Final Report A Carbon Footprint for UK Clothing and ... IV - Carbon footprint...Final Report A...

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Final Report

A Carbon Footprint for UK Clothing and Opportunities for Savings

July 2012

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Document reference: [eg WRAP, 2006, Report Name (WRAP Project TYR009-19. Report prepared by…..Banbury, WRAP]

Written by: Bernie Thomas, Matt Fishwick, James Joyce and Anton van Santen

Environmental Resources Management Limited (ERM)

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0.0 Executive summary

Environmental Resources Management Limited (ERM) was commissioned by WRAP to conduct a life

cycle carbon footprint study for UK clothing. The objective of the research was to provide WRAP with an

overview of the carbon impacts of UK clothing through the clothing life cycle, identifying the most

significant contributions to the carbon footprint (ie the ‘hotspots’), and quantifying opportunities for

carbon footprint reduction.

Estimated Current Carbon Footprint for UK Clothing

A strategic-level carbon footprint study was undertaken based on published data and information about

UK clothing. UK Clothing is defined as all clothing, both new and existing, in use in the UK over the

period of one year. The analysis covers both clothing manufactured and used in the UK and clothing

manufactured abroad and used in the UK. The datum is 2009, as the year for which the most recent

data are available.

The study’s results present the annual climate change impact associated with UK clothing, in terms of its

carbon footprint. This includes the impacts associated with the quantity of clothes that are produced for

the UK and consumed and disposed of each year, as well as the impacts associated with clothing that is

actively worn and cleaned each year (approximately 1.1 million tonnes of new clothing is consumed in

the UK each year, ~2.5 million tonnes is in active use. Note that this is greater than the annual

consumption of clothing, because clothes last for more than one year).

Figure 1 presents the baseline (current) carbon footprint estimate for all clothing in use in the UK in

2009. The results are broken down by both life cycle stage and fibre type to show their relative

contributions to the total footprint. The following conclusions can be drawn from the results.

The total annual carbon footprint of all garments, both new and existing, in use in the UK in

2009 (i.e. the volume consumed, and the actively worn quantity) is approximately 38 million

tonnes of CO2e (~0.6 tonnes per person per year). Because the majority of clothing is

manufactured outside the UK, it is estimated that ~32% occurs within the UK (contributing to

the UK’s direct carbon footprint) and 68% occurs abroad. Based on this estimate, the direct

impact of clothing in the UK can be estimated to be ~12 million tonnes of CO2e. Note that this

baseline analysis does not examine the effect of uncertainties, which are considered further in

the sensitivity analysis section of the report (Section 4.6).

To put this carbon footprint of UK clothing into context, the total direct GHG emissions in the

UK in 2009 were reported as 566 million tonnes of CO2e (DECC, 2011). It should be noted that

this total for the UK does not include GHG emissions associated with imported goods or

services or international travel. Therefore, the direct carbon footprint of clothing contributes

approximately 2% to the UK’s total direct carbon footprint.

The carbon footprint of new garments ONLY, in use in the UK in 2009, can also be calculated

by dividing the carbon footprint of both new and existing clothing by its anticipated lifetime.

This figure is approximately 17 million tonnes of CO2e.

The most dominant life cycle stage is fabric production (comprising weaving/knitting etc. and

treatment of fabric), representing 33% of total life cycle GHG impacts.

The carbon footprint of a tonne of garments, both new and existing, in use in the UK in 2009

ranges from around 15 to 46 tonnes CO2e, depending on the fibre type of the garment.

The carbon footprint of each garment, both new and existing, in use in the UK in 2009 ranges

from around 1 to 17 kg CO2e.

The per person carbon footprint of all garments, both new and existing, in use in the UK in

2009 is around 0.6 tonnes of CO2e.

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Figure 1: Carbon footprint all clothing in use in the UK in 2009, whether manufactured in or imported to the UK, represented as a total for the UK, broken down by life cycle

stage and fibre type

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Savings Achieved in the Central scenario

The study also quantifies the potential effect of a number of example impact reduction measures relative

to the estimated baseline footprint. Reduction measures are presented for a realistic ‘Central’ future

reduction scenario, and also an aspirational ‘What If?’ reduction scenario. Options for reduction are

considered across the life cycle (eg eco-efficiency in the manufacture, retail and distribution of clothing,

washing at lower temperatures, increasing load size, more reuse etc.).

Table 1 and Figure 2 below present the estimated carbon saving from the baseline footprint for 2009.

Reduction measure

Baseline

(t CO2e)

Reduction

(t CO2e) Reduction %

Eco-efficiency across supply chain

(production, distribution and retail) -

Central scenario - 5% reduction for all

fibres across supply chain 38,175,293

1,563,219 -4.1%

Design for Durability (and product lifetime

optimisation) - Central scenario - 10%

longer lifetime of clothing 38,175,293 2,941,203 -7.7%

Shift in market to higher proportion of

synthetic fibres - Central scenario -

replace 10% of cotton with 50:50 poly-

cotton. [Data exclude in-use savings] 38,175,293 164,150 -0.4%

Clean clothing less - Central scenario -

washes per year reduced by 10% 38,175,293 989,905 -2.6%

Wash at lower temperature - Central

scenario - weighted average wash

temperature of 39.3C 38,175,293 549,604 -1.4%

Increase size of washing and drying loads

- Central scenario - load increases to

3.7kg 38,175,293 531,538 -1.4%

Use the tumble dryer less - Central

scenario - 30% reduction in tumble dryer

use in summer 38,175,293 430,367 -1.1%

Dispose less - reuse more - Central

scenario – 15.4% of clothing ultimately

reused in UK 38,175,293 272,063 -0.7%

Start closed loop recycling of synthetic

fibres - Central scenario - 5% of all

clothing is recycled (closed loop) 38,175,293 352,144 -0.9%

Dispose less - recycle more (open loop) -

Central scenario - 38% of all clothing is

recycled open loop 38,175,293 195,729 -0.5%

Cumulative reduction

7,989,921 -20.9%

Table 1: Savings achieved by each reduction measure of the Central scenario

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Figure 2: Savings achieved by each reduction measure of the Central scenario

From the estimates presented in Table 1 and Figure 2, the following points are evident.

A potential 21% reduction in the carbon footprint of UK clothing would occur if all reduction

measures considered for the Central scenario were achieved.

The largest carbon footprint reductions are achieved by extending product lifetime (8%), eco-

efficiency across the supply chain (4% reduction) and washing clothing less (3% reduction).

As calculated, reduction measures resulting in minimal reductions in carbon footprint include

increasing open loop recycling, increasing reuse and a shift in the market to a larger proportion

of synthetic fibres. [Note: the term ‘synthetics’ is used here to include man-made fibres such as

viscose.]

Table 2 presents all the reduction measures considered in order of effectiveness for the Central scenario.

Rank Reduction Measure Stakeholder

1

Design for Durability (and Product lifetime optimisation) - central scenario - 10%

longer lifetime of clothing Manufacturer/

consumer

2

Eco efficiency across supply chain (production, distribution and retail) - central

scenario - 5% reduction for all fibres across supply chain Manufacturer

3 Clean clothing less - central scenario - Washes per year reduced by 10% Consumer

4

Wash at lower temperature - central scenario - weighted average wash temperature

of 39.3C Consumer

5 Increase size of washing and drying loads - central scenario - load increases to 3.7kg Consumer

6

Use the tumble dryer less - central scenario - 30% reduction in tumble dryer use in

summer Consumer

7

Start closed loop recycling of synthetic fibres - central scenario - 5% of all clothing is

recycled (closed loop) Consumer

8 Dispose less - reuse more - central scenario - 15.4% of clothing reused in the UK Consumer

9

Dispose less - recycle more (open loop) - central scenario - 19.5% of all clothing is

recycled open loop Consumer

10

Shift in market to higher proportion of synthetic fibres - central scenario - Replace

10% of cotton with 50:50 poly-cotton Manufacturer/

consumer

Table 2: Reduction measures of the Central scenario in order of effectiveness

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Savings Achieved in the What If? Scenario

Figure 3 presents the potential estimated carbon saving from the baseline generated by each reduction

measure in a more ambitious ‘What If?’ scenario.

Figure 3: Savings achieved by each reduction measure of the ‘What If?’ scenario

The estimated reductions presented in Figure 3 indicate the following.

A 71% reduction in the carbon footprint of UK clothing will occur if all reduction measures

considered by the ‘What If?’ scenario are achieved.

The largest carbon footprint reductions are achieved by extending product lifetime (27%

reduction), eco-efficiencies across the supply chain (24% reduction) and washing less (4%

reduction).

Reduction measures resulting in the smallest reductions in carbon footprint include increasing

closed loop recycling, increasing open loop recycling and a shift to a higher proportion of

synthetics.

In addition to the reduction measures presented in the above scenarios, a series of consumer

interventions were analysed in the study to examine their influence on carbon footprint results. The

impact of ten post-sale in-use interventions was examined through a change in the behaviour of 10% of

the UK population under each measure). The purpose of this exercise was to compare the effectiveness

of a variety of measures to change consumer behaviour during the use phase once the clothing has

been purchased. Consistent with the findings of the main scenarios, the in-use interventions resulting in

the greatest savings are a shift towards behaviours that lead to an increase in clothing lifetime by one

year and cleaning clothing less, followed by less reliance on tumble drying.

The report also presents a series of sensitivity analyses to investigate the study’s key uncertainties.

These examine the sensitivity of the results and conclusions to a change in a particular assumption or

data point. The sensitivity analyses undertaken were: the influence of a future decarbonised electricity

grid on the impact of the use phase; the influence of fibre type on washing and drying impacts; the

influence of product lifetime on results; the influence of washing frequency on results; and the influence

of UK fibre mix on results. The findings of these analyses indicate the following.

Future ‘decarbonisation’ of UK electricity will decrease the direct carbon footprint associated

with the cleaning of clothing. The significance of the use phase (primarily washing and drying)

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impacts, relative to upstream life cycle stages (raw materials, manufacture and distribution,

retail) and end of life impacts will reduce.

Where the energy use impacts of tumble drying are allocated to clothing based on the relative

drying time of fibre types (rather than by its mass only as they are in the main analysis), the

carbon footprint increases from the baseline for natural fibres (by ~2-5%) and decreases for

synthetic fibres (by ~3-5%). The total remains the same.

Where loads are mixed and drying energy is based on the slowest drying item of clothing (ie

natural fibres), the carbon footprint for each fibre type increases from the baseline. This

reflects an increase in the drying time of all fibre types caused by a natural fibre type being

present in each load. This is in comparison to a baseline average energy usage where some

loads are mixed and some are separated.

When the difference in washing temperature is also considered, the reduction achieved from

the shift towards synthetics in both the central and ‘What If?’ scenarios is around a third larger.

The longer the lifetime of clothing (eg from clothing simply being retained in use by the

consumer for longer, design for durability, reuse, or from leasing or resale), the lower the

carbon footprint (reduced supply chain impacts, primarily) and the shorter the lifetime of

clothing that is used, the higher the carbon footprint.

Where it is assumed in the analysis clothing is washed 5 times per kilogram per year, the total

carbon footprint is 13% less than that of the main analysis (where it is assumed clothing is

washed 9.9 times). The carbon reductions achieved through use phase improvement actions

are less and those of non-use phase improvement action are greater. Where it is assumed

clothing is washed 15 times per kilogram per year, the total carbon footprint is 13% greater

than that of the main analysis carbon footprint. The carbon reductions achieved through use

phase improvement actions are greater and those of non-use phase improvement action are

less.

The baseline carbon footprint total with an alternative Carbon Trust fibre mix data set for UK

clothing consumption is 12% less than the baseline total where the Biointelligence fibre mix

data is used. For the ‘What if?’ scenario, the reduction achieved where Carbon Trust fibre mix

data is used is 11% less than the reduction achieved where Biointelligence fibre mix data is

used. Although absolute reduction values change, the order of improvement actions changes

less with the new fibre mix, with the top three and bottom three improvement actions

remaining the same with both fibre data. (The Metrics group of the Sustainable Clothing Action

Plan is currently (July 2012) preparing to collate actual UK retailer data on fibre mix and sales

volumes, which could allow the footprint analysis to be updated at a later date.)

Conclusions

Overall, the total carbon footprint associated with clothing produced for, and in use in, the UK in 2009 is

estimated at approximately 38 million tonnes of CO2e (~0.6 tonnes per person per year). Because the

majority of UK clothing is manufactured outside the UK, it must be noted that ~32% occurs within the

UK and ~68% occurs overseas as a consequence of the garments manufactured for UK consumers. Per

tonne of clothing, the footprint ranges from around 15 to 46 tonnes CO2e per year, depending on the

fibre type of the garment.

To put this carbon footprint of UK clothing into context, the total direct GHG emissions in the UK in 2009

were reported as 566 million tonnes of CO2e (DECC, 2011). It should be noted that this total for the UK

does not include GHG emissions associated with imported goods or services or international travel.

Therefore, the direct carbon footprint of clothing is approximately 2% of the UK’s total direct carbon

footprint.

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Ten potential options for carbon footprint reduction are presented. According to the study, measures

aimed at reducing the impacts associated with the production of clothing (in design and eco-efficiency

measures in the supply chain and reuse), and also the use phase (less and better washing and drying by

the consumer), show the greatest potential. This is not unexpected, since these life cycle phases

currently contribute the greatest impacts.

For the reduction measures examined in the Central scenario, the combined effect of the ten measures

across the entire life cycle is estimated to be 21%. In the aspirational What If? Scenario, this is

increased to an estimated carbon reduction of 71%. However, it should be noted that the study does

not examine the practicability of implementing each option, or consider other non-carbon sustainability

impacts for these options. It should also be noted that these reductions from the baseline do not

include the potential decarbonisation of energy (electricity) production, which will also reduce the carbon

footprint of clothing in future.

The findings from the study sensitivity analysis indicate that, amongst other factors, the fibre mix of UK

clothing affects the magnitude of the footprint and the overall savings achievable, but has less influence

on the order of the reduction measures.

Overall, the analysis confirms the rationale for encouraging reduction measures at each and every stage

of the life cycle, including nudging consumer behaviour towards favourable outcomes. If UK electricity is

decarbonised, the sensitivity analysis undertaken for the study indicates sustainable production and

consumption measures aimed at reducing the production impacts of clothing will further increase in

importance over time, relative to use phase interventions. The study provides an initial analysis into the

potential indirect effects on the washing and drying footprint if the market is shifted towards one type of

fibre over another. There are uncertainties associated with the findings of this analysis, but it indicates

that fibre choice affects the magnitude of impact in the use phase.

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Contents

0.0 Executive summary ..................................................................................................................... 3 Estimated Current Carbon Footprint for UK Clothing ........................................................................... 3 Savings Achieved in the Central scenario ........................................................................................... 5 Savings Achieved in the What If? Scenario ......................................................................................... 7 Conclusions ..................................................................................................................................... 8

1.0 Introduction ................................................................................................................................. 1 1.1 About this study .................................................................................................................. 1 1.2 Goal of this Study ................................................................................................................ 1

2.0 Project Approach ......................................................................................................................... 1 2.1 Project Scope ...................................................................................................................... 1 2.2 System Boundary ................................................................................................................ 2 2.3 Functional Unit .................................................................................................................... 3 2.4 Literature Search ................................................................................................................. 5 2.5 Carbon Footprint Calculation ................................................................................................ 5 2.6 Reduction Measures ............................................................................................................ 6 2.7 Baseline and Future Scenarios .............................................................................................. 7 2.8 Further In-use Interventions ................................................................................................ 7 2.9 Sensitivity Analyses ............................................................................................................. 7 2.10 Excel Model ........................................................................................................................ 7

3.0 Life Cycle Inventory ................................................................................................................... 10 3.1 Life cycle Description ......................................................................................................... 10

3.1.1 Production of Fibre ................................................................................................ 10 3.1.2 Production of Yarn ................................................................................................ 10 3.1.3 Production of Fabric .............................................................................................. 10 3.1.4 Treatment of Fabric .............................................................................................. 11 3.1.5 Production of Garments ......................................................................................... 11 3.1.6 Distribution and Retail ........................................................................................... 11 3.1.7 Use ...................................................................................................................... 11 3.1.8 End of Life ........................................................................................................... 11

3.2 Key Data Sources .............................................................................................................. 13 3.3 Key Data – All Life cycle Stages .......................................................................................... 18 3.4 Key Data - Production of Fibre, Yarn, Fabric and Garments ................................................... 19 3.5 Key Data - Distribution and Retail ....................................................................................... 21 3.6 Key Data – Use ................................................................................................................. 22

3.6.1 Washing ............................................................................................................... 22 3.6.2 Drying ................................................................................................................. 23 3.6.3 Ironing................................................................................................................. 23

3.7 Key Data - End of Life........................................................................................................ 24 3.8 Reduction Measures .......................................................................................................... 26 3.9 Baseline and Future Scenarios ............................................................................................ 26 3.10 Data Quality ..................................................................................................................... 29

4.0 Impact Assessment ................................................................................................................... 31 4.1 Baseline Scenario .............................................................................................................. 31

4.1.1 Carbon Footprint of all Clothing in Use in the UK in 2009, whether manufactured in or

imported to the UK – UK Total ............................................................................................ 31 4.1.2 Carbon Footprint of all Clothing in Use in the UK in 2009, whether manufactured in or

Imported to the UK – per person ........................................................................................ 34 4.1.3 Carbon Footprint of all Clothing in Use in the UK in 2009, whether manufactured in or

Imported to the UK – per tonne.......................................................................................... 36 4.1.4 Carbon Footprint of all Clothing in Use in the UK in 2009, whether manufactured in or

Imported to the UK – per garment ...................................................................................... 38 4.2 Savings Achieved in the Central Scenario ............................................................................. 40 4.3 Savings Achieved in the ‘What If?’ Scenario ......................................................................... 43 4.4 Benchmarking Against Other Studies ................................................................................... 45 4.5 Further Analysis ................................................................................................................ 46

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4.5.1 Further In-use Interventions .................................................................................. 46 4.6 Sensitivity Analyses ........................................................................................................... 48

4.6.1 Decarbonisation of Grid Electricity (Sensitivity 1)...................................................... 48 4.6.2 Influence of Fibre Type on Drying (Sensitivity 2a and 2b) ......................................... 53 4.6.3 Influence of Fibre Type on Washing (Sensitivity 3) ................................................... 56 4.6.4 Longer Product Lifetimes (Sensitivity 4a and 4b) ...................................................... 58 4.6.5 Washing Frequency (Sensitivity 5) .......................................................................... 62 4.6.6 UK Fibre Mix (Sensitivity 6) .................................................................................... 62

4.7 Conclusions of Sensitivity Analyses ..................................................................................... 63 4.7.1 Decarbonisation of Grid Electricity (Sensitivity 1)...................................................... 63 4.7.2 Influence of Fibre Type on Drying (Sensitivity 2a and 2b) ......................................... 64 4.7.3 Influence of Fibre Type on Washing (Sensitivity 3) ................................................... 65 4.7.4 Longer Product Lifetimes (Sensitivity 4a and 4b) ...................................................... 65 4.7.5 Washing Frequency (Sensitivity 5) .......................................................................... 66 4.7.6 UK Fibre Mix (Sensitivity 6) .................................................................................... 66

5.0 Conclusions ................................................................................................................................ 66 5.1 Summary of this Study ...................................................................................................... 66 5.2 Summary of Baseline Results .............................................................................................. 67 5.3 Summary of Reduction Scenarios ........................................................................................ 67 5.4 Further Analysis Findings ................................................................................................... 68 5.5 Findings from Sensitivity Analyses ....................................................................................... 69 5.6 Concluding Remarks .......................................................................................................... 69 5.7 Suggested Next Steps ........................................................................................................ 70

6.0 References ................................................................................................................................. 71

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1.0 Introduction

1.1 About this study

WRAP (Waste & Resources Action Programme) works in England, Scotland, Wales and Northern Ireland

to help businesses and individuals reap the benefits of reducing waste, develop sustainable products and

use resources in an efficient way.

Environmental Resources Management Limited (ERM) was commissioned by WRAP to conduct a life

cycle carbon footprint study for UK clothing and indicate the scope for footprint reduction.

Many previous studies have assessed the carbon impacts of various clothing types and modelled

reduction initiatives. However, none has focused on measuring the carbon footprint of UK clothing as a

whole and modelled the total potential for reduction. To this end, WRAP commissioned ERM to

undertake research on the life cycle carbon impact of clothing in the UK. This study required a strategic-

level carbon footprint for UK clothing, based on published data and information. The footprint was

expressed in a number of ways to show the contribution and scope for reduction. Furthermore, a

scenario assessment was made for a number of different options for footprint reduction.

1.2 Goal of this Study

The stated objective of this research was to provide WRAP with an overview of the impacts of UK

clothing on carbon emissions through the clothing life cycle, identifying the most significant contributions

to the carbon footprint (ie the hotspots), and quantifying opportunities for savings.

