Final Report Environmental Life Cycle Assessment … report Washing...Document reference: WRAP, 2010, Environmental Life Cycle Assessment (LCA) Study of Replacement and Refurbishment

Final Report

Environmental Life Cycle Assessment (LCA) Study of Replacement and Refurbishment options for household washing machines

Source: DG Enterprise

Project code: MDD019 ISBN:

Research date: October 2008-December 2009 Date: 31 January 2011

WRAP helps individuals, businesses and

local authorities to reduce waste and

recycle more, making better use of

resources and helping to tackle climate

change.

Document reference: WRAP, 2010, Environmental Life Cycle Assessment (LCA) Study of Replacement and Refurbishment

options for household washing machines, MDD019. Report prepared by G Fisher, Banbury, WRAP

Written by: Mark Little, Bernie Thomas, Michael Collins, Simon Aumônier

WRAP and ERM Ltd believe the content of this report to be correct as at the date of writing. However, factors such as prices, levels of recycled content and regulatory

requirements are subject to change and users of the report should check with their suppliers to confirm the current situation. In addition, care should be taken in using

any of the cost information provided as it is based upon numerous project-specific assumptions (such as scale, location, tender context, etc.).

The report does not claim to be exhaustive, nor does it claim to cover all relevant products and specifications available on the market. While steps have been taken to

ensure accuracy, WRAP cannot accept responsibility or be held liable to any person for any loss or damage arising out of or in connection with this information being

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web site: www.wrap.org.uk

1

Executive summary

WRAP commissioned Environmental Resources Management Limited (ERM) to undertake a Life Cycle Assessment

(LCA) study to investigate and to compare replacement and refurbishment options for household washing

machines at the end of their lifetime.

Whilst the manufacture and delivery of a replacement washing machine will incur an environmental cost, it is

assumed that new machines will have an equal or improved energy efficiency compared to the machine they

replace. Conversely, refurbishment will result in lower manufacturing burdens compared to producing a new

washing machine and will delay the purchase of a replacement machine. However, it will not normally result in

improved machine energy efficiency.

This study examines:

the life cycle impacts of the disposal of a washing machine at the end of its lifetime and its replacement with

a new machine, compared with;

refurbishment of the washing machine, resulting in a lifetime extension of three, six or nine years, and its

subsequent replacement after this life time extension.

The life cycle impacts of immediate replacement and refurbishment scenarios are compared for different types C

to A++ EU energy label rated washing machines, based on their modelled performance given in the Market

Transformation Programme’s What If? tool. Data for the manufacturing of washing machines from the relevant

EC Preparatory Study on Ecodesign, and data provided by UK-based washing machine refurbishers, are also used

for the comparison.

In order to reflect the full range of potential future replacement options, this study examines the immediate

replacement, or the post refurbishment replacement, of A and C energy rated machines (from the standard 60°C

cotton wash test cycle) with A, A+ and A++ rated machines over a 12.09 year period (274 wash loads per year).

The study findings are as follows.

Immediate replacement of A and C rated machines with A++ machines represents the most environmental

preferable option for all impact categories except solid waste generation and photochemical oxidation.

With the exception of water use, refurbishment of an A rated machine is environmentally preferential to

immediate replacement with an A or an A+ rated machine. According to the MTP reference scenario data for the

UK, A rated machines will continue to represent the majority of both sales and stock of washing machines until

2020.

The relative benefits of refurbishing a C rated machine compared to its immediate replacement with A or an A+

machine are dependent on the lifetime extension achieved by refurbishment, and the impact category under

consideration.

Sensitivity analyses confirm that the study findings would be likely to hold true under a number of different

assumptions.

Presenting only the study results for Global Warming Potential impact, Tables 0.1 and 0.2 summarise the relative

differences for the replacement and refurbishment scenarios examined.

2

Table 0.1 Global Warming Potential impact values (in Kg CO2 eq) for the replacement versus refurbishment

study scenarios for an 'A' rated household washing machine.

Replaced by: 'A' rated machine

replaced

immediately

'A' rated machine

refurbished, used

for a further 3

years, then

replaced

'A' rated machine

refurbished, used

for a further 6

years, then

replaced

'A' rated machine

refurbished, used

for a further 9

years, then

replaced

A++ 1940 2030 2090 2150

A+ 2290 2290 2260 2240

A 2420 2390 2330 2270

Table 0.2 Global Warming Potential impact values (in Kg CO2 eq) for the replacement versus refurbishment study scenarios for a 'C' rated

household washing machine.

Replaced by:

'C' rated machine

replaced

immediately

'C' rated machine

refurbished, used

for a further 3

years, then

replaced

'C' rated machine

refurbished, used

for a further 6

years, then

replaced

'C' rated machine

refurbished, used

for a further 9

years, then

replaced

A++ 1940 2060 2160 2250

A+ 2290 2320 2330 2340

A 2420 2420 2400 2370

Notes

Colours in the table denote categories for percentage difference in impact values from the best performing scenario where:

0-10% difference from best performing scenario



Machines are either directly replaced immediately, or refurbished and then used for a further x years, then are subsequently

replaced by either A++, A+ or A rated machines for the remaining period.

Values in the tables are expressed in Kg CO2 eq over the 12.09 year period (274 washes per year)

The study is a full comparative LCA which was conducted to the ISO standards on LCA and was independently

peer reviewed by a panel of external experts. It provides a robust indication of the circumstances in which it

would be likely to be beneficial immediately to replace with more efficient machines, and where is preferable to

refurbish washing machines.

However, the findings of the study are limited in their application because:

there are presently only two manufacturers providing A++ rated machines to the UK market, so test cycle

performance data for this category of machine is limited;

consumer use of washing machines has not been addressed in this study; and

there are no robust data available on how long refurbished machines are used in the home.

3

Addendum Post preparation of the final modelling for this study, it came to light that the energy and water consumption data

used in the modelling for A++ energy label rated machines in the report (as sourced from the Market

Transformation Programmes What If? tool) are significantly lower than the two reported manufacturer

declarations for A++ machines which are now available on the UK market (approximately 15% less efficient for

energy use in the standard test cycle).

Readers are advised to interpret the study results for A++ machines in the executive summary and the main

body of the report with some caution as ERM believes that the scale of the benefits communicated for these

machines is likely to be significantly over estimated.

This addendum was agreed with WRAP post preparation of the final report. Given the likely interest in the study

findings, it was decided that publication of this report with an addendum was preferable to any delay to the

dissemination of the results.

4

Contents

Addendum ................................................................................................................................................ 3 1.0 Introduction ................................................................................................................................ 6

1.1 Background .........................................................................................................................6 1.1.1 About WRAP ...........................................................................................................6 1.1.2 This study ...............................................................................................................6 1.1.3 Policy context ..........................................................................................................6

2.0 Goal of the Study ......................................................................................................................... 6 3.0 Scope of the Study ...................................................................................................................... 7

3.1 Function of the Product ........................................................................................................7 3.2 Functional Unit ....................................................................................................................7 3.3 Scenarios Assessed ............................................................................................................ 12 3.4 System Boundaries ............................................................................................................ 12

3.4.1 Production and Assembly ....................................................................................... 14 3.4.2 Use ...................................................................................................................... 14 3.4.3 Refurbishment....................................................................................................... 15 3.4.4 End-of-Life ............................................................................................................ 15 3.4.5 Exclusions ............................................................................................................. 15

3.5 Allocation .......................................................................................................................... 16 3.5.1 Recycling .............................................................................................................. 16 3.5.2 Waste Management: Landfill and Incineration .......................................................... 17 3.5.3 Issues Surrounding Application to the Current Study ................................................. 17

3.6 Data Categories ................................................................................................................. 17 3.7 Cut-Off Criteria .................................................................................................................. 17 3.8 Data Requirements ............................................................................................................ 17 3.9 Data Quality Requirements ................................................................................................. 18 3.10 Inventory Analysis ............................................................................................................. 19 3.11 Impact Assessment Method ................................................................................................ 19 3.12 Interpretation and Sensitivity Analyses................................................................................. 20 3.13 Study Limitations ............................................................................................................... 20 3.14 Reporting .......................................................................................................................... 21 3.15 Critical Review Considerations ............................................................................................. 21

4.0 Inventory analysis ..................................................................................................................... 22 4.1 Production and Assembly .................................................................................................... 22 4.2 Use .................................................................................................................................. 25 4.3 Refurbishment ................................................................................................................... 26 4.4 End of Life ........................................................................................................................ 30 4.5 Data quality validation ........................................................................................................ 31 4.6 Life Cycle Inventory Results ................................................................................................ 31

5.0 Impact Assessment ................................................................................................................... 31 5.1 Replacement with an ‘A’ rated machine compared to refurbishment and subsequent replacement

with an ‘A’ rated machine ................................................................................................................ 32 5.2 Replacement with an ‘A+’ rated machine compared to refurbishment and subsequent

replacement with an ‘A+’ rated machine .......................................................................................... 35 5.3 Replacement with an ‘A++’ rated machine compared to refurbishment and subsequent

replacement with an ‘A++’ rated machine ........................................................................................ 36 6.0 Sensitivity Analyses ................................................................................................................... 38

6.1 Sensitivity Analysis 1: Variations in the distances and mode of transport from production to

consumer ...................................................................................................................................... 38 6.2 Sensitivity Analysis 2: The use of MTP reference scenario energy consumption data for a 40°C

cycle. 40 6.3 Sensitivity Analysis 3: a reduction in washing machine lifetime from 12.09 years to 9 years ...... 42 6.4 Sensitivity Analysis 4: Future, post refurbishment, replacement with a more energy efficient

machine compared to current machine selections for replacement ...................................................... 44 6.5 Sensitivity Analysis 5: Limescale accumulation ...................................................................... 45 6.6 Sensitivity Analysis 6: The use of a projected electricity generation mix for the year 2020. ....... 46

7.0 Discussion .................................................................................................................................. 47 7.1 Results for different washing machine life cycle stages .......................................................... 47 7.2 Replacement with ‘A’ Rated Machines .................................................................................. 47 7.3 Replacement with ‘A+’ Rated Machines ................................................................................ 48

5

7.4 Replacement with ‘A++’ Rated Machine ............................................................................... 48 7.5 Sensitivity Analyses ............................................................................................................ 48 7.6 Context of the results in terms of global warming potential .................................................... 48 7.7 Conclusions ....................................................................................................................... 50 7.8 Recommendations for Further Research ............................................................................... 50

8.0 External Critical Review statement .......................................................................................... 51 9.0 References ................................................................................................................................. 51 10.0 Acknowledgements ................................................................................................................... 53

Table 10.1 Acknowledgements ....................................................................................... 53 Appendix 1 ............................................................................................................................................. 54 Description of Impact Categories ......................................................................................................... 54 11.0 Environmental Impact Categories ............................................................................................ 54

11.1 Climate change (global warming) ........................................................................................ 54 11.2 Abiotic resource depletion ................................................................................................... 54 11.3 Acidification ....................................................................................................................... 54 11.4 Photo-oxidant formation ..................................................................................................... 54 11.5 Solid waste generation ....................................................................................................... 55 11.6 Water consumption ............................................................................................................ 55

Appendix 2 ............................................................................................................................................. 56 Study Data Sources and Assumptions .................................................................................................. 56 12.0 Study data Sources and Assumptions ....................................................................................... 56

12.1 Production and Assembly .................................................................................................... 56 12.2 Use .................................................................................................................................. 56 12.3 Refurbishment ................................................................................................................... 57 12.4 End of Life ........................................................................................................................ 59 12.5 Data Representation .......................................................................................................... 60

Appendix 3 ............................................................................................................................................. 61 Life Cycle Inventory Data for Example Scenario: Refurbish A; replace with A after 3 years .............. 61 Appendix 4 ............................................................................................................................................. 80 Final Critical Review Statement ............................................................................................................ 80

6

1.0 Introduction

1.1 Background

1.1.1 About WRAP The Waste and Resources Action Programme (WRAP) helps individuals, businesses and local authorities to reduce

waste and to recycle more, making better use of resources and helping to tackle climate change.

WRAP’s Manufacturing Programme aims to ensure that materials contained within products at the end of their life

are dealt with in the most cost effective and environmentally sustainable manner and materials with recycled

content are included in the manufacture of consumer products.

1.1.2 This study In order to gain an improved understanding of the environmental impacts associated with the reuse and

refurbishment of household consumer products compared to their replacement, which has become commonplace,

WRAP is undertaking a series of life cycle assessment (LCA) studies.

WRAP commissioned Environmental Resources Management Limited (ERM) to undertake an LCA study to

investigate and to compare replacement and refurbishment options for household washing machines at the end of

their lifetime. The commissioned study is consistent with the requirements of ISO14040ff (1) (2).

This full LCA study builds on a streamlined LCA which gained an insight into the key sensitivities associated with

replacing and refurbishing washing machines. This enabled the system boundaries and data collection effort to

be refined for the full study.

1.1.3 Policy context The European policy context for this study is established in European Directive 2005/32/EC (3) on the eco-design

of Energy-using Products (EuP) and the Waste Framework Directive (2008/98/EC) (4).

In particular, 2008/98/EC defines Extended Producer Responsibility as:

“one of the means to support the design and production of goods which take into full account and facilitate the

efficient use of resources during their whole life-cycle including their repair, re-use, disassembly and recycling

without compromising the free circulation of goods on the internal market”

Also of relevance to this study is the 2008/98/EC definition of waste prevention:

“measures taken before a substance, material or product has become waste, that reduce: (a) the quantity of

waste, including through the re-use of products or the extension of the life span of products”

2.0 Goal of the Study

The goal of this study is to conduct an International Standards Organisation (ISO) 14040 series compliant

comparative LCA, which will provide an indication of the environmental impacts associated with the replacement

of a washing machine at the end of its lifetime compared with those of washing machine refurbishment.

(1) ISO 14040:2006. Environmental management -- Life cycle assessment - Principles and framework. Edition 2,

International Standard Organisation

(2) ISO 14044:2006. Environmental management -- Life cycle assessment – Requirements and guidelines Edition 1,

International Standard Organisation

(3) DIRECTIVE 2005/32/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 6 July 2005 on establishing a

framework for the setting of ecodesign requirements for energy-using products amending Council Directive 92/42/EEC and

Directives 96/57/EC and 2000/55/EC

(4) DIRECTIVE 2008/98/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 19 November 2008 on waste and

repealing certain Directives

7

The study will form part of the evidence base to enable WRAP’s Policy Advisors to reach a policy position

concerning the reuse and refurbishment of consumer items, such as washing machines, relative to product

replacement. A full study report will be published by WRAP.

The study was reviewed, in accordance with the ISO standards on LCA, by an independent review panel.

3.0 Scope of the Study

3.1 Function of the Product

The function of a household washing machine is to clean laundry items, such as clothing, towels and sheets, for

their subsequent and separate drying.

Washing machines work by using a mixture of mechanical energy (the tumbling action of the drum), thermal

energy (the temperature of the wash bath) and chemical action (the detergents used) to clean laundry.

A household washing machine is principally comprised of the following components:

main motor;

cabinet;

concrete counterweight;

drum and basket;

grooved pulley belt;

large pulley wheel;

door and gasket;

electrical heating elements; and

electronic controls.

This study considered front loading washing machines as these represent the majority (approximately 87%) of

machines sold in the UK market (1).

3.2 Functional Unit

The functional unit for the study is defined as washing a total of 3313 full loads (2) of cotton fabric in a standard

60°C cotton wash cycle (3) over a 12.09 year period(4), assuming a typical machine completes 274 washes per

year(3).

This study does not consider the subsequent and separate drying of the laundry, and hence the output from the

study system is 3313 completed full washed loads of moist, spin dried laundry.

The following reference flows, which fulfil this functional unit, are considered in this study:

the disposal of a washing machine at the end of its lifetime and its replacement with a new machine; and

refurbishment of the washing machine, resulting in a lifetime extension of three, six and nine years and its

subsequent replacement(1).

(1) Market Transformation Programme 2005/6 Washing Machine Energy Label Compliance Testing: Post- Consultation Report. Market Transformation Programme

(2) Maximum load capacity will vary between machines with different energy ratings and this factor is accounted for in the MTP data used for this study. For the purposes of this investigation, it is assumed that actual load size does not influence energy consumption. Hence, it is possible to compare results for different machines.

(3) Energy label test standard method is BS EN 60456: 2005. The standard 60°C cotton wash cycle is the recognised benchmark for comparing all washing machines on the European market. The EU Energy Label Data which results from analysis on the standard cycle is provided by all manufacturers for all models. The resulting label is aimed at influencing consumer behaviour and has been used in the study as a tangible reference point to the consumer.

(4) Market Transformation Programme. What If? tool

8

Whilst the manufacture and delivery of a replacement washing machine will incur an environmental cost, it is

assumed that new machines will have an equal or improved energy efficiency compared to the machine they

replace.

The refurbishment process will incur lower manufacturing burdens compared to producing a new washing

machine and will delay the purchase of a replacement machine. However, it will not normally result in an

improved machine energy efficiency.

According to the Energy Saving Trust (EST), the majority of washing machines on the current UK market are ‘A’

rated under the EU Energy Label scheme (2) (3). Figures 3.1 to 3.6 display past and projected trends in the UK

sales and stock of various washing machine energy ratings based on data from the Market Transformation

Programme (MTP) What-If? Tool. These figures are presented for:

a reference scenario, representing the future impact of existing policy measures superimposed on underlying

market trends;

a P1 scenario, which estimates the effects of an ambitious but feasible programme of measures; and

an earliest best practice (EBP) scenario, which indicates what could happen if consumers were to adopt the

best practice options.

The following trends are apparent from the graphs:

current UK appliances (as shown in the reference scenario) are predominantly ‘A’ rated, in terms of both sales

and stock;

a sharp decrease in sales of B and C rated appliances has occurred in the UK over the past decade, resulting

in a gradual reduction in B and C rated appliance stock; and

in the reference scenario a predicted increase in the sales of A+ rated machines will result in increased A+

rated stock in future, however A rated machines are expected to continue to represent the majority of sales

and stock;

(1) Production, use and end of life burdens of the (post refurbishment) replacement machine have been allocated based on the proportion of years utilised by the functional unit.

(2) Energy Savings Trust (2007) Commercial Buyers’ Guide – Indicative Sustainable Product Performance Standards for Washing Machines and Tumble dryers

(3) Under the EU Energy Label, household washing machines are rated A to G according to their energy consumption performance over a standard wash cycle of 60°C. The industry has recently developed A+ and A++ ratings for the most efficient machines.

9

Figure 3.1 Sales of Energy Rated Washing Machines – MTP Reference Scenario

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2,000,000

1980 1985 1990 1995 2000 2005 2010 2015 2020

Year

Exp

ecte

d S

ale

s

A++ A+ A B C

Figure 3.2 Stock of Energy Rated Washing Machines – MTP Reference Scenario

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

14,000,000

16,000,000

18,000,000

20,000,000

1980 1985 1990 1995 2000 2005 2010 2015 2020

Year

Sto

ck

A++ A+ A B C

10

Figure 3.3 Sales of Energy Rated Washing Machines – MTP P1 Scenario

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2,000,000

1980 1985 1990 1995 2000 2005 2010 2015 2020

Year

Exp

ecte

d S

ale

s

A++ A+ A B C

Figure 3.4 Stock of Energy Rated Washing Machines – MTP P1 Scenario

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

14,000,000

16,000,000

18,000,000

20,000,000

1980 1985 1990 1995 2000 2005 2010 2015 2020

Year

Sto

ck

A++ A+ A B C

11

in the P1 scenario, a large increase in the sale of A+ rated machines will result in the stock of these machines

overtaking that of A rated machines in 2012 and continuing to rise till 2020; and

the EBP scenario describes a large increase in the sale of A+ rated machines up until 2010 when these

machines will represent the majority of stock. This scenario also predicts a rapid increase in the sales of A++

Figure 3.5 Sales of Energy Rated Washing Machines – MTP EBP Scenario

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2,000,000

1980 1985 1990 1995 2000 2005 2010 2015 2020

Year

Exp

ecte

d S

ale

s

A++ A+ A B C

Figure 3.6 Stock of Energy Rated Washing Machines – MTP EBP Scenario

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

14,000,000

16,000,000

18,000,000

1980 1985 1990 1995 2000 2005 2010 2015 2020

Year

Sto

ck

A++ A+ A B C

12

rated machines from 2010 onwards with the resulting in the stock of these machines overtaking that of A

rated machines by 2019.

Based on these trends, this study initially focuses on the replacement and refurbishment of A rated machines, but

it also considers less energy efficient C rated machines. Whilst C rated machines only comprise a relatively small

percentage of the current stock, they will make up a substantial proportion of the units currently discarded by

consumers, as those that are discarded now would have been purchased 9 years ago.

3.3 Scenarios Assessed

In order to reflect the full range of potential future replacement options, this study investigates the immediate

replacement or post refurbishment replacement of A and C rated machines with A, A+ and A++ rated machines.

This study therefore assesses 21 replacement and refurbishment scenarios under the following three headings:

Replacement with an ‘A’ rated machine at the end of its life compared to refurbishment and subsequent

replacement with an ‘A’ rated machine

Replacement with an A rated machine.

Refurbish A; replace with A rated machine after three years prolonged life.

Refurbish A; replace with A after six years.

Refurbish A; replace with A after nine years.

Refurbish C; replace with A after three years.

Refurbish C; replace with A after six years.

Refurbish C; replace with A after nine years.

Replacement with an ‘A+’ rated machine compared to refurbishment and subsequent replacement with an ‘A+’

rated machine

Replacement with A+.

Refurbish A; replace with A+ after three years.

Refurbish A; replace with A+ after six years.

Refurbish A; replace with A+ after nine years.

Refurbish C; replace with A+ after three years.

Refurbish C; replace with A+ after six years.

Refurbish C; replace with A+ after nine years.

Replacement with an ‘A++’ rated machine compared to refurbishment and subsequent replacement with an ‘A++’

rated machine

Replacement with A++.

Refurbish A; replace with A++ after three years.

Refurbish A; replace with A++ after six years.

Refurbish A; replace with A++ after nine years.

Refurbish C; replace with A++ after three years.

Refurbish C; replace with A++ after six years.

Refurbish C; replace with A++ after nine years.

3.4 System Boundaries

The study considers the various refurbishment and replacement options available for a washing machine at the

end of its lifetime. This requires an examination of the production, use, refurbishment and end of life

management stages of the washing machine life cycle. Water and energy consumption during use is included

within the system boundaries. Detergent and softener consumption, and waste water treatment burden

associated with use is excluded as these vary according to consumer use rather than the machine rating. This

study does not consider the treatment of clothes (eg drying) following removal from the washing machine.

13

The general system boundaries for the study are shown in Figure 3.7. Figure 3.8 shows the detailed system

boundaries and the specific life cycle stages assessed for the replacement and refurbishment scenarios identified

in Section 3.3. A description of each life cycle stage is also included in this section.

Figure 3.7 System Boundary Flow Chart

Environment: Resources

Material Inputs

Material Inputs

Refurbishment

Manufacture

Use

Water Input

Energy Input

End of Life

Environment: Air, Land & Water

Transport & PackagingT&P

T&P

T&P

T&P

T

T

Disposal

Refurbishment

En

erg

y S

up

ply

Syste

ms O

ther P

rod

uct S

ys

tem

s

T

T

TransportT

Environment: Resources

Material Inputs

Material Inputs

Refurbishment

Manufacture

Use

Water Input

Energy Input

End of Life

Environment: Air, Land & Water

Transport & PackagingT&P

T&P

T&P

T&P

T

T

Disposal

Refurbishment

En

erg

y S

up

ply

Syste

ms O

ther P

rod

uct S

ys

tem

s

T

T

TransportT

14

3.4.1 Production and Assembly Average material composition and assembly burden data (including packaging and transport) were sourced for a

5kg load capacity washing machine. These data are discussed in more detail in Section 4.1.

3.4.2 Use Distances and modes of transport from washing machine production site to the regional distribution centre

(RDC), RDC to the retailer and retailer to the consumer were based on reasoned assumptions made by ERM.

Energy consumption data for a standard 60°C cycle in use were sourced for each washing machine energy rating.

Machine cycle water consumption data were obtained for A and C energy rated machines. Water consumption

for A+ and A++ energy rated machines were extrapolated from A rated machines using the average percentage

change in water consumption between each energy rating class (A to G).

These data are discussed in more detail in Section 4.2

Figure 3.8 Detailed System Boundaries for Replacement and Refurbishment Scenarios

End of Life

Use 12.09 years End of Life

Refurbishment Use(12.09 – x)/12.09

years

Use (X/12.09) years

End of Life(12.09 – x)/12.09

years

Production(12.09-x)/12.09

years

Production

A. Replacement Scenarios

B. Refurbishment Scenarios

12.09 years

T&P

T&P T&P

T T&PT&P

T&P: Transport and Packaging

X: Lifetime extension in years

T

12.09 years

T: Transport

End of Life

T&P

End of Life

Use 12.09 years End of Life

Refurbishment Use(12.09 – x)/12.09

years

Use (X/12.09) years

End of Life(12.09 – x)/12.09

years

Production(12.09-x)/12.09

years

Production

A. Replacement Scenarios

B. Refurbishment Scenarios

12.09 years

T&P

T&P T&P

T T&PT&P

T&P: Transport and Packaging

X: Lifetime extension in years

T

12.09 years

T: Transport

End of Life

T&P

15

3.4.3 Refurbishment Following consultation with refurbishing enterprises such as Independent Service Engineering (ISE) (1) and the

Furniture Reuse Network (FRN) (2), it was established that a typical, financially economical refurbishment requires

the following replacement parts:

a set of stainless steel bearings;

aluminium alloy and stainless steel spider;

carbon brushes; and

hoses.

