CHFC1
0.03
HCFC141b
CFC12CH3
0.10
HCFC142b
cf2cich3
0.05
HCFC225ca
CF3CF2CHC12
0.02
HCFC225cb
CF2C1CF2CHFC1
0.02
1,1,1 -trichlorethane
ch3cci3
0.02
Methyl chloride
ch3ci
0.12
0.02
Halonl301
CF3Br
12
Halon 1211
CF2ClBr
5.1
Methyl bromide
CHjBr
0.64
(EPA, 1999)
* different time scale factors are available; it is recommended by the Society of Environmental Toxicology and
Chemistry (SETAC, 1997) to use infinity.
24
-------
Example
The following example calculates the stratospheric ozone depletion potential
or a hypothetical process:
Substance
Raw
Material
Acquisitio
n
EF
BP
Mariufaot
uring
Process
H
T ransport
of Product
EF
EP
Use
till
EF
End of
Life
W
liil
CFC 11
0.50
1 00
oib
10.00
LOO
1000
0
i.bo
0 t>0
0.25
100
5.00
1.00
^oo
Halon 1211
2.00
^ (jO
600
1.00
3.00
3 00
0
t)f>
0.00
0.10
3 0(1
(110
0.50
t-SO
Methyl
Bromide
1.00
0.70
it 70
4.00
0,?Q
iilsl
0
O'O
ooo
0.20
o-'o
0 14
2.00
O-'O
i'4ti
Subtotal
72
SisM:
0
0.6!>
7,9
Total for all LC staees: 31.6 e eauiv. CFC11
Environmental Relevance
ISO Criteria
Met by
Indicator
Description
Consequence
Link
~
All ozone depleting substances in the LCI are evaluated for
their ozone destruction potential, but no attempt is made to
calculate effects on endpoints.
Environmental
Condition and
Intensity
Does not account for ambient concentrations of ozone depleting
substances in the atmosphere or the intensity of the ozone
depletion effect.
Spatial
Aspects
~
Considers the potential impact on the global level of ozone,
which is appropriate for this category. More refined spatial
characterizations, such as regional ozone depletion, are not
captured.
Temporal
Aspects
~
Evaluates the ozone depletion potential of substances integrated
over their atmospheric lifetimes.
Reversibility
Does not consider the reversibility of ozone depletion effects.
Uncertainty
Does not consider the uncertainty of ozone depletion.
25
-------
Acidification
Background
Acidification, or acid rain as it is commonly known, occurs when emissions of sulfur dioxide (S02)
and oxides of nitrogen (NOx) react in the atmosphere with water, oxygen, and oxidants to form
various acidic compounds. This mixture forms a mild solution of sulfuric acid and nitric acid.
Sunlight increases the rate of most of these reactions.
These compounds then fall to the earth in either wet form (such as rain, snow, and fog) or dry form
(such as gas and particles). About half of the acidity in the atmosphere falls back to earth through
dry deposition as gases and dry particles. The wind blows these acidic particles and gases onto
buildings, cars, homes, and trees. In some instances, these gases and particles can eat away the things
on which they settle. Dry deposited gases and particles are sometimes washed from trees and other
surfaces by rainstorms. When that happens, the runoff water adds those acids to the acid rain, making
the combination more acidic than the falling rain alone. The combination of acid rain plus dry
deposited acid is called acid deposition. Prevailing winds transport the compounds, sometimes
hundreds of miles, across state and national borders.
Electric utility plants account for about 70 percent of annual S02 emissions and 30 percent of NOx
emissions in the United States. Mobile sources (transportation) also contribute significantly to NOx
emissions. Overall, over 20 million tons of S02 and NOx are emitted into the atmosphere each year.
Acid rain causes acidification of lakes and streams and contributes to damage of trees at high
elevations (for example, red spruce trees above 2,000 feet in elevation). In addition, acid rain
accelerates the decay of building materials and paints, including irreplaceable buildings, statues, and
sculptures that are part of our nation's cultural heritage. Prior to falling to the earth, S02 and NOx
gases and their particulate matter derivatives, sulfates and nitrates, contribute to visibility
degradation and impact public health.
Calculating the FRED Acidification Indicator
Several indicators exist for acidification; the most common reference substances being hydrogen ions
and sulfur dioxide. Either can be expressed in terms of the other. The FRED methodology uses S02
as the reference chemical. The method for calculating the Acidification Index (AI) is similar in
approach to other impact indicators: the LCI substances that are present in the table below are
multiplied by the equivalency factor (AP) to arrive at S02 equivalent quantities. The S02 equivalents
for each life cycle stage are summed to calculated the Acidification Index (AI).
The following equation outlines the calculation:
Acidification Index = w, X AP;, where
26
-------
weight of inventory flow i per functional unit of product
Acidification Potential Equivalency Factor
weight of S02 with the same potential acidifying effect as a unit weight
inventory flow i
Exhibit 3-3. S02 Equivalency Factors for Acidification
AP
Substance
wt S
-------
The following example uses LCI data from the
acidification potential for the various life cycle sta;
Example
BEES motor oil study (list in Appendix A) to calculate the
?es in the oil rerefming process.:
I Substance
T ransport
of Re-
refined Oil
for
Manufactur
e
AP
M
Re-
refined
Oil
productlo
n
A)
T ransport
of Re-
refined Oil
for Use
ftp
A(
Use
AP
Al
End of
Life
AP
Ar
toxnonia
3.14e<08
2.95E-08
188
6&C®
7.92E-08
lis
0
1 Kf»
8
0
t.*8
llil
-fydrogen
Chloride
6.56fc-05
0K8
S 77e-05
3.68E-03
0 8S
iiiiiil
3.UE-04
0.S8
&
0
fl.8«
0
0
Ohk
illlf
-iydmgeti
^luoride
6.26E-66
If
1 ^le-Of
4.60E-04
1 a
iilit
3.89E-05
il
©
6
1 6
0
0
45
||§|§
Nitrogen
1 S.65E-62
0.7
2 I4e-u2
5.20B-01
0.56
1.45E-01
111
a ifl2
0
¦0 7
0
0
0 7
iulfur Oxides
U
I 92*02
1 54E+00
1,0
$mm
9.11E-02
MM .M,^,
tl8#;
0
5.0
Mili
0
$0
b
Subtotal
0.04
191
©19
0
Total for all LC stages: 2.J
4 g equivalen
S02
«s
Environmental Relevance
ISO Criteria
Met by
Indicator
Description
Consequence
Link
~
All acid precursors in the LCI are convertedto acidification
potential based on their chemical equivalancies. Deposition of
protons where neutralization capacity is exceeded is the forcing
function of acidification-
Environmental
Condition and
Intensity
Does not account for ambient concentrations of acid ions in the
atmosphere or the potential intensity of acidification effects to
the environment. Does consider the variation in potency of
different pollutants and the overall potential contribution of
acid precursors to acidification in terms of SOx equivalents.
This indicator represents an upper bound to acidification.
28
-------
ISO Criteria
Met by
Indicator
Description
Spatial
Aspects
Considers the potential for forming acid ions in a generic sense.
More refined spatial characterizations, such as regional
acidification, may be preferred and are not captured by this
indicator.
Temporal
Aspects
Does not consider the temporal aspects of acidification.
Reversibility
Does not consider the reversibility of acidification.
Uncertainty
Does not consider the uncertainty of acidification.
Photochemical Smog
Background
Ground-level ozone causes a variety of short-term and long term health effects, such as eye and
respiratory irritation, and pre-cancerous lesions. The oxidative ability of ozone causes damage to
forests, agricultural products and personal property (i.e., items using paint, rubber or plastics).
When fossil fuels (e.g., gasoline) are burned, a variety of pollutants are emitted into the earth's
troposphere, i.e. the region of the atmosphere in which we live - from ground level up to about 15
km The advent of increased automobile use in the last sixty years has led to increased levels of
reactive organic gases (ROG's) and oxides of nitrogen (NOx) in the air. Under certain conditions
these gases, in the presence of sunlight, can undergo complex chemical reactions that create ground-
level ozone. Two of the pollutants that are emitted are hydrocarbons (e.g., unburned fuel) and nitric
oxide (NO). When these pollutants build up to sufficiently high levels, a chain reaction occurs from
their interaction with sunlight in which the NO is converted to nitrogen dioxide (N02). N02 is a
brown gas and at sufficiently high levels can contribute to urban haze. However, a more serious
problem is that N02 can absorb sunlight and break apart to produce oxygen atoms that combine with
the 02 in the air to produce ozone (03). Ozone is a powerful oxidizing agent, and a toxic gas. In
North America elevated levels of tropospheric ozone cause several billion dollars per year damage
to crops (45 million/per year in Ontario), structures, forests, and human health. It is believed that the
natural level of ozone in the clean troposphere is 10 to 15 parts-per-billion (ppb). Because of
increasing concentrations of hydrocarbons and NO in the atmosphere, scientists have found that
ozone levels in "clean air" are now approximately 30 ppb. A principal activity of atmospheric
chemists is to study and determine how we might reverse this trend.
29
-------
Calculating the FRED Photochemical Smog Indicator
The FRED LCA system uses the Maximum Incremental Reactivity (MIR) approach to calculate this
indicator. The MIR approach is based on the chemical composition of air in 39 urban areas in the
US, which were modeled by keeping the light and VOC concentrations constant and varying the N02
concentration to achieve the maximal ozone production. (N02 is a catalyst at low concentrations and
an inhibitor at high concentrations). MIR values are very useful, as they are valid anywhere on the
globe. However, they represent an upper bound of ozone production, and must be viewed in that
light. In many Northern cities, there is not enough light most of the year to produce the full amounts
of ozone indicated by the MIR results. (Carter, 1998) For additional information on the MIR study,
see http://www.cert.ucr.edu/~carter/bycarter.htm.
Photochemical smog potential is calculated in the same way as global warming, but substituting in
MIR values.
Photochemical Smog Index (PSI) = Wj x MIR;, where
Wj = weight of inventory flow i per functional unit of product
MIR; = Maximum Incremental Reactivity value for inventory flow i
The MIR study contains equivalency factors for a variety of chemicals; a selection of chemicals from
the study is presented in Exhibit 3-4.
Exhibit 3-4. Photochemical Smog Potential Equivalency Factors (Carter, 1998)
Substance
wt ozone/ wt substance
Acetone
0.48
Benzene
1.0
Carbon Monoxide
0.07
Ethanol
1.92
Ethylene Glycol
2.65
Formaldehyde
9.12
Methanol
0.99
NMHC's
3.93
Phenol
1.86
Toluene
4.19
30
-------
Example
tlie following example uses LCI data from the BEES motor oil study (list in Appendix A) to calculate the
Substance
T rarisport
of Re-
refined Oil
for
Manufactu
re
MIR
PSI
Re-
refined
Oil
productio
n
¦m
PSI
Transpor
t of Re-
refined
Oil for
Use
iii
PSI
Use
TJWf
liii
End of
Life
ir
w
JSenzene
8.79e-07
1
4.03e-07
4.16e-06
sSgsl
0
s;:s:si:6
0
t
6
^larbon
Monoxide
1.15e-02
0 07
S 04e-04
1.90&-01
667
5.44e-02
0
5167
Pill
0
""6"67
Q
t*orm
1.17e-05
9 12
1 07&-04
5.39e-06
5.57e-05
llll
0
iii
ilil*
0
0
^IMHCs
S.62e-03
3.93
2 6C&-A2
1.28e-03
3^3
6o2e-6i?
3.13e-02
iii;
0
iill
0
c
Subtotal
0.0269
$ O.D1«3
sw
Total for all LC stages: 0.172S
g equivalent
ozone
Environmental Relevance
ISO Criteria
Met by
Indicator
Description
Consequence
Link
~
All smog precursors in the LCI are converted to a modeled MIR
scale by using the Empirical Kinetic Modeling Approach
(EKMA) and varying the levels of NOx and Reactive Organic
Gases (ROG's) to obtain the highest incremental reactivity.
There is an established link between NOx and ROG's in the
atmosphere and subsequent smog formation.
Environmental
Condition and
Intensity
~
Does not account for actual ambient concentrations of NOx and
ROG's in the atmosphere but rather uses averages from 39
cities in the U.S. to develop a base MIR model. The intensity of
the impact can be considered to be a maximum estimate
because NOx and ROG's are held at levels to obtain the
maximum incremental reactivity. The MER scale does consider
the variation in potency of different pollutants and the overall
potential contribution of the substances to smog by relating
smog precursors along the MIR scale.
31
-------
Spatial
Aspects
Considers the potential for forming photochemical smog in a
generic sense through use of the EKMA model and average
concentrations of NOx and ROG's in the atmosphere but rather
uses averages from 39 cities in the U.S. More site-specific
characterizations may be preferred and are not captured by this
indicator.
Temporal
Aspects
Does not consider the temporal variations of smog production.
Reversibility
Does not consider the reversibility of smog.
Uncertainty
Uncertainty adjusted MIR values are available but were not
used. The authors of the MIR model recommend using the
"best estimate" values for product categories.
Eutrophication
Background
Accelerated eutrophication is the reduction in water quality caused by excess nutrient loading.
Eutrophic waters are rich in organisms and organic materials, in contrast to oligotrophic waters,
which are characterized by clear water and low biological productivity. The rate of eutrophication
depends on complex relationships between several factors including water chemistry and depth,
volume and inflow, mineral content of the surrounding watershed, and the biota of the lake itself.
Human activities can increase the rate of eutrophication through increased nutrient flows, higher
temperatures, or other changes. While increased productivity is sometimes beneficial, eutrophication
often has undesirable results.
Accelerated eutrophication damages the aesthetic and recreational water qualities, as well as altering
species composition.. Water can become opaque with unpleasant taste and odors. This increased rate
of eutrophication can cause lakes and reservoirs that normally might exist for centuries to be filled
in a matter of decades. Under eutrophic conditions, the algae in the water significantly block the light
passage. Under hypereutrophic conditions, the amount of biomass produced is so high that the
dissolved oxygen in the water is used up, leading to fish kills.
Eutrophication in marine waters is typically caused by the addition of fixed nitrogen, while fresh
waters usually respond only to phosphorus inputs. The worldwide eutrophication of estuaries is
believed to be the cause of toxic algae blooms such as Pfisteria, and has also been implicated in
cholera epidemics on the Indian sub-continent.
32
-------
Calculating the FRED Eutrophication Indicator
Exhibit 3-6 shows the substances which cause eutrophication and their related equivalency values.
The eutrophication index is essentially the sum of all eutrophication precursors expressed in the form
of phosphate ion (P04) equivalents by multiplying the loading of each with its related equivalency
factor. These equivalencies are derived form the work of Redfield (1942), who discovered that
aquatic biomass forms with a Carbon to Nitrogen to Phosphorus (C:N:P) atomic ratio of 106:16:1.
The total eutrophication index (EI) for each alternative being assessed is calculated as follows:
Eutrophication Index = Lj W| x EP;
Wj = weight of inventory flow i per functional unit of product
EP; = eutrophication potential equivalency factor
= weight of P04 with the same potential eutrophying effect as a unit weight of
inventory flow i
Exhibit 3-5. Eutrophication Potential Equivalency Factors
Substance to Air
EP
wt P04/ wt substance
Ammonia
0.33
Nitrates
0.42
NO
0.2
N02
0.13
NOx
0.13
Phosphate
1
Substance to Water
Eutrophication Potential
g PO*/ g substance
COD
0.022
NH3
0.33
NH4+
0.33
(Redfield, 1942)
33
-------
The following examplf
eutrophication potentia]
Example
i uses LCI data from the BEES motor oil study (list in Appendix A) to calculate
for the various life cycle stages in the oil rerefining process.:
Substance
T ransport
of Re-
refined Oil
for
Manufactu
re
EUT
EUTI
Re-
refined
Oil
productio
n
HUT'
EUTI
T ranspor
t of Re-
refined
Oil lor
Use
EUT
EUTI""
Use
BJT
Eur!
End of
Life
EUT
EUTi
Ammonia
SiSe-64
53
i 2>e-04
8.67e-02
ill!
2 &6e-oi
1 82e-03
0
6
0
6 55
0
COD
2.22e-02
o!i±
4898-03
5.00e+0
0
622
1 10e+d
0
1,05e-01
022
k 32e-02
0
0
0
6 iS
0
Nitrates
2.35e-68
642
S 87O-09
1.32e-06
fe 54e-0?
1.11e-07
0
iiilil
0
6.f5£
iiti
0
Phosphates
Q
lill
iliiiil
0
in!
6
0
1
0
0
III
iiliiil
0
lill
0
subtotal
0.0050
1
0
0
Total tor all LC stages: 1.1621 g
eaulvalent P04
Environmental Relevance
ISO Criteria
Met by
Indicator
Description
Consequence
Link
~
All eutrophication precursors in the LCI are converted to
biomass equivalents using the Redfield Ratio. There is an
established link between nutrients in water bodies and
subsequent eutrophication.
Environmental
Condition and
Intensity
Does not account for ambient concentrations of phosphate or
nitrogen in water bodies or the intensity of the eutrophication
effects to specific water bodies. Does consider the variation in
potency of different pollutants that contribute to eutrophication
and the overall eutrophication potential by relating the
pollutants in terms of Phosphate equivalents. This measure of
eutrophication is a worst-case estimate.
Spatial Aspects
Does not consider the spatial variations, local or regional, of
eutrophication.
34
-------
ISO Criteria
Met by
Indicator
Description
Temporal
Aspects
Does not consider the temporal variations of eutrophication.
Reversibility
Does not consider the reversibility of eutrophication.
Uncertainty
Does not consider the uncertainty of eutrophication.
Human Toxicity
Background
Industrial systems often release substances into the environment which can have toxic effects on
human beings. In order for actual effects to occur, exposure to the substance must occur, the
substance must be assimilated, and the received dose to the individual must exceed the body's ability
to detoxify it.
There are a multiplicity of potential toxic effects of industrial and natural substances, ranging from
transient irritation to permanent disability and even death. Some substances have a wide range of
different effects, and different individuals have a widely varying tolerance to different substances.
Finally, of the millions of industrial chemicals, very few have been subjected to toxicological
evaluation. All these factors make an assessment of the human toxicity potential of given substances
difficult at best. When evaluated on a life cycle basis, evaluating their impact is even more
problematic.
Nevertheless, because human toxicity is a real and important environmental issue, the FRED LCA
system incorporated an indicator based on the recommendations of the International Life Sciences
Institute, which suggested that all life cycle human toxicity indicators be based on no observable
adverse effects levels (NOEL's, NOAEL's) or lowest observable effects levels (LOEL's, LOAEL's).
In other words, concentrations or doses of chemicals tested on humans or laboratoryanimals that
caused no effect or minimal effect. Generally, the lower the NOAEL or LOAEL, the more toxic the
chemical.
Calculating the FRED Human Toxicity Indicator
The FRED methodology uses Environmental Defense Fund (EDF) Scorecard,
(http://www.scorecard.org) developed in conjunction with University of California at Berkeley, as
an indicator of human toxicity. This indicator is actually a pair of indicators, one for carcinogenic
and one for non-carcinogenic effects:
Human Toxicity Index = E, w( X TEP;
35
-------
Wj = weight of inventory flow i per functional unit of product
TEP; = toxic equivalency potential
= (for carcinogens) weight of benzene with the same potential
cancer-causing effect as a unit weight of inventory flow i
= (for non-carcinogens) weight of toluene with the same potential
toxic effect as a unit weight of inventory flow i
Exhibit 3-6. Examples of Human Toxicity Potential Equivalency Factors
Substance to Air
TEP
(carcinogens)
wt Benzene/ wt substance
TEP
(non-carcinogens)
wt Toluene/ wt substance
Ammonia
3.2
Benzene
1
17
Formaldehyde
0.003
7
Lead
15
1,300,000
Phenolics
0
0.045
Substance to
Water
Ammonia
(NH4+, NH, as N)
0
0.041
Benzene
0.99
11
Phenols
0.0038
(EDF, 2000)
Example
ttie following example uses LCI airborne emissions data from the BEES motor oil study (list in Appendix A)
^ calculate the carcinogenic human toxicity potential for the various life cycle stages in the oil rerefining
Process.:
Substance
Transport
of Re-
refined Oil
for
Manufactu
re
TEP
Hit
Re-
reflned
Oil
productio
n
.TEP
HT)
T ranspor
t of Re-
refined
Oil for
U86
in;!
, m
Use
TEP
HTI
End of
Life
TEP
HTf
1.67e-08
111
Q
ill
0
111
mm
0
ill
wmmm
8
-J
iii
0
*
0
O
j^ormalcta.
1.188-05
0.00
3
3 53e-08
""
5.40e-06
(5,00
3
1626-08
5.37e-05
flW
3
1 &7&-07
0
0 003
Q
0
TEqo
a
Q
0
0
ft'
15
Q
0
ts
8
SKfiSK
Phenolics
Subtotal
U
w
asms
V
V
IIP
—1
lili
^
i
roar tor an lc stages: s.e
Ibenzena
60-0 g equivalent ||
: : 1
36
-------
Environmental Relevance
ISO Criteria
Met by
Indicator
Description
Consequence Link
~
Uses CALTOX model to estimate media concentrations of
pollutants and to develop relative scores. Benzene is used as the
reference chemical for cancer affects and tolulene for non-
cancer effects. Does not consider specific human health effects
beyond the broad categories and cancer and non-cancer effects.
Environmental
Condition and
Intensity
Does not consider ambient environmental (beyond that
imbedded in CALTOX), exposure conditions, or the intensity
of human health effects for chemical pollutants. Considers the
relative toxicity of cancer and non-cancer effects of chemical
pollutants to humans.
Spatial Aspects
Does not consider the spatial variations, usually site-specific, in
release and exposure to populations.
Temporal Aspects
~
Considers the persistence and bioaccumulation of chemical
pollutants in the environment.
Reversibility
Does not consider the reversibility of human health effects.
Uncertainty
Does not consider the uncertainty of human health effects.
37
-------
Ecological Toxicity
Background
Ecological impact indicators consider potential adverse effects on populations of aquatic or terrestrial
organisms. Therefore, the benchmarks used tend to address survival of populations rather than single
organisms. Acute and chronic NOAEL's for aquatic (invertebrates and fish), mammalian, and avian
species are considered.
The FRED Ecological Toxicity method includes measurements of relative hazard (toxicity factors
or benchmarks) and environmental fate and transport (persistence and biomagnification factors). The
approach involves the following steps (other than screening and significance assessment steps (also
see flow chart):
1. Identify aquatic and terrestrial benchmarks for both acute and chronic toxicity.
2. Assign chemicals a default benchmark if data are missing. The geometric mean of the available
benchmarks is used as the default.
3. Normalize benchmarks within each category based on the geometric mean.
4. Select the maximum normalized benchmark as the toxicity factor.
5. Identify persistence factors for pertinent environmental media.
6. Identify biomagnification factors.
7. Multiply toxicity, persistence, and biomagnification factors (TPB score) for each inventory flow
within each environmental medium.
8. Multiply TPB scores by the inventory mass per functional unit.
9. Sum factors to derive total terrestrial and aquatic ecological toxicity impact indicator (ETI).
Determine the percentage of each ETI relative to the total ETI and select inventory flows
contributing 0.1 % (or a user-selected value) or more. Each of these steps are illustrated below.
Step 1: Ecological benchmarks have been derived primarily for fish and aquatic life, mammals,
birds, and plants. Two broad categories of ecological benchmarks were selected. Aquatic
benchmarks may be used to address releases to water and terrestrial benchmarks may be used to
address releases to air or land. The LCJ0 was selected as one of the most commonly available acute
benchmarks for aquatic life. In addition to the LC50, acute and chronic lowest observed effect
concentrations (LOEC's) or no observed effect concentrations (NOEC's), and water quality criteria
are available for many chemicals. Similarly, LDS0's and the lowest chronic no observed effect levels
(NOEL's) reported for mammalian and avian species were selected to evaluate potential impacts to
terrestrial species.
Steps 2.3 and 4: The geometric mean of each benchmark type is calculated from the available data
and is used as the default for missing values. Benchmarks are then normalized based on the
geometric mean and the highest normalized benchmark is selected as the toxicity factor for terrestrial
and aquatic impacts.
38
-------
Steps 5 and 6: ILSI (1996), USEPA (1994a,b), and RTI (1993) include persistence factors.