The study follows on from a study undertaken for WRAP by URS on the water footprint of UK clothing

entitled ‘Review of Data on Embodied Water in Clothing and Opportunities for Savings’ (URS, 2011).

2.0 Project Approach

This section describes the scope considered in the project and summarises the approach used.

2.1 Project Scope The scope of the project was to undertake a strategic-level carbon footprint of UK clothing over the

entire life cycle using secondary data available in the literature. UK clothing has been defined in this

study as all clothing, both new and existing, in use in the UK over the period of one year. The analysis

covers both clothing manufactured and used in the UK and clothing manufactured abroad and used in

the UK. The comparatively small amount of clothing manufactured in the UK and exported abroad was

not considered in the analysis. The datum for this analysis is 2009, as the year for which the most

recent data are available.

The project assesses total quantities of all major fibre types purchased (and in use) within the UK during

2009. The fibre types assessed comprise:

acrylic;

cotton;

flax / linen;

polyamide (nylon);

polyester;

polypropylene;

silk;

viscose; and

wool.

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These are the fibres selected by the Metrics group of the Sustainable Clothing Action Plan as the most

important fibres within their sales mix. There are other fibres in use, but rather less significant in terms

of quantity sold.

The scope of the project also includes consideration of a number of example reduction measures (eg

washing at lower temperatures, increasing load size etc.), whereby potential savings in relation to the

2009 ‘baseline’ are quantified for a ‘Central’ reduction scenario and a ‘What If?’ reduction scenario.

In addition to carbon footprint results for each of these three defined scenarios, the scope includes the

provision of an Excel model for use in this project that allows the modeller to examine new scenarios,

where values for each reduction measure can be changed.

The study provides a carbon footprint assessment. Therefore, it does not consider other potential social,

economic and environmental impacts such as toxicity or labour standards.

2.2 System Boundary

The entire life cycle of UK clothing is considered. Therefore, this study can be considered a full cradle-to-

grave or business-to-consumer carbon footprint. Exclusions to the assessment have been made following

the general specifications given in PAS 2050 (1). In addition, other exclusions have been made based on

their ‘materiality’, ie any process anticipated to contribute <1% of total life cycle GHG emissions has been

excluded.

The following life cycle stages have been included in the carbon footprint assessment:

extraction of raw materials required for the production of fibres;

processing of materials (e.g. production of synthetic polymer resin);

production of fibres (either at farm or factory);

production of yarn;

production of fabric;

treatment of fabric (eg bleaching, dyeing etc.);

production of garments;

packaging of garments;

transportation of materials and goods to and from production locations;

waste at all stages of production;

transportation of garments to the UK;

storage at regional distribution centre (RDC) in the UK;

transportation from RDC to retail outlets;

storage at retail outlets in the UK;

use of clothing (eg washing (energy, water and detergent use), tumble drying, ironing); and

end of life of clothing (eg reuse, recycling, landfill and incineration)

The following life cycle stages/burdens have been excluded from the carbon footprint assessment:

transportation of consumers to and from the point of retail purchase;

packaging of packaging used at all life cycle stages;

fabric softeners, colour catches etc. or other material inputs used during washing;

water use for ironing;

preparation for reuse burdens (2); and

stain removers used during the use phase.

In addition, the following aspects have been excluded, which cover more than one life cycle stage:

capital goods (eg the manufacture of weaving looms, washing machines, irons etc.);

(1) PAS 2050:2008 - Specification for the assessment of the life cycle greenhouse gas emissions of goods and services

http://www.bsigroup.com/Standards-and-Publications/How-we-can-help-you/Professional-Standards-Service/PAS-2050

(2) Preparation for Reuse burdens results from the checking, cleaning or repairing recovery operations, by which products or components of

products that have become waste are prepared so that they can be re-used without any other pre-processing. The impacts associated with them

are typically trivial relative to those at other end of life impacts.

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human energy inputs to processing; and

animals providing transport services.

2.3 Functional Unit

In Life Cycle Assessment and carbon footprinting methods, environmental impacts are represented in

terms of a metric known as the functional unit. The functional unit allows a quantified environmental

impact to be expressed as a function of the desired purpose of the product or service and ideally allows

for a straightforward comparison between similar products or services.

The carbon footprint results of this assessment are represented in terms of the following functional unit:

The entire life cycle of all garments, both new and existing, in use in the UK in 2009.

The results provided in the study relate to the annual impacts associated with UK clothing. They include

the impacts associated with the quantity of clothes that are produced for the UK and consumed and

disposed of each year, but they also include the impacts associated with clothing that is actively worn

and cleaned each year (approximately 1.1 million tonnes of new clothing is consumed in the UK each

year, ~2.5 million tonnes is in active use - note that this is greater than the annual consumed clothing

because clothes last for more than one year).

The chosen functional unit is the total carbon footprint of clothing (both new and old) in a given year (ie

in 2009). As such, it uses the anticipated lifetime of each garment type to consider the proportion of

clothing manufactured and disposed of in 2009. Use phase impacts are for one year for all clothing in

active use (both new and old) in 2009.

The rationale behind including both new and existing clothing within the functional unit is that it follows

an inclusive approach where the annual impact of all clothing is considered. An alternative approach,

that would yield identical results (assuming sales are static), is to look at new clothing only throughout

its life cycle, whereby life cycle impacts are considered throughout all years of use (ie 2009, 2010 and a

portion of 2011). This is the approach used in a water footprinting study recently carried out by URS for

WRAP. It was decided not to use this approach as, with the ultimate aim of the SCAP in mind,

measuring total impacts of all clothing on an annual basis shows in full the opportunities for reduction

and any progress towards targets that can be fully measured year on year.

The method that was used to calculate the quantity of clothing in use in a given year (both new and old,

by using the annual quantity of clothing purchased and the anticipated lifetime of that clothing) has

three main assumptions. Firstly, it is assumed that purchasing behaviour has remained static insofar as

the quantity of clothing purchased in 2009 was the same in previous years and will be the same in future

years1. In other words, new clothing will eventually replace existing clothing on a one for one basis.

Secondly, as the quantity of clothing purchased was used to calculate the quantity of clothing in use,

there is an assumption that all clothing purchased is used, rather than being purchased and never used.

Thirdly, the ‘wardrobe stockpile’ is treated separately and is not considered within the functional unit of

this study. The ‘wardrobe stockpile’ includes clothing that is retained within the home but not in active

use (eg stored away in wardrobes, boxes, the loft, garage etc.) and therefore was thought not to

constitute clothing in use.

The rationale for including both clothing manufactured and used in the UK and clothing manufactured

abroad and used in the UK is that it places the emphasis of ‘burden ownership’ on the user; the ultimate

reason for the product. In this approach, the GHG emissions associated with clothing manufactured in

China and exported to the UK for use, for example, are covered under the UK’s clothing carbon footprint.

However, those GHG emissions associated with the comparatively small amount of clothing

manufactured in the UK and exported to Italy for use in Italy, for example, are not considered under the

UK’s clothing carbon footprint (i.e. they ‘belong’ to Italy). The chosen functional unit reflects a

consumption-based approach to GHG reporting.

1 This assumption is noted as a simplification and a limitation. It is likely that consumption has grown and may continue to grow in line with gross domestic product (GDP) or retail price index (RPI). However, it was thought that accounting for economic growth adds further complexity and is unnecessary for the purposes of this study.

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As alternative expressions of this functional unit, carbon footprint results are also presented in this study

in terms of: one tonne of garments in use in the UK in 2009; garments used by one UK resident in 2009;

and one garment used in the UK in 2009.

Carbon footprint results are broken down per life cycle stage and per fabric or garment type, and are

presented in terms of the impact of those garments manufactured in the UK, those garments imported

to the UK and a sum of the two.

2.4 Literature Search

Numerous studies have been published that examine life cycle impacts of clothing. These studies vary

widely in scope. For example, some focus on particular garment or fibre types, some are qualitative or

semi-quantitative, they may consider different impact categories, and some focus on individual life cycle

stages (e.g. the use phase, in particular) rather than the entire life cycle. Alongside the information on

the environmental impacts of clothing, much of the available research also lists potential opportunities

for reduction. Therefore, at the start of the project, it was felt that the available literature would

provide data and information sufficient for a strategic-level carbon footprint of UK clothing.

The literature search initially focused on assessing previous ERM clothing studies, publications

recommended by WRAP, studies undertaken as part of the Sustainable Clothing Roadmap programme

and references cited by each of these publications and a general literature search of government,

industry and academic publications. References are provided in Section 6 of the report.

Relevant data were extracted from the literature sources, collated and reviewed for quality. Relevant

data included:

life cycle inventory (LCI) data of input and outputs to a particular process;

individual data points, such as energy used for a particular process;

GHG emissions factors for a particular process (eg for GHG emissions associated with 1 kWh of

electricity or 1 litre of tap water);

production information, such as location of raw material and finished garments by fibre type;

consumption information, such as total quantity of each fibre and garment used in UK;

information on production processes of fibre, yarn, fabric, textiles and clothing;

consumer behaviour information, such as ironing times, washing temperatures etc.;

information on clothing attributes, such as typical mass, lifetimes etc.; and

suggested carbon footprint reduction measures for estimating potential savings in the future.

A brief search of the academic literature concerning the different physical properties of clothing fibre

was undertaken for the study. No robust data were identified from this search to establish a relative

index of water retention or other properties for fibres which might affect the size of use phase burdens.

The uncertainty associated with the relative cleaning and drying impacts of different fibre types was

subsequently examined in further analysis (Section 4.6).

2.5 Carbon Footprint Calculation

Product carbon footprinting is a technique used to assess the global warming potential of a product or

service. Carbon footprinting usually takes a systematic view of the supply chain from raw material

extraction through to the final disposal (ie cradle to grave). As with any carbon footprint assessment,

this study therefore began by defining the scope of assessment, i.e. the system boundary. The inputs

and outputs of each process within the system boundary were quantified in a process of inventory

analysis. The life cycle inventory (LCI) was built entirely from relevant data collected from the literature.

An impact assessment followed, which first assessed the inventory for greenhouse gas (GHG) emissions

and quantified these over the entire life cycle. GHGs considered include carbon dioxide, methane,

nitrous oxide, hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride. The most significant of

these in terms of global contribution to global warming are carbon dioxide (CO2), methane (CH4) and

nitrous oxide (N2O).

6

The total emissions of individual greenhouse gases were subsequently normalised to CO2 using global

warming potentials which consider the ability of each gas to absorb infra-red radiation and its lifetime in

the atmosphere over a certain period of time (usually 100 years). The resulting metric is a quantity of

carbon dioxide equivalents (CO2e). The impact method applied in this study uses the 100 year global

warming potentials from the Intergovernmental Panel on Climate Change (IPCC) in BSI (2008).

This study follows the ‘attributional’ Life Cycle Assessment (LCA) approach, whereby environmental

burdens are attributable to a life cycle as described, as opposed to the consequential approach, where

possible consequences (indirect effects) of a life cycle on the wider world are considered. One

advantage of the attributional approach is that it allows the relative contribution of each process of the

life cycle to be assessed and ‘hotspots’ to be identified. However, as with many attributional carbon

footprints, it was necessary in this study to use consequential thinking for certain aspects of the life cycle

(eg using a system expansion approach to consider avoided products as a result of reuse and recycling).

The study did not consider the indirect consequential effects of the reduction options on consumption

patterns, for example of clothing in countries to which UK second hand clothing is sent. Another

consequential effect not considered was that, for reduced clothing consumption scenarios, the effect of

purchasing less clothing may indirectly reduce the demand for land to produce natural fibre clothing,

hence reducing land use change and the implications to the carbon cycle of land use change. Wearing

more layers or different types of clothing might result in less household heating required during the

winter.

Neither did the study consider potential ‘rebound effects’. These are changes in consumption patterns

as a consequence of an action or behaviour. For example, the outcome of an initiative to reduce

clothing consumption might be a reduction in consumer spending on clothing. In theory, this could lead

to an outcome where households spend more of their disposable income on environmentally damaging

activities.

2.6 Reduction Measures

Many options for environmental impact reduction of clothing have been suggested in previous research

literature, some more effective and practicable than others. The approach taken in this study was to use

the initial results of the carbon footprint assessment to identify ‘hotspots’ in the life cycle, where carbon

impacts are largest. This hotspot analysis helped to focus attention on those areas of the life cycle

where the greatest savings could be achieved, which in turn dictated which reduction measures should

be considered.

The number of identified reduction measures was narrowed down by ERM to 17. For each of these, the

potential stakeholders involved in each reduction measure were identified and a simple communication

message underpinning each option formed. WRAP and selected stakeholders of the Sustainable Clothing

Action Plan (SCAP) were consulted and the number of reduction options considered for analysis was

subsequently reduced to 10. Hence, the final options examined are based on expert understanding of

the sector and measures currently being/likely to be considered, rather than quantitative cost benefit

analysis.

Three scenarios (or three ‘versions’ of the carbon footprint model) were developed for each reduction

measure, which are listed below and discussed in the next section:

A baseline scenario: the current (2009) situation in the UK;

A Central scenario: a realistic future situation in the UK where modest reductions have

occurred for each measure; and

A ‘What If?’ scenario; an optimistic future situation in the UK where significant reductions have

occurred for each measure.

7

2.7 Baseline and Future Scenarios

To consider the effectiveness of a reduction measure, a baseline needs to be established against which

potential savings can be reported. The baseline scenario for this assessment is the current situation in

the UK (based on 2009 data), which assumes that none of the reduction scenarios considered is in place.

This was created through the collation and review of data, and used to build up a carbon footprint model

of the entire life cycle of UK clothing (described in Section 2.4 and Section 2.5).

Two different future scenarios were created in order to assess the mid-range (Central scenario) and

upper aspirational (‘What If?’ scenario) potentials for reduction. Each reduction measure considered can

be selected individually or in combination to assess the potential savings in carbon footprint that can be

made. When a reduction measure is selected, only data associated with that measure are changed in

the model; all other data will remain fixed, as per the baseline.

The Central scenario can be considered a credible future situation in the UK where modest reductions

occur for each measure. A review of data in the literature and other sources provided insight into likely

values for reduction for each measure (eg based on commitments by manufacturers or retailers). Where

possible, the values for potential reductions were aligned to the URS water footprint report for

consistency (see Section 3.8).

The ‘What If?’ scenario can be considered to be an optimistic future situation in the UK, where significant

reductions have occurred for each measure. In the same approach as above, sources were used to

create values for an optimistic reduction for each measure. Again, the values were aligned with the URS

water footprint report where possible.

WRAP and selected industry stakeholders were consulted with regard to the magnitude of each

reduction to be represented in the modelling.

2.8 Further In-use Interventions

The SCAP ‘In-use’ group identified the use phase as an area warranting further analysis. Therefore, in

addition to the reduction measures presented in the future scenarios, a series of consumer interventions

were tested for their influence on carbon footprint results. In a similar approach taken to identifying the

overall reduction measures, ERM presented a number of in-use interventions to WRAP and selected

stakeholders from the SCAP group, who agreed on which interventions should be modelled.

2.9 Sensitivity Analyses

In product carbon footprinting, it is inevitable that surrogate data and assumptions will be required for

certain aspects of the life cycle, which will lead to uncertainty in the results. For key uncertainties,

sensitivity analyses can be performed to examine the sensitivity of results and conclusions to a change in

a particular assumption or data point. By performing sensitivity analyses, the significance of a particular

assumption or use of a particular data point can be tested. A number of sensitivity analyses were

performed in this study.

2.10 Excel Model

Figure 1 provides a summary of the main information flows in the project. The modelling began with

the development of carbon footprint models in the LCA software tool SimaPro for fibre production,

manufacturing, distribution and retail by fibre type. Results for each fibre type, by life cycle stage, were

transferred to an ERM-developed Excel model. This model enables results for each of the three defined

scenarios (ie baseline, central and ‘What If?’) to be calculated and broken down by fabric type and life

cycle stage. A set of results is presented for garments manufactured in the UK, garments manufactured

outside of the UK and a sum of the two. Each of these results can be represented in terms of each of

the functional unit and the three alternative expressions of the functional unit. These results can be

considered fixed, or static, as they reflect the three scenarios that ERM has defined.

8

Figure 4 below summarises the stages involved in this project.

Figure 4: Summary of project

As well as the fixed outputs generated by the model, its dynamic aspect allows the modeller to develop

additional reduction scenarios (see Figures 5 and 6). For each reduction measure, the modeller is able

to change parameters to observe the effect on the carbon footprint. For example, the modeller can

investigate the impact on carbon footprint of increasing the average size of washing loads by 20%,

and/or if more of the population washed at 15oC.

The results of this exercise are presented in terms of the carbon footprint of the scenario created versus

the baseline, where savings are given for each reduction measure and cumulatively for all reduction

measures selected (see Section 4.2).

Figure 5 and Figure 6 below show some screen shots of the Excel model for illustrative purposes.

9

Figure 5: Screen shot of the use phase and end of life calculator of the Excel model

Figure 6: Screen shot of the transformation section of the Excel model

10

3.0 Life Cycle Inventory

This section provides a description of the life cycle under investigation and the key data used in the

study to build up the life cycle inventory of clothing in use in the UK.

3.1 Life cycle Description

Figure 7 shows a generic process map of the life cycle of clothing both manufactured in and imported to

the UK. The process map represents all fibres of this study (ie acrylic, cotton, linen, polyamide,

polyester, polypropylene, silk, viscose and wool). Inputs and outputs are displayed for each process

relevant to this carbon footprint assessment. For each input of materials and energy to a process, there

are associated GHG emissions occurring upstream from this process. Similarly, for each waste output

from a process, there are associated GHG emissions occurring downstream from this process. Where

more than one product arises from a process (i.e. co-products such as wool and meat from livestock

rearing), GHG emissions of that process are allocated on an economic or mass basis.

3.1.1 Production of Fibre

The production of natural fibre involves various farming activities; broadly, either the cultivation of crops;

or the rearing of livestock.

Cotton and linen fibre is produced through the cultivation of crops, where fertilisers, seeds, water,

pesticides (crop protection) and fuel are among the many inputs required. Outputs include the fibre, co-

products (eg seed, oils, and straw), waste and direct GHG emissions, which are released through the

breakdown of nitrate fertilisers, combustion of fuels and breakdown of crop residues. Some further

processing is required to produce fibres from crops. For example, cotton needs to be ‘ginned’, which is a

process of separating fibre from seeds.

Wool and silk are produced from livestock, where inputs include feed and water. Outputs include the

fibre, co-products (eg meat, bone and skin), waste and direct GHG emissions from enteric fermentation,

the breakdown of manure and combustion of fuels.

The production of synthetic fibre usually involves the production of a base material, in the form of a

resin or granulates, then conversion of this base into a fibre. Polyamide, polyester, polypropylene,

acrylic and viscose are all made by a process of polymerisation, which involves inputs of chemicals,

energy and water. The resulting polymer output is processed further to produce a synthetic fibre, which

in turn requires more inputs of materials and energy and produces more waste.

3.1.2 Production of Yarn

Spinning is the approach that is generally used to manufacture yarn from both natural and synthetic

fibres. This method involves twisting fibres to create a continuous length of yarn. Before spinning can

take place, other processes are sometimes required to prepare the fibre (eg roving). Inputs to this

process comprise fibre – either virgin, waste fibre from industry or from post-consumer waste – and

energy. Outputs comprise yarn, direct GHG emissions from combustion and waste fibre/yarn.

3.1.3 Production of Fabric

Yarn is then used to produce fabric using a variety of methods, including weaving, knitting, crocheting,

braiding, lacing and felting. Again, virgin material, industrial waste or post-consumer waste can be used

as the yarn feedstock and, of course energy is required. Outputs comprise the fabric itself, direct GHG

emissions from combustion and waste fabric/yarn.

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3.1.4 Treatment of Fabric

Fabric then undergoes various treatment processes to enhance its properties, depending on its

application. These processes may include dyeing, bleaching, printing and adding substances to

preventing creasing, to reduce water retention etc. Inputs of fabric (virgin or recycled), chemicals,

water, energy and fuels are required and outputs comprise the finished fabric and waste fabric.

3.1.5 Production of Garments

Finished fabric is then used to produce garments through a process of measuring, cutting, gluing,

sewing and packaging. Other input material in the form of fibre is required for the sewing process in

addition to energy. Outputs comprise the finished and packaged garments, direct GHG emissions from

combustion and waste fabric/garments.

3.1.6 Distribution and Retail

This stage involves transportation of finished garments by road, air and sea from the manufacturer to

RDC in the UK and transportation by road from RDCs to retail outlets. Inputs of fuel and outputs of GHG

emissions from combustion are associated with the process of transportation.

This stage also involves the storage of garments in RDC and retail outlets, with associated inputs of

energy required to heat, cool and light buildings and outputs of GHG emissions from combustion.

3.1.7 Use

Activities of the use phase comprise washing, drying and ironing. Washing requires material inputs of

water, detergent and potentially fabric conditioner. Drying generally requires no inputs of materials.