Materials compositions and weights were obtained for these components.

According to the FRN, refurbishment may involve a range of replacement parts and is only undertaken if

economically viable. The replacement parts outlined above represent a typical refurbishment scenario for a

household washing machine undertaken by the FRN. It was noted that a washing machine’s printed circuit

boards and the motor are not typically replaced as part of the refurbishment process.

As part of the FRN refurbishment process, washing machines are subject to a 60°C cycle without a load (motor

not connected to the drum) and a 40°C cycle with a load. These test cycles were included in the modelling of

refurbishment.

Representative distance and vehicle information was obtained from the FRN and used to model a typical

refurbishment transport scenario.


3.4.4 End-of-Life An estimate for a typical UK ‘take back’ route is included in the study for the washing machine at the end of its life. The study includes the environmental burdens associated with shredding the product.

The transport of shredder residue, packaging and replaced parts from refurbishment to recycling and landfill

operations were also considered.


3.4.5 Exclusions Average material composition and assembly burden data were taken from the ENEA (2007) Preparatory Study for

eco design requirements of energy using products for household washing machines and dishwashers for the

study. Burdens associated with washing machine component sub-assembly are not accounted for in this report.

Its absence is not considered significant and therefore has been excluded from the scope of this study.

The ENEA study states material wastage rates of 5% for metals and 1% for plastics during assembly. It was

assumed that these materials were recycled internally and were therefore excluded from the scope of the study.

Energy consumption when the washing machine is on ‘standby’ and ‘off’, burdens associated with detergent and

softener use and general maintenance during the lifetime of the washing machine were, in the absence of real

data for different machine ratings, excluded from the assessment. This is believed to be a reasonable

assumption as these burdens would be equally applicable to different energy rated machines.

This study does not consider the subsequent and separate drying of the laundry following removal from the

machine; hence factors such as potential differences in spin efficiency are not considered as part of the

(1) Personal Communication: John Hopwood, ISE 3/3/2009

(2) Personal Communication: Craig Anderson, FRN 27/2/2009, and site visit to their Bristol depot (which refurbishes ~1200 machines per year)

16

investigation. Differences in washing performance between machines of different ages have not been considered

as part of the study.

The manufacture and transport of packaging for replacement parts used in washing machine refurbishment were

excluded on a significance basis.

Burdens for discarded washing machines unsuitable for refurbishment, which are recycled by shredding are not

accounted for in the model because the study compares the impacts of a direct-replaced machine with a

refurbished machine.

Capital burdens were not included in this study. Capital burdens are normally insignificant with respect to the

outcome of LCA studies, especially where the production buildings house processes and equipment that are high

throughput and operate for many years. Other burdens associated with shared office/warehousing and the

workforce (eg driving to and from work) were also excluded on the basis of significance.

3.5 Allocation

Allocation is a term used in LCA to describe the designation of environmental loads between different parts of a

system or between systems. To meet the study goal, the following allocation approach has been devised and is

illustrated in Figure 3.9.

3.5.1 Recycling The environmental burdens of transporting material (including packaging) to the recycling operation are assigned

to the product system generating the output (Product 1). No other environmental burdens associated with

recycling are assigned to Product 1.

Environmental burdens associated with waste management operations are assigned to the product system

generating the output (see below). The avoidance of these waste management burdens by sending the output

for recycling represents a benefit for the product system generating the output.

The environmental burdens associated with recycling are assigned to the product system using the recyclate

(Product 2).

These burdens will typically be lower than those associated with the use of virgin material. This difference in

environmental burdens represents a benefit for the product system using the recyclate (Product 2).

Figure 3.9 Allocation Principles for Two Product Systems

Product 1 Recycling

Virgin Material

Product 2

Incineration

Landfill Energy

Energy

17

3.5.2 Waste Management: Landfill and Incineration The environmental burdens associated with landfill and incineration, including transport, are assigned to the

product system generating the output (Product 1).

In the case of both incineration and landfill, it is assumed that the environmental impacts of the waste

management process are not altered by the generation of electricity/heat (i.e. in the case of landfill it is assumed

that operations which do not generate electricity collect and flare landfill gas are used). As a consequence,

electricity/heat generated from these processes are available to other product systems free of burden.

3.5.3 Issues Surrounding Application to the Current Study

Metals The steel used in the appliance is assumed to be 63% virgin; 37% recycled, based on an average of global and

European production mixes (1). It is assumed that 100% of recovered steel is recycled at end of life.

Environmental burdens associated with the production of virgin steel and those associated with the recycling of

scrap steel are assigned to the washing machine system. The environmental burdens associated with the

recycling of the scrap steel leaving the washing machine system are not assigned to the washing machine

system, consistent with the approach outlined in Figure 3.9.

The same principles have been applied to all metals used in the production of the washing machine and washing

machine replacement parts.

It should be noted that this approach incentivises the increased use of recyclate. The amount of scrap steel

available in the market is relatively stable and is driven by availability of scrap as opposed to demand. Therefore,

the increased use of recyclate by one system might result in another using a higher percentage of virgin material

in its product. This represents a limitation of the current allocation approach.

3.6 Data Categories

The following data categories will be included in the study:

material and chemical inputs (2);

energy inputs;

resource inputs, such as water;

material outputs, including solid waste generation;

emissions to air, water and soil;

transport; and

packaging.

3.7 Cut-Off Criteria

Cut-off criteria have been avoided where possible. Where this was not practical, it was considered acceptable for

mass flows that on aggregate are known to contribute less than 2% of inputs to a life cycle stage to be omitted

from the inventory analysis. It is ERM’s belief that the cut-off criteria outlined above do not have an effect on the

final results. Cut-off criteria have not been applied with respect to any identified, but unquantified, potentially

toxic or eco-toxic flows.

3.8 Data Requirements

The data requirements for this LCA study are summarised below. Primary data and robust secondary data from

published sources and personal communications have been obtained for:

(1) As specified in the Ecoinvent Life Cycle Inventory database, Version 2 developed by the Swiss Centre for Life Cycle Inventories, Sweden.

(2) Excluding detergent and softener as outlined in Section 3.4.5

18

average material composition and assembly burden data (including packaging and transport) for a 5kg load capacity washing machine;

typical transport distances/modes for delivery from production to consumer;

energy and water consumption for a standard 60°C cycle;

average washing machine lifetime and number of cycles completed per year;

type, material composition and weights of replacement parts used for a typical refurbishment process;

details of test cycles used during the refurbishment process;

inventory data for the manufacture of bearings;

transport distances and modes associated with refurbishment; and

energy consumption data representative of a shredding operation.

Ecoinvent database processes have been used to represent the following inventory flows:

production of minor material inputs, where these are identified;

electricity generation (current average medium voltage supply mix for Great Britain);

packaging production;

waste management operations;

production of transport fuels; and

fuel consumption and associated emissions for haulage vehicles.

Estimated data have been used for:

burdens associated with transport of washing machine and replacement parts for refurbishment to consumer

and refurbishment operation respectively;

washing machine materials (including replacement parts) and packaging recycling rates;

transport of washing machines to shredding operation; and

transport of shredder residue, waste replaced parts from refurbishment and packaging to waste management operations.

3.9 Data Quality Requirements

Data quality requirements are defined Table 3.1. These are based on the ISO standard on goal and scope

definition and inventory analysis. (1)

Table 3.1 Data Quality Requirements

Parameter Description Requirement

Time-related coverage Desired age of data and the

minimum length of time over

which data should be collected.

General data and database

data should represent the

situation in 2008, and not be

more than 5 years old.

Geographical coverage Area from which data for unit

processes should be collected.

Data should be representative

of UK or European

marketplace.

Technology coverage Technology mix. Data should be representative

of average or typical mix of

technology.

Precision Measure of the variability of

the data values for each data

category expressed.

Representative point data will

be used in the study. Where

there is potential variability in

the data and these are

established as potentially

significant, sensitivity analysis

will be used to determine the

effect on the outcome of the

study.

(1) ISO14044:2006. Environmental management - Life Cycle Assessment - Requirements and guidelines Edition 1, International Standards Organisation,

19

Parameter Description Requirement

Completeness Assessment of whether all

relevant input and output data

are included for a certain data

set.

Specific datasets will be

benchmarked with literature

data and databases. Simple

data validation checks (eg

mass balances) will be

performed.

Representativeness Degree to which the data

represents the identified time-

related, geographical and

technological scope.

The data should fulfil the

defined time-related,

geographical and technological

scope.

Reproducibility Assessment of the method and

data, and whether an

independent practitioner will

be able to reproduce the

results.

The information about the

method and the data values

should allow an independent

practitioner to reproduce the

results reported in the study.

Sources of the data Assessment of data sources

used.

Data will be derived from

credible sources and

databases.

3.10 Inventory Analysis Life cycle inventory data are presented under the following headings:

production and assembly (including transport of components to assembly operation);

use (including transport of washing machine to regional distribution centre, retail store and consumer);

refurbishment (including transport of washing machine to refurbishment operation and transport of

refurbished machine to user); and

end of life (including transport to and between waste management operations).

3.11 Impact Assessment Method

Inventory results for each life cycle stage are characterised using the CML impact assessment method (1).

Environmental impacts are reported for the following categories:

climate change (GWP100);

abiotic resource depletion;

acidification;

photochemical oxidation potential (i.e. smog);

solid waste generation (2); and

water consumption.

These categories were selected in order to understand a wide range of environmental impacts, including the

environmental objectives of European product policy. Each impact category is described in Appendix 1.

It should be noted that the life cycle impact assessment indicators applied reflect potential, not actual, impacts

and take no account of the local receiving environment.

Normalisation and weighting of results have not been undertaken.

(1) Version 2.04, February 2008, developed by the Centre for Environmental Studies, University of Leiden, The Netherlands.

(2) Includes all material sent to waste management operations including recycling.

20

3.12 Interpretation and Sensitivity Analyses

The results for the replacement and refurbishment scenario comparisons have been interpreted to determine the

preferred environmental options in the context of data and method uncertainties. The results have also been

interpreted to indicate the scale and significance of the differences between environmental profiles for the

different replacement and refurbishment options.

Sensitivity analyses have been performed in order to determine the significance of the following on the initial

findings of the study:

variations in the distances and mode of transport from production source to the consumer;

the use of MTP reference scenario energy consumption data for a 40°C cycle;

a reduction in washing machine lifetime from 12.09 years to 9 years;

a future, post refurbishment, replacement with a more energy efficient A+ rated machine compared to

current replacement with an A rated machine;

limescale accumulation on the heating elements of the machine; and

the use of a projected future electricity generation mix for the year 2020.

3.13 Study Limitations

The study is a comparative LCA which evaluates replacement and refurbishment scenarios for household washing

machines. Whilst the study is a fair comparative LCA, and provides a robust indication of the life cycle burden of

different replacement and refurbishment scenarios in line with the study goal, it does not provide an estimate for

the actual burden caused by a washing machine in its lifetime for the following reasons.

The energy and water use profile for each rated machine used in the study is not based on real time

monitoring data for washing machines as they are used in the home. The study is limited to published data

on energy and water consumption taken from the Market Transformation Programme’s (MTP) What If? Tool.

To commission research specifically to obtain this type of primary data that is representative of UK consumers

(and future consumers) was beyond the resources available for the study.

MTP energy consumption data are based on a 60°C cotton wash test cycle. However, there is no evidence to

suggest that the 60°C test cycle is representative of consumer behaviour. In the absence of data relating to

consumer cycle preference and energy consumption data for other cycles, ERM used the MTP energy

consumption data for a 60°C cycle, since these data are based on the industry standard test against which all

machines are benchmarked. This is supplemented in the study by a sensitivity analysis using MTP energy

consumption data for a 40°C cycle (1).

MTP energy consumption data are calculated using assumed average machine load capacities which vary

between energy rating classes (machines with better energy efficiency typically have a higher load capacity).

Following consultation with MTP, this study assumes that a reduction in washing machine load size does not

affect the actual cycle energy consumption (2). As a result, energy consumption data for different washing

machine energy ratings are comparable. However, in reality certain models may incorporate an automatic

load adjustment feature, resulting in reduced energy consumption for reduced loads (3). Further research is

(1) Data based on the MTP assumption that a 40°C cycle uses 40% less energy than a 60°C cycle; see Appendix 2 for further information.

(2) According to the MTP research, reduced load size does not always result in reduced energy consumption for a 40°C cycle and the MTP has not performed tests for a 60°C cycle. Personal Communication Nicola King 10/3/2009

(3) Rüdenauer, I.; Gensch, C.; Quack, D. (2005) Eco-Efficiency Analysis of Washing Machines, Öko Instit e.V., assumes between a 13% and 21% reduction for a 60% reduced load at 60°C cycle.

21

required to test this assumption.

Machine cycle water consumption data for each energy rating class were sourced from MTP and are

calculated data based using assumed average machine load capacities. Water consumption for A+ and A++

energy rated machines were extrapolated by ERM from A rated machines using the average percentage

change in water consumption between each energy rating class (A to G).


machine. Hence, factors such as potential differences in spin efficiency are not considered as part of the

investigation.

Differences in washing performance between machines have not been considered as part of the study.

This study is also limited by the quality of available data for washing machine production, refurbishment and end

of life. Data were not available for certain aspects of these life cycle stages. Washing machine sub-assembly

was excluded from the scope of the study and reasonable assumptions were made relating to the transport of

washing machines to the final user. The same washing machine production and assembly data were applied to

all washing machines, irrespective of their energy rating and assumed load capacity.

No suitable information was available on the actual lifetime extension achieved by machine refurbishment period.

As a result, this study considers lifetime extension periods of three, six and nine years for each refurbishment

option assessed. Where important assumptions were made, their importance to the overall study results was

tested by sensitivity analyses.

Energy mix data for 2006 were used to represent washing machine energy consumption figures for the entire

12.09 year period under investigation. This represents a potential limitation of the study. The effect of energy

mix on the outcome of the study was examined through a sensitivity analysis using projected energy mix data for

the year 2020.

3.14 Reporting

According to ISO14040, when results of an LCA are to be communicated to any third party, a third-party report

shall be prepared. The third party report shall be made available to anyone to whom the communication is

made.

The final report fulfils the demands according to the ISO standard for a third party report and has been subject

to peer review.

3.15 Critical Review Considerations

In accordance with the ISO standard on LCA, the study has been reviewed by an external independent critical

reviewer. The reviewer’s statement is included in the final report. The critical review has been performed by an

independent review panel chaired by:

Dr David Dowdell

Ove Arup & Partners Ltd

Arup Campus, Blythe Gate , Blythe Valley Park

Solihull

West Midlands, B90 8AE

Tel.: +44 (0)121 213 3423

Fax.:+44 (0)121 213 3001

[email protected]

The other reviewers were: David Parker, Head of Remanufacturing, Oakdene Hollins; and Bob Shaw,

independent consultant, former Wet Laundry R&D Manager for a UK washing machine manufacturer.

22

4.0 Inventory analysis

This section details the life cycle inventory data used in this study.

The inventory analysis procedure involves data collection and calculations to quantify relevant inputs and outputs

for processes. Primary data and robust secondary data from published sources and personal communications are

presented for washing machine production and assembly, use, refurbishment and end of life. Data sources and

key data assumptions for this study are detailed in Appendix 2.

4.1 Production and Assembly

Average production (material composition) and assembly burden data (including packaging and transport) for a

5kg load capacity washing machine were taken from the ENEA (2007) Preparatory Study. Washing machine

component production and assembly is assumed to take place in Europe and Great Britain respectively. These

data, together with the processes used to represent each flow are presented in Table 4.1 and Table 4.2.

23

Table 4.1 Data Describing the Production of an Average 5kg Load Capacity Washing Machine

Category Flow Unit Amount Data representation

Material input:

ferrous metals Cast iron kg 6.214 Cast iron, at plant/RER SNI

Iron

kg 4.978 Cast iron, at plant/RER SNI

Stainless steel kg 1.939 Chromium steel 18/8, at plant/RER SNI

Stainless steel

sheet

kg 0.564 Chromium steel 18/8, at plant/RER SNI

Steel kg 12.521 Low-alloyed steel, at plant/RER SNI

Steel strip kg 6.145 Low-alloyed steel, at plant/RER SNI

Non ferrous

metals

Aluminium kg 1.503 Aluminium production mix, at plant/RER SNI

Sheet rolling, aluminium/RER SNI

Aluminium

sheet

kg 0.001 Aluminium production mix, at plant/RER SNI


Aluminium

casting

(recycled 80%)

kg 0.729 Aluminium, 80% recycled mix, cast alloy, at

plant/RER SNI

Brass kg 0.014 Brass, at plant/RER SNI; Casting, Brass, at

plant/RER SNI

Copper wire kg 0.348 Copper, at regional storage/RER SNI; Wire

drawing, copper/RER SNI

Chromium kg 1.761 Chromium, at regional storage/RER SNI

Copper kg 0.869 Copper, at regional storage/RER SNI

Nickel kg 0.001 Nickel, 99.5% at plant/RER SNI

Zinc die casting kg 0.085 Zinc, at plant/RER SNI

Packaging Cardboard kg 0.107 Corrugated board, mixed fibre, single wall, at

plant/RER SNI

EPS kg 0.678 Polystyrene, expandable, at plant/RER SNI;

Foaming, expanding/RER SNI

Paper (booklets

etc)

kg 0.01 Paper, newsprint, at regional storage/RER SNI

PE - foil kg 0.175 Polyethylene, LDPE, granulate/RER SNI;

Extrusion, plastic film/RER SNI

Plastics, others kg 0.056 Polyethylene terephthalate, granulate,

amorphous, at plant/RER SNI; Extrusion, plastic

pipes/RER SNI

PP kg 0.008 Polypropylene, granulate, amorphous, at

plant/RER SNI; Extrusion, plastic pipes/RER SNI

Wood kg 0.879 EUR-flat pallet/RER SNI

Plastics ABS kg 1.145 Acrylonitrile-butadiene-styrene copolymer, ABS,

at plant/RER SNI; Extrusion, plastic pipes/RER

SNI

EPDM – rubber kg 1.675 Synthetic rubber, at plant/RER SNI; Extrusion,

plastic pipes/RER SNI

PA kg 0.006 Nylon 66, at plant/RER SNI; Extrusion, plastic

pipes/RER SNI

PA 66 kg 0.088 Nylon 66, at plant/RER SNI; Extrusion, plastic

pipes/RER SNI

PC kg 0.188 Polycarbonate, at plant/RER SNI; Extrusion,


24


PC-G (Glass

Reinforced

kg 0.002 Polycarbonate, at plant/RER SNI; Extrusion,


PE kg 0.010 Polyethylene, LDPE, granulate/RER SNI;

Extrusion, plastic pipes/RER SNI

Plastics, others kg 1.037 Polyethylene terephthalate, granulate,


pipes/RER SNI

POM kg 0.041 Polyethylene terephthalate, granulate,


pipes/RER SNI

PP kg 5.402 Polypropylene, granulate, amorphous, at


PP-K40 kg 2.533 Polypropylene, granulate, amorphous, at


PPO (=PPE) kg 0.002 Polyethylene terephthalate, granulate,


pipes/RER SNI

PPS-GF kg 0.076 Polyphenylene sulfide, at plant/GLO SNI;

Extrusion, plastic pipes/RER SNI

PVC kg 0.221 Polyvinylchloride at regional storage; Extrusion,


PBT kg 0.008 Polyethylene terephthalate, granulate,

amorphous, at plant/RER SNI; Extrusion,


Various Bitumen kg 0.038 Bitumen, at refinery/RER SNI

Concrete kg 18.180 Concrete block, at plant/DE SNI

Electronic,

boards,

switches, lamp,

etc

kg 0.165 Printed wiring board, mixed mounted, unspec.,

solder mix, at plant/GLO SNI

Filter kg 0.028 Polyethylene terephthalate, granulate,


pipes/RER SNI

Glass kg 1.773 Packaging glass, white, at plant/DE SNI

Gravel kg 0.025 Gravel, crushed, at mine/CH SNI

Oil – Feet kg 0.028 Light fuel oil, at regional storage/RER SNI

Others kg 0.204 EUR-flat pallet/RER SNI

Paper (booklets

etc)

kg 0.106 Paper, newsprint, at regional storage/RER SNI

Wiring kg 0.088 Copper, at regional storage/RER SNI; Wire

drawing, copper/RER SNI

Wood kg 1.573 EUR-flat pallet/RER SNI

25

Table 4.2 Data Describing the Assembly of an Average 5kg Load Capacity Washing Machine


Energy input

Electricity kWh 29.98 Electricity, medium voltage, production GB, at

grid/GB SNI

Heat kWh 14.79 Heat, natural gas, at boiler condensing

modulating >100kW/RER SNI

Resource input Water m3 0.59 Water, deionised, at plant/CH SNI

Material input Lubricating Oil kg 0.045 Lubricating oil, at plant/RER SNI

Phosphating kg 0.047 Excluded

Transport Lorry km 324 Transport, lorry 16-32t, EURO4/RER SNI

Train km 324 Transport, freight, rail/RER SNI

4.2 Use

Energy and water consumption data for the different energy rated machines were taken from Market

Transformation Programme (MTP) What If? Tool (2007 reference scenario data), and are presented in Table 4.3.

These data were calculated based on assumed average load capacity data which are also presented in Table 4.3.

ERM assumptions relating to distances and modes of transport from production site to the regional distribution

centre (RDC), RDC to the retailer and retailer to the consumer are presented in Table 4.4.

Table 4.3 Data Describing the Use of a Washing Machine

Category Flow Unit Washing machine

energy rating

Data representation

C A A+ A++

Energy

input

Electricity kWh/cycle 1.12 1.06 1.00 0.83 Electricity, medium voltage,

production GB, at grid/GB SNI

Resource

input

Water litres/cycle 75 53 44.2 36.8 Tap water, at user/RER SNI

Average

Load

Capacity

kg 4.80 5.72 6.04 8.00 Used to calculate electricity and

water consumption/cycle values

Table 4.4 Data Describing the Transport of a Washing Machine to Regional Distribution Centre, Retail Store and to the Consumer


Transport

to RDC Lorry km 250 Transport, lorry 16-32t, EURO4/RER SNI

to retail store Lorry km 25 Transport, lorry 16-32t, EURO4/RER SNI

to consumer Van km 10 Transport, van <3.5t/RER SNI

26

4.3 Refurbishment

Typical economic refurbishment burdens were sourced from the Furniture Reuse Network (FRN) (1) and are

presented in Tables 4.5 to 4.7. 88% of machines received by the FRN are sourced directly from the consumer.

The remaining 12% are predominantly WEEE from central distribution centres. 9% are transported by small lorry

and 3% are transported by articulated lorry. Inventory data for the manufacture of roller bearings were obtained

from Ekdahl (2001) Life Cycle Assessment on SKF’s Spherical Roller Bearing. These data were adapted and used

to represent stainless steel bearing manufacture. This modified dataset is presented in Table 4.8.