Generally, persistence factors are derived from expected environmental half lives or from residence
times as estimated in multi-media fugacity models (Mackay, 1991). Recommended persistence
factors are those developed in RTI (1993) and range from 0.25 to 0.75. A default value of 0.5 for
organic pollutants in all media is used and a default value of 0.5 and 1 are used for metals in air and
all other media, respectively.
ILSI (1996) does not include biomagnification factors in their methodology but USEPA (1997,
1994a) and RTI (1993) do. It is recommended that pollutants be assigned to high, medium, or low
categories to represent biomagnification potential. Biomagnification factors can be derived from
Kow's or reported bioconcentration factors (BCF's) and bioaccumulation factors (BAF's). Standard
biomagnification factors (low = 1, medium = 2, and high =3) are assigned to each category. A
default value of 1 is used.
Step 7: Toxicity, persistence, and biomagnification factors are multiplied to derive the TPB score
for each pollutant.
Steps 8. 9. and 10: Mass emission data per functional unit is multiplied by the TPB score to derive
the ecological toxicity impact indicator.
Standard risk assessment practice is to assume additivity when multiple chemicals are being
evaluated. Similarly, in the LCIA, ecological toxicity impact indicators for each pollutant are added
to derive total scores for potential impacts to receiving media. Pollutants contributing 0.1% (or a
user-selected value) or more to the total ETI would be flagged for further evaluation.
39
-------
Exhibit 3-7.
FRED Ecological Toxicity Method.
llctiift antrihuting
ctaifctand
Alanine uiiivc
BipofLilttr.
40
-------
Calculating the FRED Ecological Toxicity Indicator
The ecological toxicity equivalency values are based on the model created by RTI for the
Streamlined LCA Model Development and Demonstration Project (EPA, 1995) creates an
equivalency value for chemicals based on the persistence, bio accumulation and toxicity
characteristics it exhibits in the environment. The Ecological Toxicity Index (ECOI)for the
product is derived using the following equation:
Ecological Toxicity Index (ECOI) = Lj W| X ECO;
w; = weight of inventory flow i per functional unit of product
ECO; = ecological toxicity equivalency potential
Exhibit 3-8. Sample Ecological Toxicity Potential Equivalency Factors
Substance to Air
ECO
Benzene
14.6
Fluorides
7.3
Formaldehyde
7.4
Hydrogen Chloride
11.0
Hydrogen Fluoride
11.0
Toluene
3.7
Vinyl Chloride
126.0
Xylenes (total)
3.7
Substance to Water
Benzene
0.8
Hydrocarbons
17.0
Nitrates
5.7
Phenol
3.1
TCDD-2-3-7-8
6.1E+7
Vinyl Chloride
17.0
(EPA, 1995)
41
-------
Example
'"The following example uses LCI data from the BEES motor oil study (list in Appendix A) to calculate ecological
[toxicity potential for the various life cycle stages in the oil re-refining process.:
^ ij»co j EOQI Re- |£CQ ECOJ JTranspor |ECUt ECQI
Boot
"E£"
refined
Oil
produotio
ECU
set
ms
Substance
Transport
of Re-
refined Oil
for
Manufactu
re
6.7§e-67
1.28&-05
4.03e-07
TOT
0
TE7
T ranspor
t of Re-
refined
Oil for
Use
im
0
6.07&05
Use
"SET
TTB5"
ECOI
End of
Life
EST
fecoi
senzene
TTO57
Tte
0
4.160-06
w
WjmM,
5.83S-06
¦pifc
3<496-ta
rm
W
~5
ITff
0
5.65e-65
738
S.SSe-M
TS"
TS7
henote
"TO
6.Si>e-iS
1.14S-02
5.40©-06
T5EF
u
MM
j=2.94ietj
-------
Resource Depletion
Background
Resource depletion is related to the inputs of materials into the industrial system under study.
Although resource depletion is identified as a single environmental issue for the purposes of
environmentally preferable purchasing, in fact, resource depletion is an umbrella term for several
sub-issues, which collectively can be considered to be of equal importance as all the remaining
environmental issues related to emissions.
Resource depletion directly measures the sustainability of industrial systems. If resources are
being used at or below their replacement rate, then their use does not affect the ability of future
generations to maintain their quality of life. An example of a material for which sustainable use
of the resource has been attained includes the use.
Biological resources have the potential to be used sustainably as well, and in some cases
sustainable forestry practices appear to have achieved this ideal. However, many biological
resources have gone the way of the passenger pigeon, as use rates exceeded the replacement
rates.
In the US, land use patterns (also a resource depletion issue) are not typically considered to be
sustainable. Agricultural practices typically lead to the loss of topsoil, and large and increasing
proportions of the land have become urbanized. Land use is of particular concern for bio-based
products, which typically use a large land area to produce products equivalent to mineral-based
competitors.
Calculating the FRED Resource Depletion Indicator
Resource depletion impact values can be presented as a single value or as subvalues that
represent each of the major types of resources being consumed. For the purposes of this analysis,
we are presenting resource depletion impact values within the following subcategories:
• minerals
• fossil fuels
• wood
• land use (landfill, resource extraction area,)
• water use
These sub-categories represent the inherently different types of resources, and cannot be added
together to achieve a single score.
The FRED LCA system uses the LCSEA model developed by Scientific Certification Systems
(SCS) and its partners, Soil and Water to calculate the net resource depletion as a function of (1)
43
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the material's relative rate of depletion and (2) the relative degree of the resource's recycling.
The equation for resource depletion is:
Resource Depletion Indicator (RD) = Zj W| x RDF;
W; = weight or volume of inventory flow i per functional unit of product
RDFj = resource depletion factor
= (Waste-Accretion1) *T (Total Reserve-Current Reserve")
Total Reserve + Recycling *T
where T is time in years, and Total Reserve is the known maximum extent (i.e., amount
exploited over historical time plus current known, unexploited reserves). (See USGS, 1998)
For fossil fuel, this model uses the 50 year time horizon to project use. (T = 50)
The table below contains a sample of depletion factors from the LCSEA model.
Exhibit 3-9. Resource Depletion Factors
Resource
RDF
Coal
0.08086
Natural Gas
4.812
Oil/Petroleum
1.35
Uranium
39
For net resources depleted (or accreted), the units of measure express the equivalent depletion (or
accretion) of the identified resource. All of the net resource calculations are based on the resource
depletion factors:
Indicator - Net Resource
Units of Measure
Water
equivalent cubic meters
Wood
equivalent cubic meters
Fossil Fuels
tons of oil equivalents
Non-Fuel Oil and Gas
tons of oil equivalents
Metals
tons of (metal) equivalents
Minerals
tons of (mineral) equivalents
Land Area
equivalent hectares
44
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I Example
I The following example uses LCI data from the BEES motor oil study (list in Appendix A) to calculate resource
1 depletion potential for the various life cycle stages in the oil rerefining process.:
Substance
T rarisport
of Re-
refined Oil
for
Manufactu
re
iiill
fcUTI
Re-
refined
Oil
prodoctio
n
EUTr
T ranspor
tof Re-
refined
Oil for
Use
BJT '
EUTf "
Use
eUT
" EUT! "
End of
Life
iii
EUT)
Coal
1 22e-04
6.89e-03
5.78e-04
4^ia-G5
(5
0.081
6
b
Natural Gas
3,37e-04
1.28e-02
6,176-02
1.5Se-03
0
0
m 4"in&
6
«
~ il/Petroleu
m
3.92e-03
1 35
5 29KJ3
2.03©-03
135
2 74e-oi
186e-02
'2;5t"e*C2
0
'-Z
0
1 35
'6
0
Uranium
0
09
0
6
38
'Ol
0
89
0
0
39
0
siiisifiSS
mS
0
Subtotal
ooo1?
6 093
!
D
0
i
I Total
orallLC,
¦ staaes:0.164 II
Environmental Relevance
ISO Criteria
Met by
Indicator
Description
Consequence Link
~
Models the physical rate of resource consumption with
respect to available in-ground stock, available standing
stock, and accretion of stock. Does not differentiate
whether recycled or virgin resources are consumed.
Environmental
Condition and
Intensity
~
Considers the reserves of resources in the ground, in
standing stock (e.g., buildings, bridges) as well as the
accretion of resources through natural processes. The
intensity of resource depletion is captured by relating
resource consumption to available reserves and accretion.
Spatial Aspects
~
Resource depletion is typically thought of as a global issue,
and this indicator is appropriate for that level of
assessment. While the model can consider the spatial
variations (national or regional or local) of resource
depletion, FRED does not require this level of modeling..
Temporal Aspects
~
Considers the rate of resource depletion from known
reserves.
Reversibility
~
Does consider the reversibility of resource depletion
through explicit consideration of recycling.
Uncertainty
Does not consider the uncertainty of resource depletion.
45
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Other Issues Regarding the FRED Environmental Component
The environmental impact categories, indicators and models chosen to represent the potential for
environmental impact are by no means definitive; there are many other models and systems available
for use. The models chosen for FRED use globally-based data, whereas there are many models, both
in existence and under development, which incorporate regional and localized data. These models
better approximate the environmental impact in a given area. The designers of FRED consider
impact model selection to be an iterative process. As the science and the data supporting the science
develops, newer, more environmentally relevant models will gradually replace the current models.
The case study below illustrates the development that is necessary for transition to more
environmentally relevant models.
Case Study for Meeting ISO 14042 Requirements for Environmental Relevance: Photochemical Smog
Photochemical smog is an environmental condition that causes aesthetic, human and ecological
health damages primarily at local and regional scales. The most relevant measure of the effect of
VOC's on smog formation would be the actual change in smog formation in a specific airshed that
results from changing the emission of specific VOC's in that airshed (Carter, 1994). The indicator
used in the FRED LCA system for smog formation is the Maximum Incremental Reactivity (MIR)
scale developed by Carter (1994) for use by the California Air Resources Board (CARB) for
regulatory applications.
Because smog formation is highly dependent on environmental conditions, especially the sunlight
and the presence of NOx in the airshed, the concept of the MIR scale oversimplifies the complexities
of the effects of VOC's on smog formation as well as its variation between locales and seasons. The
MIR scale calculates ability of VOC's to yield ozone under optimum conditions, and does not meet
many of the ISO 14042 requirements for environmental relevance. How could photochemical smog
be modeled to be more consistent with the ISO 14042 requirements for environmental relevance?
Some recommendations for improving the photochemical smog indicator in the context of the
environmental relevance requirements are highlighted below:
Consequence Link - There is already a well-established link between VOC's and the presence of
NOx in airsheds that lead to the formation of ground level ozone, and between ozone concentrations
and damage to human health and the environment. No improvement is needed to satisfy this criteria.
Environmental Condition and Intensity - Ozone affects different endpoints at different levels.
Natural background levels of ozone are about 25 ppbv, while crop damage has been observed at 40
ppbv and human health effects at 80 ppbv (the standard for the U.S.). In Europe, the goal is to
achieve ozone concentrations which do not exceed 60 ppbv. The MIR scale was developed using
average concentrations of NOx and ROG's in the atmosphere and thus represents a generic and
hypothetical airshed. To improve upon the use of a generic airshed, data from the airsheds for
different cities (many already collected to develop the MIR scale) could be used to model conditions
46
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for ozone formation in specific cities, including the expected concentrations of ozone at different
times of the day and of the year. The intensity of the ozone effect would then more closely related
to actual conditions within a specific local rather that using maximum MIR values. Improving the
environmental and intensity criteria would require more detail in the LCI about where emissions of
VOC's and NOx are occurring as well as airshed data for the location.
A simpler approach would be to evaluate the data on ozone concentration gathered in various
airsheds, and use this information to modulate the MIR results. For example, one can calculate the
number of days per year that the ozone concentration exceeds 40, 60 or 80 ppbv, and proportionate
the MIR results according to this site-specific information.
Spatial Aspects - The MIR scale is developed using EKMA model and average concentrations of
NOx and ROG's in airsheds from 39 cities in the U.S. To improve the spatial aspects, the EKMA
could be run using site-specific (and disaggregated) concentrations of NOx and ROG's in specific
locales. Improving the spatial criteria would require more detail in the LCI about where emissions
of VOC's and NOx are occurring.
Temporal Aspects - The MIR scale does consider the temporal aspects of ozone formation that it
calculates the total amount of ozone generated during the atmospheric lifetime of the VOC's. One
way to incorporate additional temporal aspects into this indicator would be consider the length of
the ozone season. Ozone season data is collected and available for different locations.
Reversibility - Ozone causes many kinds of damage, some reversible and some not. Some examples
include decreased crop productivity, eye irritation and in severe cases, permanent damage to lungs
and other tissues, possibly leading to carcinogenic effects. The effects of infrequent and low-level
exposure and can be reversed when ozone concentrations drop.
Uncertainty - Uncertainty adjusted MIR values are available but were not used for this indicator
because the authors of the MIR scale recommend using the "best estimate" values for evaluating
product categories. Uncertainty adjusted values may be used. The uncertainty of the effects of ozone
on humans, animals and plants are not well characterized.
Similar kinds of assessments can be performed to yield more environmentally relevant indicators for
each of the impact categories. FRED can be considered to be a baseline methodology for achieving
indicators for the purpose of environmentally preferable purchasing. More sophisticated indicators
may be desirable in some cases.
47
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Chapter 4 - Presentation and Interpretation of the Indicator Results
Overview
The first three steps of the FRED LCA system yield the results associated with eight environmental
and human health indicators for each product. The purpose of this chapter is to outline approaches
for presentation of the indicator results, weighting among indicators, relative weights development
methods, and linking of the life cycle indicator results with technical and cost information. The
elements in this step relate closely to the optional elements of life cycle impact assessment, and
interpretation phase of LCA. The reader should reference ISO 14042 (optional elements sections)
and ISO 14043 (interpretation) for more specific information.
Because of the primary focus of this project was to outline the overall FRED framework and develop
indicators, this step is presented more as possible options for consideration. Additional research will
focus on examining and testing options for presentation and interpretation.
Presentation of Indicator Results
Decision-making can be greatly enhanced by effective presentation of the results. Although the
numerical results may provide the detailed information for each variable that contributes to a
decision, graphical presentation allows for the visual summation of the results, and their comparison
to similar data-sets of the other alternatives being evaluated. Graphical presentation allows for easier
interpretation and consistency in decision making, especially by non-expert decision makers. Several
different methods can be used to present the numerical results of a study, and different types of
graphs can facilitate different aspects of the decision.
Figure A - Indicator
Figure B - Relative
Indicator Ranking
m Baseline
Case ¦ 1
-------
Exhibit 4-1 is just one example of a presentation format that can be used for environmental
performance evaluation of products. The relative indicators of the system/product are presented
graphically as compared to a baseline case (which can be one of the products being compared, or the
product currently used in that function, if data is readily available for that product). The figure on
the left in Exhibit 4-1 shows the method of translating and consolidating indicators to a common
measure. The figure on the right in Exhibit 4-1 shows the next step that compares these indicators
to a baseline (i.e. current product) in a sample graphical output. This type of output allows direct
graphical comparison of the environmental performance several products within each of the
indicators. Alternative products can be compared in each indicator 'dimension' individually. The
product that may perform best can then be selected. Another method of presenting the results is to
create ail "environmental footprint" of the product, where the results of all the relevant indicators
for the product are presented in one graphic. The "footprint" graphic may be a bar-diagram where
each bar represents an indicator, a spider-web diagram (see Exhibit 4-2), where each spoke is an
indicator, or other ways of graphically conveying the performance of the product along the
dimensions of comparison.
Splder-Web Footprint
5
~ Baseline B Product A ~ Product B
Exhibit 4-2. Spider-Web Footprint Display of Results
It should be noted, that since different units of measurement are used to measure the performance
of the products for each indicator (e.g., area of land, ethylene equivalents, C02 equivalents, etc.) it
will be difficult to create a footprint if the performance levels along the different indicators are left
in their respective original units of measurement. To allow for meaningful representation of the
environmental performance of the footprints of the products compared, a 'baseline' value should be
assigned for each indicator, and assigned to represent the 100% graph point, so that the indicator
values for other products are represented as compared to that. A meaningful way of assigning
baseline values is to use the performance levels of existing product in use as a baseline, or to select
the highest value for each indicator category from the collective values of all products being
compared, and assigning that performance as the 100% level. In this manner, the lower the values
that a product has in its "footprint", the better its environmental performance. The spider-web
footprint is one graphical representation. The following rectangle, Exhibit 4-3, presents another
49
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example of "footprint" graphical representations that may be applied. Other representations may be
equally instructive in the decision making process.
Rectangle Cut-out Footprint
a) 150 i
c
1
2
3
4
5
6
7
8
H Baseline
100
100
100
100
100
100
100
100
S Product A
42
73
35
77
64
98
75
56
~ Product B
30
64
35
70
24
20
63
37
Indicators
Exhibit 4-3. Rectangle Cut-Out Footprint
Weighting Among Indicators
In some cases, the presentation of the indicator results alone often provides information sufficient
for decision making, particularly when the results are straight forward or obvious. For example:
• When the best-performing system/product among the alternatives studied is significantly and
meaningfully better than the others in at least one indicator, and no-better-or-worse than any of
the other products in all remaining indicators (as would be the case when there are overlapping
error-bar ranges introduced by data variability and uncertainty). Then, one system is clearly
performing better, hence any relative weighing of the indicators results would not change it's
rank as first preference. The decision can be made without the weighting step.
• When the uncertainty and variability ranges (error bars) for the indicator results are larger than
the differences in indicator values among the compared systems/products, then the results are
inconclusive and adding a weighting step will not change that fact. Also, there is uncertainty
introduced in the indicator-modeling step of the comparison. This additional uncertainty may
render the analysis inconclusive if there are small differences among inventory data that are
meaningful. Hence there are two types or results where the environmental comparison can not
demonstrate enough differentiation to select one product, and the decision could be based solely
on technical and cost considerations.
50
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• When there are trade-offs in the environmental performance of two systems, then there may be
value in performing the weighting step.
Weighting is the process of converting indicator results by using numerical factors based upon value
judgements. The primary objective of weighting is to integrate information on indicator results with
stakeholder values to establish the relative significance of the indicators of the studied system
Stakeholder values (multipliers for the relative importance that stakeholders have assigned to an
indicator) are often the basis for those numerical factors. The challenge is how to adequately capture
and express the full range of stakeholders' values when the numerical factors are determined.. These
challenges have been recognized and discussed in the international LCA community as part of the
ISO efforts, SETAC, and government publications (RTI, 1995, SETAC 1992, SETAC 1998).
Several issues exist that make weighting a challenge. The first issue is subjectivity. According to ISO
14042, any judgement of preferability is a subjective judgement regarding the relative importance
of one indicator over another. Additionally, these value judgements may change with location or
time of year. For example, a federal procurement official located in Los Angeles, CA, may place
more importance on the values for photochemical smog than would a procurement official located
in Cheyenne, WY. The second issue is derived from the first: how should FRED users fairly and
consistently make decisions based on environmental preferability, given the subjective nature of
weighting?
Developing a truly objective (or universally agreeable) set of weights or weighting methods is not
feasible. However, several approaches to weighting do exist and are in fact used successfully for
decision making. Some of those approaches that are applicable to the FRED LCA application are
described below. For a more detailed discussion on weighting approaches see RTI (1995) and
SETAC (1992). The following approaches can provide ideas on how to incorporate the views of
stakeholders who will be affected by the outcome of a decision, as well as providing a systematic
process to determine those numerical factors.
Relative Weights Development Methods for the Weighting Step
Several methods exist to derive relative weights for indicators. Further description of the techniques
outlined below as well as other techniques see RTI (1995).
Adopt an Existing Weighting Scheme
One way to derive relative weights for a valuation is to adopt an existing scheme. Such a scheme was
developed by the U.S. EPA Science Advisory Board in 1990. However, caution should be used in
applying pre-developed weighting schemes, as they can become dated as environmental science and
understanding progresses, and also these tend to accommodate global priorities as more significant
than local environmental priorities, which may also vary significantly from one region to another,
51
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based on multiple variables such as availability of water, availability of landfill space, local
atmospheric conditions, population density, etc.
The U.S. EPA's Science Advisory Board (SAB) report Reducing Risk: Setting Priorities and
Strategies for Environmental Protection (EPA, 1990) provides some useful suggestions that help in
assigning relative importance to environmental attributes of a product. The EPA determined that its
Environmentally Preferable Products (EPP) Guideline will utilize and possibly build upon the SAB
results in evaluating products (EPA, 1995).
Additionally, Harvard conducted a study in 1992, which can be used to establish the relative
importance of indicators.
Analytic Hierarchy Process (AHP)
The Analytic Hierarchy Process (AHP) is a multi-criteria decision-making methodology that enables
consideration of extensive sets of dissimilar qualitative and quantitative criteria in making a decision.
AHP juxtaposes the qualities and features of the options with the relative importance of the
evaluation criteria to derive an aggregate measure of performance. This analysis is based on a
scientifically defensible mathematical algorithm, adding credibility to the ranking. The method can
handle large numbers of criteria, arranged on a simple level, or resolved on hierarchical levels.
AHP is based on the concept that assigning relative importance can be done more accurately and
reliably by using comparisons among competing issues rather than by using an arbitrary valuation
scale. The simplest and most reliable basis of comparison being that of a pair, in AHP relative
weights are developed using exhaustive pairwise comparisons among competing issues. The
derivation of relative weights is based on simple matrix algebra (RWS, 1990). AHP also provides
a mathematical measure of data consistency, giving users feedback on the quality of judgmental
information. AHP supports consistency in judgments by making use of a common comparison
vocabulary and framework.
There is software available that allows the performance of the AHP calculations required to develop
the relative weights and ranking (ExpertChoice™), that greatly simplifies the task for the user, to the
level of providing feedback to the software as to the perceived relative importance of the attributes
compared, two at-a-time.
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Modified Delphi Technique
The Delphi Technique is a procedure originally developed by the Rand Corporation for eliciting and
processing the opinions of a group of experts knowledgeable in the various areas involved. The
Delphi Technique addresses the need to structure a group communication process to obtain a useful
result for a given objective. In essence, the Delphi Technique attempts to create a structured format
to elicit collective knowledge.
In response to a number of shortcomings associated with the Delphi Technique (see Linstone and
Turoff, 1975), a modified Delphi technique has been developed. This modified Delphi technique
provides a systematic and controlled process of queuing and aggregating the judgments of group
members and stresses iteration with feedback to arrive at a convergent consensus.
The weighting procedure can be simply employed. A deck of cards is given to each person
participating in the weighting. In this example each card names a different technical specialty. Each
of the participants is then asked to rank the technical specialties according to their relative
importance to explaining changes in the environment that would result from a particular system.
Then each individual is asked to review the list and make pairwise comparisons between technical
specialties, beginning with the most important specialty. The most important technical specialty is
compared with the next important specialty by each individual, and the second technical specialty
with respect to the first.
To accomplish the second part of this technique (i.e., to rank attributes within a technical specialty),
each participant or group independently ranks attributes in his or her own specialty. The information
from these pairwise comparisons can then be used to calculate the relative importance of each of
these specialty areas; a fixed number of points (e.g., 1,000) is distributed among the technical
specialties according to individual relative importance.
After the weights are calculated from the first round of this procedure, the information about the
relative weights is presented again to the experts, a discussion of the weights ensues, and a second
round of pair-wise comparisons is made. The process is repeated until the results become relatively
stable in successive rounds.
Decision Analysis Using Multi-Attribute Utility Theory (MAUT)
Simply stated, decision analysis is a method that breaks down complex decisions involving multiple
issues into constituent parts or individual attributes to provide a better understanding of the main
factors guiding the decision. Decision analysis using MAUT is useful when deciding between largely
different types of considerations. In addition, it provides a logical structure for analyzing complex
weighting issues.
53
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The first step in decision analysis is to identify all important objectives and attributes. While this step
may seem obvious, it is necessary to ensure that the valuation focuses on the right problem The
objectives and attributes of the decision at hand may be identified by using tools such as an
objectives hierarchy (Keeney and Raiffa, 1976). Whether the objectives and attributes are determined
through a top-down or bottom-up approach, the final set of attributes should have certain
characteristics. An overall objective would be at the top and a comprehensive set of issue-specific
objectives are then derived that are consistent with the overall objective. Finally, attributes that are
meaningful, measurable, and predictable are derived for each specific objective. According to
Keeney and Raiffa (1976), who describe the entire MAUT process in detail, the set of attributes
should be:
• comprehensive,
• as small as possible in number,
• non-overlapping,
• judgmentally independent, and
• operational.