Water use in ironing was not included, but is likely to be insignificant

All activities of the use phase require inputs of energy. Each of these activities is assumed to use

electricity as an energy source and therefore no direct GHG emissions are released (ie emissions from

combustion occur upstream at power stations). Although clothes are normally washed and dried as

mixed loads, each garment is actually likely to require a different quantity of electricity to be washed or

dried, depending on its weight and the composition of fibres and the physical properties of these fibres

(e.g. drying kinetics). However, there is considerable uncertainty in quantifying these differences.

Therefore, in common with previous studies, such as Biointelligence (2009), electricity used for washing,

drying and ironing was allocated to clothing on a mass basis, rather than differentiated by fibre type.

Subsequently, a sensitivity analysis was performed to consider the impact of fibre type on drying

(Section 4.6.2).

In terms of materials outputs in the use phase, only wastewater from washing processes is considered.

3.1.8 End of Life

Five potential routes are modelled for clothing considered by consumers to be at the end of its useful

life, as follows.

1. Reuse – The garment is directly reused in the UK or outside of the UK. The clothing may be

reused in the UK through family/friendship networks; internet-based exchanges; car boot

sales/jumble sales; charity shops etc, or collected through charities; bring banks; or kerbside

collection and prepared for reuse, including the segregation of clothing unfit for reuse. Where

the garment is reused, there is said to be an output of an avoided product. In other words, by

reusing the garment, the need to manufacture a new garment is displaced.

12

2. Closed loop recycling – The garment is collected from the consumer for recycling and, being

of good enough quality, fibres can be reprocessed and reused by the clothing industry to make

another garment.

3. Open loop recycling – The garment is collected from the consumer for recycling but, being of

low quality (torn, worn or stained) it is converted into wiping cloths or processed back into

fibres to be used in equally low grade products. Uses for reclaimed fibres include filling

materials for mattresses, car insulation, roofing felts or furniture padding.

4. Disposal – The garment is disposed of by the consumer as domestic ‘black bin’ waste and

either sent to landfill or incineration. Both processes can recover energy, so there is an avoided

product of grid electricity (and possibly heat) through the combustion of clothing or landfill gas.

5. Storage – The garment is no longer used by the consumer and stored (eg in the loft or

wardrobe).

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Figure 7: Generic process map for clothing (both synthetic and natural) in the UK

3.2 Key Data Sources

Key sources of data used in this project are provided in Table 3 and Table 4 below. Table 3 provides the

ultimate data source per fibre type for each production stage and Table 4 provides the data sources for

the remaining life cycle stages (which are the same regardless of fibre type). A full list of references

used in this study is provided at the end of this report.

14

Fibre Type Fibre production Yarn Production Fabric Production Wet Treatment – all fibres

treated the same

Garment Production (Making

up) – all fibres treated the

same

Acrylic

Ecoinvent, 2010 for all stages –

‘Polyacrylonitrile fibres (PAN),

from acrylonitrile and

methacrylate, prod. Mix, PAN’.

EDIPTEX, 2007 for waste and total

energy. Ecoinvent 2010 for

breakdown of energy per fuel

type. ERM assumption for

transportation of incoming

materials.

EDIPTEX, 2007 for waste;

Danish EPA, 1993 for

production energy; ERM

assumption for transportation

of incoming materials.

Kazakevičiūtė et al, 2004 for

materials, waste and




EDIPTEX, 2007 for waste; Danish

EPA, 1995 for production energy;

ERM assumption for


materials.

Cotton


‘Cotton fibres, ginned, at

farm/CN U’.

Ecoinvent, 2010 for production

energy and transportation of

incoming materials – ‘yarn

production, cotton fibres/GLO U’.

Roberts, 1980 for waste.



incoming materials – ‘weaving,

cotton fibres/GLO U’. Danish

EPA, 1993 for waste.








ERM assumption for


materials.

Linen (flax)

INRA, 2006 for all stages. LCI

data refers to flax production in

France/Belgium.



incoming materials – ‘Yarn

production, bast fibres/IN U’.


Ecoinvent, 2010 for all aspects

of production – ‘weaving, bast

fibres/IN U’. Danish EPA, 1993

for waste.








ERM assumption for


materials.

Polyamide

Australasian, 2004 for all

stages – ‘Polyamides (Nylon)

PA 6’.

EDIPTEX, 2007 for waste. ERM

M&S study for total processing





materials.













ERM assumption for


materials.

Polyester

Ecoinvent, 2010 for all stages

of resin – ‘Polyethylene

terephthalate, granulate,

amorphous, at plant’, used as a

proxy for polyester granulate.

ERM M&S study for production

of fibre.







materials.

EDIPTEX, 2007 for waste; ERM

M&S study, 2002 for











ERM assumption for


materials.

15

Polypropylene


‘Polypropylene fibres (PP),

crude oil based, production

mix, at plant’, crude oil based,

production mix, at plant’.







materials.













ERM assumption for


materials.

Silk

ERM data on input output

analysis from FAO public data

for silk fibre production.


















ERM assumption for


materials.

Viscose Ecoinvent, 2010 for all stages –

‘Viscose fibres, at plant/GLO’.

EDIPTEX, 2007 for waste and total





materials.













ERM assumption for


materials.

Wool

Biswal et al. (2010) for

Australian wool used for all

stages


















ERM assumption for


materials.

Table 3: Key data sources for all production stages, per fabric type

16

Fibre Type Packaging of

Garments

Distribution to

the UK

Storage at RDC

and Retail Outlet Washing Drying Ironing End of Life

All Fibres

ERM assumptions

based on previous

study.

ERM assumption for

departure ports;

Portworld, 2011 for

distances;

ecoinvent, 2010 for

vehicle GHG

emissions factors.

Based on previous

ERM study.

URS, 2011 for

washing frequency

and average load

per wash; ERM

previous study for

washing machine

energy.

Defra, for drying

behaviour;

manufacturer

websites for drying

energy.

Biointelligence, 2009

for ironing behaviour

and energy

consumption.

Calculations informed by

Oakdene Hollins, 2009, ERM,

2006 and WRATE, 2010 for

GHG emissions per tonne of

waste via each disposal

pathway; Defra, 2010 for fate

of waste in the UK; WRAP,

2011 Benefits of Reuse;

Oakdene Hollins/Defra, 2009

for fate of separated clothing.

Table 4: Key data sources for all other life cycle stages

17

Figure 8: Composition of each garment type based on data from Biointelligence (2009)

18

3.3 Key Data – All Life cycle Stages

Information on typical clothing attributes was necessary to model a number of life cycle stages. Of

these, clothing mass and anticipated lifetime are considered to be the key data, since these have

greatest influence on the magnitude of the final footprint. Table 5 below shows typical masses of

clothing and anticipated lifetime of clothing from URS (2011), originally from Biointelligence (2009).

Figure 8 displays a breakdown of each garment by fibre type.

Garment Type Mass (grams) Lifetime (Years)

Tops 388 2

Underwear, nightwear and hosiery 129 2

Bottoms 568 2

Jackets 821 3

Dresses 1,125 3

Suits and ensembles 921 3

Gloves 52 2

Sportswear 475 3

Swimwear 140 3

Scarves, shawls, ties etc 98 3

Table 5: Key attributes of clothing per garment type

Based on the volumes of each fabric type given in Table 6, the lifetime of each garment type and the

composition of clothing (ie proportion of each fabric type used in garments) given in Table 5, the

‘average’ weighted lifetime of clothing in the UK was calculated to be approximately 2.177 years. Data

on clothing lifetime remains consistent with the URS (2011) report. It should be noted that this lifetime

refers to the length of time clothing is in active use, rather than being retained within the home as

‘wardrobe stock’. In addition, the variability surrounding data on the lifetime of clothing is large and

therefore represents an area of uncertainty in this study.

Total quantities of new clothing in use in the UK in 2009 were extracted from the URS (2011) report on

the water footprint of UK clothing, which was given as 1,143,039 tonnes. As the defined functional unit

in this study considers all clothing in use in the UK in a year, rather than just new clothing, the quantity

provided by URS was uplifted by 2.177 years to 2,488,396 tonnes; then production impacts and end of

life impacts were allocated per annum. Note that this method is compatible with calculations made in

the URS water footprint. This information is provided in Table 6 below. (The proportion of clothing

manufactured in the UK is 10% and is taken to be the same for all fibre types.)

Fabric Type

Proportion

of Total

Consumption

Total

Quantity

(tonnes)

Total Quantity

Imported to the

UK (tonnes)

Total Quantity

Manufactured in

the UK (tonnes)

Cotton 43% 1,070,010 963,009 107,001

Wool 9% 223,956 201,560 22,396

Silk 1% 24,884 22,396 2,488

Flax / linen 2% 49,768 44,791 4,977

Viscose 9% 223,956 201,560 22,396

Polyester 16% 398,143 358,329 39,814

Acrylic 9% 223,956 201,560 22,396

Polyamide 8% 199,072 179,164 19,907

Polyurethane /

polypropylene 3% 74,652 67,187 7,465

Total 2,488,396 2,239,556 248,840

Table 6: Total quantity of clothing in use in UK in 2009

The data on fibre mix shown in Table 6 are taken from Biointelligence (2009): in the absence of a

complete and reliable UK specific dataset regarding the split of UK clothing by fibre type, EU average

19

data from the IMPRO textiles study was used. The original source of this data is the EUROPROM

database and combines information of the production, imports and exports of manufactured textile

products in Europe. (Section 4.6.6 provides a sensitivity analysis for the carbon footprint, calculated

using a different estimate of the fibre split for UK clothing. This reduced the footprint estimate, but had

little impact on the relative importance of the carbon footprint reduction measures modelled in this

study.)

3.4 Key Data - Production of Fibre, Yarn, Fabric and Garments

A large quantity of data was used to model the production of fibre, yarn, fabric and finished garments

for each fibre type. To provide all inventory data for these stages is beyond the scope of this report.

However, all data are referenced in this report. Key data are presented here as an example of the

approach.

The weighted average locations of major producers of fibre and major producers of garments (for

modelling purposes) are summarised in Table 7 (per fibre type)1. (For more information on the

detail of locations, see Appendix 1 of the URS report.) Using this information, production stages

for each fibre type were modelled separately for each geographic location where large scale production

occurs. Where country-specific inventory data were available, they were used in the carbon footprint

model.

Fibre Type

Locations of Major Producers

of Fibres

Location of Major Overseas

Producers of Garments for UK

Acrylic 60% China, 40% India2 100% China

Cotton 47% China, 33% India, 20% USA

18% Bangladesh, 48% China, 18%

India, 16% Turkey

Linen 15% Belgium, 85% France 100% China

Polyamide 60% China, 40% India 100% China

Polyester 60% China, 40% India 100% China

Polypropylene 60% China, 40% India 100% China

Silk 89% China, 11% India 50% China, 18% France, 32% Italy

Viscose

58% China, 24% Indonesia, 18%

Europe 100% China

Wool 81% Australia, 19% New Zealand 71% China, 29% Italy

Table 7: Modelling assumptions – locations of major producers of fibre and finished garments

In cases where country-specific inventory data were not available, inventory data were adjusted to

reflect the situation in the exporting country. The key adjustment made was to the fuel mix for grid

electricity. This was considered to be an important adjustment due to the relative contribution of

electricity to the carbon footprint. Table 8 gives examples of fuel mixes for grid electricity for major

producers of fibre and fabric used in the study (International Energy Agency, 2011).

1 The URS report on the water footprint of clothing provides a more detailed breakdown of locations for fibre raw materials and garment production by fibre type in Tables A1 and A2.

In the absence of robust data on locations of fibre production, data on locations of fibre exports were used as a proxy in some cases. The URS report provides more detail on data sources and identifies the fibres for which alternative data were used (as export data did not provide a reliable basis for modelling).

2 Global man-made fibre production for 2009/10. The split recognises China and Southern Asia as the majority synthetic fibre- producing regions of the world. Indian production was taken as a proxy for all Rest of World countries for the data. This is considered fair given variability in the carbon intensity of electricity production across the countries. Production country of origin data was not available for synthetic fibre types individually. (Data taken from Oerlikon (2012), The Fibre Year 2009/10, A World Survey on Textile and Non Wovens Industry, World Man Made Fibre Volumes 2009)

Alternative data were sought following a peer review of the URS water footprint study, identifying China as the leading synthetic fibre producing country (for the process steps of polymerisation and resin conversion into fibre).

20

Fuel Type

Quantity per

kWh of

electricity in

China (kWh)

Quantity per

kWh of

electricity in

India (kWh)

Quantity per

kWh of

electricity in

USA (kWh)

Quantity per

kWh of

electricity in

UK (kWh)

Hard coal 0.78979 0.67762 0.48179 0.31541

Oil 0.00676 0.02868 0.01305 0.01519

Natural gas 0.00897 0.12221 0.20572 0.44000

Wood 0.00068 0.00219 0.01134 0.02014

Waste

incineration n/a n/a 0.00501 0.00715

Nuclear 0.01976 0.02048 0.18927 0.13066

Hydropower 0.16909 0.11749 0.06389 0.02304

Geothermal n/a n/a 0.00384 n/a

Photovoltaic 0.00005 0.00003 0.00055 0.00004

Wind power 0.00378 0.01971 0.01258 0.01767

Imports 0.00112 0.01158 0.01295 0.03071

Table 8: Fuel mixes for grid electricity for major producers of fibre and fabric

Two aspects of the inventory thought to be central to this assessment are the electricity required and

the waste fibre/yarn/fabric created in the production of yarn, fabric and garments. These data are given

in Table 9 and Table 10, respectively.

Fibre Type

Electricity

required for Yarn

Production (kWh

per kg)

Electricity

required for

Fabric

Production

(kWh per kg)

Electricity

required for

Wet Treatment

(kWh per kg)

Electricity

required for

Making Up

(kWh per kg)

Acrylic 7.7 3.5 4.1 0.0806

Cotton 8.5 10.1 4.1 0.0806

Linen 2.7 0.7 4.1 0.0806

Polyamide 3.6 3.5 4.1 0.0806

Polyester1 3.6 2.9 4.1 0.0806

Polypropylene 3.6 3.5 4.1 0.0806

Silk 8.5 10.1 4.1 0.0806

Viscose 7.7 3.5 4.1 0.0806

Wool 8.5 10.1 4.1 0.0806

Table 9: Production energy required for yarn, fabric and garment manufacturing stages

1 There are two common routes to polyester manufacture: spinning; and filament, with the latter reported as representing around 65% of the market. Data are available for the filament route, but none were found for polyester spinning. Therefore, it is noted as a limitation that only one of the two major routes to polyester manufacture has been modelled in this study, although it is not thought significantly to affect the results.

21

Fibre Type

Waste created

from Yarn

Production (kg

per kg)

Waste created

from Fabric

Production (kg

per kg)

Waste created

from Wet

Treatment (kg

per kg)

Waste created

from Making Up

(kg per kg)

Acrylic 0.176 0.015 0 0.143

Cotton 0.176 0.031 0 0.143

Linen 0.176 0.015 0 0.143

Polyamide 0.176 0.015 0 0.143

Polyester 0.176 0.015 0 0.143

Polypropylene 0.176 0.015 0 0.143

Silk 0.176 0.031 0 0.143

Viscose 0.176 0.015 0 0.143

Wool 0.176 0.031 0 0.143

Table 10: Waste fibre, yarn and fabric created at yarn, fabric and garment manufacturing stages

3.5 Key Data - Distribution and Retail

Transportation routes were assumed for all stages of the life cycle, including transportation of raw

materials, fibre to yarn production, yarn to fabric production, garments to UK RDC, garments to stores

and waste to waste treatment facilities.

Table 11 below displays transportation distances used to model the distribution of finished garments to

the UK as the most environmentally significant transport stage. These were calculated based on the

assumed transportation routes for each major producer. Data on the proportion of garments imported

to the UK via sea and air were extracted from the Biointelligence (2009) report and found to be 92%

sea, 8% air. In addition, assumed transportation routes included transportation by road to and from

ports (at either end of the journey).

Country

Distance

transported by sea

(km) Distance by air (km)

Distance by road

(km) (1)

India 11,047 7,859 650

Pakistan 10,679 6,595 650

Bangladesh 13,408 8,720 300

Sri Lanka 11,882 9,472 300

Turkey 5,199 2,703 450

Western Europe 2,454 2,147 650

USA 5,408 6,453 650

Australia 20,902 18,639 650

New Zealand 20,955 19,947 650

Middle East 11,138 5,363 450

Russia 6,052 2,769 650

Eastern Europe 2,163 1,591 450

China 18,639 10,050 300

World average 9,330 7,097 485

Table 11: Distances to the UK by sea, air and road

Storage at Retail Distribution Centre (RDC) is based on ERM’s experience of carbon footprinting retail

operations. Metrics of electricity and gas use per pallet per day were applied to the assumed volume of

(1) Transport from manufacturer to exporting port and UK transport to RDC. Additionally, transport preceding these stages was also included in

the calculations.

22

clothing for an assumed duration of 30 days. A similar approach was used for storage at retail outlet,

where the assumed duration was 20 days.

3.6 Key Data – Use

3.6.1 Washing

The proportion of UK washing by hand is very small (Biointelligence, 2009). Therefore, 100% machine

washing use was assumed.

An important data point is the frequency of washes. Defra (2009) provide a value of 274 washes per

household per year, which was extracted from a report by the Market Transformation Programme

(2006). The original source of this data point is the research carried out by the Oxford Environmental

Change Institute (published in Lower Carbon Futures for European Households, 2000).

As the carbon footprint is based on the mass of UK clothing, it was necessary to normalise washing

frequency to a metric of ‘number of washes per kilogram of clothing’. This was achieved by multiplying

the number of washes per household by the number of UK households (26,300,000) and the average

washing load size (3.43 kg), which provides the mass of clothing washed in the UK1. This value was

subsequently divided by the mass of clothing in use in the UK (2.49 million tonnes), to provide a value

of 9.9 washes per kilogram of clothing per year2.

The data can be seen as a ‘top-down’ estimate of the number of times clothing is typically washed in a

UK household. This approach was seen more representative than using ‘bottom-up’ data on the number

of washes per garment, as there are uncertainties surrounding the variation in washing frequency

between individual items of clothing of the same garment type (e.g. not all shirts will be used at the

same frequency; some may be worn once a week, some may not be worn at all, or very infrequently).

Supporting the figure of 274 washes per household per year, a separate study from Danish Energy

Agency (1995) provides a value of 4.6 washes per household per week (~240 washes per household per

year).

In terms of materials consumed during use, water and detergent use during washing were considered.

For water use, data from the Biointelligence (2009) report of 46 l per wash was used. The value used

for detergent use was 78 g per wash, which is an averaged value of manufacturers’ recommended doses

from a selection of commonly used brands (see Table 12 below and

http://www.mysupermarket.co.uk/#/grocery-categories/laundry_detergent_in_tesco.html).

Price

(£)

Mass

(kg)

Number of

washes

Persil 2in1 7.15 2.03 23

Persil Biological Powder 7.15 2.125 25

Persil Biological Powder 12.00 4.25 50

Persil Biological Colour Powder 3.59 0.85 10

Persil Biological Colour Powder 7.15 2.125 25

Tesco 2in1 Biological Gel 2.19 0.63 18

Tesco 2in1 Powder 5.60 3.36 42

Tesco 2in1 Powder 4.00 2 25

Tesco Biological Powder 5.99 3.36 42

Table 12: Manufacturers’ data used to calculate detergent mass and price per wash

(1) Mass of washed clothing per year = washing frequency per household per year (274, from Defra, 2009) x number of households in the UK

(26,300,000, from Office for National Statistics, 2012) x average washing load size (3.43, Biointelligence, 2009) = 24,717,266,000 kg

(2) Washing frequency per kilogram per year = mass of clothing in use in the UK (2,488,395,661 kg) / mass of washed clothing per year

(24,717,266,00 kg) = 9.9 kg

http://www.mysupermarket.co.uk/#/grocery-categories/laundry_detergent_in_tesco.html

23

Table 13 below displays data on the energy consumption of different washing machines (per load) at

various temperatures, ranging from 15oC to 90oC. Energy consumption values for 20oC and 50oC were

interpolated from this data. This data was calculated in a study by MTP (2009). In addition, energy

consumption of the washing machine in ‘stand by’ mode was also considered, which was taken from the

same study and given as 0.019 kWh per load.

Power Consumption (kWh/load)

Washing

Temperature A++ Rated A+ Rated A Rated

90°C 1.39 1.66 1.77

60°C 0.83 1 1.06

40°C 0.5 0.6 0.64

30°C 0.312 0.379 0.401

15°C 0.0435 0.06 0.061

Table 13: Power consumption of washing machines at different temperatures per load of washing

In terms of washing behaviour, Biointelligence (2009) gave the average washing temperature for Europe

as 46oC (where 6% of households wash at 20oC; 18% wash at 30oC; 37% wash at 40oC; 9% wash at

50oC; 23% wash at 60oC; and 7% wash at 90oC). Biointelligence (2009) also give the average washing

load size as 3.4 kg.

