sun - 2005 - integrated environmental assessment of industrial

THE UNIVERSITY OF NEW SOUTH WALES

SCHOOL OF MECHANICAL AND MANUFACTURING ENGINEERING

INTEGRATED ENVIRONMENTAL ASSESSMENT OF

INDUSTRIAL PRODUCTS

By

MINGBO SUN

A thesis submitted in fulfillment

of the requirements for the degree of

Doctor of Philosophy

July 2004

ABSTRACT

Life Cycle Assessment (LCA) has been successfully used as an environmental

assessment tool for the development of ecologically sustainable products. The

application of LCA in the early design stage has been constrained by the requirement of

large amounts of data and time for carrying out the assessment. In addition, the

complexity of LCA causes further difficulties for product developers.

In order to integrate the environmental assessment into the process of product

development, this research proposes an integrated decision model for sustainable

product development and a simplified LCA approach for the application in the early

stage of product design. The main advantage of the proposed model is that it

incorporates the environmental aspects of product development into the existing product

development framework. It enables designers to strike a balance between the product’s

environmental performance and other traditional design objectives.

The simplified LCA approach is based on the concept and application of Environmental

Impact Drivers. Material-based environmental impacts and Energy-based environmental

impacts are used to predict the total environmental impact of a product. Two sets of

impact drivers were developed accordingly. The Material-based Impact Drivers were

identified by classifying materials into 16 groups according to the nature of the

materials and their environmental performance. Energy-based Impact Drivers were

developed for various energy sources in major industrial regions.

Product LCA cases were used to verify the proposed methods. The results computed by

the application of the impact drivers were compared with the results of full LCA studies.

It is concluded that with the proposed approach, the product’s environmental

performance can be assessed in a very short time and with very basic data input

requirements and acceptable accuracy.

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ACKNOWLEDGEMENTS

There are many people who I wish to thank for their contribution and support to the

completion of this thesis.

Firstly, I would like to express my deepest gratitude to my supervisor, Professor

Kaebernick, for his technical directions and encouragement during the entire research

program. His expertise, practical orientation and thoroughness were critical to the

success of this thesis. To my co-supervisor Dr. Kayis, I am especially grateful for her

sustained support and encouragement all the way through my study at UNSW. They are

inspirational educators, not only have they been a valuable source of knowledge to me

but also important mentors. Thank you, I am so fortunate to have been your student.

With your guidance I thoroughly enjoyed my PhD adventure and gained so much.

Many thanks to my friends and fellow students. I would not have been able to go

through the journey without the generous support from you all. I appreciate your

friendship as well as your sharing insights and comments. Special thanks go to Dr. Kara

for his helpful comments and invaluable suggestions, and to Sharon and Mary for their

administrative help. My great appreciations are extended to CRC-IMST for providing

the scholarship.

Finally, I want to acknowledge my family. They have all been sources of

encouragement and support. My dearest thanks go to my parents, for the love and

dedication they poured into my education, for continually fostering my intellectual and

personal growth; to my husband Yong Tao, for his love and patience, for his

understanding and sacrificially giving. Thank you so much for your unconditional

support throughout my pursuits.

Thank you all very much.

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TABLE OF CONTENTS

1 Introduction

1.1 Environmental Issues and Challenges to the Industry 1-1

1.1.1 Motivators for Industry to ‘Go Green’ 1-2

1.1.2 Sustainable Product Development 1-3

1.1.3 Product Environmental Assessment 1-4

1.2 Research Initiation 1-4

1.3 Scope and Approach of the Research 1-6

1.4 Outline of the Thesis 1-7

2 Literature Review

2.1 Ecologically Sustainable Development and the Industry 2-1

2.1.1 Industry’s Movement towards ESD 2-2

2.1.2 Tools for Improving Environmental Performance 2-3

2.2 The Design Issues and DfE 2-4

2.2.1 Product Design 2-4

2.2.2 Design for Environment (DfE) 2-7

2.3 Environmental Life Cycle Assessment 2-7

2.3.1 Life Cycle Engineering/Life Cycle Design 2-7

2.3.2 Life Cycle Assessment Methodology 2-8

2.3.3 LCA Tools 2-11

2.3.4 LCA Application 2-14

2.3.5 LCA Limitations 2-16

2.4 Research Needs 2-17

2.4.1 Needs for an Integrated Product Development Model 2-17

2.4.2 Needs for a Simplified LCA Approach 2-18

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3 Integrated Decision Model

3.1 Product Design Objectives 3-1

3.1.1 Current Product Design Practice 3-1

3.1.2 Sustainable Product Development 3-2

3.2 An Integrated Decision Model 3-4

3.3 Case Studies 3-9

3.3.1 Case Study: Coffee Machine 3-9

3.3.2 Case Study: Computer Monitor 3-12

3.4 Conclusion 3-15

4 The Simplified Environmental Assessment Approach

4.1 Background 4-1

4.1.1 Product Classification and Group Technology 4-1

4.1.2 The Pilot Study 4-6

4.2 The Simplified Approach 4-8

4.3 Conclusion 3-11

5 The Environmental Impact Drivers

5.1 Material-Based Environmental Impacts Drivers 5-1

5.1.1 Grouping of Materials 5-2

5.1.2 Initial Grouping Attempts 5-3

5.1.3 Grouping According to Generic Material Categories 5-8

5.1.3.1 Grouping of Non-Metals 5-9

5.1.3.2 Grouping of Ferrous Metals 5-14

5.1.3.3 Grouping of Non-ferrous Metals 5-17

5.1.4 Material Groups and their Environmental Impact Drivers 5-18

5.1.5 Life Cycle Inventory Analysis for Material Groups 5-25

5.1.6 Case Studies 5-28

5.1.6.1 Coffee Machine 5-28

5.1.6.2 Disposable Shavers 5-32

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5.2 Energy-Based Environmental Impact Drivers 5-34

5.3 Conclusion 5-37

6 Verification and Case Studies

6.1 The Verification of the Simplified Approach 6-1

6.2 Correlation Between Product Environmental Impact and

Lifetime Energy Use for Active Products 6-8

6.3 Case Studies 6-10

6.3.1 Kettle 6-10

6.3.1.1 The LCA Impact Profile of the Kettle 6-11

6.3.1.2 The Simplified Assessment of the Kettle 6-13

6.3.1.3 The Eco-design Alternative of the Kettle 6-13

6.3.2 Toaster 6-16

6.3.2.1 The LCA Impact Profile of the Toaster 6-16

6.3.2.2 The Simplified Assessment of the Toaster 6-18

6.3.2.3 The Eco-design Alternative of the Toaster 6-13

6.4 Conclusion 6-22

7 Conclusion

7.1 Research Contributions 7-1

7.2 Future Research 7-3

Reference

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LIST OF TABLES

Table 2.1 Impact categories adopted by different LCA methods

Table 2.2 LCA tools

Table 3.1 Example for paired comparison of design objectives

Table 3.2 Ranking features of product development projects

Table 3.3 Decision guidelines for paired comparison

Table 3.4 Features of home appliances

Table 3.5 Relative importance of design objectives for a coffee machine

Table 3.6 Total performance of design alternatives for a coffee machine

Table 3.7 Features of computer industry

Table 3.8 Relative importance of design objectives for a computer monitor

Table 3.9 Total Performance of design alternatives for computer monitor

Table 4.1 Examples of environmentally driven product classification

Table 5.1 Environmental parameters used in grouping analyses

Table 5.2 Mechanical properties for 17 material groups

Table 5.3 Descriptions of the 16 material groups

Table 5.4 Material groups and Material-based Environmental Impact Drivers

Table 5.5 Short LCI list for material groups

Table 5.6 Major environmental impact categories for material groups

Table 5.7 Comparison of computed impacts and LCA results for model Sima

Table 5.8 Comparison of computed impacts and LCA results for model Pro

Table 5.9 The computed environmental impacts for disposable shavers

Table 5.10 Energy based Environmental Impact Drivers and the Major Substances

Table 5.11 Major environmental impact categories for Energy-based Impact Drivers

Table 6.1 Product environmental impact indicator and life cycle phases

Table 6.2 Environmental Impact Indicator for 43 product cases computed by the

simplified approach

Table 6.3 Environmental impacts with energy consumption from different regions

Table 6.4 Environmental impact of the kettle life cycle

Table 6.5 Features of a kettle

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Table 6.6 Relative importance of design objectives for a kettle

Table 6.7 Total performance of design alternatives for the kettle

Table 6.8 Environmental impact of toaster life cycle

Table 6.9 Features of the toaster

Table 6.10 Relative importance of design objectives for the toaster

Table 6.11 Total performance of design alternatives for the toaster

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LIST OF FIGURES

Figure 2.1 Representation of the design process (Rose, 2000)

Figure 2.2 Design degree of freedom and cost of changes

Figure 2.3 Generic representation of product life cycle

Figure 2.4 Design for Environment Tools and Costs

Figure 2.5 Aggregation levels of LCA results for different audience

Figure 3.1 Trade-off models for current design decision

Figure 3.2 General structure of an environmental life cycle assessment as part of a

comprehensive product assessment

Figure 3.3 Trade-off model for sustainable product development

Figure 5.1 ECO’99 weighted environmental impact and elasticity modulus for

material groups

Figure 5.2 Eco-Indicator 99 analyses for Glass & Ceramics

Figure 5.3 Eco-Indicator 99 analyses for Paper & Board

Figure 5.4 Eco-Indicator 99 analysis for Polymer

Figure 5.5 Eco-Indicator 99 analysis for Wood

Figure 5.6 Summarized dendrogram using average linkage for cluster analysis of

ferrous metals

Figure 5.7 Relationship between Nickel content in ferrous metals and Eco-Indicator

99 single score

Figure 5.8 Eco-Indicator 99 analysis for Non-ferrous Metals

Figure 5.9 Grouping solutions and accuracies

Figure 5.10 Environmental profile of the disposable shavers life cycle

Figure 5.11 Major substances for the environmental impact of disposable shavers

Figure 6.1 Deviations of computed value compared to LCA results for 43 product

cases

Figure 6.2 Correlations between product environmental impacts and lifetime energy

consumption for 3 regions.

Figure 6.3 Environmental profile of the kettle life cycle

Figure 6.4 Major substances for the environmental impact of the kettle life cycle

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Figure 6.5 Environmental profile of the toaster life cycle

Figure 6.6 Major substances for the environmental impact of the toaster life cycle

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LIST OF ABBREVIATIONS

DE The Energy-based Environmental Impact Drivers

DM The Material-based Environmental Impact Drivers

DE Development Expenses

DfE Design for Environment

DS Development Speed

EMS Environmental Management System

EP Environmental Performance

ESD Ecologically Sustainable Development

I The total Environmental Performance Indicator

IE The Energy-based Environmental Impact of the product

IM The Material-based Environmental Impact of the product

LCA Life Cycle Assessment

LCD Life Cycle Design

LCE Life Cycle Engineering

LCI Life Cycle Inventory

Pi Target performance level of the design objective i

PC Product Cost

PP Product Performance

QFD Quality Function Deployment

SETAC Society of Environmental Toxicology and Chemistry

TP The Total Performance of a design alternative

Xi Performance level of the design objective i for a design alternative

Wi Weighting factor of a design objective

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Chapter 1Introduction

CHAPTER 1

INTRODUCTION

This chapter gives a short description of the impetus of integrating environmental

assessment in the product development decision process and the motivation of

developing a simplified Life Cycle Assessment (LCA) approach to facilitate the LCA

practices of designers. It then introduces aims, scope and methodology of this research

on product environmental assessment. Finally, the thesis structure is explained at the

end of the chapter.

1.1 Environmental Issues and Challenges to the Industry

For the last two hundred years, industrial systems have achieved massive growths in

prosperity and manufactured capital, but at a severe price of the rapid declining of

natural capital (Hawken, 1999). Concerns for future generations and the alarming rate of

deterioration of Eco-systems provide the impetus for Ecologically Sustainable

Development (ESD). Since the birth of environmentalism in the 1960s, the general

concept and key principles of ESD were introduced to the mainstream after more than

two decades of development. The most widely cited definition of the ESD concept

comes from a report of Our Common Future, also known as the Brundtland report. The

report defines "sustainable development is development that meets the needs of the

present without compromising the ability of future generations to meet their own needs"

(WCED, 1987). Following this in 1992, the Earth Summit - United Nations Conference

on Environment and Development (UNCED), outlined the world’s commitment to

sustainability. Nowadays, the environmental issues are no longer only a task for

environmental specialists or a small group of idealists. Goals for achieving ecologically

sustainable development have been set up by countries and companies.

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1.1.1 Motivators for Industry to ‘Go Green’

In the last two decades, many industrial activities have been regulated from the

environmental perspectives (Stevels, 2000). Originally, the main focus of legislation has

been on production processes. The solutions to environmental damages were sought

through investments in machinery and equipment for the ‘end-of-pipe’ remediation

based on the principle of ‘polluter pays’. Little or no regulation existed for products or

the design of products.

Learning from the past, ‘end-of-pipe’ legislation had limited effect on improving

environmental performance. In recent developments, the ‘polluter pays’ principle has

been shifted to the ‘producer pays’ principle, thus transferring the responsibility to

manufacturers of products. New solutions of environmental issues seek to address the

root causes instead of the effects, by taking the causes into account when the product is

originally designed.

Consumers’ and other stakeholders’ push for continuous environmental improvements

is also an important driver. In the tough competitive marketplace, environmental

compatibility breaks ties at the shelf (Ottman, 1998). Where competing companies'

products are closely matched, the fact that a particular company has included

environmental criteria into the product’s design may sway the customer to purchase that

product over and above the product of competitors (Lucacher, 1996).

Another driving force comes from the competition. Competitors that make progress in

environmental issues put pressure on the ‘fence-sitters’ to improve environmental

performance. Companies are developing environmental strategies, roadmaps and

programs as they recognized that failing to take steps forward in environmental

initiatives may mean loss of competitiveness in the market place (Stevels, 2000).

Increasing its profitability is still the main driver for a company to take environmental

aspects into consideration. The increasing costs of materials and energy, urge

companies to implement environmental initiatives that reduce operating costs and

increase quality. As a result of stricter legislation on disposal practices, the costs of

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disposal have been rising over the last decade. A financial benefit can also be achieved

by generating less waste and by design for reuse and recycling.

These “ green drivers” have lead to challenges and opportunities for the industry, to

make changes on the conventional paradigm of product development and corporate

operation. The following section outlines the issues faced by companies to integrate

environmental considerations into to their product development process.

1.1.2 Sustainable Product Development

With the change of environmental attitude in general, industry is moving from a reactive

approach to a proactive approach. The focus concerning environmental problems has

also shifted from process related issues to product related issues. Sustainable product

development has become increasingly important. It is recognized that decisions on the

product system at stages of product development have significant influence on the kind

and amount of impact they make on the environment. Therefore, a successful way to

minimize the environmental burden is to integrate environmental aspects in the existing

product development process (Hanssen, 1999).

In light of sustainable product development, the design decision-makers have to contend

with the pressure of creating and designing product systems to meet the functional

requirements, cost and economy, quality, flexibility, time-to-market, rapidly evolving

new technologies, shorter life cycles, globalization, increasing competition and the

rapidly increasing environmental awareness (Fischer, 1993; Gardiner, 1996).

The challenge and responsibility posed to designers is therefore to strike a balance

among multiple conflicting goals while remaining competitive. Developing tools and

evaluation models for environmentally friendly product development is necessary in

order to gain market share, adhere to legislation and maintain competitive advantage.

The integration of environmental aspects into the product development process requires

both, a technical approach and a systematic product decision-making framework

reflecting the company’s environmental policy. These issues are addressed through this

research and the proposed methodology is presented in Chapters 3, 4, and 5.

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1.1.3 Product Environmental Assessment

Life Cycle Assessment (LCA) has become a standard tool for analyzing environmental

effects of products and processes. The ISO standard defines LCA as a compilation and

evaluation of the inputs and outputs and the potential environmental impacts of a

product system through its lifecycle. The aims are to understand and evaluate the

magnitude and significance of potential environmental impacts of a product system and

determine ways of reducing the associated environmental damage at all stages, from

raw materials acquisition, production, distribution, to customer use, recycling, reuse,

and disposal.

So far, LCA has been the most sophisticated method to assess environmental impacts of

products. It provides a systematic, comprehensive inventory and impact assessment of

the full environmental implications associated with the products’ entire life cycle. LCA

has been applied in many industries as a proactive approach for integrating pollution

prevention and resource conservation strategies into the development of more

ecologically and economically sustainable product systems.

There is however a continuing concern associated with LCA activities, which is the cost

and time required for conducting LCA. Furthermore, Stevels (2000) indicated that LCA

has limited applicability because, as a holistic approach, it requires delineation of all

environmental effects irrespective of their position in the life or their origin. The

resolved product and detailed product information, however, are not yet available in the

early stages of product development. Detailed reviews on the LCA methodology and its

applications are presented in Chapter 2.

1.2 Research Initiation

The trend towards sustainable development is driving many companies to consider

environmental issues in the process of product development. The early design stages

typically incorporate decisions on a product’s basic physical configuration and product

specifications (Krishnan et al., 2001). This phase is also considered to have most effect

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on the products’ environmental performance (Bhamra et al., 1999; Frei and Zuest, 1997;

Fiksel, 1996; US Congress, 1992). Decisions from this phase are then often frozen due

to the large amount of resources of time, manpower, and money needed to change the

path as product launch deadlines approach.

Therefore, the product’s environmental performance needs to be considered in the

evaluation of design alternatives together with the other traditional design objectives,

such as functional performance, cost and time to market. This requires that designers be

able to conduct timely assessment on environmental performance of many alternative

concepts early in the design process.

In the early design stages, there are particular difficulties on environmental assessment.

On the one hand, competing product concepts are numerous and have dramatic

differences, but detailed information is not available. On the other hand, multi-attribute

tradeoffs and decisions must be made quickly. Therefore the use of detailed LCA

methods is of limited value for this phase because of the amount of time and

information needed to develop the parametric LCA models.

According to literature, there has been extensive research into methods for reducing

environmental impacts at the manufacturing stages. Only recently, efforts have been

altered from reactive ‘end-of-pipe’ solutions to proactive prevention at source solutions.

Currently, the research for improving the environmental performance in the process of

product development is lagging far behind the process improvement work.

The need for an analytically based decision-making framework for the integration of

environmental criteria into the design process has motivated the development of a

decision model for sustainable product development. A simplified LCA approach is

proposed in this research, to facilitate the application of environmental assessment in

the early stages of product development.

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1.3 Scope and Approach of the Research

The main objective of the research is to develop a full methodology for designers to

integrate the product’s environmental performance into the early design stage, and to

consider it under the same framework together with the traditional design objectives. As

the core part of the methodology, the simplified LCA approach must be a quick and

easy predictive tool that is understandable and practical to the designers, without

requiring specialist environmental knowledge. The following presents the major aspects

of this research:

• Development of Environmental Impact Drivers (D), including Material-based

Environmental Impact Drivers (DM) and Energy-based Environmental Impact

Drivers (DE). This enables designers to have a quick estimation of the

environmental impacts associated with the energy consumption and material

usage of a design alternative.

• Development of a simplified LCA approach for the application at the early

stages of product development on the basis of the identified drivers DE and DM,

to generate the products’ Environmental Performance Indicator (I).

• Development of an integrated decision model for sustainable product

development, which incorporates the product’s environmental performance,

measured by the Environmental Performance Indicator (I), and balances it with

other design objectives.

• Investigation into the applicability of the integrated decision model and the

simplified LCA approach.

The research methods used in this study include a literature review, case studies and

statistical analysis. In the review of literature, information in the field of approaches to

sustainable product development, environmental policies, environmental standards and

strategies, life cycle engineering, product life cycle assessment methodologies and tools,

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material and product classifications, has been investigated through searching of books,

journals, conference proceedings, and dissertations.

In the sourcing of case studies, LCA data for 394 material cases have been derived from

the IDEMAT (2002) database and the databases in the SimaPro (2002) software

package. Forty-three product LCA cases have been collected from publications,

references, corporate documents, marketing and publicity documentation, organization

documentation and others. The gathered LCA documentations were either detailed

reports or summarized reports. For the latter case where appropriate information was

available, an initial LCA was performed. In the cases of missing data, these were

generated from reference books and databases as well as information from suppliers,

retailers, and manufacturers.

In order to make a valid comparison, all the product and material cases used in this

study were assessed by the SimaPro 5.0 LCA software package using the evaluation

method of Eco-Indicator 99 H/A (Geodkoop, 1999). It is based on normalization values

for Europe in a hierarchist (H) valuation perspective (balanced time perspective,

consensus among scientists determines inclusion of effects) and average weighting (A)

(human health 40%, ecosystem quality 40% and resources 20%). The SimaPro LCA

software was developed by Pre Consultants in the Netherlands, to calculate the Life

Cycle Inventories, classification, characterization, and evaluation indicator results. The

explanation of the eleven impact categories is included in Appendix A.

For the development of environmental impact drivers, classification tools such as simple

ordinal comparisons and hierarchical clustering were applied. Various classification

criteria were adopted in the attempt to identify material groups. The material-based

environmental impact drivers were developed by classifying materials into groups based

on the nature of the material and their environmental performance.

1.4 Outline of the Thesis

A literature review is presented in Chapter 2. Information on the research areas of

Ecologically Sustainable Development, industry’s movement towards ESD was

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investigated. Existing literature on product design issues and Design for Environment,

Life Cycle Assessment methodology, relevant LCA tools, LCA applications and

limitations were reviewed. The literature review led to the establishment of the study

background and the problem formulation for this research.

Chapter 3 is devoted to the integration of the product’s environmental performance into

the decision making process during the early stage of product design. This chapter

provides an integrated decision model for sustainable product development. The aim is

to balance the environmental performance of a product against traditional design

objectives at the early stage of product development. It also presents a weighting system

to assess the total performance of competing design alternatives. The methodology

provides a coherent evaluation of design alternatives with the consideration of their

environmental performance. Case studies were conducted to investigate the effect of

introducing environmental performance into the decision model.

Chapter 4 discusses the review of environmentally driven product classification and the

pilot study on using Group Technology to simplify product environmental assessment.

A simplified LCA approach is proposed including both energy–based environmental

impact and material-based environmental impact in the estimation of the product’s

environmental performance. The concept of Environmental Impact Drivers (D),which

represent the key factors that determine the environmental impacts associated with a

product system, is applied to the calculation of Energy-based Environmental Impact (IE)

and Material-based Environmental Impact (IM) .

Chapter 5 presents the development of two sets of Environmental Impact Drivers. They

are Material-based Environmental Impact Drivers (DM) and Energy-based

Environmental Impact Drivers (DE). Based on the analysis of the materials’ physical,

mechanical and environmental properties, materials were classified into groups

according to the type of material and their environmental performance. A Material

based Environmental Impact Driver was defined for each group. By mapping materials

into the index of DM, the material-based environmental impacts of a design alternative

can be evaluated on the basis of a few material groups. This enables designers to have a

timely assessment on the material-based environmental impacts with acceptable

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accuracy. Analysis on life cycle inventory is also provided for each material group.

Energy-based Environmental Impact Drivers were identified, representing

environmental impacts associated with the energy consumption from different sources

in different regions.

Chapter 6 presents the application of the proposed simplified LCA approach and

Environmental Impact Drivers. The calculations use very simple input data, and the

evaluation can be completed in a very short time. The computed results were compared

with results from LCA cases studies for verification. Further simplification can be

achieved by using simple regression equations for active products.

Chapter 7 summarizes the main research findings of this thesis including the crucial

lessons and observations resulting from the research. In addition, this chapter identifies

opportunities for future research.

Appendix A explains the eleven environmental impact categories used by the method of

Eco-indicator 99. Appendix B lists the material cases and their environmental impact in

damage categories. Appendix C includes the substances with major contribution to the

materials’ environmental performance. Appendix D describes the product LCA cases

included in this research. The list of publications is presented in Appendix E.

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Chapter 2 Literature Review

CHAPTER 2

LITERATURE REVIEW

Chapter 2 presents a literature review on the research background of Ecologically

Sustainable Development (ESD), and industry’s movement towards ESD in the first

section. Literature on product design issues and Design for Environment are described

in section two. Section three presents the review of the existing literature of Life Cycle

Assessment (LCA), relevant LCA tools, and the application and limitation of LCA. The

establishment of research needs and constraints are described at the end of this chapter.

2.1 Ecologically Sustainable Development and the Industry

The increase of human economic activities and the progress of industrial development

have raised the concerns about the implication of such activities on the natural capital,

which includes natural resources, living systems, and ecosystem service. These natural

capitals are deteriorating worldwide at an unprecedented rate (Hawken, 1999). The key

threats include: enhanced greenhouse effect, depletion of ozone layer, acidification of

soil and water, photochemical oxidants and ground-level ozone, urban air pollution and

noise, eutrophication of water and nitrogen saturation of soil, effects of metals, effects

of persistent organic pollutants, introduction and spread of alien organisms,

inappropriate use of land and water resources in production and supply, exploitation of

land for housing, industry and infrastructure, pressures on areas of special conservation

interest and on-cyclic material flows, wastes and environmentally hazardous residues

(Swedish EPA, 1996; Mackenzie, 1996).

Recognizing the shadow side of the industrial production, principles of Ecologically

Sustainable Development are introduced worldwide, including:

• Intergenerational equity

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• Intragenerational equity

• Precautionary principle- dealing cautiously with risk

• Global issues

2.1.1 Industry’s Movement towards ESD

A number of surveys (Pezzoli, 1997) indicate that industries have recognized their

important roles in the movement towards Ecologically Sustainable Development. A

primary concern is how to manage their environmental impacts effectively and

efficiently. Manufacturers are facing the challenge on the more effective use of natural

resources and the reduction of environmental impacts during the product life cycle,

while still meeting customer’s demands for high quality and affordable products

(Alting, 1998). A balance among these conflicting goals has to be achieved in order to

keep competitiveness.

Historically, industry responded with solutions of ‘End-of-pipe’ remediation, which are

rather reactionary, profit reducing and thus eventually they threaten its existence.

Recently, by making efforts to understand the environmental impacts caused by their

activities, industry realised that addressing environmental issues could be a source of

competitive advantage. Forward-thinking companies are shifting rapidly from a strategy

of regulatory compliance to one of proactive environmental management. By taking

advantage of regulatory requirements, companies enhance their competitiveness through

strategies offering ecological as well as financial opportunities (Porter et al., 1995).

Developing proactive and innovative responses turns out to be more cost effective than

developing processes that negate the effects after the fact (Persson, 1996; Sheng et al.,

1995).

From this perspective, environmental considerations are portrayed not as a cost of doing

business but as catalysts for innovation and new market opportunities (Azzone et al.,

1997; Walley and Whitehead, 1994). Invoking sound business sense, these interventions

provide opportunities for improved environmental protection, direct cost reductions,

savings on waste management cost, reduced health and safety risk for both public and

employee and improved operation and profit standing (Kedldgaard, 1995; Porter and

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Esty, 1998; Lanjouw, 1996; Stevels, 1999). Proactive environmental policy has been

used as a marketing tool by industrial-oriented firms (Davis, 1992; Murphy and

Gouldson, 2000).

2.1.2 Tools for Improving Environmental Performance

Research programs have been initiated to develop tools for evaluating and improving

companies’ environmental performance, so that environmental concerns can be

integrated in the product development and design process (Rombouts, 1998; Steen,

1999). These programs include: the Swedish product Ecology Project, the Nordic

project on Environmentally sound product development, the various Dutch Programs

e.g. Eco-Indicator (Goedkoop et al., 1999), Eco-design, Million and the Promise, the

Danish Programs e.g. Materials Technology, Quality Function Deployment (QFD) and

EDIP (Wenzel et al., 1997) programmes, the American Life Cycle Design Project

(Keoleian et al., 1995) and the German strategies for industrial production in the 21

century. These projects indicate how the industries place priority on addressing

environmental issues.

New concepts and systematic approaches for environmental management have been

developed and applied by industry. Examples may include Total Quality and

Environmental Management (TQEM), Industrial Ecology (Allenby, 1999), Product

Stewardship, Cleaner Production, Product-oriented Environmental Management System

(P-EMS), Concurrent Engineering, Ecologically Sustainable Manufacturing (ESM),

Green Design and Manufacture practices, ISO 14000 series standards for environmental

management etc.

At the same time, a handful of techniques are dedicated for the application of Design for

the Environment (DfE) concept, e.g. energy audits, pollution prevention and guidelines

for parts recovery and recycling, design of disassembly, design of reuse/recycling,

Material Input Per Service (MIPS), reverse distribution and life design (Biswas et al.,

1995); Environmental benchmarking is an effective engineering and environmental tool

for comparing products of similar functions or in similar market segments (Jansen et al.,

1998).

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2.2 The Design Issues and DfE

Cleaner production requires the continuous application of an integrated preventive

environmental strategy to processes and products so as to reduce risks to humans and

environment. It is achieved by applying know-how, by improving technology, and /or

by changing management attitudes. Design for Environment and Life Cycle Assessment

are major concepts and techniques for Cleaner Production. These techniques are

described in more details in the following sections.

2.2.1 Product Design

Design can be described as a set of decisions taken to solve a particular set of product

requirements. The traditional definition of a well-designed product is one that performs

its functions successfully. It is the product manufactured efficiently using appropriate

materials and techniques, is easy to use, is safe, offers good value for money and looks

attractive (Mackenzie, 1996).

As an innovation to the traditional design procedure, concurrent engineering practice

simultaneously considers product and manufacturing design. As shown in Figure 2.1,

during product design, decisions are made regarding manufacturing, distribution,

marketing, consumer usage, servicing and end-of-life. Decisions on the choices of

material, resources and processes, together with the energy, service, and disposal

influence the use of the product outside the firm and ultimately determine the

characteristics of the waste streams. Thus design decisions profoundly influence the

entire life cycle of the product. Graedel and Allenby (1995) cited design as the stage

that has the strongest influence on the product’s environmental impact.

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Strategy

Market Survey

Idea Generation

Product Design

Manufac-turing

Distri-bution

Market-ing

End-of-Life

Servic-ing

Consumer

Figure 2.1 Representation of the design process (Rose, 2000)

Figure 2.2 shows the phases of product design: product definition /product planning,

conceptual design, embodiment design and detail design. Product definition is an initial

phase in the product development process. It is at this stage where design decisions are

at the highest degree of freedom, have the most influence on the developed product

system, and the changes are the most cost effective.

The conceptual design is the most important phase in concurrent engineering after the

product definition phase. Approximately 80% of a product’s life cycle costs are

determined through design choices, such as materials and manufacturing process

selections in this phase. Conceptual design comprises concept definition, exploration,

evaluation and selection (Allen et al., 1998). Detail design is the actual physical design

of the product. As shown in Figure 2.2, design problems found later in the design

process (embodiment or detailed design stages) cause costly and time-consuming

redesign of the product, and may delay the product’s introduction to the market.

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Detail of Information

Design Degree of Freedom

Cost of Changes

Product Definition

Conceptual Design

Detail Design

Production, Use, Disposal

Figure 2.2 Design degree of freedom and cost of changes (Soriano, 2001)(modified)

As the marketplace has become increasingly competitive, product designers cannot

afford to optimise the design with respect to just the traditional functional requirements

(i.e. product performance). They must insure that the product excels in all other aspects

that lead to customer satisfaction and product profitability such as cost, quality,

reliability and environmental impact (Sarbacker, 1998). Design for X is an integrated

approach to designing products and processes for cost effective, high quality life cycle

management. 'DfX' tools have been developed to help achieve the diverse product

requirements, including:

• Design for Assembly (Boothroyd et al., 1994);

• Design for Process/Design for Producibility (Bralla, 1986);

• Design for Serviceability (Gershenson et al., 1991);

• Design for Ownership Quality (Kmenta et al., 1999);

• Design for Environment (Graedel, 1995);

• Design for Product Retirement (Ishii et al., 1994);

• Design for Recyclability (Ishii et al., 1996);

• Design for End-of-Life (Rose et al., 2000);

• Design for Product Variety (Martin, 2000); and

• Design for Supply Chain (Esterman et al., 1999)

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2.2.2 Design for Environment (DfE)

Design for Environment is based on the Design for X paradigm. It is the systematic

consideration of design performance with respect to environmental objectives over the

entire product life cycle (Boks, 2000). Keoleian et al. (1995) defines DfE as an umbrella

term for approaches and activities that incorporate environmental criteria into the design

of new products and the redesign of existing ones. In the DfE process, the environment

is given the same status as the more traditional product values such as profit,

functionality, and overall quality. With the focus of environmental protection measures

shifting from site-oriented towards a product-oriented view, companies have introduced

Design for Environment to minimise the environmental damages caused by its products.

Design pressure comes from the fact that environmental conscious products do not

always sell in the retail market because consumers still use other criteria such as

function and price. Designers cannot trade-off all other product attributes with being

green. The priority is still product function and purpose (Allenby, 1995; Gertsakis,

2000). Therefore firms that are able to design high quality and environmentally sound

products will enjoy a competitive advantage. The environmental performance can add a

premium to some products or introduce a “feel-good” factor to customers and their

businesses (BATE, 1998a-d). Addressing the variety of competing and challenging

demands, DfE has become an innovative strategy for achieving good performance,

ecologically as well as the economically.

2.3 Environmental Life Cycle Assessment

2.3.1 Life Cycle Engineering/Life Cycle Design

Life Cycle Engineering is engineering activities which include: the application of

technological and scientific principles to the design and manufacture of products, with

the goal of protecting the environmental and conserving resources, while encouraging

economic progress, keeping in mind the need for sustainability and at the same time

optimising the product life cycle and minimizing pollution and waste (Jeswiet, 2003).

Figure 2.3 provides the generic product life phases from material extraction to product

2-7


end-of-life. According to the study purpose other phases such as transportation,

distribution, maintenance, recycling, and reuse, maybe included when defining the

product system boundary to be studied. The life cycle approach is of crucial importance,

since it considers the environmental impact associated with the whole product life cycle.

A company may select those suppliers and distributors who generate less pollution. This

encourages the collaborative effort to reduce the total environmental impacts of the

product in cooperation with suppliers, distributors, users, and recycling companies.

Product

ManufacturingProduct Usage

Product Disposal

Material Production

Figure 2.3 Generic representation of product life cycle (Rose, 2000)

The use of life cycle concepts in product design is considered as a great opportunity to

bring about innovative products that fulfil the requirements of the industry, customers

and society. The developed product can be optimised for individual life cycle phases.

Life Cycle Design (LCD) however aims to optimise these stages together, instead of

separately. It is a proactive approach for integrating pollution prevention and resource

conservation strategies into the development of more ecologically and economically

sustainable product systems. The process requires tradeoffs to develop the optimal

design that balances the gains and losses in all the stages of product life cycle.

Keolerian et al. (1995) defines the aim of LCD as minimising aggregate risks and

impacts over the entire life cycle of a product, through striking a balance of

environmental performance, cost, cultural, legal, and technical requirements of a

product system. A product goes through the following stages in LCD: need recognition,

design/development, manufacturing and assembly, distribution, usage and service,

recycling, reuse, disposal and the ultimate fate of residuals (Alting, 1993). Other terms

such as Green Design, Eco Design, Environmental Conscious Design and Clean Design

are also widely used. Although the wording may have different meaning, the terms

generally have the same goal (Lagerstedt, 2003).

2-8


2.3.2 Life Cycle Assessment Methodology

The term LCA dates back to the 1960’s and 1970’s (Boustead, 1996), when the world

recognised the potential problems of resource scarcity and the climate changes caused

by pollution of the atmosphere. Product LCA methodologies and frameworks had been

developed in the 1980’s, but its practices had remained on a limited scale. In the early

1990’s industry, governmental and academic interest in LCA was revived on an

international scale, and thereafter became a famous buzzword in conferences,

workshops and seminars. LCA has gained more attention because it can highlight the

“hot spots” in a product life cycle, which have significant contribution to the total

environmental impacts. It also can keep track of impacts that are merely shifted from

one life cycle phase to another.

Life cycle assessment is one of the major tools used in implementing Design for

Environment and Cleaner Production. ISO 14000 series defines LCA as “ a holistic

environmental accounting procedure which quantifies and evaluates all wastes

discharged to the environment and energy and raw materials consumed throughout the

entire life-cycle, beginning with sourcing raw materials from the earth through

manufacturing and distribution to consumer use and disposal.”

It is a useful technique for examining and improving the environmental impact of a

product at all stages of its life cycle including the ecological rucksack carried by all its

ingredients and the impacts of its production, use and disposal. After the establishment

of study purpose and system boundary, actual analysis begins with the inventory

analysis stage wherein the characteristics of a system are described quantitatively, in

terms of raw material and energy inputs and emissions to the air, water, soil, non-

material emission and solid wastes. Then at the impact assessment stage, inputs and

outputs identified at the inventory stage are linked to environmental effects and

qualitatively evaluated. This involves classification and characterisation of the

inventory, normalisation and evaluation. Lastly, the improvement stage provides the

means to consider alternatives for redesigning the product system such that it satisfies

the same functions but with minimised environmental burden. These four components

of the LCA methodology are described in more detail in the following sections.

2-9


The first stage of LCA, goal definition and scoping, defines the purpose of the study,

the expected product of the study, the boundary conditions, and the assumptions

(SETAC, 1993).

The second stage of the LCA process is the life cycle inventory. The LCI quantifies the

resource use, energy use, and environmental releases associated with the system being

evaluated. For a product life cycle, the analysis involves all steps in the life cycle of

each component of the product being studied. This stage of LCA is critical because the

LCI results are needed to perform any type of quantitative impact assessment. If impact

assessment is not performed, then LCI results can be used directly to perform

improvement assessment based on energy and emission results, not on effects on health

or the environment.

Once the inputs and outputs of a system have been quantified by LCI, impact

assessment can be performed. The inventory analysis stage doesn't directly assess the

environmental impacts of the inputs and outputs. It provides the information for the

impact assessment. The impact assessment then converts the data from inventory

analysis into descriptions of the environmental impact. Conceptually impact assessment

consists of three stages:

• Classification is the assignment of LCI inputs and outputs to impact groups. It is

the process of assignment and initial aggregation of LCI data into relatively

homogeneous impact groups;

• Characterization is the process of developing conversion models to translate LCI

and supplemental data to impact descriptors; The process of identifying impacts

of concern and selecting actual or surrogate characteristics to describe impacts;

• Valuation is the assignment of relative values or weights to different impacts,

allowing integration across all impact categories.

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The fourth stage is improvement assessment. It is analysis of information from impact

assessment for evaluation and implementation of opportunities to make an

environmental improvement in a product or process. The goal is to identify those parts

of the system that can be changed to reduce the overall burden or impact of the product

or service system (Curran, 1994).

2.3.3 LCA Tools

LCA tools can be as simple as a qualitative assessment based on preferences or

quantitative assessment of impacts at the various phases of the products life cycle. The

applied classification and evaluation model vary among the methods. Table 2.1 shows

the environmental impact categories adopted by the methods of Eco-indicator 95, Eco-

indicator 99, EPS 2000 (Steen, 1999), and CML 2 baseline (2001). LCA practitioners

have to be aware of such differences, and the appropriate LCA tool should be selected

in accordance to the goal definition of LCA study.

2-11


Table 2.1 Impact categories adopted by different LCA methods

Methods Eco-indicator 95 Eco-indicator 99 EPS 2000 CML 2 baseline 2000

Impact

Categories

• Green house

• Ozone layer

• Acidification

• Eutrophication

• Heavy metals

• Carcinogens

• Winter smog

• Summer smog

• Pesticides

• Energy

resources

• Solid waste

• Carcinogenic

substances

• Respiratory

effects

(organics)

• Respiratory

effects

(inorganics)

• Climate

change

• Radiation

• Ozone layer

depletion

• Ecotoxicity

• Acidification/

Eutrophication

• Land use

• Depletion of

minerals

• Depletion of

fossil fuels

• Life

expectancy

• Severe

morbidity

• Morbidity

• Nuisance

• Crop growth

capacity

• Wood growth

capacity

• Fish and meat

production

solid

acidification

• Prod. Cap.

Irrigation

water

• Prod. Cap.