Linking FRED LCA with Technical Performance and Total Ownership Cost
As was mentioned in Chapter 1, the goal of FRED is to apply LCA in an overall formework for
examining the environmental perferability of a product system. FRED also provides the foundation
for linking the life cycle indicator results with consideration to technical and economic factors for
decisionmakers. To this end, environmental, economic and technical feasibility aspects of the project
are examined. A variety of approaches can be used to assist in the decision making process. One such
approach is described here. The ranking can be performed with a variety of approaches. One such
approach is Analytic Hierarchy Process method as described previously in this chapter. The ranking
produced will pinpoint at the most appropriate option, considering all aspects of product
development, use, and disposal (see Exhibit 4-4).
Exhibit 4-4. Examples of Ranking within FRED
Baseline
Option 1
Option 2
Option 3
Option 4
Environmental Performance
Medium
Low
High
Medium
Low
Cost
Low
Medium
Medium
Low
Medium
Technical Feasibility
High
Low
Low
Medium
High
54
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Summary
As we described earlier in this reference guide, Step 4 is still under development. However, certain
findings from the pilot projects and development of the eight life-cycle indicators occurred. First,
presentation of results in graphic formats facilitates the understanding and interpretation of the
indicator results. Graphic presentation allows for easier interpretation and consistency in decision
making, especially for non-experts. Second, weighting among indicators is not always necessary.
Depending upon the indicator results, the differences may be straightforward and obvious. In those
cases, weighting would not be necessary. The advantage is that in these instances the subjective
nature of weighting is eliminating and the information is presented more objectively.
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Chapter 5 - Conclusions
FRED, the Framework for Responsible Environmental Decision-Making, introduces a decision
making framework for achieving a balance among price, technical performance, and environmental
preferability. This guidance document focuses on developing an approach for quantifying a product's
environmental performance. In conducting three pilot tests to refine and validate the application of
LCA, several conclusions were reached. These conclusions and recommendations on the next steps
are presented here.
Conclusions Regarding FRED
The decision making framework introduced in this reference guide has been specifically developed
to facilitate the inclusion of environmental preferability in the procurement process. In terms of
meeting this objective, the following observations and conclusions have been drawn.
• As noted in the EPP draft guidance, environmentally preferable procurement depends on
balancing environmental preferability, price, and performance.
• Life cycle assessments are a comprehensive, practical and fair method for measuring
environmental preferability.
• Obtaining quality life cycle inventory data is critical to making an accurate assessment.
• The "greening government" requirements of Executive Order 13101 can be met by applying the
FRED LCA system
The impact assessment approach outlined in FRED helps to further define impact criteria and move
the practice toward a more consistent appraoch. Currently, the selection of criteria in LCIA may
significantly influence the outcome of the assessment by under-emphasizing potential impacts. For
example, global warming is evaluated as a single category while human health is sub-divided into
cancer and non-cancer impacts. Depending on how interpretation is conducted, the number of
categories will influence the results. While the complexity of attempting to identify all impact
considerations was beyond the scope of this simplified LCA study, it serves to illustrate the need for
further development of impact categories and criteria in order for LCIA to have a consistent
foundation that is accepted globally.
Conclusions Regarding the FRED Environmental Component (i.e. the FRED LCA System)
As explained earlier in this document, a cradle-to-grave, multi-media Life Cycle Assessment (LCA)
methodology is applied within FRED to measure environmental preferability of products and
services. This application of LCA focuses data collection by first identifying the product type, and
the impact categories and indicators being assessed, and then determining the specific, associated
data needs, greatly focusing the LCA application and significantly increasing the efficiency of the
analysis.
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As a result of this effort, the FRED LCA system was demonstrated to be a feasible approach to
supporting Environmentally Preferable Purchasing (EPP) decision-making. While the final choice
between product alternatives, that is, deciding which is "better," is left to the final decision-maker,
this research study has taken the first steps to providing scientific input to the decision-making
process. Federal government agencies can improve the ability for FRED-LCA to function as a tool
for evaluating environmental preferability by:
• Allowing vendors to provide LCA inventory data or LCA indicator results to procurement
officials in order to facilitate comparisons of different products using the FRED-LCA system
In particular, development of site-specific data over the entire vendor chain will permit the
development of indicators with a high degree of environmental relevance.
• Developing agency-specific data gathering tools and databases. This will lead to more uniformity
in the data utilized in EPP evaluations.
• Using FRED-LCA in other pilot EPP projects. The more experience is gathered with FRED, the
better the ultimate results of the analysis, and consequently the more informed the decision-
making.
• Using FRED LCA to support other decision-making activities besides facilitating procurement
selections. For example, FRED LCA could possibly be used to track and monitor an
organization's environmental performance, identify opportunities for process improvements, and
identify environmental aspects, as defined by ISO 14001. These possible additional uses of
FRED LCA were not explored in developing this reference guide and thus still require
validation.
Lessons Learned Regarding the Pilot Projects
To assist in refining the application of Life Cycle Assessment (LCA) within FRED (i.e., referred to
as the FRED LCA system), three LCA pilot projects were conducted to evaluate the process as well
as the output. These included pilot projects on motor oil, wall insulation, and asphalt coatings.
Specific information regarding the scope, data, and findings from these pilot projects is located in
Appendices A, B, and C to this report. Conclusions from these pilot projects regarding the
application of LCA within FRED include:
• The FRED LCA system can be performed in a much shorter time period than is typical for a
more detailed LCA study. This, more practical duration for procurement decisions, is achieved
through the focusing of data collection needs and simplified impact assessment.
• Process and site specific data can most readily be collected from the participating product vendor
and suppliers/customers interacting directly with the vendor. Other contributing organizations
further up and down the vendor chain (such as raw material suppliers and energy providers) are
more likely to be derived form industry averaged data sets.
• As demonstrated by the pilot projects, data collection for the application of LCA within FRED
can be accomplished by a small business/vendor. The simplified LCA application within FRED
focuses the data collection needs to the point that even a smaller size business can fulfill the data
needs without being overly burdened.
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Next Steps
This reference guide focuses solely on providing direction for applying LCA within FRED to
compare the environmental preferability of competing products. Guidance will be needed on the
methodologies used within FRED to evaluate cost (e.g., total ownership cost) and performance (i.e.,
using system functional analysis within the LCA scope and goal definition step to measure the ability
of competing products to meet technical requirements). Additional FRED reference guidance will
focus on evaluating the tradeoffs among each selection criteria. Next steps to be taken in facilitating
the application of FRED to the procurement process include:
• Providing detailed guidance on the level of data quality characteristics required to support public
procurement decisions of various levels.
• Developing the total ownership cost and technical performance evaluation component of FRED.
• Developing models of environmental impact that accomodate more site-specific information and
therefore better fulfill the ISO requirements for environmentally relevant indicators.
• Developing additional impact indicators for land use. This will be especially important for
assessing bio-based products.
• Developing guidance on how to report the combined environment, cost, and performance results
from FRED.
• Developing a users guide, possibly a software based tool to collect, evaluate, and interpret
procurement data.
• Creating incentives (e.g., regulatory, contractual, voluntary, etc.) for vendors and other
organisations to provide product-specific data for use in FRED.
• Conducting additional pilot projects to validate FRED's applicability to the procurement decision
making process. Three pilot projects were conducted in developing this FRED LCA system
reference guide. These pilot projects were used to refine the choice of environmental and human
health impact models to be included in FRED as well as to validate the impact indicator results.
In the future, additional pilot projects will be needed to validate the other components of FRED
(cost and performance) as well as to develop the trade-off analysis within FRED.
58
-------
References
Carter, 1998.
Curran, 1998.
DOE, 1996a.
DOE, 1996b.
EC, 1999.
EDF, 2000.
EPA, 1990.
EPA, 1993.
Carter, W.P.L. 1998. "Updated Maximum Incremental Reactivity Scale for
Regulatory Applications," Preliminary Report to California Air Resources
Board Contract No. 95-308, Air Pollution Research Center and College of
Engineering, Center for Environmental Research and Technology,
University of California, Riverside, California.
Curran, M. A. 1998. Life Cycle Assessment for Environmental
Prefer ability: Principles and Guidelines for Comparative Analysis
(Draft Report). September 1998.
Sample, B.E., D.M. Opresko, and G.W. Suter II. 1996. Toxicological
Benchmarks for Wildlife: 1996 Revision. Prepared by the Risk
Assessment Program Health Sciences Research Division, Oak Ridge,
TN for the U.S. Department of Energy. June. ES/ER/TM-86/R3.
Suter, G.W., II and C.L. Tsao. 1996. Toxicological Benchmarks for
Screening Potential Contaminants of Concern for Effects on Aquatic
Biota: 1996 Revision. Prepared by the Risk Assessment Program
Health Sciences Research Division, Oak Ridge, TN for the U.S.
Department of Energy. June. ES/ER/TM-96/R2.
Environment Canada's "A Primer on Environmental Citizenship."
http://www.ns.ec.gc.ca/aeb/ssd/acid/ acidfaq.html. Accessed January
19,1999.
Environmental Defense Fund, 2000. "How EDF Uses Sscreening Level
Risk Assessment to Assign Risk Scores."
http: //w w w. scorecard.org/env-realease/def/tep-caltox.html.
United States Environmental Protection Agency. 1990. Reducing Risk:
Setting Priorities and Strategies for Environmental Protection, Science
Advisory Board (A-101), SAB-EC-90-021.
United States Environmental Protection Agency, Office of Research &
Development. 1993. Life Cycle Assessment: Inventory Guidelines and
Principles. EPA/600/R-92/245.
59
-------
EPA, 1994a.
EPA, 1994b.
EPA, 1995a.
EPA, 1995b.
EPA, 1997.
EPA, 1998.
EPA, 1999.
Guinee, 1995.
IPCC, 1990.
IPCC, 1992.
United States Environmental Protection Agency. 1994. Chemical
Hazard Evaluation for Management Strategies, A Method for Ranking
and Scoring Chemicals by Potential Human Health and Environmental
Impacts. Office of Research and Development, Washington, DC.
EPA/600/R-94/177.
United States Environmental Protection Agency. 1994. Technical
Background Document to Support Rulemaking Pursuant to the Clean
Air Act - Section 112(g), Ranking of Pollutants with Respect to Hazard
to Human Health. Office of Air Quality Planning and Standards,
Research Triangle Park, NC. EPA-450/3-92-010.
United States Environmental Protection Agency. 1995. Draft for Public
Comment, Environmentally Preferable Products Guideline. Federal
Register.
United States Environmental Protection Agency, Office of Solid Waste.
1995. Guidelines for Assessing the Quality of Life Cycle Inventory
Analysis. EPA/530/R-95/010.
United States Environmental Protection Agency. 1997. Waste
Minimization Prioritization Tool. Beta Test Version 1.0. User's Guide
and System Documentation, Draft. Office of Solid Waste Office of
Pollution Prevention and Toxics, Washington, DC. EPA 530-R-97-019.
United States Environmental Protection Agency. Inventory of U.S.
Greenhouse Gas Emissions and Sinks: 1990- 1996. March 1998.
EPA/236/R-98/006.
United States Environmental Protection Agency. Ozone Depletion
Glossary. http://www.epa.gOv/spdpublc/defns.html#cfc. Accessed
January 19, 1999.
Guinee, J.B. and R. Heijungs. 1995. "A Proposal for the Definition of
Resource Equivalency Factors for Use in Product Life Cycle
Assessment." Environmental Toxicology and Chemistry, Vol. 14, No.
5, pp 917-925.
Intergovernmental Panel on Climate Change. 1990. Climate Change:
The IPCC Scientific Assessment. J.T. Houghton, G.J. Jenkins, and J.J.
Ephraums (eds). Cambridge University Press, Cambridge. UK.
Intergovernmental Panel on Climate Change. 1992. Climate Change
1992: The Supplementary Report to the IPCC Scientific Assessment.
J.T. Houghton, B.A. Callander and S.K. Varney (eds). Cambridge
University Press, Cambridge. UK.
60
-------
IPCC,1995.
ILSI, 1996.
ISO, 1997.
ISO, 1998.
ISO, 1999.
ISO, 2000.
Mackay,1991.
NIST, 1997.
Potting, etal 1998.
Redfield, 1942
RTI, 1993.
Intergovernmental Panel on Climate Change. 1995. The Science of
Climate Change, J.T. Houghton, L.G. Meira Filho, B.A. Callender, N.
Harris, A. Kattenbert and Maskell (eds). Cambridge University Press,
U.K.
International Life Sciences Institute (ILSI). 1996. Human Health
Impact Assessment in Life Cycle Assessment: Analysis by an Expert
Panel. Health and Environmental Sciences Institute, ILSI, Washington,
DC, June 7-9, 1995.
International Standards Organization. 1997. ISO 14040 - Life Cycle
Assessment - Principles and Framework.
International Standards Organization. 1998. ISO 14041 - Life Cycle
Assessment - Goal and Scope Definition and Inventory Analysis.
International Standards Organization. 1999. ISO 14042 - Life Cycle
Assessment - Life Cycle Impact Assessment.
International Standards Organization. 2000. ISO 14043 - Life Cycle
Assessment - Life Cycle Interpretation.
Mackay, D. 1991. Multimedia Environmental Models, the Fugacity
Approach. Lewis Publishers, Chelsea, Michigan.
Lippiatt, B.C. 1997. Draft BEES Beta Version. Building for
Environmental and Economic Sustainability Technical Manual and User
Guide. US Department of Commerce, Washington, DC.
J. Potting, W. Schopp, K. Block, and M. Hauschild. 1998. "Site -
Dependent Life-Cycle Impact Assessment of Acidification." J. of Ind.
Ecology, vol 2, No 2, MIT Press.
"The Process of Determining the Concentration of Oxygen, Phosphate,
and Other Organic Derivates within the Depths of the Atlantic Ocean."
1942. A.C. Redfield. et al Pap. Phys. Ocean. Meteor. 9, 22.
Research Triangle Institute, (RTI), 1993. "A Multimedia Waste
Reduction Management System for the State of North Carolina, Final
Report." Prepared for the North Carolina Department of Health,
Environment, and Natural Resources, Pollution Prevention Program.
RTI Center for Environmental Analysis, April.
RWS, 1990.
Saaty, T.L. 1990. The Analytic Hierarchy Process, RWS Publications
61
-------
SCS, 1997.
SETAC, 1997
US, 1993.
US, 1998
USGS, 1998.
Scientific Certification Systems. 1997. "Life Cycle Stressor-Effects
Assessment (LCSEA): A Framework for Integrating Life-Cycle Impact
Assessment with Environmental Assessment Techniques - Practitioners
Manual," working draft 1.2. Oakland, California, USA.
Society of Environmental Toxicology and Chemistry. 1997. "Life-
Cycle Assessment: The State-of-the-Art." SETAC LCA Impact
Assessment Workgroup and SETAC LCA Advisory Group, Pensacola,
Florida.
National Acid Precipitation Assessment Program June 1993. 1992
Report to Congress.
The Kyoto Protocol and the President's Policies to Address Climate
Change. Administration Economic Analysis. July 1998.
United States Geological Survey, 1998. "Minerals Yearbook: Vol.1
Metals and Minerals." Reston, Virginia, USA.
http://minerals.usgs.gov/minerals/pubs/Commodity/myb/
62
-------
Appendix
As part of the effort to apply LCA as a tool for environmental preferable purchasing within
FRED, three pilots were undertaken to test how best to perform the FRED LCA system in order
to make it:
§ Easy to use
§ Yield results in a timely manner
§ Meet the needs of procurement officials and vendors
§ Conform, as much as possible, to the requirements of DIS 14042 for comparative assertions
§ Support the needs of the EPP program
§ Support the needs of the National Institute of Standards and Technology (NIST) in its goals
relating to the Technology Transfer Act.
Two of those pilots (found in Appendix A - Motor Oil and Appendix B - Wall Insulation) were
based on the inventory data sets collected by the National Institute of Standards and
Technology's Building for Environmental and Economic Sustainability (BEES) program. The
third pilot (found in Appendix C - Asphalt Coating) was based on original data collection from a
small vendor.
The first two pilots, derived from existing BEES life cycle inventory data, were used primarily in
evaluating among environment and human health impact indicator models for inclusion in the
FRED LCA system. The third pilot, which used predominately original data, was utilized to
evaluate the resource requirements for a vendor to provide data for the FRED LCA system as
well as to develop an approach to evaluating results from the FRED LCA system. Pursuant to
these slightly different goals, the sections on interpretation of results and conclusions for the first
two pilots are not as detailed as reported in the third pilot.
-------
Appendix A: Motor Oil Case Study
Goal and Scope Definition
Goal
The goal of this study was to determine the feasibility of evaluating the environmental
performance of three different types of motor oil by using the FRED LCA system. The three
types of oil evaluated were virgin oil, rerefined oil and bio-based oil.
Intended Applications and Audiences
The LCA itself was intended to be used to support a comparative assertion of environmental
superiority of a product over a competing product in the context of the Federal requirement for
environmentally preferable purchasing. Audiences include purchasing agents as well as other
federal and state officials. An ancillary use of the study is to support efforts towards
environmental improvement.
Scope
Description of the Product
Motor oil is used to cool the engine and reduce friction. Historically, motor oil was created by
extracting and refining crude oil. Due to technological advances, two alternatives to virgin oil
are now commercially available: rerefined oil and "bio-based" oil. Rerefined oil is essentially
used oil that has undergone the refining process a second time, with additives to remove
impurities. Bio-based oil is an all-vegetable (in the case of this pilot project, soybean), highly
biodegradable oil that performs comparably to petroleum-based oils.
System Function and Functional Unit
The function provided by the alternative products is automobile engine protection and lubrication
for 3,000 mile without viscosity breakdown. The functional unit is one quart, 10W30 motor oil.
System Boundaries
Data for all three products came from secondary sources according to the contractor for BEES.
Virgin and refined oil data came from petroleum associations representing 90 % of
manufacturers. Bio-based data was derived from an average of 14 states. Upstream materials
and energy use data came from national sources. All data is less than 10 years old. The flow
charts below identify the systems under study.
A - 2
-------
Figure 1: Virgin Motor Oil Process Flow Diagram
Virgin Motor Oil
Crude Oil
Production
Steam
Production
Electricity
Production
Diesel
Fuel
Production
Coal
Production
Propane
Production
Foreing
Production
Production
Heavy fuel
Natural
Gas
Production
Petroleum
Coke
Production
Domestic
production
End-of-Life
Train
Transport
(Crude Oil)
Truck
Transport
(Crude Oil)
Truck
Transport
Ship
Transport
(Crude Oil)
1 quart of Crude
Oil
A - 3
-------
Figure 2: Re-refined Oil Process Flow Diagram
Re-refined Oil
Truck
Transport
End-of-Life
Ship
Transport
Train
Transport
Re-refining
Oil
Production
Truck
Transport
(Re-refined
Oil)
1 quart of re-
refined Oil
Crude Oil
refining
(see previous
graph)
Train
Transport
(Re-refined
Oil)
Ship
Transport
(Re-refined
A - 4
-------
Figure 3: Bio-Based Oil Process Flow Diagram
Bio-based Oil
Electricity
Production
Truck
Transport
End-of-Life
Ship
Transport
Train
Transport
Bio Oil
Production
Soy Bean
Production
Truck
Transport
(Bio Oil)
1 quart of Bio
Train
Transport
(Bio Oil)
Ship
Transport
(Bio Oil)
A - 5
-------
Data Gathering
The entire data gathering exercise for this project involved extracting data from the BEES
database. According to NIST, the BEES database includes both primary data as well as industry
average data.
Allocation
All allocation of emissions and resource use was performed based on a mass basis. This was
required for the production and transportation inventory results, but not for other inventory data.
Impact Assessment
Impact assessment was performed using the FRED indicators, as described in the body of this
work. The assignment of inventory data to impact categories is shown in the table below.
Table 1 Assignment of Inventory Results to Impact Categories
Inventory Result
Impact Category
Justification
Fossil Fuels and Uranium
Resource Depletion
Although Uranium is not truly a fossil
fuel, it is "used up" in a precisely
comparable fashion
C02, N20, Methane
Global Warming
These are important greenhouse gases
which do not participate to a great extent
in other impact categories
CO
Human Toxicity
Photochemical Smog Global
Warming;
CO is a human and animal toxicant, as
well as a precursor to ozone formation
and a greenhouse gas. It can participate in
the first two of these environmental
mechanisms without losing its potency
for the others.
CFC's, HCFC's, Halons
Global Warming 100%
Stratospheric Ozone Depletion
100%
These substances participate fully in both
of these parallel environmental
mechanisms
so2)
Acidification 100%
Although S02 contributes to visibility
deterioration, and human health effects
through the formation of Particulate
Matter, these environmental mechanisms
are not addressed bv FRED.
HC1.HF
Acidification 100%
Human Health 100%
These acid gases have minor human
health effects as well as contributing to
acidification. It was thought that double
counting would not significantly skew
results.
Toxic Air and Water Emissions
Human Toxicity 100%
Ecotoxicity 100%
Since it was not possible to evaluate the
partitioning of these substances, they
were double counted so as not to
underestimate their impacts.
A - 6
-------
Inventory Result
Impact Category
Justification
NOx
Acidification 100%
Eutrophication 100%
Since FRED does not currently evaluate
the fate and transport of NOx, this
emission was double counted.
VOC's, ROG's
Photochemical Smog
These are the essential precursors to
photochemically produced ozone.
Although some of them are also toxic,
unspeciated data does not permit a toxic
evaluation.
nh4
Eutrophication (water
emissions); acidification (air
Emissions)
Although NH4 is not an acid gas, it
undergoes changes in the soil leading to
acidification effects.
po4
Eutrophication 100%
Phosphate does not participate in any
other environmental mechanism
described by the FRED methodology
Inventory
The table below shows the summary inventory for the three products compared. A full inventory
by life cycle stage can be found in Tables 7, 8 and 9.