A Defra (2009) report states that A-rated washing machines are the most widely used. Therefore, an

assumption was made that all washing machines used in 2009 were A-rated.

3.6.2 Drying

An important piece of data on drying behaviour is the proportion of the population drying clothes using a

tumble dryer. A report by Defra (2009) gave a figure for the UK of 32%. The remaining 68% is

assumed to be dried on washing lines, balconies, clothes horses, radiators etc., where no additional

energy or material inputs are assumed to be required. The same Defra (2009) report highlights the

possible negative indirect consequences of drying indoors on radiators, in that increased ventilation (eg

opening windows) to remove moisture could lead to loss of heat from the home. No consideration was

given to this aspect in this assessment, nor to additional demand on central heating systems from indoor

drying.

Other key data covered aspects such as the energy required to operate the dryer (per load), the average

size of load and the speed of spin cycle during the washing phase. The Biointelligence (2009) report

provided data for power consumption of a tumble dryer per load and the typical mass of a load, which

were given as 2 kWh and 3.4 kg respectively. The impact of speed of spin cycle is captured within both

the energy consumption of a washing machine and the energy consumption of a dryer.

3.6.3 Ironing

Table 14 below shows typical ironing times for each garment type, weighted by the mass of each

garment and the proportion of washes where the garment is ironed. The information provided in this

table was calculated using data from Biointelligence (2009). To calculate energy consumption, the

weighted ironing time was then applied to the typical power rating of an iron taken from Defra (2009),

which was given as 0.75 kW.

24

Garment Type

Ironing

Time

(hours per

garment)

Ironing Time

(hours per kg

of garment)

Proportion of

washes

where

garment is

Ironed

Weighted

Ironing Time

(hours per kg of

garment)

Tops 0.043 0.017 100% 0.017

Underwear, nightwear and hosiery 0.057 0.007 0% 0.000

Bottoms 0.072 0.041 100% 0.041

Jackets 0.040 0.032 100% 0.032

Dresses 0.075 0.084 100% 0.084

Suits and ensembles 0.050 0.046 0% 0.000

Gloves 0.000 0.000 0% 0.000

Sportswear 0.033 0.016 100% 0.016

Swimwear 0.000 0.000 0% 0.000

Scarves, shawls, ties etc 0.033 0.003 0% 0.000

Table 14: Ironing time per garment

Based on the weight of each garment type given in Table 5 and the weighted ironing time for each

garment type given in Table 14, the average weighted ironing duration of clothing in the UK was

calculated to be 0.022 hours per kg of washed clothing.

3.7 Key Data - End of Life

Table 15 below provides a breakdown of the fate of clothing waste in the UK, which was extracted from

a study carried out by ERM for WRAP entitled the ‘Benefits of reuse, case study: clothing’, and relates to

the quantities of clothes that are ultimately reused, rather than the proportion of waste clothing collected

for reuse/recycling before any rejects and the directly reused fraction which together are greater than

the percentage reuse fraction in this table.

Fate of Waste Proportion to this Route

Reuse (UK) 13.9%

Reuse (abroad) 33.7%

Recycling (closed loop) 0.0%

Recycled (open loop) 14.5%

Incineration (with energy recovery) 7.2%

Incineration (without energy

recovery) 0.0%

Landfill 30.7%

Table 15: Fate of clothing waste in the UK

For each fate, there are both positive and negative implications on the carbon footprint. GHG emissions

result from activities such as transportation, sorting, recycling, the operation of an incinerator or from

the decomposition of waste in landfill. To an extent, these impacts are offset by activities that displace

the need to produce equivalent items elsewhere in the economy. For this, a benefit is given. For

example, reusing clothing displaces the need to buy new clothing; incinerating clothing generates

electricity, which displaces the need to generate electricity from conventional means; and recycling

clothing displaces the need to produce fibres. In some cases, the benefit of the displaced product

outweighs the burdens associated with the waste management and consequently a net benefit is seen,

reported as a negative carbon footprint.

Table 16 below shows carbon footprint values associated with each of the fates of clothing waste

described in Table 15. These values were calculated using the following approach.

25

Reuse abroad – Clothing that is reused abroad is not considered to displace any UK clothing

and therefore burdens and impact for this fate are zero.

Reuse in UK – The displaced product from reuse was assumed to be a finished garment of

the same fibre type as the reused garment. GHG emissions associated with this benefit were

calculated using cradle-to-gate carbon footprints of finished garments from this study. The

calculation assumes that reused clothing displaces 60% of a new finished garment (Farrant,

2008). GHG emissions associated with the sorting of clothes for reuse were calculated using a

value from WRATE (2010) of 37.8 kWh per tonne for sorting and assumes that clothing is

transported 50 km to a regional sorting facility and sorted clothing is transported 50 km to a

RDC.

Closed Loop Recycling – The displaced product from closed loop recycling was assumed to

be fibres of the same fibre type as the recycled garment. GHG emissions associated with this

benefit were calculated using cradle-to-gate carbon footprints of fibres from this study. The

calculation assumes that clothing collected for closed loop recycling displaces 90% of new fibre

(WRATE, 2010). GHG emissions associated with the process of closed loop recycling were

calculated using values from WRATE (2010) of 37.8 kWh per tonne for sorting and 400 kWh

per tonne for recycling. Clothing was assumed to be transported 50 km to a sorting facility and

250 km to a reprocessing plant.

Open Loop Recycling – The displaced product from open loop recycling was assumed to be

a low grade product (such as a wiping cloth) made from a 50:50 mix of cotton and polyester

fibres. This assumption was based on information from studies by ERM, 2006 and Oakdene

Hollins, 2009. GHG emissions associated with this benefit were calculated using cradle-to-gate

carbon footprints of 50% cotton fibre and 50% polyester fibre from this study. The calculation

assumes that clothing collected for open loop recycling displaces 90% of low grade fibre

(WRATE, 2010). GHG emissions associated with the process of open loop recycling were

calculated using values from WRATE (2010) of 37.8 kWh per tonne for sorting and 700 kWh

per tonne for recycling. Clothing was assumed to be transported 50 km to a sorting facility and

transported 50 km to an RDC.

Incineration – Default values from WRATE (2010) were extracted for natural and synthetic

fibres.

Landfill – Default values from WRATE (2010) were used.

26

Fate of Waste

Carbon Footprint (kg

CO2e per tonne

waste) (1) References

Reuse in UK (cotton) -14,904

Informed by Farrant (2008), WRATE

(2010)

Reuse in UK (wool) -27,083

Reuse in UK (silk) -13,429

Reuse in UK (flax/Linen) -6,604

Reuse in UK (viscose) -16,447

Reuse in UK (polyester) -10,680

Reuse in UK (acrylic) -21,872

Reuse in UK (polyamide) -12,658

Reuse in UK (polyurethane) -9,674

Reuse abroad (all fibres) 0

Closed loop recycling (cotton) -1,280

Informed by Oakdene Hollins (2009),

WRATE (2010)

Closed loop recycling (wool) -18,412

Closed loop recycling (silk) -1,529

Closed loop recycling (flax/linen) -3

Closed loop recycling (viscose) -1,607

Closed loop recycling (polyester) -4,522

Closed loop recycling (acrylic) -6,520

Closed loop recycling (polyamide) -6,964

Closed loop recycling (polyurethane) -2,488

Open loop recycling (all fibres) -2,259

Informed by ERM (2006), Oakdene

Hollins (2009), WRATE (2010)

Incineration (synthetic fibres) 1006 WRATE (2010)

Incineration (natural fibres) -433 WRATE (2010)

Landfill (all fibres) 222 WRATE (2010)

Table 16: Carbon footprint associated with the treatment of clothing via various routes

3.8 Reduction Measures

Table 17 describes the reduction measures considered in the study.

3.9 Baseline and Future Scenarios

The three defined scenarios considered in this study, as previously described in this report, are a

baseline scenario, a Central scenario and a ‘What If?’ scenario. Table 17 describes the data used for

each scenario with regard to each reduction measure. Where possible, values for realistic (central) and

optimistic (‘What If?’) reductions were taken from the URS (2011) water footprint report for consistency.

References for each data source are provided in the table.

In addition to the reduction measures provided for each reduction scenario, an extra intervention was

also considered. This addressed the issue of the transportation method used to import garments to the

UK. The baseline scenario that has been used for this study assumes 92% sea freight and 8% air

freight, based on data extracted from the Biointelligence (2009). In order to calculate the reductions

achievable by reducing air transportation, two reduction measures were modelled. The Central scenario

is that the proportion of clothing transported by air is reduced by 10% (ie 92.8% sea freight and 7.2%

air freight). The ‘What If?’ scenario is that the proportion of clothing transported by air is reduced by

50% (ie 96% sea freight and 4% air freight). Results are presented separately from the other reduction

measures, as it was thought the potential to influence a reduction is lower than the other ten reduction

measures.

(1) Note that the emission factors used in the study relate are by fibre type and relate to the calculated upstream impacts for fibre type. These

are different from those in WRAP 2011 Benefits of Reuse research. The UK reuse factors include preparation for reuse burdens and displace UK

clothing.

27

Clothing

Working

Group

Principal

stakeholders Message

Reduction

Measure Baseline Scenario Central Scenario

What If? Scenario

(Optimistic) References

Design &

production

Manufacturer

/ retailer

Lean

production

Eco efficiency

across supply

chain

(production,

distribution

and retail)

Baseline comprises

production based on most

recent published

ecoinvent data and 2010

energy mix (per country)

5% reduction in GHG emissions

for all fibres and across each

stage of supply chain

30% reduction in GHG emissions

for all fibres and across supply

chain

Central scenario - trade associations,

manufacturers and retailers have

committed to various qualitative

work/objectives/eco innovation.

What If? 30% Tesco commitment to

reduce supply chain carbon footprint

by 30% by 2020

Design &

production

Manufacturer

/ retailer /

consumer

Longer

product

lifetime

Design for

Durability

[and product

lifetime

optimisation]

A weighted lifetime of

clothing in the UK is

taken as 2.2 years.

Considering both lifetime

of each garment type and

proportion of total UK

clothing each garment

represents.

10% longer lifetime of clothing,

same end of life

33% longer lifetime of clothing,

same end of life

Central: both Biointelligence, 2009,

Defra 2009. URS report

What If? from WRAP Resource

efficiency GHG. Quick win scenario for

Product lifetime optimisation

Design &

production

Manufacturer

/ retailer /

consumer

Buy

differently

Shift in

market to

higher

proportion of

synthetic

fibres

~45% of fabric used in

the UK is synthetic

Replace 10% of cotton fabric

with a 50:50 poly-cotton

blended fabric 40% of cotton replaced

Baseline from Defra 2010 report on

Emerging Fibres

Central: Biointelligence and URS

What If?: Beyond best practice WRAP

(2010) RE and GHG

In use

Consumer /

retailer

Reduce

consumer

footprint

through

behavioural

change

Clean

clothing less

100% washing machine

use (as opposed to hand

washing). Weighted

average lifetime washes

(52.7)

Washing machine use

unchanged. Lifetime washes

reduced by 10%.

Washing machine use

unchanged. Lifetime washes

reduced by 15%.

Baseline: Biointelligence, 2009.

Central: URS. What If? ERM

assumption

In use

Consumer /

retailer

Reduce

consumer

footprint

through

behavioural

change

Wash at

lower

temperature

Weighted average wash

temperature for Europe is

46oC (ie weighted

averaged behaviour for

20oC, 30oC, 40oC, 60oC,

90oC)


temperature for Europe is

39.3oC (6% at 20oC, 55% at

30oC, 9% at 40oC, 30% at 60oC)


temperature for Europe is 32.9oC

(40% at 20oC, 29% at 29oC, 12%

at 40oC, 6% at 50oC, 11% at

60oC, 2% at 90oC)

Baseline, Central and What If?:

washing temperature for Europe,

Biointelligence, 2009.

28

In use

Consumer /

retailer

Reduce

consumer

footprint

through

behavioural

change

Increase size

of washing

and drying

loads

3.4 kg for both washing

and drying

3.7 kg both wash and dry (8.8%

increase)

4 kg both wash and dry

(17.6% increase on baseline)

Baseline, Central and What If?: from

Biointelligence, 2009.

In use

Consumer /

retailer

Reduce

consumer

footprint

through

behavioural

change

Use the

tumble dryer

less

32% of clothing is dried

in a tumble dryer. The

rest being either dried on

clothes lines, balconies,

clothes horses, radiators

etc.

For six months of the year (ie

summer and spring) a 30%

reduction from baseline is

achieved by an increase in the

proportion of clothing dried on

washing lines etc. For the other

half of the year (ie autumn and

winter) there is no change from

the baseline.

For six months of the year (ie

summer and spring) a 50%

reduction from baseline is

achieved by an increase in the

proportion of clothing dried on

washing lines etc. For the other

half of the year (ie autumn and

winter) there is a 15% reduction

from the baseline achieved by an

increase in the proportion of

clothing dried on radiators etc.

Baseline: Defra, 2009. Central and

What If?: from Biointelligence, 2009.

Reuse &

recycling

Consumer /

retailer Reuse more

Dispose less -

reuse more

It has been estimated

~47.6% of clothing is

ultimately reused (13.9%

is reused in the UK).

52.6% of clothing ultimately

reused (15.4% is reused in the

UK). This is in addition to

baseline end of life for reuse

and disposal.

62.6% of clothing reused (18.3%

is reused in the UK). This is in

addition to baseline end of life for

reuse and disposal.

Baseline: WRAP 2011 Benefits of

Reuse), ERM. Central and What If?

ERM assumptions.

Reuse &

recycling/

Design &

Production

Manufacturer

/ retailer /

consumer

Recycle

more

Start closed

loop recycling

of synthetic

fibres

Currently little or no

clothing is closed loop

recycled (0% for the

baseline).

5% of all fibres are recycled

(closed loop) resulting in

reduction of production burden

(1:1 basis assumed). This is in

addition to baseline end of life

for reuse and disposal.

10% of all fibres are recycled

(closed loop) resulting in

reduction of production burden.

This is in addition to baseline end

of life for reuse and disposal.

Baseline: WRAP, ERM. Central and

What If? ERM assumptions.

Reuse &

recycling

Consumer /

retailer

Recycle

more

Dispose less -

recycle more

(open loop)

~14.5% of clothing is

recycled (open loop).

19.5% of all clothing recycled

(open loop). This is in addition

to baseline end of life for reuse

and disposal.

24.5% of all fibres are recycled

(open loop). This is in addition

to baseline end of life for reuse

and disposal.

Baseline: WRAP, ERM. Central and

What If? ERM assumptions.

Table 17: Defined scenarios for each reduction measure (included in this study)

29

3.10 Data Quality

All assessments of this type will have data quality issues and it is important that these are communicated.

Due to the strategic-level nature of this study, a formal data quality review as required by ISO 14044 (1)

or PAS 2050 is out of the scope. However, ISO 14044 or PAS 2050 have been used to help to define the

data quality criteria that consideration should be given to, which are:

reliability;

precision;

completeness;

temporal specificity;

geographical specificity; and

technological specificity.

Each data set (rather than individual data points) has been assessed against these data quality criteria

and ranked according to a simple traffic light system (eg red = poor quality; amber = moderate quality;

and green = good quality). The criteria assessment is based on the lowest quality data point within the

data set. The resulting matrix below (Table 18) provides a quick guide to the likely uncertainty which

may be associated with the data set.

Life Cycle

Stage

Reliability Precision Completeness Temporal

Correlation

Geographical

Correlation

Technological

Correlation

Fibre

production

Yarn

production

Fabric

production

Fabric

treatment

Garment

production

Packaging

Distribution

to the UK

Storage at

RDC

Storage at

retail outlet

Washing

Drying

Ironing

End of life

Table 18: Data quality assessment matrix

Data highlighted as having poor data quality are as follows.

Natural fibres - Where secondary data for production of a natural fibre were not specific to

the country modelled. Agricultural inputs were not changed due to the limited scope of this

study. It is likely that agricultural inputs and outputs will vary between countries and therefore

it is seen as a limitation that the model does not consider these.

(1) ISO14040 series of life cycle assessment standard. Reference ISO 14044:2006 Environmental management -- Life cycle assessment --

Requirements and guidelines. http://www.iso.org

30

Production of silk fibre - The inventory was created using economic input output data (I/O),

which have a large inherent uncertainty due to their generic nature.

Production of polyamide fibre – Secondary data used for the production of polyamide fibre

were taken from the Australasian database, which contains data from as early as 1993.

Despite the age of these data, it was felt to be the most appropriate available, as its format

allowed grid electricity mixes to be altered to be specific to the country of fibre production.

Lifetime of clothing – The best data available were used to model the lifetime of clothing.

However, the variability between the lifetimes of individuals’ clothing is large and therefore it

may be difficult to capture this in an ‘average’ value.

Washing frequency - The data used for the number of times clothing is washed per year are

uncertain. There is variability in washing frequency between households, different garment

types and even within the same garment group (ie occasional wear versus every day wear).

Therefore, it is very difficult to represent the typical washing frequency of all clothing in the

UK.

Ironing – As with clothing lifetime data, data on the proportion of clothing ironed are highly

variable. It is noted that, despite the best data available being used, this is a potential data

limitation. However, ironing does not contribute to a significant proportion of life cycle GHG

emissions (see results section).

Transportation of finished garments to the UK – Assumptions on the transportation

routes were made to build a model of the distribution of clothing to (and within) the UK. There

is inherent uncertainty within these assumptions that can only be reduced with detailed

modelling of transport routes into the UK.

A hotspot analysis of results was carried out to identify those life cycle stages that make the greatest

contribution to the total carbon footprint. Washing, drying and fabric production were identified as

major hotspots. For each of these life cycle stages, ‘good’ or ‘moderate’ quality data were used.

Therefore, despite the use of ‘poor’ quality data for certain aspects of the life cycle, the overall quality of

data can be considered to be reasonable, and at an appropriate level for the aims of this study.

31

4.0 Impact Assessment

This section provides description and interpretation of the main results of this study. A separate Excel

model is also provided alongside this report, which contains all the results of this study.

Note: values for the use-phase impacts are presented for all clothing in use in the UK in 2009, not just for

new clothing in use bought in 2009. If values for the use phase impacts of only new clothes in use are

required, then the use phase impact values presented in this section should be divided by the factor

2.177.

4.1 Baseline Scenario

4.1.1 Carbon Footprint of all Clothing in Use in the UK in 2009, whether manufactured in or imported to the UK – UK Total

Table 19 below displays the baseline carbon footprint results of all clothing in use in the UK in 2009,

whether manufactured in or imported to the UK. Results are presented as a total for the UK and broken

down by both life cycle stage and fibre type. This is shown graphically in Figure 9.

The contribution of each life cycle stage and fibre type to the total baseline carbon footprint is shown in

Figure 10.

32

Fibre Type

Carbon Footprint (tCO2e)

Fibre

production

Yarn

production

Fabric

production

Garment

production Distribution Retail

Use -

washing

Use -

drying

Use -

ironing End of life TOTAL

Cotton 862,591 3,933,342 6,738,624 328,311 756,870 227,091 2,479,140 1,638,070 104,532 -1,161,070 15,907,502

Wool 2,138,740 885,909 1,472,743 67,392 155,982 47,531 518,890 342,852 21,879 -417,159 5,234,758

Silk 23,211 79,600 139,099 7,510 15,480 5,281 57,654 38,095 2,431 -24,658 343,704

Flax / linen 5,253 76,659 131,673 14,673 39,079 10,562 115,309 76,189 4,862 -27,628 446,632

Viscose 217,837 1,907,296 534,496 66,029 175,854 47,531 518,890 342,852 21,879 -254,415 3,578,248

Polyester 979,687 493,853 1,496,878 117,384 312,630 84,499 922,471 609,514 38,896 -305,691 4,750,120

Acrylic 779,454 1,902,845 901,967 66,029 175,854 47,531 518,890 342,852 21,879 -331,992 4,425,307

Polyamide 737,950 246,673 801,748 58,692 156,315 42,250 461,235 304,757 19,448 -177,984 2,651,085

Polyurethane /

polypropylene 106,194 92,597 300,656 22,010 58,618 15,844 172,963 114,284 7,293 -52,521 837,937

TOTAL 5,850,917 9,618,774 12,517,884 748,029 1,846,682 528,120 5,765,441 3,809,464 243,098 -2,753,116 38,175,293

Table 19: Carbon footprint all clothing in use in the UK in 2009, whether manufactured in or imported to the UK, represented as a total for the UK, broken down per fibre type

Figure 9: Carbon footprint all clothing in use in the UK in 2009, whether manufactured in or imported to the UK, represented as a total for the UK, broken down per fibre type

33

Figure 10: Contribution to the total carbon footprint of each life cycle stage and fibre type

34

From Table 19, Figure 9 and Figure 10, the following points are evident.