Drinking

water

• Depletion of

reserves

• Species

extinction

• Abiotic

depletion

• Global

warming

• Ozone layer

depletion

• Human toxicity

• Fresh water

aquatic

ecotoxicity

• Marine aquatic

ecotoxicity

• Terrestrial

ecotoxicity

• Photochemical

oxidation

• Acidification

• Eutrophication

Available LCA tools range from simple checklists to abridged and full LCA tools,

others including: matrix approaches and abridged LCA (Graedel et al., 1995), Eco-

Quantum, Volvo’s Environmental Profile tool, (Eagan et al., 1995), Screening LCA

(Bretz and Frankhauser, 1996), Interactive Screening LCA (Fleisher et al., 1997),

MECO Principle (Wenzel, 1997), Oil points (Bey and Lenau, 1999), Surrogate LCA

2-12


(Sousa et al., 1999), Eco Functional Matrix (Lagerstedt, 2003) and Integrated Economic

and Environmental Assessment through Activity Based LCA( Emblamsvag and Bras,

1999). Some other tools are summarized in Table 2.2.

Table 2.2 LCA tools (Menke et al., 1996)

Type of LCA LCA tools

Life cycle Inventory The Boustead Model, Euklid, JEM-LCA, LCAiT

Full LCA EDIP LCV tool, EIME, Gabi, PEMS,

LCAdvantage, SimaPro, TEAM, Umberto, Wisard

Specialized LCA ECOPACK2001, Ecopro 1.4, KCL ECO, Repaq.

Abridged LCA

Matrix LCA

NOH, Eco-indicator 95 Manual for designers, MET

Matrices method, AT&T product improvement

matrix and target plot, Ecoscan 2.0, Eco-it

Checklists Simple guidelines such as Ecodesign Tools by Pre

consultant

In the early stages of LCA development, much focus was given to the very long,

detailed and expensive studies. In recent years, the clear trend towards screening and

simplified studies can be observed. Conceptually, a full LCA is an extremely useful

tool. However, it may be rather costly (particularly for small firms), time consuming

and sometimes not easy to communicate with non-experts (Hockerts, 1998; Guinee et

al. 2001). According to the study by RTI, while the use of streamlined LCA methods

has been attempted and appears to be increasing as practitioners seek less expensive

methods that yield timely results, great care has to be exercised. Streamlining will

always incur the risk of obtaining a result that is different to that of a full LCA (Curran,

1996 and Mueller, 1999).

As shown in figure 2.4, LCA methodologies and tools vary widely in terms of goals,

implementation time, and amount of quantification, data requirements and costs.

2-13


Compared to simple qualitative studies, full quantitative LCAs require most detailed

data, they are more time-consuming and costly.

Time & Cost

ata plexity

Abridged LCA

Full LCA

& A

Streamlined LCA

DfE checklists Matrix LC Required D

& Com

Figure 2.4 Design for Environment Tools and Costs (Soriano, 2000) (modified)

2.3.4 LCA Application

LCA has been applied in many industries and countries, and is considered as a useful

tool for the designers to get an overall environmental insight in the products. Curran

(1996) listed over a hundred LCA case studies or related studies. Since the first LCA

case study on beverage containers in 1960s, LCA studies covered raw materials,

processes and products e.g. chemicals, copper, aluminium, iron and steel products,

cement, concrete, plastics, beverage containers for beer, milk juice and soft drink,

napkins, towels, diapers, air products, pulp and paper products, particleboard, sealants,

adhesives, carpets, textiles, surgical drapes and gowns, paint, wood, glass, and many

other. These studies were performed for government agencies, industry organizations

and societies and large industrial firms.

Results of a survey indicated that LCA studies had been carried out in four countries,

namely: 288 studies in Germany, 149 in Switzerland, 145 in Sweden and 27 in Italy

(Frankl and Rubik, 2000). Recent conferences held in Japan, Canada and USA have

also shown a multitude of LCA applications, such as automotive body systems, painting

and tires (Dewulf et al., 1999), Telecommunication products (Scheller and Hoffman,

1998).

2-14


Although many variations exist in LCA applications, the methodological framework for

LCA following SETAC guidelines has been internationally recognized and roughly

agreed upon. ISO 14042 describes the obligatory elements, e.g. classification and

characterization in LCA practices, in distinction to the optional elements, e.g.

normalization, ranking, grouping and weighting.

A recent survey (Frankl and Rubik, 2000) on how LCA is used reveals that the most

common reasons for the application of LCA are for internal purposes:

• Product improvement

• Support for strategic choices

• Benchmarking

• External communication

The use of LCA as a tool for product-oriented environmental management is now

widely accepted, and it has been applied to product improvement, the design of new

products, and ecolabelling programs. Addressing different audiences for different

purposes, information from LCA applications may be presented at different aggregation

levels in various formats (shown in Figure 2.5).

Designers

LCA experts

EMS specialists

Product managers

All details

Eco-indicators Aggregated scores & some details

Figure 2.5 Aggregation levels of LCA results for different audience (SimaPro, 2002)(modified)

2-15


Software packages, such as SimaPro and Gabi, are now available in the market to

reduce the difficulty and cost of conducting LCA studies. Instant LCAs can be

requested online using the Economic Input-Output LCA tool by Carnegie Mellon

University’s Green Design Initiatives (McMichael, 1999). There are also a number of

websites for organizations offering consultancies, training and LCA softwares.

However, to interpret the online results properly, users have to be cautious about the

setting of system boundary, the criteria of classification and normalization etc.

2.3.5 LCA Limitations

Recently, constraints on LCA application were observed as LCA had moved away from

design and designers and had become the preserve of central environmental departments

(Evans et al., 1999). Other concerns include the availability of accurate/complete

information, the complexity of LCA studies, as well as the required cost and time.

To yield reliable results, significant financial resources are required to conduct a LCA

study. Large collaborative industry LCA studies would cost between 0.5 and 1.0 million

ECU and could take a number of years to complete. Smaller studies for individual

clients could cost from 10,000 to 200,000 ECU and may take 4-6 months to complete

(Socolow et al., 1997). Hence then, the application of LCA is confined to large

companies and low LCA activity is found within the SME’s.

There are difficulties with the clarification of assumptions and the specification of

impacts. Claims based on LCA studies, especially comparative claims are especially

tricky. They may be misleading or ill founded. People unfamiliar with LCA may

wrongly assume they are being informed about the total environmental impact of the

product or wrongly assume that one product is better than another.

Taking these problems into account, Green and Ryan (2001) conclude that for most

manufactured products, a full LCA is too costly, too time consuming and too complex

in its results, to be of practical value to designers and manufacturers. They also pointed

out that simplified LCA procedures could be used to very good effect.

2-16


Furthermore LCA application has been even more difficult for new or evolving

products. Carrying out an LCA requires fully developed products, i.e. existing products

or products that are at least precisely defined with data which is available or attainable

through research or experiment (Walker, 1995; Akermark, 1999). At the beginning of

the design process knowledge about the product is limited, the data for a particular

application may not be available, simply because suppliers or the government do not

collect environmental data or suppliers are too small to commit enough resources to

generate the appropriate data.

On the other hand, resources or available data may be used on irrelevant issues. For

example, 90% of the environmental impact of a washing machine comes from energy,

water and detergent consumption during product use. If the best practices were used in

production, distribution and disposal phases, this would represent only 10% of the

impact. Thus, best practice in the usage phase would have more relevance (Hinnells,

1993).

2.4 Research Needs

2.4.1 Needs for an Integrated Product Development Model

To approach environmentally sound product design goals, environmental requirements

must be integrated into the design process together with economic restrictions and

technical feasibilities, translated and transformed in such a way that the environmental

considerations can be accounted for and evaluated together with the rest of the design

parameters.

Raar (1994) maintained the existence of classic tradeoffs between profits and the speed

of product development cycles, and environmental objectives. This, to some extent,

dictates the range and level of detail in proactive or innovative analyses. Partial

approaches pose the question of tackling the right issues to optimise environmental

efforts. Therefore, an integrated analytical model is important to trade off environmental

performance and other design objectives, and make comparison among design

alternatives. As the value of environmental impacts associated with a product system is

2-17


hard to be assessed accurately and is rather subjective, approximate measurements may

be developed to facilitate the decision-making process.

2.4.2 Needs for a Simplified LCA Approach

Weidema (2000) pointed out that efficiency and effectiveness could be derived from

correct identification of the object of the study, correct modelling of the system under

study and prioritising first before going into full LCA. At the same time, it must be

understood that designers are not being transformed into environmental scientists

(Gertsakis and Mussett, 2000), instead designers need more easy to use methods

adapted to their work place and expertise (Lagerstedt and Luttropp, 2001). In the highly

dimensional, fast-paced trade-off analyses at the early design stages, qualitative

information is difficult to use. A simplified quantitative LCA approach, which is easy to

use and understood by designers, requires less data input and generates timely results, is

needed to approach environmentally sound product development.

2-18

Chapter 3 Integrated Decision model

CHAPTER 3

INTEGRATED DECISION MODEL

This chapter provides an integrated decision model for sustainable product development

with the aim to balance the environmental performance of a product against traditional

design objectives. It also presents a weighting system to assess the total performance of

competing design alternatives. The methodology enables a coherent evaluation of

design alternatives with considerations on their environmental performance.

3.1 Product Design Objectives

The need for introducing environmental requirements into the design and development

of new products has already been discussed for more than a decade (Keith, 1997).

Today it is generally agreed that a successful way to minimize the environmental burden

is to integrate environmental aspects in the existing product development process

(Hanssen, 1999). Product development is now considered as an extremely important

area in terms of environmental improvements. The question however, remains of how

important is it to apply environmental criteria to a product design, and how can we

compare environmental requirements with the traditional design objectives such as cost,

function, and quality (Bhamra, 1999; Borland, 1998).

3.1.1 Current Product Design Practice

Current practices of product development in manufacturing companies are still

predominantly based on traditional cost/profit models (Asiedu and Gu, 1998), aiming at

achieving high quality of a product at low cost and high profit. The paradigm of

product development towards low cost and high profits is unlikely to change

significantly in the near future, if ever. Companies will have to continue to make

profits for their existence. Environmental requirements are mainly considered as an

3-1


unavoidable "must", which generates additional design constraints and increases the

costs (Bhamra, 1999; Borland, 1998; Fiksel, 1996). In an approach like this,

environmental assessments are carried out fairly late in the product development

process. They are not integrated with existing development activities, and they are

likely to increase the development costs.

Traditionally, three key objectives have been used for decision-making in a design

process, namely Product Performance (PP), Product Cost (PC), and Development

Expenses (DE) (Figure 3.1). In other words, decisions were based on the question:

"How much money can we spend in order to develop a product with low cost and high

performance?" During the last two decades, alongside with the introduction of

Concurrent Engineering, a fourth objective was added, caused by the need for

shortening the time-to-market. This is the objective of Development Speed (DS).

Traditional Time-to-Market

DE PC

PP PP

PC DE

DS

Figure 3.1 Trade-off models for current design decision

3.1.2 Sustainable Product Development

From the perspective of sustainable product development, one problem being identified

is that environmental parameters are not always included in the product design phase.

The environmental impact of a product has traditionally been assessed after the design

of the product and its related manufacturing activities were completed. In order to have

the highest effectiveness, an overall goal should be established in product development

and the environmental issues must not be treated in isolation. Sustainable product

development therefore requires the balance of the product environmental performance

3-2


with other design objectives such as product cost, product performance, development

speed and development cost. A key point is to have an integrated decision tool to

compare the environmental considerations with other requirements.

As suggested by Osnowski and Rubik (1987), LCA might be seen as part of a more

comprehensive assessment of products. Figure 3.2 shows the general structure of LCA

as part of comprehensive product assessment, including environmental assessment,

consumer safety, cost and other aspects. The first component of such a broad approach,

the general goal definition, specifies the role of the different assessment lines and is

distinguished from the goal definition component as part of the environmental LCA.

The same holds true for the general valuation.

In the general valuation, the results of different assessment lines are weighted against

each other. The existence of classic tradeoffs between profits and environmental

objectives requires the designers to balance between environmental performance and the

needs to reduce cost and time to market, improve product quality, while meeting

customer requirements. In order to have a coherent evaluation on design alternatives,

these difficult environmental trade-off decisions must be placed within the same

analytic context.

3-3


General Goal Definition

Environmental life cycle assessment

Goal definition

Inventory

Classification

Valuation Improvement

analysis

General Valuation

Life cycle assessment of other aspects: • Customer safety • Cost • Employment • Convenience of

use • Etc.

Improvement Design Ecolabelling Etc.

Application

Figure 3.2 General structure of an environmental life cycle assessment as part of a

comprehensive product assessment (Heijungs et al., 1992)

3.2 An Integrated Decision Model

A workable integrated decision model is therefore important to serve the purpose of

balancing environmental performance and other design objectives and making

comparisons between design alternatives. Based on such a model, opportunities for

simultaneous improvement of several objectives can be exploited and unavoidable

3-4


trade-offs are addressed directly. In the proposed trade-off model for sustainable

product design, a fifth objective, the Environmental Performance (EP) is introduced to

the concurrent product development model, representing the total environmental

impacts of a product system.

Sustainable Development

PP DS

PC

EP

DE

Figure 3.3 Trade-off model for sustainable product development

The advantage of this approach is that the environmental requirements are fully

integrated in the process, enjoying the same importance rating as all the traditional

objectives. The techniques for evaluating and balancing multiple objectives are well

established. The new objective, the Environmental Performance, can be evaluated by

applying various Life Cycle Assessment tools, which lead to an Environmental

Performance Indicator (I) representing the aggregate environmental impacts over the

product’s life cycle. A product’s Environmental Performance Indicator can also be

generated by a simplified Life Cycle Assessment approach presented in chapters 4 and 5,

or other LCA methods. The purpose is to minimize the aggregate environmental

impacts over the entire life cycle of a product through striking a balance of

environmental performance and other requirements of a product system.

As shown in figure 3.3, the five key objectives of sustainable product development are

all related to each other. The relationships are usually counteractive. This means for a

comparison of one pair of objectives, if we improve the performance of one objective,

the other objective will suffer. This is a trade-off in product development. As indicated

in the figure, the five objectives lead to ten trade-offs for sustainable product

development. 3-5


The ten trade-offs in the decision model can be used for evaluating design alternatives.

The Total Performance (TP) of a design alternative is evaluated as a function of

multiple attributors.

∑=

−=

n

i i

iii P

XPWTP

1 (3-1)

Where:

Xi = performance level of the design objective i for a design alternative;

Pi = target performance level of the design objective i;

Wi = weighting factor of a design objective;

n = number of design objectives;

Pi can be derived from previous project data, through benchmarking with competitors,

or as a result from structured product development procedures, such as Quality Function

Deployment, in accordance with the manufacturer’s product strategy.

The weighting factor, Wi, reflects the relative importance of each design objective

perceived by the company. It is dictated by the market and ultimately by the customer.

In order to establish the weighting factor, the method of paired comparison is used for

the five design objectives. Table 3.1 shows the example for the paired comparison.

Table 3.1 Example for paired comparison of design objectives

PP PC DE DS EP Total Weight

PP PP PP DE PP PP/EP

PC PP PC PC DS PC

DE DE PC DE DE DE/EP

DS PP DS DE DS EP

EP PP/EP PC DE/EP EP EP

3-6


In the assessment two objectives are compared at a time by answering the question,

which one is more important? For instance, for the comparison of PP and PC there are

three possible answers: PP, PC or PP/PC where both objectives are of equal importance.

The weight is then calculated as percentage of the total (see example in section 3.3).

At a glance, the decisions on importance seem to be fairly subjective, since they depend

on a company’s design strategy. However, such strategies are based on well-established

ground rules, which in their turn depend on the characteristics of the product and its

market. Fortunately the differentiation of importance levels is usually fairly obvious so

that a simple description of product characteristics is sufficient. These characteristics

can be described by a set of typical product features. For the purpose of this study, five

important product development features were identified as shown in Table 3.2. The

product characteristics can then be described by ranking the features at low, medium or

high.

Table3.2 Ranking features of product development projects

Features of product development projects Low/Short Medium High/Long

Technology level of the product

Speed of technical development

Product life cycle

Price competitiveness

Environmental awareness of the market

In order to apply the product characteristics in the decision process of the paired

comparison, a set of decision guidelines has been established as shown in Table 3.3.

The guidelines are a reflection of common knowledge and current industry practice

(Barry, 1997; Erik et al., 1997). They are of generic nature and can be modified to

reflect specific product development strategies of a company.

3-7


Table 3.3 Decision guidelines for paired comparison

Trade-offs Preference Comments

PP For most cases, PP is of more importance.

PP-PC PP / PC

For products with long product lifecycle, and low

technology level.

PP-DE PP For most cases, PP is of more importance.

PP

• Product life times are long;

• Time to peak sales is large;

• Average product margins are slowly

declining over time;

• Sales rate is large; PP-DS

PP/DS

• Product life times are short;

• Time to peak sales is small, or

• Average product margins are sharply

declining over time.

PP For most cases, PP is of more importance.

PP-EP PP/EP

For products with a target market of high

environmental consciousness. (e.g. home

appliances)

PC-DE PC For most cases, PC is of more importance.

PC For most cases, PC is of more importance.

PC-DS DS

Average product margins are sharply declining over

time.

PC For most cases, PC is of more importance.

PC-EP PC/EP



appliances)

3-8


Table 3.3 Decision guidelines for paired comparison (Con.)

Trade-offs Preference Comments

DE-DS DS For most cases, DS is of more importance.

DE/EP For products with low environmental concerns. DE-EP

EP For most cases, EP is of more importance.

DS For most cases, DS is of more importance.

DS-EP DS/EP



appliances)

3.3 Case Studies

To verify the integrated decision model, two case studies were conducted. The input

data for the case studies were collected from various sources such as publications and

non-confidential company information.

3.3.1 Case Study: Coffee Machine

In the first case study, design alternatives A and B for a coffee machine with 10-cup

capacity are investigated. Alternative A has a glass jug, using heating elements to keep

the coffee warm. Alternative B has a thermos jug with no heating elements to keep the

coffee warm. The product development and cost data for alternatives A and B were

derived from the development project of Braun’s KF 40 coffee machine series (Robert

et al., 1996). The desired performance levels of Product Cost (PC), Product

Performance (PP), Development Expenses (DE) and Development Speed (DS) were

derived from public information on new product development of electrical products.

3-9


Table 3.4 Features of home appliances

Features of product development project Low/short Medium High/long

Technology level of the product X

Speed of technical development X

Product life cycle X

Price Competitiveness X

Environmental awareness of the market X

Table 3.4 shows the development features of home appliances. A typical feature is the

long product life cycle in the order of 10 to 20 years, resulting in a medium speed of

technical development. In addition, there is a high environmental awareness in the

market due to the active nature of the product and the fact that most of the

environmental impact occurs mainly during the usage stage. By using this information,

the relative importance of the design objectives was calculated as given in Table 3.5.

Table 3.5 Relative importance of design objectives for a coffee machine


PP PP PP PP DS PP/EP 3.5 23.33%

PC PP PC PC DS EP 2 13.33%

DE PP PC DE DS EP 1 6.67%

DS DS DS DS DS DS/EP 4.5 30.00%

EP PP/EP EP EP DS/EP EP 4 26.67%

The results indicate that Product Performance (PP), Development Speed (DS), and

Environmental Performance (EP) have the highest weight, whereas Product Cost (PC)

and Development Expenses (DE) have a lower ranking. Using these weighting factors,

the Total Performance for design alternatives A and B was calculated and is given in

Table 3.6.

3-10


Table 3.6 Total performance of design alternatives for a coffee machine

Weighting Factor (∑Wi=100)

Target Performance

Levels

Performance Levels of Design

Alternatives Design Objectives

(Wi) With EP Without EP*

(Pi) A (Xi) B (Xi)

Product Cost Wc 13.33 20 Pc (DM) 31 30 35

Product Performance Wp 23.33 30 Pp (points) 100 100 110

Environmental Performance Wen 26.67 N/A Pen (mPts) 427 520 370

Development Expense Wex 6.67 10 Pex (106

DM) 1 1 1

Development Speed (months) Ws 30 40 Ps (months) 18 22 22

Total Performance ∑=

−=

n

i i

iii P

XPWTP

1

-12.03

-8.24*

-2.48

-8.47*

* Denotes the calculations without Environmental Performance included.

In the calculation, the performance levels of Product Cost, Environmental Performance,

Development Expenses and Development Speed are attributes, for which a smaller

value is preferred. Product Performance is the only attribute, for which a larger value is

preferred. The Environmental Performance Indicators (I) of the design alternatives A

and B were calculated by using a simplified LCA approach (Soriano and Kaebernick,

1999) with the Environmental Impact Driver (DE) identified as the lifetime energy

consumption. The equation of I = 1.2DE + 69.9 (Soriano and Kaebernick, 1999) was

adopted to estimate the Environmental Performance for alternatives A and B, with the

result shown in Table 3.6.

The results for the Total Performance show negative figures, which means that both

design alternatives do not reach the target performance level. The smaller negative

3-11


value is closer to the desired performance, therefore alternative B is the better design. In

order to investigate the effect of EP on the model, the total performance for the

alternatives A and B was also calculated without including EP, and the results are

shown in Table 3.6. In this case, the alternative A performs slightly better than

alternative B, or we can say they are almost equal. This clearly indicates that EP has a

significant effect on the product decision process and it should be included in the

trade-off model.

3.3.2 Case Study: Computer Monitor

As a second case study, a high-tech product, a computer monitor was selected to

demonstrate the function of the model (van Mier et al., 1996). The selected monitor is a

17” “multi-scan” monitor with a built-in stand-by mode to comply with EPA’s power

consumption regulation. It is a high-end monitor, which is mainly produced for the

professional market. Alternative A is a current model with power consumption of 100W

in operation mode and 15W in stand-by mode. Alternative B has a complete redesign of

the circuitry on the Printed Wire Boards (PWBs) with operation and stand-by power of

80W and 1.0W respectively. The features of a high-tech market are described in Table

3.7, characterized by high technology, high development speed and price competition,

but very short product life.

Table 3.7 Features of computer industry





Price competitiveness X


3-12


The importance weightings for the design objectives (Table 3.8) highlight a scenario in

which Product Performance and Development Speed are the key objectives whereas

Development Expenses and Environmental Performance are ranked fairly low.

Table 3.8 Relative importance of design objectives for a computer monitor


PP PP PP PP PP/DS PP 4.5 30.00%

PC PP PC PC DS PC 3 20.00%

DE PP PC DE DS DE/EP 1.5 10.00%

DS PP/DS DS DS DS DS 4.5 30.00%

EP PP PC DE/EP DS EP 1.5 10.00%

3-13


Table 3.9 Total Performance of design alternatives for computer monitor

Weighting Factor (∑Wi=100)

Target Performance

Levels

Performance Levels of Design

Alternatives Design Objectives

(Wi) With EP

Without EP* (Pi) A (Xi) B (Xi)

Product Cost Wc 20 20 Pc (DM) 500 500 507

Product Performance Wp 30 35 Pp (points) 100 100 110

Environmental Performance Wen 10 N/A Pen (mPts) 2914 2914 2184

Development Expense ($) Wex 10 10 Pex (106

DM) 5 5 7

Development Speed (month) Ws 30 35 Ps (months) 18 20 22


−=

n

i i

iii P

XPWTP

1

-3.33

-3.89*

-5.44

-8.56*

* Denotes the calculations without Environmental Performance included.

Table 3.9 presents the results for the Total Performance of alternatives A and B. As in

the previous case study, EP was calculated by using the simplified LCA approach with

the same Environmental Impact Driver, since both products belong to the same category

of energy based products (Kaebernick and Soriano, 2000). In this case alternative A

shows a better Total Performance than alternative B, despite the fact that alternative B

has the better and highly ranked Product Performance. This demonstrates the effect of a

typical trade-off with the other objectives.

The effect of EP was again investigated by setting the weighting of EP to zero, which

represents the traditional decision making environment. According to the calculations,

alternative A is still the desirable option due to the low weighting of EP for a computer

product.

3-14


3.4 Conclusion

This chapter presented a framework for integrating the Environmental Performance of a

product design with the traditional design objectives, leading to a trade-off decision

model. Existing assessment methodologies were applied, suitable for application in the

early design stage with limited data available. The importance of integrating the

Environmental Performance was demonstrated in the case studies.

The integrated decision model enables the decision maker to consider the product’s

environmental performance at the early design stage and to balance it against other

design requirements. Being an integrated approach, it will not purely add-on some

constraints, but it will identify new environmental features of a product that have the

potential to improve the overall quality of the product in the eyes of the customer, thus

creating additional market potential and financial gains.

3-15

Chapter 4 The Simplified Environmental Assessment Approach

CHAPTER 4

THE SIMPLIFIED ENVIRONMENTAL ASSESSMENT

APPROACH

Chapter 4 presents the development of a simplified environmental assessment approach.

The first section includes a review of product classification and an introduction of a

pilot study of applying group technology on the simplification of product environmental

assessment. The results of the existing studies provide the rationale of using an

Energy-based Environmental Impact (IE) and a Material-based Environmental Impact

(IM) to estimate a product’s environmental performance. The concept of an

environmental impact driver is adopted to calculate the IE and IM.

4.1 Background

In the decision model for sustainable product development proposed in Chapter 3,

various Life Cycle Assessment tools can be applied to evaluate the product’s

Environmental Performance. A full LCA however has limited value at this stage, as it is

very time consuming and requires very specific data, which is normally not available in

the early stages of product development. Simplified LCA tools are very useful in this

stage for estimating the environmental impacts of product alternatives and for predicting

environmental costs or burdens for manufacturers. In this study, a simplified LCA

approach was developed by looking at the dominant factors of the products’

environmental impacts.

4.1.1 Product Classification and Group Technology

Similar to Group Technology (Chang et al., 1998), classification is a separation process

wherein items are clustered into groups based on the presence or absence of product

characteristics or attributes. The grouping activity is based on the idea that products

4-1


classification could provide a useful and meaningful map to supply relevant information

for predicting and decision-making (Arabie et al, 1996; Aldenderfer and Blashfield,

1985).

Product classification can be conducted by identifying similarities among various

properties of different products. Classification criteria may vary according to different

perspectives, decision variables and the purpose of classification. Krishnan and Ulrich

(2001) refer to four perspectives reflecting different product development decision

frameworks:

• Marketing: The product is a bundle of attributes, product attribute levels and

price are examples of decision variables;

• Organizations: The product is an artifact resulting from an organizational

process. Product development team structure and incentives are examples of

decision variables;

• Engineering design: The product is a complex assembly of interacting

components. Product size, shape, function, dimension are examples of decision

variables;

• Operations management: The product is a sequence of development and/or

production process steps; development process sequence and schedule and point

of differentiation in production process are examples of decision variables.

For example, from an organizational perspective, distinct incentives on product

development can drive the classification of products into technology-push products,

platform products, process-intensive products and customized products (Ulrich and

Eppinger, 2000). Specific engineering variables such as type of materials, size or

lifetime can also serve as classification criteria. When adopting an operations

management perspective, manufacturing processes can be used as the classification

criteria.

4-2


In view of sustainable product development, environmental performance can be

considered as a new perspective. Examples of classification criteria include product

characteristics (e.g., mass, life time), level of environmental impacts (e.g., impact

indicators) and types of environmental improvement strategies (e.g., material use,

end-of-life strategies) (Sousa et al., 2003). Table 4.1 summarizes the relevant studies on

product classifications developed under the environmentally driven perspectives.

+ Table 4.1 Examples of environmentally driven product classification

Classification

Purpose

Classification

Criteria Product categories

Identify

environmental

improvement

strategies for

distinct types of

products (Hanssen,

1996)

Product’s functional

and life-cycle

properties related

with significant

environmental

impacts (e.g. raw

material production

and maintenance

generate the

significant impacts

for stationary

products without

energy

consumption in use

Products being chemically transformed

in use (e.g. solvents);

Stationary inert products without energy

consumption in use (e.g. electric

cables);

Stationary products with internal energy

consumption in use (e.g. lighting

armature);

Transportable products without internal

energy consumption in use (e.g. food

package);

Transportable products with internal

energy consumption in use (e.g. boat

with outboard motor).

Enhance

knowledge-based

system performance

for ranking

Eco-design

strategies

(Rombouts, 1998)

Aspects of product

use which are

answered by yes or

no

Product does/does not transform energy

in use;

Product does/does not transform

materials in use;

Products is/is not transported in use;

Determine

products’ feasible

Product’s technical

characteristics that

Reuse;

Service;

4-3


end-of –life

strategies early in

the design cycle

(Rose et al., 2000)

affect product’s

end-of-life

treatment (e.g.

number of parts,

wear-out life)

Remanufacturing;

Recycle (separate first);

Recycle (shred first);

Identify

environmentally-

driven product

categories (Sousa,

2003)

Product descriptors

(e.g. lifetime,

recycled content,

energy source,

mass, operational

mode)

B1: Durable, high-mass household

appliances, with efficient energy

consumption during use (active);

B2: Durable, low-mass consumer

products, with a significant amount of

plastic materials, and with energy

consumption during use (active);

B3: Durable electronic consumer


ceramic/glass materials, and with energy

consumption during the use phase

(active);

B4: Non-durable, low-mass consumer

products, with no energy consumption

during use (passive);

B5: Low-mass consumer products, with

a significant amount of fiber materials,

and with external energy consumption

for maintenance during the use phase

(active);

B6: Durable, recyclable products, with

external energy consumption for

mobility during the use phase (active);

B7: Durable, low-mass, recyclable


metals, and with external energy

consumption for maintenance during the

use phase (active);

4-4


Hanssen (1996) analyzed 18 different LCA studies of product systems to investigate

environmental impacts related to specific product groups. Criteria used for classification

focused on functional properties during the use phase and included chemical

transformation, energy conversion, and transportable vs. stationary products (see Table

4.1). Despite of the uncertainty and variation in the LCA studies, relevant trends were

identified:

• The most important life-cycle stages were generally raw material production and

product use. For both life cycle phases, conversion of fossil energy to electricity,

process energy, heat or transport was a dominating factor. The production phase,

distribution phase and production of packaging were in most product types of

very low relevance.

• Raw material production was dominant for products being chemically

transformed, stationary products without energy conversion, and transportable

products without energy conversion. Use phase was important for products

being chemically transformed, stationary products with energy conversion, and

transportable products with energy conversion. Waste generation was relevant

for products being chemically transformed, and stationary products with energy

conversion.

A hierarchical analysis of 61 products was conducted by Sousa et al. (2003) using

high-level product characteristics as the clustering variables, the identified 7 product

categories in Cut B (see Table 4.1) and 4 product categories in Cut A:

• A1 (B1, B2, B3): Durable products, with a significant amount of plastics or

ceramics/glass, and with power consumption (e.g. Refrigerators, vacuum

cleaners, mini-vacuum cleaner, coffee makers, washing machine, radios, juice

squeezers, heater, LCDs, TVs);

• A2 (B4): Generally non-durable, low-mass products, and with no power

consumption (e.g. Paper bag, coffee filter, dust bag, PE bag, PP crate,

4-5


showerhead, disposable diaper, coatings, antifreezes, disposable towel, chairs,

plastic fender);

• A3 (B5): Low-mass products, with a significant amount of fiber materials in

their composition, and with no (internal) power consumption (e.g. Home and

commercial washed cloth diapers, reusable towel);

• A4 (B6, B7): Durable, recyclable products, made primarily of metals, and with

(external) power consumption (e.g. BIWs, car fenders, sauce pans).

4.1.2 The Pilot Study

In order to find groups of products with common features that produce insight into key

points for the design or improvement of environmentally sound products, Kaebernick

and Soriano (2000) carried out a pilot study on 33 product cases in 17 product types.

The analysis was based on the principles of Group Technology (Chang et. al, 1998),

using both product characteristics and environmental performance indicators as the

clustering variables. Results from the clustering attempts are summarized below:

Attempt 1: Clustering by comparing impact contributions at each life cycle phase

Grouping was done by analysing the temporal distribution of environmental burdens

during the product life cycle, which was divided into the four discrete phases: material

production, product manufacture, product usage and disposal. Using the LCA results,

the impact indicator contributions across the product’s life cycle phases were expressed

in relative weights as percentages of total impact. Three major clusters were recognized:

• Group 1, where most of the environmental impact is caused by the production

of the material (90% of the total impact on the average for products in this

group);

• Group 2, where the major impact is attributed to the use of the product (an

average of 89% of the total impact for products in this group;

4-6


• Group 3, where both material and usage phases contribute significantly to the

total environmental impact of the product.

Attempt 2: Clustering by comparing contributions by material type component

Products were classified by the material types that bring about the most significant

impact during the material production phase. This attempt resulted in two major

clusters:

• The first group are products that have steel, plastic or wood as the dominant

material type. In this group, the main materials not only contribute to the major

impact but also represent the bulk of the product mass. A single material usually

contributes the top 70% of the impact.

• The second group is characterized by having copper, and a few other vital

materials such as CFC, aluminium or zinc contributing 30% to 60% of material

impact despite relatively low contribution to product mass.

Attempt 3: Clustering by comparing impact contribution by indicator classes

Products were classified according to the contribution of the impact indicator classes

leading to four groups:

• Group 1: where acidification is the top environmental issue followed by summer

smog;

• Group 2: where acidification is still the main issue but winter smog becomes

secondary;

• Group 3: where acidification and heavy metals are equally significant issues;

4-7


• Group 4 where a few issues such as heavy metal, summer smog, acidification

and green house effect all combine as significant environmental concerns.

Attempt 4: Clustering using a hierarchical approach

Multiple variables and their degree of association were measured applying hierarchical

cluster analysis. The variables are the mass, service life, frequency of use, energy

requirements, the presence or absence of environmental issues such as green house

effect, acidification, heavy metals, carcinogen, winter smog, summer smog, and ozone

depletion. The agglomerative hierarchical clustering showed two major clusters:

• Group A consists of cases that manifest intensity of the environmental impact at

the usage phase (e.g., coffee makers, TVs, and washing machine etc.). The mean

contribution of the usage phase is 85%.

• Group B includes products with the greatest environmental impact deriving from

the stage of material production (e.g., paper bag, PE bag, and furniture etc.).

The grouping of products defined by Attempt 1 and Attempt 4 relates partially to the

ones defined by Sousa et al (2003) and Akermark’s (1999) classification of products as

“active” if energy is needed for the product to perform its function and “passive”

otherwise. For example, in Attempt 1, Group 1 manifests “passive” attribute while for

groups 2 and 3 the “active attributes”. Group A of the Attempt 4 consists of “active”

products, and Group B comprises “passive” products. The grouping results also

confirmed general patterns proposed by Hanssen (1996), who identified the material

production and product use as the dominant factors of a product’s environmental

performance.

4.2 The Simplified Approach

The hierarchical product classification provides a structure for looking at the degree of

association among products as affected by the most general to very specific criteria. In

4-8


the pilot study, Kaebernick and Soriano (2000) explored the use of clustering results to

the development of a simplified product design assessment tool.

For products in the Group A, a high degree of correlation was identified between the

total product environmental impact and the total energy usage over its lifetime.

Therefore, it was suggested that the environmental impact of the product in Group A be

calculated as a function of the product’s total energy consumption in kWh and the

environmental impact associated with one kWh electricity. For Group B, because of the

large variety of materials involved in the products, only a fair correlation exists between

the total environmental impact and the product mass, which is affected by the type of

materials selected and the amount used. Furthermore, product groups identified by the

Attempt 1 (Soriano, 2001) and the Cut B (Sousa, 2003), indicate that sub-groups of

active products exist with significant environmental impacts from both material and

product usage phases. Altogether, the previous grouping attempts offer point solutions

for certain product groups, but do not cover the full range of product types in a

satisfactory manner.

In view of the results from these studies, a simplified environmental assessment

approach is proposed considering both energy-based impact and material-based impact

of the product. The basic concept of the approach is as follows. The total Environmental

Performance Indicator (I) of a product can be calculated by:

I = IE + IM (pts) (4-1)

The aim of the new simplified approach is to achieve better accuracy and efficiency,

instead of attempting more product classifications or investigating subgroups. Therefore

further effort of this research was focused on the development of more reliable

environmental impact drivers for the calculation of IE and IM.

Similar to the cost drivers used in Activity Based Costing, Environmental Impact

Drivers were proposed for calculating the environmental impact of a product

(Kaebernick and Soriano, 2000). An impact driver represents the key factors that

4-9


determine the impact of a product, and the driver has to have a good correlation with the

total impact of the product. The development of Energy-based Environmental Impact

Drivers (DE) and Material-based Impact Drivers (DM) will be discussed in chapter 5 in

more details.

The energy-based Environmental Performance Indicator (IE) can be estimated by the

following equation.

∑=

∗=n

iiEiE )DE(I

1 (pts) (4-2)

Where:

Ei = Lifetime energy consumption for energy source i (kWh).

DEi = Energy-based Environmental Impact Driver for energy source i (pts/kWh).

In the calculation, for a product consuming energy from n energy sources, IE is

described as the sum of the product of energy consumption and the relevant Impact

Drivers. For products with a single energy source the calculation becomes very simple.

Energy sources will be defined in Chapter 5.

The material-based Environmental Impact Driver (DM) can be applied as coefficient to

the mass of material to estimate the environmental impact for all members of a material

group. Material groups will be defined in Chapter 5. The Material-based environmental

impact of a product design can be estimated by the following equation:

(pts) (4-3) ∑=

∗=n

iiMiM DWI

1

Where:

IM = Material-based environmental performance indicator (pts)

Wi = Mass of materials in group i (kg);

DMi = Material-based Environmental Impact Driver for material group i (pts/kg)

4-10


In the calculation, for a product composed of n material groups, the Material-based

Environmental Performance Indicator (IM) is described as the sum of the products of

material mass and material-based Environmental Impact Drivers (DM). The equation

states the mass relationships observed from the pilot study. That is, the product’s

environmental impact increases with the amount of material used and the rate of

increase is determined by the types of materials. This simplified calculation can be

carried out at the early design stage with very basic data.

4.3 Conclusion

Based on the review of environmentally driven product classification and the results

from the pilot study, the simplified approach considers both Energy-based impacts and

Material-based impacts for all product groups. It is obvious that for “passive” products,

associated with no Energy-based impacts, the total Environmental Performance

Indicator (I) equals to IM. The application of environmental impact drivers DE and DM

enables the simplified approach to yield timely results with the least information

requirements.

4-11

Chapter 5 The Environmental Impact Drivers

CHAPTER 5

THE ENVIRONMENTAL IMPACT DRIVERS

This chapter focuses on the development of Environmental Impact Drivers as the basis

for the simplified environmental assessment approach described in Chapter 4. It

presents the analysis on environmental impacts associated with material selection of a

product design. Materials are classified into groups in the perspective of their

environmental performance. The development of Material based Environmental Impact

Drivers (DM) is described and the environmental Life Cycle Inventory analysis for each

material group is discussed. Energy-based Environmental Impact Drivers (DE) is also

identified, representing environmental impacts associated with the energy consumption

from different sources in different regions.

5.1 Material-Based Environmental Impacts Drivers

In the early stage of product development, detailed quantitative information of applied

materials is not available, and designers usually do not have access to a comprehensive

environmental database. Many studies were conducted in order to facilitate

environmentally friendly material selection by providing summarized information about

environmental properties of materials. For the purpose of selecting a material with

optimal environmental impact and the consideration of a wide range of other parameters,

Ashby (1999) developed charts, relating different material properties to each other.

Holloway’s (1998) material selection charts present the relationship between material

properties (modulus and strength) and air and water pollution.

The environmental impact of materials occurs in many different ways. Therefore, it

cannot be assured that optimization for minimum energy, water or air pollution will

cover the most important environmental aspects. An aggregated LCA single score,

representing the total environmental impact of a material, is hence more informative for

5-1


the designers. The environmental impact of materials can be calculated by multiplying

the mass of the material with an environmental index. However a list of indices with

specific details for each material will be cumbersome, if not difficult. Classifying

materials into groups and identifying representative impact drivers for each group of

materials is therefore a likely solution for generating an accurate estimate of the impact

indicator, while being consistent with the aim of simplifying the assessment procedure.