Table 4.5 Data Describing a Typical Economic Refurbishment by the Furniture Reuse Network (FRN): Replacement Parts


Material input Ball bearing set:

stainless steel

kg 0.571 Roller bearing Manufacture (See Table 4.8)

Spider:

aluminium alloy

kg

2.355 Aluminium alloy, AlMg3, at plant/RER SNI;


Spider: stainless

steel

kg 0.225 Chromium steel 18/8, at plant/RER SNI Wire

drawing steel/RER SNI

Carbon brush:

carbon

kg 0.006 Graphite, at plant/RER SNI

Carbon brush:

nylon

kg 0.018 Nylon 66, at plant/RER SNI; Extrusion, plastic

pipes/RER SNI

Carbon brush:

stainless steel

kg 0.004 Chromium steel 18/8, at plant/RER SNI

Carbon brush:

brass

kg 0.022 Brass, at plant/RER SNI; Casting, Brass, at

plant/RER SNI

Carbon brush:

steel

kg 0.002 Low-alloyed steel, at plant/RER SNI; Wire

drawing steel/RER SNI

Hoses: PVC kg 0.46 Polyvinylchloride at regional storage; Extrusion,


Transport;

replacement

parts

to RDC Lorry km 250 Transport, lorry 16-32t, EURO4/RER SNI

To retail store Lorry km 25 Transport, lorry 16-32t, EURO4/RER SNI

To consumer Van km 10 Transport, van <3.5t/RER SNI

Table 4.6 Data Describing a Typical Economic Refurbishment by the Furniture Reuse Network (FRN): Test Cycles

Category Flow Unit Washing machine

energy rating

Data representation

C A

Energy

input

Electricity:

60°C cycle;

no clothes

kWh/cycle 0.56 0.53 Electricity, medium voltage, production

GB, at grid/GB SNI

Electricity:

40°C cycle;

with clothes

kWh/cycle 0.67 0.64 Electricity, medium voltage, production

GB, at grid/GB SNI

Resource

input

Water litres/cycle 75 53 Tap water, at user/RER SNI

(1) Personal Communication: Craig Anderson FRN 27/2/2009

27

Table 4.7 Data Describing a Typical Economic Refurbishment by the Furniture Reuse Network (FRN): Transport


Transport

to FRN direct route Lorry km 8 Transport, lorry 3.5-7.5t, EURO4/RER SNI

to FRN centrally

distributed

Lorry km 322 Transport, lorry 16-32t, EURO4/RER SNI

to FRN centrally

distributed

Lorry km 50 Transport, lorry 3.5-7.5t, EURO4/RER SNI

FRN to user Lorry km 8 Transport, lorry 3.5-7.5t, EURO4/RER SNI

Table 4.8 Data Used to Describe the Manufacture of Stainless Steel Ball Bearings


Production of

wire rod:

Material input

Stainless steel

billets

kg

1.00E+03 Chromium steel 18/8, at plant/RER SNI

amended: no hot rolling process

Cutting fluid

kg 5.01E-05 Lubricating oil, at plant/RER SNI

Hydraulic Oil


Hydrochloric

acid

kg 1.88E-05 Hydrochloric acid, 30% in H2O, at plant/RER

SNI

Energy input Electricity J

1.59E+06 Electricity, medium voltage, production GB, at

grid/GB SNI

LPG

J 4.06E+06 Propane/ butane, at refinery/RER SNI

Light fuel oil

J 1.48E+05 Light fuel oil, at refinery/RER SNI

Resource input Surface water

kg 3.03E-01 Water, process and cooling, unspecified natural

origin

Emissions to

air

CO kg

2.55E-05 Specific emission

CO2

kg 2.66E-01 Specific emission

NOx


SO2


Soot

kg 2.48E-07 Particulates, < 10 um (stationary)

Emissions to

water

BOD kg 8.34E-07 Specific emission

Cd


COD


Cr


Cu


Fe


Mineral oil

products


Ni


28


Pb


Suspended

solids


Zn


Material

output; waste

Hazardous kg 4.90E-03 Process-specific burdens, residual material

landfill/CH SNI

Hydrochloric

acid

kg 1.88E-05 Process-specific burdens, residual material

landfill/CH SNI

Oxide scale


landfill/CH SNI

Steel scrap

kg 1.08E-01 Assumed recycled: excluded

Material input;

waste

Cement kg 2.95E-03 Cement, unspecified, at plant/CH SNI

Transport;

waste

Transport to

recycling

km 250 Transport, lorry 16-32t, EURO4/RER SNI

Transport;

waste

Transport to

landfill


Production of

surface

removed wire:

Material input Wire rod kg

1.00E+03 Modelled process

Blasting grit

kg 9.58E-03 Sand, at mine/CH SNI

Chemicals

kg 2.78E-03 Chemicals inorganic, at plant/GLO SNI

Cutting fluid


Hydraulic oil


Methanol

kg 1.45E-02 Methanol, at plant/GLO SNI

N2

kg 3.02E-

01

Nitrogen, liquid, at plant/RER SNI

Other paper

kg 1.74E-04 Kraft paper, unbleached, at plant/RER SNI

Soap

kg 2.02E-04 Soap, at plant/RER SNI

Sodium nitrite

kg 2.89E-04 Excluded

Energy inputs Electricity

J 5.09E+06 Electricity, medium voltage, production GB, at

grid/GB SNI

Hot water

J 5.85E+02 Natural gas, high pressure, at consumer/RER

SNI

Resource

inputs

Surface water kg 1.73E+-2 Water, process and cooling, unspecified natural

origin

Emissions to

air

CH4 kg 8.73E-04 Specific emission

CO


CO2


H2


N2


O2


29


Emissions to

water

Waste water kg 1.74E+02 Treatment, sewage, to wastewater treatment,

class 2/CH SNI

Material

outputs; waste

Blasting grit kg 9.85E-03 Process-specific burdens, residual material

landfill/CH SNI

Emulsion


landfill/CH SNI

Sludge


landfill/CH SNI

Steel scrap


Waste paper


Material input;

waste


Transport;

waste

Transport to

recycling


Transport;

waste

Transport to

landfill


Manufacture of

rollers:

Material input

Surface

removed wire kg 1.85 Modelled process

Anticorrosive

agent


Blasting grit

kg 5.94E-03 Sand, at mine/CH SNI

Cutting fluid


Dissolvent

kg 1.56E-02 Solvents, organic, unspecified, at plant/GLO SNI

Hydraulic oil


Trumbling chip

kg 9.13E-02 Excluded

Energy inputs District heating

J 2.17E+07 Heat, natural gas, at boiler modulating

>100kW/RER SNI

Electricity

J 2.94E+07 Electricity, medium voltage, production GB, at

grid/GB SNI

Emission to

water

Waste water

kg 1.20E-01 Treatment, sewage, to wastewater treatment,

class 2/CH SNI

Material

output; waste

Emulsion kg 1.92E-01 Process-specific burdens, residual material

landfill/CH SNI

Grinding dust


landfill/CH SNI

Mineral oil

products


landfill/CH SNI

Other paper


Other rest

products


landfill/CH SNI

Paper and

board


Sludge


landfill/CH SNI

Steel scrap


Trumbling chip


landfill/CH SNI

Wood


30


Material input;

waste


Transport;

waste

Transport to

recycling


Transport;

waste

Transport to

landfill


4.4 End of Life An estimated typical UK ‘take back’ route for washing machines and energy consumption data for the shredding of the product, taken from Manouchehri (2006) Mapping and development of shredding product stream(s): four shredding plants in Sweden, are presented in Table 4.9.

Waste and Resources Assessment Tool for the Environment (WRATE) recommended transport assumptions were

used to model distances for the transport of shredder residue, washing machine packaging and waste replaced

parts (generated from their replacement as part of the refurbishment process) to recycling and landfill

operations. Washing machine material (shredder residue) and packaging recycling rates used in this study are 80% and 75%, respectively. These figures were based on the recovery and recycling targets as outlined in Article 7 of the Waste Electrical and Electronic Equipment (WEEE) and DEFRA statistics. It was assumed that the remaining waste material is sent to landfill.

Table 4.9 Data used to Represent a Typical ‘Take Back’ Route and waste management Operations for Washing Machines, Packaging and

Waste Replaced Parts from Refurbishment.


Energy input Electricity kWh 39 Electricity, medium voltage, production GB, at

grid/GB SNI

Material output

Washing machine

materials

Landfill

kg

18.1

Disposal, inert waste, 5% water, to inert

material landfill/CH SNI

Packaging

Paper, cardboard

Landfill

kg

0.023

Disposal, packaging cardboard, 19.6% water, to

sanitary landfill/CH SNI

Plastics Landfill kg 0.183 Disposal, inert waste, 5% water, to inert


Wood Landfill kg 0.176 Disposal, wood untreated, 20% water, to

sanitary landfill/CH SNI

Waste replaced

parts

Landfill kg 0.916 Disposal, inert waste, 5% water, to inert


Transport

to local household

waste recycling

centre

16-32 tonne

lorry

km

10

Transport, lorry 16-32t, EURO4/RER SNI

To local salvage

yard

16-32 tonne

lorry


To regional

shredder facility

16-32 tonne

lorry


To recycling 16-32 tonne

lorry


To landfill 16-32 tonne

lorry


31

4.5 Data quality validation

Data quality checks have been performed for each identified flow and the secondary data used to represent

these flows using the criteria identified in Table 3.1. These included an assessment of data representativeness,

identification of necessary sensitivity analyses, benchmarking against other literature sources, and simple mass

balance and other calculation checks. Internal reviews of the life cycle model developed for the study were also

undertaken.

4.6 Life Cycle Inventory Results

An example of the results on the life cycle inventory analysis procedure is presented in Appendix 3 for the

following scenario: Refurbishment of an A rated machine and subsequent replacement with an A machine after

three years.

5.0 Impact Assessment

The potential life cycle impacts associated with the washing machine replacement and refurbishment scenarios

examined in the study are presented in this section.

The scenario results have been separated into three subsections:

replacement with an ‘A’ rated machine compared to refurbishment and subsequent replacement with an ‘A’

rated machine;

replacement with an ‘A+’ rated machine compared to refurbishment and subsequent replacement with an

‘A+’ rated machine; and

replacement with an ‘A++’ rated machine compared to refurbishment and subsequent replacement with an

‘A++’ rated machine.

Tables 5.1-5.6 provide the calculated impacts results for each of the scenarios. It should be noted that the

tabulated results are quoted to three significant figures and values may therefore not sum due to rounding.

Each table is then followed by the presentation of these results in bar charts (Figures 5.1-5.6). Values in the

charts are expressed as percentages of the largest value of each impact category in order to allow visual

comparison between the different impact categories. Commentary is provided at the end of each subsection on

the main findings of the comparisons.

For the purposes of simplicity, all table and figure headings in this section have been abbreviated using the

following approach:

replacement becomes ‘ Replace’

x rated machine becomes ‘x’

compared with becomes ‘/’

refurbishment of ‘x’ Rated Machine (with Subsequent Replacement with ‘y’ Rated Machine) becomes ‘Refurb x

then Replace y’

Such that ‘Immediate Replacement with ‘A’ Rated Machine Compared with Refurbishment of ‘A’ Rated Machine

(with Subsequent Replacement with ‘A’ Rated Machine)’ (Table 5.1) becomes ‘Replace A / Refurb A then Replace

A’

32

5.1 Replacement with an ‘A’ rated machine compared to refurbishment and subsequent replacement with an ‘A’ rated machine

Table 5.1 provides results for the replacement with an ‘A’ rated machine compared to refurbishment and

subsequent replacement with an ‘A’ rated machine scenario set. The table breaks down the relative contributions

of the different life cycle stages to each of the impacts.

Table 5.1 Replace ‘A’/ Refurb ‘A’ then Replace ‘A’ (1)

1 Impact

Category

Unit Scenario Production/

Assembly

Transport

to User

Use Refurbishment

End of Life Total

IPCC GWP 100a kg CO2 eq S1 223 3.58 2180 - 9.89 2420

S2 168 2.69 2180 25.3 8.76 2390

S3 112 1.80 2180 25.3 7.53 2330

S4 57.0 0.915 2180 25.3 6.30 2270

Resource

depletion

kg Sb eq S1 1.91 0.0226 16.7 - 0.0665 18.7

S2 1.44 0.0170 16.7 0.146 0.0586 18.4

S3 0.964 0.0114 16.7 0.146 0.0506 17.9

S4 0.489 0.00579 16.7 0.146 0.0424 17.4

Acidification kg SO2 eq S1 1.03 0.0127 7.33 - 0.0357 8.41

S2 0.774 0.00955 7.33 0.0885 0.0316 8.23

S3 0.519 0.00640 7.33 0.0885 0.0272 7.97

S4 0.263 0.00325 7.33 0.0885 0.0227 7.71

Photochemical

oxidation

kg C2H4 S1

0.138 0.00220 0.452 - 0.00486

0.598

S2 0.104 0.00165 0.452 0.00974 0.00430 0.572

S3 0.0697 0.00111 0.452 0.00974 0.00370 0.537

S4 0.0354 0.000561 0.452 0.00974 0.00309 0.501

Solid waste

generation

Kg S1 0.00 0.00 0.00 - 148 148

S2 0.00 0.00 0.00 0.00 134 134

S3 0.00 0.00 0.00 0.00 115 115

S4 0.00 0.00 0.00 0.00 96.9 96.9

Water

litres S1 0.00 0.00 17600

0

- 0.00 17600

0

S2 0.00 0.00 17600

0

53.0 0.00 17600

0

S3 0.00 0.00 17600

0

53.0 0.00 17600

0

S4 0.00 0.00 17600

0

53.0 0.00 17600

0

(1) S1: Replacement with ‘A’ rated machine

S2: Refurbishment and subsequent replacement with ‘A’ rated machine after three years

S3: Refurbishment and subsequent replacement with ‘A’ rated machine after six years

S4: Refurbishment and subsequent replacement with ‘A’ rated machine after nine years

33

Table 5.1 and Figure 5.1 show that the use stage of the washing machine life cycle makes the dominant

contribution to all impact categories except solid waste generation. Electricity generation is responsible for the

majority (>95%) of the impacts in the global warming resource deletion, acidification and photochemical

oxidation categories.

Washing machine production and assembly make an important contribution to global warming, resource

depletion, acidification and photochemical oxidation. The majority of the burden in these categories is associated

with the production of ferrous, non ferrous metals and plastics that comprise the components of the machine, as

well as electricity generation and natural gas combustion used in the assembly process.

Refurbishment makes a small (<5%) contribution to global warming, resource depletion, acidification and

photochemical oxidation, with the majority of potential impacts associated with the manufacture of the

aluminium alloy spider and the stainless steel ball bearing set. End of life is only important in terms of solid

waste generation.

The variation between the replacement and refurbishment scenarios in the global warming, resource depletion,

acidification and photochemical oxidation impact categories is due to differences in the burdens associated with

washing machine production.

The results demonstrate that the length of lifetime extension achieved by refurbishment has a strong influence

on the environmental benefits realised.

For global warming potential, resource depletion, acidification and photochemical oxidation, and solid waste

generation, refurbishment resulting in a lifetime extension of three years is of benefit for an A rated machine.

Figure 5.1 Replace ‘A’/Refurb ‘A’ then Replace

‘A’

0

10

20

30

40

50

60

70

80

90

100

S1 S2 S3 S4 S1 S2 S3 S4 S1 S2 S3 S4 S1 S2 S3 S4 S1 S2 S3 S4 S1 S2 S3 S4

End of Life

Refurbishment

Use

Transport to User

Production/Assembly

IPCC GWP 100a Resource depletion Acidification Photochemical oxidation Solid waste generation Water

%

34

Table 5.2 Replace ‘A’/Refurb ‘C’ then Replace ‘A’

Impact category Unit

Replace

with A.

Refurbish

C; Replace

with A

after three

years.

Refurbish

C; Replace

with A

after six

years.

Refurbish

C; Replace

with A

after nine

years.

IPCC GWP 100a kg CO2 eq 2420 2420 2400 2370

Resource depletion kg Sb eq 18.7 18.7 18.4 18.2

Acidification kg SO2 eq 8.41 8.35 8.21 8.07

Photochemical oxidation kg C2H4 0.598 0.580 0.553 0.525

Solid waste generation kg 148 134 115 96.9

Water litres 176000 194000 212000 230000

For global warming and resource depletion, only refurbishment scenarios resulting in a lifetime extension of more

than three years is of benefit for C rated machines. In terms of acidification, photochemical oxidation, and solid

waste generation, refurbishment resulting in a lifetime extension of three years is of benefit for C rated

machines.

These trends are the result of impacts associated with washing machine production and refurbishment being

lower for refurbishment scenarios compared to replacement scenarios.

The magnitude of these benefits increases with increased lifetime extension periods of refurbishment of six and

nine years. This pattern is most pronounced for solid waste generation with large reductions realised through

increases in lifetime extension.

Refurbishment of both A and C rated machines does not deliver benefits in terms of water use.

Figure 5.2 Replace ‘A’/ Refurb ‘C’ then Replace ‘A’

0

10

20

30

40

50

60

70

80

90

100


Comparing 1 p 'Scenario 01 Replace with A.', 1 p 'Scenario 03 Refurbish C; Replace with A after 3 years.', 1 p 'Scenario 05

Refurbish C; Replace with A after 6 years.' and 1 p 'Scenario 07 Refurbish C; Replace with A after 9 years.'; Method: WRAP

Washing

%

Scenario 01 Replace with A. Scenario 03 Refurbish C; Replace with A after 3 years.

Scenario 05 Refurbish C; Replace with A after 6 years. Scenario 07 Refurbish C; Replace with A after 9 years.

35

5.2 Replacement with an ‘A+’ rated machine compared to refurbishment and subsequent replacement with an ‘A+’ rated machine

Table 5.3 Replace ‘A+’/ Refurb ‘A’ then Replace ‘A+’


Replace

with A+.

Refurbish

A; Replace

with A+

after three

years.

Refurbish

A; Replace

with A+

after six

years.

Refurbish

A; Replace

with A+

after nine

years.

IPCC GWP 100a kg CO2 eq 2290 2290 2260 2240





Water litres 146000 154000 161000 168000

Table 5.4 Replace ‘A+’/ Refurb ‘C’ then Replace ‘A+’


Replace

with A+.

Refurbish

C; Replace

with A+

after

three

years.

Refurbish

C; Replace

with A+

after six

years.

Refurbish

C; Replace

with A+

after nine

years.

IPCC GWP 100a kg CO2 eq 2290 2320 2330 2340





Water litres 146000 172000 197000 222000

Figure 5.3 Replace ‘A+’/Refurb ‘A’ then Replace ‘A+’

0

10

20

30

40

50

60

70

80

90

100


Comparing 1 p 'Scenario 01 Replace with A+.', 1 p 'Scenario 02 Refurbish A; Replace with A+ after 3 years.', 1 p 'Scenario 04

Refurbish A; Replace with A+ after 6 years.' and 1 p 'Scenario 06 Refurbish A; Replace with A+ after 9 years.'; Method: WRAP

Was

%

Scenario 01 Replace with A+. Scenario 02 Refurbish A; Replace with A+ after 3 years.

Scenario 04 Refurbish A; Replace with A+ after 6 years. Scenario 06 Refurbish A; Replace with A+ after 9 years.

36

For global warming, refurbishment resulting in a lifetime extension beyond three years results in a small benefit

for A rated machines. In the case of resource depletion, acidification, photochemical oxidation and solid waste

generation, refurbishment resulting in a lifetime extension of three years and beyond is of benefit for A rated

machines. The magnitude of these benefits increases with increased lifetime extension periods of six and nine

years. This pattern is most pronounced for photochemical oxidation and solid waste generation. Once again,

these trends are the result of potential impacts associated with washing machine production and refurbishment

being lower for refurbishment scenarios compared to replacement scenarios.

In the case of C rated machines, refurbishment is only beneficial in terms of photochemical oxidation and waste

generation.

No refurbishment scenario delivers water savings.

5.3 Replacement with an ‘A++’ rated machine compared to refurbishment and subsequent replacement with an ‘A++’ rated machine

Table 5.5 Replace ‘A++’/ Refurb ‘A’ then Replace ‘A++’


Replace

with A++.

Refurbish

A; Replace

with A++

after three

years.

Refurbish

A; Replace

with A++

after six

years.

Refurbish

A; Replace

with A++

after nine

years.

IPCC GWP 100a kg CO2 eq 1940 2030 2090 2150





Water litres 122000 135000 149000 162000

Figure 5.4 Replace ‘A+’/ Refurb ‘C’ then Replace ‘A+’

0

10

20

30

40

50

60

70

80

90

100


Comparing 1 p 'Scenario 01 Replace with A+.', 1 p 'Scenario 03 Refurbish C; Replace with A+ after 3 years.', 1 p 'Scenario 05

Refurbish C; Replace with A+ after 6 years.' and 1 p 'Scenario 07 Refurbish C; Replace with A+ after 9 years.'; Method: WRAP

Was

%

Scenario 01 Replace with A+. Scenario 03 Refurbish C; Replace with A+ after 3 years.

Scenario 05 Refurbish C; Replace with A+ after 6 years. Scenario 07 Refurbish C; Replace with A+ after 9 years.

37

Table 5.6 Replace ‘A++’/ Refurb ‘C’ then Replace ‘A++’


Replace

with A++.

Refurbish

C; Replace

with A++

after three

years.

Refurbish

C; Replace

with A++

after six

years.

Refurbish

C; Replace

with A++

after nine

years.

IPCC GWP 100a kg CO2 eq 1940 2060 2160 2250





Water litres 122000 153000 185000 216000

Figure 5.6 Replace ‘A++’/Refurb ‘C’ then Replace ‘A++’

Figure 5.5 Replace ‘A++’/ Refurb ‘A’ then Replace ‘A++’

0

10

20

30

40

50

60

70

80

90

100


Comparing 1 p 'Scenario 01 Replace with A++.', 1 p 'Scenario 02 Refurbish A; Replace with A++ after 3 years.', 1 p 'Scenario 04

Refurbish A; Replace with A++ after 6 years.' and 1 p 'Scenario 06 Refurbish A; Replace with A++ after 9 years.'; Method: WRAP

%

Scenario 01 Replace with A++. Scenario 02 Refurbish A; Replace with A++ after 3 years.

Scenario 04 Refurbish A; Replace with A++ after 6 years. Scenario 06 Refurbish A; Replace with A++ after 9 years.

0

10

20

30

40

50

60

70

80

90

100


Comparing 1 p 'Scenario 01 Replace with A++.', 1 p 'Scenario 03 Refurbish C; Replace with A++ after 3 years.', 1 p 'Scenario 05

Refurbish C; Replace with A++ after 6 years.' and 1 p 'Scenario 07 Refurbish C; Replace with A++ after 9 years.'; Method: WRAP

%

Scenario 01 Replace with A++. Scenario 03 Refurbish C; Replace with A++ after 3 years.

Scenario 05 Refurbish C; Replace with A++ after 6 years. Scenario 07 Refurbish C; Replace with A++ after 9 years.

38

In terms of global warming, resource depletion, acidification and water use, washing machine replacement with

an A++ machine is environmentally preferable to refurbishment. This is due to the reduction in washing

machine production and assembly potential impacts of refurbishment being outweighed by increased impacts

associated with the extended use of A and C rated machines and the actual refurbishment.

For A rated machines, refurbishment resulting in a lifetime extension periods of over three years is beneficial in

terms of photochemical oxidation. This is due to increases in the potential impacts associated with the extended

use of A and C rated machines and refurbishment being compensated by larger reduction in washing machine

production and assembly potential impacts.

For solid waste generation refurbishment is environmentally preferable to replacement.

6.0 Sensitivity Analyses

The results of the sensitivity analyses performed for this study are presented in Tables 6.1 to 6.9 and Figures 6.1

to 6.9. Data and assumptions relating to each of these analyses are presented in Appendix 2.

Sensitivity analyses were typically performed on the following scenario set:

Replacement with an A+ rated machine compared to refurbishment of an A rated machine (and subsequent

replacement with an A+ rated machine after three, six and nine years).

This scenario set was selected as the results in Section 6.2 showed only a small difference between

environmental potential impacts of replacement compared to those of the refurbishment options and were

therefore most likely to be altered by changes in the input data. Where a sensitivity analysis was seen to

influence the potential impacts of refurbishment relative to replacement, the analysis was also run on the

following scenario set:

Replacement with an A++ rated machine compared to refurbishment of an A rated machine (and subsequent

replacement with an A++ rated machine after three, six and nine years).

Sensitivity analysis 4 compared the following replacement and refurbishment scenarios:

Replacement with an A rated machine compared to refurbishment of an A rated machine (and subsequent

replacement with an A+ rated machine after three, six and nine years).

6.1 Sensitivity Analysis 1: Variations in the distances and mode of transport from production to consumer

Sensitivity analysis 1 investigates the effect using of European (Eastern Europe to UK) and international (South

East Asia to UK) transport to user data in place of domestic transport to user data.

Table 6.1 Replace ‘A+’/Refurb ‘A’ then Replace ‘A+’. European Transport Scenario


Replace

with A+.

Refurbish

A; Replace

with A+

after three

years.

Refurbish

A; Replace

with A+

after six

years.

Refurbish

A; Replace

with A+

after nine

years.

IPCC GWP 100a kg CO2 eq 2300 2300 2270 2240





Water litres 146000 154000 161000 168000

39

Table 6.2 Replace ‘A+’/Refurb ‘A’ then Replace ‘A+’. International Transport Scenario


Replace

with A+.

Refurbish

A; Replace

with A+

after three

years.

Refurbish

A; Replace

with A+

after six

years.

Refurbish

A; Replace

with A+

after nine

years.

IPCC GWP 100a kg CO2 eq 2300 2300 2270 2240





Water litres 146000 154000 161000 168000

Figure 6.1 Replace ‘A+’/Refurb ‘A’ then Replace ‘A+’. European Transport Scenario

0

10

20

30

40

50

60

70

80

90

100




Was

%



40

Tables 6.1 to 6.2 and Figures 6.1 to 6.2 show that the inclusion of these alternative transport data does not alter

the outcome of the replacement and refurbishment scenario comparison.

6.2 Sensitivity Analysis 2: The use of MTP reference scenario energy consumption data for a 40°C cycle.

Sensitivity analysis 2 investigates the effect of using MTP reference scenario data for a 40°C cycle.

Table 6.3 Replace ‘A+’/Refurb ‘A’ then Replace ‘A+’. Use of MTP Reference Scenario

Energy Consumption Data for a 40°C Cycle


Replace

with A+.

Refurbish

A; Replace

with A+

after three

years.

Refurbish

A; Replace

with A+

after six

years.

Refurbish

A; Replace

with A+

after nine

years.

IPCC GWP 100a kg CO2 eq 1480 1470 1440 1400





Water litres 146000 154000 161000 168000

Figure 6.2 Replace ‘A+’/Refurb ‘A’ then Replace ‘A+’. International Transport Scenario

0

10

20

30

40

50

60

70

80

90

100




Was

%



41

This sensitivity analysis shows a slight reduction in the environmental potential impacts of refurbishment relative

to replacement. As such, for all impact categories except water use, refurbishment resulting in lifetime extension

periods of three years and over has a lower potential environmental impact compared to replacement.