Table 2 Summary Inventory
LCI Totals
Article
Units
Virgin
Re-refined
Bio
(r) Coal (in ground)
kg
3.6e-02
7.6e-03
2.2e-02
(r) Limestone (CaC03, in ground)
kg
6.8e-03
1.4e-03
4.1e-03
(r) Natural Gas (in ground)
kg
9.8e-02
1.5e-02
5.4e-02
(r) Oil (in ground)
kg
9.1e-01
2.5e-02
4.6e-02
(r) Perlite (Si02, ore)
kg
3.2e-04
2.1e-04
8.9e-06
(r) Phosphate Rock (in ground)
kg
0.0e+00
0.0e+00
5.5e-02
(r) Potash (K20, in ground)
kg
0.0e+00
0.0e+00
3.2e-02
(r) Uranium (U, ore)
kg
8.5e-07
1.8e-07
6.9e-07
Used Oil
kg
0.0e+00
8.6e-01
0.0e+00
Water Used (total)
liter
1.3e-01
3.6e-03
5.9e+02
(a) Aldehydes
g
l.le-04
2.4e-05
2.9e-04
(a) Ammonia (NH3)
g
2.3e-07
1.3e-07
1.6e-01
(a) Benzene
g
2.0e-04
5.5e-06
8.8e-06
(a) Carbon Dioxide (C02, biomass)
g
0.0e+00
0.0e+00
-2.5e+03
(a) Carbon Dioxide (C02, fossil)
g
6.1e+02
3.2e+02
3.4e+02
(a) Carbon Monoxide (CO)
g
4.6e-01
2.6e-01
5.8e-01
(a) Fluorides (F-)
g
2.6e-12
4.5e-13
4.6e-03
(a) Formaldehyde
s
2.7e-03
7.3e-05
1.2e-04
A - 7
-------
LCI Totals
Article
Units
Virgin
Re-refined
Bio
(a) Hydrocarbons (except methane)
g
1.7e-01
3.9e-02
1.8e+00
(a) Hydrocarbons (unspecified)
g
1.5e+00
8.9e-01
4.8e-01
(a) Hydrogen Chloride (HC1)
g
1.9e-02
4.1e-03
1.0e-02
(a) Hydrogen Fluoride (HF)
g
2.4e-03
5.1e-04
1.2e-03
(a) Hydrogen Sulfide (H2S)
g
6.0e-03
1.8e-04
3.0e-04
(a) Metals (unspecified)
g
2.4e-04
9.0e-05
6.7e-06
(a) Methane (CH4)
g
l.le+00
1.5e-01
4.6e-01
(a) Nitrogen Oxides (NOx as N02)
g
1.4e+00
7.0e-01
l.le+00
(a) Nitrous Oxide (N20)
g
4.7e-02
1.9e-02
1.8e-02
(a) Organic Matter (unspecified)
g
5.3e-04
l.le-04
1.2e-02
(a) Particulates (unspecified)
g
9.9e-01
4.9e-01
7.4e-01
(a) Sulfur Oxides (SOx as S02)
g
4.7e+00
1.6e+00
1.6e+00
(w) Acids (H+)
g
0.0e+00
0.0e+00
1.4e-04
(w) Ammonia (NH4+, NH3, as N)
g
1.4e-01
8.9e-02
4.0e-03
(w) Benzene
g
8.9e-14
1.9e-14
4.3e-14
(w) BOD5 (Biochemical Oxygen Demand)
g
9.5e-01
6.1e-01
3.0e-02
(w) Chlorides (C1-)
g
1.3e+01
3.5e-01
5.8e-01
(w) COD (Chemical Oxygen Demand)
g
8.0e+00
5.1e+00
2.4e-01
(w) Cyanides (CN-)
g
3.0e-18
6.4e-19
1.5e-18
(w) Dissolved Matter (unspecified)
g
1.3e+00
l.le+00
1.9e+00
(w) Fluorides (F-)
g
1.3e-04
2.7e-05
l.le-04
(w) Hydrocarbons (unspecified)
g
8.4e-04
2.3e-05
8.2e-01
(w) Metals (unspecified)
g
2.9e-02
8.0e-03
l.le-03
(w) Nitrates (N03-)
g
3.0e-05
6.4e-06
2.5e-05
(w) Nitrogenous Matter (unspecified, as N)
g
0.0e+00
0.0e+00
6.2e+01
(w) Oils (unspecified)
g
4.3e-01
2.4e-01
1.4e-02
(w) Phenols
g
1.8e-02
1.2e-02
5.1e-04
(w) Phosphates (P04 3-, HP04-, H2P04-, H3P04, as P)
g
0.0e+00
0.0e+00
9.7e+00
(w) Sodium (Na+)
g
1.7e+01
4.5e-01
7.4e-01
(w) Sulfates (S04--)
g
2.7e-05
5.7e-06
2.3e-05
(w) Suspended Matter (unspecified)
g
4.3e+00
2.8e+00
1.6e+03
Waste (50 years - prorated)
kg
8.2e-01
8.2e-01
8.6e-01
Waste (End-of-Life)
kg
8.2e-01
8.2e-01
8.6e-01
Waste (Mfg.)
kg
2.1e-02
8.0e-03
1.6e-02
Waste (non-recyclable, 50-year)
kg
8.2e-01
8.2e-01
8.6e-01
E Feedstock Energy
MJ
3.4e+01
-5.0e-02
2.5e-01
E Fuel Energy
MJ
1.0e+01
2.2e+00
5.4e+00
E Non Renewable Energy
MJ
4.5e+01
2.1e+00
5.6e+00
E Renewable Energy
MJ
5.4e-02
1.2e-02
3.9e-02
A- 8
-------
LCI Totals
Article
Units
Virgin
Re-refined
Bio
E Total Primary Energy
MJ
4.5e+01
2.1e+00
5.7e+00
Indicator Results
The table below shows the indicator results for the three systems studied.
Table 3: LCIA Results
T.CIA Totals I
ndicator
RereRnett Oil
Bio-bascd Oil
jWP (k£ C02 equiv)
iiiBi
iilliiiiili:
'illllllilllll
liilii
iilliyiii
illiliili
\ciditkation Otg S02j
5
2
jutrophicatdon (kg PQ4)
2
I'iiillil'iiiilil
S(Mg fkft©33;; • • :s
bti
0 17
7.ld
iuttun Toxicity
twicer
k J2B-D4
NonCancer
2 83E-Q2
4.29E-03
5.Z3E-01
icotoxicity
mmmmt
Resource Dqiletion
Fossil (tuns oil equivalent)
I 70&+00
"" i 63E-M
3 23E-1>1
Mineral (equiv tops}
6 " ' 111
mmmmmA
llllllkliil
Prccious^equiv fonsji
llilillllill
Oilier Indicators
Land Use (ha)
4' ""
in1 i ^
Water Use Ug)
i 35E-Q1
' 3 59E-03
' 5 S9S+02
mrnmm mmmmm mmmmM
Interpretation
As one would expect, selecting either rerefined or bio-based oil potentially appears to reduce
fossil fuel depletion. Comparing the two alternatives to Virgin Oil, rerefined oil leads (as
preferable) in the categories for Eutrophication, Photochemical Smog, Non-Cancer, and Water
Use, when looking at order of magnitude differences. Also, a decrease in cancer effects is
indicated when moving from selecting virgin oil to either alternative product system. The
differences are negligible in the other categories.
A - 9
-------
It is possible to evaluate the sources of the various impacts in order to identify opportunities for
improvements. The table below shows the indicators for each product in term of percentage of
the indicators in the different life cycle stages.
Table 4: Percentage of Indicator by Life Cycle Stage, Virgin Oil
Vitmn Oil * fey LC Stagfe
Indicator
Raw
Materials
Manufacturing
Transport
Use
Disposal
GWP
lllillillllll
73
10
0
llllllllilli
GDP
llilllllllllllll
0
0
0
illllilllllli
Acidification
28
70
2
0
llllllllilli
Eutropbication
0
98
1
0
0
Photochemical Smog
78
5
M
iiiilli
iiiilli
Human Health
Cancer
97
i
2
iiiiiiiii
0
NonCancer
n
. 20
llllllllilli;
illlllll
lillililllllil
Eco Health
>
Resource Depletion
Fossil
iilllilllllli
15
IIIIIIIII
o
inline
Mineral
lilllilll
0
illlllll
iiiilli
iiiiiiiii
Precious
iiiiiiiii
llllllllilli
illllllll
lillllli
0
Other Indicators:
Land Use
0
0
liiiiiiiiiii
iiiiilllii
Water Use (kft\
97
1
llllllllilli
iHiHIi
lilllllill
Solid Waste <*g>
0
0
o
0
100
A - 10
-------
Table 5: Percentage of Indicator by Life Cycle Stage, Rerefined Oil
I Rerefined Oil - bv LC Stage
Indicator
Raw
Materials
Manufacturing
Transport
Use
Disposal
GWF
4
n
20
iiliilli
0
OOP
0
o
0
0
0
Acidification
1
93
6
0
0
Eutrophicatlon
0
98
2
0
0
Photochemical Smog
16
11
74
liilllllli
0
Human Health
Cancer
16
IIIII1I1
Iiliilli
0
Non-Cancer
3
85
13
0
0
Eco Health
iiiiiiiiiifiiiiiii
Fossil
1
62
31
0
0
Mineral
0
0
liilllllli
liilllllli
liilllllli
Precious
0
0
lilillli
ilillli
Ililiilli
Other indicators:
Land Use
0
0
liilliiiiiiliili
0
Water Use (kg)
lilllllllil
llililililillli
Ilimii
lillili
liilllllli
Solid Waste (kg)
0
0
iiliilli
0
liilllllli
A- 11
-------
Table 6: Percentage of Indicator by Life Cycle Stage, Bio-Based Oil
Bio-Based Oil - by LC Stage
Indicator
Raw
Materials
Manufacturing
Transport
Use
Disposal
iliiifiiiiiiiii
lllllllllllil
5t
19
0
lllllllilll
OOP
0
0
0
0
0
Acidification
32
62
lltllilll
iiiiiilii
0
Eutrophication
lllillillllli
0
Iiiiiilii
0
Photochemical
ii
88
2
0
0
Human Health
50
0
50
iwillilllllllll
0
Non-Cancer
100
0
0
0
0
Eco Health
Resource Depletion
24
6$
IIIIIIIlI
0
0
Mineral
0
0
lllllllllllli:
lllllllilll
llllillllllili
Precious
0
0
I iiiiiii
¦¦I
lllllllllllilllli
Other Indicators:
Land Use
iiiiiilii
0
iiiiiiii
miifiii
liiMi
Water Use (kg)
iiiiiiiiiii
0
ill iillli
0
0
Solid Waste {kg)
0
0
0
iilllillii
IHi
For the most part, the majority of the three products indicator results can be found in the
manufacturing and the transportation phases of the life cycle. This result supports the guidance of
the FRED methodology, which recommends more intensive data gathering efforts in the
manufacturing phase for products which are durable goods which are not energy intensive in the
use phase.
Conclusions
This pilot project proved that existing LCA data sets can be used in the FRED LCA system.
Concern that arose during this pilot project centered around lack of information regarding the
LCA data sets. For example, more information regarding data sources, specificity, age, quality,
etc. would have been useful in framing the applicability of the FRED LCA system results.
A -12
-------
Table 7: Life Cycle Inventory, Virgin Oil
I Virqin Oil-LC Stage |
Article
Units
Raw
Materials
Manufacturing
T ransport
Use
End-of-
life
(r) Baryte (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bauxite (AI203.2H20, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bentonite (AI203.4Si02.H20, in
ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Borax (Na20.2B203.10H20)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Clay (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Coal (in ground)
k?
1,6e-02
1,9e-02
5.8e-04
O.Oe+OO
O.Oe+OO
(r) Copper (Cu, Ore)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Diabase Rock
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
^r) Dolomite (CaC03.MgC03, in ground)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(jr) Feldspar (ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Granite (in ground)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
|(r) Gravel
(in ground)
k9
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Gypsum CaS04: in ground)
k9
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) llmenite Ore (in ground)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Iron (Fe, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Jute
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Kaolin (AI203.2Si02.2H20, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Limestone (CaC03, in ground)
3.1e-03
3.6e-03
1.1e-04
O.Oe+OO
O.Oe+OO
(r) Natural Gas (in ground)
kg
4.6e-02
5.1e-02
1.6e-03
O.Oe+OO
O.Oe+OO
(r) Oil (in ground)
kg
8.8e-01
5.5e-03
1.9e-02
OS!
|(r) Perlite
Si02, ore)
kg
1.1e-06
3.2e-04
4.2e-06 O.Oe+OO O.Oe+OO
(r) Phosphate Rock (in ground)
O.Oe+OO
O.Oe+OO
O.Oe+OO O.Oe+OO O.Oe+OO
^ Pine Rosin
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO O.Oe+OO O.Oe+OO
(r) Potash (K20, in ground)
k?
O.Oe+OO
O.Oe+OO
ESS
(r) Potassium (ore)
kg
O.Oe+OO
j 0.0e+00| 0.0e+00| 0.0e+00| 0.0e+00|
^rj> Pyrite (FeS2, ore)
kg
O.Oe+OO
O.Oe+OO
^ Sand (in ground)
k?
O.Oe+OO
O.Oe+OO
(r) Sodium Chloride (NaCI, in ground or
in sea)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Uranium (U, ore)
kg
3.9e-07
4.5e-07
1.4e-08
O.Oe+OO
O.Oe+OO
(r) Wastepaper
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
|(r) Wood (i
standing) |
m3
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Cullet (from stock
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Fly Ash
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Iron Ore Slag
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Recovered Solids (iron scraps)
kSL.
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Used Oil
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
A- 13
-------
Virgin Oil- LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
Water Used (total)
liter
1.3e-01
1.2e-03
2.6e-03
O.Oe+OO
O.Oe+OO
^a) Aldehydes
g
4.9e-05
5.8e-05
1,9e-06
O.Oe+OO
O.Oe+OO
(Ja) Ammonia (NH3)
g
7.4e-08
8.1e-08
7.9e-08
O.Oe+OO
O.Oe+OO
(|a) Benzene
g
2.0e-04
1.1e-06
4.2e-06
O.Oe+OO
O.Oe+OO
(a) Carbon Dioxide (C02, biomass)
g
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
O.Oe+OO
(a) Carbon Dioxide (C02, fossil)
g
8.5e+01
4.6e+02
6.2e+01
O.Oe+OO
O.Oe+OO
(a) Carbon Monoxide (CO)
g
8.7e-02
3.2e-01
5.4e-02
O.Oe+OO
O.Oe+OO
(a) Fluorides (F-)
g
9.5e-13
1.6e-12
4.0e-14
O.Oe+OO
O.Oe+OO
(Ja) Formaldehyde
g
2.7e-03
1,5e-05
5.6e-05
O.Oe+OO
O.Oe+OO
^a) Hydrocarbons (except methane)
g
1,4e-01
3.5e-03
3.1e-02
O.Oe+OO
O.Oe+OO
^a| Hydrocarbons (unspecified)
g
1,5e-01
1.4e+00
2.4e-02
O.Oe+OO
O.Oe+OO
^a) Hydrogen Chloride (HCI)
g
8.7e-03
1.0e-02
3.1e-04
O.Oe+OO
O.Oe+OO
^a| Hydrogen Fluoride (HF)
g
1.1e-03
1.38-03
3.9e-05
O.Oe+OO
O.Oe+OO
(Ja) Hydrogen Sulfide (H2S)
g
5.9e-03
4.86-05
1,4e-04
O.Oe+OO
O.Oe+OO
(a) Lead (Pb)
g
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(|a) Metals (unspecified)
g
6.5e-06
1.9e-05
2.5e-05
O.Oe+OO
O.Oe+OO
^a) Methane (CH4)
a
6.8e-01
4.0e-01
2.1e-02
O.Oe+OO
O.Oe+OO
(a) Nitrogen Oxides (NOx as N02)
g
2.6e-01
9.76-01
1,4e-01
O.Oe+OO
O.Oe+OO
(a) Nitrous Oxide (N20
g
2.7e-02
9.46-03
1.1e-02
O.Oe+OO
O.Oe+OO
^a) Organic Matter (unspecified)
g
2.4e-04
2.86-04
8.8e-06
O.Oe+OO
O.Oe+OO
(a) Particulates (unspecified)
g
2.4e-01
6.06-01
1,5e-01
O.Oe+OO
O.Oe+OO
(a) Phenolics
g
0.0e+00
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
(a) Sulfur Oxides (SOx as S02)
g
1.3e+00
3.3e+00
9.1e-02
O.Oe+OO
O.Oe+OO
^a) Volatile Organic Compounds iVOCs >
g
0.0e+00
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
^w) Acids (H+)
g
0.0e+00
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
^w) Ammonia (NH4+, NH3, as N)
g
5.2e-04
1.4e-01
1.8e-03
O.Oe+OO
O.Oe+OO
(w) AOX (Adsordable Organic Halogene)
g
0.0e+00
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
(w) Benzene
g
4.0e-14
4.7e-14
1.4e-15
O.Oe+OO
O.Oe+OO
(w) BOD5 (Biochemical Oxygen
Demand)
g
3.4e-03
9.3e-01
1.2e-02
O.Oe+OO
O.Oe+OO
^w) Calcium (Ca++)
g
0.0e+00
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
(w) Chlorides (CI-)
g
1.3e+01
7.9e-02
2.7e-01
O.Oe+OO
O.Oe+OO
(w) COD (Chemical Oxygen Demand)
g
2.9e-02
7.96+00
1.10-01
O.Oe+OO
O.Oe+OO
(w) Cyanides (CN-)
g
1.4e-18
1.6e-18
4.9e-20
O.Oe+OO
O.Oe+OO
(w| Dissolved Matter (unspecified)
g
2.4e-01
2.5e-01
8.4e-01
O.Oe+OO
O.Oe+OO
^w) Fluorides (F-)
g
5.8e-05
6.8e-05
2.1e-06
O.Oe+OO
O.Oe+OO
(w) Hydrocarbons (unspecified)
g
8.2e-04
5.1e-06
1.7e-05
O.Oe+OO
O.Oe+OO
(w) Metals (unspecified
g
1.7e-02
1.2e-02
5.1e-04
O.Oe+OO
O.Oe+OO
^w) Nitrates (N03-)
g
1.4e-05
1.6e-05
4.9e-07
O.Oe+OO
O.Oe+OO
(w) Nitrogenous Matter (unspecified, as
N)
g
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
A - 14
-------
Virgin Oil- LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
Use
Ertd-of-
life
(w) Oils (unspecified)
g
6.7e-02
3.6e-01
6.2e-03
O.Oe+OO
O.Oe+OO
(w) Phenols
a
6.5e-05
1,8e-02
2.4e-04
O.Oe+OO
O.Oe+OO
(w) Phosphates (P04 3-, HP04-,
H2P04-, H3P04, as P)
9
0.0e+00
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
(jw) Sodium (Na+)
a
1.69+01
1.0e-01
3.4e-01
O.Oe+OO
O.Oe+OO
(w) Sulfates (S04-)
?
1.2e-05
1.4e-05
4.4e-07
O.Oe+OO
O.Oe+OO
(w) Suspended Matter (unspecified)
1,5e-02
4.2e+00
5.7e-02
O.Oe+OO
O.Oe+OO
1 quart (Bio-Oil)
quart
0.0e+00
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
1 quart (Re-refine Oil)
quart
0.0e+00
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
1 quart (Virgin Oil)
quart
0.0e+00
0.0e+00
O.Oe+OO
1 .Oe+OO
O.Oe+OO
Bio-oil
kg
O.Oe+OO
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
Component 2
NA
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Component 3
NA
0.0e+00
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
Lubricants (kg)
kg
0.0e+00
8.2e-01
8.2e-01
O.Oe+OO
O.Oe+OO
Waste (50 years - prorated)
kg
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
8.2e-01
Waste (End-of-Life)
k 9
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
8.2e-01
Waste (first replacement)
k?
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Waste (installation)
kg
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Waste (Mfg.)
kg
5.9e-03
1.5e-02
3.2e-04
O.Oe+OO
O.Oe+OO
Waste (non-recyclable, 50-year)
kg
0.0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
8.2e-01
Waste (second replacement)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
E Feedstock Energy
MJ
3.8e+01
-3.1e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
E Fuel Energy
MJ
2.6e+00
6.7e+00
8.9e-01
O.Oe+OO
O.Oe+OO
E Non Renewable Energy
MJ
4.0e+01
3.60+00
8.8e-01
O.Oe+OO
O.Oe+OO
E Renewable Energy
MJ
2.5e-02
2.96-02
8.8e-04
O.Oe+OO
O.Oe+OO
E Total Primary Energy
MJ
4.0e+01
3.6e+00
8.9e-01
O.Oe+OO
O.Oe+OO
A - 15
-------
Table 8: Life Cycle Inventory, Rerefined Oil
Rerefined OH - LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
(r) Baryte (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
^r) Bauxite (AI203.2H20, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bentonite (AI203.4Si02.H20, in
ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Borax (Na20.2B203.10H20)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Clay
in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
^r) Coal (in ground)
kg
1.2e-04
6.9e-03
5.8e-04
O.Oe+OO
O.Oe+OO
(r) Copper (Cu, Ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Diabase Rock
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Dolomite (CaC03.MgC03, in ground)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(jrj) Feldspar (ore)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Granite (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Gravel
in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Gypsum (CaS04: in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) llmenite Ore (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
^r| Iron (Fe, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Jute
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Kaolin i
AI203.2Si02.2H20, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Limestone
CaC03, in ground)
kg
2.3e-05
1,3e-03
1.1e-04
O.Oe+OO
O.Oe+OO
^ Natural Gas (in ground)
kg
3.4e-04
1,3e-02
1,6e-03
O.Oe+OO
O.Oe+OO
^rj) Oil (in ground)
kg
3.9e-03
2.0e-03
1,9e-02
O.Oe+OO
O.Oe+OO
r) Perlite (Si02, ore)
kg
8.9e-07
2.0e-04
4.2e-06
O.Oe+OO
O.Oe+OO
^r| Phosphate Rock (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Pine Rosin
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Potash
(K20, in ground)
fa
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Potassium
ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Pyrite (FeS2, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Sand
iound)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Sodium Chloride (NaCI, in ground or
in sea)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(jrj) Uranium (U, ore)
kg
2.9e-09
1.6e-07
1.4e-08
O.Oe+OO
O.Oe+OO
^r) Wastepaper
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
^r) Wood (standing)
m3
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Cullet (from stock)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Flv Ash
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Iron Ore Slag
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Recovered Solids (iron scraps)
!S_,„
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
A - 16
-------
I Rerefined Oil • LC Stac
e
Article
Units
Raw
Materials
Manufacturing
T ransport
Use
End-of-
life
Used Oil
kg
8.6e-01
8.6e-01
0.0e+00
0.0e+00
0.0e+00
Water Used (total)
liter
5.5e-04
4.6e-04
2.6e-03
0.0e+00
0.0e+00
(a) Aldehydes
g
4.0e-Q7
2.1e-05
1.9e-06
0.0e+00
0.0e+00
(a) Ammonia (NH3)
g
1,7e-08
3.0e-08
7.9e-08
0.0e+00
0.0e+00
(a) Benzene
g
8.8e-07
4.0e-07
4.2e-06
0.0e+00
0.0e+00
(a) Carbon Dioxide (C02, biomass)
9
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.00+00
(a) Carbon Dioxide (C02, fossil)
g
1,3e+01
2.5e+02
6.2e+01
0.0e+00
0.0e+00
(a) Carbon Monoxide (CO)
g
1.1e-02
1.9e-01
5.4e-02
0.0e+00
0.0e+00
^a) Fluorides (F-)
g
8.5e-15
4.0e-13
4.0e-14
0.0e+00
0.0e+00
(a) Formaldehyde
g
1,2e-05
5.4e-06
5.6e-05
0.0e+00
0.0e+00
(a) Hydrocarbons (except methane)
g
6.6e-03
1.3e-03
3.1e-02
0.0e+00
0.0e+00
(ja) Hydrocarbons (unspecified)
g
5.2e-03
8.6e-01
2.4e-02
0.0e+00
0.0e+00
(a) Hydrogen Chloride (HCI)
g
6.6e-05
3.7e-03
3.1e-04
0.0e+00
0.0e+00
(a) Hydrogen Fluoride (HF)
g
8.2e-06
4.66-04
3.9e-05
0.0e+00
0.0e+00
(ja) Hydrogen Sulfide (H2S)
g
2.9e-05
1.8e-05
1.4e-04
0.0e+00
0.0e+00
^a) Lead (Pb)
9
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(a) Metals (unspecified)
g
5.4e-07
6.9e-05
2.5e-05
0.0e+00
0.0e+00
^a) Methane (CH4)
g
4.5e-03
1,2e-01
2.1e-02
0.0e+00
0.0e+00
(ja) Nitrogen Oxides (NOx as N02)
g
3.1e-02
5.2e-01
1.4e-01
0.0e+00
0.0e+00
(a) Nitrous Oxide (N20)
g
2.4e-03
5.4e-03
1.1e-02
0.0e+00
0.0e+00
(a) Organic Matter (unspecified)
a
1.9e-06
1.0e-04
8.8e-06
0.0e+00
0.0e+00
(a) Particulates (unspecified)
a
3.2e-02
3.1e-01
1,5e-01
0.0e+00
0.0e+00
(ja) Phenolics
9
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(a) Sulfur Oxides (SOx as S02)
g
1.9e-02
1.5e+00
9.1e-02
0.0e+00
0.0e+00
(a) Volatile Organic Compounds (VOCs)
9
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Acids (H+)
a
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Ammonia (NH4+, NH3, as N)
9
3.8e-04
8.7e-02
1,8e-03
0.0e+00
0.0e+00
(w) AOX (Adsordable Organic Halogene)
a
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
-------
Perefined Oil - LC Stac
e
¦ Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
(w) Nitrogenous Matter (unspecified, as
N)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Oils (unspecified)
9
1.3e-03
2.3e-01
6.2e-03
0.0e+00
0.0e+00
(w) Phenols
9
5.1e-05
1.1e-02
2.4e-04
0.0e+00
0.0e+00
(w) Phosphates (P04 3-, HP04-,
H2P04-, H3P04, as P)
9
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Sodium (Na+)
9
7.2&-02
3.7e-02
3.4e-01
0.0e+00
0.0e+00
(w) Sulfates (S04--)
9
9.3e-08
5.2e-06
4.4e-07
0.0e+00
0.0e+00
(w) Suspended Matter (unspecified)
9
1,2e-02
2.7e+00
5.7e-02
O.Oe+OO
0.0e+00
1 quart (Bio-Oil)
quart
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
1 quart (Re-refine Oil)
quart
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
1 quart (Virgin Oil)
quart
0.0e+00
0.0e+00
0.0e+00
1,0e+00
0.0e+00
Bio-oil
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Component 2
NA
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Component 3
NA
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Lubricants (kg)
kg
0.0e+00
8.2e-01
8.2e-01
0.0e+00
0.0e+00
Waste (50 years - prorated)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
8.2e-01
Waste (End-of-Life)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
8.2e-01
Waste (first replacement)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Waste (installation)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Waste (Mfg.)
kg
6.7e-05
7.6e-03
3.2e-04
0.0e+00
0.0e+00
Waste (non-recyclable, 50-year)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
8.2e-01
Waste (second replacement)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
E Feedstock Energy
MJ
0.0e+00
-5.0e-02
0.0e+00
0.0e+00
0.0e+00
E Fuel Energy
MJ
1.9e-01
1.1e+00
8.9e-01
0.0e+00
0.0e+00
E Non Renewable Energy
MJ
1.9e-01
1.0e+00
8.8e-01
0.0e+00
0.0e+00
E Renewable Energy
MJ
1.9e-04
1.0e-02
8.8e-04
0.0e+00
0.0e+00
E Total Primary Energy
MJ
1 9e-01
1.0e+00
8.9e-01
0.0e+00
0.0e+00
A- 18
-------
Table 9: Life Cycle Inventory, Bio-Based Oil
Bio-Based Oil - LC Sta{
ie
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
llfe
(r) Baryte (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bauxite (AI203.2H20, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bentonite (AI203.4Si02.H20, in
ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Borax (Na2O.2B2O3.10H2O)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Clay (in ground)
ft
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Coal (in ground)
k?