In this study, a Material-based Environmental Impact Driver (DM) was defined for each

identified material group, expressed in Eco-indicator single score. At the same time, the

Life Cycle Inventory was investigated for each material group to provide insights into

the substances with major contribution to the environmental impact of the group as well

as the associated environmental issues and damages.

5.1.1 Grouping of Materials

The aim of the grouping analysis was to classify materials into groups, which satisfy

two key requirements. First, they must be meaningful to and easily understood by

product designers. The characteristics of group members should be similar enough to

allow the identification and the usage of one Environmental Impact Driver (DM) for a

simplified impact evaluation for each material in the group. Second, they must be

representative for the materials’ environmental performance,

In the analysis, 594 material cases in 6 basic material categories were investigated. They

are Glass & Ceramics, Ferrous Metals, Non-ferrous Metals, Paper & Board, Polymer,

and Wood. The materials in these categories are of primary importance to product

designers.

The LCA results for the material cases were derived from data bases included in the

SimaPro software package. The mechanical and physical properties of the materials

were taken from the IDEMAT (2002) material database. The analysis covered the

materials’ environmental lifecycle inventory substances, the classification in 11 impact

categories, the 3 damage categories and the total impact in the single score according to

5-2


the method Eco-Indicator 99 H/A (Geodkoop et. al, 1999). The mechanical and physical

properties of the materials, such as strength and density, were also investigated.

The material cases in the databases were reviewed to ensure their data quality and

consistency. Cases of recycled materials were separated from the data set. Then poor

quality data and duplicates/triplicates (i.e. LCAs of the same material conducted by

different organizations) were removed according to the Data Quality Indicator and

documentation provided by the SimaPro database. After the review, 397 material cases

were maintained for further analysis.

5.1.2 Initial Grouping Attempts

At first, grouping attempts were conducted by applying cluster analysis in SPSS, using

various combinations of the environmental parameters as grouping criteria. Table 5.1

shows the 3 environmental damage categories, 11 impact categories and examples of

some major substances considered as environmental parameters for the grouping

analyses. The grouping results generally presented good similarity on the environmental

performance of group members. However, each material group contained a mix of

materials from various generic material categories. This makes the material groups

incomprehensible and impracticable for designers.

5-3


Table 5.1 Environmental parameters used in grouping analyses

Environmental

Damage Categories

Environmental Impact

categories

Examples of Major

Substances

Human Health

• Carcinogens

• Resp. organics

• Resp. inorganics

• Climate change

• Radiation Ozone layer

CO2, CFC, NOx, Dust;

Ecosystem Quality

• Ecotoxicity

• Acidification/Eutrophication

• Land use

Heavy metals, NOx, SOx,

Conv. to continuous urban

land;

Resources

• Depletion of minerals

• Depletion of fossil fuels

Copper in ore, Nickel in

ore, Coal, Crude oil,

Natural gas;

Linear regression analysis and multivariate analysis were applied to investigate

correlations between the material’s physical parameters (e.g. density, elasticity modulus

and tensile strength) and environmental parameters (e.g. CO2, NOx and weighted

environmental impact in Eco-Indicator 99 single score) (Rydh and Sun, 2003). The idea is

that if relationships exist, the material’s physical properties can be used to predict the

environmental performance of a material, and material groups can be identified according

to the physical properties. Table 5.2 presents average values for mechanical properties

calculated from data of 214 material cases in 17 material groups.

5-4


Table 5.2 Mechanical properties for 17 material groups (Rydh and Sun, 2003)

Class Group Total (n)

Density (Mg/m3)

CV (%)

Elasticity modulus (GN/m2)

CV (%)

Yield strength (MN/m2)

CV (%)

Metals Non-ferrous 8 (Cu etc) 22 8.2 30 166 53 593 42

Metals Non-ferrous 5 (Al etc) 26 5.0 49 126 66 223 47

Metals Ferrous Ni>5% 12 7.7 3.9 193 5.1 362 40

Metals Ferrous Ni<5% 10 7.7 2.1 204 5.3 627 38

Metals Ferrous Ni=0% 40 7.8 1.9 201 4.2 452 69

Composites Composites 2 1.6 17 103 45 - -

Glasses Glasses 2 3.1 23 94 - 3600 -

Porous Ceramics

Porous Ceramics 5 2.5 6.7 58 45 173 85

Polymers Thermosets epoxy 2 2.0 54 2.1 55 65 -

Polymers Thermoplastics 50 1.1 22 2.2 59 33 47

Polymer foams

Thermosets PUR foam 6 0.060 - 0.040 - 2 89

Elastomers Rubbers 3 0.90 5.5 0.0052 28 - -

Woods Woods High impact 5 0.87 - 15 - -

Woods Woods Medium impact 4 0.81 20 11 24 - -

Woods Woods Low impact 5 0.67 20 10 9 - -

Paper Cardboards 10 0.60 - 0.80 - - -

Paper Papers 7 0.60 - 0.80 - - -

CV, Coefficient of variance= standard deviation/average · 100%

5-5


Metals, which do not contain iron, were assigned to one of three groups depending on

density. The group of Non-ferrous metals 8, with an average density of 8.2 Mg/m3

(ranging from 5.7 to 10.7), included Cu, Ni, V, Ti, Mo and alloys of Cu, Ni and Ti.

Cobalt, tin and platinum group metals were not assigned to any groups since their

weighted environmental impact was several times higher than for all other groups. The

Eco-indicator single score value was 2.4 and 6.8 times higher (for Co and Sn,

respectively) than for the group of Non-ferrous 8. Therefore a specific value has to be

used for these materials.

The group Non-ferrous metals 5 had an average density of 5.0 Mg/m3 (from1.8 to 7.5)

and included Al, Cd, Cr, Mg, Mn, Si, Zn and alloys of Al, Mg and Zn. Two outliers

were Pb and W (density 11 and 19 Mg/m3, respectively), which were included in this

group according to their environmental properties.

For metals containing iron, three different groups were distinguished depending on

their content of nickel. Equation 5-1 shows the relationship between the nickel content

of the metal (CNi, wt%) and the Eco-Indicator 99 single score, EIECO’99 (Pts/kg). The

regression coefficient is 0.79 and the linear relationship indicates a fairly good

correlation between the nickel content and the environmental impact of the metal.

0855.00314.099' += NiECO cEI (Pts/kg) (5-1)

Ferrous metals with nickel concentrations >5wt% and <5wt% made up two different

groups. The third group of Ferrous metals contained no nickel. Stainless steels could be

found in all three groups due to the use of alloying metals other than nickel.

Composites included glass fibre reinforced polymer (GFRP) and carbon fibre

reinforced polymer (CFRP). Data availability was low for this group but it was

included to provide an estimate. The group Porous Ceramics included ceramics, cement

and concrete. The group of Glasses included sodium and SiO2 glass. Data for the group

of Thermosets was limited, foams of thermosets were included in the group Thermosets

5-6


polyurethane (PUR foam). The group of thermoplastics included a broad range of

polymers e.g. ABS, HDPE, PA, PC, PE, PMMA, PP, PS, PVC and PET.

The class of paper and woods was divided into Paper, Cardboard and three groups of

woods. The grouping of woods was based on environmental properties only, since no

mechanical properties made it possible to distinguish between groups of woods. Low

impact (LI) woods were defined as Ash, Aspen, Beech, Birch, Cedar, Hickory, Larch,

Oak, Pine, Silver fir, Spruce and Teak. Medium impact (MI) woods were Afzelia, Blue

gum, Bubinga, Mahogani, Silver fir and Willow. Rare species of tropical woods were

assigned to the group high impact (HI) woods, which included Avodire, Baboen,

Guaiacum, Olon and Wenge.

Figure 5.1 shows that different groups can be distinguished depending on their Eco-

Indicator 99 single score value and elasticity modulus. The error bars indicate the

standard deviation. With the data used in the study, multivariate analysis showed weak

correlation between physical material properties and environmental parameters. The

results indicated that data for density, elasticity modulus and tensile strength explain up

to 20% of the variability in weighted environmental impact. For metals, it was

concluded that there was little or no correlation between concentration of metals in the

earth’s crust and Eco-Indicator 99 weighted environmental impact (i.e. single score

value). The analyses identified oil, natural gas, NOx, SOx and CO2 as substances highly

descriptive for the total environmental impact of different material groups.

5-7


0.01

0.1

1

10

100

0.01 0.1 1 10 100 1000Young's modulus (GN/m2)

Envi

ronm

enta

l im

pact

EC

O'9

9 (P

ts/k

g)

Porous ceramics

Composites

Non-ferous 5

Non-ferrous 8

Thermosets PU

Ferrous Ni=0%Paper Glasses

Woods HI

Woods LI

Woods MI

Thermoplasts

Thermosets

Ferrous Ni<5%

Ferrous Ni>5%

Cardboard

Figure 5.1 ECO’99 weighted environmental impact and elasticity modulus for material groups (Rydh and Sun, 2003)

5.1.3 Grouping According to Generic Material Categories

In view of the results from initial attempts, further grouping analysis was conducted based

on the 6 generic material categories and material types to enable easy allocation of a

material to one of the groups. The 6 generic material categories, which are used in the

SimaPro (2001) and IDEMAT (2002) databases, include Glass & Ceramics, Ferrous

Metals, Non-ferrous Metals, Paper & Board, Polymer, and Wood. The materials in these

categories are of primary importance to product designers.

For each category, environmental properties were used as the first criteria for grouping

and specific material properties as the second. Material cases and their types are listed

in Appendix B. Cluster analysis and scatter plots of weighted environmental impacts in

Eco-Indicator 99 single score were used to identify material groups of material cases.

For each identified group, the average value of the Eco-Indicator 99 single score and its

standard deviation were calculated as shown in Appendix B. In cases where the standard

deviation (STDEV) was more than 30% of the group average, analysis on other material

properties was conducted for further sub-division. For instance, material compositions

5-8


were used as additional criteria for clustering Ferro Metals. Different grouping solutions

were examined in terms of their simplicity of application and similarity among group

members.

5.1.3.1 Grouping of Non-Metals

The grouping of non-metal materials is relatively easy because of the distinct

differences of the environmental parameters of the material types. Therefore, a simple

scatter diagram approach was sufficient for identifying the groups.

The category of Glass & Ceramics includes 11 material cases of traditional ceramics

and glass. The scatter diagram in Figure 5.2 shows that the 6 glass materials have higher

environmental impacts than the 5 traditional ceramics materials. This leads itself to

forming two major clusters. The group of glass materials has an average value of 0.0568

Pts/kg and a standard deviation of 10.49%. The values for traditional ceramics and

cement materials are 0.0273 Pts/kg for the group average with 25.81% standard

deviation. The figures indicate that the average value of the Eco-Indicator score for the

group is representative for the group members.

The LCI analysis of Glass and Ceramics materials (see Appendix C1 & C2) indicates

that the substances with major contribution to the environmental impacts are NOX, SOX,

CO2, Dust and Pb (for Glass materials only) in the compartment of air emission, Crude

oil and Natural gas in the compartment of raw material. On average, these substances

contribute 98% to the total impact of Glass materials and 85% to Ceramics materials.

Appendix B2 shows the major environmental damages of Glass materials are in the

categories of Resources (45.72%) and Human Health (41.10%). As shown in Table 5.6

the impacts are through categories of Fossil Fuels Depletion (45.08%) and Respiratory

Effects (34.48%). Appendix B1 indicates that, for Ceramics materials, the

environmental damages are mainly on Resource (58.80%) and Human Health (24.14%).

The major impacts (see Table 5.6) are in the categories of Fossil Fuels Depletion

(58.28%), Respiratory Effects (17.05%) and Land Use (14.3%).

5-9


-

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 1 2 3 4 5 6 7 8 9 10 11 12

Case Number

Eco-

Indi

cato

r 99

(Pts

/kg)

Ceramics

Glass

Figure 5.2 Eco-Indicator 99 analyses for Glass & Ceramics.

The same scatter diagram was plotted for the category of Paper & Board. Obvious

clusters can be observed, producing two groups within the category, namely paper and

cardboard. As shown in Figure 5.3, the members in the paper group have higher

environmental impacts than those of the cardboard group. The paper group includes

kraftpaper, packaging carton, paper woody/wood-free, and paper bleached/ unbleached,

having the average value of the Eco-Indicator single score of 0.0713 Pts/kg with

18.50% standard deviation. The cases in the cardboard group have an average value of

0.0348 Pts/kg and the standard deviation is 25.60% of the group average. This group

includes cardboard cellulose/chromo/duplex/gray, kraftliner, fluting, testliner, sack

paper, and paper from mechanical pulp e.g. newsprint.

Appendix C9 and C10 presents the substances with major contribution to the

environmental impacts of Paper and Cardboard materials. They are NOX, SOX, CO2,

and Dust in the compartment of air emission, Crude Oil and Natural Gas in the

compartment of raw material. On average, these substances contribute 93% to the

environmental impact of Paper materials and 95% to the Cardboards. Appendix B9

shows the major environmental damages of Paper materials are in the categories of

Resources (48.04%) and Human Health (46.71%). The impacts (Table 5.6) are through

categories of Fossil Fuels Depletion (44.76%) and Respiratory Effects (37.86%) As

shown in Appendix B10 for Cardboards the environmental damages are mainly on

5-10


Resource (46.27%) and Human Health (48.65%). The major impacts (Table 5.6) are in

the categories of Fossil Fuels Depletion (47.80%), Respiratory Effects (36.01%).

0.00

0.02

0.04

0.06

0.08

0.10

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34

Material Case Number

Eco-

Indi

cato

r 99

(Pts

/kg)

Paper Cardboard

Figure 5.3 Eco-Indicator 99 analyses for Paper & Board

In the category of Polymers, 85 cases have been analyzed, which belong to three generic

groups of rubber, thermoplastics and thermosetting plastics. In the analysis, three cases

of epoxy were separated from their original sets of thermosetting plastics and

thermoplastic, because of their distinctive environmental properties (Figure 5.4). The 17

cases of PUR thermosetting plastics show homogenous environmental behavior with the

average value of 0.4273 Pts/kg. Four cases of rubber material have the average value of

0.309 Pts/kg. The thermoplastics group has 61 cases, covering a range of materials from

ABS, PE, PET, PP, PS, to PVC and SAN with the average of 0.3652 Pts/kg.

These three generic material groups were merged to one group considering their similar

environmental performance. The merged group has an average of 0.3753 Pts/kg in Eco-

Indicator 99 single score with a standard deviation of 25.94%. The Epoxy group has an

average of 0.718 Pts/kg, and the standard deviation is 18.70% of the group average.

For Polymer materials the substances with major contribution to the environmental

impacts are NOX, SOX, CO2, and Dust in the compartment of air emission, Crude oil&

Energy from oil and Natural Gas & Energy from gas in the compartment of raw

material. They contribute 94% to the environmental impact of Rubber, Thermoplastics

and Thermosetting plastics and 99% to the Epoxy materials (see Appendix C11 and

5-11


C12). The environmental damages associated with Polymer materials are mainly in

Resources taking 67.71% for Rubbers, Thermoplastics and Thermosetting plastics and

75.92% for Epoxy (as shown in Appendix B11 and B12). The impacts are through the

category of Fossil Fuel Depletion, which on average contributes 66.51% to the

environmental impacts of Rubbers, Thermoplastics and Thermosetting plastics and

77.76% to Epoxy materials (Table 5.6).

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Material Cases

Eco-

Indi

cato

r 99

(Pts

/Kg)

Thermoplastic Rubber

Thermoset Epoxy

Figure 5.4 Eco-Indicator 99 analysis for Polymer

The SimaPro database provides 86 cases in the category of wood. Among them, four

cases have very high environmental impacts, namely Balsa 54 Pts/kg, Cordia 21.5

Pts/kg, Guaiacum 16 Pts/kg and Avodire 14.9 Pts/kg. They should be avoided in

product design, hence they were not included in the analysis. Wood materials are very

difficult to differentiate based on the type of wood, and no reasonable grouping of plant

types could be identified. Therefore groups were formed on the basis of the magnitude

of their environmental impacts. The analysis on LCI data indicates two clusters of

Woods. The low impact cluster consists of more commonly used woods with the

environmental impact dominated by the substance of “Occupation as rail/road area”,

and the high impact cluster include woods dominated by “Conv. to continuous urban

land” (see Appendix C13-C16). These two clusters were further divided into four

groups namely Wood Low impact, Wood Low-Med impact, Wood Med-High impact,

and Wood High impact (Figure 5.5).

5-12


The group of low impact wood includes 29 types of Silver Fir, Larch, Teak, Chestnut,

Polar, and Cedar etc. The average Eco-Indicator is 0.5660 Pts/kg, with 28.39% standard

deviation. Wood Low-Med impact contains 4 cases with medium environmental impact,

including Platan, Horse Chestnut, Willow, and Walnut. The average Eco-Indicator is

1.1985 Pts/kg and the standard deviation is 17.79%.

Wood Med-High impact includes 25 materials such as Iroko, Meranti, and Yang. This

group has an average value of 5.5368 Pts/kg in Eco-Indicator with 18.05% standard

deviation. There are 24 wood materials in the high impact group including Paranapine,

Emeri, Mahogany, and Wenge, with the average of 9.3263 Pt/kg and standard deviation

of 16.76%. Most of which are not widely used materials. Tropical and rainforest woods

are associated with higher environmental impacts, which can be explained by the severe

environmental problems caused by the forest depletion.

As shown in Appendix B13-B16 and Table 5.6, the environmental damages of Wood

materials are mainly in the Ecosystem quality through the impacts on Land use. The

wood materials with higher environmental impacts associated with increasing

contribution from the impact category of Land use, which on average contribute 89.83%

to the total environmental impact of materials in the Wood Low impact group, 95.06%

to the Low-Med. impact group, 98.48% to the Med-High impact group, and 99.03% to

the High impact group.

5-13


0123456789

10111213

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85

Material Case Number

Eco

Indi

cato

r 99

(Pts

/kg)

Wood Low Impact Wood Low -Med Impact

Wood Med-High Impact Wood High Impact

Figure 5.5 Eco-Indicator 99 analysis for Wood.

5.1.3.2 Grouping of Ferrous Metals

There are 81 cases in the generic category of Ferrous Metal, including iron, steel sheet,

tin plate, cast iron, steel cast, steel spring, stainless steel, steel automatic, steel

construction, steel draw, steel high & low temperature, and steel high & low grade.

Cases of iron ore, tin plate recycled or scraps are not included in the analysis, because

they are not design materials. The members of the Ferrous Metal category show a large

variety of environmental performance. The Eco-Indicators range from 0.07 to 0.66

Pts/kg.

In order to explain the varied environmental behavior among the ferrous materials, their

physical and mechanical properties have been examined with regard to their potential

for the use as grouping criteria. The initial study found that mechanical and physical

properties, such as Young’s modulus, density, and strength only have weak

relationships to the materials’ environmental properties. However the investigation on

material composition indicates that the content of Ni, Cr, C, Si, Mn, and Mo in ferrous

metals has significant effect on the material’s environmental properties.

5-14


Further analysis found that the Nickel content is the most effective criteria for the

grouping of ferrous metals. Cluster analysis was carried out, using the Eco-Indicator and

the Nickel content as criteria. The list of material cases with their Ni and Cr contents are

presented in Appendix B3-B5 together with their environmental parameters. As shown

in the summarized dendrogram (Figure 5.6), two major groups were observed. The first

group contains 57 materials with no Nickel content with the average Eco-Indicator

value of 0.0772 Pts/kg and 20.85% standard deviation. The second group has 24

material cases with Nickel content. The average Eco-Indicator is 0.313 Pts/kg with

54.6% standard deviation, which suggests that further division is necessary for the

second group.

Case Label Num

69-76, 79-81

77-78

58-68

Group 2

Group 11-57

Distance Measure 0 5 10 15 20 25

Figure 5.6 Summarized dendrogram using average linkage for cluster analysis of

ferrous metals (n=81).

The dendrogram shows two clusters in the second group (dotted line in Figure 5.6),

where cases number 58-68 form one cluster and cases number 69-81 form the other

cluster. Analysis on the detailed Nickel content of these cases explains the common

characteristics of members within each cluster. Figure 5.7 depicts the relationship

between the Nickel content and the Eco-Indicator for these 24 cases. The cluster with a

low Nickel content <5% includes cases number 58-68 and the other cluster with a

5-15


higher Nickel content >5% includes cases number 69-81. The group average of low

Nickel ferrous metals is 0.1481 Pts/kg with 28.32% standard deviation. Ferrous metals

with more than 5% Nickel content have higher environmental impacts, with a group

average of 0.4531 Pts/kg and 20.37% standard deviation. Therefore three groups were

identified in the category of Ferrous Metal, namely No Ni ferro, Low Ni ferro, and High

Ni ferro.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.00 5.00 10.00 15.00 20.00 25.00

Nickel content (wt%)

Eco-

indi

cato

r 99

(Pts

/kg)

Ferrous metal Ni<5%Ferrous metal Ni>5%

Figure 5.7 Relationship between Nickel content in ferrous metals and Eco-

Indicator 99 single score (n=24)

Further clustering of ferrous materials was explored, producing more detailed groups.

As shown in Appendix B3-B5 (Solution B), there are 5 groups identified namely No Ni

ferro, Low Ni ferro (Ni <5%), High Ni ferro (Ni>5%), Low NiCr stainless steel

(Ni+Cr<20%), High NiCr stainless steel (Ni+Cr>20%). Another attempt produced 4

groups. One group is the merging of the two groups of High Ni ferro and High NiCr

stainless steel in Solution B and the other 3 groups remain the same as the three groups

of No Ni ferro, Low Ni ferro, Low NiCr stainless steel in Solution B. However, there

was no significant improvement on the similarity of group members. On the other hand,

the larger number of material groups would have increased the complexity for

application. Therefore more detailed grouping solutions were not adopted.

The substances with major contribution to Ferrous metals’ environmental performance

are NOX, NO2, SOX, SO2, and CO2 in the compartment of air emission, Crude Oil, Coal

and Natural Gas in the compartment of raw material. In addition, other key substances

5-16


include Occupation as industrial area for No Ni ferrous metals, Nickel in ore for ferrous

metals with Ni content (see Appendix C3-C5). As shown in Appendix B3-B5, two

environmental damage categories show high contribution to the total impact of Ferrous

metals. They are Human Health and Resources through the impact category of Fossil

Fuels Depletion and Respiratory Effects (Table 5.6).

5.1.3.3 Grouping of Non-ferrous Metals

The generic category of Non-ferrous Metals has 103 cases. Two major groups were

identified through the cluster analysis. The first group contains 56 material cases

including Al, Mg, Zn, Mn, Pb and their alloys. The average Eco-Indicator value is

0.5640 Pts/kg. Cu, Ni, V, Ti, Mo and their alloys belong to the second group. They have

much higher environmental impacts than those in the first group, 2.5436 Pts/kg as group

average. Since the standard deviations for the first and second group are 22.37% and

29.14% of the group average respectively, further sub-divisions are not necessary.

Figure 5.8 shows the distribution of non-ferrous metals in terms of their Eco-Indicator

single score.

Appendix B6-B8 presents the environmental impact of Non-ferrous materials in damage

and impact categories, indicating the major damages are in the categories of Human

Health and Resources through the impact on Fossil Fuels Depletion and Respiratory

Effects (Table 5.6). For the group of Al, Mg, Zn, Mn, Pb and their alloys, the major

substances include NOX, NO2, SOX, SO2, CO2 and Dust in the compartment of air

emission, Crude Oil and Natural Gas in the compartment of raw material. In addition to

these, Nickel, Copper, Tin and land use are identified as key substance for Cu, Ni, V,

Ti, Mo and their alloys (see Appendix C6-C8).

An outlier group, which is not shown in the diagram, was identified containing 5

material cases with extreme values, i.e. 6.34 Pts/kg for Cobalt, 16.5 Pts/kg for Tin,

4610.00 Pts/kg for Palladium, 6960.00 Pts/kg for Platinum, and 123000.00 Pts/kg for

Rhodium. Designers should be aware of the high environmental impact associated with

these materials. An average value should not be applied for the members of this group.

5-17


0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

Material Cases

Eco-

indi

cato

r 99

(Pts

/kg)

Al,Mg, Zn, Mn and their alloysCu, Ni, V, Ti, Mo and their alloys

Figure 5.8 Eco-Indicator 99 analysis for Non-ferrous Metals

5.1.4 Material Groups and their Environmental Impact Drivers

Figure 5.9 presents the accuracy of different grouping solutions, ranging from a solution

based on the 6 generic material categories to the 41 material groups classified by Ashby

(1999). The average standard deviation was calculated for each number of groups,

representing the accuracy of each grouping solution. The figure indicates that the

solution with 16 material groups provides a low standard deviation and further division

into more specific material groups offers only a marginal improvement in accuracy.

Therefore 16 groups are proposed for the simplified environmental assessment of

materials.

5-18


05

101520253035404550556065

6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

Number of material groups

Aver

age

devi

atio

n (%

)

Figure 5.9 Grouping solutions and accuracies

The description of the 16 material groups is presented in Table 5.3. The group names

reflect the common understanding of the nature of the materials in each group, so that it

can easily be understood by designers. At the same time, the members of the group have

a similar environmental performance.

5-19


Table 5.3 Descriptions of the 16 material groups(1-8)

Material

Category

Group

No. Group Name Group Description

1 Traditional

Ceramics

Porcelain, ceramics, stoneware and

cements Glass

+Ceramics2 Glass

Glass (virgin/ green/ brown/oil-fired/

white/ gas-fired)

3 No Ni Ferro

Ferrous metals without Nickel content

(Including: steel sheet, Tin plate, and

some of stainless steel, cast iron, steel

autom, steel high/low temp, steel spring,

steel construction, steel draw, steel high

grade.)

4 Low Ni Ferro

(Ni<5%)

Ferrous metals with less than 5% Nickel

content

(Including some of stainless steel, steel

high grade, steel high/ low temp, steel

cast)

Ferrous

Metal

5 High Ni Ferro

(Ni>5%)

Ferrous metals with more than 5%

Nickel content

(Including some of stainless steel, steel

low temp, steel cast, cast iron)

6 Al, Mg, Zn, Mn

& their alloys

Tu, Mn, Si, Pb, Cr, Cd, and Al, Mg, Zn

including their alloys

7 Cu, Ni, V, Ti,

Mo& their alloys

V, Mo, and Cu, Ni, Ti including their

alloys

Non-Ferrous

Metal

8 Outlier Co&Sn&

Pt&Pd&Rd) Co, Sn, Pt, Pd, and Rd

5-20


Table 5.3 Descriptions of the 16 material groups (Group 9-12)

Material

Category

Group


9 Paper

Kraftpaper bleached/unbleached,

packaging carton, paper woody/wood-

free, paper bleached/ unbleached

Paper

10 Cardboard

Cardboard cellulose, cardboard chromo,

cardboard duplex, cardboard gray,

kraftliner brown/ white, fluting, sack

paper, testliner, newsprint

11 Epoxy Epoxy resin

Polymers 12

Rubber,

Thermoplastics,

Thermoset

Rubbers, PUR, ABS, HDPE, HIPS,

LDPE, PA, PB, PC, PE, PET, PMMA,

PP, PS, PVC, PVDC, SAN

5-21


Table5.3 Descriptions of the 16 material groups (Group 13-16)

Material

Category

Group


13 Wood Low

Impact

Silver Fir, Larch, Hemlock, Teak, Ash,

Beech, Oak, European Spruce, Ahorn,

Sycamore, Birch, Merbau, Chestnut,

Aspen, Cedar, Pine, Robinia, Linden,

Alder, Elm, Poplar, Western, Hornbean,

Black Poplar

14 Wood Low-Med

Impact Walnut, Platan, Horse chestnut, Willow

15 Wood Med-High

Impact

Azobe, Moabi, Blue Gum, Angelique,

Makore, Kauri, Mersawa, Yang, Agba,

Limba, Bubinga, Mahogani, Iroko,

Meranti, Utile, Dibetou, Afzelia, Sapelli,

Movigui, Afrormosia, Idigbo, Kotibe,

Mengkulang, Peroba, Bosse Clair

Woods

16 Wood High

Impact

Carapa, Paranapine, Purpleheart,

Mansonia, Mahogany, Padouk, Tiama,

Niangon, Aningre, Mutenye, Wawa,

Tchitola, Koto, Canaria, Palissander,

Indisch, Abura, Ilomba, Antiaris,

Okoume, Baboen, Olon, Cottonwood,

Wenge, Emeri

5-22


For the 16 proposed material groups, the average Eco-Indicator single score of each

group was calculated and adopted as the material-based Environmental Impact Driver

(DM) for the group members, as shown in Table 5.4. Since the standard deviation of

each group is less than 30% of the group average, DM is acceptable for the estimation of

the environmental impact for all group members, considering the fact that the accuracy

of life-cycle energy results produced by a real LCA is typically ± 30%(UK Ecolabelling

Board, 1992). The variation of 30% has also been widely adopted by researchers as a

realistic level of the accuracy of inventory data for LCA (Rousseaux et al, 2001). The

‘Outlier’ group of Non-ferrous Metals (Group 8) contains very rare cases with

extremely high environmental impact. Their environmental performances shall be

calculated individually instead of using the group average.

5-23


Table 5.4 Material groups and Material-based Environmental Impact Drivers

Material Category

Group No. Material Groups Num of

Cases Average/

DM (Pts/kg) STDEV CV

1 Traditional Ceramics 5 0.0273 0.0070 25.81%Glass

+Ceramics 2 Glass 6 0.0568 0.0060 10.49%

3 No Ni Ferro 57 0.0772 0.0161 20.85%

4 Low Ni Ferro (Ni<5%) 11 0.1481 0.0419 28.32%

Ferrous Metal

5 High Ni Ferro (Ni>5%) 13 0.4531 0.0923 20.37%

6 Al, Mg, Zn, Mn & their alloys 49 0.5640 0.1262 22.37%

7 Cu, Ni, V, Ti, Mo& their alloys 42 2.5436 0.7413 29.14%

Non-Ferrous Metal

8 Co & Sn & Pt & Pd & Rd 5

9 Paper 10 0.0713 0.0132 18.50%Paper

10 Cardboard 23 0.0348 0.0089 25.60%

11 Epoxy 3 0.7180 0.1342 18.70%

Polymers 12

Rubber, Thermoplastics,

Thermoset 82 0.3753 0.0974 25.94%

13 Wood Low Impact 29 0.5660 0.1607 28.39%

14 Wood Low-Med Impact 4 1.1985 0.2132 17.79%

15 Wood Med-High Impact 25 5.5368 0.9995 18.05%

Woods

16 Wood High Impact 24 9.3263 1.5627 16.76%

5-24


5.1.5 Life Cycle Inventory Analysis for Material Groups

It is recognized that the LCA result in a single score has the advantage of providing

designers with comprehensible information as well as with an overall view on the

environmental impacts associated with the product’s material selection. However,

environmental impacts occur through various pathways. For better interpretation of the

single score assessment, it is useful to have additional information on the life cycle

inventory analysis. LCI data includes a full list of emissions, consumed resources and

non-material impacts, such as land use associated with a material. Usually inventory

tables are very long, and many substances have only a marginal effect on the total

environmental impact. Therefore a compact LCI list was developed including only the

main contributors.

The compact LCI list for each material group is shown in Table 5.5. They were

developed through the LCI analysis of the substances with significant contributions to

the total environmental impact (see Appendix C). The purpose is to provide designers

with additional in depth information on the materials’ environmental properties in a

summarized form. It enables the designers to conduct life cycle assessment for a

material without assessing all the substances on the LCI list, and to apply their own

evaluation method instead of using Eco-Indicator 99. The list includes those substances

that contribute to more than 80% of the total environmental impact. Table 5.6 shows the

most important impact categories identified for each material group, indicating the

major environmental concerns associated with a specific group of materials.

5-25


Table 5.5 Short LCI list for material groups

No. Material Groups Abbreviated LCI list

1 Traditional Ceramics NOX, NO2, Oil, CO2, SOx, SO2, Natural gas, Dust

2 Glass NOX, NO2, Oil, CO2, SOx, SO2, Natural gas, Pb, Dust

3 Non Ni Ferro NOX, NO2, Oil, CO2, SOx, SO2, Natural gas, Coal, Land use

4 Low Ni Ferro (Ni<5%) NOX, NO2, Oil, CO2, SOx, SO2, Natural gas, Ni (in ore)

5 High Ni Ferro (Ni>5%) NOX, NO2, Oil, CO2, SOx, SO2, Natural gas, Ni (in ore), Coal

6 Al, Mg, Zn, Mn and their alloys

Oil, Natural gas, NOX, NO2, CO2, SOx, SO2, Dust

7 Cu, Ni, V, Ti, Mo and their alloys

Oil, Natural gas, NOX, NO2, CO2, SOx, SO2, Cu, Ni, Tin, Land use

8 Outliers

(Co&Sn&Pt&Pd&Rd) Cu, Ni, Oil, Natural gas, NOX, NO2, CO2, SOx, SO2

9 Paper Natural gas, Dust, Oil, NOx, NO2, CO2, SOx, SO2

10 Cardboard Natural gas, Dust, Oil, NOx, NO2, CO2, SOx, SO2

11 Epoxy Oil, Natural gas, NOx, NO2, CO2, SOx, SO2, Dust

12 Rubber, Thermoplastic, Thermoset Oil, Natural gas, NOx, NO2, CO2, SOx, SO2, Dust

13 Wood Low Impact Occupation as rail/road area

14 Wood Med Impact Occupation as rail/road area

15 Wood Med Impact Conv. to continuous urban land

16 Wood High Impact Conv. to continuous urban land

5-26


Table 5.6 Major environmental impact categories for material groups

Material Groups

Group Average

(Pts)

Resp. inorganics

(Pts)

Climate change (Pts)

Ecotoxi-city (Pts)

Land use

(Pts)

Minerals

(Pts)

Fossil fuels (Pts)

0.0273 0.0047 0.0020 2.3E-05 0.0039 3.2E-06 0.0159 Ceramics

(%) 17.05%* 7.44% 0.08% 14.30% 0.01% 58.28%

0.0568 0.0196 0.0036 0.0051 0 2.3E-09 0.0256 Glass

(%) 34.48% 6.36% 9.05% 0.00% 0.00% 45.08%

0.0772 0.0239 0.0069 0.0035 0.0058 0.0059 0.0248 No Ni Ferro

(%) 31.01% 8.95% 4.56% 7.53% 7.59% 32.14%

0.1481 0.0695 0.0093 0.0029 0.0072 0.0166 0.0351 Low Ni Ferro (Ni<5%) (%) 46.91% 6.31% 1.92% 4.88% 11.21% 23.71%

0.4531 0.2419 0.0223 0.0018 0.0113 0.0691 0.0889 High Ni Ferro (Ni>5%) (%) 53.40% 4.91% 0.39% 2.49% 15.25% 19.62%

0.5640 0.1657 0.0612 0.0056 0.0263 0.0495 0.2174 Al,Mg,Zn,Mn alloys (%) 29.37% 10.85% 0.99% 4.66% 8.77% 38.54%

2.5436 1.0989 0.0876 0.0025 0.1079 0.7600 0.4109 Cu,Ni, V, Ti, Mo (%) 43.20% 3.44% 0.10% 4.24% 29.88% 16.16%

0.0713 0.0270 0.0061 0.0007 0.0003 1.42E-05 0.0319 Paper

(%) 37.86% 8.56% 0.94% 10.66% 0.02% 44.76%

0.0348 0.0125 0.0031 0.0003 0 1.9E-05 0.0166 Cardboard

(%) 36.01% 8.95% 0.95% 0.00% 0.06% 47.80%

0.7180 0.1174 0.0262 0.0001 0.0008 2.8E-05 0.5583 Epoxy

(%) 16.36% 3.64% 0.02% 0.11% 0.00% 77.76%

0.3753 0.0810 0.0212 0.0012 0.0015 4.8E-05 0.2496 Rubber,Thermoplast, Thermoset (%) 21.58% 5.64% 0.33% 0.39% 0.01% 66.51%

*0.0047Pts (The average Impact of Resp. inorganics) /0.0273Pts (The average total impact)= 17.05%

5-27


Table 5.6 Major environmental impact categories for material groups (Cont.)

Material Groups

Group Average

(Pt)

Resp. inorganics

(Pt)

Climate change

(Pt)

Ecotoxi-city (Pt)

Land use (Pt)

Minerals (Pt)

Fossil fuels (Pt)

0.5660 0.0197 0.0039 0.0029 0.5084 3.2E-06 0.0279 Wood Low impact (%) 3.48% 0.68% 0.51% 89.83% 0.00% 4.93%

1.1985 0.0186 0.0047 0.0032 1.1393 4.5E-06 0.0312 Wood Low-Med impact (%) 1.55% 0.39% 0.27% 95.06% 0.00% 2.60%

5.5368 0.0331 0.0052 0.0025 5.4524 3E-06 0.0398 Wood Med-High impact (%) 0.60% 0.09% 0.04% 98.48% 0.00% 0.72%

9.3263 0.0337 0.0055 0.0027 9.2354 3.3E-06 0.0417 Wood High impact

0.36% 0.06% 0.03% 99.03% 0.00% 0.45%

5.1.6 Case Studies

Case studies of an active product—coffee machine and a passive product – disposable

shaver are conducted to test the application of material-based environmental impact

drivers. The results computed by applying the simplified approach are compared to the

results of LCA.

5.1.6.1 Coffee Machine

SimaPro software package describes a demo case of two models of a coffee machine,

models Sima and Pro, to explain the results of a detailed LCA study. The same case is

adopted in this study. The functional unit is defined as using the coffee machine for 5

years twice a day 5 cups.

The results in tables 5.7 and 5.8 show that the simplified approach causes a deviation of

25.95% for the model Sima, and 11.55% for the model Pro. For the purpose of

comparing the environmental performance of the two models, the detailed LCA

5-28


indicates that in the material stage, the environmental impact of model Pro is 1.83 times

greater than that of model Sima. The simplified method shows this figure as 1.62,

causing a difference of 11%. These figures represent the material-based impacts only. If

we check the effects of the simplified method on the total product environmental impact

(including all lifecycle phases), the results are 9.29 Pts for model Sima and 7.22 Pts for

model Pro. The detailed LCA leads to results of 9.12 Pts for Sima and 7.09 Pts for Pro.

This represents a deviation is only 1.82% for Sima and 1.92% for Pro. However, the

small deviation for the total impact is expected, since a coffee machine is an active

product with its main impact in the usage phase. Therefore, in this case study only the

material based impact should be considered for verification and not the total impact.

In summary, independent on which approach a designer would choose, the results

indicate that a simplified calculation leads to the same decision in a comparison of

alternative designs and thus is acceptable for the studied cases.

5-29


Table 5.7 Comparison of computed impacts and LCA results for model Sima

Title: Coffee Machine Model Sima

Method: Eco-Indicator 99 (H) / Europe EI 99 H/A

Value: Single score

Materials AmountWi

UnitDMi

(Pts/Kg)Wi*DMi

(Pts) LCA (Pts)

Corr. cardboard mix 1 0.35 Kg 0.0348 0.0122 0.0131

Glass (white) B250 0.4 Kg 0.0568 0.0227 0.0229

Paper ETH T 0.002 Kg 0.000185

Paper wood-free U B250 0.1 Kg 0.0677 0.0069

0.0074

Steel low alloy ETH T 0.15 Kg 0.0772 0.0116 0.0162

PP granulate average B250 1 Kg 0.3060

PP granulate average B250 0.14 Kg 0.0428

PVC B250 0.02 Kg 0.00517

PET bottle grade B250 0.04 Kg 0.0149

PVC B250 0.105 Kg 0.0272

PS (EPS) B250 (1998) 0.05 Kg

0.3753 0.4949

0.0166

Aluminium ingots B250 0.1 Kg 0.5640 0.0564 0.0565

Copper ETH T 0.02 Kg 0.0281

Copper ETH T 0.06 Kg 2.5372 0.2029

0.0842

0.8077 0.6413 Material-based Environmental Impact:

∑=

∗=n

iiMiM DWI

1

Deviation 25.95%

5-30


Table 5.8 Comparison of computed impacts and LCA results for model Pro

Title: Coffee Machine Model Pro


Value: Single score

Materials AmountWi

UnitDMi

(Pts/Kg)Wi*DMi

(Pts) LCA (Pts)

Corr. cardboard mix 1 0.35 Kg 0.0348 0.0122 0.0131

Glass (white) B250 0.2 Kg 0.0568 0.0114 0.0114

Paper ETH T 0.002 Kg 0.000185

Paper wood-free U B250 0.1 Kg 0.0677 0.0069

0.0074

Steel low alloy ETH T 0.15 Kg 0.0772 0.0116 0.0162

PVC B250 0.105 Kg 0.0272


PVC B250 0.02 Kg 0.00517

PET bottle grade B250 0.04 Kg 0.0149


PS (EPS) B250 (1998) 0.05 Kg

0.3753 0.2027

0.0166

Aluminium ingots B250 1.5 Kg 0.5764 0.8646 0.848

Copper ETH T 0.06 Kg 0.0842

Copper ETH T 0.02 Kg 2.5372 0.2030

0.0281

1.3123 1.1765 Material-based Environmental Impact:

∑=

∗=n

iiMiM DWI

1 Deviation 11.55%

5-31


5.1.6.2 Disposable Shavers

A case study on disposable shavers was carried out to test the application of the

simplified method on passive products. The functional unit is defined as shaving for one

year with 260 shaves. The service life of the disposable shaver is 7-8 shaves, which

requires 34 disposable shavers per year.