Table 6.4 Replace ‘A++’/ Refurb ‘A’ then Replace ‘A++’. Use of MTP Reference Scenario Energy Consumption Data for a 40°C Cycle


Scenario

01

Replace

with A++.

Refurbish

A; Replace

with A++

after three

years.

Refurbish

A; Replace

with A++

after six

years.

Refurbish

A; Replace

with A++

after nine

years.

IPCC GWP 100a kg CO2 eq 1280 1320 1330 1350





Water litres 122000 135000 149000 162000

Figure 6.3 Replace ‘A+’/ Refurb ‘A’ then Replace ‘A+’. Use of MTP Reference Scenario Energy Consumption Data for a

40°C Cycle

0

10

20

30

40

50

60

70

80

90

100




Was

%



42

This sensitivity analysis was also run for the replacement with an A++ rated machine compared with

refurbishment of an A rated machines with subsequent replacement with an A++ rated machine.

In the case of this scenario set, the use of MTP reference scenario data for a 40°C cycle does not alter the

relative potential impacts of replacement and refurbishment, but does show the benefits are less pronounced.

6.3 Sensitivity Analysis 3: a reduction in washing machine lifetime from 12.09 years to 9 years

Sensitivity analysis 3 investigates the effect of reducing the assumed washing machine lifetime of 12.09 years to

9 years. The lifetime extension period achieved by refurbishment is also assumed to be reduced to either three

or six years.

Table 6.5 Replace ‘A+’/ Refurb ‘A’ then Replace ‘A+’. Reduction in Washing Machine Lifetime from 12.09 years to 9 years


Replace with

A+.

Refurbish A;

Replace with

A+ after three

years.

Refurbish A;

Replace with

A+ after six

years.

IPCC GWP 100a kg CO2 eq 1770 1750 1700

Resource depletion kg Sb eq 13.7 13.5 13.0

Acidification kg SO2 eq 6.21 6.05 5.81

Photochemical oxidation kg C2H4 0.462 0.431 0.390

Solid waste generation kg 148 127 103

Water litres 109000 116000 124000

Figure 6.4 Replace ‘A++’/Refurb ‘A’ then Replace ‘A++’. Use of MTP Reference Scenario Energy Consumption Data for

a 40°C Cycle

0

10

20

30

40

50

60

70

80

90

100


Comparing 1 p 'Scenario 01 Replace with A++.', 1 p 'Scenario 02 Refurbish A; Replace with A++ after 3 years.', 1 p 'Scenario 04

Refurbish A; Replace with A++ after 6 years.' and 1 p 'Scenario 06 Refurbish A; Replace with A++ after 9 years.'; Method: WRAP

%

Scenario 01 Replace with A++. Scenario 02 Refurbish A; Replace with A++ after 3 years.

Scenario 04 Refurbish A; Replace with A++ after 6 years. Scenario 06 Refurbish A; Replace with A++ after 9 years.

43

Once again, the results confirm a slight reduction in the impact of refurbishment relative to replacement. As

such, for all impact categories except water use, refurbishment resulting in lifetime extension periods of three

years and over is environmentally beneficial compared to replacement.

Table 6.6 Replace ‘A++’/ Refurb ‘A’ then Replace ‘A++’. Reduction in Washing Machine Lifetime from 12.09 years to 9 years


Replace with

A++.

Refurbish A;

Replace with

A++ after

three years.

Refurbish A;

Replace with

A++ after six

years.

IPCC GWP 100a kg CO2 eq 1510 1570 1610

Resource depletion kg Sb eq 11.7 12.1 12.4

Acidification kg SO2 eq 5.34 5.47 5.52

Photochemical oxidation kg C2H4 0.408 0.395 0.372

Solid waste generation kg 148 127 103

Water litres 90700 104000 117000

Figure 6.5 Replacement with ‘A+’ Compared to Refurbishment of ‘A’ (and Subsequent Replacement with ‘A+’).

Reduction in Washing Machine Lifetime from 12.09 years to 9 years

0

10

20

30

40

50

60

70

80

90

100


Comparing 1 p 'Scenario 01 Replace with A+.', 1 p 'Scenario 02 Refurbish A; Replace with A+ after 3 years.' and 1 p 'Scenario 04

Refurbish A; Replace with A+ after 6 years.'; Method: WRAP Washing Machine Method IPCC 2007 GWP 100 V1.00 /

characterization

%

Scenario 01 Replace with A+. Scenario 02 Refurbish A; Replace with A+ after 3 years. Scenario 04 Refurbish A; Replace with A+ after 6 years.

44

Reducing the assumed washing machine lifetime of 12.09 years to 9 years does not alter the relative impacts of

replacement with an A++ machine and refurbishment followed by replacement with an A++ machine

6.4 Sensitivity Analysis 4: Future, post refurbishment, replacement with a more energy efficient machine compared to current machine selections for replacement

Sensitivity analysis 4 investigates the effect of future, post refurbishment, replacement with a more energy

efficient A+ machine compared to current replacement with an A machine.

Table 6.7 Future, Post Refurbishment, Replacement with a More Energy Efficient Machine Compared to Current Machine Selections for

Replacement


Replace

with A.

Refurbish

A; Replace

with A+

after three

years.

Refurbish

A; Replace

with A+

after six

years.

Refurbish

A; Replace

with A+

after nine

years.

IPCC GWP 100a kg CO2 eq 2420 2290 2260 2240





Water litres 176000 154000 161000 168000

Figure 6.6 Replace ‘A++’/ Refurb ‘A’ then Replace ‘A++’. Reduction in Washing Machine Lifetime from 12.09 years to

9 years

0

10

20

30

40

50

60

70

80

90

100


Comparing 1 p 'Scenario 01 Replace with A++.', 1 p 'Scenario 02 Refurbish A; Replace with A++ after 3 years.' and 1 p 'Scenario

04 Refurbish A; Replace with A++ after 6 years.'; Method: WRAP Washing Machine Method IPCC 2007 GWP 100 V1.00 /

characterizati

%

Scenario 01 Replace with A++. Scenario 02 Refurbish A; Replace with A++ after 3 years. Scenario 04 Refurbish A; Replace with A++ after 6 years.

45

The result of this sensitivity analysis is that for all impact categories refurbishment is environmentally preferable

to replacement.

6.5 Sensitivity Analysis 5: Limescale accumulation

The effect of limescale accumulation on washing machine energy consumption was investigated as a sensitivity

analysis, using the following assumptions:

limescale accumulation: 1.5mm (1) over 12.09 years;

reduction in heating elements efficiency: 10% (2); and

percentage of energy consumption associated with heating: 77% (3).

It should be noted that limescale accumulation can impact on other parts of the washing machine, for example

accumulation in the drum can impact on water removal. These effects have not been considered as part of this

sensitivity analysis.

Table 6.8 Replace ‘A+’/ Refurb ‘A’ then Replace ‘A+’. Limescale Accumulation


Replace

with A+.

Refurbish

A; Replace

with A+

after three

years.

Refurbish

A; Replace

with A+

after six

years.

Refurbish

A; Replace

with A+

after nine

years.

IPCC GWP 100a kg CO2 eq 2410 2410 2380 2360





Water litres 146000 154000 161000 168000

(1) Adapted from worst case annual accumulation value from www.building.co.uk

(2) Value from Devoldere et al (2006)

(3) Rüdenauer, I.; Gensch, C.; Quack, D. (2005)

Figure 6.7 Future, Post Refurbishment, Replacement with a More Energy Efficient Machine Compared to Current

Machine Selections for Replacement

0

10

20

30

40

50

60

70

80

90

100


Comparing 1 p 'Scenario 01 Replace with A.', 1 p 'Scenario 02 Refurbish A; Replace with A+ after 3 years.', 1 p 'Scenario 04


Wash

%

Scenario 01 Replace with A. Scenario 02 Refurbish A; Replace with A+ after 3 years.


46

Table 6.8 and Figure 6.8 show that the inclusion of these alternative data does not alter the result of the

replacement and refurbishment scenario comparison.

6.6 Sensitivity Analysis 6: The use of a projected electricity generation mix for the year 2020.

Sensitivity analysis 6 investigates how the use of a future projected future electricity production mix for the year

2020 (1) will influence the study results.

These projected data have been used to represent washing machine assembly, use and refurbishment as well as

shredder energy consumption at end of life.

Table 6.9 Replace ‘A+’/ Refurb ‘A’ then Replace ‘A+’). Use of Projected Electricity Generation Mix for 2020


Replace

with A+.

Refurbish

A; Replace

with A+

after three

years.

Refurbish

A; Replace

with A+

after six

years.

Refurbish

A; Replace

with A+

after nine

years.

IPCC GWP 100a kg CO2 eq 2060 2050 2020 2000





Water litres 146000 154000 161000 168000

(1) Sourced from Department of Energy and Climate Change (2008) updated energy and carbon emissions projections

Figure 6.8 Replace ‘A+’/Refurb ‘A’ then Replace ‘A+’). Limescale Accumulation

0

10

20

30

40

50

60

70

80

90

100




Was

%



47

Table 6.9 and Figure 6.9 show that the inclusion of these alternative data does not alter the result of the

replacement and refurbishment scenario comparison.

7.0 Discussion

7.1 Results for different washing machine life cycle stages

The results show that the use stage of the washing machine life cycle makes the dominant contribution to all

impact categories except solid waste generation.

The preference towards replacement or refurbishment is determined by the balance between:

refurbishment process;

machine production; and

difference in energy consumption per wash between machines.

Washing machine production and assembly makes an important contribution to global warming, resource

depletion, acidification and photochemical oxidation categories. The majority of the potential impacts result from

the production of ferrous and non ferrous metals, plastics and electricity generation and natural gas combustion

for the assembly process.

The refurbishment burden modelled in this study makes a small contribution to global warming, resource

depletion, acidification and photochemical oxidation. The majority of impacts are associated with the

manufacture of the aluminium alloy spider and the stainless steel ball bearing set.

The end of life stage of the washing machine life cycle is only important in terms of solid waste generation.

7.2 Replacement with ‘A’ Rated Machines

According to the MTP reference scenario data, A rated machines will continue to represent the majority of both

sales and stock until 2020. The results of this study demonstrate that, under these circumstances, refurbishment

of both A and C machines delivers benefits in the majority of impact categories. This is the result of impacts

associated with washing machine production and refurbishment being lower for refurbishment scenarios than for

replacement scenarios, due to postponement in the production of a new machine.

Figure 6.9 Replace ‘A+’/ Refurb ‘A’ then Replace ‘A+’. Use of Projected Electricity Generation Mix for 2020.

0

10

20

30

40

50

60

70

80

90

100




Was

%



48

Refurbishment of A rated machines delivers benefits in all impact categories except water use. Increases in the

lifetime extension period achieved by refurbishment results in an increase in the magnitude of these benefits.

For C rated machines, refurbishment resulting in a lifetime extension of three years and beyond is of benefit in

three impact categories. For two impact categories, only refurbishment scenarios resulting in a lifetime extension

of more than three years are of benefit.

7.3 Replacement with ‘A+’ Rated Machines

In the MTP P1 scenario, a large increase in the sale of A+ rated machines will result in the stock of these

machines overtaking that of A machines in 2012 and continuing to rise till 2020. A comparison of immediate

replacement with an A+ machine with refurbishment and subsequent replacement with an A+ rated machine

shows that refurbishment is beneficial for the A rated machine for four out of six impact categories. Once again,

this is due to the impacts associated with washing machine production and refurbishment being lower for

refurbishment scenarios than for replacement scenarios.

For global warming potential, only refurbishment resulting in a lifetime extension beyond three years is of benefit

for A rated machines.

In the case of C rated machines, refurbishment is only beneficial in terms of photochemical oxidation and waste

generation.

7.4 Replacement with ‘A++’ Rated Machine

The MTP earliest best practice scenario forecasts a large increase in the sale of A+ rated machines up until 2010,

with these machines representing the majority of stock. However, this scenario also predicts a rapid increase in

the sales of A++ rated machines from 2010 onwards, resulting in the stock of these machines overtaking that of

A rated machines by 2019.

With the exception of solid waste generation and, in the case of A rated machines, photo chemical oxidation,

replacement with an A++ machine (based on their modelled performance according to the MTP What If? tool) is

environmentally preferable to refurbishment. This is due to a reduction in washing machine production and

assembly impacts being outweighed by increases in the impacts associated with the extended use of A and C

rated machines and those of refurbishment.

7.5 Sensitivity Analyses

Sensitivity analyses involving the use of MTP reference scenario data for a 40°C cycle and a reduction in the

assumed washing machine lifetime from 12.09 to 9 years both result in a slight reduction in the environmental

impact associated with refurbishment, relative to replacement.

Sensitivity analysis 4 investigates the effect of future, post refurbishment, replacement with a more energy

efficient A+ machine compared to current replacement with an A machine. The result is that for all impact

categories refurbishment is environmentally preferable to replacement.

The following are seen not to influence the result of the replacement and refurbishment scenario comparison.

The use of European and international transport to user data in place of domestic transport to user data.

The inclusion of energy efficiency reductions associated with limescale accumulation.

The use of a future projected future electricity production mix for the year 2020.

7.6 Context of the results in terms of global warming potential

Presenting only the study results for Global Warming Potential impact, Tables 7.1 and 7.2 summarise the relative

differences for the replacement and refurbishment scenarios examined.

49

Table 7.1 Global Warming Potential impact values (in Kg CO2 eq) for the replacement versus refurbishment study scenarios for an 'A' rated


Replaced by: 'A' rated machine

replaced

immediately

'A' rated machine

refurbished, used

for a further 3

years, then

replaced

'A' rated machine

refurbished, used

for a further 6

years, then

replaced

'A' rated machine

refurbished, used

for a further 9

years, then

replaced

A++ 1940 2030 2090 2150

A+ 2290 2290 2260 2240

A 2420 2390 2330 2270

Table 7.2 Global Warming Potential impact values (in Kg CO2 eq) for the replacement versus refurbishment study scenarios for a 'C' rated


Replaced by:

'C' rated machine

replaced

immediately

'C' rated machine

refurbished, used

for a further 3

years, then

replaced

'C' rated machine

refurbished, used

for a further 6

years, then

replaced

'C' rated machine

refurbished, used

for a further 9

years, then

replaced

A++ 1940 2060 2160 2250

A+ 2290 2320 2330 2340

A 2420 2420 2400 2370

Notes

Colours in the table denote categories for percentage difference in impact values from the best performing scenario where:




Machines are either directly replaced immediately, or refurbished and then used for a further x years, then are subsequently

replaced by either A++, A+ or A rated machines for the remaining period.

Values in the tables are expressed in Kg CO2 eq over the 12.09 year period (274 washes per year)

Refurbishment of an A rated machine, and subsequent replacement with an A rated machine after nine years,

delivers a benefit of 150kg CO2eq compared to immediate replacement with an A rated machine.

Sensitivity analysis 4 demonstrates that refurbishment of an A rated machine, and subsequent replacement with

an A+ rated machine after nine years, delivers a benefit of 180kg CO2eq compared to immediate replacement

with an A rated machine.

Replacement with an A++ rated machine delivers a benefit of 210kg CO2eq (or 0.21 tonnes CO2eq) compared to

refurbishment of an A rated machine, and subsequent replacement with an A++ rated machine after nine years.

In context, average per capita emissions for the United Kingdom (2004) and the European Union (EU 27) (2006)

have been estimated as 9.8 and 10.4 tonnes CO2eq respectively(1) (2).

Formal normalisation and weighting of results have not been undertaken for the impact categories included in

this study, due to the data uncertainties associated with the former and the subjective nature of the latter.

(1) http://hdrstats.undp.org/countries/country_fact_sheets/cty_fs_GBR.html

(2) http://dataservice.eea.europa.eu/PivotApp/pivot.aspx?pivotid=455

http://hdrstats.undp.org/countries/country_fact_sheets/cty_fs_GBR.html

http://dataservice.eea.europa.eu/PivotApp/pivot.aspx?pivotid=455

50

7.7 Conclusions

Immediate replacement of A and C machines with A++ rated machines (based on the modelled approach concerning product performance of the MTP What If? tool) represents the most environmental preferable option for all impact categories except solid waste generation and photochemical oxidation. This finding supports the

implementation of MTP’s earliest best practice scenario.

However, at present there are only two manufacturers with an A++ rated machine on the market. Under the

MTP earliest best practice scenario, it is forecast that sales of these machines will not overtake those of A+

machines until 2020.

With the exception of water use, refurbishment of an A rated machine is environmentally preferential to immediate replacement with an A or an A+ rated machine. The scale of this benefit increases the longer the refurbished machine lasts, and with reduced wash

temperature.

According to the MTP reference scenario data for the UK, A rated machines will continue to represent the

majority of both sales and stock until 2020. Under the MTP P1 scenario, a large increase in the sale of A+ rated

machines will result in the stock of these machines overtaking that of A rated machines in 2012 and continuing to

rise until 2020.

When future (post refurbishment) replacement with an A+ rated machine is compared to current replacement

with an A rated machine, the scale of refurbishment benefits are increased.

The relative benefits of refurbishing a C rated machine compared to its immediate replacement with A or an A+

machine are dependent on the lifetime extension achieved by refurbishment, and the impact category under

consideration.

This study is a comparative LCA which evaluates replacement and refurbishment scenarios for household washing

machines. Whilst the study is a fair comparative LCA, and provides a robust indication of the life cycle burden of

different replacement and refurbishment scenarios in line with the study goal, it does not provide an estimate for

the actual burden caused by a washing machine over the course of its lifetime.

The way the machine is actually used by the consumer in the home will determine the actual burden that is

caused by it (ie which wash cycles are routinely used, how the machine is loaded, whether it is maintained etc)

and such consumer behaviour has not been factored into the study. As such, the findings do not confirm

whether reduced environmental impacts will actually be realised in the home if a consumer chooses to upgrade

to a more energy efficient rated machine, or to purchase a refurbished machine.

7.8 Recommendations for Further Research

In view of the study findings, and the question of whether it makes environmental sense to replace or refurbish

an existing washing machine, the following research recommendations may be considered.

Further analysis based on the declared performance of A++ machines which are now available on the UK

market.

The collection, compilation and subsequent life cycle assessment of in the home life energy and water

consumption monitoring data for a representative sample of washing machines in each energy rating class

over a range of consumers. The data would ideally be collected for a range of washing machine cycles, wash temperatures and water supply areas. Such data is especially relevant given recent campaigns promoting

routine 30°C wash temperatures (1) and the development of washing detergents that are effective at low

wash temperatures.

An investigation of the effect of washing machine loading under experimental conditions. It is noted in the

study that washing machine load capacity tends to be larger for higher energy rated machines. Energy and water consumption data should be collected for a range of different load sizes. Moreover, the impact of

innovations such as automatic load adjustment features, which aim to reduce energy consumption when

(1) eg Ariel/Procter and Gamble 'Turn To 30º' campaign and various other retailer initiatives

51

washing reduced loads, could be corroborated under experimental conditions and examined as further research.

Consumer surveys regarding the average lifetime refurbished machines are used for in UK homes.

8.0 External Critical Review statement See Appendix 4

9.0 References

Centre for Environmental Studies (CML), University of Leiden (2007) CML Impact assessment method Version

2.04

Department of Energy and Climate Change (2008) updated energy and carbon emissions projections, available

at: http://www.berr.gov.uk/energy/environment/projections/index.html

Devoldere, T. et al (2009) The Eco-Efficiency of Reuse Centres Critically Explored – The Washing Machine Case,

International Journal of Sustainable Manufacturing, Volume 1, Number 3 / 2009, p265-285

DIRECTIVE 2005/32/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 6 July 2005 on establishing a

framework for the setting of ecodesign requirements for energy-using products amending Council Directive

92/42/EEC and Directives 96/57/EC and 2000/55/EC of the European Parliament and of the Council, available at:

http://ec.europa.eu/enterprise/eco_design/directive_2005_32.pdf

DIRECTIVE 2008/98/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 19 November 2008 on waste

and repealing certain Directives, available at:

http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2008:312:0003:0030:EN:PDF

Environment Agency (2007) Waste and Resources Assessment Tool for the Environment (WRATE)

Ekdahl, A (2001) Life Cycle Assessment on SKF’s Spherical Roller Bearing, available at:

http://www.esa.chalmers.se/Publications/PDF-files/Thesis/esa20011.pdf

Energy Savings Trust (2007) Commercial Buyers’ Guide – Indicative Sustainable Product Performance Standards

for Washing Machines and Tumble dryers, available at:

www.energysavingtrust.org.uk/esr/content/download/25429/88836/file/EST%20Washing%20Machine%206pp.pd

f

ENEA (2007) Preparatory Study for eco design requirements of (EuPs) (Tender TREN/D1/40-2005) LOT 14:

household washing machines and dishwashers, Part 1 present situation, Task 5 definition of base case, rev 2.0,

available at:

http://www.topten.info/uploads/images/upload/EUP_cold_appliances_Task5_v1%201_04012007%5B1%5D.pdf

ISO 14044:2006, Environmental management -- Life cycle assessment – Requirements and guidelines. Edition

1, International Standard Organisation, available at: http://www.iso.org

ISO 14040:2006, Environmental management -- Life cycle assessment - Principles and framework. Edition 2,

International Standard Organisation, available at: http://www.iso.org

Manouchehri (2006) Mapping and development of shredding product stream(s): four shredding plants in Sweden,

Jernkonteret Forskning, available at:

http://www.jernkontoret.se/informationsbanken/vara_publikationer/pdf_forskning/d817.pdf

Market Transformation Programme (2005/6) Washing machine energy label compliance testing: post-consultation

report, available at: www.mtprog.com

Market Transformation Programme (2004) 62014 Issue 1 Washing Machine ‘Real use’ Performance (WM1),

available at: www.mtprog.com

http://www.berr.gov.uk/energy/environment/projections/index.html

http://ec.europa.eu/enterprise/eco_design/directive_2005_32.pdf

http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2008:312:0003:0030:EN:PDF

http://www.esa.chalmers.se/Publications/PDF-files/Thesis/esa20011.pdf

http://www.energysavingtrust.org.uk/esr/content/download/25429/88836/file/EST%20Washing%20Machine%206pp.pdf

http://www.energysavingtrust.org.uk/esr/content/download/25429/88836/file/EST%20Washing%20Machine%206pp.pdf

http://www.topten.info/uploads/images/upload/EUP_cold_appliances_Task5_v1%201_04012007%5B1%5D.pdf

http://www.iso.org/

http://www.iso.org/

http://www.jernkontoret.se/informationsbanken/vara_publikationer/pdf_forskning/d817.pdf

http://www.mtprog.com/

http://www.mtprog.com/

52

Rüdenauer, I.; Gensch, C.; Quack, D. (2005) Eco-Efficiency Analysis of Washing Machines, Öko Institut e.V.,

available at: http://www.oeko-

institut.de/publications/reports_studies/dok/659.php?id=47&dokid=270&anzeige=det&ITitel1=&IAutor1=&ISchla

gw1=&sortieren=&dokid=270

Swiss Centre for Life Cycle Inventories (2007) Ecoinvent Life Cycle Inventory database, Version 2

Personal Communication, John Hopwood Independent Service Engineering, 3/3/2009

Personal Communication, Craig Anderson Furniture Reuse Network, 27/2/2009

Personal Communication, Nicola King, Market Transformation Programme 10/3/2009

Websites:



http://www.building.co.uk/story.asp?sectioncode=482&storycode=3071623

http://whatif.mtprog.com/Level3/ProductDetail.aspx?ScenarioID=0&Comparison=False&SchemeID=1&ProductID

=12

http://www.oeko-institut.de/publications/reports_studies/dok/659.php?id=47&dokid=270&anzeige=det&ITitel1=&IAutor1=&ISchlagw1=&sortieren=&dokid=270





http://www.building.co.uk/story.asp?sectioncode=482&storycode=3071623

http://whatif.mtprog.com/Level3/ProductDetail.aspx?ScenarioID=0&Comparison=False&SchemeID=1&ProductID=12

http://whatif.mtprog.com/Level3/ProductDetail.aspx?ScenarioID=0&Comparison=False&SchemeID=1&ProductID=12

53

Acknowledgements

10.0 Acknowledgements

Conducting life cycle assessment studies is a notoriously data intensive activity and this study could not have

been completed effectively without the assistance of a large number of project partners, data providers and

advisors. Many thanks to the following individuals who have kindly contributed their time and expertise to this

study:

Table 10.1 Acknowledgements

Organisation Contact Role

WRAP

Gerrard Fisher

Keith James

Project Manager

Technical advisor

Market Transformation

Programme/Intertek

Nicola King Data provision and advice

Furniture Re-use Network Craig Anderson Data provision and advice

Independent Service

Engineering

John Hopwood Data provision and advice

Ove Arup & Partners Ltd

Oakdene Hollins

Independent design &

manufacturing consultant

David Dowdell

Keith Evans

Helen Jackson

David Parker

Bob Shaw

Lead peer reviewer

Peer review panel member

Peer review panel member

54

Appendix 1

Description of Impact Categories

11.0 Environmental Impact Categories

Life cycle impact assessment indicators:

11.1 Climate change (global warming)

The gases that contribute to the enhanced greenhouse effect (eg carbon dioxide (CO2), methane (CH4), carbon

monoxide (CO), nitrous oxide (N2O) and sulphur hexafluoride (SF6) and others) all have the property of absorbing

energy in the spectral range 10-15 μm, the so-called spectral window of the atmosphere. IR-radiation scattered

back from the surface of the earth is thus hindered from escaping and increases the temperature of the

atmosphere.