5.3e-03
1.6e-02
6.0e-04
O.Oe+OO
O.Oe+OO
(r) Copper (Cu, Ore)
ft
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Diabase Rock
ft ,
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Dolomite (CaC03.MgC03, in ground)
ft
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Feldspar (ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Granite (in ground)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Gravel (in ground)
ft
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Gypsum (CaS04: in ground)
ft
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) llmenite Ore (in ground)
ft
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Iron (Fe, ore)
ft
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Jute
ft
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Kaolin (AI203.2Si02.2H20, ore)
ft
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.O0+OO
O.Oe+OO
(r) Limestone (CaC03, in ground)
ft.
9.2e-04
3.0e-03
1.1e-04
O.O0+OO
O.Oe+OO
(r) Natural Gas (in ground)
kg
9.3e-03
4.3e-02
1.70-03
O.O0+OO
O.Oe+OO
(r) Oil (in ground)
ft
2.4e-02
2.6e-03
1.90-02
O.O0+OO
O.Oe+OO
(r) Perlite (Si02, ore)
kg
4.5e-06
O.Oe+OO
4.40-06
O.O0+OO
O.Oe+OO
(r) Phosphate Rock (in ground)
ft
5.5e-02
O.Oe+OO
O.O0+OO
O.Oe+OO
O.Oe+OO
(r) Pine Rosin
ft
O.Oe+OO
O.Oe+OO
0.00+00
O.Oe+OO
O.Oe+OO
(r) Potash (K20, in ground)
kg
3.2e-02
O.Oe+OO
0.00+00
O.Oe+OO
O.Oe+OO
(r) Potassium (ore)
ft
O.Oe+OO
O.Oe+OO
O.O0+OO
O.O0+OO
O.Oe+OO
(r) Pyrite (FeS2, ore)
kg
O.Oe+OO
O.Oe+OO
O.O0+OO
O.O0+OO
O.Oe+OO
(r) Sand (in ground)
kg
O.Oe+OO
O.Oe+OO
0.00+00
O.O0+OO
O.Oe+OO
(r) Sodium Chloride (NaCI, in ground or
in sea)
kg
O.Oe+OO
O.Oe+OO
0.00+00
O.O0+OO
O.Oe+OO
(r) Uranium (U, ore)
kg
3.0e-07
3.8e-07
1.4e-08
O.O0+OO
O.Oe+OO
fr) Wastepaper
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Wood (standing i
m3
O.Oe+OO
O.Oe+OO
0.00+00
O.Oe+OO
O.Oe+OO
Cullet from stock)
kg
O.Oe+OO
O.Oe+OO
O.O0+OO
O.Oe+OO
O.Oe+OO
Fly Ash
k9
O.Oe+OO
O.Oe+OO
0.00+00
O.Oe+OO
O.Oe+OO
Iron Ore Slag
kg
O.Oe+OO
O.Oe+OO
0.00+00
O.Oe+OO
O.Oe+OO
Recovered Solids (iron scraps)
kg
O.Oe+OO
O.Oe+OO
0.00+00
O.O0+OO
O.O0+OO
Used Oil
&
O.Oe+OO
O.Oe+OO
0.00+00
O.Oe+OO
O.O0+OO
A - 19
-------
Bio-Based
Oil - LC Stai
e
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
Water Used (total
liter
5.9e+02
3.5e-03
2.7e-03
O.Oe+OO
0.0e+00
(a) Aldehydes
g
1.7e-04
1.2e-04
2.0e-06
0.0e+00
0.0e+00
(a) Ammonia (NH3)
g
1,6e-01
4.0e-05
8.3e-08
0.0e+00
0.0e+00
(a) Benzene
g
4.4e-06
0.0e+00
4.4e-06
0.0e+00
0.0e+00
(a) Carbon Dioxide (C02, biomass)
g
-1,4e+03
-1.1e+03
0.0e+00
0.0e+00
0.0e+00
^a) Carbon Dioxide (C02, fossil)
9
1,0e+02
1,7e+02
6.5e+01
0.0e+00
0.0e+00
^a) Carbon Monoxide (CO)
g
4.7e-01
5.2e-02
5.7e-02
0.0e+00
0.0e+00
(a) Fluorides (F-)
g
4.6e-03
1.4e-12
4.2e-14
0.0e+00
0.0e+00
(a) Formaldehyde
g
6.0e-05
2.6e-12
5.8e-05
0.0e+00
0.0e+00
(a) Hydrocarbons (except methane)
g
1,8e-01
1.6e+00
3.3e-02
0.0e+00
0.0e+00
(a) Hydrocarbons
unspecified)
9
4.5e-01
1.3e-03
2.6e-02
0.0e+00
0.0e+00
(a) Hydrogen Chloride (HCI)
g
1,4e-03
8.6e-03
3.2e-04
0.0e+00
0.0e+00
(a) Hydrogen Fluoride (HF)
g
4.1e-05
1.1e-03
4.1e-05
O.Oe+OO
0.0e+00
(a) Hydrogen Sulfide (H2S)
g
1,4e-04
1 0e-05
1,4e-04
0.06+00
0.0e+00
(a) Lead (Pb)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(a) Metals (unspecified)
9
2.8e-07
2.5e-08
2.7e-07
0.0e+00
0.0e+00
^a) Methane (CH4)
g
1,2e-01
3.2e-01
2.2&-02
0.0e+00
0.0e+00
(a) Nitrogen Oxides (NOx as N02)
9
6.7e-01
3.2e-01
1,5e-01
0.0e+00
0.0e+00
(a) Nitrous Oxide i
N20)
g
4.7e-03
1,6e-03
1 2e-02
0.0e+00
0.0e+00
(a) Organic Matter (unspecified)
Q
1.1e-02
2.4e-04
9.2e-06
0.0e+00
0.0e+00
(a) Particulates (unspecified)
g
3.6e-01
2.3e-01
1,6e-01
0.0e+00
0.0e+00
(a) Phenolics
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(a) Sulfur Oxides (SOx as S02)
g
3.2e-01
1,2e+00
9.5e-02
0.0e+00
0.0e+00
(Ja) Volatile Organic Compounds (VOCs)
9 ,
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Acids (H+)
g
1.4e-04
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(jw) Ammonia (NH4+, NH3, as N)
9
2.1e-03
5.1e-05
1.9e-03
0.0e+00
0.0e+00
(w) AOX (Adsordable Organic Halogene)
a
0.0e+00
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
(w) Benzene
9
1.5e-15
4.0e-14
1.5e-15
0.0e+00
0.0e+00
(w) BOD5 (Biochemical Oxygen
Demand)
g
1.7e-02
2.2e-04
1.3e-02
0.0e+00
O.Oe+OO
(w) Calcium (Ca++)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
(w) Chlorides (CI-)
g
2.9e-01
7.7e-03
2.8e-01
0.0e+00
0.06+00
(w) COD (Chemical Oxygen Demand)
a
1.2e-01
1,8e-03
1.1e-01
0.0e+00
O.Oe+OO
(w) Cyanides (CN-)
g
5.2e-20
1.4e-18
5.1e-20
0.0e+00
O.Oe+OO
(w) Dissolved Matter i unspecified)
g
9.6e-01
4.8e-02
8.8e-01
0.0e+00
O.Oe+OO
(w) Fluorides (F-
9
4.7e-05
5.7e-05
2.2e-06
0.0e+00
O.Oe+OO
(w) Hydrocarbons (unspecified)
a
4.1e-02
7.86-01
1.8e-05
0.0e+00
O.Oe+OO
(w) Metals unspecified)
9
5.5e-04
1.3e-05
5.4e-04
0.0e+00
O.Oe+OO
(w) Nitrates iN03-i
SL-
1.1e-05
1.4e-05
5.1e-07
0.0e+00
O.Oe+OO
(w) Nitrogenous Matter (unspecified, as
g
6.2e+01
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
A-20
-------
Bio*Based Oil • LC Stat
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
N)
(w) Oils (unspecified)
g
7.3e-03
4.2e-04
6.4e-03
0.0e+00
0.0e+00
(w) Phenols
g
2.5e-04
3.9e-06
2.5e-04
0.0e+00
0.0e+00
(w) Phosphates (P04 3-, HP04--,
H2P04-, H3P04, as P)
g
9.7e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
^w) Sodium (Na+)
g
3.7e-01
1,0e-02
3.6e-01
0.0e+00
0.0e+00
(w) Sulfates (S04--)
g
1,0e-05
1,2e-05
4.6e-07
0.0e+00
0.0e+00
(w) Suspended Matter (unspecified)
g
1,6e+03
9.4e-04
5.9e-02
0.0e+00
0.0e+00
1 quart
(Bio-Oil)
quart
0.0e+00
0.0e+00
0.0e+00
1,0e+00
0.0e+00
1 quart (Re-refine Oil)
quart
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
1 quart (Virgin Oil)
quart
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Bio-oil
kg
0.0e+00
0.0e+00
8.6e-01
0.0e+00
0.0e+00
Component 2
NA
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Component 3
NA
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Lubricants (kg)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Waste (50 years - prorated)
kff
0.0e+00
0.0e+00
0.0e+00
0.0e+00
8.6e-01
Waste i
End-of-Life)
fa
0.0e+00
0.0e+00
0.0e+00
0.0e+00
8.6e-01
Waste i
first replacement)
kg
0.0e+00
0.0e+00
0.0e+00
0.0©+00
0.0e+00
Waste (installation)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Waste (Mfg.)
kg
2.2e-03
1.3e-02
3.3e-04
0.0©+00
0.0e+00
Waste (non-recyclable, 50-year)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
8.6e-01
Waste (second replacement)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
E Feedstock Energy
MJ
2.1e-01
3.5e-02
0.0e+00
0.0e+00
0.0e+00
E Fuel Energy
MJ
1.60+00
2.9e+00
9.2e-01
0.00+00
0.0e+00
E Non Renewable Energy
MJ
1.8e+00
2.9e+00
9.2e-01
0.00+00
0.0e+00
E Renewable Energy
MJ
1.4e-02
2.4e-02
9.2e-04
0.0e+00
0.0e+00
E Total Primary Energy
MJ
1.8e+00
3.0e+00
9.20-01
0.0e+00
0.0e+00
A-21
-------
Appendix B: Wall Insulation Case Study
Goal and Scope Definition
Goal
The goal of this pilot study was to determine the feasibility of evaluating the environmental performance of four different
types of wall insulation by using the FRED LCA system. The four types of wall insulation evaluated were R-13 blown
cellulose insulation, R-ll fiberglass batt insulation, R-15 fiberglass batt insulation and R-12 blown mineral wool
insulation. Life cycle inventory data for this analysis was taken from NIST's Building for Environmental and Economic
sustainability program.
Intended Applications and Audiences
The LCA itself was intended to be used to support a comparative assertion of environmental superiority of a product over
a competing product in the context of the Federal requirement for environmentally preferable purchasing. Audiences
include purchasing agents as well as other federal and state officials. An ancillary use of the study is to support efforts
towards environmental improvement.
Scope
Description of the Product
The products evaluated represented several types of wall insulation with varying levels of thermal resistance. Blown
cellulose insulation is produced primarily from post-consumer wood pulp and is treated with fire retardant. Fiberglass
batt insulation is made by forming spun-glass fibers into batts. Blown mineral wool insulation is made from forming
fibers from either natural rock or iron ore blast furnace slag.
System Function and Functional Unit
The system function for the alternative products is to provide a constant thermal performance (for both heating and
cooling) for a house of 9600 cubic feet with an environment of 70 degrees F, given a typical wood frame-residential
construction, when the outside annual temperature is 55 degrees F, with average winter temperature of 32 degrees F and
average summer temperature of 85 degrees F. The functional unit is quantity of each insulation product required to
maintain the desired thermal performance over a 50-year period.
System Boundaries
B- 1
-------
The system studied included all unit processes for the manufacture of the insulation products as well as the
heating/cooling energy requirements associated with their use.
Data Gathering
The entire data gathering exercise for this project involved extracting data from the BEES database.
According to NIST, the BEES database includes both primary data as well as industry average data.
Allocation
According to the contractor for BEES, all allocation of emissions and resource use was performed
based on a mass basis.
Impact Assessment
Impact assessment was performed based on the FRED LCA system indicators, as described in the
body of this work. The assignment of inventory data to impact categories is shown in the table below.
Table 1: Assignment of Inventory Results to Impact Categories
Inventory Result
Impact Category
Justification
Fossil Fuels and Uranium
Resource Depletion
Although Uranium is not truly a
fossil fuel, it is "used up" in a
precisely comparable fashion
C02, N20, Methane
Global Warming
These are important greenhouse
gases which do not participate to a
great extent in other impact
categories
CO
Human Toxicity
Photochemical Smog
Global Warming;
CO is a human and animal
toxicant, as well as a precursor to
ozone formation and a greenhouse
gas. It can participate in the first
two of these environmental
mechanisms without losing its
potency for the others.
CFC's, HCFC's, Halons
Global Warming 100%
Stratospheric Ozone
Depletion 100%
These substances participate fully
in both of these parallel
environmental mechanisms
S02,
Acidification 100%
Although S02 contributes to
visibility deterioration, and human
health effects through the
formation of Particulate Matter,
these environmental mechanisms
are not addressed by FRED.
B - 2
-------
Inventory Result
Impact Category
Justification
HC1, HF
Acidification 100%
Human Health 100%
These acid gases have minor
human health effects as well as
contributing to acidification. It was
thought that double counting
would not significantly skew
results.
Toxic Air and Water
Emissions
Human Toxicity 100%
Ecotoxicity 100%
Since it was not possible to
evaluate the partitioning of these
substances, they were double
counted so as not to underestimate
their impacts.
NOx
Acidification 100%
Eutrophication 100%
Since FRED does not currently
evaluate the fate and transport of
NOx, this emission was double
counted.
VOC's, ROG's
Photochemical Smog
These are the essential precursors
to photochemically produced
ozone. Although some of them are
also toxic, unspeciated data does
not permit a toxic evaluation.
nh4
Eutrophication (water
emissions); acidification
(air Emissions)
Although NH4 is not an acid gas,
it undergoes changes in the soil
leading to acidification effects.
po4
Eutrophication 100%
Phosphate does not participate in
any other environmental
mechanism described by the
FRED methodology
Inventory
The table below shows the summary inventory for the four products compared. A full inventory by
life cycle stage can be found in Tables 8,9, 10 and 11.
Table 2: Summary Inventory
LCI Totals
Article
Units
Blown
Cellulose
R-11
Fiberglass
R-15
Fiberglass
Mineral Wool
B - 3
-------
(r) Bauxite (AI203.2H20, ore)
kg
2.4e-05
1.0e-06
3.4e-06
3.0e-06
(r) Borax (Na20.2B203.10H20)
kg
5.1e-02
3.5e-03
1.1e-02
0.0e+00
|r) Clay (in ground)
kg
2.2e-06
7.8e-08
2.6e-07
2.2e-07
^r) Coal (in ground)
kg
9.3e-02
2.2e-02
6.0e-02
8.9e-02
(r) Diabase Rock
kg
0.0e+00
0.0e+00
0.0e+00
6.7e-02
(r) Iron (Fe, ore)
kg
2.7e-05
7.7e-07
2.5e-06
2.1e-06
(Jr) Limestone (CaC03, in ground)
kg
1 7e-02
1,7e-02
5.5e-02
1,3e-03
^r) Natural Gas (in ground)
kg
2.5e-01
4.2e-02
1.1e-01
1.5e-01
(r) Oil (in ground)
kg
1,5e-01
1,8e-01
1,9e-01
1,8e-02
^r) Perlite (Si02, ore)
kg
1,6e-05
1,7e-05
1,7e-05
1,6e-06
Cullet (from stock)
kg
0.0e+00
3.7&-03
1 2e-02
0.0e+00
Iron Ore Slag
kg
0.0e+00
0.0e+00
0.0e+00
2.7e-01
Water Used (total)
liter
1,2e+00
2.5e-01
4.7e-01
3.0e-01
^a) Aldehydes
9
2.7e-04
1,2e-04
2.5e-04
8.8e-04
^a) Ammonia (NH3)
g
6.4G-06
2.1e-05
2.2e-05
2.0e-05
^a) Benzene
9
1.6e-05
4.0e-05
4.0e-05
1.6e-06
^a) Carbon Dioxide (C02, fossil)
9
9.4e+02
1.8e+02
4.7e+02
1.2e+02
(a) Fluorides (F-)
9
6.5 e-08
5.0e-09
1.6e-08
6.5e-03
^a) Formaldehyde
Q
2.1e-04
9.0e-02
3.0e-01
8.0e-03
(a) Hydrocarbons (except
methane)
g
2.5e-01
9.1e-02
1,8e-01
1,9e+00
(a) Hydrocarbons (unspecified)
g
1.1e+00
1,8e-01
2.9e-01
1.6e-01
^ Hydrogen Chloride (HCI)
9
5.2e-02
1.1e-02
3.1e-02
4.0e-03
(a) Hydrogen Fluoride (HF)
g
5.8e-03
1,4e-03
3.9e-03
5.2e-04
(a) Hydrogen Sulfide (H2S)
g
1.1e-03
1,4e-03
1.5e-03
9.7e-05
(a) Methane (CH4)
g
1,6e+00
4.2e-01
1,0e+00
7.4e-01
(a) Nitrogen Oxides (NOx as
N02)
g
2.9e+00
5.4e-01
1,4e+00
3.9e-01
|a) Nitrous Oxide (N20)
9
5.1e-02
9.2e-03
1,3e-02
4.0e-02
(a) Organic Matter (unspecified)
g
1,3e-03
3.9e-04
9.7e-04
1,8e-03
^a) Particulates (unspecified)
9
1,9e+00
2.4e+00
7.8e+00
1,4e+00
(a) Phenolics
g
0.0e+00
5.0e-01
1,6e+00
0.0e+00
^a) Sulfur Oxides (SOx as S02)
g
5.5e+00
1,7e+00
4.5e+00
3.7e+00
^w) Acids (H+)
9
1,3e-02
2.3e-04
7.5e-04
6.6e-04
^w) Ammonia (NH4+, NH3, as N)
9
9.78-03
7.2e-03
7.6e-03
7.8e-04
(w) AOX (Adsordable Organic
Halogene)
9
0.0e+00
1.1e-05
1.1e-05
0.0e+00
|w) Benzene
9
2.2e-13
5.2e-14
1.4e-13
1.7e-14
(w) BOD5 (Biochemical Oxygen
Demand)
9
1.1e-01
1.0e-01
2.1e-01
1.0e-01
Chlorides (CI-)
9
1.7e+00
2.5e+00
2.6e+00
1.1e-01
(w) COD (Chemical Oxygen
Demand)
9
6.2e-01
5.2e-01
7.3e-01
2.1e-01
(w) Cyanides (CN-)
g
7.3e-18
1.8e-18
4.9e-18
5.7e-19
j^w) Dissolved Matter (unspecified)
a
3.4e+00
8.0e+00
8.2e+00
3.5e-01
^w) Fluorides (F-)
Q
3.20-04
7.6e-05
2.1e-04
2.6e-05
/w) Hydrocarbons (unspecified)
9
9.0e-03
4.96-04
1.2e-03
9.56-04
B - 4
-------
(w) Metals (unspecified)
g
4.3e-02
5.3e-03
8.1e-03
3.5e-03
(w) Nitrates (N03-)
a
6.4e-02
2.6e-05
7.6e-05
3.7e-05
(w) Nitrogenous Matter
(unspecified, as N)
9
1.1e-03
3.9e-05
1.3e-04
1.1 e-04
(w) Oils (unspecified)
Q
9.3e-02
3.3e-02
3.5e-02
3.8e-03
(w) Phenols
9
9.4e-04
9.5e-04
9.9e-04
1,0e-04
(w) Phosphates (P04 3-, HP04--,
H2P04-, H3P04, as P)
9
0.0e+00
4.9e-06
1.6e-05
2.4e-05
(w) Sodium (Na+)
9
1,5e+00
3.3e+00
3.3e+00
1.4e-01
(w) Sulfates (S04--)
g
8.9e-02
6.80-04
2.0e-03
1.2e-03
(w) Suspended Matter
(unspecified)
g
2.6e-01
2.9e-01
4.4e-01
1,5e-01
Waste (50 years - prorated)
kg
1.3e+00
2.3e-01
3.8e-01
3.3e-01
Waste (End-of-Life)
kg
1.3e+00
2.3e-01
3.8e-01
3.3e-01
Waste (installation)
kg
4.0e-01
1,2e-02
2.0e-02
2.2e-02
Waste (Mfg.)
kg
3.5e-02
1,3e-02
3.8e-02
7.7e-02
E Feedstock Energy
MJ
5.4e+00
7.4e+00
7.7e+00
7.6e-01
E Fuel Energy
MJ
1.7e+01
3.4e+00
8.7e+00
1,0e+01
E Non Renewable Energy
MJ
2.3e+01
1.1e+01
1,6e+01
1.1e+01
E Renewable Energy
MJ
1.6e-01
1,9e-01
2.5e-01
2.1e-02
E Total Primary Energy
MJ
2.3e+01
1.1e+01
1.6e+01
1.1e+01
E Fuel Energy
MJ
1,0e+01
2.2e+00
5.4e+00
E Non Renewable Energy
MJ
4.5e+01
2.1e+00
5.6e+00
E Renewable Energy
MJ
5.4e-02
1,2e-02
3.9e-02
Total Primary Energy
MJ
4.5e+01
2.1e+00
5.7e+00
Indicator Results
The table below shows the indicator results for the four systems studied.
Table 3: LCIA Results
I LCIA Results I
Indicator
Blown
lilliiii
Flbftrgfo**
lllillllll
iililiipiiii
R-15
GWP (ksCO,cqutv)
liiiiiiiiii
iilillliiilllllli
153
ODPfksCFC-U)
¦¦i
iiiillillllli
iliilillllillil
Acidification {ks SO,)
iililllilllllllii
iilllllllllilll!
5
4
BtttroDhieation (kg PO,)
ilSIIii
iiiiilill
0.1^21
0.0471
Photochemical Smog (kg 00
1.08
Illlllllll
1M
Human Toxicity
Cawer
BPmf
B - 5
-------
!_CIA Results
Indicator
Blown
Cellulose
iiliililjiiiii
R-11
Fiberglass
R.16
Mineral Wool
2 19E-03
6 52E-01
2 14E+00
Iliillilll
Ecotoxicity
I/94E-02
1 49E-02
4.69E-Q2
iiiillill
Resource Depletion
Fossil {tons oil equivalent)
1.40E+00
4.48E-G1
iiiillill
7,42B»01
Mineral {.equiv tons)
O.OOE+OG
OQOE+OO
aooE+oo
0 OOE+OQ
Precious equiv tons)
0.0GE+00
O.OOE+O0
(XOQBtOO
0 00E+Q0
Other Indicators:
Land Use (ha)
0
0
iiliilllllillilillilii
0
Water Use (kg)
i 15E+00
llllllllli
4 73E-0!