With no energy consumption at usage stage, the energy-based environmental impact IE

is zero. Therefore according to the simplified approach (Equation 4-1), its total

Environmental Performance Indicator I= IM, IM is the material based environmental

impact. Table 5.9 shows the calculation of IM using the material-based environmental

impact drivers.

Table 5.9 The computed environmental impacts for disposable shavers

Title: Disposable Shaver


Value: Single score

Materials Amount Wi

Unit DMi

(Pts/Kg) Wi*DMi

(Pts)

Steel 0.017 Kg 0.0772 0.0013

PET 0.012 Kg

Polyethylene 0.021 Kg

Polystyrene 0.164 Kg

0.3753 0.0739

Material-based Environmental Impact:

∑=

∗=n

iiMiM DWI

1

0.0752

5-32


A full LCA study on the disposable shavers was conducted for comparison. The results

are presented in Figure 5.10 and Figure 5.11. As shown in Figure 5.10, the total impact

of the disposable shavers is 0.0751 Pts, with 0.070 Pts from the material stage, 0.004 Pts

from processes of injection moulding and 0.00077 Pts from the disposal of the shavers.

Compared to the LCA results, the deviation caused by the simplified calculation is

0.27%.

According to the simplified analysis, the major environmental impacts of the disposable

shaver are caused by the thermoplastics from the material stage. The major

environmental damages associated with the thermoplastics (Table 5.6) are in the

category of Human Health and Resources, through the impacts on Depletion of Fossil

Fuels and Respiratory Effects, which is in line with the environmental profile of the

disposable shaver identified by the full LCA study (Figure 5.10). The simplified

analysis also identified that the major substances for thermoplastics are Oil, Natural gas,

NOx, NO2, CO2, SOx, SO2, and dust, which represent 93.5% of the total impact

associated with the disposable shavers’ life cycle as shown in Figure 5.11.

Analyzing 1 p life cycle 'disposable shavers'; Method: Eco-indicator 99 (H) / Europe EI 99 H/A / single score

mPt

0

10

20

30

40

50

60

70

80

disposableshavers-material

Injection moulding Injection mouldingPET

Landfill B250 (98)

Carcinogens Resp. organics Resp. inorganics Climate changeRadiation Ozone layer Ecotoxicity Acidification/ EutrophicLand use Minerals Fossil fuels

70

4.160.103 0.77

Figure 5.10 Environmental profile of the disposable shavers life cycle

5-33


Analyzing 1 p life cycle 'disposable shavers'; Method: Eco-indicator 99 (H) / Europe EI 99 H/A / single score

crude oil IDEMAT 0.0337 Pt

natural gas 0.0165 Pt

NOx 0.00693 Pt crude oil ETH 0.00491 Pt

CO2 0.00346 Pt

SOx 0.003 PtSO2 0.000866 Pt

dust 0.000814 Pt

Remaining processes 0.0049

Figure 5.11 Major substances for the environmental impact of disposable shavers

The case studies indicate that the simplified approach may provide designers with a

quick analysis of a product’s environmental performance and environmental profile

with acceptable accuracy. More case studies were conducted to verify the application of

the simplified approach, including 23 active products and 20 passive products. The

results are discussed in chapter 6.

5.2 Energy-Based Environmental Impact Drivers

In the pilot study conducted by Soriano (2002), electricity in Europe was used for all

active products. Large variations were caused by cases with a different fuel source

(diesel), which lead to a subgroup in the cluster of energy based products, suggesting

that products using different energy sources might create other subgroups. It was also

recognized that the environmental impact due to the generation of electricity varies

widely between countries (Rombouts et al., 1999).

Instead of further grouping active products according to their energy source, in this

study 7 commonly used energy sources were derived from the SimaPro database (as

5-34


shown in Table 5.10), representing the environmental impacts associated with various

sources in different regions. The Energy-based environmental impact drivers (DE) were

calculated by the SimaPro software package using the method of Eco-indicator 99 H/A

presented in single score value. As the major environmental impacts of active products

are associated with energy consumption in the usage stage, the list of DE will be

extended with more data becoming available in electricity generation of different

regions.

The environmental damages associated with the energy sources are mainly Human

Health and Resources through the impact categories of Fossil Fuel Depletion,

Respiratory Effects and Climate Change (see Table 5.11). The substances with major

contribution to the environmental impact of energy sources are identified as shown in

Table 5.10 and Appendix C17 in more details.

Table 5.10 Energy based Environmental Impact Drivers and the Major Substances.

No. Energy sources DE Major Substances

1 Petrol B300 0.27 Pts/kg Oil, Natural gas, NO2, CO2, SO2, Dust

2 Diesel B300 0.185 Pts/kg Oil, Natural gas, NO2, CO2, SO2,

3 Natural gas B300 0.184Pts /kg Natural gas, Oil, NO2, CO2, SO2

4 Electricity NORDEL 0.0026Pts/MJ Oil, Natural gas, NO2, CO2, SO2,Dust

5 Electricity UCPTE 0.00571Pts/MJ Oil, Natural gas, NO2, CO2, SO2, Dust

6 Energy Australia I 0.00248Pts/MJ Oil, Natural gas, Coal, SOX, NO2, CO2,

7 Energy US I 0.00293Pts/MJ Oil, Natural gas, Coal, SOX, NO2, CO2,

5-35


Table 5.11 Major environmental impact categories for Energy-based Environmental Impact Drivers

DE (Pts)

Carcino-gens

Resp. Inorga-

nics

Climate Change

Ecotoxi-city

Acidifica-tion/

Eutroph-ication

Fossil Fuels

0.2700 0.0050 0.0223 0.0062 0.0035 0.0025 0.2300Petrol

(%) 1.84%* 8.26% 2.28% 1.29% 0.94% 85.19%

0.1850 0.0022 0.0109 0.0027 0.0015 0.0014 0.1660Diesel

(%) 1.21% 5.89% 1.44% 0.79% 0.76% 89.73%

0.1840 0.0005 0.0045 0.0026 0.0002 0.0005 0.1760Natural gas

(%) 0.28% 2.43% 1.43% 0.11% 0.26% 95.65%

0.0026 0.0004 0.0008 0.0003 0.0001 0.0001 0.0009Electricity NORDEL (%) 14.08% 32.54% 11.00% 4.65% 2.90% 34.85%

0.0057 0.0006 0.0019 0.0007 0.0002 0.0002 0.0021Electricity UCPTE (%) 10.60% 33.10% 12.00% 4.17% 2.89% 37.13%

0.0025 0 0.0009 0.0005 0 0.0001 0.0011Energy Australia (%) 0 34.76% 18.51% 0 3.82% 42.74%

0.0029 0 0.0007 0.0004 0 0.0001 0.0018Energy US

(%) 0 23.41% 12.97% 0 2.77% 60.75%

0.0026 0.0004 0.0009 0.0003 0.0001 0.0001 0.0009Electricity NORDEL (%) 14.08% 32.54% 11.00% 4.65% 2.90% 34.85%

0.0057 0.0006 0.0019 0.0007 0.0002 0.0002 0.0021Electricity UCPTE (%) 10.60% 33.10% 12.00% 4.17% 2.89% 37.13%*0.0050Pts(The impact of Carcinogens) /0.2700Pts (The total impact)=1.84%

5-36


5.3 Conclusion

The grouping of materials produced a material environmental index to evaluate the

material-based environmental impacts at the early phase of product development. By

mapping materials into the index of DM, the material-based environmental impacts of a

design alternative can be evaluated on the basis of a few material groups. It enables

designers to have a timely environmental evaluation without having access to a LCA

software package or an extensive material database. Together with the energy-based

Environmental Impact Drivers (DE), the product’s environmental performance can be

assessed with very basic data input requirements and acceptable accuracy.

In order to assess how the results would change if a weighting method other than Eco-

indicator 99 were used, a comparison was made with LCI data weighted with the

evaluation method of EPS2000. The comparison showed that the trends for the material

groups were very similar, except for the groups of woods, as EPS2000 does not include

land use as an impact category. It should be pointed out that any further findings on the

impact of materials, improvement of material acquisition technology, and modification

of the environmental impact evaluation model would have an influence on the results of

this study. However, the impact drivers can easily be updated on the basis of new data

becoming available. Changes are expected to be very minor, and in particular, the basic

grouping of materials will not be affected.

5-37

Chapter 6 Verification and Case Studies

CHAPTER 6

VERIFICATION AND CASE STUDIES

Chapter 6 presents the verification of the simplified approach and two case studies for

the integrated decision model. The first section consists of the comparison of full LCA

results of collected product cases and the results computed by the simplified approach.

Then the correlation between a product’s environmental performance and its life time

energy consumption is investigated, which resulted in further simplification of the

environmental assessment for active products. Section three discusses the application of

the integrated decision model and the simplified environmental assessment approach in

two case studies.

6.1 The Verification of the Simplified Approach

A wide range of case studies is used to verify the proposed approach described in the

previous chapters. The product cases were collected from publications, references,

corporate documents, marketing and publicity documentation, organization

documentation and others. The gathered LCA documentations were either detailed

reports or summarized reports. For the latter cases where appropriate information was

available, an initial LCA was performed. In the cases of missing data, these were

obtained from reference books and databases as well as information from suppliers,

retailers, and manufacturers. Table 6.1 presents the LCA results of 43 product cases

with their total impact indicator and a breakdown into the life cycle phases of material,

manufacturing, usage, and disposal (the negative figures in this stage are the results of

recycling practices). Sources and descriptions of these cases are included in Appendix

D.

In order to be able to make a valid comparison between different cases from different

sources, all the product and material cases used in this study were assessed by the

6-1


SimaPro 5.0 LCA software package using the evaluation method of Eco-indicator 99

H/A. The energy consumption of Europe (UCPTE) was adopted for the analysis.

Table 6.1 Product environmental impact indicator and life cycle phases

Material Manf. Usage Disposal Total Product Case

(Pts) (Pts) (Pts) (Pts) (Pts)

Hydraulic unit 0.759 0.1226 1.12 -0.000612 2.01

Coffee machine Pro 1.1765 0.0831 5.815 0.00677 7.09

Coffee machine Sima 0.6413 0.0943 8.385 -0.00552 9.12

Cleaner 1.8524 0.6431 7.7 -0.00718 10.20

Cooking pan-Gunda 0.357 0.0296 10.5 -0.00367 10.88

Cooking pan-All Steel 0.47 0.0842 10.5 0.000808 11.06

Cooking pan -356+ 0.427 0.0883 11.9 0.000736 12.42

Cooking pan-Hotpan 0.348 0.0678 12.7 -0.0029 13.11

Electrical Heater 0.357 N/A 24.6 0.00622 25.00

Power tool 2.62 N/A 27.1 0.00577 29.73

TV 7.5637 0.2354 40.5 0.000342 48.30

Washing machine F-Imp. 13.5 N/A 40.3 0.31 54.00

Hand drier 2.47 N/A 53.4 -1.22 54.70

Electric Pump 2.31 0.0605 55.7 0.00954 58.00

Washing machine F-Au 14 N/A 54.6 0.113 68.70

Refrigerator 14.63 1.068 57.1 0.878 72.90

Washing machine T-Imp 9.63 N/A 102 0.134 112.00

Washing machine T-Au 10.2 N/A 109 0.0647 119.00

PC 10.8 N/A 133 0.0221 144.00

Dish washer 12.34 10.772 157 0.0519 180.00

Garbage colletor-RL200 308.4 1.9 29900 -108 30100.00

6-2


Table 6.1 Product environmental impact indicator and life cycle phases (Con.)

Material Manf. Usage Disposal Total Product Case

(Pts) (Pts) (Pts) (Pts) (Pts)

Garbage colletor-RL300 399.31 3.54 32300 -139 32500.00

Rock crusher 27900 N/A 834000 -9940 852000.00

CD package-P 0.000299 N/A N/A -8.72E-06 0.00029

Beverage package-steel 0.00226 0.000774 N/A -7.46E-04 0.00229

Paper bag 0.00111 0.0012964 N/A 0.000143 0.00255

Shopping bag-plastic 0.00675 0.0000675 N/A 0.0000746 0.00692

PET bottle 0.0075 0.000468 N/A 6.47E-05 0.00804

Beverage package-Al 0.00869 0.000807 N/A 2.12E-05 0.00952

CD package-M 0.0124 N/A N/A -0.000265 0.01220

Paper sack 0.0118 0.000521 N/A 0.0000431 0.01236

CD package-C 0.0156 N/A N/A -0.000385 0.01520

CD package-B 0.0285 N/A N/A -0.000562 0.02800

CD package-D 0.0332 N/A N/A -0.000671 0.03250

Plastic sack 0.0364 0.000196 N/A -0.000135 0.03650

Shaver-reuse 0.05328 0.015247 N/A -0.000337 0.06800

Shaver disposal 0.07004 0.004219 N/A 0.00077 0.07500

Ceramic tile 0.505 N/A N/A 0.00175 0.50600

Steel drawer 2.33 N/A N/A 0.0012 2.33

Steel panel 4.44 N/A N/A 0.166 4.61

Wooden panel 11.5 N/A N/A -0.0483 11.45

Wooden drawer 19.1 N/A N/A 0.0153 19.12

Paper towel 74.3 N/A N/A 0.198 74.50

6-3


The results of these product cases map the product classifications from the literature.

The material and usage phases are the two major contributors to the total environmental

impact of a product. As expected, the usage phase appears to be the most significant

phase for active products, whereas for passive products the material phase contributes

most of the environmental impact.

In order to verify the simplified approach, the results of the product LCA cases were

compared to the computed results from the simplified approach (shown in Table 6.2).

The calculations were carried out by using the identified Environmental Impact Drivers

(Tables 5.4 and 5.9) and the equations for the Material-based Environmental Impact

(Equation 4-3), the Energy-based Environmental Impact (Equation 4-2) and the product

Environmental Impact Indicator (Equation 4-1). The deviations caused by the

application of the simplified approach are less than 10% for 90% of the products

included in the study, with an average deviation of 4.6% and a maximum of 18% (as

shown in Figure 6.1). As discussed before, this is acceptable for the applications in the

early stages of product development considering the uncertainties of LCA.

6-4


Table 6.2 Environmental Impact Indicator for 43 product cases computed by the simplified approach

Computed Results (Pts) Product Case LCA Results

(Pts) IM IE IM + IE

Hydraulic unit 2.01 0.70 1.12 1.82

Coffee machine Pro 7.09 1.31 5.13 6.44

Coffee machine Sima 9.12 0.81 7.70 8.51

Cleaner 10.20 2.30 7.70 10.00

Cooking pan-Gunda 10.88 0.31 10.50 10.81

Cooking pan-All Steel 11.06 0.49 10.50 10.99

Cooking pan -356+ 12.42 0.45 11.90 12.35

Cooking pan-Hotpan 13.11 0.33 12.70 13.03

Electrical Heater 25.00 0.41 24.60 25.01

Power tool 29.73 2.70 27.10 29.80

TV 48.30 8.22 40.50 48.72

Washing machine F-Imp. 54.00 15.79 40.30 56.09

Hand drier 54.70 3.15 53.40 56.55

Electric Pump 58.00 2.58 55.70 58.28

Washing machine F-Au 68.70 14.69 54.60 69.29

Refrigerator 72.90 15.21 57.10 72.31

Washing machine T- Imp. 112.00 9.75 102.00 111.75

Washing machine T-Au 119.00 11.54 109.00 120.54

PC 144.00 10.69 133.00 143.69

Dish washer 180.00 12.71 157.00 169.71

Garbage collector-RL200 30100.00 296.91 29322.00 29618.91

Garbage collector-RL300 32500.00 384.07 31671.00 32055.07

Rock crusher 852000.00 33334.73 834000.00 867334.73

6-5


Table 6.2 Environmental Impact Indicator for 43 product cases computed by the simplified approach (Con.)

Computed Results (Pts) Product Case LCA Results

(Pts) IM IE IM + IE

CD package-P 0.0003 0.0003 0 0.00029

Beverage package-steel 0.0023 0.0025 0 0.00247

Paper bag 0.0025 0.0024 0 0.00237

Shopping bag-plastic 0.0069 0.0075 0 0.00750

PET bottle 0.0080 0.0083 0 0.00826

Beverage package-Al 0.0095 0.0102 0 0.01015

CD package-M 0.0122 0.0126 0 0.01261

Paper sack 0.0124 0.0140 0 0.01400

CD package-C 0.0152 0.0153 0 0.01532

CD package-B 0.0280 0.0304 0 0.03036

CD package-D 0.0325 0.0350 0 0.03504

Plastic sack 0.0365 0.0400 0 0.04

Shaver-reuse 0.0680 0.0560 0 0.056

Shaver-disposal 0.0750 0.0752 0 0.0752

Ceramic tile 0.5060 0.5020 0 0.502

Steel drawer 2.33 2.19 0 2.19

Steel panel 4.61 4.29 0 4.29

Wooden panel 11.45 10.90 0 10.9

Wooden drawer 19.12 16.72 0 16.72

Paper towel 74.50 87.19 0 87.19

6-6

Figure 6.1 Deviations of computed value compared to LCA results for 43 product cases

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6.2 Correlation Between Product Environmental Impact and Lifetime

Energy Use for Active Products

Further simplification of the environmental assessment can be achieved by the grouping

of products. In consistency with earlier results (Kaebernick and Soriano, 2000), it is

confirmed that most products fall within two major product groups, namely active

products and passive products.

Therefore, it is suggested that the designers may skip the full calculation of IE and IM

and use only one indicator for each product group, namely IE for active products and IM

for passive products. For passive products, the total Environmental Performance

Indicators were estimated by applying the equation for IM only. The average deviation

was 7.2% in comparison to the results of detailed LCA studies.

For active products, a further simplification is possible by using regression equations.

Table 6.3 shows the relationship between environmental impact indicators and their

lifecycle energy consumption for 19 electrical appliances. Considering the significance

of the energy source to the environmental assessment, analyses were conducted for 3

regions, namely Europe (UCPTE), Australia (AU), and United States (US).

For these active products, the equations below can be applied (R2 is the regression

coefficient). They were derived through linear regression on detailed product LCA case

studies. Environmental Performance Indicators are expressed in Eco-indicator 99 single

score and the lifetime energy consumption E in kWh, as shown in Figure 6.2.

IUCPTE = 0.0229 * EUCPTE + 0.8024 R2 = 0.993 (6-1)

IAU = 0.0113 * EAU + 0.7947 R2 = 0.971 (6-2)

IUS = 0.0128 * EUS + 0.8324 R2 = 0.977 (6-3)

6-8


Table 6.3 Environmental impacts with energy consumption from different regions

Environmental Impact Indicators

(Pts) Product case IUCPTE IAU IUS

Lifecycle energy use

(kWh)

Coffee machine Pro 7.090 4.180 4.590 250

Coffee machine Sima 9.120 4.760 5.370 375

Cleaner 10.200 5.830 6.440 375

Cooking pan-Gunda 10.883 4.933 5.763 510

Cooking pan-All Steel 11.055 5.057 5.894 510

Cooking pan -356+ 12.416 5.636 6.583 580

Cooking pan-Hotpan 13.113 5.943 6.943 620

E. Heater 25.000 11.100 13.000 1200

Power tool 29.726 14.400 16.500 1320

TV 48.300 25.400 28.600 1971

Washing machine F-Imp 54.000 31.300 34.400 1960

Hand drier 54.700 24.400 28.700 2600

Electric Pump 58.000 26.500 30.900 2710

Washing machine F-Au 68.700 37.800 42.100 2660

Refrigerator 72.900 40.600 45.100 2778

Washing machine T-Imp. 112.000 54.100 62.100 4970

Washing machine T-Au 119.000 57.700 66.300 5320

PC 144.000 68.800 79.300 6500

Dish washer 180.000 91.100 103.000 7621

6-9


0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

180.00

200.00

0 1000 2000 3000 4000 5000 6000 7000 8000

Life time energy consumption (kWh)

Eco-

indi

cato

r 99

(Pts

)UCPTEAU

US

Linear (UCPTE)

Linear (US)

Linear (AU)

Figure 6.2 Correlations between product environmental impacts and lifetime

energy consumption for 3 regions.

6.3 Case Studies

Two case studies were conducted to verify the application of the simplified

environmental assessment approach as part of the integrated decision model. The

product information was provided by the EcoDesign Project Team at the Hong Kong

Polytechnic University under the EcoDesign Program for Hong Kong Electrical

Appliance Manufacturers. The initial LCAs were carried out using the software package

SimaPro 4.0. To keep consistency in the study, additional LCAs were conducted for the

two cases with the software package SimaPro 5.0 using Eco-indicator 99.

6.3.1 Kettle

The water kettle is one of the OEM (Original Equipment Manufacturer) products

manufactured in China and exported to the Netherlands. The cordless kettle is an

6-10


electrical appliance with a maximum capacity 1 litre. The functional unit is defined as

each boil carries 1 litre of cold water, and the kettle is used twice a day. The time for

fully boiling water requires five minutes and the life span of the kettle is two years,

which is due to the behaviour of the customer, for example, buying a new model. The

life cycle assessment of water is not included. The operating voltage of kettle is

220V-240V, 1250W-1500W at 50-60Hz. The major function of the kettle includes:

• Boil water within 5 minutes;

• Cut off the power automatically when water is boiled;

• Apply overheat protector in dry-boil condition;

• Since the heater is installed of the bottom of the outside face of the jug pot,

the kettle can be used for other cooking purposes.

6.3.1.1 The LCA Impact Profile of the Kettle

As shown in Table 6.4, the Eco-indicator 99 single score of the kettle life cycle is 4.2

Pts, with 0.452 Pts incurred by the kettle assemblies (including the processing of

components), 3.75 Pts generated by the energy consumption during the usage stage and

0.0033 Pts from the disposal of the kettle. Figure 6.3 depicts the environmental profile

of the kettle life cycle. It is found that the major environmental damages are in the

category of Human Health and Resource, through the impacts on Respiratory effects

and Depletion of Fossil Fuels.

6-11


Table 6.4 Environmental impact of the kettle life cycle

Life cycle of kettle Environmental Impact Indicator (Pts)

Kettle Assemblies 0.452

Complete jug handle 0.0345

Jug base unit 0.0561

Jug heater unit 0.119

Jug lid unit 0.0517

Jug pot unit 0.0985

Lead wire sub-assembly 0.0104

Noen lamp w/resistor 5.43E-05

Other plastic parts 0.0548

Power cable 0.0144

Packaging 0.0126

Usage--Electricity UCPTE B250 3.75

Disposal --Household waste NL B250 0.0033

Total 4.2

Analyzing 1 p life cycle 'Life cycle of kettle'; Method: Eco-indicator 99 (H) / Europe EI 99 H/A / single score

Pt

0

-1

1

23

4

Kettle assemblies Electricity UCPTE B250 Household w aste NL B250

Carcinogens Resp. organics Resp. inorganics Climate changeRadiation Ozone layer Ecotoxicity Acidif ication/ EutrophicaLand use Minerals Fossil fuels

0.452

3.75

-0.001830.00513

Figure 6.3 Environmental profile of the kettle life cycle

6-12


6.3.1.2 The Simplified Assessment of the Kettle

The simplified assessment was performed for the life cycle of the kettle using the

calculation for IE only, IUCPTE=EUCPTE * DE-UCPET. The computed result is 3.75 Pts with

the deviation of 10.68% compared to the LCA result of 4.2 Pts. According to the

analysis in Chapter 5, the environmental damages associated with the Energy-based

Environmental Impact (IUCPTE) are mainly in categories of Human Health and Resources

through the impact categories of Fossil Fuel Depletion, Respiratory Effects and Climate

Change. This is in line with the environmental impact profile identified by the LCA of

the kettle life cycle. Chapter 5 also identified that the major substances for IUCPTE are Oil,

Natural Gas, NO2, CO2, SO2, and Dust (Table 5.9), which in this case, represent 75.2%

of the total impact associated with the kettle life cycle (shown in Figure 6.4).

Analyzing 1 p life cycle 'Life cycle of kettle'; Method: Eco-indicator 99 (H) / Europe EI 99 H/A / single score

%

0

5

10

15

20

25

Total

crude oil ETH SOx (as SO2) natural gas ETH NOx (as NO2)CO2 dust Remaining substances

20

14.811.7 11.1 11.1

6.58

24.8

Figure 6.4 Major substances for the environmental impact of the kettle life cycle

6.3.1.3 The Eco-design Alternative of the Kettle

Under the EcoDesign Program, a redesign of the kettle was conducted with the

collaboration of an overseas institute, based on the results of the LCA. The eco-design

improved the energy efficiency by 12%. The integrated decision model proposed in

Chapter 3 was applied to compare the Eco-design of the kettle and the original design,

6-13


considering the environmental performance together with the design objectives of

product performance, product cost, product development speed, and development

expenses.

Table 6.4 shows the product development features of the kettle. A typical feature is the

short product life cycle of 2 years due to consumer behaviour with a medium speed of

technical development. The environmental awareness in the market is at medium level

with a high level of price competitiveness. As the result, the relative importance of the

design objectives was calculated as given in Table 6.5.

Table 6.5 Features of a kettle







Table 6.6 Relative importance of design objectives for a kettle


PP PP PP PP DS/PP PP/EP 4 26.67%



DS DS/PP DS DS DS DS 4.5 30.00%

EP PP/EP PC EP DS EP 2.5 16.67%

6-14


The result of the paired comparison shows that Product Performance (PP) and

Development Speed (DS) have the highest weight, whereas Product Cost (PC) and

Environmental Performance (EP) are of medium importance, and Development

Expenses (DE) has the lowest ranking. These weighting factors were applied to the

evaluation of the Total Performance for the original design of the kettle and the

eco-design. The results are given in Table 6.6 indicating that the original design has a

better total performance, which is mainly caused by the high cost (DE) and the time

consumption (DS) associated with conducting LCA for the Eco-design.

Table 6.7 Total performance of design alternatives for the kettle

Target Performance

Levels

Performance Levels of Design Alternatives Design

Objectives Weighting Factor

(∑Wi=100) (Pi)

Original design

(Xi)

Ecodesign(Xi)

Product Cost WC 20.00% Pc (USD) 13.46 13.46 12.11

Product Performance WP 26.67% PP (points) 100 100 110

Environmental Performance WEN 16.67% PEN (Pts) 4.2

(3.75)4.2

(3.75) 3.76

(3.30)

Development Expense WEX 6.67% PEX

(103 USD) 150 150 220

Development Speed (months) WS 30.00% PS(months) 12 12 16


−=

n

i i

iii P

XPWTP

1

0 (0)*

-0.07 (0.07)*

* Denotes the calculations of the simplified approach.

In order to investigate the effect of applying the simplified assessment approach, EP

was computed with the equation of IUCPTE=EUCPTE * DE-UCPET. The result of EPORIGINAL

is 3.75 Pts and EPECO is 3.30 Pts. The calculations are very simple, and therefore they

cause no extra expenses and time for conducting the environmental assessment. This

6-15


resulted in a total performance for the Eco-design of 0.07, which is slightly better than

the original design. This result is very plausible since the eco-design is expected to

perform slightly better than the original design. However, this is only possible when

applying a simplified environmental assessment. It also shows that the efforts associated

with a full LCA can be prohibitive for the introduction of eco-design solutions.

6.3.2 Toaster

Another case study was conducted on a multi-function 2-slice toaster, which is one of

the OEM products manufactured by a Hong Kong company for export to the European

market. The functional unit is defined as the toaster being used twice a day with two

slices of bread each time. Each toasting process requires four minutes. The life span of

the toaster is 3 years. The Life Cycle Assessment of bread is not included in the study.

The operating voltage of toaster is 220-240V, 780W, at 50-60Hz. The major functions of

the toaster include:

• Bread toasting;

• Bun-warming;

• Reheating: for quick heating up;

• Defrosting: for defrosting and toasting in one go;

• Canceling: to stop toast process whenever wanted;

• No overheating of outer shell (plastic);

• Removable crump tray;

• Extra lift: for removing even the smallest pieces of toast;

6.3.2.1 The LCA Impact Profile of the Toaster

Table 6.7 shows the Eco-indicator 99 single score of the Toaster Life Cycle. The total

impact is 2.62 Pts, with 0.274 Pts from the Toaster Assemblies (including the processing

of components), 2.34 Pts from the energy consumption during usage phase and 0.00335

Pts from the disposal of Toaster. Figure 6.5 presents the environmental profile of the

toaster life cycle showing that the major environmental damages are in the category of 6-16


Human Health and Resources, through the impacts on Respiratory Effects and

Depletion of Fossil Fuels.

Table 6.8 Environmental impact of toaster life cycle

Life cycle of Toaster Environmental Impact Indicator (Pts)

Toaster Assemblies 0.274

Bottom cover unit 0.0207

Heater frame unit 0.0662

Heater unit 0.0003

Metal unit 0.0061

Moving mechanism 0.0152

Outer shell unit 0.0836

Packaging 0.0250

Plastic Accessory unit 0.0280

Power cable 0.0144

Sea ship B250 0.0148

Usage--Electricity UCPTE B250 2.34

Disposal --Household waste NL B250 0.00335

Total 2.62

6-17


Analyzing 1 p life cycle 'Toaster life cycle'; Method: Eco-indicator 99 (H) / Europe EI 99 H/A / single score

Pt

0-0.5

11.5

22.5

Toaster assemblies Electricity UCPTE B250 Household w aste NL B250

Carcinogens Resp. organics Resp. inorganics Climate changeRadiation Ozone layer Ecotoxicity Acidif ication/ EutrophicaLand use Minerals Fossil fuels

0.274

2.34

-0.002990.00635

Figure 6.5 Environmental profile of the toaster life cycle

6.3.2.2 The Simplified Assessment of the Toaster

Applying the simplified approach to the life cycle of the toaster resulted in 2.34 Pts for

the total impact with the deviation of 10.65% compared to the LCA result of 2.62 Pts.

The simplified assessment identified that the major environmental damages associated

with the Energy-based Environmental Impact (IUCPTE) are in the categories of Human

Health and Resources through the impacts on Fossil Fuel Depletion, Respiratory Effects

and Climate Change. This is confirmed by the environmental impact profile identified

by the LCA of the toaster life cycle (Figure 6.5). It also identified that the major

substances for IUCPTE are Oil, Natural gas, NO2, CO2, SO2, and Dust, which represent

76% of the total impact associated with the toaster life cycle (Figure 6.6).

6-18


Analyzing 1 p life cycle 'Toaster life cycle'; Method: Eco-indicator 99 (H) / Europe EI 99 H/A / single score

%

0

5

10

15

20

25

Total

crude oil ETH SOx (as SO2) natural gas ETH NOx (as NO2)CO2 dust Remaining substances

20.5

15.111.7 11.3 10.9

6.53

24

Figure 6.6 Major substances for the environmental impact of the toaster life cycle

6.3.2.3 The Eco-design Alternative of the Toaster

The Eco-design alternative for the toaster, developed under the EcoDesign Program,

targeted the problem of material waste in the original design, and the solutions were

developed as follows:

• Minimize the outer shell size from 280 x 180 x 180mm to 240 x 170 x 167 mm;

• Reduce the wall thickness from 2.5mm to 2.2mm;

• Reduce the weight of outer shell from 296.4g to 195.4g;

• Minimize the bottom cover unit from 278 x 178 x 28mm to 238 x 168 x 28mm,

resulting in decrease of weight from 73.3g to 59.2g. The integrated decision model was applied to compare the eco-design of the toaster and

the original design. As shown in Table 6.8 the development features of the toaster

include a short product life cycle of 3 years due to consumer behaviour with a medium

speed of technical development. The price competitiveness in the market is at high level

and environmental awareness is at medium level.

6-19


Table 6.9 Features of the toaster







Table 6.10 Relative importance of design objectives for the toaster


PP PP PP PP DS/PP PP/EP 4 26.67%



DS DS/PP DS DS DS DS 4.5 30.00%

EP PP/EP PC EP DS EP 2.5 16.67%

The relative importance of the design objectives was calculated as given in Table 6.9.

The result of the paired comparison shows the highest weights for PP and DS, medium

importance for PC and EP, and low ranking for DE. These weighting factors were

applied, as shown in Table 6.10 to evaluate the Total Performance for the original

design of the toaster and the eco-design alternative. Although the design team had

reduced the cost (DE) and the time consumption (DS) associated with conducting the

LCA for the eco-design, the cost of the LCA still remains the major reason for a slightly

better total performance of the original design in comparison to the eco-desgin.

The application of the simplified approach results in 2.341 Pts for EPORIGINAL

(calculated by the equation of IUCPTE=EUCPTE * DE-UCPET). As the eco-design was

6-20


targeted at reducing the material waste, which had no effect on the energy consumption

during the usage phase, the Material-based Environmental Impact Driver (DM) of the

simplified approach was used to compute the improvement on EP for the eco-design by

using the equations (Equation 4-1,4-2,4-3). The result for EPECO is 2.337 Pts. The

reduction of 0.004 Pts was calculated by applying DM (0.03753 Pts/kg) of

Thermoplastics to the material saving of 115.1g of PP in the eco-design. It was assumed

that there is no extra expense and time for conducting the environmental assessment by

the simplified method. This resulted in a total performance for the eco-design of 0.01,

which again proves the significant effect of applying the simplified approach.

Table 6.11 Total performance of design alternatives for the toaster

Target Performance

Levels

Performance Levels of Design Alternatives

Design Objectives

Weighting Factor(∑Wi=100)

(Pi) Original design

(Xi)

Ecodesign(Xi)

Product Cost WC 20.00% Pc (USD) 9.45 9.45 8.97

Product Performance WP 26.67% PP (points) 100 100 100

Environmental Performance WEN 16.67% PEN (Pts) 2.62

(2.341)2.62

(2.341) 2.58

(2.337)

Development Expense WEX 6.67% PEX

(103 USD) 150 150 200

Development Speed (months) WS 30.00% PS(months) 12 12 16


−=

n

i i

iii P

XPWTP

1

0 (0)*

-0.11 (0.01)*

* Denotes the calculations of the simplified approach.

6-21


6.4 Conclusions

The proposed methodology was verified by the comparison of the results from different

product LCA cases. In addition, it was suggested that the assessment can be further

simplified if a product can be assigned to one of the major product impact groups. For

active products, the lifecycle energy consumption proofs to be a good indicator for the

total environmental impact. For passive product, only material-based environmental

impacts need to be calculated, using the material-based environmental impact drivers.

The case studies showed that the simplified approach could be used to estimate the total

environmental impact of a product and to provide the environmental profile with

acceptable accuracy.

The case studies of the kettle and the toaster also demonstrated that the application of

the simplified approach leads to a significant reduction in cost and time consumption for

the environmental assessment. At this point, it must be highlighted that the results for

the total performance of the kettle and the toaster show very small differences between

the original design and the eco-design. Since such small differences lie within the range

of accuracy of the whole assessment process, they could hardly be used for selecting the

better alternative of the designs. However, the main purpose of the case studies was to

prove that a full LCA at the early stage of design decisions is clearly prohibitive for

considering environmental aspects in the design process. Therefore, at least for this

early design stage, a simplified approach with reasonable accuracy and very short

calculations is the only way to integrate environmental performance in the design

process.

The simplified approach, however, does not replace a full LCA, which still needs to be

carried out at a later stage. Such more comprehensive assessment remains a valuable

tool for designers to consider environmental impacts from all life cycle phases for the

fine tuning of designs and for the final life cycle costing of a product.

6-22

Chapter 7 Conclusion

CHAPTER 7

CONCLUSION

Chapter 7 describes the main research points of this thesis and summarizes the critical

findings and observations resulting from the research. This chapter also identifies

opportunities for future research.

7.1 Research Contributions

LCA has been successfully used as an environmental assessment tool for the

development of ecologically sustainable products. The LCA application at the early

design stage depends largely on how a LCA result can be achieved in a timely manner

and how effectively it can be integrated into to the process of product development.

The research work presented in this thesis provides an integrated decision model for

sustainable product development and the associated simplified environmental

assessment approach for the application in the early stage of product design. The main

advantage of the proposed model is that it incorporates the environmental aspects into

the existing product development framework. The simplified approach is based on the

concept and application of Environmental Impact Drivers. It enables designers to

perform a quick assessment of the environmental impacts associated with a product

design, without requiring large amounts of detailed data, which in most cases, are not

available in the early stage of product development.

The study was focused on the development of Environmental Impact Drivers. This was

achieved by analyzing the properties of materials and their LCA results as well as their

environmental inventory data. The material cases were classified into 16 groups

according to the nature of the materials and their environmental performance, and the

Material-based Environmental Impact Drivers (DM) were identified for each group.

7-1


Energy-based Environmental Impact Drivers (DE) were developed for the various

energy sources in major industrial regions. The impact drivers were then adopted in the

simplified environmental assessment approach to calculate the Environmental

Performance Indicator (I) of a product design. The integrated decision model was

proposed to balance the product’s environmental performance with other design

objectives. Product LCA case studies were used to compare the results from the

proposed simplified approach with those of the LCA studies. The results indicate that it

is possible and reasonable to apply the identified environmental impact drivers for a

quick estimation of a product’s environmental impacts at the early design stage.

For active products with the environmental impacts dominated by the energy

consumption during the usage phase, environmental impacts can be estimated based on

the life cycle energy consumption and the appropriate Energy-based Environmental

Impact Driver (DE). Or even simpler, the proposed regression equations can be used for

a quick answer. For passive products with no energy consumption during the usage

phase, an index of 16 Material-based Environmental Impact Drivers was identified,

which can be used to estimate the environmental impacts associated with the material

selection of a product design. For products with environmental impacts from both,

material phase and usage phase, the aggregation of IE and IM should be calculated.

This approach simplifies the tedious task of collecting detailed information required for

LCA, and designers can use this simple guideline to optimize their effort and direct their

decisions at the early stage of product development.

The major contributions of this research work can be outlined as follows:

• The identification of Environmental Impact Drivers is the major contribution of

this research. It forms the basis of the proposed simplified environmental

assessment approach, representing the key factors that determine the

environmental impacts associated with a product system. Two sets of impact

drivers were identified, namely Material-based Environmental Impact Drivers

(DM) and Energy-based Environmental Impact Drivers (DE). Further analysis on

the environmental life cycle inventory of the impact drivers provide designers

7-2


with an insight of the environmental profiles associated with the material groups

and the energy usage.

• A simplified environmental assessment approach is proposed by applying the

impact drivers. This approach provides a timely assessment tool for the

designers to estimate the environmental impacts of a product design with limited

data requirements. It avoids the need for extensive detailed data and the complex

and time-consuming LCA tasks.

• The introduction of an environmental perspective into the concurrent product

development process provides an integrated decision model for sustainable

product development. It aims to balance the environmental performance of a

product against traditional design objectives at the early stage of product

development. Existing weighting systems are adopted to assess the total

performance of competing design alternatives. The methodology provides a

coherent evaluation of design alternatives under the consideration of their

environmental performance.