Global Warming Potential (GWP) has been developed as a method by the IPCC (Intergovernmental Panel on

Climate Change) which can be used to express the potential contribution of different gases to the greenhouse

effect. The Global Warming Potential (GWP) is a relative parameter that uses carbon dioxide (CO2) as a

reference gas. Characterisation factors are expressed as Global Warming Potential over a time horizon 100 years

(GWP100), in kg carbon dioxide-equivalents/kg emission.

11.2 Abiotic resource depletion

This environmental indicator considers the proportion of the available finite resource (in years) for each abiotic

raw material consumed by the activities in question and summing their contribution to depletion of known

reserves, giving a measure of total depletion in years. Raw materials extracted that contribute to resource

depletion are summed and compared with the antimony (Sb) reserve as a reference.

11.3 Acidification

Acidification arises due to the deposition of acids that lead to (i) a decrease in the pH, (ii) a decrease in the

mineral content of soil and (iii) an increase in concentrations of potentially toxic elements in groundwater. These

effects are caused by acid rain and dry deposition to water and surfaces; the major gaseous pollutants associated

with this are sulphur dioxide (SO2) and nitrogen oxides (NOx). These are dissolved in rainwater and

subsequently deposited. The effects of acid deposition are very site specific and will vary depending on the

receiving environment (i.e. the buffering capacity of the soil and any dilution effects which may occur).

Acidification Potential (AP) factors have been developed for potentially acidifying gases such as SO2, NOx, HCl, HF

and NH3. The AP of a substance is calculated on the basis of the number of hydrogen ions that can be produced

per mole of a substance, using SO2 as the reference substance.

11.4 Photo-oxidant formation

Low level smog contains irritants that can adversely affect human health. Photochemical oxidant formation

potential (POCP) factors have been developed for substances that contribute to the formation of photochemical

oxidants/smog. The POCP is a measure of the capacity to form ozone in the lower atmosphere using ethylene as

the reference substance. Therefore, impacts are expressed in kg C2H4 equivalents

Other indicators:

55

11.5 Solid waste generation

This indicator describes the amount (kg) of solid waste generated as a result of the appliance and packaging

disposal, and component disposal after refurbishment. This waste is subsequently sent to waste treatment

operations (recycling/landfill).

11.6 Water consumption

This indicator describes the direct water consumption (litres) which results from the use of the washing machine

during its lifetime.

56

Appendix 2

Study Data Sources and Assumptions

12.0 Study data Sources and Assumptions

12.1 Production and Assembly

Average material composition and assembly burden data were taken from The ENEA (2007) Preparatory Study for

eco design requirements of energy using products (EuP) for household washing machines and dishwashers.

Burdens associated with washing machine component subassembly are not accounted for in this report and were

therefore excluded from the scope of the study. This represents a study limitation as the burdens associated with

production and assembly are likely to be underestimated.

The ENEA study states material wastage rates of 5% for metals and 1% for plastics during assembly. It was

assumed that these materials were recycled internally and were therefore excluded form the scope of the study.

ERM has assumed the same production and assembly burdens for all energy rated machines and that production

and assembly burdens are representative of Europe and Great Britain respectively. In practice, there will be

differences in component (particularly drum) size between machines with different energy ratings.

Transport of materials to assembly plant is assumed to be 50% by rail and 50% by road (Euro IV 16-32 tonnes).

Throughout the study, transport distances are one way and it is assumed that vehicles are full (in terms of weight

capacity) on the outbound journey and empty for the return journey.

12.2 Use

Transport from production site to regional distribution centre (RDC) was subject to sensitivity analysis with the

following distances and modes of transport assumed by ERM:

Domestic: articulated lorry 16-32 tonnes Euro IV: 250km;

European (Eastern Europe to UK): articulated lorry 16-32 tonnes Euro IV: 1000km; train: 50km; and

International (South East Asia to UK): articulated lorry 16-32 tonnes Euro IV 100km; container ship

20,000km; articulated lorry 16-32 tonnes Euro IV: 250km.

ERM assumed the following distances and modes of transport for transport to the retailer and consumer:

RDC to retailer: articulated lorry 16-32 tonnes Euro IV: 25km; and

retailer to consumer: Passenger car: 10km.

It is assumed that all packaging is transported to the consumer.

This study has compared:

replacement: disposal of a washing machine and its replacement with a specific energy rated washing

machine; and

refurbishment: of the original washing machine and subsequent replacement with a washing machine

possessing the same energy rating as in the replacement scenario.

Energy consumption data for each washing machine energy rating were taken from the Market Transformation

Programme’s (MTP) What If? Tool (2007 reference scenario). These data are based on the kWh/kg energy label

value for a standard 60°C test cycle (BS EN 60456: 2005), which assumes a cold water feed, multiplied by the

average load capacity of the different energy class appliances. MTP has used market data to determine a sales-

weighted average load capacity for each energy label class.

57

The fact that these data are based on average machine load capacity which varies between energy rating classes

and that consumers do not necessarily fill their machines to the maximum stated load capacity are potential

limitations to the current study. However, following consultation with the MTP, it was assumed that energy and

water consumption per cycle are not significantly influenced by actual load size (31). As a result, energy

consumption data for different washing machine energy ratings are comparable and individual consumer

behaviour can be excluded from the scope of the study. However in practice, certain models may incorporate an

automatic load adjustment feature, resulting in reduced energy consumption for reduced loads (32). Further

research is required to test this assumption.

MTP reference scenario data for a 40°C cycle for each washing machine energy rating were also included in the

study as a sensitivity analysis. These data are based on the MTP assumption that a 40°C cycle uses 40% less

energy than a 60°C cycle, which is supported by ‘real use’ test data undertaken by the MTP (33)

It is assumed that 274 machine cycles are run per year and that the average lifetime of a washing machine is

12.09 years (2007 MTP data). The effects of a reduced washing machine lifetime were investigated as a further


Energy consumption when the washing machine is on ‘standby’ and ‘off’ were excluded from the scope of the

study.

Machine water consumption data over a cycle for each energy rating class were sourced from MTP. These data

are based on a review of consumer test data and are calculated using assumed average machine load capacities.

Water consumption for A+ and A++ energy rated machines were extrapolated from A rated machines using the

average percentage change in water consumption between each energy rating class (A to G).


machine. As a consequence, factors such as potential differences in spin efficiency are not considered as part of

the investigation. Differences in washing performance between machines of different ages have not been

considered as part of the study.

Due to the fact that refurbishment extends machine lifetime, it may be reasonable to assume that refurbished

machines will ultimately be replaced by machines with an improved energy efficiency rating and water

consumption compared to immediate replacement at end of life. This assumption was explored as a sensitivity

analysis.

Burdens associated with detergent, softener use and wastewater treatment were excluded as each will vary

according to consumer use so is not related to the energy rating of machines. General maintenance burdens

during the lifetime of the washing machine were excluded from the scope of the study.

The effect of limescale accumulation on washing machine energy consumption was investigated as a sensitivity

analysis using the following assumptions:

Limescale accumulation: 1.5mm over 12.09 years (adapted from www.building.co.uk);

Reduction in component efficiency: 10% (value from Devoldere et al 2006); and

Percentage of energy consumption associated with heating: 77% (Öko Instit e.V. 2005).

12.3 Refurbishment

Following consultation with the Furniture Reuse Network (FRN) and a site visit to their Bristol depot (which

refurbishes ~1200 machines per year), the following typical refurbishment burdens were identified:

(31) According to the MTP research, reduced load size does not always result in reduced energy consumption for a 40°C cycle and the MTP has

not performed tests for a 60°C cycle Personal Communication Nicola King 10/3/2009 (32) Rüdenauer, I.; Gensch, C.; Quack, D. (2005) Eco-Efficiency Analysis of Washing Machines, Öko Institut e.V., assumes between a 13% and 21%

reduction for a 60% reduced load at 60°C cycle. (33) MTP (2004) 62014 Issue 1Washing machine 'Real use' Performance (WM1)

58

Replacement parts A typical economical refurbishment comprises the following parts:

A set of stainless steel bearings;

aluminium alloy and stainless steel spider;

carbon brushes (various materials); and

hoses (assumed to be 100% PVC).

Materials compositions and weights were obtained for these components and modelled using representative ecoinvent database processes. FRN replace all these parts with brand new parts to ensure these parts do not fail post-refurbishment. As a result, these replacement parts are modelled as new.

Burdens for discarded washing machines unsuitable for refurbishment, which are recycled by shredding are not

accounted for in the model because the study compares the impacts of a direct-replaced machine with a

refurbished machine. FRN estimates up to 25% of the units received at their Bristol depot are shredded and

recycled, depending on their source. Inventory data for the manufacture of roller bearings were obtained from Ekdahl (2001) Life Cycle Assessment on SKF’s Spherical Roller Bearing. These data were adapted and used to represent stainless steel bearing manufacture. The manufacture and transport of packaging for these replacement parts was excluded on a significance basis.

Test cycles As part of the refurbishment process, washing machines are subject to a 60°C cycle without a load (motor not

connected to the drum) and a 40°C with a load. These cycles were modelled using MTP data for water and

energy consumption. It is assumed that energy consumption for the 60°C test cycle is 50% that of a standard

60°C cycle as the motor is not connected to the drum.

Transport The following distance and vehicle information was obtained from the FRN and used to model a typical transport

scenario.

1. Direct From User

420,000 units annually

3.5 tonnes vehicle

8km

2. Centrally Distributed WEEE

45,000 units annually

7.5 tonnes vehicle

50 km

15,000 units

articulated lorry

322Km

3. Transport to End User

3.5 tonnes vehicle

8km

Transport of the replacement parts was assumed to be over the same distance as the whole washing machine.

For the purposes of this study, it was assumed that washing machine refurbishment does not result in an

improvement in machine energy efficiency rating or water consumption.

59

ERM understands that there is the potential to flash the electronics of a washing machine in order to improve

efficiency. This approach to refurbishment was excluded from the scope of the current study.

Suitable data were not available on the actual lifetime extension achieved by machine refurbishment period. As a

result this study considers lifetime extension periods of three, six and nine years for each refurbishment option

assessed.

12.4 End of Life

Packaging This study assumes that packaging is collected from the consumer and an 80% recycling rate is achieved (with

the remainder sent to landfill), based on DEFRA statistics: http://www.defra.gov.uk/news/2009/090409a.htm

The Environment Agency’s Waste and Resources Assessment Tool for the Environment (WRATE) tool

recommended transport distances for waste management are (250km) to national recycling (national scenario for

the UK) and 50km to regional landfill.

Discarded Parts from Refurbishment The same materials recycling rate was assumed for the waste washing machine discarded parts and the washing

machine as a whole. However, discarded parts were assumed to be transported directly to recycling/landfill

operations. As above, WRATE tool recommended transport distances were used for transport to landfill and

recycling operations.

Washing Machine Article 7 of the Waste Electrical and Electronic Equipment (WEEE) Directive lists the recovery and recycling

targets for Category 1 items including washing machines as follows:

The rate of recovery shall be increased to a minimum of 80% by an average weight per appliance, and

component, material and substance reuse and recycling shall be increased to a minimum of 75% by an average

weight per appliance

This study assumes a 75% recycling rate for all washing machine materials, with the remaining 25% being sent

to inert material landfill. The effect of varying the washing machine materials recycling rate was investigated as a


The following WRATE default transport assumptions were used:

2 Transport to local household waste recycling centre

16-32 tonne lorry;

10km

3 Transport to local salvage yard –

16-32 tonne lorry;

25km

4 Transport to regional shredder facility

16-32 tonne lorry;

50km

5 Transport to national recycling facility

16-32 tonne lorry;

250km

http://www.defra.gov.uk/news/2009/090409a.htm

60

6 Transport to regional landfill

16-32 tonne lorry;

50km

Shredding operation The study includes the environmental burdens associated with shredding the product. An energy consumption

value of 39kWh/tonne was taken from Manouchehri (2006) Mapping and development of shredding product

stream(s): four shredding plants in Sweden.

12.5 Data Representation

Ecoinvent database processes have been used to represent the data identified in the inventory analysis.

Capital burdens were not included in this study. Capital burdens are normally insignificant with respect to the

outcome of LCA studies, especially where the production buildings house processes and equipment that are high

throughput and operate for many years. Other burdens associated with shared office/warehousing and the

workforce (eg driving to and from work) were also excluded on the basis of significance.

For all transport data in the inventory, it was assumed that the outbound journey is full and the return journey is

empty. Ecoinvent processes for road transport were adapted to reflect this assumption.

Electricity consumption at each life cycle stage was taken as the current average medium voltage supply mix for

Great Britain. A further sensitivity analysis was performed to determine how a projected future electricity

production mix for the year 2020 will influence the study results. This projected energy mix data was sourced

from Department of Energy and Climate Change (2008) Updated energy and carbon emissions projections.

61

Appendix 3

Life Cycle Inventory Data for Example Scenario: Refurbish A;

replace with A after 3 years

Table C.1 Life Cycle Inventory Results

Compart

ment

Substance Unit Production &

Assembly

Transport to

User

Use Refurbishment End of Life Total

Raw Aluminium, 24% in bauxite, 11% in crude

ore, in ground

kg 2.27E+00 2.90E-06 1.39E-01 5.81E-01 4.31E-05 2.99E+00

Raw Anhydrite, in ground kg 1.23E-04 4.27E-09 4.32E-07 2.80E-07 4.36E-09 1.23E-04

Raw Barite, 15% in crude ore, in ground kg 4.47E-03 2.71E-07 9.31E-04 1.42E-04 1.65E-06 5.54E-03

Raw Basalt, in ground kg 1.13E-04 4.59E-09 1.74E-05 2.84E-05 3.10E-08 1.59E-04

Raw Borax, in ground kg 8.57E-07 2.05E-10 5.38E-06 3.18E-08 7.38E-09 6.28E-06

Raw Cadmium, 0.30% in sulfide, Cd 0.18%, Pb,

Zn, Ag, In, in ground

kg 4.98E-04 -9.72E-10 1.40E-08 4.24E-08 -1.36E-09 4.98E-04

Raw Calcite, in ground kg 1.53E+01 3.89E-04 9.78E+00 6.93E-01 1.33E-02 2.58E+01

Raw Carbon dioxide, in air kg 9.78E+00 9.39E-04 7.67E+01 5.89E-01 9.65E-02 8.72E+01

Raw Carbon, in organic matter, in soil kg 4.26E-05 1.28E-07 6.37E-06 5.21E-06 2.73E-07 5.46E-05

Raw Cerium, 24% in bastnasite, 2.4% in crude

ore, in ground

kg -5.83E-21 -3.07E-23 -3.11E-20 -1.89E-22 -8.53E-23 -3.72E-20

Raw Chromium, 25.5% in chromite, 11.6% in

crude ore, in ground

kg 2.48E+00 2.34E-07 6.85E-03 2.35E-01 9.15E-06 2.72E+00

Raw Chrysotile, in ground kg 2.02E-05 2.69E-09 8.28E-06 1.54E-06 1.50E-08 3.00E-05

Raw Cinnabar, in ground kg 1.95E-06 2.55E-10 7.65E-07 2.21E-07 1.40E-09 2.94E-06

Raw Clay, bentonite, in ground kg 2.51E-01 2.57E-06 7.61E-02 5.84E-03 1.03E-04 3.33E-01

Raw Clay, unspecified, in ground kg 2.44E+00 3.72E-06 2.43E-02 3.70E-02 3.86E-05 2.51E+00

Raw Coal, brown, in ground kg 1.87E+01 1.23E-02 2.28E+01 1.92E+00 3.55E-02 4.35E+01

Raw Coal, hard, unspecified, in ground kg 3.60E+01 6.83E-03 7.72E+02 4.09E+00 1.03E+00 8.13E+02

Raw Cobalt, in ground kg 1.51E-07 1.95E-08 9.28E-08 1.73E-08 4.31E-08 3.24E-07

Raw Colemanite, in ground kg 1.12E-02 4.59E-09 1.34E-04 8.30E-07 1.81E-07 1.13E-02

Raw Copper, 0.99% in sulfide, Cu 0.36% and Mo

8.2E-3% in crude ore, in ground

kg 7.66E-03 7.55E-09 9.75E-06 1.38E-03 2.48E-08 9.05E-03

62

Compart

ment


Assembly

Transport to

User




kg 3.41E-02 1.88E-08 5.12E-05 7.63E-03 8.51E-08 4.18E-02



kg 9.06E-03 4.99E-09 1.36E-05 2.03E-03 2.26E-08 1.11E-02



kg 1.08E+00 2.49E-08 6.77E-05 1.00E-02 1.13E-07 1.09E+00

Raw Diatomite, in ground kg 5.30E-10 2.01E-13 6.21E-09 3.78E-11 8.40E-12 6.78E-09

Raw Dolomite, in ground kg 9.04E-02 2.68E-08 6.84E-05 1.88E-03 1.40E-07 9.24E-02

Raw Energy, gross calorific value, in biomass MJ 1.09E+02 8.73E-03 8.46E+02 6.31E+00 1.06E+00 9.62E+02

Raw Energy, gross calorific value, in biomass,

primary forest

MJ 2.96E-03 8.89E-06 4.42E-04 3.61E-04 1.89E-05 3.79E-03

Raw Energy, kinetic (in wind), converted MJ 7.26E+00 5.13E-03 8.59E+01 6.64E-01 1.17E-01 9.40E+01

Raw Energy, potential (in hydropower reservoir),

converted

MJ 2.46E+02 4.29E-02 2.50E+02 3.63E+01 3.73E-01 5.32E+02

Raw Energy, solar, converted MJ 9.76E-02 7.72E-05 1.34E-01 6.82E-03 2.20E-04 2.39E-01

Raw Feldspar, in ground kg 4.49E-07 1.06E-14 1.78E-10 1.04E-06 2.53E-13 1.49E-06

Raw Fluorine, 4.5% in apatite, 1% in crude ore, in

ground

kg 5.79E-04 3.43E-07 1.74E-04 8.36E-06 9.08E-07 7.62E-04

Raw Fluorine, 4.5% in apatite, 3% in crude ore, in

ground

kg 2.73E-04 1.51E-07 7.82E-05 3.75E-06 4.02E-07 3.56E-04

Raw Fluorspar, 92%, in ground kg 1.62E-02 1.05E-05 2.55E-02 1.94E-03 5.38E-05 4.37E-02

Raw Gadolinium, 0.15% in bastnasite, 0.015% in


kg -1.82E-23 -1.48E-29 -9.27E-23 -6.84E-26 -2.86E-28 -1.11E-22

Raw Gallium, 0.014% in bauxite, in ground kg 5.68E-14 8.96E-17 4.69E-13 2.91E-15 7.75E-16 5.30E-13

Raw Gas, mine, off-gas, process, coal mining/m3 m3 3.43E-01 6.62E-05 7.66E+00 3.96E-02 1.02E-02 8.05E+00

Raw Gas, natural, in ground m3 2.34E+01 5.55E-02 3.45E+02 2.58E+00 5.67E-01 3.71E+02

Raw Gold, Au 1.1E-4%, Ag 4.2E-3%, in ore, in

ground

kg 8.55E-06 8.74E-14 2.86E-10 1.82E-12 5.31E-13 8.55E-06


ground

kg 1.57E-05 1.60E-13 5.25E-10 3.34E-12 9.74E-13 1.57E-05

Raw Gold, Au 1.4E-4%, in ore, in ground kg 1.88E-05 1.92E-13 6.29E-10 4.00E-12 1.17E-12 1.88E-05


ground

kg 2.87E-05 2.93E-13 9.60E-10 6.11E-12 1.78E-12 2.87E-05





63

Compart

ment


Assembly

Transport to

User


Raw Gold, Au 9.7E-4%, Ag 9.7E-4%, Zn 0.63%,

Cu 0.38%, Pb 0.014%, in ore, in ground

kg 1.78E-06 1.82E-14 5.96E-11 3.80E-13 1.11E-13 1.78E-06

Raw Granite, in ground kg 4.79E-09 1.51E-15 1.51E-10 2.39E-12 2.01E-13 4.94E-09

Raw Gravel, in ground kg 1.43E+01 3.27E-05 1.14E+00 4.41E-01 1.29E-03 1.59E+01

Raw Gypsum, in ground kg 3.70E-04 2.13E-08 6.22E-05 7.26E-05 1.22E-07 5.05E-04

Raw Helium, 0.08% in natural gas, in ground kg 2.87E-13 4.52E-16 2.37E-12 1.47E-14 3.91E-15 2.67E-12

Raw Indium, 0.005% in sulfide, In 0.003%, Pb,

Zn, Ag, Cd, in ground

kg 8.30E-06 -1.62E-11 2.55E-10 5.45E-10 -2.27E-11 8.30E-06

Raw Iron, 46% in ore, 25% in crude ore, in

ground

kg 2.00E+01 3.68E-06 2.29E-02 4.40E-01 3.65E-05 2.04E+01

Raw Kaolinite, 24% in crude ore, in ground kg 5.76E-03 2.85E-08 3.41E-03 5.88E-05 4.55E-06 9.24E-03

Raw Kieserite, 25% in crude ore, in ground kg 1.31E-05 1.13E-10 9.55E-06 1.87E-07 1.28E-08 2.28E-05

Raw Lanthanum, 7.2% in bastnasite, 0.72% in


kg 1.82E-20 2.36E-23 1.63E-19 1.02E-21 2.60E-22 1.83E-19

Raw Lead, 5.0% in sulfide, Pb 3.0%, Zn, Ag, Cd,

In, in ground

kg 1.26E-03 5.25E-10 1.67E-06 2.15E-06 2.92E-09 1.27E-03

Raw Magnesite, 60% in crude ore, in ground kg 4.21E-01 2.31E-08 3.25E-04 1.03E-02 4.64E-07 4.32E-01

Raw Magnesium, 0.13% in water kg 2.35E-05 4.62E-13 1.88E-09 5.40E-02 3.29E-12 5.40E-02

Raw Manganese, 35.7% in sedimentary deposit,

14.2% in crude ore, in ground

kg 1.79E-01 3.07E-09 3.98E-05 2.79E-02 5.69E-08 2.07E-01

Raw Metamorphous rock, graphite containing, in

ground

kg 2.79E-03 3.65E-10 4.11E-05 1.02E-02 5.49E-08 1.30E-02

Raw Molybdenum, 0.010% in sulfide, Mo 8.2E-3%

and Cu 1.83% in crude ore, in ground

kg 2.01E-02 4.62E-10 1.26E-06 1.87E-04 2.09E-09 2.02E-02



kg 1.19E-04 6.56E-11 1.78E-07 2.66E-05 2.97E-10 1.46E-04



kg 6.20E-02 2.49E-08 1.43E-05 1.20E-05 5.43E-08 6.20E-02



kg 4.36E-04 2.40E-10 6.53E-07 9.75E-05 1.09E-09 5.34E-04



kg 1.25E-01 5.02E-08 2.89E-05 2.41E-05 1.10E-07 1.25E-01

Raw Neodymium, 4% in bastnasite, 0.4% in crude

ore, in ground

kg -2.41E-21 -1.30E-23 -1.19E-20 -6.94E-23 -3.36E-23 -1.45E-20

Raw Nickel, 1.13% in sulfide, Ni 0.76% and Cu

0.76% in crude ore, in ground

kg 1.86E-03 3.49E-08 3.03E-04 2.08E-06 4.42E-07 2.17E-03

64

Compart

ment


Assembly

Transport to

User


Raw Nickel, 1.98% in silicates, 1.04% in crude ore,

in ground

kg 1.72E+00 4.20E-07 1.12E-02 5.13E-01 1.52E-05 2.24E+00

Raw Oil, crude, in ground kg 1.78E+01 7.87E-01 2.97E+01 1.49E+00 1.66E+00 5.15E+01

Raw Olivine, in ground kg 2.23E-05 1.52E-09 1.45E-07 1.92E-07 1.49E-09 2.26E-05

Raw Pd, Pd 2.0E-4%, Pt 4.8E-4%, Rh 2.4E-5%, Ni

3.7E-2%, Cu 5.2E-2% in ore, in ground

kg 1.72E-06 1.81E-09 3.53E-08 1.50E-09 1.48E-09 1.76E-06

Raw Pd, Pd 7.3E-4%, Pt 2.5E-4%, Rh 2.0E-5%, Ni

2.3E+0%, Cu 3.2E+0% in ore, in ground

kg 4.14E-06 4.36E-09 8.48E-08 3.60E-09 3.56E-09 4.24E-06

Raw Peat, in ground kg 2.01E-02 2.64E-07 1.61E-04 2.69E-02 3.29E-07 4.71E-02

Raw Phosphorus, 18% in apatite, 12% in crude

ore, in ground

kg 1.14E-03 6.04E-07 3.13E-04 1.51E-05 1.61E-06 1.47E-03

Raw Phosphorus, 18% in apatite, 4% in crude ore,

in ground

kg 2.31E-03 1.37E-06 6.96E-04 3.34E-05 3.63E-06 3.05E-03

Raw Praseodymium, 0.42% in bastnasite, 0.042%

in crude ore, in ground

kg 3.01E-22 2.96E-25 2.90E-21 1.92E-23 4.74E-24 3.22E-21

Raw Pt, Pt 2.5E-4%, Pd 7.3E-4%, Rh 2.0E-5%, Ni


kg 1.92E-10 4.18E-11 8.14E-10 3.45E-11 3.41E-11 1.12E-09

Raw Pt, Pt 4.8E-4%, Pd 2.0E-4%, Rh 2.4E-5%, Ni


kg 6.90E-10 1.50E-10 2.92E-09 1.24E-10 1.22E-10 4.01E-09

Raw Rh, Rh 2.0E-5%, Pt 2.5E-4%, Pd 7.3E-4%, Ni


kg 1.91E-10 4.15E-11 8.05E-10 3.42E-11 3.39E-11 1.11E-09

Raw Rh, Rh 2.4E-5%, Pt 4.8E-4%, Pd 2.0E-4%, Ni


kg 5.97E-10 1.30E-10 2.52E-09 1.07E-10 1.06E-10 3.46E-09

Raw Rhenium, in crude ore, in ground kg 2.84E-10 1.63E-10 9.43E-10 6.52E-11 6.16E-11 1.52E-09