3.0QE-01
Solid Waste (kg)
1 26E+0G
2 25E-01
3 77E-01
Illlllil
Interpretation
This is an example of when it may be difficult to make a decision based on the FRED LCA model
outputs. For instance, blown cellulose has a lower indicated impact in the Human Toxicity category,
but the other products have lower indicator results for Water Use and Solid Waste. Mineral wool also
has the lowest indicator result, by an order of magnitude, for Ecotoxicity.
It is also possible to evaluate the sources of the various impacts in order to identify opportunities for
improvements. The table below shows the indicators in term of percentage for the different life cycle
stages.
B - 6
-------
Table 4: Percentage of Indicator by Life Cycle Stage, Blown Cellulose
Blown Cellulose - by LC Stage
Indicator
Raw
Materials
Manufacturing
Use
Disposal
GW*
75
21
2
1
0
ODP
0
0
0
iililllliiiil
0
Acidification
76
21
1
iiiiiiii
0
Eutrophicatio
n
90
I
5
3
0
Photochemic
al Smog
93
I
4
3
0
Human
Health
Cancer
86
0
8
6
0
NonCancer
87
0
Illlilllii
IIIIIIII
llllliilli
Eoo Health
N/A
N/A
N/A
N/A
iiiiiiili
Resource
Depletion
Fossil
96
3
lillllilili
III*
o
Mineral
llliliilll
0
0
Ilillll
llllilll
Precious
llliillllllilliii
0
llliliilll
IIIIIIII
0
Other
Indicators;
Land Use
0
0
0
0
0
Water Use
(kg)
100
0
0
0
0
Solid Waste
(kg)
0
0
0
0
too
B - 7
-------
Table 5: Percentage of Indicator by Life Cycle Stage, R-ll Fiberglass
R-ll Fiberglass - by LC Stage
Indicator
Raw
Materials
Manufacturing
Transport
Use
Disposal
GWF
6
93
1
0
lllllllllili
liillllllllliillillllllllil
0
0
iiiiiiiiiiil
0
lllllilllll
Acidification
4
96
0
iili
0
Eutrophication
16
84
t
0
lllilllii
Photochemical
Smog
9
91
0
0
0
Human Health
Cancer
4
96
0
0
0
Non-Cancer
4
96
0
0
liiiiiii
Eco Health
N/A
N/A
N/A
N/A
N/A
iiiiiiiiiliiiiiii
Fossil
S
m
0
0
lllilllii
Mineral
lllllllllili
0
I!Hum
0
lllllilllll
Precious
0
D
liiiiiii
0
lililli
Other Indicators:
Land Use
0
0
¦Hi
0
D
Water Use (kg)
lllilllii
62
liiiiiii
ill
liiiiiii
Solid Waste {kg)
0
0
1—I
lill
1 ¦¦
B - 8
-------
Table 6: Percentage of Indicator by Life Cycle Stage, R-15 Fiberglass
R-15 Fiberglass - by LC Stage
Indicator
Raw
Materials
Manufacturing
Transport
Use
Disposal
GWP
8
91
I
0
0
QDP
0
0
0
0
0
Acidification
5
94
0
0
lilllllliillli
Eutrophication
liilfllltli
61
2
ill!
liiiiiiiiiiiii
Photochemical
Smog
9
91
0
0
0
Human Health
Cancer
4
96
0
0
0
Non-Cancer
4
96
lllllllllll
0
lillillli
Eco Health
WA
N/A
llllliii
fill
llllliii
Resource Depletion
Fossil
12
U
0
0
0
Mineral
0
0
0
0
0
Precious
0
0
¦¦¦
0
ill*
Other Indicators:
Land Use
lllllllllll
0
0
0
Water Use (kg)
IM
33
0
illlllllllllii
Solid Waste (kg)
lllllilll
0
11I111I
0
illilll
B -9
-------
Table 7: Percentage of Indicator by Life Cycle Stage, Mineral Wool
Mineral Wool
liiiilli
e
Indicator
Raw
Materials
Manufacturing
Transport
Use
Disposal
GWP
34
56
7
2
0
ODP
0
0
0
0
Illillll
Acidification
1111
90
1
1
ililiil
Eutrophlcation
iiiiiliiilii
1
8
ill!!!
liiiillill
Photochemical
6
94
0
Q
0
Smog
Human Health
Cancer
96
0
3
$
0
Non-Cancer
100
0
lllllilllll
0
111 lillllll
Eco Health
N/A
N/A
liiiiiiii
N/A
lllliii
Resource Depletion
Fossil
11
m
i
' 0
0
Mineral
0
0
0
0
0
Precious
0
o
0
0
lllllilllll
iliilliljiilliiiii
Land Use
lllllllllllll
0
0
0
111*
Water Use (kg)
lllllllllii
0
;n ; 0
llllllllliillii
Solid Waste {kg)
0
0
0
0
11111111
For the most part, the majority of the four products indicator results can be found in the
manufacturing and the transportation phases of the life cycle. This result supports the guidance of the
FRED methodology, which recommends more intensive data gathering efforts in the manufacturing
phase for products which are durable goods which are not energy intensive in the use phase.
Conclusions
Like the pilot project described in Appendix A, this pilot proved that existing LCA data sets can be
used in the FRED LCA system. Concern that arose during this pilot project centered around lack of
information regarding the LCA data sets. For example, more information regarding data sources,
specificity, age, quality, etc., would have been useful in framing the applicability of the FRED LCA
system results.
B- 10
-------
Table 8: Life Cycle Inventory, Blown Cellulose
Blown Cellulose - LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
(r) Baryte (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bauxite (A1203.2H20, ore)
kg
2.4e-05
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bentonite (A1203.4Si02.H20,
in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Borax (Na20.2B203.10H20)
H
5.1e-02
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Clay (in ground)
2.2e-06
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Coal (in ground)
H
2.9e-02
6.3e-02
1.8e-04
1.2e-04
O.Oe+OO
(r) Copper (Cu, Ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Diabase Rock
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Dolomite (CaC03.MgC03, in
ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Feldspar (ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Granite (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Gravel (in ground)
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Gypsum (CaS04: in ground)
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r ) Ilmenite Ore (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Iron (Fe, ore)
kg
2.7e-05
O.Oe+OO
0. Oe+OO
O.Oe+OO
O.Oe+OO
(r) Jute
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Kaolin (A1203.2Si02.2H20,
ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Limestone (CaC03, in ground)
kg
4.5e-03
1.2e-02
3.5e-05
2.3e-05
O.Oe+OO
(r) Natural Gas (in ground)
kg
2.4e-01
6.9e-03
5.0e-04
3.4e-04
O.Oe+OO
(r) Oil (in ground)
kg
1.3e-01
2.2e-03
5.9e-03
3.9e-03
O.Oe+OO
(r) Perlite (Si02, ore)
kg
1.4e-05
O.Oe+OO
1.3e-06
9.0e-07
O.Oe+OO
(r) Phosphate Rock (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Pine Rosin
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Potash (K20, in ground)
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Potassium (ore)
kf?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Pyrite (FeS2, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Sand (in ground)
kg
4.6e-06
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Sodium Chloride (NaCl, in
ground or in sea)
kg
1.4e-02
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Uranium (U, ore)
kg
5.4e-07
1.5e-06
4.4e-09
2.9e-09
O.Oe+OO
(r) Wastepaper
kp
l.le+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Wood (standing)
m3
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
B - 11
-------
Blown Cellulose - LC Stage
Article
Units
;i: Raw
Materials
Manufacturing
Transport
End-of-
life
Cullet (from stock)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Fly Ash
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Iron Ore Slag
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Recovered Solids (iron scraps)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Water Used (total)
liter
1.2e+00
1.9e-03
8.2e-04
5.5e-04
0.0e+00
Sq Foot of Insulation (Cellulose)
Sq Ft
0.0e+00
0.0e+00
0.0e+00
0.0e+00
1.0e+00
Cellulose Insulation
kg
0.0e+00
1.3e+00
1.3e+00
1.3e+00
0.0e+00
Component 2
NA
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Component 3
NA
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(a) Aldehydes
g
7.6e-05
1.9e-04
6.1e-07
4.1e-07
0.0e+00
(a) Ammonia (NH3)
g
6.2e-06
2.3e-07
2.5e-08
1.7e-08
0.0e+00
(a) Benzene
g
1.4e-05
0.0e+00
1.3e-06
8.8e-07
0.0e+00
(a) Carbon Dioxide (C02,
biomass)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(a) Carbon Dioxide (C02, fossil)
g
7.1e+02
2.0e+02
2.0e+01
1.4e+01
0.0e+00
(a) Carbon Monoxide (CO)
g
1.0e+00
4.3e-02
1.7e-02
5.6e-02
0.0e+00
(a) Fluorides (F-)
g
6.5e-08
0.0e+00
1.3e-14
8.6e-15
0.0e+00
(a) Formaldehyde
g
1.8e-04
l,0e-ll
1.8e-05
1.2e-05
0.0e+00
(a) Hydrocarbons (except methane)
g
2.3e-01
1.6e-03
9.9e-03
6.8e-03
0.0e+00
(a) Hydrocarbons (unspecified)
g
l.le+00
5.2e-03
7.7e-03
5.2e-03
0.0e+00
fa) Hydrogen Chloride (HC1)
g
1.7e-02
3.4e-02
9.8e-05
6.6e-05
0.0e+00
(a) Hydrogen Fluoride (HF)
g
1.5e-03
4.3e-03
1.2 e-05
8.3e-06
0.0e+00
(a) Hydrogen Sulfide (H2S)
g
1.0e-03
4.1e-05
4.3e-05
2.9e-05
0.0e+00
(a) Lead (Pb)
cr
j
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(a) Metals (unspecified)
g
8.4e+03
9.8e-04
8.0e+02
5.4e+02
0.0e+00
(a) Methane (CH4)
ir
5
l.le+00
4.7e-01
6.8e-03
4.9e-03
0.0e+00
(a) Nitrogen Oxides (NOx as N02)
g
2.1e+00
6.1e-01
4.6e-02
2.1e-01
0.0e+00
(a) Nitrous Oxide (N20)
o
y
4.3e-02
3.6e-03
3.6e-03
4.4e-04
0.0e+00
(a) Organic Matter (unspecified)
g
3.4e-04
9.4e-04
2.8e-06
1.9e-06
0.0e+00
(a) Particulates (unspecified)
g
9.6e-01
8.9e-01
4.7e-02
7.0e-03
0.0e+00
(a) Fhenolics
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
(a) Sulfur Oxides (SOx as S02)
0
y
4.3e+00
l.le+00
2.9e-02
1.9e-02
0.0e+00
(a) Volatile Organic Compounds
o
y
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Acids (H+)
g
1.3e-02
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(vv) Ammonia (NH4+, NH3, as N)
g
8.5e-03
2.0e-04
5.8e-04
3.9e-04
0.0e+00
(w) AOX (Adsordable Organic
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
B- 12
-------
Blown Cellulose - LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
Halogene)
(w) Benzene
5.6e-14
1.6e-13
4.6e-16
3.1e-16
0.0e+00
(w) BOD5 (Biochemical Oxygen
Demand)
s
1.0e-01
8.2e-04
3.9e-03
2.6e-03
0.0e+00
(w) Calcium (Ca++)
s
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Chlorides (C1-)
s
1.6e+00
3.1e-02
8.4e-02
5.7e-02
0.0e+00
(w) COD (Chemical Oxygen
Demand)
g
5.5e-01
6.9e-03
3.3e-02
2.2e-02
0.0e+00
(w) Cyanides (CN-)
g
1.9e-18
5.4e-18
1.6e-20
1.0e-20
0.0e+00
(w) Dissolved Matter (unspecified)
g
2.9e+00
9.7e-02
2.7e-01
1.8e-01
0.0e+00
(w) Fluorides (F-)
g
9.3e-05
2.3e-04
6.6e-07
4.4e-07
0.0e+00
(w) Hydrocarbons (unspecified)
R
9.0e-03
2.0e-06
5.4e-06
3.6e-06
0.0e+00
(w) Metals (unspecified)
A
4.2e-02
5.2e-05
1.6e-04
l.le-04
0.0e+00
(w) Nitrates (N03-)
£
6.4e-02
5.4e-05
1.6e-07
l.le-07
0.0e+00
(w) Nitrogenous Matter
(unspecified, as N)
g
l.le-03
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Oils (unspecified)
g
9.0e-02
4.7e-04
2.0e-03
1.3e-03
0.0e+00
(w) Phenols
g
8.0e-04
1.6e-05
7.6e-05
5.1e-05
0.0e+00
(w) Phosphates (P04 3-, HP04--,
H2P04-, H3P04, as P)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Sodium (Na+)
g
1.2e+00
4.0e-02
l.le-01
7.3e-02
0.0e+00
(w) Sulfates (S04~)
g
8.9e-02
4.8e-05
1.4e-07
9.3e-08
0.0e+00
(w) Suspended Matter
(unspecified)
g
2.3e-01
3.7e-03
1.8e-02
1.2e-02
0.0e+00
B- 13
-------
1 Blown Cellulose - LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
End-of-
life
Waste (50 years - prorated)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
1.3e+00
Waste (End-of-Life)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
1.3e+00
Waste (first replacement)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Waste (installation)
kg
0.0e+00
0.0e+00
0.0e+00
3.3e-01
6.6e-02
Waste (Mfg.)
H
l.le-02
2.3e-02
1.0e-04
6.8e-05
0.0e+00
Waste (non-recyclable, 50-year)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Waste (second replacement)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
E Feedstock Energy
MJ
5.4e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
E Fuel Energy
MJ
1.4e+01
3.1e+00
2.8e-01
1.9e-01
0.0e+00
E Non Renewable Energy
MJ
1.9e+01
3.0e+00
2.8e-01
1.9e-01
0.0e+00
E Renewable Energy
MJ
6.1e-02
9.7e-02
2.8e-04
1.9e-04
0.0e+00
E Total Primary Energy
MJ
1.9e+01
3.1e+00
2.8e-01
1.9e-01
0.0e+00
E Fuel Energy
MJ
E Non Renewable Energy
MJ
E Renewable Energy
MJ
B- 14
-------
Table 9: Life Cycle Inventory, R-ll Fiberglass
R-ll Fiberglass - LC Stage
:v:'Article^
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
(r) Baryte (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
jr) Bauxite (AI203.2H20, ore)
k9
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bentonite (AI203.4Si02.H20, in
ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Borax (Na20.2B203.10H20)
k§
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Clay
in ground)
kfl
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
jr) Coal (in ground)
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
jr) Copper (Cu, Ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
jrj) Diabase Rock
k§
7.5e-07
1.4e-08
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Dolomite (CaC03.MgC03, in
ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Feldspar (ore)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
jr) Granite (in ground)
k9
1.3e-02
3.8e-03
3.6e-06
O.Oe+OO
O.Oe+OO
(r) Gravel (in ground)
kg
4.8e-03
3.7e-02
5.3e-05
O.Oe+OO
O.Oe+OO
jr| Gypsum (CaS04: in ground)
kg
3.4e-03
1.8e-01
6.2e-04
O.Oe+OO
O.Oe+OO
(r) llmenite Ore (in ground)
kg
7.4e-08
1.6e-05
1.4e-07
O.Oe+OO
O.Oe+OO
(r) Iron (Fe, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Jute
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Kaolin (AI203.2Si02.2H20, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(jr) Limestone (CaC03, in ground)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(jrj) Natural Gas (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
jr) Oil (in ground)
k?
3.7e-02
6.1e-09
O.Oe+OO
O.Oe+OO
O.Oe+OO
jr) Perlite (Si02, ore)
k?
1.1e-04
1.8e-05
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Phosphate Rock (in ground)
k?
3.3e-08
4.7e-07
4.6e-10
O.Oe+OO
O.Oe+OO
jr) Pine Rosin
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
jr) Potash (K20, in ground)
kg
O.Oe+OO
1.1e-05
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Potassium (ore)
k?
3.7e-03
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Pyrite (FeS2, ore)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
jr^ Sand
(in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Sodi
around o
um Chloride (NaCI, in
r in sea)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
jrjl Uranium U, ore)
kg
9.5e-02
1.6e-01
8.6e-05
O.Oe+OO
O.Oe+OO
fr) Wastepaper
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
1 .Oe+OO
O.Oe+OO
jr^ Wood (standing
m3
O.Oe+OO
7.0e-02
6.9e-02
O.Oe+OO
O.Oe+OO
Cullet (from stock)
kg
O.Oe+OO
1.7e-01
O.Oe+OO
O.Oe+OO
O.Oe+OO
Fly Ash
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Iron Ore Slag
kg
1.2e-05
1,0e-04
6.4e-08
O.Oe+OO
O.Oe+OO
Recovered Solids (iron scraps)
*2__
2.0e-07
2.1e-05
2.6e-09
O.Oe+OO
O.Oe+OO
B- 15
-------
R-ll Fiberglass - LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
End-of-
life
Water Used (total)
liter
7.3e-08
3.9e-05
1,4e-07
0.0©+00
0.0e+00
Sq Foot of Insulation (Cellulose)
Sq Ft
0.0e+00
3.5e+00
O.Oe+OO
0.0e+00
0.0e+00
Cellulose Insulation
k?
1.1e+01
1.7e+02
2.1e+00
0.0e+00
0.0e+00
Component 2
NA
5.1e-03
7.3e-02
1,8e-03
0.0e+00
O.Oe+OO
Component 3
NA
5.0e-09
1.1e-12
1.3e-15
0.0e+00
0.0e+00
(a) Aldehydes
g
3.9e-03
8.6e-02
1 9e-06
0.0e+00
0.0e+00
(a) Ammonia (NH3)
g
3.7e-02
5.3e-02
1.0e-03
0.0e+00
0.0e+00
^a) Benzene
g
4.6e-02
1.3e-01
8.1e-04
0.0e+00
0.0e+00
(a) Carbon Dioxide (C02, biomass)
g
7.2e-04
1.1e-02
1,0e-05
0.0e+00
0.0e+00
(ja) Carbon Dioxide (C02, fossil)
g
7.7e-05
1.3e-03
1.3e-06
0.0e+00
0.0e+00
(a) Carbon Monoxide (CO)
g
2.3e-05
1.3e-03
4.5e-06
0.00+00
0.0e+00
|a) Fluorides (F-)
g
0.0e+00
0.0e+00
0.0e+00
0.00+00
0.0e+00
(a) Formaldehyde
g
4.4e+01
9.9e+03
8.4e+01
0.0e+00
0.0e+00
^a) Hydrocarbons (except methane)
g
2.6e-02
4.0e-01
7.1e-04
0.00+00
0.0e+00
^a) Hydrocarbons (unspecified)
g
5.2e-02
4.8e-01
4.80-03
0.00+00
0.00+00
(a) Hydrogen Chloride (HCI)
&
4.6e-04
8.4e-03
3.8e-04
0.00+00
0.0e+00
^a]> Hydrogen Fluoride (HF)
g
3.0e-05
3.6e-04
2.9e-07
0.00+00
0.0e+00
(jaj) Hydrogen Sulfide (H2S)
g
1.0e+00
1.4e+00
5.0e-03
0.0e+00
0.0e+00
(a^ Lead (Pb)
a
0.0e+00
5.0e-01
0.0e+00
0.0e+00
O.Oe+OO
(a) Metals unspecified)
g
5.0e-02
1.7e+00
3.00-03
0.00+00
O.Oo+OO
(a) Methane (CH4)
g
0.0e+00
0.0e+00
0.0e+00
0.00+00
O.Oo+OO
(ja) Nitrogen Oxides (NOx as N02)
g
2.2&-04
8.2e-06
0.0e+00
0.00+00
O.Oe+OO
(a) Nitrous Oxide (N20)
g
5.5e-05
7.1e-03
6.00-05
0.0e+00
O.O0+OO
(jaj> Organic Matter (unspecified)
g
O.Oe+OO
1.1e-05
O.Oe+OO
0.0e+00
O.Oe+OO
^ Particulates (unspecified)
g
2.8e-15
4.9e-14
4.8e-17
0.0e+00
O.O0+OO
^ Phenolics
g
4.8e-02
5.1e-02
4.1e-04
0.0e+00
O.Oe+OO
jja| Sulfur Oxides (SOx as S02)
g
0.0e+00
0.0e+00
0.00+00
0.0e+00
O.Oe+OO
(a) Volatile Organic Compounds
jvOCs)
g
9.6e-03
2.5e+00
8.80-03
0.0e+00
O.Oe+OO
^w) Acids i H+)
g
8.4e-02
4.3e-01
3.5e-03
0.0e+00
O.Oe+OO
(w) Ammonia (NH4+, NH3, as N)
g
9.6e-20
1.7e-18
1.6e-21
0.00+00
O.Oe+OO
(w) AOX (Adsordable Organic
Halogene)
g
1.9e-02
8.0e+00
2.8e-02
0.00+00
O.Oe+OO
(w) Benzene
g
5,0e-06
7.1e-05
6.9e-08
0.0e+00
O.Oe+OO
(w) BOD5 (Biochemical Oxygen
Demand)
g
3.2e-04
1.6e-04
5.7e-07
0.0e+00
O.Oe+OO
Calcium (Ca++
8 „
1.2e-03
4.0e-03
1.7e-05
0.0e+00
O.Oe+OO
|w) Chlorides (CI-)
a
9.0e-06
1.7e-05
1.6e-08
0.0e+00
O.Oe+OO
(w) COD (Chemical Oxygen
Demand)
9
3.9e-05
0.0e+00
0.0e+00
0.00+00
O.Oe+OO
M Cyanides (CN-)
g
5.7e-04
3.20-02
2.00-04
0.00+00
O.O0+OO
B- 16
-------
R-ll Fiber
glass - LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
(w) Dissolved Matter (unspecified)
g
6.5e-06
9.3e-04
7.9e-06
0.0e+00
0.0e+00
(w) Fluorides (F-)
g
4.9e-06
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Hydrocarbons (unspecified)
g
7.3e-03
3.3e+00
1.1e-02
0.0e+00
0.0e+00
(w) Metals (unspecified)
g
5.5e-04
1.3e-04
1.5e-08
0.0e+00
0.0e+00
(w) Nitrates (N03-)
g
6.5e-02
2.2e-01
1,9e-03
0.0e+00
0.0e+00
(w) Nitrogenous Matter
(unspecified, as N)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Oils (unspecified)
a
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Phenols
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Phosphates (P04 3-, HP04-,
H2P04-, H3P04, as P)
g
0.0e+00
0.0e+00
0.0e+00
1,2e-02
0.0e+00
(w) Sodium (Na+)
g
5.2e-03
8.1e-03
1.1e-05
0.0e+00
0.0e+00
(w) Sulfates (S04-)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
2.3e-01
(w) Suspended Matter (unspecified)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
Waste (50 years - prorated)
k?
1.3e-01
7.3e+00
0.0e+00
0.0e+00
0.0e+00
Waste (End-of-Life)
kg
3.2e-01
3.1e+00
2.9e-02
0.0e+00
0.0e+00
Waste (first replacement)
k?
4.4e-01
1,0e+01
2.9e-02
0.0e+00
0.0e+00
Waste (installation)
kg
3.0e-03
1.9e-01
2.9e-05
0.0e+00
0.0e+00
Waste (Mfg.)
k9
4.5e-01
1,0e+01
2.9e-02
0.0e+00
0.0e+00
Waste (non-recyclable, 50-year)
k?
Waste (second replacement)
k?