The following section presents suggestions for future research areas and possible

extensions of the current research work.

7.2 Future Research

This research was based on the current knowledge of environmental impacts and

existing case studies, focusing on the most commonly used technical products with their

main impacts deriving from the material and the usage phases. However, there might be

other products of interest with their main impacts deriving from the production or

disposal phases, for instances highly toxic substances or radiation. Therefore, additional

investigations could be carried out in order to extend the application of the simplified

approach to product types with those specific, rare features.

• Group technology may be applied to production processes and product disposals.

This may lead to some simplified environmental impact drivers for products

7-3


with major environmental concerns from the stages of manufacturing and end-

of-life. New product cases with specific features in these stages need to be

defined.

Possible extensions of the current research work were also identified through the

discussion with designers. In a collaborative project with the design department of a

leading Australian household appliances manufacturer, a LCA case study of an electric

blanket was conducted using three different tools: SimaPro 5.1, Eco-it 1.3 and the

simplified environmental assessment approach proposed in this thesis. The method of

Eco-indicator 99 was used in all three tools for the comparison of the results.

The detailed LCA results from SimaPro 5.1 indicate that the major environmental

impacts of the electric blanket life cycle are from the blanket material of polyester fabric

(39.21%) and the energy consumption at usage stage (36.51%). The result of Eco-it has

a deviation of 24.48% compared to the results generated by SimaPro, and it indicates

that the energy consumption at usage stage is the dominant contributor to the total

environmental impact of the electric blanket life cycle (85%). The reasons for the

misleading results are that the material database in Eco-it does not include the polyester

fabric, which is the major contributor according to the assessment by SimaPro. At the

same time only the European energy consumption data are available in Eco-it, no

Australian data is included. Therefore designers have to be aware of those limitations

associated with the simplified software package. The missing information may have a

significant impact on the accuracy of the assessment result.

The simplified approach was also applied using the energy based and material based

impact drivers. The list of material based environmental impact drivers was updated to

include the textile material for this case. The computed result has a deviation of 13.28%

compared to the results from SimaPro 5.1, and it indicates that the material of the

blanket assembly and the energy consumption at usage stage are the major contributors

to its total environmental impact. The simplified approach also identified that the major

environmental damages associated with the electric blanket are in the category of

Depletion of Fossil Fuel and Respiratory Effects through the substances of Oil, Natural

7-4


gas, CO2, NOx, NO2, SOx, and SO2. This is in line with the Life Cycle Inventory results

from the assessment using SimaPro 5.1.

In discussions with designers on the studied case, it was agreed that comprehensive

LCA software provides more detailed and accurate results but it is associated with

higher costs and is more time consuming. The abridged LCA software is easier to use

with less costs, however it was noticed that, without providing the Life Cycle Inventory

results, the single score is a simplification of the complex interaction between a product

and the environment and the simplified databases may not cover significant contributors

to the total environmental performance of some products. The simplified LCA approach

using material based and energy based environmental impact drivers is easy to be

updated, applied and understood. The deviation caused by the simplified approach is

acceptable for the application in the early stage of product development. The extension

of the current research should include regular updates on the impact drivers according to

the improvement on environmental information about materials and energy

consumptions along with the development of the LCA methodology.

The designers also pointed out that marketing requirements and the profitability of the

new product are still the primary considerations in the design process. Environmental

assessment would not be of the same importance unless it demonstrates its benefits on

marketing or profitability. It would facilitate the application of LCA in the design

process, if the assessment results can be expressed in monetary value. A possible

extension of the current research may be on the economic assessment of the

environmental impact associated with products.

The economic assessment of the environmental impact associated with the product

system may be investigated based on the environmental profile identified from the LCI

analysis for material and energy-based environmental impact drivers. Approximate

measurements may be developed for the major contributors (e.g. CO2, NOX, and SOX

etc.) to estimate the economic cost of the environmental impacts associated with a

product system.

7-5

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APPENDIX A

BRIEF INTRODUCTION OF ECO-INDICATOR 99

DAMAGE AND IMPACT CATEGORIES

SimaPro 5.0 includes the environmental effects, weighting factors and criteria based on

the Eco-indicator 99 method, normalized to the effects of an average European

inhabitant over one year. For detailed information, the reader is referred to the

Eco-indicator 99 Manual available at the Pre website.

The default Eco-indicator 99 method is the Hierarchist version with average weighting

set (average of the full panel). In the Eco-indicator 99 method normalization and

weighting are performed at damage category level (endpoint level in ISO terminology).

The impact category indicator results, which are calculated in the Characterization step,

are added to form damage categories. Addition without weighting is justified here

because all impact categories that refer to the same damage type (like human health)

have the same unit (for instance DALY). This procedure can also be interpreted as

grouping.

The three damage categories (and not the impact categories) are normalized on an

European level (damage caused by 1 European per year), mostly based on 1993 as base

year, with some updates for the most important emissions. The Normalization Factors

and weights are specified as follows:

Normalization Weights

Human Health 1.54E-02 400

Ecosystem Quality 5.13E+03 400

Resources 8.41E+03 200

A-1

The impact categories are listed below per damage category:

Damage Category --Human Health

The damage category of Human Health includes six impact categories:

• Carcinogenic Effects on Humans;

• Respiratory Effects on Humans caused by Organic Substances;

• Respiratory Effects on Humans caused by Inorganic Substances;

• Damages to Human Health caused by Climate Change;

• Human Health Effects caused by Ionizing Radiation;

• Human Health Effects caused by Ozone Layer Depletion;

Unit: DALY= Disability adjusted life years; this means different disability caused by

diseases are weighted. A damage of 1 means one life year of one individual is lost, or

one person suffers four years from a disability with a weight of 0.25.

Damage Category --Ecosystem Quality

The damage category of Ecosystem Quality includes three impact categories:

• Damages to Ecosystem Quality caused by Ecotoxic Substances;

• Damage to Ecosystem Quality caused by Acidification and Eutrophication by

airborne emissions;

• Damage to Ecosystem caused by Land-use;

Unit: PDF*m2yr; PDF= Potentially Disappeared Fraction of plant species. A damage of

one means all species disappear from one m2 during one year, or 10% of all species

disappear from 1m2 during 10 years.

A-2

Damage Category --Resources

The damage category of Resource includes impact categories:

• Damages to Resources caused by Depletion of Fossil Fuel;

• Damages to Resources caused by Depletion of Minerals;

Unit: MJ surplus energy = Additional energy requirement to compensate lower future

ore grade. A damage of 1 means that due to a certain extraction further extraction of

these resources in the future will require one additional MJ of energy, due to the lower

resource concentration, or other unfavorable characteristics of the remaining reserves.

A-3

Appendix B1 & B2: Environmental impact of Glass & Ceramics Materials in Damage Categories

Group Name Type Pts % Pts % Pts %

ceramics Ceramics I Ceramics 0.0194 0.0034 17.47% 0.0062 31.70% 0.0099 50.77%

ceramics Ceramic (fine) Ceramics 0.0238 0.0071 29.79% 0.0006 2.55% 0.0161 67.65%

ceramics Stoneware I Ceramics 0.0269 0.0056 20.82% 0.0067 24.98% 0.0146 54.28%

ceramics Ceramics ETH T Ceramics 0.0280 0.0066 23.71% 0.0010 3.56% 0.0204 72.86%

ceramics Porcelain I Ceramics 0.0384 0.0111 28.91% 0.0087 22.63% 0.0186 48.44%

ceramics Average 0.0273 0.0068 24.14% 0.0046 17.08% 0.0159 58.80%

ceramics STDEV 0.0070

ceramics CV 25.81%

Glass Glass (brown) B250 Glass 0.0495 0.0161 32.53% 0.00395 7.98% 0.0294 59.39%

Glass Glass (green) B250 Glass 0.0505 0.014 27.72% 0.00877 17.37% 0.0278 55.05%

Glass Glass (white) B250 Glass 0.0571 0.0178 31.17% 0.0105 18.39% 0.0288 50.44%

Glass Glass oil-fired bj Glass 0.0579 0.0356 61.49% 0.00394 6.80% 0.0184 31.78%

Glass Glass gas-fired bj Glass 0.0603 0.0356 59.04% 0.00559 9.27% 0.0191 31.67%

Glass Glass (virgin) Glass 0.0652 0.0226 34.66% 0.0126 19.33% 0.03 46.01%

Glass Average 0.0568 0.0236 41.10% 0.0076 13.19% 0.0256 45.72%

Glass STDEV 0.0060

Glass CV 10.49%

ResourcesTotal (Pts)

Human Health Ecosystem QualityMaterial Cases

Appendix B3-B5:Environmental impact of Ferrous Metals in Damage Categories with Ni & Cr Cont.(Solution A)

Cr cont Ni cont

Group Name Type Pts % Pts % Pts % % %

No Ni ferro GS-22Mo4 I steel cast 0.0744 0.0338 45.43% 0.0147 19.76% 0.0259 34.81% 0.30

No Ni ferro 21MoV53 I steel high temp 0.0872 0.0356 40.83% 0.0192 22.02% 0.0324 37.16% 0.30

No Ni ferro C35 I steel high grade 0.0859 0.0436 50.76% 0.0141 16.41% 0.0282 32.83% 0.40

No Ni ferro GGG70 I Cast iron 0.0686 0.0137 19.97% 0.0053 7.76% 0.0495 72.16% 0.50

No Ni ferro 67SiCr5 I steel spring 0.0694 0.0338 48.70% 0.0124 17.87% 0.0232 33.43% 0.50

No Ni ferro 15Cr3 I steel high grade 0.0694 0.0336 48.41% 0.0124 17.87% 0.0234 33.72% 0.65

No Ni ferro A514(A) I steel low temp. 0.0765 0.0340 44.44% 0.0152 19.87% 0.0272 35.56% 0.65

No Ni ferro 13CrMo4 5 (1.7335) I steel high temp 0.0836 0.0346 41.39% 0.0183 21.89% 0.0307 36.72% 0.95

No Ni ferro 50 CrV4 I steel high grade 0.0730 0.0347 47.53% 0.0127 17.40% 0.0256 35.07% 1.00

No Ni ferro 42CrMo4 I steel high grade 0.0717 0.0343 47.84% 0.0125 17.43% 0.0249 34.73% 1.05



No Ni ferro 50CrV4 I steel spring 0.0752 0.0353 46.94% 0.0128 17.02% 0.0271 36.04% 1.05

No Ni ferro X10Cr13 (mart 410) I Stainless steels 0.1270 0.0451 35.51% 0.0119 9.37% 0.0703 55.35% 12.50

No Ni ferro X30Cr13 (~420) I Stainless steels 0.0871 0.0322 36.97% 0.0101 11.60% 0.0448 51.44% 13.00

No Ni ferro X12Cr13 (416) I Stainless steels 0.0876 0.0323 36.87% 0.0101 11.53% 0.0452 51.60% 13.00

No Ni ferro X7CrAl13 (405) I Stainless steels 0.0880 0.0326 37.05% 0.0101 11.48% 0.0452 51.36% 13.00


Material Cases ResourcesTotal (Pts)

Human Health Ecosystem Quality


Cr cont Ni cont





No Ni ferro X90CrCoMoV17 I Stainless steels 0.1070 0.0352 32.90% 0.0153 14.30% 0.0562 52.52% 17.00

No Ni ferro X90CrMoV18 (440B) I Stainless steels 0.1350 0.0478 35.41% 0.0120 8.89% 0.0750 55.56% 17.00

No Ni ferro Steel bj Ferro 0.0528 0.0200 37.88% 0.0015 2.92% 0.0312 59.09%

No Ni ferro Iron Ferro 0.0574 0.0200 34.84% 0.0015 2.58% 0.0359 62.54%

No Ni ferro Steel I Ferro 0.0644 0.0322 50.00% 0.0123 19.10% 0.0199 30.90%

No Ni ferro Crude iron I Ferro 0.0695 0.0336 48.35% 0.0128 18.42% 0.0231 33.24%

No Ni ferro Tin plate bj Ferro 0.0858 0.0369 43.01% 0.0056 6.50% 0.0433 50.47%

No Ni ferro Steel ETH T Ferro 0.0866 0.0476 54.97% 0.0173 19.98% 0.0217 25.06%

No Ni ferro Crude iron ETH T Ferro 0.0927 0.0549 59.22% 0.0140 15.10% 0.0238 25.67%

No Ni ferro Converter steel ETH T Ferro 0.0947 0.0527 55.65% 0.0187 19.75% 0.0233 24.60%

No Ni ferro ECCS steel sheet Ferro 0.0988 0.0575 58.20% 0.0055 5.59% 0.0357 36.13%

No Ni ferro Steel low alloy ETH T Ferro 0.1080 0.0590 54.63% 0.0195 18.06% 0.0295 27.31%

No Ni ferro GGG40 I Cast iron 0.0671 0.0133 19.82% 0.0053 7.84% 0.0486 72.43%


No Ni ferro 35S20 (1.0726) I Steel autom 0.0669 0.0329 49.18% 0.0124 18.54% 0.0217 32.44%

No Ni ferro 10SPb20 (1.0721) I Steel autom 0.0675 0.0328 48.59% 0.0123 18.22% 0.0223 33.04%

No Ni ferro 9SMnPb (1.0718) I Steel autom 0.0682 0.0329 48.24% 0.0123 18.04% 0.0229 33.58%


Cr cont Ni cont




No Ni ferro 9S20 I Steel autom 0.0767 0.0341 44.46% 0.0124 16.17% 0.0302 39.37%

No Ni ferro GS-70 I steel cast 0.0621 0.0305 49.11% 0.0115 18.52% 0.0201 32.37%

No Ni ferro GS-45.3 I steel cast 0.0697 0.0334 47.92% 0.0123 17.65% 0.0240 34.43%

No Ni ferro Fe360 I steel construction 0.0629 0.0310 49.28% 0.0117 18.60% 0.0202 32.11%



No Ni ferro St13 I steel construction 0.0629 0.0310 49.28% 0.0117 18.60% 0.0202 32.11%

No Ni ferro S355J2G1W I steel draw 0.0629 0.0310 49.28% 0.0117 18.60% 0.0202 32.11%

No Ni ferro St14 I steel draw 0.0629 0.0310 49.28% 0.0117 18.60% 0.0202 32.11%

No Ni ferro A517b I steel draw 0.0759 0.0341 44.93% 0.0148 19.50% 0.0269 35.44%

No Ni ferro A517a I steel draw 0.0784 0.0344 43.88% 0.0157 20.03% 0.0283 36.10%

No Ni ferro C15 I steel high grade 0.0661 0.0326 49.32% 0.0123 18.61% 0.0212 32.07%



No Ni ferro 37MnSi5 I steel high grade 0.0701 0.0337 48.07% 0.0123 17.55% 0.0241 34.38%

No Ni ferro 42MnV7 I steel high grade 0.0706 0.0337 47.73% 0.0126 17.85% 0.0244 34.56%

No Ni ferro 34CrAl6 I steel high grade 0.0788 0.0372 47.21% 0.0128 16.24% 0.0288 36.55%

No Ni ferro 22Mo4 I steel high temp 0.0759 0.0332 43.74% 0.0165 21.74% 0.0263 34.65%


Cr cont Ni cont




No Ni ferro ASt35 (1.0346) I steel low temp. 0.0660 0.0326 49.39% 0.0123 18.64% 0.0211 31.97%

No Ni ferro 38Si6 I steel spring 0.0689 0.0335 48.62% 0.0123 17.85% 0.0230 33.38%


No Ni ferro Average 0.0772 0.0343 44.69% 0.0122 16.00% 0.0307 39.31%

No Ni ferro STDEV 0.0161

No Ni ferro CV 20.85%

Low Ni Ferro GX12Cr14 (CA15) I Stainless steels 0.1160 0.0525 0.4526 0.0113 9.74% 0.0526 45.34% 13.00 1.00

Low Ni Ferro X35CrMo17 I Stainless steels 0.1140 0.0348 0.3053 0.0196 17.19% 0.0594 52.11% 16.50 1.00

Low Ni Ferro 28NiCrMo4 I steel high temp 0.1160 0.0622 0.5362 0.017 14.66% 0.0367 31.64% 1.15 1.15

Low Ni Ferro 36NiCr6 I steel high grade 0.1250 0.0717 0.5736 0.0146 11.68% 0.039 31.20% 0.50 1.25

Low Ni Ferro 15NiMn6 (1.6228) I steel low temp. 0.1210 0.0699 0.5777 0.0146 12.07% 0.0369 30.50% 1.50

Low Ni Ferro GS-10Ni6 I steel cast 0.1250 0.0730 0.5840 0.0147 11.76% 0.0371 29.68% 1.55

Low Ni Ferro X22CrNi17 (431) I Stainless steels 0.1490 0.0721 0.4839 0.0124 8.32% 0.0649 43.56% 16.00 1.88


Low Ni Ferro 30CrNiMo8 I steel high grade 0.1620 0.0873 0.5389 0.0203 12.53% 0.0548 33.83% 2.00 2.00



Low Ni Ferro Average 0.1481 0.0803 53.08% 0.0161 11.33% 0.0517 35.63%


Cr cont Ni cont




Low Ni Ferro STDEV 0.0419

Low Ni Ferro CV 28.32%

High Ni Ferro X10CrNiS (303) I Stainless steels 0.3690 0.2180 0.5908 0.0207 5.61% 0.13 35.23% 18.00 9.00

High Ni Ferro X12CrNi 18 9 I steel low temp. 0.5020 0.2910 0.5797 0.0279 5.56% 0.183 36.45% 18.00 9.00

High Ni Ferro X8Ni9 I steel low temp. 0.4070 0.2630 0.6462 0.0256 6.29% 0.119 29.24% 9.00

High Ni Ferro X5CrNi18 (304) I Stainless steels 0.4010 0.2390 0.5960 0.0219 5.46% 0.14 34.91% 19.00 9.25

High Ni Ferro X6CrNi18 (~304) I Stainless steels 0.4010 0.2390 0.5960 0.0219 5.46% 0.14 34.91% 18.00 10.00

High Ni Ferro GX5CrNi19 10 (CF8) I Stainless steels 0.3990 0.2390 0.5990 0.0219 5.49% 0.139 34.84% 19.00 10.00

High Ni Ferro X2CrNiMo1712 (316L) I Stainless steels 0.4670 0.2430 0.5203 0.0514 11.01% 0.173 37.04% 17.00 12.00

High Ni Ferro X5CrNiMo18 (316) I Stainless steels 0.4780 0.2580 0.5397 0.0467 9.77% 0.173 36.19% 17.00 12.00

High Ni Ferro GS-X40CrNiSi 25 12 I steel cast 0.6620 0.3790 0.5725 0.0391 5.91% 0.244 36.86% 26.00 12.50

High Ni Ferro X10CrNiMoNb I Stainless steels 0.6020 0.3210 0.5332 0.0529 8.79% 0.228 37.87% 17.50 13.25

High Ni Ferro GGL-NiCuCr I Cast iron 0.3340 0.2150 0.6437 0.0173 5.18% 0.101 30.24% 1.75 15.50

High Ni Ferro GGG-NiCr I Cast iron 0.4150 0.2710 0.6530 0.0206 4.96% 0.123 29.64% 1.75 20.00

High Ni Ferro GGG-NiSiCr I Cast iron 0.4530 0.2710 0.5982 0.0203 4.48% 0.161 35.54% 1.75 20.00

High Ni Ferro Average 0.4531 0.2652 58.99% 0.0299 6.46% 0.1580 34.54%

High Ni Ferro STDEV 0.0923

High Ni Ferro CV 20.37%

Appendix B3-B5:Environmental impact of Ferro Metals in Damage Categories with Ni & Cr Cont.(Solution B)

Cr cont Ni cont


No Ni ferro Steel bj Ferro 0.0528 0.0200 37.88% 0.0015 2.92% 0.0312 59.09%

No Ni ferro Iron Ferro 0.0574 0.0200 34.84% 0.0015 2.58% 0.0359 62.54%

No Ni ferro GS-70 I steel cast 0.0621 0.0305 49.11% 0.0115 18.52% 0.0201 32.37%




No Ni ferro St13 I steel construction 0.0629 0.0310 49.28% 0.0117 18.60% 0.0202 32.11%

No Ni ferro S355J2G1W I steel draw 0.0629 0.0310 49.28% 0.0117 18.60% 0.0202 32.11%

No Ni ferro St14 I steel draw 0.0629 0.0310 49.28% 0.0117 18.60% 0.0202 32.11%

No Ni ferro Steel I Ferro 0.0644 0.0322 50.00% 0.0123 19.10% 0.0199 30.90%

No Ni ferro ASt35 (1.0346) I steel low temp. 0.0660 0.0326 49.39% 0.0123 18.64% 0.0211 31.97%




No Ni ferro 35S20 (1.0726) I Steel autom 0.0669 0.0329 49.18% 0.0124 18.54% 0.0217 32.44%



No Ni ferro 10SPb20 (1.0721) I Steel autom 0.0675 0.0328 48.59% 0.0123 18.22% 0.0223 33.04%

No Ni ferro 9SMnPb (1.0718) I Steel autom 0.0682 0.0329 48.24% 0.0123 18.04% 0.0229 33.58%

No Ni ferro GGG70 I Cast iron 0.0686 0.0137 19.97% 0.0053 7.76% 0.0495 72.16% 0.50




Cr cont Ni cont






No Ni ferro 67SiCr5 I steel spring 0.0694 0.0338 48.70% 0.0124 17.87% 0.0232 33.43% 0.50

No Ni ferro Crude iron I Ferro 0.0695 0.0336 48.35% 0.0128 18.42% 0.0231 33.24%

No Ni ferro GS-45.3 I steel cast 0.0697 0.0334 47.92% 0.0123 17.65% 0.0240 34.43%


No Ni ferro 37MnSi5 I steel high grade 0.0701 0.0337 48.07% 0.0123 17.55% 0.0241 34.38%

No Ni ferro 42MnV7 I steel high grade 0.0706 0.0337 47.73% 0.0126 17.85% 0.0244 34.56%



No Ni ferro 50 CrV4 I steel high grade 0.0730 0.0347 47.53% 0.0127 17.40% 0.0256 35.07% 1.00

No Ni ferro GS-22Mo4 I steel cast 0.0744 0.0338 45.43% 0.0147 19.76% 0.0259 34.81% 0.30

No Ni ferro 50CrV4 I steel spring 0.0752 0.0353 46.94% 0.0128 17.02% 0.0271 36.04% 1.05

No Ni ferro 22Mo4 I steel high temp 0.0759 0.0332 43.74% 0.0165 21.74% 0.0263 34.65%

No Ni ferro A517b I steel draw 0.0759 0.0341 44.93% 0.0148 19.50% 0.0269 35.44%

No Ni ferro A514(A) I steel low temp. 0.0765 0.0340 44.44% 0.0152 19.87% 0.0272 35.56% 0.65

No Ni ferro 9S20 I Steel autom 0.0767 0.0341 44.46% 0.0124 16.17% 0.0302 39.37%


No Ni ferro A517a I steel draw 0.0784 0.0344 43.88% 0.0157 20.03% 0.0283 36.10%

No Ni ferro 34CrAl6 I steel high grade 0.0788 0.0372 47.21% 0.0128 16.24% 0.0288 36.55%


Cr cont Ni cont




No Ni ferro 13CrMo4 5 (1.7335) I steel high temp 0.0836 0.0346 41.39% 0.0183 21.89% 0.0307 36.72% 0.95

No Ni ferro Tin plate bj Ferro 0.0858 0.0369 43.01% 0.0056 6.50% 0.0433 50.47%

No Ni ferro C35 I steel high grade 0.0859 0.0436 50.76% 0.0141 16.41% 0.0282 32.83% 0.40

No Ni ferro Steel ETH T Ferro 0.0866 0.0476 54.97% 0.0173 19.98% 0.0217 25.06%

No Ni ferro 21MoV53 I steel high temp 0.0872 0.0356 40.83% 0.0192 22.02% 0.0324 37.16% 0.30

No Ni ferro Crude iron ETH T Ferro 0.0927 0.0549 59.22% 0.0140 15.10% 0.0238 25.67%

No Ni ferro Converter steel ETH T Ferro 0.0947 0.0527 55.65% 0.0187 19.75% 0.0233 24.60%

No Ni ferro ECCS steel sheet Ferro 0.0988 0.0575 58.20% 0.0055 5.59% 0.0357 36.13%

No Ni ferro Steel low alloy ETH T Ferro 0.1080 0.0590 54.63% 0.0195 18.06% 0.0295 27.31%

No Ni ferro Average 0.0729 0.0340 46.20% 0.0122 16.68% 0.0267 37.11%

No Ni ferro STDEV 0.0108

No Ni ferro CV 14.85%

Low Ni ferro 28NiCrMo4 I steel high temp 0.1160 0.0622 53.62% 0.0170 14.66% 0.0367 31.64% 1.15 1.15

Low Ni ferro 15NiMn6 (1.6228) I steel low temp. 0.1210 0.0699 57.77% 0.0146 12.07% 0.0369 30.50% 1.50

Low Ni ferro 36NiCr6 I steel high grade 0.1250 0.0717 57.36% 0.0146 11.68% 0.0390 31.20% 0.50 1.25

Low Ni ferro GS-10Ni6 I steel cast 0.1250 0.0730 58.40% 0.0147 11.76% 0.0371 29.68% 1.55


Low Ni ferro 30CrNiMo8 I steel high grade 0.1620 0.0873 53.89% 0.0203 12.53% 0.0548 33.83% 2.00 2.00




Cr cont Ni cont




Low Ni ferro Average 0.1563 0.0905 57.46% 0.0167 11.17% 0.0490 31.37%

Low Ni ferro STDEV 0.0461

Low Ni ferro CV 29.50%

High Ni ferro GGL-NiCuCr I Cast iron 0.3340 0.2150 64.37% 0.0173 5.18% 0.1010 30.24% 1.75 15.50

High Ni ferro X8Ni9 I steel low temp. 0.4070 0.2630 64.62% 0.0256 6.29% 0.1190 29.24% 9.00

High Ni ferro GGG-NiCr I Cast iron 0.4150 0.2710 65.30% 0.0206 4.96% 0.1230 29.64% 1.75 20.00

High Ni ferro GGG-NiSiCr I Cast iron 0.4530 0.2710 59.82% 0.0203 4.48% 0.1610 35.54% 1.75 20.00

High Ni ferro X12CrNi 18 9 I steel low temp. 0.5020 0.2910 57.97% 0.0279 5.56% 0.1830 36.45% 18.00 9.00

High Ni ferro GS-X40CrNiSi 25 12 I steel cast 0.6620 0.3790 57.25% 0.0391 5.91% 0.2440 36.86% 26.00 12.50

High Ni ferro Average 0.4622 0.2817 61.56% 0.0251 5.40% 0.1552 32.99%

High Ni ferro STDEV 0.1125

High Ni ferro CV 24.35%

Low NiCr stainless steel X30Cr13 (~420) I Stainless steels 0.0871 0.0322 36.97% 0.0101 11.60% 0.0448 51.44% 13.00

Low NiCr stainless steel X12Cr13 (416) I Stainless steels 0.0876 0.0323 36.87% 0.0101 11.53% 0.0452 51.60% 13.00

Low NiCr stainless steel X7CrAl13 (405) I Stainless steels 0.0880 0.0326 37.05% 0.0101 11.48% 0.0452 51.36% 13.00




Cr cont Ni cont




Low NiCr stainless steel X35CrMo17 I Stainless steels 0.1140 0.0348 30.53% 0.0196 17.19% 0.0594 52.11% 16.50 1.00

Low NiCr stainless steel X90CrCoMoV17 I Stainless steels 0.1070 0.0352 32.90% 0.0153 14.30% 0.0562 52.52% 17.00

Low NiCr stainless steel X10Cr13 (mart 410) I Stainless steels 0.1270 0.0451 35.51% 0.0119 9.37% 0.0703 55.35% 12.50

Low NiCr stainless steel X90CrMoV18 (440B) I Stainless steels 0.1350 0.0478 35.41% 0.0120 8.89% 0.0750 55.56% 17.00

Low NiCr stainless steel GX12Cr14 (CA15) I Stainless steels 0.1160 0.0525 45.26% 0.0113 9.74% 0.0526 45.34% 13.00 1.00

Low NiCr stainless steel X22CrNi17 (431) I Stainless steels 0.1490 0.0721 48.39% 0.0124 8.32% 0.0649 43.56% 16.00 1.88

Low NiCr stainless steel Average 0.1097 0.0411 37.06% 0.0127 11.80% 0.0560 51.19%

Low NiCr stainless steel STDEV 0.0209

Low NiCr stainless steel CV 19.04%

High NiCr stainless steel X10CrNiS (303) I Stainless steels 0.3690 0.2180 59.08% 0.0207 5.61% 0.1300 35.23% 18.00 9.00

High NiCr stainless steel GX5CrNi19 10 (CF8) I Stainless steels 0.3990 0.2390 59.90% 0.0219 5.49% 0.1390 34.84% 19.00 10.00

High NiCr stainless steel X5CrNi18 (304) I Stainless steels 0.4010 0.2390 59.60% 0.0219 5.46% 0.1400 34.91% 19.00 9.25

High NiCr stainless steel X6CrNi18 (~304) I Stainless steels 0.4010 0.2390 59.60% 0.0219 5.46% 0.1400 34.91% 18.00 10.00

High NiCr stainless steel X2CrNiMo1712 (316L) I Stainless steels 0.4670 0.2430 52.03% 0.0514 11.01% 0.1730 37.04% 17.00 12.00

High NiCr stainless steel X5CrNiMo18 (316) I Stainless steels 0.4780 0.2580 53.97% 0.0467 9.77% 0.1730 36.19% 17.00 12.00

High NiCr stainless steel X10CrNiMoNb I Stainless steels 0.6020 0.3210 53.32% 0.0529 8.79% 0.2280 37.87% 17.50 13.25

High NiCr stainless steel Average 0.4453 0.2510 56.79% 0.0339 7.37% 0.1604 35.86%

High NiCr stainless steel STDEV 0.0796

High NiCr stainless steel CV 17.87%

Appendix B6-B8: Environmental Impact of Non-ferrous Metals in Damage Categories


Al, Mg, Zn, Mn & their alloys Manganese ETH T Non-ferro 0.2500 0.1290 51.60% 0.0333 13.32% 0.0871 34.84%

Al, Mg, Zn, Mn & their alloys Silicon I Si 0.2580 0.0981 38.02% 0.0140 5.43% 0.1460 56.59%

Al, Mg, Zn, Mn & their alloys Ferrochromium I Non-ferro 0.2740 0.0855 31.20% 0.0122 4.45% 0.1760 64.23%

Al, Mg, Zn, Mn & their alloys Zamak3 I Zinc Alloy 0.3760 0.1200 31.91% 0.0413 10.98% 0.2150 57.18%

Al, Mg, Zn, Mn & their alloys Zamak5 I Zinc Alloy 0.3910 0.1270 32.48% 0.0420 10.74% 0.2220 56.78%

Al, Mg, Zn, Mn & their alloys ZnCuTi I Zinc Alloy 0.3960 0.1270 32.07% 0.0424 10.71% 0.2270 57.32%

Al, Mg, Zn, Mn & their alloys Zinc (super plastic) I Zinc Alloy 0.4020 0.1370 34.08% 0.0396 9.85% 0.2260 56.22%

Al, Mg, Zn, Mn & their alloys G-ZnAlCu I Zinc Alloy 0.4190 0.1400 33.41% 0.0432 10.31% 0.2360 56.32%

Al, Mg, Zn, Mn & their alloys Lead I lead 0.4230 0.0840 19.86% 0.0142 3.36% 0.3250 76.83%

Al, Mg, Zn, Mn & their alloys Zinc I Zinc 0.4350 0.1550 35.63% 0.0552 12.69% 0.2250 51.72%

Al, Mg, Zn, Mn & their alloys G-AlSi12 (230) I AL alloy 0.5240 0.2260 43.13% 0.0397 7.58% 0.2580 49.24%

Al, Mg, Zn, Mn & their alloys Aluminium raw bj Al 0.5300 0.3860 72.83% 0.0238 4.49% 0.1200 22.64%

Al, Mg, Zn, Mn & their alloys G-AlSi12Cu (231) I AL alloy 0.5310 0.2290 43.13% 0.0401 7.55% 0.2620 49.34%

Al, Mg, Zn, Mn & their alloys G-AlSi7Mg (Thixo) I AL alloy 0.5370 0.2330 43.39% 0.0408 7.60% 0.2630 48.98%

Al, Mg, Zn, Mn & their alloys AlMg3 (5754a) I AL alloy 0.5450 0.2390 43.85% 0.0412 7.56% 0.2650 48.62%

Al, Mg, Zn, Mn & their alloys AlSiMgMn (6009) I AL alloy 0.5590 0.2440 43.65% 0.0424 7.58% 0.2730 48.84%

Al, Mg, Zn, Mn & their alloys AlMn1.2Mg1 (3004) I AL alloy 0.5600 0.2440 43.57% 0.0424 7.57% 0.2740 48.93%

Al, Mg, Zn, Mn & their alloys AlMgSi0.7 (6005) I AL alloy 0.5610 0.2450 43.67% 0.0426 7.59% 0.2740 48.84%







Al, Mg, Zn, Mn & their alloys AlMn1 (3003) I AL alloy 0.5610 0.2440 43.49% 0.0426 7.59% 0.2740 48.84%

Al, Mg, Zn, Mn & their alloys G-AlMg3 (242) I AL alloy 0.5610 0.2460 43.85% 0.0423 7.54% 0.2730 48.66%

Al, Mg, Zn, Mn & their alloys Al99 I AL alloy 0.5640 0.2460 43.62% 0.0429 7.61% 0.2750 48.76%

Al, Mg, Zn, Mn & their alloys AlMg1 (5005) I AL alloy 0.5640 0.2470 43.79% 0.0428 7.59% 0.2750 48.76%

Al, Mg, Zn, Mn & their alloys AlMg4.5Mn (5182) I AL alloy 0.5640 0.2480 43.97% 0.0423 7.50% 0.2740 48.58%

Al, Mg, Zn, Mn & their alloys Aluminium ingots B250 AL 0.5650 0.2650 46.90% 0.0220 3.89% 0.2780 49.20%

Al, Mg, Zn, Mn & their alloys Chromium I Cr 0.5680 0.1860 32.75% 0.0248 4.37% 0.3570 62.85%

Al, Mg, Zn, Mn & their alloys AlZnCuMg (7075) I AL alloy 0.5770 0.2500 43.33% 0.0444 7.69% 0.2830 49.05%

Al, Mg, Zn, Mn & their alloys G-AlSi8Cu3 (380) I AL alloy 0.5780 0.2500 43.25% 0.0433 7.49% 0.2840 49.13%

Al, Mg, Zn, Mn & their alloys Cadmium I Cd 0.5930 0.1810 30.52% 0.2710 45.70% 0.1420 23.95%

Al, Mg, Zn, Mn & their alloys Aluminium foil B250 AL 0.5980 0.2760 46.15% 0.0232 3.88% 0.2990 50.00%

Al, Mg, Zn, Mn & their alloys AlMgSi0.5 (6060) I AL alloy 0.6040 0.2650 43.87% 0.0447 7.40% 0.2940 48.68%

Al, Mg, Zn, Mn & their alloys AlCuSiMg (2036) I AL alloy 0.6060 0.2650 43.73% 0.0452 7.46% 0.2960 48.84%

Al, Mg, Zn, Mn & their alloys G-AlMg5 (314) I AL alloy 0.6120 0.2690 43.95% 0.0449 7.34% 0.2980 48.69%

Al, Mg, Zn, Mn & their alloys AlCuMg1 (2017) I AL alloy 0.6290 0.2750 43.72% 0.0464 7.38% 0.3080 48.97%

Al, Mg, Zn, Mn & their alloys AlCuMg2 (2024) I AL alloy 0.6390 0.2800 43.82% 0.0468 7.32% 0.3120 48.83%

Al, Mg, Zn, Mn & their alloys G-AlCu4TiMg (204) I AL alloy 0.6400 0.2800 43.75% 0.0471 7.36% 0.3130 48.91%

Al, Mg, Zn, Mn & their alloys AlCuMgPb (2011) I AL alloy 0.6490 0.2800 43.14% 0.0470 7.24% 0.3220 49.61%





Al, Mg, Zn, Mn & their alloys MgZn6Zr I Mg Alloy 0.6560 0.3230 49.24% 0.0326 4.97% 0.3010 45.88%

Al, Mg, Zn, Mn & their alloys G-MgAl6Zn3 I Mg Alloy 0.6590 0.3240 49.17% 0.0326 4.95% 0.3020 45.83%


Al, Mg, Zn, Mn & their alloys GD-MgAl9Zn1 I Mg Alloy 0.6630 0.3270 49.32% 0.0324 4.89% 0.3040 45.85%


Al, Mg, Zn, Mn & their alloys MgAl6Zn I Mg Alloy 0.6640 0.3270 49.25% 0.0322 4.85% 0.3040 45.78%

Al, Mg, Zn, Mn & their alloys MgMn1.5 I Mg Alloy 0.6640 0.3290 49.55% 0.0310 4.67% 0.3040 45.78%

Al, Mg, Zn, Mn & their alloys AM100A I Mg Alloy 0.6650 0.3270 49.17% 0.0324 4.87% 0.3050 45.86%

Al, Mg, Zn, Mn & their alloys AM503 I Mg Alloy 0.6650 0.3300 49.62% 0.0310 4.66% 0.3040 45.71%

Al, Mg, Zn, Mn & their alloys MgAl3Zn I Mg Alloy 0.6650 0.3290 49.47% 0.0318 4.78% 0.3040 45.71%

Al, Mg, Zn, Mn & their alloys Magnesium I Non-ferro 0.6690 0.3330 49.78% 0.0313 4.68% 0.3050 45.59%

Al, Mg, Zn, Mn & their alloys Ni-pigmented aluminiumoxide ETH TAL 0.8100 0.5760 71.11% 0.0286 3.53% 0.2060 25.43%

Al, Mg, Zn, Mn & their alloys Tungsten I Non-ferro 0.8900 0.3500 39.33% 0.2440 27.42% 0.2960 33.26%

Al, Mg, Zn, Mn & their alloys Average 0.5640 0.2516 43.64% 0.0457 8.08% 0.2668 48.29%

Al, Mg, Zn, Mn & their alloys STDEV 0.1262

Al, Mg, Zn, Mn & their alloys CV 22.37%

Cu, Ni, V, Ti, Mo& their alloys CuZn40Pb I Copper alloy 1.5500 0.6720 43.35% 0.1030 6.65% 0.7720 49.81%

Cu, Ni, V, Ti, Mo& their alloys CuZn40 I Copper alloy 1.5900 0.6950 43.71% 0.1060 6.67% 0.7910 49.75%





Cu, Ni, V, Ti, Mo& their alloys G-CuZn40 I Copper alloy 1.5900 0.6950 43.71% 0.1060 6.67% 0.7910 49.75%

Cu, Ni, V, Ti, Mo& their alloys G-CuZn37Pb I Copper alloy 1.6100 0.7040 43.73% 0.1060 6.58% 0.8020 49.81%

Cu, Ni, V, Ti, Mo& their alloys Vanadium I Vanadium 1.6200 0.5060 31.23% 0.2550 15.74% 0.8580 52.96%


Cu, Ni, V, Ti, Mo& their alloys Ni span C902 I Ni Alloy 1.7300 1.1300 65.32% 0.0765 4.42% 0.5200 30.06%


Cu, Ni, V, Ti, Mo& their alloys Invar I Ni Alloy 1.7900 1.1100 62.01% 0.0849 4.74% 0.5900 32.96%

Cu, Ni, V, Ti, Mo& their alloys TiAl6V4 I Ti Alloy 1.8400 0.6750 36.68% 0.0685 3.72% 1.1000 59.78%

Cu, Ni, V, Ti, Mo& their alloys Titanium I Ti 1.9300 0.7080 36.68% 0.0619 3.21% 1.1600 60.10%

Cu, Ni, V, Ti, Mo& their alloys NiFe 50 50 I Ni Alloy 1.9500 1.3100 67.18% 0.0863 4.43% 0.5590 28.67%