2009 (ie the volume consumed, and the actively worn quantity) is approximately 38 million



the UK’s direct carbon footprint) and ~68% occurs abroad. Based on this estimate, the direct

impact of clothing in the UK can be estimated to be ~12 million tonnes of CO2e.

To put the direct carbon footprint of UK clothing into context, the total direct GHG emissions in

the UK in 2009 were reported to be 566 million tonnes of CO2e (DECC, 2011). It should be

noted that this total for the UK does not include GHG emissions associated with imported

goods or services, or international travel. Therefore, the direct carbon footprint contributes





The dominant life cycle stage is fabric production (comprising weaving/knitting etc. and


The second most dominant life cycle stage is use, representing 26% of total life cycle GHG

impacts. Of the activities in the use phase, washing represents is the largest contributor

(15%), followed by drying (10%) and ironing (1%).

Of all life cycle stages, garment production, distribution and retail contribute the least to the

total carbon footprint: contributing 2%; 5%; and 1%, respectively.

Of all the fibre types, the contribution of cotton to the total carbon footprint is the largest

(42%), primarily due to the large proportion of cotton used in the UK (43%). It is worth

noting that this baseline calculation does not take into account potential differences in laundry

impacts between fibre types, which is examined further in Section 4.6.

4.1.2 Carbon Footprint of all Clothing in Use in the UK in 2009, whether Manufactured in or Imported to the UK – per person


whether manufactured in or imported to the UK. Results are represented as per person figures (UK

population of 62.262 million) and broken down by both life cycle stage and fibre type. This is shown

graphically in Figure 11.

From Table 20 and Figure 11, the following points are evident.

The per person per annum carbon footprint of all garments, both new and existing, in use in

the UK in 2009 is around 0.6 tonnes of CO2e.

The general comments made on Table 19, Figure 9 and Figure 10 also apply to these results.

35

Fibre Type

Carbon Footprint (kgCO2e) per person

Fibre

production

Yarn

production

Fabric

production

Garment


Use -

washing

Use -

drying

Use -

ironing

End of

life TOTAL

Cotton 13.9 63.2 108.2 5.3 12.2 3.6 39.8 26.3 1.7 -18.6 255.5

Wool 34.4 14.2 23.7 1.1 2.5 0.8 8.3 5.5 0.4 -6.7 84.1

Silk 0.4 1.3 2.2 0.1 0.2 0.1 0.9 0.6 0.0 -0.4 5.5

Flax / linen 0.1 1.2 2.1 0.2 0.6 0.2 1.9 1.2 0.1 -0.4 7.2

Viscose 3.5 30.6 8.6 1.1 2.8 0.8 8.3 5.5 0.4 -4.1 57.5

Polyester 15.7 7.9 24.0 1.9 5.0 1.4 14.8 9.8 0.6 -4.9 76.3

Acrylic 12.5 30.6 14.5 1.1 2.8 0.8 8.3 5.5 0.4 -5.3 71.1

Polyamide 11.9 4.0 12.9 0.9 2.5 0.7 7.4 4.9 0.3 -2.9 42.6

Polyurethane /

polypropylene 1.7 1.5 4.8 0.4 0.9 0.3 2.8 1.8 0.1 -0.8 13.5

TOTAL 94.0 154.5 201.1 12.0 29.7 8.5 92.6 61.2 3.9 -44.2 613.1

Table 20: Carbon footprint all clothing in use in the UK in 2009, whether manufactured in or imported to the UK, represented per person, broken down per fibre type

Figure 11: Carbon footprint all clothing in use in the UK in 2009, whether manufactured in or imported to the UK, represented per person, broken down per fibre type

36

4.1.3 Carbon Footprint of all Clothing in Use in the UK in 2009, whether Manufactured in or Imported to the UK – per tonne


whether manufactured in or imported to the UK. Note: use phase impacts relate to all clothing in use for

one year’s use. Results are represented as per tonne and broken down by both life cycle stage and fibre

type. The data do not differentiate the ‘in-use’ carbon footprint by fibre type – which may under-

estimate the carbon footprint of water-retaining fibres, notably cotton. The baseline analysis does not

examine the effect of uncertainties which are considered in further analysis (Section 4.6). These results

are shown graphically in Figure 12.


The total carbon footprint of a tonne of clothing in 2009 ranges from around 15 to 46 tonnes

CO2e, depending on the fibre type of the garment.

The life cycle stages garment production, distribution, retail and use have the same associated

GHG impact for each fibre type (see also research suggestions in Section 5.7 and sensitivity

analyses of Section 4.6.2 and 4.6.3).

Wool displays the largest carbon footprint of all the fibre types (around 46 tonnes of CO2e per

tonne across the entire life cycle), with fibre production contributing most to the carbon

footprint (45% of total life cycle impacts). This is explained by the large impact of agriculture

inputs and outputs associated with livestock (eg methane emissions from manure

management, nitrous oxide emissions from fertilisers etc.). It is acknowledged that the

assumption that all clothing is washed and dried at the same frequency and temperature

regardless of fibre type is uncertain. It is possible that some fibre types, for example wool,

may be washed less frequently and at lower temperatures than others and may not be tumble-

dried. However, data on washing behaviour by fibre type is lacking and it cannot be assumed

that washing and drying recommendations of clothing manufacturers will be followed.

Flax/Linen displays the smallest carbon footprint of all the fibre types (around 15 tonnes of

CO2e). The main reason for this is the relatively small carbon footprint allocated in the

production of fibre (335 kg CO2e per tonne), which can be explained by the fact that linen is a

low value co-product from the production of a higher-value product, linseed oil.

37

Fibre Type

Carbon Footprint (kgCO2e) per tonne of fibre

Fibre

production

Yarn

production

Fabric

production

Garment


Use -

washing

Use -

drying

Use -

ironing

End of

life TOTAL

Cotton 1,755 7,961 13,710 668 1,540 462 2,317 1,531 98 -2,362 27,679

Wool 20,790 8,654 14,316 655 1,516 462 2,317 1,531 98 -4,055 46,284

Silk 2,031 6,964 12,169 657 1,354 462 2,317 1,531 98 -2,157 25,425

Flax / linen 335 3,353 5,760 642 1,709 462 2,317 1,531 98 -1,209 14,999

Viscose 2,118 18,540 5,196 642 1,709 462 2,317 1,531 98 -2,473 30,139

Polyester 5,357 2,700 8,185 642 1,709 462 2,317 1,531 98 -1,671 21,329

Acrylic 7,577 18,551 8,768 642 1,709 462 2,317 1,531 98 -3,227 38,427

Polyamide 8,070 2,700 8,768 642 1,709 462 2,317 1,531 98 -1,946 24,351

Polyurethane /

polypropylene 3,097 2,700 8,768 642 1,709 462 2,317 1,531 98 -1,532 19,792

Table 21: Carbon footprint all clothing in use in the UK in 2009, whether manufactured in or imported to the UK, represented per tonne, broken down per fibre type

Figure 12: Carbon footprint all clothing in use in the UK in 2009, whether manufactured in or imported to the UK, represented per tonne, broken down per fibre type

38

4.1.4 Carbon Footprint of all Clothing in Use in the UK in 2009, whether Manufactured in or Imported to the UK – per garment


whether manufactured in or imported to the UK. Results are represented as per garment and broken

down by life cycle stage. These results are shown graphically in Figure 13.




The garment types displaying the largest carbon footprint are suits and ensembles (17 kg

CO2e), dresses (15 kg CO2e) and jackets (13 kg CO2e), which can be explained by their

relatively large mass.

Those garments displaying the smallest carbon footprint are gloves (1 kg CO2e), scarves,

shawls, ties etc. (2 kg CO2e) and swimwear (2 kg CO2e), which can be explained by their

relatively small mass.

39

Garment Type

Carbon Footprint (kgCO2e) per garment

Fibre

production

Yarn

production

Fabric

production

Garment


Use -

washing

Use -

drying

Use -

ironing

End of

life TOTAL

Tops 1.1 1.8 2.1 0.1 0.2 0.2 0.9 0.6 0.0 -0.5 6.5

Underwear, nightwear and hosiery 0.3 0.4 0.7 0.0 0.1 0.1 0.3 0.2 0.0 -0.1 1.9

Bottoms 1.1 2.4 2.8 0.2 0.2 0.3 1.3 0.9 0.1 -0.6 8.7

Jackets 3.7 2.5 3.9 0.2 0.3 0.5 1.9 1.3 0.1 -1.0 13.3

Dresses 2.2 3.7 4.0 0.3 0.5 0.6 2.6 1.7 0.1 -1.0 14.8

Suits and ensembles 5.4 3.2 4.7 0.3 0.4 0.5 2.1 1.4 0.1 -1.3 16.8

Gloves 0.3 0.3 0.3 0.0 0.0 0.0 0.1 0.1 0.0 -0.1 1.1

Sportswear 1.3 0.8 1.9 0.1 0.2 0.3 1.1 0.7 0.0 -0.4 6.1

Swimwear 0.4 0.2 0.6 0.0 0.1 0.1 0.3 0.2 0.0 -0.1 1.8

Scarves, shawls, ties etc. 0.5 0.3 0.5 0.0 0.0 0.1 0.2 0.2 0.0 -0.1 1.8

Table 25: Carbon footprint all clothing in use in the UK in 2009, whether manufactured in or imported to the UK, represented per garment, broken down per garment type

Figure 13: Carbon footprint all clothing in use in the UK in 2009, whether manufactured in or imported to the UK, represented per garment, broken down per garment type

40

4.2 Savings Achieved in the Central Scenario

Table 23 and Figure 14 below display the carbon saving from the baseline generated by each reduction

measure of the Central scenario. The baseline is the total carbon footprint of all garments, both new

and existing, in use in the UK in 2009 (ie the volume consumed, and the actively worn quantity), given

in tonnes of CO2e. The figure in the next column is the reduction in total carbon footprint of all

garments after the reduction measure is put in place.

Reduction measure

Baseline

(t CO2e)

Reduction



(production, distribution and retail) -

Central scenario - 5% reduction for all

fibres across supply chain 38,175,293

1,563,219 -4.1%


optimisation) - Central scenario - 10%

longer lifetime of clothing 38,175,293 2,941,203 -7.7%


synthetic fibres - Central scenario -

replace 10% of cotton with 50:50 poly-

cotton. [Data exclude in-use savings] 38,175,293 164,150 -0.4%

Clean clothing less - Central scenario -

washes per year reduced by 10% 38,175,293 989,905 -2.6%

Wash at lower temperature - Central

scenario - weighted average wash

temperature of 39.3C 38,175,293 549,604 -1.4%

Increase size of washing and drying loads

- Central scenario - load increases to

3.7kg 38,175,293 531,538 -1.4%

Use the tumble dryer less - Central

scenario - 30% reduction in tumble dryer

use in summer 38,175,293 430,367 -1.1%

Dispose less - reuse more - Central

scenario – 15.4% of clothing ultimately

reused in the UK 38,175,293 272,063 -0.7%


fibres - Central scenario - 5% of all

clothing is recycled (closed loop) 38,175,293 352,144 -0.9%


Central scenario - 38% of all clothing is

recycled open loop 38,175,293 195,729 -0.5%

Cumulative reduction

7,989,921 -20.9%

Table 23: Savings achieved by each reduction measure of the Central scenario

41

Figure 14: Savings achieved by each reduction measure of the Central scenario

From the estimates presented in Table 23 and Figure 14, the following points are evident.

A potential 21% reduction in the carbon footprint of UK clothing would occur if all reduction

measures considered for the Central scenario were achieved.

The largest carbon footprint reductions are achieved by extending product lifetime (8%), eco-

efficiency across the supply chain (4% reduction) and washing clothing less (3% reduction).

As calculated, reduction measures resulting in minimal reductions in carbon footprint include

increasing open loop recycling, increasing reuse and a shift in the market to a larger proportion

of synthetic fibres.

An eco-efficiency measure across the supply chain (production, distribution and retail) of 5%

for all fibres results in reduction in the total carbon footprint of 4.1%.

Increasing the lifetime of clothing by 10% results reduction in carbon footprint of 7.7%.

However, as an indirect negative consequence of this measure, it is possible that a longer

lifetime might result in poorer quality clothing at the end of life. As a consequence, there

would be less benefit for reuse items, although this was not examined in the study. This

potential indirect effect is more relevant to a situation where clothing lifetime has increased

through a behavioural change rather than a technological one.

A shift to synthetic fibres by replacing 10% of cotton with 50:50 poly-cotton only results in a

very small reduction in carbon footprint (0.4%). The savings are a result of the lower

embodied carbon value associated with polyester production in comparison to cotton.

However, the difference between these two values is small. It is possible that more significant

savings may result from this shift to synthetics, due to their relative physical properties

resulting in less energy required for washing, drying and ironing. This thesis is tested in a

sensitivity analysis in Section 4.6 of this report.

A 10% reduction in the number of washes per year results in significant carbon footprint

savings (2.6%). This is a consequence of the use phase representing such a large proportion

of total life cycle emissions and the fact that both drying and ironing are reduced by 10% when

the number of washes is reduced.

A reduction of average washing temperature from 46oC to 39.3oC results in a carbon footprint

reduction of 1.4%. This is an example of where a reduction in input results in a significant

reduction in overall carbon footprint, due to the significance of the life cycle stage.

42

An increase in washing and drying load sizes from 3.4 kg to 3.7 kg results in a carbon footprint

reduction of 1.4%.

A reduction in machine drying by 30% in the summer results in a modest reduction in carbon

footprint of 1.1%. Although machine drying is very energy-intensive and represents a

significant proportion of total life cycle impact, machine dryer use in the UK is already quite low

(around 32%) and therefore a 30% reduction in use does not translate into a large absolute

reduction in use. In terms of indirect effects of this measure, there may be a positive knock-on

effect of increasing the clothing lifetime through less shrinkage or other damage to clothing

whilst machine drying.

An increase in the final reuse of clothing in the UK from 13.9% to 15.4% results in a modest

carbon footprint reduction of 0.7%. It is noted here that the proportion of UK clothing reused

in the UK is around one third, which explains the relatively small saving achieved by increases

reuse as only the UK reused fraction is given a displacement benefit in this study. On a ‘per

tonne of clothing’ basis reuse results in significant carbon reduction and is generally favoured

as a waste management option from a carbon footprint perspective1.

An increase in closed loop recycling from 0% to 5% results in a carbon footprint reduction of

0.9%.

As with closed loop recycling, increasing open loop recycling from 14.5% to 19.5% does not

result in significant savings in carbon footprint.

It should also be noted that the number of decimal places of results displayed in Table 26 and

Table 27 does not represent the level of precision, rather these are illustrative, to allow for

distinction between reduction measures.

The above reduction measures can be grouped into potential savings from consumer actions,

potential savings as a result of business actions or combination of the two. The total potential

reduction in the carbon footprint of UK clothing is broken down into these three groups:

Potential savings as a result of consumer actions – 8.7%

Potential savings as a result of business actions – 4.1%

Potential savings as a result of both consumer and business actions – 8.1%

In addition, further savings can be achieved from encouraging the use of a particular fibre type

due to the differentiation in use phase impacts between fibre type (see sensitivity analyses in

Section 4.6.2 and Section 4.6.3).

Due to the potential for large savings to be achieved through consumer actions at the use

phase, the significance of in-use interventions has been tested further in this study (see

Section 4.5).

In addition, through reducing the proportion of clothing that is imported to the UK by air by 10% (ie to

7.2%), the total carbon footprint of UK clothing is reduced by 0.2%, or 90,770 t CO2e.

(1) Note that the benefits given to ‘recycling’ collection in some carbon reporting metrics (eg Defra/Decc GHG Protocol and the Scottish Carbon

Metric) are dominated by the proportion of clothes collected for ‘recycling’ which are subsequently separated for reuse. To the greatest extent

the benefit given is dependent on the proportion that is reused, and in this study in particular, the proportion that is reused in the UK. To a

lesser extent, the benefit given for recycling is associated with that remainder which is materials recycled or recovered.

43

4.3 Savings Achieved in the ‘What If?’ Scenario

Table 24 and Figure 15 below display the carbon saving from the baseline generated by each reduction

measure of the ‘What If?’ scenario. The baseline is the total carbon footprint of all garments, both new

and existing, in use in the UK in 2009 (ie the volume consumed, and also the quantity actively worn),

given in tonnes of CO2e.

Reduction measure

Baseline

(t CO2e)

Reduction



(production, distribution and retail) - 'What

If?' - 30% reduction for all fibres across

supply chain 38,175,293 9,338,795 -24.5%


optimisation) - 'What If?' - 33% longer

lifetime of clothing 38,175,293 10,432,516 -27.3%


synthetic fibres - 'What If?' - replace 40%

of cotton with 50:50 poly-cotton [Data

exclude in-use savings] 38,175,293 632,288 -1.7%

Clean clothing less - 'What If?' - washes per

year reduced by 15% 38,175,293 1,480,805 -3.9%

Wash at lower temperature - 'What If?' -

weighted average wash temperature of

32.9C 38,175,293 1,032,401 -2.7%

Increase size of washing and drying loads -

'What If?' - load increases to 4kg 38,175,293 1,030,254 -2.7%

Use the tumble dryer less - 'What If?' -

50% reduction in tumble dryer use in

summer, 15% reduction in winter 38,175,293 1,072,163 -2.8%

Dispose less - reuse more - 'What If?' –

18.3% of clothing reused in the UK 38,175,293 799,980 -2.1%


fibres - 'What If?' - 10% of all clothing is

recycled (closed loop) 38,175,293 696,184 -1.8%


'What If?' - 43% of all clothing is recycled

open loop 38,175,293 383,353 -1.0%

Cumulative reduction 26,898,739 -70.5%

Table 24: Savings achieved by each reduction measure of the ‘What If?’ scenario

44

Figure 15: Savings achieved by each reduction measure of the ‘What If?’ scenario

From the estimates presented Table 24 and Figure 15, the following points are evident.

A 71% reduction in the carbon footprint of UK clothing will occur if all reduction measures

considered by the ‘What If?’ scenario are achieved.

The largest carbon footprint reductions are achieved by extending product lifetime (27%

reduction), eco-efficiencies across the supply chain (24% reduction) and washing less (4%

reduction).

Reduction measures resulting in the smallest reductions in carbon footprint include increasing

closed loop recycling, increasing open loop recycling and a shift to a higher proportion of

synthetics.

An eco-efficiency measure across the supply chain (production, distribution and retail) of 30%

for all fibres results in a reduction in carbon footprint of 24.5%.

Increasing the lifetime of clothing by 33% results in a large reduction in carbon footprint of

27.3%.

A shift to synthetics by replacing 40% of cotton with 50:50 poly-cotton only results in a very

small reduction in carbon footprint (1.7%). However, this result excludes savings during the

in-use stage.

A 15% reduction in the number of washes per year results in significant carbon footprint

savings (3.9%).

A reduction of average washing temperature from 46oC to 32.9oC results in a carbon footprint

reduction of 2.7%.

An increase in washing and drying load sizes from 3.4kg to 4kg results in a carbon footprint

reduction of 2.7%.

A reduction in machine drying by 50% in the summer and 15% in the winter results in a

reduction in carbon footprint of 2.8%.

An increase in the direct reuse of clothing from 13.9% to 18.3% results in a modest carbon

footprint reduction of 2.1%. It is noted here that the proportion of UK clothing reused in the

45

UK is around one third, which explains the relatively small saving achieved by increases reuse

as only the UK reused fraction is given a displacement benefit in this study. On a ‘per tonne of

clothing’ basis reuse results in significant carbon reduction and is generally favoured as a waste

management option from a carbon footprint perspective1.

An increase in closed loop recycling from 0% to 10% results in a carbon footprint reduction of

1.8%.

As with closed loop recycling, increasing open loop recycling from 14.5% to 24.5% does not

result in significant savings in the carbon footprint.

The above reduction measures can be grouped into potential savings from consumer actions,

potential savings as a result of business actions or combination of the two. The total potential

reduction in the carbon footprint of UK clothing is broken down into these three groups:

Potential savings as a result of consumer actions – 17.0%

Potential savings as a result of business actions – 24.5%

Potential savings as a result of both consumer and business actions – 29.0%

In addition, further savings can be achieved from encouraging the use of a particular fibre type

due to the differentiation in use phase impacts between fibre type (see sensitivity analyses in

Section 4.6.2 and Section 4.6.3).

Due to the potential for large savings to be achieved through consumer actions at the use

phase, the significance of in-use interventions has been tested further in this study (see

Section 4.5).

In addition, through reducing the proportion of clothing that is imported to the UK by air by 50% (ie to

4%), the total carbon footprint of UK clothing is reduced by 1.2%, or 453,850 t CO2e.

4.4 Benchmarking Against Other Studies

The results generated in this study were compared to a selection of published reports, in order to sense-

check the results. It should be noted here that often a direct comparison with other studies is difficult as

there may be differences in the scope; in particular the chosen functional unit.