E Feedstock Energy
MJ
E Fuel Energy
MJ
E Non Renewable Energy
MJ
E Renewable Energy
MJ
E Total Primary Energy
MJ
E Fuel Energy
MJ
E Non Renewable Energy
MJ
E Renewable Energy
MJ
E Total Primary Energy
MJ
B - 17
-------
Table 10: Life Cycle Inventory, R-15 Fiberglass
Units
RrlS Eibert
Manufacturing
flass - LG: Sta
Transport
• Use
End-of-
life
Materials
(r) Baryte (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bauxite (AI203.2H20, ore)
k9
3.4e-06
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bentonite (AI203.4Si02.H20, in
ground)
kg
O.Oe+OO
0,0e+00
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Borax (Na20.2B203.10H20)
kg
1.1e-02
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Clay (in ground)
kg
2.6e-07
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Coal (in ground)
kg
5.5e-03
5.4e-02
6.3e-05
O.Oe+OO
O.Oe+OO
r) Copper (Cu, Ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Diabase Rock
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Dolomite (CaC03.MgC03, in
ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Feldspar (ore)
k? ,
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r Granite (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Gravel (in ground)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Gypsum (CaS04: in ground)
k?
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) llmenite Ore (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Iron (Fe, ore)
kg
2.5e-06
1,4e-08
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Jute
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Kaolin (AI2O3.2SiO2.2H20, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Limestone (CaC03, in ground)
kg
4.4e-02
1,0e-02
1.2e-05
O.Oe+OO
O.Oe+OO
r) Natural Gas (in ground)
kg
1.6e-02
9.5e-02
1,7e-04
O.Oe+OO
O.Oe+OO
r) Oil (in ground)
kg
1.1 e-02
1.8e-01
2.0e-03
O.Oe+OO
O.Oe+OO
r) Perlite (Si02, ore)
k9
2.4e-07
1.6e-05
4.6e-07
O.Oe+OO
O.Oe+OO
r) Phosphate Rock (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Pine Rosin
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
r) Potash (K20, in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Potassium (ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Pyrite (FeS2, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Lr) Sand (in ground)
1,2e-01
6.1e-09
O.Oe+OO
O.Oe+OO
O.Oe+OO
U) Sodium Chloride (NaCI, in
ground or in sea)
kg
3.5e-04
1.8e-05
O.Oe+OO
O.Oe+OO
O.Oe+OO
L?) Uranium (U, ore)
kg
1.1e-07
1,3e-06
1,5e-09
O.Oe+OO
O.Oe+OO
LL) Wastepaper
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
ID Wood (standing)
m3
O.Oe+OO
1,1e-05
O.Oe+OO
O.Oe+OO
O.Oe+OO
^ullet (from stock)
kg
1.2e-02
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Ore Slaq
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
p^overed Solids (iron scraps)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
L^ier Used ftotaH
liter
3.1e-01
1.6e-01
2.8e-04
O.Oe+OO
O.Oe+OO
B - 18
-------
R-15 Fiberglass - LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
Sq Foot of Insulation (Cellulose)
Sq Ft
O.Oe+OO
0.0e+00
0.0e+00
1.0e+00
0.0e+00
Cellulose Insulation
0.0e+00
2.3e-01
2.3e-01
0.0e+00
0.0e+00
Component 2
NA
0.0e+00
1.7e-01
0.0e+00
0.0e+00
0.0e+00
Component 3
NA
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(a) Aldehydes
g
4.0e-05
2.1e-04
2.1e-07
0.0e+00
0.0e+00
(a) Ammonia (NH3)
g
6,7e-07
2.1e-05
8.7e-09
0.0e+00
0.0e+00
(a) Benzene
g
2.4e-07
3.9e-05
4.6e-07
0.0e+00
0.0e+00
(a) Carbon Dioxide (C02, biomass)
g
0.0e+00
3.5e+00
0.0e+00
0.0e+00
0.0e+00
(a) Carbon Dioxide (C02, fossil)
g
3.6e+01
4.2e+02
6.8e+00
0.0e+00
0.0e+00
(a) Carbon Monoxide (CO)
g
1,7e-02
1,2e-01
6.0e-03
0.0e+00
0.0e+00
(a) Fluorides (F-)
g
1,6e-08
2.9e-12
4.4e-15
0.0e+00
0.0e+00
(a) Formaldehyde
g
1,3e-02
2.8e-01
6.1e-06
0.0e+00
0.0e+00
(a) Hydrocarbons (except methane)
9
1,2e-01
5.4e-02
3.4e-03
0.0e+00
0.0e+00
(a) Hydrocarbons (unspecified)
9
1.5e-01
1.3e-01
2.7e-03
0.0e+00
0.0e+00
(a) Hydrogen Chloride (HCI)
g
2.4e-03
2.9e-02
3.4e-05
0.0e+00
0.0e+00
(a) Hydrogen Fluoride i
HF)
9
2.5e-04
3.6e-03
4.3e-06
0.0e+00
0.0e+00
(a) Hydrogen Sulfide (H2S)
g
7.6e-05
1.4e-03
1,5e-05
0.0e+00
0.0e+00
(a) Lead (Pb)
?
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(a) Metals (unspecified)
9
1.5e+02
9.9e+03
2.8e+02
0.0e+00
0.0e+00
(a) Methane (CH4)
9
8.6e-02
9.1e-01
2.3e-03
0.0e+00
0.0e+00
(a) Nitrogen Oxides (NOxas N02)
9
1.7e-01
1.2e+00
1.6e-02
0.0e+00
0.0e+00
(a) Nitrous Oxide (N20
9
1.5e-03
1.1e-02
1.2e-03
0.0e+00
0.0e+00
(a) Organic Matter (unspecified)
,9
9.9e-05
8.7e-04
9.6e-07
0.0e+00
0.0e+00
(a) Particulates (unspecified)
9
3.3e+00
4.5e+00
1,6e-02
0.0e+00
0.0e+00
(a) Phenolics
9
0.0e+00
1,6e+00
0.0e+00
0.0e+00
0.0e+00
(a) Sulfur Oxides (SOxas S02)
,9
1.7e-01
4.3e+00
1.0e-02
0.0e+00
0.0e+00
(a) Volatile Organic Compounds
(VOCs)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Acids (H+)
g
7.4e-04
8.2e-06
0.0e+00
0.0e+00
0.0e+00
(w) Ammonia (NH4+, NH3, as N)
g
1,8e-04
7.2e-03
2.06-04
0.0e+00
0.0e+00
(w) AOX (Adsordable Organic
Halogene)
g
0.0e+00
1.1e-05
0.0e+00
0.0e+00
0.0e+00
(w) Benzene
a
9.3e-15
1.3e-13
1.6e-16
0.0e+00
0.0e+00
(w) BOD5 (Biochemical Oxygen
Demand)
g
1.6e-01
5.2e-02
1.4e-03
0.0e+00
0.0e+00
|w Calcium (Ca++)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Chlorides (CI-)
9 ,
3.2e-02
2.5e+00
2.9e-02
0.0e+00
0.0e+00
(w) COD (Chemical Oxygen
Demand)
g
2.8e-01
4.4e-01
1.2e-02
0.0e+00
0.0e+00
(w) Cyanides (CN-j
g
3.2e-19
4.6e-18
5.4e-21
0.0e+00
0.0e+00
(w) Dissolved Matter (unspecified)
9 _
6.2e-02
8.0e+00
9.26-02
0.0e+00
0.0e+00
B- 19
-------
R-1S Fiberglass - LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
iife
(w) Fluorides (F-)
g
1.7e-05
1.9e-04
2.36-07
0.0e+00
0.0e+00
(w) Hydrocarbons (unspecified)
9
1.1e-03
1.6e-04
1,9e-06
0.00+00
0.0e+00
(w) Metals (unspecified)
Q
4.0e-03
4.1e-03
5.6e-05
0.00+00
0.00+00
(w) Nitrates (N03-)
Q
3.0e-05
4.6e-05
5.4e-08
0.0e+00
0.0e+00
(w) Nitrogenous Matter
(unspecified, as N)
g
1.3e-04
0.0e+00
0.06+00
0.00+00
0.00+00
(w) Oils (unspecified)
g
1,9e-03
3.2e-02
6.8e-04
0.0e+00
0.0e+00
(w) Phenols
g
2.1e-05
9.4e-04
2.6e-05
0.0e+00
0.0e+00
(w) Phosphates (P04 3-, HP04--,
H2P04-, H3P04, as P)
g
1.6e-05
0.0e+00
0.0e+00
0.0e+00
0.0e+00
(w) Sodium (Na+)
g
2.4e-02
3.3e+00
3.8e-02
0.0e+00
0.0e+00
(w) Sulfates (S04-)
g
1.8e-03
1.6e-04
4.80-O8
0.0e+00
0.00+00
(w) Suspended Matter (unspecified)
g
2.1e-01
2.2e-01
6.20-03
0.0e+00
0.00+00
Waste (50 years - prorated)
kg
0.0e+00
0.0e+00
0.00+00
0.0e+00
0.00+00
Waste (End-of-Life)
k?
0.0e+00
0.0e+00
0.00+00
0.0e+00
0.00+00
Waste (first replacement)
kg
0.0e+00
0.0e+00
0.00+00
0.0e+00
0.00+00
Waste (installation)
k?
0.0e+00
0.0e+00
0.00+00
2.00-02
0.00+00
Waste (Mfg.)
k?
1.7e-02
2.1e-02
3.50-05
0.00+00
0.0e+00
Waste (non-recyclable, 50-year)
kg
0.0e+00
0.0e+00
0.00+00
0.00+00
3.8e-01
Waste (second replacement)
k?
0.0e+00
0.0e+00
0.00+00
0.00+00
0.00+00
E Feedstock Energy
MJ
4.3e-01
7.3e+00
0.00+00
0.00+00
0.00+00
E Fuel Energy
MJ
1.0e+00
7.60+00
9.7e-02
0.06+00
0.00+00
E Non Renewable Energy
MJ
1,5e+00
1.5e+01
9.7e-02
0.0e+00
0.0e+00
E Renewable Energy
MJ
9.9e-03
2.4e-01
9.7e-05
0.0e+00
0.0e+00
E Total Primary Energy
MJ
1.5e+00
1.5e+01
9.7e-02
0.0e+00
0.0e+00
E Fuel Energy
MJ
E Non Renewable Energy
MJ
E Renewable Energy
MJ
E Total Primary Energy
MJ
B - 20
-------
Table 11: Life Cycle Inventory, Mineral Wool
Mineral Wool - LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
(r) Baryte (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bauxite (AI203.2H20, ore)
kg
3.0e-06
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Bentonite (AI203.4Si02.H20, in
ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Borax (Na20.2B203.10H20)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Clay (in ground)
kg
2.26-07
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Coal (in ground)
kg
7.1e-03
8.2e-02
9.5e-05
3.26-05
O.Oe+OO
(r) Copper (Cu, Ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Diabase Rock
kg
6.7e-02
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Dolomite (CaC03.MgC03, in
ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Feldspar (ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Granite (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Gravel (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Gypsum (CaS04: in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) llmenite Ore (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Iron (Fe, ore)
kg
2.1e-06
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Jute
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Kaolin (AI203.2Si02.2H20, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Limestone (CaC03, in ground)
kg
1.1 e-03
1.5e-04
1.8e-05
6.0e-06
O.Oe+OO
(r) Natural Gas (in ground)
kg
1.3e-02
1.3e-01
2.6e-04
8.8e-05
O.Oe+OO
(r) Oil (in ground)
kg
1,2e-02
2.0e-03
3.0e-03
1,0e-03
O.Oe+OO
(r) Perlite (Si02, ore)
kg
6.2e-07
8.0e-08
6.9e-07
2.3e-07
O.Oe+OO
(r) Phosphate Rock (in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Pine Rosin
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Potash (K20, in ground)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Potassium (ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Pyrite (FeS2, ore)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(jr) Sand (in ground)
kg
5.7e-08
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Sodium Chloride (NaCI, in ground or
in sea)
kg
2.4e-04
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(Jr) Uranium (U, ore)
kg
1.5e-07
1.9e-08
2.3e-09
7.6e-10
O.Oe+OO
(r) Wastepaper
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
(r) Wood (standing)
m3
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Cullet (from stock)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Flv Ash
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Iron Ore Slag
2.7e-01
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Recovered Solids (iron scraps)
kg
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Water Used (total)
liter
3.0e-01
7.2e-05
4.26-04
1,4e-04
O.Oe+OO
Sa Foot of Insulation (Cellulose
Sq Ft
O.Oe+OO
O.Oe+OO
O.Oe+OO
1.0e+00
O.Oe+OO
Cellulose Insulation
kg
O.Oe+OO
3.4e-01
3.4e-01
3.4e-01
O.Oe+OO
Component 2
NA
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
Component 3
NA
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
O.Oe+OO
B - 21
-------
Mineral Wool - LC Stage
¦ Article
Units
Raw
Materials
Manufacturing
Transport
End-of •
life
(a) Aldehydes
g
8.8e-05
7.9e-04
3.1e-07
1.1 e-07
O.Oe+OO
(a) Ammonia (NH3)
g
2.0e-05
4.4e-09
1 3e-08
4.4e-09
0.0e+00
(a) Benzene
6.19-07
7.9e-08
6.8e-07
2.3e-07
O.Oe+OO
(a) Carbon Dioxide (C02, biomass)
g
0.0e+00
0.0e+00
O.Oe+OO
0.0e+00
O.Oe+OO
(a) Carbon Dioxide (C02, fossil)
g
5.06+01
6.1e+01
1.0e+01
3.5e+00
O.Oe+OO
(a) Carbon Monoxide (CO)
g
2.16-02
7.3e-02
8.9e-03
1,5e-02
O.Oe+OO
(a) Fluorides (F-)
g
1,0e-08
6.5e-03
6.6e-15
2.2e-15
O.Oe+OO
(a) Formaldehyde
g
8.08-03
1.1 e-06
9.1e-06
3.1 e-06
O.Oe+OO
(a) Hydrocarbons (except methane)
J
8.80-02
1.8e+00
5.16-03
1,8e-03
O.Oe+OO
(a) Hydrocarbons (unspecified)
g
1.60-01
1,4e-03
4.0e-03
1.3e-03
O.Oe+OO
(a) Hydrogen Chloride (HCI)
y
3.5e-03
4.2e-04
5.1e-05
1.7e-05
O.Oe+OO
(a) Hydrogen Fluoride (HF)
g
4.08-04
1.1e-04
6.4e-06
2.1e-06
O.Oe+OO
(a) Hydrogen Sulfide (H2S)
g
6.40-05
3.1 e-06
2.2e-05
7.5e-06
O.Oe+OO
(a) Lead (Pb)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
(a) Metals (unspecified)
g
3.7e+02
4.8e+01
4.2e+02
1.4e+02
O.Oe+OO
(a) Methane (CH4)
g
8.36-02
6.5e-01
3.50-03
1,3e-03
O.Oe+OO
(a) Nitrogen Oxides (NOx as N02)
?
1.96-01
1.2e-01
2.46-02
5.4e-02
O.Oe+OO
(a) Nitrous Oxide (N20)
g
3.10-03
3.5e-02
1,9e-03
1.1e-04
O.Oe+OO
(a) Organic Matter (unspecified)
g
1.96-04
1,6e-03
1,4e-06
4.8e-07
O.Oe+OO
(a) Particulates (unspecified)
g
6.20-01
8.0e-01
2.4e-02
1.8e-03
O.Oe+OO
(a) Phenolics
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
(a) Sulfur Oxides (SOx as S02)
?
2.06-01
3.5e+00
1,5e-02
4.9e-03
O.Oe+OO
(a) Volatile Organic Compounds
(VOCs)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
(w) Acids (H+)
3
6.6e-04
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
(w) Ammonia (NH4+, NH3, as N)
g
3.4©-04
3.7e-05
3.0e-04
1,0e-04
O.Oe+OO
(w) AOX (Adsordable Organic
Halogene)
g
0.0e+00
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
(w) Benzene
?
1.4©-14
1.9e-15
2.4e-16
7.9e-17
O.Oe+OO
(w) BOD5 (Biochemical Oxygen
Demand)
g
1.06-01
2.5e-04
2.0e-03
6.8e-04
O.Oe+OO
(w) Calcium (Ca++)
g
O.Oe+OO
0.0e+00
0.06+00
0,0e+00
O.Oe+OO
(w) Chlorides (CI-)
g
5.16-02
5.4e-03
4.4e-02
1.56-02
O.Oe+OO
|w) COD (Chemical Oxygen Demand)
g
1.90-01
2.1 e-03
1,7e-02
5.86-03
O.Oe+OO
(w) Cyanides (CN-)
g
4.90-19
6.6e-20
8.0e-21
2.76-21
O.Oe+OO
(w) Dissolved Matter (unspecified)
g
1.50-01
1,7e-02
1.4e-01
4.66-02
O.Oe+OO
(w) Fluorides (F-)
2.36-05
2.8e-06
3.4e-07
1.1e-07
O.Oe+OO
(w) Hydrocarbons (unspecified)
g
9.50-04
3.5e-07
2.8e-06
9.4e-07
O.Oe+OO
(w) Metals (unspecified)
g
3.46-03
1 0e-05
8.4e-05
2.86-05
O.Oe+OO
(w) Nitrates (N03-
g
3.66-05
6.6e-07
8.16-08
2.76-08
O.Oe+OO
(w) Nitrogenous Matter (unspecified, as
N)
g
1.1e-04
0.0e+00
0.0e+00
0.0e+00
O.Oe+OO
(w) Oils (unspecified)
L.
2.36-03
1.2e-04
1.06-03
3.4e-04
O.Oe+OO
j|w) Phenols
g
4.3e-05
4.7e-06
3.9e-05
1.3e-05
O.Oe+OO
(w) Phosphates (P04 3-, HP04-,
2
2.4a-05
O.Oe+OO
O.Oe+OO
0.0e+00
O.Oe+OO
B - 22
-------
Mineral Wool - LC Stage
Article
Units
Raw
Materials
Manufacturing
Transport
Use
End-of-
life
H2P04-, H3P04, as P)
(w) Sodium (Na+)
g
5.5e-02
7.0e-03
5.6e-02
1.96-02
0.06+00
(w) Sulfates (S04--)
g
1,2e-03
5.9e-07
7.2e-08
2.4e-08
0.0e+00
(w) Suspended Matter (unspecified)
g
1,4e-01
1.1 e-03
9.3e-03
3.1 e-03
0.0e+00
Waste (50 years - prorated)
k?
0.0e+00
0.0e+00
0.0e+00
0.0e+00
O.O0+OO
Waste (End-of-Life)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
O.O0+OO
Waste (first replacement)
kg
0.0e+00
0.0e+00
0.0e+00
0.0e+00
0.00+00
Waste (installation)
kg
0.0e+00
0.0e+00
0.0e+00
2.20-02
0.00+00
Waste (Mfg.)
k§
8.1e-03
6.8e-02
5.2e-05
1.70-05
0.00+00
Waste (non-recyclable, 50-year)
kg
0.0e+00
0.0e+00
0.0e+00
0.00+00
3.30-01
Waste (second replacement)
kg
0.0e+00
0.0e+00
0.0e+00
0.00+00
0.00+00
E Feedstock Energy
MJ
7.5e-01
2.3e-03
0.0e+00
0.0e+00
0.00+00
E Fuel Energy
MJ
7.1e-01
9.50+00
1.5e-01
4.9e-02
0.00+00
E Non Renewable Energy
MJ
1,4e+00
9.50+00
1.5e-01
4.9e-02
0.0©+00
E Renewable Energy
MJ
1,3e-02
7.9e-03
1,4e-04
4.96-05
0.00+00
E Total Primary Energy
MJ
1.5e+00
9.5e+00
1.5e-01
4.96-02
O.Oe+OO
E Fuel Energy
MJ
E Non Renewable Energy
MJ
E Renewable Energy
MJ
E Total Primary Energy
MJ
B-
23
-------
Appendix C: Asphalt Coating Case Study
Goal and Scope Definition
Goal
An important goal of this study was to evaluate whether a small vendor would be capable of gathering
the data necessary for a life cycle assessment, in a timely fashion. If this proved to be impossible, the
application of LCA for EPP would present a significant barrier for small businesses seeking to sell
goods to the Federal government. Asphalt Systems, a small manufacturer of asphalt emulsions in
Utah, participated in providing site specific information on the manufacture, application and use of
asphalt emulsions and hot mix asphalt.
Intended Applications and Audiences
The LCA itself was intended to be used to support a comparative assertion of environmental
superiority of a product over a competing product in the context of the Federal requirement for
environmentally preferable purchasing. Audiences include purchasing agents as well as other federal
and state officials. An ancillary use of the study is to support efforts towards environmental
improvement.
Scope
Description of the Product
The products evaluated represented two methods of maintaining roads: applying a thin layer (1.5
inches thick) of asphalt cement and applying an asphalt emulsion containing a natural mineral
product, gilsonite. Both of these products are applied to asphalt roads before significant deterioration
has occurred (three to five years into the life of the road), and neither adds structural strength to the
road. Each extends the life of the road considerably. In the case of the asphalt emulsion, for three to
five years, and in the case of the asphalt cement thin layer, seven to nine years. There are some other
specialized methods for maintaining asphalt cement roadways, but these tend to be based on trade
secret chemical compositions, and were not included in this study.
Asphalt emulsion is applied by spraying diluted emulsion from a distributor truck that simultaneously
spreads sand onto the emulsion. Application is at ambient temperature. A thin layer of asphalt cement
is applied by first spreading a tack coat (consisting of a simple asphalt emulsion) with a distributor
truck, then applying a layer of asphalt, and finally rolling the layer of asphalt to assure a smooth
surface. Typically, the asphalt cement is manufactured near the construction site at a hot-mix asphalt
C- 1
-------
cement plant, which heats the asphalt and mixes it with aggregate, which is then trucked to the road
site and applied as above. Asphalt cement must be applied at 165°F or above. Traffic can ensue one
to two hours after application is complete.
System Function and Functional Unit
The function provided by the alternative products is the maintenance of good quality roads (five on
a scale of ten). The functional unit is twenty years of one lane mile. The inventory includes two
application of the thin layer of asphalt cement, and five applications of the asphalt emulsion.
System Boundaries
The system studied included all unit processes except those used for the production of hydrochloric
acid. This material comprised less that one percent of the total mass of the products, and it was
expected from the composition of the materials that the acid would be neutralized in use.
All inputs and outputs were accounted for as long as they comprised at least:
1. One percent of the mass
2. One percent of the energy, or
3. One percent of the expected toxicity scores
Primary data was not available for the asphalt production, but was gathered from published sources.
Information on the production of the asphalt emulsion and the tack coat was obtained from the
manufacturer, as was information on the application of the asphalt emulsion, the tack coat and the thin
layer of asphalt cement. The flow charts below identify the systems under study.
C - 2
-------
Asphalt Emulsion Coating
Sulfuric Acid
from SO,
Petroleum
Extraction
Uranium
Mining
Coal Mining
Water
l
Extraction
Sand Extraction
Raw Material
Extraction
Production
of HC1
*
Production
of Detergent
"H
Production
of Emulsifiers
and light oil
^ Production
of Asphalt
Production
of Electricity
3T
Production
of Diesel
Production
of Emulsion
STT
7,
Manufacture
(includes intermediate transport)
Application
of Emulsion
Application
and Use
Figure 1
C - 3
-------
Data Gathering
In general, data gathering was quite rapid. The entire data gathering exercise for this project took
place over two months (January-March 1999). This situation was aided by the simple nature of the
materials under study. However, there were some difficulties that were encountered. For example,
the source of the asphalt in the emulsions and tack coat (a large refining company) was not willing
to provide site-specific information to this small vendor. Consequently, industry average data,
obtained from the American Petroleum Institute (API) was used for estimating the inventories of this
material.
Secondly, it was not possible to obtain site-specific information from any vendor that was not a direct
vendor to the manufacturer. Thus the inventory results from some products that were obtained from
a distributor (e.g. HC1 and some detergents) were derived from data bases.
Finally, the contents of some materials (emulsifiers) are considered to be trade secrets. The issue of
trade secrets is a common one in LCA's, no matter what size of vendor one might be evaluating. Some
of the trade secret material are considered to be potentially ecotoxic, and that is reflected in the
analysis reported here.
Allocation
All allocation of emissions and resource use was performed based on a mass basis. This was required
for the production of asphalt, and for transportation inventory results, but not for other inventory data.
Impact Assessment
Impact assessment was performed based on the FRED LCA system indicators, as described in the
body of this work. The assignment of inventory data to impact categories is shown in the table below.