Cu, Ni, V, Ti, Mo& their alloys G-CuZn15 I Copper alloy 2.0700 0.9200 44.44% 0.1270 6.14% 1.0300 49.76%

Cu, Ni, V, Ti, Mo& their alloys G-CuAl10Fe I Copper alloy 2.1200 0.9470 44.67% 0.1260 5.94% 1.0500 49.53%

Cu, Ni, V, Ti, Mo& their alloys G-CuAl10Ni I Copper alloy 2.1700 1.0200 47.00% 0.1250 5.76% 1.0300 47.47%

Cu, Ni, V, Ti, Mo& their alloys TiAl5Sn2 I Ti Alloy 2.2300 0.6750 30.27% 0.0602 2.70% 1.5000 67.26%

Cu, Ni, V, Ti, Mo& their alloys CuNi18Zn I Copper alloy 2.2400 1.1500 51.34% 0.1270 5.67% 0.9670 43.17%

Cu, Ni, V, Ti, Mo& their alloys TiV15SnCrAl3 I Ti Alloy 2.2400 0.6360 28.39% 0.0883 3.94% 1.5200 67.86%

Cu, Ni, V, Ti, Mo& their alloys CuAl5 I Copper alloy 2.2700 1.0200 44.93% 0.1340 5.90% 1.1200 49.34%





Cu, Ni, V, Ti, Mo& their alloys Cu-E I Copper alloy 2.3600 1.0600 44.92% 0.1400 5.93% 1.1700 49.58%

Cu, Ni, V, Ti, Mo& their alloys CuAg-E I Copper alloy 2.3600 1.0600 44.92% 0.1400 5.93% 1.1700 49.58%

Cu, Ni, V, Ti, Mo& their alloys Copper I copper 2.3600 1.0600 44.92% 0.1400 5.93% 1.1700 49.58%

Cu, Ni, V, Ti, Mo& their alloys G-CuNi10 I Copper alloy 2.4500 1.1800 48.16% 0.1380 5.63% 1.1300 46.12%

Cu, Ni, V, Ti, Mo& their alloys CuNi10Fe I Copper alloy 2.4600 1.1900 48.37% 0.1390 5.65% 1.1400 46.34%

Cu, Ni, V, Ti, Mo& their alloys Molybdenum I Mo 2.7100 0.1620 5.98% 1.1900 43.91% 1.3500 49.82%

Cu, Ni, V, Ti, Mo& their alloys G-CuSn5Zn5Pb5 I Copper alloy 2.8800 0.9210 31.98% 0.1240 4.31% 1.8300 63.54%

Cu, Ni, V, Ti, Mo& their alloys CuNi44Mn I Copper alloy 2.9800 1.7100 57.38% 0.1470 4.93% 1.1200 37.58%

Cu, Ni, V, Ti, Mo& their alloys Supermalloy I Ni Alloy 3.0300 1.9500 64.36% 0.1820 6.01% 0.8950 29.54%

Cu, Ni, V, Ti, Mo& their alloys NiCr20TiAl I Ni Alloy 3.0900 2.0200 65.37% 0.1290 4.17% 0.9390 30.39%

Cu, Ni, V, Ti, Mo& their alloys Mumetal I Ni Alloy 3.1100 2.0600 66.24% 0.1330 4.28% 0.9190 29.55%

Cu, Ni, V, Ti, Mo& their alloys NiCr 80 20 I Ni Alloy 3.1900 2.1100 66.14% 0.1330 4.17% 0.9500 29.78%

Cu, Ni, V, Ti, Mo& their alloys NiCu30Fe I Ni Alloy 3.3000 2.0500 62.12% 0.1510 4.58% 1.1000 33.33%

Cu, Ni, V, Ti, Mo& their alloys CuSn6.7P I Copper alloy 3.3100 1.0000 30.21% 0.1320 3.99% 2.1800 65.86%

Cu, Ni, V, Ti, Mo& their alloys NiCu30Al I Ni Alloy 3.3900 2.0800 61.36% 0.1530 4.51% 1.1500 33.92%

Cu, Ni, V, Ti, Mo& their alloys NiCr20Co18Ti I Ni Alloy 3.4800 1.6000 45.98% 1.0800 31.03% 0.7880 22.64%

Cu, Ni, V, Ti, Mo& their alloys NiMo30 I Ni Alloy 3.4900 1.7700 50.72% 0.5910 16.93% 1.1200 32.09%

Cu, Ni, V, Ti, Mo& their alloys CuSn8 I Copper alloy 3.5000 0.9910 28.31% 0.1310 3.74% 2.3700 67.71%





Cu, Ni, V, Ti, Mo& their alloys Duranik I Ni Alloy 3.6600 2.4500 66.94% 0.1530 4.18% 1.0600 28.96%

Cu, Ni, V, Ti, Mo& their alloys G-CuSn10 I Copper alloy 3.7800 0.9740 25.77% 0.1290 3.41% 2.6800 70.90%

Cu, Ni, V, Ti, Mo& their alloys Ni 99.6 I Ni Alloy 3.8400 2.5900 67.45% 0.1600 4.17% 1.1000 28.65%

Cu, Ni, V, Ti, Mo& their alloys G-CuSn12 I Copper alloy 4.0600 0.9580 23.60% 0.1270 3.13% 2.9800 73.40%

Cu, Ni, V, Ti, Mo& their alloys Average 2.5436 1.1892 46.38% 0.1841 7.11% 1.1715 46.57%

Cu, Ni, V, Ti, Mo& their alloys STDEV 0.7413

Cu, Ni, V, Ti, Mo& their alloys CV 29.14%

Co & Sn & Pts & Pd & Rd Cobalt I Non-ferro 6.34 0.14 2.22% 5.95 93.85% 0.24 3.85%

Co & Sn & Pts & Pd & Rd Tin I Non-ferro 16.50 0.25 1.50% 0.03 0.19% 16.20 98.18%

Co & Sn & Pts & Pd & Rd Palladium enriched ETH TNon-ferro 4610.00 3990.00 86.55% 515.00 11.17% 103.00 2.23%

Co & Sn & Pts & Pd & Rd Platinum ETH T Non-ferro 6960.00 6030.00 86.64% 749.00 10.76% 180.00 2.59%

Co & Sn & Pts & Pd & Rd Rhodium enriched ETH T Non-ferro 12300.00 10700.00 86.99% 1310.00 10.65% 332.00 2.70%

Appendix B9 & B10: Environmental impact of Paper & Cardboard Materials in Damage Categories


paper Paper ETH T Paper 0.0926 0.0471 50.86% 0.0081 8.70% 0.0375 40.50%

paper Kraftpaper unbleached Paper 0.0900 0.0282 31.33% 0.0032 3.50% 0.0587 65.22%

paper Kraftpaper bleached B250 Paper 0.0796 0.0316 39.70% 0.0031 3.92% 0.0449 56.41%

paper Kraftpaper bleached C B250 Paper 0.0767 0.0277 36.11% 0.0028 3.60% 0.0463 60.37%

paper Paper wood-free U B250 Paper 0.0740 0.0253 34.19% 0.0025 3.36% 0.0462 62.43%

paper Paper bleached B Paper 0.0626 0.0529 84.50% 0.0034 5.50% 0.0062 9.95%

paper Paper woody C B250 Paper 0.0623 0.0183 29.37% 0.00189 3.03% 0.0422 67.74%

paper Packaging carton ETH T Paper 0.0611 0.0266 43.54% 0.0075 12.27% 0.0270 44.19%

paper Paper wood-free C B250 Paper 0.0574 0.0186 32.40% 0.0019 3.31% 0.0369 64.29%

paper Paper unbleached B Paper 0.0570 0.0485 85.09% 0.0032 5.56% 0.0053 9.28%

paper Average 0.0713 0.0325 46.71% 0.0037 5.28% 0.0351 48.04%

paper STDEV 0.0132

paper CV 18.50%

Cardboard Kraftliner brown S B250 Kraftliner 0.0190 0.0092 48.63% 0.0012 6.21% 0.0086 45.42%

Cardboard Paper newsprint B250 Newsprint 0.0206 0.0101 49.03% 0.0012 5.73% 0.0093 45.15%

Cardboard Fluting Cardboard 0.0225 0.0103 45.78% 0.0014 6.22% 0.0107 47.56%

Cardboard Cardboard gray Cardboard 0.0254 0.0215 84.65% 0.0015 5.94% 0.0024 9.29%

Cardboard Cardboard liquid Cardboard 0.0289 0.0214 74.05% 0.0019 6.71% 0.0055 19.03%

Cardboard Corrugated board heavy Cardboard 0.0296 0.0258 87.16% 0.0017 5.71% 0.0021 7.13%

Cardboard Wellenstoff Cardboard 0.0300 0.0080 26.60% 0.0012 3.93% 0.0208 69.33%

ResourcesMaterial Cases Total (Pts)


Appendix B9 & B10: Environmental impact of Paper & Cardboard Materials in Damage Categories


ResourcesMaterial Cases Total (Pts)


Cardboard Testliner Cardboard 0.0301 0.0073 24.35% 0.0011 3.49% 0.0217 72.09%

Cardboard Liquid Packaging Board Cardboard 0.0312 0.0149 47.76% 0.0019 5.99% 0.0144 46.15%

Cardboard Cardboard duplex Cardboard 0.0318 0.0270 84.91% 0.0018 5.63% 0.0030 9.31%

Cardboard Kraftliner white top S B250 Kraftliner 0.0322 0.0175 54.35% 0.0020 6.12% 0.0128 39.75%

Cardboard Cardboard cellulose Cardboard 0.0323 0.0267 82.66% 0.0021 6.38% 0.0036 11.02%

Cardboard Schrenz Cardboard 0.0333 0.0070 20.93% 0.0009 2.56% 0.0255 76.58%

Cardboard Sack paper S B250 Cardboard 0.0364 0.0175 48.08% 0.0027 7.45% 0.0161 44.23%

Cardboard Corr. cardboard mix 1 Cardboard 0.0375 0.0111 29.60% 0.0016 4.35% 0.0248 66.13%

Cardboard Corr. cardboard mix 3D Cardboard 0.0395 0.0107 27.09% 0.0016 3.95% 0.0272 68.86%

Cardboard Corr. cardboard mix 2 Cardboard 0.0421 0.0140 33.25% 0.0019 4.51% 0.0263 62.47%

Cardboard Cardboard chromo Cardboard 0.0422 0.0348 82.46% 0.0024 5.69% 0.0051 11.97%

Cardboard Kraftliner brown A B250 Kraftliner 0.0434 0.0162 37.33% 0.0019 4.31% 0.0253 58.29%

Cardboard Cardboard cellulose S B250 Cardboard 0.0451 0.0230 51.00% 0.0026 5.76% 0.0195 43.24%

Cardboard Cardboard duplex/tripl Cardboard 0.0480 0.0113 23.54% 0.0015 3.06% 0.0353 73.54%

Cardboard Corr. cardboard new Cardboard 0.0488 0.0178 36.48% 0.0023 4.67% 0.0287 58.81%

Cardboard Swisskraft Cardboard 0.0495 0.0096 19.35% 0.0009 1.73% 0.0390 78.79%

Cardboard Average 0.0348 0.0162 48.65% 0.0017 5.05% 0.0169 46.27%

Cardboard STDEV 0.0089

Cardboard CV 25.60%

Appendix B11 & B12: Environmental Impact of Polymers in Damage Categories


Rubber, Thermoplastics, Thermoset PP GF30 I Thermosplas 0.2120 0.0404 19.06% 0.0074 3.50% 0.1640 77.36%

Rubber, Thermoplastics, Thermoset PVC suspension A Thermosplas 0.2180 0.0545 25.00% 0.0050 2.30% 0.1590 72.94%

Rubber, Thermoplastics, Thermoset PVC bulk A Thermosplas 0.2190 0.0463 21.14% 0.0044 2.02% 0.1680 76.71%

Rubber, Thermoplastics, Thermoset PVC (e) I Thermosplas 0.2240 0.0770 34.38% 0.0102 4.55% 0.1370 61.16%

Rubber, Thermoplastics, Thermoset PE (LLDPE) I Thermosplas 0.2260 0.0298 13.19% 0.0065 2.85% 0.1900 84.07%

Rubber, Thermoplastics, Thermoset PVC film (calendered) A Thermosplas 0.2440 0.0702 28.77% 0.0060 2.44% 0.1670 68.44%

Rubber, Thermoplastics, Thermoset PE (HDPE) I Thermosplas 0.2500 0.0435 17.40% 0.0069 2.74% 0.2000 80.00%

Rubber, Thermoplastics, Thermoset PVC film (unplasticised) A Thermosplas 0.2510 0.0711 28.33% 0.0063 2.51% 0.1740 69.32%

Rubber, Thermoplastics, Thermoset PET 30% glass fibre I Thermosplas 0.2530 0.0797 31.50% 0.0115 4.55% 0.1620 64.03%

Rubber, Thermoplastics, Thermoset PVC B250 Thermosplas 0.2590 0.0841 32.47% 0.0089 3.45% 0.1660 64.09%

Rubber, Thermoplastics, Thermoset PVC revised P Thermosplas 0.2590 0.0748 28.88% 0.0078 3.02% 0.1770 68.34%

Rubber, Thermoplastics, Thermoset PC 30% glass fibre I Thermosplas 0.2610 0.0868 33.26% 0.0105 4.02% 0.1640 62.84%

Rubber, Thermoplastics, Thermoset PVC emulsion A Thermosplas 0.2750 0.0777 28.25% 0.0075 2.73% 0.1900 69.09%

Rubber, Thermoplastics, Thermoset PE (LDPE) I Thermosplas 0.2800 0.0563 20.11% 0.0089 3.16% 0.2150 76.79%

Rubber, Thermoplastics, Thermoset PVC high impact ETH T Thermosplas 0.2840 0.1000 35.21% 0.0162 5.70% 0.1680 59.15%

Rubber, Thermoplastics, Thermoset PVC injection moulded A Thermosplas 0.2970 0.0784 26.40% 0.0074 2.49% 0.2110 71.04%

Rubber, Thermoplastics, Thermoset PE expanded I Thermosplas 0.2990 0.0611 20.43% 0.0090 3.00% 0.2290 76.59%

Rubber, Thermoplastics, Thermoset PVC film (unplastized) P Thermosplas 0.3010 0.0991 32.92% 0.0097 3.21% 0.1920 63.79%

Rubber, Thermoplastics, Thermoset ABS I Thermosplas 0.3030 0.0672 22.18% 0.0082 2.70% 0.2280 75.25%







Rubber, Thermoplastics, Thermoset HDPE B250 Thermosplas 0.3030 0.0513 16.93% 0.0055 1.81% 0.2460 81.19%

Rubber, Thermoplastics, Thermoset LLDPE B250 Thermosplas 0.3030 0.0380 12.54% 0.0041 1.35% 0.2610 86.14%

Rubber, Thermoplastics, Thermoset PP granulate average B250 Thermosplas 0.3060 0.0572 18.69% 0.0061 2.01% 0.2420 79.08%

Rubber, Thermoplastics, Thermoset LDPE A Thermosplas 0.3160 0.0514 16.27% 0.0050 1.59% 0.2600 82.28%

Rubber, Thermoplastics, Thermoset PP A Thermosplas 0.3190 0.0559 17.52% 0.0055 1.72% 0.2570 80.56%

Rubber, Thermoplastics, Thermoset HDPE A Thermosplas 0.3230 0.0613 18.98% 0.0057 1.77% 0.2560 79.26%

Rubber, Thermoplastics, Thermoset PE granulate average B250 Thermosplas 0.3240 0.0566 17.47% 0.0062 1.91% 0.2610 80.56%

Rubber, Thermoplastics, Thermoset PE P Thermosplas 0.3350 0.0458 13.67% 0.0051 1.51% 0.2840 84.78%

Rubber, Thermoplastics, Thermoset LDPE B250 Thermosplas 0.3370 0.0653 19.38% 0.0069 2.05% 0.2650 78.64%

Rubber, Thermoplastics, Thermoset PET bottle grade I Thermosplas 0.3410 0.1070 31.38% 0.0144 4.22% 0.2190 64.22%

Rubber, Thermoplastics, Thermoset LDPE film A Thermosplas 0.3480 0.0673 19.34% 0.0065 1.85% 0.2750 79.02%

Rubber, Thermoplastics, Thermoset PS (GPPS) I Thermosplas 0.3490 0.0645 18.48% 0.0091 2.59% 0.2760 79.08%

Rubber, Thermoplastics, Thermoset PC I Thermosplas 0.3530 0.1180 33.43% 0.0131 3.71% 0.2220 62.89%

Rubber, Thermoplastics, Thermoset PET granulate amorph B250 Thermosplas 0.3570 0.1010 28.29% 0.0110 3.08% 0.2450 68.63%

Rubber, Thermoplastics, Thermoset PS (EPS) A Thermosplas 0.3590 0.0625 17.41% 0.0062 1.72% 0.2900 80.78%

Rubber, Thermoplastics, Thermoset LDPE revised P Thermosplas 0.3610 0.0633 17.53% 0.0062 1.71% 0.2910 80.61%

Rubber, Thermoplastics, Thermoset PET amorph I Thermosplas 0.3620 0.1580 43.65% 0.0195 5.39% 0.1850 51.10%

Rubber, Thermoplastics, Thermoset PS (HIPS) I Thermosplas 0.3620 0.0679 18.76% 0.0092 2.53% 0.2850 78.73%

Rubber, Thermoplastics, Thermoset HIPS ETH T Thermosplas 0.3650 0.0833 22.82% 0.0148 4.05% 0.2660 72.88%





Rubber, Thermoplastics, Thermoset HDPE pipe P Thermosplas 0.3670 0.0708 19.29% 0.0071 1.93% 0.2890 78.75%

Rubber, Thermoplastics, Thermoset PB B250 (1998) Thermosplas 0.3750 0.0927 24.72% 0.0092 2.46% 0.2730 72.80%

Rubber, Thermoplastics, Thermoset PVDC I Thermosplas 0.3780 0.1950 51.59% 0.0215 5.69% 0.1610 42.59%

Rubber, Thermoplastics, Thermoset SAN A Thermosplas 0.3800 0.0535 14.08% 0.0048 1.26% 0.3210 84.47%

Rubber, Thermoplastics, Thermoset HDPE blow moulded bottles A Thermosplas 0.3900 0.1080 27.69% 0.0090 2.31% 0.2730 70.00%

Rubber, Thermoplastics, Thermoset PET resin P (1997) Thermosplas 0.3940 0.1580 40.10% 0.0163 4.14% 0.2200 55.84%

Rubber, Thermoplastics, Thermoset PP oriented film A Thermosplas 0.4130 0.1070 25.91% 0.0100 2.42% 0.2960 71.67%

Rubber, Thermoplastics, Thermoset PMMA I Thermosplas 0.4340 0.1420 32.72% 0.0151 3.48% 0.2770 63.82%

Rubber, Thermoplastics, Thermoset PS thermoformed A Thermosplas 0.4480 0.0992 22.14% 0.0097 2.17% 0.3390 75.67%

Rubber, Thermoplastics, Thermoset PET ETH T Thermosplas 0.4490 0.1030 22.94% 0.0156 3.47% 0.3300 73.50%

Rubber, Thermoplastics, Thermoset PA 6 GF30 I Thermosplas 0.4700 0.2130 45.32% 0.0157 3.34% 0.2420 51.49%

Rubber, Thermoplastics, Thermoset PA 66 GF30 I Thermosplas 0.4700 0.2130 45.32% 0.0157 3.34% 0.2420 51.49%

Rubber, Thermoplastics, Thermoset PET stretch moulded bottles P Thermosplas 0.4750 0.1720 36.21% 0.0152 3.20% 0.2880 60.63%

Rubber, Thermoplastics, Thermoset PA 6.6 30% glass fibre A Thermosplas 0.4870 0.1660 34.09% 0.0153 3.14% 0.3050 62.63%

Rubber, Thermoplastics, Thermoset PP injection moulded A Thermosplas 0.5000 0.1490 29.80% 0.0153 3.06% 0.3360 67.20%

Rubber, Thermoplastics, Thermoset PA 66 I Thermosplas 0.5010 0.2090 41.72% 0.0179 3.57% 0.2750 54.89%

Rubber, Thermoplastics, Thermoset PET film A Thermosplas 0.5160 0.2070 40.12% 0.0211 4.09% 0.2870 55.62%

Rubber, Thermoplastics, Thermoset PET film packed A Thermosplas 0.5200 0.2090 40.19% 0.0213 4.10% 0.2900 55.77%

Rubber, Thermoplastics, Thermoset PA 6.6 30% glass P Thermosplas 0.5390 0.2130 39.52% 0.0158 2.93% 0.3110 57.70%





Rubber, Thermoplastics, Thermoset PMMA beads A Thermosplas 0.5490 0.1400 25.50% 0.0124 2.26% 0.3970 72.31%

Rubber, Thermoplastics, Thermoset PA 6.6 A Thermosplas 0.5930 0.1720 29.01% 0.0150 2.53% 0.4060 68.47%

Rubber, Thermoplastics, Thermoset PMMA sheet A Thermosplas 0.6330 0.1730 27.33% 0.0154 2.43% 0.4440 70.14%

Rubber, Thermoplastics, Thermoset PA 6 I Thermosplas 0.6570 0.0981 14.93% 0.0145 2.21% 0.5440 82.80%

Rubber, Thermoplastics, Thermoset BR I Rubber 0.2780 0.0547 19.68% 0.0084 3.02% 0.2150 77.34%

Rubber, Thermoplastics, Thermoset SBR I Rubber 0.2960 0.0664 22.43% 0.0091 3.08% 0.2200 74.32%

Rubber, Thermoplastics, Thermoset NBR I Rubber 0.2980 0.0525 17.62% 0.0083 2.77% 0.2370 79.53%

Rubber, Thermoplastics, Thermoset EPDM rubber ETH T Rubber 0.3640 0.1020 28.02% 0.0193 5.30% 0.2430 66.76%

Rubber, Thermoplastics, Thermoset PUR flex. integral skin foam A PUR 0.3950 0.1150 29.11% 0.0089 2.25% 0.2700 68.35%

Rubber, Thermoplastics, Thermoset PUR RIM amine extended A PUR 0.3960 0.1150 29.04% 0.0089 2.25% 0.2720 68.69%

Rubber, Thermoplastics, Thermoset PUR flex. moulded ccm A PUR 0.3970 0.1150 28.97% 0.0089 2.24% 0.2730 68.77%

Rubber, Thermoplastics, Thermoset PUR RIM glycol extended A PUR 0.4010 0.1140 28.43% 0.0090 2.24% 0.2780 69.33%

Rubber, Thermoplastics, Thermoset PUR energy absorbing A PUR 0.4060 0.1130 27.83% 0.0091 2.23% 0.2830 69.70%

Rubber, Thermoplastics, Thermoset PUR flex. moulded ccm/t A PUR 0.4070 0.1210 29.73% 0.0095 2.34% 0.2760 67.81%

Rubber, Thermoplastics, Thermoset PUR flex. moulded cct A PUR 0.4110 0.1240 30.17% 0.0097 2.37% 0.2770 67.40%





Rubber, Thermoplastics, Thermoset PUR flex. moulded hot cure A PUR 0.4110 0.1240 30.17% 0.0097 2.37% 0.2770 67.40%

Rubber, Thermoplastics, Thermoset PUR flexible block foam A PUR 0.4150 0.1250 30.12% 0.0099 2.39% 0.2800 67.47%

Rubber, Thermoplastics, Thermoset PUR hardfoam ETH T PUR 0.4260 0.2300 53.99% 0.0333 7.82% 0.1620 38.03%

Rubber, Thermoplastics, Thermoset PUR flex. block foam I PUR 0.4490 0.2310 51.45% 0.0207 4.61% 0.1980 44.10%

Rubber, Thermoplastics, Thermoset PUR flex. moulded TDI I PUR 0.4520 0.2360 52.21% 0.0208 4.60% 0.1950 43.14%

Rubber, Thermoplastics, Thermoset PUR rigid integr. skin foam I PUR 0.4530 0.2190 48.34% 0.0234 5.17% 0.2110 46.58%

Rubber, Thermoplastics, Thermoset PUR semi rigid foam I PUR 0.4550 0.2440 53.63% 0.0222 4.88% 0.1880 41.32%

Rubber, Thermoplastics, Thermoset PUR flex. moulded MDI/TDI I PUR 0.4570 0.2390 52.30% 0.0212 4.64% 0.1970 43.11%

Rubber, Thermoplastics, Thermoset PUR rigid foam I PUR 0.4640 0.2190 47.20% 0.0235 5.06% 0.2220 47.84%

Rubber, Thermoplastics, Thermoset PUR flex. moulded. MDI I PUR 0.4690 0.2410 51.39% 0.0225 4.80% 0.2050 43.71%

Rubber, Thermoplastics, Thermoset Average 0.3753 0.1139 29.19% 0.0117 3.09% 0.2497 67.71%

Rubber, Thermoplastics, Thermoset STDEV 0.0974

Rubber, Thermoplastics, Thermoset CV 25.94%

Epoxy Epoxy resin (liquid) P Epoxy 0.6420 0.1920 29.91% 0.0174 2.71% 0.4320 67.29%

Epoxy Epoxy resin I Epoxy 0.8730 0.0507 5.81% 0.0100 1.15% 0.8120 93.01%

Epoxy Epoxy resin A Epoxy 0.6390 0.1900 29.73% 0.0175 2.74% 0.4310 67.45%

Epoxy Average 0.7180 0.1442 21.82% 0.0150 2.20% 0.5583 75.92%

Epoxy STDEV 0.1342

Epoxy CV 18.70%

Appendix B13-B16: Environmental Impact of Woods in Damage Categories


Wood Low Impact Silver fir I 5y-10y 0.2340 0.0028 1.18% 0.227 97.01% 0.00447 1.91%

Wood Low Impact Larch, European I 10y-15y 0.2800 0.0211 7.54% 0.231 82.50% 0.0276 9.86%

Wood Low Impact Hemlock I 5y-10y 0.3520 0.0298 8.47% 0.289 82.10% 0.0331 9.40%

Wood Low Impact Pitch pine I 10y-15y 0.3710 0.0217 5.85% 0.331 89.22% 0.0186 5.01%

Wood Low Impact Oregon pine I 10y-15y 0.3880 0.0283 7.29% 0.33 85.05% 0.03 7.73%

Wood Low Impact Teak I >25y 0.4070 0.0529 13.00% 0.306 75.18% 0.0485 11.92%

Wood Low Impact Ash I <5y 0.4080 0.0211 5.17% 0.361 88.48% 0.0253 6.20%

Wood Low Impact Beech, European I <5y 0.4270 0.0203 4.75% 0.38 88.99% 0.0263 6.16%

Wood Low Impact Oak, European I 15y-25y 0.4460 0.0208 4.66% 0.398 89.24% 0.0279 6.26%

Wood Low Impact Spruce, European I 5y-10y 0.4640 0.0072 1.56% 0.446 96.12% 0.0114 2.46%

Wood Low Impact Ahorn I <5y 0.5100 0.0254 4.98% 0.454 89.02% 0.0311 6.10%

Wood Low Impact Scots pine (grenen) I 10y-15y 0.5240 0.0217 4.14% 0.474 90.46% 0.0283 5.40%

Wood Low Impact Sycamore I <5y 0.5640 0.0135 2.39% 0.538 95.39% 0.0124 2.20%

Wood Low Impact Birch I 5y-10y 0.5910 0.0187 3.16% 0.547 92.55% 0.0261 4.42%

Wood Low Impact Merbau I 15y-25y 0.6080 0.0279 4.59% 0.549 90.30% 0.0312 5.13%

Wood Low Impact Chestnut I 15y-25y 0.6280 0.0363 5.78% 0.551 87.74% 0.0408 6.50%

Wood Low Impact Aspen I <5y 0.6360 0.0270 4.25% 0.575 90.41% 0.0337 5.30%

Wood Low Impact Red oak I 5y-10y 0.6400 0.0214 3.34% 0.592 92.50% 0.0268 4.19%

Wood Low Impact Cedar I 15y-25y 0.6430 0.0292 4.54% 0.581 90.36% 0.0331 5.15%

Wood Low Impact Hickory I 5y-10y 0.6510 0.0257 3.95% 0.598 91.86% 0.0273 4.19%







Wood Low Impact Yellow pine I 5y-10y 0.6720 0.0279 4.15% 0.609 90.63% 0.0354 5.27%

Wood Low Impact Robinia I >25y 0.6870 0.0190 2.77% 0.645 93.89% 0.0233 3.39%

Wood Low Impact Linden I <5y 0.6970 0.0212 3.04% 0.649 93.11% 0.0266 3.82%

Wood Low Impact Alder I <5y 0.7040 0.0254 3.61% 0.647 91.90% 0.0314 4.46%

Wood Low Impact Elm I 5y-10y 0.7420 0.0154 2.08% 0.705 95.01% 0.0211 2.84%

Wood Low Impact Poplar I <5y 0.7620 0.0056 0.74% 0.749 98.29% 0.00685 0.90%

Wood Low Impact Red Cedar, Western I 15y-25y 0.7710 0.0666 8.64% 0.639 82.88% 0.066 8.56%

Wood Low Impact Hornbean I <5y 0.7900 0.0166 2.10% 0.752 95.19% 0.0213 2.70%

Wood Low Impact Black poplar I <5y 0.8160 0.0271 3.32% 0.755 92.52% 0.0339 4.15%

Wood Low Impact Average 0.5660 0.0241 4.52% 0.5141 90.27% 0.0279 5.23%

Wood Low Impact STDEV 0.1607

Wood Low Impact CV 28.39%

Wood Low-Med. Impact Walnut I 10y-15y 0.9540 0.0230 2.41% 0.9030 94.65% 0.0281 2.95%

Wood Low-Med. Impact Platan I <5y 1.1500 0.0186 1.62% 1.1100 96.52% 0.0245 2.13%

Wood Low-Med. Impact Horse chestnut I <5y 1.2200 0.0229 1.88% 1.1600 95.08% 0.0298 2.44%

Wood Low-Med. Impact Willow I <5y 1.4700 0.0314 2.14% 1.4000 95.24% 0.0424 2.88%

Wood Low-Med. Impact Average 1.1985 0.0240 2.01% 1.1433 95.37% 0.0312 2.60%

Wood Low-Med. Impact STDEV 0.2132

Wood Low-Med. Impact CV 17.79%

Wood Med.-High Impact Azobe I 15y-25y 2.7900 0.0277 0.99% 2.7300 97.85% 0.0294 1.05%





Wood Med.-High Impact Moabi I >25y 3.5600 0.0381 1.07% 3.4900 98.03% 0.038 1.07%

Wood Med.-High Impact Blue gum I <5y 3.7200 0.0483 1.30% 3.6300 97.58% 0.0455 1.22%

Wood Med.-High Impact Angelique I 15y-25y 4.7300 0.0259 0.55% 4.6700 98.73% 0.0323 0.68%

Wood Med.-High Impact Makore I >25y 4.8300 0.0400 0.83% 4.7500 98.34% 0.0407 0.84%

Wood Med.-High Impact Kauri I 10y-15y 5.1800 0.0391 0.75% 5.1000 98.46% 0.0417 0.81%

Wood Med.-High Impact Mersawa I 5y-10y 5.1900 0.0284 0.55% 5.1300 98.84% 0.0329 0.63%

Wood Med.-High Impact Yang I 10y-15y 5.2100 0.0273 0.52% 5.1500 98.85% 0.031 0.60%

Wood Med.-High Impact Agba I 15y-25y 5.2300 0.0497 0.95% 5.1300 98.09% 0.0499 0.95%

Wood Med.-High Impact Limba I 5y-10y 5.2500 0.0346 0.66% 5.1800 98.67% 0.035 0.67%

Wood Med.-High Impact Bubinga I 15y-25y 5.6100 0.0395 0.70% 5.5300 98.57% 0.0393 0.70%

Wood Med.-High Impact Mahogani, African I 10y-15y 5.8600 0.0416 0.71% 5.7800 98.63% 0.0419 0.72%

Wood Med.-High Impact Iroko I >25y 5.9100 0.0528 0.89% 5.8100 98.31% 0.0513 0.87%

Wood Med.-High Impact Meranti I 15y-25y 5.9400 0.0546 0.92% 5.8400 98.32% 0.053 0.89%

Wood Med.-High Impact Utile I 15y-25y 5.9600 0.039 0.65% 5.8800 98.66% 0.0391 0.66%

Wood Med.-High Impact Dibetou I 10y-15y 6.0200 0.0412 0.68% 5.9400 98.67% 0.0413 0.69%

Wood Med.-High Impact Afzelia I >25y 6.1000 0.0391 0.64% 6.0200 98.69% 0.0395 0.65%

Wood Med.-High Impact Sapelli I 10y-15y 6.2300 0.0394 0.63% 6.1500 98.72% 0.0393 0.63%

Wood Med.-High Impact Movigui I 10y-15y 6.2500 0.0348 0.56% 6.1800 98.88% 0.0353 0.56%

Wood Med.-High Impact Afrormosia I >25y 6.2800 0.047 0.75% 6.1800 98.41% 0.0461 0.73%

Wood Med.-High Impact Idigbo I 15y-25y 6.3800 0.0436 0.68% 6.2900 98.59% 0.0443 0.69%





Wood Med.-High Impact Kotibe I 10y-15y 6.4400 0.0366 0.57% 6.3700 98.91% 0.0365 0.57%

Wood Med.-High Impact Mengkulang I 5y-10y 6.4600 0.0296 0.46% 6.3900 98.92% 0.0348 0.54%

Wood Med.-High Impact Peroba I 10y-15y 6.5400 0.0308 0.47% 6.4800 99.08% 0.0353 0.54%

Wood Med.-High Impact Bosse clair I 15y-25y 6.7500 0.0417 0.62% 6.6700 98.81% 0.0417 0.62%

Wood Med.-High Impact Average 5.5368 0.0388 0.72% 5.4588 98.54% 0.0398 0.74%

Wood Med.-High Impact STDEV 0.9995

Wood Med.-High Impact CV 18.05%

Wood High Impact Carapa I 10y-15y 7.2400 0.0292 0.40% 7.1800 99.17% 0.0309 0.43%

Wood High Impact Paranapine I 5y-10y 7.2500 0.0257 0.35% 7.2000 99.31% 0.0281 0.39%

Wood High Impact Purpleheart I 15y-25y 7.5000 0.0263 0.35% 7.4400 99.20% 0.0328 0.44%

Wood High Impact Mansonia I >25y 7.5400 0.0462 0.61% 7.4500 98.81% 0.0455 0.60%

Wood High Impact Mahogany, American I 15y-25y 7.6300 0.0274 0.36% 7.5800 99.34% 0.0291 0.38%

Wood High Impact Padouk, African I >25y 8.0400 0.0424 0.53% 7.9600 99.00% 0.0423 0.53%

Wood High Impact Tiama I 10y-15y 8.1900 0.0455 0.56% 8.1000 98.90% 0.0456 0.56%

Wood High Impact Niangon I 10y-15y 8.3300 0.0389 0.47% 8.2500 99.04% 0.0389 0.47%

Wood High Impact Aningre I 5y-10y 8.4200 0.0430 0.51% 8.3400 99.05% 0.0431 0.51%

Wood High Impact Mutenye I 10y-15y 8.5400 0.0462 0.54% 8.4500 98.95% 0.0449 0.53%

Wood High Impact Wawa I <5y 8.7900 0.0481 0.55% 8.6900 98.86% 0.0489 0.56%

Wood High Impact Tchitola I 10y-15y 8.8500 0.0415 0.47% 8.7700 99.10% 0.0416 0.47%

Wood High Impact Koto I <5y 9.2200 0.0513 0.56% 9.1200 98.92% 0.0512 0.56%





Wood High Impact Canaria I <5y 9.4100 0.0497 0.53% 9.3100 98.94% 0.0499 0.53%

Wood High Impact Palissander, Indisch I >25y 9.4900 0.0268 0.28% 9.4400 99.47% 0.0295 0.31%

Wood High Impact Abura I <5y 9.5900 0.0493 0.51% 9.5000 99.06% 0.0487 0.51%

Wood High Impact Ilomba I 15y-25y 10.4000 0.0530 0.51% 10.3000 99.04% 0.0532 0.51%

Wood High Impact Antiaris I <5y 10.6000 0.0489 0.46% 10.5000 99.06% 0.0492 0.46%

Wood High Impact Okoume I 5y-10y 10.7000 0.0423 0.40% 10.6000 99.07% 0.0424 0.40%

Wood High Impact Baboen I <5y 11.0000 0.0294 0.27% 10.9000 99.09% 0.0339 0.31%

Wood High Impact Olon I 10y-15y 11.3000 0.0453 0.40% 11.2000 99.12% 0.0455 0.40%

Wood High Impact Cottonwood I <5y 11.6000 0.0322 0.28% 11.5000 99.14% 0.0451 0.39%

Wood High Impact Wenge I 15y-25y 11.8000 0.0283 0.24% 11.7000 99.15% 0.0315 0.27%

Wood High Impact Emeri I 5y-10y 12.4000 0.0353 0.28% 12.3000 99.19% 0.0491 0.40%

Wood High Impact Average 9.3263 0.0397 0.43% 9.2408 99.08% 0.0417 0.45%

Wood High Impact STDEV 1.5627

Wood High Impact CV 16.76%

Appendix C1 & C2: Environmental Impact of Glass and Ceramic Materials in Impact Categories

Name Group

Ceramics I Ceramic 0.0194 8.9E-07 1.4E-06 2.3E-03 1.1E-03 0 2.3E-10 4.4E-07 3.2E-04 5.8E-03 2.7E-08 9.9E-03

Ceramic (fine) Ceramic 0.0238 0 9.5E-05 3.6E-03 3.4E-03 0 0 2.1E-06 6.1E-04 0 0 1.6E-02

Stoneware I Ceramic 0.0269 3.3E-06 2.5E-06 4.0E-03 1.6E-03 0 9.2E-10 3.6E-06 6.6E-04 6.1E-03 6.1E-08 1.5E-02

Ceramics ETH T Ceramic 0.0280 2.6E-04 5.3E-06 4.4E-03 2.0E-03 8.5E-06 1.3E-06 9.9E-05 5.4E-04 3.6E-04 1.6E-05 2.0E-02

Porcelain I Ceramic 0.0384 1.6E-05 8.3E-06 9.1E-03 2.0E-03 0 4.5E-09 9.3E-06 1.4E-03 7.3E-03 2.4E-07 1.9E-02

0.0273 5.6E-05 2.2E-05 4.7E-03 2.0E-03 1.7E-06 2.7E-07 2.3E-05 7.0E-04 3.9E-03 3.2E-06 1.6E-02

0.20% 0.08% 17.05% 7.44% 0.01% 0.00% 0.08% 2.58% 14.30% 0.01% 58.28%

Glass (brown) B250 Glass 0.0495 6.6E-04 5.6E-05 1.1E-02 4.3E-03 0 1.5E-05 2.7E-03 1.2E-03 0 2.9E-09 2.9E-02

Glass (green) B250 Glass 0.0505 5.6E-04 4.6E-05 1.0E-02 3.3E-03 0 1.3E-05 7.4E-03 1.4E-03 0 0 2.8E-02

Glass (white) B250 Glass 0.0571 6.4E-04 5.5E-05 1.3E-02 4.2E-03 0 1.4E-05 9.2E-03 1.3E-03 0 3.4E-09 2.9E-02

Glass oil-fired bj Glass 0.0579 0 0 3.2E-02 3.3E-03 0 0 0 3.9E-03 0 0 1.8E-02

Glass gas-fired bj Glass 0.0603 0 0 3.4E-02 1.4E-03 0 0 0 5.6E-03 0 0 1.9E-02

Glass (virgin) Glass 0.0652 7.3E-04 6.6E-05 1.7E-02 5.3E-03 0 1.6E-05 1.2E-02 1.2E-03 0 7.6E-09 3.0E-02

0.0568 4.3E-04 3.7E-05 2.0E-02 3.6E-03 0 9.6E-06 5.1E-03 2.4E-03 0 2.3E-09 2.6E-02

0.76% 0.07% 34.48% 6.36% 0.00% 0.02% 9.05% 4.28% 0.00% 0.00% 45.08%

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)