A study from the Carbon Trust (2011) gives a value of the production of new clothing at around 150 kg

CO2e per person footprint, albeit the study has a different functional unit. To allow a fair comparison,

we must adjust this value to reflect both new and existing clothing over the entire life cycle. In order to

do this, we can assume production represents 75% of life cycle impacts and new clothing only

represents 45% of total clothing in use (based on a lifetime of 2.2 years). The resulting carbon footprint

for all clothing over the entire life cycle is 435 kg CO2e per person, which is closer to the results of this

study (613 kg CO2e per person).

All studies considered highlight the use phase as being dominant. Although the use phase contributes a

large proportion (~25%) of the GHG impact of clothing in this study, it is a considerably lower proportion

than suggested in other studies. A study by Business for Social Responsibility (2009) suggests that, in

most studies, the use phase accounts for 40-80% of life cycle GHG impacts. For example, a study by

the University of Cambridge (2006) calculates that the use phase of T-shirts represents 60% of energy

impacts. It is thought that washing frequency is a major contributor to these differences. In the studies

with which this assessment has been compared, the washing frequency data come from

product/garment level studies and assume that new clothing is bought and used. However, in this

study, an average cleaning frequency was calculated top down, based on average washing loads and

load size (see Section 3.6.1). The resultant wash frequency is less than predecessor studies and

(1) Note that the displacement benefit given for closed loop and open loop recycling in this study refers to materials that are recycled. The

benefits given to ‘recycling’ in some carbon reporting metrics (eg Defra/Decc GHG Protocol and the Scottish Carbon Metric) are dominated by the

proportion of clothes collected for ‘recycling’ which are subsequently separated for reuse. To a lesser extent, the benefit given for recycling is

associated with that remainder which is materials recycled or recovered.

46

suggests a significant proportion of all new clothing (perhaps half) is bought and then not used, or is

infrequently used.

In terms of impact per tonne of finished garment per fibre type, the Biointelligence (2009) report

provides values of 22.5 and 27.2 kg CO2e per kg for the production of cotton and polyester garments,

respectively (up to the garment manufacturer gate). The values given in this study for cotton and

polyester garments are 27.7 and 21.3 kg CO2e per kg, respectively. For polyester fibre, a study carried

out by Shen et al. (2010) of Utrecht University provides a value of 4.1 kg CO2e per kg, which is in line

with the value from this study of 5.3 kg CO2e per kg.

4.5 Further Analysis

4.5.1 Further In-use Interventions

The SCAP ‘In-use’ group identified the use phase as an area warranting further analysis, given its

contribution to the carbon footprint. Therefore, in addition to the reduction measures presented in the

scenarios above, a series of consumer interventions were tested for their influence on carbon footprint

results. To this end, the impact of 10 in-use interventions was tested through a behavioural change shift

in 10% of the population for each reduction measure (ie 10% of the UK population adopt each

measure). These measures are described in Table 25.

The purpose of this analysis is to compare the effectiveness of a variety of measures to change

consumer behaviour during the use phase of clothing after the clothing was purchased.

Reduction Measure Reduction Scenario

Increase size of washing and

drying loads 10% shift in population from 3.4kg loads to 4kg loads

Clean clothing less 10% shift from weighted average of 21.6 to 18.4 lifetime

washes (ie 15% reduction)

Use the tumble dryer less 10% shift in population from 32% dryer use (year round) to

16% in the summer and 27% in the winter.

Wash at 30oC (effect of a wash at

a lower temperature campaign)

10% shift in population from average wash temperature of 46oC

to 32.9oC, where no bio fouling prevention is undertaken

Wash at 30oC and periodic bio-

fouling service wash (variant of

above)


to always washing at 32.9oC, bio fouling ‘service’ wash (90oC)

every six weeks

Wash at 30oC and periodic bio-

fouling service wash and de-

scaling/detergent removal (variant

of above)


to always washing at 32.9oC with monthly bio fouling ‘service’

wash (90oC with integrated lime scale and detergent remover

and additional machine efficiency benefit of this)

Enhanced energy efficiency of

washing - improved appliance

rating of washing machines OR

achieved by more use of existing

economy wash setting for washing

machine

10% shift in population from A rated to A+ rated washing

machines OR a 10% in consumer behaviour to use economy

setting resulting in equivalent carbon saving

Increased spin drying of washing

machine

10% shift in population from spin cycle of 1000rpm to 1600rpm

with positive consequences for drying1

Reduced detergent use

10% shift in population to reduce detergent use by 10%

1 Increasing the speed of spin drying of washing machines reduces the moisture content of clothing and therefore reduces energy consumption of dryers. A study by Defra (2009) entitled ‘Reducing the environmental impact of clothing’, states that an increase in washing machine spin drying speed from 1000 rpm to 1600 rpm can reduce drying energy by 13%.

47

Better washing and drying

behaviour results increase in

lifetime of clothing

10% of the population adopt better washing and drying

behaviour, which increases the in use life of their clothing by 1

year. Behavioural changes comprise washing at lower

temperature, washing clothing less, using the tumble dryer less

and performing ‘service washes’ to reduce bio fouling.

Table 25: In-use interventions considered in this study

Bio-Fouling

The prevention of bio-fouling (the build-up of unsightly and odorous residues and mould in washing

machines) may have benefits in terms of appliance longevity and efficiency. Washing machine

manufacturers generally recommend that high temperature, no load ‘service’ washes should be run

periodically to minimise bio-fouling, blockages etc. In these service washes, consumers may also include

limescale/detergent removal tablets to help to prevent the build-up of limescale in hard water areas

and/or to remove detergent. In addition to the benefits achieved from the prevention of bio-fouling,

there are also associated burdens, principally resulting from the energy used in the service wash.

Data from a 2009 WRAP report carried out by ERM entitled ‘Environmental Life Cycle Assessment (LCA)

Study of Replacement and Refurbishment options for domestic washing machines’ suggests that 77% of

the energy consumption of a washing machine is associated with heating and that, over time, limescale

build up can reduce heating element efficiency by 10% (i.e. a 7.7% overall reduction in efficiency is a

result of limescale build up). However, the washing temperature modelled in the 2009 WRAP study was

higher than the average washing temperature of this study, and therefore savings were scaled down to

an illustrative 4%. No data were found on the reduction of efficiency associated with the build-up of

detergent and mould within the machine, and therefore an illustrative 1% was assumed as the

reduction in efficiency caused by this build up.

In this assessment, it was assumed that a service wash is undertaken at a recommended high

temperature (90oC) every six weeks. This was modelled using data on the power consumption of an A

rated washing machine, given in Table 13. The embodied carbon of limescale remover was assumed to

be equal to that of washing powder; 50g was assumed to be added to every service wash.

Table 26 below displays the carbon saving generated by a 10% shift in population towards each in-use

intervention.

48

In-use intervention

% Reduction in total

carbon footprint Rank

10% shift in the washing and drying behaviour of population, increase the

length of time clothing is use for by 1 year. Behavioural changes comprise

washing at lower temperature, washing clothing less, using the tumble

dryer less and performing ‘refresh washes’. -5.44% 1

10% shift from weighted average of 21.6 to 18.4 lifetime washes (ie 15%

reduction) -0.41% 2

10% shift in population from 32% dryer use (year round) to 16% in the

summer and 27% in the winter. -0.30% 3

10% shift in population from 3.4kg loads to 4kg loads -0.29% 4

10% shift in population from average wash temperature of 46oC to 32.9oC,

where no bio fouling prevention is undertaken -0.18% 5

10% shift in population from spin cycle of 1000rpm to 1600rpm with

positive consequences for drying -0.15% 6

10% shift in population from average wash temperature of 46oC to always

washing at 32.9oC, with monthly bio fouling ‘service’ wash (90 oC) -0.15% 7

10% shift in population from average wash temperature of 46oC to always

washing at 32.9oC with monthly bio fouling ‘service’ wash (90oC with

integrated lime scale and detergent remover and additional machine

efficiency benefit of this) -0.14% 8

10% shift in population to reduction in detergent that results in 10%

reduction in impact -0.07% 9

10% shift in population from A rated to A+ rated washing machines OR a

10% in consumer behaviour to use economy setting resulting in equivalent

carbon saving -0.07% 10

Table 26: Savings achieved by each in-use intervention

From the results presented in Table 26, the following points are evident.

The most significant in-use intervention is a behavioural shift resulting in an increase in

clothing lifetime by one year (reduction in overall carbon footprint of 5.4%). This behaviour

shift reduces both in-use and production impacts of clothing.

Cleaning clothing less, increasing the size of washing loads and reducing tumble dryer use

result in combined carbon footprint savings of greater than 1%. Other interventions have a

less significant impact.

4.6 Sensitivity Analyses

In this study, a number of uncertainties were identified that warranted further investigation through

sensitivity analyses. Sensitivity analysis is a technique to explore the sensitivity of results and

conclusions to a change in a particular assumption or data point.

The sensitivities examined are: the influence of the likely decarbonisation of grid electricity; the influence

of fibre type on washing and drying; the influence of product lifetime; the influence of washing

frequency; and the influence of UK fibre mix.

4.6.1 Decarbonisation of Grid Electricity (Sensitivity 1)

49

The Government has committed to reducing emissions of UK greenhouse gases by at least 80% by 2050

and 34% by 2020, on 1990 levels. In the latest Carbon Plan1 it sets out plans for achieving the target.

A fourth carbon budget is established in the plan, which covers the period 2023–2027, and requires

overall emissions to be cut by 50% on 1990 levels.

The contribution that the UK energy sector can make to these targets is fundamentally dependent on

two factors: future energy demand (economic growth/energy efficiency); and how clean is the future

electricity supplied (either through change in technology/grid efficiency or through carbon

mitigation/capture technologies).

The Carbon Plan gives an Emissions Performance Standard for new electricity production of 450 gCO2

per kWh in 2013, but does not set targets for each energy generation technology or a future

decarbonisation target for the energy sector overall. Hence, the sensitivity examined in this study uses

the Climate Change Committee (2008) recommendation that the overall carbon intensity of UK grid

needs to be reduced to 70 gCO2 per kWh in 2030. Figure 16 shows the potential pathway to achieving

this proposed reduction, which was extracted from chapter 5 of a 2008 report by the Climate Change

Committee entitled Building a low carbon economy.

Figure 16: Potential pathway to decarbonisation of grid electricity in the UK

The purpose of this sensitivity analysis is to assess the sensitivity of results and conclusions to the

anticipated decarbonisation of grid electricity. In particular, does the priority of reduction measures

change when considered in the context of a future UK with decarbonised electricity? Electricity is used

in many stages over the life cycle of clothing (some within the UK and some outside the UK). However,

in terms of contribution to the overall carbon footprint, the electricity used in the use phase is the most

important. Therefore, this sensitivity analysis only considers the change in UK grid electricity emissions

for the use phase.

In this study, the carbon intensity of 2009 UK grid electricity is taken from ecoinvent and calculated to

be 610 gCO2e per kWh. For this sensitivity analysis, the carbon intensity of UK grid electricity used in

the use phase of clothing was reduced to 70 g CO2 per kWh (ie recommended 2030 levels). Table 27

presents the main results of this study recalculated using this reduced emission factor for grid electricity.

Use Phase Grid Use Phase Grid % Difference

1 The Carbon Plan (2011) is accessible at http://www.decc.gov.uk/en/content/cms/tackling/carbon_plan/carbon_plan.aspx

http://www.decc.gov.uk/en/content/cms/tackling/carbon_plan/carbon_plan.aspx

50

Electricity

Emissions Factor

610 g CO2e per

kWh

Electricity

Emissions Factor

70 g CO2e per

kWh

Fibre production 5,850,917 5,850,917 0%

Yarn production 9,618,774 9,618,774 0%

Fabric production 12,517,884 12,517,884 0%

Garment production 748,029 748,029 0%

Distribution 1,846,682 1,846,682 0%

Retail 528,120 528,120 0%

Use - washing 5,765,441 2,731,655 -52.6%

Use - drying 3,809,464 437,600 -88.5%

Use - ironing 243,098 27,925 -88.5%

End of life -2,753,116 -2,753,116 0%

TOTAL 38,175,293 31,554,469 -17.3%

Table 27: Sensitivity analysis to access the effect of a decarbonised grid on use phase impacts

From the results of the sensitivity analysis presented Table 27, the following points are evident.

With the reduced carbon intensity of grid electricity applied to the use phase, the total carbon

footprint for UK clothing is reduced by 17%. The value is comparable in scale to the majority

of potential reductions across the supply chain estimated for the Central scenario;

The largest contributor in percentage terms is the reduction in drying impacts (reduced by

88.5%);

The reduction in carbon footprint of washing is only 52.6%, due to the influence of washing

detergent, which is not affected by the decarbonisation of UK grid electricity in the sensitivity

analysis. However, the reduction in terms of tonnes CO2e is roughly equivalent to that

achieved in the drying phase (Figure 17);

The significance of the use phase decreases relative to upstream life cycle stages (ie such as

manufacture) and also at end of life. It should be noted here that only use phase grid

electricity decarbonisation was modelled in this sensitivity. However, as the majority of

clothing is manufactured outside of the UK, it is anticipated that modelling decarbonisation in

all life cycles stages would not alter this conclusion significantly;

With electricity being entirely responsible for the carbon footprint for drying and ironing, a

reduction in the carbon intensity of electricity results in a direct reduction in carbon footprint.

Sensitivity analysis 1 indicates that the relative importance of non-use life cycle stages is increased

when electricity is decarbonised. Therefore, when considering reduction initiatives, some non-use phase

measures increase in importance when grid electricity is decarbonised. As it is likely that UK grid

electricity will be decarbonised in the future, both use phase and non-use phase reduction measures

should be considered. This is considered further in Table 28, which displays the difference in ranking of

carbon reduction measures where UK grid electricity is decarbonised.

51

Use Phase Grid Electricity Emissions Factor 610 g CO2e per kWh

Use Phase Grid Electricity Emissions Factor 70 g CO2e per kWh

Total

Baseline

Carbon

Footprint

(t CO2e)

Total

Reduced

Carbon

Footprint

(t CO2e)

Cumulative

Reduction

(t CO2e)

Reduction

due to

measure

from

baseline

(%)

Cumulative

Reduction

(%)

Rank

Total

Baseline

Carbon

Footprint

(t CO2e)

Total

Reduced

Carbon

Footprint

(t CO2e)

Cumulative

Reduction

(t CO2e)

Reduction

due to

measure

from

baseline

(%)

Cumulative

Reduction

(%)

Rank

Eco-efficiency across

supply chain (production,

distribution and retail) -

Central scenario - 5%

reduction for all fibres

across supply chain 38,175,293 36,612,074

1,563,219 -4.1% -4.1% 2 31,554,469 29,991,250

1,563,219 -5.0% -5.0% 2

Design for Durability (and

Product lifetime

optimisation) - Central

scenario - 10% longer

lifetime of clothing 38,175,293 33,670,871

4,504,422 -7.7% -11.8% 1 31,554,469 27,116,255

4,438,214 -9.1% -14.1% 1

Shift in market to higher

proportion of synthetic

fibres - Central scenario -

replace 10% of cotton

with 50:50 poly-cotton 38,175,293 33,506,721

4,668,572 -0.4% -12.2% 10 31,554,469 26,952,105

4,602,364 -0.5% -14.6% 9

Clean clothing less -

Central scenario - washes

per year reduced by 10% 38,175,293 32,516,816

5,658,477 -2.6% -14.8% 3 31,554,469 26,624,283

4,930,186 -1.0% -15.6% 4

Wash at lower

temperature - Central

scenario - weighted

average wash temperature

of 39.3C 38,175,293 31,967,212

6,208,081 -1.4% -16.3% 4 31,554,469 26,359,617

5,194,852 -0.8% -16.5% 6

Increase size of washing

and drying loads - Central

scenario - load increases

to 3.7kg 38,175,293 31,435,674

6,739,619 -1.4% -17.7% 5 31,554,469 26,140,377

5,414,092 -0.7% -17.2% 7

52

Use the tumble dryer less

- Central scenario - 30%

reduction in tumble dryer

use in summer 38,175,293 31,005,308

7,169,985 -1.1% -18.8% 6 31,554,469 26,083,767

5,470,702 -0.2% -17.3% 10

Dispose less - reuse more

- Central scenario – 15.4%

of clothing ultimately

reused in UK 38,175,293 30,733,245

7,442,048 -0.7% -19.5% 8 31,554,469 25,811,704

5,742,765 -0.9% -18.2% 5

Start closed loop recycling

of synthetic fibres -

Central scenario - 5% of

all clothing is recycled

(closed loop) 38,175,293 30,381,101

7,794,192 -0.9% -20.4% 7 31,554,469 25,459,560

6,094,909 -1.1% -19.3% 3

Dispose less - recycle

more (open loop) - Central

scenario - 38% of all

clothing is recycled open

loop 38,175,293 30,185,372

7,989,921 -0.5% -20.9% 9 31,554,469 25,263,832

6,290,638 -0.6% -19.9% 8

Table 28: Sensitivity analysis to access the impact on the central reduction scenario of grid decarbonisation

53

From the results of the sensitivity analysis presented in Table 28, the following points are evident.

The reduction achieved through the following measures is increased by the shift to a

decarbonised grid: eco-efficiency across the supply chain; open and closed recycling; reuse

more; shift towards synthetic fibres; and design for durability.

The reduction achieved through the following measures in decreased by the shift to a

decarbonised grid: cleaning clothing less; using the tumble dryer less; increased load sizes; and

lower washing temperature.

Therefore, in a decarbonised UK, non-use phase reduction measures become more important

relative to use phase reduction measures.

4.6.2 Influence of Fibre Type on Drying (Sensitivity 2a and 2b)

Consistent with the findings of previous environmental analyses of clothing, machine tumble drying has

been identified in this study as a significant aspect of the life cycle with respect to the carbon footprint

of clothing. Drying is also one stage of the life cycle with scope for potential intervention/innovation, ie

technological innovation (either in tumble drier functionality, or indirectly through alternative fibres with

faster-drying properties), or through consumer behavioural change (ie better separation, or selective

drying and use).

Also consistent with the previous research, the carbon footprint model of this study allocates the burden

associated with using a tumble dryer to clothing on a mass basis, regardless of the type of fibre of

which the clothing is made. For example, a kilogram of cotton shirts is ascribed the same GHG

emissions for drying as a kilogram of polyester shirts. The rationale behind this allocation choice is that

there is considerable uncertainty in the data available with regard to fibre type and drying properties.

In particular, the influence of the combined physical properties of different fibres when dried in mixed

loads is uncertain. A second argument for the mass allocation is that clothes are dried as mixed fibre

loads.

However, this mass allocation choice carries a level of uncertainty with evidence in the public domain

that different fibre types possess significantly different drying properties. Therefore, the sensitivity of

results to this allocation choice was tested through two sensitivity analyses:

Sensitivity 2a - An index of relative drying rates was created for each fibre type, which was in

turn used to allocate the impacts of drying to clothing of each fibre type, based on how quickly

each fibre type dries. In this model, there is an assumption that either clothing will be

separated by the consumer according to fibre type, or that dryers have appropriate technology

/ sensors such that drying time will reflect the fibre types being dried. Where different fibre

types are present in the dryer, it will be assumed in this analysis that they have no influence on

each other’s’ drying rate. The resulting total carbon footprints are compared with those where

a mass-based allocation was used to determine the influence on results.

Sensitivity 2b - Using the index of relative drying rates for each fibre type, further data were

collected and used to examine the influence fibres have on each other’s drying rate. Resulting

carbon footprints were compared with those of the current model.

For sensitivity 2a, two approaches were considered for the construction of a relative index of drying

times. The first was to gather data on the physical properties of fibre types in relation to the diffusion

of water through clothing. Some outputs of this research are summarised below:

A publication by Manich et al. (2005) describes that the key parameters determining drying

kinetics are the amount of moisture retained on the outside of the fibres and the diffusion of

moisture within the fibres.

The rate of drying from the surface of clothing is dependant largely on the temperature,

humidity and mass of the air in the dryer doing the drying, but not fibre type. Therefore, there

is effectively no difference in drying rate at the surface between fibre types.

54

Conversely, the process of diffusion of water within fibres is strongly determined by fibre type

and it is this parameter that affects the relative drying times of different fibre types most

significantly.

Of the fibres tested by Manich et al., polypropylene had the lowest water retention (4.1%) and

quickest drying rate (7.5% per minute), viscose had the highest water retention (83.3%) and

modal had the slowest drying rate (3.2% per minute) (cotton or wool were not assessed).

There are many other studies concerning the drying kinetics of one fibre type or comparing

two fibre types, but Manich et al. was the most comprehensive study identified. However,

Manich et al. did not access all fibre types required for this study.

A second approach to constructing a relative index of drying times was to gather data on the energy

requirements of a tumble dryer for different fibre types. It was thought that this approach was more

representative than considering the physical properties of fibre types and was therefore used in this

sensitivity analysis. Product guides for tumble dryers were reviewed for information on drying times

based on fibre type. As an example, a product guide for a Hotpoint tumble dryer is summarised in

Table 29 below.