C - 4
-------
Table 1. Assignment of Inventory Results to Impact Categories
Inventory Result
Impact Category
Justification
Fossil Fuels and Uranium
Resource Depletion
Although Uranium is not truly a
fossil fuel, it is "used up" in a
precisely comparable fashion
C02, N20, Methane
Global Warming
These are important greenhouse
gases which do not participate to a
great extent in other impact
categories
CO
Human Toxicity
Photochemical Smog
Global Warming;
CO is a human and animal toxicant,
as well as a precursor to ozone
formation and a greenhouse gas. It
can participate in the first two of
these environmental mechanisms
without losing its potency for the
others.
CFC's, HCFC's, Halons
Global Warming 100%
Stratospheric Ozone
Depletion 100%
These substances participate fully
in both of these parallel
environmental mechanisms
so2,
Acidification 100%
Although S02 contributes to
visibility deterioration, and human
health effects through the formation
of Particulate Matter, these
environmental mechanisms are not
addressed by FRED.
HC1, HF
Acidification 100%
Human Health 100%
These acid gases have minor
human health effects as well as
contributing to acidification. It was
thought that double counting would
not significantly skew results.
Toxic Air and Water
Emissions
Human Toxicity 100%
Eco toxicity 100%
Since it was not possible to
evaluate the partitioning of these
substances, they were double
counted so as not to underestimate
their impacts.
NOx
Acidification 100%
Eutrophication 100%
Since FRED does not currently
evaluate the fate and transport of
NOx, this emission was double
counted.
VOC's, ROG's
Photochemical Smog
These are the essential precursors
C - 5
-------
Inventory Result
Impact Category
Justification
to photochemically produced
ozone. Although some of them are
also toxic, unspeciated data does
not permit a toxic evaluation.
nh4
Eutrophication (water
emissions); acidification
(air Emissions)
Although NH4 is not an acid gas, it
undergoes changes in the soil
leading to acidification effects.
P04
Eutrophication 100%
Phosphate does not participate in
any other environmental
mechanism described by the FRED
methodology
The table below shows the gross inventory for the two options, normalized to the functional unit. The
functional unit is twenty years of one lane mile. The inventory includes two application of the thin
layer of asphalt cement, and five applications of the asphalt emulsion. Because the information about
asphalt cement was obtained from published sources rather than from primary data, it was not
possible to estimate the amount of land that was used to manufacture the asphalt. Since this product
uses aggregate, it is likely that the mining of gravel/aggregate produced somewhat higher land use
than the manufacture of the emulsion, perhaps ten times as much. However, the land use during
manufacturing of materials is very small. Even assuming that the production of hot mix asphalt used
ten times as much land, this would still be much smaller than the land use associated with the road
itself. Thus, the land use difference between the two products is probably not significant.
Inventory
The Table below shows the Summary inventory for the two products compared. A full inventory by
life cycle stage can be found in Tables 6 and 7.
C - 6
-------
Table 2. Summary Inventory
System Description
Raw Materials
Asphalt Cement
Thin Layer (2applic)
lb/lane mile/20 yr
Asphalt Emulsion
GSB88 (5 applic)
lb/lane mile/20yr
Asphalt
122,621
47,790
Aggregate
2.181,960
0
Diesel (application)
3,063
15
Diesel to prep hotmix
884
0
Sand
0
17,600
Gilsonite
0
21,500
HC1
32
24
Water
4,779
173,317
NP-40 (Detergent)
0
285
Surfactant
156
29
Light Cvcle Oil
0
585
Land use (road, m2)
5888
5888
Land use (mfg, m3)
???
2
C-7
-------
Indicator Results
The table below shows the indicator results for the two systems studied.
Table 3: LCI A Results
LCIA Totals
Indicator
Asphalt
Asphalt
Emulsion
Cement
GWP (kg CO, equiv)
16547
44368
ODP (kg CFC-11)
0
0
Acidification (kg SO,)
145
344
Eutrophication (kg POJ
0.0065
0.0151
Photochemical Smog (kg O,)
36
77
Human Toxicity
Cancer
7.97E-02
1.78E-01
NonCancer
2.02E+00
4.51E+00
Ecotoxicity
6.61E+04
2.12E+03
Resource Depletion
Fossil (tons oil equivalent)
3.86E+04
8.55E+04
Mineral (equiv tons)
0
0
Precious(equiv tons)
0
0
Other Indicators:
Land Use (ha)
0.6
0.6
Water Use (kg)
76982
2292
Solid Waste (kg)
31729
816165
C - 8
-------
Interpretation
We can make several interesting observations about the two products based on the total indicator
values noted in the table above. Of the 14 indicators and sub indicators evaluated, the numbers for
asphalt emulsion were significantly lower than those for asphalt cement in 11 categories, equal in two
categories (Stratospheric Ozone Depletion and Land Use) and greater in one category (Water Use).
However, given the overall uncertainty of these numbers, it is important to also look where an order
of magnitude difference occurs. An order of magnitude difference is seen between the results for
Ecotoxicity (cement is lower), Water Use (cement is lower) and Solid Waste (emulsion is lower).
It is also possible to evaluate the sources of the various impacts in order to identify opportunities for
improvements. The table below shows the asphalt emulsion and asphalt cement indicators in term of
percentage of the indicators in the different life cycle stages.
Table 4. Percentage of Indicator by Life Cycle Stage, Asphalt Emulsion
Emulsion » by LC Stage
Indicator
Haw
Material?
Manufacturing
Transport
Use
Disposal
GWP
iiiiiiiiliilii
34
111 liillll
0
¦HB
ODP
liillllill
0
¦H
0
llllilllillllill
Acidification
15
17
69
0
0
Eutrophication
0
91
lililllll
0
0
PhotochemicalSmoj»
20
7
mamm
0
!¦»
MMNMHUi
Cancer
llililliill
78
iiiii iiiiii
0
NoJiCaueer
10
81
iiiiiiM
,0
0
Eco Health
90
1
10
0
11 iiiliilll
Resource Depletion
Fossil
85
6
liillllill
0
0
Mineral
0
0
0
0
0
Precious
0
HMHK
0
• 0
Other Indicators:
Laud Use
0
0
100
0
Water Use (kg)
1 ilililli
28
lllllillll
¦n
0
Solid Waste (kg)
0
0
illliliili
0
illl«ll
C - 9
-------
Table 5: Percentage of Indicator by Life Cycle Stage, Thin Layer Asphalt Cement
feme tit - bi
liiilillii
Indicator
Raw
Material
Manufacturing
Transport
Use
Disposal
liiitiiiiiiiii
76
llllflllll:!!
ilill
lllllillll:
ODP
llliiliislll
0
0
0
lllliliillll
illlllillifl
66
iilllliilflll
llill
llllilllll
Eutrephictttioit
iiiilllillllll
98
2
llil!:
iliiilll!
i'tiutochcimcfll Smog
liiliilll
20
59
0
0
Human Health
Cancer
12
85
illllllllillll
0
llllillillll
Non-Cancer
9
88
lllllililliilll
11111
mmmmm
Kco Health
lllliillllll
50
llliillillll
iiill
lillillll
FgssO
sa
16
%
llill
iiliiiiii
Mineral
0
0
iliiiiiiiii
lilli
mmmmm
Precious
lllllililll
0
Illlllillillll
o
llllillillll
Land Use
0
0
iliiilliil
100
lllllililll
Water Use (kg)
0
100
0
lllllililll
Solid Waste fktf
0
0
llllliilill
0
100
For the most part, the majority of the two products indicator results can be found in the manufacturing
and the transportation phases of the life cycle. This result supports the guidance of the FRED
methodology, which recommends more intensive data gathering efforts in the manufacturing phase
for products which are durable goods which are not energy intensive in the use phase.
Conclusions
Although there were some issues around gathering primary data for the performance of this LCA,
overall, the data gathering went quite smoothly. This was true especially for data gathered from the
primary vendor and from one step up and one step down the vendor chain (i.e. from manufacturers
of ingredients and from contractors/customers using the materials under study). For goods that have
a very long or complicated vendor chain, (e.g., electronics) this may not be the case.
C- 10
-------
Table 6: Life Cycle Inventory, Asphalt Emulsion
Asphalt
Sum
Extraction
Manufacture
Transport
Use
Disposal
Emulsion
Product
20 year-lane mile
Inputs
Resources
Coal.Bituminous
Kg
430
167
170
93
1.34E-01
0
Coal,Lignite
Kg
79
31
31
17
2.46E-02
0
Coal,Sub bituminous
Kg
235
92
92
51
7.32E-02
0
Crude Oil
Kg
25,972
23,282
311
2,372
7
0
Gilsonite
Kg
9,336
0
9,336
0
0
0
Natural Gas
Kg
725
270
381
74
2.03E-01
0
U02
Kg
2.41E-03
9.43E-04
9.46E-04
5.25E-04
7.53E-07
0
Fresh Water
Kg
76,982
0
21,845
0
55,136
0
Land Use
ha
0.6
.002
0.6
Fuels
Coke.Petroleum
Kg
0
0
0
0
0
0
Crude Oil
Kg
0
0
0
0
0
0
Distillate Oil
Kg
0
0
0
0
0
0
Distillate Oil,#l
Kg
0
0
0
0
0
0
Distillate Oil,#2
Kg
0
0
0
0
0
0
Electricity
kW
h
0
0
0
0
0
0
Fuel,Other
Kg
0
0
0
0
0
0
Gasoline, Automotive
Kg
0
0
0
0
0
0
C- 11
-------
Asphalt
Emulsion
Sum
Extraction
Manufacture
Transport
Use
Disposal
LPG
Kg
0
0
0
0
0
0
Natural Gas
Kg
0
0
0
0
0
0
Residual Oil
Kg
0
0
0
0
0
0
Steam^Low Pressure
btu
8.57E-01
3.96E-04
7.77E-01
7.92E-02
2.39E-04
0
Still Gas
Kg
0
0
0
0
0
0
Air Emissions
1,2,4-TrimethyIbenzeae
Kg
1.25E-02
5.79E-06
1.14E-02
1.16E-03
3.49E-06
0
Aldehydes,Unspeciated
Kg
2.98E+00
4.12E-02
1.85E-03
2.94E+00
1.34E-05
0
Ammonia
Kg
1.12E-01
5.16E-05
1.01E-01
1.03E-02
3.11E-05
0
Benzene
Kg
7.97E-02
9.98E-03
6.21E-02
7.60E-03
2.22E-05
0
Carcinogen,Unspeciated
Kg
6.91E-03
3.18E-06
6.27E-03
6.35E-04
1.92E-06
0
CO
Kg
73
16
11
46
8.07E-03
0
C02
Kg
15846
1509
5421
8914
2.48
0
Cyclohexane
Kg
2.52E-02
1.16E-05
2.29E-02
2.33E-03
7.01E-06
0
Ethyl Benzene
Kg
2.47E-02
2.49E-03
1.99E-02
2.34E-03
6.90E-06
0
Ethylene
Kg
3.04E-02
1.40E-05
2.76E-02
2.81E-03
8.46E-06
0
HQ
Kg
0
0
0
0
0
0
Iso-Octane
Kg
2.63E-03
9.78E-04
1.38E-03
2.67E-04
7.37E-07
0
Methane
Kg
33.38
19.86
9.05
4.46
9.20E-03
0
Methanol
Kg
1.19E-02
5.49E-06
1.08E-02
1.10E-03
3.31E-06
0
MTBE
Kg
2.80E-02
1.29E-05
2.54E-02
2.58E-03
7.79E-06
0
n-Hexane
Kg
1.71E-02
6.36E-03
8.99E-03
1.74E-03
4.79E-06
0
NOx
Kg
154
21.81
15.08
117.57
1.12E-02
0
Organic Acids
Kg
2.45E-03
9.56E-04
9.60E-04
5.33E-04
7.64E-07
0
C- 12
-------
Asphalt
Emulsion
Sum
Extraction
Manufacture
Transport
Use
Disposal
Organic
Compounds,Unspeciated
Kg
9.25E-03
3.61E-03
3.63E-03
2.01E-03
2.89E-06
0
Particulate
Kg
2.61E+00
3.42E-01
1.16E+00
1.11E+00
7.78E-04
0
PM10
Kg
15.69
1.91E-01
5.77E-01
14.92
5.13E-04
0
Propylene
Kg
9.75E-02
4.50E-05
8.84E-02
8.99E-03
2.71E-05
0
SOx
Kg
35.66
5.65
13.45
16.55
6.02E-03
0
TNMOC,Unspeciated
Kg
7.71E+00
1.56007433
3.81E-01
5.7682512
2.15E-03
0
Toluene
Kg
1.55E-01
1.38E-02
1.26E-01
1.46E-02
4.31E-05
0
V OC .Unspeciated
Kg
27.04
0.17414189
9.91
16.95
3.15E-03
0
Xylene
Kg
1.00E-01
7.83E-03
8.29E-02
9.44E-03
2.79E-05
0
Water
Emissions
Ammonia
Kg
1.94E-02
8.9449E-06
1.76E-02
1.79E-03
5.39E-06
0
BOD
Kg
5.32E-04
0
5.32E-04
0
0
0
Carcinogen,Unspecia
Kg
2.71E-05
1.3144E-07
6.713E-07
2.625E-05
7.92E-08
0
COD
Kg
6.83E-04
0
6.83E-04
0
0
0
Dissolved Solids
Kg
3.55
1.32
1.87
0.36
0.000995
0
Oil & Grease
Kg
0.56
0
0
5.59E-01
0
0
Methanol
Kg
3.45E-04
1.7316E-07
3.10E-04
3.459E-05
1.04E-07
0
MTBE
Kg
1.16E-03
5.4019E-07
1.05E-03
1.08E-04
3.25E-07
0
Oil & Grease
Kg
5.91E-02
2.94E-04
1.59E-03
5.71E-02
1.72E-04
0
Phosphate
Kg
0
0
0
0
0
0
Produced Water
Kg
9,780
8,758
116
904
2.72
0
Surfactant
Kg
3.51
3.51
C- 13
-------
Asphalt
Emulsion
Sum I Extraction I Manufacture Transport I Use I Disposal
Solid Wastes
1,2,4-Trimethylbenzene
Kg
1.36E-04
5.9119E-08
1.24E-04
1.181E-05
3.56E-08
0
Ammonia
Kg
1.50E-03
6.8698E-07
1.37E-03
1.37E-04
4.14E-07
0
Ash, Bottom
Kg
13.87
5.42
5.44
3.02
4.33E-03
0
Ash, Fly
Kg
44.21
17.26
17.32
9.61
1.38E-02
0
Carcinogen,Unspeciated
Kg
6.18E-04
2.9683E-07
5.58E-04
5.928E-05
1.79E-07
0
Cyclohexane
Kg
2.72E-04
1.1884E-07
2.48E-04
2.374E-05
7.16E-08
0
Ethyl Benzene
Kg
4.08E-04
1.7735E-07
3.72E-04
3.543E-05
1.07E-07
0
FGD Sludge
Kg
14
5.47
5.49
3.05
0.004367
0
Solid Waste.Drilling
Kg
939
826
25
86.98
0.26
0
Solid Waste,Hazardous
Kg
8.44E-01
3.90E-04
7.65E-01
7.78E-02
2.35E-04
0
Solid Waste.Refiner
Kg
22
1.03E-02
20
2.06
6.20E-03
0
Spent Fuel,Nuclear
Kg
4.21E-03
1.64E-03
1.65E-03
9.15E-04
1.31E-06
0
Toluene
Kg
1.23E-03
5.582E-07
1.12E-03
1.11E-04
3.36E-07
0
Xylene
Kg
1.64E-03
7.7116E-07
1.49E-03
1.54E-04
4.65E-07
0
Landfilled Waste
Kg
0
0
0
0
0
0
Mining Waste
Kg
0
0
0
0
0
0
Waste in waste roadway
Kg
31,729
0
0
0
0
31,729
C- 14
-------
Table 7: Life Cycle Inventory, Thin Layer Asphalt Cement
sphaltCement
0 vear-lane mile
oduct
[nputs
Resources
Fuels
'oal.Bituminous
ZoaLLignite
Zrade Oil
Silsonite
Natural Gas
U02
^and Use
-resh Water
ZokeJPetroleum
'rude Oil
Distillate Oil
Distillate Oil,#l
Distillate Oil ,#2
Hectricity
?tteL Other
jasolme,Automotive
LPG
Natural Gas
Residual Oil
I^nw Pressure
Still Gas
UadUse
Total
Disposal
Extraction
anufactur
Trans
897
164
ZoajSubbituminous
490
57,493
0
1,612
I5.04E-03
.6
2.292
313^33
355
66
195
49,601
0
575
2.01E-03
NA
0
0
0.001
411
75
223
6,451
984
2.29E-03
NA
2.292
128
24
70
1,290
50
7.23E-04
NA
0
1.87
0
o
0.043
151
1.59E-05
NA
0
0
o
0.005
J2J^TrimethvIbenzene
C- 15
NA
0
1.24E-05
29E-04
-------
lAsDhaltCement
¦
Total
Extraction
Manufacture
Transport
Use
Disposal
\mmonia
31
2.50E-01
1.10E-04
2.44E-01
5.61E-03
6.55E-04
0
3enzene
31
1.78E-01
2.13E-02
1.52E-01
4.50E-03
4.69E-04
0
Ijircinogen.Unspeciated
31
1.54E-02
6.79E-06
1.50E-02
3.46E-M
4.04E-05
0
:o
31
126
3.44E+01
6.22E+01
2.63E+01
2.86E+00
0
ro2
31
42,793
3,215
32,956
6,106
516
0
Tvclohexane
31
5.64E-02
2.48E-05
5.50E-02
1.27E-03
1.48E-04
0
3thvl Benzene
31
5.52E-02
5.31E-03
4.84E-02
1.37E-03
1.45E-04
0
sthvlene
31
6.80E-02
3.00E-05
6.63E-02
1.53E-03
1.78E-04
0
id
31
0
0
0
0
0
0
so-Octane
31
5.84E-03
2.08E-03
3.56E-03
1.81E-04
1.55E-05
0
Vfethane
75.00
42.32
29.05
3.39
2.44E-01
0
Vfethanol
33
2.66E-02
1.17E-05
2.59E-02
5.97E-04
6.97E-05
0
vfTBE
21
6.27E-02
2.76E-05
6.11E-02
1.41E-03
1.64E-04
0
l-Hexane
33
3.80E-02
1.35E-02
2.32E-Q2
1.18E-03
1.01E-04
0
*Ox
m
236
46
108
75
7.04
0
Organic Adds
m
5.11E-03
2.04E-03
2.32E-03
7.33E-04
1.61E-05
0
Dranic Kg 11.93E-02
^omoounds.UnsDeciated I I
7.70E-03
8.78E-03
2.77E-03
6.08E-05
0
^articulate
31
26.63
7.29E-01
23.92
1.96
1.64E-02
0
>M10
m
210
4.07E-01
9.91
9.37
8.98E-01
0
'ropylene
m
2.18E-01
9.61E-05
1.90E+02
4.89E-03
5.72E-04
0
JOx
n
176
12.04
151
11.46
9.54E-01
0
rNMOC.Unsvedated
m
17.23
3.32
2.70
11.16
4.53E-02
0
Toluene
m
3.45E-01
2.95E-02
3.07E-01
8.45E-03
9.09E-04
0
VOCJJnsoedated
m
58.51
3.71E-01
47.87
9.19
1.08
0
Xylene
m
2.24E-01
1.67E-02
2.01E-01
5.42E-03
5.89E-04
0
^apthalene
m
4.72E-02
0
4.72E-02
0
0
0
'-methyl napthalene
m
6.29E-02
0
6.29E-02
0
0
0
3henanthrene
m
3.88E-02
0
3.88E-02
0
0
0
Pfaioranthrme
m
2.52E-02
0
2.52E-02
0
0
0
Pynae
m
5.76E-02
0
5.76E-02
0
0
0
Formaldehyde
31
3.35
0
3.35
0
0
0
y»tw Emissions
tCg 14.33E-0
.9 IE-05
4.22E-02
9.72E-04
1.14E-I
IbOD ttg I2.13E-03I 0 I
2.13E-03
0
0
fircinogen.Unspeciated pCg |8.79E-05| 2.80478E-07 I
7.162E-05
1.43E-05
1.67E-06 I
0
16
-------
lAsphaltCement
¦
Total
Extraction
Manufacture
Transport
Use
Disposal
:od
m
3.85E-03
0
3.85E-03
0
O.OOE+OO
0
dissolved Solids
7.89
2.81
4.81
2.44E-01
2.10E-02
0
3il & Grease
35
1.19
0
0
1.19
0
0
Vlethanol
31
7.75E-04
3.70E-07
7.53E-04
1.88E-05
2.20E-06
0
VTTBE
31
2.60E-03
1.15E-06
2.54E-03
5.87E-05
6.86E-06
0
3il & Grease
31
1.92E-01
6.27E-04
1.56E-01
3.15E-02
3.62E-03
0
Phosphate
m
0
0
0
0
0
Produced Water
31
21,861
2,652
494
57.34
0
Surfactant
m
19.78
0
0
19.78
Solid Wastes
1,2,4- lCg|3.03E-0*
rrimethvlbenzen e I I
2.96E-04
6.42E-06
7.51E-07
0
Ammonia
m
3.36E-03
1.47E-06
3.27E-03
7.47E-05
8.73E-06
0
\sh. Bottom
31
28.94
11.54
13.16
4.15
9.12E-02
0
\sh, Flv
m
92.22
36.77
41.93
13.23
2.91E-01
0
I"-arcinogen,Unspeciated
m
1.38E-03
6.33E-07
1.35E-03
3.23E-05
3.77E-06
0
lyclohexane
m
6.07E-04
2.54E-07
5.92E-04
1.29E-05
1.51E-06
0
Bthvl Benzoie
m
9.09E-04
3.78E-07
8.88E-04
1.93E-05
2.25E-06
0
PGD Sludge
m
29.22
11.65
13.28
4.19
9.20E-02
0
Solid WasteJDrillmg
31
2,098
1.760
284
47.92
5.51
0
Solid
Kg| 1.89
8.31E-04
1.84
4.23E-02
4.95E-03
0
W aste,Hazardous
Solid Waste.Refiner
49.84
2.20E-02
48.57
1.12
1.31E-01
0
Spent FueLNuclear
31
8.78E-03
3.50E-03
3.99E-03
1.26E-03
2.77E-05
0
Toluene
m
«r«aiie!
1.19E-06
2.68E-03
6.07E-05
7.09E-06
0
Kvlene
1.65E-06
3.58E-03
8.38E-05
9.79E-06
0
Landfilled Waste
33
0
0
0
0
0
0
VCiunE Waste
0
0
0
0
0
0
iVaste Roadway
m
816,165
0
0
0
0
816,165
C- 17
-------
Table 8: Data Collection Tables
Resource
Consumption
Name
Amount I Units I Date used I Source of data I Estimated Error
Fuel usage
Diesel
:uel Oils (list type)
1
>
Gasoline
Natural Gas
Electricity
Doal
Minerals (list)
1
2
3
4
Chemical Usage (list)
1
2
3
4
IFreshwater use
provide source, e.g. well, river)
ffe^PisturEeTte^rS^TTlning^
c
-------
Air Emissions
Facility Name
Emission
(Amount (Units
IDates of emissions IData Source [Estimated Error
CO, (Carbon Dioxide)
CO (Carbon monoxide)
CHi (Methane)
N20 (Nitrous Oxide)
CFC/HCFC's (list)
SOx (Oxides of Sulfur)
NOx (Oxides of Nitrogen)
HCI (Hydrogen Chloride
HF (Hydrogen fluoride)
NH4 (Ammonia)
Other acid gases (list)
1
Volatlles (list)
Hazardous Air Pollutants
-------
Water
Emissions
Facility Name
lAmount lUnlts IDates of emissions IData Source Estimated Error
Emission
Suspended Solids
Conforms
Ammonia
Phosphate
OII&Grease
BOD*"*"""
Heavy Metals (list)
Hazardous Substances
2
3
4
ITotal Water released
toes water go to
direct discharge, what is water body?
C - 20
-------
Solid Wastes
Facility Name
Data Source (Estimated
Error
AmountlUnits (Dates of
emissions
Total Solid Waste (landfilied
Mining wastes (managed on
rooe
Hazardous wastes (list)
Distance to Landfills (list)
1
2
3
The authors wish to express their gratitude for the assistance provided by Jose Qarcia of the National Highway
Administration for his extensive help in providing data on asphalt roadways and their maintenance.
C - 21
------- |