Material Cases Total (Pts)

Carcinogens (Pts)

Resp. organics

(Pts)

Contibution to total (%)

Fossil fuels (Pts)

Average


Average

Ecotoxi- city (Pts)

Acidification/ Eutrophication

(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Appendix C3-C5: Environmental Impact of Ferrous Materials in Impact Categories

Group Name

No Ni ferro Steel bj 0.0528 0.0002 1.00E-03 0.0129 0.0059 x 2.58E-07 4.92E-05 1.33E-03 0.0002 0.0009 0.0304

No Ni ferro Iron 0.0574 0.0001 1.15E-03 0.0125 0.0062 x 1.42E-07 2.77E-05 1.36E-03 0.0001 0.0010 0.0349

No Ni ferro GS-70 I 0.0621 0.0015 3.75E-05 0.0235 0.0054 x 9.39E-08 0.0030 3.00E-03 0.0055 0.0011 0.0191

No Ni ferro St13 I 0.0629 0.0016 3.82E-05 0.0239 0.0055 x 9.61E-08 0.0030 3.06E-03 0.0056 0.0011 0.0191

No Ni ferro Fe520 I 0.0629 0.0016 3.82E-05 0.0239 0.0055 x 9.61E-08 0.0030 3.06E-03 0.0056 0.0011 0.0191



No Ni ferro St14 I 0.0629 0.0016 3.82E-05 0.0239 0.0055 x 9.61E-08 0.0030 3.06E-03 0.0056 0.0011 0.0191

No Ni ferro S355J2G1W I 0.0629 0.0016 3.82E-05 0.0239 0.0055 x 9.61E-08 0.0030 3.06E-03 0.0056 0.0011 0.0191

No Ni ferro Steel I 0.0644 0.0017 4.02E-05 0.0249 0.0056 x 1.02E-07 0.0032 3.19E-03 0.0059 0.0011 0.0187

No Ni ferro ASt35 (1.0346) I 0.0660 0.0017 4.02E-05 0.0252 0.0057 x 1.01E-07 0.0032 3.22E-03 0.0059 0.0012 0.0199

No Ni ferro C15 I 0.0661 0.0017 4.02E-05 0.0252 0.0057 x 1.01E-07 0.0032 3.22E-03 0.0059 0.0012 0.0200



No Ni ferro 35S20 (1.0726) I 0.0669 0.0017 4.04E-05 0.0253 0.0058 x 1.01E-07 0.0032 3.24E-03 0.0059 0.0012 0.0205

No Ni ferro GGG40 I 0.0671 0.0002 1.79E-05 0.0107 0.0024 x 3.37E-08 0.0013 1.48E-03 0.0025 0.0384 0.0102


No Ni ferro 10SPb20 (1.0721) I 0.0675 0.0017 4.02E-05 0.0253 0.0058 x 1.01E-07 0.0032 3.23E-03 0.0059 0.0018 0.0205


Carcinogens (Pts)

Resp. organics

(Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)

Fossil fuels (Pts)

Ecotoxi- city

(Pts)

Acidification/ Eutrophi-

cation (Pts)

Land use (Pts)


Group Name


Carcinogens (Pts)

Resp. organics

(Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)

Fossil fuels (Pts)

Ecotoxi- city

(Pts)


cation (Pts)

Land use (Pts)

No Ni ferro 9SMnPb (1.0718) I 0.0682 0.0017 4.02E-05 0.0254 0.0058 x 1.01E-07 0.0032 3.23E-03 0.0059 0.0020 0.0210


No Ni ferro 38Si6 I 0.0689 0.0016 4.03E-05 0.0258 0.0061 x 9.99E-08 0.0032 3.29E-03 0.0059 0.0012 0.0219

No Ni ferro 15Cr3 I 0.0694 0.0017 4.04E-05 0.0258 0.0062 x 1.03E-07 0.0032 3.29E-03 0.0059 0.0013 0.0221

No Ni ferro 67SiCr5 I 0.0694 0.0017 4.04E-05 0.0259 0.0062 x 1.02E-07 0.0032 3.31E-03 0.0059 0.0012 0.0220

No Ni ferro Crude iron I 0.0695 0.0006 4.39E-05 0.0271 0.0058 x 1.05E-07 0.0025 3.64E-03 0.0067 0.0013 0.0218

No Ni ferro GS-45.3 I 0.0697 0.0016 4.03E-05 0.0257 0.0061 x 9.96E-08 0.0032 3.27E-03 0.0059 0.0013 0.0227

No Ni ferro 55Si7 I 0.0698 0.0016 4.03E-05 0.0259 0.0062 x 9.95E-08 0.0032 3.30E-03 0.0059 0.0012 0.0225

No Ni ferro 37MnSi5 I 0.0701 0.0016 4.03E-05 0.0259 0.0062 x 9.94E-08 0.0032 3.30E-03 0.0059 0.0012 0.0228

No Ni ferro 42MnV7 I 0.0706 0.0016 4.04E-05 0.0258 0.0062 x 9.99E-08 0.0032 3.29E-03 0.0061 0.0013 0.0231

No Ni ferro 42CrMo4 I 0.0717 0.0017 4.06E-05 0.0262 0.0064 x 1.03E-07 0.0032 3.33E-03 0.0060 0.0014 0.0235

No Ni ferro 34Cr4 I 0.0724 0.0016 4.06E-05 0.0264 0.0065 x 1.03E-07 0.0032 3.36E-03 0.0060 0.0014 0.0239

No Ni ferro 50 CrV4 I 0.0730 0.0017 4.06E-05 0.0264 0.0066 x 1.03E-07 0.0032 3.36E-03 0.0062 0.0014 0.0242

No Ni ferro GS-22Mo4 I 0.0744 0.0017 4.04E-05 0.0259 0.0062 x 1.02E-07 0.0032 3.30E-03 0.0083 0.0034 0.0225

No Ni ferro 50CrV4 I 0.0752 0.0016 4.07E-05 0.0268 0.0068 x 1.03E-07 0.0032 3.40E-03 0.0063 0.0014 0.0257

No Ni ferro A517b I 0.0759 0.0016 4.05E-05 0.0261 0.0064 x 1.02E-07 0.0032 3.32E-03 0.0083 0.0035 0.0235

No Ni ferro 22Mo4 I 0.0759 0.0017 4.03E-05 0.0255 0.0060 x 1.01E-07 0.0032 3.26E-03 0.0100 0.0049 0.0214

No Ni ferro A514(A) I 0.0765 0.0017 4.05E-05 0.0260 0.0063 x 1.02E-07 0.0032 3.31E-03 0.0088 0.0039 0.0233


Group Name


Carcinogens (Pts)

Resp. organics

(Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)

Fossil fuels (Pts)

Ecotoxi- city

(Pts)


cation (Pts)

Land use (Pts)

No Ni ferro 9S20 I 0.0767 0.0016 3.98E-05 0.0266 0.0059 x 9.81E-08 0.0031 3.28E-03 0.0060 0.0086 0.0216

No Ni ferro 25CrMo4 I 0.0780 0.0017 4.06E-05 0.0263 0.0065 x 1.04E-07 0.0032 3.35E-03 0.0089 0.0041 0.0240

No Ni ferro A517a I 0.0784 0.0016 4.05E-05 0.0262 0.0065 x 1.02E-07 0.0032 3.34E-03 0.0092 0.0043 0.0240

No Ni ferro 34CrAl6 I 0.0788 0.0020 4.10E-05 0.0279 0.0073 x 2.17E-07 0.0032 3.47E-03 0.0062 0.0019 0.0269

No Ni ferro 13CrMo4 5 (1.7335) I 0.0836 0.0017 4.06E-05 0.0263 0.0065 x 1.03E-07 0.0032 3.35E-03 0.0118 0.0067 0.0240

No Ni ferro Tin plate bj 0.0858 0.0031 1.02E-03 0.0225 0.0103 x 3.86E-06 0.0007 2.44E-03 0.0024 0.0009 0.0424


No Ni ferro Steel ETH T 0.0866 0.0220 4.33E-05 0.0156 0.0098 4.63E-05 1.24E-05 0.0140 1.54E-03 0.0018 0.0015 0.0202

No Ni ferro X30Cr13 (~420) I 0.0871 0.0012 3.16E-05 0.0235 0.0075 x 1.04E-07 0.0022 2.95E-03 0.0049 0.0133 0.0314

No Ni ferro 21MoV53 I 0.0872 0.0016 4.09E-05 0.0271 0.0069 x 1.02E-07 0.0032 3.43E-03 0.0125 0.0066 0.0258

No Ni ferro X12Cr13 (416) I 0.0876 0.0012 3.16E-05 0.0236 0.0075 x 1.04E-07 0.0022 2.96E-03 0.0049 0.0134 0.0318

No Ni ferro X7CrAl13 (405) I 0.0880 0.0013 3.16E-05 0.0238 0.0076 x 1.24E-07 0.0022 2.97E-03 0.0050 0.0134 0.0318


No Ni ferro Crude iron ETH T 0.0927 0.0267 5.08E-05 0.0169 0.0112 2.12E-05 1.20E-05 0.0109 1.72E-03 0.0015 0.0020 0.0217

No Ni ferro Converter steel ETH T 0.0947 0.0264 4.89E-05 0.0155 0.0108 2.10E-05 1.24E-05 0.0158 1.57E-03 0.0014 0.0018 0.0214

No Ni ferro ECCS steel sheet 0.0988 0.0168 3.72E-05 0.0233 0.0174 x 6.79E-06 0.0030 2.53E-03 x 0.0017 0.0340


No Ni ferro X90CrCoMoV17 I 0.1070 0.0012 3.16E-05 0.0253 0.0087 x 1.10E-07 0.0021 3.15E-03 0.0100 0.0183 0.0379


Group Name


Carcinogens (Pts)

Resp. organics

(Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)

Fossil fuels (Pts)

Ecotoxi- city

(Pts)


cation (Pts)

Land use (Pts)

No Ni ferro Steel low alloy ETH T 0.1080 0.0259 5.40E-05 0.0209 0.0121 5.55E-05 1.63E-05 0.0154 1.91E-03 0.0022 0.0024 0.0271

No Ni ferro X10Cr13 (mart 410) I 0.1270 0.0012 3.80E-05 0.0324 0.0115 x 1.04E-07 0.0024 4.00E-03 0.0056 0.0139 0.0564

No Ni ferro X90CrMoV18 (440B) I 0.1350 0.0012 3.67E-05 0.0332 0.0134 x 1.13E-07 0.0021 4.08E-03 0.0058 0.0142 0.0608

0.0772 0.0034 0.0001 0.0239 0.0069 3.60E-05 1.21E-06 0.0035 0.0030 0.0058 0.0059 0.0248

4.38% 0.12% 31.01% 8.95% 1.06% 0.00% 4.56% 3.86% 7.53% 7.59% 32.14%

Low Ni Ferro X35CrMo17 I 0.1140 0.0012 3.18E-05 0.0251 0.0086 x 1.10E-07 0.0021 0.0031 0.0144 0.0225 0.0369

Low Ni Ferro 28NiCrMo4 I 0.1160 0.0017 4.13E-05 0.0531 0.0075 x 1.05E-07 0.0032 0.0050 0.0088 0.0105 0.0262

Low Ni Ferro GX12Cr14 (CA15) I 0.1160 0.0012 3.23E-05 0.0427 0.0085 x 1.07E-07 0.0022 0.0042 0.0049 0.0179 0.0347

Low Ni Ferro 15NiMn6 (1.6228) I 0.1210 0.0017 4.20E-05 0.0604 0.0078 x 1.08E-07 0.0032 0.0054 0.0060 0.0095 0.0274

Low Ni Ferro GS-10Ni6 I 0.1250 0.0017 4.17E-05 0.0635 0.0078 x 1.08E-07 0.0032 0.0056 0.0059 0.0103 0.0268

Low Ni Ferro 36NiCr6 I 0.1250 0.0017 4.18E-05 0.0618 0.0082 x 1.08E-07 0.0031 0.0055 0.0059 0.0099 0.0291

Low Ni Ferro X22CrNi17 (431) I 0.1490 0.0012 3.31E-05 0.0606 0.0102 x 1.16E-07 0.0021 0.0053 0.0050 0.0225 0.0423


Low Ni Ferro 30CrNiMo8 I 0.1620 0.0016 4.28E-05 0.0756 0.0100 x 1.13E-07 0.0031 0.0065 0.0107 0.0174 0.0374



0.1481 0.0015 3.99E-05 0.0695 0.0093 0 1.11E-07 0.0029 0.0060 0.0072 0.0166 0.0351

1.03% 0.03% 46.91% 6.31% 0.00% 0.00% 1.92% 4.05% 4.88% 11.21% 23.71%Contibution to total (%)

Average


Average


Group Name


Carcinogens (Pts)

Resp. organics

(Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)

Fossil fuels (Pts)

Ecotoxi- city

(Pts)


cation (Pts)

Land use (Pts)

High Ni Ferro GGL-NiCuCr I 0.3340 0.0002 2.59E-05 0.2010 0.0139 x 6.30E-08 0.0011 0.0135 0.0027 0.0483 0.0527

High Ni Ferro X10CrNiS (303) I 0.3690 0.0011 3.81E-05 0.1990 0.0186 x 1.39E-07 0.0019 0.0140 0.0049 0.0558 0.0740

High Ni Ferro GX5CrNi19 10 (CF8) I 0.3990 0.0011 3.88E-05 0.2180 0.0199 x 1.44E-07 0.0018 0.0152 0.0049 0.0605 0.0780

High Ni Ferro X6CrNi18 (~304) I 0.4010 0.0011 3.88E-05 0.2180 0.0200 x 1.44E-07 0.0018 0.0152 0.0049 0.0605 0.0790

High Ni Ferro X5CrNi18 (304) I 0.4010 0.0011 3.88E-05 0.2180 0.0200 x 1.44E-07 0.0018 0.0152 0.0049 0.0605 0.0790

High Ni Ferro X8Ni9 I 0.4070 0.0016 4.86E-05 0.2420 0.0184 x 1.33E-07 0.0029 0.0168 0.0059 0.0529 0.0657

High Ni Ferro GGG-NiCr I 0.4150 0.0003 2.88E-05 0.2540 0.0171 x 7.31E-08 0.0011 0.0168 0.0027 0.0590 0.0643

High Ni Ferro GGG-NiSiCr I 0.4530 0.0002 2.78E-05 0.2540 0.0174 x 7.21E-08 0.0011 0.0168 0.0024 0.0962 0.0653

High Ni Ferro X2CrNiMo1712 (316L) I 0.4670 0.0011 3.92E-05 0.2200 0.0213 x 1.41E-07 0.0017 0.0155 0.0343 0.0872 0.0861

High Ni Ferro X5CrNiMo18 (316) I 0.4780 0.0011 4.04E-05 0.2350 0.0220 x 1.48E-07 0.0018 0.0164 0.0285 0.0855 0.0877

High Ni Ferro X12CrNi 18 9 I 0.5020 0.0014 5.47E-05 0.2600 0.0300 x 1.73E-07 0.0023 0.0188 0.0067 0.0572 0.1260

High Ni Ferro X10CrNiMoNb I 0.6020 0.0010 4.94E-05 0.2870 0.0321 x 1.49E-07 0.0017 0.0205 0.0308 0.0935 0.1350

High Ni Ferro GS-X40CrNiSi 25 12 I 0.6620 0.0013 5.97E-05 0.3390 0.0386 x 2.01E-07 0.0020 0.0241 0.0129 0.0814 0.1630

0.4531 0.0010 4.07E-05 0.2419 0.0223 0 1.33E-07 0.0018 0.0168 0.0113 0.0691 0.0889

0.22% 0.01% 53.40% 4.91% 0.00% 0.00% 0.39% 3.71% 2.49% 15.25% 19.62%

Average


Appendix C6-C8:Environmental Impact of Non-ferrous Materials in Impact Categories

Group Name

Al, Mg, Zn, Mn & their alloys Manganese ETH T 0.2500 0.0193 0.0001 0.0797 0.0294 0.0007 6.35E-05 0.0044 0.0068 0.0221 0.0086 0.0786

Al, Mg, Zn, Mn & their alloys Silicon I 0.2580 0.0000 0.0000 0.0683 0.0297 x 1.12E-08 0.0010 0.0087 0.0043 0.0000 0.1460

Al, Mg, Zn, Mn & their alloys Ferrochromium I 0.2740 0.0008 0.0000 0.0537 0.0310 x 3.33E-07 0.0001 0.0064 0.0057 0.0240 0.1520

Al, Mg, Zn, Mn & their alloys Zamak3 I 0.3760 0.0121 0.0001 0.0874 0.0205 x 4.74E-06 0.0223 0.0088 0.0103 0.1190 0.0962

Al, Mg, Zn, Mn & their alloys Zamak5 I 0.3910 0.0119 0.0001 0.0941 0.0206 x 4.69E-06 0.0220 0.0092 0.0108 0.1250 0.0973

Al, Mg, Zn, Mn & their alloys ZnCuTi I 0.3960 0.0112 0.0001 0.0949 0.0209 x 4.45E-06 0.0226 0.0094 0.0104 0.1260 0.1010

Al, Mg, Zn, Mn & their alloys Zinc (super plastic) I 0.4020 0.0147 0.0001 0.0957 0.0266 x 5.62E-06 0.0186 0.0090 0.0120 0.1110 0.1150

Al, Mg, Zn, Mn & their alloys G-ZnAlCu I 0.4190 0.0117 0.0001 0.1070 0.0208 x 4.61E-06 0.0216 0.0100 0.0117 0.1360 0.0996

Al, Mg, Zn, Mn & their alloys Lead I 0.4230 0.0000 0.0000 0.0731 0.0108 x x 0.0010 0.0055 0.0078 0.2660 0.0591

Al, Mg, Zn, Mn & their alloys Zinc I 0.4350 0.0153 0.0001 0.1140 0.0255 x 6.06E-06 0.0307 0.0116 0.0129 0.1020 0.1230

Al, Mg, Zn, Mn & their alloys G-AlSi12 (230) I 0.5240 0.0252 0.0001 0.1450 0.0556 x 9.01E-06 0.0031 0.0113 0.0253 0.0446 0.2140

Al, Mg, Zn, Mn & their alloys Aluminium raw bj 0.5300 0.0001 0.0007 0.3330 0.0521 x 2.79E-08 0.0000 0.0237 0.0000 0.0573 0.0626

Al, Mg, Zn, Mn & their alloys G-AlSi12Cu (231) I 0.5310 0.0248 0.0001 0.1490 0.0553 x 8.87E-06 0.0031 0.0115 0.0255 0.0485 0.2130

Al, Mg, Zn, Mn & their alloys G-AlSi7Mg (Thixo) I 0.5370 0.0271 0.0001 0.1480 0.0581 x 9.71E-06 0.0033 0.0113 0.0262 0.0430 0.2200

Al, Mg, Zn, Mn & their alloys AlMg3 (5754a) I 0.5450 0.0275 0.0001 0.1510 0.0598 x 9.86E-06 0.0033 0.0116 0.0263 0.0431 0.2220

Al, Mg, Zn, Mn & their alloys AlSiMgMn (6009) I 0.5590 0.0291 0.0001 0.1540 0.0606 x 1.04E-05 0.0034 0.0116 0.0273 0.0450 0.2280

Al, Mg, Zn, Mn & their alloys AlMn1.2Mg1 (3004) I 0.5600 0.0290 0.0001 0.1540 0.0609 x 1.04E-05 0.0034 0.0117 0.0273 0.0450 0.2290

Al, Mg, Zn, Mn & their alloys AlMgSi0.7 (6005) I 0.5610 0.0294 0.0001 0.1550 0.0610 x 1.05E-05 0.0035 0.0117 0.0275 0.0453 0.2280

Al, Mg, Zn, Mn & their alloys AlMn1 (3003) I 0.5610 0.0295 0.0001 0.1540 0.0606 x 1.06E-05 0.0035 0.0115 0.0276 0.0455 0.2280

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)


Group Name

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Al, Mg, Zn, Mn & their alloys G-AlMg3 (242) I 0.5610 0.0283 0.0001 0.1560 0.0614 x 1.02E-05 0.0034 0.0119 0.0270 0.0446 0.2280

Al, Mg, Zn, Mn & their alloys Al99 I 0.5640 0.0298 0.0001 0.1550 0.0611 x 1.07E-05 0.0035 0.0116 0.0278 0.0459 0.2290

Al, Mg, Zn, Mn & their alloys AlMg1 (5005) I 0.5640 0.0295 0.0001 0.1560 0.0614 x 1.06E-05 0.0035 0.0117 0.0276 0.0454 0.2290

Al, Mg, Zn, Mn & their alloys AlMg4.5Mn (5182) I 0.5640 0.0281 0.0001 0.1570 0.0623 x 1.01E-05 0.0034 0.0121 0.0268 0.0437 0.2310

Al, Mg, Zn, Mn & their alloys Aluminium ingots B250 0.5650 0.0310 0.0004 0.1760 0.0583 x 9.81E-05 0.0104 0.0116 x 0.0441 0.2340

Al, Mg, Zn, Mn & their alloys Chromium I 0.5680 0.0008 0.0001 0.1170 0.0676 x 3.33E-07 0.0001 0.0139 0.0107 0.0240 0.3330

Al, Mg, Zn, Mn & their alloys AlZnCuMg (7075) I 0.5770 0.0267 0.0001 0.1650 0.0582 x 9.59E-06 0.0048 0.0126 0.0270 0.0609 0.2220

Al, Mg, Zn, Mn & their alloys G-AlSi8Cu3 (380) I 0.5780 0.0252 0.0001 0.1690 0.0557 x 9.05E-06 0.0034 0.0127 0.0271 0.0679 0.2160

Al, Mg, Zn, Mn & their alloys Cadmium I 0.5930 0.0153 0.0001 0.1380 0.0276 x 6.08E-06 0.0040 0.0151 0.2520 0.0001 0.1420

Al, Mg, Zn, Mn & their alloys Aluminium foil B250 0.5980 0.0326 0.0004 0.1810 0.0616 x 1.01E-04 0.0111 0.0122 x 0.0441 0.2550

Al, Mg, Zn, Mn & their alloys AlMgSi0.5 (6060) I 0.6040 0.0295 0.0001 0.1680 0.0669 x 1.06E-05 0.0036 0.0132 0.0280 0.0454 0.2490

Al, Mg, Zn, Mn & their alloys AlCuSiMg (2036) I 0.6060 0.0286 0.0001 0.1760 0.0600 x 1.03E-05 0.0034 0.0129 0.0289 0.0676 0.2290

Al, Mg, Zn, Mn & their alloys G-AlMg5 (314) I 0.6120 0.0266 0.0001 0.1810 0.0611 x 9.52E-06 0.0032 0.0137 0.0279 0.0686 0.2300

Al, Mg, Zn, Mn & their alloys AlCuMg1 (2017) I 0.6290 0.0278 0.0001 0.1880 0.0596 x 9.95E-06 0.0033 0.0137 0.0293 0.0790 0.2290

Al, Mg, Zn, Mn & their alloys AlCuMg2 (2024) I 0.6390 0.0275 0.0001 0.1920 0.0600 x 9.86E-06 0.0033 0.0141 0.0295 0.0823 0.2300

Al, Mg, Zn, Mn & their alloys G-AlCu4TiMg (204) I 0.6400 0.0280 0.0001 0.1920 0.0595 x 1.00E-05 0.0033 0.0140 0.0298 0.0837 0.2290

Al, Mg, Zn, Mn & their alloys AlCuMgPb (2011) I 0.6490 0.0275 0.0001 0.1920 0.0599 x 9.86E-06 0.0033 0.0141 0.0296 0.0911 0.2310

Al, Mg, Zn, Mn & their alloys MgZn6Zr I 0.6560 0.0009 0.0000 0.2240 0.0977 x 3.33E-07 0.0028 0.0247 0.0051 0.0056 0.2950

Al, Mg, Zn, Mn & their alloys G-MgAl6Zn3 I 0.6590 0.0026 0.0000 0.2240 0.0977 x 9.36E-07 0.0022 0.0243 0.0061 0.0057 0.2970


Group Name

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)


Al, Mg, Zn, Mn & their alloys GD-MgAl9Zn1 I 0.6630 0.0033 0.0000 0.2250 0.0985 x 1.17E-06 0.0016 0.0242 0.0065 0.0047 0.3000


Al, Mg, Zn, Mn & their alloys MgAl6Zn I 0.6640 0.0025 0.0000 0.2260 0.0990 x 8.77E-07 0.0017 0.0245 0.0060 0.0039 0.3000

Al, Mg, Zn, Mn & their alloys MgMn1.5 I 0.6640 0.0000 0.0000 0.2280 0.1010 x x 0.0012 0.0252 0.0046 0.0001 0.3040

Al, Mg, Zn, Mn & their alloys AM100A I 0.6650 0.0035 0.0000 0.2250 0.0987 x 1.26E-06 0.0015 0.0242 0.0067 0.0044 0.3000

Al, Mg, Zn, Mn & their alloys AM503 I 0.6650 0.0000 0.0000 0.2290 0.1010 x x 0.0012 0.0252 0.0046 0.0001 0.3040

Al, Mg, Zn, Mn & their alloys MgAl3Zn I 0.6650 0.0012 0.0000 0.2280 0.1000 x 4.38E-07 0.0016 0.0249 0.0053 0.0024 0.3020

Al, Mg, Zn, Mn & their alloys Magnesium I 0.6690 0.0000 0.0000 0.2310 0.1020 x x 0.0012 0.0255 0.0046 0.0000 0.3050

Al, Mg, Zn, Mn & their alloys Ni-pigmented aluminiumoxide ETH T0.8100 0.4200 0.0003 0.1250 0.0296 0.0002 1.64E-04 0.0136 0.0090 0.0060 0.0130 0.1930

Al, Mg, Zn, Mn & their alloys Tungsten I 0.8900 0.0000 0.0001 0.2340 0.1160 x x 0.0010 0.0251 0.2180 0.0000 0.2960

0.5640 0.0245 0.0001 0.1657 0.0612 0.0005 1.55E-05 0.0056 0.0148 0.0263 0.0495 0.2174

4.35% 0.02% 29.37% 10.85% 1.89% 0.00% 0.99% 2.63% 4.66% 8.77% 38.54%

Cu, Ni, V, Ti, Mo& their alloysCuZn40Pb I 1.5500 0.0060 0.0000 0.6320 0.0340 x 2.39E-06 0.0122 0.0426 0.0480 0.5620 0.2100

Cu, Ni, V, Ti, Mo& their alloysCuZn40 I 1.5900 0.0061 0.0000 0.6540 0.0348 x 2.43E-06 0.0124 0.0440 0.0496 0.5750 0.2150

Cu, Ni, V, Ti, Mo& their alloysG-CuZn40 I 1.5900 0.0061 0.0000 0.6540 0.0348 x 2.43E-06 0.0124 0.0440 0.0496 0.5750 0.2150

Cu, Ni, V, Ti, Mo& their alloysG-CuZn37Pb I 1.6100 0.0059 0.0000 0.6630 0.0350 x 2.31E-06 0.0115 0.0445 0.0502 0.5860 0.2170

Cu, Ni, V, Ti, Mo& their alloysVanadium I 1.6200 0.0002 0.0001 0.3250 0.1810 x 8.19E-08 0.0000 0.0385 0.2160 0.0000 0.8580


Average



Group Name

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Cu, Ni, V, Ti, Mo& their alloysNi span C902 I 1.7300 0.0015 0.0001 1.0500 0.0739 x 3.28E-07 0.0017 0.0686 0.0061 0.2440 0.2750


Cu, Ni, V, Ti, Mo& their alloysInvar I 1.7900 0.0228 0.0001 0.9900 0.0976 x 8.21E-06 0.0026 0.0641 0.0182 0.2360 0.3550

Cu, Ni, V, Ti, Mo& their alloysTiAl6V4 I 1.8400 0.0022 0.0002 0.4390 0.2330 x 7.69E-07 0.0011 0.0521 0.0152 0.0026 1.1000

Cu, Ni, V, Ti, Mo& their alloysTitanium I 1.9300 0.0000 0.0002 0.4610 0.2470 x 1.29E-08 0.0010 0.0553 0.0056 0.0000 1.1600

Cu, Ni, V, Ti, Mo& their alloysNiFe 50 50 I 1.9500 0.0014 0.0001 1.2300 0.0756 x 2.85E-07 0.0017 0.0788 0.0058 0.2890 0.2700


Cu, Ni, V, Ti, Mo& their alloysG-CuZn15 I 2.0700 0.0023 0.0000 0.8790 0.0387 x 9.17E-07 0.0047 0.0575 0.0648 0.7730 0.2540

Cu, Ni, V, Ti, Mo& their alloysG-CuAl10Fe I 2.1200 0.0036 0.0000 0.9010 0.0430 x 1.27E-06 0.0006 0.0585 0.0671 0.7800 0.2680

Cu, Ni, V, Ti, Mo& their alloysG-CuAl10Ni I 2.1700 0.0037 0.0000 0.9640 0.0482 x 1.29E-06 0.0006 0.0624 0.0623 0.7490 0.2780

Cu, Ni, V, Ti, Mo& their alloysTiAl5Sn2 I 2.2300 0.0018 0.0002 0.4400 0.2340 x 6.41E-07 0.0012 0.0524 0.0066 0.3980 1.1000

Cu, Ni, V, Ti, Mo& their alloysCuNi18Zn I 2.2400 0.0033 0.0001 1.0900 0.0568 x 1.30E-06 0.0063 0.0708 0.0495 0.6770 0.2900

Cu, Ni, V, Ti, Mo& their alloysTiV15SnCrAl3 I 2.2400 0.0011 0.0002 0.4130 0.2210 x 4.09E-07 0.0010 0.0493 0.0380 0.4780 1.0400

Cu, Ni, V, Ti, Mo& their alloysCuAl5 I 2.2700 0.0020 0.0000 0.9750 0.0435 x 7.04E-07 0.0003 0.0631 0.0704 0.8370 0.2780

Cu, Ni, V, Ti, Mo& their alloysCopper I 2.3600 0.0000 0.0000 1.0100 0.0411 x 9.57E-09 0.0001 0.0656 0.0740 0.8910 0.2770

Cu, Ni, V, Ti, Mo& their alloysCu-E I 2.3600 0.0000 0.0000 1.0100 0.0411 x 9.57E-09 0.0001 0.0656 0.0740 0.8910 0.2770

Cu, Ni, V, Ti, Mo& their alloysCuAg-E I 2.3600 0.0000 0.0000 1.0100 0.0411 x 9.57E-09 0.0001 0.0656 0.0740 0.8910 0.2770

Cu, Ni, V, Ti, Mo& their alloysG-CuNi10 I 2.4500 0.0002 0.0000 1.1300 0.0508 x 5.66E-08 0.0002 0.0728 0.0652 0.8340 0.2970

Cu, Ni, V, Ti, Mo& their alloysCuNi10Fe I 2.4600 0.0002 0.0000 1.1400 0.0509 x 5.68E-08 0.0002 0.0732 0.0657 0.8410 0.2970


Group Name

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Cu, Ni, V, Ti, Mo& their alloysMolybdenum I 2.7100 0.0002 0.0001 0.1040 0.0585 x 8.19E-08 0.0000 0.0123 1.1800 1.0700 0.2820

Cu, Ni, V, Ti, Mo& their alloysG-CuSn5Zn5Pb5 I 2.8800 0.0008 0.0000 0.8800 0.0407 x 3.12E-07 0.0018 0.0577 0.0643 1.5700 0.2640

Cu, Ni, V, Ti, Mo& their alloysCuNi44Mn I 2.9800 0.0005 0.0001 1.6300 0.0868 x 2.12E-07 0.0002 0.1040 0.0429 0.7390 0.3830

Cu, Ni, V, Ti, Mo& their alloysSupermalloy I 3.0300 0.0011 0.0001 1.8400 0.1130 x 3.76E-07 0.0007 0.1170 0.0645 0.4860 0.4090

Cu, Ni, V, Ti, Mo& their alloysNiCr20TiAl I 3.0900 0.0015 0.0001 1.8900 0.1310 x 6.05E-07 0.0002 0.1220 0.0069 0.4440 0.4950

Cu, Ni, V, Ti, Mo& their alloysMumetal I 3.1100 0.0011 0.0001 1.9400 0.1180 x 3.83E-07 0.0007 0.1230 0.0092 0.4890 0.4300

Cu, Ni, V, Ti, Mo& their alloysNiCr 80 20 I 3.1900 0.0010 0.0001 1.9700 0.1300 x 4.41E-07 0.0001 0.1260 0.0066 0.4660 0.4840

Cu, Ni, V, Ti, Mo& their alloysNiCu30Fe I 3.3000 0.0008 0.0001 1.9400 0.1100 x 3.17E-07 0.0002 0.1230 0.0272 0.6640 0.4340

Cu, Ni, V, Ti, Mo& their alloysCuSn6.7P I 3.3100 0.0000 0.0000 0.9560 0.0436 x 9.99E-09 0.0003 0.0626 0.0695 1.8900 0.2840

Cu, Ni, V, Ti, Mo& their alloysNiCu30Al I 3.3900 0.0017 0.0001 1.9500 0.1260 x 6.55E-07 0.0003 0.1260 0.0267 0.6470 0.5050

Cu, Ni, V, Ti, Mo& their alloysNiCr20Co18Ti I 3.4800 0.0008 0.0001 1.4900 0.1140 x 3.45E-07 0.0002 0.0971 0.9860 0.3450 0.4430

Cu, Ni, V, Ti, Mo& their alloysNiMo30 I 3.4900 0.0008 0.0001 1.6600 0.1160 x 3.41E-07 0.0002 0.1070 0.4840 0.6840 0.4380

Cu, Ni, V, Ti, Mo& their alloysCuSn8 I 3.5000 0.0000 0.0000 0.9460 0.0442 x 1.01E-08 0.0004 0.0620 0.0687 2.0900 0.2860

Cu, Ni, V, Ti, Mo& their alloysDuranik I 3.6600 0.0026 0.0001 2.3100 0.1420 x 9.95E-07 0.0003 0.1470 0.0065 0.5450 0.5100

Cu, Ni, V, Ti, Mo& their alloysG-CuSn10 I 3.7800 0.0000 0.0000 0.9290 0.0450 x 1.02E-08 0.0004 0.0611 0.0674 2.3900 0.2880

Cu, Ni, V, Ti, Mo& their alloysNi 99.6 I 3.8400 0.0011 0.0001 2.4400 0.1460 x 4.69E-07 0.0001 0.1540 0.0056 0.5770 0.5210

Cu, Ni, V, Ti, Mo& their alloysG-CuSn12 I 4.0600 0.0000 0.0000 0.9130 0.0458 x 1.03E-08 0.0005 0.0603 0.0660 2.6900 0.2900

2.5436 0.0023 0.0001 1.0989 0.0876 8.69E-07 0.0025 0.0739 0.1079 0.7600 0.4109

0.09% 0.00% 43.20% 3.44% 0.00% 0.10% 2.91% 4.24% 29.88% 16.16%Contibution to total (%)

Average


Group Name

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Co & Sn & Pts & Pd & Rd Cobalt I 6.34 2.33E-05 4.58E-05 0.09 0.05 x x 0.00 0.01 5.94 0.00 0.24

Co & Sn & Pts & Pd & Rd Tin I 16.50 5.70E-05 9.83E-05 0.17 0.08 x 0.00 0.00 0.02 0.01 15.90 0.39

Co & Sn & Pts & Pd & Rd Palladium enriched ETH T 4610 251 0.05 3720 21.20 0.18 0.02 296.00 214 4.73 0.40 102.00

Co & Sn & Pts & Pd & Rd Platinum ETH T 6960 448 0.11 5510 75.70 0.28 0.04 419.00 319 9.65 0.93 179.00

Co & Sn & Pts & Pd & Rd Rhodium enriched ETH T 12300 803 0.21 9750 144.00 0.51 0.07 730.00 566 18.00 1.75 331.00

Appendix C9:Environmental Impact of Paper Materials in Impact Categories

Paper kraft-bleached B 0.0520 0 0.0002 0.0344 0.0090 0 0 9.85E-07 0.0031 0 0 0.0054

Paper unbleached B 0.0570 0 0.0002 0.0397 0.0086 0 0 2.74E-07 0.0032 0 0 0.0053

Paper wood-free C B250 0.0574 0.0015 0.0000 0.0133 0.0038 0 2.82E-06 3.91E-04 0.0015 0 2.05E-07 0.0369

Paper bleached B 0.0626 0 0.0002 0.0432 0.0095 0 0 1.24E-06 0.0034 0 0 0.0062

Paper wood-free U B250 0.0740 0.0024 0.0000 0.0179 0.0050 0 4.33E-06 4.70E-04 0.0020 0 2.45E-07 0.0462

Kraftpaper bleached C B250 0.0767 0.0029 0.0001 0.0195 0.0053 0 4.86E-06 6.10E-04 0.0022 0 1.70E-07 0.0463

Kraftpaper bleached B250 0.0796 0.0035 0.0001 0.0228 0.0053 0 5.87E-06 6.63E-04 0.0025 0 2.37E-07 0.0449

Kraftpaper unbleached 0.0900 0.0012 0.0000 0.0208 0.0062 0 7.25E-06 6.19E-04 0.0025 0 1.45E-09 0.0587

Paper ETH T 0.0926 0.0131 0.0001 0.0314 0.0024 4.93E-05 2.52E-05 3.25E-03 0.0022 0.0026 1.27E-04 0.0374

Average 0.0713 0.0027 0.0001 0.0270 0.0061 0.0000 0.0000 0.0007 0.0025 0.0003 0.0000 0.0319

Contibution to total (%) 3.82% 0.15% 37.86% 8.56% 0.20% 0.01% 0.94% 3.51% 10.66% 0.02% 44.76%

Total (Pts)

Carcinogens (Pts)

Material CasesAcidification/ Eutrophica-tion (Pts)

Ozone layer (Pts)

Ecotoxi- city

(Pts)

Minerals (Pts)

Fossil fuels (Pts)

Land use (Pts)

Resp. organics

(Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Appendix C10: Environmental Impact of Cardboard Materials in Impact Categories

Kraftliner brown S B250 0.0190 0.0004 1.91E-05 0.0077 0.0011 0 4.27E-06 0.0002 0.0009 0 3.42E-05 0.0086

Paper newsprint B250 0.0206 0.0010 1.68E-05 0.0074 0.0017 0 3.77E-06 0.0004 0.0008 0 2.62E-05 0.0093

Fluting 0.0225 0.0004 2.42E-05 0.0085 0.0014 0 5.18E-06 0.0003 0.0011 0 6.90E-09 0.0107

Cardboard gray 0.0254 0 1.37E-04 0.0156 0.0058 0 0 0 0.0015 0 0 0.0024

Cardboard liquid 0.0289 0 1.21E-04 0.0211 0.0002 0 0 0.0000 0.0019 0 0 0.0055

Corrugated board heavy 0.0296 0 1.18E-04 0.0208 0.0049 0 0 0.0000 0.0017 0 0 0.0021

Wellenstoff 0.0300 0.0007 1.73E-05 0.0051 0.0022 0 2.20E-06 0.0004 0.0008 0 0 0.0208

Testliner 0.0301 0.0006 1.31E-05 0.0044 0.0023 0 2.10E-06 0.0004 0.0007 0 0 0.0217

Cellulose sulphate BCS 0.0312 0.0020 2.92E-05 0.0162 0.0015 0 4.27E-06 0.0002 0.0017 0 1.95E-07 0.0096

Cardboard duplex 0.0318 0 1.53E-04 0.0206 0.0063 0 0 0.0000 0.0018 0 0 0.0030

Kraftliner white top S B250 0.0322 0.0015 3.04E-05 0.0141 0.0018 0 5.84E-06 0.0004 0.0016 0 3.75E-05 0.0127

Cardboard cellulose 0.0323 0 9.08E-05 0.0220 0.0045 0 0 0.0000 0.0021 0 0 0.0036

Schrenz 0.0333 0.0006 1.20E-05 0.0039 0.0025 0 1.87E-06 0.0004 0.0005 0 0 0.0255

Sack paper S B250 0.0364 0.0013 3.46E-05 0.0141 0.0020 0 7.81E-06 0.0010 0.0017 0 4.58E-05 0.0161