Fibre type

Drying

Time

(mins) Temperature

Cottons 130 High heat

Synthetics 80 Low heat

Table 29: Drying time of different fibre types

Based on the information on relative drying times provided in user manuals, an assumption was made

for this sensitivity analysis that all synthetic fibres should be given a relative value of 0.5 and all natural

fibres should be given a relative value of 1 (as per Table 30 below). In this sense, if separated, clothing

made of nature fibres is assumed to use twice the energy to dry in comparison to clothing made of

synthetic fibres. These relative values were applied to drying energy data for the first drying sensitivity

analysis (ie where clothing is separated for drying). It is recognised that there are uncertainties with

using this approach and further testing of tumble dryers by manufacturers is required to fill the gap in

available research.

Fate of Waste Relative Index of Drying Time

Cotton 1

Wool 1

Silk 1

Flax / linen 1

Viscose 0.5

Polyester 0.5

Acrylic 0.5

Polyamide 0.5

Polyurethane /

polypropylene 0.5

Weighted average 0.78

Table 30: Relative index of drying time of different fibre types

For sensitivity analysis 2b (ie where mixed loads are dried together), all clothing was assumed to dry at

the same rate as natural fibres. Manich et al. (2005) suggest that some fibre will have more influence

on drying rates than others and that the relative quantity of fibres type in a load is also an important

factor. The influence different fibre types have on each other is a complex issue but becomes a less

important consideration if clothing is not typically removed from the dryer as it dries – in which case the

rate of drying of mixed loads is largely determined by the slowest drying fibre type.

55

A final consideration is that for some fibre types it is not recommended that they are tumble dried at all.

The Fabric Care Research Association Handbook (1988) suggests that wool should not be tumble dried

as it is prone to shrinkage, silk should not be tumble dried as it is too fragile and linen should not be

tumble dried as it creases very easily. Whilst it may be the case that some consumers follow washing

instructions, it is not known what proportion of the population do this. In addition, some delicate fibre

types have been improved by manufacturers, so it is less easy for consumers to damage them by drying

(eg easy care wool) and it is not known what proportion of these types of clothing are being tumble

dried. Therefore, for these sensitivity analyses, results are presented where considering both inclusion

and exclusion of delicates (wool, silk and linen) to the tumble dryer.

Table 31 presents results of sensitivity analysis 2a and Table 32 presents results of sensitivity analysis

2b. The proportion of the population that excluded delicates (ie wool, silk, flax) from tumble dryer loads

is not known; the results of the sensitivity analysis are presented both where delicates are tumble dried

and where they are excluded.

Fibre Type

Total Carbon Footprint (t CO2e)

All fibres use

the same

energy to dry

(baseline)

Drying energy

based on

relative drying

rate of fibres,

clothing

separated,

delicates dried

in tumble dryer

% Difference

from

baseline

Drying energy

based on

relative drying

rate of fibres,

clothing

separated,

delicates not

dried in

tumble dryer

% Difference from

baseline

Cotton 15,907,502 16,383,070 3% 16,383,070 3%

Wool 5,234,758 5,334,296 2% 4,891,906 -7%

Silk 343,704 354,763 3% 305,609 -12%

Flax / linen 446,632 468,752 5% 370,443 -21%

Viscose 3,578,248 3,456,591 -4% 3,456,591 -4%

Polyester 4,750,120 4,533,840 -5% 4,533,840 -5%

Acrylic 4,425,307 4,303,650 -3% 4,303,650 -3%

Polyamide 2,651,085 2,542,945 -4% 2,542,945 -4%

Polyurethane /

Polypropylene 837,937 797,385 -5% 797,385 -5%

TOTAL 38,175,293 38,175,293 0% 37,585,440 -2%

Table 31: Sensitivity analysis to assess the influence on relative drying times of fabric types on results

(where clothing is separated)


Where drying energy is allocated according to the relative drying time of fibre types, the

carbon footprint increases from the baseline for natural fibres and decreases for synthetic

fibres. This can be explained by the hydrophobic nature of synthetic fibres causing them to

hold less water and therefore to dry more quickly (using less energy) than natural fibres.

Clearly, when the assumption is made that delicates are not dried in the tumble dryer, there is

a large reduction in carbon footprint relative to the baseline for fibre types considered delicates

(ie wool, silk and linen).

The overall carbon footprint of UK clothing remains the same, whether allocation of dryer

energy is carried out according to mass or relative drying time of fibre type.

56

Where delicates are not tumble dried, a small reduction of the overall carbon footprint of UK

clothing is observed, which is due to the removal of drying burden for three fibre types.

Fibre Type

Total Carbon Footprint (t CO2e)

All fibres use

the same

energy to dry

(baseline)

Drying energy

based on

relative drying

rate of fibres,

clothing mixed,

delicates dried

in tumble dryer % Difference

Drying energy

based on

relative drying

rate of fibres,

clothing

mixed,

delicates not

dried in

tumble dryer % Difference

Cotton 15,907,502 16,383,070 3% 16,383,070 3%

Wool 5,234,758 5,334,185 2% 4,891,906 -7%

Silk 343,704 354,751 3% 305,609 -12%

Flax / linen 446,632 468,727 5% 370,443 -21%

Viscose 3,578,248 3,677,675 3% 3,677,675 3%

Polyester 4,750,120 4,926,879 4% 4,926,879 4%

Acrylic 4,425,307 4,524,735 2% 4,524,735 2%

Polyamide 2,651,085 2,739,464 3% 2,739,464 3%

Polyurethane /

Polypropylene 837,937 871,079 4% 871,079 4%

TOTAL 38,175,293 39,280,566 3% 38,690,861 1%

Table 32: Sensitivity analysis to assess the influence on relative drying times of fabric types on results

(where clothing is mixed)



natural fibres), the carbon footprint for each fibre type increases from the baseline.

Where it is assumed that delicates are not tumble dried, there is a large reduction in carbon

footprint relative to the baseline for fibre types considered delicates.

The overall carbon footprint of UK clothing is increased from the baseline by virtue of the

increase in mixed load tumble drying.

The increase in the carbon footprint of UK clothing is less apparent where delicates are not

tumble dried, due to the reduction in impact for these fibre types.

4.6.3 Influence of Fibre Type on Washing (Sensitivity 3)

In addition to examining the effect of fibre type on drying, the SCAP in-use group is interested in the

effect of fibre type on washing. Physically, there are differences in the fibre properties (eg water and

detergent retention) that mean there may also be a rationale for differentiation in the allocation of

washing impacts in mixed loads, but this is even less certain than for drying. However, for some types

of clothing, such as white cotton, it is certainly traditional to wash these separately from other clothes at

a higher temperature.

57

In the current version of the carbon footprint model, data on washing method (eg temperature of wash)

does not consider any differences between fibre types, which can be seen as a limitation. Therefore,

this sensitivity analysis assesses how significant differentiation in washing method between fibre type

affects results, using the shift of market from cotton to poly-cotton as an example. It is anticipated that

the reduction achieved from a shift to poly-cotton will be greater when clothing is considered to be

separated for washing. This is because, in addition to lower manufacturing impacts associated with

poly-cotton in comparison to cotton, the washing energy required for synthetics is also likely to be

lower.

In a report in 2006 by the University of Cambridge entitled ‘Well Dressed?’, a typical washing

temperature for a cotton t-shirt in the UK was given as 60oC, whereas the typical washing temperature

for a viscose blouse was given as 40oC. In addition, the report also assumed the cotton t-shirt would be

machine dried and ironed whereas neither of these activities were considered necessary for the viscose

blouse. Based on information from the ‘Well Dressed?’ report, the sensitivity analysis considered in this

report assumes the temperature of a cotton only wash to be 60oC and that of a poly-cotton only wash to

be 45oC (ie the average European temperature of 46oC used in the current model for all clothing).

The following scenarios are considered for this sensitivity analysis.

Central scenario – a shift in market where 10% of cotton is replaced with 50:50 poly-cotton

mix, where clothing is not separated for washing and washed at an average temperature of

46oC.

Central scenario sensitivity - a shift in market where 10% of cotton is replaced with 50:50 poly-

cotton mix, where clothing is separated for washing and washed at a temperature appropriate

for that fibre type (ie 60oC for cotton and 46oC for poly-cotton).

‘What If?’ scenario – a shift in market where 40% of cotton is replaced with 50:50 poly-cotton

mix, where clothing is not separated for washing and washed at an average temperature of

46oC.

‘What If?’ scenario sensitivity - a shift in market where 40% of cotton is replaced with 50:50

poly-cotton mix, where clothing is separated for washing and washed at a temperature

appropriate for that fibre type (ie 60oC for cotton and 46oC for poly-cotton).

Table 33 below displays the reduction from baseline achieved by a shift in the market towards

synthetics where, firstly, clothing is not separated for washing and washed at an average temperature

of 46oC and, secondly, where clothing is separated for washing and washed at a temperature

appropriate for that fibre type. The shift towards synthetics is illustrated with two scenarios: the Central

scenario of replacing 10% of cotton with 50:50 poly-cotton; and the ‘What If?’ scenario of replacing

40% of cotton with 50:50 poly-cotton.

58

Reduction measure

Reduction % – where

clothing is not separated for

washing and washed at an

average temperature of 46oC

Reduction % – where

clothing is separated for

washing and washed at a

temperature appropriate for

that fibre type

Central scenario - replace 10% of

cotton with 50:50 poly-cotton -0.4% -0.7%

‘What If?’ scenario - replace 40% of

cotton with 50:50 poly-cotton -1.7% -2.8%

Table 33: Sensitivity analysis to assess to test the influence of fibre type on washing impacts


The reduction achieved from the shift towards synthetics in both the central and ‘What If?’

scenarios is over a third larger when the difference in washing temperature is also considered.

If the difference in washing temperature at which different fibre types are washed was considered in this

study, the carbon footprint results represented per fibre type and per garment type would be different.

However, the total carbon footprint results for UK clothing as a whole would remain the same, as the

weighted average temperature used considers all washing behaviour (including separating clothing

based on fibre type to wash at a higher or lower temperature).

4.6.4 Longer Product Lifetimes (Sensitivity 4a and 4b)

Of the reduction measures modelled in central and ‘What If?’ scenarios, one identified as warranting

further sensitivity analysis is the measure to extend the lifetime of clothing. This measure could be

brought about by a technological change (ie improving the durability of clothing through redesign)

and/or (solely) through behavioural change (ie consumers choosing to use their clothing for longer).

With the former approach, there may be an increased burden associated with manufacturing that is

necessary to bring about the extension in lifetime (eg heavier material, coating, dye etc).

Therefore, the sensitivity of the results to the requirement of an increase in manufacturing burdens to

extend the lifetime of clothing warranted testing through a sensitivity analysis. This sensitivity

compares the benefits of extending clothing lifetime where extra manufacturing is required with the

benefits of extending clothing lifetime where no extra manufacturing is required (ie current approach).

The following scenarios are considered:

Central scenario – a 10% longer lifetime of all clothing, where no increase in manufacturing

burdens is necessary;

Central scenario sensitivity - a 10% longer lifetime of all clothing, brought about by a 10%

increase in manufacturing burdens;

‘What If?’ scenario - a 33% longer lifetime of all clothing, where no increase in manufacture

burdens is necessary; and

‘What If?’ scenario sensitivity - a 33% longer lifetime of all clothing, brought about by a 10%

increase in manufacturing burdens.

In addition, there is also considerable uncertainty over the lifetime of clothing, which warrants further

investigation through a sensitivity analysis. In the current carbon footprint model, an ‘average’ weighted

lifetime of clothing in the UK of 2.177 years was used, which was based on data from the URS (2011)

report. However, it is well known that the variability between the lifetimes of individuals’ clothing is

large and therefore it may be difficult to capture this in an ‘average’ value. For example, an unpublished

Defra report undertaken by ERM presents results of a survey asking participants for how long they would

normally expect to use certain products. For jumpers, answers from one year to 17 years were given,

with the median result being two years.

59

The sensitivity of results to the choice of using 2.177 years as the weighted average lifetime of clothing

was considered in this sensitivity analysis. This was achieved by comparing the results where a

weighted average of 2.177 years was used to results where other data on clothing lifetime is used in its

place. Table 34 below provides the data on garment lifetime used to base weighted average lifetimes of

clothing in this sensitivity analysis.

Garment Type

Lifetime (Years)

URS (2011)

Defra / ERM

(2011)

Biointelligence

(2009)

Tops 2 1.5 3

Underwear, nightwear and hosiery 2 No data 2

Bottoms 2 2 2

Jackets 3 2 3

Dresses 3 No data No data

Suits and ensembles 3 3 No data

Gloves 2 No data 2

Sportswear 3 No data No data

Swimwear 3 No data No data

Scarves, shawls, ties etc 3 No data No data

Weighted average lifetime (years) 2.177 1.770 2.493

Table 34: Data on clothing lifetimes used in sensitivity analysis

The lifetime of clothing can be extended through either consumers retaining clothing for longer or

manufacturers increasing durability. In the latter scenario, it could be argued that an extra

manufacturing burden is required to allow clothing to be made more durable. However, in the current

carbon footprint model, it was assumed that no extra manufacturing burden would be required to extend

product lifetime. This sensitivity analysis tests the impact of this assumption.

Table 35 displays results of this sensitivity analysis; comparing the reduction from baseline achieved by

extending the lifetime of clothing where a 10% extra manufacturing burden is required in comparison to

where extra manufacturing burden is not required.

Reduction measure

Reduction % – excluding

extra manufacturing burden

Reduction % – including

extra manufacturing burden

Central scenario – a 10% longer

lifetime of all clothing -7.7% -1.0%

‘What If?’ scenario - a 33% longer

lifetime of all clothing -27.3% -22.4%

Table 35: Sensitivity analysis to access the impact of considering extra manufacturing burden required to

extend the lifetime of clothing


For both the central and ‘What if?’ scenarios, the reduction achieved from extending the

lifetime of clothing is less when a 10% extra manufacturing burden is required to achieve this

extension.

The decrease in reduction achieved is greater for the Central scenario than for the ‘What If?’

scenario. This is due to the fact the increase in manufacturing impact remains the same for

each scenario but the savings from extended lifetime are far greater for the ‘What If?’ scenario.

In addition to assessing the sensitivity to results of considering extra manufacturing in extending the

lifetime of clothing, another sensitivity analysis related to product lifetimes was carried out. This

considers the choice of using 2.177 years as the weighted average lifetime of clothing. Data from two

other sources was used to calculate two alternative weighted average lifetimes of clothing, as described

60

above. These lifetimes were applied to the carbon footprint model and results are presented in Table 36

below.

Fibre Type

Carbon Footprint (t CO2e)

Lifetime of 2.177

years Lifetime of 1.770 years

Lifetime of 2.493

years

Fibre production 5,850,917 7,196,298 5,109,285

Yarn production 9,618,774 11,830,548 8,399,547

Fabric production 12,517,884 15,396,290 10,931,181

Garment production 748,029 920,033 653,213

Distribution 1,846,682 2,271,314 1,612,606

Retail 528,120 649,557 461,178

Use - washing 5,765,441 5,765,441 5,765,441

Use - drying 3,809,464 3,809,464 3,809,464

Use - ironing 243,098 243,098 243,098

End of life -2,753,116 -3,386,178 -2,404,145

TOTAL 38,175,293 44,695,867 34,580,867

Table 36: Sensitivity analysis to access the impact on results of the clothing lifetime data choice

From the results of the sensitivity analysis presented Table 35, the following points are evident:

The choice of clothing lifetime data greatly influences results;

The longer the weighted average lifetime of clothing that is used, the lower the carbon

footprint;

The shorter the weighted average lifetime of clothing that is used, the higher the carbon

footprint;

Impacts from production, retail and end of life are allocated on a per annum basis and

therefore, the longer the clothing lifetimes the smaller the carbon footprint; and

Use phase impacts per annum remain the same regardless of the lifetime of clothing.

Table 37 below shows the carbon saving from the baseline generated by each reduction measure of the

Central scenario using a clothing lifetime of 2.177, 1.770 and 2.493 years. This table shows the

sensitivity of results of the central reduction central to the lifetime of clothing.

61

Lifetime of 2.177

years

Lifetime of 1.770

years

Lifetime of 2.493

years

%

Reduction Rank

%

Reduction Rank

%

Reduction Rank

Eco efficiency across supply

chain (production, distribution

and retail) - Central scenario -

5% reduction for all fibres

across supply chain -4.1% 2 -4.3% 2 -3.9% 2

Design for Durability (and

product lifetime optimisation) -

Central scenario - 10% longer

lifetime of clothing -7.7% 1 -8.0% 1 -7.5% 1

Shift in market to higher

proportion of synthetic fibres -

Central scenario - replace 10%

of cotton with 50:50 poly-

cotton -0.4% 10 -0.5% 10 -0.4% 10

Clean clothing less - Central

scenario - washes per year

reduced by 10% -2.6% 3 -2.2% 3 -2.9% 3

Wash at lower temperature -

Central scenario - weighted

average wash temperature of

39.3C -1.4% 4 -1.2% 4 -1.6% 4

Increase size of washing and

drying loads - Central scenario

- load increases to 3.7kg -1.4% 5 -1.2% 5 -1.5% 5

Use the tumble dryer less -

Central scenario - 30%

reduction in tumble dryer use

in summer -1.1% 6 -1.0% 6 -1.2% 6

Dispose less - reuse more -

Central scenario – 15.4% of

clothing ultimately reused in

the UK -0.7% 8 -0.7% 8 -0.7% 8

Start closed loop recycling of

synthetic fibres - Central

scenario - 5% of all clothing is

recycled (closed loop) -0.9% 7 -1.0% 7 -0.9% 7

Dispose less - recycle more

(open loop) - Central scenario

- 38% of all clothing is

recycled open loop -0.5% 9 -0.5% 9 -0.5% 9

Cumulative reduction -20.9% -20.7% -21.1%

Table 37: Sensitivity analysis to access the impact on the central reduction scenario of the clothing

lifetime data choice

From the results of the sensitivity analysis presented in Table 37, the following points are evident:

Although the absolute carbon reduction varies greatly when a different lifetime of clothing is

assumed, the percentage reduction for each reduction measure does not change greatly;

As a result, the order of effectiveness of reduction measures doesn’t change;

For use phase reduction measures, the longer the assumed lifetime of clothing, the greater the

reduction, which is due to use phase impacts remaining static relative to other life cycle stages

when clothing lifetime is changed; and

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For non-use phase reduction measures, the longer the assumed lifetime of clothing, the smaller

the reduction, which is due to impacts of these life cycle stages changing relative to the use

phase when clothing lifetime is changed.

4.6.5 Washing Frequency (Sensitivity 5)

The data used for the number of times clothing is washed per year are uncertain. There is variability in

washing frequency between households, different garment types and even within the same garment

group (ie occasional wear versus ‘everyday’ wear). Therefore, it is difficult to represent the typical

washing frequency of all clothing in the UK.

Currently, the number of washes per year is derived from a Defra study (2009). This study provides a

value 274 washes per household per year, which was extracted from a report by the Market

Transformation Programme (2006). The original source of this data point is from the research carried

out by the Oxford Environmental Change Institute (published in Lower Carbon Futures for European

Households, 2000).

As the carbon footprint is based on the mass of UK clothing, it was necessary to normalise washing

frequency to a metric of ‘number of washes per kilogram of clothing’. This was achieved by multiplying

the number of washes per household with the number of UK households (26,300,000) and the average

washing load size (3.43 kg), which provides the mass of clothing washed in the UK. This value was

subsequently divided by the mass of clothing in use in the UK (2.49 million tonnes), to provide a value

of 9.9 washes per kilogram of clothing per year.

In order to test the sensitivity of results to the washing frequency upper and lower values of 5 and 15

washes per kilogram of clothing per year were entered into the carbon footprint tool.

Where it is assumed clothing is washed 5 times per kilogram per year, the total carbon footprint is 13%

less than that of the current carbon footprint, where it is assumed clothing is washed 9.9 times. As a

consequence, the carbon reductions achieved through use phase improvement actions are less and

those of non-use phase improvement action are greater.

Where it is assumed clothing is washed 15 times per kilogram per year, the total carbon footprint is 13%

greater than that of the current carbon footprint. The carbon reductions achieved through use phase

improvement actions in this case are greater and those of non-use phase improvement action are less.

4.6.6 UK Fibre Mix (Sensitivity 6)

The UK fibre mix modelled may not be representative of the UK clothing market. The original source of

the fibre mix data is Biointelligence 2009, which reflects a European rather than UK specific fibre mix.

This data was first used in URS’ 2011 water footprint study and subsequently used in this study for

consistency.

In order to test the sensitivity of results to fibre mix data, the results for the baseline results and ‘What

if?’ scenario results extracted from the carbon footprint tool where a different mix was entered. This

fibre mix data is from a Carbon Trust (2011) report entitled ‘International Carbon Flows’, which is shown

in Table 38 below alongside Biointelligence data for comparison.