Raw Samarium, 0.3% in bastnasite, 0.03% in


kg -3.60E-23 -6.00E-25 -1.58E-22 -1.18E-24 -1.11E-24 -1.97E-22

Raw Sand, unspecified, in ground kg 2.68E-03 5.87E-08 6.81E-06 6.66E-05 7.36E-08 2.75E-03

Raw Shale, in ground kg 3.47E-04 1.21E-08 1.22E-06 7.93E-07 1.23E-08 3.49E-04

Raw Silver, 0.007% in sulfide, Ag 0.004%, Pb, Zn,

Cd, In, in ground

kg 1.89E-04 1.94E-12 6.37E-09 4.06E-11 1.18E-11 1.89E-04

Raw Silver, 3.2ppm in sulfide, Ag 1.2ppm, Cu and

Te, in crude ore, in ground

kg 1.35E-04 1.38E-12 4.54E-09 2.89E-11 8.42E-12 1.35E-04

Raw Silver, Ag 2.1E-4%, Au 2.1E-4%, in ore, in

ground

kg 1.24E-05 1.28E-13 4.19E-10 2.67E-12 7.77E-13 1.24E-05


ground

kg 2.84E-05 2.91E-13 9.58E-10 6.10E-12 1.77E-12 2.84E-05

65

Compart

ment


Assembly

Transport to

User



ground

kg 2.78E-05 2.86E-13 9.39E-10 5.98E-12 1.74E-12 2.78E-05

Raw Silver, Ag 9.7E-4%, Au 9.7E-4%, Zn 0.63%,

Cu 0.38%, Pb 0.014%, in ore, in ground

kg 1.83E-05 1.88E-13 6.19E-10 3.94E-12 1.15E-12 1.83E-05

Raw Sodium chloride, in ground kg 1.48E+00 1.69E-04 3.78E-01 3.60E-01 7.94E-04 2.22E+00

Raw Sodium nitrate, in ground kg 1.30E-08 1.92E-14 4.82E-12 1.90E-11 4.69E-14 1.30E-08

Raw Sodium sulphate, various forms, in ground kg 2.31E-03 2.87E-06 1.11E-03 5.42E-05 7.15E-06 3.49E-03

Raw Stibnite, in ground kg 5.51E-11 2.08E-14 6.45E-10 3.92E-12 8.73E-13 7.05E-10

Raw Sulfur, in ground kg 3.46E-02 8.54E-08 1.00E-05 3.50E-04 1.47E-07 3.49E-02

Raw Sylvite, 25 % in sylvinite, in ground kg 1.59E-02 9.03E-08 1.02E-04 2.94E-05 3.18E-07 1.60E-02

Raw Talc, in ground kg 1.85E-02 3.32E-09 3.50E-04 1.02E-05 4.68E-07 1.88E-02

Raw Tantalum, 81.9% in tantalite, 1.6E-4% in


kg 1.49E-04 1.53E-12 5.02E-09 3.19E-11 9.30E-12 1.49E-04

Raw Tellurium, 0.5ppm in sulfide, Te 0.2ppm, Cu

and Ag, in crude ore, in ground

kg 2.02E-05 2.07E-13 6.81E-10 4.34E-12 1.26E-12 2.02E-05

Raw Tin, 79% in cassiterite, 0.1% in crude ore, in

ground

kg 6.29E-03 7.20E-11 4.26E-07 4.10E-09 6.88E-10 6.30E-03

Raw TiO2, 54% in ilmenite, 2.6% in crude ore, in

ground

kg 7.07E-03 5.93E-06 6.33E-02 3.90E-04 9.50E-05 7.09E-02

Raw TiO2, 95% in rutile, 0.40% in crude ore, in

ground

kg 7.64E-05 1.29E-14 1.93E-10 1.53E-05 2.76E-13 9.17E-05

Raw Ulexite, in ground kg 7.59E-05 4.78E-12 2.35E-08 1.47E-10 3.94E-11 7.59E-05

Raw Uranium, in ground kg 9.30E-04 5.89E-07 1.78E-02 1.19E-04 2.41E-05 1.88E-02

Raw Vermiculite, in ground kg 6.57E-10 4.62E-12 2.83E-09 2.01E-11 1.12E-11 3.52E-09

Raw Washing Machine Water Use m3 x x 1.76E+02 5.30E-02 x 1.76E+02

Raw Water, cooling, unspecified natural origin/m3 m3 3.36E+00 4.23E-03 6.35E+01 6.55E-01 9.13E-02 6.76E+01

Raw Water, lake m3 1.11E-01 2.96E-06 3.61E+01 2.59E-02 6.19E-05 3.62E+01

Raw Water, process and cooling, unspecified

natural origin

m3 x x x 1.20E-04 x 1.20E-04

Raw Water, river m3 8.21E-01 7.65E-04 1.01E+02 1.28E-01 1.60E-02 1.02E+02

Raw Water, salt, ocean m3 6.89E-02 1.92E-04 1.08E+00 8.37E-03 1.78E-03 1.16E+00

Raw Water, salt, sole m3 5.89E-03 5.21E-04 2.35E-02 9.19E-04 1.11E-03 3.20E-02

Raw Water, turbine use, unspecified natural origin m3 2.57E+03 3.20E-01 2.95E+03 3.27E+02 4.19E+00 5.85E+03

Raw Water, unspecified natural origin/m3 m3 5.09E-01 1.62E-03 2.03E-01 2.37E-02 3.58E-03 7.41E-01

Raw Water, well, in ground m3 3.73E-01 5.75E-05 7.29E+01 6.41E-02 1.19E-03 7.34E+01

Raw Wood, hard, standing m3 1.29E-03 2.32E-07 2.55E-02 2.97E-04 2.89E-05 2.71E-02

Raw Wood, primary forest, standing m3 2.74E-07 8.25E-10 4.10E-08 3.35E-08 1.76E-09 3.51E-07

66

Compart

ment


Assembly

Transport to

User


Raw Wood, soft, standing m3 9.85E-03 6.10E-07 5.68E-02 2.73E-04 7.59E-05 6.70E-02

Raw Wood, unspecified, standing/m3 m3 1.16E-06 1.86E-11 1.90E-09 2.18E-08 3.58E-11 1.18E-06

Raw Zinc, 9.0% in sulfide, Zn 5.3%, Pb, Ag, Cd,

In, in ground

kg 1.09E-01 8.26E-08 3.08E-04 7.15E-02 5.21E-07 1.81E-01

Raw Zirconium, 50% in zircon, 0.39% in crude ore,

in ground

kg 2.05E-04 2.09E-12 6.86E-09 4.37E-11 1.27E-11 2.05E-04

Air 1-Propanol kg 2.58E-13 4.07E-16 2.13E-12 1.32E-14 3.52E-15 2.41E-12

Air 1,4-Butanediol kg 2.22E-06 5.08E-16 1.67E-12 1.06E-14 3.09E-15 2.22E-06

Air 2-Propanol kg 9.29E-04 9.50E-12 3.11E-08 1.98E-10 5.77E-11 9.29E-04

Air Acenaphthene kg 2.04E-10 8.62E-14 1.09E-08 2.77E-11 1.45E-11 1.11E-08

Air Acetaldehyde kg 3.38E-05 4.79E-05 2.34E-04 1.19E-05 1.76E-06 3.29E-04

Air Acetic acid kg 4.13E-04 2.99E-07 2.33E-03 2.04E-05 3.66E-06 2.77E-03

Air Acetone kg 1.15E-03 2.75E-08 3.24E-04 2.71E-06 4.74E-07 1.48E-03

Air Acetonitrile kg 2.88E-08 8.66E-11 4.30E-09 3.52E-09 1.84E-10 3.69E-08

Air Acrolein kg 3.46E-08 8.29E-11 2.68E-07 3.09E-09 1.05E-09 3.07E-07

Air Acrylic acid kg 2.40E-06 2.46E-14 8.05E-11 5.13E-13 1.49E-13 2.40E-06

Air Actinides, radioactive, unspecified Bq 5.64E-02 1.00E-05 3.50E-01 4.73E-03 4.73E-04 4.11E-01

Air Aerosols, radioactive, unspecified Bq 3.89E-01 2.39E-04 8.96E+00 5.20E-02 1.21E-02 9.41E+00

Air Aldehydes, unspecified kg 1.39E-05 2.21E-09 1.45E-05 4.27E-06 2.34E-08 3.27E-05

Air Aluminum kg 2.43E-02 4.91E-07 6.49E-02 1.23E-03 8.65E-05 9.04E-02

Air Ammonia kg 1.07E-02 3.12E-05 3.71E-02 5.70E-04 9.36E-05 4.85E-02

Air Ammonium carbonate kg 8.03E-09 6.00E-11 1.35E-09 9.90E-11 1.65E-11 9.56E-09

Air Antimony kg 1.98E-05 2.30E-10 4.30E-06 7.61E-07 5.83E-09 2.48E-05

Air Antimony-124 Bq 1.53E-06 3.94E-09 1.76E-06 9.39E-08 9.59E-09 3.40E-06

Air Antimony-125 Bq 1.59E-05 4.11E-08 1.84E-05 9.80E-07 1.00E-07 3.55E-05

Air Argon-41 Bq 1.54E+02 1.20E-01 2.11E+02 1.07E+01 3.41E-01 3.76E+02

Air Arsenic kg 7.79E-05 1.40E-08 5.64E-05 1.10E-05 1.01E-07 1.45E-04

Air Arsine kg 2.80E-11 2.86E-19 9.38E-16 5.98E-18 1.74E-18 2.80E-11

Air Barium kg 1.78E-05 4.49E-09 2.84E-04 3.25E-06 3.81E-07 3.05E-04

Air Barium-140 Bq 1.04E-03 2.67E-06 1.20E-03 6.38E-05 6.51E-06 2.31E-03

Air Benzal chloride kg 3.79E-14 2.42E-20 4.25E-16 1.16E-14 5.92E-19 4.99E-14

Air Benzaldehyde kg 1.06E-08 4.05E-11 8.82E-09 9.06E-10 3.73E-10 2.07E-08

Air Benzene kg 2.52E-03 1.03E-05 8.48E-03 7.68E-05 6.89E-05 1.12E-02

Air Benzene, ethyl- kg 1.68E-05 1.51E-06 6.15E-05 1.85E-06 2.31E-06 8.40E-05

Air Benzene, hexachloro- kg 2.87E-07 1.12E-13 1.16E-09 7.16E-09 8.49E-13 2.96E-07

Air Benzene, pentachloro- kg 5.53E-10 2.45E-13 2.36E-09 1.71E-10 1.37E-12 3.09E-09

Air Benzo(a)pyrene kg 6.71E-06 5.96E-10 3.07E-05 1.45E-06 4.17E-08 3.89E-05

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Air Beryllium kg 4.36E-07 3.52E-12 1.16E-07 2.96E-08 1.58E-10 5.83E-07

Air Boron kg 5.51E-04 3.14E-07 4.33E-03 6.93E-05 5.89E-06 4.95E-03

Air Boron trifluoride kg 2.09E-13 2.14E-21 7.00E-18 4.46E-20 1.30E-20 2.09E-13

Air Bromine kg 6.83E-05 3.46E-08 1.89E-03 9.33E-06 2.53E-06 1.97E-03

Air Butadiene kg 2.73E-08 3.22E-13 7.17E-12 2.72E-13 2.65E-13 2.73E-08

Air Butane kg 1.04E-03 4.71E-05 1.69E-02 1.56E-04 1.20E-04 1.83E-02

Air Butanol kg 6.87E-09 1.58E-18 5.17E-15 3.29E-17 9.58E-18 6.87E-09

Air Butene kg 1.00E-05 1.08E-06 3.95E-05 2.33E-06 2.28E-06 5.52E-05

Air Butyrolactone kg 6.41E-07 1.47E-16 4.82E-13 3.07E-15 8.94E-16 6.41E-07

Air Cadmium kg 1.75E-05 3.43E-08 8.35E-06 2.09E-06 7.91E-08 2.80E-05

Air Calcium kg 2.05E-04 1.45E-07 4.37E-03 3.64E-05 6.02E-06 4.61E-03

Air Carbon-14 Bq 1.51E+03 1.07E+00 2.97E+04 1.87E+02 4.03E+01 3.15E+04

Air Carbon dioxide kg x x x 1.85E-04 x 1.85E-04

Air Carbon dioxide, biogenic kg 2.51E+00 1.01E-03 7.54E+01 5.65E-01 1.16E-01 7.86E+01

Air Carbon dioxide, fossil kg 1.51E+02 2.59E+00 2.15E+03 1.83E+01 8.19E+00 2.33E+03

Air Carbon dioxide, land transformation kg 8.67E-03 3.67E-06 1.61E-01 4.82E-04 2.18E-04 1.71E-01

Air Carbon disulfide kg 8.41E-03 5.08E-08 8.29E-06 1.79E-04 5.21E-08 8.60E-03

Air Carbon monoxide kg x x x 1.06E-05 x 1.06E-05

Air Carbon monoxide, biogenic kg 1.77E-01 1.88E-07 1.47E-01 5.21E-02 1.18E-05 3.76E-01

Air Carbon monoxide, fossil kg 6.57E-01 6.87E-03 4.86E-01 2.21E-02 3.64E-03 1.17E+00

Air Cerium-141 Bq 2.51E-04 6.48E-07 2.90E-04 1.55E-05 1.58E-06 5.59E-04

Air Cesium-134 Bq 1.20E-05 3.10E-08 1.39E-05 7.40E-07 7.55E-08 2.68E-05

Air Cesium-137 Bq 2.13E-04 5.50E-07 2.47E-04 1.31E-05 1.34E-06 4.75E-04

Air Chlorine kg 3.92E-04 7.72E-08 1.53E-04 4.93E-06 3.55E-07 5.51E-04

Air Chloroform kg 2.01E-06 1.28E-11 3.53E-07 2.25E-09 4.81E-10 2.36E-06

Air Chlorosilane, trimethyl- kg 4.32E-08 4.41E-16 1.45E-12 9.21E-15 2.68E-15 4.32E-08

Air Chromium kg 3.16E-03 9.15E-08 6.33E-05 7.80E-04 2.25E-07 4.00E-03

Air Chromium-51 Bq 1.61E-05 4.15E-08 1.86E-05 9.91E-07 1.01E-07 3.58E-05

Air Chromium VI kg 7.80E-05 2.86E-10 3.95E-06 1.95E-05 5.65E-09 1.02E-04

Air Cobalt kg 3.71E-05 2.63E-08 5.66E-05 9.47E-06 1.24E-07 1.03E-04

Air Cobalt-58 Bq 2.24E-05 5.78E-08 2.59E-05 1.38E-06 1.41E-07 4.99E-05

Air Cobalt-60 Bq 1.98E-04 5.11E-07 2.29E-04 1.22E-05 1.24E-06 4.41E-04

Air Copper kg 5.45E-04 4.11E-06 7.54E-05 5.47E-05 5.34E-06 6.85E-04

Air Cumene kg 3.04E-04 5.06E-08 5.98E-06 1.72E-06 1.15E-07 3.12E-04

Air Cyanide kg 6.25E-05 8.35E-10 1.46E-05 9.06E-06 2.19E-08 8.62E-05

Air Dinitrogen monoxide kg 3.56E-03 1.12E-04 7.44E-02 5.10E-04 3.44E-04 7.90E-02

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Air Dioxins, measured as 2,3,7,8-

tetrachlorodibenzo-p-dioxin

kg 2.44E-10 9.09E-15 1.45E-10 9.91E-11 2.04E-13 4.89E-10

Air Ethane kg 3.34E-03 1.48E-05 5.63E-02 7.13E-04 9.73E-05 6.05E-02

Air Ethane, 1,1-difluoro-, HFC-152a kg 7.38E-12 1.16E-14 6.09E-11 3.78E-13 1.01E-13 6.88E-11

Air Ethane, 1,1,1-trichloro-, HCFC-140 kg 5.45E-10 9.66E-14 3.37E-09 4.57E-11 4.56E-12 3.97E-09

Air Ethane, 1,1,1,2-tetrafluoro-, HFC-134a kg 3.01E-07 2.47E-11 1.07E-06 5.76E-09 1.44E-09 1.38E-06

Air Ethane, 1,1,2-trichloro-1,2,2-trifluoro-, CFC-

113

kg 1.14E-07 1.17E-15 3.82E-12 2.43E-14 7.09E-15 1.14E-07

Air Ethane, 1,2-dichloro- kg 2.87E-05 3.00E-09 1.12E-06 7.80E-05 7.70E-09 1.08E-04

Air Ethane, 1,2-dichloro-1,1,2,2-tetrafluoro-, CFC-

114

kg 6.55E-07 4.39E-10 1.53E-05 8.78E-08 2.07E-08 1.61E-05

Air Ethane, hexafluoro-, HFC-116 kg 6.11E-05 6.25E-12 6.76E-07 1.36E-05 9.02E-10 7.54E-05

Air Ethanol kg 3.57E-05 4.79E-08 3.33E-04 4.51E-06 5.18E-07 3.74E-04

Air Ethene kg 6.62E-04 2.20E-06 1.95E-03 1.94E-04 4.87E-06 2.82E-03

Air Ethene, chloro- kg 2.07E-05 5.97E-10 1.15E-07 5.77E-05 1.36E-09 7.85E-05

Air Ethene, tetrachloro- kg 1.18E-09 2.08E-13 7.25E-09 9.96E-11 9.81E-12 8.53E-09

Air Ethyl acetate kg 4.31E-03 4.41E-11 1.45E-07 9.20E-10 2.68E-10 4.31E-03

Air Ethyl cellulose kg 8.73E-06 8.92E-14 2.92E-10 1.86E-12 5.42E-13 8.73E-06

Air Ethylene diamine kg 4.94E-08 2.39E-15 3.09E-10 5.14E-12 4.12E-13 4.97E-08

Air Ethylene oxide kg 7.87E-06 6.56E-10 7.82E-08 9.66E-09 1.49E-09 7.96E-06

Air Ethyne kg 4.10E-05 6.21E-10 2.71E-05 7.95E-06 3.73E-08 7.61E-05

Air Fluorine kg 4.73E-05 5.85E-10 3.66E-05 3.51E-06 4.90E-08 8.75E-05

Air Fluosilicic acid kg 6.22E-05 7.20E-12 7.89E-07 1.59E-05 1.05E-09 7.89E-05

Air Formaldehyde kg 2.75E-04 8.89E-05 1.85E-03 4.22E-05 5.17E-06 2.26E-03

Air Formic acid kg 5.59E-06 5.80E-10 2.90E-08 2.35E-08 1.23E-09 5.65E-06

Air Furan kg 5.47E-08 1.65E-10 8.18E-09 6.68E-09 3.50E-10 7.00E-08

Air Heat, waste MJ 2.51E+03 3.75E+01 2.54E+04 3.08E+02 9.97E+01 2.84E+04

Air Helium kg 2.67E-05 4.07E-06 1.11E-04 4.65E-06 8.59E-06 1.55E-04

Air Heptane kg 9.96E-05 1.08E-05 3.95E-04 1.69E-05 2.28E-05 5.45E-04

Air Hexane kg 4.20E-04 2.34E-05 1.20E-02 6.46E-05 6.35E-05 1.25E-02

Air Hydrocarbons, aliphatic, alkanes, cyclic kg 1.52E-05 7.22E-10 1.80E-07 1.01E-07 1.76E-09 1.55E-05

Air Hydrocarbons, aliphatic, alkanes, unspecified kg 2.77E-03 1.25E-05 4.37E-03 1.12E-04 8.47E-06 7.27E-03

Air Hydrocarbons, aliphatic, unsaturated kg 1.96E-04 2.11E-06 5.17E-03 3.09E-05 6.92E-06 5.41E-03

Air Hydrocarbons, aromatic kg 2.67E-03 2.15E-06 7.73E-05 4.03E-05 2.33E-07 2.79E-03

Air Hydrocarbons, chlorinated kg 7.81E-05 2.21E-11 3.43E-07 4.43E-05 3.81E-10 1.23E-04

Air Hydrogen kg 9.74E-04 3.40E-07 1.09E-03 4.91E-05 2.05E-06 2.12E-03

Air Hydrogen-3, Tritium Bq 8.90E+03 5.77E+00 1.87E+05 1.14E+03 2.52E+02 1.97E+05

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Air Hydrogen chloride kg 7.70E-03 3.59E-06 8.25E-02 1.35E-03 1.17E-04 9.16E-02

Air Hydrogen fluoride kg 2.41E-03 5.98E-07 3.03E-02 4.74E-04 4.08E-05 3.32E-02

Air Hydrogen peroxide kg 6.47E-06 6.61E-14 2.17E-10 1.38E-12 4.02E-13 6.47E-06

Air Hydrogen sulfide kg 8.30E-04 7.55E-08 1.97E-04 7.69E-05 2.97E-07 1.10E-03

Air Iodine kg 3.49E-05 1.84E-08 8.13E-04 4.58E-06 1.09E-06 8.54E-04

Air Iodine-129 Bq 1.53E+00 1.02E-03 3.08E+01 1.92E-01 4.17E-02 3.26E+01

Air Iodine-131 Bq 6.09E+01 4.69E-02 8.36E+01 4.25E+00 1.34E-01 1.49E+02

Air Iodine-133 Bq 8.04E-03 4.44E-06 4.50E-02 3.33E-04 6.67E-05 5.34E-02

Air Iodine-135 Bq 1.48E-02 2.70E-06 9.44E-02 5.57E-04 1.28E-04 1.10E-01

Air Iron kg 4.70E-04 1.43E-07 2.86E-04 7.69E-05 6.55E-07 8.34E-04

Air Isocyanic acid kg 1.52E-10 2.89E-13 1.25E-09 7.79E-12 2.15E-12 1.41E-09

Air Isoprene kg 2.54E-09 7.64E-12 3.79E-10 3.10E-10 1.63E-11 3.25E-09

Air Krypton-85 Bq 4.82E+02 3.75E-01 6.61E+02 3.36E+01 1.07E+00 1.18E+03

Air Krypton-85m Bq 2.26E+01 4.44E-02 2.78E+01 1.46E+00 1.11E-01 5.21E+01

Air Krypton-87 Bq 9.18E+00 1.30E-02 1.19E+01 6.14E-01 3.37E-02 2.17E+01



Air Lanthanum-140 Bq 8.86E-05 2.28E-07 1.02E-04 5.45E-06 5.56E-07 1.97E-04

Air Lead kg 4.10E-04 2.54E-07 1.82E-04 5.10E-05 5.54E-07 6.44E-04

Air Lead-210 Bq 1.25E+01 4.91E-03 3.11E+02 2.13E+00 4.16E-01 3.26E+02

Air m-Xylene kg 2.20E-06 9.39E-10 8.77E-05 3.21E-07 1.17E-07 9.03E-05

Air Magnesium kg 2.72E-04 6.16E-09 4.69E-04 6.02E-05 6.28E-07 8.02E-04

Air Manganese kg 9.99E-05 3.52E-09 2.08E-04 6.78E-06 2.79E-07 3.15E-04

Air Manganese-54 Bq 8.25E-06 2.13E-08 9.53E-06 5.07E-07 5.18E-08 1.84E-05

Air Mercury kg 4.17E-05 1.29E-08 5.82E-05 1.69E-06 1.00E-07 1.02E-04

Air Methane kg x x x 6.03E-07 x 6.03E-07

Air Methane, biogenic kg 2.25E-03 1.00E-06 3.77E-02 1.79E-03 2.94E-03 4.47E-02

Air Methane, bromo-, Halon 1001 kg 8.66E-15 5.53E-21 9.72E-17 2.64E-15 1.35E-19 1.14E-14

Air Methane, bromochlorodifluoro-, Halon 1211 kg 7.53E-07 2.55E-10 4.52E-06 9.91E-08 6.27E-09 5.38E-06

Air Methane, bromotrifluoro-, Halon 1301 kg 3.28E-07 3.36E-08 1.15E-06 4.81E-08 7.11E-08 1.63E-06

Air Methane, chlorodifluoro-, HCFC-22 kg 7.24E-06 9.88E-10 2.68E-05 3.75E-07 3.63E-08 3.44E-05