Corr. cardboard mix 1 0.0375 0.0008 2.27E-05 0.0076 0.0027 0 4.00E-06 0.0005 0.0011 0 1.21E-05 0.0247

Corr. cardboard mix 3D 0.0395 0.0008 2.16E-05 0.0070 0.0029 0 3.64E-06 0.0005 0.0011 0 7.13E-06 0.0272

Corr. cardboard mix 2 0.0421 0.0012 2.66E-05 0.0098 0.0030 0 4.59E-06 0.0006 0.0014 0 1.33E-05 0.0262

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)

Fossil fuels (Pts)

Ecotoxi- city

(Pts)

Acidification/ Eutrophica-tion (Pts)

Land use (Pts)

Material CasesTotal (Pts)

Carcinogens (Pts)

Resp. organics

(Pts)

Appendix C10: Environmental Impact of Cardboard Materials in Impact Categories

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)

Fossil fuels (Pts)

Ecotoxi- city

(Pts)

Acidification/ Eutrophica-tion (Pts)

Land use (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Cardboard chromo 0.0422 0 2.05E-04 0.0267 0.0079 0 0 0.0000 0.0024 0 0 0.0051

Kraftliner brown A B250 0.0434 0.0008 3.42E-05 0.0120 0.0034 0 8.07E-06 0.0004 0.0015 0 7.50E-05 0.0252

Cardboard cellulose S B250 0.0451 0.0024 4.34E-05 0.0179 0.0027 0 8.20E-06 0.0005 0.0021 0 9.43E-08 0.0195

Cardboard duplex/tripl 0.0480 0.0011 1.93E-05 0.0066 0.0035 0 3.38E-06 0.0008 0.0007 0 4.17E-05 0.0352

Corr. cardboard new 0.0488 0.0009 3.79E-05 0.0131 0.0037 0 8.53E-06 0.0005 0.0018 0 5.25E-05 0.0287

Swisskraft 0.0495 0.0003 1.17E-05 0.0056 0.0037 0 1.31E-06 0.0002 0.0007 0 1.01E-04 0.0389

Average 0.0348 0.0007 0.0001 0.0125 0.0031 0.0000 0.0000 0.0003 0.0014 0.0000 0.0000 0.0166

Contibution to total (%) 2.08% 0.15% 36.01% 8.95% 0.00% 0.01% 0.95% 3.93% 0.00% 0.06% 47.80%

Appendix C11 & C12: Environmental Impact of Polymers in Impact Categories

Group Name

Thermoplas PP GF30 I 0.2120 0.0004 0.0003 0.0347 0.0051 0 0 0.0007 0.0042 0.0025 4.19E-06 0.1640

Thermoplas PVC suspension A 0.2180 0.0011 0.0001 0.0418 0.0115 0 0 0.0001 0.0049 0 5.69E-06 0.1590

Thermoplas PVC bulk A 0.2190 0.0010 0.0001 0.0349 0.0103 0 0 0.0001 0.0043 0 3.88E-06 0.1680

Thermoplas PVC (e) I 0.2240 0.0007 0.0001 0.0613 0.0149 0 0 0.0001 0.0074 0.0026 4.13E-06 0.1370

Thermoplas PE (LLDPE) I 0.2260 0.0008 0.0005 0.0252 0.0033 0 0 0.0000 0.0037 0.0027 8.97E-08 0.1900

Thermoplas PVC film (calendered) A 0.2440 0.0011 0.0001 0.0551 0.0139 0 0 0.0001 0.0058 0 7.05E-06 0.1670

Thermoplas PE (HDPE) I 0.2500 0.0004 0.0007 0.0374 0.0051 0 0 0.0000 0.0049 0.0019 2.59E-06 0.2000

Thermoplas PVC film (unplasticised) A 0.2510 0.0012 0.0001 0.0559 0.0141 0 0 0.0001 0.0062 0 7.01E-06 0.1740

Thermoplas PET 30% glass fibre I 0.2530 0.0003 0.0009 0.0687 0.0098 0 4.58E-08 0.0008 0.0082 0.0025 3.68E-06 0.1620

Thermoplas PVC B250 0.2590 0.0058 0.0005 0.0666 0.0113 0 1.21E-05 0.0008 0.0082 0 2.89E-06 0.1660

Thermoplas PVC revised P 0.2590 0.0003 0.0006 0.0643 0.0096 0 0 0.0001 0.0077 0 2.87E-06 0.1770

Thermoplas PC 30% glass fibre I 0.2610 0.0005 0.0001 0.0645 0.0217 0 4.58E-08 0.0007 0.0078 0.0021 3.68E-06 0.1640

Thermoplas PVC emulsion A 0.2750 0.0011 0.0001 0.0615 0.0150 0 0 0.0002 0.0073 0 4.39E-06 0.1900

Thermoplas PE (LDPE) I 0.2800 0.0004 0.0007 0.0491 0.0062 0 0 0.0001 0.0061 0.0027 3.71E-06 0.2150

Thermoplas PVC high impact ETH T 0.2840 0.0196 0.0003 0.0528 0.0164 0.0002 0.0112 0.0059 0.0046 0.0058 4.06E-04 0.1670

Thermoplas PVC injection moulded A 0.2970 0.0012 0.0001 0.0656 0.0115 0 0 0.0002 0.0072 0 9.51E-06 0.2110

Thermoplas PE expanded I 0.2990 0.0004 0.0047 0.0497 0.0063 0 0 0.0001 0.0062 0.0027 3.71E-06 0.2290

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)


Group Name

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Thermoplas PVC film (unplastized) P 0.3010 0.0003 0.0007 0.0855 0.0126 0 0 0.0001 0.0096 0 3.21E-06 0.1920

Thermoplas ABS I 0.3030 0.0005 0.0002 0.0482 0.0183 0 0 0.0001 0.0057 0.0024 7.76E-06 0.2280

Thermoplas HDPE B250 0.3030 0.0017 0.0006 0.0374 0.0117 0 0.0000 0.0005 0.0049 0 2.59E-06 0.2460

Thermoplas LLDPE B250 0.3030 0.0015 0.0003 0.0252 0.0109 0 0.0000 0.0004 0.0037 0 1.87E-06 0.2610

Thermoplas PP granulate average B250 0.3060 0.0021 0.0003 0.0445 0.0102 0 0.0000 0.0008 0.0054 0 4.97E-06 0.2420

Thermoplas LDPE A 0.3160 0.0002 0.0002 0.0397 0.0113 0 0 0.0001 0.0050 0 1.10E-05 0.2600

Thermoplas PP A 0.3190 0.0002 0.0001 0.0447 0.0108 0 0 0.0002 0.0053 0 2.81E-05 0.2570

Thermoplas HDPE A 0.3230 0.0003 0.0002 0.0506 0.0102 0 0 0.0002 0.0055 0 4.29E-04 0.2560

Thermoplas PE granulate average B250 0.3240 0.0024 0.0006 0.0411 0.0125 0 2.46E-05 0.0007 0.0055 0 3.71E-06 0.2610

Thermoplas PE P 0.3350 0.0004 0.0007 0.0388 0.0060 0 0 0.0000 0.0050 0 3.71E-06 0.2840

Thermoplas LDPE B250 0.3370 0.0024 0.0006 0.0491 0.0132 0 2.69E-05 0.0008 0.0061 0 3.71E-06 0.2650

Thermoplas PET bottle grade I 0.3410 0.0003 0.0013 0.0931 0.0127 0 0 0.0002 0.0110 0.0032 4.24E-06 0.2190

Thermoplas LDPE film A 0.3480 0.0003 0.0002 0.0553 0.0115 0 0 0.0001 0.0063 0 1.49E-05 0.2750

Thermoplas PS (GPPS) I 0.3490 0.0006 0.0001 0.0482 0.0155 0 0 0.0002 0.0062 0.0026 1.20E-05 0.2760

Thermoplas PC I 0.3530 0.0006 0.0002 0.0870 0.0299 0 0 0.0001 0.0104 0.0026 4.24E-06 0.2220

Thermoplas PET granulate amorph B250 0.3570 0.0022 0.0015 0.0852 0.0125 0 2.30E-05 0.0008 0.0103 0 3.92E-06 0.2450

Thermoplas PS (EPS) A 0.3590 0.0012 0.0002 0.0463 0.0148 0 0 0.0001 0.0061 0 1.49E-05 0.2900


Group Name

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Thermoplas LDPE revised P 0.3610 0.0004 0.0007 0.0491 0.0131 0 0 0.0001 0.0061 0 3.71E-06 0.2910

Thermoplas PET amorph I 0.3620 0.0040 0.0005 0.1280 0.0248 0 0 0.0043 0.0120 0.0032 3.83E-06 0.1850

Thermoplas PS (HIPS) I 0.3620 0.0007 0.0001 0.0505 0.0166 0 0 0.0002 0.0063 0.0026 1.25E-05 0.2850

Thermoplas HIPS ETH T 0.3650 0.0108 0.0006 0.0549 0.0168 0.0001 2.32E-04 0.0074 0.0050 0.0023 1.97E-04 0.2660

Thermoplas HDPE pipe P 0.3670 0.0004 0.0008 0.0560 0.0137 0 0 0.0000 0.0071 0 4.04E-06 0.2890

Thermoplas PB B250 (1998) 0.3750 0.0014 0.0005 0.0712 0.0196 0 2.66E-05 0.0007 0.0085 0 5.94E-06 0.2730

Thermoplas PVDC I 0.3780 0.0003 0.0011 0.1750 0.0194 0 0 0.0002 0.0187 0.0026 9.36E-05 0.1610

Thermoplas SAN A 0.3800 0.0007 0.0001 0.0366 0.0161 0 0 0.0001 0.0047 0 9.11E-06 0.3210

Thermoplas HDPE blow moulded bottles A 0.3900 0.0003 0.0002 0.0901 0.0171 0 0 0.0002 0.0088 0 4.29E-04 0.2730

Thermoplas PET resin P (1997) 0.3940 0.0040 0.0005 0.1280 0.0248 0 0 0.0043 0.0120 0 4.51E-06 0.2200

Thermoplas PP oriented film A 0.4130 0.0003 0.0001 0.0900 0.0164 0 0 0.0002 0.0098 0 3.21E-05 0.2960

Thermoplas PMMA I 0.4340 0.0005 0.0003 0.1080 0.0334 0 0 0.0003 0.0122 0.0026 9.08E-06 0.2770

Thermoplas PS thermoformed A 0.4480 0.0014 0.0003 0.0781 0.0194 0 0 0.0002 0.0095 0 1.61E-05 0.3390

Thermoplas PET ETH T 0.4490 0.0217 0.0022 0.0586 0.0201 0.0001 0.0003 0.0071 0.0056 0.0029 2.42E-04 0.3300

Thermoplas PA 6 GF30 I 0.4700 0.0109 0.0001 0.1400 0.0619 0 0 0.0004 0.0153 0 2.81E-05 0.2420

Thermoplas PA 66 GF30 I 0.4700 0.0109 0.0001 0.1400 0.0619 0 0 0.0004 0.0153 0 2.81E-05 0.2420

Thermoplas PET stretch moulded bottles P 0.4750 0.0003 0.0014 0.1490 0.0213 0 0 0.0002 0.0150 0 4.19E-06 0.2880


Group Name

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Thermoplas PA 6.6 30% glass fibre A 0.4870 0.0053 0.0002 0.1240 0.0363 0 0 0.0003 0.0150 0 8.46E-06 0.3050

Thermoplas PP injection moulded A 0.5000 0.0003 0.0001 0.1240 0.0242 0 0 0.0010 0.0144 0 3.21E-05 0.3360

Thermoplas PA 66 I 0.5010 0.0086 0.0001 0.1310 0.0684 0 0 0.0005 0.0148 0.0026 4.60E-05 0.2750

Thermoplas PET film A 0.5160 0.0036 0.0005 0.1700 0.0336 0 0 0.0036 0.0175 0 5.11E-06 0.2870

Thermoplas PET film packed A 0.5200 0.0036 0.0005 0.1720 0.0325 0 0 0.0036 0.0178 0 7.19E-06 0.2900

Thermoplas PA 6.6 30% glass P 0.5390 0.0109 0.0001 0.1400 0.0619 0 0 0.0005 0.0153 0 3.08E-05 0.3110

Thermoplas PMMA beads A 0.5490 0.0010 0.0003 0.1060 0.0327 0 0 0.0003 0.0121 0 9.99E-06 0.3970

Thermoplas PA 6.6 A 0.5930 0.0090 0.0001 0.1210 0.0416 0 0 0.0006 0.0145 0 4.98E-05 0.4060

Thermoplas PMMA sheet A 0.6330 0.0011 0.0003 0.1310 0.0403 0 0 0.0003 0.0151 0 1.16E-05 0.4440

Thermoplas PA 6 I 0.6570 0.0014 0.0005 0.0528 0.0434 0 0 0.0031 0.0088 0.0026 1.62E-05 0.5440

Rubber BR I 0.2780 0.0033 0.0005 0.0442 0.0067 0 0 0.0008 0.0055 0.0021 2.70E-05 0.2150

Rubber NBR I 0.2980 0.0031 0.0005 0.0431 0.0056 0 1.81E-04 0.0008 0.0057 0.0019 2.78E-05 0.2370

Rubber SBR I 0.2960 0.0027 0.0005 0.0563 0.0069 0 0 0.0007 0.0068 0.0017 2.49E-05 0.2200

Rubber EPDM rubber ETH T 0.3640 0.0247 0.0010 0.0580 0.0174 0.0002 2.17E-04 0.0090 0.0050 0.0053 4.28E-04 0.2430

PUR PUR flex. integral skin foam A 0.3950 0.0023 0.0001 0.0917 0.0211 0 0 0.0002 0.0087 0 1.99E-05 0.2700

PUR PUR RIM amine extended A 0.3960 0.0025 0.0001 0.0911 0.0212 0 0 0.0002 0.0087 0 1.88E-05 0.2720

PUR PUR flex. moulded ccm A 0.3970 0.0027 0.0001 0.0908 0.0212 0 0 0.0002 0.0087 0 1.84E-05 0.2730


Group Name

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

PUR PUR RIM glycol extended A 0.4010 0.0035 0.0001 0.0889 0.0216 0 0 0.0002 0.0087 0 1.51E-05 0.2780

PUR PUR energy absorbing A 0.4060 0.0046 0.0001 0.0867 0.0219 0 0 0.0003 0.0088 0 1.14E-05 0.2830

PUR PUR flex. moulded ccm/t A 0.4070 0.0010 0.0001 0.0972 0.0231 0 0 0.0002 0.0094 0 2.09E-05 0.2760

PUR PUR flex. moulded cct A 0.4110 0.0006 0.0001 0.0990 0.0237 0 0 0.0002 0.0096 0 2.12E-05 0.2770

PUR PUR flex. moulded hot cure A 0.4110 0.0006 0.0001 0.0990 0.0237 0 0 0.0002 0.0096 0 2.12E-05 0.2770

PUR PUR flexible block foam A 0.4150 0.0007 0.0001 0.0996 0.0243 0 0 0.0002 0.0097 0 2.04E-05 0.2800

PUR PUR hardfoam ETH T 0.4260 0.0367 0.0002 0.1180 0.0745 0.0004 1.22E-04 0.0139 0.0092 0.0102 7.75E-04 0.1610

PUR PUR flex. block foam I 0.4490 0.1010 0.0021 0.1040 0.0241 0 6.22E-07 0.0028 0.0126 0.0053 1.51E-05 0.1980

PUR PUR flex. moulded TDI I 0.4520 0.1080 0.0021 0.1020 0.0237 0 6.22E-07 0.0030 0.0124 0.0054 1.53E-05 0.1950

PUR PUR rigid integr. skin foam I 0.4530 0.0615 0.0007 0.1280 0.0285 0 6.27E-07 0.0021 0.0144 0.0069 1.61E-05 0.2110

PUR PUR semi rigid foam I 0.4550 0.1080 0.0005 0.1110 0.0249 0 6.25E-07 0.0031 0.0128 0.0063 1.65E-05 0.1880

PUR PUR flex. moulded MDI/TDI I 0.4570 0.1080 0.0021 0.1050 0.0241 0 6.23E-07 0.0031 0.0125 0.0056 1.56E-05 0.1970

PUR PUR rigid foam I 0.4640 0.0591 0.0020 0.1290 0.0287 0 6.27E-07 0.0021 0.0145 0.0069 1.61E-05 0.2220

PUR PUR flex. moulded. MDI I 0.4690 0.0977 0.0022 0.1150 0.0258 0 6.26E-07 0.0029 0.0132 0.0064 1.64E-05 0.2050

0.3753 0.0110 0.0006 0.0810 0.0212 1.24E-05 0.0002 0.0012 0.0090 0.0015 4.79E-05 0.2496

2.92% 0.15% 21.58% 5.64% 0.11% 0.04% 0.33% 2.41% 0.39% 0.01% 66.51%

Epoxy Epoxy resin (liquid) P 0.6420 0.0007 0.0002 0.1550 0.0365 0 0 0.0002 0.0172 0 0.0000 0.4320

Average



Group Name

Fossil fuels (Pts)

Ecotoxi- city (Pts)


(Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Epoxy Epoxy resin I 0.8730 0.0000 0.0003 0.0443 0.0061 0 0 0.0000 0.0077 0.0023 0.0000 0.8120

Epoxy Epoxy resin A 0.6390 0.0007 0.0002 0.1530 0.0359 0 0 0.0002 0.0173 0 0.0000 0.4310

0.7180 0.0005 0.0002 0.1174 0.0262 0 0 0.0001 0.0141 0.0008 0.0000 0.5583

0.06% 0.03% 16.36% 3.64% 0.00% 0.00% 0.02% 1.96% 0.11% 0.00% 77.76%

Average


Appendix C13-C16: Environmental Impact of Woods in Impact Categories

Group Name

Wood LI Silver fir I 0.2340 0.0001 6.97E-06 0.0022 0.0004 x 5.13E-08 0.0010 0.0004 0.2250 0.0000 0.0045

Wood LI Larch, European I 0.2800 0.0005 1.08E-04 0.0163 0.0041 x 2.47E-07 0.0027 0.0021 0.2260 0.0000 0.0276

Wood LI Hemlock I 0.3520 0.0000 1.33E-04 0.0252 0.0044 x 7.11E-09 0.0026 0.0034 0.2830 0.0000 0.0331

Wood LI Pitch pine I 0.3710 0.0002 3.09E-05 0.0196 0.0019 x 6.22E-08 0.0021 0.0030 0.3260 0.0000 0.0186

Wood LI Oregon pine I 0.3880 0.0002 1.09E-04 0.0240 0.0040 x 8.24E-08 0.0019 0.0033 0.3250 0.0000 0.0300

Wood LI Teak I 0.4070 0.0001 1.24E-04 0.0467 0.0060 x 5.30E-08 0.0024 0.0066 0.2970 0.0000 0.0485

Wood LI Ash I 0.4080 0.0005 1.02E-04 0.0169 0.0037 x 2.12E-07 0.0043 0.0024 0.3550 0.0000 0.0253

Wood LI Beech, European I 0.4270 0.0005 9.62E-05 0.0159 0.0039 x 2.04E-07 0.0028 0.0021 0.3760 0.0000 0.0263

Wood LI Oak, European I 0.4460 0.0006 9.88E-05 0.0160 0.0042 x 2.69E-07 0.0027 0.0021 0.3930 0.0000 0.0279

Wood LI Spruce, European I 0.4640 0.0007 8.90E-05 0.0046 0.0019 x 3.10E-07 0.0001 0.0007 0.4450 0.0000 0.0114

Wood LI Ahorn I 0.5100 0.0005 1.17E-04 0.0202 0.0045 x 2.32E-07 0.0047 0.0028 0.4460 0.0000 0.0311

Wood LI Scots pine (grenen) I 0.5240 0.0006 1.17E-04 0.0167 0.0043 x 2.74E-07 0.0028 0.0022 0.4690 0.0000 0.0283

Wood LI Sycamore I 0.5640 0.0001 1.84E-05 0.0121 0.0012 x 5.84E-08 0.0010 0.0019 0.5360 0.0000 0.0124

Wood LI Birch I 0.5910 0.0005 9.75E-05 0.0142 0.0039 x 2.24E-07 0.0023 0.0018 0.5420 0.0000 0.0261

Wood LI Merbau I 0.6080 0.0002 3.42E-05 0.0253 0.0024 x 6.85E-08 0.0004 0.0038 0.5450 0.0000 0.0312

Wood LI Chestnut I 0.6280 0.0005 1.46E-04 0.0299 0.0057 x 2.31E-07 0.0092 0.0046 0.5370 0.0000 0.0408

Wood LI Aspen I 0.6360 0.0007 1.37E-04 0.0212 0.0050 x 2.97E-07 0.0046 0.0029 0.5680 0.0000 0.0337

Fossil fuels (Pts)

Ecotoxi- city (Pts)

Acidification/ Eutrophica-

tion (Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)


Group Name

Fossil fuels (Pts)

Ecotoxi- city (Pts)


tion (Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Wood LI Red oak I 0.6400 0.0005 9.74E-05 0.0169 0.0039 x 2.11E-07 0.0025 0.0022 0.5880 0.0000 0.0267

Wood LI Cedar I 0.6430 0.0000 1.08E-04 0.0247 0.0044 x 1.02E-08 0.0028 0.0037 0.5740 0.0000 0.0331

Wood LI Hickory I 0.6510 0.0000 8.94E-05 0.0219 0.0036 x 7.22E-09 0.0020 0.0030 0.5930 0.0000 0.0273

Wood LI Yellow pine I 0.6720 0.0008 1.50E-04 0.0216 0.0053 x 3.58E-07 0.0033 0.0028 0.6020 5.79E-06 0.0354

Wood LI Robinia I 0.6870 0.0004 8.98E-05 0.0151 0.0034 x 1.89E-07 0.0035 0.0021 0.6390 3.12E-06 0.0233

Wood LI Linden I 0.6970 0.0006 1.17E-04 0.0165 0.0040 x 2.74E-07 0.0035 0.0023 0.6430 4.45E-06 0.0266

Wood LI Alder I 0.7040 0.0006 1.24E-04 0.0200 0.0046 x 2.65E-07 0.0044 0.0028 0.6400 4.34E-06 0.0314

Wood LI Elm I 0.7420 0.0005 8.62E-05 0.0117 0.0032 x 2.15E-07 0.0014 0.0014 0.7030 3.43E-06 0.0211

Wood LI Poplar I 0.7620 0.0001 1.50E-05 0.0048 0.0007 x 5.13E-08 0.0023 0.0009 0.7460 9.63E-07 0.0069

Wood LI Red Cedar, Western I 0.7710 0.0009 2.03E-04 0.0567 0.0088 x 3.78E-07 0.0038 0.0079 0.6270 6.89E-06 0.0660

Wood LI Hornbean I 0.7900 0.0004 8.11E-05 0.0130 0.0032 x 1.78E-07 0.0024 0.0017 0.7480 2.90E-06 0.0213

Wood LI Black poplar I 0.8160 0.0007 1.44E-04 0.0212 0.0051 x 3.24E-07 0.0046 0.0029 0.7470 5.27E-06 0.0339

0.5660 0.0004 0.0001 0.0197 0.0039 0 1.84E-07 0.0029 0.0027 0.5084 3.18E-06 0.0279

0.07% 0.02% 3.48% 0.68% 0.00% 0.00% 0.51% 0.49% 89.83% 0.00% 4.93%

Wood LM Walnut I 0.9540 0.0005 1.07E-04 0.0183 0.0041 x 0.0000 0.0043 0.0026 0.8970 3.56E-06 0.0281

Wood LM Platan I 1.1500 0.0005 1.00E-04 0.0143 0.0037 x 0.0000 0.0023 0.0019 1.1100 3.79E-06 0.0245

Wood LM Horse chestnut I 1.2200 0.0006 1.17E-04 0.0177 0.0045 x 0.0000 0.0030 0.0023 1.1600 4.28E-06 0.0298

Average



Group Name

Fossil fuels (Pts)

Ecotoxi- city (Pts)


tion (Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Wood LM Willow I 1.4700 0.0009 1.72E-04 0.0239 0.0064 x 0.0000 0.0032 0.0030 1.3900 6.35E-06 0.0424

1.1985 0.0006 0.0001 0.0186 0.0047 0 0.0000 0.0032 0.0024 1.1393 4.50E-06 0.0312

0.05% 0.01% 1.55% 0.39% 0.00% 0.00% 0.27% 0.20% 95.06% 0.00% 2.60%

Wood MH Azobe I 2.7900 0.0002 7.46E-05 0.0236 0.0038 x 1.01E-07 0.0019 0.0033 2.7200 1.99E-06 0.0294

Wood MH Moabi I 3.5600 0.0004 1.07E-04 0.0326 0.0050 x 1.81E-07 0.0023 0.0046 3.4800 3.38E-06 0.0380

Wood MH Blue gum I 3.7200 0.0001 1.23E-04 0.0423 0.0058 x 1.96E-08 0.0026 0.0059 3.6200 1.09E-06 0.0455

Wood MH Angelique I 4.7300 0.0000 7.63E-05 0.0219 0.0039 x 8.67E-09 0.0023 0.0032 4.6600 5.44E-07 0.0323

Wood MH Makore I 4.8300 0.0005 1.23E-04 0.0339 0.0055 x 2.23E-07 0.0026 0.0047 4.7500 4.05E-06 0.0406

Wood MH Kauri I 5.1800 0.0000 1.42E-04 0.0335 0.0054 x 1.20E-08 0.0028 0.0046 5.1000 7.39E-07 0.0417

Wood MH Mersawa I 5.1900 0.0000 8.52E-05 0.0242 0.0041 x 1.06E-08 0.0023 0.0035 5.1200 6.36E-07 0.0328

Wood MH Yang I 5.2100 0.0000 7.65E-05 0.0234 0.0038 x 1.06E-08 0.0021 0.0034 5.1500 6.24E-07 0.0310

Wood MH Agba I 5.2300 0.0007 1.55E-04 0.0422 0.0067 x 2.92E-07 0.0030 0.0059 5.1200 5.29E-06 0.0499

Wood MH Limba I 5.2500 0.0005 1.15E-04 0.0293 0.0047 x 2.29E-07 0.0021 0.0041 5.1800 4.08E-06 0.0350

Wood MH Bubinga I 5.6100 0.0004 1.09E-04 0.0338 0.0052 x 1.79E-07 0.0024 0.0047 5.5300 3.38E-06 0.0393

Wood MH Mahogani, African I 5.8600 0.0006 1.36E-04 0.0352 0.0056 x 2.66E-07 0.0025 0.0049 5.7700 4.76E-06 0.0419

Wood MH Iroko I 5.9100 0.0005 1.39E-04 0.0454 0.0067 x 2.27E-07 0.0029 0.0064 5.8000 4.35E-06 0.0513

Wood MH Meranti I 5.9400 0.0006 1.52E-04 0.0468 0.0070 x 2.68E-07 0.0030 0.0066 5.8300 5.03E-06 0.0530

Average



Group Name

Fossil fuels (Pts)

Ecotoxi- city (Pts)


tion (Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Wood MH Utile I 5.9600 0.0005 1.20E-04 0.0331 0.0052 x 2.23E-07 0.0023 0.0046 5.8800 4.06E-06 0.0391

Wood MH Dibetou I 6.0200 0.0005 1.26E-04 0.0350 0.0055 x 2.35E-07 0.0025 0.0049 5.9300 4.28E-06 0.0413

Wood MH Afzelia I 6.1000 0.0004 1.13E-04 0.0333 0.0053 x 1.91E-07 0.0025 0.0046 6.0100 3.54E-06 0.0395

Wood MH Sapelli I 6.2300 0.0004 1.16E-04 0.0337 0.0052 x 1.86E-07 0.0024 0.0047 6.1500 3.48E-06 0.0393

Wood MH Movigui I 6.2500 0.0004 1.05E-04 0.0295 0.0047 x 1.86E-07 0.0022 0.0041 6.1700 3.39E-06 0.0353

Wood MH Afrormosia I 6.2800 0.0005 1.27E-04 0.0403 0.0061 x 2.07E-07 0.0027 0.0056 6.1800 3.95E-06 0.0461

Wood MH Idigbo I 6.3800 0.0006 1.39E-04 0.0369 0.0060 x 2.62E-07 0.0028 0.0051 6.2800 4.71E-06 0.0443

Wood MH Kotibe I 6.4400 0.0004 1.06E-04 0.0312 0.0048 x 1.85E-07 0.0022 0.0044 6.3600 3.42E-06 0.0365

Wood MH Mengkulang I 6.4600 0.0000 9.00E-05 0.0251 0.0043 x 1.06E-08 0.0025 0.0036 6.3900 6.47E-07 0.0348

Wood MH Peroba I 6.5400 0.0000 8.30E-05 0.0264 0.0042 x 1.22E-08 0.0023 0.0038 6.4700 7.12E-07 0.0353

Wood MH Bosse clair I 6.7500 0.0005 1.23E-04 0.0355 0.0056 x 2.21E-07 0.0025 0.0050 6.6600 4.06E-06 0.0417

5.5368 0.0004 1.14E-04 0.0331 0.0052 0 1.58E-07 0.0025 0.0046 5.4524 3.05E-06 0.0398

0.01% 0.00% 0.60% 0.09% 0.00% 0.00% 0.04% 0.08% 98.48% 0.00% 0.72%

Wood HI Carapa I 7.2400 4.22E-05 9.28E-05 0.0250 0.0040 x 1.18E-08 0.0023 0.0037 7.1700 6.99E-07 0.0309

Wood HI Paranapine I 7.2500 3.53E-05 9.76E-05 0.0219 0.0037 x 9.84E-09 0.0021 0.0032 7.2000 6.01E-07 0.0281

Wood HI Purpleheart I 7.5000 3.15E-05 7.38E-05 0.0222 0.0040 x 8.67E-09 0.0025 0.0032 7.4400 5.48E-07 0.0328

Wood HI Mansonia I 7.5400 5.17E-04 1.30E-04 0.0396 0.0060 x 2.23E-07 0.0027 0.0055 7.4400 4.18E-06 0.0455


Average


Group Name

Fossil fuels (Pts)

Ecotoxi- city (Pts)


tion (Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Wood HI Mahogany, American I 7.6300 2.91E-05 1.10E-04 0.0234 0.0038 x 8.03E-09 0.0021 0.0032 7.5700 5.08E-07 0.0291

Wood HI Padouk, African I 8.0400 4.74E-04 1.21E-04 0.0362 0.0056 x 2.05E-07 0.0026 0.0051 7.9500 3.83E-06 0.0423

Wood HI Tiama I 8.1900 5.83E-04 1.38E-04 0.0387 0.0061 x 2.54E-07 0.0027 0.0054 8.0900 4.63E-06 0.0456

Wood HI Niangon I 8.3300 4.70E-04 1.15E-04 0.0332 0.0052 x 2.04E-07 0.0024 0.0046 8.2500 3.76E-06 0.0389

Wood HI Aningre I 8.4200 5.79E-04 1.34E-04 0.0365 0.0058 x 2.53E-07 0.0026 0.0051 8.3300 4.57E-06 0.0431

Wood HI Mutenye I 8.5400 4.42E-04 1.20E-04 0.0398 0.0059 x 1.89E-07 0.0026 0.0056 8.4400 3.67E-06 0.0449

Wood HI Wawa I 8.7900 8.40E-04 1.73E-04 0.0405 0.0067 x 3.70E-07 0.0029 0.0057 8.6800 6.47E-06 0.0489

Wood HI Tchitola I 8.8500 5.32E-04 1.26E-04 0.0353 0.0056 x 2.32E-07 0.0025 0.0049 8.7600 4.22E-06 0.0416

Wood HI Koto I 9.2200 6.11E-04 1.50E-04 0.0437 0.0068 x 2.65E-07 0.0031 0.0061 9.1100 4.90E-06 0.0512

Wood HI Canaria I 9.4100 6.73E-04 1.55E-04 0.0422 0.0067 x 2.94E-07 0.0030 0.0059 9.3000 5.32E-06 0.0499

Wood HI Palissander, Indisch I 9.4900 3.55E-05 7.48E-05 0.0229 0.0039 x 9.84E-09 0.0025 0.0034 9.4300 6.05E-07 0.0295

Wood HI Abura I 9.5900 5.90E-04 1.43E-04 0.0422 0.0064 x 2.56E-07 0.0028 0.0059 9.4900 4.74E-06 0.0487

Wood HI Ilomba I 10.4000 7.33E-04 1.67E-04 0.0449 0.0071 x 3.20E-07 0.0032 0.0063 10.3000 5.77E-06 0.0532

Wood HI Antiaris I 10.6000 6.97E-04 1.57E-04 0.0415 0.0066 x 3.05E-07 0.0029 0.0058 10.5000 5.47E-06 0.0492

Wood HI Okoume I 10.7000 7.20E-04 1.47E-04 0.0357 0.0057 x 3.16E-07 0.0024 0.0050 10.6000 5.56E-06 0.0424

Wood HI Baboen I 11.0000 3.58E-05 1.17E-04 0.0248 0.0045 x 9.84E-09 0.0029 0.0037 10.9000 6.41E-07 0.0339

Wood HI Olon I 11.3000 6.26E-04 1.42E-04 0.0384 0.0061 x 2.73E-07 0.0027 0.0054 11.2000 4.93E-06 0.0455


Group Name

Fossil fuels (Pts)

Ecotoxi- city (Pts)


tion (Pts)

Land use (Pts)

Minerals (Pts)

Resp. inorganics

(Pts)

Climate change

(Pts)

Radia- tion (Pts)

Ozone layer (Pts)


Carcinogens (Pts)

Resp. organics

(Pts)

Wood HI Cottonwood I 11.6000 3.01E-05 1.44E-04 0.0265 0.0055 x 8.03E-09 0.0036 0.0038 11.5000 5.93E-07 0.0451

Wood HI Wenge I 11.8000 3.89E-04 9.73E-05 0.0235 0.0044 x 1.72E-07 0.0023 0.0032 11.7000 3.01E-06 0.0315

Wood HI Emeri I 12.4000 3.26E-05 1.23E-04 0.0291 0.0060 x 8.65E-09 0.0041 0.0042 12.3000 6.35E-07 0.0491

9.3263 0.0004 0.0001 0.0337 0.0055 0 1.75E-07 0.0027 0.0047 9.2354 3.33E-06 0.0417

0.00% 0.00% 0.36% 0.06% 0.00% 0.00% 0.03% 0.05% 99.03% 0.00% 0.45%

Average


Appendix D Product Cases and the Source

APPENDIX D

PRODUCT CASES AND THE SOURCE

List of the Sources for Product Cases:

[1] A Simplified Assessment Approach for Environmentally Sound Product Systems

Design, PhD Thesis, V. J. Soriano, 2001, University of NSW, Sydney .

[2] A Simple LCA Case Study of Reusable and Disposable Shavers by Marjolein

Demmers (Preliminary study carried out by Karli James ) Proceedings of the first

National LCA Conference, Melbourne, 1996.

[3] Assessment of Environmental Life Cycle Approach for Industrial Materials and

Products by Steven B Young, Canada, 1996.

[4] Product CD cases, LCA Short Course, Centre for Design, RMIT Melbourne, 2000.

[5] Sample cases from SimaPro LCA package.

[6] LCA in Practice in the commercial Furniture Industry by Michael pitcher, Second

National Conference on LCA, Melbourne 2000, and interview with Michael Pitcher

by V.J.Soriano.

[7] Environmental Assessment of Products: Volume 1 Methodology, Tools and Case

Studies in Product Development by Henrik Wenzel et. al., 1997.

[8] Life Cycle Assessment of Dishwasher by Deni Greene Consultanting for Centre for

Design at RMIT, Melbourne, 1994.

D-1


[9] Tools for Designers-Redesign of an Electric Heater by Marjolein Demmers, Centre

for Design at RMIT, Melbourne, 1995.

[10] Life Cycle Assessment of Washing Machine by Deni Greene Consultanting

Services for the Australian Consumers' Association, 1992.

[11] Waste Minimisation Case Studies for Three Products, Von Walter Stahel, Product-

Life Institute, Geneva, 1991.

[12] Life-cycle Assessment on Saucepans, KTH Project by Eriksson, M., and Izar, M.,

Stockholm, Sweden, 2000.

[13] Streamlined Life Cycle Assessment Study-Study Prepared for Airdri Ltd. And

Bobrick Washroom Equipment Inc., Environmental Resources Management Ltd,

2001.

[14] Vinexus, Life cycle analysis of RL-200 and RL-300, University of Kalmar,

Sweden, 1997.

[15] Anne H. Landfield, Vijia Karra, Life cycle assessment of a rock crusher,

Resources, Conservation and Recycling Vol. 28, 2000.

[16] Life cycle assessment of a paper and plastic checkout carrier bags, Report of Socio-

economic impact assessment of the proposed plastic bag regulations, Bentley West

Management Consultants, South Africa, 2002.

[17] Comparative Life Cycle Assessment of flooring materials: ceramic versus marble

tiles, Giuseppe M. Nicoletti, Bruno Notarnicola b, Giuseppe Tassielli, Journal of

Cleaner Production Vol.10 2002.

D-2


Table of Cases and Sources

Product Case Source 1 Source 2 Shaver-reuse [1] [2] Shaver disposal [1] [2] Beverage package-Al [1] [3] PET bottle [1] [3] Beverage package-steel [1] [3] CD package-P [1] [4] CD package-M [1] [4] CD package-C [1] [4] CD package-B [1] [4] CD package-D [1] [4] Paper bag [1] [5] Shopping bag-plastic [1] [5] Steel drawer [1] [6] Wooden drawer [1] [6] Steel panel [1] [6] Wooden panel [1] [6] Refrigerator [1] [7] Dish washer [1] [8] TV [1] [7] Coffee machine Pro [1] [5] Coffee machine Sima [1] [5] Electric Heater [1] [9] Washing Machine (Au Top Load) [1] [10] Washing Machine (Au Front Load) [1] [10] Washing Machine (Im. Top Load) [1] [10] Washing Machine (Im, Front Load) [1] [10] PC [1] [11] Power Tool [1] [11] High Pressure Cleaner [1] [7] Electric Pump [1] [7] Hydraulic Activation Unit [1] [7] Cooking pan-Gunda [12] Cooking pan-All Steel [12] Cooking pan -356+ [12] Cooking pan-Hotpan [12]

D-3


Product Case Source 1 Source 2 Hand drier [13] Garbage collector-RL300 [14] Garbage colletor-RL200 [14] Rock crusher [15] Paper sack [16] Plastic sack [16] Ceramic tile [17] Paper towel [13]

D-4

APPENDIX E

LIST OF PUBLICATIONS

• Kaebernick H., Kara S., Sun M., (2002), A Sustainable Manufacturing Paradigm

Introducing Environmental Requirements into Product Development,

Proceedings of the International Manufacturing Leaders Forum Leadership of

Future in Manufacturing, February 8-10, Adelaide, Australia, p.18-25.

• Kara S., Sun M., Kaebernick H., (2002), A Tradeoff Model for Sustainable

Product Development, 9th CIRP Seminar on Life Cycle Engineering, Erlangen,

Germany, April 9-10, pp.103-111.

• Kaebernick H., Kara S., Sun M., (2003), Sustainable Product Development and

Manufacturing by Considering Environmental Requirements, Robotics ad

Computer Integrated manufacturing, Vol. 19, pp. 461-468.

• Kaebernick H., Sun M., Kara S., (2003), Simplified Lifecycle Assessment for

the Early Design Stage of Industrial Products, Annals of CIRP, Montreal,

Canada, August 24-31, pp. 25-28.

• Sun M., Rydh C. J., Kaebernick H., (2004), Material Grouping for Simplified

Product Life Cycle Assessment, Journal of Sustainable Product Design

(Accepted).

• Rydh C.J., Sun M., (2004), Life Cycle Inventory Data for Materials Grouped

According to Environmental and Material Properties, Journal of Cleaner

Production (Accepted).

E-1

sun - 2005 - integrated environmental assessment of industrial

Documents