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Fibre Type

European Fibre Mix

(Biointelligence,

2009)

UK Specific Fibre Mix

(Carbon Trust)

Cotton 43% 32%

Wool 9% 2%

Silk 1% 2%

Flax / linen 2% 6%

Viscose 9% 4%

Polyester 16% 45%

Acrylic 9% 4%

Polyamide 8% 5%

Polyurethane / polypropylene 3% 0%

Table 38: European fibre mix data used in this study in comparison to UK specific fibre mix data used for

sensitivity 6

The baseline carbon footprint total with the Carbon Trust fibre mix data is 12% less than the baseline

total where Biointelligence fibre mix data is used. For the ‘What if?’ scenario, the reduction achieved

where Carbon Trust fibre mix data is used is 11% less than the reduction achieved where Biointelligence

fibre mix data is used. Although the absolute reduction values change, the order of improvement

actions does not change with the new fibre mix.

4.7 Conclusions of Sensitivity Analyses

4.7.1 Decarbonisation of Grid Electricity (Sensitivity 1)

Figure 17 summarises the life cycle carbon footprint of UK clothing where an electricity emission factor

of 70 g CO2e per kWh is used for the use phase, in comparison to that where 610 g CO2e per kWh is

used.

Figure 17: Graph to compare the carbon footprint of UK clothing where an electricity emission factor of

70g CO2e per kWh is used for the use phase, in comparison to that where 610g CO2e per kWh is used

With the reduced carbon intensity of grid electricity applied to the use phase, the total footprint for UK

clothing is reduced by 17%. The result of this anticipated decarbonisation of grid electricity is that the

significance of the use phase will decrease relative to upstream life cycle stages (ie such as

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manufacture) and also at end of life, further increasing the importance of production stages. It should

be noted here that only use phase grid electricity decarbonisation was modelled in this sensitivity

analysis. However, as the majority of clothing is manufactured outside of the UK, it is anticipated that

modelling decarbonisation in all life cycle stages would not alter this conclusion significantly.

The reduction achieved through the following measures is increased by the shift to a decarbonised grid:

eco-efficiency across the supply chain, open and closed recycling, reuse more, shift towards synthetic

fibres and design for durability. The reduction achieved through the following measures is decreased by

the shift to a decarbonised grid: cleaning clothing less; using the tumble dryer less; increased load sizes;

and lower washing temperature. Therefore, in a decarbonised UK, non-use phase reduction measures

become more important relative use phase reduction measure.

Sensitivity analysis 1 indicates that, with the decarbonisation of grid electricity, the use phase becomes

a smaller proportion of the total life cycle carbon footprint of UK clothing. Therefore, when considering

reduction initiatives, some non-use phase measures increase in importance when grid electricity is

decarbonised. As it is likely that UK grid electricity will be decarbonised in the future, both use phase

and non-use phase reduction measures should be considered.

4.7.2 Influence of Fibre Type on Drying (Sensitivity 2a and 2b)

Figure 18 below summarises the life cycle carbon footprint of UK clothing where different assumptions

are made on the allocation of drying energy according to fibre type.

Figure 18: Graph to compare the carbon footprint of UK clothing where different assumptions are made

on the allocation of drying energy according to fibre type

Where drying energy is allocated according to the relative drying time of fibre types, the carbon

footprint increases from the baseline for natural fibres (by ~2-5%) and decreases for synthetic fibres

(by ~3-5%), but the total remains the same. The shift of drying energy burden towards natural fibres

reflects the fact they typically take longer to dry than synthetics.

Where loads are mixed and drying energy is based on the slowest drying item of clothing (ie natural

fibres), the carbon footprint for each fibre type increases from the baseline. This reflects an increase in

the drying time of all fibre types caused by a natural fibre type being present in each load.

Sensitivity analysis 2 indicates that the choice of allocation approach in the drying stage affects the

carbon footprint of each fibre type but has little effect on the overall carbon footprint of UK clothing.

With regard to carbon reduction, any measure to encourage the use of synthetic fibres will result in a

reduction in the carbon footprint from drying, provided clothing is separated according to fibre type.

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4.7.3 Influence of Fibre Type on Washing (Sensitivity 3)

Sensitivity analysis 3 shows that the reduction achieved from the shift towards synthetics in both the

central and ‘What If?’ scenarios is around a third larger when the difference in washing temperature is

also considered.

Based on this sensitivity analysis, more weight can be put on the benefits of shifting consumer

purchasing behaviour away from natural fibres and towards synthetic fibres. Combined with the

reduced impact in production and in drying, this sensitivity indicates that a shift towards synthetics is an

effective reduction measure. However, it should be noted that this study only considers the carbon

footprint of clothing. If other impact categories were considered, a recommendation to use synthetic

fibre may not still be valid. For instance, synthetic fibres are derived from finite hydrocarbon resources

and therefore encouraging their use would further increase resource depletion.

4.7.4 Longer Product Lifetimes (Sensitivity 4a and 4b)

Sensitivity 4a shows that for both the Central and ‘What if?’ scenarios, the carbon reduction achieved

from extending the lifetime of clothing is not as great when a 10% extra manufacturing burden is

required to achieve this extension. The decrease in reduction achieved is greater for the Central

scenario than for the ‘What If?’ scenario. This is due to the fact the increase in manufacturing impact

remains the same for each scenario but the savings from extended lifetime are greater for the ‘What If?’

scenario.

Therefore, when considering the carbon savings achieved through extending the lifetime of clothing by

increasing its durability, it is important to consider if extra manufacturing burdens are required. In

addition, this sensitivity also shows that rather than extending clothing lifetimes through better design it

may be more effective to encourage consumers to keep clothing for longer.

Figure 19 below summarises the life cycle carbon footprint of UK clothing where different assumptions

are made on the lifetime of clothing, which is an output of sensitivity 4b.

Figure 19 Graph to compare the life cycle carbon footprint of UK clothing where different assumptions

are made on the lifetime of clothing.

Sensitivity 4b shows that the longer the weighted average lifetime of clothing that is used, the lower the

carbon footprint and the shorter the weighted average lifetime of clothing that is used, the higher the

carbon footprint. In addition, impacts from production, retail and end of life are allocated on a per

annum basis and therefore, the longer the clothing lifetime, the smaller the carbon footprint, and use

phase impacts remain the same regardless of the lifetime of clothing. In terms of the effectiveness of a

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reduction measure to increase clothing lifetime, in both central and ‘What If?’ scenarios this measure is

ranked the highest when either 1.770, 2.177 or 2.493 years are used.

From sensitivity 4b, it can be seen that the choice of data on clothing lifetimes is particularly important

as it influences the results greatly. Due to this importance, and to the uncertainty of the data available,

our recommendation to undertake primary research on clothing lifetimes (including sales and clothing

stock) is reinforced. In addition, sensitivity 4b indicates that consumers should be encouraged to retain

clothing for longer and the ‘disposable fashion’ end of the clothing market should be discouraged. This

initiative to retain clothing longer should be coupled with an initiative of encouraging reuse.

4.7.5 Washing Frequency (Sensitivity 5)

The results of sensitivity analysis 5 show that, where it is assumed clothing is washed 5 times per

kilogram per year, the carbon footprint is 13% less than that of the current carbon footprint. Where it is

assumed clothing is washed 15 times per kilogram per year, the carbon footprint is 13% greater than

that of the current carbon footprint. The change in carbon footprint is apparent only in the use phase,

when the burden is increased or decreased, respectively, with a decrease or increase in wash frequency.

The higher assumed washing frequency, the greater the carbon reduction achieved through use phase

improvement actions and the lesser the carbon reduction achieved through non-use phase improvement

actions. This is due to the increase in washes, increasing use phase burden so that it represents a larger

proportion of the total carbon footprint, relative to non-use phase life cycle stages.

4.7.6 UK Fibre Mix (Sensitivity 6)

Sensitivity analysis 6 shows that carbon footprint results for both baseline and improved scenarios are

affected by a change in fibre mix data. The carbon footprint total with the Carbon Trust fibre mix data is

12% less than the baseline total where Biointelligence fibre mix data is used. For the ‘What if?’ scenario,

the reduction achieved where Carbon Trust fibre mix data is used is 11% less than the reduction

achieved where Biointelligence fibre mix data is used. This result is to be expected as the carbon

footprint of each fibre type is different.

From sensitivity 6, it can be seen that the choice of fibre mix data is significant, as the results are

influenced greatly. However, as the order of improvement actions changes very little, the use of the

carbon footprint tool to compare improvement actions is unaffected by the use of this different fibre mix

data.

5.0 Conclusions

This section summarises the overall conclusions of the core study and provides suggestions for further

research.

5.1 Summary of this Study

This study provided a strategic-level carbon footprint of UK clothing over the entire life cycle using

secondary data available in the literature. A number of example reduction measures were considered

and potential savings in relation to a baseline were quantified for both a central reduction scenario and a

‘What If?’ reduction scenario. In addition, an Excel model was developed that allows the modeller to

examine new scenarios, where values for each reduction measure can be changed.

Carbon footprint results were represented in terms of the following functional unit:

The entire life cycle of all garments, both new and existing, in use in the UK in 2009.

The results provided in the study relate to the annual impacts associated with UK clothing. They include

the impacts associated with the quantity of clothes that are produced for the UK and consumed and

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disposed of each year, but they also include the impacts associated with clothing that is actively worn

and cleaned each year (approximately 1.1 million tonnes of new clothing is consumed in the UK each

year, ~2.5 million tonnes is in active use - note that this is greater than the annual consumed clothing

because clothes last for more than one year).

As alternative expressions of this functional unit, carbon footprint results were also presented in terms of

one tonne of garments in use in the UK in 2009; garments used by one UK resident in 2009; and one

garment used in the UK in 2009.

5.2 Summary of Baseline Results


2009 (ie the volume consumed, and the actively worn quantity) is approximately 38 million



the UK’s direct carbon footprint) and 68% occurs abroad. Based on this estimate, the direct

impact of clothing in the UK can be estimated to be ~12 million tonnes of CO2e. Note that this

baseline analysis does not examine the effect of uncertainties, which are considered further in

the sensitivity analysis section of the report (Section 4.6).

To put this carbon footprint of UK clothing into context, the total direct GHG emissions in the

UK in 2009 were reported as 566 million tonnes of CO2e (DECC, 2011). It should be noted that

this total for the UK does not include GHG emissions associated with imported goods or

services or international travel. Therefore, the direct carbon footprint of clothing contributes





The most dominant life cycle stage is fabric production (comprising weaving/knitting etc. and


The carbon footprint of a tonne of garments, both new and existing, in use in the UK in 2009

ranges from around 15 to 46 tonnes CO2e, depending on the fibre type of the garment.



The per person carbon footprint of all garments, both new and existing, in use in the UK in

2009 is around 0.6 tonnes of CO2e.

5.3 Summary of Reduction Scenarios

For the reduction measures examined in the Central scenario, the combined effect of the ten reduction

across the entire life cycle) is estimated to be 21%. In the aspirational ‘What If?’ scenario this is

increased - it is estimated a carbon reduction of 71% could be potentially achieved. However, it should

be noted that the study does not examine the practicability of implementing each option, nor assess

other non-carbon sustainability impacts for these options. It should also be noted that these reductions

do not include the potential decarbonisation of energy (electricity) production, which will also reduce the

carbon footprint of clothing in future.

Table 39 and Table 40 below rank reduction measures in order of effectiveness, for both the central and

‘What If?’ scenarios, respectively.

68


1

Design for Durability (and Product lifetime optimisation) - central scenario - 10%

longer lifetime of clothing Manufacturer/

consumer

2

Eco efficiency across supply chain (production, distribution and retail) - central

scenario - 5% reduction for all fibres across supply chain Manufacturer

3 Clean clothing less - central scenario - Washes per year reduced by 10% Consumer

4

Wash at lower temperature - central scenario - weighted average wash temperature

of 39.3C Consumer

5 Increase size of washing and drying loads - central scenario - load increases to 3.7kg Consumer

6

Use the tumble dryer less - central scenario - 30% reduction in tumble dryer use in

summer Consumer

7

Start closed loop recycling of synthetic fibres - central scenario - 5% of all clothing is


8 Dispose less - reuse more - central scenario - 15.4% of clothing reused in the UK Consumer

9

Dispose less - recycle more (open loop) - central scenario - 19.5% of all clothing is

recycled open loop Consumer

10

Shift in market to higher proportion of synthetic fibres - central scenario - Replace

10% of cotton with 50:50 poly-cotton Manufacturer/

consumer

Table 39: Reduction measures of the Central scenario in order of effectiveness

As can be seen from Table 39, the most effective reduction measures of the Central scenario considered

are design for durability, eco-efficiency across the supply chain and cleaning clothing less frequently.


1

Design for Durability (and Product lifetime optimisation) - 'what if?' - 33% longer

lifetime of clothing Manufacturer/

Consumer

2

Eco efficiency across supply chain (production, distribution and retail) - 'what if?' -

30% reduction for all fibres across supply chain Manufacturer

3 Clean clothing less - 'what if?' - Washes per year reduced by 15% Consumer

4

Use the tumble dryer less - 'what if?' - 50% reduction in tumble dryer use in summer,

15% reduction in winter Consumer

5

Wash at lower temperature - 'what if?' - weighted average wash temperature of

32.9C Consumer

6 Increase size of washing and drying loads - 'what if?' - load increases to 4kg Consumer

7 Dispose less - reuse more - 'what if?' - 18% of clothing reused in the UK Consumer

8

Start closed loop recycling of synthetic fibres - 'what if?' - 10% of all clothing is


9

Shift in market to higher proportion of synthetic fibres - 'what if?' - Replace 40% of

cotton with 50:50 poly-cotton Manufacturer/

Consumer

10

Dispose less - recycle more (open loop) - 'what if?' - 24.5% of all clothing is recycled

open loop Consumer

Table 40: Reduction measures of the ‘What If?’ scenario in order of effectiveness

As is apparent from Table 40, the most effective reduction measures considered in the ‘What If?’

scenario are design for durability, eco-efficiencies across the supply chain and cleaning clothing less.

5.4 Further In Use Analysis Findings

Of the 10 potential in-use behavioural change interventions examined, the hybrid intervention, in which

a shift in consumer behaviour towards better clothing care also indirectly increased the lifetime of

clothing, showed the greatest benefit. The intervention reduced both the in-use and production impacts

and, as such, represents a potential ‘win:win’ reduction measure.

69

5.5 Findings from Sensitivity Analyses

Sensitivity analyses were undertaken to investigate key uncertainties of the study. These examined the

sensitivity of results and conclusions to a change in a particular assumption or data point. The

sensitivity analyses undertaken were: the influence of a future decarbonised electricity grid on the

impact of the use phase; the influence of fibre type on washing and drying impacts; and the influence of

product lifetime on results. The results of these sensitivity analyses indicate the following.

Future ‘decarbonisation’ of UK electricity will decrease the direct carbon footprint associated

with the cleaning of clothing. The significance of the use phase (primarily washing and drying)

impacts, relative to upstream life cycle stages (raw materials, manufacture and distribution,

retail) and end of life impacts will reduce.

Where the energy use impacts of tumble drying are allocated to clothing based on the relative

drying time of fibre types (rather than by its mass only as they are in the main analysis), the

carbon footprint increases from the baseline for natural fibres (by ~2-5%) and decreases for

synthetic fibres (by ~3-5%). The total remains the same.


natural fibres), the carbon footprint for each fibre type increases from the baseline. This

reflects an increase in the drying time of all fibre types caused by a natural fibre type being

present in each load. This is in comparison to a baseline average energy usage where some

loads are mixed and some are separated.

When the difference in washing temperature is also considered, the reduction achieved from

the shift towards synthetics in both the central and ‘What If?’ scenarios is around a third larger.

The longer the lifetime of clothing (eg from clothing simply being retained in use by the

consumer for longer, design for durability, reuse, or from leasing or resale), the lower the

carbon footprint (reduced supply chain impacts, primarily) and the shorter the lifetime of

clothing that is used, the higher the carbon footprint.

Where it is assumed in the analysis clothing is washed 5 times per kilogram per year, the total

carbon footprint is 13% less than that of the main analysis (where it is assumed clothing is

washed 9.9 times). The carbon reductions achieved through use phase improvement actions

are less and those of non-use phase improvement action are greater. Where it is assumed

clothing is washed 15 times per kilogram per year, the total carbon footprint is 13% greater

than that of the main analysis carbon footprint. The carbon reductions achieved through use

phase improvement actions are greater and those of non-use phase improvement action are

less.

The baseline carbon footprint total with the alternative Carbon Trust fibre mix data is 12% less

than the baseline total where Biointelligence fibre mix data is used. For the ‘What if?’ scenario,

the reduction achieved where Carbon Trust fibre mix data is used is 11% less than the

reduction achieved where Biointelligence fibre mix data is used. Although absolute reduction

values change, the order of improvement actions changes less with the new fibre mix, with the

top three and bottom three improvement actions remaining the same with both fibre data.

5.6 Concluding Remarks

Overall, the analysis confirms the rationale for encouraging reduction measures at each and every stage

of the life cycle, including nudging consumer behaviour towards favourable outcomes. If UK electricity

is decarbonised, the sensitivity analysis undertaken indicates sustainable production and consumption

measures aimed at reducing the production impacts of clothing will increase further in importance over

time, relative to use phase interventions. The study provides initial analysis into the potential indirect

effects on the washing and drying footprint if the market is shifted towards one type of fibre over

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another. The findings from the study sensitivity analysis indicate that, amongst other factors, the fibre

mix of UK clothing affects the magnitude of the footprint and the overall savings achievable, but has

less influence on the order of the reduction measures.

5.7 Suggested Next Steps

This study is a strategic level assessment of UK clothing and, as such, there are a number of

opportunities for improvement. Below is a list of suggestions.

This report is transparent with respect to the data sources used and assumptions taken to

calculate the carbon footprint. These data and assumptions would benefit from further review.

Therefore, it is suggested that interested stakeholders (eg consumer groups, detergent

manufacturers and washing machine manufacturers) be provided with a copy of the report in

order to validate the information and to provide new data if necessary, with the overall

aspiration of developing consensus around the data.

It is also noted that there is potential for improving the data quality of the study through the

collection of primary data from a representative number of manufacturers. In particular, a

more detailed assessment of the difference between the production of fibre, yarn, fabric and

garments from the most significant countries producing clothing for the UK would be desirable

to improve the representativeness of data used for production. This is particularly relevant to

the natural fibres, such as cotton and wool where agricultural inputs and outputs are likely to

vary significantly between countries.

There is currently an evidence gap with respect to the influence of the physical properties of

different fabrics on relative cleaning impacts (washing, drying and ironing). The use phase

contributes a significant proportion of life cycle impacts and therefore it is a sensible area to

target carbon footprint reduction measures. However, in this study, through allocating use

phase impacts on a mixed load, mass basis, each fibre type is given the same impact in the

main analysis. Despite this issue being examined in this study as a sensitivity analysis, more

primary research could be undertaken by manufacturers to gain a better understanding of

consumer behaviour, including the impact of modern low-temperature detergents and fabric

treatments on the size of use phase impacts.

It should also be noted that some preliminary research was carried out within this study on the

novel fibre polylactic acid (PLA). Reasonable quality data were gathered to model the

manufacture of clothing made from this material. However, as PLA fabric is currently produced

in very small quantities and the market share in the future in uncertain, it was not included in

this report. It would be valuable to undertake research into the market potential for innovative

fibres (PLA and others) and subsequently to evaluate their impacts in the use phase since

these fibres are often reported as having characteristic physical properties.

Improvements could be made on data relating to garment sizes, weights and lifetimes with the

aspiration of providing example data for industry baseline reporting and monitoring carbon

reduction.

Consequential impacts such as rebound effects are an area of potential research interest and

analysis may be appropriate for sustainable clothing, and more generally, for the impact

assessment of sustainable consumption and production policies.

As a final point, of the most effective reduction measures in each reduction scenario, most

require behavioural change. Therefore, the development of consensus UK-specific data on the

consumer cleaning behaviour and product lifetimes for clothing would be extremely

advantageous. A UK-relevant Product Category Rule (PCR) covering both synthetic and natural

fibre clothing, and its use, could be developed by industry and stakeholders.

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6.0 References

ADEME (2006), An Environmental Product Declaration of Jeans http://www.ademe.fr/internet/eco-

jean/EPD_en_jeans_v2.pdf

BSI (2008). PAS 2050:2008 - Specification for the assessment of the life cycle greenhouse gas

emissions of goods and services http://www.bsigroup.com/Standards-and-Publications/How-we-can-

help-you/Professional-Standards-Service/PAS-2050

Biointelligence service (2009, Unpublished) EC-funded IMPRO project on “Environmental improvement

potential of textiles” (final report 2009, unpublished)

Biswal et al. (2010) entitled, ‘Global warming contributions from wheat, sheep meat and wool production

in Victoria, Australia – a life cycle assessment’ (available from:

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