Air Methane, dichloro-, HCC-30 kg 7.77E-08 2.46E-12 5.91E-08 3.01E-08 8.15E-11 1.67E-07

Air Methane, dichlorodifluoro-, CFC-12 kg 9.43E-08 2.22E-12 5.17E-09 8.47E-08 6.20E-12 1.84E-07

Air Methane, dichlorofluoro-, HCFC-21 kg 7.44E-10 7.77E-18 2.57E-14 1.64E-16 4.76E-17 7.44E-10

Air Methane, fossil kg 4.45E-01 2.56E-03 4.54E+00 3.83E-02 1.13E-02 5.04E+00

Air Methane, monochloro-, R-40 kg 1.61E-08 2.56E-12 8.94E-08 1.21E-09 1.21E-10 1.07E-07

Air Methane, tetrachloro-, CFC-10 kg 7.93E-07 1.59E-10 4.21E-07 7.91E-09 7.93E-10 1.22E-06

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Air Methane, tetrafluoro-, CFC-14 kg 4.79E-04 5.55E-11 6.08E-06 1.23E-04 8.12E-09 6.08E-04

Air Methane, trichlorofluoro-, CFC-11 kg 1.21E-09 1.26E-17 4.18E-14 2.66E-16 7.73E-17 1.21E-09

Air Methane, trifluoro-, HFC-23 kg 2.37E-07 2.47E-15 8.19E-12 5.21E-14 1.51E-14 2.37E-07

Air Methanol kg 2.45E-04 6.94E-07 4.08E-04 6.31E-06 9.20E-07 6.61E-04

Air Methyl acrylate kg 2.73E-06 2.79E-14 9.13E-11 5.82E-13 1.69E-13 2.73E-06

Air Methyl amine kg 2.31E-07 5.30E-17 1.74E-13 1.11E-15 3.22E-16 2.31E-07

Air Methyl borate kg 9.21E-13 9.41E-21 3.08E-17 1.96E-19 5.72E-20 9.21E-13

Air Methyl ethyl ketone kg 4.31E-03 4.41E-11 1.45E-07 9.20E-10 2.68E-10 4.31E-03

Air Methyl formate kg 1.06E-08 1.08E-16 3.54E-13 2.26E-15 6.57E-16 1.06E-08

Air Molybdenum kg 1.86E-06 1.29E-08 1.68E-05 2.52E-07 4.70E-08 1.90E-05

Air Monoethanolamine kg 1.21E-04 6.88E-11 2.12E-06 1.71E-08 2.87E-09 1.23E-04

Air Nickel kg 2.24E-04 5.00E-07 4.63E-04 2.76E-05 1.57E-06 7.17E-04

Air Niobium-95 Bq 9.79E-07 2.52E-09 1.13E-06 6.02E-08 6.14E-09 2.18E-06

Air Nitrate kg 1.06E-06 2.17E-11 2.89E-06 4.80E-08 3.86E-09 4.01E-06

Air Nitrogen kg x x x 1.78E-04 x 1.78E-04

Air Nitrogen oxides kg 3.45E-01 1.37E-02 3.77E+00 4.02E-02 3.61E-02 4.20E+00

Air NMVOC, non-methane volatile organic

compounds, unspecified origin

kg 8.57E-02 1.88E-03 1.38E-01 7.33E-03 5.47E-03 2.38E-01

Air Noble gases, radioactive, unspecified Bq 1.47E+07 9.82E+03 2.96E+08 1.84E+06 4.01E+05 3.13E+08

Air Oxygen kg x x x 1.21E-06 x 1.21E-06

Air Ozone kg 6.56E-04 3.39E-07 1.88E-02 9.33E-05 2.37E-05 1.96E-02

Air PAH, polycyclic aromatic hydrocarbons kg 1.91E-04 1.58E-08 1.62E-04 4.48E-05 3.14E-07 3.99E-04

Air Paraffins kg 8.14E-15 1.52E-17 5.04E-14 3.20E-16 9.31E-17 5.90E-14

Air Particulates, < 10 um (stationary) kg x x x 1.71E-10 x 1.71E-10

Air Particulates, < 2.5 um kg 9.78E-02 5.54E-04 3.52E-01 1.31E-02 1.52E-03 4.65E-01

Air Particulates, > 10 um kg 1.76E-01 2.45E-04 1.67E+00 1.61E-02 2.79E-03 1.86E+00

Air Particulates, > 2.5 um, and < 10um kg 1.22E-01 2.39E-04 6.30E-02 1.04E-02 6.08E-04 1.96E-01

Air Pentane kg 8.89E-03 5.84E-05 1.98E-02 1.92E-04 1.47E-04 2.91E-02

Air Phenol kg 2.14E-04 1.28E-11 2.31E-07 1.10E-06 3.10E-10 2.16E-04

Air Phenol, pentachloro- kg 4.05E-07 2.51E-10 1.33E-05 3.96E-08 1.78E-08 1.38E-05

Air Phosphine kg 2.08E-09 2.12E-17 6.96E-14 4.43E-16 1.29E-16 2.08E-09

Air Phosphorus kg 1.05E-05 2.56E-09 2.23E-04 2.23E-06 2.98E-07 2.36E-04

Air Platinum kg 1.65E-11 1.36E-14 2.27E-11 1.16E-12 3.84E-14 4.05E-11

Air Plutonium-238 Bq 2.09E-07 1.39E-10 4.20E-06 2.61E-08 5.69E-09 4.45E-06

Air Plutonium-alpha Bq 4.79E-07 3.20E-10 9.64E-06 5.99E-08 1.30E-08 1.02E-05

Air Polonium-210 Bq 2.22E+01 8.60E-03 5.57E+02 3.82E+00 7.44E-01 5.83E+02

Air Polychlorinated biphenyls kg 4.38E-07 3.46E-14 3.62E-10 1.05E-08 5.34E-13 4.49E-07

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Air Potassium kg 5.18E-04 1.85E-07 1.72E-02 8.46E-05 2.29E-05 1.78E-02

Air Potassium-40 Bq 3.13E+00 1.07E-03 8.53E+01 5.64E-01 1.14E-01 8.91E+01

Air Propanal kg 1.06E-08 4.05E-11 8.83E-09 9.06E-10 3.73E-10 2.07E-08

Air Propane kg 1.54E-03 4.73E-05 1.94E-02 2.24E-04 1.23E-04 2.13E-02

Air Propene kg 2.33E-04 2.19E-06 3.19E-04 2.09E-05 4.93E-06 5.80E-04

Air Propionic acid kg 9.72E-06 1.83E-09 2.19E-04 1.39E-06 2.92E-07 2.30E-04

Air Propylene oxide kg 2.01E-05 2.69E-09 6.49E-08 2.49E-09 2.89E-09 2.02E-05

Air Protactinium-234 Bq 2.13E-01 1.44E-04 4.37E+00 2.69E-02 5.92E-03 4.62E+00

Air Radioactive species, other beta emitters Bq 8.57E-01 3.27E-04 9.96E+00 6.11E-02 1.35E-02 1.09E+01

Air Radium-226 Bq 9.99E+00 5.89E-03 2.20E+02 1.40E+00 2.96E-01 2.32E+02

Air Radium-228 Bq 4.61E+00 4.45E-04 3.15E+01 1.12E+00 4.21E-02 3.73E+01

Air Radon-220 Bq 1.06E+02 4.86E-02 3.72E+03 1.64E+01 4.98E+00 3.85E+03

Air Radon-222 Bq 2.79E+07 1.91E+04 5.77E+08 3.53E+06 7.82E+05 6.09E+08

Air Ruthenium-103 Bq 2.15E-07 5.54E-10 2.49E-07 1.32E-08 1.35E-09 4.79E-07

Air Scandium kg 1.02E-07 8.79E-13 6.73E-08 2.00E-08 9.01E-11 1.89E-07

Air Selenium kg 2.13E-05 2.29E-08 1.09E-04 1.41E-06 1.85E-07 1.32E-04

Air Silicon kg 1.34E-03 1.45E-08 8.51E-04 5.23E-04 1.14E-06 2.72E-03

Air Silicon tetrafluoride kg 1.60E-08 1.04E-11 5.26E-09 2.53E-10 2.75E-11 2.16E-08

Air Silver kg 1.15E-09 3.81E-14 5.46E-10 2.73E-11 7.87E-13 1.72E-09

Air Silver-110 Bq 2.13E-06 5.49E-09 2.46E-06 1.31E-07 1.34E-08 4.75E-06

Air Sodium kg 1.12E-04 6.44E-07 1.20E-03 1.85E-05 2.83E-06 1.33E-03

Air Sodium chlorate kg 1.22E-07 1.26E-10 4.45E-07 4.73E-09 8.24E-10 5.72E-07

Air Sodium dichromate kg 7.23E-08 1.24E-13 3.69E-07 2.83E-10 1.78E-12 4.41E-07

Air Sodium formate kg 1.47E-07 4.50E-13 7.05E-09 2.75E-09 1.02E-11 1.57E-07

Air Sodium hydroxide kg 2.41E-05 2.46E-13 8.08E-10 5.14E-12 1.50E-12 2.41E-05

Air Strontium kg 2.15E-05 4.44E-09 3.01E-04 4.24E-06 4.02E-07 3.27E-04

Air Styrene kg 2.47E-05 9.60E-11 1.90E-07 1.62E-08 4.51E-10 2.49E-05

Air Sulfate kg 1.82E-03 3.78E-07 7.08E-03 8.39E-05 6.91E-06 8.99E-03

Air Sulfur dioxide kg 4.87E-01 2.22E-03 4.83E+00 5.65E-02 1.09E-02 5.39E+00

Air Sulfur hexafluoride kg 9.14E-06 4.54E-09 6.05E-04 2.10E-04 8.07E-07 8.25E-04

Air Sulfuric acid kg 5.05E-06 5.16E-14 1.69E-10 1.08E-12 3.14E-13 5.05E-06

Air t-Butyl methyl ether kg 2.31E-07 1.02E-06 1.41E-07 1.69E-07 1.68E-10 1.56E-06

Air Terpenes kg 2.40E-08 7.22E-11 3.59E-09 2.93E-09 1.54E-10 3.07E-08

Air Thallium kg 1.67E-07 1.30E-12 9.09E-08 2.51E-08 1.22E-10 2.84E-07

Air Thorium kg 1.39E-07 1.32E-12 1.01E-07 2.98E-08 1.36E-10 2.70E-07

Air Thorium-228 Bq 7.77E-01 2.19E-04 1.54E+01 1.51E-01 2.06E-02 1.64E+01


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Air Tin kg 2.55E-05 6.08E-11 3.10E-07 5.45E-06 4.68E-10 3.12E-05

Air Titanium kg 2.70E-05 2.72E-10 2.03E-05 5.92E-06 2.71E-08 5.33E-05

Air Toluene kg 2.24E-04 2.24E-05 2.17E-03 3.61E-05 3.61E-05 2.49E-03

Air Uranium kg 1.61E-07 1.76E-12 1.35E-07 3.90E-08 1.81E-10 3.35E-07

Air Uranium-234 Bq 2.49E+00 1.69E-03 5.08E+01 3.11E-01 6.88E-02 5.37E+01

Air Uranium-235 Bq 1.19E-01 8.13E-05 2.46E+00 1.51E-02 3.34E-03 2.60E+00

Air Uranium-238 Bq 4.85E+00 2.53E-03 1.11E+02 7.28E-01 1.49E-01 1.17E+02

Air Uranium alpha Bq 1.14E+01 7.83E-03 2.37E+02 1.45E+00 3.21E-01 2.50E+02

Air Vanadium kg 1.51E-04 7.10E-07 7.02E-04 1.64E-05 2.29E-06 8.73E-04

Air water kg 3.79E-02 7.62E-07 9.88E-02 1.64E-03 1.32E-04 1.38E-01

Air Xenon-131m Bq 4.21E+01 6.38E-02 5.40E+01 2.80E+00 1.64E-01 9.91E+01

Air Xenon-133 Bq 1.34E+03 2.18E+00 1.69E+03 8.80E+01 5.54E+00 3.13E+03

Air Xenon-133m Bq 5.80E+00 5.54E-03 7.83E+00 4.00E-01 1.52E-02 1.41E+01

Air Xenon-135 Bq 5.48E+02 8.83E-01 6.97E+02 3.62E+01 2.25E+00 1.28E+03

Air Xenon-135m Bq 3.23E+02 5.39E-01 4.08E+02 2.12E+01 1.37E+00 7.54E+02

Air Xenon-137 Bq 6.17E+00 1.40E-02 7.35E+00 3.88E-01 3.44E-02 1.40E+01

Air Xenon-138 Bq 5.47E+01 1.11E-01 6.68E+01 3.50E+00 2.75E-01 1.25E+02

Air Xylene kg 5.48E-04 1.70E-05 1.25E-02 7.32E-05 4.50E-05 1.32E-02

Air Zinc kg 1.00E-03 2.51E-06 5.50E-04 2.44E-04 7.04E-06 1.80E-03

Air Zinc-65 Bq 4.12E-05 1.06E-07 4.76E-05 2.53E-06 2.58E-07 9.17E-05

Air Zirconium kg 3.53E-07 6.18E-14 4.30E-10 9.58E-09 6.75E-13 3.63E-07

Air Zirconium-95 Bq 4.03E-05 1.04E-07 4.65E-05 2.48E-06 2.53E-07 8.96E-05

Water 1,4-Butanediol kg 8.87E-07 2.03E-16 6.67E-13 4.24E-15 1.24E-15 8.87E-07

Water 4-Methyl-2-pentanone kg 2.25E-10 1.44E-16 2.52E-12 6.86E-11 3.51E-15 2.96E-10

Water Acenaphthene kg 3.03E-09 2.75E-10 1.18E-08 4.69E-10 5.84E-10 1.61E-08

Water Acenaphthylene kg 1.90E-10 1.72E-11 7.36E-10 2.93E-11 3.65E-11 1.01E-09

Water Acetaldehyde kg 2.86E-05 2.92E-13 9.57E-10 6.10E-12 1.78E-12 2.86E-05

Water Acetic acid kg 6.09E-05 1.07E-08 1.20E-06 5.11E-08 2.42E-08 6.22E-05

Water Acetone kg 5.36E-10 3.42E-16 6.01E-12 1.63E-10 8.37E-15 7.05E-10

Water Acidity, unspecified kg 2.96E-05 2.32E-09 1.38E-07 8.83E-07 3.87E-09 3.06E-05

Water Acrylate, ion kg 5.69E-06 5.82E-14 1.91E-10 1.21E-12 3.53E-13 5.69E-06

Water Actinides, radioactive, unspecified Bq 2.49E+00 1.66E-03 5.01E+01 3.11E-01 6.77E-02 5.29E+01

Water Aluminum kg 2.28E-01 3.95E-05 7.37E-01 4.50E-02 5.00E-03 1.01E+00

Water Ammonium, ion kg 1.11E-03 3.52E-06 3.28E-03 3.11E-04 1.86E-04 4.89E-03

Water Antimony kg 1.52E-04 1.64E-08 1.03E-04 1.03E-05 1.48E-07 2.65E-04

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Water Antimony-122 Bq 6.16E-04 1.59E-06 7.11E-04 3.79E-05 3.86E-06 1.37E-03

Water Antimony-124 Bq 4.30E-01 3.08E-04 1.02E+01 5.83E-02 1.39E-02 1.07E+01

Water Antimony-125 Bq 4.47E-01 2.82E-04 1.41E+01 7.07E-02 1.90E-02 1.46E+01

Water AOX, Adsorbable Organic Halogen as Cl kg 8.69E-05 2.93E-08 1.10E-05 4.22E-06 7.34E-08 1.02E-04

Water Arsenic, ion kg 2.55E-04 4.21E-08 5.33E-04 2.89E-05 2.01E-06 8.19E-04

Water Barite kg 1.73E-06 2.03E-09 1.45E-05 8.94E-08 2.27E-08 1.63E-05

Water Barium kg 1.41E-03 3.91E-05 3.22E-03 1.69E-04 8.64E-05 4.92E-03

Water Barium-140 Bq 2.70E-03 6.95E-06 3.12E-03 1.66E-04 1.69E-05 6.00E-03

Water Benzene kg 7.20E-03 3.03E-06 1.42E-04 1.02E-05 6.45E-06 7.36E-03

Water Benzene, 1,2-dichloro- kg 2.98E-04 6.83E-14 2.24E-10 1.43E-12 4.16E-13 2.98E-04

Water Benzene, chloro- kg 6.15E-03 1.41E-12 4.63E-09 2.95E-11 8.58E-12 6.15E-03

Water Benzene, ethyl- kg 1.17E-05 1.06E-06 4.54E-05 1.81E-06 2.25E-06 6.22E-05

Water Beryllium kg 9.14E-06 4.97E-09 6.47E-05 1.15E-06 1.34E-07 7.52E-05

Water BOD5, Biological Oxygen Demand kg 3.76E-01 7.30E-03 9.53E-01 2.79E-02 2.53E-02 1.39E+00

Water Boron kg 1.12E-03 8.68E-07 5.80E-03 1.33E-04 9.07E-06 7.07E-03

Water Bromate kg 1.08E-04 1.42E-08 4.38E-05 8.15E-06 7.93E-08 1.60E-04

Water Bromine kg 5.52E-04 3.10E-05 1.81E-03 6.91E-05 6.64E-05 2.53E-03

Water Butanol kg 1.56E-05 1.60E-13 5.24E-10 3.34E-12 9.73E-13 1.56E-05

Water Butene kg 1.01E-07 4.21E-13 6.51E-08 1.52E-06 9.40E-12 1.69E-06

Water Butyl acetate kg 2.03E-05 2.08E-13 6.82E-10 4.34E-12 1.26E-12 2.03E-05

Water Butyrolactone kg 1.54E-06 3.53E-16 1.16E-12 7.37E-15 2.15E-15 1.54E-06

Water Cadmium kg x x x 1.17E-14 x 1.17E-14

Water Cadmium, ion kg 2.44E-05 1.48E-08 1.63E-05 9.53E-07 3.43E-07 4.20E-05

Water Calcium, ion kg 5.54E-01 1.46E-03 6.24E-01 3.44E-02 6.25E-02 1.28E+00

Water Carbonate kg 7.99E-03 7.89E-08 5.86E-04 1.44E-04 8.37E-07 8.72E-03

Water Carboxylic acids, unspecified kg 2.05E-03 1.83E-04 8.13E-03 3.19E-04 3.88E-04 1.11E-02

Water Cerium-141 Bq 1.08E-03 2.78E-06 1.25E-03 6.63E-05 6.77E-06 2.40E-03

Water Cerium-144 Bq 3.28E-04 8.46E-07 3.79E-04 2.02E-05 2.06E-06 7.31E-04

Water Cesium kg 4.87E-07 4.42E-08 1.89E-06 7.54E-08 9.39E-08 2.59E-06

Water Cesium-134 Bq 4.25E-01 2.22E-04 1.42E+01 6.97E-02 1.90E-02 1.47E+01

Water Cesium-136 Bq 1.91E-04 4.93E-07 2.21E-04 1.18E-05 1.20E-06 4.26E-04

Water Cesium-137 Bq 2.86E+02 1.92E-01 5.77E+03 3.59E+01 7.80E+00 6.10E+03

Water Chlorate kg 8.60E-04 1.16E-07 3.56E-04 1.43E-04 6.49E-07 1.36E-03

Water Chloride kg 9.68E-01 2.23E-02 9.57E+00 1.19E-01 5.79E-02 1.07E+01

Water Chlorinated solvents, unspecified kg 2.19E-06 1.21E-10 1.07E-07 1.15E-06 3.65E-10 3.45E-06

Water Chlorine kg 6.79E-05 5.79E-09 1.77E-02 1.40E-05 2.05E-07 1.78E-02

Water Chloroform kg 3.18E-07 3.25E-15 1.06E-11 6.78E-14 1.98E-14 3.18E-07

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Water Chromium kg x x x 5.59E-13 x 5.59E-13

Water Chromium-51 Bq 4.59E-01 6.18E-04 1.08E+01 6.06E-02 1.54E-02 1.14E+01

Water Chromium VI kg 1.16E-02 3.23E-08 5.12E-04 3.25E-04 7.02E-07 1.24E-02

Water Chromium, ion kg 1.61E-05 1.41E-07 7.34E-05 8.41E-07 3.89E-07 9.09E-05

Water Cobalt kg 2.69E-03 5.73E-08 1.77E-04 7.30E-04 9.01E-07 3.60E-03

Water Cobalt-57 Bq 6.08E-03 1.57E-05 7.02E-03 3.74E-04 3.81E-05 1.35E-02

Water Cobalt-58 Bq 3.48E+00 3.48E-03 8.56E+01 4.75E-01 1.18E-01 8.96E+01

Water Cobalt-60 Bq 2.70E+00 2.89E-03 6.46E+01 3.62E-01 9.00E-02 6.77E+01

Water COD, Chemical Oxygen Demand kg 9.48E-01 7.36E-03 9.92E-01 5.28E-02 5.42E-02 2.05E+00

Water Copper kg x x x 5.59E-13 x 5.59E-13

Water Copper, ion kg 1.15E-03 5.41E-07 7.21E-04 1.57E-04 5.99E-06 2.03E-03

Water Cumene kg 7.31E-04 1.22E-07 1.44E-05 4.12E-06 2.77E-07 7.50E-04

Water Cyanide kg 9.63E-04 8.98E-08 3.85E-06 8.55E-06 1.88E-07 9.75E-04

Water Dichromate kg 3.29E-10 2.38E-13 1.18E-09 3.98E-11 2.38E-12 1.55E-09

Water DOC, Dissolved Organic Carbon kg 3.21E-01 2.27E-03 3.01E-01 1.90E-02 3.93E-02 6.83E-01

Water Ethane, 1,2-dichloro- kg 4.73E-07 1.23E-10 1.64E-06 2.25E-07 2.36E-09 2.34E-06

Water Ethanol kg 3.60E-05 3.68E-13 1.21E-09 7.68E-12 2.24E-12 3.60E-05

Water Ethene kg 1.73E-05 5.11E-08 5.76E-06 5.42E-07 1.16E-07 2.37E-05

Water Ethene, chloro- kg 2.96E-07 2.66E-12 4.85E-10 8.02E-07 6.26E-12 1.10E-06

Water Ethyl acetate kg 2.46E-09 2.51E-17 8.23E-14 5.24E-16 1.53E-16 2.46E-09

Water Ethylene diamine kg 1.20E-07 5.80E-15 7.49E-10 1.25E-11 9.98E-13 1.20E-07

Water Ethylene oxide kg 2.69E-06 1.27E-13 3.20E-09 2.57E-11 4.37E-12 2.69E-06

Water Fluoride kg 3.96E-01 2.90E-06 4.14E-03 2.91E-03 1.76E-05 4.03E-01

Water Fluosilicic acid kg 1.12E-04 1.30E-11 1.42E-06 2.87E-05 1.90E-09 1.42E-04

Water Formaldehyde kg 3.82E-05 5.51E-08 1.29E-06 1.95E-07 1.52E-08 3.97E-05

Water Glutaraldehyde kg 2.13E-10 2.50E-13 1.79E-09 1.10E-11 2.81E-12 2.01E-09

Water Heat, waste MJ 9.22E+01 5.87E-01 2.13E+03 1.27E+01 9.06E+00 2.24E+03

Water Hydrocarbons, aliphatic, alkanes, unspecified kg 6.34E-05 5.75E-06 2.46E-04 9.80E-06 1.22E-05 3.37E-04

Water Hydrocarbons, aliphatic, unsaturated kg 5.85E-06 5.31E-07 2.27E-05 9.05E-07 1.13E-06 3.11E-05

Water Hydrocarbons, aromatic kg 2.57E-04 2.34E-05 9.98E-04 3.98E-05 4.96E-05 1.37E-03

Water Hydrocarbons, unspecified kg 1.08E-03 1.07E-07 8.96E-05 7.67E-05 2.90E-07 1.25E-03

Water Hydrogen-3, Tritium Bq 6.58E+05 4.38E+02 1.33E+07 8.26E+04 1.80E+04 1.41E+07

Water Hydrogen peroxide kg 5.38E-05 1.54E-11 9.29E-05 6.85E-08 2.90E-10 1.47E-04

Water Hydrogen sulfide kg 3.98E-05 8.65E-09 6.00E-04 4.31E-06 1.24E-04 7.68E-04

Water Hydroxide kg 1.79E-04 1.84E-12 6.04E-09 3.84E-11 1.12E-11 1.79E-04

Water Hypochlorite kg 3.64E-05 2.05E-08 4.26E-04 5.08E-06 5.75E-07 4.68E-04

Water Iodide kg 5.48E-05 4.42E-06 2.24E-04 8.06E-06 9.44E-06 3.01E-04

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Water Iodine-131 Bq 7.99E-02 6.05E-05 2.02E+00 1.11E-02 2.74E-03 2.11E+00

Water Iodine-133 Bq 1.69E-03 4.36E-06 1.96E-03 1.04E-04 1.06E-05 3.77E-03

Water Iron kg x x x 1.25E-10 x 1.25E-10

Water Iron-59 Bq 4.66E-04 1.20E-06 5.38E-04 2.86E-05 2.92E-06 1.04E-03

Water Iron, ion kg 9.74E-02 4.48E-05 8.68E-02 1.52E-02 3.67E-04 2.00E-01

Water Lanthanum-140 Bq 2.87E-03 7.40E-06 3.32E-03 1.77E-04 1.80E-05 6.39E-03

Water Lead kg 2.08E-04 4.66E-07 5.37E-04 1.59E-05 2.09E-05 7.82E-04

Water Lead-210 Bq 1.14E+01 6.01E-03 2.42E+02 1.01E+00 3.31E-01 2.55E+02

Water Lithium, ion kg 5.76E-05 3.68E-11 6.47E-07 1.76E-05 9.01E-10 7.59E-05

Water m-Xylene kg 1.62E-09 1.04E-15 1.82E-11 4.95E-10 2.54E-14 2.14E-09

Water Magnesium kg 4.82E-02 2.51E-04 1.58E-01 4.01E-03 7.62E-04 2.11E-01

Water Manganese kg 1.53E-03 2.28E-06 8.01E-03 9.97E-05 9.42E-05 9.74E-03

Water Manganese-54 Bq 2.21E-01 2.12E-04 5.87E+00 3.15E-02 8.09E-03 6.13E+00

Water Mercury kg 5.18E-06 6.24E-10 2.89E-06 1.62E-07 1.20E-07 8.36E-06

Water Methane, dichloro-, HCC-30 kg 3.83E-09 3.61E-12 2.42E-08 1.50E-10 3.84E-11 2.82E-08

Water Methanol kg 1.13E-04 1.88E-08 6.50E-06 1.28E-06 1.37E-08 1.21E-04

Water Methyl acrylate kg 5.33E-05 5.45E-13 1.78E-09 1.14E-11 3.31E-12 5.33E-05

Water Methyl amine kg 5.55E-07 1.27E-16 4.17E-13 2.66E-15 7.74E-16 5.55E-07

Water Methyl formate kg 4.22E-09 4.32E-17 1.41E-13 9.01E-16 2.62E-16 4.22E-09

Water Mineral oil kg x x x 1.87E-10 x 1.87E-10

Water Molybdenum kg 6.21E-05 4.18E-08 4.88E-04 6.78E-06 7.77E-07 5.57E-04

Water Molybdenum-99 Bq 9.91E-04 2.55E-06 1.14E-03 6.09E-05 6.22E-06 2.20E-03

Water Nickel kg x x x 1.22E-11 x 1.22E-11

Water Nickel, ion kg 1.13E-02 2.42E-07 1.30E-03 2.67E-03 7.95E-06 1.53E-02

Water Niobium-95 Bq 5.02E-02 2.41E-05 2.29E+00 1.00E-02 3.06E-03 2.35E+00

Water Nitrate kg 6.99E-03 5.11E-06 3.19E-02 1.67E-03 2.38E-04 4.08E-02

Water Nitrite kg 5.96E-05 4.90E-09 9.63E-05 1.24E-05 8.07E-06 1.76E-04

Water Nitrogen kg 6.55E-04 1.75E-06 5.45E-03 9.86E-05 1.17E-05 6.21E-03

Water Nitrogen, organic bound kg 1.92E-03 3.39E-06 6.71E-04 1.16E-04 2.15E-04 2.93E-03

Water o-Xylene kg 1.18E-09 7.56E-16 1.33E-11 3.61E-10 1.85E-14 1.56E-09

Water Oils, unspecified kg 3.21E-02 2.31E-03 2.98E-01 4.97E-03 5.16E-03 3.42E-01

Water PAH, polycyclic aromatic hydrocarbons kg 1.11E-05 2.47E-07 1.11E-05 1.39E-06 5.25E-07 2.43E-05

Water Paraffins kg 2.36E-14 4.40E-17 1.46E-13 9.30E-16 2.70E-16 1.71E-13

Water Phenol kg 2.72E-04 4.08E-06 1.84E-04 8.21E-06 8.67E-06 4.77E-04

Water Phosphate kg 1.86E-02 7.22E-07 8.65E-03 1.39E-03 1.45E-05 2.87E-02

Water Phosphorus kg 4.16E-04 2.06E-07 2.86E-05 9.79E-06 4.52E-07 4.55E-04

Water Polonium-210 Bq 1.46E+01 8.07E-03 2.43E+02 1.05E+00 3.36E-01 2.59E+02

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Water Potassium-40 Bq 7.39E+00 3.11E-03 3.02E+02 1.15E+00 4.04E-01 3.11E+02

Water Potassium, ion kg 2.52E-02 1.88E-04 1.97E-01 2.30E-03 6.62E-04 2.26E-01

Water Propene kg 3.20E-04 4.99E-08 5.55E-06 3.59E-06 1.08E-07 3.29E-04

Water Propylene oxide kg 4.83E-05 6.46E-09 1.56E-07 5.99E-09 6.96E-09 4.85E-05

Water Protactinium-234 Bq 3.89E+00 2.66E-03 8.05E+01 4.92E-01 1.09E-01 8.50E+01

Water Radioactive species, alpha emitters Bq 2.01E-02 1.18E-05 7.68E-03 2.98E-04 3.35E-05 2.81E-02

Water Radioactive species, Nuclides, unspecified Bq 1.49E+03 9.96E-01 2.99E+04 1.86E+02 4.05E+01 3.17E+04

Water Radium-224 Bq 2.44E+01 2.21E+00 9.46E+01 3.77E+00 4.70E+00 1.30E+02



Water Rubidium kg 5.02E-06 4.42E-07 2.20E-05 7.73E-07 9.43E-07 2.92E-05

Water Ruthenium-103 Bq 2.09E-04 5.39E-07 2.41E-04 1.29E-05 1.31E-06 4.65E-04

Water Scandium kg 2.30E-05 1.08E-08 4.26E-04 3.30E-06 5.71E-07 4.53E-04

Water Selenium kg 3.17E-05 1.74E-08 1.34E-04 5.42E-06 2.36E-07 1.71E-04

Water Silicon kg 8.97E+00 2.35E-04 2.52E+00 7.42E-01 3.68E-03 1.22E+01

Water Silver-110 Bq 2.32E+00 2.77E-03 4.32E+01 2.75E-01 6.15E-02 4.59E+01

Water Silver, ion kg 6.78E-07 4.08E-08 1.97E-06 1.16E-07 8.69E-08 2.89E-06

Water Sodium-24 Bq 7.50E-03 1.93E-05 8.66E-03 4.61E-04 4.70E-05 1.67E-02

Water Sodium formate kg 3.54E-07 1.08E-12 1.69E-08 6.60E-09 2.45E-11 3.78E-07

Water Sodium, ion kg 5.88E-01 1.34E-02 7.51E-01 7.29E-02 3.01E-02 1.46E+00

Water Solids, inorganic kg 9.25E-02 4.50E-05 1.14E-01 7.16E-03 1.73E-04 2.14E-01

Water Solved solids kg 5.82E-02 1.20E-06 1.21E-01 7.18E-03 1.61E-04 1.87E-01

Water Strontium kg 1.96E-03 8.05E-05 1.32E-02 2.62E-04 1.85E-04 1.57E-02

Water Strontium-89 Bq 5.37E-02 5.49E-05 1.82E+00 8.77E-03 2.51E-03 1.89E+00

Water Strontium-90 Bq 1.69E+03 1.30E+00 2.91E+03 1.20E+02 4.52E+00 4.73E+03

Water Sulfate kg 7.52E-01 3.00E-04 1.41E+00 5.37E-02 6.94E-03 2.23E+00

Water Sulfide kg 3.77E-06 5.28E-08 4.20E-05 5.31E-07 1.62E-07 4.66E-05

Water Sulfite kg 1.05E-04 5.58E-08 1.61E-03 1.49E-05 2.16E-06 1.73E-03

Water Sulfur kg 1.47E-04 5.22E-06 7.53E-04 1.13E-05 1.18E-05 9.28E-04

Water Suspended solids, unspecified kg 1.49E-02 4.58E-05 2.20E-02 8.70E-04 1.22E-04 3.80E-02

Water t-Butyl methyl ether kg 9.05E-07 9.07E-08 4.15E-06 1.49E-07 1.51E-07 5.44E-06

Water Technetium-99m Bq 2.29E-02 5.88E-05 2.66E-02 1.41E-03 1.43E-04 5.11E-02

Water Tellurium-123m Bq 5.13E-02 2.96E-05 1.51E+00 7.82E-03 2.03E-03 1.57E+00

Water Tellurium-132 Bq 5.74E-05 1.48E-07 6.63E-05 3.53E-06 3.60E-07 1.28E-04

Water Thallium kg 2.26E-06 6.59E-10 2.92E-05 2.31E-07 1.01E-07 3.18E-05

Water Thorium-228 Bq 9.76E+01 8.84E+00 3.78E+02 1.51E+01 1.88E+01 5.19E+02

Water Thorium-230 Bq 5.30E+02 3.63E-01 1.10E+04 6.71E+01 1.49E+01 1.16E+04

77

Compart

ment


Assembly

Transport to

User


Water Thorium-232 Bq 1.24E+00 4.92E-04 5.62E+01 2.12E-01 7.50E-02 5.78E+01

Water Thorium-234 Bq 3.89E+00 2.66E-03 8.05E+01 4.92E-01 1.09E-01 8.50E+01

Water Tin, ion kg 3.66E-05 1.50E-08 7.10E-05 3.28E-06 8.11E-07 1.12E-04

Water Titanium, ion kg 3.48E-02 1.08E-06 2.61E-02 8.34E-03 3.33E-05 6.93E-02

Water TOC, Total Organic Carbon kg 3.23E-01 2.28E-03 3.02E-01 1.92E-02 3.93E-02 6.86E-01

Water Toluene kg 6.01E-05 5.54E-06 2.34E-04 9.40E-06 1.18E-05 3.21E-04

Water Tributyltin compounds kg 3.20E-06 3.96E-08 3.68E-05 3.85E-07 1.30E-07 4.05E-05

Water Triethylene glycol kg 8.11E-06 1.92E-09 5.09E-06 1.04E-06 7.61E-09 1.43E-05

Water Tungsten kg 1.48E-05 8.00E-09 2.10E-04 1.93E-06 2.83E-07 2.27E-04

Water Uranium-234 Bq 4.66E+00 3.19E-03 9.66E+01 5.91E-01 1.31E-01 1.02E+02

Water Uranium-235 Bq 7.69E+00 5.26E-03 1.59E+02 9.74E-01 2.16E-01 1.68E+02

Water Uranium-238 Bq 1.74E+01 1.11E-02 3.62E+02 1.98E+00 4.92E-01 3.82E+02

Water Uranium alpha Bq 2.24E+02 1.53E-01 4.64E+03 2.84E+01 6.28E+00 4.90E+03

Water Vanadium, ion kg 2.68E-03 1.19E-07 2.55E-03 3.35E-04 5.57E-06 5.58E-03

Water VOC, volatile organic compounds, unspecified

origin

kg 1.80E-04 1.55E-05 8.64E-04 2.76E-05 3.31E-05 1.12E-03

Water Xylene kg 4.94E-05 4.45E-06 1.94E-04 7.69E-06 9.45E-06 2.65E-04

Water Zinc kg x x x 1.30E-12 x 1.30E-12

Water Zinc-65 Bq 1.02E-01 2.62E-04 1.17E-01 6.25E-03 6.38E-04 2.26E-01

Water Zinc, ion kg 3.06E-03 1.76E-05 1.36E-03 6.24E-05 7.00E-05 4.57E-03

Water Zirconium-95 Bq 1.18E-03 3.03E-06 1.36E-03 7.24E-05 7.38E-06 2.62E-03

Waste Washing Machine Waste kg x x x 3.66E+00 1.30E+02 1.34E+02

Soil 2,4-D kg 1.37E-08 2.91E-11 1.44E-09 1.18E-09 6.19E-11 1.64E-08

Soil Aclonifen kg 3.57E-08 4.11E-13 2.22E-08 5.77E-10 2.68E-11 5.85E-08

Soil Aldrin kg 6.18E-08 6.32E-16 2.07E-12 1.32E-14 3.84E-15 6.18E-08

Soil Aluminum kg 6.32E-05 3.25E-08 2.01E-03 1.79E-05 2.70E-06 2.10E-03

Soil Antimony kg 4.15E-09 4.57E-16 1.23E-11 7.47E-14 1.67E-14 4.16E-09

Soil Arsenic kg 3.95E-07 7.10E-12 6.48E-07 3.76E-09 8.63E-10 1.05E-06

Soil Atrazine kg 1.62E-08 1.66E-16 5.43E-13 3.46E-15 1.01E-15 1.62E-08

Soil Barium kg 1.40E-07 6.84E-10 4.92E-07 3.60E-09 2.05E-09 6.39E-07

Soil Benomyl kg 6.16E-11 1.85E-13 9.20E-12 7.52E-12 3.95E-13 7.89E-11

Soil Bentazone kg 1.82E-08 2.10E-13 1.13E-08 2.94E-10 1.37E-11 2.98E-08

Soil Boron kg 1.02E-08 1.74E-10 1.95E-08 2.75E-10 3.85E-10 3.05E-08

Soil Cadmium kg 8.94E-07 5.04E-09 1.37E-06 8.30E-09 1.36E-08 2.30E-06

Soil Calcium kg 6.72E-04 3.74E-07 2.74E-02 1.36E-04 3.67E-05 2.83E-02

Soil Carbetamide kg 8.98E-09 8.64E-14 5.55E-09 1.57E-10 6.90E-12 1.47E-08

Soil Carbofuran kg 3.37E-08 1.02E-10 5.05E-09 4.12E-09 2.16E-10 4.32E-08

78

Compart

ment


Assembly

Transport to

User


Soil Carbon kg 1.64E-04 1.96E-07 1.21E-03 1.28E-04 1.99E-06 1.50E-03

Soil Chloride kg 9.74E-06 6.68E-09 3.26E-04 1.24E-06 4.40E-07 3.37E-04

Soil Chlorothalonil kg 2.50E-06 1.20E-11 1.52E-06 5.25E-08 2.03E-09 4.08E-06

Soil Chromium kg 1.40E-06 2.42E-08 1.89E-05 1.23E-07 8.15E-08 2.05E-05

Soil Chromium VI kg 3.65E-09 5.68E-12 2.97E-08 1.84E-10 4.89E-11 3.36E-08

Soil Cobalt kg 4.53E-08 1.91E-11 1.74E-06 1.21E-08 2.32E-09 1.80E-06

Soil Copper kg 1.33E-05 3.37E-07 1.60E-05 4.10E-07 8.12E-07 3.09E-05

Soil Cypermethrin kg 5.03E-09 1.43E-11 8.78E-10 5.87E-10 3.07E-11 6.54E-09

Soil Fenpiclonil kg 9.98E-08 4.87E-13 6.06E-08 2.09E-09 8.08E-11 1.63E-07

Soil Fluoride kg 8.19E-09 1.10E-11 6.76E-08 4.18E-10 1.09E-10 7.63E-08

Soil Glyphosate kg 7.32E-08 2.03E-10 1.43E-08 8.20E-09 4.37E-10 9.64E-08

Soil Heat, waste MJ 2.81E+00 7.58E-03 8.33E+01 3.85E-01 2.65E-01 8.67E+01

Soil Iron kg 3.56E-03 1.12E-05 1.82E-02 2.84E-04 4.65E-05 2.21E-02

Soil Lead kg 2.10E-06 2.07E-07 6.39E-06 1.71E-07 4.94E-07 9.36E-06

Soil Linuron kg 2.88E-07 3.17E-12 1.71E-07 4.44E-09 2.06E-10 4.64E-07

Soil Magnesium kg 7.61E-05 3.83E-08 3.10E-03 1.54E-05 4.14E-06 3.20E-03

Soil Mancozeb kg 3.25E-06 1.56E-11 1.98E-06 6.82E-08 2.64E-09 5.30E-06

Soil Manganese kg 4.54E-05 2.20E-08 1.93E-03 7.25E-06 2.58E-06 1.99E-03

Soil Mercury kg 1.85E-09 1.97E-13 1.05E-08 1.04E-09 1.41E-11 1.34E-08

Soil Metaldehyde kg 2.33E-09 1.93E-14 1.44E-09 4.31E-11 1.82E-12 3.81E-09

Soil Metolachlor kg 1.99E-06 2.29E-11 1.24E-06 3.22E-08 1.49E-09 3.26E-06

Soil Metribuzin kg 1.15E-07 5.49E-13 6.95E-08 2.40E-09 9.28E-11 1.87E-07

Soil Molybdenum kg 1.10E-08 4.12E-12 3.58E-07 4.67E-09 4.78E-10 3.74E-07

Soil Napropamide kg 4.13E-09 3.42E-14 2.54E-09 7.62E-11 3.22E-12 6.75E-09

Soil Nickel kg 6.68E-06 6.49E-08 5.37E-06 6.76E-08 1.60E-07 1.23E-05

Soil Oils, biogenic kg 2.22E-04 1.44E-09 1.45E-04 2.39E-06 1.72E-07 3.69E-04

Soil Oils, unspecified kg 2.95E-02 2.34E-03 1.36E-01 4.79E-03 5.01E-03 1.77E-01

Soil Orbencarb kg 6.19E-07 2.96E-12 3.76E-07 1.30E-08 5.01E-10 1.01E-06

Soil Phosphorus kg 2.22E-05 1.01E-08 9.46E-04 3.46E-06 1.26E-06 9.73E-04

Soil Pirimicarb kg 1.72E-09 1.98E-14 1.07E-09 2.78E-11 1.29E-12 2.82E-09

Soil Potassium kg 1.23E-04 5.63E-08 5.26E-03 1.92E-05 7.01E-06 5.41E-03

Soil Silicon kg 2.19E-04 8.72E-08 7.98E-03 5.03E-05 1.06E-05 8.26E-03

Soil Sodium kg 2.39E-07 3.05E-10 1.97E-06 1.22E-08 3.15E-09 2.23E-06

Soil Strontium kg 1.57E-08 2.25E-09 7.10E-08 2.47E-09 4.75E-09 9.62E-08

Soil Sulfur kg 2.96E-05 1.06E-08 8.92E-04 1.43E-05 1.19E-06 9.37E-04

Soil Sulfuric acid kg 3.12E-09 3.19E-17 1.04E-13 6.65E-16 1.94E-16 3.12E-09

Soil Tebutam kg 9.78E-09 8.11E-14 6.02E-09 1.81E-10 7.62E-12 1.60E-08

79

Compart

ment


Assembly

Transport to

User


Soil Teflubenzuron kg 7.64E-09 3.66E-14 4.64E-09 1.60E-10 6.19E-12 1.24E-08

Soil Thiram kg 1.09E-10 3.29E-13 1.63E-11 1.33E-11 7.00E-13 1.40E-10

Soil Tin kg 1.92E-08 1.26E-12 4.56E-09 1.42E-08 8.32E-12 3.80E-08

Soil Titanium kg 3.12E-06 1.42E-09 1.33E-04 4.87E-07 1.78E-07 1.37E-04

Soil Vanadium kg 8.94E-08 4.08E-11 3.81E-06 1.39E-08 5.08E-09 3.92E-06

Soil Zinc kg 2.71E-05 1.42E-05 1.67E-04 7.49E-06 3.35E-05 2.49E-04

80

Appendix 4

Final Critical Review Statement

This section includes the Final Critical Review Statement from the Peer Review team, led by ARUP, and the authors’ final

response.

81

1 Introduction

As defined in ISO 1404034

, critical review “is a technique for verify whether an LCA study has

met the requirements of [ISO 14040] for methodology, data and reporting”. How a critical

review is carried out, and who carries it out, is defined in the scope of the study.

Critical review is required where an LCA compares alternatives with the intention of disclosing

results and conclusions to the public.

The purpose of a critical review, as set out in ISO 14040, is to ensure that:

The methods used to carry out the LCA are consistent with ISO 14040;

The methods used to carry out the LCA are scientifically and technically valid;

The data used are appropriate and reasonable in relation to the goal of the study;

The interpretations reflect the limitations identified and the goal of the study;

The study report is transparent and consistent.

A critical review cannot:

Verify or validate the goals that are chosen for an LCA;

The uses to which the LCA results are put.

This statement sets out the views of the critical review panel, having evaluated the study on

the basis of the criteria set out above.

2 Panel Members

The critical review panel members are as follows:

Dr David Dowdell Ove Arup & Partners Ltd (Chair);

David Parker Oakdene Hollins Ltd;

Robert Shaw Indesit

Due to David leaving Arup towards the end of this project a colleague, Helen Jackson, stood

in to complete the critical review statement.

3 Scope of the Critical Review

The members of the critical review panel met on 24th July 2009 to review the working draft

report entitled Environmental Life Cycle Assessment (LCA) Study of Replacement and

Refurbishment Options for Domestic Washing Machines (April 2009). Prior to this meeting, Dr

David Dowdell reviewed and provided comments for a Goal & Scope Report in February

2009.

Since this meeting a list of comments from the review panel were issued to ERM and the

report has since been updated to reflect these comments from the critical review panel. It

should be noted that section references mentioned in the original critical review statement do

not now correlate with the final copy of the report. The references mentioned in this critical

review relate to “Environmental Life Cycle Assessment (LCA) Study of Replacement and

34 International Organisation for Standardisation (ISO); Environmental Management – Life Cycle Assessment – Principles and Framework; 2006

82

Refurbishment options for domestic washing machines – Final Report”, issued 2nd

October

2009.

4 Further Comments

4.1 Scope

Most comments made by the Review Panel have been addressed as requested. There is one

minor outstanding issue:

Footnote on p19 gives incorrect section reference, 4.4.5 should be 3.4.5

It is still not clear if spare parts for refurbishing machines are new or overhauled parts

from old machines. Whilst transport of spare parts is stated as not included the source of

the parts are not clear.

5 Assumptions

A list of assumptions was suggested by the review panel for the sake of transparency in this

study, with Panel members requiring clarification on the following:

“Washing machine component production assembly is assumed to take place in Europe

and Great Britain respectively.” This does not quite make sense. It should say ‘production

and assembly’ to correlate with statement in Appendix 2.

6 Functional Unit

A comment from the Review Panel previously requested an additional statement in the

functional unit providing the total mass of cotton fabric washed as a result of 3313 full loads.

This change has not been implemented but a reason was given in a footnote stating that

‘reduced load size does not always result in reduced energy consumption’.

Although ERM do state that this assumption requires further research to confirm this is

feasible, current market data has been used to include average loads for different energy

label class.

This is considered the best possible solution at this time but the use of market data should

perhaps be made clearer in the main body of the report to demonstrate understanding of this

particular issue.

7 Reporting

Whilst section 6 and 7 are greatly improved with regards to visual presentation of results, the

method chosen does not maintain a static baseline. Using proportional changes for each

environmental factor compared to each maximum value only compares an individual element

in the study. If a single, unchanging baseline was considered across all environmental

measures it would be more informative overall (e.g. ‘replace A/refurb A then Replace A’ is the

base scenario against all other scenarios and between all environmental factors). It would

then demonstrate differences in the scenarios both above and below the same single, static

base line for every environmental element considered.

83

8 Miscellaneous Issues

A couple of outstanding miscellaneous issues are still to be resolved:

The use of lubricating oil data as opposed to light fuel oil has been implemented but Table

4.2 still mentions light fuel oil with respect to lubricating oil in washing machine assembly.

Mass of ball bearings has been clarified but details of the manufacturing process are

exceptionally brief. It is recommended that the comment in the tile of Table 4.8 is

removed and re-inserted in Appendix 3 with further detail.

9 Summary

None of the issues described above have any significant effect on the study outputs. These

final items noted are merely a case of completeness and transparency to the reader. ERM’s

recommendations that further research should be carried out into typical machine loading and

use will add to the reliability and feasibility of the assumptions made in what is a

comprehensive study for the data currently available.

Final response comments from ERM were received by e-mail and are quoted verbatim below:

Footnote on p19 gives incorrect section reference, 4.4.5 should be 3.4.5 *now updated It is still not clear if spare parts for refurbishing machines are new or overhauled parts from old machines. Whilst transport of spare parts is stated as not included the source of the parts are not clear. *pp58 in report – FRN replace all these parts with brand new parts to ensure these parts do not fail post-refurbishment. As a result, these replacement parts are modelled as new. “Washing machine component production assembly is assumed to take place in Europe and Great Britain respectively.” This does not quite make sense. It should say ‘production and assembly’ to correlate with statement in Appendix 2. *Typo, updated

This change has not been implemented but a reason was given in a footnote stating that ‘reduced load size does not always result in reduced energy consumption’. *footnote updated Whilst section 6 and 7 are greatly improved with regards to visual presentation of results, the method chosen does not maintain a static baseline. *not incorrect, a suggestion for presentation, not an ISO issue. No remaining budget to change. The use of lubricating oil data as opposed to light fuel oil has been implemented but Table 4.2 still mentions light fuel oil with respect to lubricating oil in washing machine assembly. * Updated Mass of ball bearings has been clarified but details of the manufacturing process are exceptionally brief. It is recommended that the comment in the tile of Table 4.8 is removed and re-inserted in Appendix 3 with further detail. *details are provided in reference ekdahl et al

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Documents

Final Report Environmental Life Cycle Assessment … report Washing...Document reference: WRAP, 2010, Environmental Life Cycle Assessment (LCA) Study of Replacement and Refurbishment